Genome-wide single-cell-level screen for protein abundance and localization changes in response to DNA damage in S. cerevisiae

Quantitative Characterisation of Low Abundant Yeast Mitochondrial Proteins Reveals Compensation for Haplo-Insufficiency in Different Environments

The quantification of low abundant membrane-binding proteins such as transcriptional factors and chaperones has proven difficult, even with the most sophisticated analytical technologies. Here, we exploit and optimise the non-invasive Fluorescence Correlation Spectroscopy (FCS) for the quantitation of low abundance proteins, and as proof of principle, we choose two interacting proteins involved in the fission of mitochondria in yeast, Fis1p and Mdv1p. In Saccharomyces cerevisiae, the recruitment of Fis1p and Mdv1p to mitochondria is essential for the scission of the organelles and the retention of functional mitochondrial structures in the cell. We use FCS in single GFP-labelled live yeast cells to quantify the protein abundance in homozygote and heterozygote cells and to investigate the impact of the environments on protein copy number, bound/unbound protein state and mobility kinetics. Both proteins were observed to localise predominantly at mitochondrial structures, with the Mdv1p bound state increasing significantly in a strictly respiratory environment. Moreover, a compensatory mechanism that controls Fis1p abundance upon deletion of one allele was observed in Fis1p but not in Mdv1p, suggesting differential regulation of Fis1p and Mdv1p protein expression.

Single-cell image analysis to explore cell-to-cell heterogeneity in isogenic populations

Single-cell image analysis provides a powerful approach for studying cell-to-cell heterogeneity, which is an important attribute of isogenic cell populations, from microbial cultures to individual cells in multicellular organisms. This phenotypic variability must be explained at a mechanistic level if biologists are to fully understand cellular function and address the genotype-to-phenotype relationship. Variability in single-cell phenotypes is obscured by bulk readouts or averaging of phenotypes from individual cells in a sample; thus, single-cell image analysis enables a higher resolution view of cellular function. Here, we consider examples of both small- and large-scale studies carried out with isogenic cell populations assessed by fluorescence microscopy, and we illustrate the advantages, challenges, and the promise of quantitative single-cell image analysis.

A predictive model of gene expression reveals the role of network motifs in the mating response of yeast

Cells use signaling pathways to receive and process information about their environment. These nonlinear systems rely on feedback and feedforward regulation to respond appropriately to changing environmental conditions. Mathematical models describing signaling pathways often lack predictive power because they are not trained on data that encompass the diverse time scales on which these regulatory mechanisms operate. We addressed this limitation by measuring transcriptional changes induced by the mating response in Saccharomyces cerevisiae exposed to different dynamic patterns of pheromone. We found that pheromone-induced transcription persisted after pheromone removal and showed long-term adaptation upon sustained pheromone exposure. We developed a model of the regulatory network that captured both characteristics of the mating response. We fit this model to experimental data with an evolutionary algorithm and used the parameterized model to predict scenarios for which it was not trained, including different temporal stimulus profiles and genetic perturbations to pathway components. Our model allowed us to establish the role of four architectural elements of the network in regulating gene expression. These network motifs are incoherent feedforward, positive feedback, negative feedback, and repressor binding. Experimental and computational perturbations to these network motifs established a specific role for each in coordinating the mating response to persistent and dynamic stimulation.

Proteomic analysis of the S. cerevisiae response to the anticancer ruthenium complex KP1019

