Abstract
BACKGROUND: The Mayaro virus (MAYV) is an alphavirus endemic to Central and South America, primarily transmitted by mosquitoes of the Haemagogus genus. Human infection causes "Mayaro fever," characterized by symptoms similar to dengue and chikungunya, including debilitating arthralgia. Despite its potential for urbanisation, many aspects of MAYV-host interactions, particularly the role of host microRNAs (miRNAs), remain poorly understood. OBJECTIVES: This study aimed to investigate the expression profile of miRNAs in Vero cells infected with MAYV and to predict their potential biological targets and associated pathways. METHODS: Infection was performed using the MAYV strain (BeAr 20290), and small RNA libraries were prepared from infected and control cells. Initial experiments were conducted to evaluate viral replication, cell viability, and small RNA expression. Based on these parameters, the 24-h post-infection time point was selected for small RNA sequencing. Bioinformatic tools were used to identify differentially expressed miRNAs and predict their targets in Homo sapiens and the MAYV genome. FINDINGS: Among the 348 miRNAs identified, 46 were differentially expressed at 24 h (42 upregulated and four downregulated). Principal component analysis (PCA) indicated a clear separation between infected and control groups. In silico predictions of the targets of these miRNAs suggest potential associations with biological processes that may be relevant to virus-host interactions, such as immune response, programmed cell death pathways, viral replication, and persistence. Additionally, one miRNA detected in Vero cells was predicted to target a viral non-structural protein. MAIN CONCLUSIONS: Our findings indicate a potential dual role for host miRNAs during MAYV infection, involving both the modulation of host responses by the virus to enhance replication and a possible antiviral effect. While these interactions underscore the prospective relevance of miRNAs as biomarkers and therapeutic targets in arboviral infections, it is important to note that these conclusions are based solely on computational analyses. Therefore, they should be interpreted with caution until they are supported by further experimental validation.