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150 results for “host microbiome”
Tick microbiomes in neotropical forest fragments are best explained by tick-associated and environmental factors rather than host blood source
<p>The composition of tick microbiomes varies both within and among tick species. Whether this variation is intrinsic (related to tick characteristics), or extrinsic (related to vertebrate host and habitat) is poorly understood but important, as microbiota can influence the reproductive success and vector competence of ticks. We aimed to uncover what intrinsic and extrinsic factors best explain the microbial composition and taxon richness of 11 species of Neotropical ticks, collected from eight species of small mammals in 18 forest fragments across central Panama. Microbial richness varied among tick species, life stages, and collection sites, but was not related to host blood source. Microbiome composition was best explained by tick life stage, with bacterial assemblages of larvae being a subset of those of nymphs. Collection site explained most of the bacterial taxa with differential abundance across intrinsic and extrinsic factors. <i>Francisella </i>and <i>Rickettsia </i>were highly prevalent, but their proportional abundance differed greatly among tick species and we found both positive and negative co-occurrence between members of these two genera. Other tick endosymbionts (e.g. <i>Coxiella</i>, <i>Rickettsiella</i>) were associated with specific tick species. In addition, we detected <i>Anaplasma</i> and <i>Bartonella </i>in several tick species. Our results indicate that the microbial composition and richness of Neotropical ticks are principally related to intrinsic factors (tick species, life stage) and collection site. Taken together, our analysis informs how tick microbiomes are structured and can help anchor our understanding of tick microbiomes from tropical environments more broadly.</p>
Data from: Epidemic and endemic pathogen dynamics correspond to distinct host population microbiomes at a landscape scale
Infectious diseases have serious impacts on human and wildlife populations, but the effects of a disease can vary, even among individuals or populations of the same host species. Identifying the reasons for this variation is key to understanding disease dynamics and mitigating infectious disease impacts, but disentangling cause and correlation during natural outbreaks is extremely challenging. This study aims to understand associations between symbiotic bacterial communities and an infectious disease, and examines multiple host populations before or after pathogen invasion to infer likely causal links. The results show that symbiotic bacteria are linked to fundamentally different outcomes of pathogen infection: host–pathogen coexistence (endemic infection) or host population extirpation (epidemic infection). Diversity and composition of skin-associated bacteria differed between populations of the frog, Rana sierrae, that coexist with or were extirpated by the fungal pathogen, Batrachochytrium dendrobatidis (Bd). Data from multiple populations sampled before or after pathogen invasion were used to infer cause and effect in the relationship between the fungal pathogen and symbiotic bacteria. Among host populations, variation in the composition of the skin microbiome was most strongly predicted by pathogen infection severity, even in analyses where the outcome of infection did not vary. This result suggests that pathogen infection shapes variation in the skin microbiome across host populations that coexist with or are driven to extirpation by the pathogen. By contrast, microbiome richness was largely unaffected by pathogen infection intensity, but was strongly predicted by geographical region of the host population, indicating the importance of environmental or host genetic factors in shaping microbiome richness. Thus, while both richness and composition of the microbiome differed between endemic and epidemic host populations, the underlying causes are most likely different: pathogen infection appears to shape microbiome composition, while microbiome richness was less sensitive to pathogen-induced disturbance. Because higher richness was correlated with host persistence in the presence of Bd, and richness appeared relatively stable to Bd infection, microbiome richness may contribute to disease resistance, although the latter remains to be directly tested.
