Functional Characterization of Co-Phosphorylation Networks

MOTIVATION

Protein phosphorylation is a ubiquitous regulatory mechanism that plays a central role in cellular signaling. According to recent estimates, up to 70% of human proteins can be phosphorylated. Therefore, characterization of phosphorylation dynamics is critical for understanding a broad range of biological and biochemical processes. Technologies based on mass spectrometry are rapidly advancing to meet the needs for high-throughput screening of phosphorylation. These technologies enable untargeted quantification of thousands of phosphorylation sites in a given sample. Many labs are already utilizing these technologies to comprehensively characterize signaling landscapes by examining perturbations with drugs and knockdown approaches, or by assessing diverse phenotypes in cancers, neuro-degerenational diseases, infectious diseases, and normal development.

RESULTS

We comprehensively investigate the concept of "co-phosphorylation", defined as the correlated phosphorylation of a pair of phosphosites across various biological states. We integrate nine publicly available phosphoproteomics datasets for various diseases (including breast cancer, ovarian cancer and Alzheimer's disease) and utilize functional data related to sequence, evolutionary histories, kinase annotations, and pathway annotations to investigate the functional relevance of co-phosphorylation. Our results across a broad range of studies consistently show that functionally associated sites tend to exhibit significant positive or negative co-phosphorylation. Specifically, we show that co-phosphorylation can be used to predict with high precision the sites that are on the same pathway or that are targeted by the same kinase. Overall, these results establish co-phosphorylation as a useful resource for analyzing phosphoproteins in a network context, which can help extend our knowledge on cellular signaling and its dysregulation.

CLUH controls astrin-1 expression to couple mitochondrial metabolism to cell cycle progression

Proliferating cells undergo metabolic changes in synchrony with cell cycle progression and cell division. Mitochondria provide fuel, metabolites, and ATP during different phases of the cell cycle, however it is not completely understood how mitochondrial function and the cell cycle are coordinated. CLUH (clustered mitochondria homolog) is a post-transcriptional regulator of mRNAs encoding mitochondrial proteins involved in oxidative phosphorylation and several metabolic pathways. Here, we show a role of CLUH in regulating the expression of astrin, which is involved in metaphase to anaphase progression, centrosome integrity, and mTORC1 inhibition. We find that CLUH binds both the SPAG5 mRNA and its product astrin, and controls the synthesis and the stability of the full-length astrin-1 isoform. We show that CLUH interacts with astrin-1 specifically during interphase. Astrin-depleted cells show mTORC1 hyperactivation and enhanced anabolism. On the other hand, cells lacking CLUH show decreased astrin levels and increased mTORC1 signaling, but cannot sustain anaplerotic and anabolic pathways. In absence of CLUH, cells fail to grow during G1, and progress faster through the cell cycle, indicating dysregulated matching of growth, metabolism, and cell cycling. Our data reveal a role of CLUH in coupling growth signaling pathways and mitochondrial metabolism with cell cycle progression.

Co-phosphorylation networks reveal subtype-specific signaling modules in breast cancer

MOTIVATION

Protein phosphorylation is a ubiquitous mechanism of post-translational modification that plays a central role in cellular signaling. Phosphorylation is particularly important in the context of cancer, as downregulation of tumor suppressors and upregulation of oncogenes by the dysregulation of associated kinase and phosphatase networks are shown to have key roles in tumor growth and progression. Despite recent advances that enable large-scale monitoring of protein phosphorylation, these data are not fully incorporated into such computational tasks as phenotyping and subtyping of cancers.

