A systems-level approach to mapping the telomere length maintenance gene circuitry

A comparative analysis of telomere length maintenance circuits in fission and budding yeast

The natural ends of the linear eukaryotic chromosomes are protected by telomeres, which also play an important role in aging and cancer development. Telomere length varies between species, but it is strictly controlled in all organisms. The process of Telomere Length Maintenance (TLM) involves many pathways, protein complexes and interactions that were first discovered in budding and fission yeast model organisms (Saccharomyces cerevisiae, Schizosaccharomyces pombe). In particular, large-scale systematic genetic screens in budding yeast uncovered a network of ≈500 genes that, when mutated, cause telomeres to lengthen or to shorten. In contrast, the TLM network in fission yeast remains largely unknown and systematic data is still lacking. In this work we try to close this gap and develop a unified interpretable machine learning framework for TLM gene discovery and phenotype prediction in both species. We demonstrate the utility of our framework in pinpointing the pathways by which TLM homeostasis is maintained and predicting novel TLM genes in fission yeast. The results of this study could be used for better understanding of telomere biology and serve as a step towards the adaptation of computational methods based on telomeric data for human prognosis.

A Robustness Analysis of Dynamic Boolean Models of Cellular Circuits

With ever growing amounts of omics data, the next challenge in biological research is the interpretation of these data to gain mechanistic insights about cellular function. Dynamic models of cellular circuits that capture the activity levels of proteins and other molecules over time offer great expressive power by allowing the simulation of the effects of specific internal or external perturbations on the workings of the cell. However, the study of such models is at its infancy and no large-scale analysis of the robustness of real models to changing conditions has been conducted to date. Here we provide a computational framework to study the robustness of such models using a combination of stochastic simulations and integer linear programming techniques. We apply our framework to a large collection of cellular circuits and benchmark the results against randomized models. We find that the steady states of real circuits tend to be more robust in multiple aspects compared with their randomized counterparts.

Telomeres and stress in yeast cells: When genes and environment interact

Telomeres are structures composed of simple DNA repeats and specific proteins that protect the eukaryotic chromosomal ends from degradation, and facilitate the replication of the genome. They are central to the maintenance of the genome integrity, and play important roles in the development of cancer and in the process of aging in humans. The yeast Saccharomyces cerevisiae has greatly contributed to our understanding of basic telomere biology. Our laboratory has carried out systematic screen for mutants that affect telomere length, and identified ∼500 genes that, when mutated, affect telomere length. Remarkably, all ∼500 TLM (Telomere Length Maintenance) genes participate in a very tight homeostatic process, and it is enough to mutate one of them to change the steady-state telomere length. Despite this complex network of balances, it is also possible to change telomere length in yeast by applying several types of external stresses. We summarize our insights about the molecular mechanisms by which genes and environment interact to affect telomere length.

Comparative Analysis of Normalization Methods for Network Propagation

Network propagation is a central tool in biological research. While a number of variants and normalizations have been proposed for this method, each has its own shortcomings and no large scale assessment of those variants is available. Here we propose a novel normalization method for network propagation that is based on evaluating the propagation results against those obtained on randomized networks that preserve node degrees. In this way, our method overcomes potential biases of previous methods. We evaluate its performance on multiple large scale datasets and find that it compares favorably to previous approaches in diverse gene prioritization tasks. We further demonstrate its utility on a focused dataset of telomere length maintenance in yeast. The normalization method is available at http://anat.cs.tau.ac.il/WebPropagate.

Recent Advances in the Systems Biology of Aging

SIGNIFICANCE

Reductionist studies have contributed greatly to our understanding of the basic biology of aging in recent years but we still do not understand fundamental mechanisms for many identified drugs and pathways. Use of systems approaches will help us move forward in our understanding of aging. Recent Advances: Recent work described here has illustrated the power of systems biology to inform our understanding of aging through the study of (i) diet restriction, (ii) neurodegenerative disease, and (iii) biomarkers of aging.

CRITICAL ISSUES

Although we do not understand all of the individual genes and pathways that affect aging, as we continue to uncover more of them, we have now also begun to synthesize existing data using systems-level approaches, often to great effect. The three examples noted here all benefit from computational approaches that were unknown a few years ago, and from biological insights gleaned from multiple model systems, from aging laboratories as well as many other areas of biology.

FUTURE DIRECTIONS

Many new technologies, such as single-cell sequencing, advances in epigenetics beyond the methylome (specifically, assay for transposase-accessible chromatin with high throughput sequencing ), and multiomic network studies, will increase the reach of systems biologists. This suggests that approaches similar to those described here will continue to lead to striking findings, and to interventions that may allow us to delay some of the many age-associated diseases in humans; perhaps sooner that we expect. Antioxid. Redox Signal. 29, 973-984.

WebPropagate: A Web Server for Network Propagation

Network propagation is a powerful tool for genetic analysis which is widely used to identify genes and genetic modules that underlie a process of interest. Here we provide a graphical, web-based platform (http://anat.cs.tau.ac.il/WebPropagate/) in which researchers can easily apply variants of this method to data sets of interest using up-to-date networks of protein-protein interactions in several organisms.

