15 research outputs found

    Induction of mastitis by cow-to-mouse fecal and milk microbiota transplantation causes microbiome dysbiosis and genomic functional perturbation in mice

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    BACKGROUND: Mastitis pathogenesis involves a wide range of opportunistic and apparently resident microorganims including bacteria, viruses and archaea. In dairy animals, microbes reside in the host, interact with environment and evade the host immune system, providing a potential for host-tropism to favor mastitis pathogenesis. To understand the host-tropism phenomena of bovine-tropic mastitis microbiomes, we developed a cow-to-mouse mastitis model. METHODS: A cow-to-mouse mastitis model was established by fecal microbiota transplantation (FMT) and milk microbiota transplantation (MMT) to pregnant mice to assess microbiome dysbiosis and genomic functional perturbations through shotgun whole metagenome sequencing (WMS) along with histopathological changes in mice mammary gland and colon tissues. RESULTS: The cow-to-mouse FMT and MMT from clinical mastitis (CM) cows induced mastitis syndromes in mice as evidenced by histopathological changes in mammary gland and colon tissues. The WMS of 24 samples including six milk (CM = 3, healthy; H = 3), six fecal (CM = 4, H = 2) samples from cows, and six fecal (CM = 4, H = 2) and six mammary tissue (CM = 3, H = 3) samples from mice generating 517.14 million reads (average: 21.55 million reads/sample) mapped to 2191 bacterial, 94 viral and 54 archaeal genomes. The Kruskal-Wallis test revealed significant differences (p = 0.009) in diversity, composition, and relative abundances in microbiomes between CM- and H-metagenomes. These differences in microbiome composition were mostly represented by Pseudomonas aeruginosa, Lactobacillus crispatus, Klebsiella oxytoca, Enterococcus faecalis, Pantoea dispersa in CM-cows (feces and milk), and Muribaculum spp., Duncaniella spp., Muribaculum intestinale, Bifidobacterium animalis, Escherichia coli, Staphylococcus aureus, Massilia oculi, Ralstonia pickettii in CM-mice (feces and mammary tissues). Different species of Clostridia, Bacteroida, Actinobacteria, Flavobacteriia and Betaproteobacteria had a strong co-occurrence and positive correlation as the indicator species of murine mastitis. However, both CM cows and mice shared few mastitis-associated microbial taxa (1.14%) and functional pathways regardless of conservation of mastitis syndromes, indicating the higher discrepancy in mastitis-associated microbiomes among lactating mammals. CONCLUSIONS: We successfully induced mastitis by FMT and MMT that resulted in microbiome dysbiosis and genomic functional perturbations in mice. This study induced mastitis in a mouse model through FMT and MMT, which might be useful for further studies- focused on pathogen(s) involved in mastitis, their cross-talk among themselves and the host

    Temporal dynamics and fatality of SARS‐CoV‐2 variants in Bangladesh

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    Abstract Background and Aims Since the beginning of the SARS‐CoV‐2 pandemic, multiple new variants have emerged posing an increased risk to global public health. This study aimed to investigate SARS‐CoV‐2 variants, their temporal dynamics, infection rate (IFR) and case fatality rate (CFR) in Bangladesh by analyzing the published genomes. Methods We retrieved 6610 complete whole genome sequences of the SARS‐CoV‐2 from the GISAID (Global Initiative on Sharing all Influenza Data) platform from March 2020 to October 2022, and performed different in‐silico bioinformatics analyses. The clade and Pango lineages were assigned by using Nextclade v2.8.1. SARS‐CoV‐2 infections and fatality data were collected from the Institute of Epidemiology Disease Control and Research (IEDCR), Bangladesh. The average IFR was calculated from the monthly COVID‐19 cases and population size while average CFR was calculated from the number of monthly deaths and number of confirmed COVID‐19 cases. Results SARS‐CoV‐2 first emerged in Bangladesh on March 3, 2020 and created three pandemic waves so far. The phylogenetic analysis revealed multiple introductions of SARS‐CoV‐2 variant(s) into Bangladesh with at least 22 Nextstrain clades and 107 Pangolin lineages with respect to the SARS‐CoV‐2 reference genome of Wuhan/Hu‐1/2019. The Delta variant was detected as the most predominant (48.06%) variant followed by Omicron (27.88%), Beta (7.65%), Alpha (1.56%), Eta (0.33%) and Gamma (0.03%) variant. The overall IFR and CFR from circulating variants were 13.59% and 1.45%, respectively. A time‐dependent monthly analysis showed significant variations in the IFR (p = 0.012, Kruskal–Wallis test) and CFR (p = 0.032, Kruskal–Wallis test) throughout the study period. We found the highest IFR (14.35%) in 2020 while Delta (20A) and Beta (20H) variants were circulating in Bangladesh. Remarkably, the highest CFR (1.91%) from SARS‐CoV‐2 variants was recorded in 2021. Conclusion Our findings highlight the importance of genomic surveillance for careful monitoring of variants of concern emergence to interpret correctly their relative IFR and CFR, and thus, for implementation of strengthened public health and social measures to control the spread of the virus. Furthermore, the results of the present study may provide important context for sequence‐based inference in SARS‐CoV‐2 variant(s) evolution and clinical epidemiology beyond Bangladesh

    Author Correction: Genome-wide analysis of SARS-CoV-2 virus strains circulating worldwide implicates heterogeneity (Scientific Reports, (2020), 10, 1, (14004), 10.1038/s41598-020-70812-6)

