Biology subjects

Johnston, I. G.

Publications and source records attributed to Johnston, I. G..

8 recordsLinked to original sources

bioRxiv2023

The cellular basis of feeding-dependent body size plasticity in sea anemones

Animals with indeterminate growth can adapt their growth rate and body size to changing food availability throughout their lifetime. As the cellular basis underlying food-dependent growth plasticity is poorly understood, we quantified how the sea anemones Nematostella vectensis and Exaiptasia diaphana (Aiptasia) respond to feeding and starvation on organismal and cellular levels. Using mathematical modelling to analyse growth phases, we found that growth and shrinkage rates in Nematostella are exponential, stereotypic and accompanied by high levels of cell gain or loss, respectively. During starvation and re-feeding, a considerable proportion of juvenile polyp cells (>7%) reversibly shift between S/G2/M and G1/G0 cell cycle phases, suggesting a tight nutritional control of quiescence and cell cycle re-entry. In the facultative symbiotic sea anemone Aiptasia, we found that growth and cell proliferation rates are dependent on the symbiotic state and, in comparison to Nematostella, respond less strongly to changes in food supply. Altogether, we provide a benchmark and resource to study the nutritional regulation of body plasticity on molecular, cellular and genomic levels using the rich functional toolkit available for Nematostella. Summary statementFeeding and starvation in sea anemones induce growth and shrinkage, cell size changes and dynamic cell proliferation changes that support a nutritional control of quiescence and cell cycle re-entry.

developmental biology↗

bioRxiv2022

Sorting of plant mitochondrial and plastid heteroplasmy is extremely rapid and depends on MSH1 activity

The fate of new mitochondrial and plastid mutations depends on their ability to persist and spread among the numerous organellar genome copies within a cell (heteroplasmy). The extent to which heteroplasmies are transmitted across generations or eliminated through genetic bottlenecks is not well understood in plants, in part because their low mutation rates make these variants so infrequent. Disruption of MutS Homolog 1 (MSH1), a gene involved in plant organellar DNA repair, results in numerous de novo point mutations, which we used to quantitatively track the inheritance of single nucleotide variants in mitochondrial and plastid genomes in Arabidopsis. We found that heteroplasmic sorting (the fixation or loss of a variant) was rapid for both organelles, greatly exceeding rates observed in animals. In msh1 mutants, plastid variants sorted faster than those in mitochondria and were typically fixed or lost within a single generation. Effective transmission bottleneck sizes for plastids and mitochondria were N {approx} 1 and 4, respectively. Restoring MSH1 function further increased the rate of heteroplasmic sorting in mitochondria (N {approx} 1.3), potentially due to its hypothesized role in promoting gene conversion as a mechanism of DNA repair, which is expected to homogenize genome copies within a cell. Heteroplasmic sorting also favored GC base pairs. Therefore, recombinational repair and gene conversion in plant organellar genomes can potentially accelerate the elimination of heteroplasmies and bias the outcome of this sorting process. Significance statementMitochondria and plastids play essential roles in eukaryotic life; thus, mutations in these organellar genomes can have severe consequences. In animals, early germline sequestration creates genetic "bottlenecks" providing cell-to-cell variance in mitochondrial mutations upon which selection can act. However, the dynamics of organellar mutations in plants and other organisms that lack early germline segregation remain unclear. Here, we show that sorting of mutations in plant organellar genomes proceeds very rapidly - much faster than in animals. In mitochondria, this process is accelerated by MSH1, a gene involved in recombination and repair of organellar genomes. This suggests that in plants, recombinational repair creates cell-to-cell variance in the frequency of organellar mutations, facilitating selection in the absence of a classical germline bottleneck.

plant biology↗

bioRxiv2021

Universal features shaping organelle gene retention

Mitochondria and plastids power complex life, and retain their own organelle DNA (oDNA) genomes, with highly reduced gene contents compared to their endosymbiont ancestors. Why some protein-coding genes are retained in oDNA and some lost remains a debated question. Here we harness over 15k oDNA sequences and over 300 whole genome sequences with tools from structural biology, bioinformatics, machine learning, and Bayesian model selection to reveal the properties of genes, and associated underlying mechanisms, that shape oDNA evolution. Striking symmetry exists between the two organelle types: gene retention patterns in both are predicted by the hydrophobicity of a protein product and its energetic centrality within its protein complex, with additional influences of nucleic acid and amino acid biochemistry. Remarkably, retention principles from one organelle type successfully and quantitatively predict retention in the other, supporting this universality; these principles also distinguish gene profiles in independent endosymbiotic relationships. The identification of these features shaping organelle gene retention both provides quantitative support for several existing evolutionary hypotheses, and suggests new biochemical and biophysical mechanisms influencing organelle genome evolution.

