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Biology subjects

James, D. E.

Publications and source records attributed to James, D. E..

23 records · Page 2Linked to original sources

Dynamic modelling of the PI3K/mTOR signalling network uncovers biphasic dependence of mTORC1 activation on the mTORC2 subunit Sin1

The PI3K/mTOR signalling network critically regulates a broad array of important biological processes, including cell growth, metabolism and autophagy. Dysregulation of PI3K/mTOR signalling is associated with a variety of human diseases, including cancer and metabolic disorders. The mechanistic target of rapamycin (mTOR) is a kinase that functions as a core catalytic subunit in two physically and functionally distinct complexes termed mTOR complex 1 (mTORC1) and mTORC2, which also share other common components such as mLTS8 (also known as G{beta}L) and DEPTOR. Despite being the subject of intensive research, a full picture of how mTORC1/2 assembly and activity are coordinated, and how they are functionally connected remain to be fully characterised. This is due primarily to the complex network wiring, featuring a growing number of intricate feedback loops and post-translational modifications, which require quantitative systems-level approaches to decipher. Here, we integrate predictive computational modelling, in vitro experiments and -omics data analysis to elucidate the dynamic and emergent features of the PI3K/mTOR network behavior. We construct new mechanistic models of the network that encapsulate novel critical mechanistic details, including mTORC1/2 coordination by mLTS8 (de)ubiquitination, and Akt-to-mTORC2 positive feedback loop. Model simulations subsequently confirmed by experimental validation revealed a previously unknown biphasic, threshold-gated dependence of mTORC1 activity on the key mTORC2 subunit Sin1, which is robust against cell-to-cell variation in protein expression. Furthermore, our results support the essential role of mLST8 in both mTORC1 and 2 activity, and suggest mLST8 could serve as a viable therapeutic target in breast cancer. Overall, our integrated analyses provide fresh systems-level insights into the dynamic behavior of PI3K/mTOR signalling and shed new light on the complexity of this important network. AUTHOR SUMMARYSignalling networks are the key information-processing machineries that underpin the ability of living cells to respond proportionately to extra- (and intra-) cellular cues. The PI3K/mTOR signalling network is one of the most important signalling networks in human cells that regulates cellular response to hormones such as insulin, yet our understanding of the network behaviour remains far from complete. Here, we employed a highly integrative approach that combines predictive mathematical modelling, biological experimentation, and data analysis to gain novel systems-level insights into PI3K/mTOR signalling. We constructed new mathematical models of this complex network incorporating important regulatory mechanisms. In contrary to commonly held views that mTORC2 lies upstream and is a positive regulator of mTORC1, we found that their relationship is highly nonlinear and dose dependent. This finding has major implications for mTORC2-directed anti-cancer strategies as depending on the cellular contexts, blocking mTORC2 may reduce or even enhance mTORC1 activation, the latter could inadvertently blunt the effect of mTORC2 blockade. Furthermore, our results demonstrate that mLST8 is required for the assembly and activity of both mTOR complexes, and suggest mLST8 is a viable therapeutic target in breast cancer, notably breast cancer.

systems biology↗

PhosR enables processing and functional analysis of phosphoproteomic data

Mass spectrometry (MS)-based phosphoproteomics has revolutionised our ability to profile phosphorylation-based signalling in cells and tissues on a global scale. To infer the action of kinases and signalling pathways in phosphoproteomic experiments, we present PhosR, a set of tools and methodologies implemented in a suite of R packages facilitating comprehensive analysis of phosphoproteomic data. By applying PhosR to both published and new phosphoproteomic datasets, we demonstrate capabilities in data imputation and normalisation using a novel set of stably phosphorylated sites, and in functional analysis for inferring active kinases and signalling pathways. In particular, we introduce a signalome construction method for identifying a collection of signalling modules to summarise and visualise the interaction of kinases and their collective actions on signal transduction. Together, our data and findings demonstrate the utility of PhosR in processing and generating novel biological knowledge from MS-based phosphoproteomic data.

systems biology↗

Discovery of drugs to treat cytokine storm-induced cardiac dysfunction using human cardiac organoids

