Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes. Nat Biotechnol. 2014;32:822-828. [PMID: 24997787 DOI: 10.1038/nbt.2939]

Gut microbial DL-endopeptidase alleviates Crohn's disease via the NOD2 pathway

The pattern-recognition receptor NOD2 senses bacterial muropeptides to regulate host immunity and maintain homeostasis. Loss-of-function mutations in NOD2 are associated with Crohn's disease (CD), but how the variations in microbial factors influence NOD2 signaling and host pathology is elusive. We demonstrate that the Firmicutes peptidoglycan remodeling enzyme, DL-endopeptidase, increased the NOD2 ligand level in the gut and impacted colitis outcomes. Metagenomic analyses of global cohorts (n = 857) revealed that DL-endopeptidase gene abundance decreased globally in CD patients and negatively correlated with colitis. Fecal microbiota from CD patients with low DL-endopeptidase activity predisposed mice to colitis. Administering DL-endopeptidase, but not an active site mutant, alleviated colitis via the NOD2 pathway. Therapeutically restoring NOD2 ligands with a DL-endopeptidase-producing Lactobacillus salivarius strain or mifamurtide, a clinical analog of muramyl dipeptide, exerted potent anti-colitis effects. Our study suggests that the depletion of DL-endopeptidase contributes to CD pathogenesis through NOD2 signaling, providing a therapeutically modifiable target.

The CD4+ T cell response to a commensal-derived epitope transitions from a tolerant to an inflammatory state in Crohn's disease

Reciprocal interactions between host T helper cells and gut microbiota enforce local immunological tolerance and modulate extra-intestinal immunity. However, our understanding of antigen-specific tolerance to the microbiome is limited. Here, we developed a systematic approach to predict HLA class-II-specific epitopes using the humanized bacteria-originated T cell antigen (hBOTA) algorithm. We identified a diverse set of microbiome epitopes spanning all major taxa that are compatible with presentation by multiple HLA-II alleles. In particular, we uncovered an immunodominant epitope from the TonB-dependent receptor SusC that was universally recognized and ubiquitous among Bacteroidales. In healthy human subjects, SusC-reactive T cell responses were characterized by IL-10-dominant cytokine profiles, whereas in patients with active Crohn's disease, responses were associated with elevated IL-17A. Our results highlight the potential of targeted antigen discovery within the microbiome to reveal principles of tolerance and functional transitions during inflammation.

Dynamics of the gut microbiota in rats after hypobaric hypoxia exposure

Background

Gut microbiota plays an important role in host health and is influenced by multiple factors. Hypobaric hypoxia usually existing at high altitude conditions can adversely affect normal physiological functions. However, the dynamic changes of gut microbiota influenced by hypobaric hypoxia have not been elucidated.

Methods

In this study, we collected fecal samples from seven rats at 14 time points from entering the hypobaric chamber (eight time points) to leaving the chamber (six time points) and five rats served as normoxic controls. Metagenome sequencing was performed on all samples and the dynamics of taxa and functions were analyzed.

Results

We found that the α-diversity was changed in the first 5 days after entering or leaving the hypobaric chamber. The β-diversity analysis revealed that gut microbiota structure was significantly separated among 14 time points. After entering the chamber, the relative abundance of Bacteroides decreased and the most abundant genus turned into Prevotella. The abundance of Firmicutes and Bacteroidetes showed an opposite trend and both have a significant change within 5 days after entering or leaving the hypobaric hypoxia chamber. Some obligate anaerobic bacteria belonging to Desulfovibrio and Alistipes were significantly enriched after entering the chamber for 5 weeks, whereas Probiotics like Bifidobacterium and Lactococcus, and short-chain fatty acids producers like Butyrivibrio and Pseudobutyrivibrio were significantly enriched after leaving the chamber for 3 weeks. Microbial functions like 'Two-component regulatory system', 'beta-carotene biosynthesis' and 'Fatty acid biosynthesis' were significantly enriched after entering the chamber for 5 weeks. Hypobaric hypoxia conditions could deeply affect the diversity and structure of gut microbiota. The alterations of abundance of dominant taxa (Firmicutes and Bacteroidetes), increased anaerobes and decreased probiotics induced by hypobaric hypoxia conditions might affect the host health.

The rhizosphere microbiome improves the adaptive capabilities of plants under high soil cadmium conditions

Cadmium (Cd) contamination of agricultural soils poses a potential public health issue for humans. Phytoremediation-based accumulating plants are an effective and sustainable technology for Cadmium remediation of contaminated agricultural soil. The rhizosphere microbiome can promote the growth and Cadmium accumulation in hyperaccumulators, but its taxonomic and functional traits remain elusive. The present study used two ecotypes of Sedum alfredii, an accumulating ecotype (AE) and a non-accumulating ecotype (NAE), as model plants to investigate the rhizosphere microbiome assemblages and influence on plant growth under high cadmium conditions. Our results showed that distinct root microbiomes assembled in association with both ecotypes of S. alfredii and that the assemblages were based largely on the lifestyles of the two ecotypes. In addition, we demonstrated that the functions of the microbes inhabiting the rhizosphere soils were closely associated with root-microbe interactions in both ecotypes of S. alfredii. Importantly, our results also demonstrated that the rhizosphere microbiome assembled in the AE rhizosphere soils contributed to plant growth and cadmium uptake under high cadmium conditions through functions such as nitrogen fixation, phosphorus solubilization, indole acetic acid (IAA) synthesis, and siderophore metabolism. However, this phenomenon was not clearly observed in the NAE. Our results suggest that the rhizosphere microbiome plays important roles in biogeochemical nutrient and metal cycling that can contribute to host plant fitness.

Effects of addition of 2-fucosyllactose to infant formula on growth and specific pathways of utilization by Bifidobacterium in healthy term infants

Oligosaccharides in human milk support health via intestinal microbiome. We studied effects of addition of 2-fucosyllactose (2′FL) to the infant formula on infant growth, occurrence of adverse events (AE), and infant microbiome, including expression of microbial genes that metabolize 2′FL. Our hypothesis was that while 2′FL would not affect growth, it would cause changes in microbiome metabolism. In a double-blinded randomized controlled study fashion, the infant formula ± 2′FL or human milk was fed to healthy term infants for 16 weeks. Fecal samples obtained at baseline and week 16 were analyzed for microbial populations, metagenomic species concept (MGS), and genetics of gut metabolic modules (GMMs). There were no effects of addition of 2′FL on growth or AEs. There were no significant differences by feeding group in MGS richness or Shannon diversity at baseline, but formula groups each had significantly greater richness (p < 0.05) and diversity (p < 0.05) after 16 weeks of feeding than the breastfed group. While two glycosyl hydrolase (GH) families (GH42 and GH112) were significantly increased, two other GH families (GH20 and GH2) were significantly decreased in the test formula group compared to the control formula group; although modest, addition of 2′FL resulted in changes in microbiome in the direction of breastfed infants, consistent with internal metabolism of HMOs by Bifidobacterium.

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

Human gut microbiota produce a variety of molecules, some of which enter the bloodstream and impact health. Conversely, dietary or pharmacological compounds may affect the microbiota before entering the circulation. Characterization of these interactions is an important step towards understanding the effects of the gut microbiota on health. In this cross-sectional study, we used deep metagenomic sequencing and ultra-high-performance liquid chromatography linked to mass spectrometry for a detailed characterization of the gut microbiota and plasma metabolome, respectively, of 8583 participants invited at age 50 to 64 from the population-based Swedish CArdioPulmonary bioImage Study. Here, we find that the gut microbiota explain up to 58% of the variance of individual plasma metabolites and we present 997 associations between alpha diversity and plasma metabolites and 546,819 associations between specific gut metagenomic species and plasma metabolites in an online atlas (https://gutsyatlas.serve.scilifelab.se/). We exemplify the potential of this resource by presenting novel associations between dietary factors and oral medication with the gut microbiome, and microbial species strongly associated with the uremic toxin p-cresol sulfate. This resource can be used as the basis for targeted studies of perturbation of specific metabolites and for identification of candidate plasma biomarkers of gut microbiota composition.

Here, Dekkers et al. characterize associations of 1528 gut metagenomic species with the plasma metabolome in 8583 participants of the SCAPIS Study, and find that gut microbiota explain up to 58% of the variance of individual plasma metabolites.

