Proteome-wide quantitative multiplexed profiling of protein expression: carbon-source dependency in Saccharomyces cerevisiae

Rewiring Saccharomyces cerevisiae metabolism for optimised Taxol® precursors production

Saccharomyces cerevisiae has been conveniently used to produce Taxol® anticancer drug early precursors. However, the harmful impact of oxidative stress by the first cytochrome P450-reductase enzymes (CYP725A4-POR) of Taxol® pathway has hampered sufficient progress in yeast. Here, we evolved an oxidative stress-resistant yeast strain with three-fold higher titre of their substrate, taxadiene. The performance of the evolved and parent strains were then evaluated in galactose-limited chemostats before and under the oxidative stress by an oxidising agent. The interaction of evolution and oxidative stress was comprehensively evaluated through transcriptomics and metabolite profiles integration in yeast enzyme-constrained genome scale model. Overall, the evolved strain showed improved respiration, reduced overflow metabolites production and oxidative stress re-induction tolerance. The cross-protection mechanism also potentially contributed to better heme, flavin and NADPH availability, essential for CYP725A4 and POR optimal activity in yeast. The results imply that the evolved strain is a robust cell factory for future efforts towards Taxol© production.

Rewiring of the phosphoproteome executes two meiotic divisions in budding yeast

The cell cycle is ordered by a controlled network of kinases and phosphatases. To generate gametes via meiosis, two distinct and sequential chromosome segregation events occur without an intervening S phase. How canonical cell cycle controls are modified for meiosis is not well understood. Here, using highly synchronous budding yeast populations, we reveal how the global proteome and phosphoproteome change during the meiotic divisions. While protein abundance changes are limited to key cell cycle regulators, dynamic phosphorylation changes are pervasive. Our data indicate that two waves of cyclin-dependent kinase (Cdc28Cdk1) and Polo (Cdc5Polo) kinase activity drive successive meiotic divisions. These two distinct phases of phosphorylation are ensured by the meiosis-specific Spo13 protein, which rewires the phosphoproteome. Spo13 binds to Cdc5Polo to promote phosphorylation in meiosis I, particularly of substrates containing a variant of the canonical Cdc5Polo motif. Overall, our findings reveal that a master regulator of meiosis directs the activity of a kinase to change the phosphorylation landscape and elicit a developmental cascade.

The regulatory landscape of the yeast phosphoproteome

The cellular ability to react to environmental fluctuations depends on signaling networks that are controlled by the dynamic activities of kinases and phosphatases. Here, to gain insight into these stress-responsive phosphorylation networks, we generated a quantitative mass spectrometry-based atlas of early phosphoproteomic responses in Saccharomyces cerevisiae exposed to 101 environmental and chemical perturbations. We report phosphosites on 59% of the yeast proteome, with 18% of the proteome harboring a phosphosite that is regulated within 5 min of stress exposure. We identify shared and perturbation-specific stress response programs, uncover loss of phosphorylation as an integral early event, and dissect the interconnected regulatory landscape of kinase-substrate networks, as we exemplify with target of rapamycin signaling. We further reveal functional organization principles of the stress-responsive phosphoproteome based on phosphorylation site motifs, kinase activities, subcellular localizations, shared functions and pathway intersections. This information-rich map of 25,000 regulated phosphosites advances our understanding of signaling networks.

The unfolded protein response of the endoplasmic reticulum supports mitochondrial biogenesis by buffering nonimported proteins

Almost all mitochondrial proteins are synthesized in the cytosol and subsequently targeted to mitochondria. The accumulation of nonimported precursor proteins occurring upon mitochondrial dysfunction can challenge cellular protein homeostasis. Here we show that blocking protein translocation into mitochondria results in the accumulation of mitochondrial membrane proteins at the endoplasmic reticulum, thereby triggering the unfolded protein response (UPRER). Moreover, we find that mitochondrial membrane proteins are also routed to the ER under physiological conditions. The level of ER-resident mitochondrial precursors is enhanced by import defects as well as metabolic stimuli that increase the expression of mitochondrial proteins. Under such conditions, the UPRER is crucial to maintain protein homeostasis and cellular fitness. We propose the ER serves as a physiological buffer zone for those mitochondrial precursors that cannot be immediately imported into mitochondria while engaging the UPRER to adjust the ER proteostasis capacity to the extent of precursor accumulation.

Turnover number predictions for kinetically uncharacterized enzymes using machine and deep learning

The turnover number k_cat, a measure of enzyme efficiency, is central to understanding cellular physiology and resource allocation. As experimental k_cat estimates are unavailable for the vast majority of enzymatic reactions, the development of accurate computational prediction methods is highly desirable. However, existing machine learning models are limited to a single, well-studied organism, or they provide inaccurate predictions except for enzymes that are highly similar to proteins in the training set. Here, we present TurNuP, a general and organism-independent model that successfully predicts turnover numbers for natural reactions of wild-type enzymes. We constructed model inputs by representing complete chemical reactions through differential reaction fingerprints and by representing enzymes through a modified and re-trained Transformer Network model for protein sequences. TurNuP outperforms previous models and generalizes well even to enzymes that are not similar to proteins in the training set. Parameterizing metabolic models with TurNuP-predicted k_cat values leads to improved proteome allocation predictions. To provide a powerful and convenient tool for the study of molecular biochemistry and physiology, we implemented a TurNuP web server.

