Trypanosoma cruzi has three biochemically and morphologically distinct developmental stages that are programmed to rapidly respond to environmental changes the parasite faces during its life cycle. Unlike other eukaryotes, Trypanosomatid genomes contain protein coding genes that are transcribed into polycistronic pre-mRNAs and have their expression controlled by post-transcriptional mechanisms. Transcriptome analyses comparing three stages of the T. cruzi life cycle revealed changes in gene expression that reflect the parasite adaptation to distinct environments. Several genes encoding RNA binding proteins (RBPs), known to act as key post-transcriptional regulatory factors, were also differentially expressed. We characterized one T. cruzi RBP, named TcZH3H12, which contains a zinc finger domain and is up-regulated in epimastigotes compared to trypomastigotes and amastigotes. TcZC3H12 knockout (KO) epimastigotes showed decreased growth rates and increased capacity to differentiate into metacyclic trypomastigotes. Transcriptome analyses comparing wild type and TcZC3H12 KOs revealed a TcZC3H12-dependent expression of epimastigote-specific genes such as genes encoding amino acid transporters and proteins associated with differentiation (PADs). RNA immunoprecipitation assays showed that transcripts from the PAD family interact with TcZC3H12. Taken together, these findings suggest that TcZC3H12 positively regulates the expression of genes involved in epimastigote proliferation and also acts as a negative regulator of metacyclogenesis.

In the current study, phage-exposed mimotopes as targets against tegumentary leishmaniasis (TL) were selected by means of bio-panning cycles employing sera of TL patients and healthy subjects, besides the immune stimulation of peripheral blood mononuclear cells (PBMCs) collected from untreated and treated TL patients and healthy subjects. The clones were evaluated regarding their specific interferon-γ (IFN-γ) and interleukin-4 (IL-4) production in the in vitro cultures, and selectivity and specificity values were calculated, and those presenting the best results were selected for the in vivo experiments. Two clones, namely A4 and A8, were identified and used in immunization protocols from BALB/c mice to protect against Leishmania amazonensis infection. Results showed a polarized Th1 response generated after vaccination, being based on significantly higher levels of IFN-γ, IL-2, IL-12, tumour necrosis factor-α (TNF-α) and granulocyte-macrophage colony-stimulating factor (GM-CSF); which were associated with lower production of specific IL-4, IL-10 and immunoglobulin G1 (IgG1) antibodies. Vaccinated mice presented significant reductions in the parasite load in the infected tissue and distinct organs, when compared with controls. In conclusion, we presented a strategy to identify new mimotopes able to induce Th1 response in PBMCs from TL patients and healthy subjects, and that were successfully used to protect against L. amazonensis infection.

The objective was to compare measures from dual-energy X-ray absorptiometry (DXA), bioelectrical impedance analysis (BIA) and anthropometry with a reference four-compartment model to estimate fat mass (FM) and fat-free mass (FFM) changes in overweight and obese women after a weight-loss programme. Forty-eight women (age 39.8 ± 5.8 years; weight 79·2 ± 11·8 kg; BMI 30·7 ± 3·6 kg/m2) were studied in an out-patient weight-loss programme, before and after the 16-month intervention. Women attended weekly meetings for the first 4 months, followed by monthly meetings from 4 to 12 months. Body composition variables were measured by the following techniques: DXA, anthropometry (waist circumference-based model; Antrform), BIA using Tanita (TBF-310) and Omron (BF300) and a reference four-compartment model. Body weight decreased significantly ( − 3·3 (sd 3·1) kg) across the intervention. At baseline and after the intervention, FM, percentage FM and FFM assessed by Antrform, Tanita, BF300 and DXA differed significantly from the reference method (P ≤ 0·001), with the exception of FFM assessed by Tanita (baseline P = 0·071 and after P = 0·007). DXA significantly overestimated the change in FM and percentage FM across weight loss ( − 4·5 v. − 3·3 kg; P < 0·001 and − 3·7 v. − 2·0 %; P < 0·001, respectively), while Antrform underestimated FM and percentage FM ( − 2·8 v. − 3·3 kg; P = 0·043 and − 1·1 v. − 2·0 %; P = 0·013) compared with the four-compartment model. Tanita and BF300 did not differ (P>0·05) from the reference model in any body composition variables. We conclude that these methods are widely used in clinical settings, but should not be applied interchangeably to detect changes in body composition. Furthermore, the several clinical methods were not accurate enough for tracking body composition changes in overweight and obese premenopausal women after a weight-loss programme.