Pathogenic shifts in endogenous microbiota impede tissue regeneration via distinct activation of TAK1/MKK/p38

  1. Christopher P Arnold
  2. M Shane Merryman
  3. Aleishia Harris-Arnold
  4. Sean A McKinney
  5. Chris W Seidel
  6. Sydney Loethen
  7. Kylie N Proctor
  8. Longhua Guo
  9. Alejandro Sánchez Alvarado  Is a corresponding author
  1. Stowers Institute for Medical Research, United States
  2. University of Missouri, United States
  3. Pittsburg State University, United States
  4. Howard Hughes Medical Institute, Stowers Institute for Medical Research, United States
10 figures and 3 tables

Figures

Figure 1 with 1 supplement
The planaria microbiome dynamically responds to changes in culture conditions and regeneration.

(A) Diagram of transition of planaria from recirculation to static culture. (B) Percentage of the phyla Bacteroidetes and Proteobacteria following exit from recirculation culture (* = t-test p<0.05). (C) Heatmap of the percentage of the top 10 bacterial genera across all the samples of CIW4 strain planaria following release from recirculation culture in the presence or absence of the antibiotic gentamycin (n = pool of ~30 worms with 2–3 generated 16 s rDNA libraries, independently sequenced twice). (D) Heatmap of the percentage of the top 18 bacterial genera of amputated head, trunk, and tail fragments during regeneration in comparison to intact worms (n = pool of 2–16 intact worms or 30–60 fragments for 16 s rDNA library generation). (E) Heatmap of the percentage of the top 5 bacterial genera across the samples of individual wild-type planaria. The heatmap of the genera Vogesella, Chryseobacterium, and Pseudomonas across wild worm samples are included for reference (n = 1–4 16 s rDNA libraries generated per worm).

https://doi.org/10.7554/eLife.16793.003
Figure 1—source data 1

16 s rDNA sequencing results.

https://doi.org/10.7554/eLife.16793.004
Figure 1—figure supplement 1
Analysis of changes in bacterial levels and composition following exit from recirculation culture.

(A) Composition of bacterial phyla during the transition from recirculation to static culture in the absence or presence of the antibiotic gentamycin (n = pool of ~30 worms with 2–3 generated 16 s rDNA libraries, independently sequenced twice). Percentage of the prominent (B) Bacteroidetes genus Candidatus Amoebophilus and Proteobacteria genera (C) Vogesella and (D) Pseudomonas during the aforementioned changes in culture conditions. (E) Composition of bacterial phyla during regeneration of head, trunk, or tail fragments in comparison to intact worms (n = a pool of 2–16 intact worms or 30–60 fragments for 16 s rDNA library generation). Percentage of the genera (F) Candidatus Amoebophilus, (G) Vogesella, and (H) Pseudomonas during regeneration. (I) Composition of bacterial phyla of individual wild type sexual planaria (n = 1–4 16 s rDNA libraries generated per worm). (J) Percentage of the genera Candidatus Amoebophilus, Vogesella, and Pseudomonas amongst wild worm samples. Proportional Venn diagram comparison of the bacterial genera of (K) individual wild worms relative to one another or (L) compared in aggregate to the genera of the CIW4 lab strain. Overlaps less than 1% not pictured. (M) Bacterial CFU quantification of prominent bacterial strains from S2F2 sexual lab strain of planaria 3 days after exit from the fill and drain system (n = 3 pooled worms). (N) qPCR of relative 16 s rDNA levels during the recirculation culture to static culture transition in the presence or absence of antibiotic (n = 3 technical replicates of pooled samples of > 30 worms). (O) Total bacterial CFUs per planaria following exit from recirculation culture in the presence and absence of the antibiotic gentamycin (n = 4 samples of 4 pooled worm homogenates, experiment independently repeated > 4 times). (P) Total bacterial CFUs per planaria or regenerating fragment after amputation (n = 3–8 pooled worm or fragment homogenates per timepoint).

https://doi.org/10.7554/eLife.16793.005
Figure 2 with 1 supplement
Bacterial infection compromises planarian tissue homeostasis and regeneration.

