MOCAT2: a metagenomic assembly, annotation and profiling framework

Gut microbial β-glucuronidases influence endobiotic homeostasis and are modulated by diverse therapeutics

Hormones and neurotransmitters are essential to homeostasis, and their disruptions are connected to diseases ranging from cancer to anxiety. The differential reactivation of endobiotic glucuronides by gut microbial β-glucuronidase (GUS) enzymes may influence interindividual differences in the onset and treatment of disease. Using multi-omic, in vitro, and in vivo approaches, we show that germ-free mice have reduced levels of active endobiotics and that distinct gut microbial Loop 1 and FMN GUS enzymes drive hormone and neurotransmitter reactivation. We demonstrate that a range of FDA-approved drugs prevent this reactivation by intercepting the catalytic cycle of the enzymes in a conserved fashion. Finally, we find that inhibiting GUS in conventional mice reduces free serotonin and increases its inactive glucuronide in the serum and intestines. Our results illuminate the indispensability of gut microbial enzymes in sustaining endobiotic homeostasis and indicate that therapeutic disruptions of this metabolism promote interindividual response variabilities.

Current concepts, advances, and challenges in deciphering the human microbiota with metatranscriptomics

Metatranscriptomics refers to the analysis of the collective microbial transcriptome of a sample. Its increased utilization for the characterization of human-associated microbial communities has enabled the discovery of many disease-state related microbial activities. Here, we review the principles of metatranscriptomics-based analysis of human-associated microbial samples. We describe strengths and weaknesses of popular sample preparation, sequencing, and bioinformatics approaches and summarize strategies for their use. We then discuss how human-associated microbial communities have recently been examined and how their characterization may change. We conclude that metatranscriptomics insights into human microbiotas under health and disease have not only expanded our knowledge on human health, but also opened avenues for rational antimicrobial drug use and disease management.

Taxonomic and functional profiling of fecal metagenomes for the early detection of colorectal cancer

Objectives

This study aimed to identify colorectal cancer (CRC)-associated phylogenetic and functional bacterial features by a large-scale metagenomic sequencing and develop a binomial classifier to accurately distinguish between CRC patients and healthy individuals.

Methods

We conducted shotgun metagenomic analyses of fecal samples from a ZhongShanMed discovery cohort of 121 CRC and 52 controls and SouthernMed validation cohort of 67 CRC and 44 controls. Taxonomic profiling and quantification were performed by direct sequence alignment against genome taxonomy database (GTDB). High-quality reads were also aligned to IGC datasets to obtain functional profiles defined by Kyoto Encyclopedia of Genes and Genomes (KEGG). A least absolute shrinkage and selection operator (LASSO) classifier was constructed to quantify risk scores of probability of disease and to discriminate CRC from normal for discovery, validation, Fudan, GloriousMed, and HongKong cohorts.

Results

A diverse spectrum of bacterial and fungi species were found to be either enriched (368) or reduced (113) in CRC patients (q<0.05). Similarly, metabolic functions associated with biosynthesis and metabolism of amino acids and fatty acids were significantly altered (q<0.05). The LASSO regression analysis of significant changes in the abundance of microbial species in CRC achieved areas under the receiver operating characteristic curve (AUROCs) of 0.94 and 0.91 in the ZhongShanMed and SouthernMed cohorts, respectively. A further analysis of Fudan, GloriousMed, and HK cohorts using the same classification model also demonstrated AUROC of 0.80, 0.78, and 0.91, respectively. Moreover, major CRC-associated bacterial biomarkers identified in this study were found to be coherently enriched or depleted across 10 metagenomic sequencing studies of gut microbiota.

Conclusion

A coherent signature of CRC-associated bacterial biomarkers modeled on LASSO binomial classifier maybe used accurately for early detection of CRC.

Hybridization altered the gut microbiota of pigs

Mammalian gut microbiota plays an important role in the host's nutrient metabolism, growth, and immune regulation. Hybridization can enable a progeny to acquire superior traits of the parents, resulting in the hybridization advantage. However, studies on the effects of hybridization on the pigs' gut microbiota are lacking. Therefore, this study used multi-omics technologies to compare and analyze the gut microbiota of the primary wild boar and its offspring. The 16S rRNA gene sequencing results revealed that the gut microbiota of F4 exhibited a host-like dominance phenomenon with a significant increase in the abundance of Lactobacillus and Bifidobacterium. The beta diversity of Duroc was significantly different from those of F0, F2, and F4; after the host hybridization, the similarity of the beta diversity in the progeny decreased with the decrease in the similarity of the F0 lineage. The metagenomic sequencing results showed that the significantly enriched metabolic pathways in F4, such as environmental, circulatory system, fatty acid degradation adaptation, and fatty acid biosynthesis, were similar to those in F0. Moreover, it also exhibited similar significantly enriched metabolic pathways as those in Duroc, such as carbohydrate metabolism, starch and sucrose metabolism, starch-degrading CAZymes, lactose-degrading CAZymes, and various amino acid metabolism pathways. However, the alpha-amylase-related KOs, lipid metabolism, and galactose metabolism in F4 were significantly higher than those in Duroc and F0. Non-targeted metabolome technology analysis found that several metabolites, such as docosahexaenoic acid, arachidonic acid, and citric acid were significantly enriched in the F4 pigs as compared to those in F0. Based on Spearman correlation analysis, Lactobacillus and Bifidobacterium were significantly positively correlated with these metabolites. Finally, the combined metagenomic and metabolomic analysis suggested that the metabolic pathways, such as valine, leucine, and isoleucine biosynthesis and alanine aspartate and glutamate metabolism were significantly enriched in F4 pigs. In conclusion, the gut microbiota of F4 showed a similar host "dominance" phenomenon, which provided reference data for the genetics and evolution of microbiota and the theory of microbial-assisted breeding.

Distribution and survival strategies of endemic and cosmopolitan diazotrophs in the Arctic Ocean

Dinitrogen (N₂) fixation is the major source of reactive nitrogen in the ocean and has been considered to occur specifically in low-latitude oligotrophic oceans. Recent studies have shown that N₂ fixation also occurs in the polar regions and thus is a global process, although the physiological and ecological characteristics of polar diazotrophs are not yet known. Here, we successfully reconstructed diazotroph genomes, including that of cyanobacterium UCYN-A (Candidatus 'Atelocyanobacterium thalassa'), from metagenome data corresponding to 111 samples isolated from the Arctic Ocean. These diazotrophs were highly abundant in the Arctic Ocean (max., 1.28% of the total microbial community), suggesting that they have important roles in the Arctic ecosystem and biogeochemical cycles. Further, we show that diazotrophs within genera Arcobacter, Psychromonas, and Oceanobacter are prevalent in the <0.2 µm fraction in the Arctic Ocean, indicating that current methods cannot capture their N₂ fixation. Diazotrophs in the Arctic Ocean were either Arctic-endemic or cosmopolitan species from their global distribution patterns. Arctic-endemic diazotrophs, including Arctic UCYN-A, were similar to low-latitude-endemic and cosmopolitan diazotrophs in genome-wide function, however, they had unique gene sets (e.g., diverse aromatics degradation genes), suggesting adaptations to Arctic-specific conditions. Cosmopolitan diazotrophs were generally non-cyanobacteria and commonly had the gene that encodes the cold-inducible RNA chaperone, which presumably makes their survival possible even in deep, cold waters of global ocean and polar surface waters. This study shows global distribution pattern of diazotrophs with their genomes and provides clues to answering the question of how diazotrophs can inhabit polar waters.

Reservoirs of antimicrobial resistance in the context of One Health

The emergence and spread of antimicrobial resistance (AMR) and resistant bacteria, are a global public health challenge. Through horizontal gene transfer, potential pathogens can acquire antimicrobial resistance genes (ARGs) that can subsequently be spread between human, animal, and environmental reservoirs. To understand the dissemination of ARGs and linked microbial taxa, it is necessary to map the resistome within different microbial reservoirs. By integrating knowledge on ARGs in the different reservoirs, the One Health approach is crucial to our understanding of the complex mechanisms and epidemiology of AMR. Here, we highlight the latest insights into the emergence and spread of AMR from the One Health perspective, providing a baseline of understanding for future scientific investigations into this constantly growing global health threat.

