Assembly of 913 microbial genomes from metagenomic sequencing of the cow rumen

Comprehensive mouse microbiota genome catalog reveals major difference to its human counterpart

Mouse is the most used model for studying the impact of microbiota on its host, but the repertoire of species from the mouse gut microbiome remains largely unknown. Accordingly, the similarity between human and mouse microbiomes at a low taxonomic level is not clear. We construct a comprehensive mouse microbiota genome (CMMG) catalog by assembling all currently available mouse gut metagenomes and combining them with published reference and metagenome-assembled genomes. The 41’798 genomes cluster into 1’573 species, of which 78.1% are uncultured, and we discovered 226 new genera, seven new families, and one new order. CMMG enables an unprecedented coverage of the mouse gut microbiome exceeding 86%, increases the mapping rate over four-fold, and allows functional microbiota analyses of human and mouse linking them to the driver species. Comparing CMMG to microbiota from the unified human gastrointestinal genomes shows an overlap of 62% at the genus but only 10% at the species level, demonstrating that human and mouse gut microbiota are largely distinct. CMMG contains the most comprehensive collection of consistently functionally annotated species of the mouse and human microbiome to date, setting the ground for analysis of new and reanalysis of existing datasets at an unprecedented depth.

The microbiome plays an indispensable role in our health. Metagenomics enables valuable insights into the composition and functional potential of microbial populations. The analysis of metagenomic data is complex and depends on the availability of reference genomes. The mouse is the most used model for studying the impact of microbiota on its host. However, the microbial species living in the mouse gut remain poorly characterized. We created a comprehensive catalog of all bacterial species commonly living in the gut of laboratory mice by analyzing all publicly available metagenomes from the mouse gut. We collected almost 42 thousand bacterial genomes from 1’573 species, of which 78.1% are uncultured. Our catalog effectively answers the need for a genome reference for this microbiome and allows efficient analysis of mouse gut metagenomes down to the species level. We discovered that mice and humans harbor a largely distinct set of species in their gastrointestinal tracts, a hereto unfeasible analysis.

Metaproteomics as a tool for studying the protein landscape of human-gut bacterial species

Host-microbiome interactions and the microbial community have broad impact in human health and diseases. Most microbiome based studies are performed at the genome level based on next-generation sequencing techniques, but metaproteomics is emerging as a powerful technique to study microbiome functional activity by characterizing the complex and dynamic composition of microbial proteins. We conducted a large-scale survey of human gut microbiome metaproteomic data to identify generalist species that are ubiquitously expressed across all samples and specialists that are highly expressed in a small subset of samples associated with a certain phenotype. We were able to utilize the metaproteomic mass spectrometry data to reveal the protein landscapes of these species, which enables the characterization of the expression levels of proteins of different functions and underlying regulatory mechanisms, such as operons. Finally, we were able to recover a large number of open reading frames (ORFs) with spectral support, which were missed by de novo protein-coding gene predictors. We showed that a majority of the rescued ORFs overlapped with de novo predicted protein-coding genes, but on opposite strands or in different frames. Together, these demonstrate applications of metaproteomics for the characterization of important gut bacterial species.

Many reference genomes for studying human gut microbiome are available, but knowledge about how microbial organisms work is limited. Identification of proteins at individual species or community level provides direct insight into the functionality of microbial organisms. By analyzing more than a thousand metaproteomics datasets, we examined protein landscapes of more than two thousands of microbial species that may be important to human health and diseases. This work demonstrated new applications of metaproteomic datasets for studying individual genomes. We made the analysis results available through a website (called GutBac), which we believe will become a resource for studying microbial species important for human health and diseases.

The microbiome of the buffalo digestive tract

Buffalo is an important livestock species. Here, we present a comprehensive metagenomic survey of the microbial communities along the buffalo digestive tract. We analysed 695 samples covering eight different sites in three compartments (four-chambered stomach, intestine, and rectum). We mapped ~85% of the raw sequence reads to 4,960 strain-level metagenome-assembled genomes (MAGs) and 3,255 species-level MAGs, 90% of which appear to correspond to new species. In addition, we annotated over 5.8 million nonredundant proteins from the MAGs. In comparison with the rumen microbiome of cattle, the buffalo microbiota seems to present greater potential for fibre degradation and less potential for methane production. Our catalogue of microbial genomes and the encoded proteins provides insights into microbial functions and interactions at distinct sites along the buffalo digestive tract.

Hi-C Metagenomics in the ICU: Exploring Clinically Relevant Features of Gut Microbiome in Chronically Critically Ill Patients

Gut microbiome in critically ill patients shows profound dysbiosis. The most vulnerable is the subgroup of chronically critically ill (CCI) patients - those suffering from long-term dependence on support systems in intensive care units. It is important to investigate their microbiome as a potential reservoir of opportunistic taxa causing co-infections and a morbidity factor. We explored dynamics of microbiome composition in the CCI patients by combining "shotgun" metagenomics with chromosome conformation capture (Hi-C). Stool samples were collected at 2 time points from 2 patients with severe brain injury with different outcomes within a 1-2-week interval. The metagenome-assembled genomes (MAGs) were reconstructed based on the Hi-C data using a novel hicSPAdes method (along with the bin3c method for comparison), as well as independently of the Hi-C using MetaBAT2. The resistomes of the samples were derived using a novel assembly graph-based approach. Links of bacteria to antibiotic resistance genes, plasmids and viruses were analyzed using Hi-C-based networks. The gut community structure was enriched in opportunistic microorganisms. The binning using hicSPAdes was superior to the conventional WGS-based binning as well as to the bin3c in terms of the number, completeness and contamination of the reconstructed MAGs. Using Klebsiella pneumoniae as an example, we showed how chromosome conformation capture can aid comparative genomic analysis of clinically important pathogens. Diverse associations of resistome with antimicrobial therapy from the level of assembly graphs to gene content were discovered. Analysis of Hi-C networks suggested multiple "host-plasmid" and "host-phage" links. Hi-C metagenomics is a promising technique for investigating clinical microbiome samples. It provides a community composition profile with increased details on bacterial gene content and mobile genetic elements compared to conventional metagenomics. The ability of Hi-C binning to encompass the MAG's plasmid content facilitates metagenomic evaluation of virulence and drug resistance dynamics in clinically relevant opportunistic pathogens. These findings will help to identify the targets for developing cost-effective and rapid tests for assessing microbiome-related health risks.

Assessment of Hydrocarbon Degradation Potential in Microbial Communities in Arctic Sea Ice

The anthropogenic release of oil hydrocarbons into the cold marine environment is an increasing concern due to the elevated usage of sea routes and the exploration of new oil drilling sites in Arctic areas. The aim of this study was to evaluate prokaryotic community structures and the genetic potential of hydrocarbon degradation in the metagenomes of seawater, sea ice, and crude oil encapsulating the sea ice of the Norwegian fjord, Ofotfjorden. Although the results indicated substantial differences between the structure of prokaryotic communities in seawater and sea ice, the crude oil encapsulating sea ice (SIO) showed increased abundances of many genera-containing hydrocarbon-degrading organisms, including Bermanella, Colwellia, and Glaciecola. Although the metagenome of seawater was rich in a variety of hydrocarbon degradation-related functional genes (HDGs) associated with the metabolism of n-alkanes, and mono- and polyaromatic hydrocarbons, most of the normalized gene counts were highest in the clean sea ice metagenome, whereas in SIO, these counts were the lowest. The long-chain alkane degradation gene almA was detected from all the studied metagenomes and its counts exceeded ladA and alkB counts in both sea ice metagenomes. In addition, almA was related to the most diverse group of prokaryotic genera. Almost all 18 good- and high-quality metagenome-assembled genomes (MAGs) had diverse HDGs profiles. The MAGs recovered from the SIO metagenome belonged to the abundant taxa, such as Glaciecola, Bermanella, and Rhodobacteracea, in this environment. The genera associated with HDGs were often previously known as hydrocarbon-degrading genera. However, a substantial number of new associations, either between already known hydrocarbon-degrading genera and new HDGs or between genera not known to contain hydrocarbon degraders and multiple HDGs, were found. The superimposition of the results of comparing HDG associations with taxonomy, the HDG profiles of MAGs, and the full genomes of organisms in the KEGG database suggest that the found relationships need further investigation and verification.

Investigation of fiber utilization in the rumen of dairy cows based on metagenome-assembled genomes and single-cell RNA sequencing

BACKGROUND

Dairy cows utilize human-inedible, low-value plant biomass to produce milk, a low-cost product with rich nutrients and high proteins. This process largely relies on rumen microbes that ferment lignocellulose and cellulose to produce volatile fatty acids (VFAs). The VFAs are absorbed and partly metabolized by the stratified squamous rumen epithelium, which is mediated by diverse cell types. Here, we applied a metagenomic binning approach to explore the individual microbes involved in fiber digestion and performed single-cell RNA sequencing on rumen epithelial cells to investigate the cell subtypes contributing to VFA absorption and metabolism.

