Complex Microbial Communities Research Articles

The importance of host physical niches for the stability of gut microbiome composition.

Gut bacteria are prevalent throughout the Metazoa and form complex microbial communities associated with food breakdown, nutrient provision and disease prevention. How hosts acquire and maintain a consistent bacterial flora remains mysterious even in the best-studied animals, including humans, mice, fishes, squid, bugs, worms and flies. This essay visits the evidence that hosts have co-evolved relationships with specific bacteria and that some of these relationships are supported by specialized physical niches that select, sequester and maintain microbial symbionts. Genetics approaches could uncover the mechanisms for recruiting and maintaining the stable and consistent members of the microbiome. This article is part of the theme issue 'Sculpting the microbiome: how host factors determine and respond to microbial colonization'.

Data-driven prediction of colonization outcomes for complex microbial communities

Microbial interactions can lead to different colonization outcomes of exogenous species, be they pathogenic or beneficial in nature. Predicting the colonization of exogenous species in complex communities remains a fundamental challenge in microbial ecology, mainly due to our limited knowledge of the diverse mechanisms governing microbial dynamics. Here, we propose a data-driven approach independent of any dynamics model to predict colonization outcomes of exogenous species from the baseline compositions of microbial communities. We systematically validate this approach using synthetic data, finding that machine learning models can predict not only the binary colonization outcome but also the post-invasion steady-state abundance of the invading species. Then we conduct colonization experiments for commensal gut bacteria species Enterococcus faecium and Akkermansia muciniphila in hundreds of human stool-derived in vitro microbial communities, confirming that the data-driven approaches can predict the colonization outcomes in experiments. Furthermore, we find that while most resident species are predicted to have a weak negative impact on the colonization of exogenous species, strongly interacting species could significantly alter the colonization outcomes, e.g., Enterococcus faecalis inhibits the invasion of E. faecium invasion. The presented results suggest that the data-driven approaches are powerful tools to inform the ecology and management of microbial communities.

Indole signaling enhances biofilm formation and quorum sensing in sequencing biofilm batch reactors

Indole is a heterocyclic organic compound that acts as a signaling molecule to regulate biofilm formation (BF) by microorganisms. However, the potential roles of indole in BF among microbial communities in wastewater treatment systems remain unknown. In this study, the effects of indole signaling on BF and quorum sensing (QS) of the complex microbial communities in sequencing batch biofilm reactors were systematically explored. The results showed that indole at 200 mg/L increased BF along with concentrations of homoserine lactones. High-throughput sequencing revealed the underlying mechanism of notable differences in the BF capacity of microbial communities between the indole-treated and control groups. The indole-related metabolic and QS functions of the genera in the biofilm were annotated based on the QS-related protein database and previous studies. Relative abundance analysis showed that the QS-related genera, such as Acinetobacter, that produce indole oxygenase were significantly enriched in the indole-treatment group. In addition, bioinformatics analyses revealed that indole at 200 mg/L enhanced BF, QS, and protein efflux. Based on a phylogenetic molecular ecological network, QS was positively correlated to indole treatment of Burkholderia, suggesting that indole promotes QS and BF. This study provides new insights into the effects of indole signaling on BF of microbes and sheds light on its potential regulatory mechanism in wastewater treatment plants.

Phyllosphere bacterial community dynamics in response to bacterial wildfire disease: succession and interaction patterns.

