Transmembrane segment proteases

Summary: Transmembrane segment proteases comprise a novel class of proteases that cleave substrates within hydrophobic membrane-spanning segments. They cleave in parts of proteins that upon first glance should be protected by the hydrophobic environment of the lipid bilayer. At present, no such protease has been isolated and biochemically characterized. They are defined according to the appearance of the respective cleavage products. All trans-membrane segment proteases seem to participate in a regulated two-step proteolytic process that plays a central role in cellular regulation or is part of a protein degradation pathwa

The Escherichia coli transcriptome mostly consists of independently regulated modules

Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome

Domain Organization of Long Signal Peptides of Single-Pass Integral Membrane Proteins Reveals Multiple Functional Capacity

Targeting signals direct proteins to their extra - or intracellular destination such as the plasma membrane or cellular organelles. Here we investigated the structure and function of exceptionally long signal peptides encompassing at least 40 amino acid residues. We discovered a two-domain organization (“NtraC model”) in many long signals from vertebrate precursor proteins. Accordingly, long signal peptides may contain an N-terminal domain (N-domain) and a C-terminal domain (C-domain) with different signal or targeting capabilities, separable by a presumably turn-rich transition area (tra). Individual domain functions were probed by cellular targeting experiments with fusion proteins containing parts of the long signal peptide of human membrane protein shrew-1 and secreted alkaline phosphatase as a reporter protein. As predicted, the N-domain of the fusion protein alone was shown to act as a mitochondrial targeting signal, whereas the C-domain alone functions as an export signal. Selective disruption of the transition area in the signal peptide impairs the export efficiency of the reporter protein. Altogether, the results of cellular targeting studies provide a proof-of-principle for our NtraC model and highlight the particular functional importance of the predicted transition area, which critically affects the rate of protein export. In conclusion, the NtraC approach enables the systematic detection and prediction of cryptic targeting signals present in one coherent sequence, and provides a structurally motivated basis for decoding the functional complexity of long protein targeting signals

PROlocalizer: integrated web service for protein subcellular localization prediction

Subcellular localization is an important protein property, which is related to function, interactions and other features. As experimental determination of the localization can be tedious, especially for large numbers of proteins, a number of prediction tools have been developed. We developed the PROlocalizer service that integrates 11 individual methods to predict altogether 12 localizations for animal proteins. The method allows the submission of a number of proteins and mutations and generates a detailed informative document of the prediction and obtained results. PROlocalizer is available at http://bioinf.uta.fi/PROlocalizer/

Expression and Characterization of Drosophila Signal Peptide Peptidase-Like (sppL), a Gene That Encodes an Intramembrane Protease

Intramembrane proteases of the Signal Peptide Peptidase (SPP) family play important roles in developmental, metabolic and signaling pathways. Although vertebrates have one SPP and four SPP-like (SPPL) genes, we found that insect genomes encode one Spp and one SppL. Characterization of the Drosophila sppL gene revealed that the predicted SppL protein is a highly conserved structural homolog of the vertebrate SPPL3 proteases, with a predicted nine-transmembrane topology, an active site containing aspartyl residues within a transmembrane region, and a carboxy-terminal PAL domain. SppL protein localized to both the Golgi and ER. Whereas spp is an essential gene that is required during early larval stages and whereas spp loss-of-function reduced the unfolded protein response (UPR), sppL loss of function had no apparent phenotype. This was unexpected given that genetic knockdown phenotypes in other organisms suggested significant roles for Spp-related proteases

Flanking signal and mature peptide residues influence signal peptide cleavage

<p>Abstract</p> <p>Background</p> <p>Signal peptides (SPs) mediate the targeting of secretory precursor proteins to the correct subcellular compartments in prokaryotes and eukaryotes. Identifying these transient peptides is crucial to the medical, food and beverage and biotechnology industries yet our understanding of these peptides remains limited. This paper examines the most common type of signal peptides cleavable by the endoprotease signal peptidase I (SPase I), and the residues flanking the cleavage sites of three groups of signal peptide sequences, namely (i) eukaryotes (Euk) (ii) Gram-positive (Gram+) bacteria, and (iii) Gram-negative (Gram-) bacteria.</p> <p>Results</p> <p>In this study, 2352 secretory peptide sequences from a variety of organisms with amino-terminal SPs are extracted from the manually curated SPdb database for analysis based on physicochemical properties such as p<it>I</it>, aliphatic index, GRAVY score, hydrophobicity, net charge and position-specific residue preferences. Our findings show that the three groups share several similarities in general, but they display distinctive features upon examination in terms of their amino acid compositions and frequencies, and various physico-chemical properties. Thus, analysis or prediction of their sequences should be separated and treated as distinct groups.</p> <p>Conclusion</p> <p>We conclude that the peptide segment recognized by SPase I extends to the start of the mature protein to a limited extent, upon our survey of the amino acid residues surrounding the cleavage processing site. These flanking residues possibly influence the cleavage processing and contribute to non-canonical cleavage sites. Our findings are applicable in defining more accurate prediction tools for recognition and identification of cleavage site of SPs.</p

The Plasmodium Export Element Revisited

We performed a bioinformatical analysis of protein export elements (PEXEL) in the putative proteome of the malaria parasite Plasmodium falciparum. A protein family-specific conservation of physicochemical residue profiles was found for PEXEL-flanking sequence regions. We demonstrate that the family members can be clustered based on the flanking regions only and display characteristic hydrophobicity patterns. This raises the possibility that the flanking regions may contain additional information for a family-specific role of PEXEL. We further show that signal peptide cleavage results in a positional alignment of PEXEL from both proteins with, and without, a signal peptide

Large-Scale Discovery and Characterization of Protein Regulatory Motifs in Eukaryotes

The increasing ability to generate large-scale, quantitative proteomic data has brought with it the challenge of analyzing such data to discover the sequence elements that underlie systems-level protein behavior. Here we show that short, linear protein motifs can be efficiently recovered from proteome-scale datasets such as sub-cellular localization, molecular function, half-life, and protein abundance data using an information theoretic approach. Using this approach, we have identified many known protein motifs, such as phosphorylation sites and localization signals, and discovered a large number of candidate elements. We estimate that ∼80% of these are novel predictions in that they do not match a known motif in both sequence and biological context, suggesting that post-translational regulation of protein behavior is still largely unexplored. These predicted motifs, many of which display preferential association with specific biological pathways and non-random positioning in the linear protein sequence, provide focused hypotheses for experimental validation

Co- and post-translational translocation through the protein-conducting channel:analogous mechanisms at work?

Many proteins are translocated across, or integrated into, membranes. Both functions are fulfilled by the 'translocon/translocase', which contains a membrane-embedded proteinconducting channel (PCC) and associated soluble factors that drive translocation and insertion reactions using nucleotide triphosphates as fuel. This perspective focuses on reinterpreting existing experimental data in light of a recently proposed PCC model comprising a front-to-front dimer of SecY or Sec61 heterotrimeric complexes. In this new framework, we propose (i) a revised model for SRP-SR-mediated docking of the ribosome-nascent polypeptide to the PCC; (ii) that the dynamic interplay between protein substrate, soluble factors and PCC controls the opening and closing of a transmembrane channel across, and/or a lateral gate into, the membrane; and (iii) that co-and post-translational translocation, involving the ribosome and SecA, respectively, not only converge at the PCC but also use analogous mechanisms for coordinating protein translocation