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Data from: Pathogen community composition and co-infection patterns in a wild community of rodents
<p><strong>ABSTRACT</strong></p> <p>Rodents are major reservoirs of pathogens that can cause disease in humans and livestock. It is therefore important to know what pathogens naturally circulate in rodent populations, and to understand the factors that may influence their distribution in the wild. Here, we describe the incidence and distribution patterns of a range of endemic and zoonotic pathogens circulating among rodent communities in northern France. The community sample consisted of 713 rodents, including 11 host species from diverse habitats. Rodents were screened for virus exposure (hantaviruses, cowpox virus, Lymphocytic choriomeningitis virus, Tick-borne encephalitis virus) using antibody assays. Bacterial communities were characterized using 16S rRNA amplicon sequencing of splenic samples. Multiple correspondence (MCA), regression and association screening (SCN) analyses were used to determine the degree to which extrinsic factors contributed to pathogen community structure, and to identify patterns of associations between pathogens within hosts. We found a rich diversity of bacterial genera, with 36 known or suspected to be pathogenic. We revealed that host species is the most important determinant of pathogen community composition, and that hosts that share habitats can have very different pathogen communities. Pathogen diversity and co-infection rates also vary among host species. Aggregation of pathogens responsible for zoonotic diseases suggests that some rodent species may be more important for transmission risk than others. Moreover we detected positive associations between several pathogens, including <em>Bartonella</em>, <em>Mycoplasma</em> species, Cowpox virus (CPXV) and hantaviruses, and these patterns were generally specific to particular host species. Altogether, our results suggest that host and pathogen specificity is the most important driver of pathogen community structure, and that interspecific pathogen-pathogen associations also depend on host species.</p> <p><strong>FILE DESCRIPTION:</strong></p> <p><strong>MiSeq raw sequences of the 16Sv4 rRNA gene from spleen rodent samples</strong></p> <p>This ZIP file contains the FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each spleen rodent sample using the MiSeq platform. The 749 multiplexed PCR products were indexed using both forward and reverse indices. Information of the multiplexed samples (<em>n</em>=363 in replicate) and positive (<em>n</em>= 6) & negative controls (<em>n</em>= 17) is provided in the following XLSX file titled: 16S_raw_abundance_data.xlsx</p> <p>File name: <strong>MiSeq raw sequences of the V4 region 16S rRNA gene.zip</strong></p> <p><strong>Raw input and output files generated by the mothur program</strong></p> <p>This ZIP file contains all the input and output files generated during the MiSeq sequence analysis with the mothur program.</p> <p>File name: <strong>Raw input and output files generated by the mothur program.zip</strong></p> <p><strong>Log file generated by the mothur program</strong></p> <p>This TXT file contains is the history of all the command lines and parameters used during the MiSeq sequence analysis with the mothur program.</p> <p>File name: <strong>mothur.1428506786.logfile</strong></p> <p><strong>Raw abundance table of the 16v4 rRNA gene from spleen rodent samples before data filtering</strong></p> <p>This XLSX file contains the number of reads for each distinct Operational Taxonomic Unit (OTU) and each of the PCR products, including the 332 spleen rodent samples analyzed in the study and the negative & positive controls, sequenced in the MiSeq run before the data filtering. This file contains also the following information: Study_site, Study_year, Sample_habitat, Host_species, Host_age, Host_sex, PCR_ID and the taxonomic classification (Kingdom to Genus) of each OTU.</p> <p>File name: <strong>16S_raw_abundance_data.xlsx</strong></p> <p><strong>Occurrence table of the 16v4 rRNA gene from spleen rodent samples after data filtering</strong></p> <p>This XLSX file contains the occurrences (presence: 1 ; absence: 0) after data filtering of each putative pathogenic Operational Taxonomic Unit (OTU) for each of the 332 spleen rodent samples analyzed in the study.</p> <p>File name: <strong>16S_presence_absence_data.xlsx</strong></p> <p><strong>Statistical Analysis Scripts and Data File</strong></p> <p>This ZIP file contains the R scripts for performing statistical analyses reported in the main text and supplemental materials. There is one main file (Analyses.R), as well as two source scripts required for association screening analyses (SCN.txt and FctTestScreenENV.txt). It also includes an R-legible data file containing occurrences (presence: 1 ; absence: 0) for all pathogen exposure variables on which statistical analyses were conducted (PA_DATA.csv) for each of the 332 spleen rodent samples analyzed in the study. The column names for bacterial exposures correspond to the “Pathogen Code” given in the 16S_presence_absence_data.xlsx file.</p> <p>File name: <strong>Statistical Analysis Scripts and Data File.zip</strong></p>
Decomposition of Microstegium vimineum litter, plants grew through the Big Oaks National Wildlife Refuge in 2019. Litter used in this experiment naturally senesced in the fall 2019, decomposition data collected through 2020. Plants were infected or not-infected with the foliar fungal pathogen Bipolaris gigantea during the 2019 growing season.
