Genomic variation landscape of the human gut microbiome. Nature. 2013;493:45-50. [PMID: 23222524 PMCID: PMC3536929 DOI: 10.1038/nature11711]

Human gut-derived B. longum subsp. longum strains protect against aging in a D-galactose-induced aging mouse model

BACKGROUND

Probiotics have been used to regulate the gut microbiota and physiology in various contexts, but their precise mechanisms of action remain unclear.

RESULTS

By population genomic analysis of 418 Bifidobacterium longum strains, including 143 newly sequenced in this study, three geographically distinct gene pools/populations, BLAsia1, BLAsia2, and BLothers, were identified. Genes involved in cell wall biosynthesis, particularly peptidoglycan biosynthesis, varied considerably among the core genomes of the different populations, but accessory genes that contributed to the carbohydrate metabolism were significantly distinct. Although active transmission was observed inter-host, inter-country, inter-city, intra-community, and intra-family, a single B. longum clone seemed to reside within each individual. A significant negative association was observed between host age and relative abundance of B. longum, while there was a strong positive association between host age and strain genotype [e.g., single nucleotide polymorphisms in the arginine biosynthesis pathway]. Further animal experiments performed with the B. longum isolates via using a D-galactose-induced aging mouse model supported these associations, in which B. longum strains with different genotypes in arginine biosynthesis pathway showed divergent abilities on protecting against host aging possibly via their different abilities to modify the metabolism of gut microbes.

CONCLUSIONS

This is the first known example of research on the evolutionary history and transmission of this probiotic species. Our results propose a new mechanistic insight for promoting host longevity via the informed use of specific probiotics or molecules. Video abstract.

Bioaccumulation of therapeutic drugs by human gut bacteria

Bacteria in the gut can modulate the availability and efficacy of therapeutic drugs. However, the systematic mapping of the interactions between drugs and bacteria has only started recently¹ and the main underlying mechanism proposed is the chemical transformation of drugs by microorganisms (biotransformation). Here we investigated the depletion of 15 structurally diverse drugs by 25 representative strains of gut bacteria. This revealed 70 bacteria-drug interactions, 29 of which had not to our knowledge been reported before. Over half of the new interactions can be ascribed to bioaccumulation; that is, bacteria storing the drug intracellularly without chemically modifying it, and in most cases without the growth of the bacteria being affected. As a case in point, we studied the molecular basis of bioaccumulation of the widely used antidepressant duloxetine by using click chemistry, thermal proteome profiling and metabolomics. We find that duloxetine binds to several metabolic enzymes and changes the metabolite secretion of the respective bacteria. When tested in a defined microbial community of accumulators and non-accumulators, duloxetine markedly altered the composition of the community through metabolic cross-feeding. We further validated our findings in an animal model, showing that bioaccumulating bacteria attenuate the behavioural response of Caenorhabditis elegans to duloxetine. Together, our results show that bioaccumulation by gut bacteria may be a common mechanism that alters drug availability and bacterial metabolism, with implications for microbiota composition, pharmacokinetics, side effects and drug responses, probably in an individual manner.

Gut microbiome colonization and development in neonatal ruminants: Strategies, prospects, and opportunities

Colonization and development of the gut microbiome is a crucial consideration for optimizing the health and performance of livestock animals. This is mainly attributed to the fact that dietary and management practices greatly influence the gut microbiota, subsequently leading to changes in nutrient utilization and immune response. A favorable microbiome can be implanted through dietary or management interventions of livestock animals, especially during early life. In this review, we explore all the possible factors (for example gestation, colostrum, and milk feeding, drinking water, starter feed, inoculation from healthy animals, prebiotics/probiotics, weaning time, essential oil and transgenesis), which can influence rumen microbiome colonization and development. We discuss the advantages and disadvantages of potential strategies used to manipulate gut development and microbial colonization to improve the production and health of newborn calves at an early age when they are most susceptible to enteric disease. Moreover, we provide insights into possible interventions and their potential effects on rumen development and microbiota establishment. Prospects of latest techniques like transgenesis and host genetics have also been discussed regarding their potential role in modulation of rumen microbiome and subsequent effects on gut development and performance in neonatal ruminants.

Embracing Metagenomic Complexity with a Genome-Free Approach

A central paradigm in microbiome data analysis, which we term the genome-centric paradigm, is that a linear (non-branching) DNA sequence is the ideal representation of a microbial genome. This representation is natural, as microbes indeed have non-branching genomes. Tremendous discoveries in microbiology were made under this paradigm, but is it always optimal for microbiome research? In this Commentary, we claim that the realization of this paradigm in metagenomic assembly, a fundamental step in the “metagenomics analysis pipeline,” suboptimally models the extensive genomic variability present in the microbiome. We outline our efforts to address these issues with a “genome-free” approach that eschews linear genomic representations in favor of a pan-metagenomic graph.

Comprehensive Strain-Level Analysis of the Gut Microbe Faecalibacterium prausnitzii in Patients with Liver Cirrhosis

Liver cirrhosis (LC) has been associated with gut microbes. However, the strain diversity of species and its association with LC have received little attention. Here, we constructed a computational framework to study the strain heterogeneity in the gut microbiome of patients with LC. Only Faecalibacterium prausnitzii shows different single-nucleotide polymorphism (SNP) patterns between the LC and healthy control (HC) groups. Strain diversity analysis discovered that although most F. prausnitzii genomes are more deficient in the LC group than in the HC group at the strain level, a subgroup of 19 F. prausnitzii strains showed no sensitivity to LC, which is inconsistent with the species-level result. The functional differences between this subgroup and other strains may involve short-chain fatty acid production and chlorine-related pathways. These findings demonstrate functional differences among F. prausnitzii subgroups, which extend current knowledge about strain heterogeneity and relationships between F. prausnitzii and LC at the strain level. IMPORTANCE Most metagenomic studies focus on microbes at the species level, thus ignoring the different effects of different strains of the same species on the host. In this study, we explored the different microbes at the strain level in the intestines of patients with liver cirrhosis and of healthy people. Previous studies have shown that the species Faecalibacterium prausnitzii has a lower abundance in patients with liver cirrhosis than in healthy people. However, our results found multiple F. prausnitzii strains that do not decrease in abundance in patients with liver cirrhosis. It is more sensitive to select the appropriate strains as indicators to distinguish between the disease and the control samples than to use the entire species as an indicator. We clustered multiple F. prausnitzii strains and discuss the functional differences of different clusters. Our findings suggest that more attention should be paid to metagenomic studies at the strain level.

The Tempo and Mode of Adaptation in a Complex Natural Population: the Microbiome

Adaptation is a fundamental process by which populations evolve to grow more fit in their environments. Recent studies are starting to show us that commensal microbes can evolve on short timescales of days and months, suggesting that ecological changes are not the only means by which microbes in complex natural populations respond to selection pressures. However, we still lack a complete understanding of the tempo and mode of adaptation in microbiomes given the many complex forces that natural populations experience, which include ecological pressures, changes in population size, spatial structure, and fluctuations in selection pressures. Advances in modeling complex populations and scenarios will allow us to understand adaptation not only in microbiomes but also more generically in other natural populations that experience similar complexities.

