High-resolution mass spectrometry maps the cytotoxic T lymphocyte (CTL) proteome and the impact of mammalian target of rapamycin complex 1 (mTORC1) on CTLs. The CTL proteome was dominated by metabolic regulators and granzymes and mTORC1 selectively repressed and promoted expression of subset of CTL proteins (~10%). These included key CTL effector molecules, signaling proteins and a subset of metabolic enzymes. Proteomic data highlighted the potential for mTORC1 negative control of phosphatidylinositol (3,4,5)-trisphosphate (PtdIns(3,4,5)P3) production in CTL. mTORC1 was shown to repress PtdIns(3,4,5)P3 production and to determine the mTORC2 requirement for activation of the kinase Akt. Unbiased proteomic analysis thus provides a comprehensive understanding of CTL identity and mTORC1 control of CTL function.

SummaryEffective network analysis of protein data requires high-quality proteomic datasets. Here, we report a near doubling in coverage of the C. elegans adult proteome, identifying >11,000 proteins in total with ∼9,400 proteins reproducibly detected in three biological replicates. Using quantitative mass spectrometry, we identify proteins whose abundances vary with age, revealing a concerted downregulation of proteins involved in specific metabolic pathways and upregulation of cellular stress responses with advancing age. Among these are ∼30 peroxisomal proteins, including the PRX-5/PEX5 import protein. Functional experiments confirm that protein import into the peroxisome is compromised in vivo in old animals. We also studied the behavior of the set of age-variant proteins in chronologically age-matched, long-lived daf-2 insulin/IGF-1-pathway mutants. Unexpectedly, the levels of many of these age-variant proteins did not scale with extended lifespan. This indicates that, despite their youthful appearance and extended lifespans, not all aspects of aging are reset in these long-lived mutants.

Starvation causes comprehensive metabolic changes, which are still not fully understood. Here, we used quantitative proteomics and RNA sequencing to examine the temporal starvation responses in wild-type Caenorhabditis elegans and animals lacking the transcription factor HLH-30. Our findings show that starvation alters the abundance of hundreds of proteins and mRNAs in a temporal manner, many of which are involved in central metabolic pathways, including lipoprotein metabolism. We demonstrate that premature death of hlh-30 animals under starvation can be prevented by knockdown of either vit-1 or vit-5, encoding two different lipoproteins. We further show that the size and number of intestinal lipid droplets under starvation are altered in hlh-30 animals, which can be rescued by knockdown of vit-1. Taken together, this indicates that survival of hlh-30 animals under starvation is closely linked to regulation of intestinal lipid stores. We provide the most detailed poly-omic analysis of starvation responses to date, which serves as a resource for further mechanistic studies of starvation.

We present a methodology using in vivo crosslinking combined with HPLC-MS for the global analysis of endogenous protein complexes by protein correlation profiling. Formaldehyde crosslinked protein complexes were extracted with high yield using denaturing buffers that maintained complex solubility during chromatographic separation. We show this efficiently detects both integral membrane and membrane-associated protein complexes,in addition to soluble complexes, allowing identification and analysis of complexes not accessible in native extracts. We compare the protein complexes detected by HPLC-MS protein correlation profiling in both native and formaldehyde crosslinked U2OS cell extracts. These proteome-wide data sets of both in vivo crosslinked and native protein complexes from U2OS cells are freely available via a searchable online database (www.peptracker.com/epd). Raw data are also available via ProteomeXchange (identifier PXD003754).

Periodic starvation of animals induces large shifts in metabolism but may also influence many other cellular systems and can lead to adaption to prolonged starvation conditions. To date, there is limited understanding of how starvation affects gene expression, particularly at the protein level. Here, we have used mass-spectrometry-based quantitative proteomics to identify global changes in the Caenorhabditis elegans proteome due to acute starvation of young adult animals. Measuring changes in the abundance of over 5,000 proteins, we show that acute starvation rapidly alters the levels of hundreds of proteins, many involved in central metabolic pathways, highlighting key regulatory responses. Surprisingly, we also detect changes in the abundance of chromatin-associated proteins, including specific linker histones, histone variants, and histone posttranslational modifications associated with the epigenetic control of gene expression. To maximize community access to these data, they are presented in an online searchable database, the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd/).

Proteomics studies typically analyze proteins at a population level, using extracts prepared from tens of thousands to millions of cells. The resulting measurements correspond to average values across the cell population and can mask considerable variation in protein expression and function between individual cells or organisms. Here, we report the development of micro‐proteomics for the analysis of Caenorhabditis elegans, a eukaryote composed of 959 somatic cells and ∼1500 germ cells, measuring the worm proteome at a single organism level to a depth of ∼3000 proteins. This includes detection of proteins across a wide dynamic range of expression levels (>6 orders of magnitude), including many chromatin‐associated factors involved in chromosome structure and gene regulation. We apply the micro‐proteomics workflow to measure the global proteome response to heat‐shock in individual nematodes. This shows variation between individual animals in the magnitude of proteome response following heat‐shock, including variable induction of heat‐shock proteins. The micro‐proteomics pipeline thus facilitates the investigation of stochastic variation in protein expression between individuals within an isogenic population of C. elegans. All data described in this study are available online via the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd), an open access, searchable database resource.

Asymmetric cell divisions are required for cellular diversity and defects can lead to altered daughter cell fates and numbers. In a genetic screen for C. elegans mutants with defects in dopaminergic head neuron specification or differentiation, we isolated a new allele of the transcription factor HAM-1 [HSN (Hermaphrodite-Specific Neurons) Abnormal Migration]. Loss of both HAM-1 and its target, the kinase PIG-1 [PAR-1(I)-like Gene], leads to abnormal dopaminergic head neuron numbers. We identified discrete genetic relationships between ham-1, pig-1 and apoptosis pathway genes in dopaminergic head neurons. We used an unbiased, quantitative mass spectrometry-based proteomics approach to characterise direct and indirect protein targets and pathways that mediate the effects of PIG-1 kinase loss in C. elegans embryos. Proteins showing changes in either abundance, or phosphorylation levels, between wild-type and pig-1 mutant embryos are predominantly connected with processes including cell cycle, asymmetric cell division, apoptosis and actomyosin-regulation. Several of these proteins play important roles in C. elegans development. Our data provide an in-depth characterisation of the C. elegans wild-type embryo proteome and phosphoproteome and can be explored via the Encyclopedia of Proteome Dynamics (EPD) – an open access, searchable online database.

DOI: Using Caenorhabditis elegans as a model system, this study describes the development of a streamlined and reproducible ‘micro‐proteomics’ workflow, allowing global proteomics analysis from single worms. This picture combines an image of a C. elegans worm of the same type used in the study (a slightly edited mosaic picture acquired in the Gartner lab) with peptide sequences identified in the dataset, an example MS2 spectrum, and in the background a heatmap from the article. For details see the article by Dalila Bensaddek et al. on page 381.