Dolosigranulum pigrum modulates immunity against SARS-CoV-2 in respiratory epithelial cells

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 in-crease 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.Fil: Islam, Md Aminul. Tohoku University; Japón. Bangladesh Agricultural University; BangladeshFil: Albarracín, Leonardo Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Centro de Referencia para Lactobacilos; ArgentinaFil: Melnikov, Vyacheslav. Gabrichevsky Research Institute for Epidemiology and Microbiology; RusiaFil: Andrade, Bruno G. N.. Munster Technological University; IrlandaFil: Cuadrat, Rafael R. C.. Berlín Institute for Medical Systems Biology; AlemaniaFil: Kitazawa, Haruki. Tohoku University; JapónFil: Villena, Julio Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Centro de Referencia para Lactobacilos; Argentin

Immunobiotic lactobacilli improve resistance of respiratory epithelial cells to sars-cov-2 infection

Previously, we reported that immunomodulatory lactobacilli, nasally administered, benefi-cially 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.Fil: Islam, Md Aminul. Tohoku University; JapónFil: Albarracín, Leonardo Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Centro de Referencia para Lactobacilos; ArgentinaFil: Tomokiyo, Mikado. Tohoku University; JapónFil: Valdéz, Juan Carlos. Universidad Nacional de Tucumán; ArgentinaFil: Sacur, Jacinto Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; ArgentinaFil: Vizoso Pinto, María Guadalupe. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; ArgentinaFil: Andrade, Bruno G. N.. No especifíca;Fil: Cuadrat, Rafael R. C.. No especifíca;Fil: Kitazawa, Haruki. Tohoku University; JapónFil: Villena, Julio Cesar. Tohoku University; Japón. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Centro de Referencia para Lactobacilos; Argentin

Identification and Characterization of Human Observational Studies in Nutritional Epidemiology on Gut Microbiomics for Joint Data Analysis

In any research field, data access and data integration are major challenges that even large, well-established consortia face. Although data sharing initiatives are increasing, joint data analyses on nutrition and microbiomics in health and disease are still scarce. We aimed to identify observational studies with data on nutrition and gut microbiome composition from the Intestinal Microbiomics (INTIMIC) Knowledge Platform following the findable, accessible, interoperable, and reusable (FAIR) principles. An adapted template from the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) consortium was used to collect microbiome-specific information and other related factors. In total, 23 studies (17 longitudinal and 6 cross-sectional) were identified from Italy (7), Germany (6), Netherlands (3), Spain (2), Belgium (1), and France (1) or multiple countries (3). Of these, 21 studies collected information on both dietary intake (24 h dietary recall, food frequency questionnaire (FFQ), or Food Records) and gut microbiome. All studies collected stool samples. The most often used sequencing platform was Illumina MiSeq, and the preferred hypervariable regions of the 16S rRNA gene were V3-V4 or V4. The combination of datasets will allow for sufficiently powered investigations to increase the knowledge and understanding of the relationship between food and gut microbiome in health and disease

Obesity Partially Mediates the Diabetogenic Effect of Lowering LDL Cholesterol

OBJECTIVE LDL cholesterol (LDLc)-lowering drugs modestly increase body weight and type 2 diabetes risk, but the extent to which the diabetogenic effect of lowering LDLc is mediated through increased BMI is unknown. RESEARCH DESIGN AND METHODS We conducted summary-level univariable and multivariable Mendelian randomization (MR) analyses in 921,908 participants to investigate the effect of lowering LDLc on type 2 diabetes risk and the proportion of this effect mediated through BMI. We used data from 92,532 participants from 14 observational studies to replicate findings in individual-level MR analyses. RESULTS A 1-SD decrease in genetically predicted LDLc was associated with increased type 2 diabetes odds (odds ratio [OR] 1.12 [95% CI 1.01, 1.24]) and BMI (b 5 0.07 SD units [95% CI 0.02, 0.12]) in univariable MR analyses. The multivariable MR analysis showed evidence of an indirect effect of lowering LDLc on type 2 diabetes through BMI (OR 1.04 [95% CI 1.01, 1.08]) with a proportion mediated of 38% of the total effect (P 5 0.03). Total and indirect effect estimates were similar across a number of sensitivity analyses. Individual-level MR analyses confirmed the indirect effect of lowering LDLc on type 2 diabetes through BMI with an estimated proportion mediated of 8% (P 5 0.04). CONCLUSIONS These findings suggest that the diabetogenic effect attributed to lowering LDLc is partially mediated through increased BMI. Our results could help advance understanding of adipose tissue and lipids in type 2 diabetes pathophysiology and inform strategies to reduce diabetes risk among individuals taking LDLc-lowering medications

