Optimizing and evaluating the reconstruction of Metagenome-assembled microbial genomes

Genome-Resolved Metagenomics and Denitrifying Strain Isolation Reveal New Insights into Microbial Denitrification in the Deep Vadose Zone

The heavy use of nitrogen fertilizer in intensive agricultural areas often leads to nitrate accumulation in subsurface soil and nitrate contamination in groundwater, which poses a serious risk to public health. Denitrifying microorganisms in the subsoil convert nitrate to gaseous forms of nitrogen, thereby mitigating the leaching of nitrate into groundwater. Here, we investigated denitrifying microorganisms in the deep vadose zone of a typical intensive agricultural area in China through microcosm enrichment, genome-resolved metagenomic analysis, and denitrifying bacteria isolation. A total of 1000 metagenome-assembled genomes (MAGs) were reconstructed, resulting in 98 high-quality, dereplicated MAGs that contained denitrification genes. Among them, 32 MAGs could not be taxonomically classified at the genus or species level, indicating that a broader spectrum of taxonomic groups is involved in subsoil denitrification than previously recognized. A denitrifier isolate library was constructed by using a strategy combining high-throughput and conventional cultivation techniques. Assessment of the denitrification characteristics of both the MAGs and isolates demonstrated the dominance of truncated denitrification. Functional screening revealed the highest denitrification activity in two complete denitrifiers belonging to the genus Pseudomonas. These findings greatly expand the current knowledge of the composition and function of denitrifying microorganisms in subsoils. The constructed isolate library provided the first pool of subsoil-denitrifying microorganisms that could facilitate the development of microbe-based technologies for nitrate attenuation in groundwater.

From germline genome to highly fragmented somatic genome: genome-wide DNA rearrangement during the sexual process in ciliated protists

Genomes are incredibly dynamic within diverse eukaryotes and programmed genome rearrangements (PGR) play important roles in generating genomic diversity. However, genomes and chromosomes in metazoans are usually large in size which prevents our understanding of the origin and evolution of PGR. To expand our knowledge of genomic diversity and the evolutionary origin of complex genome rearrangements, we focus on ciliated protists (ciliates). Ciliates are single-celled eukaryotes with highly fragmented somatic chromosomes and massively scrambled germline genomes. PGR in ciliates occurs extensively by removing massive amounts of repetitive and selfish DNA elements found in the silent germline genome during development of the somatic genome. We report the partial germline genomes of two spirotrich ciliate species, namely Strombidium cf. sulcatum and Halteria grandinella, along with the most compact and highly fragmented somatic genome for S. cf. sulcatum. We provide the first insights into the genome rearrangements of these two species and compare these features with those of other ciliates. Our analyses reveal: (1) DNA sequence loss through evolution and during PGR in S. cf. sulcatum has combined to produce the most compact and efficient nanochromosomes observed to date; (2) the compact, transcriptome-like somatic genome in both species results from extensive removal of a relatively large number of shorter germline-specific DNA sequences; (3) long chromosome breakage site motifs are duplicated and retained in the somatic genome, revealing a complex model of chromosome fragmentation in spirotrichs; (4) gene scrambling and alternative processing are found throughout the core spirotrichs, offering unique opportunities to increase genetic diversity and regulation in this group.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-023-00213-x.

MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

BACKGROUND

The possibility of recovering metagenome-assembled genomes (MAGs) from sequence reads allows for further insights into microbial communities and their members, possibly even analyzing such sequences with tools designed for single-isolate genomes. As result quality depends on sequence quality, performance of tools for single-isolate genomes on MAGs should be tested beforehand. Bioinformatics can be leveraged to quickly create varied synthetic test sets with known composition for this purpose.

RESULTS

We present MAGICIAN, a flexible, user-friendly pipeline for the simulation of MAGs. MAGICIAN combines a synthetic metagenome simulator with a metagenomic assembly and binning pipeline to simulate MAGs based on user-supplied input genomes, allowing users to test performance of tools on MAGs while having a ground truth to compare results to. Using MAGICIAN, we found that even very slight (1%) changes in depth of coverage can drastically affect whether a genome can be recovered. We also demonstrate the use of simulated MAGs by evaluating the suitability of such genomes obtained with MAGICIAN's current default pipeline for analysis with the antimicrobial resistance gene identification tool ResFinder.

CONCLUSIONS

Using MAGICIAN, it is possible to simulate MAGs which, while generally high in quality, reflect issues encountered with real-world data, thus providing realistic best-case data. Evaluating the results of ResFinder analysis of these genomes revealed a risk for plausible-looking false positives, which underlines the need for pipeline validation so that researchers are aware of the potential issues when interpreting real-world data. Furthermore, the effects of fluctuations in depth of coverage on genome recovery in our simulated "random sequencing" warrant further investigation and indicate random subsampling of reads may affect discovery of more genomes.

The long-term effect of glutaraldehyde on the bacterial community in anaerobic ammonium oxidation reactor

A 160-day incubation was performed with two anammox reactors (GA and CK) to investigate the effect of glutaraldehyde. The results indicated that anammox bacteria were very sensitive when glutaraldehyde in GA reactor increased to 40 mg/L, the nitrogen removal efficiency sharply decreased to 11%, only one-quarter of CK. Glutaraldehyde changed spatial distribution of exopolysaccharides, caused anammox bacteria (Brocadia CK_gra75) to disassociate from granules (24.70% of the reads in CK but only 14.09% in GA granules). Metagenome analysis indicated glutaraldehyde led to the denitrifier community succession from strains without nir (nitrite reductase) and nor (nitric oxide reductases) genes to those with them, and the rapid growth of denitrifiers with NodT (an outer membrane factor)-related efflux pumps replacing those with another TolC -related ones. Meanwhile, Brocadia CK_gra75 lacks the NodT proteins. This study provides important insight into community adaptation and potential resistance mechanism in an active anammox community after exposure to disinfectant.

Emergent community architecture despite distinct diversity in the global whale shark (Rhincodon typus) epidermal microbiome

Microbiomes confer beneficial physiological traits to their host, but microbial diversity is inherently variable, challenging the relationship between microbes and their contribution to host health. Here, we compare the diversity and architectural complexity of the epidermal microbiome from 74 individual whale sharks (Rhincodon typus) across five aggregations globally to determine if network properties may be more indicative of the microbiome-host relationship. On the premise that microbes are expected to exhibit biogeographic patterns globally and that distantly related microbial groups can perform similar functions, we hypothesized that microbiome co-occurrence patterns would occur independently of diversity trends and that keystone microbes would vary across locations. We found that whale shark aggregation was the most important factor in discriminating taxonomic diversity patterns. Further, microbiome network architecture was similar across all aggregations, with degree distributions matching Erdos-Renyi-type networks. The microbiome-derived networks, however, display modularity indicating a definitive microbiome structure on the epidermis of whale sharks. In addition, whale sharks hosted 35 high-quality metagenome assembled genomes (MAGs) of which 25 were present from all sample locations, termed the abundant 'core'. Two main MAG groups formed, defined here as Ecogroup 1 and 2, based on the number of genes present in metabolic pathways, suggesting there are at least two important metabolic niches within the whale shark microbiome. Therefore, while variability in microbiome diversity is high, network structure and core taxa are inherent characteristics of the epidermal microbiome in whale sharks. We suggest the host-microbiome and microbe-microbe interactions that drive the self-assembly of the microbiome help support a functionally redundant abundant core and that network characteristics should be considered when linking microbiomes with host health.

