Proteogenomic Gene Structure Validation in the Pineapple Genome.

MD2 pineapple (Ananas comosus) is the second most important tropical crop that preserves crassulacean acid metabolism (CAM), which has high water-use efficiency and is fast becoming the most consumed fresh fruit worldwide. Despite the significance of environmental efficiency and popularity, until very recently, its genome sequence has not been determined and a high-quality annotated proteome has not been available. Here, we have undertaken a pilot proteogenomic study, analyzing the proteome of MD2 pineapple leaves using liquid chromatography-mass spectrometry (LC-MS/MS), which validates 1781 predicted proteins in the annotated F153 (V3) genome. In addition, a further 603 peptide identifications are found that map exclusively to an independent MD2 transcriptome-derived database but are not found in the standard F153 (V3) annotated proteome. Peptide identifications derived from these MD2 transcripts are also cross-referenced to a more recent and complete MD2 genome annotation, resulting in 402 nonoverlapping peptides, which in turn support 30 high-quality gene candidates novel to both pineapple genomes. Many of the validated F153 (V3) genes are also supported by an independent proteomics data set collected for an ornamental pineapple variety. The contigs and peptides have been mapped to the current F153 genome build and are available as bed files to display a custom gene track on the Ensembl Plants region viewer. These analyses add to the knowledge of experimentally validated pineapple genes and demonstrate the utility of transcript-derived proteomics to discover both novel genes and genetic structure in a plant genome, adding value to its annotation.

Translation is an emerging constraint on protein homeostasis in ageing.

Proteins are molecular machines that provide structure and perform vital transport, signalling and enzymatic roles. Proteins expressed by cells require tight regulation of their concentration, folding, localisation, and modifications; however, this state of protein homeostasis is continuously perturbed by tissue-level stresses. While cells in healthy tissues are able to buffer against these perturbations, for example, by expression of chaperone proteins, protein homeostasis is lost in ageing, and can lead to protein aggregation characteristic of protein folding diseases. Here, we review reports of a progressive disconnect between transcriptomic and proteomic regulation during cellular ageing. We discuss how age-associated changes to cellular responses to specific stressors in the tissue microenvironment are exacerbated by loss of ribosomal proteins, ribosomal pausing, and mistranslation.

Translation factor and RNA binding protein mRNA interactomes support broader RNA regulons for posttranscriptional control.

The regulation of translation provides a rapid and direct mechanism to modulate the cellular proteome. In eukaryotes, an established model for the recruitment of ribosomes to mRNA depends upon a set of conserved translation initiation factors. Nevertheless, how cells orchestrate and define the selection of individual mRNAs for translation, as opposed to other potential cytosolic fates, is poorly understood. We have previously found significant variation in the interaction between individual mRNAs and an array of translation initiation factors. Indeed, mRNAs can be separated into different classes based upon these interactions to provide a framework for understanding different modes of translation initiation. Here, we extend this approach to include new mRNA interaction profiles for additional proteins involved in shaping the cytoplasmic fate of mRNAs. This work defines a set of seven mRNA clusters, based on their interaction profiles with 12 factors involved in translation and/or RNA binding. The mRNA clusters share both physical and functional characteristics to provide a rationale for the interaction profiles. Moreover, a comparison with mRNA interaction profiles from a host of RNA binding proteins suggests that there are defined patterns in the interactions of functionally related mRNAs. Therefore, this work defines global cytoplasmic mRNA binding modules that likely coordinate the synthesis of functionally related proteins.

Paralogous translation factors target distinct mRNAs to differentially regulate tolerance to oxidative stress in yeast.

