Correlating fluorescence microscopy, optical and magnetic tweezers to study single chiral biopolymers such as DNA.

Biopolymer topology is critical for determining interactions inside cell environments, exemplified by DNA where its response to mechanical perturbation is as important as biochemical properties to its cellular roles. The dynamic structures of chiral biopolymers exhibit complex dependence with extension and torsion, however the physical mechanisms underpinning the emergence of structural motifs upon physiological twisting and stretching are poorly understood due to technological limitations in correlating force, torque and spatial localization information. We present COMBI-Tweez (Combined Optical and Magnetic BIomolecule TWEEZers), a transformative tool that overcomes these challenges by integrating optical trapping, time-resolved electromagnetic tweezers, and fluorescence microscopy, demonstrated on single DNA molecules, that can controllably form and visualise higher order structural motifs including plectonemes. This technology combined with cutting-edge MD simulations provides quantitative insight into complex dynamic structures relevant to DNA cellular processes and can be adapted to study a range of filamentous biopolymers.

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

In eukaryotes, intracellular physico-chemical 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 internalized in cells is tracked and physico-chemical properties inferred from derived mean square displacement relations. Recently, the crGE2.3 Förster resonance energy transfer 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, multi-dimensional data to explore diffusion and molecular crowding characteristics of molecular crowding agents using super-resolved fluorescence microscopy and ensemble time-resolved spectroscopy. We firstly characterize 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 internalize 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.

Crowding-induced morphological changes in synthetic lipid vesicles determined using smFRET.

Lipid vesicles are valuable mesoscale molecular confinement vessels for studying membrane mechanics and lipid-protein interactions, and they have found utility among bio-inspired technologies, including drug delivery vehicles. While vesicle morphology can be modified by changing the lipid composition and introducing fusion or pore-forming proteins and detergents, the influence of extramembrane crowding on vesicle morphology has remained under-explored owing to a lack of experimental tools capable of capturing morphological changes on the nanoscale. Here, we use biocompatible polymers to simulate molecular crowding in vitro, and through combinations of FRET spectroscopy, lifetime analysis, dynamic light scattering, and single-vesicle imaging, we characterize how crowding regulates vesicle morphology. We show that both freely diffusing and surface-tethered vesicles fluorescently tagged with the DiI and DiD FRET pair undergo compaction in response to modest concentrations of sorbitol, polyethylene glycol, and Ficoll. A striking observation is that sorbitol results in irreversible compaction, whereas the influence of high molecular weight PEG-based crowders was found to be reversible. Regulation of molecular crowding allows for precise control of the vesicle architecture in vitro, with vast implications for drug delivery and vesicle trafficking systems. Furthermore, our observations of vesicle compaction may also serve to act as a mechanosensitive readout of extramembrane crowding.

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 cross-linker 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.

The End Restraint Method for Mechanically Perturbing Nucleic Acids In Silico.

Far from being a passive information store, the genome is a mechanically dynamic and diverse system in which torsion and tension fluctuate and combine to determine structure and help regulate gene expression. Much of this mechanical perturbation is due to molecular machines such as topoisomerases which must stretch and twist DNA as part of various functions including DNA repair and replication. While the broad-scale mechanical response of nucleic acids to tension and torsion is well characterized, detail at the single base pair level is beyond the limits of even super-resolution imaging. Here, we present a straightforward, flexible, and extensible umbrella-sampling protocol to twist and stretch nucleic acids in silico using the popular biomolecular simulation package Amber-though the principles we describe are applicable also to other packages such as GROMACS. We discuss how to set up the simulation system, decide force fields and solvation models, and equilibrate. We then introduce the torsionally constrained stretching protocol, and finally we present some analysis techniques we have used to characterize structural motif formation. Rather than defining forces or fictional pseudoatoms, we instead define a fixed translation of specified atoms between each umbrella-sampling step, which allows comparison with experiment without needing to estimate applied forces by simply using the fractional end-to-end displacement as a comparison metric. We hope that this easy-to-implement solution will be valuable for interrogating optical and magnetic tweezers data on nucleic acids at base pair resolution.