Ultra-resolution Metagenomics: When Enough Is Not Enough

Technological advances in community sequencing have steadily increased the taxonomic resolution at which microbes can be delineated. In high-resolution metagenomics, bacterial strains can now be resolved, enhancing medical microbiology and the description of microbial evolution in vivo. In the Hildebrand lab, we are researching novel approaches to further increase the phylogenetic resolution of metagenomics. I propose that ultra-resolution metagenomics will be the next qualitative level of community sequencing, classified by the accurate resolution of ultra-rare genetic events, such as subclonal mutations present in all populations of evolving cells. This will be used to quantify evolutionary processes at ecologically relevant scales, monitor the progress of infections within a patient, and accurately track pathogens in food and infection chains. However, to develop this next metagenomic generation, we first need to understand the currently imposed limits of sequencing technologies, metagenomic strain delineation, and genome reconstructions.

Gut Microbiota and Type 2 Diabetes Mellitus: Association, Mechanism, and Translational Applications

Gut microbiota has attracted widespread attention due to its crucial role in disease pathophysiology, including type 2 diabetes mellitus (T2DM). Metabolites and bacterial components of gut microbiota affect the initiation and progression of T2DM by regulating inflammation, immunity, and metabolism. Short-chain fatty acids, secondary bile acid, imidazole propionate, branched-chain amino acids, and lipopolysaccharide are the main molecules related to T2DM. Many studies have investigated the role of gut microbiota in T2DM, particularly those butyrate-producing bacteria. Increasing evidence has demonstrated that fecal microbiota transplantation and probiotic capsules are useful strategies in preventing diabetes. In this review, we aim to elucidate the complex association between gut microbiota and T2DM inflammation, metabolism, and immune disorders, the underlying mechanisms, and translational applications of gut microbiota. This review will provide novel insight into developing individualized therapy for T2DM patients based on gut microbiota immunometabolism.

Strain-Level Profiling of Oral Microbiota with Targeted Sequencing

Targeted sequencing of one or more regions of the bacterial 16S rRNA gene fragment has emerged as a gold standard for investigating taxonomic diversity in complex microbial communities, such as those found in the oral cavity. While this approach is useful for identifying bacteria up to genus level, its ability to distinguish between many closely related oral species, or explore strain-level variations within each species, is very limited. Here we present an approach based on targeted sequencing the 16S-23S Intergenic Spacer Region (ISR) in the bacterial ribosomal operon for taxonomic characterization of microbial communities at a subspecies or strain level. This approach retains the advantages of 16S-based methods, such as easy library preparation, high throughput, short amplicon sizes, and low cost of sequencing, while providing subspecies-level resolution as a result of naturally higher genetic diversity present in the ISR compared to the 16S hypervariable regions. These advantages make it an excellent tool for high-resolution oral microbiota characterization.

Genetic divergence and functional convergence of gut bacteria between the Eastern honey bee Apis cerana and the Western honey bee Apis mellifera

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The inter-species diversity of A. cerana and A. mellifera core gut bacteria was revealed.

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Core bacterial species of A. cerana and A. mellifera are distinctive in function.

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Functional profile of overall gut community of A. cerana and A. mellifera are similar.

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Metabolome showed that A. cerana and A. mellifera gut bacteria have similar metabolic capability.

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A. cerana and A. mellifera core gut bacteria have no strict host specificity.

Introduction

The functional relevance of intra-species diversity in natural microbial communities remains largely unexplored. The guts of two closely related honey bee species, Apis cerana and A. mellifera, are colonised by a similar set of core bacterial species composed of host-specific strains, thereby providing a good model for an intra-species diversity study.

Objectives

We aim to assess the functional relevance of intra-species diversity of A. cerana and A. mellifera gut microbiota.

Methods

Honey bee workers were collected from four regions of China. Their gut microbiomes were investigated by shotgun metagenomic sequencing, and the bacterial compositions were compared at the species level. A cross-species colonisation assay was conducted, with the gut metabolomes being characterised by LC-MS/MS.

Results

Comparative analysis showed that the strain composition of the core bacterial species was host-specific. These core bacterial species presented distinctive functional profiles between the hosts. However, the overall functional profiles of the A. cerana and A. mellifera gut microbiomes were similar; this was further supported by the consistency of the honey bees’ gut metabolome, as the gut microbiota of different honey bee species showed rather similar metabolic profiles in the cross-species colonisation assay. Moreover, this experiment also demonstrated that the gut microbiota of A. cerana and A. mellifera could cross colonise between the two honey bee species.

Conclusion

Our findings revealed functional differences in most core gut bacteria between the guts of A. cerana and A. mellifera, which may be associated with their inter-species diversity. However, the functional profiles of the overall gut microbiomes between the two honey bee species converge, probably as a result of the overlapping ecological niches of the two species. Our findings provide critical insights into the evolution and functional roles of the mutualistic microbiota of honey bees and reveal that functional redundancy could stabilise the gene content diversity at the strain-level within the gut community.

Longitudinal linked-read sequencing reveals ecological and evolutionary responses of a human gut microbiome during antibiotic treatment

Gut microbial communities can respond to antibiotic perturbations by rapidly altering their taxonomic and functional composition. However, little is known about the strain-level processes that drive this collective response. Here, we characterize the gut microbiome of a single individual at high temporal and genetic resolution through a period of health, disease, antibiotic treatment, and recovery. We used deep, linked-read metagenomic sequencing to track the longitudinal trajectories of thousands of single nucleotide variants within 36 species, which allowed us to contrast these genetic dynamics with the ecological fluctuations at the species level. We found that antibiotics can drive rapid shifts in the genetic composition of individual species, often involving incomplete genome-wide sweeps of pre-existing variants. These genetic changes were frequently observed in species without obvious changes in species abundance, emphasizing the importance of monitoring diversity below the species level. We also found that many sweeping variants quickly reverted to their baseline levels once antibiotic treatment had concluded, demonstrating that the ecological resilience of the microbiota can sometimes extend all the way down to the genetic level. Our results provide new insights into the population genetic forces that shape individual microbiomes on therapeutically relevant timescales, with potential implications for personalized health and disease.

Genomic diversity and ecology of human-associated Akkermansia species in the gut microbiome revealed by extensive metagenomic assembly

BACKGROUND

Akkermansia muciniphila is a human gut microbe with a key role in the physiology of the intestinal mucus layer and reported associations with decreased body mass and increased gut barrier function and health. Despite its biomedical relevance, the genomic diversity of A. muciniphila remains understudied and that of closely related species, except for A. glycaniphila, unexplored.

RESULTS

We present a large-scale population genomics analysis of the Akkermansia genus using 188 isolate genomes and 2226 genomes assembled from 18,600 metagenomes from humans and other animals. While we do not detect A. glycaniphila, the Akkermansia strains in the human gut can be grouped into five distinct candidate species, including A. muciniphila, that show remarkable whole-genome divergence despite surprisingly similar 16S rRNA gene sequences. These candidate species are likely human-specific, as they are detected in mice and non-human primates almost exclusively when kept in captivity. In humans, Akkermansia candidate species display ecological co-exclusion, diversified functional capabilities, and distinct patterns of associations with host body mass. Analysis of CRISPR-Cas loci reveals new variants and spacers targeting newly discovered putative bacteriophages. Remarkably, we observe an increased relative abundance of Akkermansia when cognate predicted bacteriophages are present, suggesting ecological interactions. A. muciniphila further exhibits subspecies-level genetic stratification with associated functional differences such as a putative exo/lipopolysaccharide operon.

CONCLUSIONS

We uncover a large phylogenetic and functional diversity of the Akkermansia genus in humans. This variability should be considered in the ongoing experimental and metagenomic efforts to characterize the health-associated properties of A. muciniphila and related bacteria.