(A) Bacterial CFU quantification of prevalent bacterial strains following exit from the recirculation system (n = 4 homogenates from 4 worms per time point, experiment independently repeated > 4 times); Vogesella (red), Chryseobacterium (orange), and Pseudomonas (green). (B) Depiction and enumeration of pathological stages following bacterial infection. Stage 2.5 refers to worms that reach stage 3 but ultimately regenerated anterior structures. (C) Comparison of the effects of infection of 1e8 CFU/ml Vogesella, Chryseobacterium, or Pseudomonas (green) on pathological stage progression over time (n = 15–25, experiment independently repeated > 3 times). (D) Anti-Pseudomonas antibody staining (green) and DAPI nuclear counterstain (blue) of surface and gut epithelia following infection (n = 2, experiment independently repeated > 2 times). (E) Histological sections stained with Alcian Blue/ PAS following Pseudomonas infection (n = 2). (F) Representative images depicting the effects of increasing concentrations of Pseudomonas on regenerating head, trunk, and tail fragments. Worms were amputated 1 day following infection and images were taken seven days after amputation (n = 5).

https://doi.org/10.7554/eLife.16793.008
Figure 2—figure supplement 1
Effects of bacterial infection on worm tissue homeostasis.

(A) Images of worms 30 days post recirculation culture administered food, antibiotic, or neither (experiment independently repeated > 3 times). Bacterial CFU/worm following infection with Vogesella either by (B) direct administration to planaria water or (C) by feeding bacteria mixed with beef liver paste (CFU determined from a pool of four worms per time point). (D) Percentage of worms exhibiting demarcated phenotypes following infection (n = 15–25, experiment independently repeated > 3 times). Phenotypes are color coded as follows: blue = normal, teal = posterior lesion, dark green = anterior lesion, light green = head regression, orange = partial lysis, red = full lysis, light green+squares = head regeneration following regression. (E) Anti-Pseudomonas antibody staining of histological sections of planaria immediately following the consumption of beef liver paste alone or mixed with the specified bacteria (n = 2). (F) Labeling of neoblasts via piwi WISH during Pseudomonas infection and pathological progression (n = 5–10).

https://doi.org/10.7554/eLife.16793.009
Elucidating bacterial contribution to the transcriptional changes underlying the transition of worms from recirculation to static culture conditions.

(A) Diagram depicting comparison of RNAseq samples of planaria following exit from a recirculation culture system in the absence or presence of the antibiotic gentamycin (n = 4 replicates each containing 4 planaria). (B) Hierarchical clustering of RNAseq results displaying significant clusters (1 through 9, y axis). (C) Visualization of gene expression patterns of significant clusters. (D) Differentially expressed annotated genes from cluster 1 (Day 0 vs Day 4 adj. p-value <0.05). Peptidoglycan recognition protein genes are highlighted in bold. RT and QPCR of (E) pgrp-1 and (F) pgrp-4 following Pseudomonas infection (n = 3 biological replicates, 3 technical replicates, * = t-test p<0.05). (G) WISH of pgrp-4 following Pseudomonas infection (n = 5–7).

https://doi.org/10.7554/eLife.16793.010
Figure 3—source data 1

RNAseq analysis of worms during recirculation to static culture transition.

https://doi.org/10.7554/eLife.16793.011
Figure 4 with 1 supplement
Diagram depicting workflow and data analysis of an RNAi screen to identify genes modulating pathological progression.

Planaria are transferred directly from the recirculation system to a flow culture system permitting maintenance of a reduced septic state during dsRNA feedings. Following 3 RNAi feedings, planaria are removed for infection with Pseudomonas. Observations of pathological stages are recorded every 1 to 3 days, and planaria are replenished with fresh water containing Pseudomonas every 3 to 4 days. Following enumeration of pathological stages, data for each day is reduced to an average pathological score and converted to a heat color code. Days for each RNAi condition are aligned in ascending order along the y-axis of a column. The average score of each column is calculated and used to sort the effects of RNAi conditions in ascending order along the x-axis. The result is a heat map visualization ranking the effects of RNAi treatments on the pathological progression in response to bacterial infection in planarians over time.

https://doi.org/10.7554/eLife.16793.012
Figure 4—figure supplement 1
A novel flow culture method for planarian RNAi in low septic conditions.