A Spatial Multi-Modal Dissection of Host-Microbiome Interactions within the Colitis Tissue Microenvironment
<p>All processed data used in the manuscript 'A Spatial Multi-Modal Dissection of Host-Microbiome Interactions within the Colitis Tissue Microenvironment'. For more detail please refer to the manuscript. If there is any question please contact Bokai Zhu via email: BZHU0@MGH.HARVARD.EDU.</p> <p>Data folder structure:</p> <p>Main data (eg. presented in main figures etc): Please see .zip file 'data_submission.zip'.</p> <p>Additional data (eg. during revision, or other misc files): Please see .zip file 'data_submission_part2.zip'.</p>
Data: Metabolic modeling reveals a multi-level deregulation of host-microbiome metabolic networks in IBD
<p>This archive contains all scripts, resource data and results, including intermediate results to reproduce the results for "Metabolic modeling reveals a multi-level deregulation of host-microbiome metabolic networks in IBD". </p>
Data and code for "Multi-omics Reveals Microbiome, Host Gene Expression, and Immune Landscape in Gastric Carcinogenesis" by Park et al., iScience 2022
<p>This repository is a part of the supplementary document in Park et al., "Multi-omics Reveals Microbiome, Host Gene Expression, and Immune Landscape in Gastric Carcinogenesis" published in iScience 2022.</p> <p>Abstract: To date, there has been no multi-omic analysis characterizing the intricate relationships between the intragastric microbiome and gastric mucosal gene expression in gastric carcinogenesis. Using multi-omic approaches, we provide a comprehensive view of the connections between the microbiome and host gene expression in distinct stages of gastric carcinogenesis (i.e., healthy, gastritis, cancer). We uncover associations specific to disease states. For example, uniquely in gastritis, Helicobacteraceae is highly correlated with the expression of <em>FAM3D</em>, which has been previously implicated in gastrointestinal inflammation. Additionally, in gastric cancer but not in adjacent gastritis, Lachnospiraceae is highly correlated with the expression of <em>UBD</em>, which regulates mitosis and cell cycle time. Furthermore, lower abundances of B cells in gastric cancer compared to gastritis may suggest a previously unidentified immune evasion process in gastric carcinogenesis. Our integrative analysis provides the most comprehensive description of microbial, host transcriptomic, and immune cell factors of the gastric carcinogenesis pathway.</p>
Spatial Mapping of Mobile Genetic Elements and their Cognate Hosts in Complex Microbiomes - Identifying the host taxon of a previously undescribed plasmid
<p>We investigated the taxonomic association of an unknown plasmid within a plaque biofilm of a patient diagnosed with stage 3 periodontitis. We combined long- and short- read sequencing to identify a complete plasmid with minimal homology to any sequence in the RefSeq database. The plasmid carried several predicted genes for mobilization and toxin-antitoxin systems. We designed MGE-FISH probes for the plasmid and combined this MGE-FISH stain with an 18-genera HiPR-FISH panel.</p> <p>Images are labeled by collection time such that the laser order for a given field of view (fov) is: 488nm Lambda, 514nm Lambda, 561nm Lambda, 633nm Airyscan, 405nm Lambda. We used Flye (https://github.com/fenderglass/Flye) to assemble the plasmid using long read Nanopore sequencing only and we used OPERA-MS (https://github.com/CSB5/OPERA-MS) to do hybrid assembly with Illumina short reads and Nanopore long reads. The assemblies are in the fasta files and the reads that map to the assemblies are in the fastq files. </p>
Spatial Mapping of Mobile Genetic Elements and their Cognate Hosts in Complex Microbiomes - Combined MGE and taxonomic mapping
<p>We used rRNA-FISH to stain five common oral genera, <em>Veillonella, Streptococcus, Corynebacterium, Lautropia, </em>and <em>Neisseria, </em>each with a different fluorophore, and we used MGE-FISH to stain the <em>termL</em> gene of the active prophage with a sixth fluorophore.