Understanding mitochondrial DNA maintenance disorders at the single muscle fibre level.

Clonal expansion of mitochondrial DNA (mtDNA) deletions is an important pathological mechanism in adults with mtDNA maintenance disorders, leading to a mosaic mitochondrial respiratory chain deficiency in skeletal muscle. This study had two aims: (i) to determine if different Mendelian mtDNA maintenance disorders showed similar pattern of mtDNA deletions and respiratory chain deficiency and (ii) to investigate the correlation between the mitochondrial genetic defect and corresponding respiratory chain deficiency. We performed a quantitative analysis of respiratory chain deficiency, at a single cell level, in a cohort of patients with mutations in mtDNA maintenance genes. Using the same tissue section, we performed laser microdissection and single cell genetic analysis to investigate the relationship between mtDNA deletion characteristics and the respiratory chain deficiency. The pattern of respiratory chain deficiency is similar with different genetic defects. We demonstrate a clear correlation between the level of mtDNA deletion and extent of respiratory chain deficiency within a single cell. Long-range and single molecule PCR shows the presence of multiple mtDNA deletions in approximately one-third of all muscle fibres. We did not detect evidence of a replicative advantage for smaller mtDNA molecules in the majority of fibres, but further analysis is needed to provide conclusive evidence.

Subcellular origin of mitochondrial DNA deletions in human skeletal muscle.

OBJECTIVE: In patients with mitochondrial DNA (mtDNA) maintenance disorders and with aging, mtDNA deletions sporadically form and clonally expand within individual muscle fibers, causing respiratory chain deficiency. This study aimed to identify the sub-cellular origin and potential mechanisms underlying this process. METHODS: Serial skeletal muscle cryosections from patients with multiple mtDNA deletions were subjected to subcellular immunofluorescent, histochemical, and genetic analysis. RESULTS: We report respiratory chain-deficient perinuclear foci containing mtDNA deletions, which show local elevations of both mitochondrial mass and mtDNA copy number. These subcellular foci of respiratory chain deficiency are associated with a local increase in mitochondrial biogenesis and unfolded protein response signaling pathways. We also find that the commonly reported segmental pattern of mitochondrial deficiency is consistent with the three-dimensional organization of the human skeletal muscle mitochondrial network. INTERPRETATION: We propose that mtDNA deletions first exceed the biochemical threshold causing biochemical deficiency in focal regions adjacent to the myonuclei, and induce mitochondrial biogenesis before spreading across the muscle fiber. These subcellular resolution data provide new insights into the possible origin of mitochondrial respiratory chain deficiency in mitochondrial myopathy. Ann Neurol 2018;84:289-301.

Quantitative fitness analysis shows that NMD proteins and many other protein complexes suppress or enhance distinct telomere cap defects.

To better understand telomere biology in budding yeast, we have performed systematic suppressor/enhancer analyses on yeast strains containing a point mutation in the essential telomere capping gene CDC13 (cdc13-1) or containing a null mutation in the DNA damage response and telomere capping gene YKU70 (yku70Δ). We performed Quantitative Fitness Analysis (QFA) on thousands of yeast strains containing mutations affecting telomere-capping proteins in combination with a library of systematic gene deletion mutations. To perform QFA, we typically inoculate 384 separate cultures onto solid agar plates and monitor growth of each culture by photography over time. The data are fitted to a logistic population growth model; and growth parameters, such as maximum growth rate and maximum doubling potential, are deduced. QFA reveals that as many as 5% of systematic gene deletions, affecting numerous functional classes, strongly interact with telomere capping defects. We show that, while Cdc13 and Yku70 perform complementary roles in telomere capping, their genetic interaction profiles differ significantly. At least 19 different classes of functionally or physically related proteins can be identified as interacting with cdc13-1, yku70Δ, or both. Each specific genetic interaction informs the roles of individual gene products in telomere biology. One striking example is with genes of the nonsense-mediated RNA decay (NMD) pathway which, when disabled, suppress the conditional cdc13-1 mutation but enhance the null yku70Δ mutation. We show that the suppressing/enhancing role of the NMD pathway at uncapped telomeres is mediated through the levels of Stn1, an essential telomere capping protein, which interacts with Cdc13 and recruitment of telomerase to telomeres. We show that increased Stn1 levels affect growth of cells with telomere capping defects due to cdc13-1 and yku70Δ. QFA is a sensitive, high-throughput method that will also be useful to understand other aspects of microbial cell biology.