(A) Diagram depicting comparison of worm health following execution of the RNAi protocol in static versus flow culture. Worms removed from recirculation culture and placed in static culture experience a robust amplification of bacterial levels and are susceptible to lesion formation. RNAi of components that normally inhibit lesion formation or bacterial infection would exacerbate this effect. In comparison, maintenance of worms in a flow culture system can maintain the healthy, low septic state independent of RNAi manipulation. Diagram of (B) individual planarian flow culture vessels and (C) an integrated unidirectional flow system (planaria water is administered to all cups but depicted only in the left column and the upper row to simplify visualization). (D) Comparison of bacterial CFU/worm during culture in static versus flow RNAi conditions following exit from recirculation culture. (E) Effects of flow culture on bacterial CFU of worms with pre-existing heightened bacterial levels. (F) Bacterial CFU/worm prior to and after 3 RNAi feedings in the flow culture system (experiment independently repeated > 3 times). Bacterial CFUs were determined from samples of 4 pooled worms per timepoint.

https://doi.org/10.7554/eLife.16793.013
Heatmap depicting results of an RNAi screen for mediators of pathological progression following bacterial infection in planaria.

(A) Heatmap depicting average pathological scores for each RNAi treatment following 2e8 CFU/ml Pseudomonas infection (n = 5–12 worms per condition). Days versus average pathological score over time are aligned along the y-, and x- axes, respectively. Unc control sample is indicated by a dashed box. RNAi-targeted genes that significantly reduce or enhance pathological progression are highlighted in green and red, respectively (2-way ANOVA p<0.05). (B) Focus on RNAi of genes that result in a significant reduction (activators) or enhancement (inhibitors) or pathological progression. (CF) Heatmaps depicting the percentage of worms exhibiting pathological stage (C) 0, (D) 3, (E) 5, and (F) 2.5 for each RNAi treatment following Pseudomonas infection. Ordering and significance based on average pathological score over time are maintained for reference.

https://doi.org/10.7554/eLife.16793.014
Figure 5—source data 1

Homologous innate immune and inflammatory genes from RNAi screen.

https://doi.org/10.7554/eLife.16793.015
Figure 5—source data 2

Pathological scores of worms in RNAi screen for mediators of infection induced tissue degeneration.

https://doi.org/10.7554/eLife.16793.016
Epistatic analysis of activators and inhibitors of planarian pathological progression.

(A) Diagram depicting relevant components of the TAK1 pathway in Homo sapiens. (B) Diagram depicting combinatorial RNAi experiment and assay of tissue degeneration outcome. (C) Representative images and median pathological stage of worms following RNAi treatment with each combination of 6 activators and 3 inhibitors 12 days post Pseudomonas infection (n = 6–24). (D) Table of phenotypic outcomes following combinatorial RNAi treatment and Pseudomonas infection. (E) Diagram depicting phenotypic hierarchy of the mediators of pathological progression in Schmidtea mediterranea (bold = order is consistent with Homo sapiens TAK1 Pathway).

https://doi.org/10.7554/eLife.16793.017
Figure 6—source data 1

Pathological scores of worms during combinatorial RNAi analysis.

https://doi.org/10.7554/eLife.16793.018
Effects of planarian pathological progression mediators on regeneration in the presence and absence of infection.

(A) Representative images of regenerating head, trunk, and tail fragments following specified RNAi treatment in the presence or absence of Pseudomonas infection. Worms were amputated above and below the pharynx 2 days post infection and imaged 14 days post amputation (n = 5, non-lysed fragments shown when present). (B) Quantitation of phenotypes of regenerating head, trunk, and tail fragments following specified RNAi treatment in the presence or absence of Pseudomonas infection (dark blue = normal regeneration, light blue = abnormal regeneration, green = lesions, orange = tissue regression, red = lysis). Animals were scored at the same time when representative images were taken at 16dpi 14dpa.

https://doi.org/10.7554/eLife.16793.019
Figure 8 with 3 supplements
Signaling dynamics in gut tissue during infection and regeneration visualized with a phospho-p38 antibody.

