Resilience of human gut microbial communities for the long stay with multiple dietary shifts

Gut microbiota regulates gut homeostasis, mucosal immunity and influences immune-related diseases

The intestinal microbiome constitutes a sophisticated and massive ecosystem pivotal for maintaining gastrointestinal equilibrium and mucosal immunity via diverse pathways. The gut microbiota is continuously reshaped by multiple environmental factors, thereby influencing overall wellbeing or predisposing individuals to disease state. Many observations reveal an altered microbiome composition in individuals with autoimmune conditions, coupled with shifts in metabolic profiles, which has spurred ongoing development of therapeutic interventions targeting the microbiome. This review delineates the microbial consortia of the intestine, their role in sustaining gastrointestinal stability, the association between the microbiome and immune-mediated pathologies, and therapeutic modalities focused on microbiome modulation. We emphasize the entire role of the intestinal microbiome in human health and recommend microbiome modulation as a viable strategy for disease prophylaxis and management. However, the application of gut microbiota modification for the treatment of immune-related diseases, such as fecal microbiota transplantation and probiotics, remain quite challenging. Therefore, more research is needed into the role and mechanisms of these therapeutics.

A cross-sectional comparison of gut metagenomes between dairy workers and community controls

BACKGROUND

As a nexus of routine antibiotic use and zoonotic pathogen presence, the livestock farming environment is a potential hotspot for the emergence of zoonotic diseases and antibiotic resistant bacteria. Livestock can further facilitate disease transmission by serving as intermediary hosts for pathogens before a spillover event. In light of this, we aimed to characterize the microbiomes and resistomes of dairy workers, whose exposure to the livestock farming environment places them at risk for facilitating community transmission of antibiotic resistant genes and emerging zoonotic diseases.

RESULTS

Using shotgun sequencing, we investigated differences in the taxonomy, diversity and gene presence of 10 dairy farm workers and 6 community controls' gut metagenomes, contextualizing these samples with additional publicly available gut metagenomes. We found no significant differences in the prevalence of resistance genes, virulence factors, or taxonomic composition between the two groups. The lack of statistical significance may be attributed, in part, to the limited sample size of our study or the potential similarities in exposures between the dairy workers and community controls. We did, however, observe patterns warranting further investigation including greater abundance of tetracycline resistance genes and prevalence of cephamycin resistance genes as well as lower average gene diversity (even after accounting for differential sequencing depth) in dairy workers' metagenomes. We also found evidence of commensal organism association with tetracycline resistance genes in both groups (including Faecalibacterium prausnitzii, Ligilactobacillus animalis, and Simiaoa sunii).

CONCLUSIONS

This study highlights the utility of shotgun metagenomics in examining the microbiomes and resistomes of livestock workers, focusing on a cohort of dairy workers in the United States. While our study revealed no statistically significant differences between groups in taxonomy, diversity and gene presence, we observed patterns in antibiotic resistance gene abundance and prevalence that align with findings from previous studies of livestock workers in China and Europe. Our results lay the groundwork for future research involving larger cohorts of dairy and non-dairy workers to better understand the impact of occupational exposure to livestock farming on the microbiomes and resistomes of workers.

Peeling off the layers from microbial dark matter (MDM): recent advances, future challenges, and opportunities

Microbes represent the most common organisms on Earth; however, less than 2% of microbial species in the environment can undergo cultivation for study under laboratory conditions, and the rest of the enigmatic, microbial world remains mysterious, constituting a kind of "microbial dark matter" (MDM). In the last two decades, remarkable progress has been made in culture-dependent and culture-independent techniques. More recently, studies of MDM have relied on culture-independent techniques to recover genetic material through either unicellular genomics or shotgun metagenomics to construct single-amplified genomes (SAGs) and metagenome-assembled genomes (MAGs), respectively, which provide information about evolution and metabolism. Despite the remarkable progress made in the past decades, the functional diversity of MDM still remains uncharacterized. This review comprehensively summarizes the recently developed culture-dependent and culture-independent techniques for characterizing MDM, discussing major challenges, opportunities, and potential applications. These activities contribute to expanding our knowledge of the microbial world and have implications for various fields including Biotechnology, Bioprospecting, Functional genomics, Medicine, Evolutionary and Planetary biology. Overall, this review aims to peel off the layers from MDM, shed light on recent advancements, identify future challenges, and illuminate the exciting opportunities that lie ahead in unraveling the secrets of this intriguing microbial realm.

Different gut microbial types were found in captive striped hamsters

Background

Typing analysis has become a popular approach to categorize individual differences in studies of animal gut microbial communities. However, previous definitions of gut microbial types were more understood as a passive reaction process to different external interferences, as most studies involve diverse environmental variables. We wondered whether distinct gut microbial types can also occur in animals under the same external environment. Moreover, the role of host sex in shaping gut microbiota has been widely reported; thus, the current study preliminarily explores the effects of sex on potential different microbial types.

Methods

Here, adult striped hamsters Cricetulus barabensis of different sexes were housed under the same controlled laboratory conditions, and their fecal samples were collected after two months to assess the gut microbiota by 16S rRNA sequencing.

