Biology subjects

Shepherd, J. W.

Publications and source records attributed to Shepherd, J. W..

7 recordsLinked to original sources

bioRxiv2026

A Bottom-Up Platform for Quantitative Single-Molecule Tracking Through Bacterial Biofilm Mimics

Chronic infections persist in large part thanks to protection that biofilms afford their bacterial creators. The extracellular polymeric substance of biofilms is a hydrated matrix of DNA, polysaccharides, and structural proteins, amongst other components, through which nutrients, signalling molecules, and antimicrobial agents must diffuse to reach the bacteria within. Quantitative measurement of transport on the nanoscale within in vivo biofilms remains challenging due to optical heterogeneity, autofluorescence, active remodelling of biofilms and the ambiguity in trajectory reconstruction during single-particle tracking (SPT). Here, we present a methodological framework for measuring molecular transport in defined minimal extracellular matrix models using quantum dots as fluorescent nanoscale probes imaged with high-speed SlimVar microscopy. To establish conditions in which high-diffusivity particle trajectories can be reliably reconstructed, upper limits to quantum dot concentrations were estimated from Brownian motion. The 99th-percentile inter-frame jump distance was estimated from the three-dimensional Brownian jump distance distribution and used to define a target average nearest neighbour distance, and therefore a per-particle volume, used for calculating a concentration which minimises the probability of trajectory collision during data acquisition. Quantum dot movement was imaged at sub-millisecond frame rates and diffusion coefficients were calculated in a 20% glycerol control and in DNA nanostar hydrogels modelling minimal extracellular matrix scaffolds assembled at 250 M and 500 M. Median diffusion coefficients decreased from 94.9 m2*s-1 in glycerol to 15.9 m2*s-1 and 8.3 m2*s-1 in the 250 M and 500 M hydrogels, respectively. More broadly, this work establishes a workflow for quantitative SPT in minimal biofilm models. Rather than attempting to reproduce the full biological complexity of native biofilms, this approach provides the basis of a modular experimental framework in which individual extracellular matrix components can be incorporated sequentially and their effects on molecular transport quantified.

biophysics↗

bioRxiv2022

Correlating viscosity and molecular crowding with fluorescent nanobeads and molecular probes: in vitro and in vivo

In eukaryotes, intracellular physicochemical properties like macromolecular crowding and cytoplasmic viscoelasticity influence key processes such as metabolic activities, molecular diffusion, and protein folding. However, mapping crowding and viscoelasticity in living cells remains challenging. One approach uses passive rheology in which diffusion of exogenous fluorescent particles internalised in cells is tracked and physicochemical properties inferred from derived mean square displacement relations. Recently, the crGE2.3 Forster Resonance Energy Transfer (FRET) biosensor was developed to quantify crowding in cells, though it is unclear how this readout depends on viscoelasticity and the molecular weight of the crowder. Here, we present correlative, multidimensional data to explore diffusion and molecular crowding characteristics of molecular crowding agents using super-resolved fluorescence microscopy and ensemble time-resolved spectroscopy. We firstly characterise in vitro and then apply these insights to live cells of budding yeast Saccharomyces cerevisiae. It is to our knowledge the first time this has been attempted. We demonstrate that these are usable both in vitro and in the case of endogenously expressed sensors in live cells. Finally, we present a method to internalise fluorescent beads as in situ viscoelasticity markers in the cytoplasm of live yeast cells, and discuss limitations of this approach including impairment of cellular function.

biophysics↗

bioRxiv2021

RecA and RecB: probing complexes of DNA repair proteins with mitomycin C in live Escherichia coli with single-molecule sensitivity

The RecA protein and RecBCD complex are key bacterial components for the maintenance and repair of DNA. RecBCD is a helicase-nuclease that uses homologous recombination to resolve double-stranded DNA breaks. It also facilitates coating of single-stranded DNA with RecA to form RecA filaments, a vital step in the double-stranded break DNA repair pathway. However, questions remain about the mechanistic roles of RecA and RecBCD in live cells. Here, we use millisecond super-resolved fluorescence microscopy to pinpoint the spatial localization of fluorescent reporters of RecA or RecB at physiological levels of expression in individual live Escherichia coli cells. By introducing the DNA crosslinker mitomycin C, we induce DNA damage and quantify the resulting steady state changes in stoichiometry, cellular protein copy number and molecular mobilities of RecA and RecB. We find that both proteins accumulate in molecular hotspots to effect repair, resulting in RecA stoichiometries equivalent to several hundred molecules that assemble largely in dimeric subunits before DNA damage, but form periodic subunits of approximately 3-4 molecules within mature filaments of several thousand molecules. Unexpectedly, we find that the physiologically predominant forms of RecB are not only rapidly diffusing monomers, but slowly diffusing dimers.

