Curated protein information in the Saccharomyces genome database

Mitochondrial respiration promotes Cdc37-dependent stability of the Cdk1 homolog Cdc28

Cdc28, the homolog of mammalian Cdk1, is a conserved key regulatory kinase for all major cell cycle transitions in yeast. We have found that defects in mitochondrial respiration (including deletion of ATP2, an ATP synthase subunit) inhibit growth of cells carrying a degron allele of Cdc28 (cdc28td) or Cdc28 temperature-sensitive mutations (cdc28-1 and cdc28-1N) at semi-permissive temperatures. Loss of cell proliferation in the atp2Δcdc28td double mutant is associated with aggravated cell cycle arrest and mitochondrial dysfunction, including mitochondrial hyperpolarization and fragmentation. Unexpectedly, in mutants defective in mitochondrial respiration, steady-state protein levels of mutant cdc28 are strongly reduced, accounting for the aggravated growth defects. Stability of Cdc28 is promoted by the Hsp90-Cdc37 chaperone complex. Our results show that atp2Δcdc28td double-mutant cells, but not single mutants, are sensitive to chemical inhibition of the Hsp90-Cdc37 complex, and exhibit reduced levels of additional Hsp90-Cdc37 client kinases, suggesting an inhibition of this complex. In agreement, overexpression of CDC37 improved atp2Δcdc28td cell growth and Cdc28 levels. Overall, our study shows that simultaneous disturbance of mitochondrial respiration and Cdc28 activity reduces the capacity of Cdc37 to chaperone client kinases, leading to growth arrest.

Autorepression-Based Conditional Gene Expression System in Yeast for Variation-Suppressed Control of Protein Dosage

Conditional control of gene expression allows an experimenter to investigate many aspects of a gene's function. In the model organism Saccharomyces cerevisiae, a number of methods to control gene expression are widely practiced, including induction by metabolites, small molecules, and even light. However, all current methods suffer from at least one of a set of drawbacks, including need for specialized growth conditions, leaky expression, or requirement of specialized equipment. Here we describe protocols using two transformations to construct strains that carry a new controller in which all these drawbacks are overcome. In these strains, the expression of a controlled gene of interest is repressed by the bacterial repressor TetR and induced by anhydrotetracycline. TetR also regulates its own expression, creating an autorepression loop. This autorepression allows tight control of gene expression and protein dosage with low cell-to-cell variation in expression. A second repressor, TetR-Tup1, prevents any leaky expression. We also present a protocol showing a particular workhorse application of such strains to generate synchronized cell populations. We turn off expression of the cell cycle regulator CDC20 completely, arresting the cell population, and then we turn it back on so that the synchronized cells resume cell cycle progression. This control system can be applied to any endogenous or exogenous gene for precise expression. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Generating a parent WTC846 strain Basic Protocol 2: Generating a WTC846 strain with controlled expression of the targeted gene Alternate Protocol: CRISPR-mediated promoter replacement Basic Protocol 3: Cell cycle synchronization/arrest and release using the WTC846- K3 ::CDC20 strain.

New data and collaborations at the Saccharomyces Genome Database: updated reference genome, alleles, and the Alliance of Genome Resources

Saccharomyces cerevisiae is used to provide fundamental understanding of eukaryotic genetics, gene product function, and cellular biological processes. Saccharomyces Genome Database (SGD) has been supporting the yeast research community since 1993, serving as its de facto hub. Over the years, SGD has maintained the genetic nomenclature, chromosome maps, and functional annotation, and developed various tools and methods for analysis and curation of a variety of emerging data types. More recently, SGD and six other model organism focused knowledgebases have come together to create the Alliance of Genome Resources to develop sustainable genome information resources that promote and support the use of various model organisms to understand the genetic and genomic bases of human biology and disease. Here we describe recent activities at SGD, including the latest reference genome annotation update, the development of a curation system for mutant alleles, and new pages addressing homology across model organisms as well as the use of yeast to study human disease.