RESULTS

We develop a network-based algorithm, CoPPNet, to enable unsupervised subtyping of cancers using phosphorylation data. For this purpose, we integrate prior knowledge on evolutionary, structural and functional association of phosphosites, kinase-substrate associations and protein-protein interactions with the correlation of phosphorylation of phosphosites across different tumor samples (a.k.a co-phosphorylation) to construct a context-specific-weighted network of phosphosites. We then mine these networks to identify subnetworks with correlated phosphorylation patterns. We apply the proposed framework to two mass-spectrometry-based phosphorylation datasets for breast cancer (BC), and observe that (i) the phosphorylation pattern of the identified subnetworks are highly correlated with clinically identified subtypes, and (ii) the identified subnetworks are highly reproducible across datasets that are derived from different studies. Our results show that integration of quantitative phosphorylation data with network frameworks can provide mechanistic insights into the differences between the signaling mechanisms that drive BC subtypes. Furthermore, the reproducibility of the identified subnetworks suggests that phosphorylation can provide robust classification of disease response and markers.

AVAILABILITY AND IMPLEMENTATION

CoPPNet is available at http://compbio.case.edu/coppnet/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Illuminating the dark phosphoproteome

Protein phosphorylation is a major regulator of protein function and biological outcomes. This was first recognized through functional biochemical experiments, and in the past decade, major technological advances in mass spectrometry have enabled the study of protein phosphorylation on a global scale. This rapidly growing field of phosphoproteomics has revealed that more than 100,000 distinct phosphorylation events occur in human cells, which likely affect the function of every protein. Phosphoproteomics has improved the understanding of the function of even the most well-characterized protein kinases by revealing new downstream substrates and biology. However, current biochemical and bioinformatic approaches have only identified kinases for less than 5% of the phosphoproteome, and functional assignments of phosphosites are almost negligible. Notably, our understanding of the relationship between kinases and their substrates follows a power law distribution, with almost 90% of phosphorylation sites currently assigned to the top 20% of kinases. In addition, more than 150 kinases do not have a single known substrate. Despite a small group of kinases dominating biomedical research, the number of substrates assigned to a kinase does not correlate with disease relevance as determined by pathogenic human mutation prevalence and mouse model phenotypes. Improving our understanding of the substrates targeted by all kinases and functionally annotating the phosphoproteome will be broadly beneficial. Advances in phosphoproteomics technologies, combined with functional screening approaches, should make it feasible to illuminate the connectivity and functionality of the entire phosphoproteome, providing enormous opportunities for discovering new biology, therapeutic targets, and possibly diagnostics.

Benchmarking substrate-based kinase activity inference using phosphoproteomic data

Motivation

Phosphoproteomic experiments are increasingly used to study the changes in signaling occurring across different conditions. It has been proposed that changes in phosphorylation of kinase target sites can be used to infer when a kinase activity is under regulation. However, these approaches have not yet been benchmarked due to a lack of appropriate benchmarking strategies.

Results

We used curated phosphoproteomic experiments and a gold standard dataset containing a total of 184 kinase-condition pairs where regulation is expected to occur to benchmark and compare different kinase activity inference strategies: Z-test, Kolmogorov Smirnov test, Wilcoxon rank sum test, gene set enrichment analysis (GSEA), and a multiple linear regression model. We also tested weighted variants of the Z-test and GSEA that include information on kinase sequence specificity as proxy for affinity. Finally, we tested how the number of known substrates and the type of evidence (in vivo, in vitro or in silico) supporting these influence the predictions.

Conclusions

Most models performed well with the Z-test and the GSEA performing best as determined by the area under the ROC curve (Mean AUC = 0.722). Weighting kinase targets by the kinase target sequence preference improves the results marginally. However, the number of known substrates and the evidence supporting the interactions has a strong effect on the predictions.

Availability and Implementation

The KSEA implementation is available in https://github.com/ evocellnet/ksea. Additional data is available in http://phosfate.com

Supplementary information

Supplementary data are available at Bioinformatics online.

