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

Host genetics influence the rumen microbiota and heritable rumen microbial features associate with feed efficiency in cattle

BACKGROUND

The symbiotic rumen microbiota is essential for the digestion of plant fibers and contributes to the variation of production and health traits in ruminants. However, to date, the heritability of rumen microbial features and host genetic components associated with the rumen microbiota, as well as whether such genetic components are animal performance relevant, are largely unknown.

RESULTS

In the present study, we assessed rumen microbiota from a cohort of 709 beef cattle and showed that multiple factors including breed, sex, and diet drove the variation of rumen microbiota among animals. The diversity indices, the relative abundance of ~ 34% of microbial taxa (59 out of 174), and the copy number of total bacteria had a heritability estimate (h²) ≥ 0.15, suggesting that they are heritable elements affected by host additive genetics. These moderately heritable rumen microbial features were also found to be associated with host feed efficiency traits and rumen metabolic measures (volatile fatty acids). Moreover, 19 single nucleotide polymorphisms (SNPs) located on 12 bovine chromosomes were found to be associated with 14 (12 of them had h² ≥ 0.15) rumen microbial taxa, and five of these SNPs were known quantitative trait loci for feed efficiency in cattle.

CONCLUSIONS

These findings suggest that some rumen microbial features are heritable and could be influenced by host genetics, highlighting a potential to manipulate and obtain a desirable and efficient rumen microbiota using genetic selection and breeding. It could be a useful strategy to further improve feed efficiency and optimize rumen fermentation through targeting both cattle and their rumen microbiota.

Mining of camel rumen metagenome to identify novel alkali-thermostable xylanase capable of enhancing the recalcitrant lignocellulosic biomass conversion

The aim of this study was to isolate and characterize novel alkali-thermostable xylanase genes from the mixed genome DNA of camel rumen metagenome. In this study, a five-stage computational screening procedure was utilized to find the primary candidate enzyme with superior properties from the camel rumen metagenome. This enzyme was subjected to cloning, purification, and structural and functional characterization. It showed high thermal stability, high activity in a broad range of pH (6-11) and temperature (30-90 °C) and effectivity in recalcitrant lignocellulosic biomass degradation. Our results demonstrated the power of in silico analysis to discover novel alkali-thermostable xylanases, effective for the bioconversion of lignocellulosic biomass.

Sequencing-based methods and resources to study antimicrobial resistance

Antimicrobial resistance extracts high morbidity, mortality and economic costs yearly by rendering bacteria immune to antibiotics. Identifying and understanding antimicrobial resistance are imperative for clinical practice to treat resistant infections and for public health efforts to limit the spread of resistance. Technologies such as next-generation sequencing are expanding our abilities to detect and study antimicrobial resistance. This Review provides a detailed overview of antimicrobial resistance identification and characterization methods, from traditional antimicrobial susceptibility testing to recent deep-learning methods. We focus on sequencing-based resistance discovery and discuss tools and databases used in antimicrobial resistance studies.

MAGpy: a reproducible pipeline for the downstream analysis of metagenome-assembled genomes (MAGs)

MOTIVATION

Metagenomics is a powerful tool for assaying the DNA from every genome present in an environment. Recent advances in bioinformatics have enabled the rapid assembly of near-complete metagenome-assembled genomes (MAGs), and there is a need for reproducible pipelines that can annotate and characterize thousands of genomes simultaneously, to enable identification and functional characterization.

RESULTS

Here we present MAGpy, a scalable and reproducible pipeline that takes multiple genome assemblies as FASTA and compares them to several public databases, checks quality, suggests a taxonomy and draws a phylogenetic tree.

AVAILABILITY AND IMPLEMENTATION

MAGpy is available on github: https://github.com/WatsonLab/MAGpy.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Invited review: Application of meta-omics to understand the dynamic nature of the rumen microbiome and how it responds to diet in ruminants

Ruminants are unique among livestock due to their ability to efficiently convert plant cell wall carbohydrates into meat and milk. This ability is a result of the evolution of an essential symbiotic association with a complex microbial community in the rumen that includes vast numbers of bacteria, methanogenic archaea, anaerobic fungi and protozoa. These microbes produce a diverse array of enzymes that convert ingested feedstuffs into volatile fatty acids and microbial protein which are used by the animal for growth. Recent advances in high-throughput sequencing and bioinformatic analyses have helped to reveal how the composition of the rumen microbiome varies significantly during the development of the ruminant host, and with changes in diet. These sequencing efforts are also beginning to explain how shifts in the microbiome affect feed efficiency. In this review, we provide an overview of how meta-omics technologies have been applied to understanding the rumen microbiome, and the impact that diet has on the rumen microbial community.

A metagenomic analysis of the relationship between microorganisms and flavor development in Shaoxing mechanized huangjiu fermentation mashes

Complex microbial metabolism is responsible for the unique flavor of Shaoxing mechanized huangjiu. However, the relationship between the microorganisms present during fermentation and the formation of specific flavor components is difficult to understand. In this study, gas chromatography-mass spectrometry and high-performance liquid chromatography were used to identify flavor components, and a metagenomic sequencing approach was used to characterize the taxonomic and functional attributes of the Shaoxing mechanized huangjiu fermentation microbiota. The metagenomic sequencing data were used to predict the relationship between microorganisms and flavor formation. The chromatographic analysis identified amino acids, alcohols, acids, phenols and esters as major flavor components, and six microbial genera (Saccharomyces, Aspergillus, Saccharopolyspora, Staphylococcus, Lactobacillus, and Lactococcus) were most closely related to the production of these flavor components. This study helps clarify the different metabolic roles of microorganisms in flavor formation during Shaoxing huangjiu fermentation.