Results

The gut microbiota of captive striped hamsters naturally separated into two types at the amplicon sequence variant (ASV) level. There was a significant difference in the Shannon index among these two types. A receiver operating characteristic (ROC) curve showed that the top 30 ASVs could effectively distinguish each type. Linear discriminant analysis of effect size (LEfSe) showed enrichment of the genera Lactobacillus, Treponema and Pygmaiobacter in one gut microbial type and enrichment of the genera Turicibacter and Ruminiclostridium in the other. The former type had higher carbohydrate metabolism ability, while the latter harbored a more complex co-occurrence network and higher amino acid metabolism ability. The gut microbial types were not associated with sex; however, we did find sex differences in the relative abundances of certain bacterial taxa, including some type-specific sex variations.

Conclusions

Although captive animals live in a unified environment, their gut bacteria can still differentiate into distinct types, but the sex of the hosts may not play an important role in the typing process of small-scale captive animal communities. The relevant driving factors as well as other potential types need to be further investigated to better understand host-microbe interactions.

Differences in gut metagenomes between dairy workers and community controls: a cross-sectional study

Background

As a nexus of routine antibiotic use and zoonotic pathogen presence, the livestock farming environment is a potential hotspot for the emergence of zoonotic diseases and antibiotic resistant bacteria. Livestock can further facilitate disease transmission by serving as intermediary hosts for pathogens as they undergo evolution prior to a spillover event. In light of this, we are interested in characterizing the microbiome and resistome of dairy workers, whose exposure to the livestock farming environment places them at risk for facilitating community transmission of antibiotic resistant genes and emerging zoonotic diseases.

Results

Using shotgun sequencing, we investigated differences in the taxonomy, diversity and gene presence of the human gut microbiome of 10 dairy farm workers and 6 community controls, supplementing these samples with additional publicly available gut metagenomes. We observed greater abundance of tetracycline resistance genes and prevalence of cephamycin resistance genes in dairy workers' metagenomes, and lower average gene diversity. We also found evidence of commensal organism association with plasmid-mediated tetracycline resistance genes in both dairy workers and community controls (including Faecalibacterium prausnitzii, Ligilactobacillus animalis, and Simiaoa sunii). However, we did not find significant differences in the prevalence of resistance genes or virulence factors overall, nor differences in the taxonomic composition of dairy worker and community control metagenomes.

Conclusions

This study presents the first metagenomics analysis of United States dairy workers, providing insights into potential risks of exposure to antibiotics and pathogens in animal farming environments. Previous metagenomic studies of livestock workers in China and Europe have reported increased abundance and carriage of antibiotic resistance genes in livestock workers. While our investigation found no strong evidence for differences in the abundance or carriage of antibiotic resistance genes and virulence factors between dairy worker and community control gut metagenomes, we did observe patterns in the abundance of tetracycline resistance genes and the prevalence of cephamycin resistance genes that is consistent with previous work.

Microbiome-based enrichment pattern mining has enabled a deeper understanding of the biome-species-function relationship

Microbes live in diverse habitats (i.e. biomes), yet their species and genes were biome-specific, forming enrichment patterns. These enrichment patterns have mirrored the biome-species-function relationship, which is shaped by ecological and evolutionary principles. However, a grand picture of these enrichment patterns, as well as the roles of external and internal factors in driving these enrichment patterns, remain largely unexamined. In this work, we have examined the enrichment patterns based on 1705 microbiome samples from four representative biomes (Engineered, Gut, Freshwater, and Soil). Moreover, an "enrichment sphere" model was constructed to elucidate the regulatory principles behind these patterns. The driving factors for this model were revealed based on two case studies: (1) The copper-resistance genes were enriched in Soil biomes, owing to the copper contamination and horizontal gene transfer. (2) The flagellum-related genes were enriched in the Freshwater biome, due to high fluidity and vertical gene accumulation. Furthermore, this enrichment sphere model has valuable applications, such as in biome identification for metagenome samples, and in guiding 3D structure modeling of proteins. In summary, the enrichment sphere model aims towards creating a bluebook of the biome-species-function relationships and be applied in many fields.

Tracing human life trajectory using gut microbial communities by context-aware deep learning

The gut microbial communities are highly plastic throughout life, and the human gut microbial communities show spatial-temporal dynamic patterns at different life stages. However, the underlying association between gut microbial communities and time-related factors remains unclear. The lack of context-awareness, insufficient data, and the existence of batch effect are the three major issues, making the life trajection of the host based on gut microbial communities problematic. Here, we used a novel computational approach (microDELTA, microbial-based deep life trajectory) to track longitudinal human gut microbial communities' alterations, which employs transfer learning for context-aware mining of gut microbial community dynamics at different life stages. Using an infant cohort, we demonstrated that microDELTA outperformed Neural Network for accurately predicting the age of infant with different delivery mode, especially for newborn infants of vaginal delivery with the area under the receiver operating characteristic curve of microDELTA and Neural Network at 0.811 and 0.436, respectively. In this context, we have discovered the influence of delivery mode on infant gut microbial communities. Along the human lifespan, we also applied microDELTA to a Chinese traveler cohort, a Hadza hunter-gatherer cohort and an elderly cohort. Results revealed the association between long-term dietary shifts during travel and adult gut microbial communities, the seasonal cycling of gut microbial communities for the Hadza hunter-gatherers, and the distinctive microbial pattern of elderly gut microbial communities. In summary, microDELTA can largely solve the issues in tracing the life trajectory of the human microbial communities and generate accurate and flexible models for a broad spectrum of microbial-based longitudinal researches.

