Hybridization capture coupled to next-generation sequencing to explore metagenomic samples

Les microorganismes représentent la forme de vie la plus diverse et abondante sur Terre et jouent un rôle fondamental dans tous les processus biologiques. Cependant, du fait de la grande diversité des communautés microbiennes, la caractérisation fine des environnements complexes reste difficile par les approches moléculaires actuelles de PCR et de métagénomique. En effet, ces approches ne conduisent qu’à une caractérisation partielle des communautés et ne permettent pas systématiquement d’associer la structure des communautés aux fonctions métaboliques réalisées. L’approche de capture de gènes par hybridation appliquée à des échantillons métagénomiques complexes a démontré son intérêt pour révéler toute la diversité connue mais aussi inconnue des biomarqueurs fonctionnels ciblés, ainsi que pour enrichir leurs régions flanquantes sur quelques centaines de permettant en évidence des associations de gènes. Ainsi, les travaux de thèse ont visé à développer une nouvelle méthode de capture de gènes par hybridation capable d’enrichir de façon ciblée de larges régions génomiques à partir d’échantillons complexes, permettant ainsi de faire le lien entre structure et fonction des communautés microbiennes. Ces développements ont nécessité la détermination de sondes de capture, l’utilisation d’une méthode d’extraction d’ADN de haut poids moléculaire et la mise au point d’un protocole de capture permettant de piéger des fragments nucléiques de grande taille (jusqu’à 50 kb). La validation de la méthode de capture par hybridation sur un échantillon environnemental de sol a permis de révéler tout son potentiel. Appliquée au gène exprimant l’ARNr 16S, cette stratégie a permis de révéler une diversité microbienne non accessible par les approches moléculaires conventionnelles, avec une résolution d’identification jusqu'au niveau de l’espèce rendue possible grâce à la reconstruction de la séquence complète de ce marqueur phylogénétique. Appliquée à un gène fonctionnel, elle a conduit à la reconstruction de la séquence du biomarqueur et de ses régions flanquantes pouvant atteindre plusieurs dizaines de kb, permettant d’identifier les microorganismes possédant les capacités métaboliques d’intérêt. Ainsi, la capture par hybridation représente une approche alternative prometteuse pour le diagnostic environnemental en conduisant à une meilleure caractérisation des communautés microbiennes.Microorganisms are the most diverse and abundant life forms on Earth and are key players in thefunctioning of all biological processes. Nevertheless, PCR and metagenomics strategies aiming to describemicrobial communities are hampered by their huge diversity. Indeed, these molecular methods only drive to apartial description of communities and do not systematically allow linking functions back to the identities of themicroorganisms. Hybridization capture applied to complex metagenomic samples has demonstrated its efficiency to reveal all known and unknown diversity of targeted biomarkers, and to enrich their flanking regions over a few hundred bp facilitating the discovery of gene associations.Thus, this work aimed at developing a new hybridization capture method capable of specifically enrichinglarge genomic regions from complex samples allowing to associate structure and functions of communities. Thedevelopment of this method required the design of capture probes, the use of a high molecular weight DNAextraction method, and the elaboration of a capture protocol dedicated to the enrichment of large genomicfragments (up to 50 kbp).The validation of the hybridization capture method on an environmental soil sample uncovered all itspotential. Applied to the 16S rRNA gene, this strategy revealed greater microbial diversity than conventionalmolecular methods and improved phylogenetic resolution up to the species level thanks to the reconstruction offull-length genes. Applied to a functional gene, the method enabled the reconstruction of large genomic regionscarrying the targeted biomarker and its flanking regions over several tens of kbp, leading to the identification ofmicroorganisms with specific metabolic functions. Hybridization capture thus appears as a promising alternativemethod for environmental diagnosis, through providing a better knowledge of microbial communities

Hybridization capture reveals microbial diversity missed using current profiling methods

International audienceBackground: 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.& para;& para;Results: Here, we describe a hybridization capture strategy that allows the enrichment of 165 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.& para;& para;Conclusions: Our results demonstrate that hybridization capture can lead to major breakthroughs in our understanding of microbial diversity, overcoming the limitations of conventional 165 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

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

Additional file 1: of Hybridization capture reveals microbial diversity missed using current profiling methods

