Author Response
We appreciate the editor's and reviewers' time to review our manuscript. We will work on the suggestions and have provided an initial assessment of what we can do for our revised submission.
Reviewer #1 (Public Review):
Summary:
This study aimed to investigate the effects of optically stimulating the A13 region in healthy mice and a unilateral 6-OHDA mouse model of Parkinson's disease (PD). The primary objectives were to assess changes in locomotion, motor behaviors, and the neural connectome. For this, the authors examined the dopaminergic loss induced by 6-OHDA lesioning. They found a significant loss of tyrosine hydroxylase (TH+) neurons in the substantia nigra pars compacta (SNc) while the dopaminergic cells in the A13 region were largely preserved. Then, they optically stimulated the A13 region using a viral vector to deliver the channelrhodopsine (CamKII promoter). In both sham and PD model mice, optogenetic stimulation of the A13 region induced pro-locomotor effects, including increased locomotion, more locomotion bouts, longer durations of locomotion, and higher movement speeds. Additionally, PD model mice exhibited increased ipsilesional turning during A13 region photoactivation. Lastly, the authors used whole-brain imaging to explore changes in the A13 region's connectome after 6-OHDA lesions. These alterations involved a complex rewiring of neural circuits, impacting both afferent and efferent projections. In summary, this study unveiled the pro-locomotor effects of A13 region photoactivation in both healthy and PD model mice. The study also indicates the preservation of A13 dopaminergic cells and the anatomical changes in neural circuitry following PD-like lesions that represent the anatomical substrate for a parallel motor pathway.
Strengths:
These findings hold significant relevance for the field of motor control, providing valuable insights into the organization of the motor system in mammals. Additionally, they offer potential avenues for addressing motor deficits in Parkinson's disease (PD). The study fills a crucial knowledge gap, underscoring its importance, and the results bolster its clinical relevance and overall strength.
The authors adeptly set the stage for their research by framing the central questions in the introduction, and they provide thoughtful interpretations of the data in the discussion section. The results section, while straightforward, effectively supports the study's primary conclusion the pro-locomotor effects of A13 region stimulation, both in normal motor control and in the 6-OHDA model of brain damage.
We thank the reviewer for their positive comments.
Weaknesses:
- Anatomical investigation. I have a major concern regarding the anatomical investigation of plastic changes in the A13 connectome (Figures 4 and 5). While the methodology employed to assess the connectome is technically advanced and powerful, the results lack mechanistic insight at the cell or circuit level into the pro-locomotor effects of A13 region stimulation in both physiological and pathological conditions. This concern is exacerbated by a textual description of results that doesn't pinpoint precise brain areas or subareas but instead references large brain portions like the cortical plate, making it challenging to discern the implications for A13 stimulation. Lastly, the study is generally well-written with a smooth and straightforward style, but the connectome section presents challenges in readability and comprehension. The presentation of results, particularly the correlation matrices and correlation strength, doesn't facilitate biological understanding. It would be beneficial to explore specific pathways responsible for driving the locomotor effects of A13 stimulation, including examining the strength of connections to well-known locomotor-associated regions like the Pedunculopontine nucleus, Cuneiformis nucleus, LPGi, and others in the diencephalon, midbrain, pons, and medulla.
We considered two approaches initially. The first approach was to look at specific projections to the motor regions, focusing on the MLR. The second approach was to utilize a whole-brain analysis that is presented here. Given what we know about the zona incerta, especially its integrative role, we felt that a reasonable starting point was to examine the full connectome. The value of the whole-brain approach is that it provides a high-level overview of the afferents and efferents to the region. The changes in the brain that occur following Parkinson-like lesions, such as those in the nigrostriatal pathway, are known to be complex and can affect neighbouring regions such as the A13. Therefore, we wished to highlight the A13, which we considered a therapeutic target, and examine changes in connectivity that could occur following acute lesions affecting the SNc. We acknowledge that this study does not provide a causal link, but it presents the fundamental background information for subsequent hypothesis-driven, focused, region-specific analysis.
The terms provided were from the Allen Brain Atlas terminology and were presented as abbreviations. We have looked at other ways to present it, including a greater emphasis on raw numbers and highlighting motor-related subareas. We will rewrite the connectomics section to make it more accessible, reflecting the change in the figures.
Additionally, identifying the primary inputs to A13 associated with motor function would enhance the study's clarity and relevance.
This is a great point and could help simplify the whole-brain results. We can present the motor-related inputs and outputs as part of a new figure in the main paper and add accompanying text in the results section. This will help highlight possible therapeutic pathways. We can also enhance our discussion of these motor-related pathways. We will retain the entire dataset and present it in a supplementary table for those who are interested.
The study raises intriguing questions about compensatory mechanisms in Parkinson's disease and a new perspective on the preservation of dopaminergic cells in A13, despite the SNc degeneration, and the plastic changes to input/output matrices. To gain inspiration for a more straightforward reanalysis and discussion of the results, I recommend the authors refer to the paper titled "Specific populations of basal ganglia output neurons target distinct brain stem areas while collateralizing throughout the diencephalon from the David Kleinfeld laboratory." This could guide the authors in investigating motor pathways across different brain regions.