Improved Protein Coverage in Bottom-Up Proteomes Analysis Using Fluoroalcohol-Mediated Supramolecular Biphasic Systems With Mixed Amphiphiles for Sample Extraction, Fractionation, and Enrichment

A new class of supramolecular biphasic systems containing fluoroalcohol-induced coacervates (FAiC) provides concomitant fractionation of complex protein mixtures, high solubilizing power for extraction of various types of proteins, especially those with high hydrophobicity (such as membrane proteins), and enrichment of low-abundance proteins. Subsequently, the use of FAiC biphasic systems (BPS) in the bottom-up proteomics workflow resulted in significantly higher coverage for the whole proteome, various subproteomes, especially those embedded or associated with membranes, post-translationally modified proteins, and low-abundance proteins (LAPs) as compared to the conventional methodologies. In this work, we used a new type of FAiC-BPS composed of mixed amphiphiles, a zwitterionic surfactant 3-(N,N-dimethylmyristyl ammonia) propane sulfonate (DMMAPS), a quaternary ammonium salt (QUATS), and hexafluoroisopropanol (HFIP) as the coacervator for extraction, fractionation, and enrichment of yeast proteome in bottom-up proteomics. The coverage of the lower-abundance proteins (abundance below 2000 molecules/cell) improved by more than 100% using DMMAPS and DMMAPS + QUATS systems as compared to the conventional methods using urea or detergent solutions for protein solubilization. Additionally, these coacervate systems show increased coverage of integral membrane proteins and proteins with α-helices by up to 24 and 555%, respectively.

Evaluating accessibility, usability and interoperability of genome-scale metabolic models for diverse yeasts species

Metabolic network reconstructions have become an important tool for probing cellular metabolism in the field of systems biology. They are used as tools for quantitative prediction but also as scaffolds for further knowledge contextualization. The yeast Saccharomyces cerevisiae was one of the first organisms for which a genome-scale metabolic model (GEM) was reconstructed, in 2003, and since then 45 metabolic models have been developed for a wide variety of relevant yeasts species. A systematic evaluation of these models revealed that-despite this long modeling history-the sequential process of tracing model files, setting them up for basic simulation purposes and comparing them across species and even different versions, is still not a generalizable task. These findings call the yeast modeling community to comply to standard practices on model development and sharing in order to make GEMs accessible and useful for a wider public.

Limited DNA Repair Gene Repertoire in Ascomycete Yeast Revealed by Comparative Genomics

Ascomycota is the largest phylogenetic group of fungi that includes species important to human health and wellbeing. DNA repair is important for fungal survival and genome evolution. Here, we describe a detailed comparative genomic analysis of DNA repair genes in Ascomycota. We determined the DNA repair gene repertoire in Taphrinomycotina, Saccharomycotina, Leotiomycetes, Sordariomycetes, Dothideomycetes, and Eurotiomycetes. The subphyla of yeasts, Saccharomycotina and Taphrinomycotina, have a smaller DNA repair gene repertoire comparing to Pezizomycotina. Some genes were absent from most, if not all, yeast species. To study the conservation of these genes in Pezizomycotina, we used the Gain Loss Mapping Engine algorithm that provides the expectations of gain or loss of genes given the tree topology. Genes that were absent from most of the species of Taphrinomycotina or Saccharomycotina showed lower conservation in Pezizomycotina. This suggests that the absence of some DNA repair in yeasts is not random; genes with a tendency to be lost in other classes are missing. We ranked the conservation of DNA repair genes in Ascomycota. We found that Rad51 and its paralogs were less conserved than other recombinational proteins, suggesting that there is a redundancy between Rad51 and its paralogs, at least in some species. Finally, based on the repertoire of UV repair genes, we found conditions that differentially kill the wine pathogen Brettanomyces bruxellensis and not Saccharomyces cerevisiae. In summary, our analysis provides testable hypotheses to the role of DNA repair proteins in the genome evolution of Ascomycota.

RESTful API for iPTMnet: a resource for protein post-translational modification network discovery

iPTMnet is a bioinformatics resource that integrates protein post-translational modification (PTM) data from text mining and curated databases and ontologies to aid in knowledge discovery and scientific study. The current iPTMnet website can be used for querying and browsing rich PTM information but does not support automated iPTMnet data integration with other tools. Hence, we have developed a RESTful API utilizing the latest developments in cloud technologies to facilitate the integration of iPTMnet into existing tools and pipelines. We have packaged iPTMnet API software in Docker containers and published it on DockerHub for easy redistribution. We have also developed Python and R packages that allow users to integrate iPTMnet for scientific discovery, as demonstrated in a use case that connects PTM sites to kinase signaling pathways.