RESULTS

The 52 mid-lactating dairy cows in our study (parity = 2.62 ± 0.91) had milk yield of 33.10 ± 6.72 kg. We determined the fiber digestion and fermentation capacities of 186 bacterial genomes using metagenomic binning and identified specific bacterial genomes with strong cellulose/xylan/pectin degradation capabilities that were highly associated with the biosynthesis of VFAs. Furthermore, we constructed a rumen epithelial single-cell map consisting of 18 rumen epithelial cell subtypes based on the transcriptome of 20,728 individual epithelial cells. A systematic survey of the expression profiles of genes encoding candidates for VFA transporters revealed that IGFBP5+ cg-like spinous cells uniquely highly expressed SLC16A1 and SLC4A9, suggesting that this cell type may play important roles in VFA absorption. Potential cross-talk between the microbiome and host cells and their roles in modulating the expression of key genes in the key rumen epithelial cell subtypes were also identified.

CONCLUSIONS

We discovered the key individual microbial genomes and epithelial cell subtypes involved in fiber digestion, VFA uptake and metabolism, respectively, in the rumen. The integration of these data enables us to link microbial genomes and epithelial single cells to the trophic system. Video abstract.

Insights into the Ancient Adaptation to Intertidal Environments by Red Algae Based on a Genomic and Multiomics Investigation of Neoporphyra haitanensis

Colonization of land from marine environments was a major transition for biological life on Earth, and intertidal adaptation was a key evolutionary event in the transition from marine- to land-based lifestyles. Multicellular intertidal red algae exhibit the earliest, systematic, and successful adaptation to intertidal environments, with Porphyra sensu lato (Bangiales, Rhodophyta) being a typical example. Here, a chromosome-level 49.67 Mb genome for Neoporphyra haitanensis comprising 9,496 gene loci is described based on metagenome-Hi-C-assisted whole-genome assembly, which allowed the isolation of epiphytic bacterial genome sequences from a seaweed genome for the first time. The compact, function-rich N. haitanensis genome revealed that ancestral lineages of red algae share common horizontal gene transfer events and close relationships with epiphytic bacterial populations. Specifically, the ancestor of N. haitanensis obtained unique lipoxygenase family genes from bacteria for complex chemical defense, carbonic anhydrases for survival in shell-borne conchocelis lifestyle stages, and numerous genes involved in stress tolerance. Combined proteomic, transcriptomic, and metabolomic analyses revealed complex regulation of rapid responses to intertidal dehydration/rehydration cycling within N. haitanensis. These adaptations include rapid regulation of its photosynthetic system, a readily available capacity to utilize ribosomal stores, increased methylation activity to rapidly synthesize proteins, and a strong anti-oxidation system to dissipate excess redox energy upon exposure to air. These novel insights into the unique adaptations of red algae to intertidal lifestyles inform our understanding of adaptations to intertidal ecosystems and the unique evolutionary steps required for intertidal colonization by biological life.

Alternative pathways for hydrogen sink originated from the ruminal fermentation of carbohydrates: Which microorganisms are involved in lowering methane emission?

Agriculture is responsible for a great share of the anthropogenic sources of greenhouse gases that, by warming the earth, threaten its biodiversity. Among greenhouse gas emissions, enteric CH4 from livestock is an important target to slow down climate changes. The CH4 is originated from rumen fermentation and its concentration is affected by several factors, including genetics and nutrition. Ruminants have an extraordinary symbiosis with microorganisms (bacteria, fungi, and protozoa) that ferment otherwise indigestible carbohydrates, from which they obtain energy to grow and continue actively producing, among other products, volatile fatty acids, CO2 and H2. Detrimental ruminal accumulation of H2 is avoided by methanogenesis carried out by Archaea methanogens. Importantly, methanogenesis is not the only H2 sink pathway. In fact, other bacteria can reduce substrates using metabolic hydrogen formed during carbohydrate fermentation, namely propionate production and reductive acetogenesis, thus lowering the CH4 produced. Although the complexity of rumen poses challenges to mitigate CH4 production, the emergence of sequencing techniques that allow the study of microbial communities, gene expression, and metabolome are largely contributing to unravel pathways and key players in the rumen. Indeed, it is now recognized that in vivo emissions of CH4 are correlated to microbial communities, and particularly with the abundance of methanogens, several bacterial groups, and  their genes. The goal of CH4 mitigation is to work in favor of the natural processes, without compromising rumen function, animal health, and productivity. Notwithstanding, the major challenge continues to be the feasibility and affordability of the proposed solutions.

Metagenomes Binning Using Proximity-Ligation Data

Microbial communities are key components of all ecosystems, but characterization of their complete genomic structure remains challenging. Typical analysis tends to elude the complexity of the mixes in terms of species, strains, as well as extrachromosomal DNA molecules. Recently, approaches have been developed that bins DNA contigs into individual genomes and episomes according to their 3D contact frequencies. Those contacts are quantified by chromosome conformation capture experiments (3C, Hi-C), also known as proximity-ligation approaches, applied to metagenomics samples. Here, we present a simple computational pipeline that allows to recover high-quality Metagenomics Assemble Genomes (MAGs) starting from metagenomic 3C or Hi-C datasets and a metagenome assembly.

A catalogue of 1,167 genomes from the human gut archaeome

The human gut microbiome plays an important role in health, but its archaeal diversity remains largely unexplored. In the present study, we report the analysis of 1,167 nonredundant archaeal genomes (608 high-quality genomes) recovered from human gastrointestinal tract, sampled across 24 countries and rural and urban populations. We identified previously undescribed taxa including 3 genera, 15 species and 52 strains. Based on distinct genomic features, we justify the split of the Methanobrevibacter smithii clade into two separate species, with one represented by the previously undescribed 'Candidatus Methanobrevibacter intestini'. Patterns derived from 28,581 protein clusters showed significant associations with sociodemographic characteristics such as age groups and lifestyle. We additionally show that archaea are characterized by specific genomic and functional adaptations to the host and carry a complex virome. Our work expands our current understanding of the human archaeome and provides a large genome catalogue for future analyses to decipher its impact on human physiology.

Concepts and Consequences of a Core Gut Microbiota for Animal Growth and Development

Animal microbiomes are occasionally considered as an extension of host anatomy, physiology, and even their genomic architecture. Their compositions encompass variable and constant portions when examined across multiple hosts. The latter, termed the core microbiome, is viewed as more accommodated to its host environment and suggested to benefit host fitness. Nevertheless, discrepancies in its definitions, characteristics, and importance to its hosts exist across studies. We survey studies that characterize the core microbiome, detail its current definitions and available methods to identify it, and emphasize the crucial need to upgrade and standardize the methodologies among studies. We highlight ruminants as a case study and discuss the link between the core microbiome and host physiology and genetics, as well as potential factors that shape it. We conclude with main directives of action to better understand the host-core microbiome axis and acquire the necessary insights into its controlled modulation. Expected final online publication date for the Annual Review of Animal Biosciences, Volume 10 is February 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

FI: The Fecobiome Initiative

Animal husbandry has been key to the sustainability of human societies for millennia. Livestock animals, such as cattle, convert plants to protein biomass due to a compartmentalized gastrointestinal tract (GIT) and the complementary contributions of a diverse GIT microbiota, thereby providing humans with meat and dairy products. Research on cattle gut microbial symbionts has mainly focused on the rumen (which is the primary fermentation compartment) and there is a paucity of functional insight on the intestinal (distal end) microbiota, where most foodborne zoonotic bacteria reside. Here, we present the Fecobiome Initiative (or FI), an international effort that aims at facilitating collaboration on research projects related to the intestinal microbiota, disseminating research results, and increasing public availability of resources. By doing so, the FI can help mitigate foodborne and animal pathogens that threaten livestock and human health, reduce the emergence and spread of antimicrobial resistance in cattle and their proximate environment, and potentially improve the welfare and nutrition of animals. We invite all researchers interested in this type of research to join the FI through our website: www.fecobiome.com

MetaPlatanus: a metagenome assembler that combines long-range sequence links and species-specific features

De novo metagenome assembly is effective in assembling multiple draft genomes, including those of uncultured organisms. However, heterogeneity in the metagenome hinders assembly and introduces interspecies misassembly deleterious for downstream analysis. For this purpose, we developed a hybrid metagenome assembler, MetaPlatanus. First, as a characteristic function, it assembles the basic contigs from accurate short reads and then iteratively utilizes long-range sequence links, species-specific sequence compositions, and coverage depth. The binning information was also used to improve contiguity. Benchmarking using mock datasets consisting of known bacteria with long reads or mate pairs revealed the high contiguity MetaPlatanus with a few interspecies misassemblies. For published human gut data with nanopore reads from potable sequencers, MetaPlatanus assembled many biologically important elements, such as coding genes, gene clusters, viral sequences, and over-half bacterial genomes. In the benchmark with published human saliva data with high-throughput nanopore reads, the superiority of MetaPlatanus was considerably more evident. We found that some high-abundance bacterial genomes were assembled only by MetaPlatanus as near-complete. Furthermore, MetaPlatanus can circumvent the limitations of highly fragmented assemblies and frequent interspecies misassembles obtained by the other tools. Overall, the study demonstrates that MetaPlatanus could be an effective approach for exploring large-scale structures in metagenomes.