Figure S1. Schematic representation of the hybridization capture method. Figure S2. Mock community profiles at different taxonomic levels for 16S rRNA gene amplicon sequencing, hybridization capture, and shotgun sequencing. Figure S3. Soil prokaryote composition profiles at different taxonomic levels for 16S rRNA gene amplicon sequencing, hybridization capture, and shotgun sequencing. Figure S4. Phylogenetic position of an unassigned sequence to a new phylum. Figure S5. Phylogenetic position of an unassigned sequence to a new class belonging to the Gemmatimonadetes phylum. Figure S6. Phylogenetic position of an unassigned sequence to a new class belonging to the Chloroflexi phylum. Figure S7. Phylogenetic position of new unassigned sequences to the Saccharibacteria phylum. Table S1. Microbial mock community used for hybridization capture validation and 16S rDNA relative abundances observed using the three methods (amplicons, capture, and shotgun sequencing). Table S2. Set of probes targeting the 16S rRNA gene used for hybridization capture. (DOCX 4852 kb

Additional file 1: of Revealing large metagenomic regions through long DNA fragment hybridization capture

Word document that includes supplemental Figures S1 to S5 and Table S1. Table S1. Set of probes used for hybridization capture targeting linA. Figure S1. Schematic representation of large DNA fragment hybridization capture method. Figure S2. Hexachlorocyclohexane (HCH) degradation pathways. Figure S3. Coverage of the Sphingobium japonicum genome with reads obtained through hybridization capture and shotgun sequencing on the metagenomic soil sample. Figure S4. Coverage of the Novosphingobium barchaimii genome with reads obtained through hybridization capture and shotgun sequencing on the metagenomic soil sample. Figure S5. Coverage of the Sphingobium sp. TKS plasmid pTK4 with reads obtained through hybridization capture and shotgun sequencing on the metagenomic soil sample. (DOCX 1092 kb

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 agro-terrorism 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

Revealing microbial species diversity using sequence capture by hybridization

International audienceTargeting 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

Revealing large microbial species diversity hidden behind 16S rRNA OTUs obtained from metabarcoding

International audienceTargeting 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 OTUs of interest, and particularly those belonging to the rare biosphere, we developed an innovative strategy using gene capture by hybridization that allowed us to recover the corresponding full-length sequences. From three rare OTU sequences of the human gut microbiota which increased upon polyphenol supplementation, we designed specific probes to capture the adjacent sequences of these OTUs from metagenomic DNA libraries. The resulting OTU-enriched libraries were then sequenced and analysed. Using our approach, we revealed 59 nearly full-length 16S rRNA genes sharing ≥ 97% identity with the targeted OTUs and representing 35% of all the retrieved 16S rDNA genes. We highlighted high bacterial diversity hidden behind each OTU and revealed novel taxa. In total, we identified 1 new family belonging to the Clostridiales order, 39 new genera and 52 new species. From each OTU, the revealed 16S rDNA full-length sequences could be highly distant from each other with similarities down to 85%, underlying the poor link between OTU, species and their putative functions. Using a genome mining strategy, we found bacteria related to the novel 16S sequences that are potentially involved in polyphenol degradation. Overall, our results suggest that the human gut microbiota could be much more diverse than previously thought

A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog

International audienceThe human gut microbiota performs functions that are essential for the maintenance of the host physiology. However, characterizing the functioning of microbial communities in relation to the host remains challenging in reference-based metagenomic analyses. Indeed, as taxonomic and functional analyses are performed independently, the link between genes and species remains unclear. Although a first set of species-level bins was built by clustering coabundant genes, no reference bin set is established on the most used gut microbiota catalog, the Integrated Gene Catalog (IGC). With the aim to identify the best suitable method to group the IGC genes, we benchmarked nine taxonomy-independent binners implementing abundance-based, hybrid and integrative approaches. To this purpose, we designed a simulated non-redundant gene catalog (SGC) and computed adapted assessment metrics. Overall, the best trade-off between the main metrics is reached by an integrative binner. For each approach, we then compared the results of the best-performing binner with our expected community structures and applied the method to the IGC. The three approaches are distinguished by specific advantages, and by inherent or scalability limitations. Hybrid and integrative binners show promising and potentially complementary results but require improvements to be used on the IGC to recover human gut microbial species

Environmental pollutant benzo[a]pyrene impacts the volatile metabolome and transcriptome of the human gut microbiota

International audienc