Inferring Plasmodium vivax protein biology by using omics data.

Deciphering Plasmodium vivax biology has long been a challenge for groups working on this parasite, mainly due to the complications involved in propagating it in vitro. However, adapting P. vivax strains in non-human primates and the arrival of high-performance analysis methods has led to increased knowledge regarding parasite protein composition and the ability of some molecules to trigger an immune response or participate in protein-protein interactions. This review describes the state of the art concerning proteomics-, immunomics- and interatomics-related P. vivax omic studies, discussing their potential use in developing disease control methods.

Multiple high-risk HPV genotypes are grouped by type and are associated with viral load and risk factors.

Investigating whether high-risk human papillomavirus (HR-HPV) types tend to become grouped in a particular way and whether factors are associated with such grouping is important for measuring the real impact of vaccination. In total, 219 women proving positive for HPV as detected by real-time PCR were included in the study. Each sample was analysed for detecting and quantifying six viral types and the hydroxymethylbilane synthase gene. Multiple correspondence analysis led to determining grouping patterns for six HR-HPV types and simultaneous association with multiple variables and whether viral load was related to the coexistence of other viral types. Two grouping profiles were identified: the first included HPV-16 and HPV-45 and the second profile was represented by HPV-31, HPV-33 and HPV-58. Variables such as origin, contraceptive method, births and pregnancies, educational level, healthcare affiliation regime, atypical squamous cells of undetermined significance and viral load were associated with these grouping profiles. Different socio-demographic characteristics were found when coinfection occurred by phylogenetically related HPV types and when coinfection was due to non-related types. Biological characteristics, the number of viral copies, temporality regarding acquiring infection and competition between viral types could influence the configuration of grouping patterns. Characteristics related to women and HPV, influence such interactions between coexisting HPV types reflecting the importance of their evaluation.