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Long ascending propriospinal neurons provide flexible, context-specific control of interlimb coordination

  1. Amanda M Pocratsky
  2. Courtney T Shepard
  3. Johnny R Morehouse
  4. Darlene A Burke
  5. Amberley S Riegler
  6. Josiah T Hardin
  7. Jason E Beare
  8. Casey Hainline
  9. Gregory JR States
  10. Brandon L Brown
  11. Scott R Whittemore
  12. David SK Magnuson  Is a corresponding author
  1. Department of Anatomical Sciences and Neurobiology, University of Louisville, United States
  2. Kentucky Spinal Cord Injury Research Center, University of Louisville, United States
  3. Department of Neurological Surgery, University of Louisville, United States
  4. Speed School of Engineering, University of Louisville, United States
  5. Cardiovascular Innovation Institute, Department of Physiology and Biophysics, University of Louisville, United States
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Cite this article as: eLife 2020;9:e53565 doi: 10.7554/eLife.53565

Abstract

Within the cervical and lumbar spinal enlargements, central pattern generator (CPG) circuitry produces the rhythmic output necessary for limb coordination during locomotion. Long propriospinal neurons that inter-connect these CPGs are thought to secure hindlimb-forelimb coordination, ensuring that diagonal limb pairs move synchronously while the ipsilateral limb pairs move out-of-phase during stepping. Here, we show that silencing long ascending propriospinal neurons (LAPNs) that inter-connect the lumbar and cervical CPGs disrupts left-right limb coupling of each limb pair in the adult rat during overground locomotion on a high-friction surface. These perturbations occurred independent of the locomotor rhythm, intralimb coordination, and speed-dependent (or any other) principal features of locomotion. Strikingly, the functional consequences of silencing LAPNs are highly context-dependent; the phenotype was not expressed during swimming, treadmill stepping, exploratory locomotion, or walking on an uncoated, slick surface. These data reveal surprising flexibility and context-dependence in the control of interlimb coordination during locomotion.

Introduction

Locomotion is a fundamental behavior that allows animals to move through the environment to forage, escape predators, or simply explore. Its expression is initiated supraspinally by various brain nuclei that provide locomotor command cues to spinal circuits, the downstream effectors of movement (Caggiano et al., 2018). Ultimately, it is the responsibility of the spinal cord circuitry to organize limb movements into the stepping patterns that are defined as locomotor gaits (Orlovskiĭ et al., 1999).

The two enlargements of the spinal cord serve as primary sites for the organization of forelimb and hindlimb movements, respectively (Cazalets et al., 1995; Grillner, 1981). Embedded within each enlargement are limb-specific central pattern generators (CPGs), each tasked with generating the respective patterns of limb movement (Kiehn, 2006). Through a distributed network of intra- and inter-enlargement connections, the fore- and hindlimb CPGs orchestrate the rhythm and pattern features of locomotion, including those associated with speed-dependent gaits: walk-trot, gallop, and bound (Brockett et al., 2013; Miller and van der Meché, 1976; Miller and Van der Burg, 1973; Miller et al., 1975; Juvin et al., 2005; Juvin et al., 2007). Two classes of inter-enlargement spinal neurons are thought to coordinate forelimb-hindlimb movements: long ascending propriospinal neurons (LAPNs) and long descending propriospinal neurons (LDPNs) (Miller and van der Meché, 1976; Miller et al., 1975; Juvin et al., 2005).

LDPNs reside in the cervical enlargement and project broadly to multiple sites throughout the spinal cord, including the lumbar enlargement (Reed et al., 2006; Ni et al., 2014; Alstermark et al., 1987; Giovanelli Barilari and Kuypers, 1969). Electrophysiological studies in the cat suggest that LDPNs are primarily involved in postural control by way of relaying proprioceptive inputs from the head and neck to the hindlimb motor pools (Alstermark et al., 1987). Using mouse genetics and viral technology, Ruder and colleagues revealed that not only do LDPNs ensure postural stability, but they also secure interlimb coordination during high-speed locomotion (Ruder et al., 2016).

Considerably less is known about the "reciprocal" inter-enlargement pathway: the LAPNs. Studies performed in the cat, rat, and mouse collectively reveal that LAPNs are a heterogeneous network of both ipsi- and contralaterally projecting neurons with mixed neurotransmitter phenotypes (excitatory and inhibitory) (Reed et al., 2006; Giovanelli Barilari and Kuypers, 1969; Ruder et al., 2016). The functional role of LAPNs in vivo remains unknown. Here, we used reversible synaptic silencing of the LAPNs to determine their role during locomotion. Our data suggest that LAPNs form a flexible, task-specific network for securing interlimb coordination of each limb pair (at the forelimb and hindlimb girdles, respectively) in a highly context-driven manner.

Results

Histological detection of conditionally silenced LAPNs

Spinal circuits located in the intermediate gray matter of the caudal cervical and rostral lumbar segments are the primary rhythmogenic sites for locomotor output (Cazalets et al., 1995; Juvin et al., 2005; Ballion et al., 2001). LAPNs, which are primarily embedded within the intermediate gray matter of the rostral lumbar segments, send ipsilateral or contralateral projections to the caudal cervical enlargement with sparse resident projections within the lumbar neuraxis (Figure 1—figure supplement 1). Given the critical involvement of cervical and lumbar CPGs for locomotion and the anatomical profile of the long ascending projections which connect these rhythmogenic foci, we set out to silence LAPNs in the freely behaving adult rat. We used the dual-virus TetOn system originally developed by Isa and colleagues (18), which allows doxycycline-induced reversible silencing of anatomically defined projection neurons (details in methods). Using two pairs of microinjections into the intermediate gray matter, we simultaneously targeted ipsilateral and commissural LAPNs that connect the key rhythmogenic foci (L1-L3 and C6-C8) reasoning that their silencing would lead to overt changes in hindlimb-forelimb coordination (Figure 1a). Behavioral testing was performed at Baseline (prior to injection), pre-silencing (Pre-Dox1), during DoxOn conditional silencing of LAPNs, and post-silencing (DoxOff) (Figure 1b). Repeat assessments were performed one month later (Dox2).

Figure 1 with 1 supplement see all
Histological detection of putatively silenced long ascending propriospinal neurons (LAPNs).

(a–b) Experimental design (see Materials and methods for details). (c–f) Volume rendered, high magnification images showing enhanced eTeNT.EGFP putative fibers (green) surrounding NeuN-stained neurons (red) and neurofilament-marked neural processes (magenta) in the cervical spinal cord (100x; x-y-z axis orientation shown in bottom right). Neuron in panel e is rotated about x-y-z axis to show eTeNT.EGFP fibers surrounding somata (inset panels right side). Neurofilament staining excluded in panel f for clarity (eTeNT.EGFP enshrouding cervical neuron). (g–h) eTeNT.EGFP signal co-localizes with synaptophysin (red). XZ-YZ orthogonal cross-sections through putative synapses shown in panel (h). eTeNT.EGFP signal co-localizes with the excitatory neurotransmitter marker vesicular glutamate transporter 2 (i, vGlut2; magenta) as well as the inhibitory neurotransmitter marker vesicular GABA transporter (j, vGat; magenta) (XZ-YZ orthogonal cross-sections shown). (k) Isotype controls revealed little-to-no immunoreactivity (IgG controls for synaptophysin and eTeNT.EGFP shown). (l–n) DAB enhancement of eTeNT.EGFP at the lumbar segments revealed dark immunoreactive neurons in the rostral lumbar segments (filled arrowheads) intermingled with DAB-negative neurons (open arrowheads). (o–p) Isotype control revealed little-to-no immunoreactivity. (c–k Scale bar = 25 µm; g,k scale bar = 10 µm; l,o,p Scale bar = 100 µm; m,n Scale bar = 50 µm).

To confirm that any silencing-induced behavioral changes were concomitant with eTeNT-expression in LAPNs, animals were euthanized during Dox2On LAPN silencing, following terminal behavioral assessments, and the spinal cords were processed for eTeNT.EGFP immunoreactivity. Histological analyses of the caudal cervical enlargement revealed that eTeNT.EGFP-expressing putative fibers surrounded and closely apposed neuronal somata and processes (Figure 1c–f). Moreover, eTeNT.EGFP co-localized with the synapse-related markers synaptophysin (Figure 1g–h), vesicular glutamate transporter 2 (Figure 1i, excitatory neurotransmitter), and vesicular GABA transporter (Figure 1j, inhibitory neurotransmitter). Collectively, these data suggest that the cervical projections derived from double-infected LAPNs express eTeNT and were silenced in vivo.

We next screened for the double-infected LAPN somata in the lumbar spinal cord. Using immunoperoxidase to enhance the eTeNT.EGFP signal, we observed EGFP+ neurons distributed throughout the rostral lumbar enlargement (Figure 1l–n, filled arrowheads). Intermingled with the double-infected LAPNs were non-infected lumbar neurons (open arrowheads). Isotype controls revealed little-to-no immunoreactivity suggesting that the histological detection of the conditionally expressed eTeNT.EGFP was specific (Figure 1k,o–p).

LAPNs organize interlimb coupling at each girdle during overground stepping

After validating that double-infected LAPNs conditionally expressed eTENT.EGFP in the presence of doxycycline, we next set out to determine the functional consequences of silencing this inter-enlargement pathway in the freely behaving adult rat.

Prior to silencing, animals stepped in a stereotypic walk or trot-like gait with the left-right limbs moving out-of-phase (alternating) at each girdle and the contralateral hindlimb-forelimb pairs moving in-phase (synchronously) (Figure 2a–c). Conditionally silencing LAPNs resulted in a striking spectrum of stepping behaviors, ranging from mild disruptions in left-right hindlimb alternation to a half-bound-like gait where the hindlimbs moved synchronously as the forelimbs "galloped," all the way to a full-bound where both the left-right forelimbs and hindlimbs moved synchronously (Video 1). The stepping behavior reverted back to the usual walk and trot-like gaits when silencing was reversed by removing Dox (Figure 2—figure supplement 1). Re-silencing LAPNs one month later reproduced and, in some cases, even enhanced these effects (Figure 2—figure supplement 1e). These data suggest that LAPNs secure multiple interlimb coupling patterns, not strictly hindlimb-forelimb coordination as we initially hypothesized.

Figure 2 with 1 supplement see all
Silencing long ascending propriospinal neurons (LAPNs) disrupts intra-girdle movements during overground stepping.

(a–c) Representative swing-stance graphs of stepping behaviors observed at control time points. Left: orange = homolateral HL-FL movements (out-of-phase, 0.5), blue = diagonal HL-FL movements (in-phase, 0.0/1.0). Right: green = left -right forelimb, purple = left-right hindlimb, each out-of-phase. Insets = one complete stride cycle (right limb reference). (d) Circular 0–1 phase data are transformed into a linear scale (0.5–1.0 or 0.0–0.5). (e) Left: silencing LAPNs does not disrupt homolateral ("ipsi") HL-FL coordination (# steps beyond control variability: Control n = 19/480 [3.95%] vs Dox n = 17/600 [2.83%]; p=0.31, z = 1.01, Binomial Proportion Test; circles = individual step cycles; shaded region = values beyond control variability). Right: diagonal ("contra") HL-FL coordination is significantly disrupted (Control n = 17/480 [3.54%] vs Dox n = 98/600 [16.33%]; ***p<0.001, z = 7.47). (f) Silencing LAPNs significantly disrupts left-right forelimb and left-right hindlimb coordination, respectively (forelimbs: Control n = 26/480 [5.42%] vs Dox n = 135/600 [22.50%]; p<0.001, z = 8.57; hindlimbs: Control n = 26/480 [5.42%] vs Dox n = 177/600 [29.50%]; ***p<0.001, z = 11.31). (g) Silencing LAPNs disrupts left-right movements more than hindlimb-forelimb (% total altered steps: hindlimb-forelimb 26.20 ± 3.02% vs left-right 73.80 ± 3.37%; ***p<0.001, critical t = 2.17, paired t-test; bars = group mean± S.D.; circles=% total steps taken that are altered for individual animals). (h) The quadrupedal stepping index remained unchanged during silencing (Control: 100.78 ± 0.87 vs Dox: 100.76 ± 1.55; p=0.97, critical t = 2.17; paired t-test).

Figure 2—source data 1

Contains the source data for step ratio measures.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig2-data1-v2.xlsx
Figure 2—source data 2

Contains the source data for the magnitude of change of step ratio measures.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig2-data2-v2.xlsx
Figure 2—source data 3

Contains the source data for the interlimb coordination measures.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig2-data3-v2.xlsx
Video 1
Conditionally silencing long ascending propriospinal neurons (LAPNs) disrupts interlimb coordination during overground stepping.

DoxOn videos shown from two independent experiments, three separate animals at Dox1On Day 8 of LAPN silencing. Videos shown from the same animal at 1x, 0.5x, and 0.25x speed.

In light of the unexpected changes to overall stepping behavior, we quantified the silencing-induced disruption of interlimb coordination. We first linearized the circular phase data to account for inter-animal variability in preferred lead limb during stepping (Pocratsky et al., 2017; Figure 2d) (e.g. for the left-right hindlimbs, coordination values of 0.25 or 0.75 are both gallop patterns). We then pooled the phase data from all control time points, calculated the mean temporal relationship for each limb pair, and set a control threshold based on normal variability observed during overground stepping (see methods for details) (Pocratsky et al., 2017).

When we gated our analyses to hindlimb-forelimb coordination, we observed an interesting dichotomy in the functional consequences of silencing LAPNs. Contralateral hindlimb-forelimb coordination was selectively disrupted with a significant increase in the proportion of steps that deviated beyond control variability (Figure 2e, right panel; Figure 2—figure supplement 1a–b). Coefficient of variation analyses substantiated this outcome, revealing an overall increase in the variability observed in hindlimb-forelimb coordination during silencing (CoV; Con vs Dox, 6.86 ± 1.17 vs 9.86 ± 3.91; p<0.05, paired t-test). Conversely, ipsilateral hindlimb-forelimb coordination remained intact (Figure 2e, left panel). Switching focus to intra-girdle movements revealed an even more intriguing result. Silencing LAPNs profoundly affected left-right coordination at each girdle (Figure 2f, Figure 2—figure supplement 1c–d) such that their functional decoupling allowed the full range of possible stepping phases to be expressed (Supplementary file 1; forelimb CoV: Con vs Dox, 9.81 ± 1.24 vs 18.08 ± 7.94, p<0.005; hindlimb CoV: 12.10 ± 2.20 vs 26.38 ± 14.39; p<0.005).

We then pooled the stepping bouts with altered coordination and compared the frequency of perturbed patterns (hindlimb-forelimb vs intra-girdle left-right). We found that perturbations to left-right alternation at each girdle was the primary deficit during LAPN silencing (Figure 2g). Moreover, when we screened for concurrent changes across the limb pairs, we found that the majority of hindlimb-forelimb perturbations were concomitant with intra-girdle left-right disruptions, but not vice versa (Figure 2—figure supplement 1f). These data suggest that LAPNs play a key role in securing left-right coordination at each girdle, and that changes to inter-girdle (hindlimb-forelimb) coordination are likely indirect. Despite the silencing-induced freedom in pattern expression observed within each girdle, all four limbs continued to step in a fixed 1:1 ratio (Figure 2h), indicating that other key features of locomotor control remain intact.

Intralimb coordination and postural control endure despite silencing-induced interlimb discoordination

During stepping, temporal information is distributed between (interlimb) and within (intralimb) each limb (Kiehn, 2006). Given the overt disruption to interlimb coordination, we set out to determine if intralimb movements were also affected during LAPN silencing. Using a three-segment, two-angle model of the hindlimb (Pocratsky et al., 2017; Kuerzi et al., 2010), we quantified both the spatial and temporal properties of intralimb coordination during stepping (Figure 3a).

Intralimb coordination and postural control endures despite silencing-induced generalized interlimb discoordination.

(a) Three-segment (iliac crest-hip, hip-ankle, ankle-toe), two-angle model of intralimb coordination. Five phases of step cycle illustrated with corresponding hindlimb range-of-motion (peak-to-trough excursion of the proximal and distal angles) and intralimb kinematics (b). (c) Range-of-motion was not altered during silencing (right hindlimb shown, group average ± S.D. [Baseline to Dox2On-D5]; p>0.5, mixed model ANOVA, Bonferroni post hoc). (d) Representative example of proximal-to-distal temporal coordination for one stride cycle (temporal overlap in peak angular excursions). Intralimb coordination plotted on circular graph where 0 denotes in-phase coordination. (e) Silencing long ascending propriospinal neurons (LAPNs) did not disrupt the proximal-to-distal temporal relationship across the hindlimb segments (p>0.5 for all comparisons; Watson’s U (Orlovskiĭ et al., 1999) test). White inset = control variability. Individual circles = peak to-peak proximal or distal excursion for one stride cycle. (f) Summary schematic. (g) Silencing LAPNs did not affect hindlimb base-of-support during overground stepping (Baseline vs Dox1On-D5: left hindlimb, 20.23 ± 3.00° [n = 220 steps] vs 19.13 ± 3.38° [n = 223 steps], p=0.31; right hindlimb, 19.76 ± 4.19° [n = 227 steps] vs 20.37 ± 3.39° [n = 229 steps], p=0.62; paired t-tests). (h) The number of hindlimb foot falls on the ladder significantly decreased during silencing versus control (Control 3.33 ± 2.47 vs DoxOn1.43 ± 1.33, **p<0.01; excluding outlier [red circle] yielded similar results – see Materials and mmethods for details). No significant differences were detected on the beam (Control 0.55 ± 0.38 vs Dox 0.55 ± 0.32, p=0.96). (i) Frequency of spontaneously evoked rearing events remained unchanged during silencing (Control 7.62 ± 4.89 vs Dox 9.46 ± 4.74, p=0.29). There was a slight, but significant increase in the duration of the rearing events during silencing (Control 1.56 ± 0.31 s vs Dox 1.92 ± 0.47 s, p=0.045). (j) Trunk angle during swimming remained unchanged during silencing (Control 10.23 ± 2.87° vs Dox 9.49 ± 3.78°, p=0.54). Data shown from N = 13 animals. Circles = individual averages; bars = group average± S.D.