Metagenomic Analysis Reveals New Microbiota Related to Fiber Digestion in Pigs

Making full use of high fiber and low-cost crop coproducts is helpful to alleviate the situation of people and livestock competing for crops. Digestion of dietary fibers in pigs is mainly through microbial fermentation in the large intestine. To reveal microbiota related to fiber digestion in pigs, fecal samples have been collected from 274 healthy female Suhuai pigs at 160 days of age under the same feeding conditions and have measured apparent neutral detergent fiber (NDF) and acid detergent fiber (ADF) digestibility. Samples from Suhuai pigs with extreme high and low apparent NDF digestibility and extreme high and low apparent ADF digestibility were subjected to shotgun metagenomic sequencing. At the species level, 62 microbial species in H_NDF group and 54 microbial species in H_ADF group were related to high fiber digestibility. Among them, Lachnospiraceae bacterium 3-1 and Alistipes sp. CAG:514 may be new types of microorganisms associated with fiber digestion. In addition, we found that more abundant GH5 and GH48 family (contribute to cellulose degradation) genes, GH39 and GH53 family (contribute to hemicellulose degradation) genes in microorganisms may contribute to the higher apparent NDF digestibility of pigs, and more abundant GH3 and GH9 family (contribute to cellulose degradation) genes in microorganisms may contribute to the higher apparent ADF digestibility of pigs. The abundance of AA4 family (helps in lignin degradation) genes in H_NDF and H_ADF groups was significantly higher than that in L_NDF and L_ADF groups, respectively (P < 0.05). Three pathways in H_NDF group and four pathways in H_ADF group are important pathways associated with degradation of non-starch polysaccharides, and their relative abundance is significantly higher than that in L_NDF and L_ADF groups, respectively. Gut microbiota of Suhuai pigs with high apparent fiber digestibility had higher abundance of genes and microbiota related to fiber digestion and may have stronger fiber digestion potential compared with low apparent fiber digestibility group. This study revealed that the characteristics of gut microbiota and microbial gene functions of pigs with high fiber apparent digestibility, which provided a theoretical basis and reference for further understanding the impact of gut microbiota on fiber digestibility of pigs.

A roadmap for metagenomic enzyme discovery

Covering: up to 2021Metagenomics has yielded massive amounts of sequencing data offering a glimpse into the biosynthetic potential of the uncultivated microbial majority. While genome-resolved information about microbial communities from nearly every environment on earth is now available, the ability to accurately predict biocatalytic functions directly from sequencing data remains challenging. Compared to primary metabolic pathways, enzymes involved in secondary metabolism often catalyze specialized reactions with diverse substrates, making these pathways rich resources for the discovery of new enzymology. To date, functional insights gained from studies on environmental DNA (eDNA) have largely relied on PCR- or activity-based screening of eDNA fragments cloned in fosmid or cosmid libraries. As an alternative, shotgun metagenomics holds underexplored potential for the discovery of new enzymes directly from eDNA by avoiding common biases introduced through PCR- or activity-guided functional metagenomics workflows. However, inferring new enzyme functions directly from eDNA is similar to searching for a 'needle in a haystack' without direct links between genotype and phenotype. The goal of this review is to provide a roadmap to navigate shotgun metagenomic sequencing data and identify new candidate biosynthetic enzymes. We cover both computational and experimental strategies to mine metagenomes and explore protein sequence space with a spotlight on natural product biosynthesis. Specifically, we compare in silico methods for enzyme discovery including phylogenetics, sequence similarity networks, genomic context, 3D structure-based approaches, and machine learning techniques. We also discuss various experimental strategies to test computational predictions including heterologous expression and screening. Finally, we provide an outlook for future directions in the field with an emphasis on meta-omics, single-cell genomics, cell-free expression systems, and sequence-independent methods.

Dynamics of the ruminal microbial ecosystem, and inhibition of methanogenesis and propiogenesis in response to nitrate feeding to Holstein calves

It is known that nitrate inhibits ruminal methanogenesis, mainly through competition with hydrogenotrophic methanogens for available hydrogen (H₂) and also through toxic effects on the methanogens. However, there is limited knowledge about its effects on the others members of ruminal microbiota and their metabolites. In this study, we investigated the effects of dietary nitrate inclusion on enteric methane (CH₄) emission, temporal changes in ruminal microbiota, and fermentation in Holstein calves. Eighteen animals were maintained in individual pens for 45 d. Animals were randomly allocated to either a control (CTR) or nitrate (NIT, containing 15 g of calcium nitrate/kg dry matter) diets. Methane emissions were estimated using the sulfur hexafluoride (SF₆) tracer method. Ruminal microbiota changes and ruminal fermentation were evaluated at 0, 4, and 8 h post-feeding. In this study, feed dry matter intake (DMI) did not differ between dietary treatments (P > 0.05). Diets containing NIT reduced CH₄ emissions by 27% (g/d) and yield by 21% (g/kg DMI) compared to the CTR (P < 0.05). The pH values and total volatile fatty acids (VFA) concentration did not differ between dietary treatments (P > 0.05) but differed with time, and post-feeding (P < 0.05). Increases in the concentrations of ruminal ammonia nitrogen (NH₃–N) and acetate were observed, whereas propionate decreased at 4 h post-feeding with the NIT diet (P < 0.05). Feeding the NIT diet reduced the populations of total bacteria, total methanogens, Ruminococcus albus and Ruminococcus flavefaciens, and the abundance of Succiniclasticum, Coprococcus, Treponema, Shuttlewortia, Succinivibrio, Sharpea, Pseudobutyrivibrio, and Selenomona (P < 0.05); whereas, the population of total fungi, protozoa, Fibrobacter succinogenes, Atopobium and Erysipelotrichaceae L7A_E11 increased (P < 0.05). In conclusion, feeding nitrate reduces enteric CH₄ emissions and the methanogens population, whereas it decreases the propionate concentration and the abundance of bacteria involved in the succinate and acrylate pathways. Despite the altered fermentation profile and ruminal microbiota, DMI was not influenced by dietary nitrate. These findings suggest that nitrate has a predominantly direct effect on the reduction of methanogenesis and propionate synthesis.

A review of the resistome within the digestive tract of livestock

Antimicrobials have been widely used to prevent and treat infectious diseases and promote growth in food-production animals. However, the occurrence of antimicrobial resistance poses a huge threat to public and animal health, especially in less developed countries where food-producing animals often intermingle with humans. To limit the spread of antimicrobial resistance from food-production animals to humans and the environment, it is essential to have a comprehensive knowledge of the role of the resistome in antimicrobial resistance (AMR), The resistome refers to the collection of all antimicrobial resistance genes associated with microbiota in a given environment. The dense microbiota in the digestive tract is known to harbour one of the most diverse resistomes in nature. Studies of the resistome in the digestive tract of humans and animals are increasing exponentially as a result of advancements in next-generation sequencing and the expansion of bioinformatic resources/tools to identify and describe the resistome. In this review, we outline the various tools/bioinformatic pipelines currently available to characterize and understand the nature of the intestinal resistome of swine, poultry, and ruminants. We then propose future research directions including analysis of resistome using long-read sequencing, investigation in the role of mobile genetic elements in the expression, function and transmission of AMR. This review outlines the current knowledge and approaches to studying the resistome in food-producing animals and sheds light on future strategies to reduce antimicrobial usage and control the spread of AMR both within and from livestock production systems.

Functional Diversity within Gut Microbiomes: Implications for Conserving Biodiversity

Conservation research has historically been conducted at the macro level, focusing on animals and plants and their role in the wider ecosystem. However, there is a growing appreciation of the importance of microbial communities in conservation. Most microbiome research in conservation thus far has used amplicon sequencing methods to assess the taxonomic composition of microbial communities and inferred functional capabilities from these data. However, as manipulation of the microbiome as a conservation tool becomes more and more feasible, there is a growing need to understand the direct functional consequences of shifts in microbiome composition. This review outlines the latest advances in microbiome research from a functional perspective and how these data can be used to inform conservation strategies. This review will also consider some of the challenges faced when studying the microbiomes of wild animals and how they can be overcome by careful study design and sampling methods. Environmental changes brought about by climate change or direct human actions have the potential to alter the taxonomic composition of microbiomes in wild populations. Understanding how taxonomic shifts affect the function of microbial communities is important for identifying species most threatened by potential disruption to their microbiome. Preservation or even restoration of these functions has the potential to be a powerful tool in conservation biology and a shift towards functional characterisation of gut microbiome diversity will be an important first step.

