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

Computational Tools for the Analysis of Uncultivated Phage Genomes

Over a century of bacteriophage research has uncovered a plethora of fundamental aspects of their biology, ecology, and evolution. Furthermore, the introduction of community-level studies through metagenomics has revealed unprecedented insights on the impact that phages have on a range of ecological and physiological processes. It was not until the introduction of viral metagenomics that we began to grasp the astonishing breadth of genetic diversity encompassed by phage genomes. Novel phage genomes have been reported from a diverse range of biomes at an increasing rate, which has prompted the development of computational tools that support the multilevel characterization of these novel phages based solely on their genome sequences. The impact of these technologies has been so large that, together with MAGs (Metagenomic Assembled Genomes), we now have UViGs (Uncultivated Viral Genomes), which are now officially recognized by the International Committee for the Taxonomy of Viruses (ICTV), and new taxonomic groups can now be created based exclusively on genomic sequence information. Even though the available tools have immensely contributed to our knowledge of phage diversity and ecology, the ongoing surge in software programs makes it challenging to keep up with them and the purpose each one is designed for. Therefore, in this review, we describe a comprehensive set of currently available computational tools designed for the characterization of phage genome sequences, focusing on five specific analyses: (i) assembly and identification of phage and prophage sequences, (ii) phage genome annotation, (iii) phage taxonomic classification, (iv) phage-host interaction analysis, and (v) phage microdiversity.

Short- and long-read metagenomics expand individualized structural variations in gut microbiomes

In-depth profiling of genetic variations in the gut microbiome is highly desired for understanding its functionality and impacts on host health and disease. Here, by harnessing the long read advantage provided by Oxford Nanopore Technology (ONT), we characterize fine-scale genetic variations of structural variations (SVs) in hundreds of gut microbiomes from healthy humans. ONT long reads dramatically improve the quality of metagenomic assemblies, enable reliable detection of a large, expanded set of structural variation types (notably including large insertions and inversions). We find SVs are highly distinct between individuals and stable within an individual, representing gut microbiome fingerprints that shape strain-level differentiations in function within species, complicating the associations to metabolites and host phenotypes such as blood glucose. In summary, our study strongly emphasizes that incorporating ONT reads into metagenomic analyses expands the detection scope of genetic variations, enables profiling strain-level variations in gut microbiome, and their intricate correlations with metabolome.

Here, Wang and colleagues combine short and long sequencing reads to characterize structural variations, prophage and CRISPR spacer elements in human gut microbiomes, and reveal functional differences at a finer level of bacterial strains.

Microbiome-based interventions to modulate gut ecology and the immune system

The gut microbiome lies at the intersection between the environment and the host, with the ability to modify host responses to disease-relevant exposures and stimuli. This is evident in how enteric microbes interact with the immune system, e.g., supporting immune maturation in early life, affecting drug efficacy via modulation of immune responses, or influencing development of immune cell populations and their mediators. Many factors modulate gut ecosystem dynamics during daily life and we are just beginning to realise the therapeutic and prophylactic potential of microbiome-based interventions. These approaches vary in application, goal, and mechanisms of action. Some modify the entire community, such as nutritional approaches or faecal microbiota transplantation, while others, such as phage therapy, probiotics, and prebiotics, target specific taxa or strains. In this review, we assessed the experimental evidence for microbiome-based interventions, with a particular focus on their clinical relevance, ecological effects, and modulation of the immune system.

Evaluation of the Effect of Different Dietary Lipid Sources on Dogs’ Faecal Microbial Population and Activities

Simple Summary

Saturated fatty acids might be a valuable source of energy to guarantee all physiological functions in companion animals. Polyunsaturated fatty acids are essential in several metabolic processes and structural body functions. In this regard, hemp oil can be used as a rich source of polyunsaturated fatty acids in animal diets. In this study, hemp seed oil and swine tallow were added to a commercial canned diet. These high-lipid-content diets (hemp diet: 55.1 g/100 kcal ME; tallow diet: 65.1 g/1000 kcal ME) were compared with one rich in starch. Following the recruitment of 12 dogs, three experimental groups were set up. At 30 days of diet administration, faeces samples were collected from each group to perform an in vitro trial and faecal bacteria count. In the first evaluation, the faecal inoculum obtained from dogs fed a diet supplemented with hemp showed higher fermentation activity and lower gas production at 24 h of incubation. The bacterial count demonstrated an increase in Lactobacillus when hemp group faeces were tested. Both in vivo and in vitro acetic acid production increased. The results obtained suggest an influence of the fatty acid profile on the microbial population.

Abstract

Lipids represent a significant energy source in dogs’ diets. Moreover, dogs need some essential fatty acids, such as linoleic and α-linolenic fatty acids, because they are not able to produce them endogenously. This study aimed to evaluate the effect of different dietary lipid sources on faecal microbial populations and activities using different evaluations. Hemp seed oil and swine tallow were tested as lipid supplements in a commercial canned diet at a ratio of 3.5% (HL1 and HL2, respectively). These diets were compared with one rich in starch (HS). Twelve dogs were recruited and equally divided into three groups. Faeces samples at 30 days were used as inoculum and incubated with three different substrates (MOS, inulin, and cellulose) using the in vitro gas production technique. The faecal cell numbers of relevant bacteria and secondary metabolites were analysed (in vivo trial). In vitro evaluation showed that the faeces of the group fed the diet with hemp supplementation had better fermentability despite lower gas production. The in vivo faecal bacterial count showed an increase in Lactobacillus spp. In the HL1 group. Moreover, a higher level of acetate was observed in both evaluations (in vitro and in vivo). These results seem to indicate a significant effect of the dietary fatty acid profile on the faecal microbial population.

Temporal relationship among adiposity, gut microbiota, and insulin resistance in a longitudinal human cohort

BACKGROUND

The temporal relationship between adiposity and gut microbiota was unexplored. Whether some gut microbes lie in the pathways from adiposity to insulin resistance is less clear. Our study aims to reveal the temporal relationship between adiposity and gut microbiota and investigate whether gut microbiota may mediate the association of adiposity with insulin resistance in a longitudinal human cohort study.

METHODS

We obtained repeated-measured gut shotgun metagenomic and anthropometric data from 426 Chinese participants over ~3 years of follow-up. Cross-lagged path analysis was used to examine the temporal relationship between BMI and gut microbial features. The associations between the gut microbes and insulin resistance-related phenotypes were examined using a linear mixed-effect model. We examined the mediation effect of gut microbes on the association between adiposity and insulin resistance-related phenotypes. Replication was performed in the HMP cohort.

RESULTS

Baseline BMI was prospectively associated with levels of ten gut microbial species. Among them, results of four species (Adlercreutzia equolifaciens, Parabacteroides unclassified, Lachnospiraceae bacterium 3 1 57FAA CT1, Lachnospiraceae bacterium 7 1 58FAA) were replicated in the independent HMP cohort. Lachnospiraceae bacterium 3 1 57FAA CT1 was inversely associated with HOMA-IR and fasting insulin. Lachnospiraceae bacterium 3 1 57FAA CT1 mediated the association of overweight/obesity with HOMA-IR (FDR<0.05). Furthermore, Lachnospiraceae bacterium 3 1 57FAA CT1 was positively associated with the butyrate-producing pathway PWY-5022 (p < 0.001).

CONCLUSIONS

Our study identified one potentially beneficial microbe Lachnospiraceae bacterium 3 1 57FAA CT1, which might mediate the effect of adiposity on insulin resistance. The identified microbes are helpful for the discovery of novel therapeutic targets, as to mitigate the impact of adiposity on insulin resistance.