Cardiac injury and dysfunction occur in COVID-19 patients and increase the risk of mortality. Causes are ill defined, but could be direct cardiac infection and/or inflammation-induced dysfunction. To identify mechanisms and cardio-protective drugs, we use a state-of-the-art pipeline combining human cardiac organoids with phosphoproteomics and single nuclei RNA sequencing. We identify an inflammatory cytokine-storm, a cocktail of interferon gamma, interleukin 1{beta} and poly(I:C), induced diastolic dysfunction. Bromodomain-containing protein 4 is activated along with a viral response that is consistent in both human cardiac organoids and hearts of SARS-CoV-2 infected K18-hACE2 mice. Bromodomain and extraterminal family inhibitors (BETi) recover dysfunction in hCO and completely prevent cardiac dysfunction and death in a mouse cytokine-storm model. Additionally, BETi decreases transcription of genes in the viral response, decreases ACE2 expression and reduces SARS-CoV-2 infection of cardiomyocytes. Together, BETi, including the FDA breakthrough designated drug apabetalone, are promising candidates to prevent COVID-19 mediated cardiac damage.

cell biology↗

Genome-wide analysis of diet and gene interactions in Drosophila uncovers the glucose transporter, CG4607, as a diet-responsive gene.

Genetic and environmental factors play a major role in metabolic health. However, they do not act in isolation, as a change in an environmental factor such as diet may exert different effects based on an individuals genotype. Here, we sought to understand how such gene-diet interactions influenced nutrient storage and utilisation, a major determinant of metabolic disease. We subjected the Drosophila Genetic Reference Panel (DGRP), comprising 200 genetically divergent inbred fly strains, to diets varying in sugar, fat and protein. We assessed starvation resistance, a holistic phenotype of nutrient storage and utilisation that can be robustly measured. Diet influenced the starvation resistance of each strain, but this effect varied markedly between strains. This demonstrates that genetics plays a major role in the response to diet. Furthermore, heritability analysis revealed that the greatest variability arose from diets either high in sugar or high in protein. To uncover the genetic underpinnings of this variation, we mapped 1,239 diet-responsive SNPs in 534 genes, 325 of which have human orthologues. Using whole-body knockdown, we confirmed that 30 candidate genes were required for glucose tolerance, storage and utilization. In particular, we characterised CG4607, a GLUT6/GLUT8 homolog, as a key protein involved in sugar tolerance. Overall, this provides strong evidence that genetics is a major contributor to how individuals respond to diets of varying nutrient composition. It is likely that a similar principle may be applied to metabolic disease in higher organisms thus supporting the case for nutrigenomics as an important health strategy.

genetics↗

Multi-Omic Profiling Reveals Dynamics of the Phased Progression of Pluripotency

Pluripotency is highly dynamic and progresses through a continuum of pluripotent stem-cell states. The two states that bookend the pluripotency continuum, naive and primed, are well characterized, but our understanding of the intermediate states and transitions between them remain incomplete. Here, we dissect the dynamics of pluripotent state transitions underlying pre-to post-implantation epiblast differentiation. Through comprehensive mapping of the proteome, phosphoproteome, transcriptome, and epigenome of mouse embryonic stem cells transitioning from naive to primed pluripotency, we find that rapid, acute, and widespread changes to the phosphoproteome precede ordered changes to the epigenome, transcriptome, and proteome. Reconstruction of kinase-substrate networks reveals signaling cascades, dynamics, and crosstalk. Distinct waves of global proteomic changes demarcate discrete phases of pluripotency, characterized by cell-state-specific surface marker expression. Our data provide new insights into the multi-layered control of the phased progression of pluripotency and a foundation for modeling mechanisms underlying pre-to post-implantation epiblast differentiation.\n\nHIGHLIGHTSO_LIMulti-ome maps of cells transitioning from naive to primed pluripotency\nC_LIO_LIPhosphoproteome dynamics precede changes to epigenome, transcriptome, and proteome\nC_LIO_LIKinase-substrate network reconstruction uncovers signaling dynamics and crosstalk\nC_LIO_LIProteins and cell surface markers that track pluripotent state transitions\nC_LIO_LIComparative analysis of mouse and human pluripotent states\nC_LI

genomics↗