Ancient saltern metagenomics: tracking changes in microbes and their viruses from the underground to the surface

Microbial communities in hypersaline underground waters derive from ancient organisms trapped within the evaporitic salt crystals and are part of the poorly known subterranean biosphere. Here, we characterized the viral and prokaryotic assemblages present in the hypersaline springs that dissolve Triassic-Keuper evaporite rocks and feed the Añana Salt Valley (Araba/Alava, Basque Country, Spain). Four underground water samples (around 23% total salinity) with different levels of exposure to the open air were analysed by means of microscopy and metagenomics. Cells and viruses in the spring water had lower concentrations than what are normally found in hypersaline environments and seemed to be mostly inactive. Upon exposure to the open air, there was an increase in activity of both cells and viruses as well as a selection of phylotypes. The underground water was inhabited by a rich community harbouring a diverse set of genes coding for retinal binding proteins. A total of 35 viral contigs from 15 to 104 kb, representing partial or total viral genomes, were assembled and their evolutionary changes through the spring system were followed by SNP analysis and metagenomic island tracking. Overall, both the viral and the prokaryotic assemblages changed quickly upon exposure to the open air conditions.

Shifts in gut and vaginal microbiomes are associated with cancer recurrence time in women with ovarian cancer

Many studies investigating the human microbiome-cancer interface have focused on the gut microbiome and gastrointestinal cancers. Outside of human papillomavirus driving cervical cancer, little is known about the relationship between the vaginal microbiome and other gynecological cancers, such as ovarian cancer. In this retrospective study, we investigated the relationship between ovarian cancer, platinum-free interval (PFI) length, and vaginal and gut microbiomes. We observed that Lactobacillus-dominated vaginal communities were less common in women with ovarian cancer, as compared to existing datasets of similarly aged women without cancer. Primary platinum-resistance (PPR) disease is strongly associated with survivability under one year, and we found over one-third of patients with PPR (PFI < 6 months, n = 17) to have a vaginal microbiome dominated by Escherichia (>20% relative abundance), while only one platinum super-sensitive (PFI > 24 months, n = 23) patient had an Escherichia-dominated microbiome. Additionally, L. iners was associated with little, or no, gross residual disease, while other Lactobacillus species were dominant in women with >1 cm gross residual disease. In the gut microbiome, we found patients with PPR disease to have lower phylogenetic diversity than platinum-sensitive patients. The trends we observe in women with ovarian cancer and PPR disease, such as the absence of Lactobacillus and presence of Escherichia in the vaginal microbiome as well as low gut microbiome phylogenetic diversity have all been linked to other diseases and/or pro-inflammatory states, including bacterial vaginosis and autoimmune disorders. Future prospective studies are necessary to explore the translational potential and underlying mechanisms driving these associations.

Yearly changes in the composition of gut microbiota in the elderly, and the effect of lactobacilli intake on these changes

The onset and worsening of some diseases are related to the variation and instability of gut microbiota. However, studies examining the personal variation of gut microbiota in detail are limited. Here, we evaluated the yearly variation of individual gut microbiota in 218 Japanese subjects aged 66–91 years, using Jensen-Shannon distance (JSD) metrics. Approximately 9% of the subjects showed a substantial change, as their formerly predominant bacterial families were replaced over the year. These subjects consumed fermented milk products less frequently than their peers. The relationship between the intake frequencies of fermented milk products containing Lacticaseibacillus paracasei strain Shirota (LcS) and JSD values was also investigated. The intra-individual JSD of subjects ingesting LcS products ≥ 3 days/week over the past 10 years was statistically lower than the < 3 days/week group (P = 0.045). Focusing on subjects with substantial gut microbiota changes, only 1.7% of the subjects were included in the LcS intake ≥ 3 days/week group whereas 11.3% were found in the < 3 days/week group (P = 0.029). These results suggest that about one-tenth of the elderly Japanese could experience a substantial change in their gut microbiota during a 1-year period, and that the habitual intake of probiotics may stabilize their gut microbiota.

Comparative Biofilm Assays Using Enterococcus faecalis OG1RF Identify New Determinants of Biofilm Formation

Enterococcus faecalis is a common commensal organism and a prolific nosocomial pathogen that causes biofilm-associated infections. Numerous E. faecalis OG1RF genes required for biofilm formation have been identified, but few studies have compared genetic determinants of biofilm formation and biofilm morphology across multiple conditions. Here, we cultured transposon (Tn) libraries in CDC biofilm reactors in two different media and used Tn sequencing (TnSeq) to identify core and accessory biofilm determinants, including many genes that are poorly characterized or annotated as hypothetical. Multiple secondary assays (96-well plates, submerged Aclar discs, and MultiRep biofilm reactors) were used to validate phenotypes of new biofilm determinants. We quantified biofilm cells and used fluorescence microscopy to visualize biofilms formed by six Tn mutants identified using TnSeq and found that disrupting these genes (OG1RF_10350, prsA, tig, OG1RF_10576, OG1RF_11288, and OG1RF_11456) leads to significant time- and medium-dependent changes in biofilm architecture. Structural predictions revealed potential roles in cell wall homeostasis for OG1RF_10350 and OG1RF_11288 and signaling for OG1RF_11456. Additionally, we identified growth medium-specific hallmarks of OG1RF biofilm morphology. This study demonstrates how E. faecalis biofilm architecture is modulated by growth medium and experimental conditions and identifies multiple new genetic determinants of biofilm formation.

Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation

BACKGROUND

Viruses influence global patterns of microbial diversity and nutrient cycles. Though viral metagenomics (viromics), specifically targeting dsDNA viruses, has been critical for revealing viral roles across diverse ecosystems, its analyses differ in many ways from those used for microbes. To date, viromics benchmarking has covered read pre-processing, assembly, relative abundance, read mapping thresholds and diversity estimation, but other steps would benefit from benchmarking and standardization. Here we use in silico-generated datasets and an extensive literature survey to evaluate and highlight how dataset composition (i.e., viromes vs bulk metagenomes) and assembly fragmentation impact (i) viral contig identification tool, (ii) virus taxonomic classification, and (iii) identification and curation of auxiliary metabolic genes (AMGs).

RESULTS

The in silico benchmarking of five commonly used virus identification tools show that gene-content-based tools consistently performed well for long (≥3 kbp) contigs, while k-mer- and blast-based tools were uniquely able to detect viruses from short (≤3 kbp) contigs. Notably, however, the performance increase of k-mer- and blast-based tools for short contigs was obtained at the cost of increased false positives (sometimes up to ∼5% for virome and ∼75% bulk samples), particularly when eukaryotic or mobile genetic element sequences were included in the test datasets. For viral classification, variously sized genome fragments were assessed using gene-sharing network analytics to quantify drop-offs in taxonomic assignments, which revealed correct assignations ranging from ∼95% (whole genomes) down to ∼80% (3 kbp sized genome fragments). A similar trend was also observed for other viral classification tools such as VPF-class, ViPTree and VIRIDIC, suggesting that caution is warranted when classifying short genome fragments and not full genomes. Finally, we highlight how fragmented assemblies can lead to erroneous identification of AMGs and outline a best-practices workflow to curate candidate AMGs in viral genomes assembled from metagenomes.

CONCLUSION

Together, these benchmarking experiments and annotation guidelines should aid researchers seeking to best detect, classify, and characterize the myriad viruses 'hidden' in diverse sequence datasets.

Dispersal strategies shape persistence and evolution of human gut bacteria

Human gut bacterial strains can co-exist with their hosts for decades, but little is known about how these microbes persist and disperse, and evolve thereby. Here, we examined these processes in 5,278 adult and infant fecal metagenomes, longitudinally sampled in individuals and families. Our analyses revealed that a subset of gut species is extremely persistent in individuals, families, and geographic regions, represented often by locally successful strains of the phylum Bacteroidota. These “tenacious” bacteria show high levels of genetic adaptation to the human host but a high probability of loss upon antibiotic interventions. By contrast, heredipersistent bacteria, notably Firmicutes, often rely on dispersal strategies with weak phylogeographic patterns but strong family transmissions, likely related to sporulation. These analyses describe how different dispersal strategies can lead to the long-term persistence of human gut microbes with implications for gut flora modulations.