Association of gut microbiota and SCFAs with finishing weight of Diannan small ear pigs

Finishing weight is a key economic trait in the domestic pig industry. Evidence has linked the gut microbiota and SCFAs to health and production performance in pigs. Nevertheless, for Diannan small ear (DSE) pigs, a specific pig breed in China, the potential effect of gut microbiota and SCFAs on their finishing weight remains unclear. Herein, based on the data of the 16S ribosomal RNA gene and metagenomic sequencing analysis, we found that 13 OTUs could be potential biomarkers and 19 microbial species were associated with finishing weight. Among these, carbohydrate-decomposing bacteria of the families Streptococcaceae, Lactobacillaceae, and Prevotellaceae were positively related to finishing weight, whereas the microbial taxa associated with intestinal inflammation and damage exhibited opposite effects. In addition, interactions of these microbial species were found to be linked with finishing weight for the first time. Gut microbial functional annotation analysis indicated that CAZymes, such as glucosidase and glucanase could significantly affect finishing weight, given their roles in increasing nutrient absorption efficiency. Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthologies (KOs) and KEGG pathways analysis indicated that glycolysis/gluconeogenesis, phosphotransferase system (PTS), secondary bile acid biosynthesis, ABC transporters, sulfur metabolism, and one carbon pool by folate could act as key factors in regulating finishing weight. Additionally, SCFA levels, especially acetate and butyrate, had pivotal impacts on finishing weight. Finishing weight-associated species Prevotella sp. RS2, Ruminococcus sp. AF31-14BH and Lactobacillus pontis showed positive associations with butyrate concentration, and Paraprevotella xylaniphila and Bacteroides sp. OF04-15BH were positively related to acetate level. Taken together, our study provides essential knowledge for manipulating gut microbiomes to improve finishing weight. The underlying mechanisms of how gut microbiome and SCFAs modulate pigs' finishing weight required further elucidation.

Longitudinal multi-omics analyses of the gut-liver axis reveals metabolic dysregulation in hepatitis C infection and cirrhosis

The gut and liver are connected via the portal vein, and this relationship, which includes the gut microbiome, is described as the gut-liver axis. Hepatitis C virus (HCV) can infect the liver and cause fibrosis with chronic infection. HCV has been associated with an altered gut microbiome; however, how these changes impact metabolism across the gut-liver axis and how this varies with disease severity and time is unclear. Here we used multi-omics analysis of portal and peripheral blood, faeces and liver tissue to characterize the gut-liver axis of patients with HCV across a fibrosis severity gradient before (n = 29) and 6 months after (n = 23) sustained virologic response, that is, no detection of the virus. Fatty acids were the major metabolites perturbed across the liver, portal vein and gut microbiome in HCV, especially in patients with cirrhosis. Decreased fatty acid degradation by hepatic peroxisomes and mitochondria was coupled with increased free fatty acid (FFA) influx to the liver via the portal vein. Metatranscriptomics indicated that Anaerostipes hadrus-mediated fatty acid synthesis influences portal FFAs. Both microbial fatty acid synthesis and portal FFAs were associated with enhanced hepatic fibrosis. Bacteroides vulgatus-mediated intestinal glycan breakdown was linked to portal glycan products, which in turn correlated with enhanced portal inflammation in HCV. Paired comparison of patient samples at both timepoints showed that hepatic metabolism, especially in peroxisomes, is persistently dysregulated in cirrhosis independently of the virus. Sustained virologic response was associated with a potential beneficial role for Methanobrevibacter smithii, which correlated with liver disease severity markers. These results develop our understanding of the gut-liver axis in HCV and non-HCV liver disease aetiologies and provide a foundation for future therapies.

Microbiota-directed biotherapeutics: considerations for quality and functional assessment

Mounting evidence points to causative or correlative roles of gut microbiome in the development of a myriad of diseases ranging from gastrointestinal diseases, metabolic diseases to neurological disorders and cancers. Consequently, efforts have been made to develop and apply therapeutics targeting the human microbiome, in particular the gut microbiota, for treating diseases and maintaining wellness. Here we summarize the current development of gut microbiota-directed therapeutics with a focus on novel biotherapeutics, elaborate the need of advanced -omics approaches for evaluating the microbiota-type biotherapeutics, and discuss the clinical and regulatory challenges. We also discuss the development and potential application of ex vivo microbiome assays and in vitro intestinal cellular models in this context. Altogether, this review aims to provide a broad view of promises and challenges of the emerging field of microbiome-directed human healthcare.

Rationale and study protocol for a randomized controlled feeding study to determine the structural- and functional-level effects of diet-specific interventions on the gut microbiota of non-Hispanic black and white adults

BACKGROUND

Colorectal cancer (CRC), the third leading cause of cancer-related deaths in the US, has been associated with an overrepresentation or paucity of several microbial taxa in the gut microbiota, but causality has not been established. Black men and women have among the highest CRC incidence and mortality rates of any racial/ethnic group. This study will examine the impact of the Dietary Approaches to Stop Hypertension (DASH) diet on gut microbiota and fecal metabolites associated with CRC risk.

METHODS

A generally healthy sample of non-Hispanic Black and white adults (n = 112) is being recruited to participate in a parallel-arm randomized controlled feeding study. Participants are randomized to receive the DASH diet or a standard American diet for a 28-day period. Fecal samples are collected weekly throughout the study to analyze changes in the gut microbiota using 16 s rRNA and selected metagenomics. Differences in bacterial alpha and beta diversity and taxa that have been associated with CRC (Bacteroides, Fusobacterium, Clostridium, Lactobacillus, Bifidobacterium, Ruminococcus, Porphyromonas, Succinivibrio) are being evaluated. Covariate measures include body mass index, comorbidities, medication history, physical activity, stress, and demographic characteristics.

CONCLUSION

Our findings will provide preliminary evidence for the DASH diet as an approach for cultivating a healthier gut microbiota across non-Hispanic Black and non-Hispanic White adults. These results can impact clinical, translational, and population-level approaches for modification of the gut microbiota to reduce risk of chronic diseases including CRC.

TRIAL REGISTRATION

This study was registered on ClinicalTrials.gov, identifier NCT04538482, on September 4, 2020 (https://clinicaltrials.gov/ct2/show/NCT04538482).

Analysis and Interpretation of metagenomics data: an approach

Advances in next-generation sequencing technologies have accelerated the momentum of metagenomic studies, which is increasing yearly. The metagenomics field is one of the versatile applications in microbiology, where any interaction in the environment involving microorganisms can be the topic of study. Due to this versatility, the number of applications of this omics technology reached its horizons. Agriculture is a crucial sector involving crop plants and microorganisms interacting together. Hence, studying these interactions through the lenses of metagenomics would completely disclose a new meaning to crop health and development. The rhizosphere is an essential reservoir of the microbial community for agricultural soil. Hence, we focus on the R&D of metagenomic studies on the rhizosphere of crops such as rice, wheat, legumes, chickpea, and sorghum. These recent developments are impossible without the continuous advancement seen in the next-generation sequencing platforms; thus, a brief introduction and analysis of the available sequencing platforms are presented here to have a clear picture of the workflow. Concluding the topic is the discussion about different pipelines applied to analyze data produced by sequencing techniques and have a significant role in interpreting the outcome of a particular experiment. A plethora of different software and tools are incorporated in the automated pipelines or individually available to perform manual metagenomic analysis. Here we describe 8-10 advanced, efficient pipelines used for analysis that explain their respective workflows to simplify the whole analysis process.

Depression and fatigue in active IBD from a microbiome perspective-a Bayesian approach to faecal metagenomics

BACKGROUND

Extraintestinal symptoms are common in inflammatory bowel diseases (IBD) and include depression and fatigue. These are highly prevalent especially in active disease, potentially due to inflammation-mediated changes in the microbiota-gut-brain axis. The aim of this study was to investigate the associations between structural and functional microbiota characteristics and severity of fatigue and depressive symptoms in patients with active IBD.

METHODS

We included clinical data of 62 prospectively enrolled patients with IBD in an active disease state. Patients supplied stool samples and completed the questionnaires regarding depression and fatigue symptoms. Based on taxonomic and functional metagenomic profiles of faecal gut microbiota, we used Bayesian statistics to investigate the associative networks and triangle motifs between bacterial genera, functional modules and symptom severity of self-reported fatigue and depression.

RESULTS

Associations with moderate to strong evidence were found for 3 genera (Odoribacter, Anaerotruncus and Alistipes) and 3 functional modules (pectin, glycosaminoglycan and central carbohydrate metabolism) with regard to depression and for 4 genera (Intestinimonas, Anaerotruncus, Eubacterium and Clostridiales g.i.s) and 2 functional modules implicating amino acid and central carbohydrate metabolism with regard to fatigue.

CONCLUSIONS

This study provides the first evidence of association triplets between microbiota composition, function and extraintestinal symptoms in active IBD. Depression and fatigue were associated with lower abundances of short-chain fatty acid producers and distinct pathways implicating glycan, carbohydrate and amino acid metabolism. Our results suggest that microbiota-directed therapeutic approaches may reduce fatigue and depression in IBD and should be investigated in future research.