Figure 3—source data 1

Contains the source data for trunk angle measures.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig3-data1-v2.xlsx
Figure 3—source data 2

Contains the source data for intralimb range-of-motion.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig3-data2-v2.xlsx
Figure 3—source data 3

Contains the source data for intralimb coordination measures.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig3-data3-v2.xlsx
Figure 3—source data 4

Contains the source data for foot faults on the narrow beam.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig3-data4-v2.xlsx
Figure 3—source data 5

Contains the source data for hindlimb base-of-support.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig3-data5-v2.xlsx

At control time points, the hindlimbs showed normal range-of-motion throughout the step cycle (Figure 3b) and normal proximal-to-distal coordination (Figure 3c). This spatial coordination persisted during silencing, even during bouts of synchronous stepping events. We next examined the temporal features of intralimb movement. Typically, peak excursion of both the proximal and distal limb components occurs at the end of stance phase just prior to lift-off (Figure 3d; Pocratsky et al., 2017). This salient feature of intralimb coordination also remained intact during LAPN silencing (Figure 3e), indicating that altered coordination between limb pairs did not affect the coordination of the limb itself (Figure 3f).

Given the generalized disruption to interlimb coordination, we also explored how balance/postural stability is affected during LAPN silencing. LDPNs, the pathway reciprocal to LAPNs, play a key role in this supportive feature of locomotion (Ruder et al., 2016). To interrogate postural stability, animals were challenged using a series of graded tasks with increased demand for balance control. Posturally-challenged animals often externally rotate their hindpaws during stepping to increase the overall base-of-support (Basso et al., 1995). We found no increase in the per-step angular rotation of the hindpaws during LAPN silencing, suggesting that base-of-support remained unchanged despite the disrupted phase relationship between limb pairs at each girdle (Figure 3g). Similarly, silencing LAPNs did not lead to increased footfalls on the narrow beam or horizontal ladder (Figure 3h), tasks with increased demand for balance control. Silencing LAPNs also did not negatively impact the frequency and duration of spontaneous rearing events, a task where quadrupedal animals stand bipedally (Figure 3i). Finally, animals were challenged with lap swimming, a task where the limbs are unloaded and postural control is essential for effective hindlimb-driven propulsion (Gruner and Altman, 1980). Using the body angle relative to the water surface as a proxy for trunk stability, we again found that LAPN silencing did not affect overall postural control (Figure 3j). Thus, silencing LAPNs leads to a generalized disruption of interlimb coordination without altering intralimb coordination or overall balance/postural control, key features that are required for effective locomotion.

Silencing LAPNs disrupts interlimb coordination independent of other salient features of locomotion

Hallmark features of locomotion are speed-dependent changes in interlimb coordination that are classified into different locomotor gaits, each defined by a unique set of limb coupling patterns (Hildebrand, 1965). As each gait is expressed as a function of speed, the underlying spatiotemporal features of limb movement predictably change (Lemieux et al., 2016). This fundamental relationship is highlighted in data collected from age-matched control rats assessed in a three meter long runway that allowed the full range of speed-dependent gaits to be expressed (Figure 4a, Figure 4—figure supplement 1; see methods for detail). As the speed increased (with concomitant changes in interlimb coordination and gait), the stride and stance durations decreased while the stride lengthened (Figure 4b–d).

Figure 4 with 3 supplements see all
Silencing long ascending propriospinal neurons (LAPNs) disrupts interlimb coordination independent from the salient features of locomotion.

(a) Schematic illustrating the speed-dependent gaits with representative swing-stance graphs (purple = walk trot; blue = gallop; green = half-bound; yellow = full-bound). (b) Schematic illustrating stride time (duration of one stride) and its normal relationship with speed for the volitionally expressed gaits (N = 12 age-matched controls, see methods; circles = individual steps). This relationship persisted during silencing (forelimbs: c,d, Control: p<0.001, rS = −0.845, R2 = 0.714 [n = 480 steps] vs Dox: p<0.001, rS = −0.889, R2 = 0.790 [n = 600]) (hindlimbs: e,f, Control: p<0.001, rS = −0.864, R2 = 0.746 vs Dox: p<0.001, rS = −0.908, R2 = 0.824; steps with silencing-induced altered coordination shown in blue for clarity; altered step defined as step cycle with a phase relationship that deviates beyond control variability; dashed line = line of best fit). (g) Schematic illustrating stance time (duration of paw contact for one stride) and its normal relationship with speed. This relationship persisted during silencing (h,i, forelimbs, Control: p<0.001, rS = −0.905, R2 = 0.819 vs Dox: p<0.001, rS = −0.929, R2 = 0.863) (j,k, hindlimbs, Control: p<0.001, rS = −0.901, R2 = 0.812 vs Dox: p<0.001, rS = −0.946, R2 = 0.895). (l) Schematic illustrating stride length (distance traveled for one stride) and its normal relationship with speed. This relationship persisted during silencing (m,n, forelimbs, Control: p<0.001, rS = 0.784, R2 = 0.615 vs Dox: p<0.001, rS = 0.736, R2 = 0.582; o,p, hindlimbs, Control: p<0.001, rS = 0.801, R2 = 0.642 vs Dox: p<0.001, rS = 0.787, R2 = 0.619). There was a slight change in the slopes for the lines of best fit for stride length versus speed during silencing (n, *p<0.05; t = 2.18; p, *p<0.05, t = 2.42). (q) Phase-frequency plot illustrating phase change as a function of frequency. (r) Left-right forelimb and left-right hindlimb phase-frequency relationships for the speed-dependent gaits (dashed circle = 5 Hz transition zone from the walk-trot to gallop Gillis and Biewener, 2001; Muir and Whishaw, 2000). Silencing LAPNs functionally decoupled the left-right fore- and hindlimbs, respectively (s, left: forelimbs, Control vs Dox, ***p<0.001, U2 = 0.67, n1 = 123, n2 = 187, Watson’s U (Orlovskiĭ et al., 1999) test; (s), right: hindlimbs: Control vs Dox, ***p<0.001, U2 = 1.45, n1 = 131, n2 = 204; refer to Supplementary file 2; white inset denotes control variability, circles denote individual step cycles). The decoupled limb pairs stepped at Control-level frequencies (forelimbs, Control: 99.80% [n = 479/480] at ≤5 Hz; Dox: 92.50% [n = 555/600]; hindlimbs, Control: 100% [n = 480/480] at ≤5 Hz; Dox: 95.30% [n = 572/600]).

Figure 4—source data 1

Contains the source data for stereotypical gait measures.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig4-data1-v2.xlsx
Figure 4—source data 2

Contains the source data for phase/frequency relationship.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig4-data2-v2.xlsx
Figure 4—source data 3

Contains the source data for spatiotemporal relationship.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig4-data3-v2.xlsx

Strikingly, this fundamental feature of locomotor control was unaffected during LAPN silencing. Despite the altered temporal coupling patterns expressed at the forelimbs, hindlimbs, and hindlimb-forelimb limb pairs, the spatiotemporal relationships of limb movements and speed remained intact (Figure 4e–p; blue circles = altered step cycles; Figure 4—figure supplement 2a–l). We saw no changes to the overall stride, stance, and swing durations (Figure 4—figure supplement 2m). Individual time point comparisons substantiated these results (Supplementary file 1).

Given the saliency of the intact locomotor features in the face of overt changes to interlimb coordination, we next explored the underlying stepping rhythm. We first examined the phase-frequency relationship for the left-right, fore- and hindlimb pairs. We plotted the left-right coordination value of each step taken (Figure 4q, ranging from 0 to 1) relative to the underlying step frequency with which it occurred (concentric circles of increasing frequency). The typical phase-frequency relationship is highlighted in our volitional gait dataset from age-matched control animals. Left-right alternation typically occurs at lower step frequencies (indicative of a walk-trot gait) (Figure 4r, purple circles). At higher step frequencies, the left-right limb pairs adopt a phase-shifted expression pattern (indicative of a gallop, green). At even greater step frequencies, the half or full-bound emerges wherein the hindlimbs move synchronously while the forelimbs adopt an asynchronous (half-bound, green) or synchronous-like stepping pattern (full-bound, yellow).

At control time points, the left-right limb pairs at each girdle primarily alternated with the majority of steps remaining below a 5 Hz step frequency (Figure 4r, top panels). Silencing LAPNs functionally decoupled the left-right limb pairs at each girdle, as revealed by the phasic dispersion throughout the polar plot (Figure 4s, bottom panels). Similar results were found following time point comparisons as well as parametric analyses on related measures including phasic concentration and circular variance (Supplementary file 2).

Despite the temporal decoupling of the fore- and hindlimb pairs, stepping frequencies remained similar to those of control time points (≤5 Hz). This led us to further explore the underlying stride duration within and between the girdles, with and without controlling for the effect of speed. Once again, silencing LAPNs had no impact on the underlying locomotor rhythm (Figure 4—figure supplement 3a–d). As a more sensitive assessment, we compared the stride durations between various limb pairs on a moment-by-moment basis. Each limb pair maintained a predictable relationship in the per-step stride duration despite the silencing-induced disruption to left-right coordination at each girdle (Figure 4—figure supplement 3e–h). Together, these data suggest that the rhythm of locomotor output is maintained despite the silencing-induced decoupling of limb pairs, indicating that temporal coordination can be selectively manipulated in an otherwise precisely controlled system.

Silencing-induced disruption to interlimb coordination is context-dependent

Thus far, results suggest that LAPNs coordinate interlimb movement during volitional overground stepping. To generalize the functional importance of LAPNs beyond this select condition, we assessed interlimb coordination across various locomotor tasks, behavioral modes, and external environments.

We first queried a different locomotor task: treadmill-based stepping. We found that intra-girdle left-right alternation was preferentially affected during overground locomotion as compared to treadmill stepping (Figure 5a; Video 2; Figure 5—figure supplement 1d–f; Supplementary file 3).

Figure 5 with 2 supplements see all
Silencing-induced disruption to interlimb coordination occurs in a task-specific, context-driven manner.

(a) Intra-girdle left-right coordination was affected to a greater extent during overground stepping as compared to treadmill during long ascending propriospinal neuron (LAPN) silencing (forelimbs, overground n = 135/600 [22.50%] vs treadmill n = 22/151 [17.05%], *p<0.05 [z = 2.38]; hindlimbs, overground n = 177/600 [29.50%] vs treadmill n = 28/151 [22.76%], **p<0.01 [z = 2.99]; Figure 5—figure supplement 1a–f; Supplementary file 3). (b) Silencing LAPNs does not affect interlimb coordination during exploratory-like stepping as compared to a more "directed" stepping mode ("going from A to B") (DoxOn forelimbs, non-exploratory overground n = 135/600 [22.50%] vs exploratory overground n = 13/95 [13.68%], *p<0.05 [z = 2.25]; DoxOn hindlimbs, non-exploratory overground n = 177/600 [29.50%] vs exploratory overground n = 7/95 [7.37%], **p<0.001 [z = 6.78]; Figure 5—figure supplement 1g–i; Supplementary file 3) (see Materials and methods for details). Silencing LAPNs does not affect intra-girdle left-right coordination while stepping on an uncoated plexiglass surface as compared to a Sylgard-coated base (N = 8 animals from a separate set of experiments; see methods for details; forelimbs, uncoated plexiglass n = 11/166 [6.63%] vs Sylgard-coated n = 39/170 [22.94%], ***p<0.001 [z = 4.34]; hindlimbs, uncoated plexiglass n = 12/166 [7.23%] vs Sylgard-coated n = 60/170 [35.29%], ***p<0.001 [z = 2.99]; Figure 5—figure supplement 1j–o; Supplementary file 3). (d) Silencing LAPNs did not affect left-right hindlimb alternation during swimming (n = 2/390 and 0/390 stroke cycles at Control and Dox, respectively; deviated beyond control variability; p>0.5 [z = 1.0]; Figure 5—figure supplement 1p; Supplementary file 3). Data shown in a,b, and d are from N = 13 animals. Data shown in c are from separate set of N = 8 animals. Circles = individual step or stroke cycles. Shaded region denotes variability beyond that observed at control time points for each condition described.

Figure 5—source data 1

Contains the source data for phase during exploratory walking.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig5-data1-v2.xlsx
Figure 5—source data 2

Contains the source data for phase during treadmill walking.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig5-data2-v2.xlsx
Figure 5—source data 3

Contains the source data for phase on different surfaces.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig5-data3-v2.xlsx
Figure 5—source data 4

Contains the source data for phase during swimming.

https://cdn.elifesciences.org/articles/53565/elife-53565-fig5-data4-v2.xlsx
Video 2
Silencing long ascending propriospinal neurons (LAPNs) disrupts interlimb coordination during overground stepping but not during treadmill-based locomotion.

Videos shown from the same animal at 1x, 0.5x, and 0.25x speed during overground and treadmill stepping at Dox1OnDays 4 and 5.

We then examined interlimb coordination during exploratory-like versus non-exploratory-like locomotion. Exploratory-like stepping was defined as overground locomotor passes where the snout was pointed down and was in close proximity to the ground (see methods for details) (Video 3). The non-exploratory stepping mode is the curated dataset shown thus far (Figure 5b, right panel, included for comparison purposes). In contrast to non-exploratory locomotion (snout up, "going from A to B"), silencing LAPNs had little-to-no effect on interlimb coordination during exploratory-like locomotion (Figure 5b, left panel; Video 3; Figure 5—figure supplement 1g–i; Supplementary file 3).

Video 3
Interlimb coordination is not affected during exploratory-like stepping behavior.

Videos shown from the same animal at the same DoxOn time point at 1x, 0.5x, and 0.25x speed.

In a separate experiment, animals were tested on two stepping surfaces with different coefficients of friction: an uncoated acrylic surface (CoF: 0.44) and a Sylgard-coated acrylic surface (CoF: 1.73). Silencing LAPNs significantly affected left-right alternation when animals stepped on the Sylgard coated surface, but had little-to-no effect when stepping on the uncoated surface (Figure 5c; Video 4; Figure 5—figure supplement 1j–o; Supplementary file 3). No differences in the base-of-support were detected between the two surfaces, suggesting that balance/postural changes likely do not account for this intriguing result (18.36 ± 2.97° vs 21.44 ± 4.48°; p>0.05, paired t-test).

Video 4
Silencing long ascending propriospinal neurons (LAPNs) selectively disrupts interlimb coordination when animals are locomoting on a coated, but not smooth stepping surface.

Videos shown from the same animal at the Control and DoxOn time points at 1x and 0.5x speed.

We then explored the effects of LAPN silencing on left-right hindlimb coordination in a different environmental context: water. Swimming is a bipedal task where the hindlimbs provide the major propulsive force while the forelimbs occasionally steer (Gruner and Altman, 1980). As the limbs are unloaded, both proprioceptive and cutaneous feedback associated with plantar stepping is altered (Akay et al., 2014). In contrast to our overground findings, silencing LAPNs had no effect on left-right hindlimb alternation during swimming (Figure 5d; Video 5; Figure 5—figure supplement 1p; Supplementary file 3), further supporting the concept that LAPNs help secure interlimb coordination in a context-dependent manner.

Video 5
Silencing long ascending propriospinal neurons (LAPNs) does not disrupt left-right hindlimb alternation during swimming.

Videos shown from the same animal at 1x, 0.5x, and 0.25x speed.

Finally, we explored if the context-specificity of silencing-induced disruptions to interlimb coordination was related to speed and speed-related gait changes. We discovered that silencing modestly expanded the speed ranges expressed when speed was determined by the animal (overground, exploratory, coated and smooth). However, the vast majority of disrupted steps occurred at speeds that were shared across the behavioral contexts examined, whether there were few (treadmill, exploratory and smooth surface) or many (overground and coated; Figure 5e, Figure 5—figure supplement 2). Using the data generated from age-matched control rats on the three meter long runway (Figure 4a, Figure 4—figure supplement 1) we found, as expected, a strong relationship between speed and hindlimb coordination (data not shown; Spearman Rank correlation coefficient = 0.753, N = 12 age-matched control rats, n = 403 total steps analyzed). In contrast, when we ran a similar comparison for the DoxOn overground stepping data, we could find no predictable relationship (Spearman Rank correlation coefficient = 0.410, N = 13, n = 600 total steps analyzed) suggesting that silencing the LAPNs resulted in interlimb coordination disruptions that were not speed-dependent. Overall, these data show that disrupted steps occurred throughout the speed range regardless of behavioral context, and that the majority occurred at speeds (≤90 cm/s) normally associated with walk-trot (alternating gaits; Figure 5—figure supplement 2ee), illustrating that silencing-induced changes to interlimb coordination were not related to speed-dependent gait change.