Mutational Pattern Induced by 5-Fluorouracil and Oxaliplatin in the Gut Microbiome

Chemotherapeutic agents, such as 5-fluorouracil (5-FU) and oxaliplatin (Oxi), can not only kill the cancer cell but also influence the proliferation of gut microbiota; however, the interaction between these drugs and gut microbiota remains poorly understood. In this study, we developed a powerful framework for taxonomy composition and genomic variation analysis to investigate the mutagenesis effect and proliferation influence of chemotherapeutic agents, such as 5-FU and Oxi, on gut microbiota and the interaction between these drugs and gut microbiota during chemotherapy. Using the gut microbiome data, we detected 1.45 million variations among the chemotherapy groups and found the drugs significantly affected mutation signatures of gut microbiota. Oxi notably increased transversion rate, whereas 5-FU reduced the rate. Traits related to cell division and nutrient mobilization showed evidence of strong selection pressure from chemotherapeutic agents. In addition, drug-associated bacteriome shift patterns and functional alterations were found: the metabolism changes in the 5-FU group implied that gut microbiota could provide additional nicotinamide adenine dinucleotide (NAD⁺) to inhibit cancer cell autophagy; in the Oxi group, the ribosome and lysine biosynthesis genes were obviously enriched. Our study provides a blueprint for characterizing the role of microbes and drug–microbe interaction in the gut microbiota response to chemotherapy.

Towards Strain-Level Complexity: Sequencing Depth Required for Comprehensive Single-Nucleotide Polymorphism Analysis of the Human Gut Microbiome

Intestinal bacteria strains play crucial roles in maintaining host health. Researchers have increasingly recognized the importance of strain-level analysis in metagenomic studies. Many analysis tools and several cutting-edge sequencing techniques like single cell sequencing have been proposed to decipher strains in metagenomes. However, strain-level complexity is far from being well characterized up to date. As the indicator of strain-level complexity, metagenomic single-nucleotide polymorphisms (SNPs) have been utilized to disentangle conspecific strains. Lots of SNP-based tools have been developed to identify strains in metagenomes. However, the sufficient sequencing depth for SNP and strain-level analysis remains unclear. We conducted ultra-deep sequencing of the human gut microbiome and constructed an unbiased framework to perform reliable SNP analysis. SNP profiles of the human gut metagenome by ultra-deep sequencing were obtained. SNPs identified from conventional and ultra-deep sequencing data were thoroughly compared and the relationship between SNP identification and sequencing depth were investigated. The results show that the commonly used shallow-depth sequencing is incapable to support a systematic metagenomic SNP discovery. In contrast, ultra-deep sequencing could detect more functionally important SNPs, which leads to reliable downstream analyses and novel discoveries. We also constructed a machine learning model to provide guidance for researchers to determine the optimal sequencing depth for their projects (SNPsnp, https://github.com/labomics/SNPsnp). To conclude, the SNP profiles based on ultra-deep sequencing data extend current knowledge on metagenomics and highlights the importance of evaluating sequencing depth before starting SNP analysis. This study provides new ideas and references for future strain-level investigations.

A systematic review of microbial markers for risk prediction of colorectal neoplasia

BACKGROUND

Substantial evidence indicates that dysbiosis of the gut microbial community is associated with colorectal neoplasia. This review aims to systematically summarise the microbial markers associated with colorectal neoplasia and to assess their predictive performance.

METHODS

A comprehensive literature search of MEDLINE and EMBASE databases was performed to identify eligible studies. Observational studies exploring the associations between microbial biomarkers and colorectal neoplasia were included. We also included prediction studies that constructed models using microbial markers to predict CRC and adenomas. Risk of bias for included observational and prediction studies was assessed.

RESULTS

Forty-five studies were included to assess the associations between microbial markers and colorectal neoplasia. Nine faecal microbiotas (i.e., Fusobacterium, Enterococcus, Porphyromonas, Salmonella, Pseudomonas, Peptostreptococcus, Actinomyces, Bifidobacterium and Roseburia), two oral pathogens (i.e., Treponema denticola and Prevotella intermedia) and serum antibody levels response to Streptococcus gallolyticus subspecies gallolyticus were found to be consistently associated with colorectal neoplasia. Thirty studies reported prediction models using microbial markers, and 83.3% of these models had acceptable-to-good discrimination (AUROC > 0.75). The results of predictive performance were promising, but most of the studies were limited to small number of cases (range: 9-485 cases) and lack of independent external validation (76.7%).

CONCLUSIONS

This review provides insight into the evidence supporting the association between different types of microbial species and their predictive value for colorectal neoplasia. Prediction models developed from case-control studies require further external validation in high-quality prospective studies. Further studies should assess the feasibility and impact of incorporating microbial biomarkers in CRC screening programme.

Dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution

With advances in DNA sequencing and miniaturized molecular biology workflows, rapid and affordable sequencing of single-cell genomes has become a reality. Compared to 16S rRNA gene surveys and shotgun metagenomics, large-scale application of single-cell genomics to whole microbial communities provides an integrated snapshot of community composition and function, directly links mobile elements to their hosts, and enables analysis of population heterogeneity of the dominant community members. To that end, we sequenced nearly 500 single-cell genomes from a low diversity hot spring sediment sample from Dewar Creek, British Columbia, and compared this approach to 16S rRNA gene amplicon and shotgun metagenomics applied to the same sample. We found that the broad taxonomic profiles were similar across the three sequencing approaches, though several lineages were missing from the 16S rRNA gene amplicon dataset, likely the result of primer mismatches. At the functional level, we detected a large array of mobile genetic elements present in the single-cell genomes but absent from the corresponding same species metagenome-assembled genomes. Moreover, we performed a single-cell population genomic analysis of the three most abundant community members, revealing differences in population structure based on mutation and recombination profiles. While the average pairwise nucleotide identities were similar across the dominant species-level lineages, we observed differences in the extent of recombination between these dominant populations. Most intriguingly, the creek's Hydrogenobacter sp. population appeared to be so recombinogenic that it more closely resembled a sexual species than a clonally evolving microbe. Together, this work demonstrates that a randomized single-cell approach can be useful for the exploration of previously uncultivated microbes from community composition to population structure.

Early indicators of microbial strain dysbiosis in the human gastrointestinal microbial community of certain healthy humans and hospitalized COVID-19 patients

Dysbiosis in the human gastrointestinal microbial community could functionally impact microbial metabolism and colonization resistance to pathogens. To further elucidate the indicators of microbial strain dysbiosis, we have developed an analytic method that detects patterns of presence/absence of selected KEGG metabolic pathways for a selected strain (PKS). Using a metagenomic data set consisting of multiple high-density fecal samples from six normal individuals, we found three had unique PKS for important gut commensal microbes, Bacteroides vulgatus and Bacteroides uniformis, at all sample times examined. Two individuals had multiple shared PKS clusters of B. vulgatus or B. uniformis over time. Analysis of a data set of high-density fecal samples from eight COVID-19 hospitalized patients taken over a short period revealed that two patients had shared PKS clusters for B. vulgatus and one shared cluster for B. uniformis. Our analysis demonstrates that while the majority of normal individuals with no B. vulgatus or B. uniformis strain change over time have unique PKS, in some healthy humans and patients hospitalized with COVID-19, we detected shared PKS clusters at the different times suggesting a slowing down of the intrinsic rates of strain variation that could eventually lead to a dysbiosis in the microbial strain community.

The active lung microbiota landscape of COVID-19 patients through the metatranscriptome data analysis

Introduction: With the outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the interaction between the host and SARS-CoV-2 was widely studied. However, it is unclear whether and how SARS-CoV-2 infection affects lung microflora, which contribute to COVID-19 complications.

Methods: Here, we analyzed the metatranscriptomic data of bronchoalveolar lavage fluid (BALF) of 19 COVID-19 patients and 23 healthy controls from 6 independent projects and detailed the active microbiota landscape in both healthy individuals and COVID-19 patients.