Overexpression of Hsp104 by Causing Dissolution of the Prion Seeds Cures the Yeast [PSI+] Prion

The yeast Sup35 protein misfolds into the infectious [PSI⁺] prion, which is then propagated by the severing activity of the molecular chaperone, Hsp104. Unlike other yeast prions, this prion is unique in that it is efficiently cured by the overexpression as well as the inactivation of Hsp104. However, it is controversial whether curing by overexpression is due to the dissolution of the prion seeds by the trimming activity of Hsp104 or the asymmetric segregation of the prion seeds between mother and daughter cells which requires cell division. To answer this question, we conducted experiments and found no difference in the extent of curing between mother and daughter cells when half of the cells were cured by Hsp104 overexpression in one generation. Furthermore, curing was not affected by the lack of Sir2 expression, which was reported to be required for asymmetric segregation of the [PSI⁺] seeds. More importantly, when either hydroxyurea or ethanol were used to inhibit cell division, the extent of curing by Hsp104 overexpression was not significantly reduced. Therefore, the curing of [PSI⁺] by Hsp104 overexpression is not due to asymmetric segregation of the prion seeds, but rather their dissolution by Hsp104.

Chimeric a-subunit isoforms generate functional yeast V-ATPases with altered regulatory properties in vitro and in vivo

V-ATPases are highly regulated proton pumps that acidify organelles. The V-ATPase a-subunit is a two-domain protein containing a C-terminal transmembrane domain responsible for proton transport and an N-terminal cytosolic domain (aNT) that is a regulatory hub, integrating environmental inputs to regulate assembly, localization, and V-ATPase activity. The yeast Saccharomyces cerevisiae encodes only two organelle-specific a-isoforms, Stv1 in the Golgi and Vph1 in the vacuole. On the basis of recent structures, we designed chimeric yeast aNTs in which the globular proximal and distal ends are exchanged. The Vph1 proximal-Stv1 distal (VPSD) aNT chimera binds to the glucose-responsive RAVE assembly factor in vitro but exhibits little binding to PI(3,5)P₂. The Stv1 proximal-Vph1 distal (SPVD) aNT lacks RAVE binding but binds more tightly to phosphoinositides than Vph1 or Stv1. When attached to the Vph1 C-terminal domain in vivo, both chimeras complement growth defects of a vph1∆ mutant, but only the SPVD chimera exhibits wild-type V-ATPase activity. Cells containing the SPVD chimera adapt more slowly to a poor carbon source than wild-type cells but grow more rapidly than wild-type cells after a shift to alkaline pH. This is the first example of a "redesigned" V-ATPase with altered regulatory properties and adaptation to specific stresses.

Comparative proteome analysis of different Saccharomyces cerevisiae strains during growth on sucrose and glucose

Both the identity and the amount of a carbon source present in laboratory or industrial cultivation media have major impacts on the growth and physiology of a microbial species. In the case of the yeast Saccharomyces cerevisiae, sucrose is arguably the most important sugar used in industrial biotechnology, whereas glucose is the most common carbon and energy source used in research, with many well-known and described regulatory effects, e.g. glucose repression. Here we compared the label-free proteomes of exponentially growing S. cerevisiae cells in a defined medium containing either sucrose or glucose as the sole carbon source. For this purpose, bioreactor cultivations were employed, and three different strains were investigated, namely: CEN.PK113-7D (a common laboratory strain), UFMG-CM-Y259 (a wild isolate), and JP1 (an industrial bioethanol strain). These strains present different physiologies during growth on sucrose; some of them reach higher specific growth rates on this carbon source, when compared to growth on glucose, whereas others display the opposite behavior. It was not possible to identify proteins that commonly presented either higher or lower levels during growth on sucrose, when compared to growth on glucose, considering the three strains investigated here, except for one protein, named Mnp1-a mitochondrial ribosomal protein of the large subunit, which had higher levels on sucrose than on glucose, for all three strains. Interestingly, following a Gene Ontology overrepresentation and KEGG pathway enrichment analyses, an inverse pattern of enriched biological functions and pathways was observed for the strains CEN.PK113-7D and UFMG-CM-Y259, which is in line with the fact that whereas the CEN.PK113-7D strain grows faster on glucose than on sucrose, the opposite is observed for the UFMG-CM-Y259 strain.

Pectinases Secretion by Saccharomyces cerevisiae: Optimization in Solid-State Fermentation and Identification by a Shotgun Proteomics Approach

A sequential design strategy was applied to optimize the secretion of pectinases by a Saccharomyces cerevisiae strain, from Brazilian sugarcane liquor vat, on passion fruit residue flour (PFRF), through solid-state fermentation (SSF). A factorial design was performed to determine the influence variables and two rotational central composite designs were executed. The validated experimental result was of 7.1 U mL⁻¹ using 50% PFRF (w/w), pH 5, 30 °C for 24 h, under static SSF. Polygalacturonase, pectin methyl esterase, pectin–lyase and pectate–lyase activities were 3.5; 0.08; 3.1 and 0.8 U mL⁻¹, respectively. Shotgun proteomics analysis of the crude extract enabled the identification of two pectin–lyases, one pectate–lyase and a glucosidase. The crude enzymatic extract maintained at least 80% of its original activity at pH values and temperatures ranging from 2 to 8 and 30 to 80 °C, respectively, over 60 min incubation. Results revealed that PFRF might be a cost-effective and eco-friendly substrate to produce pectinases. Statistical optimization led to fermentation conditions wherein pectin active proteins predominated. To the extent of our knowledge, this is the first study reporting the synthesis of pectate lyase by S. cerevisiae.

