Surveying the global landscape of post-transcriptional regulators.

Numerous proteins regulate gene expression by modulating mRNA translation and decay. To uncover the full scope of these post-transcriptional regulators, we conducted an unbiased survey that quantifies regulatory activity across the budding yeast proteome and delineates the protein domains responsible for these effects. Our approach couples a tethered function assay with quantitative single-cell fluorescence measurements to analyze ~50,000 protein fragments and determine their effects on a tethered mRNA. We characterize hundreds of strong regulators, which are enriched for canonical and unconventional mRNA-binding proteins. Regulatory activity typically maps outside the RNA-binding domains themselves, highlighting a modular architecture that separates mRNA targeting from post-transcriptional regulation. Activity often aligns with intrinsically disordered regions that can interact with other proteins, even in core mRNA translation and degradation factors. Our results thus reveal networks of interacting proteins that control mRNA fate and illuminate the molecular basis for post-transcriptional gene regulation.

Microdomain Protein Nce102 Is a Local Sensor of Plasma Membrane Sphingolipid Balance.

Sphingolipids are essential building blocks of eukaryotic membranes and important signaling molecules that are regulated tightly in response to environmental and physiological inputs. While their biosynthetic pathway has been well-described, the mechanisms that facilitate the perception of sphingolipid levels at the plasma membrane remain to be uncovered. In Saccharomyces cerevisiae, the Nce102 protein has been proposed to function as a sphingolipid sensor as it changes its plasma membrane distribution in response to sphingolipid biosynthesis inhibition. We show that Nce102 redistributes specifically in regions of increased sphingolipid demand, e.g., membranes of nascent buds. Furthermore, we report that the production of Nce102 increases following sphingolipid biosynthesis inhibition and that Nce102 is internalized when excess sphingolipid precursors are supplied. This finding suggests that the total amount of Nce102 in the plasma membrane is a measure of the current need for sphingolipids, whereas its local distribution marks sites of high sphingolipid demand. The physiological role of Nce102 in the regulation of sphingolipid synthesis is demonstrated by mass spectrometry analysis showing reduced levels of hydroxylated complex sphingolipids in response to heat stress in the nce102Δ deletion mutant. We also demonstrate that Nce102 behaves analogously in the widespread human fungal pathogen Candida albicans, suggesting a conserved principle of local sphingolipid control across species. IMPORTANCE Microorganisms are challenged constantly by their rapidly changing environment. To survive, they have developed diverse mechanisms to quickly perceive stressful situations and adapt to them appropriately. The primary site of both stress sensing and adaptation is the plasma membrane. We identified the yeast protein Nce102 as a marker of local sphingolipid levels and fluidity in the plasma membrane. Nce102 is an important structural and functional component of the membrane compartment Can1 (MCC), a plasma membrane microdomain stabilized by a large cytosolic hemitubular protein scaffold, the eisosome. The MCC/eisosomes are widely conserved among fungi and unicellular algae. To determine if Nce102 carries out similar functions in other organisms, we analyzed the human fungal pathogen Candida albicans and found that Nce102 responds to sphingolipid levels also in this organism, which has potential applications for the development of novel therapeutic approaches. The presented study represents a valuable model for how organisms regulate plasma membrane sphingolipids.

Immunoaffinity purification of endogenous proteins from S. cerevisiae for post-translational modification and protein interaction analysis.

Protein regulation by post-translational modifications and protein-protein interactions is critical to controlling molecular pathways. Here, we describe an immunoaffinity purification approach in Saccharomyces cerevisiae. The protocol uses an endogenously-expressed epitope-tagged protein and can be applied to the identification of post-translational modifications or protein binding partners. The lysine methyltransferase Set5 is used as an example here to purify phosphorylated Set5 and identify phosphosites; however, this approach can be applied to a diverse set of proteins in yeast. For complete details on the use and execution of this protocol, please refer to Jaiswal et al. (2020).

A Multi-Perspective Proximity View on the Dynamic Head Region of the Ribosomal 40S Subunit.