Results: The infection of SARS-CoV-2 could deeply change the lung microbiota, evidenced by the α-diversity, β-diversity, and species composition analysis based on bacterial microbiota and virome. Pathogens (e.g., Klebsiella oxytoca causing pneumonia as well), immunomodulatory probiotics (e.g., lactic acid bacteria and Faecalibacterium prausnitzii, a butyrate producer), and Tobacco mosaic virus (TMV) were enriched in the COVID-19 group, suggesting a severe microbiota dysbiosis. The significant correlation between Rothia mucilaginosa, TMV, and SARS-CoV-2 revealed drastic inflammatory battles between the host, SARS-CoV-2, and other microbes in the lungs. Notably, TMV only existed in the COVID-19 group, while human respirovirus 3 (HRV 3) only existed in the healthy group. Our study provides insights into the active microbiota in the lungs of COVID-19 patients and would contribute to the understanding of the infection mechanism of SARS-CoV-2 and the treatment of the disease and complications.

Conclusion: SARS-COV-2 infection deeply altered the lung microbiota of COVID-19 patients. The enrichment of several other pathogens, immunomodulatory probiotics (lactic acid or butyrate producers), and TMV in the COVID-19 group suggests a complex and active lung microbiota disorder.

The evolution of bacterial genome assemblies - where do we need to go next?

Genome sequencing has fundamentally changed our ability to decipher and understand the genetic blueprint of life and how it changes over time in response to environmental and evolutionary pressures. The pace of sequencing is still increasing in response to advances in technologies, paving the way from sequenced genes to genomes to metagenomes to metagenome-assembled genomes (MAGs). Our ability to interrogate increasingly complex microbial communities through metagenomes and MAGs is opening up a tantalizing future where we may be able to delve deeper into the mechanisms and genetic responses emerging over time. In the near future, we will be able to detect MAG assembly variations within strains originating from diverging sub-populations, and one of the emerging challenges will be to capture these variations in a biologically relevant way. Here, we present a brief overview of sequencing technologies and the current state of metagenome assemblies to suggest the need to develop new data formats that can capture the genetic variations within strains and communities, which previously remained invisible due to sequencing technology limitations.

Eco-evolutionary responses of the microbial loop to surface ocean warming and consequences for primary production

Predicting the response of ocean primary production to climate warming is a major challenge. One key control of primary production is the microbial loop driven by heterotrophic bacteria, yet how warming alters the microbial loop and its function is poorly understood. Here we develop an eco-evolutionary model to predict the physiological response and adaptation through selection of bacterial populations in the microbial loop and how this will impact ecosystem function such as primary production. We find that the ecophysiological response of primary production to warming is driven by a decrease in regenerated production which depends on nutrient availability. In nutrient-poor environments, the loss of regenerated production to warming is due to decreasing microbial loop activity. However, this ecophysiological response can be opposed or even reversed by bacterial adaptation through selection, especially in cold environments: heterotrophic bacteria with lower bacterial growth efficiency are selected, which strengthens the "link" behavior of the microbial loop, increasing both new and regenerated production. In cold and rich environments such as the Arctic Ocean, the effect of bacterial adaptation on primary production exceeds the ecophysiological response. Accounting for bacterial adaptation through selection is thus critically needed to improve models and projections of the ocean primary production in a warming world.

Fast and accurate metagenotyping of the human gut microbiome with GT-Pro

Single nucleotide polymorphisms (SNPs) in metagenomics are used to quantify population structure, track strains and identify genetic determinants of microbial phenotypes. However, existing alignment-based approaches for metagenomic SNP detection require high-performance computing and enough read coverage to distinguish SNPs from sequencing errors. To address these issues, we developed the GenoTyper for Prokaryotes (GT-Pro), a suite of methods to catalog SNPs from genomes and use unique k-mers to rapidly genotype these SNPs from metagenomes. Compared to methods that use read alignment, GT-Pro is more accurate and two orders of magnitude faster. Using high-quality genomes, we constructed a catalog of 104 million SNPs in 909 human gut species and used unique k-mers targeting this catalog to characterize the global population structure of gut microbes from 7,459 samples. GT-Pro enables fast and memory-efficient metagenotyping of millions of SNPs on a personal computer.

Metagenomic strain detection with SameStr: identification of a persisting core gut microbiota transferable by fecal transplantation

BACKGROUND

The understanding of how microbiomes assemble, function, and evolve requires metagenomic tools that can resolve microbiota compositions at the strain level. However, the identification and tracking of microbial strains in fecal metagenomes is challenging and available tools variably classify subspecies lineages, which affects their applicability to infer microbial persistence and transfer.

RESULTS

We introduce SameStr, a bioinformatic tool that identifies shared strains in metagenomes by determining single-nucleotide variants (SNV) in species-specific marker genes, which are compared based on a maximum variant profile similarity. We validated SameStr on mock strain populations, available human fecal metagenomes from healthy individuals and newly generated data from recurrent Clostridioides difficile infection (rCDI) patients treated with fecal microbiota transplantation (FMT). SameStr demonstrated enhanced sensitivity to detect shared dominant and subdominant strains in related samples (where strain persistence or transfer would be expected) when compared to other tools, while being robust against false-positive shared strain calls between unrelated samples (where neither strain persistence nor transfer would be expected). We applied SameStr to identify strains that are stably maintained in fecal microbiomes of healthy adults over time (strain persistence) and that successfully engraft in rCDI patients after FMT (strain engraftment). Taxonomy-dependent strain persistence and engraftment frequencies were positively correlated, indicating that a specific core microbiota of intestinal species is adapted to be competitive both in healthy microbiomes and during post-FMT microbiome assembly. We explored other use cases for strain-level microbiota profiling, as a metagenomics quality control measure and to identify individuals based on the persisting core gut microbiota.

CONCLUSION

SameStr provides for a robust identification of shared strains in metagenomic sequence data with sufficient specificity and sensitivity to examine strain persistence, transfer, and engraftment in human fecal microbiomes. Our findings identify a persisting healthy adult core gut microbiota, which should be further studied to shed light on microbiota contributions to chronic diseases. Video abstract.

Evolution of Phytoplankton as Estimated from Genetic Diversity

Phytoplankton are photosynthetic, single-celled organisms producing almost half of all oxygen on Earth and play a central role as prey for higher organisms, making them irreplaceable in the marine food web. As Global Change proceeds, imposing rapidly intensifying selection pressures, phytoplankton are forced to undergo evolution, local extinction, or redistribution, with potentially cascading effects throughout the marine ecosystem. Recent results from the field of population genetics display high levels of standing genetic diversity in natural phytoplankton populations, providing ample ‘evolutionary options’ and implying high adaptive potential to changing conditions. This potential for adaptive evolution is realized in several studies of experimental evolution, even though most of these studies investigate the evolution of only single strains. This, however, shows that phytoplankton not only evolve from standing genetic diversity, but also rely on de novo mutations. Recent global sampling campaigns show that the immense intraspecific diversity of phytoplankton in the marine ecosystem has been significantly underestimated, meaning we are only studying a minor portion of the relevant variability in the context of Global Change and evolution. An increased understanding of genomic diversity is primarily hampered by the low number of ecologically representative reference genomes of eukaryotic phytoplankton and the functional annotation of these. However, emerging technologies relying on metagenome and transcriptome data may offer a more realistic understanding of phytoplankton diversity.

