Bayesian inference of multi-point macromolecular architecture mixtures at nanometre resolution.

Gaussian spot fitting methods have significantly extended the spatial range where fluorescent microscopy can be used, with recent techniques approaching nanometre (nm) resolutions. However, small inter-fluorophore distances are systematically over-estimated for typical molecular scales. This bias can be corrected computationally, but current algorithms are limited to correcting distances between pairs of fluorophores. Here we present a flexible Bayesian computational approach that infers the distances and angles between multiple fluorophores and has several advantages over these previous methods. Specifically it improves confidence intervals for small lengths, estimates measurement errors of each fluorophore individually and infers the correlations between polygon lengths. The latter is essential for determining the full multi-fluorophore 3D architecture. We further developed the algorithm to infer the mixture composition of a heterogeneous population of multiple polygon states. We use our algorithm to analyse the 3D architecture of the human kinetochore, a macro-molecular complex that is essential for high fidelity chromosome segregation during cell division. Using triple fluorophore image data we unravel the mixture of kinetochore states during human mitosis, inferring the conformation of microtubule attached and unattached kinetochores and their proportions across mitosis. We demonstrate that the attachment conformation correlates with intersister tension and sister alignment to the metaphase plate.

Evidence for a HURP/EB free mixed-nucleotide zone in kinetochore-microtubules.

Current models infer that the microtubule-based mitotic spindle is built from GDP-tubulin with small GTP caps at microtubule plus-ends, including those that attach to kinetochores, forming the kinetochore-fibres. Here we reveal that kinetochore-fibres additionally contain a dynamic mixed-nucleotide zone that reaches several microns in length. This zone becomes visible in cells expressing fluorescently labelled end-binding proteins, a known marker for GTP-tubulin, and endogenously-labelled HURP - a protein which we show to preferentially bind the GDP microtubule lattice in vitro and in vivo. We find that in mitotic cells HURP accumulates on the kinetochore-proximal region of depolymerising kinetochore-fibres, whilst avoiding recruitment to nascent polymerising K-fibres, giving rise to a growing "HURP-gap". The absence of end-binding proteins in the HURP-gaps leads us to postulate that they reflect a mixed-nucleotide zone. We generate a minimal quantitative model based on the preferential binding of HURP to GDP-tubulin to show that such a mixed-nucleotide zone is sufficient to recapitulate the observed in vivo dynamics of HURP-gaps.

Kinetochore tracking in 3D from lattice light-sheet imaging data with KiT.

MOTIVATION: Lattice light-sheet microscopy (LLSM) is revolutionizing cell biology since it enables fast, high-resolution extended imaging in three dimensions combined with a drastic reduction in photo-toxicity and bleaching. However, analysis of such datasets still remains a major challenge. RESULTS: Automated tracking of kinetochores, the protein complex facilitating and controlling microtubule attachment of the chromosomes within the mitotic spindle, provides quantitative assessment of chromosome dynamics in mitosis. Here, we extend existing open-source kinetochore tracking software (KiT) to track (and pair) kinetochores throughout prometaphase to anaphase in LLSM data. One of the key improvements is a regularization term in the objective function to enforce biological information about the number of kinetochores in a human mitotic cell, as well as improved diagnostic tools. This software provides quantitative insights into how kinetochores robustly ensure congression and segregation of chromosomes during mitosis. AVAILABILITY AND IMPLEMENTATION: KiT is free, open-source software implemented in MATLAB and can be downloaded as a package from https://github.com/cmcb-warwick/KiT. The source repository is available at https://bitbucket.org/jarmond/kit (tag v2.4.0) and under continuing development. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Kinetochore life histories reveal an Aurora-B-dependent error correction mechanism in anaphase.