Plants interact with complex microbial communities in which microorganisms play different roles in plant development and health. While certain microorganisms may cause disease, others promote nutrient uptake and resistance to stresses through a variety of mechanisms. Developing plant protection measures requires a deeper comprehension of the factors that influence multitrophic interactions and the organization of phyllospheric communities. High-throughput sequencing was used in this work to investigate the effects of climate variables and bacterial wildfire disease on the bacterial community's composition and assembly in the phyllosphere of tobacco (Nicotiana tabacum L.). The samples from June (M1), July (M2), August (M3), and September (M4) formed statistically separate clusters. The assembly of the whole bacterial population was mostly influenced by stochastic processes. PICRUSt2 predictions revealed genes enriched in the M3, a period when the plant wildfire disease index reached climax, were associated with the development of the wildfire disease (secretion of virulence factor), the enhanced metabolic capacity and environmental adaption. The M3 and M4 microbial communities have more intricate molecular ecological networks (MENs), bursting with interconnections within a densely networked bacterial population. The relative abundances of plant-beneficial and antagonistic microbes Clostridiales, Bacillales, Lactobacillales, and Sphingobacteriales, showed significant decrease in severally diseased sample (M3) compared to the pre-diseased samples (M1/M2). Following the results of MENs, we further test if the correlating bacterial pairs within the MEN have the possibility to share functional genes and we have unraveled 139 entries of such horizontal gene transfer (HGT) events, highlighting the significance of HGT in shaping the adaptive traits of plant-associated bacteria across the MENs, particularly in relation to host colonization and pathogenicity.

The defensome of complex bacterial communities

Bacteria have developed various defense mechanisms to avoid infection and killing in response to the fast evolution and turnover of viruses and other genetic parasites. Such pan-immune system (defensome) encompasses a growing number of defense lines that include well-studied innate and adaptive systems such as restriction-modification, CRISPR-Cas and abortive infection, but also newly found ones whose mechanisms are still poorly understood. While the abundance and distribution of defense systems is well-known in complete and culturable genomes, there is a void in our understanding of their diversity and richness in complex microbial communities. Here we performed a large-scale in-depth analysis of the defensomes of 7759 high-quality bacterial population genomes reconstructed from soil, marine, and human gut environments. We observed a wide variation in the frequency and nature of the defensome among large phyla, which correlated with lifestyle, genome size, habitat, and geographic background. The defensome’s genetic mobility, its clustering in defense islands, and genetic variability was found to be system-specific and shaped by the bacterial environment. Hence, our results provide a detailed picture of the multiple immune barriers present in environmentally distinct bacterial communities and set the stage for subsequent identification of novel and ingenious strategies of diversification among uncultivated microbes.

A comparison of short-read, HiFi long-read, and hybrid strategies for genome-resolved metagenomics.

Shotgun metagenomics enables the reconstruction of complex microbial communities at a high level of detail. Such an approach can be conducted using both short-read and long-read sequencing data, as well as a combination of both. To assess the pros and cons of these different approaches, we used 22 fecal DNA extracts collected weekly for 11 weeks from two respective lab mice to study seven performance metrics over four combinations of sequencing depth and technology: (i) 20 Gbp of Illumina short-read data, (ii) 40 Gbp of short-read data, (iii) 20 Gbp of PacBio HiFi long-read data, and (iv) 40 Gbp of hybrid (20 Gbp of short-read +20 Gbp of long-read) data. No strategy was best for all metrics; instead, each one excelled across different metrics. The long-read approach yielded the best assembly statistics, with the highest N50 and lowest number of contigs. The 40 Gbp short-read approach yielded the highest number of refined bins. Finally, the hybrid approach yielded the longest assemblies and the highest mapping rate to the bacterial genomes. Our results suggest that while long-read sequencing significantly improves the quality of reconstructed bacterial genomes, it is more expensive and requires deeper sequencing than short-read approaches to recover a comparable amount of reconstructed genomes. The most optimal strategy is study-specific and depends on how researchers assess the trade-off between the quantity and quality of recovered genomes.IMPORTANCEMice are an important model organism for understanding the gut microbiome. When studying these gut microbiomes using DNA techniques, researchers can choose from technologies that use short or long DNA reads. In this study, we perform an extensive benchmark between short- and long-read DNA sequencing for studying mice gut microbiomes. We find that no one approach was best for all metrics and provide information that can help guide researchers in planning their experiments.

More than the sum of its parts: uncovering emerging effects of microbial interactions in complex communities.