Cdc73 suppresses genome instability by mediating telomere homeostasis

Defects in the genes encoding the Paf1 complex can cause increased genome instability. Loss of Paf1, Cdc73, and Ctr9, but not Rtf1 or Leo1, caused increased accumulation of gross chromosomal rearrangements (GCRs). Combining the cdc73Δ mutation with individual deletions of 43 other genes, including TEL1 and YKU80, which are involved in telomere maintenance, resulted in synergistic increases in GCR rates. Whole genome sequence analysis of GCRs indicated that there were reduced relative rates of GCRs mediated by de novo telomere additions and increased rates of translocations and inverted duplications in cdc73Δ single and double mutants. Analysis of telomere lengths and telomeric gene silencing in strains containing different combinations of cdc73Δ, tel1Δ and yku80Δ mutations suggested that combinations of these mutations caused increased defects in telomere maintenance. A deletion analysis of Cdc73 revealed that a central 105 amino acid region was necessary and sufficient for suppressing the defects observed in cdc73Δ strains; this region was required for the binding of Cdc73 to the Paf1 complex through Ctr9 and for nuclear localization of Cdc73. Taken together, these data suggest that the increased GCR rate of cdc73Δ single and double mutants is due to partial telomere dysfunction and that Ctr9 and Paf1 play a central role in the Paf1 complex potentially by scaffolding the Paf1 complex subunits or by mediating recruitment of the Paf1 complex to the different processes it functions in.

Maintaining a stable genome is crucial for all organisms, and loss of genome stability has been linked to multiple human diseases, including many cancers. Previously we found that defects in Cdc73, a component of the Paf1 transcriptional elongation complex, give rise to increased genome instability. Here, we explored the mechanism underlying this instability and found that Cdc73 defects give rise to partial defects in maintaining telomeres, which are the specialized ends of chromosomes, and interact with other mutations causing telomere defects. Remarkably, Cdc73 function is mediated through a short central region of the protein that is not a part of previously identified protein domains but targets Cdc73 to the Paf1 complex through interaction with the Ctr9 subunit. Analysis of the other components of the Paf1 complex provides a model in which the Paf1 subunit mediates recruitment of the other subunits to different processes they function in. Together, these data suggest that the mutations in CDC73 and CTR9 found in patients with hyperparathyroidism-jaw tumor syndrome and some patients with Wilms tumors, respectively, may contribute to cancer progression by contributing to genome instability.

Do long telomeres affect cellular fitness?

Telomeres protect the chromosome ends and maintain the genome stability; they, therefore, play important roles in aging and cancer. Despite the wide variability in telomere length among eukaryotes, in all telomerase-expressing cells telomere length is strictly controlled within a very narrow range. In humans, telomeres shorten with age, and it has been proposed that telomere shortening may play a causal role in aging. Using yeast strains with genetically or physiologically generated differences in telomere length, we have explored the question of whether having long telomeres affects telomere function and fitness or cellular lifespan. We found no effect of long telomeres on vegetative cell division, meiosis, or in cellular lifespan. No positive or negative effect on fitness was observed either under stressful conditions.

Long Telomeres Do Not Affect Cellular Fitness in Yeast

Telomeres, the ends of the eukaryotic chromosomes, help to maintain the genome’s integrity and thus play important roles in aging and cancer. Telomere length is strictly controlled in all organisms. In humans, telomeres shorten with age, and it has been proposed that telomere shortening may play a causal role in aging. We took advantage of the availability of yeast strains with genetically or physiologically generated differences in telomere length to measure the effect that telomere length may have on cellular growth. By comparing the growth rates affecting telomere length of various yeast mutants we show that there is no correlation between their telomere length and cellular fitness. We also show that wild-type yeast cells carrying extremely long telomeres (~5 times longer than the average) showed no signs of mitotic or meiotic defects, and competition experiments found no differences in growth between strains with normal telomeres and strains with long telomeres. No advantage or disadvantage of cells with long telomeres was detected under stress conditions either. Finally, telomere length had no effect in a chronological life span assay, which measures survival of post-mitotic-stage cells. We conclude that extreme telomere length has no effects (positive or negative) on the fitness of yeast cells.

Telomeres protect the chromosomal ends from fusion, degradation, and unwanted repair. Therefore, telomeres preserve genome stability and cell viability. In humans, telomeres shorten with each cell duplication event and with age. It has thus been proposed that telomere shortening may be responsible for human aging and that elongation of telomeres may be a way to rejuvenate cells and to combat aging. However, it is difficult to prove this hypothesis in human cells. Yeasts are easy to manipulate and have telomeres whose length is strictly maintained. Here we show that yeast cells manipulated to have extremely long telomeres (~5-fold those of normal cells) did not show any improvement or reduction in fitness compared to otherwise identical cells with telomeres of normal length under all the conditions tested. Moreover, an assay that measures cell aging showed no effect of the presence of extremely long telomeres. We thus conclude that extreme telomere length, at least in yeast cells, does not affect cellular fitness, aging, or senescence.

Role of the ESCRT Complexes in Telomere Biology

Eukaryotic chromosomal ends are protected by telomeres from fusion, degradation, and unwanted double-strand break repair events. Therefore, telomeres preserve genome stability and integrity. Telomere length can be maintained by telomerase, which is expressed in most human primary tumors but is not expressed in the majority of somatic cells. Thus, telomerase may be a highly relevant anticancer drug target. Genome-wide studies in the yeast Saccharomyces cerevisiae identified a set of genes associated with telomere length maintenance (TLM genes). Among the tlm mutants with short telomeres, we found a strong enrichment for those affecting vacuolar and endosomal traffic (particularly the endosomal sorting complex required for transport [ESCRT] pathway). Here, we present our results from investigating the surprising link between telomere shortening and the ESCRT machinery. Our data show that the whole ESCRT system is required to safeguard proper telomere length maintenance. We propose a model of impaired end resection resulting in too little telomeric overhang, such that Cdc13 binding is prevented, precluding either telomerase recruitment or telomeric overhang protection.

Telomeres are the ends of eukaryotic chromosomes. They are necessary for the proper replication of the genome and protect the chromosomes from degradation. In a large-scale systematic screen for mutants that affect telomere length in yeast, we found that mutations in any of the genes encoding the ESCRT complexes, required for the formation of transport vesicles within the cell, cause telomere shortening. We carried out an analysis of the mechanisms disrupted in these mutants and found that they are defective for the ability to elongate short telomeres, probably due to faulty end processing. We discuss the significance of these findings and how they could be relevant to anticancer therapies.