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Bacterial strains may persist within family members through transfer

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Bacteria adapt dispersal strategies: heredipersistent, spatiopersistent, and tenacious

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Dispersal strategies correlate with genetic bottlenecks and effective population size

inStrain profiles population microdiversity from metagenomic data and sensitively detects shared microbial strains

Coexisting microbial cells of the same species often exhibit genetic variation that can affect phenotypes ranging from nutrient preference to pathogenicity. Here we present inStrain, a program that uses metagenomic paired reads to profile intra-population genetic diversity (microdiversity) across whole genomes and compares microbial populations in a microdiversity-aware manner, greatly increasing the accuracy of genomic comparisons when benchmarked against existing methods. We use inStrain to profile >1,000 fecal metagenomes from newborn premature infants and find that siblings share significantly more strains than unrelated infants, although identical twins share no more strains than fraternal siblings. Infants born by cesarean section harbor Klebsiella with significantly higher nucleotide diversity than infants delivered vaginally, potentially reflecting acquisition from hospital rather than maternal microbiomes. Genomic loci that show diversity in individual infants include variants found between other infants, possibly reflecting inoculation from diverse hospital-associated sources. inStrain can be applied to any metagenomic dataset for microdiversity analysis and rigorous strain comparison.

Quantitative Detection of Bifidobacterium longum Strains in Feces Using Strain-Specific Primers

We adopted a bioinformatics-based technique to identify strain-specific markers, which were then used to quantify the abundances of three distinct B. longum sup. longum strains in fecal samples of humans and mice. A pangenome analysis of 205 B. longum sup. longum genomes revealed the accumulation of considerable strain-specific genes within this species; specifically, 28.7% of the total identified genes were strain-specific. We identified 32, 14, and 49 genes specific to B. longum sup. longum RG4-1, B. longum sup. longum M1-20-R01-3, and B. longum sup. longum FGSZY6M4, respectively. After performing an in silico validation of these strain-specific markers using a nucleotide BLAST against both the B. longum sup. longum genome database and an NR/NT database, RG4-1_01874 (1331 bp), M1-20-R01-3_00324 (1745 bp), and FGSZY6M4_01477 (1691 bp) were chosen as target genes for strain-specific quantification. The specificities of the qPCR primers were validated against 47 non-target microorganisms and fecal baseline microbiota to ensure that they produced no PCR amplification products. The performance of the qPCR primer-based analysis was further assessed using fecal samples. After oral administration, the target B. longum strains appeared to efficiently colonize both the human and mouse guts, with average population levels of >108 CFU/g feces. The bioinformatics pipeline proposed here can be applied to the quantification of various bacterial species.

Ecology and molecular targets of hypermutation in the global microbiome

Changes in the sequence of an organism's genome, i.e., mutations, are the raw material of evolution. The frequency and location of mutations can be constrained by specific molecular mechanisms, such as diversity-generating retroelements (DGRs). DGRs have been characterized from cultivated bacteria and bacteriophages, and perform error-prone reverse transcription leading to mutations being introduced in specific target genes. DGR loci were also identified in several metagenomes, but the ecological roles and evolutionary drivers of these DGRs remain poorly understood. Here, we analyze a dataset of >30,000 DGRs from public metagenomes, establish six major lineages of DGRs including three primarily encoded by phages and seemingly used to diversify host attachment proteins, and demonstrate that DGRs are broadly active and responsible for >10% of all amino acid changes in some organisms. Overall, these results highlight the constraints under which DGRs evolve, and elucidate several distinct roles these elements play in natural communities.

The impact of cross-kingdom molecular forensics on genetic privacy

Recent advances in metagenomic technology and computational prediction may inadvertently weaken an individual's reasonable expectation of privacy. Through cross-kingdom genetic and metagenomic forensics, we can already predict at least a dozen human phenotypes with varying degrees of accuracy. There is also growing potential to detect a "molecular echo" of an individual's microbiome from cells deposited on public surfaces. At present, host genetic data from somatic or germ cells provide more reliable information than microbiome samples. However, the emerging ability to infer personal details from different microscopic biological materials left behind on surfaces requires in-depth ethical and legal scrutiny. There is potential to identify and track individuals, along with new, surreptitious means of genetic discrimination. This commentary underscores the need to update legal and policy frameworks for genetic privacy with additional considerations for the information that could be acquired from microbiome-derived data. The article also aims to stimulate ubiquitous discourse to ensure the protection of genetic rights and liberties in the post-genomic era. Video abstract.

Spinal Cord Injury Changes the Structure and Functional Potential of Gut Bacterial and Viral Communities

Emerging data indicate that gut dysbiosis contributes to many human diseases, including several comorbidities that develop after traumatic spinal cord injury (SCI). To date, all analyses of SCI-induced gut dysbiosis have used 16S rRNA amplicon sequencing. This technique has several limitations, including being susceptible to taxonomic "blind spots," primer bias, and an inability to profile microbiota functions or identify viruses. Here, SCI-induced gut dysbiosis was assessed by applying genome- and gene-resolved metagenomic analysis of murine stool samples collected 21 days after an experimental SCI at the 4th thoracic spine (T4) or 10th thoracic spine (T10) spinal level. These distinct injuries partially (T10) or completely (T4) abolish sympathetic tone in the gut. Among bacteria, 105 medium- to high-quality metagenome-assembled genomes (MAGs) were recovered, with most (n = 96) representing new bacterial species. Read mapping revealed that after SCI, the relative abundance of beneficial commensals (Lactobacillus johnsonii and CAG-1031 spp.) decreased, while potentially pathogenic bacteria (Weissella cibaria, Lactococcus lactis _A, Bacteroides thetaiotaomicron) increased. Functionally, microbial genes encoding proteins for tryptophan, vitamin B6, and folate biosynthesis, essential pathways for central nervous system function, were reduced after SCI. Among viruses, 1,028 mostly novel viral populations were recovered, expanding known murine gut viral species sequence space ∼3-fold compared to that of public databases. Phages of beneficial commensal hosts (CAG-1031, Lactobacillus, and Turicibacter) decreased, while phages of pathogenic hosts (Weissella, Lactococcus, and class Clostridia) increased after SCI. Although the microbiomes and viromes were changed in all SCI mice, some of these changes varied as a function of spinal injury level, implicating loss of sympathetic tone as a mechanism underlying gut dysbiosis.IMPORTANCE To our knowledge, this is the first article to apply metagenomics to characterize changes in gut microbial population dynamics caused by a clinically relevant model of central nervous system (CNS) trauma. It also utilizes the most current approaches in genome-resolved metagenomics and viromics to maximize the biological inferences that can be made from these data. Overall, this article highlights the importance of autonomic nervous system regulation of a distal organ (gut) and its microbiome inhabitants after traumatic spinal cord injury (SCI). By providing information on taxonomy, function, and viruses, metagenomic data may better predict how SCI-induced gut dysbiosis influences systemic and neurological outcomes after SCI.