Microbial communities are not only shaped by the diversity of microorganisms and their individual metabolic potential, but also by the vast amount of intra- and interspecies interactions that can occur pairwise interactions among microorganisms, we suggest that more attention should be drawn towards the effects on the entire microbiome that emerge from individual interactions between community members. The production of certain metabolites that can be tied to a specific microbe-microbe interaction might subsequently influence the physicochemical parameters of the habitat, stimulate a change in the trophic network of the community or create new micro-habitats through the formation of biofilms, similar to the production of antimicrobial substances which might negatively affect only one microorganism but cause a ripple effect on the abundance of other community members. Here, we argue that combining established as well as innovative laboratory and computational methods is needed to predict novel interactions and assess their secondary effects. Such efforts will enable future microbiome studies to expand our knowledge on the dynamics of complex microbial communities.

Ranking environmental and edaphic attributes driving soil microbial community structure and activity with special attention to spatial and temporal scales.

The incredibly complex soil microbial communities at small scales make their analysis and identification of reasons for the observed structures challenging. Microbial community structure is mainly a result of the inoculum (dispersal), the selective advantages of those organisms under the habitat-based environmental attributes, and the ability of those colonizers to sustain themselves over time. Since soil is protective, and its microbial inhabitants have long adapted to varied soil conditions, significant portions of the soil microbial community structure are likely stable. Hence, a substantial portion of the community will not correlate to often measured soil attributes. We suggest that the drivers be ranked on the basis of their importance to the fundamental needs of the microbes: (i) those that supply energy, i.e., organic carbon and electron acceptors; (ii) environmental effectors or stressors, i.e., pH, salt, drought, and toxic chemicals; (iii) macro-organism associations, i.e., plants and their seasonality, animals and their fecal matter, and soil fauna; and (iv) nutrients, in order, N, P, and probably of lesser importance, other micronutrients, and metals. The relevance of drivers also varies with spatial and time scales, for example, aggregate to field to regional, and persistent to dynamic populations to transcripts, and with the extent of phylogenetic difference, hence phenotypic differences in organismal groups. We present a summary matrix to provide guidance on which drivers are important for particular studies, with special emphasis on a wide range of spatial and temporal scales, and illustrate this with genomic and population (rRNA gene) data from selected studies.

Gut Microbiota Modulation

This review explores the transformative potential of gut microbiota modulation in sports medicine, where the convergence of advanced technology, rigorous training, and injury management aims to mitigate sports-related injuries. Athletes in high-intensity sports demand exceptional physical prowess, adhering to grueling training regimens for peak fitness levels. However, the pursuit of athletic excellence often leads to exhaustive physical stress and sport-specific injuries. Personalized sports medicine has emerged as an adaptive discipline, utilizing diverse technologies and methods to deliver customized medical care and enhance performance. The gut microbiota, a complex microbial community in the gastrointestinal system, significantly influences energy production, digestion, and immune defense. Similar to personalized sports medicine, the gut microbiota of every individual is unique, shaped by genetics, diet, lifestyle, and environment. Recent research underscores the profound impact of gut microbiota on athletic performance, recovery, and overall health. This review consolidates current knowledge regarding gut microbiota modulation in sports medicine, revealing its potential to revolutionize athlete care and performance enhancement. The uniqueness of our review lies in considering the interplay between gut health and personalized sports medicine, a relatively unexplored area. The study highlights the prospect of tailoring nutritional and training regimens based on the unique gut microbiota profile of every individual, marking a new era in sports medicine. Addressing a significant literature gap, this review emphasizes the importance of gut microbiota modulation in personalized sports medicine—a paradigm shift poised to enhance athletic performance, expedite recovery, and reduce injury risk.

Metagenomics analysis of water samples collected from the Yamuna River of Agra city, India.