Comparison of Changes in Gut Microbiota in Wild Boars and Domestic Pigs Using 16S rRNA Gene and Metagenomics Sequencing Technologies

Simple Summary

The microbiota co-evolves with the host and plays an important role in the host's health, immunity, and nutrient absorption. Wild boars are the ancestors of domestic pigs. During the long evolutionary process, the physiological structure and living habits of modern pigs have undergone tremendous changes. However, there are few studies on the evolution of gut microbiota of wild boars and domestic pigs. In this study, by comparing the changes in the composition and function of the gut microbiota of wild boars and domestic pigs, it was found that there were significant differences between the two groups, which indicated that the gut microbiota had changed during the evolution process. This study provides some data references for the evolution of gut microbiota.

Abstract

Gut microbiota diversity is a result of co-evolution between microorganisms and their hosts. However, there are few studies on the evolution of the gut microbiota of wild boars and domestic pigs. Therefore, this study aimed to analyze the composition and function of the gut microbiota of wild boars and domestic pigs using 16S rRNA gene V3-V4 region sequencing, 16S rRNA gene full-length sequencing, and metagenomic sequencing. This study showed that after a long evolution, as compared to wild boars, the domestic pigs exhibited significantly increased relative abundances of Lactobacillus, Lactobacillus reuteri, Lactobacillus johnsonii, Lactobacillus sp.DJF_WC5, and Lactobacillus; s_uncultured bacterium, while the relative abundances of Bifidobacterium and Methanococcaceae decreased significantly. In addition, the relative abundances of “carbohydrate metabolism”, “starch and sucrose metabolism”, “valine, leucine, and isoleucine biosynthesis”, “lysine biosynthesis”, and starch-degrading CAZymes were significantly increased in the domestic pigs, while the relative abundances of “environmental adaptation”, “immune system”, “fatty acid degradation and synthesis”, and cellulose-hemicellulose-degrading CAZymes were significantly increased in the wild boars. Finally, the diversity of ARGs and the “antimicrobial resistance genes” in domestic pigs also increased significantly. This study illustrates that the gut microbiota composition and function of wild boars and domestic pigs changed during the long evolution process. These findings provide a basic research theory for the evolution of gut microbiota and the treatment of health and disease.

Gut Microbiota Composition and Metabolic Potential of Long-Living People in China

Individuals with naturally long-life spans have been extensively studied to gain a greater understanding of what factors contribute to their overall health and ability to delay or avoid certain diseases. Our previous work showed that gut microbiota can be a new avenue in healthy aging studies. In the present study, a total of 86 Chinese individuals were assigned into three groups: the long-living group (90 + years old; n = 28), the elderly group (65–75 years old; n = 31), and the young group (24–48 years old; n = 27). These groups were used to explore the composition and functional genes in the microbiota community by using the metagenomic sequencing method. We found that long-living individuals maintained high diversity in gene composition and functional profiles. Furthermore, their microbiota displays less inter-individual variation than that of elderly adults. In the taxonomic composition, it was shown that long-living people contained more short-chain fatty acid (SCFA)-producing bacteria and a decrease in certain pathogenic bacteria. Functional analysis also showed that the long-living people were enriched in metabolism metabolites methanol, trimethylamine (TMA), and CO₂ to methane, and lysine biosynthesis, but the genes related to riboflavin (vitamin B2) metabolism and tryptophan biosynthesis were significantly reduced in long-living individuals. Further, we found that long-living people with enriched SCFA- and lactic-producing bacteria and related genes, highly centered on producing key lactic acid genes (ldhA) and the genes of lysine that are metabolized to the butyrate pathway. In addition, we compared the gut microbiota signatures of longevity in different regions and found that the composition of the gut microbiota of the long-lived Chinese and Italian people was quite different, but both groups were enriched in genes related to methane production and glucose metabolism. In terms of SCFA metabolism, the Chinese long-living people were enriched with bacteria and genes related to butyric acid production, while the Italian long-living people were enriched with more acetic acid-related genes. These findings suggest that the gut microbiota of Chinese long-living individuals include more SCFA-producing bacteria and genes, metabolizes methanol, TMA, and CO₂, and contains fewer pathogenic bacteria, thereby potentially contributing to the healthy aging of humans.

Potential of Meta-Omics to Provide Modern Microbial Indicators for Monitoring Soil Quality and Securing Food Production

Soils are fundamental resources for agricultural production and play an essential role in food security. They represent the keystone of the food value chain because they harbor a large fraction of biodiversity—the backbone of the regulation of ecosystem services and “soil health” maintenance. In the face of the numerous causes of soil degradation such as unsustainable soil management practices, pollution, waste disposal, or the increasing number of extreme weather events, it has become clear that (i) preserving the soil biodiversity is key to food security, and (ii) biodiversity-based solutions for environmental monitoring have to be developed. Within the soil biodiversity reservoir, microbial diversity including Archaea, Bacteria, Fungi and protists is essential for ecosystem functioning and resilience. Microbial communities are also sensitive to various environmental drivers and to management practices; as a result, they are ideal candidates for monitoring soil quality assessment. The emergence of meta-omics approaches based on recent advances in high-throughput sequencing and bioinformatics has remarkably improved our ability to characterize microbial diversity and its potential functions. This revolution has substantially filled the knowledge gap about soil microbial diversity regulation and ecology, but also provided new and robust indicators of agricultural soil quality. We reviewed how meta-omics approaches replaced traditional methods and allowed developing modern microbial indicators of the soil biological quality. Each meta-omics approach is described in its general principles, methodologies, specificities, strengths and drawbacks, and illustrated with concrete applications for soil monitoring. The development of metabarcoding approaches in the last 20 years has led to a collection of microbial indicators that are now operational and available for the farming sector. Our review shows that despite the recent huge advances, some meta-omics approaches (e.g., metatranscriptomics or meta-proteomics) still need developments to be operational for environmental bio-monitoring. As regards prospects, we outline the importance of building up repositories of soil quality indicators. These are essential for objective and robust diagnosis, to help actors and stakeholders improve soil management, with a view to or to contribute to combining the food and environmental quality of next-generation farming systems in the context of the agroecological transition.

The OceanDNA MAG catalog contains over 50,000 prokaryotic genomes originated from various marine environments

Marine microorganisms are immensely diverse and play fundamental roles in global geochemical cycling. Recent metagenome-assembled genome studies, with particular attention to large-scale projects such as Tara Oceans, have expanded the genomic repertoire of marine microorganisms. However, published marine metagenome data is still underexplored. We collected 2,057 marine metagenomes covering various marine environments and developed a new genome reconstruction pipeline. We reconstructed 52,325 qualified genomes composed of 8,466 prokaryotic species-level clusters spanning 59 phyla, including genomes from the deep-sea characterized as deeper than 1,000 m (n = 3,337), low-oxygen zones of <90 μmol O2 per kg water (n = 7,884), and polar regions (n = 7,752). Novelty evaluation using a genome taxonomy database shows that 6,256 species (73.9%) are novel and include genomes of high taxonomic novelty, such as new class candidates. These genomes collectively expanded the known phylogenetic diversity of marine prokaryotes by 34.2%, and the species representatives cover 26.5–42.0% of prokaryote-enriched metagenomes. Thoroughly leveraging accumulated metagenomic data, this genome resource, named the OceanDNA MAG catalog, illuminates uncharacterized marine microbial ‘dark matter’ lineages.

Measurement(s)	microbial community
Technology Type(s)	marine metagenome
Sample Characteristic - Organism	Bacteria • Archaea
Sample Characteristic - Environment	marine biome

Taxonomic and functional alterations in the salivary microbiota of children with and without severe early childhood caries (S-ECC) at the age of 3

Background

Primary dental caries is the most prevalent oral disease among preschool children, which can cause severe damage to teeth and even affect the mental well-being of children. Various studies have demonstrated that the oral microbiome plays a pivotal role in the onset and development of dental caries. However, it remains uncertain about the key microbial markers associated with caries, owing to the limited evidence.

Methods

Fifteen S-ECC children and fifteen healthy controls were selected from three-year-old children in this study. Their clinical data and oral saliva samples were collected. Shotgun sequencing was conducted to investigate the microbial differences and the relevant functions between the two groups.

Results

We observed no apparent difference in oral microbial community diversity between the two groups. Still, at the genus/species levels, several characteristic genera/species such as Propionibacterium, Propionibacterium acidifaciens, Prevotella denticola, Streptococcus mutans and Actinomyces sp. oral taxon 448/414 increased significantly in S-ECC children, compared with the oral health group. Furthermore, we found that functional pathways involving glycolysis and acid production, such as starch and sucrose metabolism, fructose and mannose metabolism, glycolysis/gluconeogenesis, were prominently up-regulated in the high-caries group.

Conclusions

Our study showed that dental caries in children were associated with the alterations in the oral microbiota at the composition and functional levels, which may potentially inspire the exploration of microbial diagnosis or therapeutic treatments.