Chromosome mis-segregation during mitosis leads to aneuploidy, which is a hallmark of cancer and linked to cancer genome evolution. Errors can manifest as "lagging chromosomes" in anaphase, although their mechanistic origins and likelihood of correction are incompletely understood. Here, we combine lattice light-sheet microscopy, endogenous protein labeling, and computational analysis to define the life history of >104 kinetochores. By defining the "laziness" of kinetochores in anaphase, we reveal that chromosomes are at a considerable risk of mis-segregation. We show that the majority of lazy kinetochores are corrected rapidly in anaphase by Aurora B; if uncorrected, they result in a higher rate of micronuclei formation. Quantitative analyses of the kinetochore life histories reveal a dynamic signature of metaphase kinetochore oscillations that forecasts their anaphase fate. We propose that in diploid human cells chromosome segregation is fundamentally error prone, with an additional layer of anaphase error correction required for stable karyotype propagation.

Subcellular Euclidean distance measurements with multicolor fluorescence localization imaging in cultured cells.

This protocol measures the 3D Euclidean distance (Δ3D) between two/three fluorescently labeled kinetochore components in fixed samples using Kinetochore Delta software (KiDv1.0.1, MATLAB based). Overestimation of mean Δ3D is corrected through a Bayesian algorithm, with ΔEC distances reflecting the ensemble average positions of fluorophores within a kinetochore population. This package also enables kinetochore categorization, which can be used to sub-sample kinetochores and measure ΔEC. Together, this allows the dynamic architecture of human kinetochores to be investigated (tested in hTERT-RPE1 cells). For complete details on the use and execution of this protocol, please refer to Roscioli et al. (2020).

Ensemble-Level Organization of Human Kinetochores and Evidence for Distinct Tension and Attachment Sensors.

Kinetochores are multi-protein machines that form dynamic attachments to microtubules and control chromosome segregation. High fidelity is ensured because kinetochores can monitor attachment status and tension, using this information to activate checkpoints and error-correction mechanisms. To explore how kinetochores achieve this, we used two- and three-color subpixel fluorescence localization to define how proteins from six major complexes (CCAN, MIS12, NDC80, KNL1, RZZ, and SKA) and the checkpoint proteins Bub1, Mad1, and Mad2 are organized in the human kinetochore. This reveals how the outer kinetochore has a high nematic order and is largely invariant to the loss of attachment or tension, except for two mechanical sensors. First, Knl1 unravels to relay tension, and second, NDC80 undergoes jackknifing and loss of nematic order under microtubule detachment, with only the latter wired up to the checkpoint signaling system. This provides insight into how kinetochores integrate mechanical signals to promote error-free chromosome segregation.

Computational modelling predicts substantial carbon assimilation gains for C3 plants with a single-celled C4 biochemical pump.

Achieving global food security for the estimated 9 billion people by 2050 is a major scientific challenge. Crop productivity is fundamentally restricted by the rate of fixation of atmospheric carbon. The dedicated enzyme, RubisCO, has a low turnover and poor specificity for CO2. This limitation of C3 photosynthesis (the basic carbon-assimilation pathway present in all plants) is alleviated in some lineages by use of carbon-concentrating-mechanisms, such as the C4 cycle-a biochemical pump that concentrates CO2 near RubisCO increasing assimilation efficacy. Most crops use only C3 photosynthesis, so one promising research strategy to boost their productivity focuses on introducing a C4 cycle. The simplest proposal is to use the cycle to concentrate CO2 inside individual chloroplasts. The photosynthetic efficiency would then depend on the leakage of CO2 out of a chloroplast. We examine this proposal with a 3D spatial model of carbon and oxygen diffusion and C4 photosynthetic biochemistry inside a typical C3-plant mesophyll cell geometry. We find that the cost-efficiency of C4 photosynthesis depends on the gas permeability of the chloroplast envelope, the C4 pathway having higher quantum efficiency than C3 for permeabilities below 300 µm/s. However, at higher permeabilities the C4 pathway still provides a substantial boost to carbon assimilation with only a moderate decrease in efficiency. The gains would be capped by the ability of chloroplasts to harvest light, but even under realistic light regimes a 100% boost to carbon assimilation is possible. This could be achieved in conjunction with lower investment in chloroplasts if their cell surface coverage is also reduced. Incorporation of this C4 cycle into C3 crops could thus promote higher growth rates and better drought resistance in dry, high-sunlight climates.