Like platinum-based chemotherapeutics, the anticancer ruthenium complex indazolium trans-[tetrachlorobis(1H-indazole)ruthenate(iii)], or KP1019, damages DNA, induces apoptosis, and causes tumor regression in animal models. Unlike platinum-based drugs, KP1019 showed no dose-limiting toxicity in a phase I clinical trial. Despite these advances, the mechanism(s) and target(s) of KP1019 remain unclear. For example, the drug may damage DNA directly or by causing oxidative stress. Likewise, KP1019 binds cytosolic proteins, suggesting DNA is not the sole target. Here we use the budding yeast Saccharomyces cerevisiae as a model in a proteomic study of the cellular response to KP1019. Mapping protein level changes onto metabolic pathways revealed patterns consistent with elevated synthesis and/or cycling of the antioxidant glutathione, suggesting KP1019 induces oxidative stress. This result was supported by increased fluorescence of the redox-sensitive dye DCFH-DA and increased KP1019 sensitivity of yeast lacking Yap1, a master regulator of the oxidative stress response. In addition to oxidative and DNA stress, bioinformatic analysis revealed drug-dependent increases in proteins involved ribosome biogenesis, translation, and protein (re)folding. Consistent with proteotoxic effects, KP1019 increased expression of a heat-shock element (HSE) lacZ reporter. KP1019 pre-treatment also sensitized yeast to oxaliplatin, paralleling prior research showing that cancer cell lines with elevated levels of translation machinery are hypersensitive to oxaliplatin. Combined, these data suggest that one of KP1019's many targets may be protein metabolism, which opens up intriguing possibilities for combination therapy.

Spatial proteomics: a powerful discovery tool for cell biology

Protein subcellular localization is tightly controlled and intimately linked to protein function in health and disease. Capturing the spatial proteome - that is, the localizations of proteins and their dynamics at the subcellular level - is therefore essential for a complete understanding of cell biology. Owing to substantial advances in microscopy, mass spectrometry and machine learning applications for data analysis, the field is now mature for proteome-wide investigations of spatial cellular regulation. Studies of the human proteome have begun to reveal a complex architecture, including single-cell variations, dynamic protein translocations, changing interaction networks and proteins localizing to multiple compartments. Furthermore, several studies have successfully harnessed the power of comparative spatial proteomics as a discovery tool to unravel disease mechanisms. We are at the beginning of an era in which spatial proteomics finally integrates with cell biology and medical research, thereby paving the way for unbiased systems-level insights into cellular processes. Here, we discuss current methods for spatial proteomics using imaging or mass spectrometry and specifically highlight global comparative applications. The aim of this Review is to survey the state of the field and also to encourage more cell biologists to apply spatial proteomics approaches.

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.

Definition of the Minimal Contents for the Molecular Simulation of the Yeast Cytoplasm

The cytoplasm is a densely packed environment filled with macromolecules with hindered diffusion. Molecular simulation of the diffusion of biomolecules under such macromolecular crowding conditions requires the definition of a simulation cell with a cytoplasmic-like composition. This has been previously done for prokaryote cells (E. coli) but not for eukaryote cells such as yeast as a model organism. Yeast proteomics datasets vary widely in terms of cell growth conditions, the technique used to determine protein composition, the reported relative abundance of proteins, and the units in which abundances are reported. We determined that the gene ontology profiles of the most abundant proteins across these datasets are similar, but their abundances vary greatly. To overcome this problem, we chose five mass spectrometry proteomics datasets that fulfilled the following criteria: high internal consistency, consistency with published experimental data, and freedom from GFP-tagging artifacts. Using these datasets, the contents of a simulation cell containing a single 80S ribosome were defined, such that the macromolecular density and the mass ratio of ribosomal-to-cytoplasmic proteins were consistent with experiment and chosen datasets. Finally, multiple tRNAs were added, consistent with their experimentally-determined number in the yeast cell. The resulting composition can be readily used in molecular simulations representative of yeast cytoplasmic macromolecular crowding conditions to characterize a variety of phenomena, such as protein diffusion, protein-protein interactions and biological processes such as protein translation.

A quantitative screen for metabolic enzyme structures reveals patterns of assembly across the yeast metabolic network

Despite the proliferation of proteins that can form filaments or phase-separated condensates, it remains unclear how this behavior is distributed over biological networks. We have found that 60 of the 440 yeast metabolic enzymes robustly form structures, including 10 that assemble within mitochondria. Additionally, the ability to assemble is enriched at branch points on several metabolic pathways. The assembly of enzymes at the first branch point in de novo purine biosynthesis is coordinated, hierarchical, and based on their position within the pathway, while the enzymes at the second branch point are recruited to RNA stress granules. Consistent with distinct classes of structures being deployed at different control points in a pathway, we find that the first enzyme in the pathway, PRPP synthetase, forms evolutionarily conserved filaments that are sequestered in the nucleus in higher eukaryotes. These findings provide a roadmap for identifying additional conserved features of metabolic regulation by condensates/filaments.

