BackgroundSARS-CoV-2 is an RNA virus causing COVID-19. The clinical characteristics and epidemiology of COVID-19 have been extensively investigated, however, only one study so far focused on the patient’s nasopharynx microbiota. In this study we investigated the nasopharynx microbial community of patients that developed different severity levels of COVID-19. We performed 16S ribosomal DNA 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 microbiota diversity and OTU composition among severity groups and built bacterial co-abundance networks for each group.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 Bacteroidota (18) and Firmicutes (25). OTUs classified as Prevotella were found to be significantly more abundant in patients that developed more severe COVID-19. Furthermore, co-abundance analysis indicated a loss of network complexity among samples from patients that later developed more severe symptoms.ConclusionOur study shows that the nasopharyngeal microbiome of COVID-19 patients showed differences in the composition of specific OTUs and complexity of co-abundance networks. Taxa 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.
Background The rise of antibiotic resistance (AR) in clinical settings is of great concern. Therefore, the understanding of AR mechanisms, evolution, and global distribution is a priority for patient survival. Despite all efforts in the elucidation of AR mechanisms in clinical strains, little is known about its prevalence and evolution in environmental microorganisms. We used 293 metagenomic samples from the TARA Oceans project to detect and quantify environmental antibiotic resistance genes (ARGs) using machine learning tools. Results After manual curation of ARGs, their abundance and distribution in the global ocean are presented. Additionally, the potential of horizontal ARG transfer by plasmids and their correlation with environmental and geographical parameters is shown. A total of 99,205 environmental open reading frames (ORFs) were classified as 1 of 560 different ARGs conferring resistance to 26 antibiotic classes. We found 24,567 ORFs in putative plasmid sequences, suggesting the importance of mobile genetic elements in the dynamics of environmental ARG transmission. Moreover, 4,804 contigs with >=2 putative ARGs were found, including 2 plasmid-like contigs with 5 different ARGs, highlighting the potential presence of multi-resistant microorganisms in the natural ocean environment. Finally, we identified ARGs conferring resistance to some of the most relevant clinical antibiotics, revealing the presence of 15 ARGs similar to mobilized colistin resistance genes (mcr) with high abundance on polar biomes. Of these, 5 are assigned to Psychrobacter, a genus including opportunistic human pathogens. Conclusions This study uncovers the diversity and abundance of ARGs in the global ocean metagenome. Our results are available on Zenodo in MySQL database dump format, and all the code used for the analyses, including a Jupyter notebook js avaliable on Github. We also developed a dashboard web application (http://www.resistomedb.com) for data visualization.
Background: The success of different species of ruminants in the colonization of a diverse range of environments is due to their ability to digest and absorb nutrients from cellulose, a complex polysaccharide found in leaves and grass. Ruminants rely on a complex and diverse microbial community, or microbiota, in a unique compartment known as the rumen to break down this polysaccharide. Changes in microbial populations of the rumen can affect the host's development, health, and productivity. However, accessing the rumen is stressful for the animal. Therefore, the development and use of alternative sampling methods are needed if this technique is to be routinely used in cattle breeding. To this end, we tested if the fecal microbiome could be used as a proxy for the rumen microbiome due to its accessibility. We investigated the taxonomic composition, diversity and interrelations of two different GIT compartments, rumen and feces, of 26 Nelore (Bos indicus) bulls, using Next Generation Sequencing (NGS) metabarcoding of bacteria, archaea and ciliate protozoa. Results: We identified 4265 Amplicon Sequence Variants (ASVs) from bacteria, 571 from archaea, and 107 from protozoa, of which 143 (96 bacteria and 47 archaea) were found common between both microbiomes. The most prominent bacterial phyla identified were Bacteroidetes (41.48%) and Firmicutes (56.86%) in the ruminal and fecal microbiomes, respectively, with Prevotella and Ruminococcaceae UCG-005 the most relatively abundant genera identified in each microbiome. The most abundant archaeal phylum identified was Euryarchaeota, of which Methanobrevibacter gottschalkii, a methanogen, was the prevalent archaeal species identified in both microbiomes. Protozoa were found exclusively identified in the rumen with Bozasella/ Triplumaria being the most frequent genus identified. Co-occurrence among ruminal and fecal ASVs reinforces the relationship of microorganisms within a biological niche. Furthermore, the co-occurrence of shared archaeal ASVs between microbiomes indicates a dependency of the predominant fecal methanogen population on the rumen population.
Metagenomic approaches became increasingly popular in the past decades due to decreasing costs of DNA sequencing and bioinformatics development. So far, however, the recovery of long genes coding for secondary metabolites still represents a big challenge. Often, the quality of metagenome assemblies is poor, especially in environments with a high microbial diversity where sequence coverage is low and complexity of natural communities high. Recently, new and improved algorithms for binning environmental reads and contigs have been developed to overcome such limitations. Some of these algorithms use a similarity detection approach to classify the obtained reads into taxonomical units and to assemble draft genomes. This approach, however, is quite limited since it can classify exclusively sequences similar to those available (and well classified) in the databases. In this work, we used draft genomes from Lake Stechlin, north-eastern Germany, recovered by MetaBat, an efficient binning tool that integrates empirical probabilistic distances of genome abundance, and tetranucleotide frequency for accurate metagenome binning. These genomes were screened for secondary metabolism genes, such as polyketide synthases (PKS) and non-ribosomal peptide synthases (NRPS), using the Anti-SMASH and NAPDOS workflows. With this approach we were able to identify 243 secondary metabolite clusters from 121 genomes recovered from our lake samples. A total of 18 NRPS, 19 PKS, and 3 hybrid PKS/NRPS clusters were found. In addition, it was possible to predict the partial structure of several secondary metabolite clusters allowing for taxonomical classifications and phylogenetic inferences. Our approach revealed a high potential to recover and study secondary metabolites genes from any aquatic ecosystem.