Integrated Analysis of Gut Microbiome and Lipid Metabolism in Mice Infected with Carbapenem-Resistant Enterobacteriaceae

The disturbance in gut microbiota composition and metabolism has been implicated in the process of pathogenic bacteria infection. However, the characteristics of the microbiota and the metabolic interaction of commensals−host during pathogen invasion remain more than vague. In this study, the potential associations of gut microbes with disturbed lipid metabolism in mice upon carbapenem-resistant Escherichia coli (CRE) infection were explored by the biochemical and multi-omics approaches including metagenomics, metabolomics and lipidomics, and then the key metabolites−reaction−enzyme−gene interaction network was constructed. Results showed that intestinal Erysipelotrichaceae family was strongly associated with the hepatic total cholesterol and HDL-cholesterol, as well as a few sera and fecal metabolites involved in lipid metabolism such as 24, 25-dihydrolanosterol. A high-coverage lipidomic analysis further demonstrated that a total of 529 lipid molecules was significantly enriched and 520 were depleted in the liver of mice infected with CRE. Among them, 35 lipid species showed high correlations (|r| > 0.8 and p < 0.05) with the Erysipelotrichaceae family, including phosphatidylglycerol (42:2), phosphatidylglycerol (42:3), phosphatidylglycerol (38:5), phosphatidylcholine (42:4), ceramide (d17:1/16:0), ceramide (d18:1/16:0) and diacylglycerol (20:2), with correlation coefficients higher than 0.9. In conclusion, the systematic multi-omics study improved the understanding of the complicated connection between the microbiota and the host during pathogen invasion, which thereby is expected to lead to the future discovery and establishment of novel control strategies for CRE infection.

Seasonal microbial dynamics in the ocean inferred from assembled and unassembled data: a view on the unknown biosphere

In environmental metagenomic experiments, a very high proportion of the microbial sequencing data (> 70%) remains largely unexploited because rare and closely related genomes are missed in short-read assemblies. The identity and the potential metabolisms of a large fraction of natural microbial communities thus remain inaccessible to researchers. The purpose of this study was to explore the genomic content of unassembled metagenomic data and test their level of novelty. We used data from a three-year microbial metagenomic time series of the NW Mediterranean Sea, and conducted reference-free and database-guided analysis. The results revealed a significant genomic difference between the assembled and unassembled reads. The unassembled reads had a lower mean identity against public databases, and fewer metabolic pathways could be reconstructed. In addition, the unassembled fraction presented a clear temporal pattern, unlike the assembled ones, and a specific community composition that was similar to the rare communities defined by metabarcoding using the 16S rRNA gene. The rare gene pool was characterised by keystone bacterial taxa, and the presence of viruses, suggesting that viral lysis could maintain some taxa in a state of rarity. Our study demonstrates that unassembled metagenomic data can provide important information on the structure and functioning of microbial communities.

Intercontinental Gut Microbiome Variances in IBD

The development of biomarkers for inflammatory bowel disease (IBD) diagnosis would be relevant in a generalized context. However, intercontinental investigation on these microbial biomarkers remains scarce. We examined taxonomic microbiome variations in IBD using published DNA shotgun metagenomic data. For this purpose, we used sequenced data from our previous Spanish Crohn’s disease (CD) and ulcerative colitis (UC) cohort, downloaded sequence data from a Chinese CD cohort, and downloaded taxonomic and functional profiling tables from a USA CD and UC cohort. At the global level, geographical location and disease phenotype were the main explanatory covariates of microbiome variations. In healthy controls (HC) and UC, geography turned out to be the most important factor, while disease intestinal location was the most important one in CD. Disease severity correlated with lower alpha-diversity in UC but not in CD. Across geography, alpha-diversity was significantly different independently of health status, except for CD. Despite recruitment from different countries and with different disease severity scores, CD patients may harbor a very similar microbial taxonomic profile. Our study pointed out that geographic location, disease activity status, and other environmental factors are important contributing factors in microbiota changes in IBD. We therefore strongly recommend taking these factors into consideration for future IBD studies to obtain globally valid and reproducible biomarkers.

Abundant antibiotic resistance genes in rhizobiome of the human edible Moringa oleifera medicinal plant

Moringa oleifera (or the miracle tree) is a wild plant species widely grown for its seed pods and leaves, and is used in traditional herbal medicine. The metagenomic whole genome shotgun sequencing (mWGS) approach was used to characterize antibiotic resistance genes (ARGs) of the rhizobiomes of this wild plant and surrounding bulk soil microbiomes and to figure out the chance and consequences for highly abundant ARGs, e.g., mtrA, golS, soxR, oleC, novA, kdpE, vanRO, parY, and rbpA, to horizontally transfer to human gut pathogens via mobile genetic elements (MGEs). The results indicated that abundance of these ARGs, except for golS, was higher in rhizosphere of M. oleifera than that in bulk soil microbiome with no signs of emerging new soil ARGs in either soil type. The most highly abundant metabolic processes of the most abundant ARGs were previously detected in members of phyla Actinobacteria, Proteobacteria, Acidobacteria, Chloroflexi, and Firmicutes. These processes refer to three resistance mechanisms namely antibiotic efflux pump, antibiotic target alteration and antibiotic target protection. Antibiotic efflux mechanism included resistance-nodulation-cell division (RND), ATP-binding cassette (ABC), and major facilitator superfamily (MFS) antibiotics pumps as well as the two-component regulatory kdpDE system. Antibiotic target alteration included glycopeptide resistance gene cluster (vanRO), aminocoumarin resistance parY, and aminocoumarin self-resistance parY. While, antibiotic target protection mechanism included RbpA bacterial RNA polymerase (rpoB)-binding protein. The study supports the claim of the possible horizontal transfer of these ARGs to human gut and emergence of new multidrug resistant clinical isolates. Thus, careful agricultural practices are required especially for plants used in circles of human nutrition industry or in traditional medicine.

High throughput genome scale modeling predicts microbial vitamin requirements contribute to gut microbiome community structure

Human gut microbiome structure and emergent metabolic outputs impact health outcomes. However, what drives such community characteristics remains underexplored. Here, we rely on high throughput genomic reconstruction modeling, to infer the metabolic attributes and nutritional requirements of 816 gut strains, via a framework termed GEMNAST. This has been performed in terms of a group of human vitamins to examine the role vitamin exchanges have at different levels of community organization. We find that only 91 strains can satisfy their vitamin requirements (prototrophs) while the rest show various degrees of auxotrophy/specialization, highlighting their dependence on external sources, such as other members of the microbial community. Further, 79% of the strains in our sample were mapped to 11 distinct vitamin requirement profiles with low phylogenetic consistency. Yet, we find that human gut microbial community enterotype indicators display marked metabolic differences. Prevotella strains display a metabolic profile that can be complemented by strains from other genera often associated with the Prevotella enterotype and agrarian diets, while Bacteroides strains occupy a prototrophic profile. Finally, we identify pre-defined interaction modules (IMs) of gut species from human and mice predicted to be driven by, or highly independent of vitamin exchanges. Our analysis provides mechanistic grounding to gut microbiome stability and to co-abundance-based observations, a fundamental step toward understanding emergent processes that influence health outcomes. Further, our work opens a path to future explorations in the field through applications of GEMNAST to additional nutritional dimensions.

Establishing a novel inflammatory bowel disease prediction model based on gene markers identified from single nucleotide variants of the intestinal microbiota

The intestinal microbiota is a crucial environmental factor in the development of inflammatory bowel disease (IBD). The abundance of Faecalibacterium prausnitzii is significantly decreased in IBD patients, which is used as a biomarker for IBD diagnosis. However, this can be observed in both IBD and colorectal cancer, which would confound the diagnostic results. Thus, we first established a new model for predicting Crohn's disease (CD) with high precision according to gene characteristics based on single nucleotide variants (SNVs). Next, five gene markers belonging to two species, F. prausnitzii and Eubacterium rectale, that were enriched in the CD group were obtained to build a CD prediction model, and high accuracy in distinguishing the CD and control groups was observed in the discovery (area under curve [AUC] = 91.13%) and validation cohorts (AUC = 79.55%). The model still maintained high accuracy after expanding the healthy cohort (AUC = 89.75%). High disease specificity in distinguishing CD and CRC groups (AUC = 95.74%) was also proven. This study establishes a novel diagnostic method for predicting IBD that also provides unprecedented insight for the early, painless diagnosis of other non-communicable diseases.