Translation initiation factor 4G (eIF4G) is an integral component of the eIF4F complex which is key to translation initiation for most eukaryotic mRNAs. Many eIF4G isoforms have been described in diverse eukaryotic organisms but we currently have a poor understanding of their functional roles and whether they regulate translation in an mRNA specific manner. The yeast Saccharomyces cerevisiae expresses two eIF4G isoforms, eIF4G1 and eIF4G2, that have previously been considered as functionally redundant with any phenotypic differences arising due to alteration in eIF4G expression levels. Using homogenic strains that express eIF4G1 or eIF4G2 as the sole eIF4G isoforms at comparable expression levels to total eIF4G, we show that eIF4G1 is specifically required to mediate the translational response to oxidative stress. eIF4G1 binds the mRNA cap and remains associated with actively translating ribosomes during oxidative stress conditions and we use quantitative proteomics to show that eIF4G1 promotes oxidative stress-specific proteome changes. eIF4G1, but not eIF4G2, binds the Slf1 LARP protein which appears to mediate the eIF4G1-dependent translational response to oxidative stress. We show similar isoform specific roles for eIF4G in human cells suggesting convergent evolution of multiple eIF4G isoforms offers significant advantages especially where translation must continue under stress conditions.

Loss of regulation of protein synthesis and turnover underpins an attenuated stress response in senescent human mesenchymal stem cells.

Cells respond to stress by synthesizing chaperone proteins that seek to correct protein misfolding and maintain function. However, abrogation of protein homeostasis is a hallmark of aging, leading to loss of function and the formation of proteotoxic aggregates characteristic of pathology. Consequently, discovering the underlying molecular causes of this deterioration in proteostasis is key to designing effective interventions to disease or to maintaining cell health in regenerative medicine strategies. Here, we examined primary human mesenchymal stem cells, cultured to a point of replicative senescence and subjected to heat shock, as an in vitro model of the aging stress response. Multi -omics analysis showed how homeostasis components were reduced in senescent cells, caused by dysregulation of a functional network of chaperones, thereby limiting proteostatic competence. Time-resolved analysis of the primary response factors, including those regulating heat shock protein 70 kDa (HSPA1A), revealed that regulatory control is essentially translational. Senescent cells have a reduced capacity for chaperone protein translation and misfolded protein (MFP) turnover, driven by downregulation of ribosomal proteins and loss of the E3 ubiquitin ligase CHIP (C-terminus of HSP70 interacting protein) which marks MFPs for degradation. This limits the cell's stress response and subsequent recovery. A kinetic model recapitulated these reduced capacities and predicted an accumulation of MFP, a hypothesis supported by evidence of systematic changes to the proteomic fold state. These results thus establish a specific loss of regulatory capacity at the protein, rather than transcript, level and uncover underlying systematic links between aging and loss of protein homeostasis.

AlacatDesigner─Computational Design of Peptide Concatamers for Protein Quantitation.

Protein quantitation via mass spectrometry relies on peptide proxies for the parent protein from which abundances are estimated. Owing to the variability in signal from individual peptides, accurate absolute quantitation usually relies on the addition of an external standard. Typically, this involves stable isotope-labeled peptides, delivered singly or as a concatenated recombinant protein. Consequently, the selection of the most appropriate surrogate peptides and the attendant design in recombinant proteins termed QconCATs are challenges for proteome science. QconCATs can now be built in a "a-la-carte" assembly method using synthetic biology: ALACATs. To assist their design, we present "AlacatDesigner", a tool that supports the peptide selection for recombinant protein standards based on the user's target protein. The user-customizable tool considers existing databases, occurrence in the literature, potential post-translational modifications, predicted miscleavage, predicted divergence of the peptide and protein quantifications, and ionization potential within the mass spectrometer. We show that peptide selections are enriched for good proteotypic and quantotypic candidates compared to empirical data. The software is freely available to use either via a web interface AlacatDesigner, downloaded as a Desktop application or imported as a Python package for the command line interface or in scripts.

Uncertainty-Aware Protein-Level Quantification and Differential Expression Analysis of Proteomics Data with seaMass.

seaMass is an R package for protein-level quantification, normalization, and differential expression analysis of proteomics mass spectrometry data after peptide identification, protein grouping, and feature-level quantification. Using the concept of a blocked experimental design, seaMass can analyze all common discovery proteomics paradigms, including label-free (e.g., Waters Progenesis input), SILAC (e.g., MaxQuant input), isotope labelling (e.g., SCIEX ProteinPilot iTraq and Thermo ProteomeDiscoverer TMT input), and data-independent acquisition (e.g., OpenSWATH-PyProphet input), and is able to scale to study with hundreds of assays or more. By utilizing hierarchical Bayesian modelling, seaMass assesses the quantification reliability of each feature and peptide across assays so that only those in consensus influence the resulting protein group quantification strongly. Similarly, unexplained variation in each individual assay is captured, providing both a metric for quality control and automatic down-weighting of suspect assays. To achieve this, each protein group-level quantification outputted by seaMass is accompanied by the standard deviation of its posterior uncertainty. Moreover, seaMass integrates a flexible differential expression analysis subsystem with false discovery rate control based on the popular MCMCglmm package for Bayesian mixed-effects modelling, and also provides uncertainty-aware principal components analysis. We provide a description for using seaMass to perform an end-to-end analysis using a real dataset associated with a published clinical proteomics study.

