Biology subjects

Coutinho, F. H.

Publications and source records attributed to Coutinho, F. H..

6 recordsLinked to original sources

bioRxiv2025

Widespread and Abundant CRISPR-Cas Systems in the Deep Ocean

CRISPR-Cas systems have revolutionized modern biology. Most CRISPR-Cas systems in use for biotechnological applications derive from cultivated bacteria, but evidence suggests that environmental microbiomes harbor a large untapped diversity of these systems. Yet, our understanding of which environmental and biological factors drive the prevalence of CRISPR-Cas systems in the oceans remains limited. A search for CRISPR-Cas systems was conducted among 176 globally-distributed marine microbial metagenomes from the Malaspina expedition, which sampled both free-living and particle-attached microbiomes with emphasis on the deep ocean. We show that CRISPR-Cas systems are proportionally more abundant among microbiomes from the deep ocean than in the photic layers and among free-living microbes compared to those attached to particles, reflecting the higher concentrations of archaea and their viruses in these habitats. We identified 1,146 CRISPR-cas loci, some of which displayed unique loci architectures. From these loci, a total of 48 Cas9 proteins were identified, many of which are potentially novel. These discoveries expand the scope of CRISPR-Cas diversity and point at the deep-sea as a rich reservoir of these resources, which helps guide future bioprospecting efforts.

microbiology↗

bioRxiv2022

Water mass age structures the auxiliary metabolic gene content of free-living and particle-attached deep ocean viral communities

Viruses play important roles on the biogeochemical cycles that take place in the ocean.Yet, deep ocean viruses are one of the most under-explored fractions of the global biosphere. Little is known about the environmental factors that control the composition and functioning of their communities, or how they interact with their free-living or particle-attached microbial hosts. Thus, we analysed 58 viral communities associated to size fractionated free-living (0.2-0.8 m) and particle-attached (0.8-20 m) cellular metagenomes from bathypelagic (2,150-4,018 m deep) microbiomes obtained during the Malaspina expedition. These metagenomes yielded 6,631 viral sequences, 91% of which were novel, and 67 represented high-quality genomes. Taxonomic classification assigned 53% of the viral sequences to families of tailed viruses from the order Caudovirales. Computational host prediction associated 886 viral sequences to dominant members of the deep ocean microbiome, such as Alphaproteobacteria (284), Gammaproteobacteria (241), SAR324 (23), Marinisomatota (39), and Chloroflexota (61). Free-living and particle-attached viral communities had markedly distinct taxonomic composition, host prevalence, and auxiliary metabolic gene content, which led to the discovery of novel viral encoded metabolic genes involved in the folate and nucleotide metabolisms. Water mass age emerged as an important factor driving viral community composition. We postulated this was due to changes in quality and concentration of dissolved organic matter acting on the host communities, leading to an increase of viral auxiliary metabolic genes associated with energy metabolism among older water masses. These results shed light on the mechanisms by which environmental gradients of deep ocean ecosystems structure the composition and functioning of free-living and particle-attached viral communities.

microbiology↗

bioRxiv2022

iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes

The extraordinary diversity of viruses infecting bacteria and archaea is now primarily studied through metagenomics. While metagenomes enable high-throughput exploration of the viral sequence space, metagenome-derived genomes lack key information compared to isolated viruses, in particular host association. Different computational approaches are available to predict the host(s) of uncultivated viruses based on their genome sequences, but thus far individual approaches are limited either in precision or in recall, i.e. for a number of viruses they yield erroneous predictions or no prediction at all. Here we describe iPHoP, a two-step framework that integrates multiple methods to provide host predictions for a broad range of viruses while retaining a low (<10%) false-discovery rate. Based on a large database of metagenome-derived virus genomes, we illustrate how iPHoP can provide extensive host prediction and guide further characterization of uncultivated viruses. iPHoP is available at https://bitbucket.org/srouxjgi/iphop, through a Bioconda recipe, and a Docker container.

microbiology↗

bioRxiv2021

Wide occurrence of putative mobilized colistin resistance genes in the human gut microbiome

