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opencc-zeroAug 2020View details →

The evolution of virulence in Pseudomonas aeruginosa during chronic wound infection

Opportunistic pathogens are associated with a number of chronic human infections, yet the evolution of virulence in these organisms during chronic infection remains poorly understood. Here, we tested the evolution of virulence in the human opportunistic pathogen Pseudomonas aeruginosa in a murine chronic wound model using a two-part serial passage and sepsis experiment, and found that virulence evolved in different directions in each line of evolution. We also assessed P. aeruginosa adaptation to a chronic wound after 42 days of evolution and found that morphological diversity in our evolved populations was limited compared to that previously described in cystic fibrosis (CF) infections. Using whole-genome sequencing, we found that genes previously implicated in P. aeruginosa pathogenesis (lasR, pilR, fleQ, rpoN and pvcA), contained mutations during the course of evolution in wounds, with selection occurring in parallel across all lines of evolution. Our findings highlight that (i) P. aeruginosa heterogeneity may be less extensive in chronic wounds than in CF lungs; (ii) genes involved in P. aeruginosa pathogenesis acquire mutations during chronic wound infection; (iii) similar genetic adaptations are employed by P. aeruginosa across multiple infection environments and (iv) current models of virulence may not adequately explain the diverging evolutionary trajectories observed in an opportunistic pathogen during chronic wound infection.

opencc-zeroDec 2016View details →

Data from: Ants at plant wounds – a little-known trophic interaction with evolutionary implications for ant-plant interactions

Extrafloral nectaries (EFNs) allow plants to engage in mutualisms with ants preventing herbivory in exchange for food. EFNs occur scattered through the plant phylogeny and likely evolved independently from herbivore-created wounds subsequently visited by ants collecting leaked sap. Records of wound-feeding ants are, however, anecdotal. By surveying 38,000 trees from 40 species, we conduct the first quantitative ecological study of this overlooked behavior. Ant-wound interactions were widespread (0.5% of tree individuals) and occurred on 23 tree species. Interaction networks were opportunistic, closely resembling ant-EFNs networks. Fagaceae, a family lacking EFNs, were strongly overrepresented. For Fagaceae, ant occurrence at wounds correlated with species-level leaf damage, potentially indicating that wounds may attract mutualistic ants, supporting the hypothesis of ant-tended wounds as precursors of ant-EFNs mutualisms. Given the commonness of herbivore wounds, wound sap as steadily available food source might furthermore help to explain the overwhelming abundance of ants in (sub)tropical forest canopies.

opencc-zeroDec 2013View details →

Data from: Costs of reproduction in a long-lived female primate: injury risk and wound healing

Reproduction is a notoriously costly phase of life, exposing individuals to injury, infectious disease, and energetic tradeoffs. The strength of these costs should be influenced by life history strategies, and in long-lived species, females may be selected to mitigate costs of reproduction because life span is such an important component of their reproductive success. Here we report evidence for two costs of reproduction that may influence survival in wild female baboons— injury risk and delayed wound healing. Based on 29 years of observations in the Amboseli ecosystem, Kenya, we found that wild female baboons experienced the highest risk of injury on days when they were most likely to be ovulating. In addition, lactating females healed from wounds more slowly than pregnant or cycling females, indicating a possible tradeoff between lactation and immune function. We also found variation in injury risk and wound healing with dominance rank and age: older and low-status females were more likely to be injured than younger or high-status females, and older females exhibited slower healing than younger females. Our results support the idea that wild non-human primates experience energetic and immune costs of reproduction, and they help illuminate life history tradeoffs in long-lived species.

opencc-by-4.0Nov 2023View details →

Integrated single-cell RNA-sequencing data of unwounded and wounded mouse skin and fibroblasts.

This repository contains the .h5ad files that store the integrated scRNA-seq data we generated for the work, Almet et al. (2023), "Fibroblasts evolve in single-cell state to drive extracellular matrix and signaling changes across wound healing", to be published in the Journal of Investigative Dermatology.The integrated* files contain both raw counts, normalized counts, as well as unspliced and spliced count estimates that were obtained using kallisto|bustools and velocyto. We integrated the data from the following published datasets:<ol><li><a href=" https://doi.org/10.7554/eLife.60066">Phan et al. (2021)</a>: Unwounded P21 mice and small wound P21 + 7 mice</li><li><a href="https://doi.org/10.1016/j.celrep.2020.02.091">Haensel et al. (2020)</a>: Unwounded P49 mice and small wound P49 + 4 mice</li><li><a href="https://doi.org/10.1038/s41467-018-08247-x)">Guerrero-Juarez et al. (2019)</a>: Large wound day 12 mice</li><li><a href="https://doi.org/10.1016/j.stem.2020.07.008">Abbasi et al. (2020)</a>: Large wound day 14 mice</li><li><a href="https://doi.org/10.1126/sciadv.aay3704">Gay et al. (2020)</a>: Large wound fibrotic (hairless) and regenerative (hair follicle neogenesis) day 18 mice</li></ol>The unwounded_* files were used to briefly integrated unwounded skin scRNA-seq from mouse models of different ages that have been used to analyze wound healing in <a href="https://doi.org/10.1016/j.celrep.2020.02.091">Haensel et al. (2020),</a> <a href=" https://doi.org/10.7554/eLife.60066">Phan et al. (2021)</a>, and <a href="https://doi.org/10.1016/j.celrep.2022.111155">Vu et al. (2022)</a>, which generated scRNA-seq for unwounded skin from mice aged P21, P49, and P616, respectively. The data can be loaded using the Python package Scanpy or AnnData, but you can also load it in R if you use zellkonverter.