A comparison of overlapping proximity captures at the head region of the ribosomal 40S subunit (hr40S) in Saccharomyces cerevisiae from four adjacent perspectives, namely Asc1/RACK1, Rps2/uS5, Rps3/uS3, and Rps20/uS10, corroborates dynamic co-localization of proteins that control activity and fate of both ribosomes and mRNA. Co-locating factors that associate with the hr40S are involved in (i) (de)ubiquitination of ribosomal proteins (Hel2, Bre5-Ubp3), (ii) clamping of inactive ribosomal subunits (Stm1), (iii) mRNA surveillance and vesicular transport (Smy2, Syh1), (iv) degradation of mRNA (endo- and exonucleases Ypl199c and Xrn1, respectively), (v) autophagy (Psp2, Vps30, Ykt6), and (vi) kinase signaling (Ste20). Additionally, they must be harmonized with translation initiation factors (eIF3, cap-binding protein Cdc33, eIF2A) and mRNA-binding/ribosome-charging proteins (Scp160, Sro9). The Rps/uS-BioID perspectives revealed substantial Asc1/RACK1-dependent hr40S configuration indicating a function of the ß-propeller in context-specific spatial organization of this microenvironment. Toward resolving context-specific constellations, a Split-TurboID analysis emphasized the ubiquitin-associated factors Def1 and Lsm12 as neighbors of Bre5 at hr40S. These shuttling proteins indicate a common regulatory axis for the fate of polymerizing machineries for the biosynthesis of proteins in the cytoplasm and RNA/DNA in the nucleus.

Measuring in vivo protein turnover and exchange in yeast macromolecular assemblies.

We present a comprehensive and robust protocol to track the dynamics of all proteins in a complex in yeast cells. A single member of the protein assembly is tagged and conditionally expressed, minimizing the perturbations to the protein complex. Then, SILAC labeling and affinity purification are used for the assessment of the whole protein complex dynamics. This method can determine and distinguish both subunit turnover and exchange specifically in an assembly to provide a comprehensive picture of assembly dynamics. For complete details on the use and execution of this protocol, please refer to Hakhverdyan et al. (2021).

2nSILAC for Quantitative Proteomics of Prototrophic Baker's Yeast.

Stable isotope labeling by amino acids in cell culture (SILAC) combined with high-resolution mass spectrometry is a quantitative strategy for the comparative analysis of (sub)proteomes. It is based on the metabolic incorporation of stable isotope-coded amino acids during growth of cells or organisms. Here, complete labeling of proteins with the amino acid(s) selected for incorporation needs to be guaranteed to enable accurate quantification on a proteomic scale. Wild-type strains of baker's yeast (Saccharomyces cerevisiae ), which is a widely accepted and well-studied eukaryotic model organism, are generally able to synthesize all amino acids on their own (i.e., prototrophic). To render them amenable to SILAC, auxotrophies are introduced by genetic manipulations. We addressed this limitation by developing a generic strategy for complete "native" labeling of prototrophic S. cerevisiae with isotope-coded arginine and lysine, referred to as "2nSILAC". It allows for directly using and screening several genome-wide yeast mutant collections that are easily accessible to the scientific community for functional proteomic studies but are based on prototrophic variants of S. cerevisiae.

Small-scale hypoxic cultures for monitoring the spatial reorganization of glycolytic enzymes in Saccharomyces cerevisiae.

At normal oxygen concentration, glycolytic enzymes are scattered in the cytoplasm of Saccharomyces cerevisiae. Under hypoxia, however, most of these enzymes, including enolase, pyruvate kinase, and phosphoglycerate mutase, spatially reorganize to form cytoplasmic foci. We tested various small-scale hypoxic culture systems and showed that enolase foci formation occurs in all the systems tested, including in liquid and on solid media. Notably, a small-scale hypoxic culture in a bench-top multi-gas incubator enabled the regulation of oxygen concentration in the media and faster foci formation. Here, we demonstrate that the foci formation of enolase starts within few hours after changing the oxygen concentration to 1% in a small-scale cultivation system. The order of foci formation by each enzyme is tightly regulated, and of the three enzymes, enolase was the fastest to respond to hypoxia. We further tested the use of the small-scale cultivation method to screen reagents that can control the spatial reorganization of enzymes under hypoxia. An AMPK inhibitor, dorsomorphin, was found to delay formation of the foci in all three glycolytic enzymes tested. These methods and results provide efficient ways to investigate the spatial reorganization of proteins under hypoxia to form a multienzyme assembly, the META body, thereby contributing to understanding and utilizing natural systems to control cellular metabolism via the spatial reorganization of enzymes.