BackgroundThe high incidence of bacterial genes that confer resistance to last-resort antibiotics, such as colistin caused by MCR genes, poses an unprecedented threat to our civilizations health. To understand the spread, evolution, and distribution of such genes among human populations, with the final goal of diminishing their occurrence in human environments should be a priority. To tackle this problem, we investigated the distribution and prevalence of potential mcr genes in the human gut microbiome we used a set of bioinformatics tools to screen the Unified Human Gastrointestinal Genome (UHGG) collection for the presence, synteny and phylogeny of putative mcr genes, and co-located antibiotic resistance genes. ResultsA total of 2,079 ARGs were classified as different MCR in 2,046 Metagenome assembled genomes (MAGs), present in 1,596 individuals from 41 countries, of which 215 MCRs were identified in plasmidial contigs. The genera that presented the largest number of MCR-like genes were Suterella and Parasuterella, prevalent human gut bacteria of which Suterella wadsworthensis is associated with autism. Other potential pathogens carrying MCR genes belonged to the genus Vibrio, Escherichia and Campylobacter. Finally, we identified a total of 22,746 ARGs belonging to 21 different classes in the same 2,046 MAGs, suggesting multi-resistance potential in the corresponding bacterial strains, increasing the concern of ARGs impact in the clinical settings. ConclusionThis study uncovers the diversity of MCR-like genes in the human gut microbiome. We showed the cosmopolitan distribution of these genes in individuals worldwide and the co-presence of other antibiotic resistance genes, including Extended-spectrum beta-lactamases (ESBL). Also, we described mcr-like genes fused to a PAP2-like domain in S. wadsworthensis. Although these novel sequences increase our knowledge about the diversity and evolution of mcr-like genes, their activity and a potential colistin resistance in the corresponding strains has to be experimentally validated.

bioinformatics↗

bioRxiv2020

Nasopharyngeal microbial communities of patients infected with SARS-COV-2 that developed COVID-19.

BackgroundSARS-CoV-2 is an RNA virus causing COVID-19. The clinical characteristics and epidemiology of COVID-19 have been extensively investigated, however studies focused on the patients microbiota are still lacking. In this study, we investigated the nasopharyngeal microbiome composition of patients who developed different severity levels of COVID-19. We performed Rdna-SSU (16S) sequencing from nasopharyngeal swab samples obtained from SARS-CoV-2 positive (56) and negative (18) patients in the province of Alicante (Spain) in their first visit to the hospital. Positive SARS-CoV-2 patients were observed and later categorized in mild (symptomatic without hospitalization), moderate (hospitalization) and severe (admission to ICU). We compared the microbiome diversity and OTU composition among severity groups using Similarity Percentage (SIMPER) analysis and Maaslin2. We also built bacterial co-abundance networks for each group using Fastpar. ResultsStatistical analysis indicated differences in the nasopharyngeal microbiome of COVID19 patients. 62 OTUs were found exclusively in SARS-CoV-2 positive patients, mostly classified as members of the phylum Bacteroidetes (18) and Firmicutes (25). OTUs classified as Prevotella were found to be significantly more abundant in patients that developed more severe COVID-19. Furthemore, co-abundance analysis indicated a loss of network complexity among samples from patients that later developed more severe symptoms. ConclusionsOur preliminary study shows that the nasopharyngeal microbiome of COVID-19 patients showed differences in the composition of specific OTUs and complexity of co-abundance networks. These microbes with differential abundances among groups could serve as biomarkers for COVID-19 severity. Nevertheless, further studies with larger sample sizes should be conducted to validate these results. IMPORTANCEThis work has studied the microbiota of the nasopharyngeal tract in COVID19 patients using advanced techniques of molecular microbiology. Diverse microorganisms, most of which are harmless or even beneficial to the host, colonize the nasopharyngeal tract. These microorganisms are the microbiota, and they are present in every people. However, changes in this microbiota could be related to different diseases as cancer, gastrointestinal pathologies or even COVID19. This study has been performed to investigate the microbiota from patients with COVID19, in order to determinate its implication in the pathology severity. The results obtained showed that it is possible that several specific microorganisms are present only in patients with severe COVID19. These data, could be used as a prognostic biomarker to early detect whose patients will develop a severe COVID19 and improve their clinical management.

microbiology↗

bioRxiv2019

Robust taxonomic classification of uncharted microbial sequences and bins with CAT and BAT

Current-day metagenomics increasingly requires taxonomic classification of long DNA sequences and metagenome-assembled genomes (MAGs) of unknown microorganisms. We show that the standard best-hit approach often leads to classifications that are too specific. We present tools to classify high-quality metagenomic contigs (Contig Annotation Tool, CAT) and MAGs (Bin Annotation Tool, BAT) and thoroughly benchmark them with simulated metagenomic sequences that are classified against a reference database where related sequences are increasingly removed, thereby simulating increasingly unknown queries. We find that the query sequences are correctly classified at low taxonomic ranks if closely related organisms are present in the reference database, while classifications are made higher in the taxonomy when closely related organisms are absent, thus avoiding spurious classification specificity. In a real-world challenge, we apply BAT to over 900 MAGs from a recent rumen metagenomics study and classified 97% consistently with prior phylogeny-based classifications, but in a fully automated fashion.

bioinformatics↗