Recombination resolves the cost of horizontal gene transfer in experimental populations of Helicobacter pylori

Horizontal gene transfer (HGT)—the transfer of DNA between lineages—is responsible for a large proportion of the genetic variation that contributes to evolution in microbial populations. While HGT can bring beneficial genetic innovation, the transfer of DNA from other species or strains can also have deleterious effects. In this study, we evolve populations of the bacteria Helicobacter pylori and use DNA sequencing to identify over 40,000 genetic variants transferred by HGT. We measure the cost of many of these and find that both strongly beneficial mutations and deleterious mutations are genetic variants transferred by natural transformation. Importantly, we also show how recombination that separates linked beneficial and deleterious mutations resolves the cost of HGT.

Horizontal gene transfer (HGT) is important for microbial evolution, yet we know little about the fitness effects and dynamics of horizontally transferred genetic variants. In this study, we evolve laboratory populations of Helicobacter pylori, which take up DNA from their environment by natural transformation, and measure the fitness effects of thousands of transferred genetic variants. We find that natural transformation increases the rate of adaptation but comes at the cost of significant genetic load. We show that this cost is circumvented by recombination, which increases the efficiency of selection by decoupling deleterious and beneficial genetic variants. Our results show that adaptation with HGT, pervasive in natural microbial populations, is shaped by a combination of selection, recombination, and genetic drift not accounted for in existing models of evolution.

MetaPop: a pipeline for macro- and microdiversity analyses and visualization of microbial and viral metagenome-derived populations

BACKGROUND

Microbes and their viruses are hidden engines driving Earth's ecosystems from the oceans and soils to humans and bioreactors. Though gene marker approaches can now be complemented by genome-resolved studies of inter-(macrodiversity) and intra-(microdiversity) population variation, analytical tools to do so remain scattered or under-developed.

RESULTS

Here, we introduce MetaPop, an open-source bioinformatic pipeline that provides a single interface to analyze and visualize microbial and viral community metagenomes at both the macro- and microdiversity levels. Macrodiversity estimates include population abundances and α- and β-diversity. Microdiversity calculations include identification of single nucleotide polymorphisms, novel codon-constrained linkage of SNPs, nucleotide diversity (π and θ), and selective pressures (pN/pS and Tajima's D) within and fixation indices (FST) between populations. MetaPop will also identify genes with distinct codon usage. Following rigorous validation, we applied MetaPop to the gut viromes of autistic children that underwent fecal microbiota transfers and their neurotypical peers. The macrodiversity results confirmed our prior findings for viral populations (microbial shotgun metagenomes were not available) that diversity did not significantly differ between autistic and neurotypical children. However, by also quantifying microdiversity, MetaPop revealed lower average viral nucleotide diversity (π) in autistic children. Analysis of the percentage of genomes detected under positive selection was also lower among autistic children, suggesting that higher viral π in neurotypical children may be beneficial because it allows populations to better "bet hedge" in changing environments. Further, comparisons of microdiversity pre- and post-FMT in autistic children revealed that the delivery FMT method (oral versus rectal) may influence viral activity and engraftment of microdiverse viral populations, with children who received their FMT rectally having higher microdiversity post-FMT. Overall, these results show that analyses at the macro level alone can miss important biological differences.

CONCLUSIONS

These findings suggest that standardized population and genetic variation analyses will be invaluable for maximizing biological inference, and MetaPop provides a convenient tool package to explore the dual impact of macro- and microdiversity across microbial communities. Video abstract.

Identification and Genome Analysis of an Arsenic-Metabolizing Strain of Citrobacter youngae IITK SM2 in Middle Indo-Gangetic Plain Groundwater

Whole-genome sequencing (WGS) data of a bacterial strain IITK SM2 isolated from an aquifer located in the middle Indo-Gangetic plain is reported here, along with its physiological, morphological, biochemical, and redox-transformation characteristics in the presence of dissolved arsenic (As). The aquifer exhibits oxidizing conditions relative to As speciation. Analyses based on 16S rRNA and recN sequences indicate that IITK SM2 was clustered with C. youngae NCTC 13708T and C. pasteuri NCTC UMH17T. However, WGS analyses using the digital DNA-DNA hybridization and Rapid Annotations using Subsystems Technology suggest that IITK SM2 belongs to a strain of C. youngae. This strain can effectively reduce As(V) to As(III) but cannot oxidize As(III) to As(V). It exhibited high resistance to As(V) [32,000 mg L-1] and As(III) [1,100 mg L-1], along with certain other heavy metals typically found in contaminated groundwater. WGS analysis also indicates the presence of As-metabolizing genes such as arsC, arsB, arsA, arsD, arsR, and arsH in this strain. Although these genes have been identified in several As(V)-reducers, the clustering of these genes in the forms of arsACBADR, arsCBRH, and an independent arsC gene has not been observed in any other Citrobacter species or other selected As(V)-reducing strains of Enterobacteriaceae family. Moreover, there were differences in the number of genes corresponding to membrane transporters, virulence and defense, motility, protein metabolism, phages, prophages, and transposable elements in IITK SM2 when compared to other strains. This genomic dataset will facilitate subsequent molecular and biochemical analyses of strain IITK SM2 to identify the reasons for high arsenic resistance in Citrobacter youngae and understand its role in As mobilization in middle Indo-Gangetic plain aquifers.

Population differentiation and epidemic tracking of Bursaphelenchus xylophilus in China based on chromosome-level assembly and whole-genome sequencing data

BACKGROUND

Bursaphelenchus xylophilus, the pinewood nematode, kills millions of pine trees worldwide every year, and causes enormous economic and ecological losses. Despite extensive research on population variation, there is little understanding of the population-wide variation spectrum in China.

RESULTS

We sequenced an inbred B. xylophilus strain using Pacbio+Illumina+Bionano+Hi-C and generated a chromosome-level assembly (AH1) with six chromosomes of 77.1 Mb (chromosome N50: 12 Mb). The AH1 assembly shows very high continuity and completeness, and contains novel genes with potentially important functions compared with previous assemblies. Subsequently, we sequenced 181 strains from China and the USA and found ~7.8 million single nucleotide polymorphisms (SNPs). Analysis shows that the B. xylophilus population in China can be divided into geographically bounded subpopulations with severe cross-infection and potential migrations. In addition, distribution of B. xylophilus is dominated by temperature zones while geographically associated SNPs are mainly located on adaptation related GPCR gene families, suggesting the nematode has been evolving to adapt to different temperatures. A machine-learning based epidemic tracking method has been established to predict their geographical origins, which can be applied to any other species.

CONCLUSION

Our study provides the community with the first high-quality chromosome-level assembly which includes a comprehensive catalogue of genetic variations. It provides insights into population structure and effective tracking method for this invasive species, which facilitates future studies to address a variety of applied, genomic and evolutionary questions in B. xylophilus as well as related species.

Ecological Processes Shaping Microbiomes of Extremely Low Birthweight Infants

The human microbiome has been implicated in affecting health outcomes in premature infants, but the ecological processes governing early life microbiome assembly remain poorly understood. Here, we investigated microbial community assembly and dynamics in extremely low birth weight infants (ELBWI) over the first 2 weeks of life. We profiled the gut, oral cavity and skin microbiomes over time using 16S rRNA gene amplicon sequencing and evaluated the ecological forces shaping these microbiomes. Though microbiomes at all three body sites were characterized by compositional instability over time and had low body-site specificity (PERMANOVA, r 2 = 0.09, p = 0.001), they could nonetheless be clustered into four discrete community states. Despite the volatility of these communities, deterministic assembly processes were detectable in this period of initial microbial colonization. To further explore these deterministic dynamics, we developed a probabilistic approach in which we modeled microbiome state transitions in each ELBWI as a Markov process, or a "memoryless" shift, from one community state to another. This analysis revealed that microbiomes from different body sites had distinctive dynamics as well as characteristic equilibrium frequencies. Time-resolved microbiome sampling of premature infants may help to refine and inform clinical practices. Additionally, this work provides an analysis framework for microbial community dynamics based on Markov modeling that can facilitate new insights, not only into neonatal microbiomes but also other human-associated or environmental microbiomes.

