Secretome analysis of Trypanosoma cruzi by proteomics studies.

BACKGROUND: Chagas disease is a debilitating often fatal disease resulting from infection by the protozoan parasite Trypanosoma cruzi. Chagas disease is endemic in 21 countries of the Americas, and it is an emerging disease in other countries as a result of migration. Given the chronic nature of the infection where intracellular parasites persist for years, the diagnosis of T. cruzi by direct detection is difficult, whereas serologic tests though sensitive may yield false-positive results. The development of new rapid test based on the identification of soluble parasitic antigens in serum would be a real innovation in the diagnosis of Chagas disease. METHODS: To identify new soluble biomarkers that may improve diagnostic tests, we investigated the proteins secreted by T. cruzi using mass spectrometric analyses of conditioned culture media devoid of serum collected during the emergence of trypomastigotes from infected Vero cells. In addition, we compared the secretomes of two T. cruzi strains from DTU Tc VI (VD and CL Brener). RESULTS: Analysis of the secretome collected during the emergence of trypomastigotes from Vero cells led to the identification of 591 T. cruzi proteins. Three hundred sixty three proteins are common to both strains and most belong to different multigenic super families (i.e. TcS, GP63, MASP, and DGF1). Ultimately we have established a list of 94 secreted proteins, common to both DTU Tc VI strains that do not belong to members of multigene families. CONCLUSIONS: This study provides the first comparative analysis of the secretomes from two distinct T. cruzi strains of DTU TcVI. This led us to identify a subset of common secreted proteins that could potentially serve as serum markers for T. cruzi infection. Their potential could now be evaluated, with specific antibodies using sera collected from patients and residents from endemic regions.

Using a vector pool containing variable-strength promoters to optimize protein production in Yarrowia lipolytica.

BACKGROUND: The yeast Yarrowia lipolytica is an increasingly common biofactory. To enhance protein expression, several promoters have been developed, including the constitutive TEF promoter, the inducible POX2 promotor, and the hybrid hp4d promoter. Recently, new hp4d-inspired promoters have been created that couple various numbers of UAS1 tandem elements with the minimal LEU2 promoter or the TEF promoter. Three different protein-secretion signaling sequences can be used: preLip2, preXpr2, and preSuc2. RESULTS: To our knowledge, our study is the first to use a set of vectors with promoters of variable strength to produce proteins of industrial interest. We used the more conventional TEF and hp4d promoters along with five new hybrid promoters: 2UAS1-pTEF, 3UAS1-pTEF, 4UAS1-pTEF, 8UAS1-pTEF, and hp8d. We compared the production of RedStar2, glucoamylase, and xylanase C when strains were grown on three media. As expected, levels of RedStar2 and glucoamylase were greatest in the strain with the 8UAS1-pTEF promoter, which was stronger. However, surprisingly, the 2UAS1-pTEF promoter was associated with the greatest xylanase C production and activity. This finding underscored that stronger promoters are not always better when it comes to protein production. We therefore developed a method for easily identifying the best promoter for a given protein of interest. In this gateway method, genes for YFP and α-amylase were transferred into a pool of vectors containing different promoters and gene expression was then analyzed. We observed that, in most cases, protein production and activity were correlated with promoter strength, although this pattern was protein dependent. CONCLUSIONS: Protein expression depends on more than just promoter strength. Indeed, promoter suitability appears to be protein dependent; in some cases, optimal expression and activity was obtained using a weaker promoter. We showed that using a vector pool containing promoters of variable strength can be a powerful tool for rapidly identifying the best producer for a given protein of interest.