Biology subjects

Newman, T.

Publications and source records attributed to Newman, T..

4 recordsLinked to original sources

bioRxiv2024

THE IMPACT OF EXPERIMENTAL DESIGNS & SYSTEM SLOPPINESS ON THE PERSONALISATION PROCESS: A CARDIOVASCULAR PERSPECTIVE

To employ a reduced-order cardiovascular model as a digital twin for personalised medicine, it is essential to understand how uncertainties in the models input parameters affect its outputs. The aim is to identify a set of input parameters that can serve as clinical biomarkers, providing insight into a patients physiological state. Given the challenge of finding useful clinical data, careful consideration must be given to the experimental design used to acquire patient-specific input parameters. In this paper, we conduct the first quantification of a cardiovascular systems sloppiness to elucidate the structure of the input parameter space. By utilising Sobol indices and examining various synthetic cardiovascular measures with increasing invasiveness, we uncover how the personalisation process and the cardiovascular systems sloppiness are contingent upon the chosen experimental design. Our findings reveal that continuous clinical measures induce system sloppiness and increase the number of personalisable biomarkers, whereas discrete clinical measurements produce a non-sloppy system with a reduced number of biomarkers. This study underscores the necessity for careful consideration of available clinical data as differing measurement sets can significantly impact model personalisation. Author SummaryIn personalised medicine, computational models that replicate physical systems -- are becoming vital tools for understanding and predicting individual health. Our study explores cardiovascular models, which simulate heart and circulatory functions from which clinical metrics may be derived. These models aim to provide personalised insights into heart health and treatment planning. A key challenge in building these models is addressing "sloppiness," a property which provides vital insight into the response surface structure for which one calibrates a model searching for a global minimum point, a position in parameter space which best represents a patients cardiovascular health. In order to personalise a model different types of clinical metrics must be available for a model response to be compared to. We examined how different types of clinical data -- ranging from simple discrete blood pressure readings to detailed invasive continuous waveform data -- impact model sloppiness and the number of personalisable biomarkers. Our results show that continuous measurements increase the number of personalisable biomarkers but make the personalisation process more complex through increased sloppiness. In contrast, simpler discrete measurements reduce model sloppiness simplifying the personalisation process but yield fewer personalisable biomarkers. By analysing the impact of experimental designs on the personalisation process, our work offers practical insights into improving the reliability of cardiovascular digital twins, supporting their adoption in personalised medicine.

systems biology↗

bioRxiv2020

In silico prediction of COVID-19 test efficiency with DinoKnot

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus spreading across the world causing the disease COVID-19. The diagnosis of COVID-19 is done by quantitative reverse-transcription polymer chain reaction (qRT-PCR) testing which utilizes different primer-probe sets depending on the assay used. Using in silico analysis we aimed to determine how the secondary structure of the SARS-CoV-2 RNA genome affects the interaction between the reverse primer during qRT-PCR and how it relates to the experimental primer-probe test efficiencies. We introduce the program DinoKnot (Duplex Interaction of Nucleic acids with pseudoKnots) that follows the hierarchical folding hypothesis to predict the secondary structure of two interacting nucleic acid strands (DNA/RNA) of similar or different type. DinoKnot is the first program that utilizes stable stems in both strands as a guide to find the structure of their interaction. Using DinoKnot we predicted the interaction of the reverse primers used in four common COVID-19 qRT-PCR tests with the SARS-CoV-2 RNA genome. In addition, we predicted how 12 mutations in the primer/probe binding region may affect the primer/probe ability and subsequent SARS-CoV-2 detection. While we found all reverse primers are capable of interacting with their target area, we identified partial mismatching between the SARS-CoV-2 genome and some reverse primers. We predicted three mutations that may prevent primer binding, reducing the ability for SARS-CoV-2 detection. We believe our contributions can aid in the design of a more sensitive SARS-CoV-2 test. Author summaryThe current testing for the disease COVID-19 that is caused by the novel cornonavirus SARS-CoV-2 uses oligonucleotides called primers that bind to specific target regions on the SARS-CoV-2 genome to detect the virus. Our goal was to use computational tools to predict how the structure of the SARS-CoV-2 RNA genome affects the ability of the primers to bind to their target region. We introduce the program DinoKnot (Duplex interaction of nucleic acids with pseudoknots) that is able to predict the interactions between two DNA or RNA molecules. We used DinoKnot to predict the efficiency of four common COVID-19 tests, and the effect of mutations in the SARS-CoV-2 virus on ability of the COVID-19 tests in detecting those strains. We predict partial mismatching between some primers and the SARS-CoV-2 genome but that all primers are capable of interacting with their target areas. We also predict three mutations that prevent primer binding and thus SARS-CoV-2 detection. We discuss the limitations of the current COVID-19 testing and suggest the design of a more sensitive COVID-19 test that can be aided by our findings.

bioinformatics↗

bioRxiv2019

On the expression of co-operative feeding behaviour in 3rd instar Drosophila melanogaster larvae

Under poor nutritional conditions, 3rd instar Drosophila melanogaster larvae will work collaboratively in feeding clusters to obtain resources that cannot be reached individually. To better understand the conditions that influence the expression of this behaviour we examined the frequencies, the size and the membership in vials of flies that were initially seeded with either 100 or 200 eggs each using flies from both a large, outbred population and a replicate population that was homozygous for the bw allele. Overall, more feeding clusters, containing more larval participants were observed in the higher density vials compared to the lower density vials, consistent with the idea that this social behaviour is a response to dwindling resources in the environment. The presence of the bw allele did not result in greater egg-to-adult mortality, nor did it result in lower participation in feeding clusters.

evolutionary biology↗

bioRxiv2017

Faster Growth With Shorter Antigens Explains A VSG Hierarchy During African Trypanosome Infections: A Feint Attack By Parasites

The parasitic African trypanosome, Trypanosoma brucei, evades the adaptive host immune response by a process of antigenic variation that involves the clonal switching of variant surface glycoproteins (VSGs). The VSGs that periodically come to dominate in vivo display a hierarchy, but how this hierarchy arises is not well-understood. Combining publicly available genetic data with mathematical modelling, we report a VSG-length-dependent hierarchical timing of clonal VSG dominance in a mouse model, revealing an inverse correlation between VSG length and trypanosome growth-rate. Our analysis indicates that, among parasites switching to new VSGs, those expressing shorter VSGs preferentially accumulate to a detectable level that is sufficient to trigger an effective immune response. Subsequent elimination of faster-growing parasites then allows slower parasites with longer VSGs to accumulate. This interaction between the host and parasite is able by itself to explain the temporal distribution of VSGs observed in vivo. Thus, our findings reveal a length-dependent hierarchy that operates during T. brucei infection, representing a feint attack diversion tactic utilised during infection by these persistent parasites to out-maneuver the host immune system.\n\nSignificance StatementThe protozoan parasite Trypanosoma brucei causes devastating and lethal diseases in humans and livestock. This parasite continuously evades the host adaptive immune response by drawing on a library of variant surface proteins but the mechanisms determining the timing of surface protein - host interactions are not understood. We report a simple mechanism, based on differential growth of parasites with surface proteins of different lengths, which can explain the hierarchy of variants over time. This allows parasites to evade host immune responses for extended timeframes using limited cohorts of surface proteins. We liken this strategy to a military feint attack, that enhances the parasites ability to evade the host immune response. A similar mechanism may also operate in other important pathogens.

systems biology↗