Transcriptional responses to DNA damage

In response to the threat of DNA damage, cells exhibit a dramatic and multi-factorial response spanning from transcriptional changes to protein modifications, collectively known as the DNA damage response (DDR). Here, we review the literature surrounding the transcriptional response to DNA damage. We review differences in observed transcriptional responses as a function of cell cycle stage and emphasize the importance of experimental design in these transcriptional response studies. We additionally consider topics including structural challenges in the transcriptional response to DNA damage as well as the connection between transcription and protein abundance.

Doxorubicin-induced DNA Damage Causes Extensive Ubiquitination of Ribosomal Proteins Associated with a Decrease in Protein Translation

Protein posttranslational modifications (PTMs) play a central role in the DNA damage response. In particular, protein phosphorylation and ubiquitination have been shown to be essential in the signaling cascade that coordinates break repair with cell cycle progression. Here, we performed whole-cell quantitative proteomics to identify global changes in protein ubiquitination that are induced by DNA double-strand breaks. In total, we quantified more than 9,400 ubiquitin sites and found that the relative abundance of ∼10% of these sites was altered in response to DNA double-strand breaks. Interestingly, a large proportion of ribosomal proteins, including those from the 40S as well as the 60S subunit, were ubiquitinated in response to DNA damage. In parallel, we discovered that DNA damage leads to the inhibition of ribosome function. Taken together, these data uncover the ribosome as a major target of the DNA damage response.

Measuring cell cycle-dependent DNA damage responses and p53 regulation on a cell-by-cell basis from image analysis

DNA damage in cells occurs from both endogenous and exogenous sources, and failure to repair such damage is associated with the emergence of different cancers, neurological disorders and aging. DNA damage responses (DDR) in cells are closely associated with the cell cycle. While most of our knowledge of DDR comes from bulk biochemistry, such methods require cells to be arrested at specific stages for cell cycle studies, potentially altering measured responses; nor is cell to cell variability in DDR or direct cell-level correlation of two response metrics measured in such methods. To overcome these limitations we developed a microscopy-based assay for determining cell cycle stages over large cell numbers. This method can be used to study cell-cycle-dependent DDR in cultured cells without the need for cell synchronization. Upon DNA damage γH2A.X induction was correlated to nuclear enrichment of p53 on a cell-by-cell basis and in a cell cycle dependent manner. Imaging-based cell cycle staging was combined with single molecule P53 mRNA detection and immunofluorescence for p53 protein in the very same cells to reveal an intriguing repression of P53 transcript numbers due to reduced transcription across different stages of the cell cycle during DNA damage. Our study hints at an unexplored mechanism for p53 regulation and underscores the importance of measuring single cell level responses to DNA damage.

Database for High Throughput Screening Hits (dHITS): a simple tool to retrieve gene specific phenotypes from systematic screens done in yeast

In the last decade several collections of Saccharomyces cerevisiae yeast strains have been created. In these collections every gene is modified in a similar manner such as by a deletion or the addition of a protein tag. Such libraries have enabled a diversity of systematic screens, giving rise to large amounts of information regarding gene functions. However, often papers describing such screens focus on a single gene or a small set of genes and all other loci affecting the phenotype of choice (‘hits’) are only mentioned in tables that are provided as supplementary material and are often hard to retrieve or search. To help unify and make such data accessible, we have created a Database of High Throughput Screening Hits (dHITS). The dHITS database enables information to be obtained about screens in which genes of interest were found as well as the other genes that came up in that screen – all in a readily accessible and downloadable format. The ability to query large lists of genes at the same time provides a platform to easily analyse hits obtained from transcriptional analyses or other screens. We hope that this platform will serve as a tool to facilitate investigation of protein functions to the yeast community.

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.