Microbial Dark Matter: from Discovery to Applications

With the rapid increase of the microbiome samples and sequencing data, more and more knowledge about microbial communities has been gained. However, there is still much more to learn about microbial communities, including billions of novel species and genes, as well as countless spatiotemporal dynamic patterns within the microbial communities, which together form the microbial dark matter. In this work, we summarized the dark matter in microbiome research and reviewed current data mining methods, especially artificial intelligence (AI) methods, for different types of knowledge discovery from microbial dark matter. We also provided case studies on using AI methods for microbiome data mining and knowledge discovery. In summary, we view microbial dark matter not as a problem to be solved but as an opportunity for AI methods to explore, with the goal of advancing our understanding of microbial communities, as well as developing better solutions to global concerns about human health and the environment.

Individual variations and effects of birth facilities on the fecal microbiome of laboratory-bred marmosets (Callithrix jacchus) assessed by a longitudinal study

Laboratory animals are used for scientific research in various fields. In recent years, there has been a concern that the gut microbiota may differ among laboratory animals, which may yield different results in different laboratories where in-vivo experiments are performed. Our knowledge of the gut microbiota of laboratory-reared common marmosets (Callithrix jacchus) is limited; thus, in this study, we analyzed the daily changes in fecal microbiome composition, individual variations, and effects of the birth facility in healthy female laboratory-reared marmosets, supplied by three vendors. We showed that the marmoset fecal microbiome varied among animals from the same vendor and among animals from different vendors (birth facility), with daily changes of approximately 37%. The fecal microbiome per vendor is characterized by alpha diversity and specific bacteria, with Bifidobacterium for vendor A, Phascolarctobacterium for vendor B, and Megamonas for vendor C. Furthermore, we found that plasma progesterone concentrations and estrous cycles were not correlated with daily fecal microbiome changes. In contrast, animals with an anovulatory cycle lacked Megamonas and Desulfovibrio bacteria compared to normal estrous females. This study suggests that the source of the animal, such as breeding and housing facilities, is important for in-vivo experiments on the marmoset gut microbiota.

Microbiome Resilience and Health Implications for People in Half-Year Travel

Travel entail change in geography and diet, both of which are known as determinant factors in shaping the human gut microbiome. Additionally, altered gut microbiome modulates immunity, bringing about health implications in humans. To explore the effects of the mid-term travel on the gut microbiome, we generated 16S rRNA gene and metagenomic sequencing data from longitudinal samples collected over six months. We monitored dynamic trajectories of the gut microbiome variation of a Chinese volunteer team (VT) in their whole journey to Trinidad and Tobago (TAT). We found gut microbiome resilience that VT’s gut microbial compositions gradually transformed to the local TAT’s enterotypes during their six-month stay in TAT, and then reverted to their original enterotypes after VT’s return to Beijing in one month. Moreover, we identified driven species in this bi-directional plasticity that could play a role in immunity modulation, as exemplified by Bacteroides dorei that attenuated atherosclerotic lesion formation and effectively suppressed proinflammatory immune response. Another driven species P. copri could play a crucial role in rheumatoid arthritis pathogenesis, a chronic autoimmune disease. Carbohydrate-active enzymes are often implicated in immune and host-pathogen interactions, of which glycoside hydrolases were found decreased but glycosyltransferases and carbohydrate esterases increased during the travel; these functions were then restored after VT’ returning to Beijing. Furthermore, we discovered these microbial changes and restoration were mediated by VT people’s dietary changes. These findings indicate that half-year travel leads to change in enterotype and functional patterns, exerting effects on human health. Microbial intervention by dietary guidance in half-year travel would be conducive to immunity modulation for maintaining health.

Coated tannin supplementation improves growth performance, nutrients digestibility, and intestinal function in weaned piglets

To explore the effect of coated tannin (CT) on the growth performance, nutrients digestibility, and intestinal function in weaned piglets, a total of 180 piglets Duroc × Landrace × Yorkshire (28 d old) weighing about 8.6 kg were randomly allotted to three treatments: 1) Con: basal diet (contains ZnSO4); 2) Tan: basal diet + 0.15% CT; and 3) ZnO: basal diet + ZnO (Zn content is 1,600 mg/kg). The results showed that 0.15% CT could highly increase the average daily gain and average daily feed intake of weaned piglets compared with the control group, especially decreasing diarrhea incidence significantly (P < 0.05). Compared with the control group, crude protein apparent digestibility and digestive enzyme activity of the piglets fed with 0.15% CT were enhanced obviously (P < 0.05). Meanwhile, the intestinal villi and microvilli arranged more densely, while the content of serum diamine oxidase was decreased, and the protein expressions of zonula occludens-1 (ZO-1) and claudin-1 were significantly upregulated (P < 0.05). In addition, CT altered the structure of intestinal microbiota and augmented some butyrate-producing bacteria such as Ruminococcaceae and Megasphaera. PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) analysis also showed that the abundances of pathways related to butyrate metabolism and tryptophan metabolism were increased; however, the function of lipopolysaccharide biosynthesis proteins was significantly decreased. The results demonstrated that 0.15% CT could improve growth performance, digestibility, and intestinal function of weaned piglets, and it had the potential to replace ZnO applied to farming.