Microbial behaviours inside alternating anaerobic-anoxic environment of a sulfur cycle-driven EBPR system: A metagenomic investigation

Denitrifying sulfur conversion-assisted enhanced biological phosphorus removal (DS-EBPR) was recently developed for saline wastewater treatment. However, the main functional bacteria and the interrelationship of functional bacteria of the DS-EBPR have not been defined and identified so far. This study used metagenomics and multivariate statistics to deduce the functional microbial community and distribution of functional genes associated with the critical metabolic pathways of carbon (C), nitrogen (N), phosphorus (P) and sulfur (S), particularly regarding how they would behave under the alternating anaerobic-anoxic conditions inside a long-term DS-EBPR system. An analysis of the metagenomics and metabolic functions identified 11 major microbial species which were classifiable into four groups: sulfate reducing bacteria (SRB, 0.8-2.2%), sulfur oxidizing bacteria (SOB, 31.9-37.7%), denitrifying phosphate accumulating organisms (DPAOs, 10.0-15.8%) and glycogen accumulating organisms (GAOs, 3.7-7.7%). The four groups of microorganisms performed their respective metabolisms synergistically. In terms of distribution of functional genes, SRB (Desulfococcus and Desulfobacter) and SOB (Chromatiaceae and Thiobacillus) are not only encoded by the related sulfur conversion genes (sqr, dsrAB, aprAB and sat), but also encoded by the necessary ppx and ppk1 gene for P removal that they can be considered as the potential S-related PAOs. Between the anaerobic and anoxic conditions, the metagenome-based microbial community remained structurally similar, but the functional genes, which encode various key enzymes for the P, N, and S pathways, changed in abundance. This study contributes to our understanding on the interactions and competition between the SRB, SOB, DPAOs, and GAOs in a DS-EBPR system.

Microbial community roles and chemical mechanisms in the parasitic development of Orobanche cumana

Orobanche cumana Wallr. is a holoparasite weed that extracts water and nutrients from its host the sunflower, thereby causing yield reductions and quality losses. However, the number of O. cumana parasites in the same farmland is distinctly different. The roots of some hosts have been heavily parasitized, while others have not been parasitized. What are the factors contributing to this phenomenon? Is it possible that sunflower interroot microorganisms are playing a regulatory role in this phenomenon? The role of the microbial community in this remains unclear. In this study, we investigated the rhizosphere soil microbiome for sunflowers with different degrees of O. cumana parasitism, that is, healthy, light infection, moderate infection, and severe infection on the sunflower roots. The microbial structures differed significantly according to the degree of parasitism, where Xanthomonadaceae was enriched in severe infections. Metagenomic analyses revealed that amino acid, carbohydrate, energy, and lipid metabolism were increased in the rhizosphere soils of severely infected sunflowers, which were attributed to the proliferation of Lysobacter. Lysobacter antibioticus (HX79) was isolated and its capacity to promote O. cumana seed germination and increase the germ tube length was confirmed by germination and pot experiments. Cyclo(Pro-Val), an active metabolite of strain HX79, was identified and metabolomic and molecular docking approaches confirmed it was responsible for promoting O. cumana seed germination and growth. And we found that Pseudomonas mandelii HX1 inhibited the growth of O. cumana in the host rhizosphere soil. Our findings clarify the role of rhizosphere microbiota in regulating the parasite O. cumana to possibly facilitate the development of a new weed suppression strategy.

MAGNETO: An Automated Workflow for Genome-Resolved Metagenomics

Metagenome-assembled genomes (MAGs) represent individual genomes recovered from metagenomic data. MAGs are extremely useful to analyze uncultured microbial genomic diversity, as well as to characterize associated functional and metabolic potential in natural environments. Recent computational developments have considerably improved MAG reconstruction but also emphasized several limitations, such as the nonbinning of sequence regions with repetitions or distinct nucleotidic composition. Different assembly and binning strategies are often used; however, it still remains unclear which assembly strategy, in combination with which binning approach, offers the best performance for MAG recovery. Several workflows have been proposed in order to reconstruct MAGs, but users are usually limited to single-metagenome assembly or need to manually define sets of metagenomes to coassemble prior to genome binning. Here, we present MAGNETO, an automated workflow dedicated to MAG reconstruction, which includes a fully-automated coassembly step informed by optimal clustering of metagenomic distances, and implements complementary genome binning strategies, for improving MAG recovery. MAGNETO is implemented as a Snakemake workflow and is available at: https://gitlab.univ-nantes.fr/bird_pipeline_registry/magneto. IMPORTANCE Genome-resolved metagenomics has led to the discovery of previously untapped biodiversity within the microbial world. As the development of computational methods for the recovery of genomes from metagenomes continues, existing strategies need to be evaluated and compared to eventually lead to standardized computational workflows. In this study, we compared commonly used assembly and binning strategies and assessed their performance using both simulated and real metagenomic data sets. We propose a novel approach to automate coassembly, avoiding the requirement for a priori knowledge to combine metagenomic information. The comparison against a previous coassembly approach demonstrates a strong impact of this step on genome binning results, but also the benefits of informing coassembly for improving the quality of recovered genomes. MAGNETO integrates complementary assembly-binning strategies to optimize genome reconstruction and provides a complete reads-to-genomes workflow for the growing microbiome research community.

Identification and Characterization of Major Bile Acid 7α-Dehydroxylating Bacteria in the Human Gut

The metabolism of bile acids (BAs) by gut bacteria plays an important role in human health. This study identified and characterized 7α-dehydroxylating bacteria, which are majorly responsible for converting primary BAs to secondary BAs, in the human gut and investigated their association with human disease. Six 7α-dehydratase (BaiE) clusters were identified from human gut metagenomes through sequence similarity network and genome neighborhood network analyses. Abundance analyses of gut metagenomes and metatranscriptomes identified a cluster of bacteria (cluster 1) harboring baiE genes that may be key 7α-dehydroxylating bacteria in the human gut. The baiE gene abundance of cluster 1 was significantly and positively correlated with the ratio of secondary BAs to primary BAs. Furthermore, the baiE gene abundances of cluster 1 were significantly negatively correlated with inflammatory bowel disease, including Crohn's disease and ulcerative colitis, as well as advanced nonalcoholic fatty liver disease, liver cirrhosis, and ankylosing spondylitis. Phylogenetic and metagenome-assembled genome analyses showed that the 7α-dehydroxylating bacterial clade of cluster 1 was affiliated with the family Oscillospiraceae and may demonstrate efficient BA dehydroxylation ability by harboring both a complete bai operon, for proteins which produce secondary BAs from primary BAs, and a gene for bile salt hydrolase, which deconjugates BAs, in the human gut. IMPORTANCE In this study, we identified a key 7α-dehydroxylating bacterial group predicted to be largely responsible for converting primary bile acids (BAs) to secondary BAs in the human gut through sequence similarity network, genome neighborhood network, and gene abundance analyses using human gut metagenomes. The key bacterial group was phylogenetically quite different from known 7α-dehydroxylating bacteria, and their abundance was highly correlated with the occurrence of diverse diseases associated with bile acid 7α-dehydroxylation. In addition, we characterized the metabolic features of the key bacterial group using their metagenome-assembled genomes. This approach is useful to identify and characterize key gut bacteria highly associated with human health and diseases.

Host-microbial co-metabolites modulated by human milk oligosaccharides relate to reduced risk of respiratory tract infections

Human milk oligosaccharides (HMOs) are structurally diverse oligosaccharides present in breast milk, supporting the development of the gut microbiota and immune system. Previously, 2-HMO (2'fucosyllactose, lacto-N-neotetraose) compared to control formula feeding was associated with reduced risk of lower respiratory tract infections (LRTIs), in part linked to lower acetate and higher bifidobacteria proportions. Here, our objective was to gain further insight into additional molecular pathways linking the 2-HMO formula feeding and LRTI mitigation. From the same trial, we measured the microbiota composition and 743 known biochemical species in infant stool at 3 months of age using shotgun metagenomic sequencing and untargeted mass spectrometry metabolomics. We used multivariate analysis to identify biochemicals associated to 2-HMO formula feeding and LRTI and integrated those findings with the microbiota compositional data. Three molecular pathways stood out: increased gamma-glutamylation and N-acetylation of amino acids and decreased inflammatory signaling lipids. Integration of stool metagenomic data revealed some Bifidobacterium and Bacteroides species to be implicated. These findings deepen our understanding of the infant gut/microbiome co-metabolism in early life and provide evidence for how such metabolic changes may influence immune competence at distant mucosal sites such as the airways.