Meta-omics based analyses of microbiome involved in biomethanation of rice straw in a thermophilic anaerobic bioreactor under optimized conditions

Biomethanation of rice straw was performed at 55 °C without thermochemical pretreatment using cattle dung supplemented with Methanothermobacter thermautotrophicus strains. Methane yield of 323 ml g^-1 VS obtained under optimized conditions such as particle size (1 mm), carbon to nitrogen ratio (15:1), substrate to inoculum ratio (1:1), organic loading rate (7.5% w/v) and hydraulic retention time (20 days), was one of the highest ever reported from rice straw. Metagenome analysis revealed several putative novel taxa among resident microbes. The genomes of Clostridium, Hungateiclostridium, Alkaliphilus, Anaerocolumna, Olsenella, Paenibacillus, Pseudoclostridium, Tepidanaerobacter and Turicibacter were recovered as metagenome assisted genomes. Clostridium spp. and M. thermautotrophicus were the dominant hydrolytic and methanogenic microbes, respectively. Syntrophic acetate oxidation coupled to hydrogenotrophic methanogenesis was found to be the major pathway for methane production. Efficient thermophilic biomethanation of rice straw without thermochemical pretreatment using cattle dung supplemented with M. thermautotrophicus is reported for the first time.

Metagenome to phenome approach enables isolation and genomics characterization of Kalamiella piersonii gen. nov., sp. nov. from the International Space Station

Several evolutionarily distinct, near full-length draft metagenome-resolved genomes (MRG), were assembled from sequences recovered from the International Space Station (ISS) environments. The retrieval of MRGs facilitated the exploration of a large collection of archived strains (~ 500 isolates) and assisted in isolating seven related strains. The whole genome sequences (WGS) of seven ISS strains exhibited 100% identity to the 4.85 × 10⁶ bp of four MRGs. The "metagenome to phenome" approach led to the description of a novel bacterial genus from the ISS samples. The phylogenomics and traditional taxonomic approaches suggested that these seven ISS strains and four MRGs were not phylogenetically affiliated to any validly described genera of the family Erwiniaceae, but belong to a novel genus with the proposed name Kalamiella. Comparative genomic analyses of Kalamiella piersonii strains and MRGs showed genes associated with carbohydrate (348 genes), amino acid (384), RNA (59), and protein (214) metabolisms; membrane transport systems (108), pathways for biosynthesis of cofactors, vitamins, prosthetic groups, and pigments (179); as well as mechanisms for virulence, disease, and defense (50). Even though Kalamiella genome annotation and disc diffusion tests revealed multidrug resistance, the PathogenFinder algorithm predicted that K. piersonii strains are not human pathogens. This approach to isolating microbes allows for the characterization of functional pathways and their potential virulence properties that can directly affect human health. The isolation of novel strains from the ISS has broad applications in microbiology, not only because of concern for astronaut health but it might have a great potential for biotechnological relevance. The metagenome to phenome approach will help to improve our understanding of complex metabolic networks that control fundamental life processes under microgravity and in deep space.

New insights from uncultivated genomes of the global human gut microbiome

The genome sequences of many species of the human gut microbiome remain unknown, largely owing to challenges in cultivating microorganisms under laboratory conditions. Here we address this problem by reconstructing 60,664 draft prokaryotic genomes from 3,810 faecal metagenomes, from geographically and phenotypically diverse humans. These genomes provide reference points for 2,058 newly identified species-level operational taxonomic units (OTUs), which represents a 50% increase over the previously known phylogenetic diversity of sequenced gut bacteria. On average, the newly identified OTUs comprise 33% of richness and 28% of species abundance per individual, and are enriched in humans from rural populations. A meta-analysis of clinical gut-microbiome studies pinpointed numerous disease associations for the newly identified OTUs, which have the potential to improve predictive models. Finally, our analysis revealed that uncultured gut species have undergone genome reduction that has resulted in the loss of certain biosynthetic pathways, which may offer clues for improving cultivation strategies in the future.

Metagenomic Analyses of Microbial and Carbohydrate-Active Enzymes in the Rumen of Holstein Cows Fed Different Forage-to-Concentrate Ratios

The objectives of this study were to investigate the effects of different forage-to-concentrate ratios and sampling times on the genetic diversity of carbohydrate-active enzymes (CAZymes) and the taxonomic profile of rumen microbial communities in dairy cows. Six ruminally cannulated Holstein cows were arbitrarily divided into groups fed high-forage (HF) or low-forage (LF) diets. The results showed that, for glycoside hydrolase (GH) families, there were greater differences based on dietary forage-to-concentrate ratio than sampling time. The HF treatment group at 4 h after feeding (AF4h) had the most microbial diversity. Genes that encode GHs had the highest number of CAZymes, and accounted for 57.33% and 56.48% of all CAZymes in the HF and LF treatments, respectively. The majority of GH family genes encode oligosaccharide-degrading enzymes, and GH2, GH3, and GH43 were synthesized by a variety of different genera. Notably, we found that GH3 was higher in HF than LF diet samples, and mainly produced by Prevotella, Bacteroides, and unclassified reads. Most predicted cellulase enzymes were encoded by GH5 (the BF0h group under HF treatment was highest) and GH95 (the BF0h group under LF treatment was highest), and were primarily derived from Bacteroides, Butyrivibrio, and Fibrobacter. Approximately 67.5% (GH28) and 65.5% (GH53) of the putative hemicellulases in LF and HF treatments, respectively. GH28 under LF treatment was more abundant than under HF treatment, and was mainly produced by Ruminococcus, Prevotella, and Bacteroides. This study revealed that HF-fed cows had increased microbial diversity of CAZyme producers, which encode enzymes that efficiently degrade plant cell wall polysaccharides in the cow rumen.

De novo Assembly Vastly Expands the Known Microbial Universe

The study of the human microbiome relies heavily on the genomes of bacterial isolates that can be grown in culture. A recent study (Pasolli et al. Cell 2019;176:649-662) of stool microbiome samples generated over 150 000 microbial genomes without any culture, vastly expanding our knowledge of the biases in existing reference databases.