Decomposition of plant litter, facilitated primarily by microbial decomposers, plays a critical role in biogeochemical cycling and ecosystem function. Emerging pathogens have the potential to impact litter decomposition by altering the chemical composition and associated microbial community of host tissue. Here, we compared litter decomposition of the invasive grass Microstegium vimineum collected from sites with Bipolaris leaf spot symptoms and sites with no apparent disease symptoms in a common garden experiment. Our results revealed that leaf tissue from litter from non-infected sites decomposed more rapidly through the spring than litter from infected sites. Differences in fungal composition between infected and non-infected litter at the start of the experiment largely persisted through the summer. Our work demonstrates that pathogen colonization may facilitate the persistence of infected host litter, potentially slowing the return of nutrients to the environmental pool while also promoting the survival and dispersal of primary inoculum the following season.
Bacterial pathogens dynamic during multi-species infections
<p>Illumina gapA sequences of synthetic communities of plant bacterial pathogens: Pectobacterium and Dickeya genus. Sequencing was performed after growth on TSB synthetic medium (2 days post inoculation) or growth on potato tubers (5 days post infection).</p> <p> </p> <p>The following files are available:</p> <p>PT_table.txt: description of the potato tubers samples</p> <p>TSB_table.txt: description of samples in synthetic medium (TSB)</p> <p>gapA_PT.fasta.gz: Illumina fasta sequences after potato tubers infection (35,000 reads)</p> <p>gapA_TSB.fasta.gz: Illumina fasta sequences after synthetic medium inoculation (35,000 reads)</p> <p>gapA_without_primers.fasta: gapA sequences (without primers) of Pectobacterium and Dickeya strains used in this study (27 strains)</p> <p>species.txt: list of bacterial species used in this study (9 species)</p> <p>strains.txt: list of bacterial strains used in this study (27 strains)</p> <p>count.py: python3 script used to analyse the output of blastn</p> <p>R_script_FigureS1.R: R script for statistical analysis</p> <p>R_script_Figure2b.R: R script for statistical analysis</p> <p>R_script_Figure2a.R: R script for statistical analysis</p> <p> </p> <p>Method (examplified with the gapA_TSB sequences at the species level):</p> <p>• gapA sequences were blasted (blastn) against gapA sequences of Pectobacterium and Dickeya strains used in this study:</p> <p>makeblastdb -in gapA_without_primers.fasta -dbtype nucl -out dbblastn</p> <p>blastn -db dbblastn -query gapA_TSB.fasta -outfmt 6 -out blast.blastn -num_threads 12 -evalue 0.00001 -num_alignments 1</p> <p>• Reads count. Reads matching (100% identity) with gapA sequences of Pectobacterium and Dickeya strains used in this study were counted using the count.py python script. The output is a tab-separated values (.tsv) file:</p> <p>python3 count.py species.txt blast.blastn</p>
R scripts, input and output data for: Season of death, pathogen persistence and wildlife behaviour alter number of anthrax secondary infections from environmental reservoirs
<p>An important part of infectious disease management is predicting factors that influence disease outbreaks, such as <em>R</em>, the number of secondary infections arising from an infected individual. Estimating <em>R</em> is particularly challenging for environmentally transmitted pathogens given time lags between cases and subsequent infections. Here, we calculated <em>R</em> for <em>Bacillus anthracis</em> infections arising from anthrax carcass sites in Etosha National Park, Namibia. Combining host behavioural data, pathogen concentrations, and simulation models, we show that <em>R</em> is spatially and temporally variable, driven by spore concentrations at death, host visitation rates and early preference for foraging at infectious sites. While spores were detected up to a decade after death, most secondary infections occurred within two years. Transmission simulations under scenarios combining site infectiousness and host exposure risk under different environmental conditions led to dramatically different outbreak dynamics, from pathogen extinction (<em>R</em><1) to explosive outbreaks (<em>R</em>>10). These transmission heterogeneities may explain variation in anthrax outbreak dynamics observed globally, and more generally, the critical importance of environmental variation underlying host-pathogens interactions. Notably, our approach allowed us to estimate the lethal dose of a highly virulent pathogen non-invasively from observational studies and epidemiological data, useful when experiments on wildlife are undesirable or impractical.</p>
Host and pathogen gene expression profiles in Necrotizing Soft Tissue Infections
