Publicaciones

BACKGROUND:

Chagas disease, caused by the intracellular parasite Trypanosoma cruzi, is one of the most important parasitological infections in the Americas. It is estimated to infect approximately 6 million people from mostly low income countries in Latin America, although recent infections have been reported in southern US states. Several studies have described an extensive genetic diversity among T. cruzi isolates throughout its geographic distribution in the American continent. This diversity has been correlated with the pathology developed during an infection. However, due to a lack of a single reliable test, current diagnosis practices of the disease are not straightforward since several different tests are applied. The use of current genomic sequence data allows for the selection of molecular markers (MM) that have the ability to identify the Discrete Typing Unit (DTU) of T. cruzi in a given infection, without the need of any sequencing reaction

BACKGROUND:

Protein solubility characteristics are important determinants of success for recombinant proteins in relation to expression, purification, storage and administration. Escherichia coli offers a cost-efficient expression system. An important limitation, whether for biophysical studies or industrial-scale production, is the formation of insoluble protein aggregates in the cytoplasm. Several strategies have been implemented to improve soluble expression, ranging from modification of culture conditions to inclusion of solubility-enhancing tags.

RESULTS: 

Surface patch analysis has been applied to predict amino acid changes that can alter the solubility of expressed recombinant human erythropoietin (rHuEPO) in E. coli, a factor that has importance for both yield and subsequent downstream processing of recombinant proteins. A set of rHuEPO proteins (rHuEPO E13K, F48D, R150D, and F48D/R150D) was designed (from the framework of wild-type protein, rHuEPO WT, via amino acid mutations) that varied in terms of positively-charged patches. A variant predicted to promote aggregation (rHuEPO E13K) decreased solubility significantly compared to rHuEPO WT. In contrast, variants predicted to diminish aggregation (rHuEPO F48D, R150D, and F48D/R150D) increased solubility up to 60% in relation to rHuEPO WT.

CONCLUSIONS:

These findings are discussed in the wider context of biophysical calculations applied to the family of EPO orthologues, yielding a diverse range of calculated values. It is suggested that combining such calculations with naturally-occurring sequence variation, and 3D model generation, could lead to a valuable tool for protein solubility design.

KEYWORDS:

Abstract

Due in part to the needs of the biopharmaceutical industry, there has been an increased drive to generate high quality recombinant proteins in large amounts. However, achieving high yields can be a challenge as the novelty and increased complexity of new targets often makes them ‘difficult‐to‐express’. This study aimed to define the molecular features that restrict the production of a model ‘difficult‐to‐express’ recombinant protein, Tissue Inhibitor Metalloproteinase‐3 (TIMP‐3). Building from experimental data, computational approaches were used to rationalize the redesign of this recombinant target to generate a chimera with enhanced secretion. The results highlight the importance of early identification of unfavourable sequence attributes, enabling the generation of engineered protein forms that bypass ‘secretory’ bottlenecks and result in efficient recombinant protein production.

KEYWORDS

 difficult‐to‐express, mammalian expression system, predictive computational tool, protein engineering, recombinant protein production, tissue inhibitor of metalloproteinase

MOTIVATION:

Protein solubility is an important property in industrial and therapeutic applications. Prediction is a challenge, despite a growing understanding of the relevant physicochemical properties.

RESULTS:

Protein-Sol is a web server for predicting protein solubility. Using available data for Escherichia coli protein solubility in a cell-free expression system, 35 sequence-based properties are calculated. Feature weights are determined from separation of low and high solubility subsets. The model returns a predicted solubility and an indication of the features which deviate most from average values. Two other properties are profiled in windowed calculation along the sequence: fold propensity, and net segment charge. The utility of these additional features is demonstrated with the example of thioredoxin.