Discussion

Given their lumbar-to-cervical connectivity, we hypothesized that silencing LAPNs would disrupt hindlimb-forelimb coordination during locomotion. Instead, we unexpectedly uncovered a role for the LAPNs in securing left-right limb alternation at each girdle. The other salient features of locomotion remained wholly intact, including intralimb coordination, balance/posture, the overall 1:1 step ratio, the fundamental relationship between speed and the spatiotemporal features of limb movement, and the underlying locomotor rhythm. Collectively, these findings suggest LAPNs reside within the interlimb pattern formation layer of the locomotor hierarchy and are functionally separate from the circuitry responsible for the underlying rhythm and intralimb coordination. Interestingly, these outcomes dovetail with previous work where spinal L2 interneurons that project to L5 were silenced (Pocratsky et al., 2017). In that case, hindlimb alternation was selectively disrupted, allowing a spectrum of coupling patterns to be expressed, while other essential features of locomotion were once again preserved (Pocratsky et al., 2017). Together, these studies indicate that inter-segmental projecting lumbar pathways are key distributors of temporal information that can be used for maintaining left-right alternation during overground locomotion, and that hindlimb-forelimb coordination is either secured by other means or is less vulnerable to disruption potentially requiring silencing of larger numbers or a wider range of long propriospinal neurons.

It is generally accepted that left-right coordinating circuits are functionally organized into gait-specific ensembles, each recruited as a function of speed (Deska-Gauthier and Zhang, 2019). In the walking ensemble where the limbs move at low speed, left-right alternation is governed through a distributed network of ventrally-derived, commissural-projecting inhibitory spinal neurons (the "V0d" class) (Bellardita and Kiehn, 2015). As speed increases, the trotting ensemble is recruited wherein faster-paced left-right alternation is primarily secured through the combined actions of the excitatory V0 neuronal subclass ("V0v" spinal neurons) (Bellardita and Kiehn, 2015; Talpalar et al., 2013) and the excitatory, ipsilateral-projecting "V2a" subclass (Crone et al., 2009; Crone et al., 2008). At this time the circuits comprising the bounding ensemble remain largely unknown (Deska-Gauthier and Zhang, 2019). Through this modular organization, distributed classes of spinal interneurons are recruited as a function of speed, ensuring that appropriate patterns of limb coordination are expressed for each gait. By leveraging the spatial (anatomically defined) and temporal (inducible on-off) aspects of conditional silencing, we have highlighted an underlying complementary feature to the modular control of locomotion: flexibility. When the LAPNs were silenced, the system was able to accommodate right-left coupling patterns normally associated with the high-speed gaits of gallop and bound, but at walking speeds. This intrinsic freedom of pattern expression across a range of stepping speeds exposes a more flexible organization schema for locomotor control, a key tenet for adaptability in motor behavior.

Beyond the unexpected observation that silencing an ascending inter-enlargement pathway partially decouples the left-right limb pairs at each girdle, our most intriguing result is that the silencing phenotype is context-dependent. What could account for this striking phenomenon? A parsimonious interpretation would be that LAPNs are necessary for securing interlimb coordination in select conditions, such as overground stepping ("going from A to B") on a surface with good grip like Sylgard. Conversely, in other conditions such as stepping overground on uncoated acrylic (or during exploratory-like stepping, stepping on a treadmill, or swimming), LAPNs are dispensable. This rigid supposition may appear untenable given the rich repertoire of behaviors expressed by mammalian spinal circuitry. Thus, we offer an alternative interpretation by speculating that there exists a dynamic relationship between spinal autonomy and supraspinal oversight. Classic studies in the cat show that the lumbar spinal cord can produce the fundamental rhythm and pattern of locomotion even in the absence of all supraspinal and sensory input (Grillner, 1981). So, in a more "spinal autonomous" context (e.g. non-exploratory nose-up stepping overground "from A to B" on a Sylgard-coated surface), LAPNs are critical for limb-pair coupling such that their conditional silencing disrupts intra-girdle alternation and this disruption is not "corrected" by supraspinal (or any other) oversight. When the terrain changes (uncoated Plexiglas) or when stepping on a treadmill (Shefchyk et al., 1984), functionally parallel pathways may be engaged that would ensure a stable pattern of intra- and inter-girdle movements, thereby masking or temporarily over-riding the functional consequence(s) of silenced LAPNs. During exploratory (Sinnamon, 1993) behavior (nose-down) we observed very precise alternation of both the forelimbs and hindlimbs, and very precise hindlimb-forelimb coordination (Figure 5—figure supplement 1) that was not disrupted even slightly during LAPN silencing, arguing perhaps that exploratory stepping appropriate for olfaction or whisking involves a very stable pattern relying strongly on afferent input as dictated by the needs of supraspinal centers. Thus, the functional importance of LAPNs for securing interlimb coordination would rise or fall depending on the behavioral context or environmental conditions, which we interpret as decreased or increased supraspinal oversight. Nonetheless, this hypothesis is still parsimonious in that it does not take into account state-dependent neuromodulation of motor networks, a powerful phenomenon wherein circuits are reconfigured to produce needed frequencies and phase relationships (Marder et al., 2015). Swimming, which is primarily hindlimb-driven, may actually be a "lumbar autonomous" activity thus rendering LAPNs, and the information they carry, dispensable.

Based on the context-specificity of the phenotype, it is logical to conclude that the LAPNs carry temporal information from the hindlimb locomotor circuitry to the forelimb locomotor circuitry. However, the source of that temporally modulated information is unclear. It might be derived primarily from intrinsic spinal circuitry that generates the underlying rhythm of stepping (the rhythm-generating layer) and that is separate from, but has influence over, limb alternation at each girdle. Alternatively, it might be derived principally or entirely from hindlimb afferent input carrying temporal information associated with paw contact (cutaneous), limb loading or joint movement (proprioceptive). However, our previous work utilizing conditional synaptic silencing suggests that this alternative may be incorrect. When we silenced L2 interneurons that project to L5, we selectively disrupted hindlimb alternation, which should, in turn, have altered any temporal information derived from the hindlimb movement being carried rostrally by LAPNs. However, apart from alternation, no disruptions to forelimb function or any other salient features of stepping were observed (Pocratsky et al., 2017). Thus, the temporal information carried by the LAPNs may arise from the rhythm-generating circuitry, as suggested earlier, or may be some derivative of output from the intrinsic spinal circuitry (rhythm and pattern) and sensory input. Ultimately, the mechanisms underlying these striking results remain unknown. Computational modeling of the intrinsic and extrinsic network dynamics will be required to shed light on this phenomenon.

In conclusion, by reversibly silencing LAPNs in the otherwise intact adult rat, we show that a stable locomotor rhythm and intralimb pattern is maintained even while alternation, a key feature of the walk and trot gaits, is disrupted. We observed a wide range of coupling patterns expressed concomitantly with overall network stability. These observations highlight a surprising flexibility within locomotion and the spinal circuitry that governs it.

Materials and methods

Key resources table
Reagent type
(species) or
resource
DesignationSource or
reference
IdentifiersAdditional
information
Strain, strain background (female Sprague-Dawley rats)Envigo200–220 g, approximately 10–12 weeks old
Antibody (GFP)Rabbit IgGAbcam ab2901:5000
Antibody (NeuN)Guinea pig IgGMillipore ABN90P1:500
Antibody (NeuN)Mouse IgMMillipore MAB3771:500
Antibody (neurofilament)Mouse IgMSigma N52641:30,000
Antibody (synaptophysin)Mouse IgMMillipore MAB5258-50UG1:10,000
Antibody (vesicular glutamate transporter 2)Guinea pig IgGMillipore AB2251-I1:5000
Antibody (vesicular GABA transporter)Goat igGFrontier Institute VGAT-Go-Af6201:500
Antibody (non-immune sera)Rabbit IgGJackson ImmunoResearch #711-005-1521:5000
Antibody (secondary AlexaFluor 488)Rabbit IgGJackson ImmunoResearch # 711-545-1521:200
Antibody (secondary AlexaFluor 594)Guinea pig IgGJackson ImmunoResearch #706-585-1481:200
Antibody (secondary AlexaFluor 594)Mouse IgGJackson ImmunoResearch # 715-585-1501:200
Antibody (secondary AlexaFluor 647)Mouse IgGJackson ImmunoResearch # 715-605-1511:200
Antibody (secondary AlexaFluor 647)Guinea pig IgGJackson ImmunoResearch # 706-546-1481:200
Antibody (secondary AlexaFluor 647)Goat IgGJackson ImmunoResearch # 705-605-1471:200
HiRet-TRE-EGFP.eTeNTGenerous gift from Tadashi Isa1.6 × 107 vp/ml
AAV2-CMV-rtTAV16Generous gift from Tadashi Isa4.8 × 1012 vp/ml
HiRet-CreGenerous gift from Zhigang He1.6 × 1012 vp/ml
AAV2-CAG-FLEx-GFPUNC Vector Core3.5 × 1012 vp/ml
Chemical compound (Sylgard)Sylgard-coated surfaceSylgard 184 Silicone Elastomer Kit, Dow Corning
Chemical compound (cholera toxin B subunit conjugate)CTB-488Invitrogen/Molecular Probes C-347751.5% solution in sterile saline
Chemical compound (cholera toxin B subunit conjugate)CTB-594Invitrogen/Molecular Probes C-347771.5% solution in sterile saline
Chemical compound (cholera toxin B subunit conjugate)CTB-647Invitrogen/Molecular Probes C-347781.5% solution in sterile saline

Experiments were performed in accordance with the Public Health Service Policy on Humane Care and Use of Laboratory Animals, and with the approval of the Institutional Animal Care and Use and Institutional Biosafety Committees at the University of Louisville.

A total of N = 45 adult female Sprague-Dawley rats (Envigo; 200–220 g, approximately 10–12 weeks of age) were used throughout this study. Animals were housed two per cage under 12 hr light:dark cycle with ad libitum food and water. Power analysis of previous silencing experiments revealed that N = 6 was sufficient to detect a significant difference in behavioral outcome measures with 90–99% power (Pocratsky et al., 2017). Silencing data shown in Figures 25 represent two separate experiments, each N = 6 and N = 7, respectively. Experiments were performed in a staggered fashion separated by one month such that when the first group was undergoing Dox2 testing, the second group was performing Dox1 testing. No significant differences were detected between the two groups. Data shown are from the pooled samples (N = 13).

Viral vector production

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Dr. Tadashi Isa and colleagues generously provided the plasmid vectors (Kinoshita et al., 2012). The HiRet-TRE-EGFP.eTeNT and AAV2-CMV-rtTAV16 viral vectors were built following previously described methods with viral titers of 1.6 × 107 vp/ml and 4.8 × 1012 vp/ml, respectively (Pocratsky et al., 2017; Abdellatif et al., 2006; Sommer et al., 2003).

Intraspinal injections to double infect and silence LAPNs

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Intraspinal injections were performed as described previously (Pocratsky et al., 2017). Procedural details have been deposited into the Nature Protocol Exchange (http://dx.doi.org/10.1038/protex.2017.125).

We adapted this protocol to target LAPNs by performing a C6-C7 laminectomy to expose spinal C6 and injected HiRet-TRE-EGFP.eTeNT using coordinates of 0.6 mm mediolateral and 1.3 mm dorsoventral. The AAV2-CMV-rtTAV16 viral vector was similarly injected into L2 at 0.6 mm mediolateral and 1.5 mm dorsoventral. In double-infected neurons that constitutively express rtTAV16, doxycycline (DOX) induces enhanced tetanus neurotoxin (eTeNT) expression. eTeNT is then transported to the terminal field where it prevents exocytosis of synaptic vesicles, thereby silencing neurotransmission. Removing DOX from the drinking water restores neurotransmission, allowing acute and reversible silencing of this anatomically defined pathway in the otherwise intact adult rat.

LAPN silencing experimental timeline

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The experimental design used is similar to that of our previous silencing experiments (Pocratsky et al., 2017). In addition to the previously described control and Dox time points, we included an additional vehicle control (sucrose water without doxycycline). N = 6 animals underwent behavioral testing following 4 days of sucrose water. No significant differences were detected between the Sugar control and all other control (or Dox) time points.

Animals were acclimated to the stepping chamber prior to Baseline acquisition. All stepping behavior analyzed was spontaneous and volitional. Animals did not receive positive or negative reinforcement training. Only the walk-trot gait was observed at control time points (no spontaneous galloping or bounding was seen). The order in which animals were tested was random. Raters were blinded to animal-specific behavior across time points and behavioral tasks. Each animal served as its own control throughout the study as previously described (Pocratsky et al., 2017).

Unless otherwise stated, control data reflect the combined data from the following time points: Baseline, Pre-Dox1, DoxOff, and Pre-Dox2. Similarly, the Dox data reflect the combined data from the following time points: Dox1ONDay 3 ("-D3"), -D5, -D8 and Dox2OND3, and -D5. Unless otherwise stated, "Control" refers to collapsed data from all control time points (excluding sugar control) and "Dox" refers to collapsed data from all Dox time points.

Hindlimb kinematics and intralimb coordination analyses

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Hindlimb kinematic analyses were performed as previously described (Pocratsky et al., 2017; Kuerzi et al., 2010; Magnuson et al., 2009) , using custom-built Excel add-in macros (Morehouse, 2020; copy archived at https://github.com/elifesciences-publications/KSCIRC-Gait-Addin).

Overground locomotion analyses

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The overground locomotor analysis was performed following previously described methods and inclusion/exclusion criteria (Pocratsky et al., 2017). Data were analyzed with and without speed as a co-variate.

To calculate the magnitude change in interlimb coordination during LAPN silencing, we first calculated the number of altered steps (beyond control variability) for each animal for Control and Dox time points for the following limb pairs: left-right forelimb, left-right hindlimb, right homolateral limb pair ("ipsi hindlimb-forelimb"), and right hindlimb-left forelimb pair ("contra hindlimb-forelimb"). After calculating the total number of altered steps for each animal (in the analyzed locomotor bouts), we determined the percent of disrupted steps for left-right or hindlimb-forelimb limb pairs.

To calculate the group peak effect of LAPN silencing, we first identified the Dox time point that showed peak changes to interlimb coordination. We stratified the animals into either Dox1 or Dox2 categories and then performed comparisons (see Statistics section below). One animal did not show changes in left-right hindlimb coordination (Figure 2—figure supplement 1e, filled circles), but did show silencing-induced perturbations to left-right forelimb and contralateral hindlimb-forelimb coordination.

Interlimb coordination (phase)-frequency polar plots were created in SigmaPlot (ver 22) with each concentric circle set to 2 Hz increments (inner most: 0 Hz, outer most: 10 Hz). All steps analyzed (Control, n = 480; Dox, n = 600) were plotted for the raw left-right coordination value and its associated step frequency value. The dashed circle denotes a 5 Hz threshold at which almost all Control steps fell within (forelimbs: 99.8% of all steps; hindlimbs: 100%). Data were compared for the circular dispersion as described below (Statistics section). Phase-frequency polar plots were similarly created for the speed-dependent gaits (see the "Volitionally-expressed, speed-dependent gaits" section below for experimental details).

The underlying rhythm indices were analyzed as described previously (Pocratsky et al., 2017). Briefly, we first confirmed that there were no significant differences between the left and right limbs at Control and Dox time points, respectively. We then calculated the average stride duration for the fore- and hindlimbs, respectively. We also compared between the limb pairs for Control and DOX as well (bars: group mean ± S.D.; circles: individual means). Regression and slope analyses were performed (comparing Control vs Dox) on the following: left versus right forelimb stride duration, left versus right forelimb stride frequency, left versus right hindlimb stride duration, left versus right hindlimb stride frequency, forelimb versus hindlimb stride duration, and forelimb versus hindlimb stride frequency. The inter-girdle comparisons had the left and right limb pairs averaged together before hindlimb versus forelimb analyses.

Postural stability

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Balance, posture, and trunk control were assessed through a series of graded tasks. Base-of- support analyses were focused on the hindlimbs as this is the site wherein the major propulsive forces for locomotor behaviors are generated. Using a three-point angle model (point 1: area between shoulder blades, 2: groin, 3: hind paw position at initial contact), the rotation of the hind paws at initial contact were quantified for each step cycle. We chose to use the initial contact instead of lift-off as there is some normal rotation of the paw as weight is differentially transferred to the hindlimb throughout the stance phase. Both the left and right hindlimbs were analyzed at Baseline (n = 220–227 total step cycles analyzed per left or right hindlimb for N = 13 animals) and Dox1On-D5 (n = 223–229 total step cycles).