<p>Data underlying the article</p> <p><strong>Analysis of host-pathogen gene association networks reveals patient-specific response to streptococcal and poly-microbial necrotizing soft tissue infections</strong></p> <p>Sanjeevan Jahagirdar<sup>1</sup>, Lorna Morris<sup>2</sup>, Nirupama Benis<sup>3</sup>, Oddvar Oppegaard<sup>4</sup>, Mattias Svenson<sup>5</sup>,<sup> </sup>Ole Hyldegaard<sup>6</sup>, Steinar Skrede<sup>4,7</sup>, Anna Norrby-Teglund<sup>5</sup>, INFECT Study group, Vitor A. P. Martins dos Santos<sup>1,2</sup>, Edoardo Saccenti<sup>1*</sup></p> <p><sup>Contains</sup></p> <p>Data described in 4.3.2 Sample Selection and in Figure 6:</p> <p>INFECT_DualRNASeq_norm_counts_Human.txt Normalised counts from Kallisto mapping to GRCh38 (release 91) for 81 NSTI patients</p> <p>INFECT_DualRNASeq_relative_abundance_Bacteria.txt Relative abundance for all species from HumanN2 mapping for 81 NSTI patients</p> <p>BStrep_filtered_D1 - INFECT_DualRNASeq_relative_abundance_Bacteria.txt filtered for samples classified as Streptococcal from Thänert <em>et al </em>(2019) taken on the day of admission (day 1).</p> <p>BPoly_filtered_D1 - INFECT_DualRNASeq_relative_abundance_Bacteria.txt filtered for samples classified as polymicrobial from Thänert <em>et al </em>(2019) taken on the day of admission (day 1).</p> <p>HStrep_filtered_D1 - INFECT_DualRNASeq_norm_counts_Human.txt filtered for samples classified as Streptococcal from Thänert <em>et al </em>(2019) taken on the day of admission (day 1).</p> <p>HPoly_filtered_D1 - INFECT_DualRNASeq_norm_counts_Human.txt filtered for samples classified as polymicrobial from Thänert <em>et al </em>(2019) taken on the day of admission (day 1).</p>
High temperatures reduce growth, infection, and transmission of a naturally occurring fungal plant pathogen
<p>Climate change is rapidly altering the distribution of suitable habitats for many species as well as their pathogenic microbes. For many pathogens, including vector-borne diseases of humans and agricultural pathogens, climate change is expected to increase transmission and lead to pathogen range expansions. However, if pathogens have a lower heat tolerance than their host, increased warming could generate 'thermal refugia' for hosts. Predicting the outcomes of warming on disease transmission requires detailed knowledge of the thermal tolerances of both the host and the pathogen. Such thermal tolerance studies are generally lacking for fungal pathogens of wild plant populations, despite the fact that plants form the base of all terrestrial communities. Here, we quantified three aspects of the thermal tolerance (growth, infection, and propagule production) of the naturally occurring fungal pathogen <em>Microbotryum lychnidis-dioicae</em>, which causes a sterilizing anther-smut disease on the herbaceous plant <em>Silene latifolia</em>. We also quantified two aspects of host thermal tolerance: seedling survival and flowering rate. We found that temperatures >30 degreeC reduced the ability of anther-smut spores to germinate, grow, and conjugate in vitro. In addition, we found that high temperatures (30 degreeC) during, or shortly after the time of inoculation strongly reduced the likelihood of infection in seedlings. Finally, we found that high summer temperatures in the field temporarily cured infected plants, likely reducing transmission. Notably, high temperatures did not reduce survival or flowering of the host plants. Taken together, our results show that the fungus is considerably more sensitive to high temperatures than its host plant. A warming climate could therefore result in reduced disease spread or even local pathogen extirpation, leading to thermal refugia for the host.</p>
Infection-nutrition feedbacks: fat supports pathogen clearance but pathogens reduce fat in a wild mammal
<p>Though far less obvious than direct effects (clinical disease or mortality), the indirect influences of pathogens are difficult to estimate but may hold fitness consequences. Here, we disentangle the directional relationships between infection and energetic reserves, evaluating the hypotheses that energetic reserves influence infection status of the host and that infection elicits costs to energetic reserves. Using repeated measures of fat reserves and infection status in individual bighorn sheep (<em>Ovis canadensis</em>) in the Greater Yellowstone Ecosystem, we documented that fat influenced ability to clear pathogens (<em>Mycoplasma ovipneumoniae</em>) and infection with respiratory pathogens was costly to fat reserves. Costs of infection approached, and in some instances exceeded, costs of rearing offspring to independence in terms of reductions to fat reserves. Fat influenced probability of clearing pathogens, pregnancy, and over-winter survival; from an energetic perspective, an animal could survive for up to 23 days on the amount of fat that was lost to high levels of infection. Cost of pathogens may amplify tradeoffs between reproduction and survival. In the absence of an active outbreak, the influence of resident pathogens often is overlooked. Nevertheless, the energetic burden of pathogens likely has consequences for fitness and population dynamics, especially when food resources are insufficient.</p> <p><span> </span></p>
Fig. 3 in Effects of cold-acclimation, pathogen infection, and varying temperatures on insecticide susceptibility, feeding, and detoxifying enzyme levels in Diaphorina citri (Hemiptera: Liviidae)
Fig. 3. Correlations between mean percentage mortality of Diaphorina citri and temperature for field-collected and uninfected D. citri and field-collected and 'Candidatus' Liberibacter asiaticus–infected D. citri, when exposed to chlorpyriphos (A), fenpropathrin (B), imidacloprid (C), thiamethoxam (D), and spinetoram (E).
