DeepMPTB: a vaginal microbiome-based deep neural network as artificial intelligence strategy for efficient preterm birth prediction.

In recent decades, preterm birth (PTB) has become a significant research focus in the healthcare field, as it is a leading cause of neonatal mortality worldwide. Using five independent study cohorts including 1290 vaginal samples from 561 pregnant women who delivered at term (n = 1029) or prematurely (n = 261), we analysed vaginal metagenomics data for precise microbiome structure characterization. Then, a deep neural network (DNN) was trained to predict term birth (TB) and PTB with an accuracy of 84.10% and an area under the receiver operating characteristic curve (AUROC) of 0.875 ± 0.11. During a benchmarking process, we demonstrated that our DL model outperformed seven currently used machine learning algorithms. Finally, our results indicate that overall diversity of the vaginal microbiota should be taken in account to predict PTB and not specific species. This artificial-intelligence based strategy should be highly helpful for clinicians in predicting preterm birth risk, allowing personalized assistance to address various health issues. DeepMPTB is open source and free for academic use. It is licensed under a GNU Affero General Public License 3.0 and is available at https://deepmptb.streamlit.app/ . Source code is available at https://github.com/oschakoory/DeepMPTB and can be easily installed using Docker ( https://www.docker.com/ ).

Applying targeted gene hybridization capture to viruses with a focus to SARS-CoV-2.

Although next-generation sequencing technologies are advancing rapidly, many research topics often require selective sequencing of genomic regions of interest. In addition, sequencing low-titre viruses is challenging, especially for coronaviruses, which are the largest RNA viruses. Prior to sequencing, enrichment of viral particles can help to significantly increase target sequence information as well as avoid large sequencing efforts and, consequently, can increase sensitivity and reduce sequencing costs. Targeting nucleic acids using capture by hybridization is another efficient method that can be performed by applying complementary probes (DNA or RNA baits) to directly enrich genetic information of interest while removing background non-target material. In studies where sequence capture by hybridization has been applied to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, most authors agree that this technique is useful to easily access sequence targets in complex samples. Furthermore, this approach allows for complete or near-complete sequencing of the viral genome, even in samples with low viral load or poor nucleic acid integrity. In addition, this strategy is highly efficient at discovering new variants by facilitating downstream investigations, such as phylogenetics, epidemiology, and evolution. Commercial kits, as well as in-house protocols, have been developed for enrichment of viral sequences. However, these kits have multiple variations in procedure, with differences in performance. This review compiles and describes studies in which hybridization capture has been applied to SARS-CoV-2 variant genomes.

Targeted 16S rRNA Gene Capture by Hybridization and Bioinformatic Analysis.

Next-generation sequencing technologies have impressively unlocked capacities to depict the complexity of microbial communities. Microbial community structure is for now routinely monitored by sequencing of 16S rRNA gene, a phylogenetic marker almost conserved among bacteria and archaea. Nevertheless, amplicon sequencing, the most popular used approach, suffers from several biases impacting the picture of microbial communities. Here, we describe an innovative method based on gene capture by hybridization for the targeted enrichment of 16S rDNA biomarker from metagenomic samples. Coupled to near full-length 16S rDNA reconstruction, this approach enables an exhaustive and accurate description of microbial communities by enhancing taxonomic and phylogenetic resolutions. Furthermore, access of captured 16S flanking regions opens link between structure and function in microbial communities.

The Arabidopsis thaliana-Streptomyces Interaction Is Controlled by the Metabolic Status of the Holobiont.