Applying Genome-Resolved Metagenomics to Deconvolute the Halophilic Microbiome

In the past decades, the study of microbial life through shotgun metagenomic sequencing has rapidly expanded our understanding of environmental, synthetic, and clinical microbial communities. Here, we review how shotgun metagenomics has affected the field of halophilic microbial ecology, including functional potential reconstruction, virus–host interactions, pathway selection, strain dispersal, and novel genome discoveries. However, there still remain pitfalls and limitations from conventional metagenomic analysis being applied to halophilic microbial communities. Deconvolution of halophilic metagenomes has been difficult due to the high G + C content of these microbiomes and their high intraspecific diversity, which has made both metagenomic assembly and binning a challenge. Halophiles are also underrepresented in public genome databases, which in turn slows progress. With this in mind, this review proposes experimental and analytical strategies to overcome the challenges specific to the halophilic microbiome, from experimental designs to data acquisition and the computational analysis of metagenomic sequences. Finally, we speculate about the potential applications of other next-generation sequencing technologies in halophilic communities. RNA sequencing, long-read technologies, and chromosome conformation assays, not initially intended for microbiomes, are becoming available in the study of microbial communities. Together with recent analytical advancements, these new methods and technologies have the potential to rapidly advance the field of halophile research.

Metagenomics of the Viral Community in Three Cattle Slurry Samples

The diversity of viruses in slurries from dairy farming remains largely uncharacterized. Here we report viral diversity found in cattle slurry from a dairy farm in the East Midlands in the United Kingdom.

The diversity of viruses in slurries from dairy farming remains largely uncharacterized. Here we report viral diversity found in cattle slurry from a dairy farm in the East Midlands in the United Kingdom. The same slurry tank was sampled in three consecutive years, and the viral fraction was isolated and sequenced.

A new genomic blueprint of the human gut microbiota

The composition of the human gut microbiota is linked to health and disease, but knowledge of individual microbial species is needed to decipher their biological roles. Despite extensive culturing and sequencing efforts, the complete bacterial repertoire of the human gut microbiota remains undefined. Here we identify 1,952 uncultured candidate bacterial species by reconstructing 92,143 metagenome-assembled genomes from 11,850 human gut microbiomes. These uncultured genomes substantially expand the known species repertoire of the collective human gut microbiota, with a 281% increase in phylogenetic diversity. Although the newly identified species are less prevalent in well-studied populations compared to reference isolate genomes, they improve classification of understudied African and South American samples by more than 200%. These candidate species encode hundreds of newly identified biosynthetic gene clusters and possess a distinctive functional capacity that might explain their elusive nature. Our work expands the known diversity of uncultured gut bacteria, which provides unprecedented resolution for taxonomic and functional characterization of the intestinal microbiota.

The known species repertoire of the collective human gut microbiota is substantially expanded with the discovery of 1,952 uncultured bacterial species that greatly improve classification of understudied African and South American samples.

Comparative metagenomic and metatranscriptomic analyses reveal the breed effect on the rumen microbiome and its associations with feed efficiency in beef cattle

BACKGROUND

Microorganisms are responsible for fermentation within the rumen and have been reported to contribute to the variation in feed efficiency of cattle. However, to what extent the breed affects the rumen microbiome and its association with host feed efficiency is unknown. Here, rumen microbiomes of beef cattle (n = 48) from three breeds (Angus, Charolais, Kinsella composite hybrid) with high and low feed efficiency were explored using metagenomics and metatranscriptomics, aiming to identify differences between functional potentials and activities of same rumen microbiomes and to evaluate the effects of host breed and feed efficiency on the rumen microbiome.

RESULTS

Rumen metagenomes were more closely clustered together and thus more conserved among individuals than metatranscriptomes, suggesting that inter-individual functional variations at the RNA level were higher than those at the DNA level. However, while mRNA enrichment significantly increased the sequencing depth of mRNA and generated similar functional profiles to total RNA-based metatranscriptomics, it led to biased abundance estimation of several transcripts. We observed divergent rumen microbial composition (metatranscriptomic level) and functional potentials (metagenomic level) among three breeds, but differences in functional activity (metatranscriptomic level) were less apparent. Differential rumen microbial features (e.g., taxa, diversity indices, functional categories, and genes) were detected between cattle with high and low feed efficiency, and most of them were breed-specific.

CONCLUSIONS

Metatranscriptomes represent real-time functional activities of microbiomes and have the potential to better associate rumen microorganisms with host performances compared to metagenomics. As total RNA-based metatranscriptomics seem to avoid potential biases caused by mRNA enrichment and allow simultaneous use of rRNA for generation of compositional profiles, we suggest their use for linking the rumen microbiome with host phenotypes in future studies. However, if exploration of specific lowly expressed genes is desired, mRNA enrichment is recommended as it will enhance the resolution of mRNA. Finally, the differential microbial features observed between efficient and inefficient steers tended to be specific to breeds, suggesting that interactions between host breed genotype and the rumen microbiome contribute to the variations in feed efficiency observed. These breed-associated differences represent an opportunity to engineer specific rumen microbiomes through selective breeding of the hosts.

Fecal pollution can explain antibiotic resistance gene abundances in anthropogenically impacted environments

Discharge of treated sewage leads to release of antibiotic resistant bacteria, resistance genes and antibiotic residues to the environment. However, it is unclear whether increased abundance of antibiotic resistance genes in sewage and sewage-impacted environments is due to on-site selection pressure by residual antibiotics, or is simply a result of fecal contamination with resistant bacteria. Here we analyze relative resistance gene abundance and accompanying extent of fecal pollution in publicly available metagenomic data, using crAssphage sequences as a marker of human fecal contamination (crAssphage is a bacteriophage that is exceptionally abundant in, and specific to, human feces). We find that the presence of resistance genes can largely be explained by fecal pollution, with no clear signs of selection in the environment, with the exception of environments polluted by very high levels of antibiotics from manufacturing, where selection is evident. Our results demonstrate the necessity to take into account fecal pollution levels to avoid making erroneous assumptions regarding environmental selection of antibiotic resistance.

