Biology subjects

Smith, C. S.

Publications and source records attributed to Smith, C. S..

14 recordsLinked to original sources

bioRxiv2026

Organelle Volume Facilitates Spindle Positioning During C. elegans Female Meiosis

Cortical positioning of oocyte meiotic spindles is required for reducing chromosome number by segregating chromosomes into polar bodies. In C. elegans, kinesin-1 transports membrane-bound organelles inward into a central ball that is hypothesized to push the meiotic spindle outward. Using focused ion beam scanning electron microscopy, we found that the percent volume occupied by membrane-bound organelles was 28% in a mature oocyte that has completed endocytosis of the yolk precursor, vitellogenin, compared to 17% in a less mature oocyte that has not yet endocytosed vitellogenin. We therefore hypothesized that blocking endocytosis of vitellogenin would reduce the size of the central ball of organelles packed inward by kinesin-1 and limit outward movement of the spindle. Depletion of vitellogenin or proteins required for endocytosis resulted in a smaller central volume of kinesin-coated organelles and defective spindle positioning. A computer simulation of a simple exclusion model faithfully recapitulated wildtype and mutant spindle position phenotypes. These results support a volume exclusion model for positioning acentriolar meiotic spindles.

cell biology↗

bioRxiv2026

System Identification and Control for Optogenetics in Mammalian Nucleocytoplasmic Transport

Optogenetics enables experiments in out-of-equilibrium conditions to clarify biological mechanisms and quantify biophysical parameters. However, modelling and control techniques to study mammalian cell biology under optogenetic perturbation remain underutilised. Here, we benchmark these methods within mammalian cells by steering nucleocytoplasmic transport via the optogenetic LEXY protein in outcome-driven microscopy. First, we employ system identification to obtain models that predict transport dynamics by minimising the prediction error. We quantify this prediction accuracy for one biophysical model and two black-box models. Second, we evaluate closed-loop control efficacy by steering transport along a predefined trajectory using model-free Proportional Integral (PI) control, model-based Linear Quadratic Regulation (LQR) and Model Predictive Control (MPC). Both the predictive models and the applied control techniques demonstrate robust performance against cell-to-cell variation. This biological variation is quantified by the parameter distributions obtained from model identification with single-cell trajectories. While we show that model-free techniques such as PI and gain-scheduled PI achieve steering without explict model knowledge, predictive architectures offer better performance under this cell-to-cell variation and time-varying setpoints. Moreover, black-box predictive accuracy suggests that this model-based control is possible, even when explicit mechanistic understanding is missing. Ultimately, we demonstrate that predictive modelling and optogenetics enable quantitative characterisation and precise manipulation of mammalian cells, while offering practical guidelines for the implementation of these techniques. SIGNIFICANCEOptogenetics provides the unique ability to steer cellular processes with light. Variable and localised light inputs allow us to extract more data and guide living cells to specific states. Despite this potential, application of predictive modelling and control techniques with optogenetics remain underutilised in mammalian cell biology. Here, we benchmark these techniques within mammalian cells to steer nucleocytoplasmic transport. Benchmarking these techniques demonstrates their direct applicability to mammalian systems, enabling the extraction of new biological insight in outcome-driven microscopy.

bioengineering↗

bioRxiv2025

Clustered VEGF Nanoparticles in Microporous Annealed Particle (MAP) Hydrogel Accelerates Functional Recovery and Brain Tissue Repair after Stroke