Enterobacteriaceae and Bacteroidaceae provide resistance to travel-associated intestinal colonization by multi-drug resistant Escherichia coli

Previous studies have shown high acquisition risks of extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-E) among international travelers visiting antimicrobial resistance (AMR) hotspots. Although antibiotic use and travelers' diarrhea have shown to influence the ESBL-E acquisition risk, it remains largely unknown whether successful colonization of ESBL-E during travel is associated with the composition, functional capacity and resilience of the traveler's microbiome. The microbiome of pre- and post-travel fecal samples from 190 international travelers visiting Africa or Asia was profiled using whole metagenome shotgun sequencing. A metagenomics species concept approach was used to determine the microbial composition, population diversity and functional capacity before travel and how it is altered longitudinally. Eleven travelers were positive for ESBL-E before travel and removed from the analysis. Neither the microbial richness (Chao1), diversity (effective Shannon) and community structure (Bray-Curtis dissimilarity) in pretravel samples nor the longitudinal change of these metrics during travel were predictive for ESBL-E acquisition. A zero-inflated two-step beta-regression model was used to determine how the longitudinal change in both prevalence and abundance of each taxon was related to ESBL acquisition. There were detected increases in both the prevalence and abundance of Citrobacter freundii and two members of the genus Bacteroides, in association with remaining uncolonized by ESBL-E. These results highlight the potential of these individual microbes as a microbial consortium to prevent the acquisition of ESBL-E. The ability to alter a person's colonization resistance to a bacterium could be key to intervention strategies that aim to minimize the spread of MDR bacteria.

Metagenomics combined with activity-based proteomics point to gut bacterial enzymes that reactivate mycophenolate

Mycophenolate mofetil (MMF) is an important immunosuppressant prodrug prescribed to prevent organ transplant rejection and to treat autoimmune diseases. MMF usage, however, is limited by severe gastrointestinal toxicity that is observed in approximately 45% of MMF recipients. The active form of the drug, mycophenolic acid (MPA), undergoes extensive enterohepatic recirculation by bacterial β-glucuronidase (GUS) enzymes, which reactivate MPA from mycophenolate glucuronide (MPAG) within the gastrointestinal tract. GUS enzymes demonstrate distinct substrate preferences based on their structural features, and gut microbial GUS enzymes that reactivate MPA have not been identified. Here, we compare the fecal microbiomes of transplant recipients receiving MMF to healthy individuals using shotgun metagenomic sequencing. We find that neither microbial composition nor the presence of specific structural classes of GUS genes are sufficient to explain the differences in MPA reactivation measured between fecal samples from the two cohorts. We next employed a GUS-specific activity-based chemical probe and targeted metaproteomics to identify and quantify the GUS proteins present in the human fecal samples. The identification of specific GUS enzymes was improved by using the metagenomics data collected from the fecal samples. We found that the presence of GUS enzymes that bind the flavin mononucleotide (FMN) is significantly correlated with efficient MPA reactivation. Furthermore, structural analysis identified motifs unique to these FMN-binding GUS enzymes that provide molecular support for their ability to process this drug glucuronide. These results indicate that FMN-binding GUS enzymes may be responsible for reactivation of MPA and could be a driving force behind MPA-induced GI toxicity.

Variation and transmission of the human gut microbiota across multiple familial generations

Although the composition and functional potential of the human gut microbiota evolve over the lifespan, kinship has been identified as a key covariate of microbial community diversification. However, to date, sharing of microbiota features within families has mostly been assessed between parents and their direct offspring. Here we investigate the potential transmission and persistence of familial microbiome patterns and microbial genotypes in a family cohort (n = 102) spanning 3 to 5 generations over the same female bloodline. We observe microbiome community composition associated with kinship, with seven low abundant genera displaying familial distribution patterns. While kinship and current cohabitation emerge as closely entangled variables, our explorative analyses of microbial genotype distribution and transmission estimates point at the latter as a key covariate of strain dissemination. Highest potential transmission rates are estimated between sisters and mother-daughter pairs, decreasing with increasing daughter's age and being higher among cohabiting pairs than those living apart. Although rare, we detect potential transmission events spanning three and four generations, primarily involving species of the genera Alistipes and Bacteroides. Overall, while our analyses confirm the existence of family-bound microbiome community profiles, transmission or co-acquisition of bacterial strains appears to be strongly linked to cohabitation.

Combinatorial, additive and dose-dependent drug-microbiome associations

During the transition from a healthy state to cardiometabolic disease, patients become heavily medicated, which leads to an increasingly aberrant gut microbiome and serum metabolome, and complicates biomarker discovery^1-5. Here, through integrated multi-omics analyses of 2,173 European residents from the MetaCardis cohort, we show that the explanatory power of drugs for the variability in both host and gut microbiome features exceeds that of disease. We quantify inferred effects of single medications, their combinations as well as additive effects, and show that the latter shift the metabolome and microbiome towards a healthier state, exemplified in synergistic reduction in serum atherogenic lipoproteins by statins combined with aspirin, or enrichment of intestinal Roseburia by diuretic agents combined with beta-blockers. Several antibiotics exhibit a quantitative relationship between the number of courses prescribed and progression towards a microbiome state that is associated with the severity of cardiometabolic disease. We also report a relationship between cardiometabolic drug dosage, improvement in clinical markers and microbiome composition, supporting direct drug effects. Taken together, our computational framework and resulting resources enable the disentanglement of the effects of drugs and disease on host and microbiome features in multimedicated individuals. Furthermore, the robust signatures identified using our framework provide new hypotheses for drug-host-microbiome interactions in cardiometabolic disease.

Fecal Microbiome Composition Does Not Predict Diet-Induced TMAO Production in Healthy Adults

Background Trimethylamine-N-oxide (TMAO) is a small molecule derived from the metabolism of dietary nutrients by gut microbes and contributes to cardiovascular disease. Plasma TMAO increases following consumption of red meat. This metabolic change is thought to be partly because of the expansion of gut microbes able to use nutrients abundant in red meat. Methods and Results We used data from a randomized crossover study to estimate the degree to which TMAO can be estimated from fecal microbial composition. Healthy participants received a series of 3 diets that differed in protein source (red meat, white meat, and non-meat), and fecal, plasma, and urine samples were collected following 4 weeks of exposure to each diet. TMAO was quantitated in plasma and urine, while shotgun metagenomic sequencing was performed on fecal DNA. While the cai gene cluster was weakly correlated with plasma TMAO (rho=0.17, P=0.0007), elastic net models of TMAO were not improved by abundances of bacterial genes known to contribute to TMAO synthesis. A global analysis of all taxonomic groups, genes, and gene families found no meaningful predictors of TMAO. We postulated that abundances of known genes related to TMAO production do not predict bacterial metabolism, and we measured choline- and carnitine-trimethylamine lyase activity during fecal culture. Trimethylamine lyase genes were only weakly correlated with the activity of the enzymes they encode. Conclusions Fecal microbiome composition does not predict systemic TMAO because, in this case, gene copy number does not predict bacterial metabolic activity. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT01427855.

Unravelling the collateral damage of antibiotics on gut bacteria

Antibiotics are used to fight pathogens but also target commensal bacteria, disturbing the composition of gut microbiota and causing dysbiosis and disease1. Despite this well-known collateral damage, the activity spectrum of different antibiotic classes on gut bacteria remains poorly characterized. Here we characterize further 144 antibiotics from a previous screen of more than 1,000 drugs on 38 representative human gut microbiome species2. Antibiotic classes exhibited distinct inhibition spectra, including generation dependence for quinolones and phylogeny independence for β-lactams. Macrolides and tetracyclines, both prototypic bacteriostatic protein synthesis inhibitors, inhibited nearly all commensals tested but also killed several species. Killed bacteria were more readily eliminated from in vitro communities than those inhibited. This species-specific killing activity challenges the long-standing distinction between bactericidal and bacteriostatic antibiotic classes and provides a possible explanation for the strong effect of macrolides on animal3-5 and human6,7 gut microbiomes. To mitigate this collateral damage of macrolides and tetracyclines, we screened for drugs that specifically antagonized the antibiotic activity against abundant Bacteroides species but not against relevant pathogens. Such antidotes selectively protected Bacteroides species from erythromycin treatment in human-stool-derived communities and gnotobiotic mice. These findings illluminate the activity spectra of antibiotics in commensal bacteria and suggest strategies to circumvent their adverse effects on the gut microbiota.