(A) Colorimetric WISH of genes comprising the TAK/MKK/p38 signaling module (n > 3 worms). Combinatorial fluorescent whole mount ISH and immuno-labeling of gut marker mat1 and phospho-p38 (P-p38) (B) prior to stimulation, (C) following infection with 2e8 CFU/ml Pseudomonas, or (D) after amputation (n = 2–11 worms). (E) Higher magnification images of P-p38+ cells co-labeled with gut markers mat1, porc, hnf4, and nkx-2.2 following amputation (35-65 mpa). Quantification of P-p38 (F) Fraction Volume and (G) Average Intensity following infection or amputation (* = t-test p<0.05).

https://doi.org/10.7554/eLife.16793.020
Figure 8—figure supplement 1
Co-expression of TAK1/MKK/p38 pathway components.

Fluorescent double WISH of mkk6-1/p38-1, pp6/cyld-1, p38-1/cyld-1, and pp6/mkk6-1 in (A) whole worms and (B) posterior gut tissue (n = 6–8 worms).(C) Fluorescent double WISH of pp6/cyld-1 and p38-1/cyld-1 in the anterior mesenchyme (n = 6–8 worms). Identical settings used for posterior gut and anterior mesenchyme for comparison of cells surrounding the gut. Negative controls treated identically but lacking DIG and DNP labeled probes were used to determine non-specific background staining.

https://doi.org/10.7554/eLife.16793.021
Figure 8—figure supplement 2
Validation of an antibody that recognizes planarian P-p38.

(A) Conservation of the amino acids surrounding the Thr180/Tyr182 p38 phosphorylation in Homo sapiens and Schmidtea mediterranea. (B) Western blot of planarian protein lysate that is untreated or treated with 30 min of UV irradiation and stained with P-p38 antibody #1 (polyclonal) or P-p38 antibody #2 (monoclonal). (C) Whole mount P-p38 antibody of staining of planaria that are untreated or treated with 30 min of UV irradiation (n > 4 worms). (D) Whole mount P-p38 antibody staining of planaria following unc or p38-1 RNAi and subjected to the following treatments: untreated, 30 min post amputation, 30 min post UV irradiation (n > 3 worms). Confocal images of (E) infected posterior gut or (F) amputated fragments following WISH of the gut marker mat1 and anti-P-38 staining. (H) Whole mount ISH of porc and P-p38 staining of gut tissue injured via poking or lateral cut (n > 2 worms).

https://doi.org/10.7554/eLife.16793.022
Figure 8—figure supplement 3
High resolution analysis of P-p38 signaling in gut tissue following amputation.

Whole mount ISH of porc and P-p38 staining of anterior gut tissue 5 min post amputation. Z-series of images.

https://doi.org/10.7554/eLife.16793.023
Figure 9 with 1 supplement
TAK1/MKK/p38 signaling mediates contrasting regulation of apoptosis in infection versus regeneration.

(A) P-p38 staining or (B) TUNEL of Unc RNAi worms following Pseudomonas infection. Focus on the effects of pp6 and cyld-1 RNAi on (C) P-p38 signaling and (D) TUNEL in the anterior regions of planaria during Pseudomonas infection. Quantification of RNAi effects on (E) P-p38+ and (F) TUNEL+ cells in the anterior during infection (n = 5–9). Confocal images of TUNEL in amputated tail fragments following RNAi of TAK1/MKK/p38 signaling components. RNAi effects assayed at (G) 72 hr or (H) 48 hr post-amputation (two independent experiments). (I, J) Quantification of RNAi effects on corresponding TUNEL experiment (n = 1–7) (* = t-test p<0.05).

https://doi.org/10.7554/eLife.16793.024
Figure 9—figure supplement 1
Effects of TAK1/MKK/p38 signaling on proliferation and apoptosis.