Mesh Fragmentation Improves Dissociation Efficiency in Top-down Proteomics.

Top-down proteomics is a key mass spectrometry-based technology for comprehensive analysis of proteoforms. Proteoforms exhibit multiple high charge states and isotopic forms in full MS scans. The dissociation behavior of proteoforms in different charge states and subjected to different collision energies is highly variable. The current widely employed data-dependent acquisition (DDA) method selects a narrow m/z range (corresponding to a single proteoform charge state) for dissociation from the most abundant precursors. We describe here Mesh, a novel dissociation strategy, to dissociate multiple charge states of one proteoform with multiple collision energies. We show that the Mesh strategy has the potential to generate fragment ions with improved sequence coverage and improve identification ratios in top-down proteomic analyses of complex samples. The strategy is implemented within an open-source instrument control software program named MetaDrive to perform real time deconvolution and precursor selection.

Phenyl-bonded monolithic silica capillary column liquid chromatographic separation and detection of fluorogenic derivatized intact proteins.

Prior to the identification of proteins for proteomics analysis in human cells, separation of fluorogenic derivatized proteins with a fluorogenic reagent, 7-chloro-N-[2-(dimethylamino)ethyl]-2,1,3-benzoxadiazole-4-sulfonamide, has typically been performed by using a conventional reversed-phase HPLC column. However, the number of proteins in human cells (HepaRG) that are separated by this conventional approach is limited to approximately 500. In this study, a nanoflow liquid chromatography system with an evaluated phenyl-bonded monolithic silica capillary column (0.1 mm i.d., 700 mm length) was used to increase the number of separated fluorogenic derivatized proteins. This system was used to separate derivatized human cell proteins (K562) and yeast (Saccharomyces cerevisiae) proteins as model cell proteomes. More than 1,300 protein peaks were separated/detected from both cell proteomes. We present a straightforward comparison of multiple separation profiles using a novel chromatogram display approach, termed the "spiderweb" chromatogram. In addition, to validate that the detected peaks are derived from proteins, a mass spectrometer was connected to the capillary column and deconvolution of the obtained mass spectra was performed. Furthermore, different molecular weight distribution profiles of the expressed proteins were observed between the two cell proteomes.

A comparative study of evaluating missing value imputation methods in label-free proteomics.

The presence of missing values (MVs) in label-free quantitative proteomics greatly reduces the completeness of data. Imputation has been widely utilized to handle MVs, and selection of the proper method is critical for the accuracy and reliability of imputation. Here we present a comparative study that evaluates the performance of seven popular imputation methods with a large-scale benchmark dataset and an immune cell dataset. Simulated MVs were incorporated into the complete part of each dataset with different combinations of MV rates and missing not at random (MNAR) rates. Normalized root mean square error (NRMSE) was applied to evaluate the accuracy of protein abundances and intergroup protein ratios after imputation. Detection of true positives (TPs) and false altered-protein discovery rate (FADR) between groups were also compared using the benchmark dataset. Furthermore, the accuracy of handling real MVs was assessed by comparing enriched pathways and signature genes of cell activation after imputing the immune cell dataset. We observed that the accuracy of imputation is primarily affected by the MNAR rate rather than the MV rate, and downstream analysis can be largely impacted by the selection of imputation methods. A random forest-based imputation method consistently outperformed other popular methods by achieving the lowest NRMSE, high amount of TPs with the average FADR < 5%, and the best detection of relevant pathways and signature genes, highlighting it as the most suitable method for label-free proteomics.

