Strain Structure and Dynamics Revealed by Targeted Deep Sequencing of the Honey Bee Gut Microbiome

ABSTRACT Host-associated microbiomes can be critical for the health and proper development of animals and plants. The answers to many fundamental questions regarding the modes of acquisition and microevolution of microbiome communities remain to be established. Deciphering strain-level dynamics is essential to fully understand how microbial communities evolve, but the forces shaping the strain-level dynamics of microbial communities remain largely unexplored, mostly because of methodological issues and cost. Here, we used targeted strain-level deep sequencing to uncover the strain dynamics within a host-associated microbial community using the honey bee gut microbiome as a model system. Our results revealed that amplicon sequencing of conserved protein-coding gene regions using species-specific primers is a cost-effective and accurate method for exploring strain-level diversity. In fact, using this method we were able to confirm strain-level results that have been obtained from whole-genome shotgun sequencing of the honey bee gut microbiome but with a much higher resolution. Importantly, our deep sequencing approach allowed us to explore the impact of low-frequency strains (i.e., cryptic strains) on microbiome dynamics. Results show that cryptic strain diversity is not responsible for the observed variations in microbiome composition across bees. Altogether, the findings revealed new fundamental insights regarding strain dynamics of host-associated microbiomes. IMPORTANCE The factors driving fine-scale composition and dynamics of gut microbial communities are poorly understood. In this study, we used metagenomic amplicon deep sequencing to decipher the strain dynamics of two key members of the honey bee gut microbiome. Using this high-throughput and cost-effective approach, we were able to confirm results from previous large-scale whole-genome shotgun (WGS) metagenomic sequencing studies while also gaining additional insights into the community dynamics of two core members of the honey bee gut microbiome. Moreover, we were able to show that cryptic strains are not responsible for the observed variations in microbiome composition across bees.

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Immune Gene Expression Covaries with Gut Microbiome Composition in Stickleback

mBio ◽

10.1128/mbio.00145-21 ◽

2021 ◽

Vol 12 (3) ◽

Author(s):

Lauren E. Fuess ◽

Stijn den Haan ◽

Fei Ling ◽

Jesse N. Weber ◽

Natalie C. Steinel ◽

...

Keyword(s):

Gene Expression ◽

Microbial Communities ◽

Gut Microbiome ◽

Alpha Diversity ◽

Host Immunity ◽

Host Gene ◽

Microbiota Composition ◽

Host Gene Expression ◽

Microbiome Composition ◽

Immune Genes

ABSTRACT Commensal microbial communities have immense effects on their vertebrate hosts, contributing to a number of physiological functions, as well as host fitness. In particular, host immunity is strongly linked to microbiota composition through poorly understood bi-directional links. Gene expression may be a potential mediator of these links between microbial communities and host function. However, few studies have investigated connections between microbiota composition and expression of host immune genes in complex systems. Here, we leverage a large study of laboratory-raised fish from the species Gasterosteus aculeatus (three-spined stickleback) to document correlations between gene expression and microbiome composition. First, we examined correlations between microbiome alpha diversity and gene expression. Our results demonstrate robust positive associations between microbial alpha diversity and expression of host immune genes. Next, we examined correlations between host gene expression and abundance of microbial taxa. We identified 15 microbial families that were highly correlated with host gene expression. These families were all tightly correlated with host expression of immune genes and processes, falling into one of three categories—those positively correlated, negatively correlated, and neutrally related to immune processes. Furthermore, we highlight several important immune processes that are commonly associated with the abundance of these taxa, including both macrophage and B cell functions. Further functional characterization of microbial taxa will help disentangle the mechanisms of the correlations described here. In sum, our study supports prevailing hypotheses of intimate links between host immunity and gut microbiome composition. IMPORTANCE Here, we document associations between host gene expression and gut microbiome composition in a nonmammalian vertebrate species. We highlight associations between expression of immune genes and both microbiome diversity and abundance of specific microbial taxa. These findings support other findings from model systems which have suggested that gut microbiome composition and host immunity are intimately linked. Furthermore, we demonstrate that these correlations are truly systemic; the gene expression detailed here was collected from an important fish immune organ (the head kidney) that is anatomically distant from the gut. This emphasizes the systemic impact of connections between gut microbiota and host immune function. Our work is a significant advancement in the understanding of immune-microbiome links in nonmodel, natural systems.