Oral Microbiota of Children Is Conserved across Han, Tibetan and Hui Groups and Is Correlated with Diet and Gut Microbiota

The oral microbiota can be affected by several factors; however, little is known about the relationship between diet, ethnicity and commensal oral microbiota among school children living in close geographic proximity. In addition, the relationship between the oral and gut microbiota remains unclear. We collected saliva from 60 school children from the Tibetan, Han and Hui ethnicities for a 16S rRNA gene sequencing analysis and comparison with previously collected fecal samples. The study revealed that Bacteroidetes and Proteobacteria were the dominant phyla in the oral microbiota. The Shannon diversity was lowest in the Tibetan group. A PCA showed a substantial overlap in the distribution of the taxa, indicating a high degree of conservation among the oral microbiota across ethnic groups while the enrichment of a few specific taxa was observed across different ethnic groups. The consumption of seafood, poultry, sweets and vegetables was significantly correlated with multiple oral microbiotas. Furthermore, 123 oral genera were significantly associated with 191 gut genera. A principal coordinate analysis revealed that the oral microbiota clustered separately from the gut microbiota. This work extends the findings of previous studies comparing microbiota from human populations and provides a basis for the exploration of the interactions governing the tri-partite relationship between diet, oral microbiota and gut microbiota.

A Benchmark of Genetic Variant Calling Pipelines Using Metagenomic Short-Read Sequencing

Microbes live in complex communities that are of major importance for environmental ecology, public health, and animal physiology and pathology. Short-read metagenomic shotgun sequencing is currently the state-of-the-art technique for exploring these communities. With the aid of metagenomics, our understanding of the microbiome is moving from composition toward functionality, even down to the genetic variant level. While the exploration of single-nucleotide variation in a genome is a standard procedure in genomics, and many sophisticated tools exist to perform this task, identification of genetic variation in metagenomes remains challenging. Major factors that hamper the widespread application of variant-calling analysis include low-depth sequencing of individual genomes (which is especially significant for the microorganisms present in low abundance), the existence of large genomic variation even within the same species, the absence of comprehensive reference genomes, and the noise introduced by next-generation sequencing errors. Some bioinformatics tools, such as metaSNV or InStrain, have been created to identify genetic variants in metagenomes, but the performance of these tools has not been systematically assessed or compared with the variant callers commonly used on single or pooled genomes. In this study, we benchmark seven bioinformatic tools for genetic variant calling in metagenomics data and assess their performance. To do so, we simulated metagenomic reads to mimic human microbial composition, sequencing errors, and genetic variability. We also simulated different conditions, including low and high depth of coverage and unique or multiple strains per species. Our analysis of the simulated data shows that probabilistic method-based tools such as HaplotypeCaller and Mutect2 from the GATK toolset show the best performance. By applying these tools to longitudinal gut microbiome data from the Human Microbiome Project, we show that the genetic similarity between longitudinal samples from the same individuals is significantly greater than the similarity between samples from different individuals. Our benchmark shows that probabilistic tools can be used to call metagenomes, and we recommend the use of GATK's tools as reliable variant callers for metagenomic samples.

Food intake and its effect on the species and abundance of intestinal flora in colorectal cancer and healthy individuals

BACKGROUND/AIM

It is known that an imbalance in the intestinal f lora plays a crucial role in colorectal cancer (CRC), but the effect of food consumption patterns on the types of intestinal flora remains to be clarified. We aimed to analyze the associations between food intake and intestinal flora in healthy and CRC individuals.

METHODS

Food intake data were recorded using the Food Frequency Questionnaire (FFQ). The composition and diversity of the intestinal flora detected by 16S rRNA gene sequencing, and the data were analyzed by R version 3.1.1 software.

RESULTS

Higher intake of red meat or pickled foods, and lower intake of white meat, fruits, vegetables, beans, nuts were found in the CRC group compared with the healthy group. Higher levels of Fusobacteria and Proteobacteria, and lower levels of Firmicutes were observed in the CRC group. Partial correlation analysis revealed that the intake of fruits, beans, and nuts was negatively correlated with Proteobacteria and Fusobacteria, but pickled food was positively correlated with Fusobacteria (p < 0.05). Fish, beans, and nuts intake was negatively correlated with Escherichia (p = 0.01). Multiple regression analysis revealed that vegetable oil (odds ratio [OR], 0.26; 95% confidence interval [CI], 0.13 to 0.82), vegetables (OR, 0.26; 95% CI, 0.10 to 0.64), eggs (OR, 0.26; 95% CI, 0.10 to 0.69), pickled foods (OR, 21.02; 95% CI, 6.02 to 73.45), and red meat (OR, 4.23; 95% CI, 1.68 to 10.60) had an impact on CRC risk.

CONCLUSION

The species and abundance of intestinal flora varies between CRC and healthy individuals and may be affected by their food preference.

Improved metagenome binning and assembly using deep variational autoencoders

Despite recent advances in metagenomic binning, reconstruction of microbial species from metagenomics data remains challenging. Here we develop variational autoencoders for metagenomic binning (VAMB), a program that uses deep variational autoencoders to encode sequence coabundance and k-mer distribution information before clustering. We show that a variational autoencoder is able to integrate these two distinct data types without any previous knowledge of the datasets. VAMB outperforms existing state-of-the-art binners, reconstructing 29-98% and 45% more near-complete (NC) genomes on simulated and real data, respectively. Furthermore, VAMB is able to separate closely related strains up to 99.5% average nucleotide identity (ANI), and reconstructed 255 and 91 NC Bacteroides vulgatus and Bacteroides dorei sample-specific genomes as two distinct clusters from a dataset of 1,000 human gut microbiome samples. We use 2,606 NC bins from this dataset to show that species of the human gut microbiome have different geographical distribution patterns. VAMB can be run on standard hardware and is freely available at https://github.com/RasmussenLab/vamb .

Dysbiosis and Alzheimer's Disease: A Role for Chronic Stress?

Alzheimer’s disease (AD) is an incurable, neuropsychiatric, pathological condition that deteriorates the worth of geriatric lives. AD is characterized by aggregated senile amyloid plaques, neurofibrillary tangles, neuronal loss, gliosis, oxidative stress, neurotransmitter dysfunction, and bioenergetic deficits. The changes in GIT composition and harmony have been recognized as a decisive and interesting player in neuronal pathologies including AD. Microbiota control and influence the oxidoreductase status, inflammation, immune system, and the endocrine system through which it may have an impact on the cognitive domain. The altered and malfunctioned state of microbiota is associated with minor infections to complicated illnesses that include psychosis and neurodegeneration, and several studies show that microbiota regulates neuronal plasticity and neuronal development. The altered state of microbiota (dysbiosis) may affect behavior, stress response, and cognitive functions. Chronic stress-mediated pathological progression also has a well-defined role that intermingles at various physiological levels and directly impacts the pathological advancement of AD. Chronic stress-modulated alterations affect the well-established pathological markers of AD but also affect the gut–brain axis through the mediation of various downstream signaling mechanisms that modulate the microbial commensals of GIT. The extensive literature reports that chronic stressors affect the composition, metabolic activities, and physiological role of microbiota in various capacities. The present manuscript aims to elucidate mechanistic pathways through which stress induces dysbiosis, which in turn escalates the neuropathological cascade of AD. The stress–dysbiosis axis appears a feasible zone of work in the direction of treatment of AD.