Murine Model for Measuring Effects of Humanized-Dosing of Antibiotics on the Gut Microbiome

There is a current need for enhancing our insight in the effects of antimicrobial treatment on the composition of human microbiota. Also, the spontaneous restoration of the microbiota after antimicrobial treatment requires better understanding. This is best addressed in well-defined animal models. We here present a model in which immune-competent or neutropenic mice were administered piperacillin-tazobactam (TZP) according to human treatment schedules. Before, during and after the TZP treatment, fecal specimens were longitudinally collected at established intervals over several weeks. Gut microbial taxonomic distribution and abundance were assessed through culture and molecular means during all periods. Non-targeted metabolomics analyses of stool samples using Quadrupole Time of Flight mass spectrometry (QTOF MS) were also applied to determine if a metabolic fingerprint correlated with antibiotic use, immune status, and microbial abundance. TZP treatment led to a 5–10-fold decrease in bacterial fecal viability counts which were not fully restored during post-antibiotic follow up. Two distinct, relatively uniform and reproducible restoration scenarios of microbiota changes were seen in post TZP-treatment mice. Post-antibiotic flora could consist of predominantly Firmicutes or, alternatively, a more diverse mix of taxa. In general, the pre-treatment microbial communities were not fully restored within the screening periods applied. A new species, closely related to Eubacterium siraeum, Mageeibacillus indolicus, and Saccharofermentans acetigenes, became predominant post-treatment in a significant proportion of mice, identified by 16S rRNA gene sequencing. Principal component analysis of QTOF MS of mouse feces successfully distinguished treated from non-treated mice as well as immunocompetent from neutropenic mice. We observe dynamic but distinct and reproducible responses in the mouse gut microbiota during and after TZP treatment and propose the current murine model as a useful tool for defining the more general post-antibiotic effects in the gastro-intestinal ecosystem where humanized antibiotic dosing may ultimately facilitate extrapolation to humans.

Periodontal and Peri-Implant Microbiome Dysbiosis Is Associated With Alterations in the Microbial Community Structure and Local Stability

Periodontitis and peri-implantitis are common biofilm-mediated infectious diseases affecting teeth and dental implants and have been considered to be initiated with microbial dysbiosis. To further understand the essence of oral microbiome dysbiosis in terms of bacterial interactions, community structure, and microbial stability, we analyzed 64 plaque samples from 34 participants with teeth or implants under different health conditions using metagenomic sequencing. After taxonomical annotation, we computed the inter-species correlations, analyzed the bacterial community structure, and calculated the microbial stability in supra- and subgingival plaques from hosts with different health conditions. The results showed that when inflammation arose, the subgingival communities became less connective and competitive with fewer hub species. In contrast, the supragingival communities tended to be more connective and competitive with an increased number of hub species. Besides, periodontitis and peri-implantitis were associated with significantly increased microbial stability in subgingival microbiome. These findings indicated that the periodontal and peri-implant dysbiosis is associated with aberrant alterations in the bacterial correlations, community structures, and local stability. The highly connected hub species, as well as the major contributing species of negative correlations, should also be given more concern in future studies.

Microbial Evolution: An overlooked biomarker of host diet

The evolutionary dynamics of gut microbiota are still being explored. In this issue of Cell Host & Microbe, Dapa et al. conduct an experimental evolution study in mice to track the rapid adaptation of the gut microbiome based on host diet.

Interactions between strains govern the eco-evolutionary dynamics of microbial communities

Genomic data has revealed that genotypic variants of the same species, that is, strains, coexist and are abundant in natural microbial communities. However, it is not clear if strains are ecologically equivalent, and at what characteristic genetic distance they might exhibit distinct interactions and dynamics. Here, we address this problem by tracking 10 taxonomically diverse microbial communities from the pitcher plant Sarracenia purpurea in the laboratory for more than 300 generations. Using metagenomic sequencing, we reconstruct their dynamics over time and across scales, from distant phyla to closely related genotypes. We find that most strains are not ecologically equivalent and exhibit distinct dynamical patterns, often being significantly more correlated with strains from another species than their own. Although even a single mutation can affect laboratory strains, on average, natural strains typically decouple in their dynamics beyond a genetic distance of 100 base pairs. Using mathematical consumer-resource models, we show that these taxonomic patterns emerge naturally from ecological interactions between community members, but only if the interactions are coarse-grained at the level of strains, not species. Finally, by analyzing genomic differences between strains, we identify major functional hubs such as transporters, regulators, and carbohydrate-catabolizing enzymes, which might be the basis for strain-specific interactions. Our work suggests that fine-scale genetic differences in natural communities could be created and stabilized via the rapid diversification of ecological interactions between strains.

Recent advances in microbial community analysis from machine learning of multiparametric flow cytometry data

Dynamic analysis of microbial composition is crucial for understanding community functioning and detecting dysbiosis. Compositional information is mostly obtained through sequencing of taxonomic markers or whole meta-genomes, which may be productively complemented by real-time quantitative community multiparametric flow cytometry data (FCM). Patterns and clusters in FCM community data can be distinguished and compared by unsupervised machine learning. Alternatively, FCM data from preselected individual strain phenotypes can be used for supervised machine-training in order to differentiate similar cell types within communities. Both types of machine learning can quantitatively deconvolute community FCM data sets and rapidly analyse global changes in response to treatment. Procedures may further be optimized for recurrent microbiome samples to simultaneously quantify physiological and compositional states.

Challenges and future directions for studying effects of host genetics on the gut microbiome

The human gut microbiome is a complex ecosystem that is involved in its host's metabolism, immunity and health. Although interindividual variations in gut microbial composition are mainly driven by environmental factors, some gut microorganisms are heritable and thus can be influenced by host genetics. In the past 5 years, 12 microbial genome-wide association studies (mbGWAS) with >1,000 participants have been published, yet only a few genetic loci have been consistently confirmed across multiple studies. Here we discuss the state of the art for mbGWAS, focusing on current challenges such as the heterogeneity of microbiome measurements and power issues, and we elaborate on potential future directions for genetic analysis of the microbiome.

Functional strain redundancy and persistent phage infection in Swiss hard cheese starter cultures

Undefined starter cultures are poorly characterized bacterial communities from environmental origin used in cheese making. They are phenotypically stable and have evolved through domestication by repeated propagation in closed and highly controlled environments over centuries. This makes them interesting for understanding eco-evolutionary dynamics governing microbial communities. While cheese starter cultures are known to be dominated by a few bacterial species, little is known about the composition, functional relevance, and temporal dynamics of strain-level diversity. Here, we applied shotgun metagenomics to an important Swiss cheese starter culture and analyzed historical and experimental samples reflecting 82 years of starter culture propagation. We found that the bacterial community is highly stable and dominated by only a few coexisting strains of Streptococcus thermophilus and Lactobacillus delbrueckii subsp. lactis. Genome sequencing, metabolomics analysis, and co-culturing experiments of 43 isolates show that these strains are functionally redundant, but differ tremendously in their phage resistance potential. Moreover, we identified two highly abundant Streptococcus phages that seem to stably coexist in the community without any negative impact on bacterial growth or strain persistence, and despite the presence of a large and diverse repertoire of matching CRISPR spacers. Our findings show that functionally equivalent strains can coexist in domesticated microbial communities and highlight an important role of bacteria-phage interactions that are different from kill-the-winner dynamics.

