Improving genome annotation of enterotoxigenicEscherichia coliTW10598 by a label-free quantitative MS/MS approach

Proteomic Characterization of Prostate Cancer to Distinguish Nonmetastasizing and Metastasizing Primary Tumors and Lymph Node Metastases

Patients with metastatic prostate cancer (PCa) have a poorer prognosis than patients with organ-confined tumors. We strove to uncover the proteome signature of primary PCa and associated lymph node metastases (LNMs) in order to identify proteins that may indicate or potentially promote metastases formation. We performed a proteomic comparative profiling of PCa tissue from radical prostatectomy (RPE) of patients without nodal metastases or relapse at the time of surgical resection (n=5) to PCa tissue from RPE of patients who suffered from nodal relapse (n=5). For the latter group, we also included patient-matched tissue of the nodal metastases. All samples were formalin fixed and paraffin embedded. We identified and quantified more than 1200 proteins by liquid chromatography tandem mass spectrometry with subsequent label-free quantification. An increase of ribosomal or proteasomal proteins in LNM (compared to corresponding PCa) became apparent, while extracellular matrix components rather decreased. Immunohistochemistry (IHC) corroborated accumulation of poly-(ADP-ribose)-polymerase 1 and N-myc-downstream-regulated-gene 3, alpha/beta hydrolase domain-containing protein 11, and protein phosphatase slingshot homolog 3 in LNM. These findings strengthen the present interest in examining PARP inhibitors for the treatment of aggressive PCa. IHC also corroborated increased abundance of retinol dehydrogenase 11 in metastasized primary PCa compared to organ-confined PCa. Generally, metastasizing primary tumors were characterized by an enrichment of proteins involved in cellular lipid metabolic processes with concomitant decrease of cell adhesion proteins. This study highlights the usefulness of a combined proteomic-IHC approach to explore novel aspects in tumor biology. Our initial results open novel opportunities for follow-up studies.

Comparative Proteomics Enables Identification of Nonannotated Cold Shock Proteins in E. coli

Recent advances in mass spectrometry-based proteomics have revealed translation of previously nonannotated microproteins from thousands of small open reading frames (smORFs) in prokaryotic and eukaryotic genomes. Facile methods to determine cellular functions of these newly discovered microproteins are now needed. Here, we couple semiquantitative comparative proteomics with whole-genome database searching to identify two nonannotated, homologous cold shock-regulated microproteins in Escherichia coli K12 substr. MG1655, as well as two additional constitutively expressed microproteins. We apply molecular genetic approaches to confirm expression of these cold shock proteins (YmcF and YnfQ) at reduced temperatures and identify the noncanonical ATT start codons that initiate their translation. These proteins are conserved in related Gram-negative bacteria and are predicted to be structured, which, in combination with their cold shock upregulation, suggests that they are likely to have biological roles in the cell. These results reveal that previously unknown factors are involved in the response of E. coli to lowered temperatures and suggest that further nonannotated, stress-regulated E. coli microproteins may remain to be found. More broadly, comparative proteomics may enable discovery of regulated, and therefore potentially functional, products of smORF translation across many different organisms and conditions.

Reannotation of Genomes by Means of Proteomics Data

Omics approaches have become popular in biology as powerful discovery tools, and currently gain in interest for diagnostic applications. Establishing the accurate genome sequence of any organism is easy, but the outcome of its annotation by means of automatic pipelines remains imprecise. Some protein-encoding genes may be missed as soon as they are specific and poorly conserved in a given taxon, while important to explain the specific traits of the organism. Translational starts are also poorly predicted in a relatively important number of cases, thus impacting the protein sequence database used in proteomics, comparative genomics, and systems biology. The use of high-throughput proteomics data to improve genome annotation is an attractive option to obtain a more comprehensive molecular picture of a given organism. Here, protocols for reannotating prokaryote genomes are described based on shotgun proteomics and derivatization of protein N-termini with a positively charged reagent coupled to high-resolution tandem mass spectrometry.

Proteogenomic Analysis of Mycobacterium smegmatis Using High Resolution Mass Spectrometry

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.