YAAM: Yeast Amino Acid Modifications Database

Physiological relevance, localization and substrate specificity of the alternative (type II) mitochondrial NADH dehydrogenases of Ogataea parapolymorpha

Mitochondria from Ogataea parapolymorpha harbor a branched electron-transport chain containing a proton-pumping Complex I NADH dehydrogenase and three Type II NADH dehydrogenases (NDH-2). To investigate the physiological role, localization and substrate specificity of these enzymes, the growth of various NADH dehydrogenase knockout mutants was quantitatively characterized in shake-flask and chemostat cultures, followed by oxygen-uptake experiments with isolated mitochondria. NAD(P)H:quinone oxidoreduction of the three NDH-2 were individually assessed. Our findings reveal that the O. parapolymorpha respiratory chain contains an internal NADH-accepting NDH-2 (Ndh2-1/OpNdi1), at least one external NAD(P)H-accepting enzyme, and likely additional mechanisms for respiration-linked oxidation of cytosolic NADH. Metabolic regulation appears to prevent competition between OpNdi1 and Complex I for mitochondrial NADH. With the exception of OpNdi1, the respiratory chain of O. parapolymorpha exhibits metabolic redundancy and tolerates deletion of multiple NADH-dehydrogenase genes without compromising fully respiratory metabolism.

Current computational tools for protein lysine acylation site prediction

As a main subtype of post-translational modification (PTM), protein lysine acylations (PLAs) play crucial roles in regulating diverse functions of proteins. With recent advancements in proteomics technology, the identification of PTM is becoming a data-rich field. A large amount of experimentally verified data is urgently required to be translated into valuable biological insights. With computational approaches, PLA can be accurately detected across the whole proteome, even for organisms with small-scale datasets. Herein, a comprehensive summary of 166 in silico PLA prediction methods is presented, including a single type of PLA site and multiple types of PLA sites. This recapitulation covers important aspects that are critical for the development of a robust predictor, including data collection and preparation, sample selection, feature representation, classification algorithm design, model evaluation, and method availability. Notably, we discuss the application of protein language models and transfer learning to solve the small-sample learning issue. We also highlight the prediction methods developed for functionally relevant PLA sites and species/substrate/cell-type-specific PLA sites. In conclusion, this systematic review could potentially facilitate the development of novel PLA predictors and offer useful insights to researchers from various disciplines.

The tubulin database: Linking mutations, modifications, ligands and local interactions

Microtubules are polymeric filaments, constructed of α-β tubulin heterodimers that underlie critical subcellular structures in eukaryotic organisms. Four homologous proteins (γ-, δ-, ε- and ζ-tubulin) additionally contribute to specialized microtubule functions. Although there is an immense volume of publicly available data pertaining to tubulins, it is difficult to assimilate all potentially relevant information across diverse organisms, isotypes, and categories of data. We previously assembled an extensive web-based catalogue of published missense mutations to tubulins with >1,500 entries that each document a specific substitution to a discrete tubulin, the species where the mutation was described and the associated phenotype with hyperlinks to the amino acid sequence and citation(s) for research. This report describes a significant update and expansion of our online resource (TubulinDB.bio.uci.edu) to nearly 18,000 entries. It now encompasses a cross-referenced catalog of post-translational modifications (PTMs) to tubulin drawn from public datasets, primary literature, and predictive algorithms. In addition, tubulin protein structures were used to define local interactions with bound ligands (GTP, GDP and diverse microtubule-targeting agents) and amino acids at the intradimer interface, within the microtubule lattice and with associated proteins. To effectively cross-reference these datasets, we established a universal tubulin numbering system to map entries into a common framework that accommodates specific insertions and deletions to tubulins. Indexing and cross-referencing permitted us to discern previously unappreciated patterns. We describe previously unlinked observations of loss of PTM sites in the context of cancer cells and tubulinopathies. Similarly, we expanded the set of clinical substitutions that may compromise MAP or microtubule-motor interactions by collecting tubulin missense mutations that alter amino acids at the interface with dynein and doublecortin. By expanding the database as a curated resource, we hope to relate model organism data to clinical findings of pathogenic tubulin variants. Ultimately, we aim to aid researchers in hypothesis generation and design of studies to dissect tubulin function.