Metatranscriptomics of the Hu sheep rumen microbiome reveals novel cellulases

BACKGROUND

Cellulosic biomass has great potential as a renewable biofuel resource. Robust, high-performance enzymes are needed to effectively utilize this valuable resource. In this study, metatranscriptomics was used to explore the carbohydrate-active enzymes (CAZymes), especially glycoside hydrolases (GHs), present in the rumen microbiome of Hu sheep. Select CAZymes were experimentally verified and characterized after cloning and expression in E. coli.

RESULTS

The metatranscriptomes of six Hu sheep rumen microbiomes yielded 42.3 Gbp of quality-checked sequence data that represented in total 2,380,783 unigenes after de novo assembling using Trinity and clustered with CD-HIT-EST. Annotation using the CAZy database revealed that 2.65% of the unigenes encoded GHs, which were assigned to 111 different CAZymes families. Firmicutes (18.7%) and Bacteroidetes (13.8%) were the major phyla to which the unigenes were taxonomically assigned. In total, 14,489 unigenes were annotated to 15 cellulase-containing GH families, with GH3, GH5 and GH9 being the predominant. From these putative cellulase-encoding unigenes, 4225 open reading frames (ORFs) were predicted to contain 2151 potential cellulase catalytic modules. Additionally, 147 ORFs were found to encode proteins that contain carbohydrate-binding modules (CBMs). Heterogeneous expression of 30 candidate cDNAs from the GH5 family in E. coli BL21 showed that 17 of the tested proteins had endoglucanase activity, while 7 exhibited exoglucanase activity. Interestingly, two of the GH5 proteins (Cel5A-h28 and Cel5A-h11) showed high specific activity against carboxymethylcellulose (CMC) and p-nitrophenyl-β-d-cellobioside (pNPC) (222.2 and 142.8 U/mg), respectively. The optimal pH value for activity of Cel5A-h11 and Cel5A-h28 was 6.0 for both enzymes, and optimal temperatures were 40 and 50 °C, respectively. Both enzymes retained over 70 and 60%, respectively, of their original activities after incubation at 40 °C for 60 min. However, their activities were rapidly diminished upon exposure to higher temperatures. Cel5A-h11 and Cel5A-h28 retained more than 80 and 60% of their maximal enzymatic activities after incubation for 16 h in buffered solutions in the pH range from 4.0 to 9.0.

CONCLUSION

The metatranscriptomic results revealed that the rumen microbiome of Hu sheep encoded a repertoire of new enzymes capable of cellulose degradation and metatranscriptomics was an effective method to discover novel cellulases for biotechnological applications.

Functional metagenomics reveals abundant polysaccharide-degrading gene clusters and cellobiose utilization pathways within gut microbiota of a wood-feeding higher termite

Plant cell-wall polysaccharides constitute the most abundant but recalcitrant organic carbon source in nature. Microbes residing in the digestive tract of herbivorous bilaterians are particularly efficient at depolymerizing polysaccharides into fermentable sugars and play a significant support role towards their host's lifestyle. Here, we combine large-scale functional screening of fosmid libraries, shotgun sequencing, and biochemical assays to interrogate the gut microbiota of the wood-feeding "higher" termite Globitermes brachycerastes. A number of putative polysaccharide utilization gene clusters were identified with multiple fibrolytic genes. Our large-scale functional screening of 50,000 fosmid clones resulted in 464 clones demonstrating plant polysaccharide-degrading activities, including 267 endoglucanase-, 24 exoglucanase-, 72 β-glucosidase-, and 101 endoxylanase-positive clones. We sequenced 173 functionally active clones and identified ~219 genes encoding putative carbohydrate-active enzymes (CAZymes) targeting cellulose, hemicellulose and pectin. Further analyses revealed that 68 of 154 contigs encode one or more CAZyme, which includes 35 examples of putative saccharolytic operons, suggesting that clustering of CAZymes is common in termite gut microbial inhabitants. Biochemical characterization of a representative xylanase cluster demonstrated that constituent enzymes exhibited complementary physicochemical properties and saccharolytic capabilities. Furthermore, diverse cellobiose-metabolizing enzymes include β-glucosidases, cellobiose phosphorylases, and phopho-6-β-glucosidases were identified and functionally verified, indicating that the termite gut micro-ecosystem utilizes diverse metabolic pathways to interconnect hydrolysis and central metabolism. Collectively, these results provide an in-depth view of the adaptation and digestive strategies employed by gut microbiota within this tiny-yet-efficient host-associated ecosystem.

The human archaeome: methodological pitfalls and knowledge gaps

Forty years ago, archaea were described as a separate domain of life, distinct from bacteria and eukarya. Although it is known for quite a long time that methanogenic archaea are substantial components of the human gastrointestinal tract (GIT) and the oral cavity, the knowledge on the human archaeome is very limited. Various methodological problems contribute to the invisibility of the human archaeome, resulting in severe knowledge gaps and contradictory information. Similar to the bacteriome, the archaeal biogeography was found to be site-specific, forming (i) the thaumarchaeal skin landscape, (ii) the (methano)euryarchaeal GIT landscape, (iii) a mixed skin/GIT landscape in nose, and (iv) a woesearchaeal lung landscape, including numerous unknown archaeal clades. Compared with so-called universal microbiome approaches, archaea-specific protocols reveal a wide diversity and high quantity of archaeal signatures in various human tissues, with up to 1 : 1 ratios of bacteria and archaea in appendix and nose samples. The archaeome interacts closely with the bacteriome and the human body cells, whereas the roles of the human-associated archaea with respect to human health are only sparsely described. Methanogenic archaea and methane production were correlated with many health issues, including constipation, periodontitis and multiple sclerosis. However, one of the most burning questions - do archaeal pathogens exist? - still remains obscure to date.

