Trypanosoma and Leishmania parasites cause devastating tropical diseases resulting in serious global health consequences. These organisms have complex life cycles with mammalian hosts and insect vectors. The parasites must, therefore, survive in different environments, demanding rapid physiological and metabolic changes. These responses depend upon regulation of gene expression, which primarily occurs posttranscriptionally. Altering the composition or conformation of RNA through nucleotide modifications is one posttranscriptional mechanism of regulating RNA fate and function, and modifications including N6‐methyladenosine (m6A), N1‐methyladenosine (m1A), N5‐methylcytidine (m5C), N4‐acetylcytidine (ac4C), and pseudouridine (Ψ), dynamically regulate RNA stability and translation in diverse organisms. Little is known about RNA modifications and their machinery in Trypanosomatids, but we hypothesize that they regulate parasite gene expression and are vital for survival. Here, we identified Trypanosomatid homologs for writers of m1A, m5C, ac4C, and Ψ and analyze their evolutionary relationships. We systematically review the evidence for their functions and assess their potential use as therapeutic targets. This work provides new insights into the roles of these proteins in Trypanosomatid parasite biology and treatment of the diseases they cause and illustrates that Trypanosomatids provide an excellent model system to study RNA modifications, their molecular, cellular, and biological consequences, and their regulation and interplay.

Background The ZIKA virus (ZIKV) belongs to the Flaviviridae family, was first isolated in the 1940s, and remained underreported until its global threat in 2016, where drastic consequences were reported as Guillan-Barre syndrome and microcephaly in newborns. Understanding molecular interactions of ZIKV proteins during the host infection is important to develop treatments and prophylactic measures; however, large-scale experimental approaches normally used to detect protein-protein interaction (PPI) are onerous and labor-intensive. On the other hand, computational methods may overcome these challenges and guide traditional approaches on one or few protein molecules. The prediction of PPIs can be used to study host-parasite interactions at the protein level and reveal key pathways that allow viral infection. Results Applying Random Forest and Support Vector Machine (SVM) algorithms, we performed predictions of PPI between two ZIKV strains and human proteomes. The consensus number of predictions of both algorithms was 17,223 pairs of proteins. Functional enrichment analyses were executed with the predicted networks to access the biological meanings of the protein interactions. Some pathways related to viral infection and neurological development were found for both ZIKV strains in the enrichment analysis, but the JAK-STAT pathway was observed only for strain PE243 when compared with the FSS13025 strain. Conclusions The consensus network of PPI predictions made by Random Forest and SVM algorithms allowed an enrichment analysis that corroborates many aspects of ZIKV infection. The enrichment results are mainly related to viral infection, neuronal development, and immune response, and presented differences among the two compared ZIKV strains. Strain PE243 presented more predicted interactions between proteins from the JAK-STAT signaling pathway, which could lead to a more inflammatory immune response when compared with the FSS13025 strain. These results show that the methodology employed in this study can potentially reveal new interactions between the ZIKV and human cells.

Yersinia pestis, the etiological agent of the plague, is considered a genetically homogeneous species. Brazil is currently in a period of epidemiological silence but plague antibodies are still detected in sentinel animals, suggesting disease activity in the sylvatic cycle. The present study deployed an in silico approach to analyze virulence factors among 407 Brazilian genomes of Y. pestis belonging to the Fiocruz Collection (1966–1997). The pangenome analysis associated several known virulence factors of Y. pestis in clades according to the presence or absence of genes. Four main strain clades (C, E, G, and H) exhibited the absence of various virulence genes. Notably, clade G displayed the highest number of absent genes, while clade E showed a significant absence of genes related to the T6SS secretion system and clade H predominantly demonstrated the absence of plasmid-related genes. These results suggest attenuation of virulence in these strains over time. The cgMLST analysis associated genomic and epidemiological data highlighting evolutionary patterns related to the isolation years and outbreaks of Y. pestis in Brazil. Thus, the results contribute to the understanding of the genetic diversity and virulence within Y. pestis and the potential for utilizing genomic data in epidemiological investigations.