A stagewise response to mitochondrial dysfunction in mitochondrial DNA maintenance disorders.

Mitochondrial DNA (mtDNA) deletions which clonally expand in skeletal muscle of patients with mtDNA maintenance disorders, impair mitochondrial oxidative phosphorylation dysfunction. Previously we have shown that these mtDNA deletions arise and accumulate in perinuclear mitochondria causing localised mitochondrial dysfunction before spreading through the muscle fibre. We believe that mito-nuclear signalling is a key contributor in the accumulation and spread of mtDNA deletions, and that knowledge of how muscle fibres respond to mitochondrial dysfunction is key to our understanding of disease mechanisms. To understand the contribution of mito-nuclear signalling to the spread of mitochondrial dysfunction, we use imaging mass cytometry. We characterise the levels of mitochondrial Oxidative Phosphorylation proteins alongside a mitochondrial mass marker, in a cohort of patients with mtDNA maintenance disorders. Our expanded panel included protein markers of key signalling pathways, allowing us to investigate cellular responses to different combinations of oxidative phosphorylation dysfunction and ragged red fibres. We find combined Complex I and IV deficiency to be most common. Interestingly, in fibres deficient for one or more complexes, the remaining complexes are often upregulated beyond the increase of mitochondrial mass typically observed in ragged red fibres. We further find that oxidative phosphorylation deficient fibres exhibit an increase in the abundance of proteins involved in proteostasis, e.g. HSP60 and LONP1, and regulation of mitochondrial metabolism (including oxidative phosphorylation and proteolysis, e.g. PHB1). Our analysis suggests that the cellular response to mitochondrial dysfunction changes depending on the combination of deficient oxidative phosphorylation complexes in each fibre.

Imaging mass cytometry analysis of Becker muscular dystrophy muscle samples reveals different stages of muscle degeneration.

Becker muscular dystrophy (BMD) is characterised by fiber loss and expansion of fibrotic and adipose tissue. Several cells interact locally in what is known as the degenerative niche. We analysed muscle biopsies of controls and BMD patients at early, moderate and advanced stages of progression using Hyperion imaging mass cytometry (IMC) by labelling single sections with 17 markers identifying different components of the muscle. We developed a software for analysing IMC images and studied changes in the muscle composition and spatial correlations between markers across disease progression. We found a strong correlation between collagen-I and the area of stroma, collagen-VI, adipose tissue, and M2-macrophages number. There was a negative correlation between the area of collagen-I and the number of satellite cells (SCs), fibres and blood vessels. The comparison between fibrotic and non-fibrotic areas allowed to study the disease process in detail. We found structural differences among non-fibrotic areas from control and patients, being these latter characterized by increase in CTGF and in M2-macrophages and decrease in fibers and blood vessels. IMC enables to study of changes in tissue structure along disease progression, spatio-temporal correlations and opening the door to better understand new potential pathogenic pathways in human samples.

Resistance Exercise Training Rescues Mitochondrial Dysfunction in Skeletal Muscle of Patients with Myotonic Dystrophy Type 1.

BACKGROUND: Myotonic dystrophy type 1 (DM1) is a dominant autosomal neuromuscular disorder caused by the inheritance of a CTG triplet repeat expansion in the Dystrophia Myotonica Protein Kinase (DMPK) gene. At present, no cure currently exists for DM1 disease. OBJECTIVE: This study investigates the effects of 12-week resistance exercise training on mitochondrial oxidative phosphorylation in skeletal muscle in a cohort of DM1 patients (n = 11, men) in comparison to control muscle with normal oxidative phosphorylation. METHODS: Immunofluorescence was used to assess protein levels of key respiratory chain subunits of complex I (CI) and complex IV (CIV), and markers of mitochondrial mass and cell membrane in individual myofibres sampled from muscle biopsies. Using control's skeletal muscle fibers population, we classified each patient's fibers as having normal, low or high levels of CI and CIV and compared the proportions of fibers before and after exercise training. The significance of changes observed between pre- and post-exercise within patients was estimated using a permutation test. RESULTS: At baseline, DM1 patients present with significantly decreased mitochondrial mass, and isolated or combined CI and CIV deficiency. After resistance exercise training, in most patients a significant increase in mitochondrial mass was observed, and all patients showed a significant increase in CI and/or CIV protein levels. Moreover, improvements in mitochondrial mass were correlated with the one-repetition maximum strength evaluation. CONCLUSIONS: Remarkably, 12-week resistance exercise training is sufficient to partially rescue mitochondrial dysfunction in DM1 patients, suggesting that the response to exercise is in part be due to changes in mitochondria.