Bayesian inference of origin firing time distributions, origin interference and licencing probabilities from Next Generation Sequencing data.

DNA replication is a stochastic process with replication forks emanating from multiple replication origins. The origins must be licenced in G1, and the replisome activated at licenced origins in order to generate bi-directional replication forks in S-phase. Differential firing times lead to origin interference, where a replication fork from an origin can replicate through and inactivate neighbouring origins (origin obscuring). We developed a Bayesian algorithm to characterize origin firing statistics from Okazaki fragment (OF) sequencing data. Our algorithm infers the distributions of firing times and the licencing probabilities for three consecutive origins. We demonstrate that our algorithm can distinguish partial origin licencing and origin obscuring in OF sequencing data from Saccharomyces cerevisiae and human cell types. We used our method to analyse the decreased origin efficiency under loss of Rat1 activity in S. cerevisiae, demonstrating that both reduced licencing and increased obscuring contribute. Moreover, we show that robust analysis is possible using only local data (across three neighbouring origins), and analysis of the whole chromosome is not required. Our algorithm utilizes an approximate likelihood and a reversible jump sampling technique, a methodology that can be extended to analysis of other mechanistic processes measurable through Next Generation Sequencing data.

Actin turnover ensures uniform tension distribution during cytokinetic actomyosin ring contraction.

In many eukaryotes, cytokinesis is facilitated by the contraction of an actomyosin ring (AMR). The exact mechanisms that lead to this contractility are unknown, although some models posit that actin turnover in the AMR is essential. The effect of reduced actin dynamics during AMR formation has been well studied in Schizosaccharomyces pombe; however, the corresponding effects on AMR contraction are not well understood. By using mutants of the fission yeast actin severing protein Adf1, we observed that contracting AMRs display a "peeling" phenotype, where bundles of actin and myosin peel off from one side of the AMR, and are pulled across to the opposite side. This occurs multiple times during cytokinesis and is dependent on the activity of myosins Myo2, Myp2, and Myo51. We found that the distribution of Myo2 in the AMR anticorrelates with the location of peeling events, suggesting that peeling is caused by a nonuniform tension distribution around the AMR, and that one of the roles of actin turnover is to maintain a uniform tension distribution around the AMR.

A Hidden Markov Model for Detecting Confinement in Single-Particle Tracking Trajectories.

State-of-the-art single-particle tracking (SPT) techniques can generate long trajectories with high temporal and spatial resolution. This offers the possibility of mechanistically interpreting particle movements and behavior in membranes. To this end, a number of statistical techniques have been developed that partition SPT trajectories into states with distinct diffusion signatures, allowing a statistical analysis of diffusion state dynamics and switching behavior. Here, we develop a confinement model, within a hidden Markov framework, that switches between phases of free diffusion and confinement in a harmonic potential well. By using a Markov chain Monte Carlo algorithm to fit this model, automated partitioning of individual SPT trajectories into these two phases is achieved, which allows us to analyze confinement events. We demonstrate the utility of this algorithm on a previously published interferometric scattering microscopy data set, in which gold-nanoparticle-tagged ganglioside GM1 lipids were tracked in model membranes. We performed a comprehensive analysis of confinement events, demonstrating that there is heterogeneity in the lifetime, shape, and size of events, with confinement size and shape being highly conserved within trajectories. Our observations suggest that heterogeneity in confinement events is caused by both individual nanoparticle characteristics and the binding-site environment. The individual nanoparticle heterogeneity ultimately limits the ability of interferometric scattering microscopy to resolve molecule dynamics to the order of the tag size; homogeneous tags could potentially allow the resolution to be taken below this limit by deconvolution methods. In a wider context, the presented harmonic potential well confinement model has the potential to detect and characterize a wide variety of biological phenomena, such as hop diffusion, receptor clustering, and lipid rafts.

Kinesin expands and stabilizes the GDP-microtubule lattice.