Growth-rate-dependent and nutrient-specific gene expression resource allocation in fission yeast

Cellular resources are limited and their relative allocation to gene expression programmes determines physiological states and global properties such as the growth rate. Here, we determined the importance of the growth rate in explaining relative changes in protein and mRNA levels in the simple eukaryote Schizosaccharomyces pombe grown on non-limiting nitrogen sources. Although expression of half of fission yeast genes was significantly correlated with the growth rate, this came alongside wide-spread nutrient-specific regulation. Proteome and transcriptome often showed coordinated regulation but with notable exceptions, such as metabolic enzymes. Genes positively correlated with growth rate participated in every level of protein production apart from RNA polymerase II-dependent transcription. Negatively correlated genes belonged mainly to the environmental stress response programme. Critically, metabolic enzymes, which represent ∼55-70% of the proteome by mass, showed mostly condition-specific regulation. In summary, we provide a rich account of resource allocation to gene expression in a simple eukaryote, advancing our basic understanding of the interplay between growth-rate-dependent and nutrient-specific gene expression.

IRC3 regulates mitochondrial translation in response to metabolic cues in Saccharomyces cerevisiae

Mitochondrial oxidative phosphorylation (OXPHOS) enzymes are made up of dual genetic origin. Mechanisms regulating the expression of nuclear-encoded OXPHOS subunits in response to metabolic cues (glucose vs. glycerol), is significantly understood while regulation of mitochondrially encoded OXPHOS subunits is poorly defined. Here, we show that IRC3 a DEAD/H box helicase, previously implicated in mitochondrial DNA maintenance, is central to integrating metabolic cues with mitochondrial translation. Irc3 associates with mitochondrial small ribosomal subunit in cells consistent with its role in regulating translation elongation based on Arg8^m reporter system. IRC3 deleted cells retained mitochondrial DNA despite growth defect on glycerol plates. Glucose grown Δirc3ρ⁺ and irc3 temperature-sensitive cells at 37⁰C have reduced translation rates from majority of mRNAs. In contrast, when galactose was the carbon source, reduction in mitochondrial translation was observed predominantly from Cox1 mRNA in Δirc3ρ⁺ but no defect was observed in irc3 temperature-sensitive cells, at 37⁰C. In support, of a model whereby IRC3 responds to metabolic cues to regulate mitochondrial translation, suppressors of Δirc3 isolated for restoration of growth on glycerol media restore mitochondrial protein synthesis differentially in presence of glucose vs. glycerol.

In vitro turnover numbers do not reflect in vivo activities of yeast enzymes

Turnover numbers (k_cat values) quantitatively represent the activity of enzymes, which are mostly measured in vitro. While a few studies have reported in vivo catalytic rates (k_app values) in bacteria, a large-scale estimation of k_app in eukaryotes is lacking. Here, we estimated k_app of the yeast Saccharomyces cerevisiae under diverse conditions. By comparing the maximum k_app across conditions with in vitro k_cat we found a weak correlation in log scale of R² = 0.28, which is lower than for Escherichia coli (R² = 0.62). The weak correlation is caused by the fact that many in vitro k_cat values were measured for enzymes obtained through heterologous expression. Removal of these enzymes improved the correlation to R² = 0.41 but still not as good as for E. coli, suggesting considerable deviations between in vitro and in vivo enzyme activities in yeast. By parameterizing an enzyme-constrained metabolic model with our k_app dataset we observed better performance than the default model with in vitro k_cat in predicting proteomics data, demonstrating the strength of using the dataset generated here.

The impact of carbon and nitrogen catabolite repression in microorganisms

Organisms have cellular machinery that is focused on optimum utilization of resources to maximize growth and survival depending on various environmental and developmental factors. Catabolite repression is a strategy utilized by various species of bacteria and fungi to accommodate changes in the environment such as the depletion of resources, or an abundance of less-favored nutrient sources. Catabolite repression allows for the rapid use of certain substrates like glucose over other carbon sources. Effective handling of carbon and nitrogen catabolite repression in microorganisms is crucial to outcompete others in nutrient limiting conditions. Investigations into genes and proteins linked to preferential uptake of different nutrients under various environmental conditions can aid in identifying regulatory mechanisms that are crucial for optimum growth and survival of microorganisms. The exact time and way bacteria and fungi switch their utilization of certain nutrients is of great interest for scientific, industrial, and clinical reasons. Catabolite repression is of great significance for industrial applications that rely on microorganisms for the generation of valuable bio-products. The impact catabolite repression has on virulence of pathogenic bacteria and fungi and disease progression in hosts makes it important area of interest in medical research for the prevention of diseases and developing new treatment strategies. Regulatory networks under catabolite repression exemplify the flexibility and the tremendous diversity that is found in microorganisms and provides an impetus for newer insights into these networks.

Customized yeast cell factories for biopharmaceuticals: from cell engineering to process scale up

The manufacture of recombinant therapeutics is a fastest-developing section of therapeutic pharmaceuticals and presently plays a significant role in disease management. Yeasts are established eukaryotic host for heterologous protein production and offer distinctive benefits in synthesising pharmaceutical recombinants. Yeasts are proficient of vigorous growth on inexpensive media, easy for gene manipulations, and are capable of adding post translational changes of eukaryotes. Saccharomyces cerevisiae is model yeast that has been applied as a main host for the manufacture of pharmaceuticals and is the major tool box for genetic studies; nevertheless, numerous other yeasts comprising Pichia pastoris, Kluyveromyces lactis, Hansenula polymorpha, and Yarrowia lipolytica have attained huge attention as non-conventional partners intended for the industrial manufacture of heterologous proteins. Here we review the advances in yeast gene manipulation tools and techniques for heterologous pharmaceutical protein synthesis. Application of secretory pathway engineering, glycosylation engineering strategies and fermentation scale-up strategies in customizing yeast cells for the synthesis of therapeutic proteins has been meticulously described.