The endophytome (plant-associated microbiome): methodological approaches, biological aspects, and biotech applications

Similar to other organisms, plants establish interactions with a variety of microorganisms in their natural environment. The plant microbiome occupies the host plant's tissues, either internally or on its surfaces, showing interactions that can assist in its growth, development, and adaptation to face environmental stresses. The advance of metagenomics and metatranscriptomics approaches has strongly driven the study and recognition of plant microbiome impacts. Research in this regard provides comprehensive information about the taxonomic and functional aspects of microbial plant communities, contributing to a better understanding of their dynamics. Evidence of the plant microbiome's functional potential has boosted its exploitation to develop more ecological and sustainable agricultural practices that impact human health. Although microbial inoculants' development and use are promising to revolutionize crop production, interdisciplinary studies are needed to identify new candidates and promote effective practical applications. On the other hand, there are challenges in understanding and analyzing complex data generated within a plant microbiome project's scope. This review presents aspects about the complex structuring and assembly of the microbiome in the host plant's tissues, metagenomics, and metatranscriptomics approaches for its understanding, covering descriptions of recent studies concerning metagenomics to characterize the microbiome of non-model plants under different aspects. Studies involving bio-inoculants, isolated from plant microbial communities, capable of assisting in crops' productivity, are also reviewed.

Music of metagenomics-a review of its applications, analysis pipeline, and associated tools

This humble effort highlights the intricate details of metagenomics in a simple, poetic, and rhythmic way. The paper enforces the significance of the research area, provides details about major analytical methods, examines the taxonomy and assembly of genomes, emphasizes some tools, and concludes by celebrating the richness of the ecosystem populated by the "metagenome."

Effects of gut microbiota and fatty acid metabolism on dyslipidemia following weight-loss diets in women: Results from a randomized controlled trial

BACKGROUND & AIMS

In our early feeding trial among overweight and obese Chinese women, both low-carbohydrate (LC) and calorie-restricted (CR) diets reduced weight and fat mass, but only the LC diet significantly improved dyslipidemia. We aimed to investigate the impacts of altered gut microbiota, fatty acid (FAs), and acylcarnitines, markers of mitochondrial function on blood lipids.

METHODS

Fecal and blood samples from 48 participants at baseline and the end of a 12-week trial were used to perform metagenomics and targeted-metabolomics including erythrocyte FAs and plasma acylcarnitines, respectively.

RESULTS

The two diets altered microbial structure and co-abundance gene clusters (CAGs) at different magnitudes. After a 12-week intervention, the Bacteroidetes/Firmicutes ratio increased significantly in the LC diet (P = 0.015) but not in the CR diet, which only showed an increased trend (P = 0.28). At the microbial function level, the LC group showed lower branched-chain amino acid biosynthesis and higher serine biosynthesis than the CR group. Moreover, the LC diet reduced levels of 14:0 and 16:1n-7 FAs in the de novo lipogenesis pathway, but increased 20:5n-3 compared with the CR diet. Both groups had increased plasma acylcarnitines except that the LC group had larger elevated short-chain acylcarnitines. After backward stepwise selection, a cluster of changed CAGs, FAs and acylcarnitines were found to be associated with improved lipid profile. However, changed CAGs showed higher contribution rates in elevating HDL-cholesterol (81.6%) and reducing triglycerides (89.3%) than changed FAs and acylcarnitines.

CONCLUSIONS

The two weight-loss diets induced different changes of gut microbiota, plasma acylcarnitines, and erythrocyte FAs. Changes in gut microbiota rather than FA or acylcarnitine profiles showed greater contribution to improved lipid profile in these overweight and obese Chinese women.

TRIAL REGISTRATION

The trial was registered at http://clinicaltrials.gov/show/NCT01358890.

Probiotics maintain the gut microbiome homeostasis during Indian Antarctic expedition by ship

Ship voyage to Antarctica is a stressful journey for expedition members. The response of human gut microbiota to ship voyage and a feasible approach to maintain gut health, is still unexplored. The present findings describe a 24-day long longitudinal study involving 19 members from 38th Indian Antarctic Expedition, to investigate the impact of ship voyage and effect of probiotic intervention on gut microbiota. Fecal samples collected on day 0 as baseline and at the end of ship voyage (day 24), were analyzed using whole genome shotgun sequencing. Probiotic intervention reduced the sea sickness by 10% compared to 44% in placebo group. The gut microbiome in placebo group members on day 0 and day 24, indicated significant alteration compared to a marginal change in the microbial composition in probiotic group. Functional analysis revealed significant alterations in carbohydrate and amino acid metabolism. Carbohydrate-active enzymes analysis represented functional genes involved in glycoside hydrolases, glycosyltransferases and carbohydrate binding modules, for maintaining gut microbiome homeostasis. Suggesting thereby the possible mechanism of probiotic in stabilizing and restoring gut microflora during stressful ship journey. The present study is first of its kind, providing a feasible approach for protecting gut health during Antarctic expedition involving ship voyage.

Characterization of Shallow Whole-Metagenome Shotgun Sequencing as a High-Accuracy and Low-Cost Method by Complicated Mock Microbiomes

Characterization of the bacterial composition and functional repertoires of microbiome samples is the most common application of metagenomics. Although deep whole-metagenome shotgun sequencing (WMS) provides high taxonomic resolution, it is generally cost-prohibitive for large longitudinal investigations. Until now, 16S rRNA gene amplicon sequencing (16S) has been the most widely used approach and usually cooperates with WMS to achieve cost-efficiency. However, the accuracy of 16S results and its consistency with WMS data have not been fully elaborated, especially by complicated microbiomes with defined compositional information. Here, we constructed two complex artificial microbiomes, which comprised more than 60 human gut bacterial species with even or varied abundance. Utilizing real fecal samples and mock communities, we provided solid evidence demonstrating that 16S results were of poor consistency with WMS data, and its accuracy was not satisfactory. In contrast, shallow whole-metagenome shotgun sequencing (shallow WMS, S-WMS) with a sequencing depth of 1 Gb provided outputs that highly resembled WMS data at both genus and species levels and presented much higher accuracy taxonomic assignments and functional predictions than 16S, thereby representing a better and cost-efficient alternative to 16S for large-scale microbiome studies.

The maintenance of microbial community in human fecal samples by a cost effective preservation buffer

In the burgeoning microbiome field, powerful sequencing approaches and accompanied bioanalytical methods have made tremendous contributions to the discoveries of breakthroughs, which favor to unravel the intimate interplay between gut microbiota and human health. The proper preservation of samples before being processed is essential to guarantee the authenticity and reliability of microbiome studies. Hence, the development of preservation methods is extremely important to hold samples eligible for the consequent analysis, especially population cohort-based investigations or those spanning species or geography, which frequently facing difficulties in suppling freezing conditions. Although there are several commercial products available, the exploration of cost-efficient and ready-to-use preservation methods are still in a large demand. Here, we performed shotgun metagenomic sequencing and demonstrated that microbial consortia in human fecal samples were substantially preserved within a temporary storage of 4 h, independent of the storage temperature. We also verified a previous reported self-made preservation buffer (PB buffer) could not only preserve fecal microbiota at room temperature up to 4 weeks but also enable samples to endure a high temperature condition which mimics temperature variations in summer logistics. Moreover, PB buffer exhibited suitability for human saliva as well. Collectively, PB buffer may be a valuable choice to stabilize samples if neither freezing facilities nor liquid nitrogen is available.

A guide to human microbiome research: study design, sample collection, and bioinformatics analysis

The purpose of this review is to provide medical researchers, especially those without a bioinformatics background, with an easy-to-understand summary of the concepts and technologies used in microbiome research. First, we define primary concepts such as microbiota, microbiome, and metagenome. Then, we discuss study design schemes, the methods of sample size calculation, and the methods for improving the reliability of research. We emphasize the importance of negative and positive controls in this section. Next, we discuss statistical analysis methods used in microbiome research, focusing on problems with multiple comparisons and ways to compare β-diversity between groups. Finally, we provide step-by-step pipelines for bioinformatics analysis. In summary, the meticulous study design is a key step to obtaining meaningful results, and appropriate statistical methods are important for accurate interpretation of microbiome data. The step-by-step pipelines provide researchers with insights into newly developed bioinformatics analysis methods.

Microbiota-associated risk factors for asymptomatic gut colonisation with multi-drug-resistant organisms in a Dutch nursing home

Background

Nursing home residents have increased rates of intestinal colonisation with multidrug-resistant organisms (MDROs). We assessed the colonisation and spread of MDROs among this population, determined clinical risk factors for MDRO colonisation and investigated the role of the gut microbiota in providing colonisation resistance against MDROs.

Methods

We conducted a prospective cohort study in a Dutch nursing home. Demographical, epidemiological and clinical data were collected at four time points with 2-month intervals (October 2016–April 2017). To obtain longitudinal data, faecal samples from residents were collected for at least two time points. Ultimately, twenty-seven residents were included in the study and 93 faecal samples were analysed, of which 27 (29.0%) were MDRO-positive. Twelve residents (44.4%) were colonised with an MDRO at at least one time point throughout the 6-month study.

