Biology subjects

Sharp, J. A.

Publications and source records attributed to Sharp, J. A..

7 recordsLinked to original sources

bioRxiv2025

Role of the SAF-A/HNRNPU ATPase and RGG domains in X chromosome inactivation, nuclear dynamics, transcription, splicing, and cell proliferation

The SAF-A/HNRNPU gene encodes an abundant nuclear protein conserved throughout vertebrates, and is mutated in individuals with HNRNPU syndrome, a neurological human disease. SAF-A is important for maintaining lncRNA localization, splicing, and gene expression state. The mechanistic role of SAF-A in each of these processes is coordinated by one or more of its functional domains, which include an N-terminal SAP domain, a central ATPase domain, and a series of C-terminal RGG repeats embedded in a low-complexity region. The SAP domain and RGG repeats define two nucleic acid interaction domains, with both capable of binding DNA or RNA. Here we use an allelic reconstitution strategy to investigate the role of the SAF-A ATPase domain and RGG repeats. We show that both the ATPase and RGG repeats control SAF-A nuclear dynamics, and present genetic evidence that SAF-A interacts with nascent transcripts through the RGG repeats. The SAF-A ATPase domain and RGG repeats were also required for maintaining XIST RNA and facultative heterochromatin marks on the inactive X chromosome, with distinct effects of mutations that block ATP binding and ATP hydrolysis. Analysis of transcriptome datasets revealed that the SAF-A ATPase domain and RGG repeats are both required for proper mRNA splicing, but not for gene expression. Importantly, we found that like the SAP domain, the SAF-A ATPase domain and RGG repeats are required for cell proliferation. Collectively, our findings highlight the importance of the SAF-A SAP, ATPase and RGG domains in essential functions of nuclear biology. These analyses will therefore inform our understanding of the disease state in HNRNPU syndrome.

cell biology↗

bioRxiv2024

Role of the SAF-A SAP domain in X inactivation, transcription, splicing, and cell proliferation

SAF-A is conserved throughout vertebrates and has emerged as an important factor regulating a multitude of nuclear functions, including lncRNA localization, gene expression, and splicing. SAF-A has several functional domains, including an N-terminal SAP domain that binds directly to DNA. Phosphorylation of SAP domain serines S14 and S26 are important for SAF-A localization and function during mitosis, however whether these serines are involved in interphase functions of SAF-A is not known. In this study we tested for the role of the SAP domain, and SAP domain serines S14 and S26 in X chromosome inactivation, protein dynamics, gene expression, splicing, and cell proliferation. Here we show that the SAP domain serines S14 and S26 are required to maintain XIST RNA localization and polycomb-dependent histone modifications on the inactive X chromosome in female cells. In addition, we present evidence that an Xi localization signal resides in the SAP domain. We found that that the SAP domain is not required to maintain gene expression and plays only a minor role in mRNA splicing. In contrast, the SAF-A SAP domain, in particular serines S14 and S26, are required for normal protein dynamics, and to maintain normal cell proliferation. We propose a model whereby dynamic phosphorylation of SAF-A serines S14 and S26 mediates rapid turnover of SAF-A interactions with DNA during interphase.

cell biology↗

bioRxiv2021

Quantitative analysis of tumour spheroid structure

Tumour spheroids are common in vitro experimental models of avascular tumour growth. Compared with traditional two-dimensional culture, tumour spheroids more closely mimic the avascular tumour microenvironment where spatial differences in nutrient availability strongly influence growth. We show that spheroids initiated using significantly different numbers of cells grow to similar limiting sizes, suggesting that avascular tumours have a limiting structure; in agreement with untested predictions of classical mathematical models of tumour spheroids. We develop a novel mathematical and statistical framework to study the structure of tumour spheroids seeded from cells transduced with fluorescent cell cycle indicators, enabling us to discriminate between arrested and cycling cells and identify an arrested region. Our analysis shows that transient spheroid structure is independent of initial spheroid size, and the limiting structure can be independent of seeding density. Standard experimental protocols compare spheroid size as a function of time; however, our analysis suggests that comparing spheroid structure as a function of overall size produces results that are relatively insensitive to variability in spheroid size. Our experimental observations are made using two melanoma cell lines, but our modelling framework applies across a wide range of spheroid culture conditions and cell lines.

