Functional analysis of the stable phosphoproteome reveals cancer vulnerabilities

Phosphoproteomics Uncovers Exercise Intensity-Specific Skeletal Muscle Signaling Networks Underlying High-Intensity Interval Training in Healthy Male Participants

BACKGROUND

In response to exercise, protein kinases and signaling networks are engaged to blunt homeostatic threats generated by acute contraction-induced increases in skeletal muscle energy and oxygen demand, as well as serving roles in the adaptive response to chronic exercise training to blunt future disruptions to homeostasis. High-intensity interval training (HIIT) is a time-efficient exercise modality that induces superior or similar health-promoting skeletal muscle and whole-body adaptations compared with prolonged, moderate-intensity continuous training (MICT). However, the skeletal muscle signaling pathways underlying HIIT's exercise intensity-specific adaptive responses are unknown.

OBJECTIVE

We mapped human muscle kinases, substrates, and signaling pathways activated/deactivated by an acute bout of HIIT versus work-matched MICT.

METHODS

In a randomized crossover trial design (Australian New Zealand Clinical Trials Registry number ACTRN12619000819123; prospectively registered 6 June 2019), ten healthy male participants (age 25.4 ± 3.2 years; BMI 23.5 ± 1.6 kg/m2;V ˙ O 2 max 37.9 ± 5.2 ml/kg/min, mean values ± SD) completed a single bout of HIIT and MICT cycling separated by ≥ 10 days and matched for total work (67.9 ± 10.2 kJ) and duration (10 min). Mass spectrometry-based phosphoproteomic analysis of muscle biopsy samples collected before, during (5 min), and immediately following (10 min) each exercise bout, to map acute temporal signaling responses to HIIT and MICT, identified and quantified 14,931 total phosphopeptides, corresponding to 8509 phosphorylation sites.

RESULTS

Bioinformatic analyses uncovered exercise intensity-specific signaling networks, including > 1000 differentially phosphorylated sites (± 1.5-fold change; adjusted P < 0.05; ≥ 3 participants) after 5 min and 10 min HIIT and/or MICT relative to rest. After 5 and 10 min, 92 and 348 sites were differentially phosphorylated by HIIT, respectively, versus MICT. Plasma lactate concentrations throughout HIIT were higher than MICT (P < 0.05), and correlation analyses identified > 3000 phosphosites significantly correlated with lactate (q < 0.05) including top functional phosphosites underlying metabolic regulation.

CONCLUSIONS

Collectively, this first global map of the work-matched HIIT versus MICT signaling networks has revealed rapid exercise intensity-specific regulation of kinases, substrates, and pathways in human skeletal muscle that may contribute to HIIT's skeletal muscle adaptations and health-promoting effects.  Preprint: The preprint version of this work is available on medRxiv, https://doi.org/10:1101/2024.07.11.24310302 .

Positional distribution and conservation of major phosphorylated sites in the human kinome

The human protein kinome is a group of over 500 therapeutically relevant kinases. Exemplified by over 10,000 phosphorylated sites reported in global phosphoproteomes, kinases are also highly regulated by phosphorylation. Currently, 1008 phosphorylated sites in 273 kinases are associated with their regulation of activation/inhibition, and a few in 30 kinases are associated with altered activity. Phosphorylated sites in 196 kinases are related to other molecular functions such as localization and protein interactions. Over 8,000 phosphorylated sites, including all those in 517 kinases are unassigned to any functions. This imposes a significant bias and challenge for the effective analysis of global phosphoproteomics datasets. Hence, we derived a set of stably and frequently detected phosphorylated sites (representative phosphorylated sites) across diverse experimental conditions annotated in the PhosphoSitePlus database and presumed them to be relevant to the human kinase regulatory network. Analysis of these representative phosphorylated sites led to the classification of 449 kinases into four distinct categories (kinases with phosphorylated sites apportioned (PaKD) and enigmatic (PeKD), and those with predominantly within kinase domain (PiKD) and outside kinase domain (PoKD)). Knowledge-based functional analysis and sequence conservation across the family/subfamily identified phosphorylated sites unique to specific kinases that could contribute to their unique functions. This classification of representative kinase phosphorylated sites enhance our understanding of prioritized validation and provides a novel framework for targeted phosphorylated site enrichment approaches. Phosphorylated sites in kinases associated with dysregulation in diseases were frequently located outside the kinase domain, and suggesting their regulatory roles and opportunities for phosphorylated site-directed therapeutic approaches.