evolutionary biology↗

bioRxiv2019

Intracellular Energy Variability Modulates Cellular Decision-Making Capacity

Cells are able to generate phenotypic diversity both during development and in response to stressful and changing environments, aiding survival. The biologically and medically vital process of a cell assuming a functionally important fate from a range of phenotypic possibilities can be thought of as a cell decision. To make these decisions, a cell relies on energy dependent pathways of signalling and expression. However, energy availability is often overlooked as a modulator of cellular decision-making. As cells can vary dramatically in energy availability, this limits our knowledge of how this key biological axis affects cell behaviour. Here, we consider the energy dependence of a highly generalisable decision-making regulatory network, and show that energy variability changes the sets of decisions a cell can make and the ease with which they can be made. Increasing intracellular energy levels can increase the number of stable phenotypes it can generate, corresponding to increased decision-making capacity. For this decision-making architecture, a cell with intracellular energy below a threshold is limited to a singular phenotype, potentially forcing the adoption of a specific cell fate. We suggest that common energetic differences between cells may explain some of the observed variability in cellular decision-making, and demonstrate the importance of considering energy levels in several diverse biological decision-making phenomena.

systems biology↗

bioRxiv2018

Precision identification and prediction of high mortality phenotypes and disease progression pathways in severe malaria without requiring longitudinal data

The parasite Plasmodium falciparum is the main cause of severe malaria (SM). Despite treatment with antimalarial drugs, more than 450,000 SM deaths are reported every year, mainly in African children. The diversity of clinical presentations associated with SM indicate important differences in disease pathogenesis that often require specific treatment, and this clinical heterogeneity of SM is largely unresolved. In this study, we apply new machine learning and inference tools for large-scale data analysis to dissect the heterogeneity in patterns of clinical features associated with SM in 2,695 Gambian children admitted to hospital with Plasmodium falciparum malaria. This quantitative analysis, including the powerful HyperTraPS algorithm for inference of progressive processes, reveals pathways of SM symptom progression and features predicting the severity of individual patient outcomes. Notably, our approach allows the identification and dissection of disease progression pathways without the need for longitudinal observations. Learning these pathways and features from this rich dataset allows us to construct several quantitative measures of the mortality risk associated with a patient presenting with a given set of symptoms. By independently surveying expert practitioners, we show that this data-driven approach agrees with and expands the current state of knowledge on malaria progression, while simultaneously providing a data-supported framework for predicting clinical risk.

pathology↗

bioRxiv2018

Mitochondrial network fragmentation modulates mutant mtDNA accumulation independently of absolute fission-fusion rates

Mitochondrial DNA (mtDNA) mutations cause severe congenital diseases but may also be associated with healthy aging. MtDNA is stochastically replicated and degraded, and exists within organelles which undergo dynamic fusion and fission. The role of the resulting mitochondrial networks in the time evolution of the cellular proportion of mutated mtDNA molecules (heteroplasmy), and cell-to-cell variability in heteroplasmy (heteroplasmy variance), remains incompletely understood. Heteroplasmy variance is particularly important since it modulates the number of pathological cells in a tissue. Here, we provide the first wide-reaching theoretical framework which bridges mitochondrial network and genetic states. We show that, under a range of conditions, the (genetic) rate of increase in heteroplasmy variance and de novo mutation are proportionally modulated by the (physical) fraction of unfused mitochondria, independently of the absolute fission-fusion rate. In the context of selective fusion, we show that intermediate fusion/fission ratios are optimal for the clearance of mtDNA mutants. Our findings imply that modulating network state, mitophagy rate and copy number to slow down heteroplasmy dynamics when mean heteroplasmy is low could have therapeutic advantages for mitochondrial disease and healthy aging.

cell biology↗

bioRxiv2018

Inferring high-dimensional pathways of trait acquisition in evolution and disease

The explosion of data throughout the sciences provides unprecedented opportunities to learn about the dynamics of evolution and disease progression. Here, we describe a highly generalisable statistical platform to infer the dynamic pathways by which many, potentially interacting, discrete traits are acquired or lost over time in biological processes. The platform uses HyperTraPS (hypercubic transition path sampling) to learn progression pathways from cross-sectional, longitudinal, or phylogenetically-linked data with unprecedented efficiency, readily distinguishing multiple competing pathways, and identifying the most parsimonious mechanisms underlying given observations. Its Bayesian structure quantifies uncertainty in pathway structure and allows interpretable predictions of behaviours, such as which symptom a patient will acquire next. We exploit the models topology to provide visualisation tools for intuitive assessment of multiple, variable pathways. We apply the method to ovarian cancer progression and the evolution of multidrug resistance in tuberculosis, demonstrating its power to reveal previously undetected dynamic pathways.

bioinformatics↗

bioRxiv2017

Energetic Costs Of Cellular And Therapeutic Control Of Stochastic mtDNA Populations

Mitochondrial DNA (mtDNA) copy numbers fluctuate over time due to stochastic cellular dynamics. Understanding mtDNA dynamics and the accumulation of mutations is vital for understanding mitochondrial-related diseases. Here, we use stochastic modelling to derive general results for the impact of cellular control on mtDNA populations, the cost to the cell of different mtDNA states, and the optimisation of therapeutic control of mtDNA populations. We provide theoretical evidence that an increasing mtDNA variance can increase the energetic cost of maintaining a tissue, that intermediate levels of heteroplasmy can be more detrimental than ho-moplasmy even for a dysfunctional mutant, that het-eroplasmy distribution (not mean alone) is crucial for the success of gene therapies, and that long-term rather than short intense gene therapies are more likely to beneficially impact mtDNA populations. New experiments validate our predictions on heteroplasmy dependence of therapeutic outcomes.

cell biology↗