Genomic and microbial factors affect the prognosis of anti-pd-1 immunotherapy in nasopharyngeal carcinoma

Antibodies targeting the programmed cell death protein-1 (PD-1) molecule have been reported to hold promising antitumor activities in patients with nasopharyngeal carcinoma (NPC). However, only a small subset of NPC patients benefits from the anti-PD-1 monotherapy and factors that affect the treatment response need further investigation. This study aimed to examine the impact of multiple genetic and environmental factors on outcome of anti-PD-1 immunotherapy by identifying tumor size, tumor mutation burden (TMB) based on whole exon sequencing, human leukocyte antigen class I (HLA-I) homo-/heterozygosity and supertypes, blood Epstein-Barr virus (EBV) DNA load, T cell proportions, and interferon-γ(IFN-γ) levels in a cohort of 57 NPC patients that received Nivolumab or Camrelizumab treatment. Moreover, we profiled the longitudinal changes in gut microbiota composition using shotgun metagenomics sequencing. We observed that high TMB combined with HLA-I heterozygosity was associated with improved clinical outcomes. In agreement with previous studies, we found that patients with higher plasma EBV DNA load showed worse progression-free survival. We found no evidence for an effect of gut bacterial diversity on the treatment response, but identified a higher abundance of seven specific gut bacteria at baseline of non-responders, including Blautia wexlera and Blautia obeum, as well as four other bacteria belonging to the Clostridiales order, and one Erysipelatoclostridium. Combined, this study provides insight into the influence of several genetic and environmental factors on anti-PD-1 immunotherapy responses in NPC patients.

The systemic anti-microbiota IgG repertoire can identify gut bacteria that translocate across gut barrier surfaces

Unique gut microbiota compositions have been associated with inflammatory diseases, but identifying gut bacterial functions linked to immune activation in humans remains challenging. Translocation of pathogens from mucosal surfaces into peripheral tissues can elicit immune activation, although whether and which gut commensal bacteria translocate in inflammatory diseases is difficult to assess. We report that a subset of commensal gut microbiota constituents that translocate across the gut barrier in mice and humans are associated with heightened systemic immunoglobulin G (IgG) responses. We present a modified high-throughput, culture-independent approach to quantify systemic IgG against gut commensal bacteria in human serum samples without the need for paired stool samples. Using this approach, we highlight several commensal bacterial species that elicit elevated IgG responses in patients with inflammatory bowel disease (IBD) including taxa within the clades Collinsella, Bifidobacterium, Lachnospiraceae, and Ruminococcaceae. These and other taxa identified as translocating bacteria or targets of systemic immunity in IBD concomitantly exhibited heightened transcriptional activity and growth rates in IBD patient gut microbiomes. Our approach represents a complementary tool to illuminate interactions between the host and its gut microbiota and may provide an additional method to identify microbes linked to inflammatory disease.

Analysis and evaluation of different sequencing depths from 5 to 20 million reads in metagenome shotgun sequencing, with optimal minimum depth recommended

Our study is to analyze and evaluate the impact of different shotgun metagenomic sequencing depths from 5 to 20 million in MWAS, and to determine the optimal minimum sequencing depth. Our results showed that more genes and species were identified following the increase in sequencing depths. When it reached 15 million or higher, the species richness became more stable with changing rate of 5% or lower, and the species composition more stable with ICC higher than 0.75. In terms of species abundance, 81% and 97% of species showed significant differences in IGC and MetaPhlAn2 among all groups with p <0.05; Diversity showed significant differences across all groups, with decreasing differences of diversity between the experimental and the control groups following the increase of sequencing depth. The AUC of the obesity classifier for running the obesity testing samples showed an increasing trend following the increase of sequencing depth (τ=0.29). The validation results are consistent with the above results. Our study found that the higher the sequencing depth is, the more microbial information in structure and composition it provides. We also found that when sequencing depth is 15 million or higher, we obtained more stable species compositions and disease classifiers with good performance.

Functional characterization of prokaryotic dark matter: the road so far and what lies ahead

Eight-hundred thousand to one trillion prokaryotic species may inhabit our planet. Yet, fewer than two-hundred thousand prokaryotic species have been described. This uncharted fraction of microbial diversity, and its undisclosed coding potential, is known as the "microbial dark matter" (MDM). Next-generation sequencing has allowed to collect a massive amount of genome sequence data, leading to unprecedented advances in the field of genomics. Still, harnessing new functional information from the genomes of uncultured prokaryotes is often limited by standard classification methods. These methods often rely on sequence similarity searches against reference genomes from cultured species. This hinders the discovery of unique genetic elements that are missing from the cultivated realm. It also contributes to the accumulation of prokaryotic gene products of unknown function among public sequence data repositories, highlighting the need for new approaches for sequencing data analysis and classification. Increasing evidence indicates that these proteins of unknown function might be a treasure trove of biotechnological potential. Here, we outline the challenges, opportunities, and the potential hidden within the functional dark matter (FDM) of prokaryotes. We also discuss the pitfalls surrounding molecular and computational approaches currently used to probe these uncharted waters, and discuss future opportunities for research and applications.

Metagenomics Approach to the Intestinal Microbiome Structure and Abundance in High-Fat-Diet-Induced Hyperlipidemic Rat Fed with (-)-Epigallocatechin-3-Gallate Nanoparticles

The effects of nanoparticles (NPs) on microbiota homeostasis and their physiological relevance are still unclear. Herein, we compared the modulation and consequent pharmacological effects of oral administration of (−)-epigallocatechin-3-gallate (EGCG)-loaded β-cyclodextrin (β-CD) NPs (EGCG@β-CD NPs) and EGCG on gut microbiota. EGCG@β-CD NPs were prepared using self-assembly and their influence on the intestinal microbiome structure was analyzed using a metagenomics approach. The “Encapsulation efficiency (EE), particle size, polydispersity index (PDI), zeta potential” of EGCG@β-CD NPs were recorded as 98.27 ± 0.36%, 124.6 nm, 0.313 and –24.3 mV, respectively. Surface morphology of EGCG@β-CD NPs was observed as spherical. Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD) and molecular docking studies confirmed that EGCG could be well encapsulated in β-CD and formed as EGCG@β-CD NPs. After being continuously administered EGCG@β-CD NPs for 8 weeks, the serum cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and liver malondialdehyde (MDA) levels in the rats were significantly decreased, while the levels of catalase (CAT) and apolipoprotein-A1 (apo-A1) in the liver increased significantly in the hyperlipidemia model of rats, when compared to the high-fat-diet group. Furthermore, metagenomic analysis revealed that the ratio of Verrucomicrobia/Bacteroidetes was altered and Bacteroidetes decreased in the high-fat diet +200 mg/kg·bw EGCG@β-CD NPs group, while the abundance of Verrucomicrobia was significantly increased, especially Akkermansia muciniphila in rat feces. EGCG@β-CD NPs could be a promising EGCG delivery strategy to modulate the gut microbiota, enhancing its employment in the prevention of hyperlipidemia.