The Effect of Lithium on the Budding Yeast Saccharomyces cerevisiae upon Stress Adaptation.

Lithium salts are used in the treatment of mood disorders, cancer, and Alzheimer's disease. It has been shown to prolong life span in several phyla; however, not yet in budding yeast. In our study, we investigate the influence of lithium on yeast cells' viability by characterizing protein aggregate formation, cell volume, and molecular crowding in the context of stress adaptation. While our data suggest a concentration-dependent growth inhibition caused by LiCl, we show an extended long-term survival rate as an effect of lithium addition upon glucose deprivation. We show that caloric restriction mitigates the negative impact of LiCl on cellular survival. Therefore, we suggest that lithium could affect glucose metabolism upon caloric restriction, which could explain the extended long-term survival observed in our study. We find furthermore that lithium chloride did not affect an immediate salt-induced Hsp104-dependent aggregate formation but cellular adaptation to H2O2 and acute glucose starvation. We presume that different salt types and concentrations interfere with effective Hsp104 recruitment or its ATP-dependent disaggregase activity as a response to salt stress. This work provides novel details of Li+ effect on live eukaryotic cells which may also be applicable in further research on the treatment of cancer, Alzheimer's, or other age-related diseases in humans.

Investigating molecular crowding during cell division and hyperosmotic stress in budding yeast with FRET.

Cell division, aging, and stress recovery triggers spatial reorganization of cellular components in the cytoplasm, including membrane bound organelles, with molecular changes in their compositions and structures. However, it is not clear how these events are coordinated and how they integrate with regulation of molecular crowding. We use the budding yeast Saccharomyces cerevisiae as a model system to study these questions using recent progress in optical fluorescence microscopy and crowding sensing probe technology. We used a Förster Resonance Energy Transfer (FRET) based sensor, illuminated by confocal microscopy for high throughput analyses and Slimfield microscopy for single-molecule resolution, to quantify molecular crowding. We determine crowding in response to cellular growth of both mother and daughter cells, in addition to osmotic stress, and reveal hot spots of crowding across the bud neck in the burgeoning daughter cell. This crowding might be rationalized by the packing of inherited material, like the vacuole, from mother cells. We discuss recent advances in understanding the role of crowding in cellular regulation and key current challenges and conclude by presenting our recent advances in optimizing FRET-based measurements of crowding while simultaneously imaging a third color, which can be used as a marker that labels organelle membranes. Our approaches can be combined with synchronized cell populations to increase experimental throughput and correlate molecular crowding information with different stages in the cell cycle.

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 microscopy. 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.

Elucidating the Role of Topological Constraint on the Structure of Overstretched DNA Using Fluorescence Polarization Microscopy.

The combination of DNA force spectroscopy and polarization microscopy of fluorescent DNA intercalator dyes can provide valuable insights into the structure of DNA under tension. These techniques have previously been used to characterize S-DNA-an elongated DNA conformation that forms when DNA overstretches at forces ≥ 65 pN. In this way, it was deduced that the base pairs of S-DNA are highly inclined, relative to those in relaxed (B-form) DNA. However, it is unclear whether and how topological constraints on the DNA may influence the base-pair inclinations under tension. Here, we apply polarization microscopy to investigate the impact of DNA pulling geometry, torsional constraint, and negative supercoiling on the orientations of intercalated dyes during overstretching. In contrast to earlier predictions, the pulling geometry (namely, whether the DNA molecule is stretched via opposite strands or the same strand) is found to have little influence. However, torsional constraint leads to a substantial reduction in intercalator tilting in overstretched DNA, particularly in AT-rich sequences. Surprisingly, the extent of intercalator tilting is similarly reduced when the DNA molecule is negatively supercoiled up to a critical supercoiling density (corresponding to ∼70% reduction in the linking number). We attribute these observations to the presence of P-DNA (an overwound DNA conformation). Our results suggest that intercalated DNA preferentially flanks regions of P-DNA rather than those of S-DNA and also substantiate previous suggestions that P-DNA forms predominantly in AT-rich sequences.