Identification of Yeast Mutants Exhibiting Altered Sensitivity to Valinomycin and Nigericin Demonstrate Pleiotropic Effects of Ionophores on Cellular Processes

Ionophores such as valinomycin and nigericin are potent tools for studying the impact of ion perturbance on cellular functions. To obtain a broader picture about molecular components involved in mediating the effects of these drugs on yeast cells under respiratory growth conditions, we performed a screening of the haploid deletion mutant library covering the Saccharomyces cerevisiae nonessential genes. We identified nearly 130 genes whose absence leads either to resistance or to hypersensitivity to valinomycin and/or nigericin. The processes affected by their protein products range from mitochondrial functions through ribosome biogenesis and telomere maintenance to vacuolar biogenesis and stress response. Comparison of the results with independent screenings performed by our and other laboratories demonstrates that although mitochondria might represent the main target for both ionophores, cellular response to the drugs is very complex and involves an intricate network of proteins connecting mitochondria, vacuoles, and other membrane compartments.

Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast

Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments.

Estimating the activity of transcription factors by the effect on their target genes

Motivation: Understanding regulation of transcription is central for elucidating cellular regulation. Several statistical and mechanistic models have come up the last couple of years explaining gene transcription levels using information of potential transcriptional regulators as transcription factors (TFs) and information from epigenetic modifications. The activity of TFs is often inferred by their transcription levels, promoter binding and epigenetic effects. However, in principle, these methods do not take hard-to-measure influences such as post-transcriptional modifications into account.

Results: For TFs, we present a novel concept circumventing this problem. We estimate the regulatory activity of TFs using their cumulative effects on their target genes. We established our model using expression data of 59 cell lines from the National Cancer Institute. The trained model was applied to an independent expression dataset of melanoma cells yielding excellent expression predictions and elucidated regulation of melanogenesis.

Availability and implementation: Using mixed-integer linear programming, we implemented a switch-like optimization enabling a constrained but optimal selection of TFs and optimal model selection estimating their effects. The method is generic and can also be applied to further regulators of transcription.

Contact:rainer.koenig@uni-jena.de

Supplementary information:Supplementary data are available at Bioinformatics online.

Inferring host gene subnetworks involved in viral replication

Systematic, genome-wide loss-of-function experiments can be used to identify host factors that directly or indirectly facilitate or inhibit the replication of a virus in a host cell. We present an approach that combines an integer linear program and a diffusion kernel method to infer the pathways through which those host factors modulate viral replication. The inputs to the method are a set of viral phenotypes observed in single-host-gene mutants and a background network consisting of a variety of host intracellular interactions. The output is an ensemble of subnetworks that provides a consistent explanation for the measured phenotypes, predicts which unassayed host factors modulate the virus, and predicts which host factors are the most direct interfaces with the virus. We infer host-virus interaction subnetworks using data from experiments screening the yeast genome for genes modulating the replication of two RNA viruses. Because a gold-standard network is unavailable, we assess the predicted subnetworks using both computational and qualitative analyses. We conduct a cross-validation experiment in which we predict whether held-aside test genes have an effect on viral replication. Our approach is able to make high-confidence predictions more accurately than several baselines, and about as well as the best baseline, which does not infer mechanistic pathways. We also examine two kinds of predictions made by our method: which host factors are nearest to a direct interaction with a viral component, and which unassayed host genes are likely to be involved in viral replication. Multiple predictions are supported by recent independent experimental data, or are components or functional partners of confirmed relevant complexes or pathways. Integer program code, background network data, and inferred host-virus subnetworks are available at http://www.biostat.wisc.edu/~craven/chasman_host_virus/.

Genome-wide studies of telomere biology in budding yeast

Telomeres are specialized DNA-protein structures at the ends of eukaryotic chromosomes. Telomeres are essential for chromosomal stability and integrity, as they prevent chromosome ends from being recognized as double strand breaks. In rapidly proliferating cells, telomeric DNA is synthesized by the enzyme telomerase, which copies a short template sequence within its own RNA moiety, thus helping to solve the "end-replication problem", in which information is lost at the ends of chromosomes with each DNA replication cycle. The basic mechanisms of telomere length, structure and function maintenance are conserved among eukaryotes. Studies in the yeast Saccharomyces cerevisiae have been instrumental in deciphering the basic aspects of telomere biology. In the last decade, technical advances, such as the availability of mutant collections, have allowed carrying out systematic genome-wide screens for mutants affecting various aspects of telomere biology. In this review we summarize these efforts, and the insights that this Systems Biology approach has produced so far.

Toward a role model

With ever‐growing amounts of 'omics data, the challenge is to develop an automatic modelling pipeline that receives as input large‐scale data pertaining to the system of interest and outputs a complete, logical model that maximizes the fit to the given data.

Nature vs nurture: interplay between the genetic control of telomere length and environmental factors

Telomeres are nucleoprotein structures that cap the ends of the linear eukaryotic chromosomes, thus protecting their stability and integrity. They play important roles in DNA replication and repair and are central to our understanding of aging and cancer development. In rapidly dividing cells, telomere length is maintained by the activity of telomerase. About 400 TLM (telomere length maintenance) genes have been identified in yeast, as participants of an intricate homeostasis network that keeps telomere length constant. Two papers have recently shown that despite this extremely complex control, telomere length can be manipulated by external stimuli. These results have profound implications for our understanding of cellular homeostatic systems in general and of telomere length maintenance in particular. In addition, they point to the possibility of developing aging and cancer therapies based on telomere length manipulation.