The Gut Microbiota Determines the High-Altitude Adaptability of Tibetan Wild Asses (Equus kiang) in Qinghai-Tibet Plateau

It was acknowledged long ago that microorganisms have played critical roles in animal evolution. Tibetan wild asses (TWA, Equus kiang) are the only wild perissodactyls on the Qinghai-Tibet Plateau (QTP) and the first national protected animals; however, knowledge about the relationships between their gut microbiota and the host's adaptability remains poorly understood. Herein, 16S rRNA and meta-genomic sequencing approaches were employed to investigate the gut microbiota–host associations in TWA and were compared against those of the co-resident livestock of yak (Bos grunnies) and Tibetan sheep (Ovis aries). Results revealed that the gut microbiota of yak and Tibetan sheep underwent convergent evolution. By contrast, the intestinal microflora of TWA diverged in a direction enabling the host to subsist on sparse and low-quality forage. Meanwhile, high microbial diversity (Shannon and Chao1 indices), cellulolytic activity, and abundant indicator species such as Spirochaetes, Bacteroidetes, Prevotella_1, and Treponema_2 supported forage digestion and short-chain fatty acid production in the gut of TWA. Meanwhile, the enterotype identification analysis showed that TWA shifted their enterotype in response to low-quality forage for a better utilization of forage nitrogen and short-chain fatty acid production. Metagenomic analysis revealed that plant biomass degrading microbial consortia, genes, and enzymes like the cellulolytic strains (Prevotella ruminicola, Ruminococcus flavefaciens, Ruminococcus albus, Butyrivibrio fibrisolvens, and Ruminobacter amylophilus), as well as carbohydrate metabolism genes (GH43, GH3, GH31, GH5, and GH10) and enzymes (β-glucosidase, xylanase, and β-xylosidase, etc.) had a significantly higher enrichment in TWA. Our results indicate that gut microbiota can improve the adaptability of TWA through plant biomass degradation and energy maintenance by the functions of gut microbiota in the face of nutritional deficiencies and also provide a strong rationale for understanding the roles of gut microbiota in the adaptation of QTP wildlife when facing harsh feeding environments.

Use of Metagenomic Whole Genome Shotgun Sequencing Data in Taxonomic Assignment of Dipterygium glaucum Rhizosphere and Surrounding Bulk Soil Microbiomes, and Their Response to Watering

The metagenomic whole genome shotgun sequencing (mWGS) approach was used to detect signatures of the rhizosphere microbiomes of Dipterygium glaucum and surrounding bulk soil microbiomes, and to detect differential microbial responses due to watering. Preliminary results reflect the reliability of the experiment and the rationality of grouping microbiomes. Based on the abundance of non-redundant genes, bacterial genomes showed the highest level, followed by Archaeal and Eukaryotic genomes, then, the least abundant viruses. Overall results indicate that most members of bacteria have a higher abundance/relative abundance (AB/RA) pattern in the rhizosphere towards plant growth promotion, while members of eukaryota have a higher pattern in bulk soil, most likely acting as pathogens. The results also indicate the contribution of mycorrhiza (genus Rhizophagus) in mediating complex mutualistic associations between soil microbes (either beneficial or harmful) and plant roots. Some of these symbiotic relationships involve microbes of different domains responding differentially to plant root exudates. Among these are included the bacterial genus Burkholderia and eukaryotic genus Trichoderma, which have antagonistic activities against the eukaryotic genus Fusarium. Another example involves Ochrobactrum phage POA1180, its bacterial host and plant roots. One of the major challenges in plant nutrition involves other microbes that manipulate nitrogen levels in the soil. Among these are the microbes that perform contraversal actions of nitrogen fixation (the methanogen Euryarchaeota) and ammonia oxidation (Crenarchaeota). The net nitrogen level in the soil is originally based on the AB/RA of these microbes and partially on the environmental condition. Watering seems to influence the AB/RA of a large number of soil microbes, where drought-sensitive microbes (members of phyla Acidobacteria and Gemmatimonadetes) showed an increased AB/RA pattern after watering, while others (Burkholderia and Trichoderma) seem to be among microbes assisting plants to withstand abiotic stresses. This study sheds light on the efficient use of mWGS in the taxonomic assignment of soil microbes and in their response to watering. It also provides new avenues for improving biotic and abiotic resistance in domestic plant germplasm via the manipulation of soil microbes.

The vaginal microbiome following orally administered probiotic

INTRODUCTION

Here we present a longitudinal shotgun sequencing metagenomics study of 16 healthy, Danish women in the reproductive age. The aim of the study was to investigate whether lactobacilli, orally consumed, had any impact on the vaginal microbiome and its functional potential.

MATERIALS AND METHODS

The 16 women aged 19-45 years were recruited from Copenhagen, Denmark. One baseline vaginal sample (day 0) and two study samples (day 25-30 and day 55-60, respectively) were sampled. The vaginal samples were analyzed by shotgun metagenomics.

RESULTS

We detected 26 species in the vaginal microbiota of the 16 women, of which six belonged to the Lactobacillus genus. We observed three vaginal microbiome clusters mainly dominated by Gardnerella vaginalis, Lactobacillus iners or Lactobacillus crispatus. The oral probiotic had no detectable effect on either the composition or the functional potential of the vaginal microbiota.

DISCUSSION

Most of the study subjects (11 out of 16 women) exhibited only minor changes in the vaginal microbiome during the treatment with probiotics. Any compositional changes could not be associated to the probiotic treatment. Future studies may benefit from an increased number of participants, and administration of the probiotics during conditions with bacterial imbalance (e.g. during/after antibiotic treatment) or the use of different Lactobacillus spp. known to colonize the vagina.

Infant Formula With a Specific Blend of Five Human Milk Oligosaccharides Drives the Gut Microbiota Development and Improves Gut Maturation Markers: A Randomized Controlled Trial

Background

Human milk oligosaccharides (HMOs) have important biological functions for a healthy development in early life.

Objective

This study aimed to investigate gut maturation effects of an infant formula containing five HMOs (2′-fucosyllactose, 2′,3-di-fucosyllactose, lacto-N-tetraose, 3′-sialyllactose, and 6′-sialyllactose).

Methods

In a multicenter study, healthy infants (7–21 days old) were randomly assigned to a standard cow’s milk-based infant formula (control group, CG); the same formula with 1.5 g/L HMOs (test group 1, TG1); or with 2.5 g/L HMOs (test group 2, TG2). A human milk-fed group (HMG) was enrolled as a reference. Fecal samples collected at baseline (n∼150/formula group; HMG n = 60), age 3 (n∼140/formula group; HMG n = 65) and 6 (n∼115/formula group; HMG n = 60) months were analyzed for microbiome (shotgun metagenomics), metabolism, and biomarkers.

Results

At both post-baseline visits, weighted UniFrac analysis indicated different microbiota compositions in the two test groups (TGs) compared to CG (P < 0.01) with coordinates closer to that of HMG. The relative abundance of Bifidobacterium longum subsp. infantis (B. infantis) was higher in TGs vs. CG (P < 0.05; except at 6 months: TG2 vs. CG P = 0.083). Bifidobacterium abundance was higher by ∼45% in TGs vs. CG at 6-month approaching HMG. At both post-baseline visits, toxigenic Clostridioides difficile abundance was 75–85% lower in TGs vs. CG (P < 0.05) and comparable with HMG. Fecal pH was significantly lower in TGs vs. CG, and the overall organic acid profile was different in TGs vs. CG, approaching HMG. At 3 months, TGs (vs. CG) had higher secretory immunoglobulin A (sIgA) and lower alpha-1-antitrypsin (P < 0.05). At 6 months, sIgA in TG2 vs. CG remained higher (P < 0.05), and calprotectin was lower in TG1 (P < 0.05) vs. CG.

Conclusion

Infant formula with a specific blend of five HMOs supports the development of the intestinal immune system and gut barrier function and shifts the gut microbiome closer to that of breastfed infants with higher bifidobacteria, particularly B. infantis, and lower toxigenic Clostridioides difficile.

Clinical Trial Registration

[https://clinicaltrials.gov/ct2/show/], identifier [NCT03722550].

A Changed Gut Microbiota Diversity Is Associated With Metabolic Improvements After Duodenal Mucosal Resurfacing With Glucagon-Like-Peptide-1 Receptor Agonist in Type 2 Diabetes in a Pilot Study

Introduction

The gut microbiota influences and interacts with the host metabolism through effects on nutrient metabolism and digestion. Duodenal Mucosal Resurfacing (DMR) is a novel endoscopic procedure involving duodenal mucosal ablation by the use of hydrothermal energy. DMR, when combined with a glucagon-like peptide-1 receptor agonist (GLP-1RA), resulted in discontinuation of exogenous insulin treatment in 69% of patients with insulin dependent type 2 diabetes mellitus (T2DM) in the INSPIRE study. These patients also experienced improved glycaemic control and metabolic health. We thus investigated if these clinical effects were associated with a change in gut microbiota alpha and beta diversity.