Impact of High-Pressure Processed Onion on Colonic Metabolism Using a Dynamic Gastrointestinal Digestion Simulator

Onions are the main dietary source of flavonols that have been associated with important health-promoting properties. Onion treated by high-pressure processing (HPP-treated onion) was subjected to a dynamic gastrointestinal digestion and colon fermentation simulator (DGID-CF) to study the effect on the gut microbiota metabolism in the three colon regions (ascending—AC, transverse—TC, and descending—DC) by means of chronic feeding with 27 g/day for 14 days. HPP-treated onion presented a high content of the flavonols quercetin-3,4’-diglucoside and quercetin-4’-glucoside, and a large percentage of them reached the AC without change. TC and DC progressively increased the total phenolic metabolites 2.5 times respective to day 2, mainly 3-hydroxyphenylacetic, 4-hydroxyphenylacetic, 3-(4-hydroxyphenyl)-propionic, and 3,4-dihydroxyphenylpropionic acids. In addition, the chronic feeding increased the beneficial colon bacteria Bifidobacterium spp. and Lactobacillus spp. and the production of total SCFAs (acetic, propionic, and butyric acids) 9 times (AC), 2.2 times (TC), and 4.4 times (DC) respective to day 1. A multivariate analysis (principal component analysis, PCA) showed a clear separation between the three colon regions based on their phenolic composition (precursors and metabolites). These results showed that HPP-treated onion modulated the human gut microbiota’s metabolism and the DGID-CF is a good system to study these changes.

The long-term genetic stability and individual specificity of the human gut microbiome

By following up the gut microbiome, 51 human phenotypes and plasma levels of 1,183 metabolites in 338 individuals after 4 years, we characterize microbial stability and variation in relation to host physiology. Using these individual-specific and temporally stable microbial profiles, including bacterial SNPs and structural variations, we develop a microbial fingerprinting method that shows up to 85% accuracy in classifying metagenomic samples taken 4 years apart. Application of our fingerprinting method to the independent HMP cohort results in 95% accuracy for samples taken 1 year apart. We further observe temporal changes in the abundance of multiple bacterial species, metabolic pathways, and structural variation, as well as strain replacement. We report 190 longitudinal microbial associations with host phenotypes and 519 associations with plasma metabolites. These associations are enriched for cardiometabolic traits, vitamin B, and uremic toxins. Finally, mediation analysis suggests that the gut microbiome may influence cardiometabolic health through its metabolites.

Best Practices for Microbiome Study Design in Companion Animal Research

The gut microbiome is a community of microorganisms that inhabits an animal host's gastrointestinal tract, with important effects on animal health that are shaped by multiple environmental, dietary, and host-associated factors. Clinical and dietary trials in companion animals are increasingly including assessment of the microbiome, but interpretation of these results is often hampered by suboptimal choices in study design. Here, we review best practices for conducting feeding trials or clinical trials that intend to study the effects of an intervention on the microbiota. Choices for experimental design, including a review of basic designs, controls, and comparison groups, are discussed in the context of special considerations necessary for microbiome studies. Diet is one of the strongest influences on the composition of gut microbiota, so applications specific to nutritional interventions are discussed in detail. Lastly, we provide specific advice for successful recruitment of colony animals and household pets into an intervention study. This review is intended to serve as a resource to academic and industry researchers, clinicians, and veterinarians alike, for studies that test many different types of interventions.

Manipulating the Microbiome: An Alternative Treatment for Bile Acid Diarrhoea

Bile acid diarrhoea (BAD) is a widespread gastrointestinal disease that is often misdiagnosed as irritable bowel syndrome and is estimated to affect 1% of the United Kingdom (UK) population alone. BAD is associated with excessive bile acid synthesis secondary to a gastrointestinal or idiopathic disorder (also known as primary BAD). Current licensed treatment in the UK has undesirable effects and has been the same since BAD was first discovered in the 1960s. Bacteria are essential in transforming primary bile acids into secondary bile acids. The profile of an individual’s bile acid pool is central in bile acid homeostasis as bile acids regulate their own synthesis. Therefore, microbiome dysbiosis incurred through changes in diet, stress levels and the introduction of antibiotics may contribute to or be the cause of primary BAD. This literature review focuses on primary BAD, providing an overview of bile acid metabolism, the role of the human gut microbiome in BAD and the potential options for therapeutic intervention in primary BAD through manipulation of the microbiome.

Effectiveness of decontamination protocols when analyzing ancient DNA preserved in dental calculus

Ancient DNA analysis of human oral microbial communities within calcified dental plaque (calculus) has revealed key insights into human health, paleodemography, and cultural behaviors. However, contamination imposes a major concern for paleomicrobiological samples due to their low endogenous DNA content and exposure to environmental sources, calling into question some published results. Decontamination protocols (e.g. an ethylenediaminetetraacetic acid (EDTA) pre-digestion or ultraviolet radiation (UV) and 5% sodium hypochlorite immersion treatments) aim to minimize the exogenous content of the outer surface of ancient calculus samples prior to DNA extraction. While these protocols are widely used, no one has systematically compared them in ancient dental calculus. Here, we compare untreated dental calculus samples to samples from the same site treated with four previously published decontamination protocols: a UV only treatment; a 5% sodium hypochlorite immersion treatment; a pre-digestion in EDTA treatment; and a combined UV irradiation and 5% sodium hypochlorite immersion treatment. We examine their efficacy in ancient oral microbiota recovery by applying 16S rRNA gene amplicon and shotgun sequencing, identifying ancient oral microbiota, as well as soil and skin contaminant species. Overall, the EDTA pre-digestion and a combined UV irradiation and 5% sodium hypochlorite immersion treatment were both effective at reducing the proportion of environmental taxa and increasing oral taxa in comparison to untreated samples. This research highlights the importance of using decontamination procedures during ancient DNA analysis of dental calculus to reduce contaminant DNA.

Potential virus-mediated nitrogen cycling in oxygen-depleted oceanic waters

Viruses play an important role in the ecology and biogeochemistry of marine ecosystems. Beyond mortality and gene transfer, viruses can reprogram microbial metabolism during infection by expressing auxiliary metabolic genes (AMGs) involved in photosynthesis, central carbon metabolism, and nutrient cycling. While previous studies have focused on AMG diversity in the sunlit and dark ocean, less is known about the role of viruses in shaping metabolic networks along redox gradients associated with marine oxygen minimum zones (OMZs). Here, we analyzed relatively quantitative viral metagenomic datasets that profiled the oxygen gradient across Eastern Tropical South Pacific (ETSP) OMZ waters, assessing whether OMZ viruses might impact nitrogen (N) cycling via AMGs. Identified viral genomes encoded six N-cycle AMGs associated with denitrification, nitrification, assimilatory nitrate reduction, and nitrite transport. The majority of these AMGs (80%) were identified in T4-like Myoviridae phages, predicted to infect Cyanobacteria and Proteobacteria, or in unclassified archaeal viruses predicted to infect Thaumarchaeota. Four AMGs were exclusive to anoxic waters and had distributions that paralleled homologous microbial genes. Together, these findings suggest viruses modulate N-cycling processes within the ETSP OMZ and may contribute to nitrogen loss throughout the global oceans thus providing a baseline for their inclusion in the ecosystem and geochemical models.

Dissecting Individual Interactions between Pathogenic and Commensal Bacteria within a Multispecies Gut Microbial Community

Interactions of commensal bacteria within the gut microbiota and with invading pathogens are critical in determining the outcome of an infection. While murine studies have been valuable, we lack in vitro models to monitor community responses to pathogens at a single-species level. We have developed a multispecies community of nine representative gut species cultured together as a mixed biofilm and tracked numbers of individual species over time using a quantitative PCR (qPCR)-based approach. Introduction of the major nosocomial gut pathogen, Clostridioides difficile, to this community resulted in increased adhesion of commensals and inhibition of C. difficile multiplication. Interestingly, we observed an increase in individual Bacteroides species accompanying the inhibition of C. difficile. Furthermore, Bacteroides dorei reduced C. difficile growth within biofilms, suggesting a role for Bacteroides spp. in prevention of C. difficile colonization. We report here an in vitro tool with excellent applications for investigating bacterial interactions within a complex community.

