Proteins are likely to organize into complexes that assemble and disassemble depending on cellular needs. When Ϸ800 yeast strains expressing GFP-tagged proteins were grown to stationary phase, a surprising number of proteins involved in intermediary metabolism and stress response were observed to form punctate cytoplasmic foci. The formation of these discrete physical structures was confirmed by immunofluorescence and mass spectrometry of untagged proteins. The purine biosynthetic enzyme Ade4-GFP formed foci in the absence of adenine, and cycling between punctate and diffuse phenotypes could be controlled by adenine subtraction and addition. Similarly, glutamine synthetase (Gln1-GFP) foci cycled reversibly in the absence and presence of glucose. The structures were neither targeted for vacuolar or autophagosome degradation nor colocalized with P bodies or major organelles. Thus, upon nutrient depletion we observe widespread protein assemblies displaying nutrient-specific formation and dissolution.aggregation ͉ metabolism ͉ microscopy ͉ proteomics ͉ quiescence

Proteomics experiments commonly aim to estimate and detect differential abundance across all expressed proteins. Within this experimental design, some of the most challenging measurements are small fold changes for lower abundance proteins. While bottom-up proteomics methods are approaching comprehensive coverage of even complex eukaryotic proteomes, failing to reliably quantify lower abundance proteins can limit the precision and reach of experiments to much less than the identified—let alone total—proteome. Here we test the ability of two common methods, a tandem mass tagging (TMT) method and a label-free quantitation method (LFQ), to achieve comprehensive quantitative coverage by benchmarking their capacity to measure 3 different levels of change (3-, 2-, and 1.5-fold) across an entire data set. Both methods achieved comparably accurate estimates for all 3-fold-changes. However, the TMT method detected changes that reached statistical significance three times more often due to higher precision and fewer missing values. These findings highlight the importance of refining proteome quantitation methods to bring the number of usefully quantified proteins into closer agreement with the number of total quantified proteins.

Isobaric labeling is a powerful strategy for quantitative mass spectrometry-based proteomic investigations. A complication of such analyses has been the co-isolation of multiple analytes of similar mass-to-charge resulting in the distortion of relative protein abundance measurements across samples. When properly implemented, triple-stage mass spectrometry and synchronous precursor selection (SPS-MS3) can reduce the occurrence of this phenomena, referred to as ion interference. However, no diagnostic tool is available currently to rapidly and accurately assess ion interference. To address this need, we developed a multiplexed TMT-based standard, termed the triple knockout (TKO). This standard is comprised of three yeast proteomes in triplicate, each from a strain deficient in a highly abundant protein (Met6, Pfk2, or Ura2). The relative abundance patterns of these proteins, which can be inferred from dozens of peptide measurements, are representative of ion interference in peptide quantification. We expect no signal in channels where the protein is knocked out, permitting maximum sensitivity for measurements of ion interference against a null background. Here, we emphasize the need to investigate further ion interference-generated ratio distortion and promote the TKO standard as a tool to investigate such issues.

The budding yeast Saccharomyces cerevisiae is a model system for investigating biological processes. Cellular processes are known to be dysregulated because of shifts in carbon sources. However, the comprehensive proteomic alterations thereof have not been fully investigated. Here we examined proteomic alterations in S. cerevisiae due to the adaptation of yeast from glucose to nine different carbon sources – maltose, trehalose, fructose, sucrose, glycerol, acetate, pyruvate, lactic acid, and oleate. Isobaric tag-based mass spectrometry techniques are at the forefront of global proteomic investigations. As such, we used a TMT10-plex strategy to study multiple growth conditions in a single experiment. The SPS-MS3 method on an Orbitrap Fusion Lumos mass spectrometer enabled the quantification of over 5000 yeast proteins across ten carbon sources at a 1% protein-level FDR. On average, the proteomes of yeast cultured in fructose and sucrose deviated the least from those cultured in glucose. As expected, gene ontology classification revealed the major alteration in protein abundances occurred in metabolic pathways and mitochondrial proteins. Our protocol lays the groundwork for further investigation of carbon source-induced protein alterations. Additionally, these data offer a hypothesis-generating resource for future studies aiming to investigate both characterized and uncharacterized genes.