Comparison of Mothur and QIIME for the Analysis of Rumen Microbiota Composition Based on 16S rRNA Amplicon Sequences

Background: Microbiome studies need to analyze massive sequencing data, which requires the use of sophisticated bioinformatics pipelines. Up to date, several tools are available, although the literature is scarce on studies that compare the performance of different bioinformatics pipelines on rumen microbiota when 16S rRNA amplicons are analyzed. The impact of the pipeline on the outcome of the results is also unknown, mainly in terms of the output from studies using these tools as an intermediate phenotype (pseudophenotypes). This study compares two commonly used software (Quantitative Insights Into Microbial Ecology) (QIIME) and mothur, and two microbial gene data bases (GreenGenes and SILVA) for 16S rRNA gene analysis, using metagenome read data collected from rumen content of a cohort of dairy cows.

Results: We compared the relative abundance (RA) of the identified OTUs at the genus level. Both tools presented a high degree of agreement at identifying the most abundant genera: Bifidobacterium, Butyrivibrio, Methanobrevibacter, Prevotella, and Succiniclasticum (RA > 1%), regardless the database. There were no statistical differences between mothur and QIIME (P > 0.05) at estimating the overall RA of the most abundant (RA > 10%) genera, either using SILVA or GreenGenes. However, differences were found at RA < 10% (P < 0.05) when using GreenGenes as database, with mothur assigning OTUs to a larger number of genera and in larger RA for these less frequent microorganisms. With this database mothur resulted in larger richness (P < 0.05), more favorable rarefaction curves and a larger analytic sensitivity. These differences caused significant and relevant differences between tools at identifying the dissimilarity of microbiotas between pairs of animals. However, these differences were attenuated, but not erased, when SILVA was used as the reference database.

Conclusion: The findings showed that the SILVA database seemed a preferred reference dataset for classifying OTUs from rumen microbiota. If this database was used, both QIIME and mothur produced comparable richness and diversity, and also in the RA of most common rumen microbes. However, important differences were found for less common microorganisms which impacted on the beta diversity calculated between pipelines. This may have relevant implications at studying global rumen microbiota.

Assembling a genome for novel nitrogen-fixing bacteria with capabilities for utilization of aromatic hydrocarbons

Metagenome from refinery wastewater treatment plant running under nitrogen stress was analyzed for mining of novel aromatic hydrocarbon-degrading bacteria. The sequence data were assembled using metaspade followed by binning using the Metabat tool to assemble genome; where coverage and depth were calculated using bowtie and samtools. The analysis picked a novel genome belonging to family Bradyrhizobiaceae, identified based on 16S rDNA gene which was supported by CheckM and Kraken analysis. Using RAST, the assembled genome showed the capabilities for nitrogen fixation with the utilization of multiple hydrocarbon substrates with 14 different types of oxygenases as mapped by Minpath. An additional genetic feature like genes for stress and resistance towards heavy metals and antibiotic suggested that the genome has gone through the rigorous process of adaptation. If such bacteria could be cultivated then it will open the broad window of bioremediation strategies under nitrogen stress environment.

Understanding the microbial basis of body odor in pre-pubescent children and teenagers

BACKGROUND

Even though human sweat is odorless, bacterial growth and decomposition of specific odor precursors in it is believed to give rise to body odor in humans. While mechanisms of odor generation have been widely studied in adults, little is known for teenagers and pre-pubescent children who have distinct sweat composition from immature apocrine and sebaceous glands, but are arguably more susceptible to the social and psychological impact of malodor.

RESULTS

We integrated information from whole microbiome analysis of multiple skin sites (underarm, neck, and head) and multiple time points (1 h and 8 h after bath), analyzing 180 samples in total to perform the largest metagenome-wide association study to date on malodor. Significant positive correlations were observed between odor intensity and the relative abundance of Staphylococcus hominis, Staphylococcus epidermidis, and Cutibacterium avidum, as well as negative correlation with Acinetobacter schindleri and Cutibacterium species. Metabolic pathway analysis highlighted the association of isovaleric and acetic acid production (sour odor) from enriched S. epidermidis (teen underarm) and S. hominis (child neck) enzymes and sulfur production from Staphylococcus species (teen underarm) with odor intensity, in good agreement with observed odor characteristics in pre-pubescent children and teenagers. Experiments with cultures on human and artificial sweat confirmed the ability of S. hominis and S. epidermidis to independently produce malodor with distinct odor characteristics.

CONCLUSIONS

These results showcase the power of skin metagenomics to study host-microbial co-metabolic interactions, identifying distinct pathways for odor generation from sweat in pre-pubescent children and teenagers and highlighting key enzymatic targets for intervention.

Characterisation of the British honey bee metagenome

The European honey bee (Apis mellifera) plays a major role in pollination and food production. Honey bee health is a complex product of the environment, host genetics and associated microbes (commensal, opportunistic and pathogenic). Improved understanding of these factors will help manage modern challenges to bee health. Here we used DNA sequencing to characterise the genomes and metagenomes of 19 honey bee colonies from across Britain. Low heterozygosity was observed in many Scottish colonies which had high similarity to the native dark bee. Colonies exhibited high diversity in composition and relative abundance of individual microbiome taxa. Most non-bee sequences were derived from known honey bee commensal bacteria or pathogens. However, DNA was also detected from additional fungal, protozoan and metazoan species. To classify cobionts lacking genomic information, we developed a novel network analysis approach for clustering orphan DNA contigs. Our analyses shed light on microbial communities associated with honey bees and demonstrate the power of high-throughput, directed metagenomics for identifying novel biological threats in agroecosystems.