Recovering Genomics Clusters of Secondary Metabolites from Lakes Using Genome-Resolved Metagenomics

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

Metagenomic Analysis of Upwelling-Affected Brazilian Coastal Seawater Reveals Sequence Domains of Type I PKS and Modular NRPS

Submitted by sandra infurna ([email protected]) on 2016-04-18T12:55:02Z No. of bitstreams: 1 rafael_cuadrat_etal_IOC_2015.pdf: 1349645 bytes, checksum: 1e9e4c31b62514366f2804feff5831d0 (MD5)Approved for entry into archive by sandra infurna ([email protected]) on 2016-04-18T13:08:57Z (GMT) No. of bitstreams: 1 rafael_cuadrat_etal_IOC_2015.pdf: 1349645 bytes, checksum: 1e9e4c31b62514366f2804feff5831d0 (MD5)Made available in DSpace on 2016-04-18T13:08:57Z (GMT). No. of bitstreams: 1 rafael_cuadrat_etal_IOC_2015.pdf: 1349645 bytes, checksum: 1e9e4c31b62514366f2804feff5831d0 (MD5) Previous issue date: 2015Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Computacional e Sistemas. Rio de Janeiro, RJ, Brasil / Leibniz-Institute of Freshwater Ecology and Inland Fisheries. Stechlin, Germany / Berlin Center for Genomics in Biodiversity Research. Berlin, Germany.Universidade Federal de São João del-Rei. Laboratório de Microbiologia Molecular. Sete Lagoas, MG, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Computacional e Sistemas. Rio de Janeiro, RJ, Brasil.Marine environments harbor a wide range of microorganisms from the three domains of life. These microorganisms have great potential to enable discovery of new enzymes and bioactive compounds for industrial use. However, only ~1% of microorganisms from the environment can currently be identified through cultured isolates, limiting the discovery of new compounds. To overcome this limitation, a metagenomics approach has been widely adopted for biodiversity studies on samples from marine environments. In this study, we screened metagenomes in order to estimate the potential for new natural compound synthesis mediated by diversity in the Polyketide Synthase (PKS) and Nonribosomal Peptide Synthetase (NRPS) genes. The samples were collected from the Praia dos Anjos (Angel’s Beach) surface water—Arraial do Cabo (Rio de Janeiro state, Brazil), an environment affected by upwelling. In order to evaluate the potential for screening natural products in Arraial do Cabo samples, we used KS (keto-synthase) and C (condensation) domains (from PKS and NRPS, respectively) to build Hidden Markov Models (HMM) models. From both samples, a total of 84 KS and 46 C novel domain sequences were obtained, showing the potential of this environment for the discovery of new genes of biotechnological interest. These domains were classified by phylogenetic analysis and this was the first study conducted to screen PKS and NRPS genes in an upwelling affected sample

Distribution and Classification of Serine β-Lactamases in Brazilian Hospital Sewage and Other Environmental Metagenomes Deposited in Public Databases