Baseline metagenome-assembled genome (MAG) data of Sikkim hot springs from Indian Himalayan geothermal belt (IHGB) showcasing its potential CAZymes, and sulfur-nitrogen metabolic activity

Here we present the construction and characterization of metagenome assembled genomes (MAGs) from two hot springs residing in the vicinity of Indian Himalayan Geothermal Belt (IHGB). A total of 78 and 7 taxonomic bins were obtained for Old Yume Samdong (OYS) and New Yume Samdong (NYS) hot springs respectively. After passing all the criteria only 21 and 4 MAGs were further studied based on the successful prediction of their 16 S rRNA. Various databases were used such as GTDB, Kaiju, EzTaxon, BLAST XY Plot and NCBI BLAST to get the taxonomic classification of various 16 S rRNA predicted MAGs. The bacterial genomes found were from both thermophilic and mesophilic bacteria among which Proteobacteria, Chloroflexi, Bacteroidetes and Firmicutes were the abundant phyla. However, in case of OYS, two genomes belonged to archaeal Methanobacterium and Methanocaldococcus. Functional characterization revealed the richness of CAZymes such as Glycosyl Transferase (GT) (56.7%), Glycoside Hydrolase (GH) (37.4%), Carbohydrate Esterase family (CE) (8.2%), and Polysaccharide Lyase (PL) (1.9%). There were negligible antibiotic resistance genes in the MAGs however, a significant heavy metal tolerance gene was found in the MAGs. Thus, it may be assumed that there is no coexistence of antibiotic and heavy metal resistance genes in these hot spring microbiomes. Since the selected hot springs possess good sulfur content thus, we also checked the presence of genes for sulfur and nitrogen metabolism. It was found that MAGs from both the hot springs possess significant number of genes related to sulfur and nitrogen metabolism.

The Promise and Pitfalls of Prophages

Phages dominate every ecosystem on the planet. While virulent phages sculpt the microbiome by killing their bacterial hosts, temperate phages provide unique growth advantages to their hosts through lysogenic conversion. Many prophages benefit their host, and prophages are responsible for genotypic and phenotypic differences that separate individual microbial strains. However, the microbes also endure a cost to maintain those phages: additional DNA to replicate and proteins to transcribe and translate. We have never quantified those benefits and costs. Here, we analysed over two and a half million prophages from over half a million bacterial genome assemblies. Analysis of the whole dataset and a representative subset of taxonomically diverse bacterial genomes demonstrated that the normalised prophage density was uniform across all bacterial genomes above 2 Mbp. We identified a constant carrying capacity of phage DNA per bacterial DNA. We estimated that each prophage provides cellular services equivalent to approximately 2.4 % of the cell's energy or 0.9 ATP per bp per hour. We demonstrate analytical, taxonomic, geographic, and temporal disparities in identifying prophages in bacterial genomes that provide novel targets for identifying new phages. We anticipate that the benefits bacteria accrue from the presence of prophages balance the energetics involved in supporting prophages. Furthermore, our data will provide a new framework for identifying phages in environmental datasets, diverse bacterial phyla, and from different locations.

Assembly of novel microbial genomes from gut metagenomes of rhesus macaque (Macaca mulatta)

Rhesus macaque (RM, Macaca mulatta), as an important model animal, commonly suffers from chronic diarrheal disease, challenging the breeding of RMs. Gut microbiomes play key roles in maintaining intestinal health of RMs. However, it is still unclear about more features of gut microbiome as responsible for intestinal health of RMs. In this study, we performed de novo assembly of metagenome-assembled genomes (MAGs) based on fecal metagenomes from chronic diarrheal RMs and asymptomatic individuals. In total of 731 non-redundant MAGs with at least 80% completeness were reconstructed in this study. More than 97% MAGs were novel genomes compared with more than 250,000 reference genomes. MAGs of Campylobacter and Helicobacteraceae from RM guts mainly carried flagella-associated virulence genes and chemotaxis-associated virulence genes, which might mediate motility and adhesion of bacteria. Comparing to MAGs of Campylobacter from humans, distributions and functions of these MAGs of Campylobacter from RMs exhibited significant differences. Most members of Bacteroidota, Spirochaetota, Helicobacteraceae, Lactobacillaceae and Anaerovibrio significantly decreased in guts of chronic diarrhea RMs. More than 92% MAGs in this study were not contained in 2,985 MAGs previously reported from other 22 non-human primates (NHPs), expanding the microbial diversity in guts of NHPs. The distributions and functions of gut microbiome were prominently influenced by host phylogeny of NHPs. Our results could help to more clearly understand about the diversity and function of RMs gut microbiome.

Stingray epidermal microbiomes are species-specific with local adaptations

Marine host-associated microbiomes are affected by a combination of species-specific (e.g., host ancestry, genotype) and habitat-specific features (e.g., environmental physiochemistry and microbial biogeography). The stingray epidermis provides a gradient of characteristics from high dermal denticles coverage with low mucus to reduce dermal denticles and high levels of mucus. Here we investigate the effects of host phylogeny and habitat by comparing the epidermal microbiomes of Myliobatis californica (bat rays) with a mucus rich epidermis, and Urobatis halleri (round rays) with a mucus reduced epidermis from two locations, Los Angeles and San Diego, California (a 150 km distance). We found that host microbiomes are species-specific and distinct from the water column, however composition of M. californica microbiomes showed more variability between individuals compared to U. halleri. The variability in the microbiome of M. californica caused the microbial taxa to be similar across locations, while U. halleri microbiomes were distinct across locations. Despite taxonomic differences, Shannon diversity is the same across the two locations in U. halleri microbiomes suggesting the taxonomic composition are locally adapted, but diversity is maintained by the host. Myliobatis californica and U. halleri microbiomes maintain functional similarity across Los Angeles and San Diego and each ray showed several unique functional genes. Myliobatis californica has a greater relative abundance of RNA Polymerase III-like genes in the microbiome than U. halleri, suggesting specific adaptations to a heavy mucus environment. Construction of Metagenome Assembled Genomes (MAGs) identified novel microbial species within Rhodobacteraceae, Moraxellaceae, Caulobacteraceae, Alcanivoracaceae and Gammaproteobacteria. All MAGs had a high abundance of active RNA processing genes, heavy metal, and antibiotic resistant genes, suggesting the stingray mucus supports high microbial growth rates, which may drive high levels of competition within the microbiomes increasing the antimicrobial properties of the microbes.