How specific interactions between plant and pathogenic, commensal, or mutualistic microorganisms are mediated and how bacteria are selected by a plant are important questions to address. Here, an Arabidopsis thaliana mutant called chs5 partially deficient in the biogenesis of isoprenoid precursors was shown to extend its metabolic remodeling to phenylpropanoids and lipids in addition to carotenoids, chlorophylls, and terpenoids. Such a metabolic profile was concomitant to increased colonization of the phyllosphere by the pathogenic strain Pseudomonas syringae pv. tomato DC3000. A thorough microbiome analysis by 16S sequencing revealed that Streptomyces had a reduced colonization potential in chs5. This study revealed that the bacteria-Arabidopsis interaction implies molecular processes impaired in the chs5 mutant. Interestingly, our results revealed that the metabolic status of A. thaliana was crucial for the specific recruitment of Streptomyces into the microbiota. More generally, this study highlights specific as well as complex molecular interactions that shape the plant microbiota.

RiboTaxa: combined approaches for rRNA genes taxonomic resolution down to the species level from metagenomics data revealing novelties.

Metagenomic classifiers are widely used for the taxonomic profiling of metagenomics data and estimation of taxa relative abundance. Small subunit rRNA genes are a gold standard for phylogenetic resolution of microbiota, although the power of this marker comes down to its use as full-length. We aimed at identifying the tools that can efficiently lead to taxonomic resolution down to the species level. To reach this goal, we benchmarked the performance and accuracy of rRNA-specialized versus general-purpose read mappers, reference-targeted assemblers and taxonomic classifiers. We then compiled the best tools (BBTools, FastQC, SortMeRNA, MetaRib, EMIRGE, VSEARCH, BBMap and QIIME 2's Sklearn classifier) to build a pipeline called RiboTaxa. Using metagenomics datasets, RiboTaxa gave the best results compared to other tools (i.e. Kraken2, Centrifuge, METAXA2, phyloFlash, SPINGO, BLCA, MEGAN) with precise taxonomic identification and relative abundance description without false positive detection (F-measure of 100% and 83.7% at genus level and species level, respectively). Using real datasets from various environments (i.e. ocean, soil, human gut) and from different approaches (e.g. metagenomics and gene capture by hybridization), RiboTaxa revealed microbial novelties not discerned by current bioinformatics analysis opening new biological perspectives in human and environmental health.

Fungal dye-decolorizing peroxidase diversity: roles in either intra- or extracellular processes.

Fungal dye-decolorizing peroxidases (DyPs) have found applications in the treatment of dye-contaminated industrial wastes or to improve biomass digestibility. Their roles in fungal biology are uncertain, although it has been repeatedly suggested that they could participate in lignin degradation and/or modification. Using a comprehensive set of 162 fully sequenced fungal species, we defined seven distinct fungal DyP clades on basis of a sequence similarity network. Sequences from one of these clades clearly diverged from all others, having on average the lower isoelectric points and hydropathy indices, the highest number of N-glycosylation sites, and N-terminal sequence peptides for secretion. Putative proteins from this clade are absent from brown-rot and ectomycorrhizal species that have lost the capability of degrading lignin enzymatically. They are almost exclusively present in white-rot and other saprotrophic Basidiomycota that digest lignin enzymatically, thus lending support for a specific role of DyPs from this clade in biochemical lignin modification. Additional nearly full-length fungal DyP genes were isolated from the environment by sequence capture by hybridization; they all belonged to the clade of the presumably secreted DyPs and to another related clade. We suggest focusing our attention on the presumably intracellular DyPs from the other clades, which have not been characterized thus far and could represent enzyme proteins with novel catalytic properties. KEY POINTS: • A fungal DyP phylogeny delineates seven main sequence clades. • Putative extracellular DyPs form a single clade of Basidiomycota sequences. • Extracellular DyPs are associated to white-rot fungi.

Capture by hybridization for full-length barcode-based eukaryotic and prokaryotic biodiversity inventories of deep sea ecosystems.