Multi-Omics Analyses Characterize the Gut Microbiome and Metabolome Signatures of Soldiers Under Sustained Military Training

Exercise can directly alter the gut microbiome at the compositional and functional metabolic levels, which in turn may beneficially influence physical performance. However, data how the gut microbiome and fecal metabolome change, and how they interact in soldiers who commonly undergo sustained military training are limited. To address this issue, we first performed 16S rRNA sequencing to assess the gut microbial community patterns in a cohort of 80 soldiers separated into elite soldiers (ES, n = 40) and non-elite soldiers (N-ES, n = 40). We observed that the α-diversities of the ES group were higher than those of the N-ES group. As for both taxonomical structure and phenotypic compositions, elite soldiers were mainly characterized by an increased abundance of bacteria producing short-chain fatty acids (SCFAs), including Ruminococcaceae_UCG-005, Prevotella_9, and Veillonella, as well as a higher proportion of oxidative stress tolerant microbiota. The taxonomical signatures of the gut microbiome were significantly correlated with soldier performance. To further investigate the metabolic activities of the gut microbiome, using an untargeted metabolomic method, we found that the ES and N-ES groups displayed significantly different metabolic profiles and differential metabolites were primarily involved in the metabolic network of carbohydrates, energy, and amino acids, which might contribute to an enhanced exercise phenotype. Furthermore, these differences in metabolites were strongly correlated with the altered abundance of specific microbes. Finally, by integrating multi-omics data, we identified a shortlist of bacteria-metabolites associated with physical performance, following which a random forest classifier was established based on the combinatorial biomarkers capable of distinguishing between elite and non-elite soldiers with high accuracy. Our findings suggest possible future modalities for improving physical performance through targeting specific bacteria associated with more energetically efficient metabolic patterns.

Ontology-aware neural network: a general framework for pattern mining from microbiome data

With the rapid accumulation of microbiome data around the world, numerous computational bioinformatics methods have been developed for pattern mining from such paramount microbiome data. Current microbiome data mining methods, such as gene and species mining, rely heavily on sequence comparison. Most of these methods, however, have a clear trade-off, particularly, when it comes to big-data analytical efficiency and accuracy. Microbiome entities are usually organized in ontology structures, and pattern mining methods that have considered ontology structures could offer advantages in mining efficiency and accuracy. Here, we have summarized the ontology-aware neural network (ONN) as a novel framework for microbiome data mining. We have discussed the applications of ONN in multiple contexts, including gene mining, species mining and microbial community dynamic pattern mining. We have then highlighted one of the most important characteristics of ONN, namely, novel knowledge discovery, which makes ONN a standout among all microbiome data mining methods. Finally, we have provided several applications to showcase the advantage of ONN over other methods in microbiome data mining. In summary, ONN represents a paradigm shift for pattern mining from microbiome data: from traditional machine learning approach to ontology-aware and model-based approach, which has found its broad application scenarios in microbiome data mining.

The gut microbial diversity of colon cancer patients and the clinical significance

The microbial diversity and communities in the excrement of healthy and patients suffered from cancer were identified by 16SrDNA sequencing performed on the Illumina Hi Seq sequencing platform. The microbial difference was also analyzed. The sequencing results showed high quality of the data, and the microbial communities were more various in the excrement of cancer patients. And the abundance of Firmicutes phylum was significantly reduced in cancer group. The phylum of Fermicutes, Bacteroidetes in cancer group are significantly down-regulated and up-regulated compared with normal group. The species of Faecalibacterium prausnitzii, Bateroides vulgatus and Fusicatenibacter saccharivorans are significantly lower in cancer group than that in normal group (P< 0.05). The species of Prevetella copri, M. uniformis, and Escherichia coli are significantly higher in the cancer group than that in normal group. The comparative results indicated that beneficial bacterium significantly decreased in colorectal cancer (CRC) group, and harmful bacterium significantly increased in the colon cancer group, meanwhile the acidity, sugar increased whereas the oxygen content decreased to facilitate the growth of harmful bacterium. The results would provide microbial approaches for the treatment of colon cancer by the intake of beneficial microbial communities.

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.

