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High Throughput Expression Screening of Arabinofuranosyltransferases from Mycobacteria

Authors: José Rodrigues; Vanessa T. Almeida; Ana L. Rosário; Yong Zi Tan; Brian Kloss; Filippo Mancia; Margarida Archer;

High Throughput Expression Screening of Arabinofuranosyltransferases from Mycobacteria

Abstract

Studies on membrane proteins can help to develop new drug targets and treatments for a variety of diseases. However, membrane proteins continue to be among the most challenging targets in structural biology. This uphill endeavor can be even harder for membrane proteins from Mycobacterium species, which are notoriously difficult to express in heterologous systems. Arabinofuranosyltransferases are involved in mycobacterial cell wall synthesis and thus potential targets for antituberculosis drugs. A set of 96 mycobacterial genes coding for Arabinofuranosyltransferases was selected, of which 17 were successfully expressed in E. coli and purified by metal-affinity chromatography. We herein present an efficient high-throughput strategy to screen in microplates a large number of targets from Mycobacteria and select the best conditions for large-scale protein production to pursue functional and structural studies. This methodology can be applied to other targets, is cost and time effective and can be implemented in common laboratories.

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Singapore
Keywords

Technology, Science & Technology, PURIFICATION, Mycobacteria, Chemical, membrane proteins, overexpression in E. coli, overexpression in <i>E. coli</i>, 004, Engineering, ESCHERICHIA-COLI, protein purification, MEMBRANE-PROTEIN OVEREXPRESSION, high-throughput protocol, ARABINOGALACTAN, BIOSYNTHESIS, Arabinofuranosyltransferases, STRATEGY, <i>Mycobacteria</i>

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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