The plant pathogen Pseudomonas syringae pv.tomato (DC3000) causes virulence by delivering effector proteins into host plant cells through its type three secretion system (T3SS). In response to the plant environment DC3000 expresses hypersensitive response and pathogenicity genes (hrp). Pathogenesis depends on the ability of the pathogen to manipulate the plant metabolism and to inhibit plant immunity, which depends to a large degree on the plant's capacity to recognize both pathogen and microbial determinants (PAMP/MAMP-triggered immunity). We have developed and employed MS-based shotgun and targeted proteomics to (i) elucidate the extracellular and secretome composition of DC3000 and (ii) evaluate temporal features of the assembly of the T3SS and the secretion process together with its dependence of pH. The proteomic screen, under hrp inducing in vitro conditions, of extracellular and cytoplasmatic fractions indicated the segregated presence of not only T3SS implicated proteins such as HopP1, HrpK1, HrpA1 and AvrPto1, but also of proteins not usually associated with the T3SS or with pathogenicity. Using multiple reaction monitoring MS (MRM-MS) to quantify HrpA1 and AvrPto1, we found that HrpA1 is rapidly expressed, at a strict pH-dependent rate and is post-translationally processed extracellularly. These features appear to not interfere with rapid AvrPto1 expression and secretion but may suggest some temporal post-translational regulatory mechanism of the T3SS assembly. The high specificity and sensitivity of the MRM-MS approach should provide a powerful tool to measure secretion and translocation in infected tissues.
Mitochondria are ancient endosymbiotic organelles crucial to eukaryotic growth and metabolism. Mammalian mitochondria carry a small genome containing thirteen protein-coding genes with the remaining mitochondrial proteins encoded by the nuclear genome. Little is known about how coordination between the two sets of genes is achieved. Correlation analysis of RNA-seq expression data from large publicly-available datasets is a common method to leverage genetic diversity to infer gene co-expression modules. Here we use this method to investigate nuclear-mitochondrial gene expression coordination. We identify a pitfall in correlation analysis that results from the large variation in the proportion of transcripts from the mitochondrial genome in RNA-seq data. Commonly used normalization techniques based on total read count (such as FPKM or TPM) produce artefactual negative correlations between mitochondrial- and nuclear-encoded transcripts. This also results in artefactual correlations between pairs of nuclear-encoded genes, thus having important consequences for inferring co-expression modules beyond mitochondria. We show that these effects can be overcome by normalizing using the median-ratio normalization (MRN) or trimmed mean of M values (TMM) methods. Using these normalizations, we find only weak and inconsistent correlations between mitochondrial and nuclear-encoded mitochondrial genes in the majority of healthy human tissues from the GTEx database. However, a subset of healthy tissues with high expression of NFkB show significant coordination supporting a role for NFkB in retrograde signalling. Contrastingly, most cancer types show robust coordination of nuclear and mitochondrial OXPHOS gene expression, identifying this as a feature of gene regulation in cancer.
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