The dynamic state of protein turnover: It's about time

In silico estimation of translation efficiency in human cell lines: potential evidence for widespread translational control

Recently large scale transcriptome and proteome datasets for human cells have become available. A striking finding from these studies is that the level of an mRNA typically predicts no more than 40% of the abundance of protein. This correlation represents the overall figure for all genes. We present here a bioinformatic analysis of translation efficiency – the rate at which mRNA is translated into protein. We have analysed those human datasets that include genome wide mRNA and protein levels determined in the same study. The analysis comprises five distinct human cell lines that together provide comparable data for 8,170 genes. For each gene we have used levels of mRNA and protein combined with protein stability data from the HeLa cell line to estimate translation efficiency. This was possible for 3,990 genes in one or more cell lines and 1,807 genes in all five cell lines. Interestingly, our analysis and modelling shows that for many genes this estimated translation efficiency has considerable consistency between cell lines. Some deviations from this consistency likely result from the regulation of protein degradation. Others are likely due to known translational control mechanisms. These findings suggest it will be possible to build improved models for the interpretation of mRNA expression data. The results we present here provide a view of translation efficiency for many genes. We provide an online resource allowing the exploration of translation efficiency in genes of interest within different cell lines (http://bioanalysis.otago.ac.nz/TranslationEfficiency).

An Internal Standard-Assisted Synthesis and Degradation Proteomic Approach Reveals the Potential Linkage between VPS4B Depletion and Activation of Fatty Acid β-Oxidation in Breast Cancer Cells

The endosomal/lysosomal system, in particular the endosomal sorting complexes required for transport (ESCRTs), plays an essential role in regulating the trafficking and destination of endocytosed receptors and their associated signaling molecules. Recently, we have shown that dysfunction and down-regulation of vacuolar protein sorting 4B (VPS4B), an ESCRT-III associated protein, under hypoxic conditions can lead to the abnormal accumulation of epidermal growth factor receptor (EGFR) and aberrant EGFR signaling in breast cancer. However, the pathophysiological consequences of VPS4B dysfunction remain largely elusive. In this study, we used an internal standard-assisted synthesis and degradation mass spectrometry (iSDMS) method, which permits the direct measurement of protein synthesis, degradation and protein dynamic expression, to address the effects of VPS4B dysfunction in altering EGF-mediated protein expression. Our initial results indicate that VPS4B down-regulation decreases the expression of many proteins involved in glycolytic pathways, while increased the expression of proteins with roles in mitochondrial fatty acid β-oxidation were up-regulated in VPS4B-depleted cells. This observation is also consistent with our previous finding that hypoxia can induce VPS4B down-regulated, suggesting that the adoption of fatty acid β-oxidation could potentially serve as an alternative energy source and survival mechanism for breast cancer cells in response to hypoxia-mediated VPS4B dysfunction.

Linking post-translational modifications and variation of phenotypic traits

Enzymes can be post-translationally modified, leading to isoforms with different properties. The phenotypic consequences of the quantitative variability of isoforms have never been studied. We used quantitative proteomics to dissect the relationships between the abundances of the enzymes and isoforms of alcoholic fermentation, metabolic traits, and growth-related traits in Saccharomyces cerevisiae. Although the enzymatic pool allocated to the fermentation proteome was constant over the culture media and the strains considered, there was variation in abundance of individual enzymes and sometimes much more of their isoforms, which suggests the existence of selective constraints on total protein abundance and trade-offs between isoforms. Variations in abundance of some isoforms were significantly associated to metabolic traits and growth-related traits. In particular, cell size and maximum population size were highly correlated to the degree of N-terminal acetylation of the alcohol dehydrogenase. The fermentation proteome was found to be shaped by human selection, through the differential targeting of a few isoforms for each food-processing origin of strains. These results highlight the importance of post-translational modifications in the diversity of metabolic and life-history traits.

Proteome dynamics: revisiting turnover with a global perspective

Although bulk protein turnover has been measured with the use of stable isotope labeled tracers for over half a century, it is only recently that the same approach has become applicable to the level of the proteome, permitting analysis of the turnover of many proteins instead of single proteins or an aggregated protein pool. The optimal experimental design for turnover studies is dependent on the nature of the biological system under study, which dictates the choice of precursor label, protein pool sampling strategy, and treatment of data. In this review we discuss different approaches and, in particular, explore how complexity in experimental design and data processing increases as we shift from unicellular to multicellular systems, in particular animals.