Early life host regulation of the mammalian enteric microbiota composition

The enteric microbiota exerts a major influence on the host. It promotes food degradation, nutrient absorption, immune maturation and protects from infection with pathogenic microorganisms. However, certain compositional alterations also enhance the risk to develop metabolic, inflammatory and immune-mediated diseases. This suggests that the enteric microbiota is subject to strong evolutionary pressure. Here, we hypothesize that endogenous, genetically determined mechanisms exist that shape and optimize the enteric microbiota. We discuss that the postnatal period as the starting point of the host-microbial interaction bears the greatest chance to identify such regulatory mechanisms and report on two recently identified ways how the neonate host favours or disfavours colonization by certain bacteria and thereby manipulates the postnatally emerging bacterial ecosystem. A better understanding of these mechanisms might ultimately help to define the features of a beneficial enteric microbiota and to develop interventional strategies to overcome adverse microbiota alterations.

Finding Colon Cancer- and Colorectal Cancer-Related Microbes Based on Microbe-Disease Association Prediction

Microbes are closely associated with the formation and development of diseases. The identification of the potential associations between microbes and diseases can boost the understanding of various complex diseases. Wet experiments applied to microbe-disease association (MDA) identification are costly and time-consuming. In this manuscript, we developed a novel computational model, NLLMDA, to find unobserved MDAs, especially for colon cancer and colorectal carcinoma. NLLMDA integrated negative MDA selection, linear neighborhood similarity, label propagation, information integration, and known biological data. The Gaussian association profile (GAP) similarity of microbes and GAPs similarity and symptom similarity of diseases were firstly computed. Secondly, linear neighborhood method was then applied to the above computed similarity matrices to obtain more stable performance. Thirdly, negative MDA samples were selected, and the label propagation algorithm was used to score for microbe-disease pairs. The final association probabilities can be computed based on the information integration method. NLLMDA was compared with the other five classical MDA methods and obtained the highest area under the curve (AUC) value of 0.9031 and 0.9335 on cross-validations of diseases and microbe-disease pairs. The results suggest that NLLMDA was an effective prediction method. More importantly, we found that Acidobacteriaceae may have a close link with colon cancer and Tannerella may densely associate with colorectal carcinoma.

Mechanisms of niche-neutrality balancing can drive the assembling of microbial community

One hotspot of present community ecology is to uncover the mechanisms of community succession. In this study, two popular concepts, niche-neutrality dynamic balancing and co-occurrence network analysis, were integrated to investigate the dispersal dynamics of microbial communities in a freshwater river continuum in subtropical China. Results showed that when habitat conditions were mild and appropriate, such as in the clean upstream river, free of heavy pollution or long-lasting extreme disturbances, stochastic processes could increase species diversities, and organize communities into relatively loosely linked and stable networks with higher modularity and more modules. However, when conditions became degraded under heavy pollution, the influence of neutrality diminished, and niche-based selection imposed more constraints on communities and guided the assembling processes in certain directions: depleting species richness, strengthening interspecies connections and breaking boundaries of modules. Consequently, communities became more sensitive to fluctuations so as to deal with the harsh conditions efficiently. Another interesting finding was that, both as keystone taxa of communities, module hubs were mostly neutrally distributed generalists with high abundances, and were beneficial to many related operational taxonomic units. In contrast, connectors were less abundant and their distributions were more subjected to the environments. Therefore, connectors were probably responsible for the information transmission between microbial communities and environments, as well as between different modules, and thus could restrict the dispersal of microbes and guide the direction of community assembly.

Utilizing microbiome approaches to assist source tracking, treatment and prevention of COVID-19: Review and assessment

COVID-19 has been one of the most serious infectious diseases since the end of 2019. However, the original source, as well as the treatment and prevention of causative agent of COVID-19 (namely SARS-CoV-2) are still unclear nearly a year after its publicly report. The microbiome approach, which has emerged in recent years focusing on human-related microbes, has become one of the promising avenues for source tracking, treatment, and prevention of a variety of infectious diseases including COVID-19. In this review, we summarized the microbiome approach as a supplementary approach for source tracking, treatment, and prevention of SARS-CoV-2 infection. We first provided background information on SARS-CoV-2 and microbiome approaches. Then we illustrated current strategies of microbiome methods to assist three aspects of COVID-19 research, namely source tracking, treatment, and prevention, respectively. Finally, we summarized the microbiome approaches and provided perspectives for future studies on faster and more effective SARS-CoV-2 epidemiology and pathogenesis based on microbiome approaches.

Stratification of athletes' gut microbiota: the multifaceted hubs associated with dietary factors, physical characteristics and performance

Gut microbial communities of athletes differ from that of sedentary persons in both diversity and the presence of certain taxa. However, it is unclear to what degree elite athletes and non-elite athletes harbor different gut microbial community patterns and if we can effectively monitor the potential of athletes based on microbiota. A team of professional female rowing athletes in China was recruited and 306 fecal samples were collected from 19 individuals, which were separated into three cohorts: adult elite athlete's (AE), youth elite athlete's (YE), and youth non-elite athlete's (YN). The differences in gut microbiome among different cohorts were compared, and their associations with dietary factors, physical characteristics, and athletic performance were investigated. The microbial diversities of elite athletes were higher than those of youth non-elite athletes. The taxonomical, functional, and phenotypic compositions of AE, YE and YN were significantly different. Additionally, three enterotypes with clear separation were identified in athlete's fecal samples, with majority of elite athletes stratified into enterotype 3. And this enterotype-dependent gut microbiome is strongly associated with athlete performances. These differences in athlete gut microbiota lead to establishment of a random forest classifier based on taxonomical and functional biomarkers, capable of differentiating elite athletes and non-elite athletes with high accuracy. Finally, these versatilities of athlete microbial communities of athletes were found to be associated with dietary factors and physical characteristics, which can in concert explain 41% of the variability in gut microbiome.