Environmental stresses disrupt telomere length homeostasis

Telomeres protect the chromosome ends from degradation and play crucial roles in cellular aging and disease. Recent studies have additionally found a correlation between psychological stress, telomere length, and health outcome in humans. However, studies have not yet explored the causal relationship between stress and telomere length, or the molecular mechanisms underlying that relationship. Using yeast as a model organism, we show that stresses may have very different outcomes: alcohol and acetic acid elongate telomeres, whereas caffeine and high temperatures shorten telomeres. Additional treatments, such as oxidative stress, show no effect. By combining genome-wide expression measurements with a systematic genetic screen, we identify the Rap1/Rif1 pathway as the central mediator of the telomeric response to environmental signals. These results demonstrate that telomere length can be manipulated, and that a carefully regulated homeostasis may become markedly deregulated in opposing directions in response to different environmental cues.

Over 70 years ago, Barbara McClintock described telomeres and hypothesized about their role in protecting the integrity of chromosomes. Since then, scientists have shown that telomere length is highly regulated and associated with cell senescence and longevity, as well as with age-related disorders and cancer. Here, we show that despite their importance, the tight, highly complex regulation of telomeres may be disrupted by environmental cues, leading to changes in telomere length. We have introduced yeast cells to 13 different environmental stresses to show that some stresses directly alter telomere length. Our results indicate that alcohol and acetic acid elongate telomeres, while caffeine and high temperatures shorten telomeres. Using expression data, bioinformatics tools, and a large genetic screen, we explored the mechanisms responsible for the alterations of telomere length under several stress conditions. We identify Rap1 and Rif1, central players in telomere length maintenance, as the central proteins directly affected by external cues that respond by altering telomere length. Because many human diseases are related to alterations in telomere length that fuel the disease's pathology, controlling telomere length by manipulating simple stressing agents may point the way to effective treatment, and will supply scientists with an additional tool to study the machinery responsible for telomere length homeostasis.

A systems biology approach to identify the signalling network regulated by Rho-GDI-γ during neural stem cell differentiation

Understanding the molecular mechanism that underlies the differentiation of neural stem cells (NSCs) is vital to develop regenerative medicines for neurological disorders. In our previous work, Rho-GDI-γ was found to be able to prompt neuronal differentiation when it was down regulated. However, it is unclear how Rho-GDI-γ regulates this differentiation process. Therefore, a novel systems biology approach is presented here to identify putative signalling pathways regulated by Rho-GDI-γ during NSC differentiation, and these pathways can provide insights into the NSC differentiation mechanisms. In particular, our proposed approach combines the predictive power of computational biology and molecular experiments. With different biological experiments, the genes in the computationally identified signalling network were validated to be indeed regulated by Rho-GDI-γ during the differentiation of NSCs. In particular, one randomly selected pathway involving Vcp, Mapk8, Ywhae and Ywhah was experimentally verified to be regulated by Rho-GDI-γ. These promising results demonstrate the effectiveness of our proposed systems biology approach, indicating the potential predictive power of integrating computational and experimental approaches.

iPoint: an integer programming based algorithm for inferring protein subnetworks

Large scale screening experiments have become the workhorse of molecular biology, producing data at an ever increasing scale. The interpretation of such data, particularly in the context of a protein interaction network, has the potential to shed light on the molecular pathways underlying the phenotype or the process in question. A host of approaches have been developed in recent years to tackle this reconstruction challenge. These approaches aim to infer a compact subnetwork that connects the genes revealed by the screen while optimizing local (individual path lengths) or global (likelihood) aspects of the subnetwork. Yosef et al. [Mol. Syst. Biol., 2009, 5, 248] were the first to provide a joint optimization of both criteria, albeit approximate in nature. Here we devise an integer linear programming formulation for the joint optimization problem, allowing us to solve it to optimality in minutes on current networks. We apply our algorithm, iPoint, to various data sets in yeast and human and evaluate its performance against state-of-the-art algorithms. We show that iPoint attains very compact and accurate solutions that outperform previous network inference algorithms with respect to their local and global attributes, their consistency across multiple experiments targeting the same pathway, and their agreement with current biological knowledge.

Systems biology and bioinformatics in aging research: a workshop report

In an "aging society," health span extension is most important. As in 2010, talks in this series of meetings in Rostock-Warnemünde demonstrated that aging is an apparently very complex process, where computational work is most useful for gaining insights and to find interventions that counter aging and prevent or counteract aging-related diseases. The specific topics of this year's meeting entitled, "RoSyBA: Rostock Symposium on Systems Biology and Bioinformatics in Ageing Research," were primarily related to "Cancer and Aging" and also had a focus on work funded by the German Federal Ministry of Education and Research (BMBF). The next meeting in the series, scheduled for September 20-21, 2013, will focus on the use of ontologies for computational research into aging, stem cells, and cancer. Promoting knowledge formalization is also at the core of the set of proposed action items concluding this report.

Discovering the hidden sub-network component in a ranked list of genes or proteins derived from genomic experiments

Genomic experiments (e.g. differential gene expression, single-nucleotide polymorphism association) typically produce ranked list of genes. We present a simple but powerful approach which uses protein–protein interaction data to detect sub-networks within such ranked lists of genes or proteins. We performed an exhaustive study of network parameters that allowed us concluding that the average number of components and the average number of nodes per component are the parameters that best discriminate between real and random networks. A novel aspect that increases the efficiency of this strategy in finding sub-networks is that, in addition to direct connections, also connections mediated by intermediate nodes are considered to build up the sub-networks. The possibility of using of such intermediate nodes makes this approach more robust to noise. It also overcomes some limitations intrinsic to experimental designs based on differential expression, in which some nodes are invariant across conditions. The proposed approach can also be used for candidate disease-gene prioritization. Here, we demonstrate the usefulness of the approach by means of several case examples that include a differential expression analysis in Fanconi Anemia, a genome-wide association study of bipolar disorder and a genome-scale study of essentiality in cancer genes. An efficient and easy-to-use web interface (available at http://www.babelomics.org) based on HTML5 technologies is also provided to run the algorithm and represent the network.