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IMMU-09. HUMAN MICROBIOTA INFLUENCE THE EFFICACY OF IMMUNOTHERAPY IN A MOUSE MODEL OF GLIOBLASTOMA

Neuro-Oncology ◽

10.1093/neuonc/noab196.369 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi93-vi94

Author(s):

Kory Dees ◽

Hyunmin Koo ◽

James Humphreys ◽

Joseph Hakim ◽

David Crossman ◽

...

Keyword(s):

Mouse Model ◽

Microbial Communities ◽

Mouse Models ◽

Gut Microbiome ◽

Positive Response ◽

Checkpoint Inhibitors ◽

Metagenomic Sequencing ◽

Sequencing Data ◽

Microbial Composition ◽

Healthy Human

Abstract Although immunotherapy works well in glioblastoma (GBM) pre-clinical mouse models, the therapy has unfortunately not demonstrated efficacy in humans. In melanoma and other cancers, the composition of the gut microbiome has been shown to determine responsiveness or resistance to immune checkpoint inhibitors (anti-PD-1). Most pre-clinical cancer studies have been done in mouse models using mouse gut microbiomes, but there are significant differences between mouse and human microbial gut compositions. To address this inconsistency, we developed a novel humanized microbiome (HuM) model to study the response to immunotherapy in a pre-clinical mouse model of GBM. We used five healthy human donors for fecal transplantation of gnotobiotic mice. After the transplanted microbiomes stabilized, the mice were bred to generate five independent humanized mouse lines (HuM1-HuM5). Analysis of shotgun metagenomic sequencing data from fecal samples revealed a unique microbiome with significant differences in diversity and microbial composition among HuM1-HuM5 lines. Interestingly, we found that the HuM lines responded differently to anti-PD-1. Specifically, we demonstrate that HuM2 and HuM3 mice are responsive to anti-PD-1 and displayed significantly increased survival compared to isotype controls, while HuM1, HuM4, and HuM5 mice are resistant to anti-PD-1. These mice are genetically identical, and only differ in the composition of the gut microbiome. In a correlative experiment, we found that disrupting the responder HuM2 microbiome with antibiotics abrogated the positive response to anti-PD-1, indicating that HuM2 microbiota must be present in the mice to elicit the positive response to anti-PD-1 in the GBM model. The question remains of whether the “responsive” microbial communities in HuM2 and HuM3 can be therapeutically exploited and applicable in other tumor models, or if the “resistant” microbial communities in HuM1, HuM4, and HuM5 can be depleted and/or replaced. Future studies will assess responder microbial transplants as a method of enhancing immunotherapy.

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Microbial resolution of whole genome shotgun and 16S amplicon metagenomic sequencing using publicly available NEON data

PLoS ONE ◽

10.1371/journal.pone.0228899 ◽

2020 ◽

Vol 15 (2) ◽

pp. e0228899 ◽

Cited By ~ 8

Author(s):

Kyle D. Brumfield ◽

Anwar Huq ◽

Rita R. Colwell ◽

James L. Olds ◽

Menu B. Leddy

Keyword(s):

Whole Genome Shotgun ◽

Whole Genome ◽

Metagenomic Sequencing

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Colorectal Cancer and the Human Gut Microbiome: Reproducibility with Whole-Genome Shotgun Sequencing

PLoS ONE ◽

10.1371/journal.pone.0155362 ◽

2016 ◽

Vol 11 (5) ◽

pp. e0155362 ◽

Cited By ~ 100

Author(s):

Emily Vogtmann ◽

Xing Hua ◽

Georg Zeller ◽

Shinichi Sunagawa ◽

Anita Y. Voigt ◽

...

Keyword(s):

Colorectal Cancer ◽

Gut Microbiome ◽

Shotgun Sequencing ◽

Whole Genome Shotgun ◽

Whole Genome ◽

Human Gut ◽

Human Gut Microbiome ◽

Whole Genome Shotgun Sequencing

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Delivery mode impacts newborn gut colonization efficiency

10.1101/2020.01.29.919993 ◽

2020 ◽

Cited By ~ 2

Author(s):

Caroline Mitchell ◽

Larson Hogstrom ◽

Allison Bryant ◽

Agnes Bergerat ◽

Avital Cher ◽

...