Yamuna River water in Agra city of India is contaminated with toxic pollutants, including heavy metals that cause damage to the environment and human health. At present, the direct use of river water for drinking purposes and household activities lead to the direct exposure of society to the contaminants. In this study, Yamuna River water samples were collected from three different sites in Agra city during the monsoon, summer, and winter seasons. The physico-chemical parameters were estimated along with heavy metals. In physico-chemical parameter, the values found were mostly above the permissible limits. The results water samples contain high levels of cadmium, chromium, lead, and nickel above the desirable levels in most cases. The metagenomic analysis revealed that Proteobacteria, Bacteroidetes, Verrucomicrobia, Actinobacteria, and Planctobacteria were the most abundant phyla with a relative abundance of 61%, 9.34%, 5.23%, 4.64%, and 4.3%, respectively. The Comamonadaceae, the most abundant family consists of the genera involved in hydrogen oxidation, iron reduction, degraders of polycyclic aromatic hydrocarbons, and fermentation. The presence of Pseudomonas, Nitrosomonas sp., Thauera humireducens and Dechloromonas denitrificans (decomposition of sewage and organic matter) and Pseudomonas aeruginosa indicates the presence of heavy metal degrading bacteria in water sample. Functional prediction showed the presence of genes responsible for different metabolic pathways that could help developing new bioremediation strategies. The study concludes the status of water contamination, the presence of complex microbial community and suggests the futuristic use and their role in bioremediation.

Progress on network modeling and analysis of gut microecology: a review.

The gut microecological network is a complex microbial community within the human body that plays a key role in linking dietary nutrition and host physiology. To understand the complex relationships among microbes and their functions within this community, network analysis has emerged as a powerful tool. By representing the interactions between microbes and their associated omics data as a network, we can gain a comprehensive understanding of the ecological mechanisms that drive the human gut microbiota. In addition, the network-based approach provides a more intuitive analysis of the gut microbiota, simplifying the study of its complex dynamics and interdependencies. This review provides a comprehensive overview of the methods used to construct and analyze networks in the context of gut microecological background. We discuss various types of network modeling approaches, including co-occurrence networks, causal networks, dynamic networks, and multi-omics networks, and describe the analytical techniques used to identify important network properties. We also highlight the challenges and limitations of network modeling in this area, such as data scarcity and heterogeneity, and provide future research directions to overcome these limitations. By exploring these network-based methods, researchers can gain valuable insights into the intricate relationships and functional roles of microbial communities within the gut, ultimately advancing our understanding of the gut microbiota's impact on human health.

Differential Microbial Composition and Interkingdom Interactions in the Intestinal Microbiota of Holstein and German Simmental × Holstein Cross F1 Calves: A Comprehensive Analysis of Bacterial and Fungal Diversity.

Calf intestines are colonized by rich and complex microbial communities, playing a crucial role in animal physiology, metabolism, nutrition, and immune function. In this study, we provide insight into the composition of fecal microbial bacteria and fungi, respectively, as well as the cross-kingdom interactions. We investigated the intestinal microbiota of different breeds of calves by characterizing the bacterial and fungal communities in the rectal feces of Holstein calves and German Simmental × Holstein cross F1 generation (GXH) using 16S rRNA and ITS amplicon sequencing techniques. PICRUSt2 (version 2.2.0) were used to determine microbial diversity and function and explore the reasons why Holstein calves are more susceptible to diarrhea. The results revealed no significant difference in the diversity of fecal microbiota among the groups (p > 0.05). We identified Firmicutes, Bacteroidetes, and Proteobacteria as the dominant bacterial phyla in the fecal bacterial communities of the two breeds of calves. Ascomycota and Basidiomycota play important roles in the fungal community but differ in relative abundance. Bacteroides was the dominant genus at the group level for calf fecal microbiota in both breeds. The relative abundance of Prevotella, Escherichia-Shigella, Peptostreptococcus, and Butyricicoccus was higher in Holstein calves, and the relative abundance of Faecalibacterium, Megamonas, Butyricicoccus, and Alloprevotella was lower than GXH group. Aspergillus and Cladosporium were the dominating genera of fecal fungi in both groups of calves. LEfSe analysis revealed 33 different bacteria and 23 different fungi between the two groups, with more differential strains found in GXH. In addition, the feces fungi-bacteria interkingdom interactions varied among breeds. Thus, the composition and structure of bacterial and fungal communities in calf feces varied by breed, indicating a potential association between breed and microbial communities. We also found differences in the network between bacterial-fungal kingdoms. We explain the reasons for Holstein calves being more prone to diarrhea. This indicated that breed makes differences in calf diarrhea rates by influencing gut microbial composition and interactions.