Biodiversity inventory of marine systems remains limited due to unbalanced access to the three ocean dimensions. The use of environmental DNA (eDNA) for metabarcoding allows fast and effective biodiversity inventory and is forecast as a future biodiversity research and biomonitoring tool. However, in poorly understood ecosystems, eDNA results remain difficult to interpret due to large gaps in reference databases and PCR bias limiting the detection of some major phyla. Here, we aimed to circumvent these limitations by avoiding PCR and recollecting larger DNA fragments to improve assignment of detected taxa through phylogenetic reconstruction. We applied capture by hybridization (CBH) to enrich DNA from deep-sea sediment samples and compared the results with those obtained through an up-to-date metabarcoding PCR-based approach (MTB). Originally developed for bacterial communities and targeting 16S rDNA, the CBH approach was applied to 18S rDNA to improve the detection of species forming benthic communities of eukaryotes, with a particular focus on metazoans. The results confirmed the possibility of extending CBH to metazoans with two major advantages: (i) CBH revealed a broader spectrum of prokaryotic, eukaryotic, and particularly metazoan diversity, and (ii) CBH allowed much more robust phylogenetic reconstructions of full-length barcodes with up to 1900 base pairs. This is particularly important for taxa whose assignment is hampered by gaps in reference databases. This study provides a database and probes to apply 18S CBH to diverse marine systems, confirming this promising new tool to improve biodiversity assessments in data-poor ecosystems such as those in the deep sea.

Revealing microbial species diversity using sequence capture by hybridization.

Targeting small parts of the 16S rDNA phylogenetic marker by metabarcoding reveals microorganisms of interest but cannot achieve a taxonomic resolution at the species level, precluding further precise characterizations. To identify species behind operational taxonomic units (OTUs) of interest, even in the rare biosphere, we developed an innovative strategy using gene capture by hybridization. From three OTU sequences detected upon polyphenol supplementation and belonging to the rare biosphere of the human gut microbiota, we revealed 59 nearly full-length 16S rRNA genes, highlighting high bacterial diversity hidden behind OTUs while evidencing novel taxa. Inside each OTU, revealed 16S rDNA sequences could be highly distant from each other with similarities down to 85 %. We identified one new family belonging to the order Clostridiales, 39 new genera and 52 novel species. Related bacteria potentially involved in polyphenol degradation have also been identified through genome mining and our results suggest that the human gut microbiota could be much more diverse than previously thought.

Microbial Diversity Under the Influence of Natural Gas Storage in a Deep Aquifer.

Deep aquifers (up to 2km deep) contain massive volumes of water harboring large and diverse microbial communities at high pressure. Aquifers are home to microbial ecosystems that participate in physicochemical balances. These microorganisms can positively or negatively interfere with subsurface (i) energy storage (CH4 and H2), (ii) CO2 sequestration; and (iii) resource (water, rare metals) exploitation. The aquifer studied here (720m deep, 37°C, 88bar) is naturally oligotrophic, with a total organic carbon content of <1mg.L-1 and a phosphate content of 0.02mg.L-1. The influence of natural gas storage locally generates different pressures and formation water displacements, but it also releases organic molecules such as monoaromatic hydrocarbons at the gas/water interface. The hydrocarbon biodegradation ability of the indigenous microbial community was evaluated in this work. The in situ microbial community was dominated by sulfate-reducing (e.g., Sva0485 lineage, Thermodesulfovibriona, Desulfotomaculum, Desulfomonile, and Desulfovibrio), fermentative (e.g., Peptococcaceae SCADC1_2_3, Anaerolineae lineage and Pelotomaculum), and homoacetogenic bacteria ("Candidatus Acetothermia") with a few archaeal representatives (e.g., Methanomassiliicoccaceae, Methanobacteriaceae, and members of the Bathyarcheia class), suggesting a role of H2 in microenvironment functioning. Monoaromatic hydrocarbon biodegradation is carried out by sulfate reducers and favored by concentrated biomass and slightly acidic conditions, which suggests that biodegradation should preferably occur in biofilms present on the surfaces of aquifer rock, rather than by planktonic bacteria. A simplified bacterial community, which was able to degrade monoaromatic hydrocarbons at atmospheric pressure over several months, was selected for incubation experiments at in situ pressure (i.e., 90bar). These showed that the abundance of various bacterial genera was altered, while taxonomic diversity was mostly unchanged. The candidate phylum Acetothermia was characteristic of the community incubated at 90bar. This work suggests that even if pressures on the order of 90bar do not seem to select for obligate piezophilic organisms, modifications of the thermodynamic equilibria could favor different microbial assemblages from those observed at atmospheric pressure.

