The Optimal Exponent Base for emPAI Is 6.5

Exponentially Modified Protein Abundance Index (emPAI) is an established method of estimating protein abundances from peptide counts in a single LC-MS/MS experiment. EmPAI is defined as 10PAI minus one, where PAI (Protein Abundance Index) denotes the ratio of observed to observable peptides. EmPAI was first proposed by Ishihama et al [1] who found that PAI is approximately proportional to the logarithm of absolute protein concentration. I define emPAI65 = 6.5PAI-1 and show that it performs significantly better than emPAI, while it is equally easy to compute. The higher accuracy of emPAI65 is demonstrated by analyzing three data sets, including the one used in the original study [1]. I conclude that emPAI65 ought to be used instead of the original emPAI for protein quantitation

A 'resource allocator' for transcription based on a highly fragmented T7 RNA polymerase

Synthetic genetic systems share resources with the host, including machinery for transcription and translation. Phage RNA polymerases (RNAPs) decouple transcription from the host and generate high expression. However, they can exhibit toxicity and lack accessory proteins (σ factors and activators) that enable switching between different promoters and modulation of activity. Here, we show that T7 RNAP (883 amino acids) can be divided into four fragments that have to be co‐expressed to function. The DNA‐binding loop is encoded in a C‐terminal 285‐aa ‘σ fragment’, and fragments with different specificity can direct the remaining 601‐aa ‘core fragment’ to different promoters. Using these parts, we have built a resource allocator that sets the core fragment concentration, which is then shared by multiple σ fragments. Adjusting the concentration of the core fragment sets the maximum transcriptional capacity available to a synthetic system. Further, positive and negative regulation is implemented using a 67‐aa N‐terminal ‘α fragment’ and a null (inactivated) σ fragment, respectively. The α fragment can be fused to recombinant proteins to make promoters responsive to their levels. These parts provide a toolbox to allocate transcriptional resources via different schemes, which we demonstrate by building a system which adjusts promoter activity to compensate for the difference in copy number of two plasmids.United States. Office of Naval Research (N00014‐13‐1‐0074)National Institutes of Health (U.S.) (5R01GM095765)National Science Foundation (U.S.) (Synthetic Biology Engineering Research Center (SA5284‐11210))United States. Dept. of Defense (National Defense Science and Engineering Graduate Fellowship (NDSEG) Program))Hertz Foundation (Fellowship

Two Ck1δ transcripts regulated by m6A methylation code for two antagonistic kinases in the control of the circadian clock.

Fustin, J.-M., Kojima, R., Itoh, K., Chang, H.-Y., Shiqi, Y., Zhuang, B., . . . Okamura, H. (2018). Two Ck1δ transcripts regulated by m6A methylation code for two antagonistic kinases in the control of the circadian clock. Proceedings of the National Academy of Sciences of the United States of America, 115(23), 5980-5985. doi:10.1073/pnas.172137111

An RxLR effector from phytophthora infestans prevents re-localisation of two plant NAC transcription factors from the endoplasmic reticulum to the nucleus

The plant immune system is activated following the perception of exposed, essential and invariant microbial molecules that are recognised as non-self. A major component of plant immunity is the transcriptional induction of genes involved in a wide array of defence responses. In turn, adapted pathogens deliver effector proteins that act either inside or outside plant cells to manipulate host processes, often through their direct action on plant protein targets. To date, few effectors have been shown to directly manipulate transcriptional regulators of plant defence. Moreover, little is known generally about the modes of action of effectors from filamentous (fungal and oomycete) plant pathogens. We describe an effector, called Pi03192, from the late blight pathogen Phytophthora infestans, which interacts with a pair of host transcription factors at the endoplasmic reticulum (ER) inside plant cells. We show that these transcription factors are released from the ER to enter the nucleus, following pathogen perception, and are important in restricting disease. Pi03192 prevents the plant transcription factors from accumulating in the host nucleus, revealing a novel means of enhancing host susceptibility

Phosphorylation of the ribosomal protein RPL12/uL11 affects translation during mitosis

Emerging evidence indicates that heterogeneity in ribosome composition can give rise to specialized functions. Until now, research mainly focused on differences in core ribosomal proteins and associated factors. The effect of posttranslational modifications has not been studied systematically. Analyzing ribosome heterogeneity is challenging because individual proteins can be part of different subcomplexes (40S, 60S, 80S, and polysomes). Here we develop polysome proteome profiling to obtain unbiased proteomic maps across ribosomal subcomplexes. Our method combines extensive fractionation by sucrose gradient centrifugation with quantitative mass spectrometry. The high resolution of the profiles allows us to assign proteins to specific subcomplexes. Phosphoproteomics on the fractions reveals that phosphorylation of serine 38 in RPL12/uL11, a known mitotic CDK1 substrate, is strongly depleted in polysomes. Follow-up experiments confirm that RPL12/uL11 phosphorylation regulates the translation of specific subsets of mRNAs during mitosis. Together, our results show that posttranslational modification of ribosomal proteins can regulate translation