Enrofloxacin Alters Fecal Microbiota and Resistome Irrespective of Its Dose in Calves

Enrofloxacin is a fluoroquinolone drug used to prevent and control bovine respiratory disease (BRD) complex in multiple or single doses, ranging from 7.5 to 12.5 mg/kg body weight. Here, we examined the effects of high and low doses of a single subcutaneously injected enrofloxacin on gut microbiota and resistome in calves. Thirty-five calves sourced for this study were divided into five groups: control (n = 7), two low dose groups (n = 14, 7.5 mg/kg), and two high dose groups (n = 14, 12.5 mg/kg). One group in the low and high dose groups was challenged with Mannheimia haemolytica to induce BRD. Both alpha and beta diversities were significantly different between pre- and post-treatment microbial communities (q < 0.05). The high dose caused a shift in a larger number of genera than the low dose. Using metagenomic ProxiMeta Hi-C, 32 unique antimicrobial resistance genes (ARGs) conferring resistance to six antibiotic classes were detected with their reservoirs, and the high dose favored clonal expansion of ARG-carrying bacterial hosts. In conclusion, enrofloxacin treatment can alter fecal microbiota and resistome irrespective of its dose. Hi-C sequencing provides significant benefits for unlocking new insights into the ARG ecology of complex samples; however, limitations in sample size and sequencing depth suggest that further work is required to validate the findings.

Prospects for multi-omics in the microbial ecology of water engineering

Advances in high-throughput sequencing technologies and bioinformatics approaches over almost the last three decades have substantially increased our ability to explore microorganisms and their functions - including those that have yet to be cultivated in pure isolation. Genome-resolved metagenomic approaches have enabled linking powerful functional predictions to specific taxonomical groups with increasing fidelity. Additionally, related developments in both whole community gene expression surveys and metabolite profiling have permitted for direct surveys of community-scale functions in specific environmental settings. These advances have allowed for a shift in microbiome science away from descriptive studies and towards mechanistic and predictive frameworks for designing and harnessing microbial communities for desired beneficial outcomes. Water engineers, microbiologists, and microbial ecologists studying activated sludge, anaerobic digestion, and drinking water distribution systems have applied various (meta)omics techniques for connecting microbial community dynamics and physiologies to overall process parameters and system performance. However, the rapid pace at which new omics-based approaches are developed can appear daunting to those looking to apply these state-of-the-art practices for the first time. Here, we review how modern genome-resolved metagenomic approaches have been applied to a variety of water engineering applications from lab-scale bioreactors to full-scale systems. We describe integrated omics analysis across engineered water systems and the foundations for pairing these insights with modeling approaches. Lastly, we summarize emerging omics-based technologies that we believe will be powerful tools for water engineering applications. Overall, we provide a framework for microbial ecologists specializing in water engineering to apply cutting-edge omics approaches to their research questions to achieve novel functional insights. Successful adoption of predictive frameworks in engineered water systems could enable more economically and environmentally sustainable bioprocesses as demand for water and energy resources increases.

Disproportionate microbial responses to decadal drainage on a Siberian floodplain

Permafrost thaw induces soil hydrological changes which in turn affects carbon cycle processes in the Arctic terrestrial ecosystems. However, hydrological impacts of thawing permafrost on microbial processes and greenhouse gas (GHG) dynamics are poorly understood. This study examined changes in microbial communities using gene and genome-centric metagenomics on an Arctic floodplain subject to decadal drainage, and linked them to CO₂ and CH₄ flux and soil chemistry. Decadal drainage led to significant changes in the abundance, taxonomy, and functional potential of microbial communities, and these modifications well explained the changes in CO₂ and CH₄ fluxes between ecosystem and atmosphere-increased fungal abundances potentially increased net CO₂ emission rates and highly reduced CH₄ emissions in drained sites corroborated the marked decrease in the abundance of methanogens and methanotrophs. Interestingly, various microbial taxa disproportionately responded to drainage: Methanoregula, one of the key players in methanogenesis under saturated conditions, almost disappeared, and also Methylococcales methanotrophs were markedly reduced in response to drainage. Seven novel methanogen population genomes were recovered, and the metabolic reconstruction of highly correlated population genomes revealed novel syntrophic relationships between methanogenic archaea and syntrophic partners. These results provide a mechanistic view of microbial processes regulating GHG dynamics in the terrestrial carbon cycle, and disproportionate microbial responses to long-term drainage provide key information for understanding the effects of warming-induced soil drying on microbial processes in Arctic wetland ecosystems.

The potential for mitigation of methane emissions in ruminants through the application of metagenomics, metabolomics, and other -OMICS technologies

Ruminant supply chains contribute 5.7 gigatons of CO_2-eq per annum, which represents approximately 80% of the livestock sector emissions. One of the largest sources of emission in the ruminant sector is methane (CH₄), accounting for approximately 40% of the sectors total emissions. With climate change being a growing concern, emphasis is being put on reducing greenhouse gas emissions, including those from ruminant production. Various genetic and environmental factors influence cattle CH₄ production, such as breed, genetic makeup, diet, management practices, and physiological status of the host. The influence of genetic variability on CH₄ yield in ruminants indicates that genomic selection for reduced CH₄ emissions is possible. Although the microbiology of CH₄ production has been studied, further research is needed to identify key differences in the host and microbiome genomes and how they interact with one another. The advancement of “-omics” technologies, such as metabolomics and metagenomics, may provide valuable information in this regard. Improved understanding of genetic mechanisms associated with CH₄ production and the interaction between the microbiome profile and host genetics will increase the rate of genetic progress for reduced CH₄ emissions. Through a systems biology approach, various “-omics” technologies can be combined to unravel genomic regions and genetic markers associated with CH₄ production, which can then be used in selective breeding programs. This comprehensive review discusses current challenges in applying genomic selection for reduced CH₄ emissions, and the potential for “-omics” technologies, especially metabolomics and metagenomics, to minimize such challenges. The integration and evaluation of different levels of biological information using a systems biology approach is also discussed, which can assist in understanding the underlying genetic mechanisms and biology of CH₄ production traits in ruminants and aid in reducing agriculture’s overall environmental footprint.

Adoption of Climate Smart Agriculture by Communal Livestock Farmers in South Africa

The importance of adopting modern technology in agriculture, especially in a changing climate, cannot be underestimated in Africa. The aim of this review was to highlight the past and the status quo with regard to the adoption of current farming practices in relation to climate-smart agriculture (CSA) by communal livestock farmers in South Africa. The impact of animal agriculture on climate change was also deliberated. Different internet search engines and databases, like Google Scholar, EBSCO Host, Science Direct, etc., and peer-reviewed articles, books, and government and academic reports were employed to provide information to adequately address the aim. Keywords like “the impact of climate smart agriculture on communal livestock farmers”, “communal livestock in South Africa”, “communal farming and technology adoption”, etc. were used for the search. Various issues pertaining to the impact of animal agriculture on climate change, greenhouse gas (GHG) emissions, and implementing CSA in livestock farming were extensively discussed. The findings indicated that there is limited research on the adoption of CSA by communal livestock farmers in South Africa. The review concluded that strategies to adopt modern technology in communal areas should address the issues to enhance knowledge of farmers and all stakeholders, through increasing awareness, trainings, and skills programs. The government should build local capacity in innovative and affordable water and agricultural solutions, and reliable financial mechanisms should be in place to implement innovative sound technologies in communal areas.

Estimating maximal microbial growth rates from cultures, metagenomes, and single cells via codon usage patterns

Despite the wide perception that microbes have rapid growth rates, many environments like seawater and soil are often dominated by microorganisms that can only grow very slowly. Our knowledge about growth is necessarily biased toward easily culturable organisms, which tend to be those that grow fast, because microbial growth rates have traditionally been measured using laboratory growth experiments. However, how are potential growth rates distributed in nature? Using genomic data, we predicted the growth rates of over 200,000 organisms, including many as yet uncultivated species. These data reveal how current culture collections are strongly biased toward fast-growing organisms. Finally, we noticed a bimodal distribution of maximal growth rates, suggesting a natural division of microbial growth strategies into two classes.