Understanding the Role of Yeast Yme1 in Mitochondrial Function Using Biochemical and Proteomics Analyses.

Mitochondrial i-AAA proteinase Yme1 is a multifunctional protein that plays important roles in maintaining mitochondrial protein homeostasis and regulating biogenesis and function of mitochondrial proteins. However, due to the complex interplay of mitochondria and the multifunctional nature of Yme1, how Yme1 affects mitochondrial function and protein homeostasis is still poorly understood. In this study, we investigated how YME1 deletion affects yeast Saccharomyces cerevisiae growth, chronological life span, mitochondrial protein homeostasis and function, with a focus on the mitochondrial oxidative phosphorylation (OXPHOS) complexes. Our results show that whilst the YME1 deleted cells grow poorly under respiratory conditions, they grow similar to wild-type yeast under fermentative conditions. However, the chronological life span is impaired, indicating that Yme1 plays a key role in longevity. Using highly enriched mitochondrial extract and proteomic analysis, we show that the abundances of many mitochondrial proteins are altered by YME1 deletion. Several components of the respiratory chain complexes II, III, IV and V were significantly decreased, suggesting that Yme1 plays an important role in maintaining the level and function of complexes II-V. This result was confirmed using blue native-PAGE and in-solution-based enzyme activity assays. Taken together, this study shows that Yme1 plays an important role in the chronological life span and mitochondrial protein homeostasis and has deciphered its function in maintaining the activity of mitochondrial OXPHOS complexes.

Yeast Protein Kinase A Isoforms: A Means of Encoding Specificity in the Response to Diverse Stress Conditions?

Eukaryotic cells have developed a complex circuitry of signalling molecules which monitor changes in their intra- and extracellular environments. One of the most widely studied signalling pathways is the highly conserved cyclic AMP (cAMP)/protein kinase A (PKA) pathway, which is a major glucose sensing circuit in the yeast Saccharomyces cerevisiae. PKA activity regulates diverse targets in yeast, positively activating the processes that are associated with rapid cell growth (e.g., fermentative metabolism, ribosome biogenesis and cell division) and negatively regulating the processes that are associated with slow growth, such as respiratory growth, carbohydrate storage and entry into stationary phase. As in higher eukaryotes, yeast has evolved complexity at the level of the PKA catalytic subunit, and Saccharomyces cerevisiae expresses three isoforms, denoted Tpk1-3. Despite evidence for isoform differences in multiple biological processes, the molecular basis of PKA signalling specificity remains poorly defined, and many studies continue to assume redundancy with regards to PKA-mediated regulation. PKA has canonically been shown to play a key role in fine-tuning the cellular response to diverse stressors; however, recent studies have now begun to interrogate the requirement for individual PKA catalytic isoforms in coordinating distinct steps in stress response pathways. In this review, we discuss the known non-redundant functions of the Tpk catalytic subunits and the evolving picture of how these isoforms establish specificity in the response to different stress conditions.

Implementing the reuse of public DIA proteomics datasets: from the PRIDE database to Expression Atlas.

The number of mass spectrometry (MS)-based proteomics datasets in the public domain keeps increasing, particularly those generated by Data Independent Acquisition (DIA) approaches such as SWATH-MS. Unlike Data Dependent Acquisition datasets, the re-use of DIA datasets has been rather limited to date, despite its high potential, due to the technical challenges involved. We introduce a (re-)analysis pipeline for public SWATH-MS datasets which includes a combination of metadata annotation protocols, automated workflows for MS data analysis, statistical analysis, and the integration of the results into the Expression Atlas resource. Automation is orchestrated with Nextflow, using containerised open analysis software tools, rendering the pipeline readily available and reproducible. To demonstrate its utility, we reanalysed 10 public DIA datasets from the PRIDE database, comprising 1,278 SWATH-MS runs. The robustness of the analysis was evaluated, and the results compared to those obtained in the original publications. The final expression values were integrated into Expression Atlas, making SWATH-MS experiments more widely available and combining them with expression data originating from other proteomics and transcriptomics datasets.