Recovering microbial genomes from metagenomes in hypersaline environments: The Good, the Bad and the Ugly

Current metagenomic tools allow the recovery of microbial genomes directly from the environment. This can be accomplished by binning metagenomic contigs according to their coverage and tetranucleotide frequency, followed by an estimation of the bin quality. The public availability of bioinformatics tools, together with the decreasing cost of next generation sequencing, are democratizing this powerful approach that is spreading from specialized research groups to the general public. Using metagenomes from hypersaline environments, as well as mock metagenomes composed of Archaea and Bacteria frequently found in these systems, we have analyzed the advantages and difficulties of the binning process in these extreme environments to tackle microbial population diversity. These extreme systems harbor relatively low species diversity but high intraspecific diversity, which can compromise metagenome assembly and therefore the whole binning process. The main goal is to compare the output of the binning process with what is previously known from the analyzed samples, based on years of study using different approaches. Several scenarios have been analyzed in detail: (i) a good quality bin from a species highly abundant in the environment; (ii) an intermediate quality bin with incongruences that can be solved by further analyses and manual curation, and (iii) a low-quality bin to investigate the failure to recover a very abundant microbial genome as well as some possible solutions. The latter can be considered the "great metagenomics anomaly" and is mainly due to assembly problems derived from the microdiversity of naturally co-existing populations in nature.

Interspecies cross-feeding orchestrates carbon degradation in the rumen ecosystem

Because of their agricultural value, there is a great body of research dedicated to understanding the microorganisms responsible for rumen carbon degradation. However, we lack a holistic view of the microbial food web responsible for carbon processing in this ecosystem. Here, we sampled rumen-fistulated moose, allowing access to rumen microbial communities actively degrading woody plant biomass in real time. We resolved 1,193 viral contigs and 77 unique, near-complete microbial metagenome-assembled genomes, many of which lacked previous metabolic insights. Plant-derived metabolites were measured with NMR and carbohydrate microarrays to quantify the carbon nutrient landscape. Network analyses directly linked measured metabolites to expressed proteins from these unique metagenome-assembled genomes, revealing a genome-resolved three-tiered carbohydrate-fuelled trophic system. This provided a glimpse into microbial specialization into functional guilds defined by specific metabolites. To validate our proteomic inferences, the catalytic activity of a polysaccharide utilization locus from a highly connected metabolic hub genome was confirmed using heterologous gene expression. Viral detected proteins and linkages to microbial hosts demonstrated that phage are active controllers of rumen ecosystem function. Our findings elucidate the microbial and viral members, as well as their metabolic interdependencies, that support in situ carbon degradation in the rumen ecosystem.

A combination of proteomics, metagenome-assembled genomes and heterologous gene expression experiments reveals a trophic system for carbon utilization in the moose rumen microbiome and provides insights into phage dynamics in this ecosystem.

The diverse and extensive plant polysaccharide degradative apparatuses of the rumen and hindgut Prevotella species: A factor in their ubiquity?

Although the Prevotella are commonly observed in high shares in the mammalian hindgut and rumen studies using NGS approach, the knowledge on their actual role, though postulated to lie in soluble fibre degradation, is scarce. Here we analyse in total 23, more than threefold of hitherto known rumen and hindgut Prevotella species and show that rumen/hindgut Prevotella generally possess extensive repertoires of polysaccharide utilization loci (PULs) and carbohydrate active enzymes targeting various plant polysaccharides. These PUL repertoires separate analysed Prevotella into generalists and specialists yet a finer diversity among generalists is evident too, both in range of substrates targeted and in PUL combinations targeting the same broad substrate classes. Upon evaluation of the shares of species analysed in this study in rumen metagenomes we found firstly, that they contributed significantly to total Prevotella abundance though much of rumen Prevotella diversity may still be unknown. Secondly, the hindgut Prevotella species originally isolated in pigs and humans occasionally dominated among the Prevotella with surprisingly high metagenome read shares and were consistently found in rumen metagenome samples from sites as apart as New Zealand and Scotland. This may indicate frequent passage between different hosts and relatively low barriers to their successful establishment in rumen versus the hindgut.

Genomes from uncultivated prokaryotes: a comparison of metagenome-assembled and single-amplified genomes

BACKGROUND

Prokaryotes dominate the biosphere and regulate biogeochemical processes essential to all life. Yet, our knowledge about their biology is for the most part limited to the minority that has been successfully cultured. Molecular techniques now allow for obtaining genome sequences of uncultivated prokaryotic taxa, facilitating in-depth analyses that may ultimately improve our understanding of these key organisms.

RESULTS

We compared results from two culture-independent strategies for recovering bacterial genomes: single-amplified genomes and metagenome-assembled genomes. Single-amplified genomes were obtained from samples collected at an offshore station in the Baltic Sea Proper and compared to previously obtained metagenome-assembled genomes from a time series at the same station. Among 16 single-amplified genomes analyzed, seven were found to match metagenome-assembled genomes, affiliated with a diverse set of taxa. Notably, genome pairs between the two approaches were nearly identical (average 99.51% sequence identity; range 98.77-99.84%) across overlapping regions (30-80% of each genome). Within matching pairs, the single-amplified genomes were consistently smaller and less complete, whereas the genetic functional profiles were maintained. For the metagenome-assembled genomes, only on average 3.6% of the bases were estimated to be missing from the genomes due to wrongly binned contigs.

CONCLUSIONS

The strong agreement between the single-amplified and metagenome-assembled genomes emphasizes that both methods generate accurate genome information from uncultivated bacteria. Importantly, this implies that the research questions and the available resources are allowed to determine the selection of genomics approach for microbiome studies.