Exploring the Diversity of Fungal DyPs in Mangrove Soils to Produce and Characterize Novel Biocatalysts.

The functional diversity of the New Caledonian mangrove sediments was examined, observing the distribution of fungal dye-decolorizing peroxidases (DyPs), together with the complete biochemical characterization of the main DyP. Using a functional metabarcoding approach, the diversity of expressed genes encoding fungal DyPs was investigated in surface and deeper sediments, collected beneath either Avicennia marina or Rhizophora stylosa trees, during either the wet or the dry seasons. The highest DyP diversity was observed in surface sediments beneath the R. stylosa area during the wet season, and one particular operational functional unit (OFU1) was detected as the most abundant DyP isoform. This OFU was found in all sediment samples, representing 51-100% of the total DyP-encoding sequences in 70% of the samples. The complete cDNA sequence corresponding to this abundant DyP (OFU 1) was retrieved by gene capture, cloned, and heterologously expressed in Pichia pastoris. The recombinant enzyme, called DyP1, was purified and characterized, leading to the description of its physical-chemical properties, its ability to oxidize diverse phenolic substrates, and its potential to decolorize textile dyes; DyP1 was more active at low pH, though moderately stable over a wide pH range. The enzyme was very stable at temperatures up to 50 °C, retaining 60% activity after 180 min incubation. Its ability to decolorize industrial dyes was also tested on Reactive Blue 19, Acid Black, Disperse Blue 79, and Reactive Black 5. The effect of hydrogen peroxide and sea salt on DyP1 activity was studied and compared to what is reported for previously characterized enzymes from terrestrial and marine-derived fungi.

Food Chemicals Disrupt Human Gut Microbiota Activity And Impact Intestinal Homeostasis As Revealed By In Vitro Systems.

Growing evidence indicates that the human gut microbiota interacts with xenobiotics, including persistent organic pollutants and foodborne chemicals. The toxicological relevance of the gut microbiota-pollutant interplay is of great concern since chemicals may disrupt gut microbiota functions, with a potential impairment of host homeostasis. Herein we report within batch fermentation systems the impact of food contaminants (polycyclic aromatic hydrocarbons, polychlorobiphenyls, brominated flame retardants, dioxins, pesticides and heterocyclic amines) on the human gut microbiota by metatranscriptome and volatolome i.e. "volatile organic compounds" analyses. Inflammatory host cell response caused by microbial metabolites following the pollutants-gut microbiota interaction, was evaluated on intestinal epithelial TC7 cells. Changes in the volatolome pattern analyzed via solid-phase microextraction coupled to gas chromatography-mass spectrometry mainly resulted in an imbalance in sulfur, phenolic and ester compounds. An increase in microbial gene expression related to lipid metabolism processes as well as the plasma membrane, periplasmic space, protein kinase activity and receptor activity was observed following dioxin, brominated flame retardant and heterocyclic amine exposure. Conversely, all food contaminants tested induced a decreased in microbial transcript levels related to ribosome, translation and nucleic acid binding. Finally, we demonstrated that gut microbiota metabolites resulting from pollutant disturbances may promote the establishment of a pro-inflammatory state in the gut, as stated with the release of cytokine IL-8 by intestinal epithelial cells.

Comparing 16S rDNA amplicon sequencing and hybridization capture for pea aphid microbiota diversity analysis.