Acidic microenvironment plays a key role in human melanoma progression through a sustained exosome mediated transfer of clinically relevant metastatic molecules

Background: Microenvironment cues involved in melanoma progression are largely unknown. Melanoma is highly influenced in its aggressive phenotype by the changes it determinates in its microenvironment, such as pH decrease, in turn influencing cancer cell invasiveness, progression and tissue remodelling through an abundant secretion of exosomes, dictating cancer strategy to the whole host. A role of exosomes in driving melanoma progression under microenvironmental acidity was never described. Methods: We studied four differently staged human melanoma lines, reflecting melanoma progression, under microenvironmental acidic pHs pressure ranging between pH 6.0-6.7. To estimate exosome secretion as a function of tumor stage and environmental pH, we applied a technique to generate native fluorescent exosomes characterized by vesicles integrity, size, density, markers expression, and quantifiable by direct FACS analysis. Functional roles of exosomes were tested in migration and invasion tests. Then we performed a comparative proteomic analysis of acid versus control exosomes to elucidate a specific signature involved in melanoma progression. Results: We found that metastatic melanoma secretes a higher exosome amount than primary melanoma, and that acidic pH increases exosome secretion when melanoma is in an intermediate stage, i.e. metastatic non-invasive. We were thus able to show that acidic pH influences the intercellular cross-talk mediated by exosomes. In fact when exposed to exosomes produced in an acidic medium, pH naïve melanoma cells acquire migratory and invasive capacities likely due to transfer of metastatic exosomal proteins, favoring cell motility and angiogenesis. A Prognoscan-based meta-analysis study of proteins enriched in acidic exosomes, identified 11 genes (HRAS, GANAB, CFL2, HSP90B1, HSP90AB1, GSN, HSPA1L, NRAS, HSPA5, TIMP3, HYOU1), significantly correlating with poor prognosis, whose high expression was in part confirmed in bioptic samples of lymph node metastases. Conclusions: A crucial step of melanoma progression does occur at melanoma intermediate -stage, when extracellular acidic pH induces an abundant release and intra-tumoral uptake of exosomes. Such exosomes are endowed with pro-invasive molecules of clinical relevance, which may provide a signature of melanoma advancement

Cell-selective labeling using amino acid precursors for proteomic studies of multicellular environments.

We report a technique to selectively and continuously label the proteomes of individual cell types in coculture, named cell type-specific labeling using amino acid precursors (CTAP). Through transgenic expression of exogenous amino acid biosynthesis enzymes, vertebrate cells overcome their dependence on supplemented essential amino acids and can be selectively labeled through metabolic incorporation of amino acids produced from heavy isotope-labeled precursors. When testing CTAP in several human and mouse cell lines, we could differentially label the proteomes of distinct cell populations in coculture and determine the relative expression of proteins by quantitative mass spectrometry. In addition, using CTAP we identified the cell of origin of extracellular proteins secreted from cells in coculture. We believe that this method, which allows linking of proteins to their cell source, will be useful in studies of cell-cell communication and potentially for discovery of biomarkers

Integrative Features of the Yeast Phosphoproteome and Protein–Protein Interaction Map

Following recent advances in high-throughput mass spectrometry (MS)–based proteomics, the numbers of identified phosphoproteins and their phosphosites have greatly increased in a wide variety of organisms. Although a critical role of phosphorylation is control of protein signaling, our understanding of the phosphoproteome remains limited. Here, we report unexpected, large-scale connections revealed between the phosphoproteome and protein interactome by integrative data-mining of yeast multi-omics data. First, new phosphoproteome data on yeast cells were obtained by MS-based proteomics and unified with publicly available yeast phosphoproteome data. This revealed that nearly 60% of ∼6,000 yeast genes encode phosphoproteins. We mapped these unified phosphoproteome data on a yeast protein–protein interaction (PPI) network with other yeast multi-omics datasets containing information about proteome abundance, proteome disorders, literature-derived signaling reactomes, and in vitro substratomes of kinases. In the phospho-PPI, phosphoproteins had more interacting partners than nonphosphoproteins, implying that a large fraction of intracellular protein interaction patterns (including those of protein complex formation) is affected by reversible and alternative phosphorylation reactions. Although highly abundant or unstructured proteins have a high chance of both interacting with other proteins and being phosphorylated within cells, the difference between the number counts of interacting partners of phosphoproteins and nonphosphoproteins was significant independently of protein abundance and disorder level. Moreover, analysis of the phospho-PPI and yeast signaling reactome data suggested that co-phosphorylation of interacting proteins by single kinases is common within cells. These multi-omics analyses illuminate how wide-ranging intracellular phosphorylation events and the diversity of physical protein interactions are largely affected by each other