In a previous work, we demonstrated that nasally administered Dolosigranulum pigrum 040417 beneficially modulated the respiratory innate immune response triggered by the activation of Toll-like receptor 3 (TLR3) and improved protection against Respiratory Syncytial Virus (RSV) in mice. In this work, we aimed to evaluate the immunomodulatory effects of D. pigrum 040417 in human respiratory epithelial cells and the potential ability of this immunobiotic bacterium to increase the protection against Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The respiratory commensal bacterium D. pigrum 040417 differentially modulated the production of IFN-β, IL-6, CXCL8, CCL5 and CXCL10 in the culture supernatants of Calu-3 cells stimulated with poly(I:C) or challenged with SARS-CoV-2. The differential cytokine profile induced by the 040417 strain was associated with a significant reduction in viral replication and cellular damage after coronavirus infection. Of note, D. pigrum 030918 was not able to modify the resistance of Calu-3 cells to SARS-CoV-2 infection, indicating a strain-specific immunomodulatory effect for respiratory commensal bacteria. The findings of this work improve our understanding of the immunological mechanisms involved in the modulation of respiratory immunity induced by respiratory commensal bacteria, by demonstrating their specific effect on respiratory epithelial cells. In addition, the results suggest that particular strains such as D. pigrum 040417 could be used as a promising alternative for combating SARS-CoV-2 and reducing the severity of COVID-19.
Estimated Δ5-desaturase (D5D) and Δ6-desaturase (D6D) are key enzymes in metabolism of polyunsaturated fatty acids (PUFA) and have been associated with cardiometabolic risk; however, causality needs to be clarified. We applied two-sample Mendelian randomization (MR) approach using a representative sub-cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC)–Potsdam Study and public data from DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) and Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) genome-wide association studies (GWAS). Furthermore, we addressed confounding by linkage disequilibrium (LD) as all instruments from FADS1 (encoding D5D) are in LD with FADS2 (encoding D6D) variants. Our univariable MRs revealed risk-increasing total effects of both, D6D and D5D on type 2 diabetes (T2DM) risk; and risk-increasing total effect of D6D on risk of coronary artery disease (CAD). The multivariable MR approach could not unambiguously allocate a direct causal effect to either of the individual desaturases. Our results suggest that D6D is causally linked to cardiometabolic risk, which is likely due to downstream production of fatty acids and products resulting from high D6D activity. For D5D, we found indication for causal effects on T2DM and CAD, which could, however, still be confounded by LD.
ProtozoaDB (http://www.biowebdb.org/protozoadb) is being developed to initially host both genomics and post-genomics data from Plasmodium falciparum, Entamoeba histolytica, Trypanosoma brucei, T. cruzi and Leishmania major, but will hopefully host other protozoan species as more genomes are sequenced. It is based on the Genomics Unified Schema and offers a modern Web-based interface for user-friendly data visualization and exploration. This database is not intended to duplicate other similar efforts such as GeneDB, PlasmoDB, TcruziDB or even TDRtargets, but to be complementary by providing further analyses with emphasis on distant similarities (HMM-based) and phylogeny-based annotations including orthology analysis. ProtozoaDB will be progressively linked to the above-mentioned databases, focusing in performing a multi-source dynamic combination of information through advanced interoperable Web tools such as Web services. Also, to provide Web services will allow third-party software to retrieve and use data from ProtozoaDB in automated pipelines (workflows) or other interoperable Web technologies, promoting better information reuse and integration. We also expect ProtozoaDB to catalyze the development of local and regional bioinformatics capabilities (research and training), and therefore promote/enhance scientific advancement in developing countries.
Previously, we reported that immunomodulatory lactobacilli, nasally administered, beneficially regulated the lung antiviral innate immune response induced by Toll-like receptor 3 (TLR3) activation and improved protection against the respiratory pathogens, influenza virus and respiratory syncytial virus in mice. Here, we assessed the immunomodulatory effects of viable and non-viable Lactiplantibacillus plantarum strains in human respiratory epithelial cells (Calu-3 cells) and the capacity of these immunobiotic lactobacilli to reduce their susceptibility to the acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Immunobiotic L. plantarum MPL16 and CRL1506 differentially modulated IFN-β, IL-6, CXCL8, CCL5 and CXCL10 production and IFNAR2, DDX58, Mx1 and OAS1 expression in Calu-3 cells stimulated with the TLR3 agonist poly(I:C). Furthermore, the MPL16 and CRL1506 strains increased the resistance of Calu-3 cells to the challenge with SARS-CoV-2. L. plantarum MPL16 induced these beneficial effects more efficiently than the CRL1506 strain. Of note, neither non-viable MPL16 and CRL1506 strains nor the non-immunomodulatory strains L. plantarum CRL1905 and MPL18 could modify the resistance of Calu-3 cells to SARS-CoV-2 infection or the immune response to poly(I:C) challenge. To date, the potential beneficial effects of immunomodulatory probiotics on SARS-CoV-2 infection and COVID-19 outcome have been extrapolated from studies carried out in the context of other viral pathogens. To the best of our knowledge, this is the first demonstration of the ability of immunomodulatory lactobacilli to positively influence the replication of the new coronavirus. Further mechanistic studies and in vivo experiments in animal models of SARS-CoV-2 infection are necessary to identify specific strains of beneficial immunobiotic lactobacilli like L. plantarum MPL16 or CRL1506 for the prevention or treatment of the COVID-19.
scite is a Brooklyn-based startup that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2023 scite Inc. All rights reserved.
Made with 💙 for researchers