Epidermal Microbiomes of Leopard Sharks (Triakis semifasciata) Are Consistent across Captive and Wild Environments

Characterizations of shark-microbe systems in wild environments have outlined patterns of species-specific microbiomes; however, whether captivity affects these trends has yet to be determined. We used high-throughput shotgun sequencing to assess the epidermal microbiome belonging to leopard sharks (Triakis semifasciata) in captive (Birch Aquarium, La Jolla California born and held permanently in captivity), semi-captive (held in captivity for <1 year in duration and scheduled for release; Scripps Institute of Oceanography, San Diego, CA, USA) and wild environments (Moss Landing and La Jolla, CA, USA). Here, we report captive environments do not drive epidermal microbiome compositions of T. semifasciata to significantly diverge from wild counterparts as life-long captive sharks maintain a species-specific epidermal microbiome resembling those associated with semi-captive and wild populations. Major taxonomic composition shifts observed were inverse changes of top taxonomic contributors across captive duration, specifically an increase of Pseudoalteromonadaceae and consequent decrease of Pseudomonadaceae relative abundance as T. semifasciata increased duration in captive conditions. Moreover, we show captivity did not lead to significant losses in microbial α-diversity of shark epidermal communities. Finally, we present a novel association between T. semifasciata and the Muricauda genus as Metagenomes associated genomes revealed a consistent relationship across captive, semi-captive, and wild populations. Since changes in microbial communities is often associated with poor health outcomes, our report illustrates that epidermally associated microbes belonging to T. semifasciata are not suffering detrimental impacts from long or short-term captivity. Therefore, conservation programs which house sharks in aquariums are providing a healthy environment for the organisms on display. Our findings also expand on current understanding of shark epidermal microbiomes, explore the effects of ecologically different scenarios on benthic shark microbe associations, and highlight novel associations that are consistent across captive gradients.

Metagenome-Assembled Genomes of Komagataeibacter from Kombucha Exposed to Mars-Like Conditions Reveal the Secrets in Tolerating Extraterrestrial Stresses

Kombucha mutualistic community (KMC) is composed by acetic acid bacteria and yeasts, producing fermented tea with health benefits. As part of the BIOlogy and Mars EXperiment (BIOMEX) project, the effect of Mars-like conditions on the KMC was analyzed. Here, we analyzed metagenome-assembled genomes (MAGs) of the Komagataeibacter, which is a predominant genus in KMC, to understand their roles in the KMC after exposure to Mars-like conditions (outside the International Space Station) based on functional genetic elements. We constructed three MAGs: K. hansenii, K. rhaeticus, and K. oboediens. Our results showed that (i) K. oboediens MAG functionally more complex than K. hansenii, (ii) K. hansenii is a keystone in KMCs with specific functional features to tolerate extreme stress, and (iii) genes related to the PPDK, betaine biosynthesis, polyamines biosynthesis, sulfate-sulfur assimilation pathway as well as type II toxin-antitoxin (TA) system, quorum sensing (QS) system, and cellulose production could play important roles in the resilience of KMC after exposure to Mars-like stress. Our findings show the potential mechanisms through which Komagataeibacter tolerates the extraterrestrial stress and will help to understand minimal microbial composition of KMC for space travelers.

How Metagenomics Has Transformed Our Understanding of Bacteriophages in Microbiome Research

The microbiome is an essential part of most ecosystems. It was originally studied mostly through culturing but relatively few microbes can be cultured, so much of the microbiome was left unexplored. The emergence of metagenomic sequencing techniques changed that and allowed the study of microbiomes from all sorts of habitats. Metagenomic sequencing also allowed for a more thorough exploration of prophages, viruses that integrate into bacterial genomes, and how they benefit their hosts. One issue with using open-access metagenomic data is that sequences added to databases often have little to no metadata to work with, so finding enough sequences can be difficult. Many metagenomes have been manually curated but this is a time-consuming process and relies heavily on the uploader to be accurate and thorough when filling in metadata fields and the curators to be working with the same ontologies. Using algorithms to automatically sort metagenomes based on either the taxonomic profile or the functional profile may be a viable solution to the issues with manually curated metagenomes, but it requires that the algorithm is trained on carefully curated datasets and using the most informative profile possible in order to minimize errors.

Nocardioides carbamazepini sp. nov., an ibuprofen degrader isolated from a biofilm bacterial community enriched on carbamazepine

From the metagenome of a carbamazepine amended selective enrichment culture the genome of a new to science bacterial species affiliating with the genus Nocardioides was reconstructed. From the same enrichment an aerobic actinobacterium, strain CBZ_1^T, sharing 99.4% whole-genome sequence similarity with the reconstructed Nocardioides sp. bin genome was isolated. On the basis of 16S rRNA gene sequence similarity the novel isolate affiliated to the genus Nocardioides, with the closest relatives Nocardioides kongjuensis DSM19082^T (98.4%), Nocardioides daeguensis JCM17460^T (98.4%) and Nocardioides nitrophenolicus DSM15529^T (98.2%). Using a polyphasic approach it was confirmed that the isolate CBZ_1^T represents a new phyletic lineage within the genus Nocardioides. According to metagenomic, metatranscriptomic studies and metabolic analyses strain CZB_1^T was abundant in both carbamazepine and ibuprofen enrichments, and harbors biodegradative genes involved in the biodegradation of pharmaceutical compounds. Biodegradation studies supported that the new species was capable of ibuprofen biodegradation. After 7 weeks of incubation, in mineral salts solution supplemented with glucose (3 g l^-1) as co-substrate, 70% of ibuprofen was eliminated by strain CBZ_1^T at an initial conc. of 1.5 mg l^-1. The phylogenetic, phenotypic and chemotaxonomic data supported the classification of strain CBZ_1^T to the genus Nocardioides, for which the name Nocardioides carbamazepini sp. nov. (CBZ_1^T = NCAIM B.0.2663 = LMG 32395) is proposed. To the best of our knowledge, this is the first study that reports simultaneous genome reconstruction of a new to science bacterial species using metagenome binning and at the same time the isolation of the same novel bacterial species.

Introduction to the principles and methods underlying the recovery of metagenome-assembled genomes from metagenomic data

The rise of metagenomics offers a leap forward for understanding the genetic diversity of microorganisms in many different complex environments by providing a platform that can identify potentially unlimited numbers of known and novel microorganisms. As such, it is impossible to imagine new major initiatives without metagenomics. Nevertheless, it represents a relatively new discipline with various levels of complexity and demands on bioinformatics. The underlying principles and methods used in metagenomics are often seen as common knowledge and often not detailed or fragmented. Therefore, we reviewed these to guide microbiologists in taking the first steps into metagenomics. We specifically focus on a workflow aimed at reconstructing individual genomes, that is, metagenome‐assembled genomes, integrating DNA sequencing, assembly, binning, identification and annotation.

The functional evolution of termite gut microbiota

BACKGROUND

Termites primarily feed on lignocellulose or soil in association with specific gut microbes. The functioning of the termite gut microbiota is partly understood in a handful of wood-feeding pest species but remains largely unknown in other taxa. We intend to fill this gap and provide a global understanding of the functional evolution of termite gut microbiota.

RESULTS

We sequenced the gut metagenomes of 145 samples representative of the termite diversity. We show that the prokaryotic fraction of the gut microbiota of all termites possesses similar genes for carbohydrate and nitrogen metabolisms, in proportions varying with termite phylogenetic position and diet. The presence of a conserved set of gut prokaryotic genes implies that essential nutritional functions were present in the ancestor of modern termites. Furthermore, the abundance of these genes largely correlated with the host phylogeny. Finally, we found that the adaptation to a diet of soil by some termite lineages was accompanied by a change in the stoichiometry of genes involved in important nutritional functions rather than by the acquisition of new genes and pathways.