Protein Design Strategies for the Structural–Functional Studies of G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are an important family of membrane proteins responsible for many physiological functions in human body. High resolution GPCR structures are required to understand their molecular mechanisms and perform rational drug design, as GPCRs play a crucial role in a variety of diseases. That is difficult to obtain for the wild-type proteins because of their low stability. In this review, we discuss how this problem can be solved by using protein design strategies developed to obtain homogeneous stabilized GPCR samples for crystallization and cryoelectron microscopy.

Transcription factor binding process is the primary driver of noise in gene expression

Noise in expression of individual genes gives rise to variations in activity of cellular pathways and generates heterogeneity in cellular phenotypes. Phenotypic heterogeneity has important implications for antibiotic persistence, mutation penetrance, cancer growth and therapy resistance. Specific molecular features such as the presence of the TATA box sequence and the promoter nucleosome occupancy have been associated with noise. However, the relative importance of these features in noise regulation is unclear and how well these features can predict noise has not yet been assessed. Here through an integrated statistical model of gene expression noise in yeast we found that the number of regulating transcription factors (TFs) of a gene was a key predictor of noise, whereas presence of the TATA box and the promoter nucleosome occupancy had poor predictive power. With an increase in the number of regulatory TFs, there was a rise in the number of cooperatively binding TFs. In addition, an increased number of regulatory TFs meant more overlaps in TF binding sites, resulting in competition between TFs for binding to the same region of the promoter. Through modeling of TF binding to promoter and application of stochastic simulations, we demonstrated that competition and cooperation among TFs could increase noise. Thus, our work uncovers a process of noise regulation that arises out of the dynamics of gene regulation and is not dependent on any specific transcription factor or specific promoter sequence.

Thirty years of molecular dynamics simulations on posttranslational modifications of proteins

Posttranslational modifications (PTMs) are an integral component to how cells respond to perturbation. While experimental advances have enabled improved PTM identification capabilities, the same throughput for characterizing how structural changes caused by PTMs equate to altered physiological function has not been maintained. In this Perspective, we cover the history of computational modeling and molecular dynamics simulations which have characterized the structural implications of PTMs. We distinguish results from different molecular dynamics studies based upon the timescales simulated and analysis approaches used for PTM characterization. Lastly, we offer insights into how opportunities for modern research efforts on in silico PTM characterization may proceed given current state-of-the-art computing capabilities and methodological advancements.

Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

Background

Starch, a vital plant-derived polysaccharide comprised of branched glucans, is essential in nutrition and many industrial applications. Starch is often modified post-extraction to alter its structure and enhance its functionality. Targeted metabolic engineering of crops to produce valuable and versatile starches requires knowledge of the relationships between starch biosynthesis, structure, and properties, but systematic studies to obtain this knowledge are difficult to conduct in plants. Here we used Saccharomyces cerevisiae as a testbed to dissect the functions of plant starch biosynthetic enzymes and create diverse starch-like polymers.

Results

We explored yeast promoters and terminators to tune the expression levels of the starch-biosynthesis machinery from Arabidopsis thaliana. We systematically modulated the expression of each starch synthase (SS) together with a branching enzyme (BE) in yeast. Protein quantification by parallel reaction monitoring (targeted proteomics) revealed unexpected effects of glucan biosynthesis on protein abundances but showed that the anticipated broad range of SS/BE enzyme ratios was maintained during the biosynthetic process. The different SS/BE ratios clearly influenced glucan structure and solubility: The higher the SS/BE ratio, the longer the glucan chains and the more glucans were partitioned into the insoluble fraction. This effect was irrespective of the SS isoform, demonstrating that the elongation/branching ratio controls glucan properties separate from enzyme specificity.

Conclusions

Our results provide a quantitative framework for the in silico design of improved starch biosynthetic processes in plants. Our study also exemplifies a workflow for the rational tuning of a complex pathway in yeast, starting from the selection and evaluation of expression modules to multi-gene assembly and targeted protein monitoring during the biosynthetic process.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01408-x.