Kinesin-1 is a nanoscale molecular motor that walks towards the fast-growing (plus) ends of microtubules, hauling molecular cargo to specific reaction sites in cells. Kinesin-driven transport is central to the self-organization of eukaryotic cells and shows great promise as a tool for nano-engineering 1 . Recent work hints that kinesin may also play a role in modulating the stability of its microtubule track, both in vitro2,3 and in vivo 4 , but the results are conflicting5-7 and the mechanisms are unclear. Here, we report a new dimension to the kinesin-microtubule interaction, whereby strong-binding state (adenosine triphosphate (ATP)-bound and apo) kinesin-1 motor domains inhibit the shrinkage of guanosine diphosphate (GDP) microtubules by up to two orders of magnitude and expand their lattice spacing by ~1.6%. Our data reveal an unexpected mechanism by which the mechanochemical cycles of kinesin and tubulin interlock, and so allow motile kinesins to influence the structure, stability and mechanics of their microtubule track.

Changes in Gene Expression in Space and Time Orchestrate Environmentally Mediated Shaping of Root Architecture.

Shaping of root architecture is a quintessential developmental response that involves the concerted action of many different cell types, is highly dynamic, and underpins root plasticity. To determine to what extent the environmental regulation of lateral root development is a product of cell-type preferential activities, we tracked transcriptomic responses to two different treatments that both change root development in Arabidopsis thaliana at an unprecedented level of temporal detail. We found that individual transcripts are expressed with a very high degree of temporal and spatial specificity, yet biological processes are commonly regulated, in a mechanism we term response nonredundancy. Using causative gene network inference to compare the genes regulated in different cell types and during responses to nitrogen and a biotic interaction, we found that common transcriptional modules often regulate the same gene families but control different individual members of these families, specific to response and cell type. This reinforces that the activity of a gene cannot be defined simply as molecular function; rather, it is a consequence of spatial location, expression timing, and environmental responsiveness.

Size matters for single-cell C4 photosynthesis in Bienertia.

Bienertia cycloptera belongs to a diverse set of plants, recently discovered to perform C4 photosynthesis within individual mesophyll cells. How these plants accomplish high photosynthetic efficiency without adopting Kranz anatomy remains unanswered. By modelling the processes of diffusion, capture, and release of carbon dioxide and oxygen inside a typical Bienertia mesophyll cell geometry, we show that a spatial separation as low as 10 µm between the primary and the secondary carboxylases, can, on its own, provide enough diffusive resistance to sustain a viable C4 pathway at 20 °C, with a CO2 leakage <35%. This critical separation corresponds to a cell diameter of 50 µm, consistent with the observed range where Bienertia's mesophyll cells start to develop their characteristic mature anatomy. Our results are robust to significant alterations in model assumptions and environmental conditions, their applicability extending even to aquatic plants.

Human kinetochores are swivel joints that mediate microtubule attachments.

Chromosome segregation is a mechanical process that requires assembly of the mitotic spindle - a dynamic microtubule-based force-generating machine. Connections to this spindle are mediated by sister kinetochore pairs, that form dynamic end-on attachments to microtubules emanating from opposite spindle poles. This bi-orientation generates forces that have been reported to stretch the kinetochore itself, which has been suggested to stabilise attachment and silence the spindle checkpoint. We reveal using three dimensional tracking that the outer kinetochore domain can swivel around the inner kinetochore/centromere, which results in large reductions in intra-kinetochore distance (delta) when viewed in lower dimensions. We show that swivel provides a mechanical flexibility that enables kinetochores at the periphery of the spindle to engage microtubules. Swivel reduces as cells approach anaphase, suggesting an organisational change linked to checkpoint satisfaction and/or obligatory changes in kinetochore mechanochemistry may occur before dissolution of sister chromatid cohesion.

Actomyosin Ring Formation and Tension Generation in Eukaryotic Cytokinesis.