Animals were tested on the horizontal ladder (Columbus Instruments; Columbus, OH, USA, 2.5 mm rungs spaced 3.5 cm apart) (Burke et al., 2012) during the following time points: Baseline, Pre-Dox1, Dox1On-D4, Dox1On-D8, DoxOff, Pre-Dox2, Dox2On-D4, and Dox2On-D5. Each animal underwent five stepping trials per time point. The total number of footfalls were quantified for the left and right hindlimbs, respectively, for each animal at each time point. As no statistical difference between the left and right hindlimbs was observed, we combined the trials for the left and right limbs and determined each animal’s overall average number of footslips for Control and Dox, respectively. Statistics were performed on the group means (bars: average ± S.D.; circles: individual means overlaid). There was one outlier in the data set (red circle;>4 s.D.). Excluding the outlier from analyses did not change the results (Control mean: 3.33 ± 2.4 with outlier, 2.70 ± 1.02 without outlier; both p<0.001 when compared to Dox [1.09 ± 0.54]).

Animals traversed a custom-built 1.8 cm wide beam during the following time points: Baseline, Pre-Dox1, Dox1On-D3, Dox1On-D5, Dox1ON-D8, DoxOff, Pre-Dox2, Dox2On-D3, and Dox2On-D5. Each animal underwent three beam walk trials per time point assessment. The total number of foot falls from each trial per animal per time point for the left and right hindlimbs, respectively, were calculated. As no significant difference between the left and right sides was detected, we combined the trials for both hindlimbs and calculated the average number of footfalls for Control and Dox, respectively, for each animal. Statistical analyses were performed on the group means. Excluding the outlier shown in Figure 3j (red circle) yielded similar results. Animals also stepped on beams with a width of 3.6 cm and 5.4 cm, respectively, and showed little-to-no footfalls (data not shown).

Sagittal recordings of animals in the stepping chamber were analyzed for volitional rearing. We defined rearing as when the animal fully supported itself on its hindlimbs only (grooming events excluded). We defined the onset of rearing as when the animal removed its last forepaw from the ground (removal of all digits). The completion of the rearing event was defined as when a forepaw returned to the ground. We quantified the frequency and duration of all spontaneously expressed rearing events for all animals across all time points. To stratify the rearing events based on the level of forepaw support, we documented the onset times of when the forepaw contacted the side of the acrylic chamber, came into visual focus, and demonstrated weight bearing through spreading of fingertips and postural adjustments. The completion of forepaw support was defined as when the paw was removed from the glass as seen by postural movements, blurring of the hand, and narrowing of the fingertips. As such, we could define the degree of forepaw support by both frequency and duration of the events. Any event where the forepaws were out the field of view were excluded from analysis. The overall average frequency and duration of spontaneously evoked rearing bouts were calculated for each animal across all Control and DoxOn time points, respectively.

The trunk angle (degree at which the animals held their bodies relative to the water surface) was calculated using a four-point angle model (points 1 and 2: water surface [left and right extremes of the videos], 3: iliac crest; 4: hip). The trunk angle was calculated throughout the stroke cycle on a stroke-by-stroke basis for each swimming pass. Data shown are from Pre-Dox1 and Dox1ON-D5 with a total of n = 7873 and n = 10,520 trunk angles analyzed, respectively, for each hindlimb per animal. Data shown are the group mean ± S.D. (circles denote individual animal means).

Generalized behavioral analyses: context is key

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Treadmill-based locomotion (Single Lane Gait Analysis Treadmill, Columbus Instruments; Columbus, OH, USA) was analyzed following previously described methods (Pocratsky et al., 2017; Beare et al., 2009). Treadmill testing was performed at the following time points: Baseline, Pre-Dox1, Dox1On-D4, DoxOf, Pre-Dox2, and Dox2ON-D4. Inclusion criteria for the steps analyzed including the following: locomotor bouts where animals (1) consistently stepped in the middle of the treadmill, (2) did not hesitate/pause and "ride" to the back of the enclosure, (3) had minimal lateral deviations during stepping, and (4) did not have forward propulsive actions from the end of the enclosure to the middle and/or front. Recordings were analyzed using the MaxTRAQ software package (Innovision Systems Inc; Columbiaville, MI, USA). Care was taken to minimize the number of stepping sessions due to the adverse training effects associated with increased exposure to treadmill stepping (Beare et al., 2009; Hamers et al., 2006). We observed no instances where the animals spontaneously bounded (half or full) on the treadmill (N > 430 steps).

We noticed that when animals were ‘exploring’ their environment (e.g. snout in close proximity to the ground during locomotor bout), the silencing phenotype was absent. However, if the animals were stepping across the walkway chamber with no distractions, the phenotype was expressed. For descriptive purposes, we have termed these two behaviors as exploratory and non-exploratory stepping "modes." To analyze the effects of LAPN silencing during these two behavioral conditions, we applied strict criteria to the analyses of exploratory stepping. Using sagittal recordings as the reference, the following inclusion criteria were applied: (1) animals must have their snouts pointed downwards throughout the entirety of the step sequence, (2) animals must step consistently with no pauses or hesitations at any moment throughout the locomotor bout, (3) animals must step across at least ¾ the walkway, and (4) animals must locomote with little-to-no lateral deviations. Every animal displayed some form of "snout down" exploratory behavior at a Control and DoxOn time point, respectively. A total of n = 100 and n = 95 step cycles were analyzed across all Control and Dox time points, respectively. The non-exploratory stepping data are shown from that in Figures 24.

The influence of the stepping surface was discovered in a separate LAPN silencing study. N = 8 adult female Sprague-Dawley rats (215–225 grams) received the aforementioned viral vector injections with behavioral testing performed at Baseline, Pre-Dox1 (approximately 3 weeks post-injections), Dox1On-D5, Dox1On-D8, and DoxOff. In this study, animals were tested in two acrylic walkway chambers with different stepping surfaces. One walkway was coated with a clear, silicone substance ("coated"; coefficient of friction = 1.41) (Sylgard 184 Silicone Elastomer Kit; Dow Corning; Midland, MI, USA) while the other walkway was uncoated acrylic (coefficient of friction = 0.47). A total of 10–12 step cycles were analyzed for each animal across all time points. The control threshold (average + 2 s.D.) was calculated for each stepping surface, respectively, from data generated at Baseline, Pre-Dox1, and DoxOff. No significant differences were detected between the stepping surfaces at control time points.

The coefficients of friction reported for each stepping surface were calculated using the following approach. First, an alert adult female Sprague-Dawley rat (229 grams) was positioned into one side of the stepping chamber. While the animal calmly rested, the tank was slowly raised until paw traction was lost. This angle was measured in three separate trials for both the Syglard-coated and uncoated acrylic tanks, respectively. The coefficient of friction was then calculated based on the average of the tangent of the three measured angles. This process was repeated with an object that closely approximates the texture of the paw surface (e.g. smooth wooden block), yielding similar coefficients for each surface (uncoated acrylic: 0.44, Sylgard coated: 1.73).

Hindlimb swim analyses were performed following previously described methods (Pocratsky et al., 2017).

Volitionally-expressed, speed-dependent gaits

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To interpret our silencing data with respect to the speed-dependent locomotor gaits, we had to devise a strategy that would allow animals to freely express these fast-paced gaits overground, but still be compatible with our in-house methods for gait analyses (ventral recordings). To do this, we designed and built a runway chamber ("long tank") that was 305 cm long, 30.5 cm wide, and 14 cm tall with four high-speed video cameras (200 Hz) evenly spaced beneath the stepping surface.

To "stitch" together the multiple cameras such that all steps could be accounted for across the length of the tank, we used the following strategy. First, we arranged the cameras such that the FOV overlapped (e.g. camera 1–2, 2–3, 3–4). We placed two markers (between the first and second as well as the third and fourth cameras) to use as points of reference during video analysis. These points were copied to all videos such that the stepping coordinates were integrated across the four individual files acquired (one per camera). Using these strategies, we had no missing frames or steps when animals stepped between the different FOVs. To prevent or "subtract out" digitization of steps that fell within two FOVs, we created a series of inter-camera markers throughout the length of the tank. We measured the distance between the start of the tank to each of these markers and quantified these points during video analysis. Thereafter, we custom built a macro that would detect these digitized inter-camera markers to then filter out the "extra digitizing" between two overlapping FOVs. These processes were also repeated for cameras three and four. Each camera has a 5 cm scale visible, allowing us calibrate the video files using the MaxTRAQ scale feature. Within our macro, we created a pixel-to-cm conversion factor that allowed us to reliably measure the various spatiotemporal indices of locomotion. This experimental design allowed us to stitch together multiple videos for seamless step analyses.

Given the length of the tank, we found that animals were often distracted and rarely completed one complete locomotor bout without pausing to explore. To combat this, we devised a training program that included positive reinforcement to encourage the completion of a locomotor bout across the 3 m tank. N = 12 naïve adult female Sprague-Dawley rats (200–220 g) underwent this training program to generate the speed-dependent gait data. Details of this program are as follows.

First, animals were extensively handled by the experimenters to where they would freely approach and climb into the researchers outstretched hand. During these gentling sessions, animals were handled individually and/or with their cage mates and provided positive reinforcement after they were returned to their home cage (food reward). Once animals were well-acclimatized to the experimenters, they were then introduced to the long tank. Cage mates were placed in chamber together, allowing them to freely explore and run/play throughout the full length of the tank. Food rewards were provided at each end of the tank during these sessions such that animals began to associate these areas with treats. This phase of the training program lasted approximately 3–4 days.

After the initial introduction phase to the long tank, animals began extensive training where they were encouraged to step across the entire length of the runway with little-to-no pausing/hesitations. During these training sessions, two experimenters were positioned at either end of the tank. To start, one trainer would create a sound (gently tapping the side of the tank or lightly rubbing two gloved fingers back and forth). Animals typically stepped towards the side of the stimuli where they received a food reward. Thereafter, the second experimenter would provide auditory stimuli and the animal would turn around to fully traverse the tank again to receive another food reward. No food reward was given if the animal did not successfully complete one pass start to finish (no pausing, no hesitations). (This phase of the training program lasted two weeks with twice a day training sessions during the first week and one training session per day during the second week). By the end of these training sessions, animals freely expressed their natural repertoire of gaits (walk-trot, gallop, half-bound, and full-bound), sometimes even to the sound of the experimenter rubbing their gloves.

Data shown are from seven separate recording sessions that were spread out over a fourth month period. Food rewards were not given during the video recording sessions. However, the experimenters did provide the auditory stimuli to which the animals were accustomed during training. Our defining criteria for the distinct locomotor gaits are based on previously described coupling patterns (Bellardita and Kiehn, 2015). We did not distinguish between the two alternating gaits: walk (three limbs in contact with the ground) and trot (two limbs in contact with the ground at any moment). A total of n = 160, 50, 108, and 80 step cycles were analyzed for the walk-trot, gallop, half-bound, and full-bound gaits, respectively. Fewer gallop step cycles were analyzed due to the transient nature of this gait (Lemieux et al., 2016).

We did not test for the expression of the speed-dependent gaits in the long tank during LAPN silencing. In the long tank paradigm, we applied positive reinforcement to encourage the volitional expression of the faster-paced gaits. These gaits are volitional in the sense that the animals were not placed on a treadmill and "forced" to step a fast rates of speed. During silencing, we did not want to confound our results by "encouraging" the expression of distinct coupling patterns. It would be challenging to reconcile whether changes in the coupling patterns expressed were due to LAPN silencing or the reinforcement of fast-paced gait expression. Instead, we first wanted to assess how the nervous system would intrinsically respond to the "functional loss" of LAPNs. Going forward, these data may serve as a foundation for future experiments where the gaits are systematically assessed during conditional silencing.

Histological processing for double-infected LAPNs

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Following terminal assessments, animals were sacrificed with an overdose of ketamine:xylazine and transcardially perfused with 0.1 M PBS (pH 7.4) followed by 4% paraformaldehyde (PFA). Spinal cords were dissected, post-fixed in 4% PFA for 1 to 3 hr, and transferred to 30% sucrose for 3–4 days at 4°C. The cervical and lumbar injection sites were dissected, embedded in tissue- freezing medium, cryosectioned at 30 µm in five sets, and stored at −20°C.

Immunohistochemical detection of EGFP.eTeNT-positive terminals in the caudal cervical segments was performed following previously described methods (Pocratsky et al., 2017) (Nature Protocol Exchange: http://dx.doi.org/10.1038/protex.2017.141). Antibodies used include the following: rabbit anti-GFP (abcam ab290, 1:5,000), guinea pig anti-NeuN (Millipore ABN90P, 1:500), mouse anti-NeuN (Millipore MAB377, 1:500), mouse anti-neurofilament (Sigma N5264, 1:30,000), mouse anti-synaptophysin (Millipore MAB5258-50UG, 1:10,000), guinea pig anti-vesicular glutamate transporter 2 (Millipore AB2251-I, 1:5,000), and goat anti-vesicular GABA transporter (Frontier Institute VGAT-Go-Af620, 1:500; see manufacturer for validation details). Negative controls include non-immune sera matched for protein concentration and dilution (donkey anti-rabbit IgG; Jackson ImmunoResearch #711-005-152, 1:5,000). Secondary antibodies were used at a dilution of 1:200 and included the following (all donkey host): anti-rabbit IgG AlexaFluor 488 (Jackson ImmunoResearch # 711-545-152), anti-guinea pig IgG AlexaFluor 594 (Jackson ImmunoResearch #706-585-148), anti-mouse IgG AlexaFluor 594 (Jackson ImmunoResearch # 715-585-150), anti-mouse IgG AlexaFluor 647 (Jackson ImmunoResearch # 715-605-151), anti-guinea pig IgG AlexaFluor 647 (Jackson ImmunoResearch # 706-546-148), and anti-goat IgG AlexaFluor647 (Jackson ImmunoResearch # 705-605-147). The applied microscopy settings and post hoc image processing are previously described (Pocratsky et al., 2017).

Double-infected LAPNs were detected following methods previously described (Nature Protocol Exchange: http://dx.doi.org/10.1038/protex.2017.142). In light of the reduced post-fixation time (1–3 hr vs overnight), the following modifications were applied: (1) antigen retrieval was excluded, (2) rabbit anti-GFP was used at a range of 1:30,000 to 1:60,000 to amplify endogenous eTeNT.EGFP signal, and (3) the blocking, secondary, and streptavidin HRP steps were each 30 min in duration. For a negative control for GFP, an isotype-matched IgG at identical protein concentration and dilution was used (donkey anti-rabbit IgG; Jackson ImmunoResearch #711-005-152). The microscopy settings and post hoc image processing are previously described (Pocratsky et al., 2017).

LAPN anatomical work-up

CTB Labeling

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Power analyses revealed that a sample size of N = 5 animals was sufficient to detect a significant difference in the number of ipsilateral-projecting vs contralateral-projecting rostral LAPNs, with or without local projections to spinal L1 or spinal L5, respectively (power >95%). A total of N = 11 adult female Sprague-Dawley rats (210–230 grams) were used in this study, with N = 5 and N = 6 comprising two separate groups (described below).

Cervical and lumbar injections were performed during the same day of surgery

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Animals were anesthetized with a cocktail of ketamine/xylazine/acepromazine (80 mg/kg, 4 mg/kg, and 305 mg/kg; i.p.) and received a C6-C7 laminectomy to expose spinal C6. Following previously described methods, two different AlexaFluor conjugates of cholera toxin B subunit (CTB) were bilaterally injected into the intermediate gray matter (Pocratsky et al., 2017). Animals received one unilateral injection of CTB-AlexaFluor-594 on the left field of view (FOV) and one unilateral injection of CTB-AlexaFluor-647 on the right field of view. Injection coordinates were 0.5 mm mediolateral and 1.3 mm dorsoventral, respectively. Following the cervical injections, animals were randomly assigned to two groups. One group received a T12 laminectomy to expose spinal L1 (N = 6) while the second group received a ~ T13 L1 laminectomy to expose spinal L5 (N = 5). Both groups received one unilateral injection of CTB-AlexaFluor-488 (right FOV). The L1 injections were performed at the rostral FOV with mediolateral-dorsoventral coordinates of 0.5 mm and 1.3 mm, respectively. The L5 injections were performed at the caudal FOV with mediolateral-dorsoventral coordinates of 0.5 mm and 1.4 mm, respectively. All CTB conjugates were prepared as a 1.5% solution (0.1 M PBS, pH 7.4; Molecular Probes, Eugene, OR, USA) and delivered in two, 0.25 µl boluses separated by three minutes to allow for tracer uptake. Post-operative care was performed as described above.

Three weeks later, animals were euthanized and the spinal cords were dissected, post-fixed for one hour, and then stored at 4°C in a 30% sucrose solution. To analyze retrogradely-labeled LAPNs, spinal T13-L6 was dissected, embedded in tissue-freezing medium, and cryosectioned at 20 µm in sets of five (adjacent sections separated by 100 µm rostrocaudally). To analyze the cervical injection sites, spinal C5-C8 was dissected, embedded, and serially cryosectioned at 30 µm. All sections were mounted onto charged glass slides and stored at −20°C.