CONCLUSIONS

Our results reveal that the composition and function of termite gut prokaryotic communities have been remarkably conserved since termites first appeared ~ 150 million years ago. Therefore, the "world's smallest bioreactor" has been operating as a multipartite symbiosis composed of termites, archaea, bacteria, and cellulolytic flagellates since its inception. Video Abstract.

Metagenome-assembled genomes of phytoplankton microbiomes from the Arctic and Atlantic Oceans

BACKGROUND

Phytoplankton communities significantly contribute to global biogeochemical cycles of elements and underpin marine food webs. Although their uncultured genomic diversity has been estimated by planetary-scale metagenome sequencing and subsequent reconstruction of metagenome-assembled genomes (MAGs), this approach has yet to be applied for complex phytoplankton microbiomes from polar and non-polar oceans consisting of microbial eukaryotes and their associated prokaryotes.

RESULTS

Here, we have assembled MAGs from chlorophyll a maximum layers in the surface of the Arctic and Atlantic Oceans enriched for species associations (microbiomes) with a focus on pico- and nanophytoplankton and their associated heterotrophic prokaryotes. From 679 Gbp and estimated 50 million genes in total, we recovered 143 MAGs of medium to high quality. Although there was a strict demarcation between Arctic and Atlantic MAGs, adjacent sampling stations in each ocean had 51-88% MAGs in common with most species associations between Prasinophytes and Proteobacteria. Phylogenetic placement revealed eukaryotic MAGs to be more diverse in the Arctic whereas prokaryotic MAGs were more diverse in the Atlantic Ocean. Approximately 70% of protein families were shared between Arctic and Atlantic MAGs for both prokaryotes and eukaryotes. However, eukaryotic MAGs had more protein families unique to the Arctic whereas prokaryotic MAGs had more families unique to the Atlantic.

CONCLUSION

Our study provides a genomic context to complex phytoplankton microbiomes to reveal that their community structure was likely driven by significant differences in environmental conditions between the polar Arctic and warm surface waters of the tropical and subtropical Atlantic Ocean. Video Abstract.

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.

Construction of Aerobic/Anaerobic-Substrate-Induced Gene Expression Procedure for Exploration of Metagenomes From Subseafloor Sediments

Substrate-induced gene expression (SIGEX) is a high-throughput promoter-trap method. It is a function-based metagenomic screening tool that relies on transcriptional activation of a reporter gene green fluorescence protein (gfp) by a metagenomic DNA library upon induction with a substrate. However, its use is limited because of the relatively small size of metagenomic DNA libraries and incompatibility with screening metagenomes from anaerobic environments. In this study, these limitations of SIGEX were addressed by fine-tuning metagenome DNA library construction protocol and by using Evoglow, a green fluorescent protein that forms a chromophore even under anaerobic conditions. Two metagenomic libraries were constructed for subseafloor sediments offshore Shimokita Peninsula (Pacific Ocean) and offshore Joetsu (Japan Sea). The library construction protocol was improved by (a) eliminating short DNA fragments, (b) applying topoisomerase-based high-efficiency ligation, (c) optimizing insert DNA concentration, and (d) column-based DNA enrichment. This led to a successful construction of metagenome DNA libraries of approximately 6 Gbp for both samples. SIGEX screening using five aromatic compounds (benzoate, 3-chlorobenzoate, 3-hydroxybenzoate, phenol, and 2,4-dichlorophenol) under aerobic and anaerobic conditions revealed significant differences in the inducible clone ratios under these conditions. 3-Chlorobenzoate and 2,4-dichlorophenol led to a higher induction ratio than that for the other non-chlorinated aromatic compounds under both aerobic and anaerobic conditions. After the further screening of induced clones, a clone induced by 3-chlorobenzoate only under anaerobic conditions was isolated and characterized. The clone harbors a DNA insert that encodes putative open reading frames of unknown function. Previous aerobic SIGEX attempts succeeded in the isolation of gene fragments from anaerobes. This study demonstrated that some gene fragments require a strict in vivo reducing environment to function and may be potentially missed when screened by aerobic induction. The newly developed anaerobic SIGEX scheme will facilitate functional exploration of metagenomes from the anaerobic biosphere.

Evaluating de Novo Assembly and Binning Strategies for Time Series Drinking Water Metagenomes

Reconstructing microbial genomes from metagenomic short-read data can be challenging due to the unknown and uneven complexity of microbial communities. This complexity encompasses highly diverse populations, which often includes strain variants. Reconstructing high-quality genomes is a crucial part of the metagenomic workflow, as subsequent ecological and metabolic inferences depend on their accuracy, quality, and completeness. In contrast to microbial communities in other ecosystems, there has been no systematic assessment of genome-centric metagenomic workflows for drinking water microbiomes. In this study, we assessed the performance of a combination of assembly and binning strategies for time series drinking water metagenomes that were collected over 6 months. The goal of this study was to identify the combination of assembly and binning approaches that result in high-quality and -quantity metagenome-assembled genomes (MAGs), representing most of the sequenced metagenome. Our findings suggest that the metaSPAdes coassembly strategies had the best performance, as they resulted in larger and less fragmented assemblies, with at least 85% of the sequence data mapping to contigs greater than 1 kbp. Furthermore, a combination of metaSPAdes coassembly strategies and MetaBAT2 produced the highest number of medium-quality MAGs while capturing at least 70% of the metagenomes based on read recruitment. Utilizing different assembly/binning approaches also assists in the reconstruction of unique MAGs from closely related species that would have otherwise collapsed into a single MAG using a single workflow. Overall, our study suggests that leveraging multiple binning approaches with different metaSPAdes coassembly strategies may be required to maximize the recovery of good-quality MAGs. IMPORTANCE Drinking water contains phylogenetic diverse groups of bacteria, archaea, and eukarya that affect the esthetic quality of water, water infrastructure, and public health. Taxonomic, metabolic, and ecological inferences of the drinking water microbiome depend on the accuracy, quality, and completeness of genomes that are reconstructed through the application of genome-resolved metagenomics. Using time series metagenomic data, we present reproducible genome-centric metagenomic workflows that result in high-quality and -quantity genomes, which more accurately signifies the sequenced drinking water microbiome. These genome-centric metagenomic workflows will allow for improved taxonomic and functional potential analysis that offers enhanced insights into the stability and dynamics of drinking water microbial communities.

Elasmobranch microbiomes: emerging patterns and implications for host health and ecology

Elasmobranchs (sharks, skates and rays) are of broad ecological, economic, and societal value. These globally important fishes are experiencing sharp population declines as a result of human activity in the oceans. Research to understand elasmobranch ecology and conservation is critical and has now begun to explore the role of body-associated microbiomes in shaping elasmobranch health. Here, we review the burgeoning efforts to understand elasmobranch microbiomes, highlighting microbiome variation among gastrointestinal, oral, skin, and blood-associated niches. We identify major bacterial lineages in the microbiome, challenges to the field, key unanswered questions, and avenues for future work. We argue for prioritizing research to determine how microbiomes interact mechanistically with the unique physiology of elasmobranchs, potentially identifying roles in host immunity, disease, nutrition, and waste processing. Understanding elasmobranch–microbiome interactions is critical for predicting how sharks and rays respond to a changing ocean and for managing healthy populations in managed care.

