Comparative Functional Analysis of the Caenorhabditis elegans and Drosophila melanogaster Proteomes

The nematode Caenorhabditis elegans is a popular model system in genetics, not least because a majority of human disease genes are conserved in C. elegans. To generate a comprehensive inventory of its expressed proteome, we performed extensive shotgun proteomics and identified more than half of all predicted C. elegans proteins. This allowed us to confirm and extend genome annotations, characterize the role of operons in C. elegans, and semiquantitatively infer abundance levels for thousands of proteins. Furthermore, for the first time to our knowledge, we were able to compare two animal proteomes (C. elegans and Drosophila melanogaster). We found that the abundances of orthologous proteins in metazoans correlate remarkably well, better than protein abundance versus transcript abundance within each organism or transcript abundances across organisms; this suggests that changes in transcript abundance may have been partially offset during evolution by opposing changes in protein abundance

A two‐dimensional protein map of Caenorhabditis elegans

A protein map of Caenorhabditis elegans was constructed by using two‐dimensional gel electrophoresis followed by peptide mass fingerprinting. A whole worm extract of a mixed population was separated on immobilized pH gradient strips 4‐7 L, 3‐10 NL, 6‐11 L and 12 % sodium dodecyl sulfate‐polyacrylamide gel eletrophoresis (SDS‐PAGE) gels. Gels were stained with colloidal Coomassie blue and 286 spots representing 152 proteins were subsequently identified by matrix‐assisted laser desorption/ionization‐mass spectrometry after in‐gel digestion with trypsin. Most of the identified proteins with known cellular function were enzymes related to carbohydrate and lipid metabolism, or structural proteins with subcellular locations in the cytoplasm, mitochondria or cytoskeleton

Multi-Organism Proteomes (iMOP): Advancing our Understanding of Human Biology

A major objective of the Human Proteome Organisation (HUPO) is to promote and support the area of proteomics as it relates to human health and disease. HUPO activity is based on thematic initiatives, work groups and hosting of international conferences [1]. In 2011, a new HUPO initiative on Model Organism Proteomes (iMOP) was established to support an action in which principles, protocols, and data standards developed for human proteomics, could be readily disseminated to proteome researchers working with a wide range of model organisms [2]. In the past four years, iMOP members have hosted international workshops, iMOP sessions under larger international conferences, and actively liaised with proteomics communities outside the sphere of HUPO [3-5]. These exchanges have aided in the evolution of iMOP from an initiative aiming to bridge the research on model organisms and human proteomics to one that embraces the full diversity of the countless organism proteomes that impact human health. These include most significantly species important for agriculture and food production, and bacteria that are indeed of major significance for human health. It soon became clear that the iMOP initiative covered communities that go far beyond what is commonly thought of as model organisms. As a consequence, in 2014 the initiative underwent a self-re-evaluation, to embrace a broader perspective, and re-named the Initiative on Multi-Organism Proteomes (iMOP) to better reflect and support the needs of scientific communities working with non-human proteomes

Model organisms proteomics--from holobionts to human nutrition

Model organisms are an important tool for the development and validation of analytical approaches for proteomics and for the study of basic mechanisms of biological processes. The Initiative on Model Organism Proteomics (iMOP) organized a session during the 11th HUPO World Congress in Boston in 2012, highlighting the potential of proteomics studies in model organism for the elucidation of important mechanisms regulating the interaction of humans with its environment. Major subjects were the use of model organisms for the study of molecular events triggering the interaction of host organisms with the surrounding microbiota and the elucidation of the complex influence of nutrition on the health of human beings

Natural genetic variation differentially affects the proteome and transcriptome in Caenorhabditis elegans