RNMFMDA: A Microbe-Disease Association Identification Method Based on Reliable Negative Sample Selection and Logistic Matrix Factorization With Neighborhood Regularization

Microbes with abnormal levels have important impacts on the formation and development of various complex diseases. Identifying possible Microbe-Disease Associations (MDAs) helps to understand the mechanisms of complex diseases. However, experimental methods for MDA identification are costly and time-consuming. In this study, a new computational model, RNMFMDA, was developed to find possible MDAs. RNMFMDA contains two main processes. First, Reliable Negative MDA samples were selected based on Positive-Unlabeled (PU) learning and random walk with restart on the heterogeneous microbe-disease network. Second, Logistic Matrix Factorization with Neighborhood Regularization (LMFNR) was developed to compute the association probabilities for all microbe-disease pairs. To evaluate the performance of the proposed RNMFMDA method, we compared RNMFMDA with five state-of-the-art MDA prediction methods based on five-fold cross-validations on microbes, diseases, and MDAs. As a result, RNMFMDA obtained the best AUCs of 0.6332, 0.8669, and 0.9081, respectively for the three five-fold cross validations, significantly outperforming other models. The promising prediction performance may be attributed to the following three features: highly quality negative MDA sample selection, LMFNR-based MDA prediction model, and various biological information integration. In addition, a few predicted microbe-disease pairs with high association scores are worthy of further experimental validation.

Gut microecology: Why our microbes could be key to our health

The human body contains a large number of microorganisms, and the gut microecology environment contains the largest number and types of microorganisms. The structure and function of gut microbiota are closely related to the health of the human body. In a cascade of studies, the diversity of gut microbiota and its metabolite often found changed in patients or mice model. What kind of gut microbiota that associated with the occurrence or treatment of diseases were also found in many studies. Gut microbiota and its products can affect the function of the human body. Short-chain fatty acids, bile acid, indoles and so on were found can regulate the inflammation, immune response to affect the process of diseases. Immune cells like natural killer T cells, CD3 + T cells were also found had a link to gut microbiota which associated with diseases. Changes in gut microbiota are associated with changes in the body's major systems, such as the digestive system, the endocrine system, the cardiovascular system, the endocrine and metabolic system, the urinary system diseases, the respiratory system and so on. It is of great significance to study gut microecology for the prevention and treatment of various human diseases.

Escherichia coli Residency in the Gut of Healthy Human Adults

Escherichia coli is one of the most well-studied bacterial species, but several significant knowledge gaps remain regarding its ecology and natural history. Specifically, the most important factors influencing its life as a member of the healthy human gut microbiome are either underevaluated or currently unknown. Distinct E. coli population dynamics have been observed over the past century from a handful of temporal studies conducted in healthy human adults. Early studies using serology up to the most recent studies using genotyping and DNA sequencing approaches have all identified long-lived E. coli residents and short-lived transients. This review summarizes these discoveries and other studies that focused on the underlying mechanisms that lead to establishment and maintenance of E. coli residency in healthy human adults. Many fundamental knowledge gaps remain and are highlighted with the hope of facilitating future studies in this exciting research area.

Enterotypes of the Gut Microbial Community and Their Response to Plant Secondary Compounds in Plateau Pikas

Animal gut microbiomes can be clustered into “enterotypes” characterized by an abundance of signature genera. The characteristic determinants, stability, and resilience of these community clusters remain poorly understood. We used plateau pika (Ochotona curzoniae) as a model and identified three enterotypes by 16S rDNA sequencing. Among the top 15 genera, 13 showed significantly different levels of abundance between the enterotypes combined with different microbial functions and distinct fecal short-chain fatty acids. We monitored changes in the microbial community associated with the transfer of plateau pikas from field to laboratory and observed that feeding them a single diet reduced microbial diversity, resulting in a single enterotype with an altered composition of the dominant bacteria. However, microbial diversity, an abundance of some changed dominant genera, and enterotypes were partially restored after adding swainsonine (a plant secondary compound found in the natural diet of plateau pikas) to the feed. These results provide strong evidence that gut microbial diversity and enterotypes are directly related to specific diet, thereby indicating that the formation of different enterotypes can help animals adapt to complex food conditions. Additionally, natural plant secondary compounds can maintain dominant bacteria and inter-individual differences of gut microbiota and promote the resilience of enterotypes in small herbivorous mammals.