Cell division facilitated by a contractile ring is an almost universal feature across all branches of cellular life, with the notable exception of higher plants. In all organisms that use a contractile ring for cell division, the process of cytokinesis can be divided into four distinct stages. Firstly, the cell needs to specify a location at which to place the cell division ring to ensure proper separation of the cell contents into two daughter cells. Secondly, the cell needs to be able to transport all the necessary components to this region, and construct the cell division ring reliably and efficiently. Thirdly, the cell division ring needs to generate contractile stress in a regulated manner, to physically cleave the mother cell into two daughter cells. Finally, the ring must be disassembled to allow for the final abscission and separation of the daughter cells. In this review, we will discuss some of the proposed mechanisms by which eukaryotic cells are able to complete the first three of these stages. While there is a good understanding of the mechanisms of division site specification in most organisms, and the mechanisms of actomyosin ring formation are well studied in fission and budding yeast, there is relatively poor understanding of how actomyosin interactions are able to generate contractile stresses during ring constriction, although a number of models have been proposed. We also discuss a number of myosin motor-independent mechanisms that have been proposed to generate contractile stress in various organisms.

Regulation of Gene Expression in Shewanella oneidensis MR-1 during Electron Acceptor Limitation and Bacterial Nanowire Formation.

UNLABELLED: In limiting oxygen as an electron acceptor, the dissimilatory metal-reducing bacterium Shewanella oneidensis MR-1 rapidly forms nanowires, extensions of its outer membrane containing the cytochromes MtrC and OmcA needed for extracellular electron transfer. RNA sequencing (RNA-Seq) analysis was employed to determine differential gene expression over time from triplicate chemostat cultures that were limited for oxygen. We identified 465 genes with decreased expression and 677 genes with increased expression. The coordinated increased expression of heme biosynthesis, cytochrome maturation, and transport pathways indicates that S. oneidensis MR-1 increases cytochrome production, including the transcription of genes encoding MtrA, MtrC, and OmcA, and transports these decaheme cytochromes across the cytoplasmic membrane during electron acceptor limitation and nanowire formation. In contrast, the expression of the mtrA and mtrC homologs mtrF and mtrD either remains unaffected or decreases under these conditions. The ompW gene, encoding a small outer membrane porin, has 40-fold higher expression during oxygen limitation, and it is proposed that OmpW plays a role in cation transport to maintain electrical neutrality during electron transfer. The genes encoding the anaerobic respiration regulator cyclic AMP receptor protein (CRP) and the extracytoplasmic function sigma factor RpoE are among the transcription factor genes with increased expression. RpoE might function by signaling the initial response to oxygen limitation. Our results show that RpoE activates transcription from promoters upstream of mtrC and omcA The transcriptome and mutant analyses of S. oneidensis MR-1 nanowire production are consistent with independent regulatory mechanisms for extending the outer membrane into tubular structures and for ensuring the electron transfer function of the nanowires. IMPORTANCE: Shewanella oneidensis MR-1 has the capacity to transfer electrons to its external surface using extensions of the outer membrane called bacterial nanowires. These bacterial nanowires link the cell's respiratory chain to external surfaces, including oxidized metals important in bioremediation, and explain why S. oneidensis can be utilized as a component of microbial fuel cells, a form of renewable energy. In this work, we use differential gene expression analysis to focus on which genes function to produce the nanowires and promote extracellular electron transfer during oxygen limitation. Among the genes that are expressed at high levels are those encoding cytochrome proteins necessary for electron transfer. Shewanella coordinates the increased expression of regulators, metabolic pathways, and transport pathways to ensure that cytochromes efficiently transfer electrons along the nanowires.

KiT: a MATLAB package for kinetochore tracking.

UNLABELLED: During mitosis, chromosomes are attached to the mitotic spindle via large protein complexes called kinetochores. The motion of kinetochores throughout mitosis is intricate and automated quantitative tracking of their motion has already revealed many surprising facets of their behaviour. Here, we present 'KiT' (Kinetochore Tracking)-an easy-to-use, open-source software package for tracking kinetochores from live-cell fluorescent movies. KiT supports 2D, 3D and multi-colour movies, quantification of fluorescence, integrated deconvolution, parallel execution and multiple algorithms for particle localization. AVAILABILITY AND IMPLEMENTATION: KiT is free, open-source software implemented in MATLAB and runs on all MATLAB supported platforms. KiT can be downloaded as a package from http://www.mechanochemistry.org/mcainsh/software.php The source repository is available at https://bitbucket.org/jarmond/kit and under continuing development. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: jonathan.armond@warwick.ac.uk.