MCHAN: Prediction of Human Microbe-drug Associations Based on Multiview Contrastive Hypergraph Attention Network

Background: Complex and diverse microbial communities play a pivotal role in human health and have become a new drug target. Exploring the connections between drugs and microbes not only provides profound insights into their mechanisms but also drives progress in drug discovery and repurposing. The use of wet lab experiments to identify associations is time-consuming and laborious. Hence, the advancement of precise and efficient computational methods can effectively improve the efficiency of association identification between microorganisms and drugs. Objective: In this experiment, we propose a new deep learning model, a new multiview comparative hypergraph attention network (MCHAN) method for human microbe–drug association prediction. Methods: First, we fuse multiple similarity matrices to obtain a fused microbial and drug similarity network. By combining graph convolutional networks with attention mechanisms, we extract key information from multiple perspectives. Then, we construct two network topologies based on the above fused data. One topology incorporates the concept of hypernodes to capture implicit relationships between microbes and drugs using virtual nodes to construct a hyperheterogeneous graph. Next, we propose a cross-contrastive learning task that facilitates the simultaneous guidance of graph embeddings from both perspectives, without the need for any labels. This approach allows us to bring nodes with similar features and network topologies closer while pushing away other nodes. Finally, we employ attention mechanisms to merge the outputs of the GCN and predict the associations between drugs and microbes. Results: To confirm the effectiveness of this method, we conduct experiments on three distinct datasets. The results demonstrate that the MCHAN model surpasses other methods in terms of performance. Furthermore, case studies provide additional evidence confirming the consistent predictive accuracy of the MCHAN model. Conclusion: MCHAN is expected to become a valuable tool for predicting potential associations between microbiota and drugs in the future.

Effects of operational parameters on bacterial communities in Hong Kong and global wastewater treatment plants.

Wastewater treatment plants (WWTPs) are an indispensable component of modern cities, as they can remove pollutants in wastewater to prevent anthropogenic activities. Activated sludge (AS) is a fundamental wastewater treatment process and it harbors a highly complex microbial community that forms the main components and contains functional groups. Unveiling "who is there" is a long-term goal of the research on AS microbiology. High-throughput sequencing provides insights into the inventory diversity of microbial communities to an unprecedented level of detail. At present, the analysis of communities in WWTPs usually comes from a specific WWTP and lacks comparisons and verification among different WWTPs. The wide-scale and long-term sampling project and research in this study could help us evaluate the AS community more accurately to find the similarities and different results for different WWTPs in Hong Kong and other regions of the world.

High-throughput screening of the effects of 90 xenobiotics on the simplified human gut microbiota model (SIHUMIx): a metaproteomic and metabolomic study.

The human gut microbiota is a complex microbial community with critical functions for the host, including the transformation of various chemicals. While effects on microorganisms has been evaluated using single-species models, their functional effects within more complex microbial communities remain unclear. In this study, we investigated the response of a simplified human gut microbiota model (SIHUMIx) cultivated in an in vitro bioreactor system in combination with 96 deep-well plates after exposure to 90 different xenobiotics, comprising 54 plant protection products and 36 food additives and dyes, at environmentally relevant concentrations. We employed metaproteomics and metabolomics to evaluate changes in bacterial abundances, the production of Short Chain Fatty Acids (SCFAs), and the regulation of metabolic pathways. Our findings unveiled significant changes induced by 23 out of 54 plant protection products and 28 out of 36 food additives across all three categories assessed. Notable highlights include azoxystrobin, fluroxypyr, and ethoxyquin causing a substantial reduction (log2FC < -0.5) in the concentrations of the primary SCFAs: acetate, butyrate, and propionate. Several food additives had significant effects on the relative abundances of bacterial species; for example, acid orange 7 and saccharin led to a 75% decrease in Clostridium butyricum, with saccharin causing an additional 2.5-fold increase in E. coli compared to the control. Furthermore, both groups exhibited up- and down-regulation of various pathways, including those related to the metabolism of amino acids such as histidine, valine, leucine, and isoleucine, as well as bacterial secretion systems and energy pathways like starch, sucrose, butanoate, and pyruvate metabolism. This research introduces an efficient in vitro technique that enables high-throughput screening of the structure and function of a simplified and well-defined human gut microbiota model against 90 chemicals using metaproteomics and metabolomics. We believe this approach will be instrumental in characterizing chemical-microbiota interactions especially important for regulatory chemical risk assessments.