IMPORTANCE Studying interactions between bacterial species that reside in the human gut is crucial for gaining a better insight into how they provide protection from pathogen colonization. In vitro models of multispecies bacterial communities wherein behaviors of single species can be accurately tracked are key to such studies. Here, we have developed a synthetic, trackable, gut microbiota community which reduces growth of the human gut pathogen Clostridioides difficile. We report that Bacteroides spp. within this community respond by multiplying in the presence of this pathogen, resulting in reduction of C. difficile growth. Defined in vitro communities that can be tailored to include different species are well suited to functional genomic approaches and are valuable tools for understanding interbacterial interactions.

Recent advances in the therapeutic application of short-chain fatty acids (SCFAs): An updated review

Over the past decade, the gut microbiota has emerged as an important frontier in understanding the human body's homeostasis and the development of diseases. Gut flora in human beings regulates various metabolic functionalities, including enzymes, amino acid synthesis, bio-transformation of bile acid, fermentation of non-digestible carbohydrates (NDCs), generation of indoles and polyamines (PAs), and production of short-chain fatty acids (SCFAs). Among all the metabolites produced by gut microbiota, SCFAs, the final product of fermentation of dietary fibers by gut microbiota, receive lots of attention from scientists due to their pharmacological and physiological characteristics. However, the molecular mechanisms underlying the role of SCFAs in the interaction between diet, gut microbiota, and host energy metabolism is still needed in-depth research. This review highlights the recent biotechnological advances in applying SCFAs as important metabolites to treat various diseases and maintain colonic health.

Microbiome in Death and Beyond: Current Vistas and Future Trends

Forensic medicine has, for a long time, been relying on biochemical, anthropologic, and histopathologic evidences in solving various investigations. However, depending on the method used, lengthy sample processing time, scanty sample, and less sensitivity and accuracy pervade these procedures. Accordingly, newer arenas such as the thanatomicrobiome have come forward to aid in its quandaries; furthermore, the parallel advances in genomic and proteomic techniques have complemented and are still emerging to be used in forensic experiments and investigations. Postmortem interval (PMI) is one of the most important aspects of medico-legal investigations. The current trend in PMI estimation is toward genomic analyses of autopsy samples. Similarly, determination of cause of death, although a domain of medical sciences, is being targeted as the next level of forensic casework. With the current trend in laboratory sciences moving to the discovery of newer disease-specific markers for diagnostic and prognostic purposes, the same is being explored for the determination of the cause of death by using techniques such as Real-Time PCR, DNA micro-array, to Next-Gen Sequencing. Establishing an individual’s biological profile has been done using medicolegal methods and anthropology as well as bar-bodies/Davidson bodies (gender determination); and in cases where the determination of age/gender is a challenge using morphological characteristics; the recent advances in the field of genomics and proteomics have played a significant role, e.g., use of mitochondrial DNA in age estimation and in maternity disputes. The major hurdle forensic medical research faces is the fact that most of the studies are conducted in animal models, which are often difficult to mimic in human and real-time scenarios. Additionally, the high accuracy required in criminal investigations to be used in a court of law as evidence has prevented these results to come out of the labs and be used to the optimum. The current review aims at giving a comprehensive and critical account of the various molecular biology techniques including “thanatogenomics,” currently being utilized in the veritable fields of forensic medicine.

Evolution of Microbiota-Host Associations: The Microbe's Perspective

Microbiota-host associations are ubiquitous in nature. They are often studied using a host-centered view, while microbes are assumed to have coevolved with hosts or colonize hosts as nonadapted entities. Both assumptions are often incorrect. Instead, many host-associated microbes are adapted to a biphasic life cycle in which they alternate between noncoadapted hosts and a free-living phase. Full appreciation of microbiota-host symbiosis thus needs to consider how microbes optimize fitness across this life cycle. Here, we evaluate the key stages of the biphasic life cycle and propose a new conceptual framework for microbiota-host interactions which includes an integrative measure of microbial fitness, related to the parasite fitness parameter R₀, and which will help in-depth assessment of the evolution of these widespread associations.

Home, sweet home: how mucus accommodates our microbiota

As a natural environment for human-microbiota interactions, healthy mucus houses a remarkably stable and diverse microbial community. Maintaining this microbiota is essential to human health, both to support the commensal bacteria that perform a wide array of beneficial functions and to prevent the outgrowth of pathogens. However, how the host selects and maintains a specialized microbiota remains largely unknown. In this viewpoint, we propose several strategies by which mucus may regulate the composition and function of the human microbiota and discuss how compromised mucus barriers in disease can give rise to microbial dysbiosis.

The structure and diversity of strain-level variation in vaginal bacteria

The vaginal microbiome plays an important role in human health and species of vaginal bacteria have been associated with reproductive disease. Strain-level variation is also thought to be important, but the diversity, structure and evolutionary history of vaginal strains is not as well characterized. We developed and validated an approach to measure strain variation from metagenomic data based on SNPs within the core genomes for six species of vaginal bacteria: Gardnerella vaginalis, Lactobacillus crispatus, Lactobacillus iners, Lactobacillus jensenii, Lactobacillus gasseri and Atopobium vaginae. Despite inhabiting the same environment, strain diversity and structure varies across species. All species except L. iners are characterized by multiple distinct groups of strains. Even so, strain diversity is lower in the Lactobacillus species, consistent with a more recent colonization of the human vaginal microbiome. Both strain diversity and the frequency of multi-strain samples is related to species-level diversity of the microbiome in which they occur, suggesting similar ecological factors influencing diversity within the vaginal niche. We conclude that the structure of strain-level variation provides both the motivation and means of testing whether strain-level differences contribute to the function and health consequences of the vaginal microbiome.

Strain heterogeneity, cooccurrence network, taxonomic composition and functional profile of the healthy ocular surface microbiome

BACKGROUND

There is growing evidence indicating that the microbial communities that dwell on the human ocular surface are crucially important for ocular surface health and disease. Little is known about interspecies interactions, functional profiles, and strain heterogeneity across individuals in healthy ocular surface microbiomes.

METHODS

To comprehensively characterize the strain heterogeneity, cooccurrence network, taxonomic composition and functional profile of the healthy ocular surface microbiome, we performed shotgun metagenomics sequencing on ocular surface mucosal membrane swabs of 17 healthy volunteers.

RESULTS

The healthy ocular surface microbiome was classified into 12 phyla, 70 genera, and 140 species. The number of species in each healthy ocular surface microbiome ranged from 6 to 47, indicating differences in microbial diversity among individuals. The species with high relative abundances and high positivity rates were Streptococcus pyogenes, Staphylococcus epidermidis, Propionibacterium acnes, Corynebacterium accolens, and Enhydrobacter aerosaccus. A correlation network analysis revealed a competitive interaction of Staphylococcus epidermidis with Streptococcus pyogenes in ocular surface microbial ecosystems. Staphylococcus epidermidis and Streptococcus pyogenes revealed phylogenetic diversity among different individuals. At the functional level, the pathways related to transcription were the most abundant. We also found that there were abundant lipid and amino acid metabolism pathways in the healthy ocular surface microbiome.

CONCLUSION

This study explored the strain heterogeneity, cooccurrence network, taxonomic composition, and functional profile of the healthy ocular surface microbiome. These findings have important significance for the future development of probiotic-based eye therapeutic drugs.