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    The Acknowledgments section in the original version of this Article was incomplete. “The authors of this manuscript would like to extend their thank to all who have contributed sequences to the GISAID database (https:// www. gisaid. org/).” now reads: “The authors of this manuscript would like to extend their thanks to all who have contributed sequences (Acknowledgements File) to the GISAID database (https:// www. gisaid. org/).” The original Article and accompanying Supplementary Information files have been corrected

    Transcriptome analysis reveals increased abundance and diversity of opportunistic fungal pathogens in nasopharyngeal tract of COVID-19 patients

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    We previously reported that SARS-CoV-2 infection reduces human nasopharyngeal commensal microbiomes (bacteria, archaea and commensal respiratory viruses) with inclusion of pathobionts. This study aimed to assess the possible changes in the abundance and diversity of resident mycobiome in the nasopharyngeal tract (NT) of humans due to SARS-CoV-2 infections. Twenty-two (n = 22) nasopharyngeal swab samples (including COVID-19 = 8, Recovered = 7, and Healthy = 7) were collected for RNA-sequencing followed by taxonomic profiling of mycobiome. Our analyses indicate that SARS-CoV-2 infection significantly increased (p < 0.05, Wilcoxon test) the population and diversity of fungi in the NT with inclusion of a high proportion of opportunistic pathogens. We detected 863 fungal species including 533, 445, and 188 species in COVID-19, Recovered, and Healthy individuals, respectively that indicate a distinct mycobiome dysbiosis due to the SARS-CoV-2 infection. Remarkably, 37% of the fungal species were exclusively associated with SARS-CoV-2 infection, where S. cerevisiae (88.62%) and Phaffia rhodozyma (10.30%) were two top abundant species. Likewise, Recovered humans NT samples were predominated by Aspergillus penicillioides (36.64%), A. keveii (23.36%), A. oryzae (10.05%) and A. pseudoglaucus (4.42%). Conversely, Nannochloropsis oceanica (47.93%), Saccharomyces pastorianus (34.42%), and S. cerevisiae (2.80%) were the top abundant fungal species in Healthy controls nasal swabs. Importantly, 16% commensal fungal species found in the Healthy controls were not detected in either COVID-19 patients or when they were cured from COVID-19 (Recovered). We also detected several altered metabolic pathways correlated with the dysbiosis of fungal mycobiota in COVID-19 patients. Our results suggest that SARS-CoV-2 infection causes significant dysbiosis of mycobiome and related metabolic functions possibly play a determining role in the progression of SARS-CoV-2 pathogenesis. These findings might be helpful for developing mycobiome-based diagnostics, and also devising appropriate therapeutic regimens including antifungal drugs for prevention and control of concurrent fungal coinfections in COVID-19 patients

    Phylogenetic diversity and functional potential of the microbial communities along the Bay of Bengal coast

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    Abstract The Bay of Bengal, the world's largest bay, is bordered by populous countries and rich in resources like fisheries, oil, gas, and minerals, while also hosting diverse marine ecosystems such as coral reefs, mangroves, and seagrass beds; regrettably, its microbial diversity and ecological significance have received limited research attention. Here, we present amplicon (16S and 18S) profiling and shotgun metagenomics data regarding microbial communities from BoB’s eastern coast, viz., Saint Martin and Cox’s Bazar, Bangladesh. From the 16S barcoding data, Proteobacteria appeared to be the dominant phylum in both locations, with Alteromonas, Methylophaga, Anaerospora, Marivita, and Vibrio dominating in Cox’s Bazar and Pseudoalteromonas, Nautella, Marinomonas, Vibrio, and Alteromonas dominating the Saint Martin site. From the 18S barcoding data, Ochrophyta, Chlorophyta, and Protalveolata appeared among the most abundant eukaryotic divisions in both locations, with significantly higher abundance of Choanoflagellida, Florideophycidae, and Dinoflagellata in Cox’s Bazar. The shotgun sequencing data reveals that in both locations, Alteromonas is the most prevalent bacterial genus, closely paralleling the dominance observed in the metabarcoding data, with Methylophaga in Cox’s Bazar and Vibrio in Saint Martin. Functional annotations revealed that the microbial communities in these samples harbor genes for biofilm formation, quorum sensing, xenobiotics degradation, antimicrobial resistance, and a variety of other processes. Together, these results provide the first molecular insight into the functional and phylogenetic diversity of microbes along the BoB coast of Bangladesh. This baseline understanding of microbial community structure and functional potential will be critical for assessing impacts of climate change, pollution, and other anthropogenic disturbances on this ecologically and economically vital bay

    Epitope-based chimeric peptide vaccine design against S, M and e proteins of SARS-CoV-2, the etiologic agent of COVID-19 pandemic: An in silico approach

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    Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19), a public health emergency of international concerns declared by the World Health Organization (WHO). An immuno-informatics approach along with comparative genomics was applied to design a multi-epitope-based peptide vaccine against SARS-CoV-2 combining the antigenic epitopes of the S, M, and E proteins. The tertiary structure was predicted, refined and validated using advanced bioinformatics tools. The candidate vaccine showed an average of ≥90.0% world population coverage for different ethnic groups. Molecular docking and dynamics simulation of the chimeric vaccine with the immune receptors (TLR3 and TLR4) predicted efficient binding. Immune simulation predicted significant primary immune response with increased IgM and secondary immune response with high levels of both IgG1 and IgG2. It also increased the proliferation of T-helper cells and cytotoxic T-cells along with the increased IFN-γ and IL-2 cytokines. The codon optimization and mRNA secondary structure prediction revealed that the chimera is suitable for high-level expression and cloning. Overall, the constructed recombinant chimeric vaccine candidate demonstrated significant potential and can be considered for clinical validation to fight against this global threat, COVID-19
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