Inferring the Forces Controlling Metaphase Kinetochore Oscillations by Reverse Engineering System Dynamics.

Kinetochores are multi-protein complexes that mediate the physical coupling of sister chromatids to spindle microtubule bundles (called kinetochore (K)-fibres) from respective poles. These kinetochore-attached K-fibres generate pushing and pulling forces, which combine with polar ejection forces (PEF) and elastic inter-sister chromatin to govern chromosome movements. Classic experiments in meiotic cells using calibrated micro-needles measured an approximate stall force for a chromosome, but methods that allow the systematic determination of forces acting on a kinetochore in living cells are lacking. Here we report the development of mathematical models that can be fitted (reverse engineered) to high-resolution kinetochore tracking data, thereby estimating the model parameters and allowing us to indirectly compute the (relative) force components (K-fibre, spring force and PEF) acting on individual sister kinetochores in vivo. We applied our methodology to thousands of human kinetochore pair trajectories and report distinct signatures in temporal force profiles during directional switches. We found the K-fibre force to be the dominant force throughout oscillations, and the centromeric spring the smallest although it has the strongest directional switching signature. There is also structure throughout the metaphase plate, with a steeper PEF potential well towards the periphery and a concomitant reduction in plate thickness and oscillation amplitude. This data driven reverse engineering approach is sufficiently flexible to allow fitting of more complex mechanistic models; mathematical models of kinetochore dynamics can therefore be thoroughly tested on experimental data for the first time. Future work will now be able to map out how individual proteins contribute to kinetochore-based force generation and sensing.

Detection of Diffusion Heterogeneity in Single Particle Tracking Trajectories Using a Hidden Markov Model with Measurement Noise Propagation.

We develop a Bayesian analysis framework to detect heterogeneity in the diffusive behaviour of single particle trajectories on cells, implementing model selection to classify trajectories as either consistent with Brownian motion or with a two-state (diffusion coefficient) switching model. The incorporation of localisation accuracy is essential, as otherwise false detection of switching within a trajectory was observed and diffusion coefficient estimates were inflated. Since our analysis is on a single trajectory basis, we are able to examine heterogeneity between trajectories in a quantitative manner. Applying our method to the lymphocyte function-associated antigen 1 (LFA-1) receptor tagged with latex beads (4 s trajectories at 1000 frames s(-1)), both intra- and inter-trajectory heterogeneity were detected; 12-26% of trajectories display clear switching between diffusive states dependent on condition, whilst the inter-trajectory variability is highly structured with the diffusion coefficients being related by D1 = 0.68D0 - 1.5 × 10(4) nm2 s(-1), suggestive that on these time scales we are detecting switching due to a single process. Further, the inter-trajectory variability of the diffusion coefficient estimates (1.6 × 10(2) - 2.6 × 10(5) nm2 s(-1)) is very much larger than the measurement uncertainty within trajectories, suggesting that LFA-1 aggregation and cytoskeletal interactions are significantly affecting mobility, whilst the timescales of these processes are distinctly different giving rise to inter- and intra-trajectory variability. There is also an 'immobile' state (defined as D < 3.0 × 103 nm2 s-1) that is rarely involved in switching, immobility occurring with the highest frequency (47%) under T cell activation (phorbol-12-myristate-13-acetate (PMA) treatment) with enhanced cytoskeletal attachment (calpain inhibition). Such 'immobile' states frequently display slow linear drift, potentially reflecting binding to a dynamic actin cortex. Our methods allow significantly more information to be extracted from individual trajectories (ultimately limited by time resolution and time-series length), and allow statistical comparisons between trajectories thereby quantifying inter-trajectory heterogeneity. Such methods will be highly informative for the construction and fitting of molecule mobility models within membranes incorporating aggregation, binding to the cytoskeleton, or traversing membrane microdomains.