Thank you for the advice, and as pointed out, Kleinfeld’s group had a nice, focused presentation of their data. For the connectomic piece, we can certainly adopt their reporting style, which, as you point out, may highlight key motor-related regions. There are a few ideas here that we can explore further, as mentioned above.
- Description of locomotor performance. Figure 3 provides valuable data on the locomotor effects of A13 region photoactivation in both control and 6-OHDA mice. However, a more detailed analysis of the changes in locomotion during stimulation would enhance our understanding of the pro-locomotor effects, especially in the context of 6-OHDA lesions. For example, it would be informative to explore whether the probability of locomotion changes during stimulation in the control and 6-OHDA groups. Investigating reaction time, speed, total distance, and even kinematic aspects during stimulation could reveal how A13 is influencing locomotion, particularly after 6-OHDA lesions. The laboratory of Whelan has a deep knowledge of locomotion and the neural circuits driving it so these features may be instructive to infer insights on the neural circuits driving movement. On the same line, examining features like the frequency or power of stimulation related to walking patterns may help elucidate whether A13 is engaging with the Mesencephalic Locomotor Region (MLR) to drive the pro-locomotor effects. These insights would provide a more comprehensive understanding of the mechanisms underlying A13-mediated locomotor changes in both healthy and pathological conditions.
Thank you for these suggestions. We will revise as suggested. We will provide additional and/or updated data in revised figures and text. We will also move Supplementary Figures S1 and S2, which present additional locomotor data, into the main text to partly address the reviewers' points.
Reviewer #2 (Public Review):
Summary:
The paper by Kim et al. investigates the potential of stimulating the dopaminergic A13 region to promote locomotor restoration in a Parkinson's mouse model. Using wild-type mice, 6-OHDA injection depletes dopaminergic neurons in the substantia nigra pars compacta, without impairing those of the A13 region and the ventral tegmentum area, as previously reported in humans. Moreover, photostimulation of presumably excitatory (CAMKIIa) neurons in the vicinity of the A13 region improves bradykinesia and akinetic symptoms after 6-OHDA injection. Whole-brain imaging with retrograde and anterograde tracers reveals that the A13 region undergoes substantial changes in the distribution of its afferents and projections after 6-OHDA injection. The study suggests that if the remodeling of the A13 region connectome does not promote recovery following chronic dopaminergic depletion, photostimulation of the A13 region restores locomotor functions.
Strengths:
Photostimulation of presumably excitatory (CAMKIIa) neurons in the vicinity of the A13 region promotes locomotion and locomotor recovery of wild-type mice 1 month after 6-OHDA injection in the medial forebrain bundle, thus identifying a new potential target for restoring motor functions in Parkinson's disease patients.
Weaknesses:
Electrical stimulation of the medial Zona Incerta, in which the A13 region is located, has been previously reported to promote locomotion (Grossman et al., 1958). Recent mouse studies have shown that if optogenetic or chemogenetic stimulation of GABAergic neurons of the Zona Incerta promotes and restores locomotor functions after 6-OHDA injection (Chen et al., 2023), stimulation of glutamatergic ZI neurons worsens motor symptoms after 6-OHDA (Lie et al., 2022).
Thank you - we will add this reference. It is useful as Grossman did stimulate the zona incerta in the cat and elicit locomotion, suggesting that stimulation of the area in normal mice has external validity. The area targeted by Chen et al. (2023) is in the lateral aspect of central/medial zona incerta, formed by dorsal and ventral zona incerta, which may account for the differing results. Our data were robust for stimulation of the medial aspect of the rostromedial zona incerta. The thigmotactic behaviour that we observed in our work that focused on CamKII neurons has not been observed with chemogenetic, optogenetic activation or with photoinhibition of GABAergic central/medial ZI (Chen et al. 2023).
Although CAMKIIa is a marker of presumably excitatory neurons and can be used as an alternative marker of dopaminergic neurons, behavioral results of this study raise questions about the neuronal population targeted in the vicinity of the A13 region. Moreover, if YFP and CHR2-YFP neurons express dopamine (TH) within the A13 region (Fig. 2), there is also a large population of transduced neurons within and outside of the A13 region that do not, thus suggesting the recruitment of other neuronal cell types that could be GABAergic or glutamatergic.
