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Rudra, P.

Publications and source records attributed to Rudra, P..

2 recordsLinked to original sources

Tools, strains, and strategies to effectively conduct anaerobic and aerobic transcriptional reporter screens and assays in Staphylococcus aureus

Transcriptional reporters are reliable and time-tested tools to study gene regulation. In Staphylococcus aureus, {beta}-galactosidase (lacZ)-based genetic screens are not widely used because of the necessity of selectable markers for strain construction and the production of staphyloxanthin pigment which obfuscates results. We describe a series of vectors that allow for markerless insertion of codon-optimized lacZ-based transcriptional reporters. The vectors encode for different ribosomal binding sites allowing for tailored lacZ expression. A {Delta}crtM::kanR deletion insertion mutant was constructed that prevents the synthesis of staphyloxanthin, thereby permitting blue-white screening without the interference of carotenoid production. We demonstrate the utility of these vectors to monitor aerobic and anaerobic transcriptional activity. For the latter, we describe the use of a ferrocyanide-ferricyanide redox system (Fe(CN)63-/4-) permitting blue-white screening in the absence of oxygen. We also describe additional reporter systems and methods for monitoring transcriptional activity during anaerobic culture including a FAD-binding fluorescent protein (EcFbFP), alpha-hemolysin (hla), or lipase (geh). The systems and methods described are compatible with vectors utilized to create and screen high-density transposon mutant libraries. ImportanceStaphylococcus aureus is a human pathogen and a leading cause of infectious disease-related illness and death worldwide. For S. aureus to successfully colonize and invade host tissues, it must tightly control the expression of genes encoding for virulence factors. Oxygen tension varies greatly at infection sites and many abscesses are devoid of oxygen. In this study, we have developed novel tools and methods to study how and when S. aureus alters transcription of genes. A key advantage to these methods and tools is that they can be utilized in the presence and absence of oxygen. A better understanding of anaerobic gene expression in S. aureus will provide important insight into the regulation of genes in low oxygen environments.

microbiology

Compositional Data Analysis using Kernels in Mass Cytometry Data

MotivationCell type abundance data arising from mass cytometry experiments are compositional in nature. Classical association tests do not apply to the compositional data due to their non-Euclidean nature. Existing methods for analysis of cell type abundance data suffer from several limitations for high-dimensional mass cytometry data, especially when the sample size is small. ResultsWe proposed a new multivariate statistical learning methodology, Compositional Data Analysis using Kernels (CODAK), based on the kernel distance covariance (KDC) framework to test the association of the cell type compositions with important predictors (categorical or continuous) such as disease status. CODAK scales well for high-dimensional data and provides satisfactory performance for small sample sizes (n < 25). We conducted simulation studies to compare the performance of the method with existing methods of analyzing cell type abundance data from mass cytometry studies. The method is also applied to a high-dimensional dataset containing different subgroups of populations including Systemic Lupus Erythematosus (SLE) patients and healthy control subjects. Availability and ImplementationCODAK is implemented using R. The codes and the data used in this manuscript are available on the web at http://github.com/GhoshLab/CODAK/. Supplementary informationSupplementary Materials.pdf.

bioinformatics