Methods

Faecal samples from the 16 patients were obtained for Illumina shotgun sequencing at baseline and 3 months after DMR. We assessed alpha and beta diversity of the gut microbiota in these samples and analysed its correlations with changes in HbA1c, body weight, and liver MRI proton density fat fraction (PDFF).

Results

HbA1c correlated negatively with alpha diversity (p=0.011, rho: -0.62) whereas changes in PDFF correlated significantly with beta diversity (p=0.036, rho: 0.55) 3 months after initiation of the combined intervention. These correlations with metabolic parameters were observed despite finding no change in gut microbiota diversity at 3 months post DMR.

Discussion

The correlation between gut microbiota richness (alpha diversity) and HbA1c as well as the change in PDFF and changed microbiota composition (beta diversity) suggests that changed gut microbiota diversity is associated with metabolic improvements after DMR in combination with glucagon-like-peptide-1 receptor agonist in type 2 diabetes. Larger controlled studies are however needed to find causal links between DMR with GLP-1RA, the gut microbiota, and improvements in metabolic health.

Pangenome Evolution in Environmentally Transmitted Symbionts of Deep-Sea Mussels Is Governed by Vertical Inheritance

Microbial pangenomes vary across species; their size and structure are determined by genetic diversity within the population and by gene loss and horizontal gene transfer (HGT). Many bacteria are associated with eukaryotic hosts where the host colonization dynamics may impact bacterial genome evolution. Host-associated lifestyle has been recognized as a barrier to HGT in parentally transmitted bacteria. However, pangenome evolution of environmentally acquired symbionts remains understudied, often due to limitations in symbiont cultivation. Using high-resolution metagenomics, here we study pangenome evolution of two co-occurring endosymbionts inhabiting Bathymodiolus brooksi mussels from a single cold seep. The symbionts, sulfur-oxidizing (SOX) and methane-oxidizing (MOX) gamma-proteobacteria, are environmentally acquired at an early developmental stage and individual mussels may harbor multiple strains of each symbiont species. We found differences in the accessory gene content of both symbionts across individual mussels, which are reflected by differences in symbiont strain composition. Compared with core genes, accessory genes are enriched in genome plasticity functions. We found no evidence for recent HGT between both symbionts. A comparison between the symbiont pangenomes revealed that the MOX population is less diverged and contains fewer accessory genes, supporting that the MOX association with B. brooksi is more recent in comparison to that of SOX. Our results show that the pangenomes of both symbionts evolved mainly by vertical inheritance. We conclude that genome evolution of environmentally transmitted symbionts that associate with individual hosts over their lifetime is affected by a narrow symbiosis where the frequency of HGT is constrained.

Composition and Ecological Roles of the Core Microbiome along the Abyssal-Hadal Transition Zone Sediments of the Mariana Trench

The unique geological features of hadal trenches are known to influence both the structure and ecological function of microbial communities. It is also well known that heterotrophs and chemoautotrophs dominate the hadal and abyssal pelagic zones, respectively. Here, a metagenomic investigation was conducted on sediment samples obtained from the abyssal-hadal transition zone in the Mariana Trench to gain a better understanding of the general diversity and potential function of the core microbiome in this zone. A high level of cosmopolitanism existed in the core microbiome referred from a high community similarity among different stations. Niche differentiation along the fine-scale of different sediment layers was observed, especially for major archaeal groups, largely due to sediment depth and the source of organic matter. A prevalence of nitrogen biogeochemical cycles driven by various nitrifying groups with the capability of dark carbon fixation in the abyssal-hadal biosphere was also demonstrated. The predominance of heterotrophic over chemolithoautotrophic pathways in this transition zone was found, and a high abundance of genes related to respiration and carbon fixation (i.e., the intact Calvin and rTCA cycles) were detected as well, which might reflect the intensive microbial activities known to occur in this deep biosphere. The presence of those metabolic processes and associated microbes were reflected by functional and genetic markers generated from the metagenomic data in the current study. However, their roles and contributions to the nitrogen/carbon biogeochemical cycles and flux in the abyssal-hadal transition zone still need further analysis. IMPORTANCE The Mariana Trench is the deepest oceanic region on earth, its microbial ecological exploration has become feasible with the rapid progress of submersible and metagenomic sequencing. We investigated the community compositions and metabolic functions of the core microbiome along the abyssal-hadal transition zone of the Mariana Trench, although most studies by far were focused on the pelagic zone. We found a predominance of heterotrophic groups and related metabolic pathways, which were closely associated with nitrogen biogeochemical cycles driven by various nitrifying groups with the capability of dark carbon fixation.

Genome-Resolved Characterization of Structure and Potential Functions of the Zebrafish Stool Microbiome

Zebrafish have been used as a model organism for more than 50 years and are considered an excellent model for studying host-microbiome interactions. However, this largely depends on our understanding of the zebrafish gut microbiome itself. Despite advances in sequencing and data analysis methods, the zebrafish gut microbiome remains highly understudied. This study performed the de novo metagenome assembly and recovery of the metagenome-assembled genomes (MAGs) through genome binning (and refinement) of the contigs assembled from the zebrafish stool. The results indicate that majority of the MAGs had excellent quality i.e. high completeness (≥90%) and low contamination levels (≤5%). MAGs mainly belong to the taxa that are known to be members of the core zebrafish stool microbiome, including the phylum Proteobacteria, Fusobacteriota, and Actinobacteriota. However, most of the MAGs remained unclassified at the species level and reflected previously unexplored microbial taxa and their potential novelty. These MAGs also contained genes with predicted functions associated with diverse metabolic pathways that included carbohydrate, amino acid, and lipid metabolism pathways. Lastly, we performed a comparative analysis of Paucibacter MAGs and reference genomes that highlighted the presence of novel Paucibacter species and enriched metabolic potential in the recovered MAGs.

Risk assessment with gut microbiome and metabolite markers in NAFLD development

A growing body of evidence suggests interplay between the gut microbiota and the pathogenesis of nonalcoholic fatty liver disease (NAFLD). However, the role of the gut microbiome in early detection of NAFLD is unclear. Prospective studies are necessary for identifying reliable, microbiome markers for early NAFLD. We evaluated 2487 individuals in a community-based cohort who were followed up 4.6 years after initial clinical examination and biospecimen sampling. Metagenomic and metabolomic characterizations using stool and serum samples taken at baseline were performed for 90 participants who progressed to NAFLD and 90 controls who remained NAFLD free at the follow-up visit. Cases and controls were matched for gender, age, body mass index (BMI) at baseline and follow-up, and 4-year BMI change. Machine learning models integrating baseline microbial signatures (14 features) correctly classified participants (auROCs of 0.72 to 0.80) based on their NAFLD status and liver fat accumulation at the 4-year follow up, outperforming other prognostic clinical models (auROCs of 0.58 to 0.60). We confirmed the biological relevance of the microbiome features by testing their diagnostic ability in four external NAFLD case-control cohorts examined by biopsy or magnetic resonance spectroscopy, from Asia, Europe, and the United States. Our findings raise the possibility of using gut microbiota for early clinical warning of NAFLD development.

A neural network-based framework to understand the type 2 diabetes-related alteration of the human gut microbiome

The identification of microbial markers adequate to delineate the disease-related microbiome alterations from the complex human gut microbiota is of great interest. Here, we develop a framework combining neural network (NN) and random forest, resulting in 40 marker species and 90 marker genes identified from the metagenomic data set (185 healthy and 183 type 2 diabetes [T2D] samples), respectively. In terms of these markers, the NN model obtained higher accuracy in classifying the T2D-related samples than other methods; the interaction network analyses identified the key species and functional modules; the regression analysis determined that fasting blood glucose is the most significant factor (p < 0.05) in the T2D-related alteration of the human gut microbiome. We also observed that those marker species varied little across the case and control samples greatly shift in the different stages of the T2D development, suggestive of their important roles in the T2D-related microbiome alteration. Our study provides a new way of identifying the disease-related biomarkers and analyzing the role they may play in the development of the disease.