T cell differentiation drives the negative selection of pathogenic mitochondrial DNA variants.

Pathogenic mitochondrial DNA (mtDNA) single-nucleotide variants are a common cause of adult mitochondrial disease. Levels of some variants decrease with age in blood. Given differing division rates, longevity, and energetic requirements within haematopoietic lineages, we hypothesised that cell-type-specific metabolic requirements drive this decline. We coupled cell-sorting with mtDNA sequencing to investigate mtDNA variant levels within progenitor, myeloid, and lymphoid lineages from 26 individuals harbouring one of two pathogenic mtDNA variants (m.3243A>G and m.8344A>G). For both variants, cells of the T cell lineage show an enhanced decline. High-throughput single-cell analysis revealed that decline is driven by increasing proportions of cells that have cleared the variant, following a hierarchy that follows the current orthodoxy of T cell differentiation and maturation. Furthermore, patients with pathogenic mtDNA variants have a lower proportion of T cells than controls, indicating a key role for mitochondrial function in T cell homeostasis. This work identifies the ability of T cell subtypes to selectively purify their mitochondrial genomes, and identifies pathogenic mtDNA variants as a new means to track blood cell differentiation status.

CaliBayes and BASIS: integrated tools for the calibration, simulation and storage of biological simulation models.

Dynamic simulation modelling of complex biological processes forms the backbone of systems biology. Discrete stochastic models are particularly appropriate for describing sub-cellular molecular interactions, especially when critical molecular species are thought to be present at low copy-numbers. For example, these stochastic effects play an important role in models of human ageing, where ageing results from the long-term accumulation of random damage at various biological scales. Unfortunately, realistic stochastic simulation of discrete biological processes is highly computationally intensive, requiring specialist hardware, and can benefit greatly from parallel and distributed approaches to computation and analysis. For these reasons, we have developed the BASIS system for the simulation and storage of stochastic SBML models together with associated simulation results. This system is exposed as a set of web services to allow users to incorporate its simulation tools into their workflows. Parameter inference for stochastic models is also difficult and computationally expensive. The CaliBayes system provides a set of web services (together with an R package for consuming these and formatting data) which addresses this problem for SBML models. It uses a sequential Bayesian MCMC method, which is powerful and flexible, providing very rich information. However this approach is exceptionally computationally intensive and requires the use of a carefully designed architecture. Again, these tools are exposed as web services to allow users to take advantage of this system. In this article, we describe these two systems and demonstrate their integrated use with an example workflow to estimate the parameters of a simple model of Saccharomyces cerevisiae growth on agar plates.

Detecting respiratory chain defects in osteoblasts from osteoarthritic patients using imaging mass cytometry.

