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Patel, D. S.

Publications and source records attributed to Patel, D. S..

2 recordsLinked to original sources

pTSara-NatB, an improved N-terminal acetylation system for recombinant protein expression in E. coli

N-terminal acetylation is one of the most common post-translational modifications of the eukaryotic proteome and regulates numerous aspects of cellular physiology, such as protein folding, localization and turnover. In particular -synuclein, whose dyshomeostasis has been tied to the pathogenesis of several neurodegenerative disorders, is completely N-acetylated in nervous tissue. In this work, building on previous reports, we develop and characterize a bacterial N-terminal acetylation system based on the expression of the yeast N-terminal acetyltransferase B (NatB) complex under the control of the PBAD (L-arabinose-inducible) promoter. We show its functionality and the ability to completely N-acetylate our model substrate -synuclein both upon induction of the construct with L-arabinose and also by only relying on the constitutive expression of the NatB genes.

molecular biology

Next-generation Sequence-analysis Toolkit (NeST): A standardized bioinformatics framework for analyzing Single Nucleotide Polymorphisms in next-generation sequencing data

Rapid advancements in next-generation sequencing (NGS) technologies have led to the development of numerous bioinformatics tools and pipelines. As these tools vary in their output function and complexity and some are not well-standardized, it is harder to choose a suitable pipeline to identify variants in NGS data. Here, we present NeST (NGS-analysis Toolkit), a modular consensus-based variant calling framework. NeST uses a combination of variant callers to overcome potential biases of an individual method used alone. NeST consists of four modules, that integrate open-source bioinformatics tools, a custom Variant Calling Format (VCF) parser and a summarization utility, that generate high-quality consensus variant calls. NeST was validated using targeted-amplicon deep sequencing data from 245 Plasmodium falciparum isolates to identify single-nucleotide polymorphisms conferring drug resistance. The results were verified using Sanger sequencing data for the same dataset in a supporting publication [28]. NeST offers a user-friendly pipeline for variant calling with standardized outputs and minimal computational demands for easy deployment for use with various organisms and applications.

bioinformatics