A yeast FRET biosensor enlightens cAMP signaling

The cAMP-PKA signaling cascade in budding yeast regulates adaptation to changing environments. We developed yEPAC, a FRET-based biosensor for cAMP measurements in yeast. We used this sensor with flow cytometry for high-throughput single cell-level quantification during dynamic changes in response to sudden nutrient transitions. We found that the characteristic cAMP peak differentiates between different carbon source transitions and is rather homogenous among single cells, especially for transitions to glucose. The peaks are mediated by a combination of extracellular sensing and intracellular metabolism. Moreover, the cAMP peak follows the Weber-Fechner law; its height scales with the relative, and not the absolute, change in glucose. Last, our results suggest that the cAMP peak height conveys information about prospective growth rates. In conclusion, our yEPAC-sensor makes possible new avenues for understanding yeast physiology, signaling, and metabolic adaptation.

Quantitative single-cell proteomics as a tool to characterize cellular hierarchies

Large-scale single-cell analyses are of fundamental importance in order to capture biological heterogeneity within complex cell systems, but have largely been limited to RNA-based technologies. Here we present a comprehensive benchmarked experimental and computational workflow, which establishes global single-cell mass spectrometry-based proteomics as a tool for large-scale single-cell analyses. By exploiting a primary leukemia model system, we demonstrate both through pre-enrichment of cell populations and through a non-enriched unbiased approach that our workflow enables the exploration of cellular heterogeneity within this aberrant developmental hierarchy. Our approach is capable of consistently quantifying ~1000 proteins per cell across thousands of individual cells using limited instrument time. Furthermore, we develop a computational workflow (SCeptre) that effectively normalizes the data, integrates available FACS data and facilitates downstream analysis. The approach presented here lays a foundation for implementing global single-cell proteomics studies across the world.

Developing a Yeast Platform Strain for an Enhanced Taxadiene Biosynthesis by CRISPR/Cas9

Paclitaxel is an important diterpenoid commonly used as an anticancer drug. Although the paclitaxel biosynthetic pathway has been mostly revealed, some steps remain to be elucidated. The difficulties in plant transformations and the scarcity of the precursor of paclitaxel, (+)-taxa-4(5), 11(12)-diene (taxadiene), have hindered the full comprehension of paclitaxel biochemistry and, therefore, its production by biotechnological approaches. One solution is to use the budding yeast, Saccharomyces cerevisiae, as a platform to elucidate the paclitaxel biosynthesis. As taxadiene is a diterpenoid, its common precursor, geranylgeranyl pyrophosphate (GGPP), needs to be increased in yeast. In this study, we screened various GGPP synthases (GGPPS) to find the most suitable GGPPS for taxadiene production in yeast. We also optimized the taxadiene production by increasing the flux toward the terpenoid pathway. Finally, to remove selection markers, we integrated the required genes using a CRISPR/Cas9 system in the yeast genome. Our result showed that a titer of 2.02 ± 0.40 mg/L (plasmid) and 0.41 ± 0.06 mg/L (integrated) can be achieved using these strategies. This platform strain can be used to readily test the gene candidates for microbial paclitaxel biosynthesis in the future.

The identification of novel promoters and terminators for protein expression and metabolic engineering applications in Kluyveromyces marxianus

The K. marxianus has emerged as a potential yeast strain for various biotechnological applications. However, the limited number of available genetic tools has hindered the widespread usage of this yeast. In the current study we have expanded the molecular tool box by identifying novel sets of promoters and terminators for increased recombinant protein expression in K. marxianus. The previously available transcriptomic data were analyzed to identify top 10 promoters of highest gene expression activity. We further characterized and compared strength of these identified promoters using eGFP as a reporter protein, at different temperatures and carbon sources. To examine the regulatory region driving protein expression, serially truncated shorter versions of two selected strong promoters were designed, and examined for their ability to drive eGFP protein expression. The activities of these two promoters were further enhanced using different combinations of native transcription terminators of K. marxianus. We further utilized the identified DNA cassette encoding strong promoter in metabolic engineering of K. marxianus for enhanced β-galactosidase activity. The present study thus provides novel sets of promoters and terminators as well as engineered K. marxianus strain for its wider utility in applications requiring lactose degradation such as in cheese whey and milk.

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Novel promoters and terminators for constitutive gene expression in K. marxianus.

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The promoters show constitutive expression at varying temperature and carbon source.

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K. marxianus strain with improved production of β-galactosidase.

A proteome-integrated, carbon source dependent genetic regulatory network in Saccharomyces cerevisiae

Integrated regulatory networks can be powerful tools to examine and test properties of cellular systems, such as modelling environmental effects on the molecular bioeconomy, where protein levels are altered in response to changes in growth conditions. Although extensive regulatory pathways and protein interaction data sets exist which represent such networks, few have formally considered quantitative proteomics data to validate and extend them. We generate and consider such data here using a label-free proteomics strategy to quantify alterations in protein abundance for S. cerevisiae when grown on minimal media using glucose, galactose, maltose and trehalose as sole carbon sources. Using a high quality-controlled subset of proteins observed to be differentially abundant, we constructed a proteome-informed network, comprising 1850 transcription factor interactions and 37 chaperone interactions, which defines the major changes in the cellular proteome when growing under different carbon sources. Analysis of the differentially abundant proteins involved in the regulatory network pointed to their significant roles in specific metabolic pathways and function, including glucose homeostasis, amino acid biosynthesis, and carbohydrate metabolic process. We noted strong statistical enrichment in the differentially abundant proteome of targets of known transcription factors associated with stress responses and altered carbon metabolism. This shows how such integrated analysis can lend further experimental support to annotated regulatory interactions, since the proteomic changes capture both magnitude and direction of gene expression change at the level of the affected proteins. Overall this study highlights the power of quantitative proteomics to help define regulatory systems pertinent to environmental conditions.

