Estudo metagenômico microbiano em transportes públicos circulantes na região metropolitana de Natal/RN durante o inverno

Abstract

Knowledge about microorganisms increasingly grows, due to their great relevance in the scientific and health field. Microbial diversity is quite wide, however, although there are microorganisms with beneficial properties for other organisms, there are those that pose a threat to human health, making them targets of studies and strategies for their combat and control. However, little is known about the presence of microorganisms and their interactions in urban spaces, especially in public transport systems. The aim of the presente work was the identification of the microbial community existing in the circulating buses in the city of Natal/RN. To this end, samples were collected from the surfaces of 67 buses distributed on several lines that circulate around the city during the winter period (07/18/2022 to 09/21/2022). The extraction of viral and bacterial genetic material was carried out, and its yield and purity checked in NanoDrop and Qubit. Genomic libraries were made, and their yields analyzed in Qubit and Bioanalyzer. Sequencing was performed using the Illumina NextSeq 1000 and the initial bioinformatics analysis were performed using the KBase platform. Partial results revealed low concentrations and yields of post-extraction samples, with only three samples having values good enough for library preparation (DNA Bac A2: 0.18 ng/µL; DNA Viral A2: 0.04 ng/µL; DNA Bac B: 0.46 ng/µl). However, when analyzing the post-sequencing genomic library profiles and their statistical data, significant qualities of these libraries were observed. The sequence numbers for Bacterial A2 DNA, Viral A2 DNA, and Bacterial DNA B were 14,844,879, 18,805,942, and 18,288,666, respectively, and their N50 values, after assembly, were 12,528, 5,769, and 17,553. These characteristics indicate good parameters for the continuity of the project, in which the taxonomy of the samples, abundance and diversity of in silico taxa and their correlations with data on temperature, humidity and epidemiology will be carried out.