Osteoporosis is a skeletal disease which is characterised by reduced bone mass and microarchitecture, with a subsequent loss of strength that predisposes to fragility and risk of fractures. The pathogenesis of falling bone mineral density, ultimately leading to a diagnosis of osteoporosis is incompletely understood but the disease is currently thought to be multifactorial. Humans are known to accumulate mitochondrial mutations and respiratory chain deficiency with age and mounting evidence suggests that this may indeed be the overarching cause intrinsic to the changing phenotype in advancing age and age-related disease. Mitochondrial mutations are detectable from the age of about 30 years onwards. Mitochondria contain their own genome which encodes 13 essential mitochondrial proteins and accumulates somatic variants at up to 10 times the rate of the nuclear genome. Once the concentration of any pathogenic mitochondrial genome variant exceeds a threshold, respiratory chain deficiency and cellular dysfunction occur. The PolgD257A/D257A mouse model is a knock-in mutant that expresses a proof-reading-deficient version of PolgA, a nuclear encoded subunit of mtDNA polymerase. These mice are a useful model of age-related accumulation of mtDNA mutations in humans since their defective proof-reading mechanism leads to a mitochondrial DNA mutation rate 3-5 times higher than in wild-type mice. These mice showed enhanced levels of age-related osteoporosis along with respiratory chain deficiency in osteoblasts. To explore whether respiratory chain deficiency is also seen in human osteoblasts, we developed a protocol and analysis framework for imaging mass cytometry in bone tissue sections to analyse osteoblasts in situ. By comparing bone tissue sampled at one timepoint from femoral neck of 10 older healthy volunteers aged 40-85 with samples from young patients aged 1-19, we have identified complex I defect in osteoblasts from 6 out of 10 older volunteers, complex II defect in 2 out of 10 older volunteers, complex IV defect in 1 out of 10 older volunteers and complex V defect in 4 out of 10 older volunteers. These observations are consistent with findings from the PolgD257A/D257A mouse model and suggest that respiratory chain deficiency, as a consequence of the accumulation of age-related pathogenic mitochondrial DNA mutations, may play a significant role in the pathogenesis of human age-related osteoporosis.

Quantifying Variation in Bacterial Reproductive Fitness: a High-Throughput Method.

To evaluate changes in reproductive fitness of bacteria, e.g., after acquisition of antimicrobial resistance, a low-cost high-throughput method to analyze bacterial growth on agar is desirable for broad usability. In our bacterial quantitative fitness analysis (BaQFA), arrayed cultures are spotted on agar and photographed sequentially while growing. These time-lapse images are analyzed using a purpose-built open-source software to derive normalized image intensity (NI) values for each culture spot. Subsequently, a Gompertz growth model is fitted to NI values, and fitness is calculated from model parameters. To represent a range of clinically important pathogenic bacteria, we used different strains of Enterococcus faecium, Escherichia coli, and Staphylococcus aureus, with and without antimicrobial resistance. Relative competitive fitness (RCF) was defined as the mean fitness ratio of two strains growing competitively on one plate.BaQFA permitted the accurate construction of growth curves from bacteria grown on semisolid agar plates and fitting of Gompertz models. Normalized image intensity values showed a strong association with the total CFU/ml count per spotted culture (P < 0.001) for all strains of the three species. BaQFA showed relevant reproductive fitness differences between individual strains, suggesting substantially higher fitness of methicillin-resistant S. aureus JE2 than Cowan (RCF, 1.58; P < 0.001). Similarly, the vancomycin-resistant E. faecium ST172b showed higher competitive fitness than susceptible E. faecium ST172 (RCF, 1.59; P < 0.001). Our BaQFA method allows detection of fitness differences between bacterial strains and may help to estimate epidemiological antimicrobial persistence or contribute to the prediction of clinical outcomes in severe infections.IMPORTANCE Reproductive fitness of bacteria is a major factor in the evolution and persistence of antimicrobial resistance and may play an important role in severe infections. With a computational approach to quantify fitness in bacteria growing competitively on agar plates, our high-throughput method has been designed to obtain additional phenotypic data for antimicrobial resistance analysis at a low cost. Furthermore, our bacterial quantitative fitness analysis (BaQFA) enables the investigation of a link between bacterial fitness and clinical outcomes in severe invasive bacterial infections. This may allow future use of our method for patient management and risk stratification of clinical outcomes. Our proposed method uses open-source software and a hardware setup that can utilize consumer electronics. This will enable a wider community of researchers, including those from low-resource countries, where the burden of antimicrobial resistance is highest, to obtain valuable information about emerging bacterial strains.

Colonyzer: automated quantification of micro-organism growth characteristics on solid agar.