Ischemic stroke, a blockage in the vasculature of the brain that results in insufficient blood flow, is one of the worlds leading causes of disability. The cascade of inflammation and cell death that occurs immediately following stroke drives vascular and functional loss that does not fully recover over time, and no FDA-approved therapies exist that stimulate regeneration post-stroke. We have previously developed a hydrogel scaffold that delivered heparin nanoparticles with and without VEGF bound to their surface to promote angiogenesis and reduce inflammation, respectively. However, the inclusion of the naked heparin nanoparticles warranted concern over the development of bleeding complications. Here, we explore how microporous annealed particle (MAP) scaffolds functionalized with VEGF coated heparin nanoparticles can both reduce inflammation and promote angiogenesis - without the inclusion of free heparin nanoparticles. We show that our updated design not only successfully promotes de novo tissue formation, including the development of mature vessels and neurite sprouting, but it also leads to functional improvement in a photothrombotic stroke model. In addition, we find increased astrocyte infiltration into the infarct site correlated with mature vessel formation. This work demonstrates how our biomaterial design can enhance endogenous regeneration post-stroke while eliminating the need for excess heparin.

bioengineering↗

bioRxiv2024

Effects of Concussion on the Relative Contributions of Sensorimotor Memories during Adaptation to Unpredictable Spring-Like Loads

We examined the extent to which concussion impacts how implicit sensorimotor memories are used to compensate for changes in hand-held loads during goal-directed reaching. Recently concussed individuals performed computerized cognition tests and a robotic test of sensorimotor adaptation on three occasions: as soon as possible after injury; after clearance to return to activity; three months after injury. Non-concussed individuals (controls) were tested at inter-session intervals mimicking concussed group intervals. During robotic testing, subjects grasped the handle of a horizontal planar robot while reaching repeatedly to a target. The robot exerted spring-like forces that changed unpredictably between trials; this allowed us to estimate contributions of implicit sensorimotor memories to trial-by-trial performance by fitting a computational model to the time series of reach errors and robot forces. Symptom severity varied considerably within the concussed group at the first session. Computerized cognition tests revealed longer reaction times in the concussed group relative to control group in Session 1 only. Concussed subjects likewise had slower reaction time in the reaching task during the first but not later sessions. Computational modeling found abnormally high values of effective limb compliance in concussed individuals relative to the control group in the first session only, but did not find group differences in how sensorimotor memories contribute to reach adaptation in any session. Analysis of control group models identified a practice effect affecting the memory coefficients that may have masked initial effects of concussion on how implicit memories contribute to sensorimotor adaptation. Although a practice effect and a heterogeneous concussed cohort preclude strong conclusions, our findings suggest procedural improvements that may decrease the robotic tests sensitivity to practice effects and increase its sensitivity to concussion-related changes in how implicit memories contribute to sensorimotor adaptation to unpredictable hand-held loads during reaching.

neuroscience↗

bioRxiv2024

Self-Assembled Origami Neural Probes for Scalable, Multifunctional, Three-Dimensional Neural Interface

Flexible intracortical neural probes have drawn attention for their enhanced longevity in high-resolution neural recordings due to reduced tissue reaction. However, the conventional monolithic fabrication approach has met significant challenges in: (i) scaling the number of recording sites for electrophysiology; (ii) integrating of other physiological sensing and modulation; and (iii) configuring into three-dimensional (3D) shapes for multi-sided electrode arrays. We report an innovative self-assembly technology that allows for implementing flexible origami neural probes as an effective alternative to overcome these challenges. By using magnetic-field-assisted hybrid self-assembly, multiple probes with various modalities can be stacked on top of each other with precise alignment. Using this approach, we demonstrated a multifunctional device with scalable high-density recording sites, dopamine sensors and a temperature sensor integrated on a single flexible probe. Simultaneous large-scale, high-spatial-resolution electrophysiology was demonstrated along with local temperature sensing and dopamine concentration monitoring. A high-density 3D origami probe was assembled by wrapping planar probes around a thin fiber in a diameter of 80[~]105 m using optimal foldable design and capillary force. Directional optogenetic modulation could be achieved with illumination from the neuron-sized micro-LEDs (LEDs) integrated on the surface of 3D origami probes. We could identify angular heterogeneous single-unit signals and neural connectivity 360{degrees} surrounding the probe. The probe longevity was validated by chronic recordings of 64-channel stacked probes in behaving mice for up to 140 days. With the modular, customizable assembly technologies presented, we demonstrated a novel and highly flexible solution to accommodate multifunctional integration, channel scaling, and 3D array configuration.