Systematic identification of gene annotation errors in the widely used yeast mutation collections

The baker's yeast mutation collections are extensively used genetic resources that are the basis for many genome-wide screens and new technologies. Anecdotal evidence has previously pointed to the putative existence of a neighboring gene effect (NGE) in these collections. NGE occurs when the phenotype of a strain carrying a particular perturbed gene is due to the lack of proper function of its adjacent gene. Here we performed a large-scale study of NGEs, presenting a network-based algorithm for detecting NGEs and validating software predictions using complementation experiments. We applied our approach to four datasets uncovering a similar magnitude of NGE in each (7-15%). These results have important consequences for systems biology, as the mutation collections are extensively used in almost every aspect of the field, from genetic network analysis to functional gene annotation.

Haploinsufficiency and telomere length homeostasis

In humans, autosomal dominant or X-linked disease can arise through a phenomenon termed haploinsufficiency, where one remaining wild-type allele is insufficient for function. In model organisms, the impact of heterozygosity can be tested directly with engineered mutant alleles or in a hemizygous state where the expression of one allele is abrogated completely. This review will focus on haploinsufficiency as it relates to telomerase and telomere length maintenance and, citing selected examples in various model organisms, it will discuss how the problem of gene dosage relates to telomere function in normal and diseased states.

Tor complex 1 controls telomere length by affecting the level of Ku

Telomeres are specialized DNA-protein structures at the ends of eukaryotic chromosomes. Telomeric DNA is synthesized by telomerase, which is expressed only at the early stages of development [1, 2]. To become malignant, any cell has to be able to replenish telomeres [3]. Thus, understanding how telomere length is monitored has significant medical implications, especially in the fields of aging and cancer. In yeast, telomerase is constitutively active. A large network of genes participates in controlling telomere length [4-8]. Tor1 and Tor2 (targets of rapamycin [9]) are two similar kinases that regulate cell growth [10]. Both can be found as part of the TOR complex 1 (TORC1 [11]), which coordinates the response to nutrient starvation and is sensitive to rapamycin [12]. The rapamycin-insensitive TOR complex 2 (TORC2) contains only Tor2 and regulates actin cytoskeleton polarization [13]. Here we provide evidence for a role of TORC1 in telomere shortening upon starvation in yeast cells. The TORC1 signal is transduced by the Gln3/Gat1/Ure2 pathway, which controls the levels of the Ku heterodimer, a telomere regulator. We discuss the potential implications for the usage of rapamycin as a therapeutic agent against cancer and the effect that calorie restriction may have on telomere length.

ANAT: a tool for constructing and analyzing functional protein networks

Genome-scale screening studies are gradually accumulating a wealth of data on the putative involvement of hundreds of genes in various cellular responses or functions. A fundamental challenge is to chart the molecular pathways that underlie these systems. ANAT is an interactive software tool, implemented as a Cytoscape plug-in, for elucidating functional networks of proteins. It encompasses a number of network inference algorithms and provides access to networks of physical associations in several organisms. In contrast to existing software tools, ANAT can be used to infer subnetworks that connect hundreds of proteins to each other or to a given set of "anchor" proteins, a fundamental step in reconstructing cellular subnetworks. The interactive component of ANAT provides an array of tools for evaluating and exploring the resulting subnetwork models and for iteratively refining them. We demonstrate the utility of ANAT by studying the crosstalk between the autophagic and apoptotic cell death modules in humans, using a network of physical interactions. Relative to published software tools, ANAT is more accurate and provides more features for comprehensive network analysis. The latest version of the software is available at http://www.cs.tau.ac.il/~bnet/ANAT_SI.

Genome-wide analysis to identify pathways affecting telomere-initiated senescence in budding yeast

In telomerase-deficient yeast cells, like equivalent mammalian cells, telomeres shorten over many generations until a period of senescence/crisis is reached. After this, a small fraction of cells can escape senescence, principally using recombination-dependent mechanisms. To investigate the pathways that affect entry into and recovery from telomere-driven senescence, we combined a gene deletion disrupting telomerase (est1Δ) with the systematic yeast deletion collection and measured senescence characteristics in high-throughput assays. As expected, the vast majority of gene deletions showed no strong effects on entry into/exit from senescence. However, around 200 gene deletions behaving similarly to a rad52Δest1Δ archetype (rad52Δ affects homologous recombination) accelerated entry into senescence, and such cells often could not recover growth. A smaller number of strains similar to a rif1Δest1Δ archetype (rif1Δ affects proteins that bind telomeres) accelerated entry into senescence but also accelerated recovery from senescence. Our genome-wide analysis identifies genes that affect entry into and/or exit from telomere-initiated senescence and will be of interest to those studying telomere biology, replicative senescence, cancer, and ageing. Our dataset is complementary to other high-throughput studies relevant to telomere biology, genetic stability, and DNA damage responses.

From sequence to function: Insights from natural variation in budding yeasts

Background

Natural variation offers a powerful approach for assigning function to DNA sequence—a pressing challenge in the age of high throughput sequencing technologies.

Scope of Review

Here we review comparative genomic approaches that are bridging the sequence–function and genotype–phenotype gaps. Reverse genomic approaches aim to analyse sequence to assign function, whereas forward genomic approaches start from a phenotype and aim to identify the underlying genotype responsible.

Major Conclusions

Comparative genomic approaches, pioneered in budding yeasts, have resulted in dramatic improvements in our understanding of the function of both genes and regulatory sequences. Analogous studies in other systems, including humans, demonstrate the ubiquity of comparative genomic approaches. Recently, forward genomic approaches, exploiting natural variation within yeast populations, have started to offer powerful insights into how genotype influences phenotype and even the ability to predict phenotypes.

General Significance

Comparative genomic experiments are defining the fundamental rules that govern complex traits in natural populations from yeast to humans.