BACKGROUND: High-throughput screens comparing growth rates of arrays of distinct micro-organism cultures on solid agar are useful, rapid methods of quantifying genetic interactions. Growth rate is an informative phenotype which can be estimated by measuring cell densities at one or more times after inoculation. Precise estimates can be made by inoculating cultures onto agar and capturing cell density frequently by plate-scanning or photography, especially throughout the exponential growth phase, and summarising growth with a simple dynamic model (e.g. the logistic growth model). In order to parametrize such a model, a robust image analysis tool capable of capturing a wide range of cell densities from plate photographs is required. RESULTS: Colonyzer is a collection of image analysis algorithms for automatic quantification of the size, granularity, colour and location of micro-organism cultures grown on solid agar. Colonyzer is uniquely sensitive to extremely low cell densities photographed after dilute liquid culture inoculation (spotting) due to image segmentation using a mixed Gaussian model for plate-wide thresholding based on pixel intensity. Colonyzer is robust to slight experimental imperfections and corrects for lighting gradients which would otherwise introduce spatial bias to cell density estimates without the need for imaging dummy plates. Colonyzer is general enough to quantify cultures growing in any rectangular array format, either growing after pinning with a dense inoculum or growing with the irregular morphology characteristic of spotted cultures. Colonyzer was developed using the open source packages: Python, RPy and the Python Imaging Library and its source code and documentation are available on SourceForge under GNU General Public License. Colonyzer is adaptable to suit specific requirements: e.g. automatic detection of cultures at irregular locations on streaked plates for robotic picking, or decreasing analysis time by disabling components such as lighting correction or colour measures. CONCLUSION: Colonyzer can automatically quantify culture growth from large batches of captured images of microbial cultures grown during genome-wide scans over the wide range of cell densities observable after highly dilute liquid spot inoculation, as well as after more concentrated pinning inoculation. Colonyzer is open-source, allowing users to assess it, adapt it to particular research requirements and to contribute to its development.

Correction of radiolabel pulse-chase data by a mathematical model: application to mitochondrial turnover studies.

Metabolic labelling pulse-chase experiments are important means to study molecular turnover rates. However, the inherent problem associated with the method is precursor re-utilization, which can cause a significant overestimation of the actual rates of molecular degradation. In published studies on mitochondrial degradation, this problem has led to widely differing results. Practically, the extra information required to correct these errors is not easy to obtain. Using an example of a mitochondrial protein degradation study with NaH(14)CO(3) as the precursor label, we explain the limitations of the method and our approaches to mathematical correction. A dynamic model, including error, used the full power of the data and resulted in sensitive and specific distributed parameter estimates, helping to reduce numbers of experimental animals. This example has important implications not only for similar pulse-chase experiments, but also in a more general context where comparable types of data are generated.

The rise and rise of mitochondrial DNA mutations.

How mitochondrial DNA mutations clonally expand in an individual cell is a question that has perplexed mitochondrial biologists for decades. A growing body of literature indicates that mitochondrial DNA mutations play a major role in ageing, metabolic diseases, neurodegenerative diseases, neuromuscular disorders and cancers. Importantly, this process of clonal expansion occurs for both inherited and somatic mitochondrial DNA mutations. To complicate matters further there are fundamental differences between mitochondrial DNA point mutations and deletions, and between mitotic and post-mitotic cells, that impact this pathogenic process. These differences, along with the challenges of investigating a longitudinal process occurring over decades in humans, have so far hindered progress towards understanding clonal expansion. Here we summarize our current understanding of the clonal expansion of mitochondrial DNA mutations in different tissues and highlight key unanswered questions. We then discuss the various existing biological models, along with their advantages and disadvantages. Finally, we explore what has been achieved with mathematical modelling so far and suggest future work to advance this important area of research.

Decoding mitochondrial heterogeneity in single muscle fibres by imaging mass cytometry.