HYpro16: A Two-Proteome Mixture to Assess Interference in Isobaric Tag-Based Sample Multiplexing Experiments

Isobaric tagging is a powerful strategy for global proteome profiling. A caveat of isobaric-tag-based quantification is "interference", which may be caused by coeluting peptides that are coisolated, cofragmented, and coanalyzed, thereby confounding quantitative accuracy. Here, we present a two-proteome standard that challenges the mass spectrometer to measure a range of protein abundance ratios in a background of potential interference. The HYpro16 standard consists of tandem mass tag (TMT) pro16-labeled human peptides at a 1:1 ratio across all channels into which is spiked TMTpro16-labeled yeast peptides in triplicate at 20:1, 10:1, 4:1, and 2:1 ratios. We showcase the HYpro16 standard by (1) altering the MS2 isolation window width and (2) examining different data acquisition methods (hrMS2, SPS-MS3, RTS-MS3). Our data illustrate that wider isolation widths moderately increase the TMT signal, the benefits of which are offset by decreased ratio accuracy. We also show that using real-time database searching (RTS)-MS3 resulted in the most accurate ratios. Additionally, the number of quantified yeast proteins using RTS-MS3 approaches that of hrMS2 when using a yeast-specific database for real-time searching. In short, this quality control standard allows for the assessment of multiple quantitative measurements within a single run, which can be compared across instruments to benchmark and track performance.

The activity of yeast Apn2 AP endonuclease at uracil-derived AP sites is dependent on the major carbon source

Yeast Apn2 is an AP endonuclease and DNA 3'-diesterase that belongs to the Exo III family with homology to the E. coli exonuclease III, Schizosaccharomyces pombe eth1, and human AP endonucleases APEX1 and APEX2. In the absence of Apn1, the major AP endonuclease in yeast, Apn2 can cleave the DNA backbone at an AP lesion initiating the base excision repair pathway. To study the role and relative contribution of Apn2, we took advantage of a reporter system that was previously used to delineate how uracil-derived AP sites are repaired. At this reporter, disruption of the Apn1-initiated base excision repair pathway led to a significant elevation of A:T to C:G transversions. Here we show that such highly elevated A:T to C:G transversion mutations associated with uracil residues in DNA are abolished when apn1∆ yeast cells are grown in glucose as the primary carbon source. We also show that the disruption of Apn2, either by the complete gene deletion or by the mutation of a catalytic residue, results in a similarly reduced rate of the uracil-associated mutations. Overall, our results indicate that Apn2 activity is regulated by the glucose repression pathway in yeast.

Proteome profiling and vector yield optimization in a recombinant adeno-associated virus-producing yeast model

Recent studies on recombinant adeno‐associated viral (rAAV) vector production demonstrated the generation of infectious viral particles in Saccharomyces cerevisiae. Proof‐of‐concept results showed low vector yields that correlated with low AAV DNA encapsidation rates. In an attempt to understand the host cell response to rAAV production, we profiled proteomic changes throughout the fermentation process by mass spectrometry. By comparing an rAAV‐producing yeast strain with a respective non‐producer control, we identified a subset of yeast host proteins with significantly different expression patterns during the rAAV induction period. Gene ontology enrichment and network interaction analyses identified changes in expression patterns associated mainly with protein folding, as well as amino acid metabolism, gluconeogenesis, and stress response. Specific fold change patterns of heat shock proteins and other stress protein markers suggested the occurrence of a cytosolic unfolded protein response during rAAV protein expression. Also, a correlative increase in proteins involved in response to oxidative stress suggested cellular activities to ameliorate the effects of reactive oxygen species or other oxidants. We tested the functional relevance of the identified host proteins by overexpressing selected protein leads using low‐ and high‐copy number plasmids. Increased vector yields up to threefold were observed in clones where proteins SSA1, SSE1, SSE2, CCP1, GTT1, and RVB2 were overexpressed. Recombinant expression of SSA1 and YDJ insect homologues (HSP40 and HSC70, respectively) in Sf9 cells led to a volumetric vector yield increase of 50% relative to control, which validated the importance of chaperone proteins in rAAV‐producing systems. Overall, these results highlight the utility of proteomic‐based tools for the understanding and optimization of rAAV‐producing recombinant strains.

Chemical Biology Toolkit for DCLK1 Reveals Connection to RNA Processing

Doublecortin-like kinase 1 (DCLK1) is critical for neurogenesis, but overexpression is also observed in multiple cancers and is associated with poor prognosis. Nevertheless, the function of DCLK1 in cancer, especially the context-dependent functions, are poorly understood. We present a "toolkit" that includes the DCLK1 inhibitor DCLK1-IN-1, a complementary DCLK1-IN-1-resistant mutation G532A, and kinase dead mutants D511N and D533N, which can be used to investigate signaling pathways regulated by DCLK1. Using a cancer cell line engineered to be DCLK1 dependent for growth and cell migration, we show that this toolkit can be used to discover associations between DCLK1 kinase activity and biological processes. In particular, we show an association between DCLK1 and RNA processing, including the identification of CDK11 as a potential substrate of DCLK1 using phosphoproteomics.