Fig. 4 in Transcriptomic analysis of wound-healing in Solanum tuberosum (potato) tubers: Evidence for a stepwise induction of suberin-associated genes

Fig. 4. Transcript accumulation of genes associated with wound induced suberization. Transcript accumulation of known and putative genes encoding steps in suberin biosynthesis, from starch degradation to final assembly, over the wound-healing time course were retrieved from RNA-seq data. Heatmaps depict log2FPKM means for n = 3 biological replicates for each time point. Numbered pathway steps correspond to numbers in the suberin roadmap (Supplemental Fig. S4). Fumarase (step 63) is included as a step in the TCA pathway, but is shown in grey because its sequence did not have a corresponding PGSC gene identification number, and therefore transcript abundance could not be estimated in this study.

Fig. 6 in Transcriptomic analysis of wound-healing in Solanum tuberosum (potato) tubers: Evidence for a stepwise induction of suberin-associated genes

Fig. 6. Transcript accumulation of wound-induced CASP and GDSL genes. Transcript accumulation of known and putative CASP and GDSL genes, over the wound-healing time course were retrieved from RNA-seq data. Heatmaps depict log2FPKM means for n = 3 biological replicates for each time point.

Fig. 3. Network modules for suberin-associated metabolism genes. Expression profiles for 317 in Transcriptomic analysis of wound-healing in Solanum tuberosum (potato) tubers: Evidence for a stepwise induction of suberin-associated genes

Fig. 3. Network modules for suberin-associated metabolism genes. Expression profiles for 317 wound-induced and suberin-associated genes encompassing primary carbohydrate metabolism and the formation of suberin phenolic and aliphatic monomers were subjected to WGCNA. Genes belonging to carbohydrate (C), tricarboxylic acid cycle (TCA), shikimate pathway (S), phenolic metabolism (P), phenolic assembly (PA), fatty acid biosynthesis (FAB), fatty acid modification (FAM) and aliphatic assembly (AA) are colour-coded (see legend). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 2 in Transcriptomic analysis of wound-healing in Solanum tuberosum (potato) tubers: Evidence for a stepwise induction of suberin-associated genes

Fig. 2. Gene set enrichment analysis (GSEA) of biological processes across differentially expressed genes (DEGs). Time point comparison panels represent a union parametric analysis of gene set enrichment (PAGE) of biological process (BP) categorized gene ontology (GO) terms. Nodes represent gene sets and their size represents a range from 5 to 464 genes, and edges show overlapping genes between sets, with width representing ranges from 5 to 149 genes. Blue sets are downregulated, red are up-regulated, and grey nodes denote terms that were not detected as significantly differentially regulated (i.e. enriched) at that time point comparison. Labels denote assigned node numbers that correspond to Table 1 with associated GO ID, GO term and regulation overview. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 1 in Transcriptomic analysis of wound-healing in Solanum tuberosum (potato) tubers: Evidence for a stepwise induction of suberin-associated genes

Fig. 1. Global overview of the wound-healing transcriptome. A. Principle component analysis (PCA) of RNA-seq libraries. Colours represent biological replicate libraries generated from the same time point (gene log2FPKM space with scaling). B. Differentially expressed genes (DEGs) across time point comparisons. Genes were considered significantly up- or down-regulated if they met p ≤ 0.01 and |log2 (fold change)| (| LFC|) ≥ 2 significance cut-offs. Lists of significantly DEGs were generated using voom by applying these parameters with the Benjamini-Hochberg procedure to TMM-normalized HT-Seq count data. C. Venn diagram of DEGs significantly up- (red) or down-regulated (blue) over the wound-healing time course. Genes were considered significantly up- or down-regulated if they met p ≤ 0.01 and |LFC| ≥ 2 significance cut-offs. Lists of significantly DEGs were generated using voom by applying these parameters with the Benjamini-Hochberg procedure to TMM-normalized HT-Seq count data. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 5 in Transcriptomic analysis of wound-healing in Solanum tuberosum (potato) tubers: Evidence for a stepwise induction of suberin-associated genes

Fig. 5. Transcript accumulation of genes associated with wound induced ABA biosynthesis and degradation. Transcript accumulation of known and putative genes encoding steps in ABA biosynthesis and degradation, over the wound-healing time course were retrieved from RNA-seq data. Heatmaps depict log2FPKM means for n = 3 biological replicates for each time point. Numbered pathway steps correspond to numbers in the ABA metabolism pathway (Supplemental Fig. 6).

