Comprehensive characterization of the Hsp70 interactome reveals novel client proteins and interactions mediated by posttranslational modifications.

Hsp70 interactions are critical for cellular viability and the response to stress. Previous attempts to characterize Hsp70 interactions have been limited by their transient nature and the inability of current technologies to distinguish direct versus bridged interactions. We report the novel use of cross-linking mass spectrometry (XL-MS) to comprehensively characterize the Saccharomyces cerevisiae (budding yeast) Hsp70 protein interactome. Using this approach, we have gained fundamental new insights into Hsp70 function, including definitive evidence of Hsp70 self-association as well as multipoint interaction with its client proteins. In addition to identifying a novel set of direct Hsp70 interactors that can be used to probe chaperone function in cells, we have also identified a suite of posttranslational modification (PTM)-associated Hsp70 interactions. The majority of these PTMs have not been previously reported and appear to be critical in the regulation of client protein function. These data indicate that one of the mechanisms by which PTMs contribute to protein function is by facilitating interaction with chaperones. Taken together, we propose that XL-MS analysis of chaperone complexes may be used as a unique way to identify biologically important PTMs on client proteins.

ScreenGarden: a shinyR application for fast and easy analysis of plate-based high-throughput screens.

BACKGROUND: Colony growth on solid media is a simple and effective measure for high-throughput genomic experiments such as yeast two-hybrid, synthetic dosage lethality and Synthetic Physical Interaction screens. The development of robotic pinning tools has facilitated the experimental design of these assays, and different imaging software can be used to automatically measure colony sizes on plates. However, comparison to control plates and statistical data analysis is often laborious and pinning issues or plate specific growth effects can lead to the detection of false-positive growth defects. RESULTS: We have developed ScreenGarden, a shinyR application, to enable easy, quick and robust data analysis of plate-based high throughput assays. The code allows comparisons of different formats of data and different sized arrays of colonies. A comparison of ScreenGarden with previous analysis tools shows that it performs, at least, equivalently. The software can be run either via a website or offline via the RStudio program; the code is available and can be modified by expert uses to customise the analysis. CONCLUSIONS: ScreenGarden provides a simple, fast and effective tool to analyse colony growth data from genomic experiments.

Forced association of SARS-CoV-2 proteins with the yeast proteome perturb vesicle trafficking.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the highly infectious coronavirus disease COVID-19. Extensive research has been performed in recent months to better understand how SARS-CoV-2 infects and manipulates its host to identify potential drug targets and support patient recovery from COVID-19. However, the function of many SARS-CoV-2 proteins remains uncharacterised. Here we used the Synthetic Physical Interactions (SPI) method to recruit SARS-CoV-2 proteins to most of the budding yeast proteome to identify conserved pathways which are affected by SARS-CoV-2 proteins. The set of yeast proteins that result in growth defects when associated with the viral proteins have homologous functions that overlap those identified in studies performed in mammalian cells. Specifically, we were able to show that recruiting the SARS-CoV-2 NSP1 protein to HOPS, a vesicle-docking complex, is sufficient to perturb membrane trafficking in yeast consistent with the hijacking of the endoplasmic-reticulum-Golgi intermediate compartment trafficking pathway during viral infection of mammalian cells. These data demonstrate that the yeast SPI method is a rapid way to identify potential functions of ectopic viral proteins.

Quantitative high-confidence human mitochondrial proteome and its dynamics in cellular context.

Mitochondria are key organelles for cellular energetics, metabolism, signaling, and quality control and have been linked to various diseases. Different views exist on the composition of the human mitochondrial proteome. We classified >8,000 proteins in mitochondrial preparations of human cells and defined a mitochondrial high-confidence proteome of >1,100 proteins (MitoCoP). We identified interactors of translocases, respiratory chain, and ATP synthase assembly factors. The abundance of MitoCoP proteins covers six orders of magnitude and amounts to 7% of the cellular proteome with the chaperones HSP60-HSP10 being the most abundant mitochondrial proteins. MitoCoP dynamics spans three orders of magnitudes, with half-lives from hours to months, and suggests a rapid regulation of biosynthesis and assembly processes. 460 MitoCoP genes are linked to human diseases with a strong prevalence for the central nervous system and metabolism. MitoCoP will provide a high-confidence resource for placing dynamics, functions, and dysfunctions of mitochondria into the cellular context.