Incorporation of a unified protein abundance dataset into the Saccharomyces genome database

The identification and accurate quantitation of protein abundance has been a major objective of proteomics research. Abundance studies have the potential to provide users with data that can be used to gain a deeper understanding of protein function and regulation and can also help identify cellular pathways and modules that operate under various environmental stress conditions. One of the central missions of the Saccharomyces Genome Database (SGD; https://www.yeastgenome.org) is to work with researchers to identify and incorporate datasets of interest to the wider scientific community, thereby enabling hypothesis-driven research. A large number of studies have detailed efforts to generate proteome-wide abundance data, but deeper analyses of these data have been hampered by the inability to compare results between studies. Recently, a unified protein abundance dataset was generated through the evaluation of more than 20 abundance datasets, which were normalized and converted to common measurement units, in this case molecules per cell. We have incorporated these normalized protein abundance data and associated metadata into the SGD database, as well as the SGD YeastMine data warehouse, resulting in the addition of 56 487 values for untreated cells grown in either rich or defined media and 28 335 values for cells treated with environmental stressors. Abundance data for protein-coding genes are displayed in a sortable, filterable table on Protein pages, available through Locus Summary pages. A median abundance value was incorporated, and a median absolute deviation was calculated for each protein-coding gene and incorporated into SGD. These values are displayed in the Protein section of the Locus Summary page. The inclusion of these data has enhanced the quality and quantity of protein experimental information presented at SGD and provides opportunities for researchers to access and utilize the data to further their research.

Measuring similarity between gene interaction profiles

Background

Gene and protein interaction data are often represented as interaction networks, where nodes stand for genes or gene products and each edge stands for a relationship between a pair of gene nodes. Commonly, that relationship within a pair is specified by high similarity between profiles (vectors) of experimentally defined interactions of each of the two genes with all other genes in the genome; only gene pairs that interact with similar sets of genes are linked by an edge in the network. The tight groups of genes/gene products that work together in a cell can be discovered by the analysis of those complex networks.

Results

We show that the choice of the similarity measure between pairs of gene vectors impacts the properties of networks and of gene modules detected within them. We re-analyzed well-studied data on yeast genetic interactions, constructed four genetic networks using four different similarity measures, and detected gene modules in each network using the same algorithm. The four networks induced different numbers of putative functional gene modules, and each similarity measure induced some unique modules. In an example of a putative functional connection suggested by comparing genetic interaction vectors, we predict a link between SUN-domain proteins and protein glycosylation in the endoplasmic reticulum.

Conclusions

The discovery of molecular modules in genetic networks is sensitive to the way of measuring similarity between profiles of gene interactions in a cell. In the absence of a formal way to choose the “best” measure, it is advisable to explore the measures with different mathematical properties, which may identify different sets of connections between genes.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-3024-x) contains supplementary material, which is available to authorized users.

The Regulation of Cbf1 by PAS Kinase Is a Pivotal Control Point for Lipogenesis vs. Respiration in Saccharomyces cerevisiae

PAS kinase 1 (Psk1) is a key regulator of respiration in Saccharomyces cerevisiae. Herein the molecular mechanisms of this regulation are explored through the characterization of its substrate, Centromere binding factor 1 (Cbf1). CBF1-deficient yeast displayed a significant decrease in cellular respiration, while PAS kinase-deficient yeast, or yeast harboring a Cbf1 phosphosite mutant (T211A) displayed a significant increase. Transmission electron micrographs showed an increased number of mitochondria in PAS kinase-deficient yeast consistent with the increase in respiration. Although the CBF1-deficient yeast did not appear to have an altered number of mitochondria, a mitochondrial proteomics study revealed significant differences in the mitochondrial composition of CBF1-deficient yeast including altered Atp3 levels, a subunit of the mitochondrial F₁-ATP synthase complex. Both beta-galactosidase reporter assays and western blot analysis confirmed direct transcriptional control of ATP3 by Cbf1. In addition, we confirmed the regulation of yeast lipid genes LAC1 and LAG1 by Cbf1. The human homolog of Cbf1, Upstream transcription factor 1 (USF1), is also known to be involved in lipid biogenesis. Herein, we provide the first evidence for a role of USF1 in respiration since it appeared to complement Cbf1in vivo as determined by respiration phenotypes. In addition, we confirmed USF1 as a substrate of human PAS kinase (hPASK) in vitro. Combined, our data supports a model in which Cbf1/USF1 functions to partition glucose toward respiration and away from lipid biogenesis, while PAS kinase inhibits respiration in part through the inhibition of Cbf1/USF1.

