Biology subjects

Tsaneva-Atanasova, K.

Publications and source records attributed to Tsaneva-Atanasova, K..

25 records · Page 2Linked to original sources

bioRxiv2020

Dynamic modulation of glucose utilisation by glucocorticoid rhythms in health and disease

A systems level coordination of physiological rhythms is essential to sustain healthy states, especially in the face of stimuli that may disrupt such rhythms. The timing of meals, medication and chronic stress can profoundly influence metabolism, which depends on the dynamic interactions between glucose, insulin and cortisol. Although the metabolic and stress endocrine axes are simultaneously disrupted in many diseases, a theoretical framework to understand how chronodisruption leads to disease is lacking. By developing a mathematical model of glucose utilisation that accounts for the antagonism between insulin and cortisol, we investigate the dynamic effects of glucose boluses under normal and disrupted cortisol rhythms, including the effects of cortisol agonists and antagonists. We also predict how cortisol rhythms modulate circadian responses to oral glucose diagnostic tests, and analyse the disruptions caused by hypercortisolism. Finally, we predict the mechanisms leading to type 2 diabetes in patients with normal and excess cortisol.

systems biology↗

bioRxiv2019

Label-free single-cell microfluidics reveals antibiotic transport kinetics in Gram-negative bacteria

The double-membrane cell envelope of Gram-negative bacteria is a formidable barrier to intracellular antibiotic accumulation. A quantitative understanding of antibiotic transport in these cells is crucial for drug development, but this has proved elusive due to the complexity of the problem and a dearth of suitable investigative techniques. Here we combine microfluidics and time-lapse auto-fluorescence microscopy to quantify antibiotic uptake label-free in hundreds of individual Escherichia coli cells. By manipulating the microenvironment, we showed that drug (ofloxacin) accumulation is higher in growing versus non-growing cells. Using genetic knockouts, we provide the first direct evidence that growth phase is more important for drug accumulation than the presence or absence of individual transport pathways. We use our experimental results to inform a mathematical model that predicts drug accumulation kinetics in subcellular compartments. These novel experimental and theoretical results pave the way for the rational design of new Gram-negative antibiotics.

biophysics↗

bioRxiv2018

GeTallele: a mathematical model and a toolbox for integrative analysis and visualization of DNA and RNA allele frequencies

BackgroundAsymmetric allele expression typically indicates functional and/or structural features associated with the underlying genetic variants. When integrated, RNA and DNA allele frequencies can reveal patterns characteristic of a wide-range of biological traits, including ploidy changes, genome admixture, allele-specific expression and gene-dosage transcriptional response. ResultsTo assess RNA and DNA allele frequencies from matched sequencing datasets, we introduce a method for generating model distributions of variant allele frequencies (VAF) with a given variant read probability. In contrast to other methods, based on whole sequences or single SNV, proposed methodology uses continuous multi-SNV genomic regions. The methodology is implemented in a GeTallele toolbox that provides a suite of functions for integrative analysis, statistical assessment and visualization of Genome and Transcriptome allele frequencies. Using model VAF probabilities, GeTallele allows estimation and comparison of variant read probabilities (VAF distributions) in a sequencing dataset. We demonstrate this functionality across cancer DNA and RNA sequencing datasets. ConclusionBased on our evaluation, variant read probabilities can serve as a dependable indicator to assess gene and chromosomal allele asymmetries and to aid calls of genomic events in matched sequencing RNA and DNA datasets. ContactP.M.Slowinski@exeter.ac.uk