Fig. 1 in Effects of cold-acclimation, pathogen infection, and varying temperatures on insecticide susceptibility, feeding, and detoxifying enzyme levels in Diaphorina citri (Hemiptera: Liviidae)
Fig. 1. Comparison of cytochrome P450 (A), general esterase (B), and glutathione S-transferase (C) activity levels in laboratory susceptible Diaphorina citri adults at 5 temperatures. For glutathione S-transferase, means with the same uppercase letters are not significantly different from one another for imidacloprid-treated D. citri. Means with the same lowercase letters are not significantly different from one another for spinetoram-treated D. citri.
Рис. 8. ОтноситеΛьная преΑставΛенность транскриптов патогенраспознающих рецепторов в гемоцитах моΛΛюсков Planorbarius corneus, заражённых трематоΑами Bilharziella polonica (I) и незаражённых особей (N) Fig. 8. Relative number of transcripts of pattern recognition receptors from hemocytes of Planorbarius corneus molluscs infected with Bilharziella polonica trematodes (I) and uninfected individuals (N) in Pathogen recognition molecules from hemocytes of Planorbarius corneus molluscs (Planorbidae, Pulmonata)
Рис. 8. ОтноситеΛьная преΑставΛенность транскриптов патогенраспознающих рецепторов в гемоцитах моΛΛюсков Planorbarius corneus, заражённых трематоΑами Bilharziella polonica (I) и незаражённых особей (N) Fig. 8. Relative number of transcripts of pattern recognition receptors from hemocytes of Planorbarius corneus molluscs infected with Bilharziella polonica trematodes (I) and uninfected individuals (N)
Fig. 2 in Experimental evaluation of pathogenicity and acquired immunity of Eimeria species, E. uekii and E. raichoi, infecting Japanese rock ptarmigans in a subspecies of the birds
Fig. 2. The number of oocysts per gram of feces (OPG) after inoculation with E. uekii and E. raichoi oocysts. Panels A and B show E. uekii and E. raichoi OPG, respectively. Chicks Nos. 1–3 were inoculated depending on the manner of oocysts E. uekii and E. raichoi as described at the bottom of Figure, and mouse no. 4 was inoculated with oocysts of E. raichoi.
Fig. 1 in Experimental evaluation of pathogenicity and acquired immunity of Eimeria species, E. uekii and E. raichoi, infecting Japanese rock ptarmigans in a subspecies of the birds
Fig. 1. Weight gain of Svalbard rock ptarmigans after inoculation with E. uekii and E. raichoi oocysts. The inoculation doses of E. uekii and E. raichoi were 4 104 and × 17 103 or 4 103 (A), 2 104 and 8 103 (B), 4 103 and 17 or 4 102 (C), and 4 102 and 17 or 4 101 (D), respectively. Group E was administered PBS as a × × × × × × × × control, and group F was inoculated with 4 104 oocysts of E. raichoi that had been passed in turkeys. "n" indicates the numbers of examined chicks.