</p> <p>We assembled contigs using combined long- and short-read sequencing and identified a highly abundant plasmid. Alignment of this contig to the plasmid database (PLSDB) showed that the plasmid had previously been observed in <em>Prevotella nigrescens</em> (https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_018127865.1/). We selected two genes from the contig with metallo-β-lactamase (MBL) domains as targets for MGE-FISH (https://www.uniprot.org/uniprotkb/V8CNR4/entry, https://www.uniprot.org/uniprotkb/V8CNR9/entry). We stained both putative MBL genes (<em>pMBL</em>) with the same color using MGE-FISH. For taxonomic mapping, we broadened our target panel by employing HIPR-FISH. We selected a target panel of 18 genera that are highly abundant and prevalent in human plaque. We designed a HiPR-FISH spectral encoding using a 5-fluorophore combinatorial barcoding scheme, whereby each fluorophore represents a binary bit, providing 31 possible barcodes (2^5 - 1 = 31). The fluorophore for MGE-FISH was spectrally distinct from those of HiPR-FISH, enabling simultaneous implementation of both methods.</p> <p>Images are labeled by collection time such that the laser order for a given field of view (fov) is: 488nm Lambda, 514nm Lambda, 561nm Lambda, 633nm Airyscan, 405nm Lambda. We used OPERA-MS (https://github.com/CSB5/OPERA-MS) to do hybrid assembly with Illumina short reads and Nanopore long reads. The assemblies are in the fasta files and the reads that map to the assemblies are in the fastq files. </p>
A Comprehensive Assessment of Demographic, Environmental and Host Genetic Associations with Gut Microbiome Diversity in Healthy Individuals (GWAS)
<p>GWAS summary statistics accompanying manuscript "A Comprehensive Assessment of Demographic, Environmental and Host Genetic Associations with Gut Microbiome Diversity in Healthy Individuals".</p>
Dataset for the paper "Network-Based Differential Abundance Analysis: Bridging Community Interactions and Host-Microbiome Dynamics."
<p>The files with extension rds are files that contain simulated data and the tsv files contain original data along with their meta data.</p>
Data from: Host genotype and age shape the leaf and root microbiomes of a wild perennial plant
Bacteria living on and in leaves and roots influence many aspects of plant health, so the extent of a plant's genetic control over its microbiota is of great interest to crop breeders and evolutionary biologists. Laboratory-based studies, because they poorly simulate true environmental heterogeneity, may misestimate or totally miss the influence of certain host genes on the microbiome. Here we report a large-scale field experiment to disentangle the effects of genotype, environment, age and year of harvest on bacterial communities associated with leaves and roots of Boechera stricta (Brassicaceae), a perennial wild mustard. Host genetic control of the microbiome is evident in leaves but not roots, and varies substantially among sites. Microbiome composition also shifts as plants age. Furthermore, a large proportion of leaf bacterial groups are shared with roots, suggesting inoculation from soil. Our results demonstrate how genotype-by-environment interactions contribute to the complexity of microbiome assembly in natural environments.
Feeding on a Bartonella henselae infected host triggers temporary changes in the Ctenocephalides felis microbiome
<p>The effect of <em>Bartonella</em> <em>henselae</em> on the microbiome of its vector, <em>Ctenocephalides</em> <em>felis</em> (the cat flea) is largely unknown, as a majority of <em>C. felis</em> microbiome studies have utilized wild-caught pooled fleas. Therefore, we surveyed the microbiome of laboratory-origin <em>C. felis</em> fed on <em>B. henselae-</em>infected cats to identify changes to microbiome diversity and microbe prevalence compared to unfed fleas, and fleas fed on uninfected cats. To evaluate changes over time, fleas were fed on cats for 24 hours or 9 days. Utilizing Next Generation Sequencing (NGS) on the Illumina platform, we documented an increase in microbial diversity, richness, and evenness in <em>C. felis</em> fed on <em>Bartonella</em>-infected cats for 24 hours, changes that returned to baseline (unfed fleas or fleas fed on uninfected cats) after 9 days on the host. The increased diversity in the <em>C. felis</em> microbiome when fed on <em>B. henselae</em>-infected cats may be related to the mammalian, flea, or endosymbiont response, factors that remain to be explored and potentially exploited for pathogen control. In addition, poor <em>B</em>. <em>henselae</em> acquisition was documented in these laboratory-maintained <em>C. felis</em>. Potential hypotheses to account for this finding include poor acquisition by adult fleas, the influence of flea genetic variation on <em>B. henselae</em> acquisition, and lack of co-feeding with <em>B. henselae</em>-infected <em>C. felis</em>. This study provides an investigation of the <em>C. felis</em> microbiome response to blood feeding and blood-feeding on <em>B. henselae</em>-infected cats; however, future studies are necessary to fully characterize the effect of endosymbionts and <em>C. felis</em> diversity on <em>B. henselae</em> acquisition.</p>