Cytosolic aspartate aminotransferase moonlights as a ribosome-binding modulator of Gcn2 activity during oxidative stress.

Regulation of translation is a fundamental facet of the cellular response to rapidly changing external conditions. Specific RNA-binding proteins (RBPs) co-ordinate the translational regulation of distinct mRNA cohorts during stress. To identify RBPs with previously under-appreciated roles in translational control, we used polysome profiling and mass spectrometry to identify and quantify proteins associated with translating ribosomes in unstressed yeast cells and during oxidative stress and amino acid starvation, which both induce the integrated stress response (ISR). Over 800 proteins were identified across polysome gradient fractions, including ribosomal proteins, translation factors, and many others without previously described translation-related roles, including numerous metabolic enzymes. We identified variations in patterns of PE in both unstressed and stressed cells and identified proteins enriched in heavy polysomes during stress. Genetic screening of polysome-enriched RBPs identified the cytosolic aspartate aminotransferase, Aat2, as a ribosome-associated protein whose deletion conferred growth sensitivity to oxidative stress. Loss of Aat2 caused aberrantly high activation of the ISR via enhanced eIF2α phosphorylation and GCN4 activation. Importantly, non-catalytic AAT2 mutants retained polysome association and did not show heightened stress sensitivity. Aat2 therefore has a separate ribosome-associated translational regulatory or 'moonlighting' function that modulates the ISR independent of its aspartate aminotransferase activity.

Whole-cell modeling in yeast predicts compartment-specific proteome constraints that drive metabolic strategies.

When conditions change, unicellular organisms rewire their metabolism to sustain cell maintenance and cellular growth. Such rewiring may be understood as resource re-allocation under cellular constraints. Eukaryal cells contain metabolically active organelles such as mitochondria, competing for cytosolic space and resources, and the nature of the relevant cellular constraints remain to be determined for such cells. Here, we present a comprehensive metabolic model of the yeast cell, based on its full metabolic reaction network extended with protein synthesis and degradation reactions. The model predicts metabolic fluxes and corresponding protein expression by constraining compartment-specific protein pools and maximising growth rate. Comparing model predictions with quantitative experimental data suggests that under glucose limitation, a mitochondrial constraint limits growth at the onset of ethanol formation-known as the Crabtree effect. Under sugar excess, however, a constraint on total cytosolic volume dictates overflow metabolism. Our comprehensive model thus identifies condition-dependent and compartment-specific constraints that can explain metabolic strategies and protein expression profiles from growth rate optimisation, providing a framework to understand metabolic adaptation in eukaryal cells.

MRSD: A quantitative approach for assessing suitability of RNA-seq in the investigation of mis-splicing in Mendelian disease.

Variable levels of gene expression between tissues complicates the use of RNA sequencing of patient biosamples to delineate the impact of genomic variants. Here, we describe a gene- and tissue-specific metric to inform the feasibility of RNA sequencing. This overcomes limitations of using expression values alone as a metric to predict RNA-sequencing utility. We have derived a metric, minimum required sequencing depth (MRSD), that estimates the depth of sequencing required from RNA sequencing to achieve user-specified sequencing coverage of a gene, transcript, or group of genes. We applied MRSD across four human biosamples: whole blood, lymphoblastoid cell lines (LCLs), skeletal muscle, and cultured fibroblasts. MRSD has high precision (90.1%-98.2%) and overcomes transcript region-specific sequencing biases. Applying MRSD scoring to established disease gene panels shows that fibroblasts, of these four biosamples, are the optimum source of RNA for 63.1% of gene panels. Using this approach, up to 67.8% of the variants of uncertain significance in ClinVar that are predicted to impact splicing could be assayed by RNA sequencing in at least one of the biosamples. We demonstrate the utility and benefits of MRSD as a metric to inform functional assessment of splicing aberrations, in particular in the context of Mendelian genetic disorders to improve diagnostic yield.

