Uncovering Genes with Divergent mRNA-Protein Dynamics in Streptomyces coelicolor

Many biological processes are intrinsically dynamic, incurring profound changes at both molecular and physiological levels. Systems analyses of such processes incorporating large-scale transcriptome or proteome profiling can be quite revealing. Although consistency between mRNA and proteins is often implicitly assumed in many studies, examples of divergent trends are frequently observed. Here, we present a comparative transcriptome and proteome analysis of growth and stationary phase adaptation in Streptomyces coelicolor, taking the time-dynamics of process into consideration. These processes are of immense interest in microbiology as they pertain to the physiological transformations eliciting biosynthesis of many naturally occurring therapeutic agents. A shotgun proteomics approach based on mass spectrometric analysis of isobaric stable isotope labeled peptides (iTRAQ™) enabled identification and rapid quantification of approximately 14% of the theoretical proteome of S. coelicolor. Independent principal component analyses of this and DNA microarray-derived transcriptome data revealed that the prominent patterns in both protein and mRNA domains are surprisingly well correlated. Despite this overall correlation, by employing a systematic concordance analysis, we estimated that over 30% of the analyzed genes likely exhibited significantly divergent patterns, of which nearly one-third displayed even opposing trends. Integrating this data with biological information, we discovered that certain groups of functionally related genes exhibit mRNA-protein discordance in a similar fashion. Our observations suggest that differences between mRNA and protein synthesis/degradation mechanisms are prominent in microbes while reaffirming the plausibility of such mechanisms acting in a concerted fashion at a protein complex or sub-pathway level

The Type III Secreted Protein BspR Regulates the Virulence Genes in Bordetella bronchiseptica

Bordetella bronchiseptica is closely related with B. pertussis and B. parapertussis, the causative agents of whooping cough. These pathogenic species share a number of virulence genes, including the gene locus for the type III secretion system (T3SS) that delivers effector proteins. To identify unknown type III effectors in Bordetella, secreted proteins in the bacterial culture supernatants of wild-type B. bronchiseptica and an isogenic T3SS-deficient mutant were compared with iTRAQ-based, quantitative proteomic analysis method. BB1639, annotated as a hypothetical protein, was identified as a novel type III secreted protein and was designated BspR (Bordetella secreted protein regulator). The virulence of a BspR mutant (ΔbspR) in B. bronchiseptica was significantly attenuated in a mouse infection model. BspR was also highly conserved in B. pertussis and B. parapertussis, suggesting that BspR is an essential virulence factor in these three Bordetella species. Interestingly, the BspR-deficient strain showed hyper-secretion of T3SS-related proteins. Furthermore, T3SS-dependent host cell cytotoxicity and hemolytic activity were also enhanced in the absence of BspR. By contrast, the expression of filamentous hemagglutinin, pertactin, and adenylate cyclase toxin was completely abolished in the BspR-deficient strain. Finally, we demonstrated that BspR is involved in the iron-responsive regulation of T3SS. Thus, Bordetella virulence factors are coordinately but inversely controlled by BspR, which functions as a regulator in response to iron starvation

Mapping differential interactomes by affinity purification coupled with data independent mass spectrometry acquisition

Characterizing changes in protein-protein interactions associated with sequence variants (e.g. disease-associated mutations or splice forms) or following exposure to drugs, growth factors or hormones is critical to understanding how protein complexes are built, localized and regulated. Affinity purification (AP) coupled with mass spectrometry permits the analysis of protein interactions under near-physiological conditions, yet monitoring interaction changes requires the development of a robust and sensitive quantitative approach, especially for large-scale studies where cost and time are major considerations. To this end, we have coupled AP to data-independent mass spectrometric acquisition (SWATH), and implemented an automated data extraction and statistical analysis pipeline to score modulated interactions. Here, we use AP-SWATH to characterize changes in protein-protein interactions imparted by the HSP90 inhibitor NVP-AUY922 or melanoma-associated mutations in the human kinase CDK4. We show that AP-SWATH is a robust label-free approach to characterize such changes, and propose a scalable pipeline for systems biology studies

Identification of Novel Molecular Targets for Endometrial Cancer Using a Drill-Down LC-MS/MS Approach with iTRAQ