Bacteriophage specificity is impacted by interactions between bacteria.

There is significant natural diversity in how many different types of bacteria a bacteriophage can infect, but the mechanisms driving this diversity are unclear. This study uses a combination of mathematical modeling and an in vitro system consisting of Escherichia coli, Salmonella enterica, a T5-like generalist phage, and the specialist phage P22vir to highlight the connection between bacteriophage specificity and interactions between their potential microbial prey. Mathematical modeling suggests that competing bacteria tend to favor generalist bacteriophage, while bacteria that benefit each other tend to favor specialist bacteriophage. Experimental results support this general finding. The experiments also show that the optimal phage strategy is impacted by phage degradation and bacterial physiology. These findings enhance our understanding of how complex microbial communities shape selection on bacteriophage specificity, which may improve our ability to use phage to manage antibiotic-resistant microbial infections.

Effect of Gut Microbiota-Mediated Tryptophan Metabolism on Inflammaging in Frailty and Sarcopenia.

Frailty syndrome refers to the nonspecific state of increased body vulnerability and decreased antistress and recovery abilities after stress during aging. Sarcopenia is the major component of frailty and is characterized by the gradual loss of muscle mass, strength, and function with age. Inflammaging is the gradual increase in inflammatory status during aging, and it disrupts immune tolerance, causes physiological changes in tissues, organs, and normal cells, and is related to frailty and sarcopenia. The gut microbiota is an extremely complex and diverse microbial community that coevolves with the host. The composition and structure of the gut microbiota and the metabolism of tryptophan (Trp) significantly change in older adults with frailty and sarcopenia. The gut microbiota participates in regulating the Trp metabolic pathways of kynurenine (Kyn), 5-hydroxytryptamine (5-HT), and indole in the gastrointestinal tract. The Trp metabolites derived from the gut microbiota may synergistically promote the occurrence of age-related frailty and sarcopenia by promoting inflammation in the intestines, nervous system, and muscles. The role and mechanisms of the gut microbiota, Trp metabolism, and inflammaging in age-related frailty and sarcopenia may be a worthwhile research direction to help promote healthy aging.

Cryopreservation and recovery of a complex hypersaline microbial mat community

Cryopreservation of microorganisms is an essential tool in industrial- and food applications where conservation of microbial activity and critical beneficial traits need to be guaranteed to provide a consistent product or production process. This often refers to simple, single species or low diversity assemblages in liquid cultures that can easily be revived and regrown to perform the desired process. Cryopreservation is also of essence for scientific experimentation where many environmental samples are taken in remote sampling sites and at high costs. Biobanking, or the long term preservation and potential revival of complex, structured samples come with an additional challenge related to maintaining the structure upon revival. Here we look at cryopreserving and reviving a complex photosynthesis driven microbial mat from a hypersaline ecosystem. Amplicon sequencing of the 16S and 18S ribosomal RNA gene was used to determine the community composition of bacteria and eukaryotes respectively. The tests included the use of different cryopreservative agents and different times of cryopreservation at −150 °C. Upon revival, the cryopreservatives cannot be separated from the preserved samples without disturbing the community structure, while carryover of these compounds may influence reconstitution of the communities. Indeed, although both glycerol and Me2SO are good cryopreservatives of microbial assemblages, carryover of these compounds had a profound negative effect on the reestablishment of a functional microbial mat. Best cryopreservation and reconstitution results were obtained in the absence of a cryopreservative agent or when methanol was used.

Identification of a microbial sub-community from the feral chicken gut that reduces Salmonella colonization and improves gut health in a gnotobiotic chicken model.