Metabolic potential and survival strategies of microbial communities across extreme temperature gradients on Deception Island volcano, Antarctica

Active volcanoes in Antarctica have remarkable temperature and geochemical gradients that could select for a wide variety of microbial adaptive mechanisms and metabolic pathways. Deception Island is a stratovolcano flooded by the sea, resulting in contrasting ecosystems such as permanent glaciers and active fumaroles, which creates steep gradients that have been shown to affect microbial diversity. In this study, we used shotgun metagenomics and metagenome-assembled genomes to explore the metabolic potentials and survival strategies of microbial communities along an extreme temperature gradient in fumarole and glacier sediments on Deception Island. We observed that communities from a 98 °C fumarole were significantly enriched in genes related to hyperthermophilic (e.g. reverse gyrase, GroEL/GroES and thermosome) and oxidative stress responses, as well as genes related to sulfate reduction, ammonification and carbon fixation. Communities from <80 °C fumaroles possessed more genes related osmotic, cold- and heat-shock responses, and diverse metabolic potentials, such as those related to sulfur oxidation and denitrification, while glacier communities showed abundant metabolic potentials mainly related to heterotrophy. Through the reconstruction of genomes, we were able to reveal the metabolic potentials and different survival strategies of underrepresented taxonomic groups, especially those related to Nanoarchaeota, Pyrodictiaceae and thermophilic ammonia-oxidizing archaeal lineages.

309 metagenome assembled microbial genomes from deep sediment samples in the Gulfs of Kathiawar Peninsula

Prokaryoplankton genomes from the deep marine sediments are less explored compared to shallow shore sediments. The Gulfs of Kathiawar peninsula experience varied currents and inputs from different on-shore activities. Any perturbations would directly influence the microbiome and their normal homeostasis. Advancements in reconstructing genomes from metagenomes allows us to understand the role of individual unculturable microbes in ecological niches like the Gulf sediments. Here, we report 309 bacterial and archaeal genomes assembled from metagenomics data of deep sediments from sites in the Gulf of Khambhat and Gulf of Kutch as well as a sample from the Arabian Sea. Phylogenomics classified them into 5 archaeal and 18 bacterial phyla. The genomes will facilitate understanding of the physiology, adaptation and impact of on-shore anthropogenic activities on the deep sediment microbes.

Early response of methanogenic archaea to H2 as evaluated by metagenomics and metatranscriptomics

BACKGROUND

The molecular machinery of the complex microbiological cell factory of biomethane production is not fully understood. One of the process control elements is the regulatory role of hydrogen (H2). Reduction of carbon dioxide (CO2) by H2 is rate limiting factor in methanogenesis, but the community intends to keep H2 concentration low in order to maintain the redox balance of the overall system. H2 metabolism in methanogens becomes increasingly important in the Power-to-Gas renewable energy conversion and storage technologies.

RESULTS

The early response of the mixed mesophilic microbial community to H2 gas injection was investigated with the goal of uncovering the first responses of the microbial community in the CH4 formation and CO2 mitigation Power-to-Gas process. The overall microbial composition changes, following a 10 min excessive bubbling of H2 through the reactor, was investigated via metagenome and metatranscriptome sequencing. The overall composition and taxonomic abundance of the biogas producing anaerobic community did not change appreciably 2 hours after the H2 treatment, indicating that this time period was too short to display differences in the proliferation of the members of the microbial community. There was, however, a substantial increase in the expression of genes related to hydrogenotrophic methanogenesis of certain groups of Archaea. As an early response to H2 exposure the activity of the hydrogenotrophic methanogenesis in the genus Methanoculleus was upregulated but the hydrogenotrophic pathway in genus Methanosarcina was downregulated. The RT-qPCR data corroborated the metatranscriptomic RESULTS: H2 injection also altered the metabolism of a number of microbes belonging in the kingdom Bacteria. Many Bacteria possess the enzyme sets for the Wood-Ljungdahl pathway. These and the homoacetogens are partners for syntrophic community interactions between the distinct kingdoms of Archaea and Bacteria.

CONCLUSIONS

External H2 regulates the functional activity of certain Bacteria and Archaea. The syntrophic cross-kingdom interactions in H2 metabolism are important for the efficient operation of the Power-to-Gas process. Therefore, mixed communities are recommended for the large scale Power-to-Gas process rather than single hydrogenotrophic methanogen strains. Fast and reproducible response from the microbial community can be exploited in turn-off and turn-on of the Power-to-Gas microbial cell factories.

Application of a bioinformatic pipeline to RNA-seq data identifies novel viruslike sequence in human blood

Numerous reports have suggested that infectious agents could play a role in neurodegenerative diseases, but specific etiological agents have not been convincingly demonstrated. To search for candidate agents in an unbiased fashion, we have developed a bioinformatic pipeline that identifies microbial sequences in mammalian RNA-seq data, including sequences with no significant nucleotide similarity hits in GenBank. Effectiveness of the pipeline was tested using publicly available RNA-seq data and in a reconstruction experiment using synthetic data. We then applied this pipeline to a novel RNA-seq dataset generated from a cohort of 120 samples from amyotrophic lateral sclerosis patients and controls, and identified sequences corresponding to known bacteria and viruses, as well as novel virus-like sequences. The presence of these novel virus-like sequences, which were identified in subsets of both patients and controls, were confirmed by quantitative RT-PCR. We believe this pipeline will be a useful tool for the identification of potential etiological agents in the many RNA-seq datasets currently being generated.

Clustering based approach for population level identification of condition-associated T-cell receptor β-chain CDR3 sequences

BACKGROUND

Deep immune receptor sequencing, RepSeq, provides unprecedented opportunities for identifying and studying condition-associated T-cell clonotypes, represented by T-cell receptor (TCR) CDR3 sequences. However, due to the immense diversity of the immune repertoire, identification of condition relevant TCR CDR3s from total repertoires has mostly been limited to either "public" CDR3 sequences or to comparisons of CDR3 frequencies observed in a single individual. A methodology for the identification of condition-associated TCR CDR3s by direct population level comparison of RepSeq samples is currently lacking.

RESULTS

We present a method for direct population level comparison of RepSeq samples using immune repertoire sub-units (or sub-repertoires) that are shared across individuals. The method first performs unsupervised clustering of CDR3s within each sample. It then finds matching clusters across samples, called immune sub-repertoires, and performs statistical differential abundance testing at the level of the identified sub-repertoires. It finally ranks CDR3s in differentially abundant sub-repertoires for relevance to the condition. We applied the method on total TCR CDR3β RepSeq datasets of celiac disease patients, as well as on public datasets of yellow fever vaccination. The method successfully identified celiac disease associated CDR3β sequences, as evidenced by considerable agreement of TRBV-gene and positional amino acid usage patterns in the detected CDR3β sequences with previously known CDR3βs specific to gluten in celiac disease. It also successfully recovered significantly high numbers of previously known CDR3β sequences relevant to each condition than would be expected by chance.