Both focused and large-scale cell biological and biochemical studies have revealed that hundreds of metabolic enzymes across diverse organisms form large intracellular bodies. These proteinaceous bodies range in form from fibers and intracellular foci—such as those formed by enzymes of nitrogen and carbon utilization and of nucleotide biosynthesis—to high-density packings inside bacterial microcompartments and eukaryotic microbodies. Although many enzymes clearly form functional mega-assemblies, it is not yet clear for many recently discovered cases whether they represent functional entities, storage bodies, or aggregates. In this article, we survey intracellular protein bodies formed by metabolic enzymes, asking when and why such bodies form and what their formation implies for the functionality—and dysfunctionality—of the enzymes that comprise them. The panoply of intracellular protein bodies also raises interesting questions regarding their evolution and maintenance within cells. We speculate on models for how such structures form in the first place and why they may be inevitable.

Meiotic chromosome segregation is critical for fertility across eukaryotes, and core meiotic processes are well conserved even between kingdoms. Nevertheless, recent work in animals has shown that at least some meiosis genes are highly diverse or strongly differentiated among populations. What drives this remains largely unknown. We previously showed that autotetraploid Arabidopsis arenosa evolved stable meiosis, likely through reduced crossover rates, and that associated with this there is strong evidence for selection in a subset of meiosis genes known to affect axis formation, synapsis, and crossover frequency. Here, we use genome-wide data to study the molecular evolution of 70 meiosis genes in a much wider sample of A. arenosa. We sample the polyploid lineage, a diploid lineage from the Carpathian Mountains, and a more distantly related diploid lineage from the adjacent, but biogeographically distinct Pannonian Basin. We find that not only did selection act on meiosis genes in the polyploid lineage but also independently on a smaller subset of meiosis genes in Pannonian diploids. Functionally related genes are targeted by selection in these distinct contexts, and in two cases, independent sweeps occurred in the same loci. The tetraploid lineage has sustained selection on more genes, has more amino acid changes in each, and these more often affect conserved or potentially functional sites. We hypothesize that Pannonian diploid and tetraploid A. arenosa experienced selection on structural proteins that mediate sister chromatid cohesion, the formation of meiotic chromosome axes, and synapsis, likely for different underlying reasons.

Mutations in multiple RNA/DNA binding proteins cause Amyotrophic Lateral Sclerosis (ALS). Included among these are the three members of the FET family (FUS, EWSR1 and TAF15) and the structurally similar MATR3. Here, we characterized the interactomes of these four proteins, revealing that they largely have unique interactors, but share in common an association with U1 snRNP. The latter observation led us to analyze the interactome of the U1 snRNP machinery. Surprisingly, this analysis revealed the interactome contains ~220 components, and of these, >200 are shared with the RNA polymerase II (RNAP II) machinery. Among the shared components are multiple ALS and Spinal muscular Atrophy (SMA)-causative proteins and numerous discrete complexes, including the SMN complex, transcription factor complexes, and RNA processing complexes. Together, our data indicate that the RNAP II/U1 snRNP machinery functions in a wide variety of molecular pathways, and these pathways are candidates for playing roles in ALS/SMA pathogenesis.

Mass spectrometry (MS) has become an accessible tool for whole proteome quantitation with the ability to characterize protein expression across thousands of proteins within a single experiment. A subset of MS quantification methods (e.g., SILAC and label-free) monitor the relative intensity of intact peptides, where thousands of measurements can be made from a single mass spectrum. An alternative approach, isobaric labeling, enables precise quantification of multiple samples simultaneously through unique and sample specific mass reporter ions. Consequently, in a single scan, the quantitative signal comes from a limited number of spectral features (≤11). The signal observed for these features is constrained by automatic gain control, forcing codependence of concurrent signals. The study of constrained outcomes primarily belongs to the field of compositional data analysis. We show experimentally that isobaric tag proteomics data are inherently compositional and highlight the implications for data analysis and interpretation. We present a new statistical model and accompanying software that improves estimation accuracy and the ability to detect changes in protein abundance. Finally, we demonstrate a unique compositional effect on proteins with infinite changes. We conclude that many infinite changes will appear small and that the magnitude of these estimates is highly dependent on experimental design.