Keyword(s):

Gut Microbiome ◽

Dominant Factor ◽

Delivery Mode ◽

Metagenomic Sequencing ◽

Vaginal Microbiome ◽

Abdominal Incision ◽

Birth Canal ◽

Microbiome Composition ◽

Gut Colonization ◽

Infant Gut Microbiome

AbstractDelivery mode is the variable with the greatest influence on the infant gut microbiome composition in the first few months of life. Children born by Cesarean section (C-section) lack species from the Bacteroides genus in their gut microbial community, and this difference can be detectable until 6-18 months of age. One hypothesis is that these differences stem from lack of exposure to the maternal vaginal microbiome, as children born by C-section do not pass through the birth canal; however, Bacteroides species are not common members of the vaginal microbiome, thus this explanation seems inadequate. Here, we set out to re-evaluate this hypothesis by collecting rectal and vaginal samples before delivery from 73 mothers with paired stool from their infants in the first two weeks of life. We compared microbial profiles of infants born by planned, pre-labor C-section to those born by emergent, post-labor surgery (where the child was in the birth canal, but eventually delivered through an abdominal incision), and found no significant differences in the microbiome between these two groups. Both groups showed the characteristic signature lack of Bacteroides species, despite their difference in exposure to the birth canal. Surprisingly, this signature was only evident in samples from week two of life, but not in the first week. Children born by C-section often had high abundance of Bacteroides in their first few days of life, but these were not stable colonizers of the infant gut, as they were not detectable by week two. Finally, we used metagenomic sequencing to compare microbial strains in maternal vaginal and rectal samples and samples from their infants; we found evidence for mother-to-child transmission of rectal rather than vaginal strains. These results challenge birth canal exposure as the dominant factor in infant gut microbiome establishment and implicate colonization efficiency rather than exposure as a dictating factor of the newborn gut microbiome composition.

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Studying vertical microbiome transmission from mothers to infants by strain-level metagenomic profiling

10.1101/081828 ◽

2016 ◽

Cited By ~ 1

Author(s):

Francesco Asnicar ◽

Serena Manara ◽

Moreno Zolfo ◽

Duy Tin Truong ◽

Matthias Scholz ◽

...

Keyword(s):

Vertical Transmission ◽

Gut Microbiome ◽

Community Dynamics ◽

Infant Health ◽

Common Species ◽

Strain Level ◽

Metagenomic Sequencing ◽

Shotgun Metagenomics ◽

Early Infant

AbstractThe gut microbiome starts to be shaped in the first days of life and continues to increase its diversity during the first months. Several investigations are assessing the link between the configuration of the infant gut microbiome and infant health, but a comprehensive strain-level assessment of vertically transmitted microbes from mother to infant is still missing. We longitudinally collected fecal and breast milk samples from multiple mother-infant pairs during the first year of life, and applied shotgun metagenomic sequencing followed by strain-level profiling. We observed several specific strains including those from Bifidobacterium bifidum, Coprococcus comes, and Ruminococcus bromii, that were present in samples from the same mother-infant pair, while being clearly distinct from those carried by other pairs, which is indicative of vertical transmission. We further applied metatranscriptomics to study the in vivo expression of vertically transmitted microbes, for example Bacteroides vulgatus and Bifidobacterium spp., thus suggesting that transmitted strains are functionally active in the two rather different environments of the adult and infant guts. By combining longitudinal microbiome sampling and newly developed computational tools for strain-level microbiome analysis, we showed that it is possible to track vertical transmission of members of the microbiome from mother to infants and characterize their transcriptional activity. Our work poses the basis for surveying at larger scale the sources of microbial diversity in the infants and starts associating these transmissions with the subsequent longer-term development of a healthy or dysbiotic microbiome.ImportanceEarly infant exposure is important in the acquisition and ultimate development of a healthy infant microbiome. There is increasing support that the maternal microbial reservoir is a key route of microbial transmission, yet much is inferred from the observation of shared species in mother and infant. Common species, per se, does not necessarily equate vertical transmission as species exhibit considerable strain heterogeneity and it is therefore imperative to identify shared strains. We demonstrate here the potential of shotgun metagenomics and strain-level resolution to identify vertical transmission events via the maternal source. Combined with a metatranscriptomic approach, we show the potential not only to identify and track the fate of microbes in the early infant microbiome but also identify the metabolically active members. These approaches will ultimately provide important insights into the acquisition, development and community dynamics of the infant microbiome.

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Interplay between the human gut microbiome and host metabolism

10.1101/561787 ◽

2019 ◽

Cited By ~ 1

Author(s):

Alessia Visconti ◽

Caroline I. Le Roy ◽

Fabio Rosa ◽

Niccolo Rossi ◽

Tiphaine C. Martin ◽

...