This article is part of a Special Issue entitled Systems Biology of Microorganisms.

Dynamic energy budget approaches for modelling organismal ageing

Ageing is a complex multifactorial process involving a progressive physiological decline that, ultimately, leads to the death of an organism. It involves multiple changes in many components that play fundamental roles under healthy and pathological conditions. Simultaneously, every organism undergoes accumulative 'wear and tear' during its lifespan, which confounds the effects of the ageing process. The scenario is complicated even further by the presence of both age-dependent and age-independent competing causes of death. Various manipulations have been shown to interfere with the ageing process. Calorie restriction, for example, has been reported to increase the lifespan of a wide range of organisms, which suggests a strong relation between energy metabolism and ageing. Such a link is also supported within the main theories for ageing: the free radical hypothesis, for instance, links oxidative damage production directly to energy metabolism. The Dynamic Energy Budgets (DEB) theory, which characterizes the uptake and use of energy by living organisms, therefore constitutes a useful tool for gaining insight into the ageing process. Here we compare the existing DEB-based modelling approaches and, then, discuss how new biological evidence could be incorporated within a DEB framework.

Modular analysis of the probabilistic genetic interaction network

Motivation: Epistatic Miniarray Profiles (EMAP) has enabled the mapping of large-scale genetic interaction networks; however, the quantitative information gained from EMAP cannot be fully exploited since the data are usually interpreted as a discrete network based on an arbitrary hard threshold. To address such limitations, we adopted a mixture modeling procedure to construct a probabilistic genetic interaction network and then implemented a Bayesian approach to identify densely interacting modules in the probabilistic network.

Results: Mixture modeling has been demonstrated as an effective soft-threshold technique of EMAP measures. The Bayesian approach was applied to an EMAP dataset studying the early secretory pathway in Saccharomyces cerevisiae. Twenty-seven modules were identified, and 14 of those were enriched by gold standard functional gene sets. We also conducted a detailed comparison with state-of-the-art algorithms, hierarchical cluster and Markov clustering. The experimental results show that the Bayesian approach outperforms others in efficiently recovering biologically significant modules.

Contact:dengmh@pku.edu.cn; fangtingli@pku.edu.cn; zhuyp@hupo.org.cn

Supplementary Information:Supplementary data are available at Bioinformatics online.

Different sets of QTLs influence fitness variation in yeast

We have carried out a combination of in-lab-evolution (ILE) and congenic crosses to identify the gene sets that contribute to the ability of yeast cells to survive under alkali stress.

Each selected line acquired a different set of mutations, all resulting in the same phenotype. We identified a total of 15 genes in ILE and 17 candidates in the congenic approach, and studied their individual contribution to the phenotype.

The total additive effect of the QTLs was much larger than the difference between the ancestor and the evolved strains, suggesting epistatic interactions between the QTLs.

None of the genes identified encode structural components of the pH machinery. Instead, most encode regulatory functions, such as ubiquitin ligases, chromatin remodelers, GPI anchoring and copper/iron sensing transcription factors.

The majority of phenotypes in nature are complex traits affected by multiple genes [usually called quantitative trait loci (QTLs)], as well as by environmental factors. Many traits with practical importance such as crop yield in plants and susceptibility to various diseases in humans fall under this category. Understanding the architecture of complex traits has become the new frontier of genetic research, and many studies have greatly contributed to this field. However, to date, the genetic basis of only a few of these traits has been identified, and many questions regarding the architecture of complex traits and the accumulation of QTLs during evolution still remain unanswered. Among them are: How many QTLs affect complex phenotypes? What is the effect of each QTL? How do complex traits change during evolution? Is the adaptation process repeatable?, etc. In order to identify the QTLs that affect one of the important components of fitness variability in yeast, and to answer some of the questions above, we combined in-lab evolution (ILE) with the construction of congenic lines to isolate and map several gene sets that contribute to the ability of yeast cells to survive under alkali stress.

We carried out an ILE experiment, in which we grew yeast populations under increasing alkali stress to enrich for beneficial mutations. This process was followed by hybridizations to tiling arrays to identify the mutations acquired during the laboratory selective process. The ILE procedure revealed mutations in 15 genes, thus defining the QTLs and mechanisms that affect, in a quantitative fashion, the ability to cope with alkali stress. Our results indicate that during ILE several populations acquired different sets of QTLs that conferred the same phenotype. We identified each individual mutation in these strains, and validated and estimated their contribution to the phenotype. The total additive effect of the QTLs was much larger than the difference between the ancestor and the evolved strains, suggesting epistatic interactions between the QTLs.

In addition to the ILE, we have studied the mechanisms regulating fitness under alkali stress at natural habitats. We used a clinically isolated strain able to grow at high pH and a standard laboratory strain with a limited ability to sustain high pH as the parents of series of backcrosses to construct congenic lines up to the 8th generation. Seventeen genomic intervals that are candidates to contain QTLs were thus identified. In order to detect the contributing QTL in each interval, a predictive algorithm was applied, which scored the candidate genes in each genomic interval based on their interactions and similarity to the ILE genes. The algorithm was validated by testing the effect of the predicted candidate gene's deletions on the phenotype. Twelve out of 29 deletions were found to affect the trait (P-value 0.023).

Interestingly, our results show that almost all beneficial mutations affected regulatory genes, and not structural components of the pH homeostasis machinery (such as proton pumps, which control the cell's pH). The genes identified affect global regulators, such as ubiquitin ligases, proteins involved in GPI anchoring, copper sensing and chromatin remodelers. Thus, we show that adaptive changes tend to occur in genes with wide influence, rather than in genes narrowly affecting the phenotype selected for.