The study of skeletal muscle continues to support the accurate diagnosis of mitochondrial disease and remains important in delineating molecular disease mechanisms. The heterogeneous expression of oxidative phosphorylation proteins and resulting respiratory deficiency are both characteristic findings in mitochondrial disease, hence the rigorous assessment of these at a single cell level is incredibly powerful. Currently, the number of proteins that can be assessed in individual fibres from a single section by immunohistochemistry is limited but imaging mass cytometry (IMC) enables the quantification of further, discrete proteins in individual cells. We have developed a novel workflow and bespoke analysis for applying IMC in skeletal muscle biopsies from patients with genetically-characterised mitochondrial disease, investigating the distribution of nine mitochondrial proteins in thousands of single muscle fibres. Using a semi-automated analysis pipeline, we demonstrate the accurate quantification of protein levels using IMC, providing an accurate measure of oxidative phosphorylation deficiency for complexes I-V at the single cell level. We demonstrate signatures of oxidative phosphorylation deficiency for common mtDNA variants and nuclear-encoded complex I variants and a compensatory upregulation of unaffected oxidative phosphorylation components. This technique can now be universally applied to evaluate a wide range of skeletal muscle disorders and protein targets.

Kinase inhibition profiles as a tool to identify kinases for specific phosphorylation sites.

There are thousands of known cellular phosphorylation sites, but the paucity of ways to identify kinases for particular phosphorylation events remains a major roadblock for understanding kinase signaling. To address this, we here develop a generally applicable method that exploits the large number of kinase inhibitors that have been profiled on near-kinome-wide panels of protein kinases. The inhibition profile for each kinase provides a fingerprint that allows identification of unknown kinases acting on target phosphosites in cell extracts. We validate the method on diverse known kinase-phosphosite pairs, including histone kinases, EGFR autophosphorylation, and Integrin ß1 phosphorylation by Src-family kinases. We also use our approach to identify the previously unknown kinases responsible for phosphorylation of INCENP at a site within a commonly phosphorylated motif in mitosis (a non-canonical target of Cyclin B-Cdk1), and of BCL9L at S915 (PKA). We show that the method has clear advantages over in silico and genetic screening.

Quantitative 3D Mapping of the Human Skeletal Muscle Mitochondrial Network.

Genetic and biochemical defects of mitochondrial function are a major cause of human disease, but their link to mitochondrial morphology in situ has not been defined. Here, we develop a quantitative three-dimensional approach to map mitochondrial network organization in human muscle at electron microscopy resolution. We establish morphological differences between human and mouse and among patients with mitochondrial DNA (mtDNA) diseases compared to healthy controls. We also define the ultrastructure and prevalence of mitochondrial nanotunnels, which exist as either free-ended or connecting membrane protrusions across non-adjacent mitochondria. A multivariate model integrating mitochondrial volume, morphological complexity, and branching anisotropy computed across individual mitochondria and mitochondrial populations identifies increased proportion of simple mitochondria and nanotunnels as a discriminant signature of mitochondrial stress. Overall, these data define the nature of the mitochondrial network in human muscle, quantify human-mouse differences, and suggest potential morphological markers of mitochondrial dysfunction in human tissues.

Genome-Wide Quantitative Fitness Analysis (QFA) of Yeast Cultures.

We provide a detailed protocol for robot-assisted, genome-wide measurement of fitness in the model yeast Saccharomyces cerevisiae using Quantitative Fitness Analysis (QFA). We first describe how we construct thousands of double or triple mutant yeast strains in parallel using Synthetic Genetic Array (SGA) procedures. Strains are inoculated onto solid agar surfaces by liquid spotting followed by repeated photography of agar plates. Growth curves are constructed and the fitness of each strain is estimated. Robot-assisted QFA, can be used to identify genetic interactions and chemical sensitivity/resistance in genome-wide experiments, but QFA can also be used in smaller scale, manual workflows.

The contribution of non-essential Schizosaccharomyces pombe genes to fitness in response to altered nutrient supply and target of rapamycin activity.