Keyword(s):

Gut Microbiome ◽

Metabolic Pathways ◽

Taxonomic Composition ◽

Metagenomic Sequencing ◽

Human Gut ◽

Metabolic Potential ◽

Microbial Ecosystem ◽

Microbiome Composition ◽

Shotgun Metagenomic Sequencing ◽

Key Species

AbstractThe human gut is inhabited by a complex and metabolically active microbial ecosystem regulating host health. While many studies have focused on the effect of individual microbial taxa, the metabolic potential of the entire gut microbial ecosystem has been largely under-explored. We characterised the gut microbiome of 1,004 twins via whole shotgun metagenomic sequencing (average 39M reads per sample). We observed greater similarity, across unrelated individuals, for functional metabolic pathways (82%) than for taxonomic composition (43%). We conducted a microbiota-wide association study linking both taxonomic information and microbial metabolic pathways with 673 blood and 713 faecal metabolites (Metabolon, Inc.). Metabolic pathways associated with 34% of blood and 95% of faecal metabolites, with over 18,000 significant associations, while species-level results identified less than 3,000 associations, suggesting that coordinated action of multiple taxa is required to affect the metabolome. Finally, we estimated that the microbiome mediated a crosstalk between 71% of faecal and 15% of blood metabolites, highlighting six key species (unclassified Subdoligranulum spp., Faecalibacterium prausnitzii, Roseburia inulinivorans, Methanobrevibacter smithii, Eubacterium rectale, and Akkermansia muciniphila). Because of the large inter-person variability in microbiome composition, our results underline the importance of studying gut microbial metabolic pathways rather than focusing purely on taxonomy to find therapeutic and diagnostic targets.

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An online atlas of human plasma metabolite signatures of gut microbiome composition

10.1101/2021.12.23.21268179 ◽

2021 ◽

Author(s):

Koen F. Dekkers ◽

Sergi Sayols-Baixeras ◽

Gabriel Baldanzi ◽

Christoph Nowak ◽

Ulf Hammar ◽

...

Keyword(s):

Gut Microbiota ◽

Gut Microbiome ◽

High Performance ◽

Alpha Diversity ◽

Plasma Metabolites ◽

Uremic Toxin ◽

Metagenomic Sequencing ◽

Microbiome Composition ◽

Plasma Metabolite

The human gut microbiota produces a variety of small compounds, some of which enter the bloodstream and impact host health. Conversely, various exogenous nutritional and pharmaceutical compounds affect the gut microbiome composition before entering circulation. Characterization of the gut microbiota—host plasma metabolite interactions is an important step towards understanding the effects of the gut microbiota on human health. However, studies involving large and deeply phenotyped cohorts that would reveal such meaningful interactions are scarce. Here, we used deep metagenomic sequencing and ultra-high-performance liquid chromatography linked to mass spectrometry for detailed characterization of the fecal microbiota and plasma metabolome, respectively, of 8,584 participants invited at age 50 to 64 of the Swedish CArdioPulmonary bioImage Study (SCAPIS). After adjusting for multiple comparisons, we identified 1,008 associations between species alpha diversity and plasma metabolites, and 318,944 associations between specific gut metagenomic species and plasma metabolites. The gut microbiota explained up to 50% of the variance of individual plasma metabolites (mean of 4.7%). We present all results as the searchable association atlas "GUTSY" as a rich resource for mining associations, and exemplify the potential of the atlas by presenting novel associations between oral medication and the gut microbiome, and microbiota species strongly associated with levels of the uremic toxin p-cresol sulfate. The association atlas can be used as the basis for targeted studies of perturbation of specific bacteria and for identification of candidate plasma biomarkers of gut flora composition.

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Alterations in gut microbiome composition and function in irritable bowel syndrome and increased probiotic abundance with daily supplementation

10.1101/2021.09.02.458777 ◽

2021 ◽

Author(s):

Joann Phan ◽

Divya Nair ◽

Suneer Jain ◽

Thibaut Montagne ◽

Demi Valeria Flores ◽

...

Keyword(s):