Review: The application of omics to rumen microbiota function

Rumen microbiome profiling uses 16S rRNA (18S rRNA, internal transcribed spacer) gene sequencing, a method that usually sequences a small portion of a single gene and is often biased and varies between different laboratories. Functional information can be inferred from this data, but only for those that are closely related to known annotated species, and even then may not truly reflect the function performed within the environment being studied. Genome sequencing of isolates and metagenome-assembled genomes has now reached a stage where representation of the majority of rumen bacterial genera are covered, but this still only represents a portion of rumen microbial species. The creation of a microbial genome (bins) database with associated functional annotations will provide a consistent reference to allow mapping of RNA-Seq reads for functional gene analysis from within the rumen microbiome. The integration of multiple omic analytics is linking functional gene activity, metabolic pathways and rumen metabolites with the responsible microbiota, supporting our biological understanding of the rumen system. The application of these techniques has advanced our understanding of the major microbial populations and functional pathways that are used in relation to lower methane emissions, higher feed efficiencies and responses to different feeding regimes. Continued and more precise use of these tools will lead to a detailed and comprehensive understanding of compositional and functional capacity and design of techniques for the directed intervention and manipulation of the rumen microbiota towards a desired state.

Characterization of novel glycosyl hydrolases discovered by cell wall glycan directed monoclonal antibody screening and metagenome analysis of maize aerial root mucilage

An indigenous maize landrace from the Sierra Mixe region of Oaxaca, Mexico exhibits extensive formation of aerial roots which exude large volumes of a polysaccharide-rich gel matrix or "mucilage" that harbors diazotrophic microbiota. We hypothesize that the mucilage associated microbial community carries out multiple functions, including disassembly of the mucilage polysaccharide. In situ, hydrolytic assay of the mucilage revealed endogenous arabinofuranosidase, galactosidase, fucosidase, mannosidase and xylanase activities. Screening the mucilage against plant cell wall glycan-specific monoclonal antibodies recognized the presence of carbohydrate epitopes of hemicellulosic polysaccharides like xyloglucan (both non-fucosylated and fucosylated), xylan (both substituted and unsubstituted xylan domains) and pectic-arabinogalactans, all of which are potential carbon sources for mucilage microbial residents. Mucilage metagenome annotation using MG-RAST identified the members forming the microbial community, and gene fragments with predicted functions associated with carbohydrate disassembly. Data from the in situ hydrolytic activity and monoclonal antibody screening assays were used to guide the selection of five full length genes with predicted glycosyl hydrolase function from the GenBank database that were similar to gene fragments of high relative abundance in the mucilage metagenomes. These five genes were then synthesized for recombinant production in Escherichia coli. Here we report the characterization of an α-N-arabinofuranosidase (GH51) and an oligosaccharide reducing-end xylanase (GH8) from Flavobacterium johnsoniae; an α-L-fucosidase (GH29) and a xylan β-1,4 xylosidase (GH39) from Spirosoma linguale, and a β-mannosidase (GH2) from Agrobacterium fabrum. Biochemical characterization of these enzymes revealed a β-Mannosidase that also exhibits a secondary activity towards the cleavage of galactosyl residues. We also describe two xylanases (GH8 and GH39) from underexplored glycosyl hydrolase families, one thermostable α-L-Fucosidase (GH29) and a thermostable α-N-Arabinofuranosidase (GH51).

Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future

The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges.

The Planktonic Core Microbiome and Core Functions in the Cattle Rumen by Next Generation Sequencing

The cow rumen harbors a great variety of diverse microbes, which form a complex, organized community. Understanding the behavior of this multifarious network is crucial in improving ruminant nutrient use efficiency. The aim of this study was to expand our knowledge by examining 10 Holstein dairy cow rumen fluid fraction whole metagenome and transcriptome datasets. DNA and mRNA sequence data, generated by Ion Torrent, was subjected to quality control and filtering before analysis for core elements. The taxonomic core microbiome consisted of 48 genera belonging to Bacteria (47) and Archaea (1). The genus Prevotella predominated the planktonic core community. Core functional groups were identified using co-occurrence analysis and resulted in 587 genes, from which 62 could be assigned to metabolic functions. Although this was a minimal functional core, it revealed key enzymes participating in various metabolic processes. A diverse and rich collection of enzymes involved in carbohydrate metabolism and other functions were identified. Transcripts coding for enzymes active in methanogenesis made up 1% of the core functions. The genera associated with the core enzyme functions were also identified. Linking genera to functions showed that the main metabolic pathways are primarily provided by Bacteria and several genera may serve as a “back-up” team for the central functions. The key actors in most essential metabolic routes belong to the genus Prevotella. Confirming earlier studies, the genus Methanobrevibacter carries out the overwhelming majority of rumen methanogenesis and therefore methane emission mitigation seems conceivable via targeting the hydrogenotrophic methanogenesis.

The rumen microbiome: a crucial consideration when optimising milk and meat production and nitrogen utilisation efficiency

Methane is generated in the foregut of all ruminant animals by the microorganisms present. Dietary manipulation is regarded as the most effective and most convenient way to reduce methane emissions (and in turn energy loss in the animal) and increase nitrogen utilization efficiency. This review examines the impact of diet on bovine rumen function and outlines what is known about the rumen microbiome. Our understanding of this area has increased significantly in recent years due to the application of omics technologies to determine microbial composition and functionality patterns in the rumen. This information can be combined with data on nutrition, rumen physiology, nitrogen excretion and/or methane emission to provide comprehensive insights into the relationship between rumen microbial activity, nitrogen utilisation efficiency and methane emission, with an ultimate view to the development of new and improved intervention strategies.

Analysis of sequencing strategies and tools for taxonomic annotation: Defining standards for progressive metagenomics

Metagenomics research has recently thrived due to DNA sequencing technologies improvement, driving the emergence of new analysis tools and the growth of taxonomic databases. However, there is no all-purpose strategy that can guarantee the best result for a given project and there are several combinations of software, parameters and databases that can be tested. Therefore, we performed an impartial comparison, using statistical measures of classification for eight bioinformatic tools and four taxonomic databases, defining a benchmark framework to evaluate each tool in a standardized context. Using in silico simulated data for 16S rRNA amplicons and whole metagenome shotgun data, we compared the results from different software and database combinations to detect biases related to algorithms or database annotation. Using our benchmark framework, researchers can define cut-off values to evaluate the expected error rate and coverage for their results, regardless the score used by each software. A quick guide to select the best tool, all datasets and scripts to reproduce our results and benchmark any new method are available at https://github.com/Ales-ibt/Metagenomic-benchmark. Finally, we stress out the importance of gold standards, database curation and manual inspection of taxonomic profiling results, for a better and more accurate microbial diversity description.