We found that CamKII transfection of the A13 region was extremely effective in promoting locomotor activity, which was critical for our work in exploring its possible therapeutic potential. We acknowledge that specific viral approaches that target the GABAergic, glutamatergic, and dopaminergic circuits would be very useful. The range of tools to target A13 dopaminergic circuits is more limited than the SNc, for example, because the A13 region lacks DAT, and TH-IRES-Cre approaches, while useful, are less specific than DAT-Cre mouse models. Intersectional approaches targeting multiple transmitters (glutamate & dopamine, for example) may be one solution as we do not expect that a single transmitter-specific pathway would work, as well as broad targeting of the A13 region. Recent work suggests that GABAergic neuron activation may have more general effects on behaviour rather than control of ongoing locomotor parameters. However, this is in contrast to recent work showing a positive valence effect of dopamine A13 activation on motivated food-seeking behavior, which differs from consummatory behavior observed with GABAergic modulation (Ye, Nunez, and Zhang 2023). Chemogenetic inactivation and ablation of dopaminergic A13 revealed that they contribute to grip strength and prehensile movements, uncoupling food-seeking grasping behavior from motivational factors (Garau et al. 2023). Overall, this suggests differing effects of GABA compared to DA and/or glutamatergic cell types, consistent with our effects of stimulating CamKII.
Regarding the analysis of interregional connectivity of the A13 region, there is a lack of specificity (the viral approach did not specifically target the A13 region), the number of mice is low for such correlation analyses (2 sham and 3 6-OHDA mice), and there are no statistics comparing 6-OHDA versus sham (Fig. 4) or contra- versus ipsilesional sides (Fig. 5). Moreover, the data are too processed, and the color matrices (Fig. 4) are too packed in the current format to enable proper visualization of the data. The A13 afferents/efferents analysis is based on normalized relative values; absolute values should also be presented to support the claim about their upregulation or downregulation.
Generally, papers using tissue-clearing imaging approaches have low sample sizes due to technical complexity and challenges. The technical challenges of obtaining these data were substantial in both collection and analysis. There are multiple technical complexities arising from dual injections (A13 and MFB coordinates) and targeting the area correctly. The A13 region is difficult to target as it spans only around 300 µm in the anterior-posterior axis. While clearing the brain takes weeks, and light-sheet imaging also takes time, the time necessary to analyze the tissue using whole-brain quantification is labor intensive, especially with a lack of a standardized analysis pipeline from atlas registrations, signal segmentations, and quantifications. The field is still relatively new, requiring additional time to refine pipelines.
Correlation matrices are often used in analyzing connectivity patterns on a brain-wide scale, as they can identify any observable patterns within a large amount of data. We used correlation matrices to display estimated correlation coefficients between the afferent and efferent proportions from one brain subregion to another across 251 brain regions in total in a pairwise manner (not for hypothesis testing). We provided descriptive statistics (mean and error bars) in Figure 5C and G. As mentioned in comments for Reviewer 1, we will also present data in a revised Figure 5 and/or a new figure that focuses specifically on motor-related pathways to provide information on possible therapeutic pathways. As suggested, absolute values will be shared in a supplemental table.
In the absence of changes in the number of dopaminergic A13 neurons after 6-OHDA injection, results from this correlation analysis are difficult to interpret as they might reflect changes from various impaired brain regions independently of the A13 region.
We acknowledge that models of Parkinson’s disease, particularly those using 6-OHDA, induce plasticity in various regions, which may subsequently affect A13 connectivity. Our aim is to emphasize the residual, intact A13 pathways that could serve as therapeutic targets in future investigations. This emphasis is pertinent in the context of potential clinical applications, as the overall input and output to the region fundamentally dictate the significance of the A13 region in lesioned nigrostriatal models. We agree with the reviewer that the changes certainly can be independent of A13; however, the fact that there was a significant change in the connectome post-6-OHDA injection and striatonigral degeneration is in and of itself important and important to document.
There is no causal link between anatomical and behavioral data, which raises questions about the relevance of the anatomical data.
This point was also addressed earlier in response to a comment from Reviewer 1. Focusing on specific motor pathways is one avenue to explore. However, given that the zona incerta acts as an integrative hub, we believed it is prudent to initially examine both afferent and efferent pathways using a brain-wide approach. For instance, without employing this methodology, the potential significance of cortical interconnectivity to the A13 region might not have been fully appreciated. As mentioned previously, we will place additional emphasis on motor-related regions in our revised paper, thereby enhancing the relevance of the anatomical data presented. With these modifications, we anticipate that our data will underscore specific motor-related targets for future exploration, employing optogenetic targeting to assess necessity and sufficiency.
Overall, the study does not take advantage of genetic tools accessible in the mouse to address the direct or indirect behavioral and anatomical contributions of the A13 region to motor control and recovery after 6-OHDA injection.
We acknowledge that our study has not specifically targeted neurons that express dopaminergic, glutamatergic, or GABAergic properties (refer to earlier comment for more detail). However, like others, we find that targeting one neuronal population often does not result in a pure transmitter phenotype. For instance, evidence suggests co-localization of dopamine neurons with a subpopulation of GABA neurons in the A13/medial zona incerta (Negishi et al. 2020). In the hypothalamus, research by Deisseroth and colleagues (Romanov et al. 2017) indicates the presence of multiple classes of dopamine cells, each containing different ratios of co-localized peptides and/or fast neurotransmitters. Consequently, we believe our work lays the foundation for the investigations suggested by the reviewer. Furthermore, if one considers this work in the context of a preclinical study to determine whether the A13 might be a target in human Parkinson's disease, the existing technology that could be utilized is deep brain stimulation (DBS) or electrical modulation, which would also affect different neuronal populations in a non-specific manner. While optogenetic stimulation therapy is longer term, using CamKII combined with the DJ hybrid AAV could be a translatable strategy for targeting A13 neuronal populations in non-human primates (Watakabe et al. 2015; Watanabe et al. 2020).