Nutrient fluctuations in the cellular environment promote changes in cell metabolism and growth to adapt cell proliferation accordingly. The target of rapamycin (TOR) signalling network plays a key role in the coordination of growth and cell proliferation with the nutrient environment and, importantly, nutrient limitation reduces TOR complex 1 (TORC1) signalling. We have performed global quantitative fitness profiling of the collection of Schizosaccharomyces pombe strains from which non-essential genes have been deleted. We identified genes that regulate fitness when cells are grown in a nutrient-rich environment compared with minimal environments, with varying nitrogen sources including ammonium, glutamate and proline. In addition, we have performed the first global screen for genes that regulate fitness when both TORC1 and TORC2 signalling is reduced by Torin1. Analysis of genes whose deletions altered fitness when nutrients were limited, or when TOR signalling was compromised, identified a large number of genes that regulate transmembrane transport, transcription and chromatin organization/regulation and vesicle-mediated transport. The ability to tolerate reduced TOR signalling placed demands upon a large number of biological processes including autophagy, mRNA metabolic processing and nucleocytoplasmic transport. Importantly, novel biological processes and all processes known to be regulated by TOR were identified in our screens. In addition, deletion of 62 genes conserved in humans gave rise to strong sensitivity or resistance to Torin1, and 29 of these 62 genes have novel links to TOR signalling. The identification of chromatin and transcriptional regulation, nutritional uptake and transport pathways in this powerful genetic model now paves the way for a molecular understanding of how cells adapt to the chronic and acute fluctuations in nutrient supply that all eukaryotes experience at some stage, and which is a key feature of cancer cells within solid tumours.

A Functional Link Between Bir1 and the Saccharomyces cerevisiae Ctf19 Kinetochore Complex Revealed Through Quantitative Fitness Analysis.

The chromosomal passenger complex (CPC) is a key regulator of eukaryotic cell division, consisting of the protein kinase Aurora B/Ipl1 in association with its activator (INCENP/Sli15) and two additional proteins (Survivin/Bir1 and Borealin/Nbl1). Here, we report a genome-wide genetic interaction screen in Saccharomyces cerevisiae using the bir1-17 mutant, identifying through quantitative fitness analysis deletion mutations that act as enhancers and suppressors. Gene knockouts affecting the Ctf19 kinetochore complex were identified as the strongest enhancers of bir1-17, while mutations affecting the large ribosomal subunit or the mRNA nonsense-mediated decay pathway caused strong phenotypic suppression. Thus, cells lacking a functional Ctf19 complex become highly dependent on Bir1 function and vice versa. The negative genetic interaction profiles of bir1-17 and the cohesin mutant mcd1-1 showed considerable overlap, underlining the strong functional connection between sister chromatid cohesion and chromosome biorientation. Loss of some Ctf19 components, such as Iml3 or Chl4, impacted differentially on bir1-17 compared with mutations affecting other CPC components: despite the synthetic lethality shown by either iml3∆ or chl4∆ in combination with bir1-17, neither gene knockout showed any genetic interaction with either ipl1-321 or sli15-3 Our data therefore imply a specific functional connection between the Ctf19 complex and Bir1 that is not shared with Ipl1.

Systematic Analysis of the DNA Damage Response Network in Telomere Defective Budding Yeast.

Functional telomeres are critically important to eukaryotic genetic stability. Scores of proteins and pathways are known to affect telomere function. Here, we report a series of related genome-wide genetic interaction screens performed on budding yeast cells with acute or chronic telomere defects. Genetic interactions were examined in cells defective in Cdc13 and Stn1, affecting two components of CST, a single stranded DNA (ssDNA) binding complex that binds telomeric DNA. For comparison, genetic interactions were also examined in cells with defects in Rfa3, affecting the major ssDNA binding protein, RPA, which has overlapping functions with CST at telomeres. In more complex experiments, genetic interactions were measured in cells lacking EXO1 or RAD9, affecting different aspects of the DNA damage response, and containing a cdc13-1 induced telomere defect. Comparing fitness profiles across these data sets helps build a picture of the specific responses to different types of dysfunctional telomeres. The experiments show that each context reveals different genetic interactions, consistent with the idea that each genetic defect causes distinct molecular defects. To help others engage with the large volumes of data, the data are made available via two interactive web-based tools: Profilyzer and DIXY. One particularly striking genetic interaction observed was that the chk1∆ mutation improved fitness of cdc13-1 exo1∆ cells more than other checkpoint mutations (ddc1∆, rad9∆, rad17∆, and rad24∆), whereas, in cdc13-1 cells, the effects of all checkpoint mutations were similar. We show that this can be explained by Chk1 stimulating resection-a new function for Chk1 in the eukaryotic DNA damage response network.