Cell-cycle phospho-regulation of the kinetochore.

The kinetochore is a mega-dalton protein assembly that forms within centromeric regions of chromosomes and directs their segregation during cell division. Here we review cell cycle-mediated phosphorylation events at the kinetochore, with a focus on the budding yeast Saccharomyces cerevisiae and the insight gained from forced associations of kinases and phosphatases. The point centromeres found in the budding yeast S. cerevisiae are one of the simplest such structures found in eukaryotes. The S. cerevisiae kinetochore comprises a single nucleosome, containing a centromere-specific H3 variant Cse4CENP-A, bound to a set of kinetochore proteins that connect to a single microtubule. Despite the simplicity of the budding yeast kinetochore, the proteins are mostly homologous with their mammalian counterparts. In some cases, human proteins can complement their yeast orthologs. Like its mammalian equivalent, the regulation of the budding yeast kinetochore is complex: integrating signals from the cell cycle, checkpoints, error correction, and stress pathways. The regulatory signals from these diverse pathways are integrated at the kinetochore by post-translational modifications, notably phosphorylation and dephosphorylation, to control chromosome segregation. Here we highlight the complex interplay between the activity of the different cell-cycle kinases and phosphatases at the kinetochore, emphasizing how much more we have to understand this essential structure.

Unifying the mechanism of mitotic exit control in a spatiotemporal logical model.

The transition from mitosis into the first gap phase of the cell cycle in budding yeast is controlled by the Mitotic Exit Network (MEN). The network interprets spatiotemporal cues about the progression of mitosis and ensures that release of Cdc14 phosphatase occurs only after completion of key mitotic events. The MEN has been studied intensively; however, a unified understanding of how localisation and protein activity function together as a system is lacking. In this paper, we present a compartmental, logical model of the MEN that is capable of representing spatial aspects of regulation in parallel to control of enzymatic activity. We show that our model is capable of correctly predicting the phenotype of the majority of mutants we tested, including mutants that cause proteins to mislocalise. We use a continuous time implementation of the model to demonstrate that Cdc14 Early Anaphase Release (FEAR) ensures robust timing of anaphase, and we verify our findings in living cells. Furthermore, we show that our model can represent measured cell-cell variation in Spindle Position Checkpoint (SPoC) mutants. This work suggests a general approach to incorporate spatial effects into logical models. We anticipate that the model itself will be an important resource to experimental researchers, providing a rigorous platform to test hypotheses about regulation of mitotic exit.

A functional drug re-purposing screening identifies carfilzomib as a drug preventing 17ß-estradiol: ERα signaling and cell proliferation in breast cancer cells.

Most cases of breast cancer (BC) are estrogen receptor α-positive (ERα+) at diagnosis. The presence of ERα drives the therapeutic approach for this disease, which often consists of endocrine therapy (ET). 4OH-Tamoxifen and faslodex (i.e., fulvestrant - ICI182,780) are two ETs that render tumor cells insensitive to 17ß-estradiol (E2)-dependent proliferative stimuli and prevent BC progression. However, ET has limitations and serious failures in different tissues and organs. Thus, there is an urgent need to identify novel drugs to fight BC in the clinic. Re-positioning of old drugs for new clinical purposes is an attractive alternative for drug discovery. For this analysis, we focused on the modulation of intracellular ERα levels in BC cells as target for the screening of about 900 Food and Drug Administration (FDA) approved compounds that would hinder E2:ERα signaling and inhibit BC cell proliferation. We found that carfilzomib induces ERα degradation and prevents E2 signaling and cell proliferation in two ERα+ BC cell lines. Remarkably, the analysis of carfilzomib effects on a cell model system with an acquired resistance to 4OH-tamoxifen revealed that this drug has an antiproliferative effect superior to faslodex in BC cells. Therefore, our results identify carfilzomib as a drug preventing E2:ERα signaling and cell proliferation in BC cells and suggest its possible re-position for the treatment of ERα+ BC as well as for those diseases that have acquired resistance to 4OH-tamoxifen.