No transcription, no problem: Protein phosphorylation changes and the transition from oocyte to embryo

Although mature oocytes are arrested in a differentiated state, they are provisioned with maternally-derived macromolecules that will start embryogenesis. The transition to embryogenesis, called 'egg activation', occurs without new transcription, even though it includes major cell changes like completing stalled meiosis, translating stored mRNAs, cytoskeletal remodeling, and changes to nuclear architecture. In most animals, egg activation is triggered by a rise in free calcium in the egg's cytoplasm, but we are only now beginning to understand how this induces the egg to transition to totipotency and proliferation. Here, we discuss the model that calcium-dependent protein kinases and phosphatases modify the phosphorylation landscape of the maternal proteome to activate the egg. We review recent phosphoproteomic mass spectrometry analyses that revealed broad phospho-regulation during egg activation, both in number of phospho-events and classes of regulated proteins. Our interspecies comparisons of these proteins pinpoints orthologs and protein families that are phospho-regulated in activating eggs, many of which function in hallmark events of egg activation, and others whose regulation and activity warrant further study. Finally, we discuss key phospho-regulating enzymes that may act apically or as intermediates in the phosphorylation cascades during egg activation. Knowing the regulators, targets, and effects of phospho-regulation that cause an egg to initiate embryogenesis is crucial at both fundamental and applied levels for understanding female fertility, embryo development, and cell-state transitions.

SnapKin: a snapshot deep learning ensemble for kinase-substrate prediction from phosphoproteomics data

A major challenge in mass spectrometry-based phosphoproteomics lies in identifying the substrates of kinases, as currently only a small fraction of substrates identified can be confidently linked with a known kinase. Machine learning techniques are promising approaches for leveraging large-scale phosphoproteomics data to computationally predict substrates of kinases. However, the small number of experimentally validated kinase substrates (true positive) and the high data noise in many phosphoproteomics datasets together limit their applicability and utility. Here, we aim to develop advanced kinase-substrate prediction methods to address these challenges. Using a collection of seven large phosphoproteomics datasets, and both traditional and deep learning models, we first demonstrate that a 'pseudo-positive' learning strategy for alleviating small sample size is effective at improving model predictive performance. We next show that a data resampling-based ensemble learning strategy is useful for improving model stability while further enhancing prediction. Lastly, we introduce an ensemble deep learning model ('SnapKin') by incorporating the above two learning strategies into a 'snapshot' ensemble learning algorithm. We propose SnapKin, an ensemble deep learning method, for predicting substrates of kinases from large-scale phosphoproteomics data. We demonstrate that SnapKin consistently outperforms existing methods in kinase-substrate prediction. SnapKin is freely available at https://github.com/PYangLab/SnapKin.

Computational systems approach towards phosphoproteomics and their downstream regulation

Protein phosphorylation plays an essential role in modulating cell signalling and its downstream transcriptional and translational regulations. Until recently, protein phosphorylation has been studied mostly using low-throughput biochemical assays. The advancement of mass spectrometry (MS)-based phosphoproteomics transformed the field by enabling measurement of proteome-wide phosphorylation events, where tens of thousands of phosphosites are routinely identified and quantified in an experiment. This has brought a significant challenge in analysing large-scale phosphoproteomic data, making computational methods and systems approaches integral parts of phosphoproteomics. Previous works have primarily focused on reviewing the experimental techniques in MS-based phosphoproteomics, yet a systematic survey of the computational landscape in this field is still missing. Here, we review computational methods and tools, and systems approaches that have been developed for phosphoproteomics data analysis. We categorise them into four aspects including data processing, functional analysis, phosphoproteome annotation and their integration with other omics, and in each aspect, we discuss the key methods and example studies. Lastly, we highlight some of the potential research directions on which future work would make a significant contribution to this fast-growing field. We hope this review provides a useful snapshot of the field of computational systems phosphoproteomics and stimulates new research that drives future development.