Ready, SET, Go: Post-translational regulation of the histone lysine methylation network in budding yeast

Histone lysine methylation is a key epigenetic modification that regulates eukaryotic transcription. Here, we comprehensively review the function and regulation of the histone methylation network in the budding yeast and model eukaryote, Saccharomyces cerevisiae. First, we outline the lysine methylation sites that are found on histone proteins in yeast (H3K4me1/2/3, H3K36me1/2/3, H3K79me1/2/3, and H4K5/8/12me1) and discuss their biological and cellular roles. Next, we detail the reduced but evolutionarily conserved suite of methyltransferase (Set1p, Set2p, Dot1p, and Set5p) and demethylase (Jhd1p, Jhd2p, Rph1p, and Gis1p) enzymes that are known to control histone lysine methylation in budding yeast cells. Specifically, we illustrate the domain architecture of the methylation enzymes and highlight the structural features that are required for their respective functions and molecular interactions. Finally, we discuss the prevalence of post-translational modifications on yeast histone methylation enzymes and how phosphorylation, acetylation, and ubiquitination in particular are emerging as key regulators of enzyme function. We note that it will be possible to completely connect the histone methylation network to the cell's signaling system, given that all methylation sites and cognate enzymes are known, most phosphosites on the enzymes are known, and the mapping of kinases to phosphosites is tractable owing to the modest set of protein kinases in yeast. Moving forward, we expect that the rich variety of post-translational modifications that decorates the histone methylation machinery will explain many of the unresolved questions surrounding the function and dynamics of this intricate epigenetic network.

Discovery of Arginine Methylation, Phosphorylation, and Their Co-occurrence in Condensate-Associated Proteins in Saccharomyces cerevisiae

The formation of condensates in membraneless organelles is thought to be driven by protein phase separation. Arginine methylation and serine/threonine phosphorylation are important in the phase separation process; however, these post-translational modifications are often present in intrinsically disordered regions that are difficult to analyze with standard proteomic techniques. To understand their presence and co-occurrence in condensate-associated proteins, here, we use a multiprotease and multi-tandem mass spectrometry (MS/MS) fragmentation approach, coupled with heavy methyl stable isotope labeling of amino acids in cell culture (SILAC) and phospho- or methyl-peptide enrichment. For Saccharomyces cerevisiae, we report a 50% increase in the known arginine methylproteome, involving 15 proteins that are all condensate-associated. Importantly, some of these proteins have arginine methylation on all predicted sites-providing evidence that this modification can be pervasive. We explored whether arginine-methylated, condensate-associated proteins are also phosphorylated and found 12 such proteins to carry phosphorylated serine or threonine. In Npl3, Ded1, and Sbp1, single peptides were found to carry both modifications, indicating a co-occurrence in close proximity and on the same protein molecule. These co-modifications occur in regions of disorder, whereas arginine methylation is typically on regions of disorder that are also basic. For phosphorylation, its association with charged regions of condensate-associated proteins was less consistent, although some regions with multisite phosphorylation sites were strongly acidic. We conclude that arginine-methylated proteins associated with condensates are typically also modified with protein phosphorylation.

PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact

Post-translational modifications (PTMs) play very important roles in various cell signaling pathways and biological process. Due to PTMs' extremely important roles, many major PTMs have been studied, while the functional and mechanical characterization of major PTMs is well documented in several databases. However, most currently available databases mainly focus on protein sequences, while the real 3D structures of PTMs have been largely ignored. Therefore, studies of PTMs 3D structural signatures have been severely limited by the deficiency of the data. Here, we develop PRISMOID, a novel publicly available and free 3D structure database for a wide range of PTMs. PRISMOID represents an up-to-date and interactive online knowledge base with specific focus on 3D structural contexts of PTMs sites and mutations that occur on PTMs and in the close proximity of PTM sites with functional impact. The first version of PRISMOID encompasses 17 145 non-redundant modification sites on 3919 related protein 3D structure entries pertaining to 37 different types of PTMs. Our entry web page is organized in a comprehensive manner, including detailed PTM annotation on the 3D structure and biological information in terms of mutations affecting PTMs, secondary structure features and per-residue solvent accessibility features of PTM sites, domain context, predicted natively disordered regions and sequence alignments. In addition, high-definition JavaScript packages are employed to enhance information visualization in PRISMOID. PRISMOID equips a variety of interactive and customizable search options and data browsing functions; these capabilities allow users to access data via keyword, ID and advanced options combination search in an efficient and user-friendly way. A download page is also provided to enable users to download the SQL file, computational structural features and PTM sites' data. We anticipate PRISMOID will swiftly become an invaluable online resource, assisting both biologists and bioinformaticians to conduct experiments and develop applications supporting discovery efforts in the sequence-structural-functional relationship of PTMs and providing important insight into mutations and PTM sites interaction mechanisms. The PRISMOID database is freely accessible at http://prismoid.erc.monash.edu/. The database and web interface are implemented in MySQL, JSP, JavaScript and HTML with all major browsers supported.