Genome-wide ribosome profiling reveals complex translational regulation in response to oxidative stress

Information on unique and coordinated regulation of transcription and translation in response to stress is central to the understanding of cellular homeostasis. Here we used ribosome profiling coupled with next-generation sequencing to examine the interplay between transcription and translation under conditions of hydrogen peroxide treatment in Saccharomyces cerevisiae. Hydrogen peroxide treatment led to a massive and rapid increase in ribosome occupancy of short upstream ORFs, including those with non-AUG translational starts, and of the N-terminal regions of ORFs that preceded the transcriptional response. In addition, this treatment induced the synthesis of N-terminally extended proteins and elevated stop codon read-through and frameshift events. It also increased ribosome occupancy at the beginning of ORFs and potentially the duration of the elongation step. We identified proteins whose synthesis was regulated rapidly by hydrogen peroxide posttranscriptionally; however, for the majority of genes increased protein synthesis followed transcriptional regulation. These data define the landscape of genome-wide regulation of translation in response to hydrogen peroxide and suggest that potentiation (coregulation of the transcript level and translation) is a feature of oxidative stress.

The degradative inventory of the cell: proteomic insights

SIGNIFICANCE

Protein degradation has been identified as being deregulated in numerous human diseases. Hence, proteins involved in proteasomal as well as lysosomal degradation are regarded as interesting potential drug targets and are thoroughly investigated in clinical studies.

RECENT ADVANCES

Technical advances in the field of quantitative mass spectrometry (MS)-based proteomics allow for detailed investigations of protein degradation dynamics and identifications of responsible protein-protein interaction networks enabling a systematic analysis of the degradative inventory of the cell and its underlying molecular mechanisms.

CRITICAL ISSUES

In the current review we outline recent technical advances and their limitations in MS-based proteomics and discuss their use for the analysis of protein dynamics involved in degradation processes.

FUTURE DIRECTIONS

In the next years the analysis of crosstalk between different posttranslational modifications (PTMs) will be a major focus of MS-based proteomics studies. Increasing evidence highlights the complexity of PTMs with positive and negative feedbacks being discovered. In this regard, the generation of absolute quantitative proteomic data will be essential for theoretical scientists to construct predictive network models that constitute a valuable tool for fast hypothesis testing and for explaining underlying molecular mechanisms.

Mapping the stabilome: a novel computational method for classifying metabolic protein stability

Background

The half-life of a protein is regulated by a range of system properties, including the abundance of components of the degradative machinery and protein modifiers. It is also influenced by protein-specific properties, such as a protein’s structural make-up and interaction partners. New experimental techniques coupled with powerful data integration methods now enable us to not only investigate what features govern protein stability in general, but also to build models that identify what properties determine each protein’s metabolic stability.

Results

In this work we present five groups of features useful for predicting protein stability: (1) post-translational modifications, (2) domain types, (3) structural disorder, (4) the identity of a protein’s N-terminal residue and (5) amino acid sequence. We incorporate these features into a predictive model with promising accuracy. At a 20% false positive rate, the model exhibits an 80% true positive rate, outperforming the only previously proposed stability predictor. We also investigate the impact of N-terminal protein tagging as used to generate the data set, in particular the impact it may have on the measurements for secreted and transmembrane proteins; we train and test our model on a subset of the data with those proteins removed, and show that the model sustains high accuracy. Finally, we estimate system-wide metabolic stability by surveying the whole human proteome.

Conclusions

We describe a variety of protein features that are significantly over- or under-represented in stable and unstable proteins, including phosphorylation, acetylation and destabilizing N-terminal residues. Bayesian networks are ideal for combining these features into a predictive model with superior accuracy and transparency compared to the only other proposed stability predictor. Furthermore, our stability predictions of the human proteome will find application in the analysis of functionally related proteins, shedding new light on regulation by protein synthesis and degradation.