Maximal growth rate is a basic parameter of microbial lifestyle that varies over several orders of magnitude, with doubling times ranging from a matter of minutes to multiple days. Growth rates are typically measured using laboratory culture experiments. Yet, we lack sufficient understanding of the physiology of most microbes to design appropriate culture conditions for them, severely limiting our ability to assess the global diversity of microbial growth rates. Genomic estimators of maximal growth rate provide a practical solution to survey the distribution of microbial growth potential, regardless of cultivation status. We developed an improved maximal growth rate estimator and predicted maximal growth rates from over 200,000 genomes, metagenome-assembled genomes, and single-cell amplified genomes to survey growth potential across the range of prokaryotic diversity; extensions allow estimates from 16S rRNA sequences alone as well as weighted community estimates from metagenomes. We compared the growth rates of cultivated and uncultivated organisms to illustrate how culture collections are strongly biased toward organisms capable of rapid growth. Finally, we found that organisms naturally group into two growth classes and observed a bias in growth predictions for extremely slow-growing organisms. These observations ultimately led us to suggest evolutionary definitions of oligotrophy and copiotrophy based on the selective regime an organism occupies. We found that these growth classes are associated with distinct selective regimes and genomic functional potentials.

Genome-resolved metagenomics using environmental and clinical samples

Recent advances in high-throughput sequencing technologies and computational methods have added a new dimension to metagenomic data analysis i.e. genome-resolved metagenomics. In general terms, it refers to the recovery of draft or high-quality microbial genomes and their taxonomic classification and functional annotation. In recent years, several studies have utilized the genome-resolved metagenome analysis approach and identified previously unknown microbial species from human and environmental metagenomes. In this review, we describe genome-resolved metagenome analysis as a series of four necessary steps: (i) preprocessing of the sequencing reads, (ii) de novo metagenome assembly, (iii) genome binning and (iv) taxonomic and functional analysis of the recovered genomes. For each of these four steps, we discuss the most commonly used tools and the currently available pipelines to guide the scientific community in the recovery and subsequent analyses of genomes from any metagenome sample. Furthermore, we also discuss the tools required for validation of assembly quality as well as for improving quality of the recovered genomes. We also highlight the currently available pipelines that can be used to automate the whole analysis without having advanced bioinformatics knowledge. Finally, we will highlight the most widely adapted and actively maintained tools and pipelines that can be helpful to the scientific community in decision making before they commence the analysis.

Horizontal Gene Transfer Is the Main Driver of Antimicrobial Resistance in Broiler Chicks Infected with Salmonella enterica Serovar Heidelberg

The overuse and misuse of antibiotics in clinical settings and in food production have been linked to the increased prevalence and spread of antimicrobial resistance (AR). Consequently, public health and consumer concerns have resulted in a remarkable reduction in antibiotics used for food animal production. However, there are no data on the effectiveness of antibiotic removal in reducing AR shared through horizontal gene transfer (HGT). In this study, we used neonatal broiler chicks and Salmonella enterica serovar Heidelberg, a model food pathogen, to test if chicks raised antibiotic free harbor transferable AR. We challenged chicks with an antibiotic-susceptible S. Heidelberg strain using various routes of inoculation and determined if S. Heidelberg isolates recovered carried plasmids conferring AR. We used antimicrobial susceptibility testing and whole-genome sequencing (WGS) to show that chicks grown without antibiotics harbored an antimicrobial resistant S. Heidelberg population at 14 days after challenge and chicks challenged orally acquired AR at a higher rate than chicks inoculated via the cloaca. Using 16S rRNA gene sequencing, we found that S. Heidelberg infection perturbed the microbiota of broiler chicks, and we used metagenomics and WGS to confirm that a commensal Escherichia coli population was the main reservoir of an IncI1 plasmid acquired by S. Heidelberg. The carriage of this IncI1 plasmid posed no fitness cost to S. Heidelberg but increased its fitness when exposed to acidic pH in vitro. These results suggest that HGT of plasmids carrying AR shaped the evolution of S. Heidelberg and that antibiotic use reduction alone is insufficient to limit antibiotic resistance transfer from commensal bacteria to Salmonella enterica.

IMPORTANCE The reported increase in antibiotic-resistant bacteria in humans has resulted in a major shift away from antibiotic use in food animal production. This shift has been driven by the assumption that removing antibiotics will select for antibiotic susceptible bacterial taxa, which in turn will allow the currently available antibiotic arsenal to be more effective. This change in practice has highlighted new questions that need to be answered to assess the effectiveness of antibiotic removal in reducing the spread of antibiotic resistance bacteria. This research demonstrates that antibiotic-susceptible Salmonella enterica serovar Heidelberg strains can acquire multidrug resistance from commensal bacteria present in the gut of neonatal broiler chicks, even in the absence of antibiotic selection. We demonstrate that exposure to acidic pH drove the horizontal transfer of antimicrobial resistance plasmids and suggest that simply removing antibiotics from food animal production might not be sufficient to limit the spread of antimicrobial resistance.

Effects of Age, Diet CP, NDF, EE, and Starch on the Rumen Bacteria Community and Function in Dairy Cattle

To understand the effects of diet and age on the rumen bacterial community and function, forty-eight dairy cattle at 1.5 (M1.5), 6 (M6), 9 (M9), 18 (M18), 23 (M23), and 27 (M27) months old were selected. Rumen fermentation profile, enzyme activity, and bacteria community in rumen fluid were measured. The acetate to propionate ratio (A/P) at M9, M18, and M23 was higher than other ages, and M6 was the lowest (p < 0.05). The total volatile fatty acid (TVFA) at M23 and M27 was higher than at other ages (p < 0.05). The urease at M18 was lower than at M1.5, M6, and M9, and the xylanase at M18 was higher than at M1.5, M23, and M27 (p < 0.05). Thirty-three bacteria were identified as biomarkers of the different groups based on the linear discriminant analysis (LDA) when the LDA score >4. The variation partitioning approach analysis showed that the age and diet had a 7.98 and 32.49% contribution to the rumen bacteria community variation, respectively. The richness of Succinivibrionaceae_UCG-002 and Fibrobacter were positive correlated with age (r > 0.60, p < 0.01) and positively correlated with TVFA and acetate (r > 0.50, p < 0.01). The Lachnospiraceae_AC2044_group, Pseudobutyrivibrio, and Saccharofermentans has a positive correlation (r > 0.80, p < 0.05) with diet fiber and a negative correlation (r < −0.80, p < 0.05) with diet protein and starch, which were also positively correlated with the acetate and A/P (r > 0.50, p < 0.01). The genera of Lachnospiraceae_AC2044_group, Pseudobutyrivibrio, and Saccharofermentans could be worked as the target bacteria to modulate the rumen fermentation by diet; meanwhile, the high age correlated bacteria such as Succinivibrionaceae_UCG-002 and Fibrobacter also should be considered when shaping the rumen function.

New approaches for metagenome assembly with short reads

In recent years, the use of longer range read data combined with advances in assembly algorithms has stimulated big improvements in the contiguity and quality of genome assemblies. However, these advances have not directly transferred to metagenomic data sets, as assumptions made by the single genome assembly algorithms do not apply when assembling multiple genomes at varying levels of abundance. The development of dedicated assemblers for metagenomic data was a relatively late innovation and for many years, researchers had to make do using tools designed for single genomes. This has changed in the last few years and we have seen the emergence of a new type of tool built using different principles. In this review, we describe the challenges inherent in metagenomic assemblies and compare the different approaches taken by these novel assembly tools.

Metagenome-Assembled Genomes Contribute to Unraveling of the Microbiome of Cocoa Fermentation

Metagenomic studies about cocoa fermentation have mainly reported on the analysis of short reads for determination of operational taxonomic units. However, it is also important to determine metagenome-assembled genomes (MAGs), which are genomes deriving from the assembly of metagenomics. For this research, all the cocoa metagenomes from public databases were downloaded, resulting in five data sets: one from Ghana and four from Brazil. In addition, in silico approaches were used to describe putative phenotypes and the metabolic potential of MAGs. A total of 17 high-quality MAGs were recovered from these microbiomes, as follows: (i) for fungi, Yamadazyma tenuis (n = 1); (ii) lactic acid bacteria, Limosilactobacillus fermentum (n = 5), Liquorilactobacillus cacaonum (n = 1), Liquorilactobacillus nagelli (n = 1), Leuconostoc pseudomesenteroides (n = 1), and Lactiplantibacillus plantarum subsp. plantarum (n = 1); (iii) acetic acid bacteria, Acetobacter senegalensis (n = 2) and Kozakia baliensis (n = 1); and (iv) Bacillus subtilis (n = 1), Brevundimonas sp. (n = 2), and Pseudomonas sp. (n = 1). Medium-quality MAGs were also recovered from cocoa microbiomes, including some that, to our knowledge, were not previously detected in this environment (Liquorilactobacillus vini, Komagataeibacter saccharivorans, and Komagataeibacter maltaceti) and others previously described (Fructobacillus pseudoficulneus and Acetobacter pasteurianus). Taken together, the MAGs were useful for providing an additional description of the microbiome of cocoa fermentation, revealing previously overlooked microorganisms, with prediction of key phenotypes and biochemical pathways. IMPORTANCE The production of chocolate starts with the harvesting of cocoa fruits and the spontaneous fermentation of the seeds in a microbial succession that depends on yeasts, lactic acid bacteria, and acetic acid bacteria in order to eliminate bitter and astringent compounds present in the raw material, which will be further roasted and grinded to originate the cocoa powder that will enter the food processing industry. The microbiota of cocoa fermentation is not completely known, and yet it advanced from culture-based studies to the advent of next-generation DNA sequencing, with the generation of a myriad of data that need bioinformatic approaches to be properly analyzed. Although the majority of metagenomic studies have been based on short reads (operational taxonomic units), it is also important to analyze entire genomes to determine more precisely possible ecological roles of different species. Metagenome-assembled genomes (MAGs) are very useful for this purpose; here, MAGs from cocoa fermentation microbiomes are described, and the possible implications of their phenotypic and metabolic potentials are discussed.

