Optimization of lung tissue pre-treatment by bead homogenization for subsequent culturomics.

The discovery that the lung harbors a diverse microbiome, as revealed by next-generation sequencing, has significantly altered our understanding of respiratory health and disease. Despite the association between the lung microbiota and disease, the nature of their relationship remains poorly understood, and culture isolation of these microorganisms could help to determine their role in lung physiology. Current procedures for processing samples from the lower respiratory tract have been shown to affect the viability of microorganisms, so it is crucial to develop new methods to improve their survival. This study aimed to improve the isolation and characterization of lung microorganisms using a bead-beating homogenization method in a mouse model. Microsphere diameter and bead-beating time affected the survival of the microorganisms (E. coli, S. aureus and C. albicans). Using 2.3 mm diameter microspheres for 60 s of bead-beating promoted the survival of both bacteria and yeast strains. After intratracheal instillation of these microorganisms in mice, approximately 70% of the cells were recovered after the tissue homogenization. To assess the efficiency of the proposed method, the diversity of bacteria was compared between the homogenate and lung tissue samples. Ninety-one genera were detected in the lung tissue, and 63 in the homogenate. Bacterial genera detected in the homogenate represented 84% of the total abundance of the microbiota identified in the lung tissue. Taken together, these results demonstrate that the tissue homogenization process developed in this study recovered the majority of the microorganisms present in the lung. This study presents a bead-beating homogenization method for effective cultivation of lung tissue microorganisms, which may help to improve the understanding of host-microbe interactions in the lung.

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.