Data from: Gut microbiome dysbiosis is associated with host genetics in the Norwegian Lundehund
<p class="MsoNormal"><span>A group of diseases have been shown to correlate with a phenomenon called microbiome dysbiosis, where the bacterial species composition of the gut becomes abnormal. The gut microbiome of an animal is influenced by many factors including diet, exposures to bacteria during post-gestational growth, lifestyle, and disease status. Studies also show that host genetics can affect microbiome composition. We sought to test whether host genetic background is associated with gut microbiome composition in the Norwegian Lundehund dog, a highly inbred breed with an effective population size of 13 individuals. The Lundehund has a high rate of a protein-losing enteropathy in the small intestine that is often reported as Lundehund syndrome, which negatively affects longevity and life-quality. An outcrossing project with the Buhund, Norrbottenspets and Icelandic sheepdog was recently established to reintroduce genetic diversity to the Lundehund and improve its health. To assess whether there was an association between host genetic diversity and the microbiome composition, we sampled the fecal microbiomes of 75 dogs of the parental (Lundehund), F1 (Lundehund x Buhund), and F2 (F1 x Lundehund) generations. We found significant variation in microbiome composition from the parental Lundehund generation compared to the outcross progeny. The variation observed in purebred Lundehunds corresponded to dysbiosis as seen by a highly variable microbiome composition with an elevated Firmicutes to Bacteroidetes ratio and an increase in the prevalence of <em>Streptococcus bovis/Streptococcus equinus </em>complex, a known pathobiont that can cause several diseases. We tracked several other environmental factors including diet, the presence of a cat in the household, living on a farm and the use of probiotics, but we did not find evidence of an effect of these on microbiome composition and alpha diversity. In conclusion, we found an association between host genetics and gut microbiome composition, which in turn may be associated with the high incidence of Lundehund syndrome in the purebred parental dogs.</span></p>
Data for: Environments and hosts structure the bacterial microbiomes of fungus-gardening ants and their symbiotic fungus gardens
<p>The fungus gardening-ant system is considered a complex, multi-tiered symbiosis between the ants, their fungus, and microorganisms associated with either ants or fungus. We examine the bacterial microbiome of <em>Trachymyrmex septentrionalis</em> and <em>Mycetomoellerius turrifex</em> ants and their symbiotic fungus garden, using 16S rRNA Illumina sequencing, over a large geographical region. Typically microorganisms can be acquired from a parent colony (vertical transmission) or from the environment (horizontal transmission). Because the symbiosis is characterized by co-dispersal of the ants and fungus, elements of both ant and fungus garden microbiome could be characterized by vertical transmission, for example. The goals of this study were to explore how both the ant and fungus garden bacterial microbiome were acquired. The main findings were that different mechanisms appear to explain the structure the microbiomes of ants and their symbiotic fungus gardens. Ant associated microbiomes had a strong host ant signature, which suggests vertical inheritance of the ant associated bacterial microbiome. On the other hand, the bacterial microbiome of the fungus garden was more complex in that some components appear to be structured by the ant host species whereas other by fungal lineage or region. Thus bacteria in fungus gardens appear to be acquired both horizontally and vertically. </p>
Spatial Mapping and Host Linking of Mobile Genetic Elements in Complex Microbiomes - Mapping MGEs in oral plaque biofilms at high specificity