Integrated multi-omics reveals common properties underlying stress granule and P-body formation.

Non-membrane-bound compartments such as P-bodies (PBs) and stress granules (SGs) play important roles in the regulation of gene expression following environmental stresses. We have systematically and quantitatively determined the protein and mRNA composition of PBs and SGs formed before and after nutrient stress. We find that high molecular weight (HMW) complexes exist prior to glucose depletion that we propose may act as seeds for further condensation of proteins forming mature PBs and SGs. We identify an enrichment of proteins with low complexity and RNA binding domains, as well as long, structured mRNAs that are poorly translated following nutrient stress. Many proteins and mRNAs are shared between PBs and SGs including several multivalent RNA binding proteins that promote condensate interactions during liquid-liquid phase separation. We uncover numerous common protein and RNA components across PBs and SGs that support a complex interaction profile during the maturation of these biological condensates. These interaction networks represent a tuneable response to stress, highlighting previously unrecognized condensate heterogeneity. These studies therefore provide an integrated and quantitative understanding of the dynamic nature of key biological condensates.

Core Fermentation (CoFe) granules focus coordinated glycolytic mRNA localization and translation to fuel glucose fermentation.

Glycolysis is a fundamental metabolic pathway for glucose catabolism across biology, and glycolytic enzymes are among the most abundant proteins in cells. Their expression at such levels provides a particular challenge. Here we demonstrate that the glycolytic mRNAs are localized to granules in yeast and human cells. Detailed live cell and smFISH studies in yeast show that the mRNAs are actively translated in granules, and this translation appears critical for the localization. Furthermore, this arrangement is likely to facilitate the higher level organization and control of the glycolytic pathway. Indeed, the degree of fermentation required by cells is intrinsically connected to the extent of mRNA localization to granules. On this basis, we term these granules, core fermentation (CoFe) granules; they appear to represent translation factories, allowing high-level coordinated enzyme synthesis for a critical metabolic pathway.

Characterisation of protein isoforms encoded by the Drosophila Glycogen Synthase Kinase 3 gene shaggy.

The Drosophila shaggy gene (sgg, GSK-3) encodes multiple protein isoforms with serine/threonine kinase activity and is a key player in diverse developmental signalling pathways. Currently it is unclear whether different Sgg proteoforms are similarly involved in signalling or if different proteoforms have distinct functions. We used CRISPR/Cas9 genome engineering to tag eight different Sgg proteoform classes and determined their localization during embryonic development. We performed proteomic analysis of the two major proteoform classes and generated mutant lines for both of these for transcriptomic and phenotypic analysis. We uncovered distinct tissue-specific localization patterns for all of the tagged proteoforms we examined, most of which have not previously been characterised directly at the protein level, including one proteoform initiating with a non-standard codon. Collectively, this suggests complex developmentally regulated splicing of the sgg primary transcript. Further, affinity purification followed by mass spectrometric analyses indicate a different repertoire of interacting proteins for the two major proteoforms we examined, one with ubiquitous expression (Sgg-PB) and one with nervous system specific expression (Sgg-PA). Specific mutation of these proteoforms shows that Sgg-PB performs the well characterised maternal and zygotic segmentations functions of the sgg locus, while Sgg-PA mutants show adult lifespan and locomotor defects consistent with its nervous system localisation. Our findings provide new insights into the role of GSK-3 proteoforms and intriguing links with the GSK-3α and GSK-3ß proteins encoded by independent vertebrate genes. Our analysis suggests that different proteoforms generated by alternative splicing are likely to perform distinct functions.

Disease modeling of core pre-mRNA splicing factor haploinsufficiency.