Molecular crowding in single eukaryotic cells: Using cell environment biosensing and single-molecule optical microscopy to probe dependence on extracellular ionic strength, local glucose conditions, and sensor copy number.

The physical and chemical environment inside cells is of fundamental importance to all life but has traditionally been difficult to determine on a subcellular basis. Here we combine cutting-edge genomically integrated FRET biosensing to readout localized molecular crowding in single live yeast cells. Confocal microscopy allows us to build subcellular crowding heatmaps using ratiometric FRET, while whole-cell analysis demonstrates crowding is reduced when yeast is grown in elevated glucose concentrations. Simulations indicate that the cell membrane is largely inaccessible to these sensors and that cytosolic crowding is broadly uniform across each cell over a timescale of seconds. Millisecond single-molecule optical microscopy was used to track molecules and obtain brightness estimates that enabled calculation of crowding sensor copy numbers. The quantification of diffusing molecule trajectories paves the way for correlating subcellular processes and the physicochemical environment of cells under stress.

SerraNA: a program to determine nucleic acids elasticity from 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 apply SerraNA to the whole set of 136 tetra-bp combinations and we observe a high degree of sequence-dependence with differences over 200% for all elastic parameters. Tetramers with TA and CA base-pair steps are especially flexible, while the ones containing AA and AT tend to be the most rigid. Thus, AT-rich motifs can generate extreme mechanical properties, which are critical for creating strong global bends when phased properly. Our results also indicate base mismatches would make DNA more flexible, while protein binding would make it more rigid. SerraNA is a tool to be applied in the next generation of interdisciplinary investigations to further understand what determines the elasticity of DNA.

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 resulting from mechanical perturbations in cells have physiological relevance but their dependence on sequence remains unclear. Here, we use molecular dynamics simulations showing sequence differences result in markedly different structural motifs upon physiological twisting and stretching. We simulate overextension on different sequences of DNA ((AA)12, (AT)12, (CC)12 and (CG)12) with supercoiling densities at 200 and 50 mM salt concentrations. We find that DNA denatures in the majority of stretching simulations, surprisingly including those with over-twisted DNA. GC-rich sequences are observed to be more stable than AT-rich ones, with the specific response dependent on the base pair order. Furthermore, we find that (AT)12 forms stable periodic structures with non-canonical hydrogen bonds in some regions and non-canonical stacking in others, whereas (CG)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.

Single-molecule techniques in biophysics: a review of the progress in methods and applications.

Single-molecule biophysics has transformed our understanding of biology, but also of the physics of life. More exotic than simple soft matter, biomatter lives far from thermal equilibrium, covering multiple lengths from the nanoscale of single molecules to up to several orders of magnitude higher in cells, tissues and organisms. Biomolecules are often characterized by underlying instability: multiple metastable free energy states exist, separated by levels of just a few multiples of the thermal energy scale k B T, where k B is the Boltzmann constant and T absolute temperature, implying complex inter-conversion kinetics in the relatively hot, wet environment of active biological matter. A key benefit of single-molecule biophysics techniques is their ability to probe heterogeneity of free energy states across a molecular population, too challenging in general for conventional ensemble average approaches. Parallel developments in experimental and computational techniques have catalysed the birth of multiplexed, correlative techniques to tackle previously intractable biological questions. Experimentally, progress has been driven by improvements in sensitivity and speed of detectors, and the stability and efficiency of light sources, probes and microfluidics. We discuss the motivation and requirements for these recent experiments, including the underpinning mathematics. These methods are broadly divided into tools which detect molecules and those which manipulate them. For the former we discuss the progress of super-resolution microscopy, transformative for addressing many longstanding questions in the life sciences, and for the latter we include progress in 'force spectroscopy' techniques that mechanically perturb molecules. We also consider in silico progress of single-molecule computational physics, and how simulation and experimentation may be drawn together to give a more complete understanding. Increasingly, combinatorial techniques are now used, including correlative atomic force microscopy and fluorescence imaging, to probe questions closer to native physiological behaviour. We identify the trade-offs, limitations and applications of these techniques, and discuss exciting new directions.