One example of genes identified both in the ILE and in the congenic lines is the copper-sensing transcription factor MAC1, and its downstream targets CTR1 and CTR3, which encode copper transporters. Different mutations at the same residue (Cys 271) were found in four out of five independent ILE lines. These mutations inactivate a copper-sensing region of Mac1 and cause up-regulation of its target genes. The CTR1 and CTR3 genes were identified in the congenic lines. Moreover, we found that a Ty transposable element is responsible for the decreased expression of CTR3 in some strains, and its excision caused transcriptional activation, affecting the ability to thrive at high pH.

This work provides insights on both evolutionary and genetic issues (such as the appearance of adaptive mutations and the architecture of complex traits), while at the same time providing information about the mechanisms that contribute to growth at high pH, a subject with ramifications for cell physiology, pathogenicity, and stress response.

Most of the phenotypes in nature are complex and are determined by many quantitative trait loci (QTLs). In this study we identify gene sets that contribute to one important complex trait: the ability of yeast cells to survive under alkali stress. We carried out an in-lab evolution (ILE) experiment, in which we grew yeast populations under increasing alkali stress to enrich for beneficial mutations. The populations acquired different sets of affecting alleles, showing that evolution can provide alternative solutions to the same challenge. We measured the contribution of each allele to the phenotype. The sum of the effects of the QTLs was larger than the difference between the ancestor phenotype and the evolved strains, suggesting epistatic interactions between the QTLs. In parallel, a clinical isolated strain was used to map natural QTLs affecting growth at high pH. In all, 17 candidate regions were found. Using a predictive algorithm based on the distances in protein-interaction networks, candidate genes were defined and validated by gene disruption. Many of the QTLs found by both methods are not directly implied in pH homeostasis but have more general, and often regulatory, roles.

A systems level strategy for analyzing the cell death network: implication in exploring the apoptosis/autophagy connection

The mammalian cell death network comprises three distinct functional modules: apoptosis, autophagy and programmed necrosis. Currently, the field lacks systems level approaches to assess the extent to which the intermodular connectivity affects cell death performance. Here, we developed a platform that is based on single and double sets of RNAi-mediated perturbations targeting combinations of apoptotic and autophagic genes. The outcome of perturbations is measured both at the level of the overall cell death responses, using an unbiased quantitative reporter, and by assessing the molecular responses within the different functional modules. Epistatic analyses determine whether seemingly unrelated pairs of proteins are genetically linked. The initial running of this platform in etoposide-treated cells, using a few single and double perturbations, identified several levels of connectivity between apoptosis and autophagy. The knock down of caspase3 turned on a switch toward autophagic cell death, which requires Atg5 or Beclin-1. In addition, a reciprocal connection between these two autophagic genes and apoptosis was identified. By applying computational tools that are based on mining the protein-protein interaction database, a novel biochemical pathway connecting between Atg5 and caspase3 is suggested. Scaling up this platform into hundreds of perturbations potentially has a wide, general scope of applicability, and will provide the basis for future modeling of the cell death network.

In Saccharomyces cerevisiae, yKu and subtelomeric core X sequences repress homologous recombination near telomeres as part of the same pathway

Unlike in meiosis where recombination near telomeres is repressed, subtelomeric regions appear to recombine with each other frequently in vegetative cells with no detrimental consequences. To test whether or not such recombination is prevented in the core of chromosomes for maintenance of genome stability, we measured allelic homologous recombination (HR) along chromosome arms and between different ectopic locations. We found that there is an increase of recombination at telomeres in wild-type cells compared with sequences at proximal subtelomeric and interstitial regions of the genome. We also screened for mutations that result in an increase in HR between a telomeric sequence and a more internal sequence, which normally exhibit very low rates of HR. YKU80 was hit most frequently in our screen, and we show that the yKu heterodimer specifically represses HR in the vicinity of telomeres. This repression of HR is not explained solely by the role of yKu in maintaining telomere length, silencing, or tethering to the nuclear periphery. Analysis of mutant strains harboring deleted core X sequences revealed a role for this subtelomeric element in preventing telomeric recombination. Furthermore, core X bestowed this protection as part of the same pathway as yKu. Our findings implicate a role for both yKu and core X in stabilizing the genome against recombination events involving telomeric sequences.

Taming the tiger by the tail: modulation of DNA damage responses by telomeres

Telomeres are by definition stable and inert chromosome ends, whereas internal chromosome breaks are potent stimulators of the DNA damage response (DDR). Telomeres do not, as might be expected, exclude DDR proteins from chromosome ends but instead engage with many DDR proteins. However, the most powerful DDRs, those that might induce chromosome fusion or cell-cycle arrest, are inhibited at telomeres. In budding yeast, many DDR proteins that accumulate most rapidly at double strand breaks (DSBs), have important functions in physiological telomere maintenance, whereas DDR proteins that arrive later tend to have less important functions. Considerable diversity in telomere structure has evolved in different organisms and, perhaps reflecting this diversity, different DDR proteins seem to have distinct roles in telomere physiology in different organisms. Drawing principally on studies in simple model organisms such as budding yeast, in which many fundamental aspects of the DDR and telomere biology have been established; current views on how telomeres harness aspects of DDR pathways to maintain telomere stability and permit cell-cycle division are discussed.

A systems biology view of cancer

In order to understand how a cancer cell is functionally different from a normal cell it is necessary to assess the complex network of pathways involving gene regulation, signaling, and cell metabolism, and the alterations in its dynamics caused by the several different types of mutations leading to malignancy. Since the network is typically complex, with multiple connections between pathways and important feedback loops, it is crucial to represent it in the form of a computational model that can be used for a rigorous analysis. This is the approach of systems biology, made possible by new -omics data generation technologies. The goal of this review is to illustrate this approach and its utility for our understanding of cancer. After a discussion of recent progress using a network-centric approach, three case studies related to diagnostics, therapy, and drug development are presented in detail. They focus on breast cancer, B-cell lymphomas, and colorectal cancer. The discussion is centered on key mathematical and computational tools common to a systems biology approach.