OBJECTIVE: Targeted sequencing of 16S rDNA amplicons is routinely used for microbial community profiling but this method suffers several limitations such as bias affinity of universal primers and short read size. Gene capture by hybridization represents a promising alternative. Here we used a metagenomic extract from the pea aphid Acyrthosiphon pisum to compare the performances of two widely used PCR primer pairs with DNA capture, based on solution hybrid selection. RESULTS: All methods produced an exhaustive description of the 8 bacterial taxa known to be present in this sample. In addition, the methods yielded similar quantitative results, with the number of reads strongly correlating with quantitative PCR controls. Both methods can thus be considered as qualitatively and quantitatively robust on such a sample with low microbial complexity.

ASaiM: a Galaxy-based framework to analyze microbiota data.

Background: New generations of sequencing platforms coupled to numerous bioinformatics tools have led to rapid technological progress in metagenomics and metatranscriptomics to investigate complex microorganism communities. Nevertheless, a combination of different bioinformatic tools remains necessary to draw conclusions out of microbiota studies. Modular and user-friendly tools would greatly improve such studies. Findings: We therefore developed ASaiM, an Open-Source Galaxy-based framework dedicated to microbiota data analyses. ASaiM provides an extensive collection of tools to assemble, extract, explore, and visualize microbiota information from raw metataxonomic, metagenomic, or metatranscriptomic sequences. To guide the analyses, several customizable workflows are included and are supported by tutorials and Galaxy interactive tours, which guide users through the analyses step by step. ASaiM is implemented as a Galaxy Docker flavour. It is scalable to thousands of datasets but also can be used on a normal PC. The associated source code is available under Apache 2 license at https://github.com/ASaiM/framework and documentation can be found online (http://asaim.readthedocs.io). Conclusions: Based on the Galaxy framework, ASaiM offers a sophisticated environment with a variety of tools, workflows, documentation, and training to scientists working on complex microorganism communities. It makes analysis and exploration analyses of microbiota data easy, quick, transparent, reproducible, and shareable.

Chloromethane formation and degradation in the fern phyllosphere.

Chloromethane (CH3Cl) is the most abundant halogenated trace gas in the atmosphere. It plays an important role in natural stratospheric ozone destruction. Current estimates of the global CH3Cl budget are approximate. The strength of the CH3Cl global sink by microbial degradation in soils and plants is under discussion. Some plants, particularly ferns, have been identified as substantial emitters of CH3Cl. Their ability to degrade CH3Cl remains uncertain. In this study, we investigated the potential of leaves from 3 abundant ferns (Osmunda regalis, Cyathea cooperi, Dryopteris filix-mas) to produce and degrade CH3Cl by measuring their production and consumption rates and their stable carbon and hydrogen isotope signatures. Investigated ferns are able to degrade CH3Cl at rates from 2.1 to 17 and 0.3 to 0.9µggdw-1day-1 for C. cooperi and D. filix-mas respectively, depending on CH3Cl supplementation and temperature. The stable carbon isotope enrichment factor of remaining CH3Cl was -39±13‰, whereas negligible isotope fractionation was observed for hydrogen (-8±19‰). In contrast, O. regalis did not consume CH3Cl, but produced it at rates ranging from 0.6 to 128µggdw-1day-1, with stable isotope values of -97±8‰ for carbon and -202±10‰ for hydrogen, respectively. Even though the 3 ferns showed clearly different formation and consumption patterns, their leaf-associated bacterial diversity was not notably different. Moreover, we did not detect genes associated with the only known chloromethane utilization pathway "cmu" in the microbial phyllosphere of the investigated ferns. Our study suggests that still unknown CH3Cl biodegradation processes on plants play an important role in global cycling of atmospheric CH3Cl.

Hybridization capture reveals microbial diversity missed using current profiling methods.