Protein Localization and Interaction Studies in Plants: Toward Defining Complete Proteomes by Visualization

Protein interaction and localization studies in plants are a fundamental component of achieving mechanistic understanding of virus:plant interactions at the systems level. Many such studies are conducted using transient expression assays in leaves of Nicotiana benthamiana, the most widely used experimental plant host in virology, examined by laser-scanning confocal microscopy. This chapter provides a workflow for protein interaction and localization experiments, with particular attention to the many control and supporting assays that may also need to be performed. Basic principles of microscopy are introduced to aid researchers in the early stages of adding imaging techniques to their experimental repertoire. Three major types of imaging-based experiments are discussed in detail: (i) protein localization using autofluorescent proteins, (ii) colocalization studies, and (iii) bimolecular fluorescence complementation, with emphasis on judicious interpretation of the data obtained from these approaches. In addition to establishing a general framework for protein localization experiments in plants, the need for proteome-scale localization projects is discussed, with emphasis on nuclear-localized proteins.

Selective aggregation of the splicing factor Hsh155 suppresses splicing upon genotoxic stress

Upon genotoxic stress, dynamic relocalization events control DNA repair as well as alterations of the transcriptome and proteome, enabling stress recovery. How these events may influence one another is only partly known. Beginning with a cytological screen of genome stability proteins, we find that the splicing factor Hsh155 disassembles from its partners and localizes to both intranuclear and cytoplasmic protein quality control (PQC) aggregates under alkylation stress. Aggregate sequestration of Hsh155 occurs at nuclear and then cytoplasmic sites in a manner that is regulated by molecular chaperones and requires TORC1 activity signaling through the Sfp1 transcription factor. This dynamic behavior is associated with intron retention in ribosomal protein gene transcripts, a decrease in splicing efficiency, and more rapid recovery from stress. Collectively, our analyses suggest a model in which some proteins evicted from chromatin and undergoing transcriptional remodeling during stress are targeted to PQC sites to influence gene expression changes and facilitate stress recovery.

P-body proteins regulate transcriptional rewiring to promote DNA replication stress resistance

mRNA-processing (P-) bodies are cytoplasmic granules that form in eukaryotic cells in response to numerous stresses to serve as sites of degradation and storage of mRNAs. Functional P-bodies are critical for the DNA replication stress response in yeast, yet the repertoire of P-body targets and the mechanisms by which P-bodies promote replication stress resistance are unknown. In this study we identify the complete complement of mRNA targets of P-bodies during replication stress induced by hydroxyurea treatment. The key P-body protein Lsm1 controls the abundance of HHT1, ACF4, ARL3, TMA16, RRS1 and YOX1 mRNAs to prevent their toxic accumulation during replication stress. Accumulation of YOX1 mRNA causes aberrant downregulation of a network of genes critical for DNA replication stress resistance and leads to toxic acetaldehyde accumulation. Our data reveal the scope and the targets of regulation by P-body proteins during the DNA replication stress response.

P-bodies form in response to stress and act as sites of mRNA storage and degradation. Here the authors identify the mRNA targets of P-bodies during DNA replication stress, and show that P-body proteins act to prevent toxic accumulation of these target transcripts.

Early-onset torsion dystonia: a novel high-throughput yeast genetic screen for factors modifying protein levels of torsinAΔE

Dystonia is the third most common movement disorder, but its diagnosis and treatment remain challenging. One of the most severe types of dystonia is early-onset torsion dystonia (EOTD). The best studied and validated EOTD-associated mutation, torsinAΔE, is a deletion of a C-terminal glutamate residue in the AAA+ ATPase torsinA. TorsinA appears to be an endoplasmic reticulum (ER)/nuclear envelope chaperone with multiple roles in the secretory pathway and in determining subcellular architecture. Many functions are disabled in the torsinAΔE variant, and torsinAΔE is also less stable than wild-type torsinA and is a substrate for ER-associated degradation. Nevertheless, the molecular factors involved in the biogenesis and degradation of torsinA and torsinAΔE have not been fully explored. To identify conserved cellular factors that can alter torsinAΔE protein levels, we designed a new high-throughput, automated, genome-wide screen utilizing our validated Saccharomyces cerevisiae torsinA expression system. By analyzing the yeast non-essential gene deletion collection, we identified 365 deletion strains with altered torsinAΔE steady-state levels. One notable hit was EUG1, which encodes a member of the protein disulfide isomerase family (PDIs). PDIs reside in the ER and catalyze the formation of disulfide bonds, mediate protein quality control and aid in nascent protein folding. We validated the role of select human PDIs in torsinA biogenesis in mammalian cells and found that overexpression of PDIs reduced the levels of torsinA and torsinAΔE. Together, our data report the first genome-wide screen to identify cellular factors that alter expression levels of the EOTD-associated protein torsinAΔE. More generally, the identified hits help in dissecting the cellular machinery involved in folding and degrading a torsinA variant, and constitute potential therapeutic factors for EOTD. This screen can also be readily adapted to identify factors impacting the levels of any protein of interest, considerably expanding the applicability of yeast in both basic and applied research.