Reviewer #3 (Public Review):
Kim, Lognon et al. present an important finding on pro-locomotor effects of optogenetic activation of the A13 region, which they identify as a dopamine-containing area of the medial zona incerta that undergoes profound remodeling in terms of afferent and efferent connectivity after administration of 6-OHDA to the MFB. The authors claim to address a model of PD-related gait dysfunction, a contentious problem that can be difficult to treat with dopaminergic medication or DBS in conventional targets. They make use of an impressive array of technologies to gain insight into the role of A13 remodeling in the 6-OHDA model of PD. The evidence provided is solid and the paper is well written, but there are several general issues that reduce the value of the paper in its current form, and a number of specific, more minor ones.
Also, some suggestions, that may improve the paper compared to its recent form, come to mind.
Thank you for the suggestions and careful consideration of our work - it is appreciated.
The most fundamental issue that needs to be addressed is the relation of the structural to the behavioral findings. It would be very interesting to see whether the structural heterogeneity in afferent/effects projections induced by 6-OHDA is related to the degree of symptom severity and motor improvement during A13 stimulation.
As mentioned in comments for Reviewer 1, we will be highlighting motor-related A13 pathways in a revised Figure 5 and/or a new figure. We hope that our work will provide a roadmap for future studies to disentangle divergent or convergent A13 pathways that are involved in different or all PD-related motor symptoms. Because we could not measure behavioural change in the same animals studied with the anatomic study (essentially because the optrode would have significantly disrupted the connectome we are measuring), we cannot directly compare behaviour to structure.
The authors provide extensive interrogation of large-scale changes in the organization of the A13 region afferent and efferent distributions. It remains unclear how many animals were included to produce Fig 4 and 5. Fig S5 suggests that only 3 animals were used, is that correct? Please provide details about the heterogeneity between animals. Please provide a table detailing how many animals were used for which experiment. Were the same animals used for several experiments?
The behavioral set and the anatomical set were necessarily distinct. In the anatomical experiments, we employed both anterograde and retrograde viral approaches to target the afferent and efferent A13 populations with fluorescent proteins. For the behavioral approach, a single ChR2 opsin was utilized to photostimulate the A13 region; hence combining the two populations was not feasible. We were also concerned that the optrode itself would interfere with connectomics. A lower number of animals were used for the whole-brain work due to technical limitations described earlier. We will provide more details regarding numbers we can identify as a table and text.
While the authors provide evidence that photoactivation of the A13 is sufficient in driving locomotion in the OFT, this pro-locomotor effect seems to be independent of 6-OHDA-induced pathophysiology. Only in the pole test do they find that there seems to be a difference between Sham vs 6-OHDA concerning the effects of photoactivation of the A13. Because of these behavioral findings, optogenic activation of A13 may represent a gain of function rather than disease-specific rescue. This needs to be highlighted more explicitly in the title, abstract, and conclusion.
We agree with the reviewer that this aspect needs to be highlighted more. Optogenetic activation of A13 may represent a gain of function in both healthy and 6-OHDA mice, highlighting a parallel descending motor pathway that remains intact. 6-OHDA lesions have multiple effects on motor and cognitive function. This makes a single pathway unlikely to rescue all deficits observed in 6-OHDA models. We can say that the lack of locomotion observed in 6-OHDA models can be reversed by A13 region stimulation. We have discussed some aspects of the gain of function possibility but will augment this in other areas of the paper as well, as suggested.
The authors claim that A13 may be a possible target for DBS to treat gait dysfunction. However, the experimental evidence provided (in particular the lack of disease-specific changes in the OFT) seems insufficient to draw such conclusions. It needs to be highlighted that optogenetic activation does not necessarily have the same effects as DBS (see the recent review from Neumann et al. in Brain: https://pubmed.ncbi.nlm.nih.gov/37450573/). This is important because ZI-DBS so far had very mixed clinical effects. The authors should provide plausible reasons for these discrepancies. Is cell-specificity, which only optogenetic interventions can achieve, necessary? Can new forms of cyclic burst DBS achieve similar specificity (Spix et al, Science 2021)? Please comment.
Thank you for the useful comments - we will update our discussion accordingly.