Disentangling the syntrophic electron transfer mechanisms of Candidatus geobacter eutrophica through electrochemical stimulation and machine learning

Interspecies hydrogen transfer (IHT) and direct interspecies electron transfer (DIET) are two syntrophy models for methanogenesis. Their relative importance in methanogenic environments is still unclear. Our recent discovery of a novel species Candidatus Geobacter eutrophica with the genetic potential of IHT and DIET may serve as a model species to address this knowledge gap. To experimentally demonstrate its DIET ability, we performed electrochemical enrichment of Ca. G. eutrophica-dominating communities under 0 and 0.4 V vs. Ag/AgCl based on the presumption that DIET and extracellular electron transfer (EET) share similar metabolic pathways. After three batches of enrichment, Geobacter OTU650, which was phylogenetically close to Ca. G. eutrophica, was outcompeted in the control but remained abundant and active under electrochemical stimulation, indicating Ca. G. eutrophica's EET ability. The high-quality draft genome further showed high phylogenomic similarity with Ca. G. eutrophica, and the genes encoding outer membrane cytochromes and enzymes for hydrogen metabolism were actively expressed. A Bayesian network was trained with the genes encoding enzymes for alcohol metabolism, hydrogen metabolism, EET, and methanogenesis from dominant fermentative bacteria, Geobacter, and Methanobacterium. Methane production could not be accurately predicted when the genes for IHT were in silico knocked out, inferring its more important role in methanogenesis. The genomics-enabled machine learning modeling approach can provide predictive insights into the importance of IHT and DIET.

Genome reconstruction and haplotype phasing using chromosome conformation capture methodologies

Genomic analysis of individuals or organisms is predicated on the availability of high-quality reference and genotype information. With the rapidly dropping costs of high-throughput DNA sequencing, this is becoming readily available for diverse organisms and for increasingly large populations of individuals. Despite these advances, there are still aspects of genome sequencing that remain challenging for existing sequencing methods. This includes the generation of long-range contiguity during genome assembly, identification of structural variants in both germline and somatic tissues, the phasing of haplotypes in diploid organisms and the resolution of genome sequence for organisms derived from complex samples. These types of information are valuable for understanding the role of genome sequence and genetic variation on genome function, and numerous approaches have been developed to address them. Recently, chromosome conformation capture (3C) experiments, such as the Hi-C assay, have emerged as powerful tools to aid in these challenges for genome reconstruction. We will review the current use of Hi-C as a tool for aiding in genome sequencing, addressing the applications, strengths, limitations and potential future directions for the use of 3C data in genome analysis. We argue that unique features of Hi-C experiments make this data type a powerful tool to address challenges in genome sequencing, and that future integration of Hi-C data with alternative sequencing assays will facilitate the continuing revolution in genomic analysis and genome sequencing.

Accessing Dietary Effects on the Rumen Microbiome: Different Sequencing Methods Tell Different Stories

The current study employed both amplicon and shotgun sequencing to examine and compare the rumen microbiome in Angus bulls fed with either a backgrounding diet (BCK) or finishing diet (HG), to assess if both methods produce comparable results. Rumen digesta samples from 16 bulls were subjected for microbial profiling. Distinctive microbial profiles were revealed by the two methods, indicating that choice of sequencing approach may be a critical facet in studies of the rumen microbiome. Shotgun-sequencing identified the presence of 303 bacterial genera and 171 archaeal species, several of which exhibited differential abundance. Amplicon-sequencing identified 48 bacterial genera, 4 archaeal species, and 9 protozoal species. Among them, 20 bacterial genera and 5 protozoal species were differentially abundant between the two diets. Overall, amplicon-sequencing showed a more drastic diet-derived effect on the ruminal microbial profile compared to shotgun-sequencing. While both methods detected dietary differences at various taxonomic levels, few consistent patterns were evident. Opposite results were seen for the phyla Firmicutes and Bacteroidetes, and the genus Selenomonas. This study showcases the importance of sequencing platform choice and suggests a need for integrative methods that allow robust comparisons of microbial data drawn from various omic approaches, allowing for comprehensive comparisons across studies.

Hi-C deconvolution of a textile dye-related microbiome reveals novel taxonomic landscapes and links phenotypic potential to individual genomes

Microbial biodiversity is represented by a variety of genomic landscapes adapted to dissimilar environments on Earth. These genomic landscapes contain functional signatures connected with the community phenotypes. Here, we assess the genomic microbial diversity landscape at a high-resolution level of a polluted river-associated microbiome (Morelos, México), cultured in a medium enriched with anthraquinone Deep Blue 35 dye. We explore the resultant textile dye microbiome to infer links between predicted biodegradative functions, and metagenomic and metabolic potential, especially using the information obtained from individual reconstructed genomes. By using Hi-C proximity-ligation deconvolution method, we deconvoluted 97 genome composites (80% potentially novel species). The main taxonomic determinants were Methanobacterium, Clostridium, and Cupriavidus genera constituting 50, 22, and 11% of the total community profile. Also, we observed a rare biosphere of novel taxa without clear taxonomic standing. Removal of 50% chemical oxygen demand with 23% decolorization was observed after 30 days of dye enrichment. Genes related to catalase-peroxidase, polyphenol oxidase, and laccase enzymes were predicted as associated with textile dye biodegradation phenotype under our study conditions, highlighting the potential of metagenome-wide analysis to predict biodegradative determinants. This study prompts high-resolution screening of individual genomes within textile dye river sediment microbiomes or complex communities under environmental pressures.

Insights into rumen microbial biosynthetic gene cluster diversity through genome-resolved metagenomics

Ruminants are critical to global food security as they transform lignocellulosic biomass into high-quality protein products. The rumen microbes ferment feed to provide necessary energy and nutrients for the ruminant host. However, we still lack insight into the metabolic processes encoded by most rumen microbial populations. In this study, we implemented metagenomic binning approaches to recover 2,809 microbial genomes from cattle, sheep, moose, deer, and bison. By clustering genomes based on average nucleotide identity, we demonstrate approximately one-third of the metagenome-assembled genomes (MAGs) to represent species not present in current reference databases and rumen microbial genome collections. Combining these MAGs with other rumen genomic datasets permitted a phylogenomic characterization of the biosynthetic gene clusters (BGCs) from 8,160 rumen microbial genomes, including the identification of 195 lanthipeptides and 5,346 diverse gene clusters for nonribosomal peptide biosynthesis. A subset of Prevotella and Selenomonas BGCs had higher expression in steers with lower feed efficiency. Moreover, the microdiversity of BGCs was fairly constant across types of BGCs and cattle breeds. The reconstructed genomes expand the genomic representation of rumen microbial lineages, improve the annotation of multi-omics data, and link microbial populations to the production of secondary metabolites that may constitute a source of natural products for manipulating rumen fermentation.

Anderson and Fernando use metagenomic binning approaches to reconstruct 2,809 microbial metagenome-assembled genomes from ruminants, and perform phylogenomic analyses on the biosynthetic gene clusters from over 8,000 total rumen microbial genomes. These genomes provide insight into the relationship between microbial populations and the production of secondary metabolites that may be important for manipulating rumen fermentation.

An integrated gene catalog and over 10,000 metagenome-assembled genomes from the gastrointestinal microbiome of ruminants

BACKGROUND

Gastrointestinal tract (GIT) microbiomes in ruminants play major roles in host health and thus animal production. However, we lack an integrated understanding of microbial community structure and function as prior studies. are predominantly biased towards the rumen. Therefore, to acquire a microbiota inventory of the discrete GIT compartments, In this study, we used shotgun metagenomics to profile the microbiota of 370 samples that represent 10 GIT regions of seven ruminant species.