Genome-wide and protein kinase-focused RNAi screens reveal conserved and novel damage response pathways in Trypanosoma brucei

All cells are subject to structural damage that must be addressed for continued growth. A wide range of damage affects the genome, meaning multiple pathways have evolved to repair or bypass the resulting DNA lesions. Though many repair pathways are conserved, their presence or function can reflect the life style of individual organisms. To identify genome maintenance pathways in a divergent eukaryote and important parasite, Trypanosoma brucei, we performed RNAi screens to identify genes important for survival following exposure to the alkylating agent methyl methanesulphonate. Amongst a cohort of broadly conserved and, therefore, early evolved repair pathways, we reveal multiple activities not so far examined functionally in T. brucei, including DNA polymerases, DNA helicases and chromatin factors. In addition, the screens reveal Trypanosoma- or kinetoplastid-specific repair-associated activities. We also provide focused analyses of repair-associated protein kinases and show that loss of at least nine, and potentially as many as 30 protein kinases, including a nuclear aurora kinase, sensitises T. brucei to alkylation damage. Our results demonstrate the potential for synthetic lethal genome-wide screening of gene function in T. brucei and provide an evolutionary perspective on the repair pathways that underpin effective responses to damage, with particular relevance for related kinetoplastid pathogens. By revealing that a large number of diverse T. brucei protein kinases act in the response to damage, we expand the range of eukaryotic signalling factors implicated in genome maintenance activities.

Damage to the genome is a universal threat to life. Though the repair pathways used to tackle damage can be widely conserved, lineage-specific specialisations are found, reflecting the differing life styles of extant organisms. Using RNAi coupled with next generation sequencing we have screened for genes that are important for growth of Trypanosoma brucei, a diverged eukaryotic microbe and important parasite, in the presence of alkylation damage caused by methyl methanesulphonate. We reveal both repair pathway conservation relative to characterised eukaryotes and specialisation, including uncharacterised roles for translesion DNA polymerases, DNA helicases and chromatin factors. Furthermore, we demonstrate that loss of around 15% of T. brucei protein kinases sensitises the parasites to alkylation, indicating phosphorylation signalling plays widespread and under-investigated roles in the damage response pathways of eukaryotes.

A Critical and Comparative Review of Fluorescent Tools for Live-Cell Imaging

Fluorescent tools have revolutionized our ability to probe biological dynamics, particularly at the cellular level. Fluorescent sensors have been developed on several platforms, utilizing either small-molecule dyes or fluorescent proteins, to monitor proteins, RNA, DNA, small molecules, and even cellular properties, such as pH and membrane potential. We briefly summarize the impressive history of tool development for these various applications and then discuss the most recent noteworthy developments in more detail. Particular emphasis is placed on tools suitable for single-cell analysis and especially live-cell imaging applications. Finally, we discuss prominent areas of need in future fluorescent tool development-specifically, advancing our capability to analyze and integrate the plethora of high-content data generated by fluorescence imaging.