(A) Imaging and (B) quantification of the effects of p38-1 RNAi on P-p38 staining of cells in the anterior region prior to or following infection (n = 7–9). (C) Confocal images and (D) quantification of H3P labeling in worms prior to and following Pseudomonas infection of cyld-1 RNAi worms in comparison to unc control (n = 2–5). Magnified images of cells in which TUNEL+ cells either (E) overlap with or are in (F) proximity of P-p38+ cells. Quantification of the effects of TAK1/MKK/p38 signaling on proliferation within tail fragments following amputation (n = 1–13) (* = t-test p<0.05).

https://doi.org/10.7554/eLife.16793.025
Effects of TAK1 components on the immune response.

Bacterial CFU/worm following infection with a single dose of 2e8 CFU/ml Pseudomonas and RNAi of (A) jun D, (B) p38-1, (C) pp6, or (D) cyld-1 (n = 1–4 pools of 1–4 worms each). (E) Pathological state of individual infected worms (squares) pooled for bacterial CFU/worm analysis.

https://doi.org/10.7554/eLife.16793.027

Tables

Table 1

Distribution of Species reads in CIW4 S. mediterranea.

https://doi.org/10.7554/eLife.16793.006
No. of species (Average)No. of species (Standard deviation)
Sample≥1 read≥10 reads≥100 reads≥1 read≥10 reads≥100 reads
Recirc D0268.785.337.536.313.995.3
D1 -Gent245.879.634.217.45.10.8
D1 +Gent281.889.441.210.87.82.7
D3 -Gent36814458.857.22811.6
D3 +Gent354.6126.457.226.514.855.8
Table 2

16 s rDNA homology of emergent bacterial strains.