biophysics↗

bioRxiv2021

PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy data

As camera pixel arrays have grown larger and faster, and optical microscopy techniques ever more refined, there has been an explosion in the quantity of data acquired during routine light microcopy. At the single-molecule level, analysis involves multiple steps and can rapidly become computationally expensive, in some cases intractable on office workstations. Complex bespoke software can present high activation barriers to entry for new users. Here, we redevelop our quantitative single-molecule analysis routines into an optimized and extensible Python program, with GUI and command-line implementations to facilitate use on local machines and remote clusters, by beginners and advanced users alike. We demonstrate that its performance is on par with previous MATLAB implementations but runs an order of magnitude faster. We tested it against challenge data and demonstrate its performance is comparable to state-of-the-art analysis platforms. We show the code can extract fluorescence intensity values for single reporter dye molecules and, using these, estimate molecular stoichiometries and cellular copy numbers of fluorescently-labeled biomolecules. It can evaluate 2D diffusion coefficients for the characteristically short single-particle tracking data. To facilitate benchmarking we include data simulation routines to compare different analysis programs. Finally, we show that it works with 2-color data and enables colocalization analysis based on overlap integration, to infer interactions between differently labelled biomolecules. By making this freely available we aim to make complex light microscopy single-molecule analysis more democratized. HighlightsO_LIWe present PySTACHIO, a refined version of our spot tracking algorithm C_LIO_LIWe demonstrate highly improved performance over previous MATLAB versions C_LIO_LIPySTACHIO can accurately estimate stoichiometries and 2D diffusion coefficients C_LIO_LIPerformance is comparable to state-of-the-art packages on challenge data C_LIO_LIPySTACHIO has both GUI and command line interfaces and can be hosted as a web app C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/435952v3_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@17cc45dorg.highwire.dtl.DTLVardef@3fb66eorg.highwire.dtl.DTLVardef@e20360org.highwire.dtl.DTLVardef@4ba47d_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2021

Combining single-molecule super-resolved localization microscopy with fluorescence polarization imaging to study cellular processes

Super-resolution microscopy has catalyzed valuable insights into the sub-cellular, mechanistic details of many different biological processes across a wide range of cell types. Fluorescence polarization spectroscopy tools have also enabled important insights into cellular processes through identifying orientational changes of biological molecules typically at an ensemble level. Here, we combine these two biophysical methodologies in a single home-made instrument to enable the simultaneous detection of orthogonal fluorescence polarization signals from single fluorescent protein molecules used as common reporters on the localization of proteins in cellular processes. These enable measurement of spatial location to a super-resolved precision better than the diffraction-limited optical resolution, as well as estimation of molecular stoichiometry based on the brightness of individual fluorophores. In this innovation we have adapted a millisecond timescale microscope used for single-molecule detection to enable splitting of fluorescence polarization emissions into two separate imaging channels for s- and p-polarization signals, which are imaged onto separate halves of the same high sensitivity back-illuminated CMOS camera detector. We applied this fluorescence polarization super-resolved imaging modality to a range of test fluorescent samples relevant to the study of biological processes, including purified monomeric green fluorescent protein, single combed DNA molecules, and protein assemblies and complexes from live Escherichia coli and Saccharomyces cerevisiae cells. Our findings are qualitative but demonstrate promise in showing how fluorescence polarization and super-resolved localization microscopy can be combined on the same sample to enable simultaneous measurements of polarization and stoichiometry of tracked molecular complexes, as well as the translational diffusion coefficient.

biophysics↗

bioRxiv2020

SerraNA: a program to infer elastic constants from local to global using nucleic acids simulation data

The resistance of DNA to stretch, twist and bend is broadly well estimated by experiments and is important for gene regulation and chromosome packing. However, their sequence-dependence and how bulk elastic constants emerge from local fluctuations is less understood. Here, we present SerraNA, which is an open software that calculates elastic parameters of double-stranded nucleic acids from dinucleotide length up to the whole molecule using ensembles from numerical simulations. The program reveals that global bendability emerge from local periodic bending angles in phase with the DNA helicoidal shape. We also apply SerraNA to the whole set of 136 tetra-bp combinations and we observe a high degree of sequence-dependence for all elastic parameters with differences over 200%. Tetramers with TA and CA base-pair steps are especially flexible, while tetramers containing AA and AT tend to be the most rigid. Our results thus suggest AT-rich motifs generate extreme mechanical properties depending of the exact sequence ordering, which seems critical for creating strong global bendability on longer sequences when phased properly. SerraNA is a tool to be applied in the next generation of interdisciplinary investigations to further understand what determines the elasticity of DNA. Graphical TOC Entry O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/004945v2_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@18aa2ddorg.highwire.dtl.DTLVardef@ca5e02org.highwire.dtl.DTLVardef@1e1febeorg.highwire.dtl.DTLVardef@1b772b_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2019

The emergence of sequence-dependent structural motifs in stretched, torsionally constrained DNA

The double-helical structure of DNA results from canonical base pairing and stacking interactions. However, variations from steady-state conformations result from mechanical perturbations in cells. These different topologies have physiological relevance but their dependence on sequence remains unclear. Here, we use molecular dynamics simulations to show that sequence differences result in markedly different structural motifs upon physiological twisting and stretching. We simulated overextension on four different sequences of DNA ((AA)12, (AT)12, (GG)12 and (GC)12) with supercoiling densities within the physiological range. We found that DNA denatures in the majority of stretching simulations, surprisingly including those with overtwisted DNA. GC-rich sequences were observed to be more stable than AT-rich, with the specific response dependent on base pair ordering. Furthermore, we found that (AT)12 forms stable periodic structures with non-canonical hydrogen bonds in some regions and non-canonical stacking in others, whereas (GC)12 forms a stacking motif of four base pairs independent of supercoiling density. Our results demonstrate that 20-30% DNA extension is sufficient for breaking B-DNA around and significantly above cellular supercoiling, and that the DNA sequence is crucial for understanding structural changes under mechanical stress. Our findings have important implications for the activities of protein machinery interacting with DNA in all cells.

biophysics↗