High-Throughput Microscopy-Based Screening in Saccharomyces cerevisiae

The budding yeastSaccharomyces cerevisiaehas served as the pioneer model organism for virtually all genome-scale methods, including genome sequencing, DNA microarrays, gene deletion collections, and a variety of proteomic platforms. Yeast has also provided a test-bed for the development of systematic fluorescence-based imaging screens to enable the analysis of protein localization and abundance in vivo. Especially important has been the integration of high-throughput microscopy with automated image-processing methods, which has allowed researchers to overcome issues associated with manual image analysis and acquire unbiased, quantitative data. Here we provide an introduction to automated imaging in budding yeast.

MTE1 Functions with MPH1 in Double-Strand Break Repair

Double-strand DNA breaks occur upon exposure of cells to ionizing radiation and certain chemical agents or indirectly through replication fork collapse at DNA damage sites. If left unrepaired, double-strand breaks can cause genome instability and cell death, and their repair can result in loss of heterozygosity. In response to DNA damage, proteins involved in double-strand break repair by homologous recombination relocalize into discrete nuclear foci. We identified 29 proteins that colocalize with recombination repair protein Rad52 in response to DNA damage. Of particular interest, Ygr042w/Mte1, a protein of unknown function, showed robust colocalization with Rad52. Mte1 foci fail to form when the DNA helicase gene MPH1 is absent. Mte1 and Mph1 form a complex and are recruited to double-strand breaks in vivo in a mutually dependent manner. MTE1 is important for resolution of Rad52 foci during double-strand break repair and for suppressing break-induced replication. Together our data indicate that Mte1 functions with Mph1 in double-strand break repair.

High-throughput fluorescence microscopic analysis of protein abundance and localization in budding yeast

Proteins directly carry out and regulate cellular functions. As a result, changes in protein levels within a cell directly influence cellular processes. Similarly, it is intuitive that the intracellular localization of proteins is a key component of their functionality. Optimal activity is achieved by a combination of protein concentration, co-compartmentalization with substrates, co-factors and regulators and sequestration from deleterious locales. The proteome within a cell is highly dynamic and changes in response to different environmental conditions. High-throughput microscopic analysis in the budding yeast Saccharomyces cerevisiae has afforded proteome-wide views of protein organization in living cells, and of how protein abundance and location is regulated and remodeled in response to stress.

A high-throughput confocal fluorescence microscopy platform to study DNA replication stress in yeast cells

High-throughput imaging of yeast cells expressing fluorescent proteins can be used to understand biological pathways in the context of spatial organization. Here we describe a method for imaging yeast cells expressing proteins tagged with green fluorescent protein (GFP) and/or red fluorescent protein (RFP), with or without drug treatment, in a 384-well format, using the PerkinElmer Opera high-content confocal imaging microscope.

Time series modeling of live-cell shape dynamics for image-based phenotypic profiling

Live-cell imaging can be used to capture spatio-temporal aspects of cellular responses that are not accessible to fixed-cell imaging. As the use of live-cell imaging continues to increase, new computational procedures are needed to characterize and classify the temporal dynamics of individual cells. For this purpose, here we present the general experimental-computational framework SAPHIRE (Stochastic Annotation of Phenotypic Individual-cell Responses) to characterize phenotypic cellular responses from time series imaging datasets. Hidden Markov modeling is used to infer and annotate morphological state and state-switching properties from image-derived cell shape measurements. Time series modeling is performed on each cell individually, making the approach broadly useful for analyzing asynchronous cell populations. Two-color fluorescent cells simultaneously expressing actin and nuclear reporters enabled us to profile temporal changes in cell shape following pharmacological inhibition of cytoskeleton-regulatory signaling pathways. Results are compared with existing approaches conventionally applied to fixed-cell imaging datasets, and indicate that time series modeling captures heterogeneous dynamic cellular responses that can improve drug classification and offer additional important insight into mechanisms of drug action. The software is available at http://saphire-hcs.org.