Power analyses revealed that N = 5–7 sections/animal were needed to detect a significant difference in the number of ipsilateral-projecting versus contralateral-projecting rostral LAPNs, positive or negative for L1 or L5 local collaterals (power >82%). Proportional cell counts of LAPNs with L1 or L5-projecting collaterals were performed as previously described (Pocratsky et al., 2017). A total of n = 6,775 LAPNs were counted across N = 11 animals. Careful attention was paid to the in vivo injection site FOVs for the schematics shown as well as projection pattern identification (ipsi- vs contralateral). Representative images are shown. Data shown are proportional cell counts of total LAPNs labeled. All analyses were performed by experimenters blinded to the experimental conditions. Image processing and a priori inclusion/exclusion criteria for analyses are previously described (Pocratsky et al., 2017).

Laminar distribution analyses and heatmap generation were performed as previously described (Pocratsky et al., 2017). To generate contour plots, neurons were first marked using Nikon Elements software. A custom-made MatLab program was then developed to reconstruct and normalize the position of labeled neurons across sections. A reference axis was created for each image with the origin centered on the central canal, the y-axis parallel to the spinal cord midline, and the x-axis orthogonal to the y-axis (States, 2020; copy archived at https://github.com/elifesciences-publications/Pocratsky_et_al_2020). Contour/scatter plotting was performed using R. Distribution contours were created by calculating the two-dimensional kernel density (using the kde2d function in the MASS library), then connecting points of equal density values between 30–100% of the estimated density range in increments of 10% (States, 2020).

Immunohistochemical detection of putative synaptic inputs onto LAPNs was performed in accordance with methods previously described (Pocratsky et al., 2017).

Statistical analyses

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Statistical analyses were performed using the SPSS v22 software package from IBM. Additional references for parametric and non-parametric testing were used in complementation to SPSS (Hays, 1981; Siegel and Castellan, 1988; Batschelet, 1972; Zar, 1974; Ott, 1977; Lenth, 2006). Differences between groups were deemed statistically significant at p≤0.05. Two-tail p values are reported.

The Binomial Proportion Test was used to detect significant differences in the proportion of coordination values beyond control threshold for the raw and transformed interlimb coordination data of various limb pairs. It was also used to detect a significant group peak effect (Dox1 vs Dox2), per-step changes in left-right coordination and stride durations (beyond control thresholds), the interaction between altered coupling patterns, testing for the preferred "altered" forelimb coupling pattern during silencing, the stroke-by-stroke changes in hindlimb coordination as well as stroke cycle durations (beyond control variability), and the various behavioral contexts (e.g. stepping surface).

Circular statistics were performed on the stepping inter- and intralimb coordination datasets, as well as the swimming hindlimb coordination data (Pocratsky et al., 2017; Zar, 1974). We primarily used the non-parametric two-sample U (Orlovskiĭ et al., 1999) test for the following rationale. Typically, parametric tests are performed to determine whether the data have a uniform distribution (Batschelet, 1972; Zar, 1974). Importantly, these analyses are based on strict assumptions that the distribution is restricted to two patterns: uniform or unimodal (Batschelet, 1972; Zar, 1974). Our data do not fit these criteria (e.g. differences in lead limb and natural intra- and inter-animal variability in interlimb coordination). Moreover, the various control time points (Baseline, Pre-Dox1, DoxOff, Pre-Dox2) do not have unimodal distributions with the exact same degree of concentration. Therefore, we used non-parametric two-sample U (Orlovskiĭ et al., 1999) test. The null hypothesis tested here is whether two time points have the same concentration (or phasic direction) in couple pattern expression.

Spearman Rank correlations were performed on the speed versus spatiotemporal gait indices for the forelimbs and hindlimbs during Control and Dox, respectively. These comparisons included speed versus stance, swing, and stride durations as well as the stride length and frequency.

Regression analyses to compare the slopes for the lines of best fit were performed on the speed versus spatiotemporal gait indices datasets (Control vs Dox for forelimbs and hindlimbs, respectively, as well as between the limb pairs). Regression and slope analyses were also performed to test for preferred coupling patterns in the altered stepping datasets as well as comparing the left versus right fore- and hindlimb step frequency and durations as well as comparing between the two girdles.

One and two-way ANOVAs were used to test for significant differences in the laminar distribution and projection patterns of LAPNs as previously described (Pocratsky et al., 2017).

Mixed model ANOVA followed by Bonferroni post hoc t-tests (where appropriate) were used to detect a significant difference in the peak, trough, and excursion of the proximal and distal hindlimb segments for range-of-motion analyses.

Repeated measures ANOVA without speed as a co-variate were performed when comparing the mean stride durations between the fore- and hindlimbs within the individual time points.

Repeated measures ANOVA with speed as a co-variate were used when comparing Control vs Dox stride, swing, and stance durations for the fore- and hindlimbs as well as between the girdles. Sidák post hoc t-tests were used when appropriate.

Multivariate analysis of variance (MANOVA) with speed as a co-variate followed by Sidák post hoc t-tests were used when comparing the mean stride frequencies and durations for Control vs Dox for the fore- and hindlimbs as well as between the two girdles. These analyses were also used when comparing the average stride durations of the left and right forelimbs and hindlimbs, respectively, over time (nine total time points, excluding vehicle control) as well as within the individual time points.

Paired t-tests were used to detect significant differences in: (1) the magnitude change in interlimb coordination during silencing, (2) the proportion of steps with per-stride changes that were ≤0.1 or>0.1, (3) the hindlimb:forelimb step index, (3) when comparing the percent of Dox steps that were ≤90 cm/s versus >90 cm/s as well as (4) for the altered steps alone, (5) when comparing the base-of-support, (6) average number of foots slips on the ladder (7) and beam (8 , 9) the frequency and (10) duration of spontaneously expressed rearing events, (11) the trunk angle during swimming, (12) when comparing the swing-stance durations within speed categories of ≤90 cm/s or >90 cm/s for the fore- and hindlimbs, respectively, at Control and Dox, and comparing the coefficient of variation at Control and Dox time points.

Levene’s Test for Equality of Variances were performed to test for a normal distribution within the interlimb coordination datasets. Notably, at control time points (e.g. Baseline) the coordination data have a non-normal distribution as phase values will naturally concentrate towards one value (e.g. 0.5 for left-right alternation in the hindlimbs).

Code availability

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Kinematic and gait data were analyzed using custom-built Excel add-in macros (Morehouse, 2020; copy archived at https://github.com/elifesciences-publications/KSCIRC-Gait-Addin). Heatmaps and contour plots of LAPN laminar distribution were generated using custom-designed MatLab and R scripts (States, 2020; copy archived at https://github.com/elifesciences-publications/Pocratsky_et_al_2020).

Data availability

Source data has been provided for: Figures 2, 3, 4 and 5, Figure 1—figure supplement 1 and Figure 4—figure supplement 2.

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Decision letter

  1. Ronald L Calabrese
    Senior and Reviewing Editor; Emory University, United States
  2. Tuan V Bui
    Reviewer; University of Ottawa, Canada

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

Procratsky and colleagues provide an anatomical and functional evaluation of long ascending propriospinal neurons (LAPNs) connecting lumbar hindlimb-related segments and cervical forelimb-related segments. They use an elegant method (developed by Tadashi Isa) to specifically and reversibly silence LAPNs in rat, expecting to uncouple fore/hindlimb coordination. Instead, they observe changes in left-right coupling that occur only during non-exploratory locomotion on high friction surfaces not for example during swimming, treadmill stepping, or on a slick surface.

Decision letter after peer review:

Thank you for submitting your article "Long ascending propriospinal neurons provide flexible, context-specific control of interlimb coordination" for consideration by eLife. Your article has been reviewed by Ronald Calabrese as the Senior Editor, a Reviewing Editor, and three reviewers. The following individuals involved in review of your submission have agreed to reveal their identity: Tuan V Bui (Reviewer #3).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

This paper explores the functional role of long-range ascending projection neurons (LAPNs) in rat spinal cord. Procratsky and colleagues provide an anatomical and functional evaluation of LAPNs, which connect lumbar hindlimb-related segments and cervical forelimb-related segments. They use an elegant method (developed by Tadashi Isa) to specifically and reversibly silence LAPNs – doxycycline-mediated TeNT silencing of LAPNs whose cell bodies reside mainly in L1-L3 segments – expecting to uncouple fore/hindlimb coordination. Instead, they observe changes in left-right coupling that occur during non-exploratory locomotion on high friction surfaces, but not during treadmill locomotion, nose-down exploratory locomotion, slippery surface locomotion and swimming. Overall, the experiments are done rigorously. Several controls have been done to suggest that neurons affected by Dox are indeed long ascending propriospinal neurons from L1-L3. Many features of locomotor activity have been taken into consideration in their analysis, and data capture for locomotor activity used several different approaches and appears well done. The study of different forms of locomotor activity provides greater insight into the possible roles of long ascending propriospinal neurons and is a strength of this work. The insights from this study advance our understanding of how spinal circuitry regulates different facets of locomotor activity and pushes the field to consider that the contributions of spinal circuits shift depending on the type of activity performed.

Essential revisions:

All the reviewers were supportive of the work, while voicing significant concerns. All the complementary concerns of the reviewers should be addressed. Two issues arose as shared concerns of the reviewers.

1) We require further analysis of which neurons the viral strategy is labeling/manipulating, perhaps using the tissue used in Figure 2. Is this labeling similar to the CtB? If not, how? Are the differences laminar-related? Ideally, the authors should show that most or a subset of CtB labeled neurons are eTeNT.GFP+, and more importantly that >95% of eTeNT.GFP+ are CtB+. Minimally, there should be comparative analysis of the maps of each.

2) We require a thorough analysis of speed in all the forms of locomotion tested. The potentially most exciting aspect of the work is the context dependence. However, the authors must demonstrate that the other behaviors that were unperturbed were operating over the same speed range. Otherwise this changes the interpretation altogether. Instead of the same movement pattern being perturbed in one context but not in the other, it would instead suggest that a particular movement pattern is disrupted, and this is most obvious in contexts when that pattern is utilized.

Reviewer #1:

This paper explores the functional role of long-range ascending projection neurons (LAPNs) that connect rostral lumbar and mid-caudal cervical spinal enlargements in rats. The authors use a viral combinatorial strategy that can selectively and reversibly silence neurons based on their projection patterns. The authors then use a battery of behavioral tests to reveal the impact of LAPNs on coordination within and between the limbs. While no impact was observed in coordination within limbs, the authors find that coordination between limbs was disrupted by their perturbations. Strikingly, this effect was observed not only for coordination between hindlimbs and forelimbs (as expected based on their projection patterns), but also for coordination between the left- and right sides. This was thought to rely on local connections and now appears to also rely on these LAPNs. Since the projection patterns are the only defining feature presented here, the identity of these neurons is still unclear. However, the authors demonstrate that this impact is context-dependent, meaning that locomotion in different behavioral contexts is not always consistently altered. Specifically, the phenotype is most obvious during overground locomotion on a gripping surface, but not during treadmill locomotion, nose-down exploratory locomotion, slippy surface locomotion and swimming. The writing is clear and the figures are beautiful, however I have some suggestions regarding analysis and interpretation that I hope help bolster their conclusions.

Major comments:

1) The authors state that chemical based tracers can label fibers of passage, while viruses do not (subsection “Histological detection of putatively silenced LAPNs”). It seems critical to confirm that their viral labeling is labeling the same populations in L1-3 as their tracers do. There are examples provided for labeling in Figure 2J-L, but no detailed segmental or laminar analysis as provided for tracer labeling. It is also not clear what sort of variability from animal to animal they observed in labeling. Was it always bilateral and limited to laminae 6-7 in L1-3? Without a better idea of which neurons were labeled where and how reliably, it is difficult to interpret the subsequent behavioral tests. For example, subsection “LAPNs organize interlimb coupling at each girdle during overground stepping”, were different stepping behaviors observed within the same animal or different gaits in different animals? Could differences in extent of labeling account for weaker versus stronger effects?

2) As I understand it, eTeNT and GFP expression should be linked and activated by retrograde transport to the soma. So, it's not clear to me why somatic GFP labeling would be much dimmer than axon terminal labeling, if eTeNT and GFP at the terminals are arriving anterogradely from the soma (at least that is what I surmised from the need for GFP signal amplification in subsection “Histological detection of putatively silenced LAPNs”). Apologies if I've misunderstood something. A more systematic analysis of eTeNT-GFP expression patterns along the rostrocaudal axis would help with this concern too.

3) From the contour density analysis in Figure 1H-J, there appear to be differences in the relative bilateral distribution of ipsi and contra cells (if I am interpreting the yellow and blue lines correctly) that indicate systematic differences in the distribution of ipsi versus contra LAPNs as you move caudally. Also, there are differences in lamina distribution in L3 compared to L1 and L2 (Figure 1M-O). It is difficult to understand the functional implications or why the authors carried out this analysis without a bit more information. All of the data are normalized to total, so it is difficult to get a handle on real numbers and variation.

4) The lack of any sort of identification, either by transcription factor or by transmitter phenotype, makes it difficult to generalize to other locomotor networks. Although glutamatergic and GABAergic axon terminals are identified, the source (whether ipsilateral or contralateral, L1,2,3 or elsewhere) is still unclear. Molecularly-defined excitatory and inhibitory spinal interneurons can migrate some distance from their point of origin, but tend to settle in consistent regions. If laminar distribution is an important clue to their identity (sensory, motor, other), it should be more clearly stated.

5) Rhythms within a limb aren't effected so I think it's safe to say that these LAPNs are not rhythm-generating. However, without a better idea of the identity of these neurons, one cannot rule out the possibility that they are sensory interneurons relaying proprioceptive or exteroceptive signals. I think this possibility should be raised in the Discussion section along with a potential pattern-forming motor function.

6) Since different speeds of locomotion are used in different behavioral contexts, it is difficult to separate which of these two features is more important with the current analysis. For example, if bilateral synchrony is observed at faster speeds, then behaviors that are slow would not be affected. It would be worth plotting the phase data as a function of speed in the overground behavioral tasks (e.g., Figure 3), to see if bilateral activity becomes more obvious at faster speeds or if it is observed over the entire speed range. Similarly, it would be good to know the speed range/cycle duration of the other tasks (e.g., treadmill stepping subsection “Silencing LAPNs disrupts interlimb coordination independent from the salient features of locomotion.”) to see how they may overlap. For example, the Arber lab observed no effects on slow treadmill locomotion when they ablated LDPNs, only at fast speeds was a deficit observed. I couldn't find the range of speeds used for treadmill locomotion, but these should be reported.

7) From Figure 5, it looks like the Dox treated mice are capable of moving faster (cm/s) than controls (panels C-F, H-K, M-P). Could this also explain the increased co-contraction? They are operating in a higher speed regime for more time? Plotting phase against frequency in control and Dox treated animals would also help determine whether this is a context- versus speed-dependent phenomenon.

Reviewer #2:

Procratsky and colleagues provide an anatomical and functional evaluation of long ascending propriospinal neurons (LAPNs) connecting lumbar hindlimb-related segments and cervical forelimb-related segments. They use an elegant method (developed by Tadashi Isa) to specifically and reversibly silence LAPNs in rat, expecting to uncouple fore/hindlimb coordination. Instead, they observe changes in left-right coupling that occur only during non-exploratory locomotion on high friction surfaces. This study is well-presented and the datasets are comprehensive, and the findings are thought-provoking.

In addition to the unexpected (and quite puzzling) primary result, there are other key findings of interest, including the identification of spinal neurons involved in locomotion in a context-dependent manner, and a potential demonstration that disruption of locomotor pattern that does not affect the rhythm. Further, it is exciting to see reversable silencing experiments in an animal model aside from transgenic mice. These results are novel and contribute to our understanding of the spinal locomotor circuit.

Major comments:

1) For the interpretation of manipulation studies, it is essential to know which neurons are being targeted. The CtB and eTeNT.EGFP histology presented does not directly get at this issue. On one hand, the CtB data provides a thorough description of lumbar LAPNs. However, the overlap with the neurons being manipulated with the eTeNT is missing and, as pointed out by the authors, CtB labels fibers of passage which belong to neurons that are not being silenced. This raises the question of whether the eTeNT.GFP directly overlaps with the CtB-labeled populations, just the numbers are less, or are there specific regions where there are eTeNT.GFP neurons within the more widespread CtB labeling? This is not possible to determine with the results presented in Figure 2. A mapping similar to what was performed for the CtB data would allow the reader to compare and would be helpful to assess exactly what is being manipulated.

2) I'm not entirely convinced one can conclude that the local commissural projections of the LAPNs are minor from the data presented. According to Figure 1—figure supplement 1, it is about 10% of the commissural LAPNs that do have projections to L1 and L5 (30% of 16% in L1 + 45% of 9% in L5 = ~10%). This is not counting any that may project within segments L2-L4 and even if that's just an additional 5%/segment, that could be 25% which is substantial. The tracer would have needed to be injected into a wider region of the contralateral cord and a low overlap observed to make this conclusion (but if the experiment were to be performed in this way, information regarding ipsilateral LAPNs would have been lost).

