Biology subjects

Waigh, T. A.

Publications and source records attributed to Waigh, T. A..

6 recordsLinked to original sources

bioRxiv2025

AC electro-osmosis in bacterial biofilms: a cautionary tale for electrophysiology experiments

Synthetic cationic fluorophores are used widely as probes to measure the membrane potentials of bacterial cells, eukaryotic cells and organelles, such as mitochondria. An external oscillating electric field was applied to Escherichia coli cells using microelectrodes and AC electro-osmosis was observed for the fluorophores, independent of the electrophysiology of the bacteria, giving rise to phantom action potentials. The fluorophores migrate around the microfluidic device in vortices modulating their concentration having decreases or dips in fluorescence. We show that the fluorescent dips are universally present when using cationic fluorophores, such as thioflavin-T, propidium iodide, Syto9 and Sytox Green, with or without E. coli cells in the inoculum, when stimulated with AC voltages. This is in contrast to the study of Stratford et al (PNAS, 2019) who claim the existence of action potentials. Furthermore, E. coli biofilms also demonstrated similar phenomena with dips in the fluorescence. We measured the relaxation times of the fluorophores experiencing AC electro-osmosis, which depended on the biofilm, the cells and the fluorophores used. PI had the smallest relaxation time and Syto9 the highest. Removing the cells resulted in longer relaxation times and introducing biofilm did not significantly change the relaxation times compared with the single cell experiments. Furthermore, fluorescently labelled DNA and fluorescent colloidal beads also demonstrate fluorescent dips through AC electro-osmosis, showing that these particles can be driven through biofilms. This is the first study of AC electro-osmosis in bacterial biofilms, indicating a surprisingly high mobility of charged molecules within the extracellular polymeric substance, which could be used to treat biofilms i.e. to increase the kinetics of delivery of antibiotics.

biophysics↗

bioRxiv2023

Electrical impedance spectroscopy with bacterial biofilms: neuronal-like behaviour

Negative capacitance at low frequencies for neurons was first demonstrated in 1941 (Kenneth S. Cole) using extracellular electrodes. The phenomenon subsequently was explained by Cole using the Hodgkin-Huxley model and is due to the activity of voltage-gated potassium ion channels. We show that E. coli biofilms exhibit significant stable negative capacitances at low frequencies when they experience a small DC bias voltage in electrical impedance spectroscopy experiments. Using a frequency domain Hodgkin-Huxley model, we characterize the conditions for the emergence of this feature and demonstrate that the negative capacitance exists only in biofilms containing living cells. Furthermore, we established the importance of the voltage-gated potassium ion channel, Kch, using knock-down mutants. The experiments provide further evidence for voltage-gated ion channels in E. coli and a new, low-cost method to probe biofilm electrophysiology e.g. to understand the efficacy of antibiotics. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=67 SRC="FIGDIR/small/568527v1_ufig1.gif" ALT="Figure 1"> View larger version (11K): org.highwire.dtl.DTLVardef@e3df05org.highwire.dtl.DTLVardef@46c5d2org.highwire.dtl.DTLVardef@6572a6org.highwire.dtl.DTLVardef@4a104a_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2023

Electrical Signalling in Three Dimensional Bacterial Biofilms Using an Agent Based Fire-Diffuse-Fire Model

Agent based models were used to describe electrical signalling in bacterial biofilms in three dimensions. Specifically, wavefronts of potassium ions in E. coli biofilms subjected to stress from blue light were modelled from experimental data. Electrical signalling only occurs when the biofilms grow beyond a threshold size, which we have shown to vary with the K+ ion diffusivity and the K+ ion threshold concentration which triggered firing in the fire-diffuse-fire model. The transport of the propagating wavefronts shows super-diffusive scaling on time. K+ ion diffusivity is the main factor that affects the wavefront velocity. The K+ ion diffusivity and the firing threshold also affect the anomalous exponent for the propagation of the wavefront determining whether the wavefront is sub-diffusive or super-diffusive. The geometry of the biofilm and its relation to the mean square displacement (MSD) of the wavefront as a function of time was investigated for spherical, cylindrical, cubical and mushroom-like structures. The MSD varied significantly with geometry; an additional regime to the kinetics occurred when the potassium wavefront leaves the biofilm. Adding cylindrical defects to the biofilm, which are known to occur in E. coli biofilms, the wavefront MSD also had an extra kinetic regime for the propagation through the defect.