Navigating yeast genome maintenance with functional genomics

Maintenance of genome integrity is a fundamental requirement of all organisms. To address this, organisms have evolved extremely faithful modes of replication, DNA repair and chromosome segregation to combat the deleterious effects of an unstable genome. Nonetheless, a small amount of genome instability is the driver of evolutionary change and adaptation, and thus a low level of instability is permitted in populations. While defects in genome maintenance almost invariably reduce fitness in the short term, they can create an environment where beneficial mutations are more likely to occur. The importance of this fact is clearest in the development of human cancer, where genome instability is a well-established enabling characteristic of carcinogenesis. This raises the crucial question: what are the cellular pathways that promote genome maintenance and what are their mechanisms? Work in model organisms, in particular the yeast Saccharomyces cerevisiae, has provided the global foundations of genome maintenance mechanisms in eukaryotes. The development of pioneering genomic tools inS. cerevisiae, such as the systematic creation of mutants in all nonessential and essential genes, has enabled whole-genome approaches to identifying genes with roles in genome maintenance. Here, we review the extensive whole-genome approaches taken in yeast, with an emphasis on functional genomic screens, to understand the genetic basis of genome instability, highlighting a range of genetic and cytological screening modalities. By revealing the biological pathways and processes regulating genome integrity, these analyses contribute to the systems-level map of the yeast cell and inform studies of human disease, especially cancer.

Ndd1 turnover by SCF(Grr1) is inhibited by the DNA damage checkpoint in Saccharomyces cerevisiae

In Saccharomyces cerevisiae, Ndd1 is the dedicated transcriptional activator of the mitotic gene cluster, which includes thirty-three genes that encode key mitotic regulators, making Ndd1 a hub for the control of mitosis. Previous work has shown that multiple kinases, including cyclin-dependent kinase (Cdk1), phosphorylate Ndd1 to regulate its activity during the cell cycle. Previously, we showed that Ndd1 was inhibited by phosphorylation in response to DNA damage. Here, we show that Ndd1 is also subject to regulation by protein turnover during the mitotic cell cycle: Ndd1 is unstable during an unperturbed cell cycle, but is strongly stabilized in response to DNA damage. We find that Ndd1 turnover in metaphase requires Cdk1 activity and the ubiquitin ligase SCF^Grr1. In response to DNA damage, Ndd1 stabilization requires the checkpoint kinases Mec1/Tel1 and Swe1, the S. cerevisiae homolog of the Wee1 kinase. In both humans and yeast, the checkpoint promotes Wee1-dependent inhibitory phosphorylation of Cdk1 following exposure to DNA damage. While this is critical for checkpoint-induced arrest in most organisms, this is not true in budding yeast, where the function of damage-induced inhibitory phosphorylation is less well understood. We propose that the DNA damage checkpoint stabilizes Ndd1 by inhibiting Cdk1, which we show is required for targeting Ndd1 for destruction.

All cells must regulate cell division in response to extracellular and intracellular cues, and one of the most critical steps to regulate is the process of cell division, or mitosis. In response to DNA damage in budding yeast, cells activate a checkpoint that promotes DNA repair and arrests the cell cycle before division to give the cell time to repair the lesion. One of the key regulators of mitosis is an essential transcription factor called Ndd1. Ndd1 is known to be regulated by transcription and phosphorylation, both in unperturbed cells and following exposure to DNA damage. Here, we show that Ndd1 protein turnover is also regulated in both situations. Ndd1 is degraded quickly during an unperturbed cell cycle, but is strongly stabilized following exposure to DNA damage. We identify the machinery that targets Ndd1 for turnover and the signaling pathways required to stabilize Ndd1 in response to DNA damage. Maintaining high levels of Ndd1 after exposure to DNA damage may allow the cell to reactivate Ndd1 after the damage has been repaired to promote mitosis.

Aag-initiated base excision repair promotes ischemia reperfusion injury in liver, brain, and kidney