Comparison of protein and peptide fractionation approaches in protein identification and quantification from Saccharomyces cerevisiae.

Shotgun proteomics is a high-throughput technology which has been developed with the aim of investigating the maximum number of proteins in cells in a given experiment. However, protein discovery and data generation vary in depth and coverage when different technical strategies are selected. In this study, three different sample preparation approaches, and peptide or protein fractionation methods, were applied to identify and quantify proteins from log-phase yeast lysate: sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), filter-aided sample preparation coupled with gas phase fractionation (FASP-GPF), and FASP - high pH reversed phase fractionation (HpH). Fractions were initially analyzed and compared using nanoflow liquid chromatography - tandem mass spectrometry (nanoLC-MS/MS) employing data dependent acquisition on a linear ion trap instrument. The number of fractions and analytical replicates was adjusted so that each experiment used a similar amount of mass spectrometric instrument time. A second set of experiments was performed, comparing FASP-GPF, SDS-PAGE and FASP-HpH using a Q Exactive Orbitrap mass spectrometer. Compared with results from the linear ion trap mass spectrometer, the use of a Q Exactive Orbitrap mass spectrometer enabled a substantial increase in protein identifications, and an even greater increase in peptide identifications. This shows that the main advantage of using the higher resolution instrument is in increased proteome coverage. A total of 1035, 1357 and 2134 proteins were separately identified by FASP-GPF, SDS-PAGE and FASP-HpH. Combining results from the Orbitrap experiments, there were a total of 2269 proteins found, with 94% of them identified using the FASP-HpH method. Therefore, the FASP-HpH method is the optimal choice among these approaches, when applied to this type of sample.

In vivo mRNA display enables large-scale proteomics by next generation sequencing.

Large-scale proteomic methods are essential for the functional characterization of proteins in their native cellular context. However, proteomics has lagged far behind genomic approaches in scalability, standardization, and cost. Here, we introduce in vivo mRNA display, a technology that converts a variety of proteomics applications into a DNA sequencing problem. In vivo-expressed proteins are coupled with their encoding messenger RNAs (mRNAs) via a high-affinity stem-loop RNA binding domain interaction, enabling high-throughput identification of proteins with high sensitivity and specificity by next generation DNA sequencing. We have generated a high-coverage in vivo mRNA display library of the Saccharomyces cerevisiae proteome and demonstrated its potential for characterizing subcellular localization and interactions of proteins expressed in their native cellular context. In vivo mRNA display libraries promise to circumvent the limitations of mass spectrometry-based proteomics and leverage the exponentially improving cost and throughput of DNA sequencing to systematically characterize native functional proteomes.

A Single Site Phosphorylation on Hsp82 Ensures Cell Survival during Starvation in Saccharomyces cerevisiae.

Unicellular organisms live under diverse stressful conditions and must respond and adapt quickly to these stresses. When these stresses persist, cells favor a transition to quiescence. There are changes to many processes when cells begin their entry into quiescence. It has been reported that Hsp82 plays an important role in several such processes, and its distribution and activity change according to nutrient conditions. In this study, we found that the subcellular distribution of Hsp82 is regulated by its co-chaperone Ppt1. Under starvation conditions, Ppt1 expression was significantly reduced by a TOR-independent pathway. Furthermore, we found that Ppt1 regulates Hsp82 distribution in the cytoplasm and nucleus by dephosphorylating the S485 residue on Hsp82. The Hsp82S485A strain has impaired membrane-related protein transport, and its cell size did not become larger in quiescence compared to log phase, resulting in failure to survive during starvation.

Developing a cell-bound detection system for the screening of oxidase activity using the fluorescent peroxide sensor roGFP2-Orp1.