Integrated genomic analysis reveals mutated ELF3 as a potential gallbladder cancer vaccine candidate

Gallbladder cancer (GBC) is an aggressive gastrointestinal malignancy with no approved targeted therapy. Here, we analyze exomes (n = 160), transcriptomes (n = 115), and low pass whole genomes (n = 146) from 167 gallbladder cancers (GBCs) from patients in Korea, India and Chile. In addition, we also sequence samples from 39 GBC high-risk patients and detect evidence of early cancer-related genomic lesions. Among the several significantly mutated genes not previously linked to GBC are ETS domain genes ELF3 and EHF, CTNNB1, APC, NSD1, KAT8, STK11 and NFE2L2. A majority of ELF3 alterations are frame-shift mutations that result in several cancer-specific neoantigens that activate T-cells indicating that they are cancer vaccine candidates. In addition, we identify recurrent alterations in KEAP1/NFE2L2 and WNT pathway in GBC. Taken together, these define multiple targetable therapeutic interventions opportunities for GBC treatment and management.

Probiotics maintain the intestinal microbiome homeostasis of the sailors during a long sea voyage

The challenging conditions encountered during long sea voyages increase the risk of health-threatening physiological and psychological stress for sailors compared with land-based workers. However, how the intestinal microbiota responds to a long sea voyage and whether there is a feasible approach for protecting gut health during sea voyage are still unexplored. Here, we designed a 30-d longitudinal study including a placebo group (n = 42) and a probiotic group (n = 40) and used shotgun metagenomic sequencing to explore the impacts of sea voyage on the intestinal microbiome of sailors. By comparing the intestinal microbiome of subjects in the placebo group at baseline (d 0) and at the end of the sea voyage (d 30), we observed an alteration in the intestinal microbiome during the long sea voyage based on the microbial structure; the results revealed an increase in the species Streptococcus gordonii and Klebsiella pneumoniae as well as a decrease in some functional features. However, the change in the microbial structure of sailors in the probiotic group between d 0 and d 30 was limited, which indicated a maintenance effect of probiotics on intestinal microbiome homeostasis. At the metagenomic strain level, a generally positive correlation was observed between probiotics and the strains belonging to Bifidobacterium longum and Bifidobacterium animalis, whereas a common negative correlation was observed between probiotics and Clostridium leptum; this result revealed the potential mechanism of maintaining intestinal microbiome homeostasis by probiotics. The present study provided a feasible approach for protecting gut health during a long sea voyage.

Adjusting the Prerelease Gut Microbial Community by Diet Training to Improve the Postrelease Fitness of Captive-Bred Acipenser dabryanus

As one of the most important tool for biodiversity restoration and endangered species conservation, reintroduction has been implemented worldwide. In reintroduction projects, prerelease conditioning could effectively increase postrelease fitness and survival by improving animals’ adaptation to transformation from artificial to natural environments. However, how early-life diet training affects individuals’ adaptation, fitness, and survival after release remains largely unknown. We hypothesized that early-life diet training would adjust the host’s gut microbial community, the gut microbial community would influence the host’s diet preference, and the host’s diet preference would impact its adaptation to diet provision transformation and then determine postrelease fitness and survival. To verify this hypothesis, we investigated the growth characteristics and gut microbes of Yangtze sturgeon (Acipenser dabryanus) trained with natural and formula diets at both the prerelease and postrelease stages. The results showed that (1) the gut microbial communities of the individuals trained with a natural diet (i.e., natural diet group) and formula diet (i.e., formula diet group) evolved to the optimal status for their corresponding diet provisions, (2) the individuals in the natural diet group paid a lower cost (i.e., changed their gut microbial communities less) during diet transformation and release into the natural environment than did the individuals in the formula diet group, and (3) the gut microbes in the natural diet group better supported postrelease fitness and survival than did the gut microbes in the formula diet group. The results indicated that better prerelease diet training with more appropriate training diets and times could improve the reintroduction of Yangtze sturgeon by adjusting the prerelease gut microbial community. Because a relationship between diet (preference) and gut microbes is common in animals from insects (such as Drosophila melanogaster) to mammals (such as Homo sapiens), our hypothesis verified by the case study on Yangtze sturgeon applies to other animals. We therefore encourage future studies to identify optimal training diets and times for each species to best adjust its prerelease gut microbial community and then improve its postrelease fitness and survival in reintroduction projects.

Environmental remodeling of human gut microbiota and antibiotic resistome in livestock farms

Anthropogenic environments have been implicated in enrichment and exchange of antibiotic resistance genes and bacteria. Here we study the impact of confined and controlled swine farm environments on temporal changes in the gut microbiome and resistome of veterinary students with occupational exposure for 3 months. By analyzing 16S rRNA and whole metagenome shotgun sequencing data in tandem with culture-based methods, we show that farm exposure shapes the gut microbiome of students, resulting in enrichment of potentially pathogenic taxa and antimicrobial resistance genes. Comparison of students’ gut microbiomes and resistomes to farm workers’ and environmental samples revealed extensive sharing of resistance genes and bacteria following exposure and after three months of their visit. Notably, antibiotic resistance genes were found in similar genetic contexts in student samples and farm environmental samples. Dynamic Bayesian network modeling predicted that the observed changes partially reverse over a 4-6 month period. Our results indicate that acute changes in a human’s living environment can persistently shape their gut microbiota and antibiotic resistome.