CONCLUSION

We conclude that immune sub-repertoires of similar immuno-genomic features shared across unrelated individuals can serve as viable units of immune repertoire comparison, serving as proxy for identification of condition-associated CDR3s.

Metagenomic Quantification of Genes with Internal Standards

qPCR and metagenomics are central molecular techniques that have offered insights into biological processes for decades, from monitoring spatial and temporal gene dynamics to tracking ARGs or pathogens. Still needed is a tool that can quantify thousands of relevant genes in a sample as gene copies per sample mass or volume.

We demonstrate that an assembly-independent and spike-in facilitated metagenomic quantification approach can be used to screen and quantify over 2,000 genes simultaneously, while delivering absolute gene concentrations comparable to those for quantitative PCR (qPCR). DNA extracted from dairy manure slurry, digestate, and compost was spiked with genomic DNA from a marine bacterium and sequenced using the Illumina HiSeq4000. We compared gene copy concentrations, in gene copies per mass of sample, of five antimicrobial resistance genes (ARGs) generated with (i) our quantitative metagenomic approach, (ii) targeted qPCR, and (iii) a hybrid quantification approach involving metagenomics and qPCR-based 16S rRNA gene quantification. Although qPCR achieved lower quantification limits, the metagenomic method avoided biases caused by primer specificity inherent to qPCR-based methods and was able to detect orders of magnitude more genes than is possible with qPCR assays. We used the approach to simultaneously quantify ARGs in the Comprehensive Antimicrobial Resistance Database (CARD). We observed that the total abundance of tetracycline resistance genes was consistent across different stages of manure treatment on three farms, but different samples were dominated by different tetracycline resistance gene families.

Metagenomic applications in exploration and development of novel enzymes from nature: a review

BACKGROUND

Microbial community has an essential role in various fields, especially the industrial sector. Microbes produce metabolites in the form of enzymes, which are one of the essential compounds for industrial processes. Unfortunately, there are still numerous microbes that cannot be identified and cultivated because of the limitations of the culture-based method. The metagenomic approach is a solution for researchers to overcome these problems. Metagenomics is a strategy used to analyze the genomes of microbial communities in the environment directly. Metagenomics application used to explore novel enzymes is essential because it allows researchers to obtain data on microbial diversity, reaching of 99% and various types of genes encoding an enzyme that has not yet been identified. Basic methods in metagenomics have been developed and are commonly used in various studies. A basic understanding of metagenomics for researchers is needed, especially young researchers to support the success of the research.

SHORT CONCLUSION

Therefore, this review was done in order to provide a deep understanding of metagenomics. It also discussed the application and basic methods of metagenomics in the exploration of novel enzymes, especially in the latest research. Several types of enzymes, such as cellulases, proteases, and lipases, which have been explored using metagenomics, were reviewed in this article.

Evaluating metagenomics tools for genome binning with real metagenomic datasets and CAMI datasets

Background

Shotgun metagenomics based on untargeted sequencing can explore the taxonomic profile and the function of unknown microorganisms in samples, and complement the shortage of amplicon sequencing. Binning assembled sequences into individual groups, which represent microbial genomes, is the key step and a major challenge in metagenomic research. Both supervised and unsupervised machine learning methods have been employed in binning. Genome binning belonging to unsupervised method clusters contigs into individual genome bins by machine learning methods without the assistance of any reference databases. So far a lot of genome binning tools have emerged. Evaluating these genome tools is of great significance to microbiological research. In this study, we evaluate 15 genome binning tools containing 12 original binning tools and 3 refining binning tools by comparing the performance of these tools on chicken gut metagenomic datasets and the first CAMI challenge datasets.

Results

For chicken gut metagenomic datasets, original genome binner MetaBat, Groopm2 and Autometa performed better than other original binner, and MetaWrap combined the binning results of them generated the most high-quality genome bins. For CAMI datasets, Groopm2 achieved the highest purity (> 0.9) with good completeness (> 0.8), and reconstructed the most high-quality genome bins among original genome binners. Compared with Groopm2, MetaBat2 had similar performance with higher completeness and lower purity. Genome refining binners DASTool predicated the most high-quality genome bins among all genomes binners. Most genome binner performed well for unique strains. Nonetheless, reconstructing common strains still is a substantial challenge for all genome binner.

Conclusions

In conclusion, we tested a set of currently available, state-of-the-art metagenomics hybrid binning tools and provided a guide for selecting tools for metagenomic binning by comparing range of purity, completeness, adjusted rand index, and the number of high-quality reconstructed bins. Furthermore, available information for future binning strategy were concluded.

A Modular Metagenomics Pipeline Allowing for the Inclusion of Prior Knowledge Using the Example of Anaerobic Digestion

Metagenomics analysis revealing the composition and functional repertoire of complex microbial communities typically relies on large amounts of sequence data. Numerous analysis strategies and computational tools are available for their analysis. Fully integrated automated analysis pipelines such as MG-RAST or MEGAN6 are user-friendly but not designed for integrating specific knowledge on the biological system under study. In order to facilitate the consideration of such knowledge, we introduce a modular, adaptable analysis pipeline combining existing tools. We applied the novel pipeline to simulated mock data sets focusing on anaerobic digestion microbiomes and compare results to those obtained with established automated analysis pipelines. We find that the analysis strategy and choice of tools and parameters have a strong effect on the inferred taxonomic community composition, but not on the inferred functional profile. By including prior knowledge, computational costs can be decreased while improving result accuracy. While automated off-the-shelf analysis pipelines are easy to apply and require no knowledge on the microbial system under study, custom-made pipelines require more preparation time and bioinformatics expertise. This extra effort is minimized by our modular, flexible, custom-made pipeline, which can be adapted to different scenarios and can take available knowledge on the microbial system under study into account.

Microbial Community Distribution and Core Microbiome in Successive Wound Grades of Individuals with Diabetic Foot Ulcers