Our study highlights a parallel motor pathway provided by the A13 region that remains intact in 6-OHDA mice and can be sufficiently driven to rescue the hypolocomotor pathology observed in the OFT and overcome bradykinesia and akinesia. The photoactivation of ipsilesional A13 also has an overall additive effect on ipsiversive circling, representing a gain of function on the intact side that contributes to the magnitude of overall motor asymmetry against the lesioned side. The effects of DBS are rather complex, ranging from micro-, meso-, to macro-scales, involving activation, inhibition, and informational lesioning, and network interactions. This could contribute to the mixed clinical effects observed with ZI-DBS, in addition to differences in targeting and DBS programming among the studies (see review (Ossowska 2019)). Also the DBS studies targeting ZI have never targeted the rostromedial ZI which extends towards the hypothalamus and contains the A13. Furthermore, DBS and electrical stimulation of neural tissue, in general, are always limited by current spread and lower thresholds of activation of axons (e.g., axons of passage), both of which can reduce the specificity of the true therapeutic target. Optogenetic studies have provided mechanistic insights that could be leveraged in overcoming some of the limitations in targeting with conventional DBS approaches. Spix et al. (2021) provided an interesting approach highlighting these advancements. They devised burst stimulation to facilitate population-specific neuromodulation within the external globus pallidus. Moreover, they found a complementary role for optogenetics in exploring the pathway-specific activation of neurons activated by DBS. To ascertain whether A13 DBS may be a viable therapy for PD gait, it will be necessary to perform many more preclinical experiments, and tuning of DBS parameters could be facilitated by optogenetic stimulation in these murine models.
In a recent study, Jeon et al (Topographic connectivity and cellular profiling reveal detailed input pathways and functionally distinct cell types in the subthalamic nucleus, 2022, Cell Reports) provided evidence on the topographically graded organization of STN afferents and McElvain et al. (Specific populations of basal ganglia output neurons target distinct brain stem areas while collateralizing throughout the diencephalon, 2021, Neuron) have shown similar topographical resolution for SNr efferents. Can a similar topographical organization of efferents and afferents be derived for the A13/ ZI in total?
The ZI can be subdivided into four subregions in the antero-posterior axis: rostral (ZIr), dorsal (ZId), ventral (ZIv), and caudal (ZIc) regions. The dorsal and ventral ZI is also referred together as central/medial/intermediate ZI. There are topographical gradients in different cell types and connectivity across these subregions (see reviews: (Mitrofanis 2005; Monosov et al. 2022; Ossowska 2019). Recent work by Yang and colleagues (2022) demonstrated a topographical organization among the inputs and outputs of GABAergic (VGAT) populations across four ZI subregions. Given that A13 region encompasses a smaller portion (the medial aspect) of both rostral and medial/central ZI (three of four ZI subregions) and coexpress VGAT, A13 region likely falls under rostral and intermediate medial ZI dataset found in Yang et al. (2022). With our data, we would not be able to capture the breadth of topographical organization shown in Yang et al (2022).
In conclusion, this is an interesting study that can be improved by taking into consideration the points mentioned above.
Reviewer #1 (Recommendations For The Authors):
- Figure 2 indeed presents valuable information regarding the effects of A13 region photoactivation. To enhance the comprehensiveness of this figure and gain a deeper understanding of the neurons driving the pro-locomotor effect of stimulation, it would be beneficial to include quantifications of various cell types:
• cFos-Positive Cells/TH-Positive Cells: it can help determine the impact of A13 stimulation on dopaminergic neurons and the associated pro-locomotor effect in the healthy condition and especially in the context of Parkinson's disease (PD) modeling.
• cFos-Positive Cells /TH-Negative Cells: Investigating the number of TH-negative cells activated by stimulation is also important, as it may reveal non-dopaminergic neurons that play a role in locomotor responses. Identifying the location and characteristics of these TH-negative cells can provide insights into their functional significance.
Incorporating these quantifications into Figure 2 would enhance the figure's informativeness and provide a more comprehensive view of the neuronal populations involved in the locomotor effects of A13 stimulation.
Agreed - we will add quantification and create graphs to present the data in Figure 2.
- Refer to Figure 3. In the main text (page 5) when describing the animal with 6-OHDA the wrong panels are indicated. It is indicated in Fgure 2A-E but it should be replaced with 3A-E. Please do that.
Will be done
Reviewer #2 (Recommendations For The Authors):
Abstract
Page 1: Inhibitory or lesion studies will be necessary to support the claim that the global remodeling of afferent and efferent projections of the A13 region highlights the Zona Incerta's role as a crucial hub for the rapid selection of motor function.
We believe that overall, there is quite a bit of evidence that the zona incerta is a hub for afferent/efferents. Mitrofanis (2005) and, more recently, Wang et al. (2020) summarize some of the evidence. Yang (2022) illustrates that the zona incerta shows multiple inputs to GABAergic neurons and outputs to diverse regions. Recent work suggests that the zona incerta contributes to various motor functions such as hunting, exploratory locomotion, and integrating multiple modalities (Zhao et al. 2019; Wang et al. 2019; Monosov et al. 2022; Chometton et al. 2017). We will update our paper to reflect these references.
Introduction
Page 2, paragraph 2: "However, little attention has been placed on the medial zona incerta (mZI), particularly the A13, the only dopamine-containing region of the rostral ZI" Is the A13 region located in the rostral or medial ZI or both?
It should have been written “rostromedial” ZI. The A13 is located in the medial aspect of rostromedial ZI. We will update the introduction.