Results

Univariable generalised estimating equation logistic regression indicated that antibiotic use in the previous 2 months and hospital admittance in the previous year were associated with MDRO colonisation. Characterisation of MDRO isolates through whole-genome sequencing revealed Escherichia coli sequence type (ST)131 to be the most prevalent MDRO and ward-specific clusters of E. coli ST131 were identified. Microbiota analysis by 16S rRNA gene amplicon sequencing revealed no differences in alpha or beta diversity between MDRO-positive and negative samples, nor between residents who were ever or never colonised. Three bacterial taxa (Dorea, Atopobiaceae and Lachnospiraceae ND3007 group) were more abundant in residents never colonised with an MDRO throughout the 6-month study. An unexpectedly high abundance of Bifidobacterium was observed in several residents. Further investigation of a subset of samples with metagenomics showed that various Bifidobacterium species were highly abundant, of which B. longum strains remained identical within residents over time, but were different between residents.

Conclusions

Our study provides new evidence for the role of the gut microbiota in colonisation resistance against MDROs in the elderly living in a nursing home setting. Dorea, Atopobiaceae and Lachnospiraceae ND3007 group may be associated with protection against MDRO colonisation. Furthermore, we report a uniquely high abundance of several Bifidobacterium species in multiple residents and excluded the possibility that this was due to probiotic supplementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00869-z.

Microbiome meta-analysis and cross-disease comparison enabled by the SIAMCAT machine learning toolbox

The human microbiome is increasingly mined for diagnostic and therapeutic biomarkers using machine learning (ML). However, metagenomics-specific software is scarce, and overoptimistic evaluation and limited cross-study generalization are prevailing issues. To address these, we developed SIAMCAT, a versatile R toolbox for ML-based comparative metagenomics. We demonstrate its capabilities in a meta-analysis of fecal metagenomic studies (10,803 samples). When naively transferred across studies, ML models lost accuracy and disease specificity, which could however be resolved by a novel training set augmentation strategy. This reveals some biomarkers to be disease-specific, with others shared across multiple conditions. SIAMCAT is freely available from siamcat.embl.de .

Strain-Resolved Dynamics of the Lung Microbiome in Patients with Cystic Fibrosis

Cystic fibrosis patients frequently suffer from recurring respiratory infections caused by colonizing pathogenic and commensal bacteria. Although modern therapies can sometimes alleviate respiratory symptoms by ameliorating residual function of the protein responsible for the disorder, management of chronic respiratory infections remains an issue.

In cystic fibrosis, dynamic and complex communities of microbial pathogens and commensals can colonize the lung. Cultured isolates from lung sputum reveal high inter- and intraindividual variability in pathogen strains, sequence variants, and phenotypes; disease progression likely depends on the precise combination of infecting lineages. Routine clinical protocols, however, provide a limited overview of the colonizer populations. Therefore, a more comprehensive and precise identification and characterization of infecting lineages could assist in making corresponding decisions on treatment. Here, we describe longitudinal tracking for four cystic fibrosis patients who exhibited extreme clinical phenotypes and, thus, were selected from a pilot cohort of 11 patients with repeated sampling for more than a year. Following metagenomics sequencing of lung sputum, we find that the taxonomic identity of individual colonizer lineages can be easily established. Crucially, even superficially clonal pathogens can be subdivided into multiple sublineages at the sequence level. By tracking individual allelic differences over time, an assembly-free clustering approach allows us to reconstruct multiple lineage-specific genomes with clear structural differences. Our study showcases a culture-independent shotgun metagenomics approach for longitudinal tracking of sublineage pathogen dynamics, opening up the possibility of using such methods to assist in monitoring disease progression through providing high-resolution routine characterization of the cystic fibrosis lung microbiome.

A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog

The human gut microbiota performs functions that are essential for the maintenance of the host physiology. However, characterizing the functioning of microbial communities in relation to the host remains challenging in reference-based metagenomic analyses. Indeed, as taxonomic and functional analyses are performed independently, the link between genes and species remains unclear. Although a first set of species-level bins was built by clustering co-abundant genes, no reference bin set is established on the most used gut microbiota catalog, the Integrated Gene Catalog (IGC). With the aim to identify the best suitable method to group the IGC genes, we benchmarked nine taxonomy-independent binners implementing abundance-based, hybrid and integrative approaches. To this purpose, we designed a simulated non-redundant gene catalog (SGC) and computed adapted assessment metrics. Overall, the best trade-off between the main metrics is reached by an integrative binner. For each approach, we then compared the results of the best-performing binner with our expected community structures and applied the method to the IGC. The three approaches are distinguished by specific advantages, and by inherent or scalability limitations. Hybrid and integrative binners show promising and potentially complementary results but require improvements to be used on the IGC to recover human gut microbial species.

PathoFact: a pipeline for the prediction of virulence factors and antimicrobial resistance genes in metagenomic data

BACKGROUND

Pathogenic microorganisms cause disease by invading, colonizing, and damaging their host. Virulence factors including bacterial toxins contribute to pathogenicity. Additionally, antimicrobial resistance genes allow pathogens to evade otherwise curative treatments. To understand causal relationships between microbiome compositions, functioning, and disease, it is essential to identify virulence factors and antimicrobial resistance genes in situ. At present, there is a clear lack of computational approaches to simultaneously identify these factors in metagenomic datasets.

RESULTS

Here, we present PathoFact, a tool for the contextualized prediction of virulence factors, bacterial toxins, and antimicrobial resistance genes with high accuracy (0.921, 0.832 and 0.979, respectively) and specificity (0.957, 0.989 and 0.994). We evaluate the performance of PathoFact on simulated metagenomic datasets and perform a comparison to two other general workflows for the analysis of metagenomic data. PathoFact outperforms all existing workflows in predicting virulence factors and toxin genes. It performs comparably to one pipeline regarding the prediction of antimicrobial resistance while outperforming the others. We further demonstrate the performance of PathoFact on three publicly available case-control metagenomic datasets representing an actual infection as well as chronic diseases in which either pathogenic potential or bacterial toxins are hypothesized to play a role. In each case, we identify virulence factors and AMR genes which differentiated between the case and control groups, thereby revealing novel gene associations with the studied diseases.

CONCLUSION

PathoFact is an easy-to-use, modular, and reproducible pipeline for the identification of virulence factors, bacterial toxins, and antimicrobial resistance genes in metagenomic data. Additionally, our tool combines the prediction of these pathogenicity factors with the identification of mobile genetic elements. This provides further depth to the analysis by considering the genomic context of the pertinent genes. Furthermore, PathoFact's modules for virulence factors, toxins, and antimicrobial resistance genes can be applied independently, thereby making it a flexible and versatile tool. PathoFact, its models, and databases are freely available at https://pathofact.lcsb.uni.lu . Video abstract.

Gut microbiota in healthy and unhealthy long-living people

The human gut microbiota in long-living people has been characterized, however, its metabolic potential is still largely unknown in this group. In this study, the gut microbiota was assessed in 37 Chinese long-living participants (aged 90 + years) by metagenomic sequencing of stool samples. Participants were categorized into two groups, healthy long-living (n = 28) and unhealthy long-living (n = 9). Gut microbiota composition and function were compared among these two groups. We found that the gut microbiota in the healthy long-living group was significantly separated from the unhealthy group. The healthy long-living group contained a higher abundance of Bacteroidetes and more functional pathways in energy metabolism, glycan biosynthesis and metabolism, metabolism of cofactors and vitamins, and biosynthesis of other secondary metabolites. The unhealthy group contained a higher abundance of Streptococcus and other pathogenic bacteria, and also contained more functional pathways for xenobiotics biodegradation and metabolism than the healthy group. Additionally, the unhealthy group had decreased levels of carbohydrate-active enzymes, including host-glycan and fiber degrading enzymes, and an increase in starch-degrading enzymes. In conclusion, the gut microbiota of unhealthy long-living people contains more pathogenic bacteria, and the overall gut microbiota may be in an unhealthy state, "dysbiosis", which leads to a decrease in carbohydrate digestion, glycan and thiamine (B1) metabolites, and fatty acid biosynthesis.

Guild-based analysis for understanding gut microbiome in human health and diseases

To demonstrate the causative role of gut microbiome in human health and diseases, we first need to identify, via next-generation sequencing, potentially important functional members associated with specific health outcomes and disease phenotypes. However, due to the strain-level genetic complexity of the gut microbiota, microbiome datasets are highly dimensional and highly sparse in nature, making it challenging to identify putative causative agents of a particular disease phenotype. Members of an ecosystem seldomly live independently from each other. Instead, they develop local interactions and form inter-member organizations to influence the ecosystem's higher-level patterns and functions. In the ecological study of macro-organisms, members are defined as belonging to the same "guild" if they exploit the same class of resources in a similar way or work together as a coherent functional group. Translating the concept of "guild" to the study of gut microbiota, we redefine guild as a group of bacteria that show consistent co-abundant behavior and likely to work together to contribute to the same ecological function. In this opinion article, we discuss how to use guilds as the aggregation unit to reduce dimensionality and sparsity in microbiome-wide association studies for identifying candidate gut bacteria that may causatively contribute to human health and diseases.