3) Following the previous point, there may be significant overlap with the V0 and V2a populations here. It is impossible to know for certain as the overlap of the LAPNs manipulated here with genetic populations cannot be determined and the mouse work does not detail the degree to which local vs LPNs are manipulated. Where the presented locomotor phenotype is similar in some ways to the phenotype seen in V0V and V2a mutants (i.e. left/right synchrony are more prominent and observed at a lower locomotor frequency ), there are distinct differences between the findings here and the mouse studies (trot is lost in the mouse mutants but it is present in the rats, the speed profiles are more compressed in the genetic mutants and that does not seem to be the case here, LAPN silencing effects depend on condition, etc.). Can these experiments be considered as complementary and, if so, does this provide additional insight into the circuitry?

4) It seems that the figure that was uploaded as Supplementary Figure 5 is incorrect. The figure is identical to Figure 5 but figure legend does not match.

5) In the Discussion section, although it was clear that the authors expected that forelimb and hindlimb coordination would be disrupted and the lack of that finding is well-described, there is no discussion about why this is not the case. Additionally, the suggestion of LAPNs being "distributors of temporal information" comes up a few times (Discussion section). How that may result in the locomotor changes seen in the data is not obvious and it would help to have an expansion of that idea for clarification.

Reviewer #3:

Long propriospinal neurons link motor circuits involved in the control of forelimbs and hindlimbs. Locomotion requires the constant coordination of forelimb and hindlimbs and this likely involves long propriospinal neurons. To what extent these neurons influence the rhythm and pattern of limb activity across limbs and within each girdle is not well understood. This study uses doxycycline-mediated TeNT silencing of long ascending propriospinal neurons whose cell bodies reside mainly in L1-L3 segments of the spinal cord to provide insights into the role of long propriospinal neurons in limb coordination. Their results suggest that these neurons are involved with intra-girdle and interlimb coordination in a manner that is independent of the regulation of general features of locomotion such as limb kinematics, as well as stride times and lengths, and durations of different phases. Interestingly, the disruption of coordination occurs within only certain types of activity such as overground stepping, and not during treadmill walking or exploratory activity.

Overall, the experiments are done rigorously. A number of controls have been done to suggest that neurons affected by Dox are indeed long ascending propriospinal neurons from L1-L3. Many features of locomotor activity have been taken into consideration in their analysis. Data capture for locomotor activity used several different approaches and appears well done, however, certain experimental details need some clarification (see discussion of treadmill experiments below). The study of different forms of locomotor activity provides greater insight into the possible roles of long ascending propriospinal neurons and is a strength of this work. The insights from this study advance our understanding of how spinal circuitry regulates different facets of locomotor activity and pushes the field to consider that the contributions of spinal circuits shift depending on the type of activity performed.

We have one substantive concern to raise that is related to whether there is a speed-dependence related to the loss of coordination. This issue stems from data illustrated in Figure 5 where steps in Dox-treated animals are colour-coded to show the steps that are unaffected (red) and those that are affected (blue). It looks like affected steps (blue) are on average occurring at higher speeds than those that are not (red). This suggests that loss of coordination is more likely at higher speeds in Dox-treated animals. Could it be that the differences seen in a different context are purely related to the speed of locomotion achieved in these different locomotor activities? The Dox-treated animals appear to have a greater proportion of strides performed at a fast pace (>90 cm/s) than controls in the volitional locomotion experiment (Figure 5C-P). Perhaps re-analyzing using a sample of steps uniformly distributed across speeds in control and Dox-treated animals could answer whether loss of coordination is speed-dependent or context-dependent.

In the same line as above, we did not find details related to the speeds tested for the treadmill experiments. Were the animals tested on the treadmill at multiple speeds (ie. slow, medium, fast)? If so – what speeds were tested and were any differences noted? Similarly, were the average walking speeds different between trials on uncoated and Sylgard-coated surfaces? These details could provide a common factor that explains the apparent context-dependence of the data.

Finally, while the data clearly demonstrate abnormalities in intra-girdle patterning following inhibition of the LAPNs, the basis for these abnormalities isn't clear. The effects on the hindlimb pattern are particularly perplexing if we assume that since the LAPNs are unlikely to directly interact with the lumbar CPG based upon their sparser connectivity within the lumbar spinal cord. Rather than the LAPNs being necessary for intra-girdle coordination, is it not more plausible that they act by compensating for the proprioceptive confound caused by forward propulsion from the opposite girdle? This could also help to explain why volitional locomotion – where there is likely more variation in speed (and thus more sensory confounds from acceleration and deceleration) – exhibited more gait abnormalities than treadmill walking. While this difference in interpretation might seem trivial, it would help to fit these results within the context of spinal cord injury literature – wherein loss of LAPN connections to the cervical spinal cord by thoracic transection has not (to our knowledge) produced similar forelimb gait abnormalities. In these spinal cord injured animals, the hindlimbs do not produce forward propulsion, and therefore do not have a destabilizing influence on forelimb proprioception/CPG function – thus not necessitating LAPN input to maintain appropriate forelimb alternation. Further discussion or justification for the current interpretation of the results should be provided.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Thank you for resubmitting your article "Long ascending propriospinal neurons provide flexible, context-specific control of interlimb coordination" for consideration by eLife. Your revised article has been reviewed by Ronald Calabrese as the Senior Editor, a Reviewing Editor, and three reviewers. The following individuals involved in review of your submission have agreed to reveal their identity: Tuan V Bui (Reviewer #3).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission. In recognition of the fact that revisions may take longer than the two months we typically allow, until the research enterprise restarts in full, we will give authors as much time as they need to submit revised manuscripts.

Summary:

The paper has been much improved by new experiments, clarifications, and rewriting. Nevertheless, significant changes are needed before the paper can be published in eLife.

Essential revisions:

Quantification (alternative changes provided):

In response to our comments the authors have provided a viral labeling method that better matches the approach used to silence neurons. While it is still not the same construct, it is a closer approximation. Indeed, this demonstrates that the method used to characterize LAPNs in Figure 1 overestimates the populations labeled. However, the authors have chosen to focus exclusively on ipsilateral populations, when data from Figure 1 clearly illustrate that commissural populations make up a larger fraction of the LAPN population (significant difference, little overlap in values, but downplayed in the main test). The new data are included as 'supplemental', when these are the key experiment to demonstrate which populations are labeled. Since much of the analysis in Figure 1 is not raised in the results and since the authors have already published data describing the populations of LAPNs in the lumbar spinal cord, this figure no longer seems relevant. Instead we suggest one of the following:

Alternative 1

a) A more detailed analysis of the new viral labeling strategies and their distribution on ipsilateral and contralateral sides of L1-2 to start out as Figure 1. This would provide more space to outline the caveats of the approach to the reader up front.

b) Move current Figure 1 into supplemental and provide some context and interpretation to the analysis you have performed and how it differs from their previous study (Reed et al., 2006). The authors say in their response that they do not want to speculate, but at least accurately reporting differences in distribution where they exist (e.g., L3 versus L1-2) is warranted. Particularly since labeling in L3 looks more like their new viral data. Also, please use bold colors instead of a gradient to mark laminae, since this is challenging to discern distinct laminae based on subtle shade differences. For this figure, it would also be more helpful for ease of interpretation, if the contour density analysis was pooled so that contra and ipsi populations are on different sides, not as they are based on dye labeling approaches (where one gets the impression one dye is better at labeling than the other or that contra populations also have ipsi projections or both).

Alternative 2

a) Remove current Figure 1 altogether and replace with more detailed analysis of the new viral labeling data.

Specificity of labeling (alternative changes provided):

The bright local labeling presented in Figure 2 is explained in the response to reviews, but not in the main text. The utility of this figure is also not clear, since the new labeling data better serve this purpose. Also, the new data suggest that axons of passage can be labeled by their CTB label, yet there are no L2 neurons labeled by injecting in L1 (Figure 1—figure supplement 1). Some clarification here is required, since the current argument is that spinocerebellar neurons are labeled as axons of passage. The point of this experiment is also not clearly articulated and just adds confusion.

We suggest one of the following:

Alternative 1:

a) Moving Figure 2 to supplemental, with a stronger statement or data supporting the idea that this does not reflect more proximal ectopic labeling. For example, were sections performed in cervical or thoracic levels to rule this out? Is this technically impossible or controlled for in past work? In addition, marking the laminae in which the labeled neurons are located would help link to new viral labeling work.

b) Provide a better justification for the experiments and an interpretation of the lack of labeling using local injections.

Alternative 2:

a) Removing Figure 2, since the new labeling experiments serve this purpose and do not raise as many questions.

Data curation (alternative changes provided):

Much of the critical data is currently found in supplemental, which could replace current main figure components that convey the same information. For example, in Figure 3, the running mouse illustrations are beautiful in panels c-e, but they take up a large fraction of the figure and add little beyond what is presented in panel b with respect to differences in coordination. Also, Figure 3 sets up the interlimb coordination differences, then moves to Figure 4 which demonstrates no impact on intralimb effects, then moves back to interlimb differences in Figure 5, requiring another cartoon summary of different gaits. Space could be saved for the inclusion of supplemental data if the figures are re-ordered. We suggest one of the following:

Alternative 1:

a) Re-order the figures, so that a new Figure 1 deals with the method of labeling and distribution of neurons with bilateral analysis, Figure 2 deals with the lack of impact on rhythm generation, as expected. Then Figure 3 and Figure 4 move into the impact on left-right alternation and limb coordination. In particular, moving data from Figure 5—figure supplement 2 into the main figures is strongly encouraged.

Alternative 2:

a) Keep figure ordered as they are, but reduce redundant information in figures (e.g., introductory cartoons) to make room for supplemental data that make key arguments (e.g., Figure 5—figure supplement 2). For example, panel 3C could be incorporated into panel 3B and panels 3B and 5A essentially convey the same information.

Speed versus context control:

The revision still does not rule out the possibility that Dox silencing is simply most obvious in contexts when the animal must move at faster speeds. It seems clear that silencing pushes the animals into a faster range of frequencies and the premature adoption of gaits normally used during very fast locomotion. This would be consistent with the impact of disruptions to spinal interneuronal control circuits in mammals and bolster their argument that LAPNs play similar roles in coordination. For over-ground locomotion (Figure 5—figure supplement 2), altered steps dominate the shift to higher speeds (cm/s). For treadmill locomotion, the mouse does not reach the higher range of speeds observed during over-ground locomotion and instead appears to use a strategy more reliant on longer stride times and lower stride frequencies. So, the lack of altered steps could be because the animal is not pushed to move as fast and adopts a different locomotor strategy (that is still impacted by Dox silencing, but not as much because deficits are always more obvious at faster speeds). The same argument could be made for exploratory mode walking, where the animal is not pushed to move as fast. The coated surface is like over-ground because they can reach faster speeds, while the smooth one is a bit slower (cm/s wise) and so not as impacted. Overall, it seems that deficits evoked by Dox silencing are most obvious in contexts in which the animal needs to move faster, not because they are moving the same way in different contexts however Dox silencing preferentially impacts one context. To better rule out this possibility, we suggest the following:

a) Statistical tests of the overall speeds between tasks in addition to the within-tasks analysis of altered versus unaltered that you've already performed. This is presented in Figure 5—figure supplement 2E, but no stats are reported, and it looks like the movements most greatly impacted are ones that have the highest range of frequencies (over-ground and coated, grey bars). If this is significant, the idea that speed is playing a role needs to be considered in the interpretation presented.

https://doi.org/10.7554/eLife.53565.sa1

Author response

Essential revisions:

All the reviewers were supportive of the work, while voicing significant concerns. All the complementary concerns of the reviewers should be addressed. Two issues arose as shared concerns of the reviewers.

1) We require further analysis of which neurons the viral strategy is labeling/manipulating, perhaps using the tissue used in Figure 2. Is this labeling similar to the CtB? If not, how? Are the differences laminar-related? Ideally, the authors should show that most or a subset of CtB labeled neurons are eTeNT.GFP+, and more importantly that >95% of eTeNT.GFP+ are CtB+. Minimally, there should be comparative analysis of the maps of each.

We did not have sufficient tissue from the animals that were assessed behaviorally to perform the exact comparison requested. However, we generated an independent set of animals using viral tracing and detailed both the numbers of infected cells and their laminar location for unilaterally projecting LAPNs. The new supplemental figure 2 quantifies those data and shows heat maps and neuron counts that are compared directly with the existing heat maps of CTB+ neurons. We observe that the comparison between the CTB and virally-labeled neurons highly corresponds with the outlier being the larger percentage of CTB+ lamina 5 neurons. These likely reflect spinocerebellar neurons (Matsushita, 1999; Arsenio Nunes and Sotelo, 1985) whose fibers of passage were labeled by CTB. These data highlight the greater specificity of viral labeling which is based both on cell soma and axon terminal locations. These results and relevant discussion have been added to the text.

2) We require a thorough analysis of speed in all the forms of locomotion tested. The potentially most exciting aspect of the work is the context dependence. However, the authors must demonstrate that the other behaviors that were unperturbed were operating over the same speed range. Otherwise this changes the interpretation altogether. Instead of the same movement pattern being perturbed in one context but not in the other, it would instead suggest that a particular movement pattern is disrupted, and this is most obvious in contexts when that pattern is utilized.

We appreciate this critical feedback and agree that a more in-depth exploration of speed is necessary across the behavioral contexts. Our new Figure 5—figure supplement 2 focuses on the speed ranges observed across the various behavioral conditions. We concentrated on the hindlimbs as this was the site most affected by LAPN silencing and presented the data in a format similar to that of Figure 5 (speed vs hindlimb stride time/frequency/length) as it clearly illustrates the full variability observed across all datasets.

Key outcomes illustrated include:

a) The speed range (minimum-maximum) observed across each behavioral condition at Control time points (gray inset in panels a-dd). These values reflect the instantaneous, per-step speed observed with each successive step cycle. Outcome(s): the various behavioral conditions show overlapping speed ranges at Control time points.

b) Expanded speed ranges observed during DoxOn are illustrated with pink insets. Outcome(s): apart from treadmill stepping, the speed range observed is expanded during DoxOn LAPN silencing (detect slower and faster speeds as compared to control time points). The increased expansion observed is still well below the speed at which synchronous-like gaits such as half and full bound are observed in adult rats (as shown in Figure 5 and previously published – references previously reported within text).

c) The DoxOn data (with irregular steps shown in yellow) is overlaid onto the control speed range. Outcome(s): across each behavioral condition, the majority of DoxOn steps fall within speed ranges observed at control time points.

d) The percent of silencing-induced irregular steps that fall within the control speed range across is behavioral context is reported in panels b, d, f, h, and j. Outcome(s): the preponderance of altered step cycles falls within the control speed range for each behavioral condition.

e) All speed ranges observed across each behavioral context are plotted together in panel ee. Data reported includes: (i) the speed range observed at control time points (gray bars), (ii) DoxOn time points (red bars), and (iii) DoxOn-induced irregular steps (yellow bars). (iv) Control and DoxOn averages and standard deviations are overlaid onto the corresponding bar plots.

f) The overground stepping data was binned for further analysis where we compared the proportion of steps that were ≤90 cm/s vs >90 cm/s for all DoxOn steps as well as the irregular steps only. Analyses were performed for left-right forelimb and left-right hindlimb coordination, respectively. Outcome(s): the majority of DoxOn steps were ≤90 cm/s and we saw no association between higher speeds (>90 cm/s) and number of irregular steps observed (hypothesis tested: if speed was a contributing factor, then we would see a significant proportion of irregular steps taken at >90 cm/s).

g) data not shown but reported in results (subsection “Silencing-induced disruption to interlimb coordination is context-dependent”). The phase-speed relationship was also quantitatively assessed, testing the hypothesis that changes in speed correlate with changes in coordination (ergo gait switches). We first tested this association in our long-tank gait dataset where rats expressed their full gait repertoire at the corresponding naturalistic speeds. As expected, we saw a predictable relationship between increased speed and corresponding changes to hindlimb coordination (Spearman Rank correlation coefficient = 0.753, N=12 age-matched control rats, n=403 total steps analyzed). When we ran similar comparisons for the DoxOn overground stepping dataset, no predictable relationship was detected with a weak correlation coefficient of 0.410 (N=13 rats, n=600 total steps analyzed).

These additional analyses show that animals (with or without silencing) express overlapping speed ranges across the various behavioral contexts. Silencing LAPNs does expand the speed range expressed. The expansion of speeds observed may be a consequence, but not a cause of the totality of silencing-induced changes to interlimb coordination.

Reviewer #1:

This paper explores the functional role of long-range ascending projection neurons (LAPNs) that connect rostral lumbar and mid-caudal cervical spinal enlargements in rats. The authors use a viral combinatorial strategy that can selectively and reversibly silence neurons based on their projection patterns. The authors then use a battery of behavioral tests to reveal the impact of LAPNs on coordination within and between the limbs. While no impact was observed in coordination within limbs, the authors find that coordination between limbs was disrupted by their perturbations. Strikingly, this effect was observed not only for coordination between hindlimbs and forelimbs (as expected based on their projection patterns), but also for coordination between the left- and right sides. This was thought to rely on local connections and now appears to also rely on these LAPNs. Since the projection patterns are the only defining feature presented here, the identity of these neurons is still unclear. However, the authors demonstrate that this impact is context-dependent, meaning that locomotion in different behavioral contexts is not always consistently altered. Specifically, the phenotype is most obvious during overground locomotion on a gripping surface, but not during treadmill locomotion, nose-down exploratory locomotion, slippy surface locomotion and swimming. The writing is clear and the figures are beautiful, however I have some suggestions regarding analysis and interpretation that I hope help bolster their conclusions.

