Biology subjects

Groves, T.

Publications and source records attributed to Groves, T..

7 recordsLinked to original sources

bioRxiv2026

Improved Metabolic Flux Estimations through Compositional Data Analysis

Isotopic Metabolic Flux Analysis (I-MFA) is a standard approach for estimating intracellular metabolic fluxes. I-MFA infers fluxes by comparing simulated and measured metabolite isotopologue distributions (MIDs) of metabolites from isotope labeling experiments. MIDs represent fractional abundances that strictly sum to one for any given metabolite, thus they are inherently compositional data. However, state-of-the-art estimation approaches rely on calculating standard Euclidean distances between MIDs in a non-compositional paradigm, introducing a systemic bias. To resolve this, our study proposes compositional I-MFA. We demonstrate how to construct a meaningful orthonormal basis for MIDs via ordered sequential binary partitioning, which can be used to perform isometric log-ratio (ILR) transformation. As a minimal change to existing I-MFA workflows, we suggest estimating fluxes by minimizing Euclidean distances between ILR-transformed MIDs. We validated this framework against traditional methods using both a toy model and a biologically realistic model, evaluating point estimates, sensitivity across varied true fluxes, and confidence intervals. In the two examples, compositional I-MFA consistently outperformed traditional approaches, reducing mean squared error of flux point estimates by an average of 42.6% and substantially narrowing confidence intervals. We conclude that compositional data analysis significantly improves I-MFA and can be implemented as a simple drop-in replacement for current pipelines. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/742769v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1792c69org.highwire.dtl.DTLVardef@52b5beorg.highwire.dtl.DTLVardef@19cf29org.highwire.dtl.DTLVardef@6fb6db_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LINew compositional data approach improves metabolic flux estimation. C_LIO_LIThis data transformation requires minimal changes to existing workflows. C_LIO_LIThe new method reduced MSE of flux estimates by 42.6% in two examples tested. C_LIO_LIThe confidence intervals of the estimated fluxes were substantially narrowed. C_LIO_LIEstimation accuracy remained robust across a wide range of metabolic fluxes. C_LI

systems biology↗

bioRxiv2026

Light-dependent metabolism and proteome allocation in Synechocystis sp. PCC 6803: an enzyme-constrained metabolic model across light intensities

Genome-scale metabolic models (GEMs) are widely used to relate genotype to phenotype and to study how organisms respond to their environment, but conventional flux-balance analysis relies on simplifying assumptions that limit its predictive power. Enzyme-constrained models (ecModels) address this by bounding each reaction by the abundance and turnover number of its catalyzing enzyme. Here we reconstruct ecModels of Synechocystis sp. PCC 6803 at light-limited, light-saturated and photoinhibited intensities (27.5, 440 and 1100 {micro}mol photons m-{superscript 2} s-{superscript 1}) to study how light shapes its metabolism and enzyme usage. Using the GECKO framework, we constrained the model first by a total protein pool and then by condition-specific quantitative proteomics. The pool-constrained ecModel reproduced the decline in growth at high light as a consequence of a finite proteome, whereas the unconstrained GEM predicted growth to continue rising. Integrating proteomics reduced the median flux variability across reactions by up to two orders of magnitude relative to the conventional GEM. The enzyme budget was dominated by four subsystems (oxidative phosphorylation, transport, photosynthesis and carbon fixation), which together accounted for close to 70% of the minimum enzyme mass in every condition, and the total mass required tracked growth rate rather than light intensity. Enzyme-usage variability analysis found that only about 40% of usages were uniquely determined, a fraction stable across the light gradient. Enzyme constraints thus improve the models description of light-dependent cyanobacterial metabolism and identify the functional sectors that carry the metabolic protein budget.

systems biology↗

bioRxiv2026

Loss of contractile pericytes and their impaired calcium dynamics exacerbate brain ischemic stroke of awake mice in acute and chronic phases

Ischemic stroke disrupts neurovascular uncoupling, in which neuronal activity fails to evoke appropriate microvascular blood flow responses, despite successful recanalization of upstream arteries. The cellular mechanisms underlying this dysfunction remain poorly defined. We examined Ca{superscript 2} signaling and contractile dynamics of vascular smooth muscle cells, precapillary sphincters and contractile pericytes, using two-photon microscopy and laser speckle imaging in awake mice subjected to transient middle cerebral artery occlusion. During occlusion, precapillary sphincters exhibited pronounced Ca{superscript 2} elevations and constriction, amplifying downstream capillary resistance. Following reperfusion, elevated Ca{superscript 2} signals persisted without proportional diameter changes, indicating early uncoupling between Ca{superscript 2} dynamics and vascular responses. In the chronic phase, loss of precapillary sphincters-associated contractile pericytes was associated with capillary dilation and persistent neurovascular uncoupling. Although partial recovery of pericyte coverage and Ca{superscript 2} activity occurred, stimulus-evoked vascular responses remained blunted. These findings highlight precapillary sphincters as a key contributor to ischemia-induced microvascular dysfunction.