BACKGROUND: Microorganisms comprise the majority of living organisms on our planet. For many years, exploration of the composition of microbial communities has been performed through the PCR-based study of the small subunit rRNA gene due to its high conservation across the domains of life. The application of this method has resulted in the discovery of many unexpected evolutionary lineages. However, amplicon sequencing is subject to numerous biases, with some taxa being missed, and is limited by the read length of second-generation sequencing platforms, which drastically reduces the phylogenetic resolution. RESULTS: Here, we describe a hybridization capture strategy that allows the enrichment of 16S rRNA genes from metagenomic samples and enables an exhaustive identification and a complete reconstruction of the biomarker. Applying this approach to a microbial mock community and a soil sample, we demonstrated that hybridization capture is able to reveal greater microbial diversity than 16S rDNA amplicon sequencing and shotgun sequencing. The reconstruction of full-length 16S rRNA genes facilitated the improvement of phylogenetic resolution and the discovery of novel prokaryotic taxa. CONCLUSIONS: Our results demonstrate that hybridization capture can lead to major breakthroughs in our understanding of microbial diversity, overcoming the limitations of conventional 16S rRNA gene studies. If applied to a broad range of environmental samples, this innovative approach could reveal the undescribed diversity of the still underexplored microbial communities and could provide a better understanding of ecosystem function.

FibroChip, a Functional DNA Microarray to Monitor Cellulolytic and Hemicellulolytic Activities of Rumen Microbiota.

Ruminants fulfill their energy needs for growth primarily through microbial breakdown of plant biomass in the rumen. Several biotic and abiotic factors influence the efficiency of fiber degradation, which can ultimately impact animal productivity and health. To provide more insight into mechanisms involved in the modulation of fibrolytic activity, a functional DNA microarray targeting genes encoding key enzymes involved in cellulose and hemicellulose degradation by rumen microbiota was designed. Eight carbohydrate-active enzyme (CAZyme) families (GH5, GH9, GH10, GH11, GH43, GH48, CE1, and CE6) were selected which represented 392 genes from bacteria, protozoa, and fungi. The DNA microarray, designated as FibroChip, was validated using targets of increasing complexity and demonstrated sensitivity and specificity. In addition, FibroChip was evaluated for its explorative and semi-quantitative potential. Differential expression of CAZyme genes was evidenced in the rumen bacterium Fibrobacter succinogenes S85 grown on wheat straw or cellobiose. FibroChip was used to identify the expressed CAZyme genes from the targeted families in the rumen of a cow fed a mixed diet based on grass silage. Among expressed genes, those encoding GH43, GH5, and GH10 families were the most represented. Most of the F. succinogenes genes detected by the FibroChip were also detected following RNA-seq analysis of RNA transcripts obtained from the rumen fluid sample. Use of the FibroChip also indicated that transcripts of fiber degrading enzymes derived from eukaryotes (protozoa and anaerobic fungi) represented a significant proportion of the total microbial mRNA pool. FibroChip represents a reliable and high-throughput tool that enables researchers to monitor active members of fiber degradation in the rumen.

PtxtPME1 and homogalacturonans influence xylem hydraulic properties in poplar.

While the xylem hydraulic properties, such as vulnerability to cavitation (VC), are of paramount importance in drought resistance, their genetic determinants remain unexplored. There is evidence that pectins and their methylation pattern are involved, but the detail of their involvement and the corresponding genes need to be clarified. We analyzed the hydraulic properties of the 35S::PME1 transgenic aspen that ectopically under- or over-express a xylem-abundant pectin methyl esterase, PtxtPME1. We also produced and analyzed 4CL1::PGII transgenic poplars expressing a fungal polygalacturonase, AnPGII, under the control of the Ptxa4CL1 promoter that is active in the developing xylem after xylem cell expansion. Both the 35S::PME1 under- and over-expressing aspen lines developed xylem with lower-specific hydraulic conductivity and lower VC, while the 4CL1::PGII plants developed xylem with a higher VC. These xylem hydraulic changes were associated with modifications in xylem structure or in intervessel pit structure that can result in changes in mechanical behavior of the pit membrane. This study shows that homogalacturonans and their methylation pattern influence xylem hydraulic properties, through its effect on xylem cell expansion and on intervessel pit properties and it show a role for PtxtPME1 in the xylem hydraulic properties.