Major comments:

1) The authors state that chemical based tracers can label fibers of passage, while viruses do not (subsection “Histological detection of putatively silenced LAPNs”). It seems critical to confirm that their viral labeling is labeling the same populations in L1-3 as their tracers do. There are examples provided for labeling in Figure 2J-L, but no detailed segmental or laminar analysis as provided for tracer labeling. It is also not clear what sort of variability from animal to animal they observed in labeling. Was it always bilateral and limited to laminae 6-7 in L1-3? Without a better idea of which neurons were labeled where and how reliably, it is difficult to interpret the subsequent behavioral tests. For example, subsection “LAPNs organize interlimb coupling at each girdle during overground stepping”, were different stepping behaviors observed within the same animal or different gaits in different animals? Could differences in extent of labeling account for weaker versus stronger effects?

See comment 1 above and the new Figure 5—figure supplement 2.

2) As I understand it, eTeNT and GFP expression should be linked and activated by retrograde transport to the soma. So, it's not clear to me why somatic GFP labeling would be much dimmer than axon terminal labeling, if eTeNT and GFP at the terminals are arriving anterogradely from the soma (at least that is what I surmised from the need for GFP signal amplification in subsection “Histological detection of putatively silenced LAPNs”). Apologies if I've misunderstood something. A more systematic analysis of eTeNT-GFP expression patterns along the rostrocaudal axis would help with this concern too.

The reviewer is correct – the transgene expressed is an eTeNT-EGFP fusion protein which is expressed in double infected neurons, but is only activated when doxcycyline is provided ad libitum. The dimmer labeling in the somata has puzzled us as well. We’ve attempted to address this issue by adjusting various technical parameters to no avail, including changes to the fixation (e.g. overnight vs 1-3 hours post-fixation) with or without antigen retrieval, using various anti-GFP antibodies (e.g. mouse, rabbit, chicken, goat), and modifying the histological protocol itself (e.g. various buffers, detergents, serums), and using 3,3′-Diaminobenzidine (DAB) enhancement.

One explanation for weak EGFP expression could be that the eTeNT-EGFP fusion protein is concentrated in the axons terminals as it is actively transported in a small volume. Cell body eTeNT-EGFP may be too dilute to enable that larger signal:background ratio. Alternatively, the lower signal could arise from our emphasis on acute silencing. To avoid potential silencing-induced compensatory mechanisms, we collected tissue at 5 days of doxycycline. This time frame was sufficient to detect functional changes, but could be insufficient for robust histological detection of eTeNT-EGFP. Indeed, the beautiful somatic labeling detected in the original viral vector paper was generated following longer durations of silencing (Kinoshita et al., 2012). Another plausible explanation is that our viral titer was too low for robust EGFP-based labeling. In the Kinoshita et al., (2012), the eTeNT.EGFP and AAV titers were x1011 and x1013, respectively. With our in-house methods and equipment, we were only able to generate virus of x107 and x1012, respectively. However, even with lower cell soma concentration of eTeNT-EGFP, terminal levels were obviously sufficient to functionally alter synaptic transmission.

3) From the contour density analysis in Figure 1H-J, there appear to be differences in the relative bilateral distribution of ipsi and contra cells (if I am interpreting the yellow and blue lines correctly) that indicate systematic differences in the distribution of ipsi versus contra LAPNs as you move caudally. Also, there are differences in lamina distribution in L3 compared to L1 and L2 (Figure 1M-O). It is difficult to understand the functional implications or why the authors carried out this analysis without a bit more information. All of the data are normalized to total, so it is difficult to get a handle on real numbers and variation.

These differences are “real”, in that the variability is relatively modest given that the technique has some inherent variability in pipette localization, volume, etc. We did not provide additional information simply because there wasn’t much more to say that would not be purely speculative and since the literature provides little to go on in terms of L2 and L3 differences in interneuron populations/distributions and any functional implications, at least in our opinion.

We decided to perform these experiments given the unresolvable technical issues we had with detecting the double-infected somata. Using identical methods for the cervical viral injections (e.g. age/sex/strain of rats, injection coordinates and volume), we injected CtB to robustly label the somata thereby allowing us to perform subsequent anatomical analyses.

4) The lack of any sort of identification, either by transcription factor or by transmitter phenotype, makes it difficult to generalize to other locomotor networks. Although glutamatergic and GABAergic axon terminals are identified, the source (whether ipsilateral or contralateral, L1,2,3 or elsewhere) is still unclear. Molecularly-defined excitatory and inhibitory spinal interneurons can migrate some distance from their point of origin, but tend to settle in consistent regions. If laminar distribution is an important clue to their identity (sensory, motor, other), it should be more clearly stated.

We have not provided information/discussion along these lines, again because, in the absence of techniques able to classify interneurons in adult rat spinal cord tissue, it would be purely speculative and perhaps detract from the primary point. The transcription factors that classically delineate the various ventrally-derived “V-class” of spinal interneurons are developmentally regulated. Few are expressed beyond postnatal maturation, thus precluding post hoc V-class categorization in our adult rat tissue through immunohistochemical approaches.

The closest approximation of how our LAPNs fit into the transcriptionally delineated locomotor framework comes from Silvia Arber’s group (Ruder et al., 2016). Using intersectional breeding and viral-based fluorescent tagging, she has shown that V0 (Dbx1-expressing) and V2 (Shox2-expressing) progenitor domains give rise to lumbo-cervical spinal neurons. Contralateral projections predominantly arise from V0-Dbx1 while ipsilateral from V2-Shox2. With AAV-flex injections into the lumbar segments of vGlutOn or vGATOn mice, she revealed that the bulk are excitatory in nature with comparatively fewer inhibitory lumbo-cervical projections which are preferentially confined to the ventral horn of the caudal cervical enlargement.

We mapped the LAPN laminar distributions and found that these neurons are embedded within regions where proprioceptive afferent input or descending drive access the spinal locomotor circuitry (Noga et al., 1995). However, this is not really conclusive, and we would prefer to limit discussion in this area.

5) Rhythms within a limb aren't effected so I think it's safe to say that these LAPNs are not rhythm-generating. However, without a better idea of the identity of these neurons, one cannot rule out the possibility that they are sensory interneurons relaying proprioceptive or exteroceptive signals. I think this possibility should be raised in the discussion along with a potential pattern-forming motor function.

We agree that we certainly cannot rule out that these neurons are relaying primarily sensory information or sensory-derived temporal information. We have included that in the current Discussion section and have added emphasis to this possibility in the appropriate paragraph, as follows: “Alternatively, it might be derived principally or entirely from hindlimb afferent input carrying temporal information associated with paw contact…”. We hope this is sufficient.

6) Since different speeds of locomotion are used in different behavioral contexts, it is difficult to separate which of these two features is more important with the current analysis. For example, if bilateral synchrony is observed at faster speeds, then behaviors that are slow would not be affected. It would be worth plotting the phase data as a function of speed in the overground behavioral tasks (e.g., Figure 3), to see if bilateral activity becomes more obvious at faster speeds or if it is observed over the entire speed range. Similarly, it would be good to know the speed range/cycle duration of the other tasks (e.g., treadmill stepping subsection “Silencing LAPNs disrupts interlimb coordination independent from the salient features of locomotion.”) to see how they may overlap. For example, the Arber lab observed no effects on slow treadmill locomotion when they ablated LDPNs, only at fast speeds was a deficit observed. I couldn't find the range of speeds used for treadmill locomotion, but these should be reported.

See comment 1 above and the new Figure 5—figure supplement 2.

7) From Figure 5, it looks like the Dox treated mice are capable of moving faster (cm/s) than controls (panels C-F, H-K, M-P). Could this also explain the increased co-contraction? They are operating in a higher speed regime for more time? Plotting phase against frequency in control and Dox treated animals would also help determine whether this is a context- versus speed-dependent phenomenon.

We would argue that the rats are expressing a larger range of speeds during silencing, rather than being “capable of moving faster” and this may be due to natural tendency for a non-alternating pattern to be easier to perform when moving faster. However, we think the main point is that silencing induced disrupted steps throughout the speed range, which immediately distinguishes it from normal speed-dependent gait changes. We would argue that this concern should be alleviated by our results showing speed-dependent changes, since there is a strong relationship between speed and frequency. These data are found in Figure 4 and Figure 4—figure supplement 1 and Figure 4—figure supplement 2, and in the new Figure 5—figure supplement 2. Also, see comment 1 above. This has been added to the final paragraph of the Results section.

Reviewer #2:

Procratsky and colleagues provide an anatomical and functional evaluation of long ascending propriospinal neurons (LAPNs) connecting lumbar hindlimb-related segments and cervical forelimb-related segments. They use an elegant method (developed by Tadashi Isa) to specifically and reversibly silence LAPNs in rat, expecting to uncouple fore/hindlimb coordination. Instead, they observe changes in left-right coupling that occur only during non-exploratory locomotion on high friction surfaces. This study is well-presented and the datasets are comprehensive, and the findings are thought-provoking.

In addition to the unexpected (and quite puzzling) primary result, there are other key findings of interest, including the identification of spinal neurons involved in locomotion in a context-dependent manner, and a potential demonstration that disruption of locomotor pattern that does not affect the rhythm. Further, it is exciting to see reversable silencing experiments in an animal model aside from transgenic mice. These results are novel and contribute to our understanding of the spinal locomotor circuit.

Major comments:

1) For the interpretation of manipulation studies, it is essential to know which neurons are being targeted. The CtB and eTeNT.EGFP histology presented does not directly get at this issue. On one hand, the CtB data provides a thorough description of lumbar LAPNs. However, the overlap with the neurons being manipulated with the eTeNT is missing and, as pointed out by the authors, CtB labels fibers of passage which belong to neurons that are not being silenced. This raises the question of whether the eTeNT.GFP directly overlaps with the CtB-labeled populations, just the numbers are less, or are there specific regions where there are eTeNT.GFP neurons within the more widespread CtB labeling? This is not possible to determine with the results presented in Figure 2. A mapping similar to what was performed for the CtB data would allow the reader to compare and would be helpful to assess exactly what is being manipulated.

See comment 1.

2) I'm not entirely convinced one can conclude that the local commissural projections of the LAPNs are minor from the data presented. According to Figure 1—figure supplement 1, it is about 10% of the commissural LAPNs that do have projections to L1 and L5 (30% of 16% in L1 + 45% of 9% in L5 = ~10%). This is not counting any that may project within segments L2-L4 and even if that's just an additional 5%/segment, that could be 25% which is substantial. The tracer would have needed to be injected into a wider region of the contralateral cord and a low overlap observed to make this conclusion (but if the experiment were to be performed in this way, information regarding ipsilateral LAPNs would have been lost).

We anticipated that a much larger proportion of LAPNs would have extensive projections to L1 and L5, and thus our response to the “scarcity” was to refer to it that way. We agree that this does not rule out these projections as important for function, just that, if they are important functionally it is via fairly modest local outputs compared to what might be expected. We have altered the description of these data to indicate that these are “modest” rather than “sparse”. We have indicated the specificity of the experiment being limited to L1 and L5 (second paragraph of Results section) to ensure that the reader does not come to the wrong conclusion.

12) Following the previous point, there may be significant overlap with the V0 and V2a populations here. It is impossible to know for certain as the overlap of the LAPNs manipulated here with genetic populations cannot be determined and the mouse work does not detail the degree to which local vs LPNs are manipulated. Where the presented locomotor phenotype is similar in some ways to the phenotype seen in V0V and V2a mutants (i.e. left/right synchrony are more prominent and observed at a lower locomotor frequency ), there are distinct differences between the findings here and the mouse studies (trot is lost in the mouse mutants but it is present in the rats, the speed profiles are more compressed in the genetic mutants and that does not seem to be the case here, LAPN silencing effects depend on condition, etc.). Can these experiments be considered as complementary and, if so, does this provide additional insight into the circuitry?

The reviewer raises excellent points concerning the similarities/differences between our silencing approach in rats and the experiments using transgenic mouse models, which are clearly important for investigating how spinal circuits organize locomotor behaviors. Despite the dissimilarities in rodent models and methods, we consider these experiments to be complementary as each affords similar, yet distinct insight into how the spinal cord ultimately secures locomotion.

The genetic-based approach in the mouse affords large-scale, proof-of-concept circuit investigations into how the spinal cord broadly organizes movements. While emphasis is usually placed on the lumbar CPG for delineating roles in locomotion (e.g. fictive locomotion preparations in the elegant experiments of Crone et al., 2008; Crone et al., 2009; Dougherty and Kiehn, 2010; Zhong et al., 2010), the alternation-securing Chx10+ V2a interneurons and Dbx1+ V0v interneurons are actually distributed network throughout the entire spinal neuraxis (Francius et al., 2013) as well as supraspinal centers such as the forebrain (Dbx1+; Causeret et al., 2011) and medullary reticular formation, which in itself is a powerful modulator of locomotor behaviors (Chx10+; Bretzner and Brownstone 2013; Bouvier et al., 2015). Thus, it is somewhat unsurprising that a knockout/manipulation of a broadly distributed network based on its expression of a post (or pre)-mitotic transcription factor leads to a more prominent “all-or-none” phenomena, such as the striking “locked-in” hopping phenotype observed in V0-deleted mice (Talpalar et al., 2013).

Distinct, yet complementary to the large-scale approach described above is our comparatively small-scale, circuit-based approach. These are anatomical-driven investigations of the spinal locomotor circuitry and are designed to acutely and reversibly manipulate select pathways in the otherwise intact and mature nervous system, negating the potential confounding influences of compensatory mechanisms (e.g. compensation following developmental knockouts or plasticity following irreversible ablations) or unintended “off-target” effects (e.g. manipulating a broad and distributed class of neurons which is comprised of multiple subtypes of various functions). This subtler approach affords insight into not just the functional role (e.g. left-right hindlimb alternation), but also the functional importance of discrete pathways in securing locomotion. For example, we find that LAPNs are necessary for alternation during overground stepping, but dispensible for alternation during swimming.

4) It seems that the figure that was uploaded as Supplementary Figure 5 is incorrect. The figure is identical to Figure 5 but figure legend does not match.

We apologize for this mistake. It has been corrected. We are particularly disappointed about this mistake because we believe the data presented speaks to some of the concerns voiced regarding speed and phase.

5) In the Discussion section, although it was clear that the authors expected that forelimb and hindlimb coordination would be disrupted and the lack of that finding is well-described, there is no discussion about why this is not the case. Additionally, the suggestion of LAPNs being "distributors of temporal information" comes up a few times (Discussion section). How that may result in the locomotor changes seen in the data is not obvious and it would help to have an expansion of that idea for clarification.

We agree that this was not included in the discussion at any level. To correct this oversight we have added the following to the first paragraph of the Discussion section. Together, these studies indicate that inter-segmental projecting lumbar pathways are key distributors of temporal information that can be used for maintaining left-right alternating during overground locomotion, and that hindlimb-forelimb coordination is either secured by other means or is less vulnerable to disruption potentially requiring silencing of larger numbers or a wider range of long-propriospinal neurons.

Reviewer #3:

[…]

We have one substantive concern to raise that is related to whether there is a speed-dependence related to the loss of coordination. This issue stems from data illustrated in Figure 5 where steps in Dox-treated animals are colour-coded to show the steps that are unaffected (red) and those that are affected (blue). It looks like affected steps (blue) are on average occurring at higher speeds than those that are not (red). This suggests that loss of coordination is more likely at higher speeds in Dox-treated animals. Could it be that the differences seen in a different context are purely related to the speed of locomotion achieved in these different locomotor activities? The Dox-treated animals appear to have a greater proportion of strides performed at a fast pace (>90 cm/s) than controls in the volitional locomotion experiment (Figure 5C-P). Perhaps re-analyzing using a sample of steps uniformly distributed across speeds in control and Dox-treated animals could answer whether loss of coordination is speed-dependent or context-dependent.

This question/concern has been addressed in #2. The key point is that disrupted steps occurred at all speeds and, even in the different contexts there is no relationship suggesting that silencing induced higher speeds at which the disrupted steps occurred.

In the same line as above, we did not find details related to the speeds tested for the treadmill experiments. Were the animals tested on the treadmill at multiple speeds (ie. slow, medium, fast)? If so – what speeds were tested and were any differences noted? Similarly, were the average walking speeds different between trials on uncoated and Sylgard-coated surfaces? These details could provide a common factor that explains the apparent context-dependence of the data.

This question/concern has been addressed in comment 2.