Accurate yet efficient high-throughput screenings have emerged as essential technology for enzyme engineering via directed evolution. Modern high-throughput screening platforms for oxidoreductases are commonly assisted by technologies such as surface display and rely on emulsification techniques to facilitate single-cell analysis via fluorescence-activated cell sorting. Empowered by the dramatically increased throughput, the screening of significantly larger sequence spaces in acceptable time frames is achieved but usually comes at the cost of restricted applicability. In this work, we tackle this problem by utilizing roGFP2-Orp1 as a fluorescent one-component detection system for enzymatic H2O2 formation. We determined the kinetic parameters of the roGFP2-Orp1 reaction with H2O2 and established an efficient immobilization technique for the sensor on Saccharomyces cerevisiae cells employing the lectin Concanavalin A. This allowed to realize a peroxide-sensing shell on enzyme-displaying cells, a system that was successfully employed to screen for H2O2 formation of enzyme variants in a whole-cell setting.

Differential distribution and proteomic response of Saccharomyces cerevisiae and non-model yeast species to zinc.

Zinc surplus in yeast cells has been previously investigated thanks to transcriptomic studies by using traditionally Saccharomyces cerevisiae as a model. However, proteome response under zinc-replete conditions needs to be further studied in yeast. For that reason, eight yeast strains from seven different species were inoculated in zinc-depleted and zinc-replete media. The quantitative and qualitative comparative label-free proteomic analysis enabled the identification of between 2000 and 3000 proteins from each strain, and changes to the proteome ranged from 2.5% to 43.7% of identified proteins. Functional analysis (Blast2Go) has allowed the characterization of differentially abundant proteins. Common zinc-responsive proteins have been detected for the eight strains such as oxidoreductases and transferases (increased in abundance) although more of the changes detected were not shared by all the strains tested. Zinc distribution under replete conditions has been analysed in cell wall fractions, and cytoplasm plus organelles (intracellular fraction), with the latter identified to be the main zinc reservoir. Additionally, the energy dispersive spectroscopy coupled to the scanning electron microscopy technique has permitted the visualization of zinc in the whole cell. Proteomic analysis revealed that while there were some shared responses, the non-model yeast species also showed distinct proteomic profiles in zinc-replete conditions, compared to S. cerevisiae, revealing new zinc-responsive proteins in yeast.

Yeast Intracellular Staining (yICS): Enabling High-Throughput, Quantitative Detection of Intracellular Proteins via Flow Cytometry for Pathway Engineering.

The complexities of pathway engineering necessitate screening libraries to discover phenotypes of interest. However, this approach is challenging when desirable phenotypes cannot be directly linked to growth advantages or fluorescence. In these cases, the ability to rapidly quantify intracellular proteins in the pathway of interest is critical to expedite the clonal selection process. While Saccharomyces cerevisiae remains a common host for pathway engineering, current approaches for intracellular protein detection in yeast either have low throughput, can interfere with protein function, or lack the ability to detect multiple proteins simultaneously. To fill this need, we developed yeast intracellular staining (yICS) that enables fluorescent antibodies to access intracellular compartments of yeast cells while maintaining their cellular integrity for analysis by flow cytometry. Using the housekeeping proteins ß actin and glyceraldehyde 3-phophate dehydrogenase (GAPDH) as targets for yICS, we demonstrated for the first time successful antibody-based flow cytometric detection of yeast intracellular proteins with no modification. Further, yICS characterization of a recombinant d-xylose assimilation pathway showed 3-plexed, quantitative detection of the xylose reductase (XR), xylitol dehydrogenase (XDH), and xylulokinase (XK) enzymes each fused with a small (6-10 amino acids) tag, revealing distinct enzyme expression profiles between plasmid-based and genome-integrated expression approaches. As a result of its high-throughput and quantitative capability, yICS enabled rapid screening of a library created from CRISPR-mediated XDH integration into the yeast δ site, identifying rare (1%) clones that led to an 8.4-fold increase in XDH activity. These results demonstrate the utility of yICS for greatly accelerating pathway engineering efforts, as well as any application where the high-throughput and quantitative detection of intracellular proteins is desired.

Mass Defect-Based DiLeu Tagging for Multiplexed Data-Independent Acquisition.