Evaluating Established Methods for Rumen 16S rRNA Amplicon Sequencing With Mock Microbial Populations

The rumen microbiome scientific community has utilized amplicon sequencing as an aid in identifying potential community compositional trends that could be used as an estimation of various production and performance traits including methane emission, animal protein production efficiency, and ruminant health status. In order to translate rumen microbiome studies into executable application, there is a need for experimental and analytical concordance within the community. The objective of this study was to assess these factors in relation to selected currently established methods for 16S phylogenetic community analysis on a microbial community standard (MC) and a DNA standard (DS; ZymoBIOMICS^TM). DNA was extracted from MC using the RBBC method commonly used for microbial DNA extraction from rumen digesta samples. 16S rRNA amplicon libraries were generated for the MC and DS using primers routinely used for rumen bacterial and archaeal community analysis. The primers targeted the V4 and V3–V4 region of the 16S rRNA gene and samples were subjected to both 20 and 28 polymerase chain reaction (PCR) cycles under identical cycle conditions. Sequencing was conducted using the Illumina MiSeq platform. As the bacteria contained in the microbial mock community were well-classified species, and for ease of explanation, we used the results of the Basic Local Alignment Search Tool classification to assess the DNA, PCR cycle number, and primer type. Sequence classification methodology was assessed independently. Spearman’s correlation analysis indicated that utilizing the repeated bead beating and column method for DNA extraction in combination with primers targeting the 16S rRNA gene using 20 first-round PCR cycles was sufficient for amplicon sequencing to generate a relatively accurate depiction of the bacterial communities present in rumen samples. These results also emphasize the requirement to develop and utilize positive mock community controls for all rumen microbiomic studies in order to discern errors which may arise at any step during a next-generation sequencing protocol.

The Present and Future of Whole Genome Sequencing (WGS) and Whole Metagenome Sequencing (WMS) for Surveillance of Antimicrobial Resistant Microorganisms and Antimicrobial Resistance Genes across the Food Chain

Antimicrobial resistance (AMR) surveillance is a critical step within risk assessment schemes, as it is the basis for informing global strategies, monitoring the effectiveness of public health interventions, and detecting new trends and emerging threats linked to food. Surveillance of AMR is currently based on the isolation of indicator microorganisms and the phenotypic characterization of clinical, environmental and food strains isolated. However, this approach provides very limited information on the mechanisms driving AMR or on the presence or spread of AMR genes throughout the food chain. Whole-genome sequencing (WGS) of bacterial pathogens has shown potential for epidemiological surveillance, outbreak detection, and infection control. In addition, whole metagenome sequencing (WMS) allows for the culture-independent analysis of complex microbial communities, providing useful information on AMR genes occurrence. Both technologies can assist the tracking of AMR genes and mobile genetic elements, providing the necessary information for the implementation of quantitative risk assessments and allowing for the identification of hotspots and routes of transmission of AMR across the food chain. This review article summarizes the information currently available on the use of WGS and WMS for surveillance of AMR in foodborne pathogenic bacteria and food-related samples and discusses future needs that will have to be considered for the routine implementation of these next-generation sequencing methodologies with this aim. In particular, methodological constraints that impede the use at a global scale of these high-throughput sequencing (HTS) technologies are identified, and the standardization of methods and protocols is suggested as a measure to upgrade HTS-based AMR surveillance schemes.

A metagenomic analysis of the camel rumen's microbiome identifies the major microbes responsible for lignocellulose degradation and fermentation

BACKGROUND

The diverse microbiome present in the rumen of ruminant animals facilitates the digestion of plant-based fiber. In this study, a shotgun metagenomic analysis of the microbes adhering to plant fiber in the camel rumen was undertaken to identify the key species contributing to lignocellulose degradation and short chain volatile fatty acids (VFA) fermentation.

RESULTS

The density of genes in the metagenome encoding glycoside hydrolases was estimated to be 25 per Mbp of assembled DNA, which is significantly greater than what has been reported in other sourced metagenomes, including cow rumen. There was also a substantial representation of sequences encoding scaffoldins, dockerins and cohesins, indicating the potential for cellulosome-mediated lignocellulose degradation. Binning of the assembled metagenome has enabled the definition of 65 high-quality genome bins which showed high diversity for lignocellulose degrading enzymes. Species associated to Bacteroidetes showed a high proportion of genes for debranching and oligosaccharide degrading enzymes, while those belonging to Firmicutes and Fibrobacteres were rich in cellulases and hemicellulases and thus these lineages were probably the key for ensuring the degradation of lignocellulose. The presence of many "polysaccharide utilization loci" (PULs) in Bacteroidetes genomes indicates their broad substrate specificity and high potential carbohydrate degradation ability. An analysis of VFA biosynthesis pathways showed that genes required for the synthesis of acetate were present in a range of species, except for Elusimicrobiota and Euryarchaeota. The production of propionate, exclusively via the succinate pathway, was carried out by species belonging to the phyla Bacteroidetes, Firmicutes, Spirochaetes and Fibrobacteres. Butyrate was generated via the butyrylCoA: acetate CoA-transferase pathway by Bacteroidetes and Lentisphaerae species, but generally via the butyrate kinase pathway by Firmicutes species.

CONCLUSION

The analysis confirmed the camel rumen's microbiome as a dense and yet largely untapped source of enzymes with the potential to be used in a range of biotechnological processes including biofuel, fine chemicals and food processing industries.