Page 2, para 3: Li et al (2021) used a mini-endoscope to record the GCaMP6 signal. Masini and Kiehn, 2022 transiently blocked the dopaminergic transmission; they never used 6-OHDA. Please correct through the text.
We will correct this.
Page 2, para 4: the A13 connectome encompasses the cerebral cortex,... MLR. The MLR is a functional region, correct this for the CNF and PPN.
Thank you, we will correct this.
Page 3, the last paragraph of the introduction could be clarified by presenting the behavioral data first, followed by the anatomy.
We will correct this.
Figure 1 is nice and clear, and well summarizes the experimental design.
Thank you.
Figure 2 shows an example of the extent of the ChR2-YFP expression and the position of an optical fiber tip above the dopaminergic A13 region from a mouse. Without any quantification, these images could be included in Figure 1. Despite a very small volume (36.8nL) of AAV, the extent of ChR2-YFP expression is quite large and includes dopaminergic and unidentified neurons within the A13 region but also a large population of unidentified neurons outside of it, thus raising questions about the volume and the types of neurons recruited.
This is an important consideration. As mentioned previously, we will provide more information on viral spread and optrode location. The issue of viral spread is complex and depends on factors including tissue type, serotype, and promotor of the virus. Li et al. (2021), for example, used different virus serotypes and promotors, injecting 150 nL, whereas we used AAV DJ, injecting 36.8nL. AAV-DJ is a hybrid viral type consisting of multiple serotypes. It has a high transduction efficiency, which leads to greater gene delivery than single-serotype AAV viral constructs (Mao et al. 2016). A secondary consideration regarding translation was that AAV-DJ could effectively transduce non-primate neurons (Watanabe et al. 2020). We have addressed the issue of neurons recruited earlier and will provide c-Fos quantification to illustrate the extent of co-localization with TH.
Anatomical reconstruction of the extent of the ChR2-YFP expression and the location of the tip of the optical fiber will be necessary to confirm that ChR2-YFP expression was restricted to the A13 region.
We will provide additional information regarding viral spread, ferrule tip placement, and c-fos cell counts.
Page 5, 1st para: Double-check the references, as not all of them are 6-OHDA injections in the MLF.
Will correct.
Page 5, 1st para, 4th line: Replace ferrule with optical canula or fiber.
Will correct.
Page 5, 1st para, 9th line: Replace Figure 2 with Figure 3.
Will correct.
Page 5, 2nd para: About the refractory decrease in traveled distance by sham-ChR2 mice: is this significant?
It was not significant (Figure S1, 1-way RM ANOVA: F5,25 = 0.486, P = 0.783)). We will update this.
Figure 3 showing behavioral assessments is nice, but the stats are not always clear. In Fig 3A, are each of the off and on boxes 1 minute long? The figure legend states the test lasts 1 min, but isn't it 4 minutes? In Figure 3B-E and 3J-M, what are the differences? Do the stats identify a significant difference only during the stimulation phase? Fig. 3F-I are nice and could have been presented as primary examples prior to data analysis in Fig. 3B-E. Group labels above the graph would help.
Yes, the off-on boxes are 1 minute long. We will correct the error in the legend. Great suggestion for F-I - we will move them ahead of the summary figures.
Fig. 3L-M, what do PreSur, Post, and Ferrule mean? I assume that Ferrule refers to mice tested with the optical fiber without stimulation, whereas Stim. refers to the stimulation. It would be helpful to standardize the format of stats in Fig. 3B-E and 3-J-M. What are time points a, b, and c referring to?
We will do this.
Figure S2A: the higher variability in 6-OHDA-YFP mice in comparison to 6-OHDA-ChR2 mice prior to stimulation suggests that 6-OHDA-YFP mice were less impaired. Why use boxplots only for these data? Would a pairwise comparison be more appropriate?
Data did not follow a normal distribution and thus, were plotted as box and whiskers with the horizontal line through the box indicating the group median, interquartile range indicated by the limits of the box, and group minimum and maximum indicated by the whiskers. And indeed, a non-parametric equivalent of paired t-test (Wilcoxon signed-rank test) was used.
Fig. S2B: add the statistical marker.
Will do
Page 7, para 1, line 8: to add "in comparison to 6-OHDA-YFP and YFP mice" to during photostimulation... (Figure 3E).
Will do
Page 7, para 3, line 5: about larger improvement, replace "sham ChR2" with "6-OHDA."
Will do
Page 8, para 1, line 4: Perier et al., 2000 reported that 6-OHDA injection increased the firing frequency of the ZI over a month.
We will add that time frame. Agreed, it is shorter than the behavioral work, which was started 3 weeks after 6-OHDA injection.
Page 8, para 2, line 1: Since the results were expected, add some references.
Will do
Page 8, para 3, line 4. Double-check the reference.
Will correct and update
Page 8: About large-scale changes in the A13 region, the relevance of correlation matrices is difficult to grasp. Analysis of local connectivity would have been more informative in the context of GABAergic and glutamatergic neurons of the ZI in the vicinity of the A13 region.
We will explore alternative methods to present the data.