RESULTS

Our analyses reconstructed a GIT microbial reference catalog with > 154 million nonredundant genes and identified 8745 uncultured candidate species from over 10,000 metagenome-assembled genomes. The integrated gene catalog across the GIT regions demonstrates spatial associations between the microbiome and physiological adaptations, and 8745 newly characterized genomes substantially expand the genomic landscape of ruminant microbiota, particularly those from the lower gut. This substantially expands the previously known set of endogenous microbial diversity and the taxonomic classification rate of the GIT microbiome. These candidate species encode hundreds of enzymes and novel biosynthetic gene clusters that improve our understanding concerning methane production and feed efficiency in ruminants. Overall, this study expands the characterization of the ruminant GIT microbiota at unprecedented spatial resolution and offers clues for improving ruminant livestock production in the future.

CONCLUSIONS

Having access to a comprehensive gene catalog and collections of microbial genomes provides the ability to perform efficiently genome-based analysis to achieve a detailed classification of GIT microbial ecosystem composition. Our study will bring unprecedented power in future association studies to investigate the impact of the GIT microbiota in ruminant health and production. Video abstract.

Major genetic discontinuity and novel toxigenic species in Clostridioides difficile taxonomy

Clostridioides difficile infection (CDI) remains an urgent global One Health threat. The genetic heterogeneity seen across C. difficile underscores its wide ecological versatility and has driven the significant changes in CDI epidemiology seen in the last 20 years. We analysed an international collection of over 12,000 C. difficile genomes spanning the eight currently defined phylogenetic clades. Through whole-genome average nucleotide identity, and pangenomic and Bayesian analyses, we identified major taxonomic incoherence with clear species boundaries for each of the recently described cryptic clades CI–III. The emergence of these three novel genomospecies predates clades C1–5 by millions of years, rewriting the global population structure of C. difficile specifically and taxonomy of the Peptostreptococcaceae in general. These genomospecies all show unique and highly divergent toxin gene architecture, advancing our understanding of the evolution of C. difficile and close relatives. Beyond the taxonomic ramifications, this work may impact the diagnosis of CDI.

A Metagenomic Insight Into the Hindgut Microbiota and Their Metabolites for Dairy Goats Fed Different Rumen Degradable Starch

High starch diets have been proven to increase the risk of hindgut acidosis in high-yielding dairy animals. As an effective measurement of dietary carbohydrate for ruminants, studies on rumen degradable starch (RDS) and the effects on the gut microbiota diversity of carbohydrate-active enzymes (CAZymes), and Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology functional categories are helpful to understand the mechanisms between gut microbiota and carbohydrate metabolism in dairy goats. A total of 18 lactating goats (45.8 ± 1.54 kg) were randomly divided equally into three dietary treatments with low dietary RDS concentrations of 20.52% (LRDS), medium RDS of 22.15% (MRDS), and high RDS of 24.88% (HRDS) on a DM basis for 5 weeks. Compared with the LRDS and MRDS groups, HRDS increased acetate molar proportion in the cecum. For the HRDS group, the abundance of family Ruminococcaceae and genus Ruminococcaceae UCG-010 were significantly increased in the cecum. For the LRDS group, the butyrate molar proportion and the abundance of butyrate producer family Bacteroidale_S24-7, family Lachnospiraceae, and genus Bacteroidale_S24-7_group were significantly increased in the cecum. Based on the BugBase phenotypic prediction, the microbial oxidative stress tolerant and decreased potentially pathogenic in the LRDS group were increased in the cecum compared with the HRDS group. A metagenomic study on cecal bacteria revealed that dietary RDS level could affect carbohydrate metabolism by increasing the glycoside hydrolase 95 (GH95) family and cellulase enzyme (EC 3.2.1.4) in the HRDS group; increasing the GH13_20 family and isoamylase enzyme (EC 3.2.1.68) in the LRDS group. PROBIO probiotics database showed the relative gene abundance of cecal probiotics significantly decreased in the HRDS group. Furthermore, goats fed the HRDS diet had a lower protein expression of Muc2, and greater expression RNA of interleukin-1β and secretory immunoglobulin A in cecal mucosa than did goats fed the LRDS diet. Combined with the information from previous results from rumen, dietary RDS level altered the degradation position of carbohydrates in the gastrointestinal (GI) tract and increased the relative abundance of gene encoded enzymes degrading cellulose in the HRDS group in the cecum of dairy goats. This study revealed that the HRDS diet could bring disturbances to the microbial communities network containing taxa of the Lachnospiraceae and Ruminococcaceae and damage the mucus layer and inflammation in the cecum of dairy goats.

Pd-promoting reduction of zinc salt to PdZn alloy catalyst for the hydrogenation of nitrothioanisole

Catalytic hydrogenation of sulfur-containing substrates is an important and challenging reaction in the chemical industry. In this work, active carbon supported PdZn alloy catalyst was prepared by self-reduction method using zinc acetate as precursor without H₂ atmosphere. During the process of self-reduction, Zn²⁺ was firstly reduced to Zn⁰ at 300 °C by active carbon and reducing gas from the decompose of acetate under the promotion of metal Pd, and Zn⁰ further reacted with metal Pd to form PdZn alloy phase at 500 °C. These PdZn/AC-X catalysts showed the higher conversion and stability for the hydrogenation of 4-nitrothioanisole than the Pd/AC-600 catalyst. The excellent catalytic performance of PdZn/AC-600 catalyst can be attributed to formation of PdZn alloy, in which electron-rich Pd atoms weaken the binding ability between Pd and S and enhance the sulfur-resistance of catalyst. On the other hand, H₂-TPR and DFT theory calculation further indicated that the PdZn alloy phase weakens the adsorption capacity of S. Compared with the Pd/AC-600 catalyst, the PdZn alloy phase in PdZn/AC-600 catalyst has not changed and only a small amount of sulfur-containing substrates deposited on the catalyst surface after three cycles. PdZn/AC-600 catalyst exhibited improved stability in the hydrogenation of 4-nitrothioanisole and can be used three cycles with little decrease in activity.

Recovery of human gut microbiota genomes with third-generation sequencing

Human gut microbiota modulates normal physiological functions, such as maintenance of barrier homeostasis and modulation of metabolism, as well as various chronic diseases including type 2 diabetes and gastrointestinal cancer. Despite decades of research, the composition of the gut microbiota remains poorly understood. Here, we established an effective extraction method to obtain high quality gut microbiota genomes, and analyzed them with third-generation sequencing technology. We acquired a large quantity of data from each sample and assembled large numbers of reliable contigs. With this approach, we constructed tens of completed bacterial genomes in which there were several new bacteria species. We also identified a new conditional pathogen, Enterococcus tongjius, which is a member of Enterococci. This work provided a novel and reliable approach to recover gut microbiota genomes, facilitating the discovery of new bacteria species and furthering our understanding of the microbiome that underlies human health and diseases.

Automated analysis of genomic sequences facilitates high-throughput and comprehensive description of bacteria

The study of microbial communities is hampered by the large fraction of still unknown bacteria. However, many of these species have been isolated, yet lack a validly published name or description. The validation of names for novel bacteria requires that the uniqueness of those taxa is demonstrated and their properties are described. The accepted format for this is the protologue, which can be time-consuming to create. Hence, many research fields in microbiology and biotechnology will greatly benefit from new approaches that reduce the workload and harmonise the generation of protologues.We have developed Protologger, a bioinformatic tool that automatically generates all the necessary readouts for writing a detailed protologue. By producing multiple taxonomic outputs, functional features and ecological analysis using the 16S rRNA gene and genome sequences from a single species, the time needed to gather the information for describing novel taxa is substantially reduced. The usefulness of Protologger was demonstrated by using three published isolate collections to describe 34 novel taxa, encompassing 17 novel species and 17 novel genera, including the automatic generation of ecologically and functionally relevant names. We also highlight the need to utilise multiple taxonomic delineation methods, as while inconsistencies between each method occur, a combined approach provides robust placement. Protologger is open source; all scripts and datasets are available, along with a webserver at www.protologger.de.

Early-Life Immune System Maturation in Chickens Using a Synthetic Community of Cultured Gut Bacteria

The gut microbiome is crucial for both maturation of the immune system and colonization resistance against enteric pathogens. Although chicken are important domesticated animals, the impact of their gut microbiome on the immune system is understudied. Therefore, we investigated the effect of microbiome-based interventions on host mucosal immune responses. Increased levels of IgA and IgY were observed in chickens exposed to maternal feces after hatching compared with strict hygienic conditions. This was accompanied by increased gut bacterial diversity as assessed by 16S rRNA gene amplicon sequencing. Cultivation work allowed the establishment of a collection of 43 bacterial species spanning 4 phyla and 19 families, including the first cultured members of 3 novel genera and 4 novel species that were taxonomically described. This resource is available at www.dsmz.de/chibac. A synthetic community consisting of nine phylogenetically diverse and dominant species from this collection was designed and found to be moderately efficient in boosting immunoglobulin levels when provided to chickens early in life.