From organ-on-chip to body-on-chip: The next generation of microfluidics platforms for in vitro drug efficacy and toxicity testing

The high failure rate in drug development is often attributed to the lack of accurate pre-clinical models that may lead to false discoveries and inconclusive data when the compounds are eventually tested in clinical phase. With the evolution of cell culture technologies, drug testing systems have widely improved, and today, with the emergence of microfluidics devices, drug screening seems to be at the dawn of an important revolution. An organ-on-chip allows the culture of living cells in continuously perfused microchambers to reproduce physiological functions of a particular tissue or organ. The advantages of such systems are not only their ability to recapitulate the complex biochemical interactions between different human cell types but also to incorporate physical forces, including shear stress and mechanical stretching or compression. To improve this model, and to reproduce the absorption, distribution, metabolism, and elimination process of an exogenous compound, organ-on-chips can even be linked fluidically to mimic physiological interactions between different organs, leading to the development of body-on-chips. Although these technologies are still at a young age and need to address a certain number of limitations, they already demonstrated their relevance to study the effect of drugs or toxins on organs, displaying a similar response to what is observed in vivo. The purpose of this review is to present the evolution from organ-on-chip to body-on-chip, examine their current use for drug testing and discuss their advantages and future challenges they will face in order to become an essential pillar of pharmaceutical research.

Functional strain redundancy and persistent phage infection in Swiss hard cheese starter cultures

Undefined starter cultures are poorly characterized bacterial communities from environmental origin used in cheese making. They are phenotypically stable and have evolved through domestication by repeated propagation in closed and highly controlled environments over centuries. This makes them interesting for understanding eco-evolutionary dynamics governing microbial communities. While cheese starter cultures are known to be dominated by a few bacterial species, little is known about the composition, functional relevance, and temporal dynamics of strain-level diversity. Here, we applied shotgun metagenomics to an important Swiss cheese starter culture and analyzed historical and experimental samples reflecting 82 years of starter culture propagation. We found that the bacterial community is highly stable and dominated by only a few coexisting strains of Streptococcus thermophilus and Lactobacillus delbrueckii subsp. lactis. Genome sequencing, metabolomics analysis, and co-culturing experiments of 43 isolates show that these strains are functionally redundant, but differ tremendously in their phage resistance potential. Moreover, we identified two highly abundant Streptococcus phages that seem to stably coexist in the community without any negative impact on bacterial growth or strain persistence, and despite the presence of a large and diverse repertoire of matching CRISPR spacers. Our findings show that functionally equivalent strains can coexist in domesticated microbial communities and highlight an important role of bacteria-phage interactions that are different from kill-the-winner dynamics.

Toward hypothesis-driven, personalized microbiome screening

The human gut microbiome is crucial for human health and disease but exhibits extensive individual-level strain variation. Distinct strains encode and express different functions. The resulting emergent properties therefore differentially affect human health and disease in a personalized manner. Pryszlak et al. have made strides in tackling the challenge of genome-based microbiome screening which will ultimately yield strain-level understanding of the functional roles played by the human gut microbiome.

Pelzer B, Khodamoradi Y, Vehreschild MJGT. The role of the human gut microbiota in colonization and infection with multidrug-resistant bacteria

About 100 years ago, the first antibiotic drug was introduced into health care. Since then, antibiotics have made an outstanding impact on human medicine. However, our society increasingly suffers from collateral damage exerted by these highly effective drugs. The rise of resistant pathogen strains, combined with a reduction of microbiota diversity upon antibiotic treatment, has become a significant obstacle in the fight against invasive infections worldwide.Alternative and complementary strategies to classical "Fleming antibiotics" comprise microbiota-based treatments such as fecal microbiota transfer and administration of probiotics, live-biotherapeutics, prebiotics, and postbiotics. Other promising interventions, whose efficacy may also be influenced by the human microbiota, are phages and vaccines. They will facilitate antimicrobial stewardship, to date the only globally applied antibiotic resistance mitigation strategy.In this review, we present the available evidence on these nontraditional interventions, highlight their interaction with the human microbiota, and discuss their clinical applicability.

Comparative Population Genetics in the Human Gut Microbiome

Genetic variation in the human gut microbiome is responsible for conferring a number of crucial phenotypes like the ability to digest food and metabolize drugs. Yet, our understanding of how this variation arises and is maintained remains relatively poor. Thus, the microbiome remains a largely untapped resource, as the large number of coexisting species in the microbiome presents a unique opportunity to compare and contrast evolutionary processes across species to identify universal trends and deviations. Here we outline features of the human gut microbiome that, while not unique in isolation, as an assemblage make it a system with unparalleled potential for comparative population genomics studies. We consciously take a broad view of comparative population genetics, emphasizing how sampling a large number of species allows researchers to identify universal evolutionary dynamics in addition to new genes, which can then be leveraged to identify exceptional species that deviate from general patterns. To highlight the potential power of comparative population genetics in the microbiome, we reanalyze patterns of purifying selection across ∼40 prevalent species in the human gut microbiome to identify intriguing trends which highlight functional categories in the microbiome that may be under more or less constraint.

Hybrid, ultra-deep metagenomic sequencing enables genomic and functional characterization of low-abundance species in the human gut microbiome

A large number of microbial genomes have already been identified from the human gut microbiome, but the understanding of the role of the low-abundance species at the individual level remains challenging, largely due to the relatively shallow sequencing depth used in most studies. To improve genome assembling performance, a HiSeq-PacBio hybrid, ultra-deep metagenomic sequencing approach was used to reconstruct metagenomic-assembled genomes (MAGs) from 12 fecal samples. Such approach combined third-generation sequencing with ultra-deep second-generation sequencing to improve the sequencing coverage of the low-abundance subpopulation in the gut microbiome. Our study generated a total of 44 megabase-scale scaffolds, achieving four single-scaffolds of complete (circularized, no gaps) MAGs (CMAGs) that were the first circular genomes of their species. Moreover, 475 high-quality MAGs were assembled across all samples. Among them, 234 MAGs were currently uncultured, including 24 MAGs that were not found in any public genome database. Additionally, 287 and 77 MAGs were classified as low-abundance (0.1-1%) and extra-low-abundance (<0.1%) gut species in each individual, respectively. Our results also revealed individual-specific genomic features in the MAG profiles, including microbial genome growth rate, selective pressure, and frequency of chromosomal mobile genetic elements. Finally, thousands of extrachromosomal mobile genetic elements were identified from the metagenomic data, including 5097 bacteriophages and 79 novel plasmid genomes. Overall, our strategy represents an important step toward comprehensive genomic and functional characterization of the human gut microbiome at an individual level.

Next steps after 15 stimulating years of human gut microbiome research

Gut microbiome research has bloomed over the past 15 years. We have learnt a lot about the complex microbial communities that colonize our intestine. Promising avenues of research and microbiome-based applications are being implemented, with the goal of sustaining host health and applying personalized disease management strategies. Despite this exciting outlook, many fundamental questions about enteric microbial ecosystems remain to be answered. Organizational measures will also need to be taken to optimize the outcome of discoveries happening at an extremely rapid pace. This article highlights our own view of the field and perspectives for the next 15 years.

Hypoglycemic Effects of Plant Flavonoids: A Review

Diabetes mellitus is a metabolic disorder with chronic high blood glucose levels, and it is associated with defects in insulin secretion, insulin resistance, or both. It is also a major public issue, affecting the world's population. This disease contributes to long-term health complications such as dysfunction and failure of multiple organs, including nerves, heart, blood vessels, kidneys, and eyes. Flavonoids are phenolic compounds found in nature and usually present as secondary metabolites in plants, vegetables, and fungi. Flavonoids possess many health benefits such as anti-inflammatory and antioxidant activities, and naturally occurring flavonoids contribute to antidiabetic effects.Many studies conducted in vivo and in vitro have proven the hypoglycemic effect of plant flavonoids. A large number of studies showed that flavonoids hold positive results in controlling the blood glucose level in streptozotocin (STZ)-induced diabetic rats and further prevent the complications of diabetes. The future development of flavonoid-based drugs is believed to provide significant effects on diabetes mellitus and diabetes complication diseases. This review aims at summarizing the various types of flavonoids that function as hyperglycemia regulators such as inhibitors of α-glucosidase and glucose cotransporters in the body. This review article discusses the hypoglycemic effects of selected plant flavonoids namely quercetin, kaempferol, rutin, naringenin, fisetin, and morin. Four search engines, PubMed, Google Scholar, Scopus, and SciFinder, are used to collect the data.