<p>We stained for the GFP gene in samples that contained mixtures of plaque and GFP-transformed E. coli. We mapped mefE, an AMR gene located on a plasmid and encoding an antibiotic efflux pump, in the plaque metagenomic data of volunteer A but not volunteer B. To test the efficacy of gel embedding and clearing, we used orthogonal FISH probes, designed to not target any sequence in the plaque. We identified a T7-like prophage via metagenomic analysis and developed probes targeting its capsB gene, which encodes the minor capsid protein. We identified a highly prevalent prophage of the class Caudoviricetes with a large terminase gene, termL, and were able to design a large set of FISH probes to stain in three different colors simultaneously. We identified three non-plasmid AMR genes within metagenome assembled genomes: patA, patB, and adeF.</p>
Spatial Mapping and Host Linking of Mobile Genetic Elements in Complex Microbiomes - Optimization of single molecule MGE FISH
<p>We used <em>Escherichia coli </em>transformed with pJKR-H-tetR plasmids encoding an inducible <em>GFP</em> gene as a model system to assess and optimize MGE-FISH on a confocal microscope. We designed FISH probes for the non-coding strand of the <em>GFP</em> gene, used non-transformed <em>E. coli </em>as a negative control, and tested six different FISH protocols.<strong> </strong></p>
Spatial Mapping and Host Linking of Mobile Genetic Elements in Complex Microbiomes - Combined taxonomic mapping and MGE mapping
<p>We used rRNA FISH to stain five common oral genera, <em>Veillonella, Streptococcus, Corynebacterium, Lautropia, </em>and <em>Neisseria</em>, each with a different fluorophore, and we used MGE-FISH to stain the <em>termL</em> gene of an active prophage with a sixth fluorophore. </p> <p>We chose a target panel of 18 genera that are highly abundant and prevalent in human plaque and designed a HiPR-FISH probe panel using a 5-fluorophore combinatorial barcoding scheme. Using MGE-FISH, we stained a plasmid carrying mefE, subunit of a major-facilitator-superfamily antibiotic efflux pump. </p>
Data from: Host phylogeny and functional traits differentiate gut microbiomes in a diverse natural community of small mammals
<p>Differences in the bacteria inhabiting mammalian gut microbiomes tend to reflect the phylogenetic relatedness of their hosts, a pattern dubbed phylosymbiosis. Although most research on this pattern has compared the gut microbiomes of host species across biomes, understanding the evolutionary and ecological processes that generate phylosymbiosis requires comparisons across phylogenetic scales and under similar ecological conditions. We analyzed the gut microbiomes of 14 sympatric small-mammal species in a semi-arid African savanna, hypothesizing that there would be a strong phylosymbiosis pattern associated with the different body sizes and diets of the mammalian lineages present. Consistent with phylosymbiosis, microbiome dissimilarity increased with phylogenetic distance among hosts, ranging from congeneric sets of mice and hares that did not differ significantly in microbiome composition to species from different taxonomic orders that had almost no gut bacteria in common. While phylosymbiosis was detected among just the 11 species of rodents, it was substantially weaker than comparisons involving all 14 species together. In contrast, microbiome diversity and composition were generally more strongly correlated with body size, dietary breadth, and dietary overlap in comparisons restricted to rodents than in those including all lineages. The starkest divides in microbiome composition thus reflected the broad evolutionary divergence of hosts, regardless of body size or dietary composition, while subtler microbiome differences reflected variation in ecologically important traits between closely related hosts. Strong phylosymbiotic patterns arose deep in the phylogeny, and ecological filters that promote functional differentiation of cooccurring host species may disrupt or obscure this pattern near the tips.</p>
TAC/MTX vs. TAC/MMF/PTCY for Prevention of Graft-versus-Host Disease and Microbiome and Immune Reconstitution Study (BMT CTN 1703/1801)
ClinicalTrials.gov study NCT03959241. IPD Sharing: YES. Countries: 1. Publications: 3.
Remedial Mechanism of Simvastatin and Ursodeoxycholic Acid in Liver Cirrhosis: Crosstalk of Bile Secretion, Gut Microbiome, and Host Immune Response
ClinicalTrials.gov study NCT07102979. IPD Sharing: NO. Countries: 1. Publications: 4.
Data from: Microbial solutions to dietary stress: Experimental evolution reveals host-microbiome interplay in Drosophila melanogaster
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