IMPORTANCE The immune system plays a crucial role in sustaining animal health. Its development is markedly influenced by early microbial colonization of the gastrointestinal tract. As chicken are fully dependent on environmental microbes after hatching, extensive hygienic measures in production facilities are detrimental to the microbiota, resulting in low colonization resistance against pathogens. To combat enteric infections, antibiotics are frequently used, which aggravates the issue by altering gut microbiota colonization. Intervention strategies based on cultured gut bacteria are proposed to influence immune responses in chicken.

Diversity and genomic determinants of the microbiomes associated with COVID-19 and non-COVID respiratory diseases

The novel coronavirus disease 2019 (COVID-19) is a rapidly emerging and highly transmissible disease caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). Understanding the microbiomes associated with the upper respiratory tract infection (URTI), chronic obstructive pulmonary disease (COPD) and COVID-19 diseases has clinical interest. We hypothesize that microbiome diversity and composition, and their genomic features are associated with different pathological conditions of these human respiratory tract diseases. To test this hypothesis, we analyzed 21 RNASeq metagenomic data including eleven COVID-19 (BD = 6 and China = 5), six COPD (UK = 6) and four URTI (USA = 4) samples to unravel the microbiome diversity and related genomic metabolic functions. The metagenomic data mapped to 534 bacterial, 60 archaeal and 61 viral genomes with distinct variation in the microbiome composition across the samples (COVID-19 > COPD > URTI). Notably, 94.57%, 80.0% and 24.59% bacterial, archaeal and viral genera shared between the COVID-19 and non-COVID samples, respectively. However, the COVID-19 related samples had sole association with 16 viral genera other than SARS-CoV-2. Strain-level virome profiling revealed 660 and 729 strains in COVID-19 and non-COVID samples, respectively, and of them 34.50% strains shared between the conditions. Functional annotation of the metagenomic data identified the association of several biochemical pathways related to basic metabolism (amino acid and energy), ABC transporters, membrane transport, virulence, disease and defense, regulation of virulence, programmed cell death, and primary immunodeficiency. We also detected 30 functional gene groups/classes associated with resistance to antibiotics and toxic compounds (RATC) in both COVID-19 and non-COVID microbiomes. Furthermore, we detected comparatively higher abundance of cobalt-zinc-cadmium resistance (CZCR) and multidrug resistance to efflux pumps (MREP) genes in COVID-19 metagenome. The profiles of microbiome diversity and associated microbial genomic features found in both COVID-19 and non-COVID (COPD and URTI) samples might be helpful in developing microbiome-based diagnostics and therapeutics for COVID-19 and non-COVID respiratory diseases. However, future studies might be carried out to explore the microbiome dynamics and the cross-talk between host and microbiomes employing larger volume of samples from different ethnic groups and geoclimatic conditions.

A practical guide to amplicon and metagenomic analysis of microbiome data

Advances in high-throughput sequencing (HTS) have fostered rapid developments in the field of microbiome research, and massive microbiome datasets are now being generated. However, the diversity of software tools and the complexity of analysis pipelines make it difficult to access this field. Here, we systematically summarize the advantages and limitations of microbiome methods. Then, we recommend specific pipelines for amplicon and metagenomic analyses, and describe commonly-used software and databases, to help researchers select the appropriate tools. Furthermore, we introduce statistical and visualization methods suitable for microbiome analysis, including alpha- and beta-diversity, taxonomic composition, difference comparisons, correlation, networks, machine learning, evolution, source tracing, and common visualization styles to help researchers make informed choices. Finally, a step-by-step reproducible analysis guide is introduced. We hope this review will allow researchers to carry out data analysis more effectively and to quickly select the appropriate tools in order to efficiently mine the biological significance behind the data.

Recovering prokaryotic genomes from host-associated, short-read shotgun metagenomic sequencing data

Recovering genomes from shotgun metagenomic sequence data allows detailed taxonomic and functional characterization of individual species or strains in a microbial community. Retrieving these metagenome-assembled genomes (MAGs) involves seven stages. First, low-quality bases, along with adapter and host sequences, are removed. Second, overlapping sequences are assembled to create longer contiguous fragments. Third, these fragments are clustered based on sequence composition and abundance. Fourth, these sequence clusters, or bins, undergo rounds of quality assessment and refinement to yield MAGs. The optional fifth stage is dereplication of MAGs to select representatives. Next, each MAG is taxonomically classified. The optional seventh stage is assessing the fraction of diversity that has been recovered. The output of this protocol is draft genomes, which can provide invaluable clues about uncultured organisms. This protocol takes ~1 week to run, depending on computational resources available, and requires prior experience with high-performance computing, shell script programming and Python.

Characterizing rumen microbiota and CAZyme profile of Indian dromedary camel (Camelus dromedarius) in response to different roughages

In dromedary camels, which are pseudo-ruminants, rumen or C1 section of stomach is the main compartment involved in fiber degradation, as in true ruminants. However, as camels are adapted to the harsh and scarce grazing conditions of desert, their ruminal microbiota makes an interesting target of study. The present study was undertaken to generate the rumen microbial profile of Indian camel using 16S rRNA amplicon and shotgun metagenomics. The camels were fed three diets differing in the source of roughage. The comparative metagenomic analysis revealed greater proportions of significant differences between two fractions of rumen content followed by diet associated differences. Significant differences were also observed in the rumen microbiota collected at different time-points of the feeding trial. However, fraction related differences were more highlighted as compared to diet dependent changes in microbial profile from shotgun metagenomics data. Further, 16 genera were identified as part of the core rumen microbiome of Indian camels. Moreover, glycoside hydrolases were observed to be the most abundant among all Carbohydrate-Active enzymes and were dominated by GH2, GH3, GH13 and GH43. In all, this study describes the camel rumen microbiota under different dietary conditions with focus on taxonomic, functional, and Carbohydrate-Active enzymes profiles.

Extensive microbial diversity within the chicken gut microbiome revealed by metagenomics and culture

BACKGROUND

The chicken is the most abundant food animal in the world. However, despite its importance, the chicken gut microbiome remains largely undefined. Here, we exploit culture-independent and culture-dependent approaches to reveal extensive taxonomic diversity within this complex microbial community.

RESULTS

We performed metagenomic sequencing of fifty chicken faecal samples from two breeds and analysed these, alongside all (n = 582) relevant publicly available chicken metagenomes, to cluster over 20 million non-redundant genes and to construct over 5,500 metagenome-assembled bacterial genomes. In addition, we recovered nearly 600 bacteriophage genomes. This represents the most comprehensive view of taxonomic diversity within the chicken gut microbiome to date, encompassing hundreds of novel candidate bacterial genera and species. To provide a stable, clear and memorable nomenclature for novel species, we devised a scalable combinatorial system for the creation of hundreds of well-formed Latin binomials. We cultured and genome-sequenced bacterial isolates from chicken faeces, documenting over forty novel species, together with three species from the genus Escherichia, including the newly named species Escherichia whittamii.

CONCLUSIONS

Our metagenomic and culture-based analyses provide new insights into the bacterial, archaeal and bacteriophage components of the chicken gut microbiome. The resulting datasets expand the known diversity of the chicken gut microbiome and provide a key resource for future high-resolution taxonomic and functional studies on the chicken gut microbiome.

Metagenomic analysis reveals a dynamic microbiome with diversified adaptive functions to utilize high lignocellulosic forages in the cattle rumen

Rumen microbiota play a key role in the digestion and utilization of plant materials by the ruminant species, which have important implications for greenhouse gas emission. Yet, little is known about the key taxa and potential gene functions involved in the digestion process. Here, we performed a genome-centric analysis of rumen microbiota attached to six different lignocellulosic biomasses in rumen-fistulated cattle. Our metagenome sequencing provided novel genomic insights into functional potential of 523 uncultured bacteria and 15 mostly uncultured archaea in the rumen. The assembled genomes belonged mainly to Bacteroidota, Firmicutes, Verrucomicrobiota, and Fibrobacterota and were enriched for genes related to the degradation of lignocellulosic polymers and the fermentation of degraded products into short chain volatile fatty acids. We also found a shift from copiotrophic to oligotrophic taxa during the course of rumen fermentation, potentially important for the digestion of recalcitrant lignocellulosic substrates in the physiochemically complex and varying environment of the rumen. Differential colonization of forages (the incubated lignocellulosic materials) by rumen microbiota suggests that taxonomic and metabolic diversification is an evolutionary adaptation to diverse lignocellulosic substrates constituting a major component of the cattle's diet. Our data also provide novel insights into the key role of unique microbial diversity and associated gene functions in the degradation of recalcitrant lignocellulosic materials in the rumen.

A genomic catalog of Earth's microbiomes

The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth's continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes.