Cross-cohort single-nucleotide-variant profiling of gut microbiota suggests a novel gut-health assessment approach.

IMPORTANCE: Most studies focused much on the change in abundance and often failed to explain the microbiome variation related to disease conditions, Herein, we argue that microbial genetic changes can precede the ecological changes associated with the host physiological changes and, thus, would offer a new information layer from metagenomic data for predictive modeling of diseases. Interestingly, we preliminarily found a few genetic biomarkers on SCFA production can cover most chronic diseases involved in the meta-analysis. In the future, it is of both scientific and clinical significance to further explore the dynamic interactions between adaptive evolution and ecology of gut microbiota associated with host health status.

VIRify: An integrated detection, annotation and taxonomic classification pipeline using virus-specific protein profile hidden Markov models.

The study of viral communities has revealed the enormous diversity and impact these biological entities have on various ecosystems. These observations have sparked widespread interest in developing computational strategies that support the comprehensive characterisation of viral communities based on sequencing data. Here we introduce VIRify, a new computational pipeline designed to provide a user-friendly and accurate functional and taxonomic characterisation of viral communities. VIRify identifies viral contigs and prophages from metagenomic assemblies and annotates them using a collection of viral profile hidden Markov models (HMMs). These include our manually-curated profile HMMs, which serve as specific taxonomic markers for a wide range of prokaryotic and eukaryotic viral taxa and are thus used to reliably classify viral contigs. We tested VIRify on assemblies from two microbial mock communities, a large metagenomics study, and a collection of publicly available viral genomic sequences from the human gut. The results showed that VIRify could identify sequences from both prokaryotic and eukaryotic viruses, and provided taxonomic classifications from the genus to the family rank with an average accuracy of 86.6%. In addition, VIRify allowed the detection and taxonomic classification of a range of prokaryotic and eukaryotic viruses present in 243 marine metagenomic assemblies. Finally, the use of VIRify led to a large expansion in the number of taxonomically classified human gut viral sequences and the improvement of outdated and shallow taxonomic classifications. Overall, we demonstrate that VIRify is a novel and powerful resource that offers an enhanced capability to detect a broad range of viral contigs and taxonomically classify them.

Evaluation of a high-throughput, cost-effective Illumina library preparation kit.

Library preparation for high-throughput sequencing applications is a critical step in producing representative, unbiased sequencing data. The iGenomX Riptide High Throughput Rapid Library Prep Kit purports to provide high-quality sequencing data with lower costs compared to other Illumina library kits. To test these claims, we compared sequence data quality of Riptide libraries to libraries constructed with KAPA Hyper and NEBNext Ultra. Across several single-source genome samples, mapping performance and de novo assembly of Riptide libraries were similar to conventional libraries prepared with the same DNA. Poor performance of some libraries resulted in low sequencing depth. In particular, degraded DNA samples may be challenging to sequence with Riptide. There was little cross-well plate contamination with the overwhelming majority of reads belong to the proper source genomes. The sequencing of metagenome samples using different Riptide primer sets resulted in variable taxonomic assignment of reads. Increased adoption of the Riptide kit will decrease library preparation costs. However, this method might not be suitable for degraded DNA.

Microbial and Genetic Resources for Cobalamin (Vitamin B12) Biosynthesis: From Ecosystems to Industrial Biotechnology.

Many microbial producers of coenzyme B12 family cofactors together with their metabolically interdependent pathways are comprehensively studied and successfully used both in natural ecosystems dominated by auxotrophs, including bacteria and mammals, and in the safe industrial production of vitamin B12. Metabolic reconstruction for genomic and metagenomic data and functional genomics continue to mine the microbial and genetic resources for biosynthesis of the vital vitamin B12. Availability of metabolic engineering techniques and usage of affordable and renewable sources allowed improving bioprocess of vitamins, providing a positive impact on both economics and environment. The commercial production of vitamin B12 is mainly achieved through the use of the two major industrial strains, Propionobacterium shermanii and Pseudomonas denitrificans, that involves about 30 enzymatic steps in the biosynthesis of cobalamin and completely replaces chemical synthesis. However, there are still unresolved issues in cobalamin biosynthesis that need to be elucidated for future bioprocess improvements. In the present work, we review the current state of development and challenges for cobalamin (vitamin B12) biosynthesis, describing the major and novel prospective strains, and the studies of environmental factors and genetic tools effecting on the fermentation process are reported.

Higher-order Markov models for metagenomic sequence classification.

MOTIVATION: Alignment-free, stochastic models derived from k-mer distributions representing reference genome sequences have a rich history in the classification of DNA sequences. In particular, the variants of Markov models have previously been used extensively. Higher-order Markov models have been used with caution, perhaps sparingly, primarily because of the lack of enough training data and computational power. Advances in sequencing technology and computation have enabled exploitation of the predictive power of higher-order models. We, therefore, revisited higher-order Markov models and assessed their performance in classifying metagenomic sequences. RESULTS: Comparative assessment of higher-order models (HOMs, 9th order or higher) with interpolated Markov model, interpolated context model and lower-order models (8th order or lower) was performed on metagenomic datasets constructed using sequenced prokaryotic genomes. Our results show that HOMs outperform other models in classifying metagenomic fragments as short as 100 nt at all taxonomic ranks, and at lower ranks when the fragment size was increased to 250 nt. HOMs were also found to be significantly more accurate than local alignment which is widely relied upon for taxonomic classification of metagenomic sequences. A novel software implementation written in C++ performs classification faster than the existing Markovian metagenomic classifiers and can therefore be used as a standalone classifier or in conjunction with existing taxonomic classifiers for more robust classification of metagenomic sequences. AVAILABILITY AND IMPLEMENTATION: The software has been made available at https://github.com/djburks/SMM. CONTACT: Rajeev.Azad@unt.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Comparative assessment of faecal microbial composition and metabonome of swine, farmers and human control.

The gastrointestinal tract of humans and swine consist of a wide range of bacteria which interact with hosts metabolism. Due to the differences in co-evolution and co-adaptation, a large fraction of the gut microbiome is host-specific. In this study, we evaluated the effect of close human-animal interaction to the faecal metagenome and metabonome of swine, farmer and human control. Three distinct clusters were observed based on T-RFLP-derived faecal microbial composition. However, 16S-inferred faecal microbiota and metabolic profiles showed that only human control was significantly different from the swine (P < 0.05). The metabonome of farmers and human controls were highly similar. Notably, higher trimethylamine N-oxide (TMAO) and butyrate were detected in human control and swine, respectively. The relative abundance of TMAO was positively correlated with Prevotella copri. Overall, we compared and established the relationship between the metabolites and microbiota composition of swine, farmers and human control. Based on the data obtained, we deduced that long term occupational exposure to swine and farm environment had affected the gut bacterial composition of farmers. Nonetheless, the effect was less prominent in the metabolite profiles, suggesting the gut bacteria expressed high functional plasticity and are therefore resilience to the level of community shift detected.

A metagenomic assessment of microbial eukaryotic diversity in the global ocean.

Surveying microbial diversity and function is accomplished by combining complementary molecular tools. Among them, metagenomics is a PCR free approach that contains all genetic information from microbial assemblages and is today performed at a relatively large scale and reasonable cost, mostly based on very short reads. Here, we investigated the potential of metagenomics to provide taxonomic reports of marine microbial eukaryotes. We prepared a curated database with reference sequences of the V4 region of 18S rDNA clustered at 97% similarity and used this database to extract and classify metagenomic reads. More than half of them were unambiguously affiliated to a unique reference whilst the rest could be assigned to a given taxonomic group. The overall diversity reported by metagenomics was similar to that obtained by amplicon sequencing of the V4 and V9 regions of the 18S rRNA gene, although either one or both of these amplicon surveys performed poorly for groups like Excavata, Amoebozoa, Fungi and Haptophyta. We then studied the diversity of picoeukaryotes and nanoeukaryotes using 91 metagenomes from surface down to bathypelagic layers in different oceans, unveiling a clear taxonomic separation between size fractions and depth layers. Finally, we retrieved long rDNA sequences from assembled metagenomes that improved phylogenetic reconstructions of particular groups. Overall, this study shows metagenomics as an excellent resource for taxonomic exploration of marine microbial eukaryotes.

An assessment of Oxford Nanopore sequencing for human gut metagenome profiling: A pilot study of head and neck cancer patients.

Gut metagenome profiling using the Oxford Nanopore Technologies (ONT) sequencer was assessed in a pilot-sized study of 10 subjects. The taxonomic abundance of gut microbiota derived from ONT was comparable with Illumina Technology (IT) for the high-abundance species. IT better detected low-abundance species through amplification, when material was limited.

Development of a colorectal cancer diagnostic model and dietary risk assessment through gut microbiome analysis.

Colorectal cancer (CRC) is the third most common form of cancer and poses a critical public health threat due to the global spread of westernized diets high in meat, cholesterol, and fat. Although the link between diet and colorectal cancer has been well established, the mediating role of the gut microbiota remains elusive. In this study, we sought to elucidate the connection between the gut microbiota, diet, and CRC through metagenomic analysis of bacteria isolated from the stool of CRC (n = 89) and healthy (n = 161) subjects. This analysis yielded a dozen genera that were significantly altered in CRC patients, including increased Bacteroides, Fusobacterium, Dorea, and Porphyromonas prevalence and diminished Pseudomonas, Prevotella, Acinetobacter, and Catenibacterium carriage. Based on these altered genera, we developed two novel CRC diagnostic models through stepwise selection and a simplified model using two increased and two decreased genera. As both models yielded strong AUC values above 0.8, the simplified model was applied to assess diet-based CRC risk in mice. Mice fed a westernized high-fat diet (HFD) showed greater CRC risk than mice fed a regular chow diet. Furthermore, we found that nonglutinous rice, glutinous rice, and sorghum consumption reduced CRC risk in HFD-fed mice. Collectively, these findings support the critical mediating role of the gut microbiota in diet-induced CRC risk as well as the potential of dietary grain intake to reduce microbiota-associated CRC risk. Further study is required to validate the diagnostic prediction models developed in this study as well as the preventive potential of grain consumption to reduce CRC risk.

A simple, reproducible and cost-effective procedure to analyse gut phageome: from phage isolation to bioinformatic approach.

The microbiota of the human gut is a complex and rich community where bacteria and their viruses, the bacteriophages, are dominant. There are few studies on the phage community and no clear standard for isolating them, sequencing and analysing their genomes. Since this makes comparisons between studies difficult, we aimed at defining an easy, low-cost, and reproducible methodology. We analysed five different techniques to isolate phages from human adult faeces and developed an approach to analyse their genomes in order to quantify contamination and classify phage contigs in terms of taxonomy and lifestyle. We chose the polyethylene glycol concentration method to isolate phages because of its simplicity, low cost, reproducibility, and of the high number and diversity of phage sequences that we obtained. We also tested the reproducibility of this method with multiple displacement amplification (MDA) and showed that MDA severely decreases the phage genetic diversity of the samples and the reproducibility of the method. Lastly, we studied the influence of sequencing depth on the analysis of phage diversity and observed the beginning of a plateau for phage contigs at 20,000,000 reads. This work contributes to the development of methods for the isolation of phages in faeces and for their comparative analysis.

GraftM: a tool for scalable, phylogenetically informed classification of genes within metagenomes.

Large-scale metagenomic datasets enable the recovery of hundreds of population genomes from environmental samples. However, these genomes do not typically represent the full diversity of complex microbial communities. Gene-centric approaches can be used to gain a comprehensive view of diversity by examining each read independently, but traditional pairwise comparison approaches typically over-classify taxonomy and scale poorly with increasing metagenome and database sizes. Here we introduce GraftM, a tool that uses gene specific packages to rapidly identify gene families in metagenomic data using hidden Markov models (HMMs) or DIAMOND databases, and classifies these sequences using placement into pre-constructed gene trees. The speed and accuracy of GraftM was benchmarked with in silico and in vitro mock communities using taxonomic markers, and was found to have higher accuracy at the family level with a processing time 2.0-3.7× faster than currently available software. Exploration of a wetland metagenome using 16S rRNA- and methyl-coenzyme M reductase (McrA)-specific gpkgs revealed taxonomic and functional shifts across a depth gradient. Analysis of the NCBI nr database using the McrA gpkg allowed the detection of novel sequences belonging to phylum-level lineages. A growing collection of gpkgs is available online (https://github.com/geronimp/graftM_gpkgs), where curated packages can be uploaded and exchanged.