Growth media selection alters the proteome profiles of three model microorganisms

The selection of growth media is a very important consideration of any cell-based proteomics experiment. Alterations thereof may result in differences in basal proteomes simply due to disparities in the metabolite composition of the media. We investigate the effect of growth media on the proteomes of three microorganisms, specifically E. coli, S. cerevisiae, and S. pombe, using tandem mass tag (TMT)-based quantitative proteomics. We compared the protein abundance profiles of these microorganisms propagated in two distinct growth media that are commonly used for the respective organism. Our sample preparation strategy included SP3 bead-assisted protein isolation and digestion. In addition, we assembled a replicate set of samples in which we altered the proteolytic digestion from sequential treatment with LysC and trypsin to only LysC. Despite differences in peptides identified and a drop in quantified proteins, the results were similar between the two datasets for all three microorganisms. Approximately 10% of the proteins of each respective microorganism were significantly altered in each dataset. As expected, gene ontology analysis revealed that the majority of differentially expressed proteins are implicated in metabolism. These data emphasize further the importance and the potential consequences of growth media selection. SIGNIFICANCE: Various microorganisms are used as model systems throughout in biological studies, including proteomics-based investigations. The growth conditions of these organisms are of utmost importance, of which one major consideration is the choice of growth media. We hypothesize that growth media selection has a considerable impact on the baseline proteome of a given microorganism. To test this hypothesis, we used tandem mass tag (TMT)-based quantitative multiplexed proteomics to profile the proteomes of E. coli, S. cerevisiae, and S. pombe each grown in two different, yet common, growth media for the respective species. Our data show that approximately 10% of the proteins of each respective microorganism were significantly altered and that many of the differentially expressed proteins are implicated in metabolism. We provide several datasets which are potentially valuable for growth media selection with respect to downstream biochemical analysis.

A Standardized and Reproducible Proteomics Protocol for Bottom-Up Quantitative Analysis of Protein Samples Using SP3 and Mass Spectrometry

The broad utility of mass spectrometry (MS) for investigating the proteomes of a diverse array of sample types has significantly expanded the use of this technology in biological studies. This widespread use has resulted in a substantial collection of protocols and acquisition approaches designed to obtain the highest-quality data for each experiment. As a result, distilling this information to develop a standard operating protocol for essential workflows, such as bottom-up quantitative shotgun whole proteome analysis, can be complex for users new to MS technology. Further complicating this matter, in-depth description of the methodological choices is seldom given in the literature. In this work, we describe a workflow for quantitative whole proteome analysis that is suitable for biomarker discovery, giving detailed consideration to important stages, including (1) cell lysis and protein cleanup using SP3 paramagnetic beads, (2) quantitative labeling, (3) offline peptide fractionation, (4) MS analysis, and (5) data analysis and interpretation. Special attention is paid to providing comprehensive details for all stages of this proteomics workflow to enhance transferability to external labs. The standardized protocol described here will provide a simplified resource to the proteomics community toward efficient adaptation of MS technology in proteomics studies.

Methodologies and Applications of Proteomics for Study of Yeast Strains: An Update

Yeasts are one of the mostly used microorganisms as models in several studies. A wide range of applications in different processes can be attributed to their intrinsic characteristics. They are eukaryotes and therefore valuable expression hosts that require elaborate post-translational modifications. Their arsenal of proteins has become a valuable biochemical tool for the catalysis of several reactions of great value to the food (beverages), pharmaceutical and energy industries. Currently, the main challenge in systemic yeast biology is the understanding of the expression, function and regulation of the protein pool encoded by such microorganisms. In this review, we will provide an overview of the proteomic methodologies used in the analysis of yeasts. This research focuses on the advantages and improvements in their most recent applications with an understanding of the functionality of the proteins of these microorganisms, as well as an update of the advances of methodologies employed in mass spectrometry.

Established and Upcoming Yeast Expression Systems

Yeast was the first microorganism used by mankind for biotransformation of feedstock that laid the foundations of industrial biotechnology. Long historical use, vast amount of data, and experience paved the way for Saccharomyces cerevisiae as a first yeast cell factory, and still it is an important expression platform as being the production host for several large volume products. Continuing special needs of each targeted product and different requirements of bioprocess operations have led to identification of different yeast expression systems. Modern bioprocess engineering and advances in omics technology, i.e., genomics, transcriptomics, proteomics, secretomics, and interactomics, allow the design of novel genetic tools with fine-tuned characteristics to be used for research and industrial applications. This chapter focuses on established and upcoming yeast expression platforms that have exceptional characteristics, such as the ability to utilize a broad range of carbon sources or remarkable resistance to various stress conditions. Besides the conventional yeast S. cerevisiae, established yeast expression systems including the methylotrophic yeasts Pichia pastoris and Hansenula polymorpha, the dimorphic yeasts Arxula adeninivorans and Yarrowia lipolytica, the lactose-utilizing yeast Kluyveromyces lactis, the fission yeast Schizosaccharomyces pombe, and upcoming yeast platforms, namely, Kluyveromyces marxianus, Candida utilis, and Zygosaccharomyces bailii, are compiled with special emphasis on their genetic toolbox for recombinant protein production.

Layers of regulation of cell-cycle gene expression in the budding yeast Saccharomyces cerevisiae

In the budding yeast Saccharomyces cerevisiae, transcription factors (TFs) regulate the periodic expression of many genes during the cell cycle, including gene products required for progression through cell-cycle events. Experimental evidence coupled with quantitative models suggests that a network of interconnected TFs is capable of regulating periodic genes over the cell cycle. Importantly, these dynamical models were built on transcriptomics data and assumed that TF protein levels and activity are directly correlated with mRNA abundance. To ask whether TF transcripts match protein expression levels as cells progress through the cell cycle, we applied a multiplexed targeted mass spectrometry approach (parallel reaction monitoring) to synchronized populations of cells. We found that protein expression of many TFs and cell-cycle regulators closely followed their respective mRNA transcript dynamics in cycling wild-type cells. Discordant mRNA/protein expression dynamics was also observed for a subset of cell-cycle TFs and for proteins targeted for degradation by E3 ubiquitin ligase complexes such as SCF (Skp1/Cul1/F-box) and APC/C (anaphase-promoting complex/cyclosome). We further profiled mutant cells lacking B-type cyclin/CDK activity ( clb1-6) where oscillations in ubiquitin ligase activity, cyclin/CDKs, and cell-cycle progression are halted. We found that a number of proteins were no longer periodically degraded in clb1-6 mutants compared with wild type, highlighting the importance of posttranscriptional regulation. Finally, the TF complexes responsible for activating G1/S transcription (SBF and MBF) were more constitutively expressed at the protein level than at periodic mRNA expression levels in both wild-type and mutant cells. This comprehensive investigation of cell-cycle regulators reveals that multiple layers of regulation (transcription, protein stability, and proteasome targeting) affect protein expression dynamics during the cell cycle.