Compositional and functional alterations of gut microbiota in patients with stroke

BACKGROUND AND AIMS

There is accumulating evidence that gut microbiota plays a key role in cardiovascular diseases. Gut bacteria can transform dietary choline, l-carnitine, and trimethylamine N-oxide (TMAO) into trimethylamine, which can be oxidized into TMAO again in the liver. However, the alterations of the gut microbiota in large artery atherosclerotic (LAA) stroke and cardioembolic (CE) stroke have been less studied.

METHODS AND RESULTS

We performed a case-control study in patients with LAA and CE types of strokes. We profiled the gut microbiome using Illumina sequencing of the 16S ribosomal RNA gene (V4-V5 regions), and TMAO was determined via liquid chromatography-tandem mass spectrometry. Our results showed that the TMAO levels in the plasma of patients with LAA and CE strokes were significantly higher than those in controls (LAA stroke, 2931 ± 456.4 ng/mL; CE stroke, 4220 ± 577.6 ng/mL; healthy control, 1663 ± 117.8 ng/mL; adjusted p < 0.05). The TMAO level in the plasma of patients with LAA stroke was positively correlated with the carotid plaque area (rho = 0.333, 95% CI = 0.08-0.55, p = 0.0093). Notably, the composition and the function of gut microbiota in the LAA stroke group were significantly different from those in the control group (FDR-adjusted p-value < 0.05). There was no significant association between gut microbiota and CE stroke in our study.

CONCLUSION

This study provides evidence for significant compositional and functional alterations of the gut microbiome in patients with LAA stroke. Gut microbiota might serve as a potential biomarker for patients with LAA stroke.

Predicting Inchinkoto efficacy, in patients with obstructive jaundice associated with malignant tumors, through pharmacomicrobiomics

Inchinkoto (ICKT) is a popular choleretic and hepatoprotective herbal medicine that is widely used in Japan. Geniposide, a major ingredient of ICKT, is metabolized to genipin by gut microbiota, which exerts a choleretic effect. This study investigates the relationship between stool genipin-producing activity and diversity of the clinical effect of ICKT in patients with malignant obstructive jaundice. Fifty-two patients with malignant obstructive jaundice who underwent external biliary drainage were included. ICKT was administered as three packets per day (7.5 g/day) for three days and 2.5 g on the morning of the fourth day. Stool samples were collected before ICKT administration and bile flow was monitored on a daily basis. The microbiome, genipin-producing activity, and organic acids in stools were analyzed. The Shannon-Wiener (SW) index was calculated to evaluate gut microbiome diversity. The stool genipin-producing activity showed a significant positive correlation with the SW index. Stool genipin-producing activity positively correlated with the order Clostridia (obligate anaerobes), but negatively correlated with the order Lactobacillales (facultative anaerobes). Moreover, stool genipin-producing activity was positively correlated to the concentration valeric acid, but negatively correlated to the concentration of lactic acid and succinic acid. The change of bile flow at 2 and 3 days after ICKT administration showed significant positive correlation with genipin-producing activity (correlation coefficient, 0.40 and 0.29, respectively, P < 0.05). An analysis of stool profile, including stool genipin-producing activity, may predict the efficacy of ICKT. Modification of the microbiome may be a target to enhance the therapeutic effect of ICKT.

Evaluation of Effects of Laboratory Disinfectants on Mouse Gut Microbiota

Disturbances in the gut microbiota are known to be associated with numerous human diseases. Mice have proven to be an invaluable tool for investigating the role of the gut microbiota in disease processes. Nonexperimental factors related to maintaining mice in the laboratory environment are increasingly being shown to have inadvertent effects on the gut microbiotaand may function as confounding variables. Microisolation technique is a term used to describe the common biosecuritypractice of spraying gloved hands with disinfectant before handling research mice. This practice prevents contamination with pathogenic microorganisms. To investigate if exposure to disinfectants can affect the mouse gut microbiota, C57BL/6 micewere exposed daily for 27 consecutive days to commonly used laboratory disinfectants through microisolation technique.The effects of 70% ethanol and disinfectant products containing chlorine dioxide, hydrogen peroxide, or potassium peroxymonosulfate were each evaluated. Fecal pellets were collected after 7, 14, 21, and 28 d of disinfectant exposure, and cecal contents were collected at day 28. DNA extractions were performed on all cecal and fecal samples, and microbial community structure was characterized using 16S ribosomal RNA amplicon sequencing. Alpha and β diversity metrics and taxon-level analyses were used to evaluate differences in microbial communities. Disinfectant had a small but significant effect on fecal microbial communities compared with sham-exposed controls, and effects varied by disinfectant type. In general, longerexposure times resulted in greater changes in the fecal microbiota. Effects on the cecal microbiota were less pronounced and only seen with the hydrogen peroxide and potassium peroxymonosulfate disinfectants. These results indicate that laboratory disinfectant use should be considered as a potential factor that can affect the mouse gut microbiota.

Compositional and genetic alterations in Graves' disease gut microbiome reveal specific diagnostic biomarkers

Graves' Disease is the most common organ-specific autoimmune disease and has been linked in small pilot studies to taxonomic markers within the gut microbiome. Important limitations of this work include small sample sizes and low-resolution taxonomic markers. Accordingly, we studied 162 gut microbiomes of mild and severe Graves' disease (GD) patients and healthy controls. Taxonomic and functional analyses based on metagenome-assembled genomes (MAGs) and MAG-annotated genes, together with predicted metabolic functions and metabolite profiles, revealed a well-defined network of MAGs, genes and clinical indexes separating healthy from GD subjects. A supervised classification model identified a combination of biomarkers including microbial species, MAGs, genes and SNPs, with predictive power superior to models from any single biomarker type (AUC = 0.98). Global, cross-disease multi-cohort analysis of gut microbiomes revealed high specificity of these GD biomarkers, notably discriminating against Parkinson's Disease, and suggesting that non-invasive stool-based diagnostics will be useful for these diseases.

Microbial Species that Initially Colonize the Human Gut at Birth or in Early Childhood Can Stay in Human Body for Lifetime

In recent years, many studies have described the composition and function of the human microbiome at different body sites and suggested a role for the microbiome in various diseases and health conditions. Some studies, using longitudinal samples, have also suggested how the microbiome changes over time due to disease, diet, development, travel, and other environmental factors. However, to date, no study has demonstrated whether the microorganisms established at birth or in early childhood, either transmitted from parents or obtained from the environment, can stay in the human body until adult or senior age. To directly answer this question is difficult, because microbiome samples at childhood and at later adulthood for the same individual will need to be compared and the field is not old enough to have allowed for that type of sample collection. Here, using a metagenomic approach, we analyzed 1004 gut microbiome samples from senior adults (65 ± 7.8 years) from the TwinsUK cohort. Our data indicate that many species in the human gut acquired in early childhood can stay for a lifetime until senior ages. We identified the rare genomic variants (single nucleotide variation and indels) for 27 prevalent species with enough sequencing coverage for confident genomic variant identification. We found that for some species, twin pairs, including both monozygotic (MZ) and dizygotic (DZ) twins, share significantly more rare variants than unrelated subject pairs. But no significant difference is found between MZ and DZ twin pairs. These observations strongly suggest that these species acquired in early childhood remained in these persons until senior adulthood.