Prolonged α-amanitin treatment of cells for studying mutated polymerases causes degradation of DSIF160 and other proteins

A useful method for studying the function of the mammalian RNA polymerase II takes advantage of the extreme sensitivity of its largest subunit, Rpb1, to α-amanitin. Mutations of interest are introduced into an α-amanitin-resistant version of Rpb1, which is then expressed ectopically in cells. The phenotypes of these cells are then examined after inhibiting the endogenous wild-type polymerase with α-amanitin. Here, we show that cells that are enabled to grow in α-amanitin by expression of an α-amanitin-resistant Rpb1 exhibit changes in cell physiology that can lead to misleading experimental outcomes. The changes we have characterized include the accelerated degradation of some proteins, such as DSIF160, and the reduced rate of synthesis of others. In one series of experiments, we examined an α-amanitin-resistant construct, with a mutant C-terminal domain (CTD), that was unable to direct poly(A)-dependent transcription termination in cells growing in α-amanitin. The potential interpretation that the termination defect in this construct is due to the mutation in the CTD was rejected when the construct was found to be termination-competent in cells grown in the absence of α-amanitin. Instead, it appears that certain termination factors become limiting when the cells are grown in α-amanitin, presumably due to the α-amanitin-induced degradation we have characterized and/or to the inadequate transcription of certain genes by the α-amanitin-resistant Rpb1-containing polymerase.

Determining degradation and synthesis rates of arabidopsis proteins using the kinetics of progressive 15N labeling of two-dimensional gel-separated protein spots

The growth and development of plant tissues is associated with an ordered succession of cellular processes that are reflected in the appearance and disappearance of proteins. The control of the kinetics of protein turnover is central to how plants can rapidly and specifically alter protein abundance and thus molecular function in response to environmental or developmental cues. However, the processes of turnover are largely hidden during periods of apparent steady-state protein abundance, and even when proteins accumulate it is unclear whether enhanced synthesis or decreased degradation is responsible. We have used a (15)N labeling strategy with inorganic nitrogen sources coupled to a two-dimensional fluorescence difference gel electrophoresis and mass spectrometry analysis of two-dimensional IEF/SDS-PAGE gel spots to define the rate of protein synthesis (K(S)) and degradation (K(D)) of Arabidopsis cell culture proteins. Through analysis of MALDI-TOF/TOF mass spectra from 120 protein spots, we were able to quantify K(S) and K(D) for 84 proteins across six functional groups and observe over 65-fold variation in protein degradation rates. K(S) and K(D) correlate with functional roles of the proteins in the cell and the time in the cell culture cycle. This approach is based on progressive (15)N labeling that is innocuous for the plant cells and, because it can be used to target analysis of proteins through the use of specific gel spots, it has broad applicability.

How are tonoplast proteins degraded?

Protein turnover is fundamental both for development and cellular homeostasis. The mechanisms responsible for the turnover of integral membrane proteins in plant cells are however still largely unknown. Recently, considerable attention has been devoted to the degradation of plasma membrane proteins. We have now studied the turnover of a tonoplast protein, the potassium channel TPK1, in fully differentiated Arabidopsis leaf cells and showed that its degradation occurs upon internalization into the vacuole. Here, we discuss the possible mechanisms and triggering events involved.

Systematic analysis of protein pools, isoforms, and modifications affecting turnover and subcellular localization

In higher eukaryotes many genes encode protein isoforms whose properties and biological roles are often poorly characterized. Here we describe systematic approaches for detection of either distinct isoforms, or separate pools of the same isoform, with differential biological properties. Using information from ion intensities we have estimated protein abundance levels and using rates of change in stable isotope labeling with amino acids in cell culture isotope ratios we measured turnover rates and subcellular distribution for the HeLa cell proteome. Protein isoforms were detected using three data analysis strategies that evaluate differences between stable isotope labeling with amino acids in cell culture isotope ratios for specific groups of peptides within the total set of peptides assigned to a protein. The candidate approach compares stable isotope labeling with amino acids in cell culture isotope ratios for predicted isoform-specific peptides, with ratio values for peptides shared by all the isoforms. The rule of thirds approach compares the mean isotope ratio values for all peptides in each of three equal segments along the linear length of the protein, assessing differences between segment values. The three in a row approach compares mean isotope ratio values for each sequential group of three adjacent peptides, assessing differences with the mean value for all peptides assigned to the protein. Protein isoforms were also detected and their properties evaluated by fractionating cell extracts on one-dimensional SDS-PAGE prior to trypsin digestion and MS analysis and independently evaluating isotope ratio values for the same peptides isolated from different gel slices. The effect of protein phosphorylation on turnover rates was analyzed by comparing mean turnover values calculated for all peptides assigned to a protein, either including, or excluding, values for cognate phosphopeptides. Collectively, these experimental and analytical approaches provide a framework for expanding the functional annotation of the genome.