Proteogenomic Analysis of Mycobacterium smegmatis Using High Resolution Mass Spectrometry

Abstract

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 six previously described interrupted coding sequences at the peptide level, and provide evidence for four novel frameshift positions. Analysis of peptide posterior error probability (PEP) scores indicates high-confidence novel peptide identifications and shows that the genome of M. smegmatis mc2155 is not yet fully annotated. Data are available via ProteomeXchange with identifier PXD003500.

Integrated Multi-Omic Analysis of Mycobacterium tuberculosis H37Ra Redefines Virulence Attributes

“…Using an integrated OMICs approach, we have earlier successfully demonstrated the utility of proteomic analysis in the refinement of genome annotations of several clinically important organisms (Chaerkady et al, 2011 ; Kelkar et al, 2011 ; Renuse et al, 2011 ; Potgieter et al, 2016 ; Prasad et al, 2017 ). In this study, we report a multi-OMICs approach for the in-depth characterization of M. tuberculosis H37Ra.…”

Methods, Tools and Current Perspectives in Proteogenomics

“…In 2004, Jaffe et al introduced the concept of a proteogenomic map as a complementary method for genome annotation, which used evidence of protein expression to predict ORFs in Mycoplasma pneumoniae (1). Since then, a proteomics-based approach to gene annotation model refinement has been successfully applied in both model and nonmodel organisms (37)(38)(39)(40)(41)(42)(43). Proteogenomic gene annotation is most been used to train algorithms for gene model prediction (43).…”

Small open reading frames and cellular stress responses

“…3 However, with the advent of proteogenomic 4 technologies, thousands of previously unannotated small open reading frames (smORFs) 3,5 encoding products of fewer than 100 amino acids have been shown to undergo translation in organisms spanning all domains of life, including bacteria, yeast, flies, mouse, and human. [6][7][8][9][10][11][12][13][14][15][16][17] With this increase in coding sequence annotation comes a need to determine the functions of smORF-encoded polypeptides (SEPs). Three classes of smORFs have been proposed in eukaryotes, 18 based on RNA ''location'' and conservation: (1) non-functional intergenic smORFs that may represent newly evolving genes 19 (2) smORFs that encode functional SEPs and (3) translated upstream ORFs (uORFs) encoded in 5 0 untranslated regions of mRNA that function as cis-translational regulators of downstream coding sequences.…”