Irritable Bowel Syndrome ◽

Gut Microbiome ◽

The United States ◽

Supporting Evidence ◽

Metagenomic Sequencing ◽

Healthy Controls ◽

Microbiome Composition ◽

Significant Difference ◽

Stool Samples ◽

Irritable Bowel

AbstractBackgroundIrritable bowel syndrome (IBS) is characterized by abdominal discomfort and irregular bowel movements and stool consistency. Because there are different symptoms associated with IBS, it is difficult to diagnose the role of the microbiome in IBS.ObjectiveHere, we present a study that includes metagenomic sequencing of stool samples from subjects with the predominant subtypes of IBS and a healthy cohort. We collected longitudinal samples from individuals with IBS who took daily made-to-order precision probiotic and prebiotic supplementation throughout the study.Materials and MethodsThis study includes a population of 489 individuals with IBS and 122 healthy controls. All stool samples were subjected to shotgun metagenomic sequencing. Precision probiotics and prebiotics were formulated for all subjects with longitudinal timepoints.ResultsThere was significant variation explained in the microbiome between the healthy and IBS cohorts. Individuals with IBS had a lower gut microbiome diversity and reduced anti-inflammatory microbes compared to the healthy controls. Eubacterium rectale and Faecalibacterium prausnitzii were associated with healthy microbiomes while Shigella species were associated with IBS. Pathway analysis indicated a functional imbalance of short chain fatty acids, vitamins, and a microbial component of Gram-negative bacteria in IBS compared to healthy controls. In the longitudinal dataset, there was a significant difference in microbiome composition between timepoints 1 and 3. There was also a significant increase in the overall microbiome score and relative abundances of probiotic species used to target the symptoms associated with IBS.ConclusionsWe identified microbes and pathways that differentiate healthy and IBS microbiomes. In response to precision probiotic supplementation, we identified a significant improvement in the overall microbiome score in individuals with IBS. These results suggest an important role for probiotics in managing IBS symptoms and modulation of the microbiome as a potential management strategy.ImportanceAn estimated 35 million people in the United States and 11.5% of the population globally are affected by IBS. Immunity, genetics, environment, diet, small intestinal bacterial overgrowth (SIBO), and the gut microbiome are all factors that contribute to the onset or triggers of IBS. With strong supporting evidence that the gut microbiome may influence symptoms associated with IBS, elucidating the important microbes that contribute to the symptoms and severity is important to make decisions for targeted treatment. As probiotics have become more common in treating IBS symptoms, identifying effective probiotics may help inform future studies and treatment.

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Intestinal microbiota domination under extreme selective pressures characterized by metagenomic read cloud sequencing and assembly

BMC Bioinformatics ◽

10.1186/s12859-019-3073-1 ◽

2019 ◽

Vol 20 (S16) ◽

Author(s):

Joyce B. Kang ◽

Benjamin A. Siranosian ◽

Eli L. Moss ◽

Niaz Banaei ◽

Tessa M. Andermann ◽

...

Keyword(s):

Resistance Genes ◽

Gut Microbiome ◽

Draft Genome ◽

Strain Level ◽

Comparative Genomic ◽

Metagenomic Sequencing ◽

Antibiotic Exposure ◽

E Coli ◽

Selective Pressures ◽

Antimicrobial Resistance Genes

Abstract Background Low diversity of the gut microbiome, often progressing to the point of intestinal domination by a single species, has been linked to poor outcomes in patients undergoing hematopoietic cell transplantation (HCT). Our ability to understand how certain organisms attain intestinal domination over others has been restricted in part by current metagenomic sequencing technologies that are typically unable to reconstruct complete genomes for individual organisms present within a sequenced microbial community. We recently developed a metagenomic read cloud sequencing and assembly approach that generates improved draft genomes for individual organisms compared to conventional short-read sequencing and assembly methods. Herein, we applied metagenomic read cloud sequencing to four stool samples collected longitudinally from an HCT patient preceding treatment and over the course of heavy antibiotic exposure. Results Characterization of microbiome composition by taxonomic classification of reads reveals that that upon antibiotic exposure, the subject’s gut microbiome experienced a marked decrease in diversity and became dominated by Escherichia coli. While diversity is restored at the final time point, this occurs without recovery of the original species and strain-level composition. Draft genomes for individual organisms within each sample were generated using both read cloud and conventional assembly. Read clouds were found to improve the completeness and contiguity of genome assemblies compared to conventional assembly. Moreover, read clouds enabled the placement of antibiotic resistance genes present in multiple copies both within a single draft genome and across multiple organisms. The occurrence of resistance genes associates with the timing of antibiotics administered to the patient, and comparative genomic analysis of the various intestinal E. coli strains across time points as well as the bloodstream isolate showed that the subject’s E. coli bloodstream infection likely originated from the intestine. The E. coli genome from the initial pre-transplant stool sample harbors 46 known antimicrobial resistance genes, while all other species from the pre-transplant sample each contain at most 5 genes, consistent with a model of heavy antibiotic exposure resulting in selective outgrowth of the highly antibiotic-resistant E. coli. Conclusion This study demonstrates the application and utility of metagenomic read cloud sequencing and assembly to study the underlying strain-level genomic factors influencing gut microbiome dynamics under extreme selective pressures in the clinical context of HCT.

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