BACKGROUND: The number of patients with endometrial carcinoma (EmCa) with advanced stage or high histological grade is increasing and prognosis has not improved for over the last decade. There is an urgent need for the discovery of novel molecular targets for diagnosis, prognosis and treatment of EmCa, which will have the potential to improve the clinical strategy and outcome of this disease. METHODOLOGY AND RESULTS: We used a "drill-down" proteomics approach to facilitate the identification of novel molecular targets for diagnosis, prognosis and/or therapeutic intervention for EmCa. Based on peptide ions identified and their retention times in the first LC-MS/MS analysis, an exclusion list was generated for subsequent iterations. A total of 1529 proteins have been identified below the Proteinpilot® 5% error threshold from the seven sets of iTRAQ experiments performed. On average, the second iteration added 78% new peptides to those identified after the first run, while the third iteration added 36% additional peptides. Of the 1529 proteins identified, only 40 satisfied our criteria for significant differential expression in EmCa in comparison to normal proliferative tissues. These proteins included metabolic enzymes (pyruvate kinase M2 and lactate dehydrogenase A); calcium binding proteins (S100A6, calcyphosine and calumenin), and proteins involved in regulating inflammation, proliferation and invasion (annexin A1, interleukin enhancer-binding factor 3, alpha-1-antitrypsin, macrophage capping protein and cathepsin B). Network analyses revealed regulation of these molecular targets by c-myc, Her2/neu and TNF alpha, suggesting intervention with these pathways may be a promising strategy for the development of novel molecular targeted therapies for EmCa. CONCLUSIONS: Our analyses revealed the significance of drill-down proteomics approach in combination with iTRAQ to overcome some of the limitations of current proteomics strategies. This study led to the identification of a number of novel molecular targets having therapeutic potential for targeted molecular therapies for endometrial carcinoma

Proteomic Analyses Reveal High Expression of Decorin and Endoplasmin (HSP90B1) Are Associated with Breast Cancer Metastasis and Decreased Survival

BACKGROUND: Breast cancer is the most common malignancy among women worldwide in terms of incidence and mortality. About 10% of North American women will be diagnosed with breast cancer during their lifetime and 20% of those will die of the disease. Breast cancer is a heterogeneous disease and biomarkers able to correctly classify patients into prognostic groups are needed to better tailor treatment options and improve outcomes. One powerful method used for biomarker discovery is sample screening with mass spectrometry, as it allows direct comparison of protein expression between normal and pathological states. The purpose of this study was to use a systematic and objective method to identify biomarkers with possible prognostic value in breast cancer patients, particularly in identifying cases most likely to have lymph node metastasis and to validate their prognostic ability using breast cancer tissue microarrays. METHODS AND FINDINGS: Differential proteomic analyses were employed to identify candidate biomarkers in primary breast cancer patients. These analyses identified decorin (DCN) and endoplasmin (HSP90B1) which play important roles regulating the tumour microenvironment and in pathways related to tumorigenesis. This study indicates that high expression of Decorin is associated with lymph node metastasis (p<0.001), higher number of positive lymph nodes (p<0.0001) and worse overall survival (p = 0.01). High expression of HSP90B1 is associated with distant metastasis (p<0.0001) and decreased overall survival (p<0.0001) these patients also appear to benefit significantly from hormonal treatment. CONCLUSIONS: Using quantitative proteomic profiling of primary breast cancers, two new promising prognostic and predictive markers were found to identify patients with worse survival. In addition HSP90B1 appears to identify a group of patients with distant metastasis with otherwise good prognostic features

Proteomic Analysis of Neisseria gonorrhoeae Biofilms Shows Shift to Anaerobic Respiration and Changes in Nutrient Transport and Outermembrane Proteins