Page 8, para 3, line: given Fig. 2, there is concern about the claim that only the A13 region was targeted. The time of the analysis after 6-OHDA should be mentioned. Some sections of the paragraph could be moved to methods.
As mentioned earlier, we will provide additional information regarding viral spread, ferrule tip placement, and c-fos cell counts. We will mention analysis time after 6-OHDA and update Figure 1a to include this.
Fig. 4: The color code helps the reader visualize distribution differences. However, statistical analyses comparing 6-OHDA versus sham should be included. Quantification per region would greatly help readers visualize the data and support the conclusion. The relationship between the type of correlation (positive or negative) and absolute change (increase or decrease) is unknown in the current format, which limits the interpretation of the data. Moreover, examples of raw images of axons and cells should be presented for several brain regions. The experimental design with a timeline, as in Fig. 1, would be helpful. The legend for Fig. 4 is a bit long. Some sections are very descriptive, whereas others are more interpretive.
We will explore alternative methods of presenting the data, as suggested in a previous comment. Should we retain the correlation matrix, we will incorporate the reviewer’s suggestions.
Page 10, para 1, line 1: add "afferent" to "changes in -afferent and- projection patterns."
Will do
Page 10, para 1, line 9: remove the 2nd "compared to sham" in the sentence.
Will do
10, para 1, line 10: remove "coordinated" in "several regions showed a coordinated reduction in afferent density." We cannot say anything about the timing of events, as there is only info at 1 month.
Will do
Page 10, para 2: the section should be written in the past tense.
Will do
Page 13, para 2, the last sentence is overstated. Please remove "cells" and refer to the A13 region instead.
Will do
About differential remodelling of the A13 region connectome: Figure 5C and 5G: The proportion of total afferents ipsi- and contralateral to 6-OHDA injection argues that the A13 region primarily receives inputs from the cortical plate and the striatum. Unfortunately, there are no statistics.
Due to the small sample size, we provided descriptive statistics (mean and error bars) in Figure 5C and G. As mentioned in comments for Reviewers 1 and 2, we will revise Figure 5 to present data focusing on motor-related pathways to provide clarity. In addition, absolute values will be shared in a supplemental table.
Figure 5 D and 5H: Changes in the proportion of total afferents/projections are relatively modest (less than 10% of the whole population for the highest changes). There is no standard deviation for these data and no statistics. Do they reflect real changes or variability from the injection site?
The changes are relatively modest (less than 10%) since a small brain region usually provides a very small proportion of total input (McElvain et al. 2021; Yang et al. 2022). The changes in the proportions reflect real differences between average proportions observed in sham and 6-OHDA mice. The variability in the total labeling of neurons and fibers was minimized by normalizing individual regional counts against total counts found in each individual animal.
Fig 5F and H: The example in F shows a huge decrease in the striatum, but H indicates only a
2% change, which makes the example not very representative. Absolute values would be helpful.
While a 2% change may seem small, it represents a relatively large change in the A13 efferent connectome. To provide further clarity, we will provide absolute values as suggested in our new supplemental table.
Figure 6 is inaccurate and unnecessary.
Agree - it is too simplistic. We will remove it and replace it with one outlined in comments to Reviewer 1.
Discussion
Although interesting, the discussion is too long.
We will make it more concise in the revised paper.
Page 12: para 2. If the A13 region has a pro-locomotor effect and has therapeutical potential; the claim about its plasticity relies on Fig. 4 and 5, which have a limited scope in the current analysis and presentation (see comments above).
We will revise the paper per the comments above and then update this accordingly.
Methods
Page 17, para 1: include the stereotaxic coordinates of the optical cannula above the A13 region.
We will include this information.
References
Chen, Fenghua, Junliang Qian, Zhongkai Cao, Ang Li, Juntao Cui, Limin Shi, and Junxia Xie. 2023. “Chemogenetic and Optogenetic Stimulation of Zona Incerta GABAergic Neurons Ameliorates Motor Impairment in Parkinson’s Disease.” iScience 26 (7).
https://doi.org/10.1016/j.isci.2023.107149.
Chometton, S., K. Charrière, L. Bayer, C. Houdayer, G. Franchi, F. Poncet, D. Fellmann, and P. Y. Risold. 2017. “The Rostromedial Zona Incerta Is Involved in Attentional Processes While Adjacent LHA Responds to Arousal: C-Fos and Anatomical Evidence.” Brain Structure & Function 222 (6): 2507–25.
Garau, Celia, Jessica Hayes, Giulia Chiacchierini, James E. McCutcheon, and John Apergis-Schoute. 2023. “Involvement of A13 Dopaminergic Neurons in Prehensile Movements but Not Reward in the Rat.” Current Biology: CB, October. https://doi.org/10.1016/j.cub.2023.09.044.
Li, Zhuoliang, Giorgio Rizzi, and Kelly R. Tan. 2021. “Zona Incerta Subpopulations Differentially Encode and Modulate Anxiety.” Science Advances 7 (37): eabf6709.