Linking Gut Microbiome and Lipid Metabolism: Moving beyond Associations

Various studies aiming to elucidate the role of the gut microbiome-metabolome co-axis in health and disease have primarily focused on water-soluble polar metabolites, whilst non-polar microbial lipids have received less attention. The concept of microbiota-dependent lipid biotransformation is over a century old. However, only recently, several studies have shown how microbial lipids alter intestinal and circulating lipid concentrations in the host, thus impacting human lipid homeostasis. There is emerging evidence that gut microbial communities play a particularly significant role in the regulation of host cholesterol and sphingolipid homeostasis. Here, we review and discuss recent research focusing on microbe-host-lipid co-metabolism. We also discuss the interplay of human gut microbiota and molecular lipids entering host systemic circulation, and its role in health and disease.

Combined whole cell wall analysis and streamlined in silico carbohydrate-active enzyme discovery to improve biocatalytic conversion of agricultural crop residues

The production of biofuels as an efficient source of renewable energy has received considerable attention due to increasing energy demands and regulatory incentives to reduce greenhouse gas emissions. Second-generation biofuel feedstocks, including agricultural crop residues generated on-farm during annual harvests, are abundant, inexpensive, and sustainable. Unlike first-generation feedstocks, which are enriched in easily fermentable carbohydrates, crop residue cell walls are highly resistant to saccharification, fermentation, and valorization. Crop residues contain recalcitrant polysaccharides, including cellulose, hemicelluloses, pectins, and lignin and lignin-carbohydrate complexes. In addition, their cell walls can vary in linkage structure and monosaccharide composition between plant sources. Characterization of total cell wall structure, including high-resolution analyses of saccharide composition, linkage, and complex structures using chromatography-based methods, nuclear magnetic resonance, -omics, and antibody glycome profiling, provides critical insight into the fine chemistry of feedstock cell walls. Furthermore, improving both the catalytic potential of microbial communities that populate biodigester reactors and the efficiency of pre-treatments used in bioethanol production may improve bioconversion rates and yields. Toward this end, knowledge and characterization of carbohydrate-active enzymes (CAZymes) involved in dynamic biomass deconstruction is pivotal. Here we overview the use of common "-omics"-based methods for the study of lignocellulose-metabolizing communities and microorganisms, as well as methods for annotation and discovery of CAZymes, and accurate prediction of CAZyme function. Emerging approaches for analysis of large datasets, including metagenome-assembled genomes, are also discussed. Using complementary glycomic and meta-omic methods to characterize agricultural residues and the microbial communities that digest them provides promising streams of research to maximize value and energy extraction from crop waste streams.

Effect of host breeds on gut microbiome and serum metabolome in meat rabbits

BACKGROUND

Gut microbial compositional and functional variation can affect health and production performance of farm animals. Analysing metabolites in biological samples provides information on the basic mechanisms that affect the well-being and production traits in farm animals. However, the extent to which host breeds affect the gut microbiome and serum metabolome in meat rabbits is still unknown. In this study, the differences in phylogenetic composition and functional capacities of gut microbiota in two commercial rabbit breeds Elco and Ira were determined by 16S rRNA gene and metagenomic sequencing. The alternations in serum metabolome in the two rabbit breeds were detected using ultra-performance liquid chromatography system coupled with quadrupole time of flight mass spectrometry (UPLC-QTOFMS).

RESULTS

Sequencing results revealed that there were significant differences in the gut microbiota of the two breeds studied, suggesting that host breeds affect structure and diversity of gut microbiota. Numerous breed-associated microorganisms were identified at different taxonomic levels and most microbial taxa belonged to the families Lachnospiraceae and Ruminococcaceae. In particular, several short-chain fatty acids (SCFAs) producing species including Coprococcus comes, Ruminococcus faecis, Ruminococcus callidus, and Lachnospiraceae bacterium NK4A136 could be considered as biomarkers for improving the health and production performance in meat rabbits. Additionally, gut microbial functional capacities related to bacterial chemotaxis, ABC transporters, and metabolism of different carbohydrates, amino acids, and lipids varied greatly between rabbit breeds. Several fatty acids, amino acids, and organic acids in the serum were identified as breed-associated, where certain metabolites could be regarded as biomarkers correlated with the well-being and production traits of meat rabbits. Correlation analysis between breed-associated microbial species and serum metabolites revealed significant co-variations, indicating the existence of cross-talk among host-gut microbiome-serum metabolome.

CONCLUSIONS

Our study provides insight into how gut microbiome and serum metabolome of meat rabbits are affected by host breeds and uncovers potential biomarkers important for breed improvement of meat rabbits.

CAMAMED: a pipeline for composition-aware mapping-based analysis of metagenomic data

Metagenomics is the study of genomic DNA recovered from a microbial community. Both assembly-based and mapping-based methods have been used to analyze metagenomic data. When appropriate gene catalogs are available, mapping-based methods are preferred over assembly based approaches, especially for analyzing the data at the functional level. In this study, we introduce CAMAMED as a composition-aware mapping-based metagenomic data analysis pipeline. This pipeline can analyze metagenomic samples at both taxonomic and functional profiling levels. Using this pipeline, metagenome sequences can be mapped to non-redundant gene catalogs and the gene frequency in the samples are obtained. Due to the highly compositional nature of metagenomic data, the cumulative sum-scaling method is used at both taxa and gene levels for compositional data analysis in our pipeline. Additionally, by mapping the genes to the KEGG database, annotations related to each gene can be extracted at different functional levels such as KEGG ortholog groups, enzyme commission numbers and reactions. Furthermore, the pipeline enables the user to identify potential biomarkers in case-control metagenomic samples by investigating functional differences. The source code for this software is available from https://github.com/mhnb/camamed. Also, the ready to use Docker images are available at https://hub.docker.com.

Comparison of gut microbiota structure and Actinobacteria abundances in healthy young adults and elderly subjects: a pilot study

BACKGROUND

The aim was to determine the potential association of the gut microbiota composition, especially the abundance of Actinobacteria, as well as the differentiation of functional and resistance genes with age (young adults vs elderly subjects) in China.

RESULTS

The patterns of relative abundance of all bacteria isolated from fecal samples differed between young adults and elderly subjects, but the alpha diversity (Chao1 P = 0.370, Shannon P = 0.560 and Simpson P = 0.270) and beta diversity (ANOSIM R = 0.031, P = 0.226) were not significantly different. There were 3 Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways (carbon metabolism, inositol phosphate metabolism, and sesquiterpenoid and triterpenoid biosynthesis) and 7 antibiotic resistant genes (ARGs) (macrolide lincosamide-streptogramin B (MLSB), tetracycline, aminoglycoside, sulfonamide, fosmidomycin, lincomycin, and vancomycin) that showed significant differences between the 2 groups (all P < 0.05). The abundance of Actinomycetes was enriched (about 2.4-fold) in young adults. Bifidobacteria dominated in both young adults and elderly subjects, with overall higher abundances in young adults (P > 0.05). Only the Bifidobacterium_dentium species showed significant differences between the 2 groups (P = 0.013), with a higher abundance in elderly subjects but absent in young adults.

CONCLUSIONS

The present study revealed that there were 3 KEGG metabolic pathways and 7 ARGs as well as enhanced Bifidobacterium_dentium species abundance in elderly compared to young subjects.

Metagenomics-Based Proficiency Test of Smoked Salmon Spiked with a Mock Community

An inter-laboratory proficiency test was organized to assess the ability of participants to perform shotgun metagenomic sequencing of cold smoked salmon, experimentally spiked with a mock community composed of six bacteria, one parasite, one yeast, one DNA, and two RNA viruses. Each participant applied its in-house wet-lab workflow(s) to obtain the metagenomic dataset(s), which were then collected and analyzed using MG-RAST. A total of 27 datasets were analyzed. Sample pre-processing, DNA extraction protocol, library preparation kit, and sequencing platform, influenced the abundance of specific microorganisms of the mock community. Our results highlight that despite differences in wet-lab protocols, the reads corresponding to the mock community members spiked in the cold smoked salmon, were both detected and quantified in terms of relative abundance, in the metagenomic datasets, proving the suitability of shotgun metagenomic sequencing as a genomic tool to detect microorganisms belonging to different domains in the same food matrix. The implementation of standardized wet-lab protocols would highly facilitate the comparability of shotgun metagenomic sequencing dataset across laboratories and sectors. Moreover, there is a need for clearly defining a sequencing reads threshold, to consider pathogens as detected or undetected in a food sample.