Phosphoproteomic profiling of mouse primary HSPCs reveals new regulators of HSPC mobilization

Protein phosphorylation is a central mechanism of signal transduction that both positively and negatively regulates protein function. Large-scale studies of the dynamic phosphorylation states of cell signaling systems have been applied extensively in cell lines and whole tissues to reveal critical regulatory networks, and candidate-based evaluations of phosphorylation in rare cell populations have also been informative. However, application of comprehensive profiling technologies to adult stem cell and progenitor populations has been challenging, due in large part to the scarcity of such cells in adult tissues. Here, we combine multicolor flow cytometry with highly efficient 3-dimensional high performance liquid chromatography/mass spectrometry to enable quantitative phosphoproteomic analysis from 200 000 highly purified primary mouse hematopoietic stem and progenitor cells (HSPCs). Using this platform, we identify ARHGAP25 as a novel regulator of HSPC mobilization and demonstrate that ARHGAP25 phosphorylation at serine 363 is an important modulator of its function. Our approach provides a robust platform for large-scale phosphoproteomic analyses performed with limited numbers of rare progenitor cells. Data from our study comprises a new resource for understanding the molecular signaling networks that underlie hematopoietic stem cell mobilization.

Tousled-like kinase 2 regulates recovery from a DNA damage-induced G2 arrest

In order to maintain a stable genome, cells need to detect and repair DNA damage before they complete the division cycle. To this end, cell cycle checkpoints prevent entry into the next cell cycle phase until the damage is fully repaired. Proper reentry into the cell cycle, known as checkpoint recovery, requires that a cell retains its original cell cycle state during the arrest. Here, we have identified Tousled-like kinase 2 (Tlk2) as an important regulator of recovery after DNA damage in G2. We show that Tlk2 regulates the Asf1A histone chaperone in response to DNA damage and that depletion of Asf1A also produces a recovery defect. Both Tlk2 and Asf1A are required to restore histone H3 incorporation into damaged chromatin. Failure to do so affects expression of pro-mitotic genes and compromises the cellular competence to recover from damage-induced cell cycle arrests. Our results demonstrate that Tlk2 promotes Asf1A function during the DNA damage response in G2 to allow for proper restoration of chromatin structure at the break site and subsequent recovery from the arrest.

Fanconi anemia cells with unrepaired DNA damage activate components of the checkpoint recovery process

Background

The FA/BRCA pathway repairs DNA interstrand crosslinks. Mutations in this pathway cause Fanconi anemia (FA), a chromosome instability syndrome with bone marrow failure and cancer predisposition. Upon DNA damage, normal and FA cells inhibit the cell cycle progression, until the G2/M checkpoint is turned off by the checkpoint recovery, which becomes activated when the DNA damage has been repaired. Interestingly, highly damaged FA cells seem to override the G2/M checkpoint. In this study we explored with a Boolean network model and key experiments whether checkpoint recovery activation occurs in FA cells with extensive unrepaired DNA damage.

Methods

We performed synchronous/asynchronous simulations of the FA/BRCA pathway Boolean network model. FA-A and normal lymphoblastoid cell lines were used to study checkpoint and checkpoint recovery activation after DNA damage induction. The experimental approach included flow cytometry cell cycle analysis, cell division tracking, chromosome aberration analysis and gene expression analysis through qRT-PCR and western blot.

Results

Computational simulations suggested that in FA mutants checkpoint recovery activity inhibits the checkpoint components despite unrepaired DNA damage, a behavior that we did not observed in wild-type simulations. This result implies that FA cells would eventually reenter the cell cycle after a DNA damage induced G2/M checkpoint arrest, but before the damage has been fixed. We observed that FA-A cells activate the G2/M checkpoint and arrest in G2 phase, but eventually reach mitosis and divide with unrepaired DNA damage, thus resolving the initial checkpoint arrest. Based on our model result we look for ectopic activity of checkpoint recovery components. We found that checkpoint recovery components, such as PLK1, are expressed to a similar extent as normal undamaged cells do, even though FA-A cells harbor highly damaged DNA.

Conclusions

Our results show that FA cells, despite extensive DNA damage, do not loss the capacity to express the transcriptional and protein components of checkpoint recovery that might eventually allow their division with unrepaired DNA damage. This might allow cell survival but increases the genomic instability inherent to FA individuals and promotes cancer.