Functional metagenomics reveals a novel carbapenem-hydrolyzing mobile beta-lactamase from Indian river sediments contaminated with antibiotic production waste.

Evolution has provided environmental bacteria with a plethora of genes that give resistance to antibiotic compounds. Under anthropogenic selection pressures, some of these genes are believed to be recruited over time into pathogens by horizontal gene transfer. River sediment polluted with fluoroquinolones and other drugs discharged from bulk drug production in India constitute an environment with unprecedented, long-term antibiotic selection pressures. It is therefore plausible that previously unknown resistance genes have evolved and/or are promoted here. In order to search for novel resistance genes, we therefore analyzed such river sediments by a functional metagenomics approach. DNA fragments providing resistance to different antibiotics in E. coli were sequenced using Sanger and PacBio RSII platforms. We recaptured the majority of known antibiotic resistance genes previously identified by open shot-gun metagenomics sequencing of the same samples. In addition, seven novel resistance gene candidates (six beta-lactamases and one amikacin resistance gene) were identified. Two class A beta-lactamases, blaRSA1 and blaRSA2, were phylogenetically close to clinically important ESBLs like blaGES, blaBEL and blaL2, and were further characterized for their substrate spectra. The blaRSA1 protein, encoded as an integron gene cassette, efficiently hydrolysed penicillins, first generation cephalosporins and cefotaxime, while blaRSA2 was an inducible class A beta-lactamase, capable of hydrolyzing carbapenems albeit with limited efficiency, similar to the L2 beta-lactamase from Stenotrophomonas maltophilia. All detected novel genes were associated with plasmid mobilization proteins, integrons, and/or other resistance genes, suggesting a potential for mobility. This study provides insight into a resistome shaped by an exceptionally strong and long-term antibiotic selection pressure. An improved knowledge of mobilized resistance factors in the external environment may make us better prepared for the resistance challenges that we may face in clinics in the future.

A metagenomic assessment of viral contamination on fresh parsley plants irrigated with fecally tainted river water.

Microbial food-borne diseases are still frequently reported despite the implementation of microbial quality legislation to improve food safety. Among all the microbial agents, viruses are the most important causative agents of food-borne outbreaks. The development and application of a new generation of sequencing techniques to test for viral contaminants in fresh produce is an unexplored field that allows for the study of the viral populations that might be transmitted by the fecal-oral route through the consumption of contaminated food. To advance this promising field, parsley was planted and grown under controlled conditions and irrigated using contaminated river water. Viruses polluting the irrigation water and the parsley leaves were studied by using metagenomics. To address possible contamination due to sample manipulation, library preparation, and other sources, parsley plants irrigated with nutritive solution were used as a negative control. In parallel, viruses present in the river water used for plant irrigation were analyzed using the same methodology. It was possible to assign viral taxons from 2.4 to 74.88% of the total reads sequenced depending on the sample. Most of the viral reads detected in the river water were related to the plant viral families Tymoviridae (66.13%) and Virgaviridae (14.45%) and the phage viral families Myoviridae (5.70%), Siphoviridae (5.06%), and Microviridae (2.89%). Less than 1% of the viral reads were related to viral families that infect humans, including members of the Adenoviridae, Reoviridae, Picornaviridae and Astroviridae families. On the surface of the parsley plants, most of the viral reads that were detected were assigned to the Dicistroviridae family (41.52%). Sequences related to important viral pathogens, such as the hepatitis E virus, several picornaviruses from species A and B as well as human sapoviruses and GIV noroviruses were detected. The high diversity of viral sequences found in the parsley plants suggests that irrigation on fecally-tainted food may have a role in the transmission of a wide diversity of viral families. This finding reinforces the idea that the best way to avoid food-borne viral diseases is to introduce good field irrigation and production practices. New strains have been identified that are related to the Picornaviridae and distantly related to the Hepeviridae family. However, the detection of a viral genome alone does not necessarily indicate there is a risk of infection or disease development. Thus, further investigation is crucial for correlating the detection of viral metagenomes in samples with the risk of infection. There is also an urgent need to develop new methods to improve the sensitivity of current Next Generation Sequencing (NGS) techniques in the food safety area.