The craniofacial disorder mandibulofacial dysostosis Guion-Almeida type is caused by haploinsufficiency of the U5 snRNP gene EFTUD2/SNU114. However, it is unclear how reduced expression of this core pre-mRNA splicing factor leads to craniofacial defects. Here we use a CRISPR-Cas9 nickase strategy to generate a human EFTUD2-knockdown cell line and show that reduced expression of EFTUD2 leads to diminished proliferative ability of these cells, increased sensitivity to endoplasmic reticulum (ER) stress and the mis-expression of several genes involved in the ER stress response. RNA-Seq analysis of the EFTUD2-knockdown cell line revealed transcriptome-wide changes in gene expression, with an enrichment for genes associated with processes involved in craniofacial development. Additionally, our RNA-Seq data identified widespread mis-splicing in EFTUD2-knockdown cells. Analysis of the functional and physical characteristics of mis-spliced pre-mRNAs highlighted conserved properties, including length and splice site strengths, of retained introns and skipped exons in our disease model. We also identified enriched processes associated with the affected genes, including cell death, cell and organ morphology and embryonic development. Together, these data support a model in which EFTUD2 haploinsufficiency leads to the mis-splicing of a distinct subset of pre-mRNAs with a widespread effect on gene expression, including altering the expression of ER stress response genes and genes involved in the development of the craniofacial region. The increased burden of unfolded proteins in the ER resulting from mis-splicing would exceed the capacity of the defective ER stress response, inducing apoptosis in cranial neural crest cells that would result in craniofacial abnormalities during development.

Glycolytic flux in Saccharomyces cerevisiae is dependent on RNA polymerase III and its negative regulator Maf1.

Protein biosynthesis is energetically costly, is tightly regulated and is coupled to stress conditions including glucose deprivation. RNA polymerase III (RNAP III)-driven transcription of tDNA genes for production of tRNAs is a key element in efficient protein biosynthesis. Here we present an analysis of the effects of altered RNAP III activity on the Saccharomyces cerevisiae proteome and metabolism under glucose-rich conditions. We show for the first time that RNAP III is tightly coupled to the glycolytic system at the molecular systems level. Decreased RNAP III activity or the absence of the RNAP III negative regulator, Maf1 elicit broad changes in the abundance profiles of enzymes engaged in fundamental metabolism in S. cerevisiae In a mutant compromised in RNAP III activity, there is a repartitioning towards amino acids synthesis de novo at the expense of glycolytic throughput. Conversely, cells lacking Maf1 protein have greater potential for glycolytic flux.

Ribosomal flavours: an acquired taste for specific mRNAs?

The regulation of translation is critical in almost every aspect of gene expression. Nonetheless, the ribosome is historically viewed as a passive player in this process. However, evidence is accumulating to suggest that variations in the ribosome can have an important influence on which mRNAs are translated. Scope for variation is provided via multiple avenues, including heterogeneity at the level of both ribosomal proteins and ribosomal RNAs and their covalent modifications. Together, these variations provide the potential for hundreds, if not thousands, of flavours of ribosome, each of which could have idiosyncratic preferences for the translation of certain messenger RNAs. Indeed, perturbations to this heterogeneity appear to affect specific subsets of transcripts and manifest as cell-type-specific diseases. This review provides a historical perspective of the ribosomal code hypothesis, before outlining the various sources of heterogeneity, their regulation and functional consequences for the cell.

Archetypal transcriptional blocks underpin yeast gene regulation in response to changes in growth conditions.

The transcriptional responses of yeast cells to diverse stresses typically include gene activation and repression. Specific stress defense, citric acid cycle and oxidative phosphorylation genes are activated, whereas protein synthesis genes are coordinately repressed. This view was achieved from comparative transcriptomic experiments delineating sets of genes whose expression greatly changed with specific stresses. Less attention has been paid to the biological significance of 1) consistent, albeit modest, changes in RNA levels across multiple conditions, and 2) the global gene expression correlations observed when comparing numerous genome-wide studies. To address this, we performed a meta-analysis of 1379 microarray-based experiments in yeast, and identified 1388 blocks of RNAs whose expression changes correlate across multiple and diverse conditions. Many of these blocks represent sets of functionally-related RNAs that act in a coordinated fashion under normal and stress conditions, and map to global cell defense and growth responses. Subsequently, we used the blocks to analyze novel RNA-seq experiments, demonstrating their utility and confirming the conclusions drawn from the meta-analysis. Our results provide a new framework for understanding the biological significance of changes in gene expression: 'archetypal' transcriptional blocks that are regulated in a concerted fashion in response to external stimuli.