https://doi.org/10.7554/eLife.16793.007
Planarian sourceColony morphologyTop 10 sequence hitsMax scoreTotal scoreQuery coverE valueIdentAccession
Sexual strain S2F2Large WhiteHafnia paralvei strain ATCC 29927 16 sribosomal RNA gene, partial sequence1991199198%096%NR_116898.1
Obesumbacterium proteus strain 42 16 s ribosomal RNA gene, partial sequence1932193298%096%NR_025334.1
Hafnia alvei strain JCM 1666 16 s ribosomal RNA gene, partial sequence1927192798%096%NR_112985.1
Obesumbacterium proteus strain NCIMB 8771 16 s ribosomal RNA gene, partial sequence1927192798%095%NR_116603.1
Hafnia alvei strain ATCC 13337 16 s ribosomal RNA gene, complete sequence1917191798%095%NR_044729.2
Ewingella americana strain CIP 81.94 16 s ribosomal RNA gene, complete sequence1908190893%097%NR_104925.1
Rouxiella chamberiensis 16 s ribosomal RNA, partial sequence1881188193%097%NR_135871.1
Hafnia psychrotolerans strain DJC1-1 16 s ribosomal RNA, partial sequence1875187593%097%NR_134741.1
Serratia liquefaciens strain ATCC 27592 16 s ribosomal RNA gene, complete sequence1871187198%095%NR_121703.1
Serratia grimesii strain DSM 30063 16 s ribosomal RNA gene, partial sequence1871187198%095%NR_025340.1
Medium yellowish beigePseudomonas peli strain R-20805 16 s ribosomal RNA gene, partial sequence2002200298%097%NR_042451.1
Pseudomonas guineae strain M8 16 s ribosomal RNA gene, partial sequence1953195398%096%NR_042607.1
Pseudomonas anguilliseptica strain S 1 16 s ribosomal RNA gene, partial sequence1908190898%096%NR_029319.1
Pseudomonas cuatrocienegasensis strain 1N 16 s ribosomal RNA gene, partial sequence1897189798%095%NR_044569.1
Pseudomonas pseudoalcaligenes strain Stanier 63 16 s ribosomal RNA gene, partial sequence1868186898%095%NR_037000.1
Pseudomonas pseudoalcaligenes strain NBRC 14167 16 s ribosomal RNA gene, partial sequence1866186698%095%NR_113653.1
Pseudomonas indoloxydans strain IPL-1 16 s ribosomal RNA gene, partial sequence1866186698%095%NR_115922.1
Pseudomonas alcaligenes strain ATCC 14909 16 s ribosomal RNA gene, partial sequence1864186498%095%NR_114472.1
Pseudomonas alcaligenes strain NBRC 14159 16 s ribosomal RNA gene, partial sequence1864186498%095%NR_113646.1
Pseudomonas composti strain C2 16 s ribosomal RNA gene, partial sequence1864186498%095%NR_116992.1
Small Beige with circleVogesella mureinivorans strain 389 16 s ribosomal RNA gene, partial sequence2039203999%097%NR_104556.1
Vogesella perlucida strain DS-28 16 s ribosomal RNA gene, partial sequence2039203999%097%NR_044326.1
Vogesella amnigena strain Npb-02 16 s ribosomal RNA, partial sequence1967196799%096%NR_137334.1
Vogesella oryzae strain L3B39 16 s ribosomal RNA gene, partial sequence1934193499%095%NR_135212.1
Vogesella lacus strain GR13 16 s ribosomal RNA gene, partial sequence1895189599%095%NR_116268.1
Vogesella fluminis strain Npb-07 16 s ribosomal RNA gene, partial sequence1890189099%095%NR_109463.1
Vogesella indigofera strain ATCC 19706 16 s ribosomal RNA gene, complete sequence1869186999%094%NR_040800.1
Vogesella alkaliphila strain JC141 16 s ribosomal RNA gene, partial sequence1862186299%094%NR_108891.1
Gulbenkiania mobilis strain E4FC31 16 s ribosomal RNA gene, complete sequence1805180597%094%NR_042548.1
Gulbenkiania indica strain HT27 16 s ribosomal RNA gene, partial sequence1762176297%093%NR_115769.1
Sexual strain S2F2Tiny WhiteCarbophilus carboxidus strain Z-1171 16 s ribosomal RNA gene, complete sequence1951195198%096%NR_104931.1
Aminobacter aminovorans strain DSM 7048 16 s ribosomal RNA gene, partial sequence1951195198%096%NR_025301.1
Aminobacter lissarensis strain CC495 16 s ribosomal RNA gene, complete sequence1945194598%096%NR_041724.1
Aminobacter niigataensis strain DSM 7050 16 s ribosomal RNA gene, partial sequence1940194098%096%NR_025302.1
Aminobacter aganoensis strain TH-3 16 s ribosomal RNA gene, partial sequence1940194098%096%NR_028876.1
Aminobacter anthyllidis strain STM4645 16 s ribosomal RNA gene, partial sequence1934193498%096%NR_108530.1
Aminobacter ciceronei strain IMB-1 16 s ribosomal RNA gene, complete sequence1929192998%096%NR_041700.1
Mesorhizobium australicum strain WSM2073 16 s ribosomal RNA gene, complete sequence1882188294%096%NR_102452.1
Mesorhizobium qingshengii strain CCBAU 33460 16 s ribosomal RNA gene, partial sequence1882188294%096%NR_109565.1