Effects of an Amino Acid-Based Formula Supplemented with Two Human Milk Oligosaccharides on Growth, Tolerability, Safety, and Gut Microbiome in Infants with Cow's Milk Protein Allergy

This open-label, non-randomized, multicenter trial (Registration: NCT03661736) aimed to assess if an amino acid-based formula (AAF) supplemented with two human milk oligosaccharides (HMO) supports normal growth and is well tolerated in infants with a cow's milk protein allergy (CMPA). Term infants aged 1-8 months with moderate-to-severe CMPA were enrolled. The study formula was an AAF supplemented with 2'-fucosyllactose (2'-FL) and lacto-N-neotetraose (LNnT). Infants were fed the study formula for 4 months and were offered to remain on the formula until 12 months of age. Tolerance and safety were assessed throughout the trial. Out of 32 infants (mean age 18.6 weeks; 20 (62.5%) male), 29 completed the trial. During the 4-month principal study period, the mean weight-for-age Z score (WAZ) increased from -0.31 at the baseline to +0.28 at the 4-months' follow-up. Linear and head growth also progressed along the WHO child growth reference, with a similar small upward trend. The formula was well tolerated and had an excellent safety profile. When comparing the microbiome at the baseline to the subsequent visits, there was a significant on-treatment enrichment in HMO-utilizing bifidobacteria, which was associated with a significant increase in fecal short-chain fatty acids. In addition, we observed a significant reduction in the abundance of fecal Proteobacteria, suggesting that the HMO-supplemented study formula partially corrected the gut microbial dysbiosis in infants with CMPA.

A randomized controlled trial for response of microbiome network to exercise and diet intervention in patients with nonalcoholic fatty liver disease

Exercise and diet are treatments for nonalcoholic fatty liver disease (NAFLD) and prediabetes, however, how exercise and diet interventions impact gut microbiota in patients is incompletely understood. We previously reported a 8.6-month, four-arm (Aerobic exercise, n = 29; Diet, n = 28; Aerobic exercise + Diet, n = 29; No intervention, n = 29) randomized, singe blinded (for researchers), and controlled intervention in patients with NAFLD and prediabetes to assess the effect of interventions on the primary outcomes of liver fat content and glucose metabolism. Here we report the third primary outcome of the trial—gut microbiota composition—in participants who completed the trial (22 in Aerobic exercise, 22 in Diet, 23 in Aerobic exercise + Diet, 18 in No Intervention). We show that combined aerobic exercise and diet intervention are associated with diversified and stabilized keystone taxa, while exercise and diet interventions alone increase network connectivity and robustness between taxa. No adverse effects were observed with the interventions. In addition, in exploratory ad-hoc analyses we find that not all subjects responded to the intervention in a similar manner, when using differentially altered gut microbe amplicon sequence variants abundance to classify the responders and low/non-responders. A personalized gut microbial network at baseline could predict the individual responses in liver fat to exercise intervention. Our findings suggest an avenue for developing personalized intervention strategies for treatment of NAFLD based on host-gut microbiome ecosystem interactions, however, future studies with large sample size are needed to validate these discoveries. The Trial Registration Number is ISRCTN 42622771.

Exercise and diet interventions are treatments for nonalcoholic fatty liver disease (NAFLD). Here the authors report that in randomized, controlled trial in patients with NAFLD exercise and diet intervention were associated with diversified gut microbiome keystone taxa. Exploratory analysis suggests gut microbial network may be used to predict the individual liver fat response to exercise intervention, if validated in future studies.

Inferring antibiotic susceptibility from metagenomic data: dream or reality?

BACKGROUND

The diagnosis of bacterial infections continues to rely on culture, a slow process in which antibiotic susceptibility profiles of potential pathogens are made available to clinicians 48h after sampling, at best. Recently, clinical metagenomics (CMg), the metagenomic sequencing of samples with the purpose of identifying microorganisms and determining their susceptibility to antimicrobials, has emerged as a potential diagnostic tool that could prove faster than culture. CMg indeed has the potential to detect antibiotic resistance genes (ARGs) and mutations associated with resistance. Nevertheless, many challenges have yet to be overcome in order to make rapid phenotypic inference of antibiotic susceptibility from metagenomic data a reality.

OBJECTIVES

The objective of this narrative review is to discuss the challenges underlying the phenotypic inference of antibiotic susceptibility from metagenomic data.

SOURCES

We conducted a narrative review using published articles available in the NCBI Pubmed database.

CONTENT

We review the current ARG databases with a specific emphasis on those which now provide associations with phenotypic data. Next, we discuss the bioinformatic tools designed to identify ARGs in metagenomes. We then report on the performance of phenotypic inference from genomic data and the issue predicting the expression of ARGs. Finally, we address the challenge of linking an ARG to this host.

IMPLICATIONS

Significant improvements have recently been made in associating ARG and phenotype, and the inference of susceptibility from genomic data has been demonstrated in pathogenic bacteria such as Staphylococci and Enterobacterales. Resistance involving gene expression is more challenging however, and inferring susceptibility from species such as Pseudomonas aeruginosa remains difficult. Future research directions include the consideration of gene expression via RNA sequencing and machine learning.

CBEA: Competitive balances for taxonomic enrichment analysis

Research in human-associated microbiomes often involves the analysis of taxonomic count tables generated via high-throughput sequencing. It is difficult to apply statistical tools as the data is high-dimensional, sparse, and compositional. An approachable way to alleviate high-dimensionality and sparsity is to aggregate variables into pre-defined sets. Set-based analysis is ubiquitous in the genomics literature and has demonstrable impact on improving interpretability and power of downstream analysis. Unfortunately, there is a lack of sophisticated set-based analysis methods specific to microbiome taxonomic data, where current practice often employs abundance summation as a technique for aggregation. This approach prevents comparison across sets of different sizes, does not preserve inter-sample distances, and amplifies protocol bias. Here, we attempt to fill this gap with a new single-sample taxon enrichment method that uses a novel log-ratio formulation based on the competitive null hypothesis commonly used in the enrichment analysis literature. Our approach, titled competitive balances for taxonomic enrichment analysis (CBEA), generates sample-specific enrichment scores as the scaled log-ratio of the subcomposition defined by taxa within a set and the subcomposition defined by its complement. We provide sample-level significance testing by estimating an empirical null distribution of our test statistic with valid p-values. Herein, we demonstrate, using both real data applications and simulations, that CBEA controls for type I error, even under high sparsity and high inter-taxa correlation scenarios. Additionally, CBEA provides informative scores that can be inputs to downstream analyses such as prediction tasks.

HDHL-INTIMIC: A European Knowledge Platform on Food, Diet, Intestinal Microbiomics, and Human Health

Studies indicate that the intestinal microbiota influences general metabolic processes in humans, thereby modulating the risk of chronic diseases such as type 2 diabetes, allergy, cardiovascular disease, and colorectal cancer (CRC). Dietary factors are also directly related to chronic disease risk, and they affect the composition and function of the gut microbiota. Still, detailed knowledge on the relation between diet, the microbiota, and chronic disease risk is limited. The overarching aim of the HDHL-INTIMIC (INtesTInal MICrobiomics) knowledge platform is to foster studies on the microbiota, nutrition, and health by assembling available knowledge of the microbiota and of the other aspects (e.g., food science and metabolomics) that are relevant in the context of microbiome research. The goal is to make this information findable, accessible, interoperable, and reusable (FAIR) to the scientific community, and to share information with the various stakeholders. Through these efforts a network of transnational and multidisciplinary collaboration has emerged, which has contributed to further develop and increase the impact of microbiome research in human health. The roles of microbiota in early infancy, during ageing, and in subclinical and clinically manifested disease are identified as urgent areas of research in this knowledge platform.

HiFine: integrating Hi-c-based and shotgun-based methods to reFine binning of metagenomic contigs

MOTIVATION

Metagenomic binning aims to retrieve microbial genomes directly from ecosystems by clustering metagenomic contigs assembled from short reads into draft genomic bins. Traditional shotgun-based binning methods depend on the contigs' composition and abundance profiles and are impaired by the paucity of enough samples to construct reliable co-abundance profiles. When applied to a single sample, shotgun-based binning methods struggle to distinguish closely related species only using composition information. As an alternative binning approach, Hi-C-based binning employs metagenomic Hi-C technique to measure the proximity contacts between metagenomic fragments. However, spurious inter-species Hi-C contacts inevitably generated by incorrect ligations of DNA fragments between species link the contigs from varying genomes, weakening the purity of final draft genomic bins. Therefore, it is imperative to develop a binning pipeline to overcome the shortcomings of both types of binning methods on a single sample.