Environmental Pollutant Benzo[a]Pyrene Impacts the Volatile Metabolome and Transcriptome of the Human Gut Microbiota.

Benzo[a]pyrene (B[a]P) is a ubiquitous, persistent, and carcinogenic pollutant that belongs to the large family of polycyclic aromatic hydrocarbons. Population exposure primarily occurs via contaminated food products, which introduces the pollutant to the digestive tract. Although the metabolism of B[a]P by host cells is well known, its impacts on the human gut microbiota, which plays a key role in health and disease, remain unexplored. We performed an in vitro assay using 16S barcoding, metatranscriptomics and volatile metabolomics to study the impact of B[a]P on two distinct human fecal microbiota. B[a]P exposure did not induce a significant change in the microbial structure; however, it altered the microbial volatolome in a dose-dependent manner. The transcript levels related to several metabolic pathways, such as vitamin and cofactor metabolism, cell wall compound metabolism, DNA repair and replication systems, and aromatic compound metabolism, were upregulated, whereas the transcript levels related to the glycolysis-gluconeogenesis pathway and bacterial chemotaxis toward simple carbohydrates were downregulated. These primary findings show that food pollutants, such as B[a]P, alter human gut microbiota activity. The observed shift in the volatolome demonstrates that B[a]P induces a specific deviation in the microbial metabolism.

OCaPPI-Db: an oligonucleotide probe database for pathogen identification through hybridization capture.

The detection and identification of bacterial pathogens involved in acts of bio- and agroterrorism are essential to avoid pathogen dispersal in the environment and propagation within the population. Conventional molecular methods, such as PCR amplification, DNA microarrays or shotgun sequencing, are subject to various limitations when assessing environmental samples, which can lead to inaccurate findings. We developed a hybridization capture strategy that uses a set of oligonucleotide probes to target and enrich biomarkers of interest in environmental samples. Here, we present Oligonucleotide Capture Probes for Pathogen Identification Database (OCaPPI-Db), an online capture probe database containing a set of 1,685 oligonucleotide probes allowing for the detection and identification of 30 biothreat agents up to the species level. This probe set can be used in its entirety as a comprehensive diagnostic tool or can be restricted to a set of probes targeting a specific pathogen or virulence factor according to the user's needs. Database URL: : http://ocappidb.uca.works.

Revealing large metagenomic regions through long DNA fragment hybridization capture.

BACKGROUND: High-throughput DNA sequencing technologies have revolutionized genomic analysis, including the de novo assembly of whole genomes from single organisms or metagenomic samples. However, due to the limited capacity of short-read sequence data to assemble complex or low coverage regions, genomes are typically fragmented, leading to draft genomes with numerous underexplored large genomic regions. Revealing these missing sequences is a major goal to resolve concerns in numerous biological studies. METHODS: To overcome these limitations, we developed an innovative target enrichment method for the reconstruction of large unknown genomic regions. Based on a hybridization capture strategy, this approach enables the enrichment of large genomic regions allowing the reconstruction of tens of kilobase pairs flanking a short, targeted DNA sequence. RESULTS: Applied to a metagenomic soil sample targeting the linA gene, the biomarker of hexachlorocyclohexane (HCH) degradation, our method permitted the enrichment of the gene and its flanking regions leading to the reconstruction of several contigs and complete plasmids exceeding tens of kilobase pairs surrounding linA. Thus, through gene association and genome reconstruction, we identified microbial species involved in HCH degradation which constitute targets to improve biostimulation treatments. CONCLUSIONS: This new hybridization capture strategy makes surveying and deconvoluting complex genomic regions possible through large genomic regions enrichment and allows the efficient exploration of metagenomic diversity. Indeed, this approach enables to assign identity and function to microorganisms in natural environments, one of the ultimate goals of microbial ecology.