IMRPS: Inserted and Modified Residues in Protein Structures. A database

Modified residues present in proteins are the result of post-translational modifications (PTMs). These PTMs increase the functional diversity of the proteome and influence various biological processes and diseased conditions. Therefore, identification and understanding of PTMs in various protein structures is of great significance. In view of this, an online database, Inserted and Modified Residues in Protein Structures (IMRPS), has been developed. IMRPS is a derived database that furnishes information on the residues modified and inserted in the protein structures available in the Protein Data Bank (PDB). The database is equipped with a graphical user interface and has an option to view the data for non-redundant protein structures (25 and 90%) as well. A quality criteria cutoff has been incorporated to assist in displaying the specific set of PDB codes. The entire protein structure along with the inserted or modified residues can be visualized in JSmol. This database will be updated regularly (presently, every three months) and can be accessed through the URL http://cluster.physics.iisc.ac.in/imrps/.

Shot-gun proteomics: why thousands of unidentified signals matter

Mass spectrometry-based proteomics has become a constitutional part of the multi-omics toolbox in yeast research, advancing fundamental knowledge of molecular processes and guiding decisions in strain and product developmental pipelines. Nevertheless, post-translational protein modifications (PTMs) continue to challenge the field of proteomics. PTMs are not directly encoded in the genome; therefore, they require a sensitive analysis of the proteome itself. In yeast, the relevance of post-translational regulators has already been established, such as for phosphorylation, which can directly affect the reaction rates of metabolic enzymes. Whereas, the selective analysis of single modifications has become a broadly employed technique, the sensitive analysis of a comprehensive set of modifications still remains a challenge. At the same time, a large number of fragmentation spectra in a typical shot-gun proteomics experiment remain unidentified. It has been estimated that a good proportion of those unidentified spectra originates from unexpected modifications or natural peptide variants. In this review, recent advancements in microbial proteomics for unrestricted protein modification discovery are reviewed, and recent research integrating this additional layer of information to elucidate protein interaction and regulation in yeast is briefly discussed.

Tunicamycin Sensitivity-Suppression by High Gene Dosage Reveals New Functions of the Yeast Hog1 MAP Kinase

In the yeast Saccharomyces cerevisiae, components of the High Osmolarity Glycerol (HOG) pathway are important for the response to diverse stresses including response to endoplasmic reticulum stress (ER stress), which is produced by the accumulation of unfolded proteins in the lumen of this organelle. Accumulation of unfolded proteins may be due to the inhibition of protein N-glycosylation, which can be achieved by treatment with the antibiotic tunicamycin (Tn). In this work we were interested in finding proteins involved in the ER stress response regulated by Hog1, the mitogen activated protein kinase (MAPK) of the HOG pathway. A high gene dosage suppression screening allowed us to identify genes that suppressed the sensitivity to Tn shown by a hog1Δ mutant. The suppressors participate in a limited number of cellular processes, including lipid/carbohydrate biosynthesis and protein glycosylation, vesicle-mediated transport and exocytosis, cell wall organization and biogenesis, and cell detoxification processes. The finding of suppressors Rer2 and Srt1, which participate in the dolichol biosynthesis pathway revealed that the hog1Δ strain has a defective polyprenol metabolism. This work uncovers new genetic and functional interactors of Hog1 and contributes to a better understanding of the participation of this MAPK in the ER stress response.

Yeast Systems Biology: The Continuing Challenge of Eukaryotic Complexity

Research on yeast has produced a plethora of tools and resources that have been central to the progress of systems biology. This chapter reviews these resources, explains the innovations that have been made since the first edition of this book, and introduces the constituent chapters of the current edition. The value of these resources not only in building and testing models of the functional networks of the yeast cell, but also in providing a foundation for network studies on the molecular basis of complex human diseases is considered. The gaps in this vast compendium of data, including enzyme kinetic characteristics, biomass composition, transport processes, and cell-cell interactions are discussed, as are the interactions between yeast cells and those of other species. The relevance of these studies to both traditional and advanced biotechnologies and to human medicine is considered, and the opportunities and challenges in using unicellular yeasts to model the systems of multicellular organisms are presented.