Mao, Yingying, Xuejun Wang, Renhe Yan, Wei Hu, Andrew Li, Shengqi Wang, and Hongwei Li. 2016. “Single Point Mutation in Adeno-Associated Viral Vectors -DJ Capsid Leads to Improvement for Gene Delivery in Vivo.” BMC Biotechnology 16 (January): 1.
McElvain, Lauren E., Yuncong Chen, Jeffrey D. Moore, G. Stefano Brigidi, Brenda L. Bloodgood, Byung Kook Lim, Rui M. Costa, and David Kleinfeld. 2021. “Specific Populations of Basal Ganglia Output Neurons Target Distinct Brain Stem Areas While Collateralizing throughout the Diencephalon.” Neuron 109 (10): 1721–38.e4.
Mitrofanis, J. 2005. “Some Certainty for the ‘Zone of Uncertainty’? Exploring the Function of the Zona Incerta.” Neuroscience 130 (1): 1–15.
Monosov, Ilya E., Takaya Ogasawara, Suzanne N. Haber, J. Alexander Heimel, and Mehran Ahmadlou. 2022. “The Zona Incerta in Control of Novelty Seeking and Investigation across Species.” Current Opinion in Neurobiology 77 (December): 102650.
Negishi, Kenichiro, Mikayla A. Payant, Kayla S. Schumacker, Gabor Wittmann, Rebecca M.
Butler, Ronald M. Lechan, Harry W. M. Steinbusch, Arshad M. Khan, and Melissa J. Chee. 2020. “Distributions of Hypothalamic Neuron Populations Coexpressing Tyrosine Hydroxylase and the Vesicular GABA Transporter in the Mouse.” The Journal of Comparative Neurology 528 (11): 1833–55.
Ossowska, Krystyna. 2019. “Zona Incerta as a Therapeutic Target in Parkinson’s Disease.” Journal of Neurology. https://doi.org/10.1007/s00415-019-09486-8.
Romanov, Roman A., Amit Zeisel, Joanne Bakker, Fatima Girach, Arash Hellysaz, Raju Tomer,
Alán Alpár, et al. 2017. “Molecular Interrogation of Hypothalamic Organization Reveals Distinct Dopamine Neuronal Subtypes.” Nature Neuroscience 20 (2): 176–88.
Spix, Teresa A., Shruti Nanivadekar, Noelle Toong, Irene M. Kaplow, Brian R. Isett, Yazel Goksen, Andreas R. Pfenning, and Aryn H. Gittis. 2021. “Population-Specific
Neuromodulation Prolongs Therapeutic Benefits of Deep Brain Stimulation.” Science 374 (6564): 201–6.
Wang, Xiyue, Xiaolin Chou, Bo Peng, Li Shen, Junxiang J. Huang, Li I. Zhang, and Huizhong W. Tao. 2019. “A Cross-Modality Enhancement of Defensive Flight via Parvalbumin Neurons in Zona Incerta.” eLife 8 (April). https://doi.org/10.7554/eLife.42728.
Wang, Xiyue, Xiao-Lin Chou, Li I. Zhang, and Huizhong Whit Tao. 2020. “Zona Incerta: An Integrative Node for Global Behavioral Modulation.” Trends in Neurosciences 43 (2): 82–87.
Watakabe, Akiya, Masanari Ohtsuka, Masaharu Kinoshita, Masafumi Takaji, Kaoru Isa, Hiroaki Mizukami, Keiya Ozawa, Tadashi Isa, and Tetsuo Yamamori. 2015. “Comparative Analyses of Adeno-Associated Viral Vector Serotypes 1, 2, 5, 8 and 9 in Marmoset, Mouse and Macaque Cerebral Cortex.” Neuroscience Research 93 (April): 144–57.
Watanabe, Hidenori, Hiromi Sano, Satomi Chiken, Kenta Kobayashi, Yuko Fukata, Masaki
Fukata, Hajime Mushiake, and Atsushi Nambu. 2020. “Forelimb Movements Evoked by Optogenetic Stimulation of the Macaque Motor Cortex.” Nature Communications 11 (1): 3253.
Yang, Yang, Tao Jiang, Xueyan Jia, Jing Yuan, Xiangning Li, and Hui Gong. 2022. “Whole-Brain Connectome of GABAergic Neurons in the Mouse Zona Incerta.” Neuroscience Bulletin 38 (11): 1315–29.
Ye, Qiying, Jeremiah Nunez, and Xiaobing Zhang. 2023. “Zona Incerta Dopamine Neurons Encode Motivational Vigor in Food Seeking.” bioRxiv : The Preprint Server for Biology, June. https://doi.org/10.1101/2023.06.29.547060.
Zhao, Zheng-Dong, Zongming Chen, Xinkuan Xiang, Mengna Hu, Hengchang Xie, Xiaoning Jia, Fang Cai, et al. 2019. “Zona Incerta GABAergic Neurons Integrate Prey-Related Sensory Signals and Induce an Appetitive Drive to Promote Hunting.” Nature Neuroscience 22 (6): 921–32.