Fig. 5 in Experimental evaluation of pathogenicity and acquired immunity of Eimeria species, E. uekii and E. raichoi, infecting Japanese rock ptarmigans in a subspecies of the birds
Fig. 5. Histopathological photomicrographs of sections of the intestines of challenged chicks. Panels A and B show the ileum and duodenum of the primary inoculated chick at 7 days PI, respectively. Panels C and D show the ileum and colon of a non-inoculated chick at 7 days PI, respectively. Arrows indicate developmental zoites (sexual stages in panels C and D). Scale bars are 20 μm in panels A and C and 50 μm in panels B and D.
Fig. 4 in Experimental evaluation of pathogenicity and acquired immunity of Eimeria species, E. uekii and E. raichoi, infecting Japanese rock ptarmigans in a subspecies of the birds
Fig. 4. Weight gain of Svalbard rock ptarmigans after challenge inoculation. Panels A and B show the weight of control (PBS) and primary inoculated chicks, respectively. Two-direction arrows indicate the period of challenge inoculation, 4 104 E. uekii and 2 103 E. raichoi for 5 days.
Fig. 3 in Experimental evaluation of pathogenicity and acquired immunity of Eimeria species, E. uekii and E. raichoi, infecting Japanese rock ptarmigans in a subspecies of the birds
Fig. 3. Histopathological photomicrographs of sections from an experimentally inoculated chick (Svalbard rock ptarmigan). Panel A shows the ileum of the chick at 4 days PI after inoculation with 4 × 104 E. uekii and 2 × 103 E. raichoi oocysts. Panel B is a higher magnification of the section. Arrows indicate developmental zoites or mature schizonts (in panel B). Scale bars in panels A and B are 20 μm and 50 μm, respectively.
Sand lizards (Lacerta agilis) decrease nymphal infection prevalence for tick-borne pathogens Borrelia burgdorferi sensu lato and Anaplasma phagocytophilum in a coastal dune ecosystem
<p>1. Understanding which factors determine tick-borne disease hazard can contribute to effective disease control. In Europe, the hazard of the pathogens <em>Borrelia burgdorferi</em> s.l. and <em>Anaplasma phagocytophilum</em> is determined by local tick densities (mainly <em>Ixodes ricinus</em>) and the reservoir competence of the host species community. Sand lizards (<em>Lacerta agilis</em>) are common hosts for larvae and nymphs of <em>I. ricinus</em> and non-competent reservoirs for both pathogens. Consequently, high relative abundance of <em>L. agilis</em> is hypothesized to be associated with lower infection prevalence in nymphs. Here, we aimed to test whether this effectively occurs in natural settings.</p> <p>2. We sampled different habitat types within a heterogenous dune landscape at the Dutch coast and estimated 1) <em>L. agilis</em> densities, 2) host community competence, 3) the density and infection prevalence of questing<em> I. ricinus</em> ticks, and 4) the number and infection prevalence of ticks feeding on <em>L. agilis</em>.</p> <p>3. Captured <em>L. agilis</em> had high tick burdens and contributed substantially to feeding <em>I. ricinus</em> larvae in their natural habitat. <em>B. burgdorferi</em> s.l. and <em>A. phagocytophilum</em> were virtually absent from feeding larvae and nymphs.</p> <p>4. The nymphal infection prevalence of both pathogens in questing ticks was lower in habitat types where <em>L. agilis</em> was more abundant. Hence, <em>L. agilis</em> strongly reduced community competence.</p> <p>5. The density of questing nymphs was higher in habitat types with denser vegetation and also varied more between habitat types than infection prevalence. As a result, nymphal density had a stronger effect on the density of infected ticks than did nymphal infection prevalence.</p> <p>6. Synthesis and applications. Coastal dune habitats favourable for <em>L. agilis</em> have lower densities of questing nymphs, and a lower human infection hazard. These results might be applicable to similar ecosystems where <em>L. agilis</em> is present. From a public health perspective, this underlines the importance of preserving early successional habitat, as encroaching shrubs are associated with higher tick-borne disease hazard, and vegetation removal might be a solution to reduce hazard in coastal dunes. The high degree of spatial heterogeneity in the abundance of tick-borne pathogens also poses opportunities to manage recreational activities to limit human exposure to tick-borne diseases.</p>
R scripts, input and output data for: Season of death, pathogen persistence and wildlife behaviour alter number of anthrax secondary infections from environmental reservoirs
Open the record for dataset details and reuse information.
High temperatures reduce growth, infection, and transmission of a naturally occurring fungal plant pathogen
Open the record for dataset details and reuse information.
Part 2: Kiss and spit metabolomics highlight the role of host purine metabolism during pathogen infection
Open the record for dataset details and reuse information.
Infection-nutrition feedbacks: fat supports pathogen clearance but pathogens reduce fat in a wild mammal
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