Inflammation is accompanied by the release of highly reactive oxygen and nitrogen species (RONS) that damage DNA, among other cellular molecules. Base excision repair (BER) is initiated by DNA glycosylases and is crucial in repairing RONS-induced DNA damage; the alkyladenine DNA glycosylase (Aag/Mpg) excises several DNA base lesions induced by the inflammation-associated RONS release that accompanies ischemia reperfusion (I/R). Using mouse I/R models we demonstrate that Aag(-/-) mice are significantly protected against, rather than sensitized to, I/R injury, and that such protection is observed across three different organs. Following I/R in liver, kidney, and brain, Aag(-/-) mice display decreased hepatocyte death, cerebral infarction, and renal injury relative to wild-type. We infer that in wild-type mice, Aag excises damaged DNA bases to generate potentially toxic abasic sites that in turn generate highly toxic DNA strand breaks that trigger poly(ADP-ribose) polymerase (Parp) hyperactivation, cellular bioenergetics failure, and necrosis; indeed, steady-state levels of abasic sites and nuclear PAR polymers were significantly more elevated in wild-type vs. Aag(-/-) liver after I/R. This increase in PAR polymers was accompanied by depletion of intracellular NAD and ATP levels plus the translocation and extracellular release of the high-mobility group box 1 (Hmgb1) nuclear protein, activating the sterile inflammatory response. We thus demonstrate the detrimental effects of Aag-initiated BER during I/R and sterile inflammation, and present a novel target for controlling I/R-induced injury.

Quantitative proteomics of the yeast Hsp70/Hsp90 interactomes during DNA damage reveal chaperone-dependent regulation of ribonucleotide reductase

The highly conserved molecular chaperones Hsp90 and Hsp70 are indispensible for folding and maturation of a significant fraction of the proteome, including many proteins involved in signal transduction and stress response. To examine the dynamics of chaperone-client interactions after DNA damage, we applied quantitative affinity-purification mass spectrometry (AP-MS) proteomics to characterize interactomes of the yeast Hsp70 isoform Ssa1 and Hsp90 isoform Hsp82 before and after exposure to methyl methanesulfonate. Of 256 proteins identified and quantified via (16)O(/18)O labeling and LC-MS/MS, 142 are novel Hsp70/90 interactors. Nearly all interactions remained unchanged or decreased after DNA damage, but 5 proteins increased interactions with Ssa1 and/or Hsp82, including the ribonucleotide reductase (RNR) subunit Rnr4. Inhibiting Hsp70 or 90 chaperone activity destabilized Rnr4 in yeast and its vertebrate homolog hRMM2 in breast cancer cells. In turn, pre-treatment of cancer cells with chaperone inhibitors sensitized cells to the RNR inhibitor gemcitabine, suggesting a novel chemotherapy strategy. All MS data have been deposited in the ProteomeXchange with identifier PXD001284.

BIOLOGICAL SIGNIFICANCE

This study provides the dynamic interactome of the yeast Hsp70 and Hsp90 under DNA damage which suggest key roles for the chaperones in a variety of signaling cascades. Importantly, the cancer drug target ribonucleotide reductase was shown to be a client of Hsp70 and Hsp90 in both yeast and breast cancer cells. As such, this study highlights the potential of a novel cancer therapeutic strategy that exploits the synergy of chaperone and ribonucleotide reductase inhibitors.

Heritability and genetic basis of protein level variation in an outbred population

The genetic basis of heritable traits has been studied for decades. Although recent mapping efforts have elucidated genetic determinants of transcript levels, mapping of protein abundance has lagged. Here, we analyze levels of 4084 GFP-tagged yeast proteins in the progeny of a cross between a laboratory and a wild strain using flow cytometry and high-content microscopy. The genotype of trans variants contributed little to protein level variation between individual cells but explained >50% of the variance in the population’s average protein abundance for half of the GFP fusions tested. To map trans-acting factors responsible, we performed flow sorting and bulk segregant analysis of 25 proteins, finding a median of five protein quantitative trait loci (pQTLs) per GFP fusion. Further, we find that cis-acting variants predominate; the genotype of a gene and its surrounding region had a large effect on protein level six times more frequently than the rest of the genome combined. We present evidence for both shared and independent genetic control of transcript and protein abundance: More than half of the expression QTLs (eQTLs) contribute to changes in protein levels of regulated genes, but several pQTLs do not affect their cognate transcript levels. Allele replacements of genes known to underlie trans eQTL hotspots confirmed the correlation of effects on mRNA and protein levels. This study represents the first genome-scale measurement of genetic contribution to protein levels in single cells and populations, identifies more than a hundred trans pQTLs, and validates the propagation of effects associated with transcript variation to protein abundance.