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.

In this paper, we discuss the challenge of large-scale quantification of a proteome, referring to our programme that aims to define the absolute quantity, in copies per cell, of at least 4000 proteins in the yeast Saccharomyces cerevisiae. We have based our strategy on the well-established method of stable isotope dilution, generating isotopically labelled peptides using QconCAT technology, in which artificial genes, encoding concatenations of tryptic fragments as surrogate quantification standards, are designed, synthesised de novo and expressed in bacteria using stable isotopically enriched media. A known quantity of QconCAT is then co-digested with analyte proteins and the heavy:light isotopologues are analysed by mass spectrometry to yield absolute quantification. This workflow brings issues of optimal selection of quantotypic peptides, their assembly into QconCATs, expression, purification and deployment.

Some enteric bacteria including Salmonella have evolved the propanediol-utilising microcompartment (Pdu MCP), a specialised proteinaceous organelle that is essential for 1,2propanediol degradation and enteric pathogenesis. Pdu MCPs are a family of bacterial microcompartments that are self-assembled from hundreds of proteins within the bacterial cytosol. Here, we seek a comprehensive understanding of the stoichiometric composition and organisation of Pdu MCPs. We obtain accurate stoichiometry of shell proteins and internal enzymes of the natural Pdu MCP by QconCAT-driven quantitative mass spectrometry. Genetic deletion of the major shell protein and absolute quantification reveal the stoichiometric and structural remodelling of metabolically functional Pdu MCPs. Decoding the precise protein stoichiometry allows us to develop an organisational model of the Pdu metabolosome. The structural insights into the Pdu MCP are critical for both delineating the general principles underlying bacterial organelle formation, structural robustness and function, and repurposing natural microcompartments using synthetic biology for biotechnological applications.

Defining intracellular protein concentration is critical in molecular systems biology. Although strategies for determining relative protein changes are available, defining robust absolute values in copies per cell has proven significantly more challenging. Here we present a reference data set quantifying over 1800 Saccharomyces cerevisiae proteins by direct means using protein-specific stable-isotope labeled internal standards and selected reaction monitoring (SRM) mass spectrometry, far exceeding any previous study. This was achieved by careful design of over 100 QconCAT recombinant proteins as standards, defining 1167 proteins in terms of copies per cell and upper limits on a further 668, with robust CVs routinely less than 20%. The selected reaction monitoring-derived proteome is compared with existing quantitative data sets, highlighting the disparities between methodologies. Coupled with a quantification of the transcriptome by RNA-seq taken from the same cells, these data support revised estimates of several fundamental molecular parameters: a total protein count of ∼100 million molecules-per-cell, a median of ∼1000 proteins-per-transcript, and a linear model of protein translation explaining 70% of the variance in translation rate. This work contributes a “gold-standard” reference yeast proteome (including 532 values based on high quality, dual peptide quantification) that can be widely used in systems models and for other comparative studies.

Prefractionation of complex mixtures of proteins derived from biological samples is indispensable for proteome analysis via top-down mass spectrometry (MS). Polyacrylamide gel electrophoresis (PAGE), which enables high-resolution protein separation based on molecular size, is a widely used technique in biochemical experiments and has the potential to be useful in sample fractionation for top-down MS analysis. However, the lack of a means to efficiently recover the separated proteins in-gel has always been a barrier to its use in sample prefractionation. In this study, we present a novel experimental workflow, called Passively Eluting Proteins from Polyacrylamide gels as Intact species for MS (“PEPPI-MS”), which allows top-down MS of PAGE-separated proteins. The optimization of Coomassie brilliant blue staining followed by the passive extraction step in the PEPPI-MS workflow enabled the efficient recovery of proteins, separated on commercial precast gels, from a wide range of molecular weight regions in under 10 min. Two-dimensional separation combining offline PEPPI-MS with online reversed-phase liquid chromatographic separation resulted in identification of over 1000 proteoforms recovered from the target region of the gel (≤50 kDa). Given the widespread availability and relatively low cost of traditional sodium dodecyl sulfate (SDS)-PAGE equipment, the PEPPI-MS workflow will be a powerful prefractionation strategy for top-down proteomics.