From Binary Model Systems to the Human Microbiome: Factors That Drive Strain Specificity in Host-Symbiont Associations

Microbial symbionts are ubiquitous and can have significant impact on hosts. These impacts can vary in the sign (positive or negative) and degree depending on the identity of the interacting partners. Studies on host-symbiont associations indicate that subspecies (strain) genetic variation can influence interaction outcomes, making it necessary to go beyond species-level distinction to understand host-symbiont dynamics. In this review, we discuss examples of strain specificity found in host-symbiont associations, from binary model systems to the human microbiome. Although host and bacterial factors identified as mediators for specificity could be distinct at the molecular level, they generally fall into two broad functional categories: (1) those that contribute a required activity in support of the association and (2) those involved in antagonistic interactions with organisms outside of the association. We argue here based on current literature that factors from these two categories can work in concert to drive strain specificity and that this strain specificity must be considered to fully understand the molecular and ecological dynamics of host-symbiont associations, including the human microbiome.

GUT MICROBIOTA, PREBIOTICS, PROBIOTICS, AND SYNBIOTICS IN GASTROINTESTINAL AND LIVER DISEASES: PROCEEDINGS OF A JOINT MEETING OF THE BRAZILIAN SOCIETY OF HEPATOLOGY (SBH), BRAZILIAN NUCLEUS FOR THE STUDY OF HELICOBACTER PYLORI AND MICROBIOTA (NBEHPM), AND BRAZILIAN FEDERATION OF GASTROENTEROLOGY (FBG)

Over the last years, there is growing evidence that microorganisms are involved in the maintenance of our health and are related to various diseases, both intestinal and extraintestinal. Changes in the gut microbiota appears to be a key element in the pathogenesis of hepatic and gastrointestinal disorders, including non-alcoholic fatty liver disease, alcoholic liver disease, liver cirrhosis, inflammatory bowel disease, irritable bowel syndrome, and Clostridium difficile - associated diarrhea. In 2019, the Brazilian Society of Hepatology (SBH) in cooperation with the Brazilian Nucleus for the Study of Helicobacter Pylori and Microbiota (NBEHPM), and Brazilian Federation of Gastroenterology (FBG) sponsored a joint meeting on gut microbiota and the use of prebiotics, probiotics, and synbiotics in gastrointestinal and liver diseases. This paper summarizes the proceedings of the aforementioned meeting. It is intended to provide practical information about this topic, addressing the latest discoveries and indicating areas for future studies.

Tumor-Associated Microbiome: Where Do We Stand?

The study of the human microbiome in oncology is a growing and rapidly evolving field. In the past few years, there has been an exponential increase in the number of studies investigating associations of microbiome and cancer, from oncogenesis and cancer progression to resistance or sensitivity to specific anticancer therapies. The gut microbiome is now known to play a significant role in antitumor immune responses and in predicting the efficacy of immune-checkpoint inhibitors in cancer patients. Beyond the gut, the tumor-associated microbiome-microbe communities located either in the tumor or within its body compartment-seems to interact with the local microenvironment and the tumor immune contexture, ultimately impacting cancer progression and treatment outcome. However, pre-clinical research focusing on causality and mechanistic pathways as well as proof-of-concept studies are still needed to fully understand the potential clinical utility of microbiome in cancer patients. Moreover, there is a need for the standardization of methodology and the implementation of quality control across microbiome studies to allow for a better interpretation and greater comparability of the results reported between them. This review summarizes the accumulating evidence in the field and discusses the current and upcoming challenges of microbiome studies.

Computational modeling of the gut microbiota reveals putative metabolic mechanisms of recurrent Clostridioides difficile infection

Approximately 30% of patients who have Clostridioides difficile infection (CDI) will suffer at least one incident of reinfection. While the underlying causes of CDI recurrence are poorly understood, interactions between C. difficile and commensal gut bacteria are thought to play an important role. In this study, an in silico pipeline was used to process 16S rRNA gene amplicon sequence data of 225 stool samples from 93 CDI patients into sample-specific models of bacterial community metabolism. Clustered metabolite production rates generated from post-diagnosis samples generated a high Enterobacteriaceae abundance cluster containing disproportionately large numbers of recurrent samples and patients. This cluster was predicted to have significantly reduced capabilities for secondary bile acid synthesis but elevated capabilities for aromatic amino acid catabolism. When applied to 16S sequence data of 40 samples from fecal microbiota transplantation (FMT) patients suffering from recurrent CDI and their stool donors, the community modeling method generated a high Enterobacteriaceae abundance cluster with a disproportionate large number of pre-FMT samples. This cluster also was predicted to exhibit reduced secondary bile acid synthesis and elevated aromatic amino acid catabolism. Collectively, these in silico predictions suggest that Enterobacteriaceae may create a gut environment favorable for C. difficile spore germination and/or toxin synthesis.

The seasonal changes of the gut microbiome of the population living in traditional lifestyles are represented by characteristic species-level and functional-level SNP enrichment patterns

Background

Most studies investigating human gut microbiome dynamics are conducted on humans living in an urban setting. However, few studies have researched the gut microbiome of the populations living traditional lifestyles. These understudied populations are arguably better subjects in answering human-gut microbiome evolution because of their lower exposure to antibiotics and higher dependence on natural resources. Hadza hunter-gatherers in Tanzania have exhibited high biodiversity and seasonal patterns in their gut microbiome composition at the family level, where some taxa disappear in one season and reappear later. Such seasonal changes have been profiled, but the nucleotide changes remain unexplored at the genome level. Thus, it is still elusive how microbial communities change with seasonal changes at the genome level.

Results

In this study, we performed a strain-level single nucleotide polymorphism (SNP) analysis on 40 Hadza fecal metagenome samples spanning three seasons. With more SNP presented in the wet season, eight prevalent species have significant SNP enrichment with the increasing number of SNP calling by VarScan2, among which only three species have relatively high abundances. Eighty-three genes have the most SNP distributions between the wet season and dry season. Many of these genes are derived from Ruminococcus obeum, and mainly participated in metabolic pathways including carbon metabolism, pyruvate metabolism, and glycolysis.

Conclusions

Eight prevalent species have significant SNP enrichments with the increasing number of SNP, among which only Eubacterium biforme, Eubacterium hallii and Ruminococcus obeum have relatively high species abundances. Many genes in the microbiomes also presented characteristic SNP distributions between the wet season and the dry season. This implies that the seasonal changes might indirectly impact the mutation patterns for specific species and functions for the gut microbiome of the population that lives in traditional lifestyles through changing the diet in wet and dry seasons, indicating the role of these variants in these species’ adaptation to the changing environment and diets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07372-0.

Genomic and Functional Characterization of Enterococcus faecalis Isolates Recovered From the International Space Station and Their Potential for Pathogenicity

Enterococcus faecalis is a multidrug resistant, opportunistic human pathogen and a leading cause of hospital acquired infections. Recently, isolates have been recovered from the air and surfaces onboard the International Space Station (ISS). Pangenomic and functional analyses were carried out to assess their potential impact on astronaut health. Genomes of each ISS isolate, and both clinical and commensal reference strains, were evaluated for their core and unique gene content, acquired antibiotic resistance genes, phage, plasmid content, and virulence traits. In order to determine their potential survival when outside of the human host, isolates were also challenged with three weeks of desiccation at 30% relative humidity. Finally, pathogenicity of the ISS strains was evaluated in the model organism Caenorhabditis elegans. At the culmination of this study, there were no defining signatures that separated known pathogenic strains from the more commensal phenotypes using the currently available resources. As a result, the current reliance on database information alone must be shifted to experimentally evaluated genotypic and phenotypic characteristics of clinically relevant microorganisms.