bioinformatics↗

bioRxiv2018

ReQTL - an allele-level measure of variation-expression genomic relationships

MotivationBy testing for association of DNA genotypes with gene expression levels, expression quantitative trait locus (eQTL) analyses have been instrumental in understanding how thousands of single nucleotide variants (SNVs) may affect gene expression. As compared to DNA genotypes, RNA genetic variation represents a phenotypic trait that reflects the actual allele content of the studied system. RNA genetic variation can be measured at expressed genome regions, and differs from the DNA genotype in sites subjected to regulatory forces. Therefore, assessment of correlation between RNA genetic variation and gene expression can reveal regulatory genomic relationships in addition to eQTLs.\n\nResultsWe introduce ReQTL, an eQTL modification which substitutes the DNA allele count for the variant allele frequency (VAF) at expressed SNV loci in the transcriptome. We exemplify the method on sets of RNA-sequencing data from human tissues obtained though the Genotype-Tissue Expression Project (GTEx) and demonstrate that ReQTL analyses show consistently high performance and sufficient power to identify both previously known and novel molecular associations. The majority of the SNVs implicated in significant cis-ReQTLs identified by our analysis were previously reported as significant cis-eQTL loci. Notably, trans ReQTL loci in our data were substantially enriched in RNA-editing sites. In summary, ReQTL analyses are computationally feasible and do not require matched DNA data, hence they have a high potential to facilitate the discovery of novel molecular interactions through exploration of the increasingly accessible RNA-sequencing datasets.\n\nAvailability and implementationSample scripts used in our ReQTL analyses are available with the Supplementary Material (ReQTL_sample_code).\n\nContacthorvatha@gwu.edu or lfspurr@gwmail.gwu.edu\n\nSupplementary InformationRe_QTL_Supplementary_Data.zip

genomics↗

bioRxiv2018

A mathematical model of the hypothalamic network controlling the ultradian secretion of reproductive hormones.

Fertility critically depends on the gonadotropin-releasing hormone (GnRH) pulse generator, a neural construct comprised of hypothalamic neurons co-expressing kisspeptin, neurokoinin-B and dynorphin that drives the pulsatile release of GnRH. How this neural network generates and controls the appropriate ultradian frequency essential for gametogenesis and ovulation is unknown. Here, we present a mathematical model of the GnRH pulse generator with theoretical evidence and in vivo experimental data showing that robust pulsatile release of luteinizing hormone, a proxy for GnRH, emerges abruptly as we increase the basal activity of the neuronal network using continuous low frequency optogenetic stimulation of the neural construct. Further increases in basal activity markedly increase pulse frequency. Model predictions that such behaviors are concomitant of non-linear positive and negative feedback interactions mediated through neurokinin-B and dynorphin signaling respectively are confirmed neuropharmacologically. Our mathematical model sheds light on the long-elusive GnRH pulse generator offering new horizons for fertility regulation.

physiology↗

bioRxiv2017

Acetylcholine reconfigures hippocampal circuits to enable rapid formation of overlapping memory ensembles

In the hippocampus, episodic memories are thought to be encoded by the formation of ensembles of synaptically coupled CA3 pyramidal cells driven by sparse but powerful mossy fiber inputs from dentate gyrus granule cells. Since CA3 network capacity is finite, a mechanism for enhancing memory encoding during important events would ensure greater efficiency, but the salient signal that might determine this memory selectivity filter is unknown. Using experimental and computational methods we show that the cholinergic system can operate as a memory selectivity filter by combining 3 separate mechanisms: disinhibition of feed-forward mossy fiber inhibition enables synaptic plasticity at CA3-CA3 recurrent synapses; Increasing cellular excitability lowers the threshold for ensemble formation; Reduction of overall CA3-CA3 recurrent synapse strength allows for an increase in overlap between ensembles. Thus, we show that acetylcholine release enables the selective encoding of salient high-density episodic memories in the hippocampus.

neuroscience↗

bioRxiv2017

Modelling of the cardiopulmonary responses to maximal aerobic exercise in patients with cystic fibrosis

Cystic fibrosis (CF) is a debilitating chronic condition, which requires complex and expensive disease management. Exercise has now been recognised as a critical factor in improving health and quality of life in patients with CF. Hence, cardiopulmonary exercise testing (CPET) is used to determine aerobic fitness of young patients as part of the clinical management of CF. However, at present there is a lack of conclusive evidence for one limiting system of aerobic fitness for CF patients at an individual patient level.\n\nHere, we perform detailed data analysis that allows us to identify important systems-level factors that affect aerobic fitness. We use patients data and principal component analysis to confirm the dependence of CPET performance on variables associated with ventilation and metabolic rates of oxygen consumption. We find that the time at which participants cross the anaerobic threshold (AT) is well correlated with their overall performance. Furthermore, we propose a predictive modelling framework that captures the relationship between ventilatory dynamics, lung capacity and function and performance in CPET within a group of children and adolescents with CF. Specifically, we show that using Gaussian processes (GP) we can predict AT at the individual patient level with reasonable accuracy given the small sample size of the available group of patients. We conclude by presenting future perspectives for improving and extending the proposed framework.\n\nOur modelling and analysis have the potential to pave the way to designing personalised exercise programmes that are tailored to specific individual needs relative to patients treatment therapies.

physiology↗