Abstract
Streptococcus sanguinis is a commensal and early colonizer of oral cavity as well as an opportunistic pathogen of infectious endocarditis. Extracting the soluble proteome of this bacterium provides deep insights about the physiological dynamic changes under different growth and stress conditions, thus defining “proteomic signatures” as targets for therapeutic intervention. In this protocol, we describe an experimentally verified approach to extract maximal cytoplasmic proteins from Streptococcus sanguinis SK36 strain. A combination of procedures was adopted that broke the thick cell wall barrier and minimized denaturation of the intracellular proteome, using optimized buffers and a sonication step. Extracted proteome was quantitated using Pierce BCA Protein Quantitation assay and protein bands were macroscopically assessed by Coomassie Blue staining. Finally, a high resolution detection of the extracted proteins was conducted through Synapt G2Si mass spectrometer, followed by label-free relative quantification via Progenesis QI. In conclusion, this pipeline for proteomic extraction and analysis of soluble proteins provides a fundamental tool in deciphering the biological complexity of Streptococcus sanguinis.
Highlights
Understanding bacterial gene functions necessitates dissecting its transcriptomic and proteomic profiles at given conditions (Wang et al, 2010)
As proteomic approaches for insoluble membrane proteins have been discussed elsewhere (Smith, 2011; Moore, Hess, Jorgenson, 2016), here we provide a proteomic approach for quantifying the soluble proteins in an oral commensal (Siqueira & Rôças, 2017) and opportunistic causative agent of infective endocarditis, Streptococcus sanguinis SK36 (Do et al, 2011; Kim et al, 2016)
S. sanguinis SK36 strain was routinely grown in brain heart infusion (BHI) broth (BD, San Jose, CA) under micro-aerobic conditions (7.2% H2, 7.2% CO2, 79.6% N2, and 6% O2) at 37°C
Summary
Understanding bacterial gene functions necessitates dissecting its transcriptomic and proteomic profiles at given conditions (Wang et al, 2010). With the high pace advances in transcriptomics that govern global coverage of genome to measure its mRNA transcript counts even in a single cell, the need for efficient proteomic approaches that cover a maximal number of proteins is overwhelmingly huge to address an ever-growing list of biological questions. After sequencing the genome (Xu et al, 2007) and identifying the essential genes (Xu et al, 2011) of S. sanguinis SK36, the current challenge is to identify the dynamics of its proteins, especially the essential proteins, under different stress conditions that mimic clinical situations it induces, to define “pathogenesis signatures” as promising therapeutic targets
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