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Aburashed, R.

Publications and source records attributed to Aburashed, R..

2 recordsLinked to original sources

DigestR an open-source software tool for visualizing LC-MS proteomics data resulting from natural protein catabolism

Protein catabolism is an essential biological function supported by every living organism. Although liquid chromatography mass spectrometry proteomics has advanced considerably over the past decade, protein catabolism in natural systems is still difficult to study. One reason for this is the lack of software tools designed specifically for decoding the complex mixtures of peptides that result from in vivo protein digestion. To address this, we developed DigestR, an open-source software tool designed specifically for the analysis of LC-MS proteomics data. DigestR allows users to visualize naturally occurring peptides and align them to a reference proteome at display them at either a proteome-wide and protein-specific level. These visualization tools allow users to track the patters of peptides occurring in natural systems and map naturally-occurring proteolytic cut sites. To demonstrate these functions, we used DigestR to analyze a mixture of peptides resulting from the in vitro digestion of human hemoglobin and bovine albumin with a cocktail of well characterized proteases. As expected, DigestR correctly identified both the proteins involved and the proteolytic cut sites produced by our protease cocktail. We then used DigestR to analyze the complex semi-ordered hemoglobin digestion pathway used by the malaria parasite Plasmodium falciparum. We show that DigestR successfully identified the proteolytic cut sites linked to the Plasmepsins, a protease known to be involved in hemoglobin digestion by the parasite. Collectively, these findings show that DigestR can be used to help visualize and interpret the complex mixtures of peptides occurring through in vivo protein catabolism. DigestR can be downloaded from www.lewisresearchgroup.org/software.

bioinformatics↗

Method for quantifying the metabolic boundary fluxes of cell cultures in large cohorts by high resolution hydrophilic liquid chromatography mass spectrometry

Metabolomics is a mainstream approach for investigating the metabolic underpinnings of complex biological phenomena and is increasingly being applied to large scale studies involving hundreds or thousands of samples. Although metabolomics methods are robust in smaller scale studies, they can be challenging to apply in larger cohorts due to the inherent variability of liquid chromatography mass spectrometry (LC-MS). Much of this difficulty results from the time-dependent changes in the LC-MS system, which affects both the qualitative and quantitative performance of the instrument. Herein, we introduce an analytical strategy for addressing this problem in large-scale microbial studies. Our approach quantifies microbial boundary fluxes using two zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) columns that are plumbed to enable offline column equilibration. Using this strategy, we show that over 360 common metabolites can be resolved in 4.5 minutes per sample and that metabolites can be quantified with a median coefficient of variation of 0.127 across 1,100 technical replicates. We illustrate the utility of this strategy via an analysis of 960 strains of Staphylococcus aureus isolated from blood stream infections. These data capture the diversity of metabolic phenotypes observed in clinical isolates and provide an example of how large-scale investigations can leverage our novel analytical strategy.

biochemistry↗