18) Finally, while the data clearly demonstrate abnormalities in intra-girdle patterning following inhibition of the LAPNs, the basis for these abnormalities isn't clear. The effects on the hindlimb pattern are particularly perplexing if we assume that since the LAPNs are unlikely to directly interact with the lumbar CPG based upon their sparser connectivity within the lumbar spinal cord. Rather than the LAPNs being necessary for intra-girdle coordination, is it not more plausible that they act by compensating for the proprioceptive confound caused by forward propulsion from the opposite girdle? This could also help to explain why volitional locomotion – where there is likely more variation in speed (and thus more sensory confounds from acceleration and deceleration) – exhibited more gait abnormalities than treadmill walking. While this difference in interpretation might seem trivial, it would help to fit these results within the context of spinal cord injury literature – wherein loss of LAPN connections to the cervical spinal cord by thoracic transection has not (to our knowledge) produced similar forelimb gait abnormalities. In these spinal cord injured animals, the hindlimbs do not produce forward propulsion, and therefore do not have a destabilizing influence on forelimb proprioception/CPG function – thus not necessitating LAPN input to maintain appropriate forelimb alternation. Further discussion or justification for the current interpretation of the results should be provided.

We totally understand viewpoint and hope that the extensive analysis of speed-dependent changes has alleviated these concerns. See comment 2.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Summary:

The paper has been much improved by new experiments, clarifications, and rewriting. Nevertheless, significant changes are needed before the paper can be published in eLife.

Essential revisions:

Quantification (alternative changes provided):

In response to our comments the authors have provided a viral labeling method that better matches the approach used to silence neurons. While it is still not the same construct, it is a closer approximation. Indeed, this demonstrates that the method used to characterize LAPNs in Figure 1 overestimates the populations labeled. However, the authors have chosen to focus exclusively on ipsilateral populations, when data from Figure 1 clearly illustrate that commissural populations make up a larger fraction of the LAPN population (significant difference, little overlap in values, but downplayed in the main test). The new data are included as 'supplemental', when these are the key experiment to demonstrate which populations are labeled. Since much of the analysis in Figure 1 is not raised in the results and since the authors have already published data describing the populations of LAPNs in the lumbar spinal cord, this figure no longer seems relevant. Instead we suggest one of the following:

Alternative 1

a) A more detailed analysis of the new viral labeling strategies and their distribution on ipsilateral and contralateral sides of L1-2 to start out as Figure 1. This would provide more space to outline the caveats of the approach to the reader up front.

b) Move current Figure 1 into supplemental and provide some context and interpretation to the analysis you have performed and how it differs from their previous study (Reed et al., 2006). The authors say in their response that they do not want to speculate, but at least accurately reporting differences in distribution where they exist (e.g., L3 versus L1-2) is warranted. Particularly since labeling in L3 looks more like their new viral data. Also, please use bold colors instead of a gradient to mark laminae, since this is challenging to discern distinct laminae based on subtle shade differences. For this figure, it would also be more helpful for ease of interpretation, if the contour density analysis was pooled so that contra and ipsi populations are on different sides, not as they are based on dye labeling approaches (where one gets the impression one dye is better at labeling than the other or that contra populations also have ipsi projections or both).

Alternative 2

a) Remove current Figure 1 altogether and replace with more detailed analysis of the new viral labeling data.

Regarding the new viral labeling strategy, we focused on mapping the ipsilateral LAPNs in an effort to reduce the potential for artefactual labeling of fibers of passage. We believe this gave us a less ambiguous approach to compare CTB-labelled vs dual virus infected LAPNs. This rationale was not provided in the previous response and we apologize for any confusion it may have raised.

Our original intent for the CTB experiments was to determine how LAPNs are embedded within the lumbar spinal gray matter. Our previous anatomical research did provide quantitative data to address this question. Given the rhythmogenic capacity of the lumbar intermediate gray matter, we designed our CTB experiments to address this primary question (in addition to their projection patterns, which we described previously in Reed et al., 2006). To this end, the original CTB data achieve this goal.

We thank the reviewers for their suggestions. We have opted to pursue the Alternative 1b revision. The following changes have been made:

a) The CTB dataset (original Figure 1) has been moved to supplemental (Figure 1—figure supplement 1). Therefore, all CTB related data are now shown in Figure 1—figure supplement 1.

b) In the Figure 1—figure supplement 1, we switched to bold colors instead of a gradient to demarcate the laminae.

c) We appreciate the suggestion for revising the heatmaps and contour plots to aid in interpretation. We have since re-written our Matlab code to pool data generated from both CTB tracers to create a master contour (and heatmap) plot. Per the reviewer suggestion, we now show ipsi- and contralateral LAPNs on different sides (Figure 1—figure supplement 1). We have made the code openly accessible at GitHub (details provided on the Key Resources Table).

d) In terms of context, given the rather crude analysis we performed at the time (Reed et al., 2006) we believe the Fluororuby and current CTB approaches gave largely similar outcomes with respect to a broad characterization of LAPN anatomy. The only apparent differences are the relative lack of deep dorsal horn neurons in the L2 segments in Reed et al., as compared to the current data set, and these differences may likely be due to the overall lower numbers of neurons labeled with the less-efficient FR. We have removed the viral-based ipsilateral only labeling included in the last revision, so no further description or discussion is necessary in our opinion. The CTB labeling presented in supplemental figure 1 provides the needed anatomical description of the LAPN population being targeted for silencing.

Specificity of labeling (alternative changes provided):

The bright local labeling presented in Figure 2 is explained in the response to reviews, but not in the main text. The utility of this figure is also not clear, since the new labeling data better serve this purpose. Also, the new data suggest that axons of passage can be labeled by their CTB label, yet there are no L2 neurons labeled by injecting in L1 (Figure 1—figure supplement 1). Some clarification here is required, since the current argument is that spinocerebellar neurons are labeled as axons of passage. The point of this experiment is also not clearly articulated and just adds confusion.

We suggest one of the following:

Alternative 1:

a) Moving Figure 2 to supplemental, with a stronger statement or data supporting the idea that this does not reflect more proximal ectopic labeling. For example, were sections performed in cervical or thoracic levels to rule this out? Is this technically impossible or controlled for in past work? In addition, marking the laminae in which the labeled neurons are located would help link to new viral labeling work.

b) Provide a better justification for the experiments and an interpretation of the lack of labeling using local injections.

Alternative 2:

a) Removing Figure 2, since the new labeling experiments serve this purpose and do not raise as many questions.

We believe there might be some confusion regarding Figure 2. Data shown in the original Figure 2 are not CTB, but instead the histology from the eTeNT.EGFP silenced animals. The utility of these data is validation of the silencing constructs. Data shown confirm eTeNT.EGFP expression at the level of the terminal field and somata during Dox2On. Given this confusion, some of the Figure 2 revisions suggested are not applicable.

If the revisions suggested were indeed related to the CTB experiments and not eTeNT.EGFP, we would like to provide the following clarifications:

1) “The utility of this figure is also not clear, since the new labeling data better serve this purpose.”

As stated above, the utility of original Figure 2 was to validate the eTeNT.EGFP silencing construct through histological approaches. Given that we have moved original Figure 1 (CTB dataset) to supplemental per reviewer suggestions above, the original Figure 2 (eTeNT) is now Figure 1. We have updated it to include a schematic illustrating the injection paradigm and experimental design (Figure 1A).

2) “ Also, the new data suggest that axons of passage can be labeled by their CTB label, yet there is no L2 neurons labeled by injecting in L1 (Figure 1—figure supplement 1).”

We acknowledge that axons of passage could be labelled with CTB. However, it is also important to note that the more restricted labeling observed with the dual virus approach could also be by virtue of the technique itself. Given that neurons labelled must be double-infected via retrograde delivery of Cre followed by local delivery of Cre-sensitive AAV, and then undergo cre-recombination for fluorescent tagging, we expected fewer neurons to be labelled from the get-go. Nonetheless, our primary goal was to determine where within the lumbar rhythmogenic core LAPNs are embedded. We believe our CTB data adequately address this question.

While not shown in the supplementary figure, there are numerous L2 neurons labelled following injection at L1. This was not included as we have previously reported these data (Pocratsky et al., 2017, Figure 8 panels M-Q).

(3) “The point of this experiment is also not clearly articulated and just adds confusion.”

We hope we have clarified this with our response.

The original CTB dataset meets the original objective of reconciling where within the rhythmogenic lumbar gray matter LAPNs reside. To this end, the new viral labeling data provided using a separate two-virus system further supports the primary outcome from the CTB data (LAPNs reside within intermediate gray matter, laminae 5-8). Performing additional experiments using a dual virus labeling strategy will not provide significant insight beyond what we already show. As these data were reported for the benefit of reviewers and are not the primary focus of this manuscript (functional study), these data have been removed from the previous Supplemental Figure 1. The new Figure 1—figure supplement 1, revised based on reviewer suggestion related to CTB data, now presents the anatomical story for LAPNs.

Data curation (alternative changes provided):

Much of the critical data is currently found in supplemental, which could replace current main figure components that convey the same information. For example, in Figure 3, the running mouse illustrations are beautiful in panels c-e, but they take up a large fraction of the figure and add little beyond what is presented in panel b with respect to differences in coordination. Also, Figure 3 sets up the interlimb coordination differences, then moves to Figure 4 which demonstrates no impact on intralimb effects, then moves back to interlimb differences in Figure 5, requiring another cartoon summary of different gaits. Space could be saved for the inclusion of supplemental data if the figures are re-ordered. We suggest one of the following:

Alternative 1:

a) Re-order the figures, so that a new Figure 1 deals with the method of labeling and distribution of neurons with bilateral analysis, Figure 2 deals with the lack of impact on rhythm generation, as expected. Then Figure 3 and Figure 4 move into the impact on left-right alternation and limb coordination. In particular, moving data from Figure 5—figure supplement 2 into the main figures is strongly encouraged.

Alternative 2:

a) Keep figure ordered as they are, but reduce redundant information in figures (e.g., introductory cartoons) to make room for supplemental data that make key arguments (e.g., Figure 5—figure supplement 2). For example, panel 3C could be incorporated into panel 3B and panels 3B and 5A essentially convey the same information.

To reduce redundant information per Alternative 2a, we have removed the schematics illustrating the phenotype (Figure 2) and merged data shown in panels a-c in Figure 3 (intralimb coordination).

Data show in the previous Figure 5—figure supplement 2 is plotted in a manner to illustrate the full range of variability observed (speed vs spatiotemporal parameters for the various locomotor contexts). This format is identical to that shown in Figure 4. In the vein of reducing redundant information per reviewer request, we have elected to move panel ee from Figure 5—figure supplement 2 to Figure 5. Therefore, Figure 5 shows the proportion of disrupted hindlimb steps across the various locomotor contexts as well as the corresponding stepping speed range, mean, and standard deviation. Panel ee was selected in particular as it distills the salient points of the context-related speed data into an easy to interpret graph.

Speed versus context control:

The revision still does not rule out the possibility that Dox silencing is simply most obvious in contexts when the animal must move at faster speeds. It seems clear that silencing pushes the animals into a faster range of frequencies and the premature adoption of gaits normally used during very fast locomotion. This would be consistent with the impact of disruptions to spinal interneuronal control circuits in mammals and bolster their argument that LAPNs play similar roles in coordination. For over-ground locomotion (Figure 5—figure supplement 2), altered steps dominate the shift to higher speeds (cm/s). For treadmill locomotion, the mouse does not reach the higher range of speeds observed during over-ground locomotion and instead appears to use a strategy more reliant on longer stride times and lower stride frequencies. So, the lack of altered steps could be because the animal is not pushed to move as fast and adopts a different locomotor strategy (that is still impacted by Dox silencing, but not as much because deficits are always more obvious at faster speeds). The same argument could be made for exploratory mode walking, where the animal is not pushed to move as fast. The coated surface is like over-ground because they can reach faster speeds, while the smooth one is a bit slower (cm/s wise) and so not as impacted. Overall, it seems that deficits evoked by Dox silencing are most obvious in contexts in which the animal needs to move faster, not because they are moving the same way in different contexts however Dox silencing preferentially impacts one context. To better rule out this possibility, we suggest the following:

a) Statistical tests of the overall speeds between tasks in addition to the within-tasks analysis of altered versus unaltered that you've already performed. This is presented in Figure 5—figure supplement 2E, but no stats are reported, and it looks like the movements most greatly impacted are ones that have the highest range of frequencies (over-ground and coated, grey bars). If this is significant, the idea that speed is playing a role needs to be considered in the interpretation presented.

The reviewer indicated that the “altered steps dominate the shift to higher speeds.” We disagree. Data shown in Figure 5—figure supplement 1 panel B clearly shows that only ~4% of altered hindlimb steps occur at speeds beyond that observed at control time point (the “Dox expanded range” shown by the shaded pink-red region). Therefore, 96% of silencing-induced altered steps occur at walk-trot speeds observed during control stepping (normal left-right alternation). In addition, in Figure 5E we show that the vast majority of disrupted steps occurred at speeds that were shared across the behavioral contexts assessed, whether there were many steps disrupted (overground and coated) or few (exploratory and smooth). Finally, disrupted steps clearly occurred throughout the speed range (Figure 4). Also, please note that the data provided is raw, representing all the analyzed steps and is thus transparent. In short, we feel that there is no evidence supporting a relationship between disrupted steps and speed and further analytical efforts are not warranted.

https://doi.org/10.7554/eLife.53565.sa2

Article and author information

Author details

  1. Amanda M Pocratsky

    1. Department of Anatomical Sciences and Neurobiology, University of Louisville, Louisville, United States
    2. Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, United States
    Present address
    Department of Neuromuscular Diseases, Institute of Neurology, University College London, London, United Kingdom
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration
    Competing interests
    No competing interests declared
  2. Courtney T Shepard

    1. Department of Anatomical Sciences and Neurobiology, University of Louisville, Louisville, United States
    2. Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, United States
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared
  3. Johnny R Morehouse

    1. Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, United States
    2. Department of Neurological Surgery, University of Louisville, Louisville, United States
    Contribution
    Formal analysis, Validation, Methodology
    Competing interests
    No competing interests declared
  4. Darlene A Burke

    1. Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, United States
    2. Department of Neurological Surgery, University of Louisville, Louisville, United States
    Contribution
    Data curation, Formal analysis, Validation, Visualization
    Competing interests
    No competing interests declared
  5. Amberley S Riegler

    1. Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, United States
    2. Department of Neurological Surgery, University of Louisville, Louisville, United States
    Contribution
    Formal analysis, Investigation, Visualization
    Competing interests
    No competing interests declared
  6. Josiah T Hardin

    Speed School of Engineering, University of Louisville, Louisville, United States
    Contribution
    Data curation, Formal analysis, Visualization
    Competing interests
    No competing interests declared
  7. Jason E Beare

    1. Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, United States
    2. Cardiovascular Innovation Institute, Department of Physiology and Biophysics, University of Louisville, Louisville, United States
    Contribution
    Formal analysis, Visualization
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3988-1223
  8. Casey Hainline

    Speed School of Engineering, University of Louisville, Louisville, United States
    Contribution
    Data curation, Formal analysis, Visualization
    Competing interests
    No competing interests declared
  9. Gregory JR States

    1. Department of Anatomical Sciences and Neurobiology, University of Louisville, Louisville, United States
    2. Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, United States
    Contribution
    Formal analysis, Investigation, Visualization
    Competing interests
    No competing interests declared
  10. Brandon L Brown

    Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, United States
    Contribution
    Formal analysis, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
  11. Scott R Whittemore

    1. Department of Anatomical Sciences and Neurobiology, University of Louisville, Louisville, United States
    2. Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, United States
    3. Department of Neurological Surgery, University of Louisville, Louisville, United States
    Contribution
    Conceptualization, Supervision, Funding acquisition, Validation, Project administration
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6437-7200
  12. David SK Magnuson

    1. Department of Anatomical Sciences and Neurobiology, University of Louisville, Louisville, United States
    2. Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, United States
    3. Department of Neurological Surgery, University of Louisville, Louisville, United States
    4. Speed School of Engineering, University of Louisville, Louisville, United States
    Contribution
    Conceptualization, Supervision, Funding acquisition, Validation, Visualization
    For correspondence
    dsmagn01@louisville.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3816-3676

Funding

National Institute of Neurological Disorders and Stroke (R01 NS089324)

  • Scott R Whittemore
  • David SK Magnuson

National Institute of Neurological Disorders and Stroke (P30 GM103507)

  • Scott R Whittemore
  • David SK Magnuson

Kentucky Spinal Cord and Head Injury Research Trust (13-14)

  • Scott R Whittemore
  • David SK Magnuson

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

The authors thank Dr. Tadashi Isa and Dr. Akiya Watakabe for providing the silencing viral vector plasmids, Russell M Howard for assistance in vector production, Christine Yarberry for surgical support and Alice Shum-Siu for histological assistance.

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to the approved institutional animal care and use committee (IACUC) protocol (#16669) of the University of Louisville. All surgery was performed under sodium pentobarbital or isoflurane anesthesia, and every effort was made to minimize suffering.

Senior and Reviewing Editor

  1. Ronald L Calabrese, Emory University, United States

Reviewer

  1. Tuan V Bui, University of Ottawa, Canada

Publication history

  1. Received: November 13, 2019
  2. Accepted: September 8, 2020
  3. Accepted Manuscript published: September 9, 2020 (version 1)
  4. Version of Record published: September 30, 2020 (version 2)

Copyright

© 2020, Pocratsky et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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