A genome-wide screen for essential yeast genes that affect telomere length maintenance

Telomeres are structures composed of repetitive DNA and proteins that protect the chromosomal ends in eukaryotic cells from fusion or degradation, thus contributing to genomic stability. Although telomere length varies between species, in all organisms studied telomere length appears to be controlled by a dynamic equilibrium between elongating mechanisms (mainly addition of repeats by the enzyme telomerase) and nucleases that shorten the telomeric sequences. Two previous studies have analyzed a collection of yeast deletion strains (deleted for nonessential genes) and found over 270 genes that affect telomere length (Telomere Length Maintenance or TLM genes). Here we complete the list of TLM by analyzing a collection of strains carrying hypomorphic alleles of most essential genes (DAmP collection). We identify 87 essential genes that affect telomere length in yeast. These genes interact with the nonessential TLM genes in a significant manner, and provide new insights on the mechanisms involved in telomere length maintenance. The newly identified genes span a variety of cellular processes, including protein degradation, pre-mRNA splicing and DNA replication.

Toward accurate reconstruction of functional protein networks

Genome-scale screening studies are gradually accumulating a wealth of data on the putative involvement of hundreds of genes/proteins in various cellular responses or functions. A fundamental challenge is to chart out the protein pathways that underlie these systems. Previous approaches to the problem have either employed a local optimization criterion, aiming to infer each pathway independently, or a global criterion, searching for the overall most parsimonious subnetwork. Here, we study the trade-off between the two approaches and present a new intermediary scheme that provides explicit control over it. We demonstrate its utility in the analysis of the apoptosis network in humans, and the telomere length maintenance (TLM) system in yeast. Our results show that in the majority of real-life cases, the intermediary approach provides the most plausible solutions. We use a new set of perturbation experiments measuring the role of essential genes in telomere length regulation to further study the TLM network. Surprisingly, we find that the proteasome plays an important role in telomere length regulation through its associations with transcription and DNA repair circuits.

Bridging high-throughput genetic and transcriptional data reveals cellular responses to alpha-synuclein toxicity

Cells respond to stimuli by changes in various processes, including signaling pathways and gene expression. Efforts to identify components of these responses increasingly depend on mRNA profiling and genetic library screens. By comparing the results of these two assays across various stimuli, we found that genetic screens tend to identify response regulators, whereas mRNA profiling frequently detects metabolic responses. We developed an integrative approach that bridges the gap between these data using known molecular interactions, thus highlighting major response pathways. We used this approach to reveal cellular pathways responding to the toxicity of alpha-synuclein, a protein implicated in several neurodegenerative disorders including Parkinson's disease. For this we screened an established yeast model to identify genes that when overexpressed alter alpha-synuclein toxicity. Bridging these data and data from mRNA profiling provided functional explanations for many of these genes and identified previously unknown relations between alpha-synuclein toxicity and basic cellular pathways.

Atomic structure of the KEOPS complex: an ancient protein kinase-containing molecular machine

Kae1 is a universally conserved ATPase and part of the essential gene set in bacteria. In archaea and eukaryotes, Kae1 is embedded within the protein kinase-containing KEOPS complex. Mutation of KEOPS subunits in yeast leads to striking telomere and transcription defects, but the exact biochemical function of KEOPS is not known. As a first step to elucidating its function, we solved the atomic structure of archaea-derived KEOPS complexes involving Kae1, Bud32, Pcc1, and Cgi121 subunits. Our studies suggest that Kae1 is regulated at two levels by the primordial protein kinase Bud32, which is itself regulated by Cgi121. Moreover, Pcc1 appears to function as a dimerization module, perhaps suggesting that KEOPS may be a processive molecular machine. Lastly, as Bud32 lacks the conventional substrate-recognition infrastructure of eukaryotic protein kinases including an activation segment, Bud32 may provide a glimpse of the evolutionary history of the protein kinase family.

A genomewide suppressor and enhancer analysis of cdc13-1 reveals varied cellular processes influencing telomere capping in Saccharomyces cerevisiae

In Saccharomyces cerevisiae, Cdc13 binds telomeric DNA to recruit telomerase and to "cap" chromosome ends. In temperature-sensitive cdc13-1 mutants telomeric DNA is degraded and cell-cycle progression is inhibited. To identify novel proteins and pathways that cap telomeres, or that respond to uncapped telomeres, we combined cdc13-1 with the yeast gene deletion collection and used high-throughput spot-test assays to measure growth. We identified 369 gene deletions, in eight different phenotypic classes, that reproducibly demonstrated subtle genetic interactions with the cdc13-1 mutation. As expected, we identified DNA damage checkpoint, nonsense-mediated decay and telomerase components in our screen. However, we also identified genes affecting casein kinase II activity, cell polarity, mRNA degradation, mitochondrial function, phosphate transport, iron transport, protein degradation, and other functions. We also identified a number of genes of previously unknown function that we term RTC, for restriction of telomere capping, or MTC, for maintenance of telomere capping. It seems likely that many of the newly identified pathways/processes that affect growth of budding yeast cdc13-1 mutants will play evolutionarily conserved roles at telomeres. The high-throughput spot-testing approach that we describe is generally applicable and could aid in understanding other aspects of eukaryotic cell biology.

Protein networks in disease

During a decade of proof-of-principle analysis in model organisms, protein networks have been used to further the study of molecular evolution, to gain insight into the robustness of cells to perturbation, and for assignment of new protein functions. Following these analyses, and with the recent rise of protein interaction measurements in mammals, protein networks are increasingly serving as tools to unravel the molecular basis of disease. We review promising applications of protein networks to disease in four major areas: identifying new disease genes; the study of their network properties; identifying disease-related subnetworks; and network-based disease classification. Applications in infectious disease, personalized medicine, and pharmacology are also forthcoming as the available protein network information improves in quality and coverage.