The unbiased selection of peptide precursors makes data-independent acquisition (DIA) an advantageous alternative to data-dependent acquisition (DDA) for discovery proteomics, but traditional multiplexed quantification approaches employing mass difference labeling or isobaric tagging are incompatible with DIA. Here, we describe a strategy that permits multiplexed quantification by DIA using mass defect-based N,N-dimethyl leucine (mdDiLeu) tags and high-resolution tandem mass spectrometry (MS2) analysis. Millidalton mass differences between mdDiLeu isotopologues produce fragment ion multiplet peaks separated in mass by as little as 5.8 mDa, enabling up to 4-plex quantification in DIA MS2 spectra. Quantitative analysis of yeast samples displayed comparable accuracy and precision for MS2-based DIA and MS1-based DDA methods. Multiplexed DIA analysis of cerebrospinal fluid revealed the dynamic proteome changes in Alzheimer's disease, demonstrating its utility for discovery of potential clinical biomarkers. We show that the mdDiLeu tagging approach for multiplexed DIA is a viable methodology for investigating proteome changes, particularly for low-abundance proteins, in different biological matrices.

Aggregation and Prion-Inducing Properties of the G-Protein Gamma Subunit Ste18 are Regulated by Membrane Association.

Yeast prions and mnemons are respectively transmissible and non-transmissible self-perpetuating protein assemblies, frequently based on cross-ß ordered detergent-resistant aggregates (amyloids). Prions cause devastating diseases in mammals and control heritable traits in yeast. It was shown that the de novo formation of the prion form [PSI+] of yeast release factor Sup35 is facilitated by aggregates of other proteins. Here we explore the mechanism of the promotion of [PSI+] formation by Ste18, an evolutionarily conserved gamma subunit of a G-protein coupled receptor, a key player in responses to extracellular stimuli. Ste18 forms detergent-resistant aggregates, some of which are colocalized with de novo generated Sup35 aggregates. Membrane association of Ste18 is required for both Ste18 aggregation and [PSI+] induction, while functional interactions involved in signal transduction are not essential for these processes. This emphasizes the significance of a specific location for the nucleation of protein aggregation. In contrast to typical prions, Ste18 aggregates do not show a pattern of heritability. Our finding that Ste18 levels are regulated by the ubiquitin-proteasome system, in conjunction with the previously reported increase in Ste18 levels upon the exposure to mating pheromone, suggests that the concentration-dependent Ste18 aggregation may mediate a mnemon-like response to physiological stimuli.

Assessing Budding Yeast Phosphoproteome Dynamics in a Time-Resolved Manner using TMT10plex Mass Tag Labeling.

Amine-reactive Tandem Mass Tag 10plex (TMT10plex) labeling permits multiplexed protein identification and quantitative analysis by tandem mass spectrometry (MS/MS). We have used this technology to label 20 Saccharomyces cerevisiae samples collected in a time-resolved manner from a wild-type and phosphatase mutant background to characterize phosphoproteome dynamics. Here, we provide a detailed protocol for biological and mass spectrometry sample preparation and analysis. For complete details on the use and execution of this protocol, please refer to Touati et al. (2019).

Detection of Multisite Phosphorylation of Intrinsically Disordered Proteins Using Phos-tag SDS-PAGE.

Phos-tagTM SDS-PAGE is a method that enables electrophoretic separation of proteins based on their phosphorylation status. With Phos-tagTM SDS-PAGE, it is possible to discriminate between different phosphoforms of proteins based on their phosphorylation level and the number of phosphorylated sites, and to determine the stoichiometry of different phosphorylation products. Phos-tagTM SDS-PAGE is useful for analyzing disordered proteins with multiple phosphorylation sites and can be used for any of the downstream applications used in combination with conventional SDS-PAGE, for example, Western blotting and mass-spectrometry. To obtain the best results with Phos-tagTM SDS-PAGE, however, it is often necessary to optimize the gel composition. Depending on the molecular weight and number of phosphoryl groups added to the protein, different gel composition or running conditions should be used. Here, we provide protocols for Mn2+- and Zn2+-Phos-tagTM SDS-PAGE and give examples of how disordered proteins with different characteristics behave in gels with various Phos-tag concentrations.