Associations of the gut microbiome and clinical factors with acute GVHD in allogeneic HSCT recipients

Acute graft-versus-host disease (aGVHD) is a leading cause of transplantation-related mortality after allogeneic hematopoietic stem cell transplantation (aHSCT). 16S ribosomal RNA (16S rRNA) gene-based studies have reported that lower gut bacterial diversity and the relative abundance of certain bacteria after aHSCT are associated with aGVHD. Using shotgun metagenomic sequencing and a large cohort, we aimed to confirm and extend these observations. Adult aHSCT recipients with stool samples collected from day -30 to day 100 relative to aHSCT were included. One sample was selected per patient per period (pre-aHSCT (day -30 to day 0), early post-aHSCT (day 1 to day 28), and late post-aHSCT (day 29 to day 100)), resulting in 150 aHSCT recipients and 259 samples. Microbial and clinical factors were tested for differences between time periods and an association with subsequent aGVHD. Patients showed a decline in gut bacterial diversity posttransplant, with several patients developing a dominance of Enterococcus. A total of 36 recipients developed aGVHD at a median of 34 days (interquartile range, 26-50 days) post-aHSCT. Lower microbial gene richness (P = .02), a lower abundance of the genus Blautia (P = .05), and a lower abundance of Akkermansia muciniphila (P = .01) early post-aHSCT was observed in those who developed aGVHD. Myeloablative conditioning was associated with aGVHD along with a reduction in gene richness and abundance of Blautia and A muciniphila. These results confirm low diversity and Blautia being associated with aGVHD. Crucially, we add that pretransplant conditioning is associated with changes in gut microbiota. Investigations are warranted to determine the interplay of gut microbiota and conditioning in the development of aGVHD.

Metagenome-assembled genome distribution and key functionality highlight importance of aerobic metabolism in Svalbard permafrost

Permafrost underlies a large portion of the land in the Northern Hemisphere. It is proposed to be an extreme habitat and home for cold-adaptive microbial communities. Upon thaw permafrost is predicted to exacerbate increasing global temperature trend, where awakening microbes decompose millennia old carbon stocks. Yet our knowledge on composition, functional potential and variance of permafrost microbiome remains limited. In this study, we conducted a deep comparative metagenomic analysis through a 2 m permafrost core from Svalbard, Norway to determine key permafrost microbiome in this climate sensitive island ecosystem. To do so, we developed comparative metagenomics methods on metagenomic-assembled genomes (MAG). We found that community composition in Svalbard soil horizons shifted markedly with depth: the dominant phylum switched from Acidobacteria and Proteobacteria in top soils (active layer) to Actinobacteria, Bacteroidetes, Chloroflexi and Proteobacteria in permafrost layers. Key metabolic potential propagated through permafrost depths revealed aerobic respiration and soil organic matter decomposition as key metabolic traits. We also found that Svalbard MAGs were enriched in genes involved in regulation of ammonium, sulfur and phosphate. Here, we provide a new perspective on how permafrost microbiome is shaped to acquire resources in competitive and limited resource conditions of deep Svalbard soils.

Alterations of intestinal microbiota in liver cirrhosis with muscle wasting

OBJECTIVES

The intestinal microbiota plays an important role in the nutritional status and energy metabolism of the host. Liver cirrhosis is accompanied by muscle wasting or sarcopenia. The aim of this study was to to explore the changes in intestinal microbiota in patients with liver cirrhosis and muscle wasting by using metagenomics.

METHODS

This was a cross-sectional study of patients with (n = 30) and without (n = 30) muscle wasting and age- and sex-matched healthy controls (n = 30) to evaluate changes in intestinal microbiota by metagenomic gene sequencing. Muscle wasting was determined by the third lumbar vertebrae skeletal muscle index (L3 SMI).

RESULTS

The Shannon index, which represents species diversity, of patients in the muscle-wasting group (2.11 ± 0.88) was lower than in the non-muscle-wasting group (2.64 ± 0.68; P = 0.039), which was significantly lower than in the healthy control group (2.70 ± 0.53; P = 0.023). There were 17 microbial species with significant differences in relative abundance between the two groups (linear discriminant analysis score >2; P < 0.05). The relative abundance of Escherichia coli, Peptostreptococcus stomatis, and Bacteroides uniformis showed the most significant association with L3 SMI.

CONCLUSIONS

There were compositional alterations in intestinal microbiota in patients with liver cirrhosis and muscle wasting. L3 SMI is closely related to E. coli, P. stomatis, and B. uniformis in liver cirrhosis. Further interventional studies are needed to confirm whether improving intestinal microbiota can improve the nutritional status of patients with liver cirrhosis.

Metagenomics reveals impact of geography and acute diarrheal disease on the Central Indian human gut microbiome

BACKGROUND

The Central Indian gut microbiome remains grossly understudied. Herein, we sought to investigate the burden of antimicrobial resistance and diarrheal diseases, particularly Clostridioides difficile, in rural-agricultural and urban populations in Central India, where there is widespread unregulated antibiotic use. We utilized shotgun metagenomics to comprehensively characterize the bacterial and viral fractions of the gut microbiome and their encoded functions in 105 participants.

RESULTS

We observed distinct rural-urban differences in bacterial and viral populations, with geography exhibiting a greater influence than diarrheal status. Clostridioides difficile disease was more commonly observed in urban subjects, and their microbiomes were enriched in metabolic pathways relating to the metabolism of industrial compounds and genes encoding resistance to 3^rd generation cephalosporins and carbapenems. By linking phages present in the microbiome to their bacterial hosts through CRISPR spacers, phage variation could be directly related to shifts in bacterial populations, with the auxiliary metabolic potential of rural-associated phages enriched for carbon and amino acid energy metabolism.

CONCLUSIONS

We report distinct differences in antimicrobial resistance gene profiles, enrichment of metabolic pathways and phage composition between rural and urban populations, as well as a higher burden of Clostridioides difficile disease in the urban population. Our results reveal that geography is the key driver of variation in urban and rural Indian microbiomes, with acute diarrheal disease, including C. difficile disease exerting a lesser impact. Future studies will be required to understand the potential role of dietary, cultural, and genetic factors in contributing to microbiome differences between rural and urban populations.

Metagenome association study of the gut microbiome revealed biomarkers linked to chemotherapy outcomes in locally advanced and advanced lung cancer

Background

The gut microbiome is important in the development and immunotherapy efficacy of lung cancer. However, the relationship between the intestinal flora and chemotherapy outcomes remains unclear and was investigated in this study.

Methods

We analyzed baseline stool samples from patients with locally advanced and advanced lung cancer before chemotherapy treatment, through metagenomics of the gut microbiota. The composition, diversity, function, and metabolic pathway analysis were compared among patients with different clinical outcomes.

Results

From 64 patients, 33 responded to treatment (responders) and 31 did not (nonresponders). Streptococcus mutans and Enterococcus casseliflavus were enriched in responders (P < 0.05), while 11 bacteria including Leuconostoc lactis and Eubacterium siraeum were enriched in nonresponders (P < 0.05) by variance analysis. Responders were associated with significantly higher Acidobacteria and Granulicella, while Streptococcus oligofermentans, Megasphaera micronuciformis, and Eubacterium siraeum were more abundant in nonresponders by Lefse analysis. Streptococcus mutans and Enterococcus casseliflavus were further identified as bacterial markers relevant to responders using unsupervised clustering, and Leuconostoc lactis and Eubacterium siraeum were related to nonresponders. The L‐glutamate degradation VIII pathway was enriched in responders (P = 0.014), and the C4 photosynthetic carbon assimilation cycle, reductive TCA cycle I, and hexitol fermentation to lactate, formate, ethanol, and acetate were enriched in nonresponders (P < 0.05). Additionally, significant associations of bacterial species with clinical phenotypes were observed by Spearman correlation analysis.

Conclusions

The specific gut microbiome of patients with lung cancer might be connected to the clinical outcomes of chemotherapy.

Key points

RBUD: A New Functional Potential Analysis Approach for Whole Microbial Genome Shotgun Sequencing

Whole metagenome shotgun sequencing is a powerful approach to detect the functional potential of microbial communities. Currently, the read-based metagenomics profiling for established database (RBED) method is one of the two kinds of conventional methods for species and functional annotations. However, the databases, which are established based on test samples or specific reference genomes or protein sequences, limit the coverage of global microbial diversity. The other assembly-based metagenomics profiling for unestablished database (ABUD) method has a low utilization rate of reads, resulting in a lot of biological information loss. In this study, we proposed a new method, read-based metagenomics profiling for unestablished database (RBUD), based on Metagenome Database of Global Microorganisms (MDGM), to solve the above problems. To evaluate the accuracy and effectiveness of our method, the intestinal bacterial composition and function analyses were performed in both avian colibacillosis chicken cases and type 2 diabetes mellitus patients. Comparing to the existing methods, RBUD is superior in detecting proteins, percentage of reads mapping and ontological similarity of intestinal microbes. The results of RBUD are in better agreement with the classical functional studies on these two diseases. RBUD also has the advantages of fast analysis speed and is not limited by the sample size.