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.

WormQTL--public archive and analysis web portal for natural variation data in Caenorhabditis spp.

Here, we present WormQTL (http://www.wormqtl.org), an easily accessible database enabling search, comparative analysis and meta-analysis of all data on variation in Caenorhabditis spp. Over the past decade, Caenorhabditis elegans has become instrumental for molecular quantitative genetics and the systems biology of natural variation. These efforts have resulted in a valuable amount of phenotypic, high-throughput molecular and genotypic data across different developmental worm stages and environments in hundreds of C. elegans strains. WormQTL provides a workbench of analysis tools for genotype-phenotype linkage and association mapping based on but not limited to R/qtl (http://www.rqtl.org). All data can be uploaded and downloaded using simple delimited text or Excel formats and are accessible via a public web user interface for biologists and R statistic and web service interfaces for bioinformaticians, based on open source MOLGENIS and xQTL workbench software. WormQTL welcomes data submissions from other worm researchers.

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.

A quantitative targeted proteomics approach to validate predicted microRNA targets in C. elegans.

Efficient experimental strategies are needed to validate computationally predicted microRNA (miRNA) target genes. Here we present a large-scale targeted proteomics approach to validate predicted miRNA targets in Caenorhabditis elegans. Using selected reaction monitoring (SRM), we quantified 161 proteins of interest in extracts from wild-type and let-7 mutant worms. We demonstrate by independent experimental downstream analyses such as genetic interaction, as well as polysomal profiling and luciferase assays, that validation by targeted proteomics substantially enriched for biologically relevant let-7 interactors. For example, we found that the zinc finger protein ZTF-7 was a bona fide let-7 miRNA target. We also validated predicted miR-58 targets, demonstrating that this approach is adaptable to other miRNAs. We propose that targeted mass spectrometry can be applied generally to validate candidate lists generated by computational methods or in large-scale experiments, and that the described strategy should be readily adaptable to other organisms.

The initiative on Model Organism Proteomes (iMOP) Session September 6, 2011, Geneva, Switzerland.

iMOP--the Initiative on Model Organism Proteomes--was accepted as a new HUPO initiative at the Ninth HUPO meeting in Sydney in 2010. A goal of iMOP is to integrate research groups working on a great diversity of species into a model organism community. At the Tenth HUPO meeting in Geneva this variety was reflected in the iMOP session on Tuesday September 6, 2011. The presentations covered the quantitative proteome database PaxDb, proteomics projects studying farm animals, Arabidopsis thaliana, as well as host-pathogen interactions.

The HUPO initiative on Model Organism Proteomes, iMOP.

The community working on model organisms is growing steadily and the number of model organisms for which proteome data are being generated is continuously increasing. To standardize efforts and to make optimal use of proteomics data acquired from model organisms, a new Human Proteome Organisation (HUPO) initiative on model organism proteomes (iMOP) was approved at the HUPO Ninth Annual World Congress in Sydney, 2010. iMOP will seek to stimulate scientific exchange and disseminate HUPO best practices. The needs of model organism researchers for central databases will be better represented, catalyzing the integration of proteomics and organism-specific databases. Full details of iMOP activities, members, tools and resources can be found at our website http://www.imop.uzh.ch/ and new members are invited to join us.

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.

Protein identification false discovery rates for very large proteomics data sets generated by tandem mass spectrometry.

Comprehensive characterization of a proteome is a fundamental goal in proteomics. To achieve saturation coverage of a proteome or specific subproteome via tandem mass spectrometric identification of tryptic protein sample digests, proteomics data sets are growing dramatically in size and heterogeneity. The trend toward very large integrated data sets poses so far unsolved challenges to control the uncertainty of protein identifications going beyond well established confidence measures for peptide-spectrum matches. We present MAYU, a novel strategy that reliably estimates false discovery rates for protein identifications in large scale data sets. We validated and applied MAYU using various large proteomics data sets. The data show that the size of the data set has an important and previously underestimated impact on the reliability of protein identifications. We particularly found that protein false discovery rates are significantly elevated compared with those of peptide-spectrum matches. The function provided by MAYU is critical to control the quality of proteome data repositories and thereby to enhance any study relying on these data sources. The MAYU software is available as standalone software and also integrated into the Trans-Proteomic Pipeline.

Shotgun proteomics data from multiple organisms reveals remarkable quantitative conservation of the eukaryotic core proteome.