RESULTS

We develop HiFine, a novel binning pipeline to refine the binning results of metagenomic contigs by integrating both Hi-C-based and shotgun-based binning tools. HiFine designs a strategy of fragmentation for the original bin sets derived from the Hi-C-based and shotgun-based binning methods, which considerably increases the purity of initial bins, followed by merging fragmented bins and recruiting unbinned contigs. We demonstrate that HiFine significantly improves the existing binning results of both types of binning methods and achieves better performance in constructing species genomes on publicly available datasets. To the best of our knowledge, HiFine is the first pipeline to integrate different types of tools for the binning of metagenomic contigs.

AVAILABILITY

HiFine is available at https://github.com/dyxstat/HiFine.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A deep siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments

Metagenomic binning is the step in building metagenome-assembled genomes (MAGs) when sequences predicted to originate from the same genome are automatically grouped together. The most widely-used methods for binning are reference-independent, operating de novo and enable the recovery of genomes from previously unsampled clades. However, they do not leverage the knowledge in existing databases. Here, we introduce SemiBin, an open source tool that uses deep siamese neural networks to implement a semi-supervised approach, i.e. SemiBin exploits the information in reference genomes, while retaining the capability of reconstructing high-quality bins that are outside the reference dataset. Using simulated and real microbiome datasets from several different habitats from GMGCv1 (Global Microbial Gene Catalog), including the human gut, non-human guts, and environmental habitats (ocean and soil), we show that SemiBin outperforms existing state-of-the-art binning methods. In particular, compared to other methods, SemiBin returns more high-quality bins with larger taxonomic diversity, including more distinct genera and species.

Distinct Functional Metagenomic Markers Predict the Responsiveness to Anti-PD-1 Therapy in Chinese Non-Small Cell Lung Cancer Patients

Background

Programmed death 1 (PD-1) and the ligand of PD-1 (PD-L1) are central targets for immune-checkpoint therapy (ICT) blocking immune evasion-related pathways elicited by tumor cells. A number of PD-1 inhibitors have been developed, but the efficacy of these inhibitors varies considerably and is typically below 50%. The efficacy of ICT has been shown to be dependent on the gut microbiota, and experiments using mouse models have even demonstrated that modulation of the gut microbiota may improve efficacy of ICT.

Methods

We followed a Han Chinese cohort of 85 advanced non-small cell lung cancer (NSCLC) patients, who received anti-PD-1 antibodies. Tumor biopsies were collected before treatment initiation for whole exon sequencing and variant detection. Fecal samples collected biweekly during the period of anti-PD-1 antibody administration were used for metagenomic sequencing. We established gut microbiome abundance profiles for identification of significant associations between specific microbial taxa, potential functionality, and treatment responses. A prediction model based on random forest was trained using selected markers discriminating between the different response groups.

Results

NSCLC patients treated with antibiotics exhibited the shortest survival time. Low level of tumor-mutation burden and high expression level of HLA-E significantly reduced progression-free survival. We identified metagenomic species and functional pathways that differed in abundance in relation to responses to ICT. Data on differential enrichment of taxa and predicted microbial functions in NSCLC patients responding or non-responding to ICT allowed the establishment of random forest algorithm-adopted models robustly predicting the probability of whether or not a given patient would benefit from ICT.

Conclusions

Overall, our results identified links between gut microbial composition and immunotherapy efficacy in Chinese NSCLC patients indicating the potential for such analyses to predict outcome prior to ICT.

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.

Precise genotyping of circular mobile elements from metagenomic data uncovers human-associated plasmids with recent common ancestors

Mobile genetic elements with circular genomes play a key role in the evolution of microbial communities. Their circular genomes correspond to circular walks in metagenome graphs, and yet, assemblies derived from natural microbial communities produce graphs riddled with spurious cycles, complicating the accurate reconstruction of circular genomes. We present DomCycle, an algorithm that reconstructs likely circular genomes based on the identification of so-called 'dominant' graph cycles. In the implementation we leverage paired reads to bridge assembly gaps and scrutinize cycles through a nucleotide-level analysis, making the approach robust to misassembly artifacts. We validated the approach using simulated and real sequencing data. Application of DomCycle to 32 publicly available DNA shotgun sequence data sets from diverse natural environments led to the reconstruction of hundreds of circular mobile genomes. Clustering revealed 20 highly prevalent and cryptic plasmids that have clonal population structures with recent common ancestors. This method facilitates the study of microbial communities that evolve through horizontal gene transfer.

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.

Inter-species Metabolic Interactions in an In-vitro Minimal Human Gut Microbiome of Core Bacteria

Knowledge of the functional roles and interspecies interactions are crucial for improving our understanding of the human intestinal microbiome in health and disease. However, the complexity of the human intestinal microbiome and technical challenges in investigating it pose major challenges. In this proof-of-concept study, we rationally designed, assembled and experimentally tested a synthetic Diet-based Minimal Microbiome (Db-MM) consisting of ten core intestinal bacterial species that together are capable of efficiently converting dietary fibres into short chain fatty acids (SCFAs). Despite their genomic potential for metabolic competition, all ten bacteria coexisted during growth on a mixture of dietary fibres, including pectin, inulin, xylan, cellobiose and starch. By integrated analyses of metabolite production, community composition and metatranscriptomics-based gene expression data, we identified interspecies metabolic interactions leading to production of key SCFAs such as butyrate and propionate. While public goods, such as sugars liberated from colonic fibres, are harvested by non-degraders, some species thrive by cross-feeding on energetically challenging substrates, including the butyrogenic conversion of acetate and lactate. Using a reductionist approach in an in-vitro system combined with functional measurements, our study provides key insights into the complex interspecies metabolic interactions between core intestinal bacterial species.

Comparative Analysis of the Gut Microbiota of Mongolian Gazelle (Procapra gutturosa) Under Fragmented Habitats

The existence of man-made facilities such as pasture fences makes the grassland ecosystem fragmented and endangers the survival of local wild animals. The Mongolian gazelle is highly sensitive to hunting and habitat destruction, and is one of the most threatened artiodactyls in Eurasia. It provides a critical model to studying gut microbiota under fragmented habitats. Therefore, we applied metagenomics sequencing to analyze the gut microbiota communities and functions of Mongolian gazelle under fragmented habitats. The results demonstrated that there were no significant differences in gut microbial communities between the different groups at both the phylum and genus level. The functional analyses showed that the Mongolian gazelle in fragmented habitat had a stronger ability to degrade naphthalene, but their ability to absorb carbohydrates was weaker. This study provided fundamental information about the gut microbiota of Mongolian gazelle, and we recommend reducing habitat fragmentation to better protect the Mongolian gazelle.

Life History Recorded in the Vagino-cervical Microbiome Along with Multi-omes

The vagina contains at least a billion microbial cells, dominated by lactobacilli. Here we perform metagenomic shotgun sequencing on cervical and fecal samples from a cohort of 516 Chinese women of reproductive age, as well as cervical, fecal, and salivary samples from a second cohort of 632 women. Factors such as pregnancyhistory, delivery history, cesarean section, and breastfeeding were all more important than menstrual cycle in shaping the microbiome, and such information would be necessary before trying to interpret differences between vagino-cervical microbiome data. Greater proportion of Bifidobacterium breve was seen with older age at sexual debut. The relative abundance of lactobacilli especially Lactobacillus crispatus was negatively associated with pregnancy history. Potential markers for lack of menstrual regularity, heavy flow, dysmenorrhea, and contraceptives were also identified. Lactobacilli were rare during breastfeeding or post-menopause. Other features such as mood fluctuations and facial speckles could potentially be predicted from the vagino-cervical microbiome. Gut and salivary microbiomes, plasma vitamins, metals, amino acids, and hormones showed associations with the vagino-cervical microbiome. Our results offer an unprecedented glimpse into the microbiota of the female reproductive tract and call for international collaborations to better understand its long-term health impact other than in the settings of infection or pre-term birth.