Marine Metagenome as A Resource for Novel Enzymes.

More than 99% of identified prokaryotes, including many from the marine environment, cannot be cultured in the laboratory. This lack of capability restricts our knowledge of microbial genetics and community ecology. Metagenomics, the culture-independent cloning of environmental DNAs that are isolated directly from an environmental sample, has already provided a wealth of information about the uncultured microbial world. It has also facilitated the discovery of novel biocatalysts by allowing researchers to probe directly into a huge diversity of enzymes within natural microbial communities. Recent advances in these studies have led to a great interest in recruiting microbial enzymes for the development of environmentally-friendly industry. Although the metagenomics approach has many limitations, it is expected to provide not only scientific insights but also economic benefits, especially in industry. This review highlights the importance of metagenomics in mining microbial lipases, as an example, by using high-throughput techniques. In addition, we discuss challenges in the metagenomics as an important part of bioinformatics analysis in big data.

Subsistence strategies in traditional societies distinguish gut microbiomes.

Recent studies suggest that gut microbiomes of urban-industrialized societies are different from those of traditional peoples. Here we examine the relationship between lifeways and gut microbiota through taxonomic and functional potential characterization of faecal samples from hunter-gatherer and traditional agriculturalist communities in Peru and an urban-industrialized community from the US. We find that in addition to taxonomic and metabolic differences between urban and traditional lifestyles, hunter-gatherers form a distinct sub-group among traditional peoples. As observed in previous studies, we find that Treponema are characteristic of traditional gut microbiomes. Moreover, through genome reconstruction (2.2-2.5 MB, coverage depth × 26-513) and functional potential characterization, we discover these Treponema are diverse, fall outside of pathogenic clades and are similar to Treponema succinifaciens, a known carbohydrate metabolizer in swine. Gut Treponema are found in non-human primates and all traditional peoples studied to date, suggesting they are symbionts lost in urban-industrialized societies.

The metagenomic telescope.

Next generation sequencing technologies led to the discovery of numerous new microbe species in diverse environmental samples. Some of the new species contain genes never encountered before. Some of these genes encode proteins with novel functions, and some of these genes encode proteins that perform some well-known function in a novel way. A tool, named the Metagenomic Telescope, is described here that applies artificial intelligence methods, and seems to be capable of identifying new protein functions even in the well-studied model organisms. As a proof-of-principle demonstration of the Metagenomic Telescope, we considered DNA repair enzymes in the present work. First we identified proteins in DNA repair in well-known organisms (i.e., proteins in base excision repair, nucleotide excision repair, mismatch repair and DNA break repair); next we applied multiple alignments and then built hidden Markov profiles for each protein separately, across well-researched organisms; next, using public depositories of metagenomes, originating from extreme environments, we identified DNA repair genes in the samples. While the phylogenetic classification of the metagenomic samples are not typically available, we hypothesized that some very special DNA repair strategies need to be applied in bacteria and Archaea living in those extreme circumstances. It is a difficult task to evaluate the results obtained from mostly unknown species; therefore we applied again the hidden Markov profiling: for the identified DNA repair genes in the extreme metagenomes, we prepared new hidden Markov profiles (for each genes separately, subsequent to a cluster analysis); and we searched for similarities to those profiles in model organisms. We have found well known DNA repair proteins, numerous proteins with unknown functions, and also proteins with known, but different functions in the model organisms.

Improving prokaryotic transposable elements identification using a combination of de novo and profile HMM methods.