cancer biology↗

bioRxiv2021

Implementation and acceleration of optimal control for systems biology

Optimal control theory provides insight into complex resource allocation decisions. The forward-backward sweep method (FBSM) is an iterative technique commonly implemented to solve two-point boundary value problems (TPBVPs) arising from the application of Pontryagins Maximum Principle (PMP) in optimal control. In this review we discuss the PMP approach to optimal control and the implementation of the FBSM. By conceptualising the FBSM as a fixed point iteration process, we leverage and adapt existing acceleration techniques to improve its rate of convergence. We show that convergence improvement is attainable without prohibitively costly tuning of the acceleration techniques. Further, we demonstrate that these methods can induce convergence where the underlying FBSM fails to converge. All code used in this work to implement the FBSM and acceleration techniques is available on GitHub at https://github.com/Jesse-Sharp/Sharp2021.

systems biology↗

bioRxiv2019

Persistence is an optimal hedging strategy for bacteria in volatile environments

Bacteria invest in a slow-growing subpopulation, called persisters, to ensure survival in the face of uncertainty. This hedging strategy is remarkably similar to financial hedging, where diversifying an investment portfolio protects against economic uncertainty. We provide a new theoretical foundation for understanding cellular hedging by unifying the study of biological population dynamics and the mathematics of financial risk management through optimal control theory. Motivated by the widely accepted role of volatility in the emergence of persistence, we consider several novel models of environmental volatility described by continuous-time stochastic processes. This allows us to study an emergent cellular hedging strategy that maximizes the expected per-capita growth rate of the population. Analytical and simulation results probe the optimal persister strategy, revealing results that are consistent with experimental observations and suggest at new opportunities for experimental investigation and design. Overall, we provide a new way of conceptualising and modelling cellular decision-making in volatile environments by explicitly unifying theory from mathematical biology and finance.

systems biology↗

bioRxiv2019

Designing combination therapies using multiple optimal controls

Strategic management of populations of interacting biological species routinely requires interventions combining multiple treatments or therapies. This is important in key research areas such as ecology, epidemiology, wound healing and oncology. Despite the well developed theory and techniques for determining single optimal controls, there is limited practical guidance supporting implementation of combination therapies. In this work we use optimal control theory to calculate optimal strategies for applying combination therapies to a model of acute myeloid leukaemia. We consider various combinations of continuous and bang-bang (discrete) controls, and we investigate how the control dynamics interact and respond to changes in the weighting and form of the pay-off characterising optimality. We demonstrate that the optimal controls respond non-linearly to treatment strength and control parameters, due to the interactions between species. We discuss challenges in appropriately characterising optimality in a multiple control setting and provide practical guidance for applying multiple optimal controls. Code used in this work to implement multiple optimal controls is available on GitHub.

systems biology↗

bioRxiv2019

Prophase removal of chromosome-associated RNAs facilitates anaphase chromosome segregation

During mitosis, the genome is transformed from a decondensed, transcriptionally active state to a highly condensed, transcriptionally inactive state. Mitotic chromosome reorganization is marked by the general attenuation of transcription on chromosome arms, yet how the cell regulates nuclear and chromatin-associated RNAs after chromosome condensation and nuclear envelope breakdown is unknown. SAF-A/hnRNPU is an abundant nuclear protein with RNA-to-DNA tethering activity, coordinated by two spatially distinct nucleic acid binding domains. Here we show that RNA is evicted from prophase chromosomes through Aurora-B-dependent phosphorylation of the SAF-A DNA-binding domain; failure to execute this pathway leads to accumulation of SAF-A:RNA complexes on mitotic chromosomes and elevated rates of anaphase segregation defects. This work reveals a role for Aurora-B in removing chromatin-associated RNAs during prophase, and demonstrates that Aurora-B dependent relocalization of SAF-A during cell division contributes to the fidelity of chromosome segregation.

cell biology↗