Neisseria gonorrhoeae, the causative agent of gonorrhea, can form biofilms in vitro and in vivo. In biofilms, the organism is more resistant to antibiotic treatment and can serve as a reservoir for chronic infection. We have used stable isotope labeling by amino acids in cell culture (SILAC) to compare protein expression in biofilm and planktonic organisms. Two parallel populations of N. gonorrhoeae strain 1291, which is an arginine auxotroph, were grown for 48 h in continuous-flow chambers over glass, one supplemented with 13C6-arginine for planktonic organisms and the other with unlabeled arginine for biofilm growth. The biofilm and planktonic cells were harvested and lysed separately, and fractionated into three sequential protein extracts. Corresponding heavy (H) planktonic and light (L) biofilm protein extracts were mixed and separated by 1D SDS-PAGE gels, and samples were extensively analyzed by liquid chromatography-mass spectrometry. Overall, 757 proteins were identified, and 152 unique proteins met a 1.5-fold cutoff threshold for differential expression with p-values <0.05. Comparing biofilm to planktonic organisms, this set included 73 upregulated and 54 downregulated proteins. Nearly a third of the upregulated proteins were involved in energy metabolism, with cell envelope proteins making up the next largest group. Of the downregulated proteins, the largest groups were involved in protein synthesis and energy metabolism. These proteomics results were compared with our previously reported results from transcriptional profiling of gonococcal biofilms using microarrays. Nitrite reductase and cytochrome c peroxidase, key enzymes required for anaerobic growth, were detected as highly upregulated in both the proteomic and transcriptomic datasets. These and other protein expression changes observed in the present study were consistent with a shift to anaerobic respiration in gonococcal biofilms, although changes in membrane proteins not explicitly related to this shift may have other functions

Rapid Dopaminergic Modulation of the Fish Hypothalamic Transcriptome and Proteome

Background - Dopamine (DA) is a major neurotransmitter playing an important role in the regulation of vertebrate reproduction. We developed a novel method for the comparison of transcriptomic and proteomic data obtained from in vivo experiments designed to study the neuroendocrine actions of DA. // Methods and Findings - Female goldfish were injected (i.p.) with DA agonists (D1-specific; SKF 38393, or D2-specific; LY 171555) and sacrificed after 5 h. Serum LH levels were reduced by 57% and 75% by SKF 38393 and LY 171555, respectively, indicating that the treatments produced physiologically relevant responses in vivo. Bioinformatic strategies and a ray-finned fish database were established for microarray and iTRAQ proteomic analysis of the hypothalamus, revealing a total of 3088 mRNAs and 42 proteins as being differentially regulated by the treatments. Twenty one proteins and mRNAs corresponding to these proteins appeared on both lists. Many of the mRNAs and proteins affected by the treatments were grouped into the Gene Ontology categorizations of protein complex, signal transduction, response to stimulus, and regulation of cellular processes. There was a 57% and 14% directional agreement between the differentially-regulated mRNAs and proteins for SKF 38393 and LY 171555, respectively. // Conclusions - The results demonstrate the applicability of advanced high-throughput genomic and proteomic analyses in an amendable well-studied teleost model species whose genome has yet to be sequenced. We demonstrate that DA rapidly regulates multiple hypothalamic pathways and processes that are also known to be involved in pathologies of the central nervous system

Towards a Rigorous Network of Protein-Protein Interactions of the Model Sulfate Reducer Desulfovibrio vulgaris Hildenborough

Protein–protein interactions offer an insight into cellular processes beyond what may be obtained by the quantitative functional genomics tools of proteomics and transcriptomics. The aforementioned tools have been extensively applied to study Escherichia coli and other aerobes and more recently to study the stress response behavior of Desulfovibrio vulgaris Hildenborough, a model obligate anaerobe and sulfate reducer and the subject of this study. Here we carried out affinity purification followed by mass spectrometry to reconstruct an interaction network among 12 chromosomally encoded bait and 90 prey proteins based on 134 bait-prey interactions identified to be of high confidence. Protein-protein interaction data are often plagued by the lack of adequate controls and replication analyses necessary to assess confidence in the results, including identification of potential false positives. We addressed these issues through the use of biological replication, exponentially modified protein abundance indices, results from an experimental negative control, and a statistical test to assign confidence to each putative interacting pair applicable to small interaction data studies. We discuss the biological significance of metabolic features of D. vulgaris revealed by these protein-protein interaction data and the observed protein modifications. These include the distinct role of the putative carbon monoxide-induced hydrogenase, unique electron transfer routes associated with different oxidoreductases, and the possible role of methylation in regulating sulfate reduction