Mesorhizobium shangrilense strain CCBAU 65327 16 s ribosomal RNA gene, partial sequence1882188294%096%NR_116163.1
Asexual strain CIW4Small Beige with circleVogesella perlucida strain DS-28 16 s ribosomal RNA gene, partial sequence2167216794%097%NR_044326.1
Vogesella mureinivorans strain 389 16 s ribosomal RNA gene, partial sequence2156215694%097%NR_104556.1
Vogesella lacus strain GR13 16 s ribosomal RNA gene, partial sequence2019201995%095%NR_116268.1
Vogesella oryzae strain L3B39 16 s ribosomal RNA gene, partial sequence2013201395%095%NR_135212.1
Vogesella fluminis strain Npb-07 16 s ribosomal RNA gene, partial sequence2012201294%095%NR_109463.1
Vogesella indigofera strain ATCC 19706 16 s ribosomal RNA gene, complete sequence1989198994%094%NR_040800.1
Vogesella alkaliphila strain JC141 16 s ribosomal RNA gene, partial sequence1980198094%094%NR_108891.1
Gulbenkiania mobilis strain E4FC31 16 s ribosomal RNA gene, complete sequence1884188494%093%NR_042548.1
Pseudogulbenkiania gefcensis strain yH16 16 s ribosomal RNA gene, partial sequence1857185795%092%NR_118145.1
Aquaphilus dolomiae strain LMB64 16 s ribosomal RNA gene, partial sequence1855185594%093%NR_118538.1
Medium YellowChryseobacterium lactis strain KC1864 16 s ribosomal RNA gene, partial sequence2017201798%096%NR_126256.1
Chryseobacterium viscerum strain 687B-08 16 s ribosomal RNA gene, partial sequence2012201298%095%NR_117206.1
Chryseobacterium tructae strain 1084-08 16 s ribosomal RNA gene, partial sequence1995199598%095%NR_108531.1
Chryseobacterium oncorhynchi strain 701B-08 16 s ribosomal RNA gene, partial sequence1995199598%095%NR_108481.1
Chryseobacterium ureilyticum strain F-Fue-04IIIaaaa 16 s ribosomal RNA gene, partial sequence1980198098%095%NR_042503.1
Chryseobacterium indologenes strain NBRC 14944 16 s ribosomal RNA gene, partial sequence1969196998%095%NR_112975.1
Chryseobacterium gleum strain NBRC 15054 16 s ribosomal RNA gene, partial sequence1967196798%095%NR_113722.1
Chryseobacterium gleum strain CCUG 14555 16 s ribosomal RNA gene, partial sequence1967196798%095%NR_042506.1
Chryseobacterium indologenes strain LMG 8337 16 s ribosomal RNA gene, partial sequence1964196498%095%NR_042507.1
Chryseobacterium artocarpi strain UTM-3 16 s ribosomal RNA, partial sequence1960196098%095%NR_134001.1
Asexual strain CIW4Large BeigePseudomonas fluorescens Pf0-1 strain Pf0-1 16 s ribosomal RNA, complete sequence2242224294%099%NR_102835.1
Pseudomonas koreensis strain Ps 9-14 16 s ribosomal RNA gene, partial sequence2220222094%098%NR_025228.1
Pseudomonas reinekei strain MT1 16 s ribosomal RNA gene, partial sequence2217221794%098%NR_042541.1
Pseudomonas moraviensis strain 1B4 16 s ribosomal RNA gene, partial sequence2215221594%098%NR_043314.1
Pseudomonas vancouverensis strain DhA-51 16 s ribosomal RNA gene, partial sequence2215221594%098%NR_041953.1
Pseudomonas helmanticensis strain OHA11 16 s ribosomal RNA gene, partial sequence2193219394%098%NR_126220.1
Pseudomonas baetica strain a390 16 s ribosomal RNA gene, partial sequence2193219394%098%NR_116899.1
Pseudomonas jessenii strain CIP 105274 16 s ribosomal RNA gene, partial sequence2185218594%098%NR_024918.1
Pseudomonas umsongensis strain Ps 3-10 16 s ribosomal RNA gene, partial sequence2170217094%098%NR_025227.1
Pseudomonas mucidolens strain NBRC 103159 16 s ribosomal RNA gene, partial sequence2167216794%098%NR_114225.1
Table 3

Quantitation of overlapping and proximal P-p38 and TUNEL signal.

https://doi.org/10.7554/eLife.16793.026
RNAi conditionDays post infection% of P-p38 signal overlapping with TUNEL% of P-p38 signal proximal to TUNEL
unc01.2712.66
cyld-105.7845.66
pp604.2967.86
unc11.1639.31
cyld-114.5262.05
pp618.8779.31
unc21.9034.29
cyld-123.4860.65
pp625.7357.96
unc32.5544.19
cyld-133.9854.23
pp638.2957.46

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  1. Christopher P Arnold
  2. M Shane Merryman
  3. Aleishia Harris-Arnold
  4. Sean A McKinney
  5. Chris W Seidel
  6. Sydney Loethen
  7. Kylie N Proctor
  8. Longhua Guo
  9. Alejandro Sánchez Alvarado
(2016)
Pathogenic shifts in endogenous microbiota impede tissue regeneration via distinct activation of TAK1/MKK/p38
eLife 5:e16793.
https://doi.org/10.7554/eLife.16793