Comparative proteomic analysis reveals mechanistic insights into Pseudomonas putida F1 growth on benzoate and citrate

Pseudomonas species are capable to proliferate under diverse environmental conditions and thus have a significant bioremediation potential. To enhance our understanding of their metabolic versatility, this study explores the changes in the proteome and physiology of Pseudomonas putida F1 resulting from its growth on benzoate, a moderate toxic compound that can be catabolized, and citrate, a carbon source that is assimilated through central metabolic pathways. A series of repetitive batch cultivations were performed to ensure a complete adaptation of the bacteria to each of these contrasting carbon sources. After several growth cycles, cell growth stabilized at the maximum level and exhibited a reproducible growth profile. The specific growth rates measured for benzoate (1.01 ± 0.11 h-1) and citrate (1.11 ± 0.12 h-1) were similar, while a higher yield was observed for benzoate (0.6 and 0.3 g cell mass per g of benzoate and citrate, respectively), reflecting the different degrees of carbon reduction in the two substrates. Comparative proteomic analysis revealed an enrichment of several oxygenases/dehydrogenases in benzoate-grown cells, indicative of the higher carbon reduction of benzoate. Moreover, the upregulation of all 14 proteins implicated in benzoate degradation via the catechol ortho-cleavage pathway was observed, while several stress-response proteins were increased to aid cells to cope with benzoate toxicity. Unexpectedly, citrate posed more challenges than benzoate in the maintenance of pH homeostasis, as indicated by the enhancement of the Na+/H+ antiporter and carbonic anhydrase. The study provides important mechanistic insights into Pseudomonas adaptation to varying carbon sources that are of great relevance to bioremediation efforts

Pathway analysis and transcriptomics improve protein identification by shotgun proteomics from samples comprising small number of cells - a benchmarking study

BACKGROUND: Proteomics research is enabled with the high-throughput technologies, but our ability to identify expressed proteome is limited in small samples. The coverage and consistency of proteome expression are critical problems in proteomics. Here, we propose pathway analysis and combination of microproteomics and transcriptomics analyses to improve mass-spectrometry protein identification from small size samples. RESULTS: Multiple proteomics runs using MCF-7 cell line detected 4,957 expressed proteins. About 80% of expressed proteins were present in MCF-7 transcripts data; highly expressed transcripts are more likely to have expressed proteins. Approximately 1,000 proteins were detected in each run of the small sample proteomics. These proteins were mapped to gene symbols and compared with gene sets representing canonical pathways, more than 4,000 genes were extracted from the enriched gene sets. The identified canonical pathways were largely overlapping between individual runs. Of identified pathways 182 were shared between three individual small sample runs. CONCLUSIONS: Current technologies enable us to directly detect 10% of expressed proteomes from small sample comprising as few as 50 cells. We used knowledge-based approaches to elucidate the missing proteome that can be verified by targeted proteomics. This knowledge-based approach includes pathway analysis and combination of gene expression and protein expression data for target prioritization. Genes present in both the enriched gene sets (canonical pathways collection) and in small sample proteomics data correspond to approximately 50% of expressed proteomes in larger sample proteomics data. In addition, 90% of targets from canonical pathways were estimated to be expressed. The comparison of proteomics and transcriptomics data, suggests that highly expressed transcripts have high probability of protein expression. However, approximately 10% of expressed proteins could not be matched with the expressed transcripts.The cost of this publication was funded by Vladimir Brusic. (Vladimir Brusic)Published versio

Tumor antigens as proteogenomic biomarkers in invasive ductal carcinomas

Background: The majority of genetic biomarkers for human cancers are defined by statistical screening of high-throughput genomics data. While a large number of genetic biomarkers have been proposed for diagnostic and prognostic applications, only a small number have been applied in the clinic. Similarly, the use of proteomics methods for the discovery of cancer biomarkers is increasing. The emerging field of proteogenomics seeks to enrich the value of genomics and proteomics approaches by studying the intersection of genomics and proteomics data. This task is challenging due to the complex nature of transcriptional and translation regulatory mechanisms and the disparities between genomic and proteomic data from the same samples. In this study, we have examined tumor antigens as potential biomarkers for breast cancer using genomics and proteomics data from previously reported laser capture microdissected ER+ tumor samples. Results: We applied proteogenomic analyses to study the genetic aberrations of 32 tumor antigens determined in the proteomic data. We found that tumor antigens that are aberrantly expressed at the genetic level and expressed at the protein level, are likely involved in perturbing pathways directly linked to the hallmarks of cancer. The results found by proteogenomic analysis of the 32 tumor antigens studied here, capture largely the same pathway irregularities as those elucidated from large-scale screening of genomics analyses, where several thousands of genes are often found to be perturbed. Conclusion: Tumor antigens are a group of proteins recognized by the cells of the immune system. Specifically, they are recognized in tumor cells where they are present in larger than usual amounts, or are physiochemically altered to a degree at which they no longer resemble native human proteins. This proteogenomic analysis of 32 tumor antigens suggests that tumor antigens have the potential to be highly specific biomarkers for different cancers

Histone deacetylase activity is necessary for left-right patterning during vertebrate development

<p>Abstract</p> <p>Background</p> <p>Consistent asymmetry of the left-right (LR) axis is a crucial aspect of vertebrate embryogenesis. Asymmetric gene expression of the TGFβ superfamily member <it>Nodal related 1 </it>(<it>Nr1) </it>in the left lateral mesoderm plate is a highly conserved step regulating the <it>situs </it>of the heart and viscera. In <it>Xenopus</it>, movement of maternal serotonin (5HT) through gap-junctional paths at cleavage stages dictates asymmetry upstream of <it>Nr1</it>. However, the mechanisms linking earlier biophysical asymmetries with this transcriptional control point are not known.</p> <p>Results</p> <p>To understand how an early physiological gradient is transduced into a late, stable pattern of <it>Nr1 </it>expression we investigated epigenetic regulation during LR patterning. Embryos injected with mRNA encoding a dominant-negative of Histone Deacetylase (HDAC) lacked <it>Nr1 </it>expression and exhibited randomized sidedness of the heart and viscera (heterotaxia) at stage 45. Timing analysis using pharmacological blockade of HDACs implicated cleavage stages as the active period. Inhibition during these early stages was correlated with an absence of <it>Nr1 </it>expression at stage 21, high levels of heterotaxia at stage 45, and the deposition of the epigenetic marker H3K4me2 on the <it>Nr1 </it>gene. To link the epigenetic machinery to the 5HT signaling pathway, we performed a high-throughput proteomic screen for novel cytoplasmic 5HT partners associated with the epigenetic machinery. The data identified the known HDAC partner protein Mad3 as a 5HT-binding regulator. While Mad3 overexpression led to an absence of <it>Nr1 </it>transcription and randomized the LR axis, a mutant form of Mad3 lacking 5HT binding sites was not able to induce heterotaxia, showing that Mad3's biological activity is dependent on 5HT binding.</p> <p>Conclusion</p> <p>HDAC activity is a new LR determinant controlling the epigenetic state of <it>Nr1 </it>from early developmental stages. The HDAC binding partner Mad3 may be a new serotonin-dependent regulator of asymmetry linking early physiological asymmetries to stable changes in gene expression during organogenesis.</p