neuroscience↗

bioRxiv2025

Two-photon microscopy of brain endothelial glycocalyx uncovers spatial heterogeneity, vesicular transport, and lectin-binding kinetics in the living brain

The endothelial glycocalyx is a key regulator of cerebrovascular function and remains one of the most difficult structures to study in vivo. Here we uncover new structural and dynamical features of the brain endothelial glycocalyx using in vivo two-photon microscopy. We identified glycocalyx enrichment at endothelial junctions and arteriolar branch points, visualized its Vesicular transport in real-time, and found evidence for its compositional Variations along the arteriovenous axis. Fluorescence recovery after photobleaching revealed two distinct kinetics of wheat germ agglutinin binding, including a previously undescribed one. Finally, super-localization of the glycocalyx estimated glycocalyx thickness as 775{+/-}17 nm and 622{+/-}34 nm before and after enzymatic shedding, reconciling discrepancies between past optical and electron microscopy estimates. Together these findings establish the first miltiscale framework of glycocalyx distribution and heterogeneity, transport, and molecular interaction kinetics in the living brain.

neuroscience↗

bioRxiv2025

Bayesian Independent Component Analysis reconstructs independent modules of gene expression

Transcriptional regulation--the modulation of gene expression in response to environmental stimuli--is fundamental to cellular function. Identifying groups of co-regulated genes helps elucidate gene functions and characterize how an organism has evolved to respond to various stimuli. In previous works, signal processing algorithms have been applied to characterize the transcriptional regulatory modes, known as iModulons, of bacteria. However, these methods do not quantify uncertainty of the results and are difficult to integrate with different sources of information. In this work, we propose a Bayesian model of Independent Component Analysis that addresses these issues by providing a formal structure to quantify the uncertainty of gene activations and membership of co-regulated genes, achieving state-of-the-art alignment with known regulators. Furthermore, we expand this Bayesian model to explain and integrate first multi-strain and then multi-omics data. Author summaryUnderstanding how genes are turned on and off is crucial for deciphering how living organisms respond to their environment. Genes often work together in groups, and identifying these co-regulated groups can reveal their functions and how organisms adapt to changes. Previous methods have used complex mathematical techniques to find these gene groups in bacteria, but they come with limitations: they do not measure how confident we can be in the results and are hard to combine with other types of biological information. In our study, we introduce a new approach using Bayesian statistics to overcome these challenges. This method not only helps us identify groups of co-regulated genes more accurately but also allows us to quantify our confidence in these findings. Additionally, our approach can easily integrate different kinds of data, such as information from various bacterial strains or other biological processes. This makes our method a powerful tool for exploring gene regulation, with potential applications in understanding diseases, developing new treatments and advancing biotechnology.

systems biology↗

bioRxiv2025

Brain precapillary sphincters modulate myogenic tone in adult and aged mice

Brain precapillary sphincters, which are surrounded by contractile pericytes and are located at the junction of penetrating arterioles and first-order capillaries, can increase their diameter by [~]30% in a few seconds during sensory stimulation, allowing for rapid control of capillary blood flow over a wide dynamic range. We hypothesized that these properties could help precapillary sphincters maintain the capillary blood flow and shield the downstream capillaries during surges in blood pressure. To test this, we visualized microvessels in adult and old anaesthetized mice using in vivo two-photon microscopy. We showed that a blood pressure surge disrupts both microvascular myogenic response and neurovascular coupling in both adult and old mice, with old mice exhibiting a more diminished myogenic response. Similarly, laser ablation of contractile pericytes encircling precapillary sphincters disrupted neurovascular coupling and myogenic response. The resistance provided by precapillary sphincters may be increasingly important in old mice, where we found changes in the topology of microvessels, potentially affecting microvascular blood flow. Old mice displayed more tortuous penetrating arterioles, reduced pial collateral arteriolar density and altered capillary densities: reduced in the arterial end and increased in the venous end. Our results illustrate how blood pressure surges affect brain microvascular function, underscore the protective role of precapillary sphincters during cerebrovascular autoregulation in response to blood pressure surges and compare vascular topology in adult and old mice in vivo.

neuroscience↗

bioRxiv2024

Pseudo batch transformation: A novel method to correct for mass removal through sample withdrawal of fed-batch fermentations

SummaryWe present a novel "pseudo batch" transformation algorithm that maps analytical data obtained for fed-batch bioreactor cultivations onto a constant volume batch process, significantly decreasing the complexity of characterizing the fed-batch process. Availability and implementationOur method is implemented in both Excel and Python and is available with tutorials and example data from https://github.com/biosustain/pseudobatch. The Python package is also available on PYPI under the name "pseudobatch". ContactLars Keld Nielsen, e-mail: lars.nielsen@uq.edu.au Supplementary informationA comprehensive explanation of the simulated fed-batch, parameter estimation procedures, and the Bayesian model can be found in supplementary information (S1-S5).

bioinformatics↗