BACKGROUND: Insertion Sequences (ISs) and their non-autonomous derivatives (MITEs) are important components of prokaryotic genomes inducing duplication, deletion, rearrangement or lateral gene transfers. Although ISs and MITEs are relatively simple and basic genetic elements, their detection remains a difficult task due to their remarkable sequence diversity. With the advent of high-throughput genome and metagenome sequencing technologies, the development of fast, reliable and sensitive methods of ISs and MITEs detection become an important challenge. So far, almost all studies dealing with prokaryotic transposons have used classical BLAST-based detection methods against reference libraries. Here we introduce alternative methods of detection either taking advantages of the structural properties of the elements (de novo methods) or using an additional library-based method using profile HMM searches. RESULTS: In this study, we have developed three different work flows dedicated to ISs and MITEs detection: the first two use de novo methods detecting either repeated sequences or presence of Inverted Repeats; the third one use 28 in-house transposase alignment profiles with HMM search methods. We have compared the respective performances of each method using a reference dataset of 30 archaeal and 30 bacterial genomes in addition to simulated and real metagenomes. Compared to a BLAST-based method using ISFinder as library, de novo methods significantly improve ISs and MITEs detection. For example, in the 30 archaeal genomes, we discovered 30 new elements (+20%) in addition to the 141 multi-copies elements already detected by the BLAST approach. Many of the new elements correspond to ISs belonging to unknown or highly divergent families. The total number of MITEs has even doubled with the discovery of elements displaying very limited sequence similarities with their respective autonomous partners (mainly in the Inverted Repeats of the elements). Concerning metagenomes, with the exception of short reads data (<300 bp) for which both techniques seem equally limited, profile HMM searches considerably ameliorate the detection of transposase encoding genes (up to +50%) generating low level of false positives compare to BLAST-based methods. CONCLUSION: Compared to classical BLAST-based methods, the sensitivity of de novo and profile HMM methods developed in this study allow a better and more reliable detection of transposons in prokaryotic genomes and metagenomes. We believed that future studies implying ISs and MITEs identification in genomic data should combine at least one de novo and one library-based method, with optimal results obtained by running the two de novo methods in addition to a library-based search. For metagenomic data, profile HMM search should be favored, a BLAST-based step is only useful to the final annotation into groups and families.

Evolutionary insight into the functional amyloids of the pseudomonads.

Functional bacterial amyloids (FuBA) are important components in many environmental biofilms where they provide structural integrity to the biofilm, mediate bacterial aggregation and may function as virulence factor by binding specifically to host cell molecules. A novel FuBA system, the Fap system, was previously characterized in the genus Pseudomonas, however, very little is known about the phylogenetic diversity of bacteria with the genetic capacity to apply this system. Studies of genomes and public metagenomes from a diverse range of habitats showed that the Fap system is restricted to only three classes in the phylum Proteobacteria, the Beta-, Gamma- and Deltaproteobacteria. The structural organization of the fap genes into a single fapABCDEF operon is well conserved with minor variations such as a frequent deletion of fapA. A high degree of variation was seen within the primary structure of the major Fap fibril monomers, FapC, whereas the minor monomers, FapB, showed less sequence variation. Comparison of phylogenetic trees based on Fap proteins and the 16S rRNA gene of the corresponding bacteria showed remarkably similar overall topology. This indicates, that horizontal gene transfer is an infrequent event in the evolution of the Fap system.

Localizing transcripts to single cells suggests an important role of uncultured deltaproteobacteria in the termite gut hydrogen economy.

Identifying microbes responsible for particular environmental functions is challenging, given that most environments contain an uncultivated microbial diversity. Here we combined approaches to identify bacteria expressing genes relevant to catabolite flow and to locate these genes within their environment, in this case the gut of a "lower," wood-feeding termite. First, environmental transcriptomics revealed that 2 of the 23 formate dehydrogenase (FDH) genes known in the system accounted for slightly more than one-half of environmental transcripts. FDH is an essential enzyme of H2 metabolism that is ultimately important for the assimilation of lignocellulose-derived energy by the insect. Second, single-cell PCR analysis revealed that two different bacterial types expressed these two transcripts. The most commonly transcribed FDH in situ is encoded by a previously unappreciated deltaproteobacterium, whereas the other FDH is spirochetal. Third, PCR analysis of fractionated gut contents demonstrated that these bacteria reside in different spatial niches; the spirochete is free-swimming, whereas the deltaproteobacterium associates with particulates. Fourth, the deltaproteobacteria expressing FDH were localized to protozoa via hybridization chain reaction-FISH, an approach for multiplexed, spatial mapping of mRNA and rRNA targets. These results underscore the importance of making direct vs. inference-based gene-species associations, and have implications in higher termites, the most successful termite lineage, in which protozoa have been lost from the gut community. Contrary to expectations, in higher termites, FDH genes related to those from the protozoan symbiont dominate, whereas most others were absent, suggesting that a successful gene variant can persist and flourish after a gut perturbation alters a major environmental niche.