Signaling to and from the RNA Polymerase III Transcription and Processing Machinery

RNA polymerase (Pol) III has a specialized role in transcribing the most abundant RNAs in eukaryotic cells, transfer RNAs (tRNAs), along with other ubiquitous small noncoding RNAs, many of which have functions related to the ribosome and protein synthesis. The high energetic cost of producing these RNAs and their central role in protein synthesis underlie the robust regulation of Pol III transcription in response to nutrients and stress by growth regulatory pathways. Downstream of Pol III, signaling impacts posttranscriptional processes affecting tRNA function in translation and tRNA cleavage into smaller fragments that are increasingly attributed with novel cellular activities. In this review, we consider how nutrients and stress control Pol III transcription via its factors and its negative regulator, Maf1. We highlight recent work showing that the composition of the tRNA population and the function of individual tRNAs is dynamically controlled and that unrestrained Pol III transcription can reprogram central metabolic pathways.

Updated regulation curation model at the Saccharomyces Genome Database

The Saccharomyces Genome Database (SGD) provides comprehensive, integrated biological information for the budding yeast Saccharomyces cerevisiae, along with search and analysis tools to explore these data, enabling the discovery of functional relationships between sequence and gene products in fungi and higher organisms. We have recently expanded our data model for regulation curation to address regulation at the protein level in addition to transcription, and are presenting the expanded data on the ‘Regulation’ pages at SGD. These pages include a summary describing the context under which the regulator acts, manually curated and high-throughput annotations showing the regulatory relationships for that gene and a graphical visualization of its regulatory network and connected networks. For genes whose products regulate other genes or proteins, the Regulation page includes Gene Ontology enrichment analysis of the biological processes in which those targets participate. For DNA-binding transcription factors, we also provide other information relevant to their regulatory function, such as DNA binding site motifs and protein domains. As with other data types at SGD, all regulatory relationships and accompanying data are available through YeastMine, SGD’s data warehouse based on InterMine.

Database URL: http://www.yeastgenome.org

Enrichment of Circular Code Motifs in the Genes of the Yeast Saccharomyces cerevisiae

A set X of 20 trinucleotides has been found to have the highest average occurrence in the reading frame, compared to the two shifted frames, of genes of bacteria, archaea, eukaryotes, plasmids and viruses. This set X has an interesting mathematical property, since X is a maximal C3 self-complementary trinucleotide circular code. Furthermore, any motif obtained from this circular code X has the capacity to retrieve, maintain and synchronize the original (reading) frame. Since 1996, the theory of circular codes in genes has mainly been developed by analysing the properties of the 20 trinucleotides of X, using combinatorics and statistical approaches. For the first time, we test this theory by analysing the X motifs, i.e., motifs from the circular code X, in the complete genome of the yeast Saccharomyces cerevisiae. Several properties of X motifs are identified by basic statistics (at the frequency level), and evaluated by comparison to R motifs, i.e., random motifs generated from 30 different random codes R. We first show that the frequency of X motifs is significantly greater than that of R motifs in the genome of S. cerevisiae. We then verify that no significant difference is observed between the frequencies of X and R motifs in the non-coding regions of S. cerevisiae, but that the occurrence number of X motifs is significantly higher than R motifs in the genes (protein-coding regions). This property is true for all cardinalities of X motifs (from 4 to 20) and for all 16 chromosomes. We further investigate the distribution of X motifs in the three frames of S. cerevisiae genes and show that they occur more frequently in the reading frame, regardless of their cardinality or their length. Finally, the ratio of X genes, i.e., genes with at least one X motif, to non-X genes, in the set of verified genes is significantly different to that observed in the set of putative or dubious genes with no experimental evidence. These results, taken together, represent the first evidence for a significant enrichment of X motifs in the genes of an extant organism. They raise two hypotheses: the X motifs may be evolutionary relics of the primitive codes used for translation, or they may continue to play a functional role in the complex processes of genome decoding and protein synthesis.