Diabetic foot ulcer (DFU) is a major complication of diabetes with high morbidity and mortality rates. The pathogenesis of DFUs is governed by a complex milieu of environmental and host factors. The empirical treatment is initially based on wound severity since culturing and profiling the antibiotic sensitivity of wound-associated microbes is time-consuming. Hence, a thorough and rapid analysis of the microbial landscape is a major requirement toward devising evidence-based interventions. Toward this, 122 wound (100 diabetic and 22 nondiabetic) samples were sampled for their bacterial community structure using both culture-based and next-generation 16S rRNA-based metagenomics approach. Both the approaches showed that the Gram-negative microbes were more abundant in the wound microbiome. The core microbiome consisted of bacterial genera, including Alcaligenes, Pseudomonas, Burkholderia, and Corynebacterium in decreasing order of average relative abundance. Despite the heterogenous nature and extensive sharing of microbes, an inherent community structure was apparent, as revealed by a cluster analysis based on Euclidean distances. Facultative anaerobes (26.5%) were predominant in Wagner grade 5, while strict anaerobes were abundant in Wagner grade 1 (26%). A nonmetric dimensional scaling analysis could not clearly discriminate samples based on HbA1c levels. Sequencing approach revealed the presence of major culturable species even in samples with no bacterial growth in culture-based approach. Our study indicates that (i) the composition of core microbial community varies with wound severity, (ii) polymicrobial species distribution is individual specific, and (iii) antibiotic susceptibility varies with individuals. Our study suggests the need to evolve better-personalized care for better wound management therapies.IMPORTANCE Chronic nonhealing diabetic foot ulcers (DFUs) are a serious complication of diabetes and are further exacerbated by bacterial colonization. The microbial burden in the wound of each individual displays diverse morphological and physiological characteristics with unique patterns of host-pathogen interactions, antibiotic resistance, and virulence. Treatment involves empirical decisions until definitive results on the causative wound pathogens and their antibiotic susceptibility profiles are available. Hence, there is a need for rapid and accurate detection of these polymicrobial communities for effective wound management. Deciphering microbial communities will aid clinicians to tailor their treatment specifically to the microbes prevalent in the DFU at the time of assessment. This may reduce DFUs associated morbidity and mortality while impeding the rise of multidrug-resistant microbes.

Microbial abundance, composition, and function in nectar are shaped by flower visitor identity

Microbial dispersal is essential for establishment in new habitats, but the role of vector identity is poorly understood in community assembly and function. Here, we compared microbial assembly and function in floral nectar visited by legitimate pollinators (hummingbirds) and nectar robbers (carpenter bees). We assessed effects of visitation on the abundance and composition of culturable bacteria and fungi and their taxonomy and function using shotgun metagenomics and nectar chemistry. We also compared metagenome-assembled genomes (MAGs) of Acinetobacter, a common and highly abundant nectar bacterium, among visitor treatments. Visitation increased microbial abundance, but robbing resulted in 10× higher microbial abundance than pollination. Microbial communities differed among visitor treatments: robbed flowers were characterized by predominant nectar specialists within Acetobacteraceae and Metschnikowiaceae, with a concurrent loss of rare taxa, and these resulting communities harbored genes relating to osmotic stress, saccharide metabolism and specialized transporters. Gene differences were mirrored in function: robbed nectar contained a higher percentage of monosaccharides. Draft genomes of Acinetobacter revealed distinct amino acid and saccharide utilization pathways in strains isolated from robbed versus pollinated flowers. Our results suggest an unrecognized cost of nectar robbing for pollination and distinct effects of visitor type on interactions between plants and pollinators. Overall, these results suggest vector identity is an underappreciated factor structuring microbial community assembly and function.

Novel sequencing technologies to support industrial biotechnology

Industrial biotechnology develops and applies microorganisms for the production of bioproducts and enzymes with applications ranging from food and feed ingredients and processing to bio-based chemicals, biofuels and pharmaceutical products. Next generation DNA sequencing technologies play an increasingly important role in improving and accelerating microbial strain development for existing and novel bio-products via screening, gene and pathway discovery, metabolic engineering and additional optimization and understanding of large-scale manufacturing. In this mini-review, we describe novel DNA sequencing and analysis technologies with a focus on applications to industrial strain development, enzyme discovery and microbial community analysis.

Effect of Long-Term Farming Practices on Agricultural Soil Microbiome Members Represented by Metagenomically Assembled Genomes (MAGs) and Their Predicted Plant-Beneficial Genes

To follow the hypothesis that agricultural management practices affect structure and function of the soil microbiome regarding soil health and plant-beneficial traits, high-throughput (HT) metagenome analyses were performed on Chernozem soil samples from a long-term field experiment designated LTE-1 carried out at Bernburg-Strenzfeld (Saxony-Anhalt, Germany). Metagenomic DNA was extracted from soil samples representing the following treatments: (i) plough tillage with standard nitrogen fertilization and use of fungicides and growth regulators, (ii) plough tillage with reduced nitrogen fertilization (50%), (iii) cultivator tillage with standard nitrogen fertilization and use of fungicides and growth regulators, and (iv) cultivator tillage with reduced nitrogen fertilization (50%). Bulk soil (BS), as well as root-affected soil (RS), were considered for all treatments in replicates. HT-sequencing of metagenomic DNA yielded approx. 100 Giga bases (Gb) of sequence information. Taxonomic profiling of soil communities revealed the presence of 70 phyla, whereby Proteobacteria, Actinobacteria, Bacteroidetes, Planctomycetes, Acidobacteria, Thaumarchaeota, Firmicutes, Verrucomicrobia and Chloroflexi feature abundances of more than 1%. Functional microbiome profiling uncovered, i.a., numerous potential plant-beneficial, plant-growth-promoting and biocontrol traits predicted to be involved in nutrient provision, phytohormone synthesis, antagonism against pathogens and signal molecule synthesis relevant in microbe–plant interaction. Neither taxonomic nor functional microbiome profiling based on single-read analyses revealed pronounced differences regarding the farming practices applied. Soil metagenome sequences were assembled and taxonomically binned. The ten most reliable and abundant Metagenomically Assembled Genomes (MAGs) were taxonomically classified and metabolically reconstructed. Importance of the phylum Thaumarchaeota for the analyzed microbiome is corroborated by the fact that the four corresponding MAGs were predicted to oxidize ammonia (nitrification), thus contributing to the cycling of nitrogen, and in addition are most probably able to fix carbon dioxide. Moreover, Thaumarchaeota and several bacterial MAGs also possess genes with predicted functions in plant–growth–promotion. Abundances of certain MAGs (species resolution level) responded to the tillage practice, whereas the factors compartment (BS vs. RS) and nitrogen fertilization only marginally shaped MAG abundance profiles. Hence, soil management regimes promoting plant-beneficial microbiome members are very likely advantageous for the respective agrosystem, its health and carbon sequestration and accordingly may enhance plant productivity. Since Chernozem soils are highly fertile, corresponding microbiome data represent a valuable reference resource for agronomy in general.

Isolation of novel gut bifidobacteria using a combination of metagenomic and cultivation approaches

Whole metagenome shotgun (WMGS) sequencing is a method that provides insights into the genomic composition and arrangement of complex microbial consortia. Here, we report how WMGS coupled with a cultivation approach allows the isolation of novel bifidobacteria from animal fecal samples. A combination of in silico analyses based on nucleotide and protein sequences facilitate the identification of genetic material belonging to putative novel species. Consequently, the prediction of metabolic properties by in silico analyses permits the identification of specific substrates that are then employed to isolate these species through a cultivation method.