Genome-wide, absolute quantification of expressed proteins is not yet within reach for most eukaryotes. However, large numbers of MS-based protein identifications have been deposited in databases, together with information on the observation frequencies of each peptide spectrum ("spectral counts"). We have conducted a meta-analysis using several million peptide observations from five model eukaryotes, establishing a consistent, semi-quantitative analysis pipeline. By inferring and comparing protein abundances across orthologs, we observe: (i) the accuracy of spectral counting predictions increases with sampling depth and can rival that of direct biochemical measurements, (ii) the quantitative makeup of the consistently observed core proteome in eukaryotes is remarkably stable, with abundance correlations exceeding R(S)=0.7 at an evolutionary distance greater than 1000 million years, and (iii) some groups of proteins are more constrained than others. We argue that our observations reveal stabilizing selection: central parts of the eukaryotic proteome appear to be expressed at well-balanced, near-optimal abundance levels. This is consistent with our further observations that essential proteins show lower abundance variations than non-essential proteins, and that gene families that tend to undergo gene duplications are less well constrained than families that keep a single-copy status.

A high-quality catalog of the Drosophila melanogaster proteome.

Understanding how proteins and their complex interaction networks convert the genomic information into a dynamic living organism is a fundamental challenge in biological sciences. As an important step towards understanding the systems biology of a complex eukaryote, we cataloged 63% of the predicted Drosophila melanogaster proteome by detecting 9,124 proteins from 498,000 redundant and 72,281 distinct peptide identifications. This unprecedented high proteome coverage for a complex eukaryote was achieved by combining sample diversity, multidimensional biochemical fractionation and analysis-driven experimentation feedback loops, whereby data collection is guided by statistical analysis of prior data. We show that high-quality proteomics data provide crucial information to amend genome annotation and to confirm many predicted gene models. We also present experimentally identified proteotypic peptides matching approximately 50% of D. melanogaster gene models. This library of proteotypic peptides should enable fast, targeted and quantitative proteomic studies to elucidate the systems biology of this model organism.

Natural Genetic Variation Influences Protein Abundances in C. elegans Developmental Signalling Pathways.

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 N2 (Bristol) and CB4856 (Hawaii) to enable quantitative trait locus (QTL) mapping. About half of the cases from the 44 genes tested showed a statistically significant change in protein abundance between various strains, most of these were however very weak (below 1.3-fold change). We detected a distant 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.

A worm rich in protein: Quantitative, differential, and global proteomics in Caenorhabditis elegans.

The nematode Caenorhabditis elegans (C. elegans) has been used with much success to study a number of biological processes. Although mostly known for its powerful forward and reverse genetics, work from many different groups over the past years has allowed this model organism to develop into a respectable system for proteomics studies as well. Large-scale survey studies led to improved genome annotation and to the generation of proteome catalogs, which set the stage for subsequent targeted proteomics studies. A number of focused comparative studies contributed to a better understanding of insulin signaling, spermatogenesis, oogenesis, and differential gene expression during development. In addition, C. elegans subproteomes and posttranslational modifications like glycosylation and phosphorylation have been identified. Here we describe the history of C. elegans proteomics, and provide a survey of the different methods that have been applied for relative and absolute quantification in comparative and global protein profiling studies in the worm. These studies suggest that C. elegans will provide a rich trove for "worm proteomicists".

Proteomic analysis of synaptosomes using isotope-coded affinity tags and mass spectrometry.

Synaptosomes are isolated synapses produced by subcellular fractionation of brain tissue. They contain the complete presynaptic terminal, including mitochondria and synaptic vesicles, and portions of the postsynaptic side, including the postsynaptic membrane and the postsynaptic density (PSyD). A proteomic characterisation of synaptosomes isolated from mouse brain was performed employing the isotope-coded affinity tag (ICAT) method and tandem mass spectrometry (MS/MS). After isotopic labelling and tryptic digestion, peptides were fractionated by cation exchange chromatography and cysteine-containing peptides were isolated by affinity chromatography. The peptides were identified by microcapillary liquid chromatography-electrospray ionisation MS/MS (muLC-ESI MS/MS). In two experiments, peptides representing a total of 1131 database entries were identified. They are involved in different presynaptic and postsynaptic functions, including synaptic vesicle exocytosis for neurotransmitter release, vesicle endocytosis for synaptic vesicle recycling, as well as postsynaptic receptors and proteins constituting the PSyD. Moreover, a large number of soluble and membrane-bound molecules serving functions in synaptic signal transduction and metabolism were detected. The results provide an inventory of the synaptic proteome and confirm the suitability of the ICAT method for the assessment of synaptic structure, function and plasticity.