Automethylation-induced conformational switch in Clr4 (Suv39h) maintains epigenetic stability

Histone H3 lysine 9 methylation (H3K9me) mediates heterochromatic gene silencing and is important for genome stability and the regulation of gene expression1-4. The establishment and epigenetic maintenance of heterochromatin involve the recruitment of H3K9 methyltransferases to specific sites on DNA, followed by the recognition of pre-existing H3K9me by the methyltransferase and methylation of proximal histone H35-11. This positive feedback loop must be tightly regulated to prevent deleterious epigenetic gene silencing. Extrinsic anti-silencing mechanisms involving histone demethylation or boundary elements help to limit the spread of inappropriate H3K9me12-15. However, how H3K9 methyltransferase activity is locally restricted or prevented from initiating random H3K9me-which would lead to aberrant gene silencing and epigenetic instability-is not fully understood. Here we reveal an autoinhibited conformation in the conserved H3K9 methyltransferase Clr4 (also known as Suv39h) of the fission yeast Schizosaccharomyces pombe that has a critical role in preventing aberrant heterochromatin formation. Biochemical and X-ray crystallographic data show that an internal loop in Clr4 inhibits the catalytic activity of this enzyme by blocking the histone H3K9 substrate-binding pocket, and that automethylation of specific lysines in this loop promotes a conformational switch that enhances the H3K9me activity of Clr4. Mutations that are predicted to disrupt this regulation lead to aberrant H3K9me, loss of heterochromatin domains and inhibition of growth, demonstrating the importance of the intrinsic inhibition and auto-activation of Clr4 in regulating the deposition of H3K9me and in preventing epigenetic instability. Conservation of the Clr4 autoregulatory loop in other H3K9 methyltransferases and the automethylation of a corresponding lysine in the human SUV39H2 homologue16 suggest that the mechanism described here is broadly conserved.

Streamlined Tandem Mass Tag (SL-TMT) Protocol: An Efficient Strategy for Quantitative (Phospho)proteome Profiling Using Tandem Mass Tag-Synchronous Precursor Selection-MS3

Mass spectrometry (MS) coupled toisobaric labeling has developed rapidly into a powerful strategy for high-throughput protein quantification. Sample multiplexing and exceptional sensitivity allow for the quantification of tens of thousands of peptides and, by inference, thousands of proteins from multiple samples in a single MS experiment. Accurate quantification demands a consistent and robust sample-preparation strategy. Here, we present a detailed workflow for SPS-MS3-based quantitative abundance profiling of tandem mass tag (TMT)-labeled proteins and phosphopeptides that we have named the streamlined (SL)-TMT protocol. We describe a universally applicable strategy that requires minimal individual sample processing and permits the seamless addition of a phosphopeptide enrichment step ("mini-phos") with little deviation from the deep proteome analysis. To showcase our workflow, we profile the proteome of wild-type Saccharomyces cerevisiae yeast grown with either glucose or pyruvate as the carbon source. Here, we have established a streamlined TMT protocol that enables deep proteome and medium-scale phosphoproteome analysis.

Multiplexed Isobaric Tag-Based Profiling of Seven Murine Tissues Following In Vivo Nicotine Treatment Using a Minimalistic Proteomics Strategy

Nicotine is a major addictive compound in tobacco and a component of smoking-related products, such as e-cigarettes. Once internalized, nicotine can perturb many cellular pathways and can induce alterations in proteins across different cell types; however, the mechanisms thereof remain undetermined. The authors hypothesize that both tissue-specific and global protein abundance alterations result from nicotine exposure. Presented here is the first proteomic profiling of multiple tissues from mice treated orally with nicotine. Proteins extracted from seven tissues (brain, heart, kidney, liver, lung, pancreas, and spleen) from treated (n = 5) and untreated control (n = 5) mice are assembled into a TMT10-plex experiment. A minimalistic proteomics strategy is employed using TMT reagents efficiently and centrifugation-based reversed-phase columns to streamline sample preparation. Combined, over 11 000 non-redundant proteins from over 138 000 different peptides are quantified in seven TMT10-plex experiments. Between 7 and 126 proteins are significantly altered in tissues from nicotine-exposed mice, 11 which are altered in two or more tissues. Our data showcase the vast extent of nicotine exposure across murine tissue.

Quantitative proteomics identifies redox switches for global translation modulation by mitochondrially produced reactive oxygen species

The generation of reactive oxygen species (ROS) is inevitably linked to life. However, the precise role of ROS in signalling and specific targets is largely unknown. We perform a global proteomic analysis to delineate the yeast redoxome to a depth of more than 4,300 unique cysteine residues in over 2,200 proteins. Mapping of redox-active thiols in proteins exposed to exogenous or endogenous mitochondria-derived oxidative stress reveals ROS-sensitive sites in several components of the translation apparatus. Mitochondria are the major source of cellular ROS. We demonstrate that increased levels of intracellular ROS caused by dysfunctional mitochondria serve as a signal to attenuate global protein synthesis. Hence, we propose a universal mechanism that controls protein synthesis by inducing reversible changes in the translation machinery upon modulating the redox status of proteins involved in translation. This crosstalk between mitochondria and protein synthesis may have an important contribution to pathologies caused by dysfunctional mitochondria.