Taxonomic and Functional Characterization of the Microbial Community During Spontaneous in vitro Fermentation of Riesling Must

Although there is an extensive tradition of research into the microbes that underlie the winemaking process, much remains to be learnt. We combined the high-throughput sequencing (HTS) tools of metabarcoding and metagenomics, to characterize how microbial communities of Riesling musts sampled at four different vineyards, and their subsequent spontaneously fermented derivatives, vary. We specifically explored community variation relating to three points: (i) how microbial communities vary by vineyard; (ii) how community biodiversity changes during alcoholic fermentation; and (iii) how microbial community varies between musts that successfully complete alcoholic fermentation and those that become 'stuck' in the process. Our metabarcoding data showed a general influence of microbial composition at the vineyard level. Two of the vineyards (4 and 5) had strikingly a change in the differential abundance of Metschnikowia. We therefore additionally performed shotgun metagenomic sequencing on a subset of the samples to provide preliminary insights into the potential relevance of this observation, and used the data to both investigate functional potential and reconstruct draft genomes (bins). At these two vineyards, we also observed an increase in non-Saccharomycetaceae fungal functions, and a decrease in bacterial functions during the early fermentation stage. The binning results yielded 11 coherent bins, with both vineyards sharing the yeast bins Hanseniaspora and Saccharomyces. Read recruitment and functional analysis of this data revealed that during fermentation, a high abundance of Metschnikowia might serve as a biocontrol agent against bacteria, via a putative iron depletion pathway, and this in turn could help Saccharomyces dominate the fermentation. During alcoholic fermentation, we observed a general decrease in biodiversity in both the metabarcoding and metagenomic data. Unexpected Micrococcus behavior was observed in vineyard 4 according to metagenomic analyses based on reference-based read mapping. Analysis of open reading frames using these data showed an increase of functions assigned to class Actinobacteria in the end of fermentation. Therefore, we hypothesize that bacteria might sit-and-wait until Saccharomyces activity slows down. Complementary approaches to annotation instead of relying a single database provide more coherent information true species. Lastly, our metabarcoding data enabled us to identify a relationship between stuck fermentations and Starmerella abundance. Given that robust chemical analysis indicated that although the stuck samples contained residual glucose, all fructose had been consumed, we hypothesize that this was because fructophilic Starmerella, rather than Saccharomyces, dominated these fermentations. Overall, our results showcase the different ways in which metagenomic analyses can improve our understanding of the wine alcoholic fermentation process.

Taking Advantage of the Genomics Revolution for Monitoring and Conservation of Chondrichthyan Populations

Chondrichthyes (sharks, rays, skates and chimaeras) are among the oldest extant predators and are vital to top-down regulation of oceanic ecosystems. They are an ecologically diverse group occupying a wide range of habitats and are thus, exploited by coastal, pelagic and deep-water fishing industries. Chondrichthyes are among the most data deficient vertebrate species groups making design and implementation of regulatory and conservation measures challenging. High-throughput sequencing technologies have significantly propelled ecological investigations and understanding of marine and terrestrial species’ populations, but there remains a paucity of NGS based research on chondrichthyan populations. We present a brief review of current methods to access genomic and metagenomic data from Chondrichthyes and discuss applications of these datasets to increase our understanding of chondrichthyan taxonomy, evolution, ecology and population structures. Last, we consider opportunities and challenges offered by genomic studies for conservation and management of chondrichthyan populations.

Limited Correlation of Shotgun Metagenomics Following Host Depletion and Routine Diagnostics for Viruses and Bacteria in Low Concentrated Surrogate and Clinical Samples

The etiologic cause of encephalitis, meningitis or meningo-encephalitis is unknown in up to 70% of cases. Clinical shotgun metagenomics combined with host depletion is a promising technique to identify infectious etiologies of central nervous system (CNS) infections. We developed a straightforward eukaryotic host nucleic acid depletion method that preserves intact viruses and bacteria for subsequent shotgun metagenomics screening of clinical samples, focusing on cerebrospinal fluid (CSF). A surrogate CSF sample for a CNS infection paradigm was used to evaluate the proposed depletion method consisting of selective host cell lysis, followed by enzymatic degradation of the liberated genomic DNA for final depletion with paramagnetic beads. Extractives were subjected to reverse transcription, followed by whole genome amplification and next generation sequencing. The effectiveness of the host depletion method was demonstrated in surrogate CSF samples spiked with three 1:100 dilutions of Influenza A H3N2 virus (qPCR Ct-values 20.7, 28.8, >42/negative). Compared to the native samples, host depletion increased the amount of the virus subtype reads by factor 7127 and 132, respectively, while in the qPCR negative sample zero vs. 31 (1.4E-4 %) virus subtype reads were detected (native vs. depleted). The workflow was applied to thirteen CSF samples of patients with meningo-/encephalitis (two bacterial, eleven viral etiologies), a serum of an Andes virus infection and a nose swab of a common cold patient. Unlike surrogate samples, host depletion of the thirteen human CSF samples and the nose swab did not result in more reads indicating presence of damaged pathogens due to, e.g., host immune response. Nevertheless, previously diagnosed pathogens in the human CSF samples (six viruses, two bacteria), the serum, and the nose swab (Human rhinovirus A31) were detected in the depleted and/or the native samples. Unbiased evaluation of the taxonomic profiles supported the diagnosed pathogen in two native CSF samples and the native and depleted serum and nose swab, while detecting various contaminations that interfered with pathogen identification at low concentration levels. In summary, damaged pathogens and contaminations complicated analysis and interpretation of clinical shotgun metagenomics data. Still, proper consideration of these issues may enable future application of metagenomics for clinical diagnostics.

Identifying Group-Specific Sequences for Microbial Communities Using Long k-mer Sequence Signatures

Comparing metagenomic samples is crucial for understanding microbial communities. For different groups of microbial communities, such as human gut metagenomic samples from patients with a certain disease and healthy controls, identifying group-specific sequences offers essential information for potential biomarker discovery. A sequence that is present, or rich, in one group, but absent, or scarce, in another group is considered "group-specific" in our study. Our main purpose is to discover group-specific sequence regions between control and case groups as disease-associated markers. We developed a long k-mer (k ≥ 30 bps)-based computational pipeline to detect group-specific sequences at strain resolution free from reference sequences, sequence alignments, and metagenome-wide de novo assembly. We called our method MetaGO: Group-specific oligonucleotide analysis for metagenomic samples. An open-source pipeline on Apache Spark was developed with parallel computing. We applied MetaGO to one simulated and three real metagenomic datasets to evaluate the discriminative capability of identified group-specific markers. In the simulated dataset, 99.11% of group-specific logical 40-mers covered 98.89% disease-specific regions from the disease-associated strain. In addition, 97.90% of group-specific numerical 40-mers covered 99.61 and 96.39% of differentially abundant genome and regions between two groups, respectively. For a large-scale metagenomic liver cirrhosis (LC)-associated dataset, we identified 37,647 group-specific 40-mer features. Any one of the features can predict disease status of the training samples with the average of sensitivity and specificity higher than 0.8. The random forests classification using the top 10 group-specific features yielded a higher AUC (from ∼0.8 to ∼0.9) than that of previous studies. All group-specific 40-mers were present in LC patients, but not healthy controls. All the assembled 11 LC-specific sequences can be mapped to two strains of Veillonella parvula: UTDB1-3 and DSM2008. The experiments on the other two real datasets related to Inflammatory Bowel Disease and Type 2 Diabetes in Women consistently demonstrated that MetaGO achieved better prediction accuracy with fewer features compared to previous studies. The experiments showed that MetaGO is a powerful tool for identifying group-specific k-mers, which would be clinically applicable for disease prediction. MetaGO is available at https://github.com/VVsmileyx/MetaGO.