The same, only different - DNA damage checkpoints and their reversal throughout the cell cycle

Cell cycle checkpoints activated by DNA double-strand breaks (DSBs) are essential for the maintenance of the genomic integrity of proliferating cells. Following DNA damage, cells must detect the break and either transiently block cell cycle progression, to allow time for repair, or exit the cell cycle. Reversal of a DNA-damage-induced checkpoint not only requires the repair of these lesions, but a cell must also prevent permanent exit from the cell cycle and actively terminate checkpoint signalling to allow cell cycle progression to resume. It is becoming increasingly clear that despite the shared mechanisms of DNA damage detection throughout the cell cycle, the checkpoint and its reversal are precisely tuned to each cell cycle phase. Furthermore, recent findings challenge the dogmatic view that complete repair is a precondition for cell cycle resumption. In this Commentary, we highlight cell-cycle-dependent differences in checkpoint signalling and recovery after a DNA DSB, and summarise the molecular mechanisms that underlie the reversal of DNA damage checkpoints, before discussing when and how cell fate decisions after a DSB are made.

USP17- and SCFβTrCP--regulated degradation of DEC1 controls the DNA damage response

In response to genotoxic stress, DNA damage checkpoints maintain the integrity of the genome by delaying cell cycle progression to allow for DNA repair. Here we show that the degradation of the basic helix-loop-helix (bHLH) transcription factor DEC1, a critical regulator of cell fate and circadian rhythms, controls the DNA damage response. During unperturbed cell cycles, DEC1 is a highly unstable protein that is targeted for proteasome-dependent degradation by the SCF(βTrCP) ubiquitin ligase in cooperation with CK1. Upon DNA damage, DEC1 is rapidly induced in an ATM/ATR-dependent manner. DEC1 induction results from protein stabilization via a mechanism that requires the USP17 ubiquitin protease. USP17 binds and deubiquitylates DEC1, markedly extending its half-life. Subsequently, during checkpoint recovery, DEC1 proteolysis is reestablished through βTrCP-dependent ubiquitylation. Expression of a degradation-resistant DEC1 mutant prevents checkpoint recovery by inhibiting the downregulation of p53. These results indicate that the regulated degradation of DEC1 is a key factor controlling the DNA damage response.

System level dynamics of post-translational modifications

Attempts to characterize cellular behaviors with static, univariate measurements cannot fully capture biological complexity and lead to an inadequate interpretation of cellular processes. Significant biological insight can be gleaned by considering the contribution of dynamic protein post-translational modifications (PTMs) utilizing systems-level quantitative analysis. High-resolution mass spectrometry coupled with computational modeling of dynamic signal-response relationships is a powerful tool to reveal PTM-mediated regulatory networks. Recent advances using this approach have defined network kinetics of growth factor signaling pathways, identified systems level responses to cytotoxic perturbations, elucidated kinase-substrate relationships, and unraveled the dynamics of PTM cross-talk. Innovations in multiplex measurement capacity, PTM annotation accuracy, and computational integration of datasets promise enhanced resolution of dynamic PTM networks and further insight into biological intricacies.

Inhibition of mTORC1 by astrin and stress granules prevents apoptosis in cancer cells

Mammalian target of rapamycin complex 1 (mTORC1) controls growth and survival in response to metabolic cues. Oxidative stress affects mTORC1 via inhibitory and stimulatory inputs. Whereas downregulation of TSC1-TSC2 activates mTORC1 upon oxidative stress, the molecular mechanism of mTORC1 inhibition remains unknown. Here, we identify astrin as an essential negative mTORC1 regulator in the cellular stress response. Upon stress, astrin inhibits mTORC1 association and recruits the mTORC1 component raptor to stress granules (SGs), thereby preventing mTORC1-hyperactivation-induced apoptosis. In turn, balanced mTORC1 activity enables expression of stress factors. By identifying astrin as a direct molecular link between mTORC1, SG assembly, and the stress response, we establish a unifying model of mTORC1 inhibition and activation upon stress. Importantly, we show that in cancer cells, apoptosis suppression during stress depends on astrin. Being frequently upregulated in tumors, astrin is a potential clinically relevant target to sensitize tumors to apoptosis.