Environments where antibiotics are used indiscriminately exhibit microbial communities that can represent hot-spots of resistance gene enrichment, which in turn could spread to humans. Here, the authors characterize how exposure to swine farms environment lead to temporal changes in the gut microbiome and resistome of healthy veterinary students.

Gut microbiota in ulcerative colitis: insights on pathogenesis and treatment

Gut microbiota constitute the largest reservoir of the human microbiome and are an abundant and stable ecosystem-based on its diversity, complexity, redundancy, and host interactions This ecosystem is indispensable for human development and health. The integrity of the intestinal mucosal barrier depends on its interactions with gut microbiota. The commensal bacterial community is implicated in the pathogenesis of inflammatory bowel disease (IBD), including ulcerative colitis (UC). The dysbiosis of microbes is characterized by reduced biodiversity, abnormal composition of gut microbiota, altered spatial distribution, as well as interactions among microbiota, between different strains of microbiota, and with the host. The defects in microecology, with the related metabolic pathways and molecular mechanisms, play a critical role in the innate immunity of the intestinal mucosa in UC. Fecal microbiota transplantation (FMT) has been used to treat many diseases related to gut microbiota, with the most promising outcome reported in antibiotic-associated diarrhea, followed by IBD. This review evaluated the results of various reports of FMT in UC. The efficacy of FMT remains highly controversial, and needs to be regularized by integrated management, standardization of procedures, and individualization of treatment.

Impacts of the Plateau Environment on the Gut Microbiota and Blood Clinical Indexes in Han and Tibetan Individuals

The intestinal microbiota is significantly affected by the external environment, but our understanding of the effects of extreme environments such as plateaus is far from adequate. In this study, we systematically analyzed the variation in the intestinal microbiota and 76 blood clinical indexes among 393 healthy adults with different plateau living durations (Han individuals with no plateau living, with plateau living for 4 to 6 days, with plateau living for >3 months, and who returned to the plain for 3 months, as well as plateau-living Tibetans). The results showed that the high-altitude environment rapidly (4 days) and continually (more than 3 months) shaped both the intestinal microbiota and clinical indexes of the Han population. With prolongation of plateau living, the general characteristics of the intestinal microbiota and clinical indexes of the Han population were increasingly similar to those of the Tibetan population. The intestinal microbiota of the Han population that returned to the plain area for 3 months still resembled that of the plateau-living Han population rather than that of the Han population on the plain. Moreover, clinical indexes such as blood glucose were significantly lower in the plateau groups than in the nonplateau groups, while the opposite result was obtained for testosterone. Interestingly, there were Tibetan-specific correlations between glucose levels and Succinivibrio and Sarcina abundance in the intestine. The results of this study suggest that a hypoxic environment could rapidly and lastingly affect both the human intestinal microbiota and blood clinical indexes, providing new insights for the study of plateau adaptability.IMPORTANCE The data presented in the present study demonstrate that the hypoxic plateau environment has a profound impact on the gut microbiota and blood clinical indexes in Han and Tibetan individuals. The plateau-changed signatures of the gut microbiota and blood clinical indexes were not restored to the nonplateau status in the Han cohorts, even when the individuals returned to the plain from the plateau for several months. Our study will improve the understanding of the great impact of hypoxic environments on the gut microbiota and blood clinical indexes as well as the adaptation mechanism and intervention targets for plateau adaptation.

Microbiome Big-Data Mining and Applications Using Single-Cell Technologies and Metagenomics Approaches Toward Precision Medicine

With the development of high-throughput sequencing technologies as well as various bioinformatics analytic tools, microbiome is not a “microbial dark matter” anymore. In this review, we first summarized the current analytical strategies used for big-data mining such as single-cell sequencing and metagenomics. We then provided insights into the integration of these strategies, showing significant advantages in fully describing microbiome from multiple aspects. Moreover, we discussed the correlation between gut microbiome with host organs and diseases, confirming the importance of big-data mining in clinical practices. We finally proposed new ideas about the trend of big-data mining in microbiome using multi-omics approaches and single-cell sequencing. The integration of multi-omics approaches and single-cell sequencing can provide full understanding of microbiome at both macroscopic level and microscopic level, thus contributing to precision medicine.

Stereotypes About Enterotype: the Old and New Ideas

In 2011, the term “enterotype” first appeared to the general public in Nature, which refers to stratification of human gut microbiota. However, with more studies on enterotypes conducted nowadays, doubts about the existence and robustness of enterotypes have also emerged. Here we reviewed current opinions about enterotypes from both conceptual and analytical points of view. We firstly illustrated the definition of the enterotype and various factors influencing enterotypes, such as diet, administration of antibiotics, and age. Then we summarized lines of evidence that pose the concept against the enterotype, and described the current methods for enterotype analysis. Finally, we showed that the concept of enterotype has been extended to other ecological niches. Based on current studies on enterotypes, it has been clear that more studies with larger sample sizes are needed to characterize the enterotypes. Improved computational methods are also required to build sophisticated models, reflecting the dynamics and resilience of enterotypes.