A complex microbial community in the gut may prevent the colonization of enteric pathogens such as Salmonella. Some individual or a combination of species in the gut may confer colonization resistance against Salmonella. To gain a better understanding of the colonization resistance against Salmonella enterica, we isolated a library of 1,300 bacterial strains from feral chicken gut microbiota which represented a total of 51 species. Using a co-culture assay, we screened the representative species from this library and identified 30 species that inhibited Salmonella enterica subspecies enterica serovar Typhimurium in vitro. To improve the Salmonella inhibition capacity, from a pool of fast-growing species, we formulated 66 bacterial blends, each of which composed of 10 species. Bacterial blends were more efficient in inhibiting Salmonella as compared to individual species. The blend that showed maximum inhibition (Mix10) also inhibited other serotypes of Salmonella frequently found in poultry. The in vivo effect of Mix10 was examined in a gnotobiotic and conventional chicken model. The Mix10 consortium significantly reduced Salmonella load at day 2 post-infection in gnotobiotic chicken model and decreased intestinal tissue damage and inflammation in both models. Cell-free supernatant of Mix10 did not show Salmonella inhibition, indicating that Mix10 inhibits Salmonella through either nutritional competition, competitive exclusion, or through reinforcement of host immunity. Out of 10 species, 3 species in Mix10 did not colonize, while 3 species constituted more than 70% of the community. Two of these species were previously uncultured bacteria. Our approach could be used as a high-throughput screening system to identify additional bacterial sub-communities that confer colonization resistance against enteric pathogens and its effect on the host.IMPORTANCESalmonella colonization in chicken and human infections originating from Salmonella-contaminated poultry is a significant problem. Poultry has been identified as the most common food linked to enteric pathogen outbreaks in the United States. Since multi-drug-resistant Salmonella often colonize chicken and cause human infections, methods to control Salmonella colonization in poultry are needed. The method we describe here could form the basis of developing gut microbiota-derived bacterial blends as a microbial ecosystem therapeutic against Salmonella.

From wolves to humans: oral microbiome resistance to transfer across mammalian hosts.

The mammalian mouth is colonized by complex microbial communities, adapted to specific niches, and in homeostasis with the host. Individual microbes interact metabolically and rely primarily on nutrients provided by the host, with which they have potentially co-evolved along the mammalian lineages. The oral environment is similar across mammals, but the diversity, specificity, and evolution of community structure in related or interacting mammals are little understood. Here, we compared the oral microbiomes of dogs with those of wild wolves and humans. In dogs, we found an increased microbial diversity relative to wolves, possibly related to the transition to omnivorous nutrition following domestication. This includes a larger diversity of Patescibacteria than previously reported in any other oral microbiota. The oral microbes are most distinct at bacterial species or strain levels, with few if any shared between humans and canids, while the close evolutionary relationship between wolves and dogs is reflected by numerous shared taxa. More taxa are shared at higher taxonomic levels including with humans, supporting their more ancestral common mammalian colonization followed by diversification. Phylogenies of selected oral bacterial lineages do not support stable human-dog microbial transfers but suggest diversification along mammalian lineages (apes and canids). Therefore, despite millennia of cohabitation and close interaction, the host and its native community controls and limits the assimilation of new microbes, even if closely related. Higher resolution metagenomic and microbial physiological studies, covering a larger mammalian diversity, should help understand how oral communities assemble, adapt, and interact with their hosts.IMPORTANCENumerous types of microbes colonize the mouth after birth and play important roles in maintaining oral health. When the microbiota-host homeostasis is perturbed, proliferation of some bacteria leads to diseases such as caries and periodontitis. Unlike the gut microbiome, the diversity of oral microbes across the mammalian evolutionary space is not understood. Our study compared the oral microbiomes of wild wolves, dogs, and apes (humans, chimpanzees, and bonobos), with the aim of identifying if microbes have been potentially exchanged between humans and dogs as a result of domestication and cohabitation. We found little if any evidence for such exchanges. The significance of our research is in finding that the oral microbiota and/or the host limit the acquisition of exogenous microbes, which is important in the context of natural exclusion of potential novel pathogens. We provide a framework for expanded higher-resolution studies across domestic and wild animals to understand resistance/resilience.