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In the marine environment, coastal nutrient pollution and algal blooms are increasing in many coral reefs and surface waters around the world, leading to higher concentrations of dissolved organic carbon (DOC), nitrogen (N), phosphate (P), and sulfur (S) compounds. The adaptation of the marine microbiota to this stress involves evolutionary processes through mutations that can provide selective phenotypes. The aim of this in silico analysis is to elucidate the potential candidate hub proteins, biological processes, and key metabolic pathways involved in the pathogenicity of bacterioplankton during excess of nutrients. The analysis was carried out on the model organism Escherichia coli K-12, by adopting an analysis pipeline consisting of a set of packages from the Cystoscape platform. The results obtained show that the metabolism of carbon and sugars generally are the 2 driving mechanisms for the expression of virulence factors.

Microorganisms such as viruses, bacteria, and protozoa are the cause of many waterborne human infections. These microbes are either naturally present in aquatic environments or transferred within them by fecal sources. They remain in these environments for varying lengths of time before contaminating a new host. With the emergence of the COVID-19 pandemic, some studies have reported the presence of viral nucleic acids in stool samples from COVID-19 patients, suggesting the possibility of fecal-oral transmission. The SARS-CoV-2 RNA was thereby detected in the wastewater of symptomatic and asymptomatic people with a risk to human and environmental health. In this work, we try to discuss the different potential sources of this contamination, the forms of persistence in the environment, the techniques of partial elimination, and the possibility of creating new reservoirs.

Nowadays, the integration of biological data is a major challenge for bioinformatics. Many studies have examined gene expression in the epithelial tissue in the intestines of infants born to term and breastfed, generating a large amount of data. The integration of these data is important to understand the biological processes involved during bacterial colonization of the newborns intestine, particularly through breast milk. This work aims to exploit the bioinformatics approaches, to provide a new representation and interpretation of the interactions between differentially expressed genes in the host intestine induced by the microbiota.