Microbial adaptive evolution

Bacterial species can adapt to significant changes in their environment by mutation followed by selection, a phenomenon known as “adaptive evolution.” With the development of bioinformatics and genetic engineering, research on adaptive evolution has progressed rapidly, as have applications of the process. In this review, we summarize various mechanisms of bacterial adaptive evolution, the technologies used for studying it, and successful applications of the method in research and industry. We particularly highlight the contributions of Dr. L. O. Ingram. Microbial adaptive evolution has significant impact on our society not only from its industrial applications, but also in the evolution, emergence, and control of various pathogens.

Probiotic consumption influences universal adaptive mutations in indigenous human and mouse gut microbiota

The adaptive evolution in indigenous intestinal microbes derived from probiotics is critical to safety and efficacy evaluation of probiotics, yet it is still largely underexplored. Here, through 11 publicly accessible datasets, we demonstrated that probiotic consumption can lead to widespread single-nucleotide variants (SNVs) in the native microbiota. Interestingly, the same probiotic strains introduced far more SNVs in mouse gut than humans. Furthermore, the pattern of probiotics-induced SNVs was highly probiotic-strain specific, and 17 common SNVs in Faecalibacterium prausnitzii genome were identified cross studies, which might lead to changes in bacterial protein structure. Further, nearly 50% of F. prausnitzii SNVs can be inherited for six months in an independent human cohort, whereas the other half only transiently occurred. Collectively, our study substantially extended our understanding of co-evolution of the probiotics and the indigenous gut microbiota, highlighting the importance of assessment of probiotics efficacy and safety in an integrated manner.

Chenchen Ma, Chengcheng Zhang, and Denghui Chen et al. examine how probiotic consumption impacts gut microbiota composition in human and mice through a global, cross-cohort metagenomic analysis. Their results suggest that probiotic consumption may result in widespread variation among the native microbiota in both the human and mouse gut.

Ecologically coherent population structure of uncultivated bacterioplankton

Bacterioplankton are main drivers of biogeochemical cycles and important components of aquatic food webs. While sequencing-based studies have revealed how bacterioplankton communities are structured in time and space, relatively little is known about intraspecies diversity patterns and their ecological relevance. Here, we use the newly developed software POGENOM (POpulation GENomics from Metagenomes) to investigate genomic diversity and differentiation in metagenome-assembled genomes from the Baltic Sea, and investigate their genomic variation using metagenome data spanning a 1700 km transect and covering seasonal variation at one station. The majority of the investigated species, representing several major bacterioplankton clades, displayed population structures correlating significantly with environmental factors such as salinity and temperature. Population differentiation was more pronounced over spatial than temporal scales. We discovered genes that have undergone adaptation to different salinity regimes, potentially responsible for the populations' existence along with the salinity range. This in turn implies the broad existence of ecotypes that may remain undetected by rRNA gene sequencing. Our findings emphasize the importance of physiological barriers, and highlight the role of adaptive divergence as a structuring mechanism of bacterioplankton species.

Controlled Complexity: Optimized Systems to Study the Role of the Gut Microbiome in Host Physiology

The profound impact of the gut microbiome on host health has led to a revolution in biomedical research, motivating researchers from disparate fields to define the specific molecular mechanisms that mediate host-beneficial effects. The advent of genomic technologies allied to the use of model microbiomes in gnotobiotic mouse models has transformed our understanding of intestinal microbial ecology and the impact of the microbiome on the host. However, despite incredible advances, our understanding of the host-microbiome dialogue that shapes host physiology is still in its infancy. Progress has been limited by challenges associated with developing model systems that are both tractable enough to provide key mechanistic insights while also reflecting the enormous complexity of the gut ecosystem. Simplified model microbiomes have facilitated detailed interrogation of transcriptional and metabolic functions of the microbiome but do not recapitulate the interactions seen in complex communities. Conversely, intact complex communities from mice or humans provide a more physiologically relevant community type, but can limit our ability to uncover high-resolution insights into microbiome function. Moreover, complex microbiomes from lab-derived mice or humans often do not readily imprint human-like phenotypes. Therefore, improved model microbiomes that are highly defined and tractable, but that more accurately recapitulate human microbiome-induced phenotypic variation are required to improve understanding of fundamental processes governing host-microbiome mutualism. This improved understanding will enhance the translational relevance of studies that address how the microbiome promotes host health and influences disease states. Microbial exposures in wild mice, both symbiotic and infectious in nature, have recently been established to more readily recapitulate human-like phenotypes. The development of synthetic model communities from such "wild mice" therefore represents an attractive strategy to overcome the limitations of current approaches. Advances in microbial culturing approaches that allow for the generation of large and diverse libraries of isolates, coupled to ever more affordable large-scale genomic sequencing, mean that we are now ideally positioned to develop such systems. Furthermore, the development of sophisticated in vitro systems is allowing for detailed insights into host-microbiome interactions to be obtained. Here we discuss the need to leverage such approaches and highlight key challenges that remain to be addressed.

Infant gut strain persistence is associated with maternal origin, phylogeny, and traits including surface adhesion and iron acquisition

Gut microbiome succession affects infant development. However, it remains unclear what factors promote persistence of initial bacterial colonizers in the developing gut. Here, we perform strain-resolved analyses to compare gut colonization of preterm and full-term infants throughout the first year of life and evaluate associations between strain persistence and strain origin as well as genetic potential. Analysis of fecal metagenomes collected from 13 full-term and 9 preterm infants reveals that infants' initially distinct microbiomes converge by age 1 year. Approximately 11% of early colonizers, primarily Bacteroides and Bifidobacterium, persist during the first year of life, and those are more prevalent in full-term, compared with preterm infants. Examination of 17 mother-infant pairs reveals maternal gut strains are significantly more likely to persist in the infant gut than other strains. Enrichment in genes for surface adhesion, iron acquisition, and carbohydrate degradation may explain persistence of some strains through the first year of life.

Incongruence between dominant commensal donor microbes in recipient feces post fecal transplant and response to anti-PD-1 immunotherapy

Background

To understand inter-individual variability of fecal microbe transplantation (FMT) to enhance anti-PD-1 immunotherapy (IT) for melanoma, we analyzed the data sets from two recent publications with a microbial strain-tracking tool to determine if donor strains were dominant in the recipient feces following FMT.

Results

Analysis of the Baruch et al. data set found that the presence of commensal donor microbes in recipient feces post-FMT did not correlate with the patient response to IT. From the Davar et al., data set, we found 4 patients that responded to IT had donor’s related strain post-FMT, while 2 patients that did not respond to the IT also had donor’s strain post-FMT. Importantly, we identified no donor microbes in the feces in one recipient post-FMT that responded to IT. Furthermore, in depth analysis from two patients who responded to IT revealed both donor and recipient strains at different times post-FMT. Colonization of the gastrointestinal tract niches is important for the interaction with the host immune system. Using a separate data set, we show that mucosa from the cecum, transverse colon, and sigmoid colon share strains, providing a large reservoir of niches containing recipient microbes.

Conclusions

We demonstrated using strain-tracking analysis individual variation with the respect to the presence of fecal dominant donor microbes in the recipient following FMT that did not correlate with the response to anti-PD-1 immunotherapy. The inter-individual differences of FMT to enhance IT might be explained by the variability of the donor microbes to occupy and outcompete recipient microbes for the gastrointestinal niches. The result from our study supports the use of new approaches to clear the niches in the gastrointestinal tract to promote donor colonization to reduce inter-individual variability of IT for melanoma and potentially other cancers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02312-0.