Submitted by Sandra Infurna ([email protected]) on 2017-02-23T16:17:17Z No. of bitstreams: 1 adriana_froes_etal_IOC_2016.pdf: 3634032 bytes, checksum: 7c46bcadcfb95fd20f649d9b3ebcd5df (MD5)Approved for entry into archive by Sandra Infurna ([email protected]) on 2017-02-23T16:27:21Z (GMT) No. of bitstreams: 1 adriana_froes_etal_IOC_2016.pdf: 3634032 bytes, checksum: 7c46bcadcfb95fd20f649d9b3ebcd5df (MD5)Made available in DSpace on 2017-02-23T16:27:21Z (GMT). No. of bitstreams: 1 adriana_froes_etal_IOC_2016.pdf: 3634032 bytes, checksum: 7c46bcadcfb95fd20f649d9b3ebcd5df (MD5) Previous issue date: 2016Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Computacional e Sistemas. Rio de Janeiro, RJ. Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Computacional e Sistemas. Rio de Janeiro, RJ. Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Computacional e Sistemas. Rio de Janeiro, RJ. Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Computacional e Sistemas. Rio de Janeiro, RJ. Brasil.β-lactam is the most used antibiotic class in the clinical area and it acts on blocking the bacteria cell wall synthesis, causing cell death. However, some bacteria have evolved resistance to these antibiotics mainly due the production of enzymes known as β-lactamases. Hospital sewage is an important source of dispersion of multidrug-resistant bacteria in rivers and oceans. In this work, we used next-generation DNA sequencing to explore the diversity and dissemination of serine β-lactamases in two hospital sewage from Rio de Janeiro, Brazil (South Zone, SZ and North Zone, NZ), presenting different profiles, and to compare them with public environmental data available. Also, we propose a Hidden-Markov-Model approach to screen potential serine β-lactamases genes (in public environments samples and generated hospital sewage data), exploring its evolutionary relationships. Due to the high variability in β-lactamases, we used a position-specific scoring matrix search method (RPS-BLAST) against conserved domain database profiles (CDD, Pfam, and COG) followed by visual inspection to detect conserved motifs, to increase the reliability of the results and remove possible false positives. We were able to identify novel β-lactamases from Brazilian hospital sewage and to estimate relative abundance of its types. The highest relative abundance found in SZ was the Class A (50%), while Class D is predominant in NZ (55%). CfxA (65%) and ACC (47%) types were the most abundant genes detected in SZ, while in NZ the most frequent were OXA-10 (32%), CfxA (28%), ACC (21%), CEPA (20%), and FOX (19%). Phylogenetic analysis revealed β-lactamases from Brazilian hospital sewage grouped in the same clade and close to sequences belonging to Firmicutes and Bacteroidetes groups, but distant from potential β-lactamases screened from public environmental data, that grouped closer to β-lactamases of Proteobacteria. Our results demonstrated that HMM-based approach identified homologs of serine β-lactamases, indicating the specificity and high sensitivity of this approach in large datasets, contributing for the identification and classification of a large number of homologous genes, comprising possible new ones. Phylogenetic analysis revealed the potential reservoir of β-lactam resistance genes in the environment, contributing to understanding the evolution and dissemination of these genes

Towards a Comprehensive Search of Putative Chitinases Sequences in Environmental Metagenomic Databases

Chitinases catalyze the hydrolysis of chitin, a linear homopolymer of β-(1,4)-linked N-acetylglucosamine. The broad range of applications of chitinolytic enzymes makes their identification and study very promising. Metagenomic approaches offer access to functional genes in uncultured representatives of the microbiota and hold great potential in the discovery of novel enzymes, but tools to extensively explore these data are still scarce. In this study, we develop a chitinase mining pipeline to facilitate the comprehensive search of these enzymes in environmental metagenomic databases and also to explore phylogenetic relationships among the retrieved sequences. In order to perform the analyses, UniprotKB fungal and bacterial chitinases sequences belonging to the glycoside hydrolases (GH) family-18, 19 and 20 were used to generate 15 reference datasets, which were then used to generate high quality seed alignments with the MAFFT program. Profile Hidden Markov Models (pHMMs) were built from each seed alignment using the hmmbuild program of HMMER v3.0 package. The best-hit sequences returned by hmmsearch against two environmental metagenomic databases (Community Cyberinfrastructure for Advanced Microbial Ecology Research and Analysis—CAMERA and Integrated Microbial Genomes—IMG/M) were retrieved and further analyzed. The NJ trees generated for each chitinase dataset showed some variability in the catalytic domain region of the metagenomic sequences and revealed common sequence patterns among all the trees. The scanning of the retrieved metagenomic sequences for chitinase conserved domains/signatures using both the InterPro and the RPS-BLAST tools confirmed the efficacy and sensitivity of our pHMM-based approach in detecting putative chitinases sequences. These analyses provide insight into the potential reservoir of novel molecules in metagenomic databases while supporting the chitinase mining pipeline developed in this work. By using our chitinase mining pipeline, a larger number of previously unannotated metagenomic chitinase sequences can be classified, enabling further studies on these enzymes

Table3.XLSX

<p>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.</p

Table2.XLSX

<p>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.</p