Unification of Protein Abundance Datasets Yields a Quantitative Saccharomyces cerevisiae Proteome

Protein activity is the ultimate arbiter of function in most cellular pathways, and protein concentration is fundamentally connected to protein action. While the proteome of yeast has been subjected to the most comprehensive analysis of any eukaryote, existing datasets are difficult to compare, and there is no consensus abundance value for each protein. We evaluated 21 quantitative analyses of the S. cerevisiae proteome, normalizing and converting all measurements of protein abundance into the intuitive measurement of absolute molecules per cell. We estimate the cellular abundance of 92% of the proteins in the yeast proteome and assess the variation in each abundance measurement. Using our protein abundance dataset, we find that a global response to diverse environmental stresses is not detected at the level of protein abundance, we find that protein tags have only a modest effect on protein abundance, and we identify proteins that are differentially regulated at the mRNA abundance, mRNA translation, and protein abundance levels.

Loss of the deubiquitinase USP36 destabilizes the RNA helicase DHX33 and causes preimplantation lethality in mice

Deubiquitinases are proteases with a wide functional diversity that profoundly impact multiple biological processes. Among them, the ubiquitin-specific protease 36 (USP36) has been implicated in the regulation of nucleolar activity. However, its functional relevance in vivo has not yet been fully described. Here, we report the generation of an Usp36-deficient mouse model to examine the function of this enzyme. We show that Usp36 depletion is lethal in preimplantation mouse embryos, where it blocks the transition from morula to blastocyst during embryonic development. USP36 reduces the ubiquitination levels and increases the stability of the DEAH-box RNA helicase DHX33, which is critically involved in ribosomal RNA synthesis and mRNA translation. In agreement with this finding, O-propargyl-puromycin incorporation experiments, Northern blot, and electron microscopy analyses demonstrated the role of USP36 in ribosomal RNA and protein synthesis. Finally, we show that USP36 down-regulation alters cell proliferation in human cancer cells by inducing both apoptosis and cell cycle arrest, and that reducing DHX33 levels through short hairpin RNA interference has the same effect. Collectively, these results support that Usp36 is essential for cell and organism viability because of its role in ribosomal RNA processing and protein synthesis, which is mediated, at least in part, by regulating DHX33 stability.

Principles of cellular resource allocation revealed by condition-dependent proteome profiling

Growing cells coordinate protein translation with metabolic rates. Central to this coordination is ribosome production. Ribosomes drive cell growth, but translation of ribosomal proteins competes with production of non-ribosomal proteins. Theory shows that cell growth is maximized when all expressed ribosomes are constantly translating. To examine whether budding yeast function at this limit of full ribosomal usage, we profiled the proteomes of cells growing in different environments. We find that cells produce excess ribosomal proteins, amounting to a constant ≈8% of the proteome. Accordingly, ≈25% of ribosomal proteins expressed in rapidly growing cells does not contribute to translation. Further, this fraction increases as growth rate decreases and these excess ribosomal proteins are employed when translation demands unexpectedly increase. We suggest that steadily growing cells prepare for conditions that demand increased translation by producing excess ribosomes, at the expense of lower steady-state growth rate.

UBE2O remodels the proteome during terminal erythroid differentiation

During terminal differentiation, the global protein complement is remodeled, as epitomized by erythrocytes, whose cytosol is ~98% globin. The erythroid proteome undergoes a rapid transition at the reticulocyte stage; however, the mechanisms driving programmed elimination of preexisting cytosolic proteins are unclear. We found that a mutation in the murine Ube2o gene, which encodes a ubiquitin-conjugating enzyme induced during erythropoiesis, results in anemia. Proteomic analysis suggested that UBE2O is a broad-spectrum ubiquitinating enzyme that remodels the erythroid proteome. In particular, ribosome elimination, a hallmark of reticulocyte differentiation, was defective in Ube2o-/- mutants. UBE2O recognized ribosomal proteins and other substrates directly, targeting them to proteasomes for degradation. Thus, in reticulocytes, the induction of ubiquitinating factors may drive the transition from a complex to a simple proteome.

Multi-omics analysis identifies ATF4 as a key regulator of the mitochondrial stress response in mammals

Mitochondrial stress activates a mitonuclear response to safeguard and repair mitochondrial function and to adapt cellular metabolism to stress. Using a multiomics approach in mammalian cells treated with four types of mitochondrial stressors, we identify activating transcription factor 4 (ATF4) as the main regulator of the stress response. Surprisingly, canonical mitochondrial unfolded protein response genes mediated by ATF5 are not activated. Instead, ATF4 activates the expression of cytoprotective genes, which reprogram cellular metabolism through activation of the integrated stress response (ISR). Mitochondrial stress promotes a local proteostatic response by reducing mitochondrial ribosomal proteins, inhibiting mitochondrial translation, and coupling the activation of the ISR with the attenuation of mitochondrial function. Through a trans-expression quantitative trait locus analysis, we provide genetic evidence supporting a role for Fh1 in the control of Atf4 expression in mammals. Using gene expression data from mice and humans with mitochondrial diseases, we show that the ATF4 pathway is activated in vivo upon mitochondrial stress. Our data illustrate the value of a multiomics approach to characterize complex cellular networks and provide a versatile resource to identify new regulators of mitochondrial-related diseases.

A Triple Knockout (TKO) Proteomics Standard for Diagnosing Ion Interference in Isobaric Labeling Experiments

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, synchronous precursor selection and triple-stage mass spectrometry (SPS-MS3) can reduce the occurrence of this phenomenon, 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 tandem mass tag (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 can demonstrate 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. Graphical Abstract ᅟ.