Natural genetic variation is the raw material of evolution and influences disease development and progression. An important question is how this genetic variation translates into variation in protein abundance. To analyze the effects of the genetic background on gene and protein expression in the nematode Caenorhabditis elegans, we quantitatively compared the two genetically highly divergent wild-type strains N2 and CB4856. Gene expression was analyzed by microarray assays, and proteins were quantified using stable isotope labeling by amino acids in cell culture. Among all transcribed genes, we found 1,532 genes to be differentially transcribed between the two wild types. Of the total 3,238 quantified proteins, 129 proteins were significantly differentially expressed between N2 and CB4856. The differentially expressed proteins were enriched for genes that function in insulin-signaling and stress-response pathways, underlining strong divergence of these pathways in nematodes. The protein abundance of the two wild-type strains correlates more strongly than protein abundance versus transcript abundance within each wild type. Our findings indicate that in C. elegans only a fraction of the changes in protein abundance can be explained by the changes in mRNA abundance. These findings corroborate with the observations made across species

コクゴカ ガクシュウ シドウアン ヘイセイ 24ネンド ジッセン ホウコク

Complex traits, including common disease-related traits, are affected by many different genes that function in multiple pathways and networks. The apoptosis, MAPK, Notch and Wnt signalling pathways play important roles in development and disease progression. At the moment we have a poor understanding of how allelic variation affects gene expression in these pathways at the level of translation. Here we report the effect of natural genetic variation on transcript and protein abundance involved in developmental signalling pathways in Caenorhabditis elegans. We used selected reaction monitoring to analyse proteins from the abovementioned four pathways in a set of recombinant inbred lines (RILs) generated from the wild-type strains Bristol N2 and Hawaii CB4856 to enable quantitative trait loci (QTL) mapping. Variation in gene expression was greater in the RILs than in the parental lines, at the proteome as well as at the transcriptome levels. We detected a trans-QTL on the left arm of chromosome II that affected protein abundance of the phosphatidylserine receptor protein PSR-1, and two separate QTLs that influenced embryonic and ionizing radiation-induced apoptosis on chromosome IV. Our results demonstrate that natural variation in C. elegans is sufficient to cause significant changes in signalling pathways both at the gene expression (transcript and protein abundance) and phenotypic levels

pQTL profiles of seven selected signalling pathway proteins.

<p>Blue curves show the significance of the pQTLs multiplied by the sign of the effect of the N2 allele (positive values of blue curve indicate higher protein abundance when the N2 allele is present, whereas negative values indicate higher protein abundance when the CB4856 allele is present). Horizontal orange and red dashed lines show 0.1 and 0.05 FDR thresholds respectively. Vertical dotted grey lines separate chromosomes I to V and X from left to right. Vertical magenta bands indicate the position of the gene in the genome. PSR-1 shows a significant pQTL on the left arm of chromosome II.</p

RILs show similar protein and transcript abundance variation for the tested 44 genes as the parental strains.

<p>Comparison of protein and transcript abundance (log₂ scaled fold changes relative to N2) for 44 signalling pathway proteins in CB4856 and four selected RILs. Horizontal and vertical dashed lines represent the fold change cut-off of 1.3 (~ 0.38 on log₂ scale). Tukey-style box plot on top and right side represents variability in protein and transcript log₂ fold changes respectively. Pearson correlation coefficient is denoted by r. Table on bottom right represents the <i>P</i>-values from the Fligner-Killeen test for homogeneity of variances between protein (column 1) and transcript (column 2) data for RILs compared with CB4856.</p

Signalling pathway proteins show a similar variation in abundance between N2 and CB4856 as a <i>C</i>. <i>elegans</i> shotgun proteome dataset.

<p>Histogram with Tukey-style box plot [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0149418#pone.0149418.ref036" target="_blank">36</a>] on the top for protein abundances measured in CB4856 relative to N2. Vertical dashed lines represent the fold change cut-off of 1.3 (~ 0.38 on log₂ scale). (A) The <i>C</i>. <i>elegans</i> shotgun proteome dataset was quantified using SILAC (data from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0149418#pone.0149418.ref035" target="_blank">35</a>]). (B) Signalling pathway proteins were quantified using SRM.</p