RESUMEN
In an integrated poultry-fish (IPF) farming system, fish and bird are reared simultaneously. It is a common practice in Sub-Saharan Africa countries like Nigeria, Cameroon, Madagascar, and Benin, offering economic benefits to farmers and minimizing farm running costs. It seems like another way for farmers to manage poultry waste as it is a common practice in IPF farm settings to feed reared fishes with wastes emanating from the poultry. This work provides dataset on the bacterial taxonomic profile and abundance in IPF farm pond water samples using the 16S rRNA sequencing approach. Using ZymoBIOMICS®-96 MagBead DNA Kit, total DNA was extracted from pond water samples collected from IPF farm located at Ila-Orangun, Osun State, Southwest Nigeria (Long: 8° 1' N; Lat: 4° 54' E) during two sampling visits. The V3-V4 region of the rRNA gene was amplified and sequenced on the Miseq Illumina sequencing platform. Raw reads obtained after demultiplexing were analyzed using DADA2 pipeline to obtain distinctive or unique amplicon sequence variants which were grouped into Operational Taxonomic Units (OTUs) based on similarities. Taxonomy assignment was performed using UCLUST and Bayesian classifier from QIIME v.1.9.1 with the Zymo Research Database as reference. The phyla Proteobacteria (26.7%), Actinobacteria (26.0%), Firmicutes (13.1%), and Cyanobacteria (10.1%) dominated the 35 phyla obtained from the OTUs. Interestingly, the abundance of bacterial pathogens commonly associated with human infections was low. The sequence and sample data have been deposited in NCBI database under Sequence Read Archive (SRA) with Bioproject identification number PRJNA760919 (Accession number: SRX12020336 - SRX12020346). The dataset obtained can bridge the gap of limited information on the impact of IPF farming on pond bacterial diversity, a critical factor for considerations as regards food safety, fish, and public health.
RESUMEN
Background: SARS-CoV-2 infection or COVID-19 is a major global public health issue that requires urgent attention in terms of drug development. Transmembrane Protease Serine 2 (TMPRSS2) is a good drug target against SARS-CoV-2 because of the role it plays during the viral entry into the cell. Virtual screening of phytochemicals as potential inhibitors of TMPRSS2 can lead to the discovery of drug candidates for the treatment of COVID-19. Purpose: The study was designed to screen 132 phytochemicals from three medicinal plants traditionally used as antivirals; Zingiber officinalis Roscoe (Zingiberaceae), Artemisia annua L. (Asteraceae), and Moringa oleifera Lam. (Moringaceae), as potential inhibitors of TMPRSS2 for the purpose of finding therapeutic options to treat COVID-19. Methods: Homology model of TMPRSS2 was built using the ProMod3 3.1.1 program of the SWISS-MODEL. Binding affinities and interaction between compounds and TMPRSS2 model was examined using molecular docking and molecular dynamics simulation. The drug-likeness and ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of potential inhibitors of TMPRSS2 were also assessed using admetSAR web tool. Results: Three compounds, namely, niazirin, quercetin, and moringyne from M. oleifera demonstrated better molecular interactions with binding affinities ranging from -7.1 to -8.0 kcal/mol compared to -7.0 kcal/mol obtained for camostat mesylate (a known TMPRSS2 inhibitor), which served as a control. All the three compounds exhibited good drug-like properties by not violating the Lipinski rule of 5. Niazirin and moringyne possessed good ADMET properties and were stable in their interactions with the TMPRSS2 based on the molecular dynamics simulation. However, the ADMET tool predicted the potential hepatotoxic and mutagenic effects of quercetin. Conclusion: This study demonstrated the potentials of niazirin, quercetin, and moringyne from M. oleifera, to inhibit the activities of human TMPRSS2, thus probably being good candidates for further development as new drugs for the treatment or management of COVID-19.