biophysics↗

bioRxiv2022

Emergence of ion-channel mediated electrical oscillations in E. coli biofilms

Bacterial biofilms are communities of bacteria usually attached to solid strata and often differentiated into complex structures. Communication across biofilms has been shown to involve chemical signaling and, more recently, electrical signaling in Gram positive biofilms. We report for the first time, community-level synchronized membrane potential dynamics in three-dimensional E. coli biofilms. Two hyperpolarization events are observed in response to light stress. The first requires mechanically sensitive ion channels (MscK, MscL and MscS) and the second needs the Kch-potassium channel. The channels mediated both local spiking of single E. coli biofilms and long-range coordinated electrical signaling in E. coli biofilms. The electrical phenomena are explained using Hodgkin-Huxley and 3D fire-diffuse-fire agent-based models. These data demonstrate that electrical wavefronts based on potassium ions are a mechanism by which signaling occurs in Gram negative biofilms and as such may represent a conserved mechanism for communication across biofilms.

biophysics↗

bioRxiv2020

Network Organisation and the Dynamics of Tubules in the Endoplasmic Reticulum

The endoplasmic reticulum (ER) is a eukaryotic subcellular organelle composed of tubules and sheet-like areas of membrane connected at junctions. The tubule network is highly dynamic and undergoes rapid and continual rearrangement. There are currently few tools to evaluate network organisation and dynamics. We quantified ER network organisation in Vero and MRC5 cells, and developed a classification system for ER dynamics in live cells. The persistence length, tubule length, junction coordination number and angles of the network were quantified. Hallmarks of imbalances in ER tension, indications of interactions with microtubules and other subcellular organelles, and active reorganisation and dynamics were observed. Live cell ER tubule dynamics were classified using a Gaussian mixture model, defining tubule motion as active or thermal and conformational phase space analysis allowed this classification to be refined by tubule curvature states. STATEMENT OF SIGNIFICANCEThe endoplasmic reticulum (ER), a subcellular organelle, is an underexplored real-world example of active matter. Many processes essential to cell survival are performed by the ER, the efficacy of which may depend on its organisation and dynamics. Abnormal ER morphology is linked to diseases such as hereditary spastic paraplegias and it is possible that the dynamics are also implicated. Therefore, analysing the ER network in normal cells is important for the understanding of disease-related alterations. In this work, we outline the first thorough quantification methods for determining ER organisation and dynamics, deducing that tubule motion has a binary classification as active or thermal. Active reorganisation and dynamics along with indications of tension imbalances and membrane contact sites were observed.

biophysics↗

bioRxiv2019

Deciphering anomalous heterogeneous intracellular transport with neural networks

Biological intracellular transport is predominantly heterogeneous in both time and space, exhibiting varying non-Brownian behaviour. Characterisation of this movement through averaging methods over an ensemble of trajectories or over the course of a single trajectory often fails to capture this heterogeneity adequately. Here, we have developed a deep learning feedforward neural network trained on fractional Brownian motion, which provides a novel, accurate and efficient characterization method for resolving heterogeneous behaviour of intracellular transport both in space and time. Importantly, the neural network requires significantly fewer data points compared to established methods, such as mean square displacements, rescaled range analysis and sequential range analysis. This enables robust estimation of Hurst exponents for very short time series data, making possible direct, dynamic segmentation and analysis of experimental tracks of rapidly moving cellular structures such as endosomes and lysosomes. By using this analysis, we were able to interpret anomalous intracellular dynamics as fractional Brownian motion with a stochastic Hurst exponent.

cell biology↗