Project description:Serratia marcescens (S. marcescens), an opportunistic human pathogen, has been identified as a major cause of nosocomial infection and outbreaks. The purpose of this analysis is to examine the S. marcescens (ATCC 13880) protein profile using a high resolution mass spectrometry (MS). S. marcescens ATCC 13880 strain was grown in Luria-Bertani broth and the protein extracted underwent trypsin digestion followed by simple reverse phase liquid chromatography fractionation. Peptide fractions were then analyzed using Orbitrap Fusion Mass Spectrometry and raw MS data was processed using Proteome Discoverer software. The proteomic study identified 2,541 unique protein groups, corresponding to approximately 54% of the measured protein-coding genes. Bioinformatics analysis of these identified proteins demonstrated their involvement in biological processes such as cell wall organization, caperone-mediated protein folding and ATP binding. To our knowledge, this is the first high-performance S.marcescens proteomics analysis (ATCC 13880). These novel observations provide a key baseline molecular profile of the S. marcescens proteome which will prove to be helpful for the future research in understanding the host-pathogen interactions during infection, elucidating the mechanism of multidrug resistance and for developing novel diagnostic markers or vaccine for the disease.
Project description:Biochemical evidence is vital for accurate genome annotation. The integration of experimental data collected at the proteome level using high resolution mass spectrometry allows for improvements in genome annotation by providing evidence for novel gene models, while validating or modifying others. Here we report the results of a proteogenomic analysis of a reference strain of Mycobacterium smegmatis (mc2155), a fast growing model organism for the pathogenic Mycobacterium tuberculosis, the causative agent for Tuberculosis. By integrating high throughput LC/MS/MS proteomic data with genomic six frame translation and ab initio gene prediction databases, a total of 2887 ORFs were identified, including 2810 ORFs annotated to a Reference protein, and 63 ORFs not previously annotated to a Reference protein. Further, the translational start site (TSS) was validated for 558 Reference proteome gene models, while upstream translational evidence was identified for 81. In addition, N-terminus derived peptide identifications allowed for downstream TSS modification of a further 24 gene models. We validated the existence of 6 previously described interrupted coding sequences at the peptide level, and provide evidence for 4 novel frameshift positions. Analysis of peptide posterior error probability (PEP) scores indicate high-confidence novel peptide identifications and indicate that the genome of M. smegmatis is not yet fully annotated.