Fig. 7 in Transcriptomic analysis of wound-healing in Solanum tuberosum (potato) tubers: Evidence for a stepwise induction of suberin-associated genes

Fig. 7. RT-qPCR validation of select wound-induced genes. Gene expression values for 14 genes from RT-qPCR (ΔΔCq) and RNA-seq (CPM) analyses were normalized to 0 dpw values, then log2-transformed to generate log2 (foldchange) values. Pearson's correlation coefficients were calculated for log2 (foldchange) values from the two experimental procedures, with α = 0.05 (Supplemental Table 9). The 95% confidence interval was calculated and plotted as 95% confidence bands.

Fig. 4 in Arachidonic acid-dependent carbon-eight volatile synthesis from wounded liverwort (Marchantia polymorpha)

Fig. 4. Effect of incubation after tissue-disruption on the amounts of endogenous volatiles. Volatiles were extracted with methyl tert-butyl ether from intact thalli (lower chromatogram) or from freeze–thaw treated thalli (upper chromatogram), and analyzed using GC–MS. Inset shows the enlarged chromatogram from 15.8 to 18.4 min. C15 sesquiterpenoids with the chemical formulas C15H24 (m/z 204, with peaks k to p) and C15H26O (m/z 222, with the peaks q and r) were tentatively identified based on their MS profiles (Supplemental Fig. S2).

Fig. 6 in Arachidonic acid-dependent carbon-eight volatile synthesis from wounded liverwort (Marchantia polymorpha)

Fig. 6. Resolution of enantiomers of 5 formed from racemic 3. The crude enzyme extract prepared from des6KO thalli was reacted with racemic 3, and the 5 formed by enzyme catalyzed hydrolysis was subjected to chiral phase GC analysis (upper chromatogram). 5 was not detected with the reaction mixture prepared without substrate (middle chromatogram) or without enzyme (lower chromatogram).

Fig. 3 in Arachidonic acid-dependent carbon-eight volatile synthesis from wounded liverwort (Marchantia polymorpha)

Fig. 3. Time course of emission of 1 and 5 after mechanical wounding of M. polymorpha thallus grown in a field. Average ± s.e. (n = 6) is shown. Different letters for each compound refer to significant differences (ANOVA, Bonferroni, P <0.01).

Fig. 5 in Arachidonic acid-dependent carbon-eight volatile synthesis from wounded liverwort (Marchantia polymorpha)

Fig. 5. Effect of incubation after tissue disruption on C8 volatile formation. The thalli were frozen and the volatiles were extracted (white bars), or the frozen thalli were thawed, and incubated for 5 min at 24 °C to facilitate the enzyme reaction (gray bar). Average ± s.e. (n = 4) is shown. Asterisks indicate significant differences for the noted compound (Student's t-test, ⁄⁄⁄P <0.001).

Fig. 8 in Arachidonic acid-dependent carbon-eight volatile synthesis from wounded liverwort (Marchantia polymorpha)

Fig. 8. Effect of addition of NAD(P)H on the C8 volatiles emitted from M. polymorpha thalli. C8 volatiles extracted from intact (white bars), partially wounded (50%, gray bars), totally disrupted (black bars), totally disrupted in the presence of NADH (coarse stripe), and totally disrupted M. polymorpha thalli in the presence of NADPH (dense stripe) were quantified. The average ± s.e. (n = 4–5) is shown. Different letters for each compound refer to significant differences (one way ANOVA, Fisher, P <0.05).

opencc-by-4.0Apr 2017View details →

Isolation of a novel Streptococcus anginosus subspecies, AW1 from wound infection in Al-Madinah Al-Munawarah province

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opencc-zeroNov 2021View details →

Expression profile of microRNAs in different stages of wound healing in mice

Wound healing response is characterized by progression from clot formation to an inflammatory phase, a repair phase, and finally remodeling. MicroRNAs (miRNAs) are 20-24 nucleotide noncoding RNAs that can affect protein expression at the posttranscriptional level by modulating the stability and translation of corresponding messenger RNAs (mRNAs). The roles that miRNAs play in various physiological and pathological processes have received increasingly widespread attention. However, the differentially expressed miRNAs involved in different stages of wound healing and their roles remain to be further explored. In this study, we established wound model on the shaved dorsum using a punch biopsy tool in C57BL/6J mice. Biopsies were harvested on postoperative days 0, 1, 3, and 7. Then, we identified the differentially expressed miRNAs in different stages of wound healing through Illumina sequencing and miRDeep2 analysis. This study help to find out the expression profile of microRNAs during normal wound healing in mice.