neuroscience↗

bioRxiv2024

Using splines for point spread function calibration atnon-uniform depths in localization microscopy

Single-molecule localization microscopy methods extensively leverage the microscope point spread function (PSF) for fitting the molecules. Calibrating an accurate PSF model is especially difficult in the presence of depth-dependent aberrations which alter the PSF shape depending on the imaging depth. The aberrations at depths of a few micrometers become substantial enough to considerably impoverish the conventional calibration methods performance. In our work, we propose a novel spline model which enables the depth-dependent PSF model calibration by interpolating between the beads at arbitrary depths. We show that diffspline reduces the PSF intensity overestimation by 67.8 percentage points and underestimation by 21.8 percentage points. Moreover, it eliminates the depth-dependent bias and improves the localization precision two-fold compared to previous approaches.

biophysics↗

bioRxiv2021

Drift correction in localization microscopy using entropy minimization

Localization microscopy offers resolutions down to a single nanometer, but currently requires additional dedicated hardware or fiducial markers to reduce resolution loss from drift of the sample. Drift estimation without fiducial markers is typically implemented using redundant cross correlation (RCC). We show that RCC has sub-optimal precision and bias, which leaves room for improvement. Here, we minimize a bound on the entropy of the obtained localizations to efficiently compute a precise drift estimate. Within practical compute-time constraints, simulations show a 5x improvement in drift estimation precision over the widely used RCC algorithm. The algorithm operates directly on fluorophore localizations and is tested on simulated and experimental datasets in 2D and 3D. An open source implementation is provided, implemented in Python and C++, and can utilize a GPU if available.

biophysics↗

bioRxiv2021

Structured illumination microscopy with noise-controlled image reconstructions

Super-resolution structured illumination microscopy (SIM) has become a widely used method for biological imaging. Standard reconstruction algorithms, however, are prone to generate noise-specific artefacts that limit their applicability for lower signal-to-noise data. Here, we present a physically realistic noise model that explains the structured noise artefact and that is used to motivate new complementary reconstruction approaches. True Wiener-filtered SIM optimizes contrast given the available signal-to-noise ratio, flat-noise SIM fully overcomes the structured noise artefact while maintaining resolving power. Both methods eliminate ad-hoc user adjustable reconstruction parameters in favour of physical parameters, enhancing objectivity. The new reconstructions point to a trade-off between contrast and a natural noise appearance. This trade-off can be partly overcome by additional notch filtering, but at the expense of a decrease in signal-to-noise ratio. The benefits of the proposed approaches are demonstrated on focal adhesion and tubulin samples in 2D and 3D, and on nano-fabricated fluorescent test patterns.

biophysics↗

bioRxiv2020

Matchathon: A guide to student-faculty connections in PhD programs

Relevant and impactful mentors are essential to a graduate students career. Finding mentors can be challenging in umbrella programs with hundreds of faculty members. To foster connections between potential mentors and students with similar research interests, we created a Matchathon event, which has successfully enabled students to find mentors. We developed an easy-to-use R Shiny app (https://github.com/UM-OGPS/matchathon/) to facilitate matching and organizing the event that can be used at any institution. It is our hope that this resource will improve the environment and retention rates for students in the academy. The open source app is publicly available on the web (app: https://UM-OGPS.shinyapps.io/matchathon/; source code: https://github.com/UM-OGPS/matchathon/).

scientific communication and education↗

bioRxiv2020

Dendritic localization of mRNA in Drosophila Mushroom Body Output Neurons

Memory-relevant neuronal plasticity is believed to require local translation of new proteins at synapses. Understanding this process requires the visualization of the relevant mRNAs within these neuronal compartments. Here we used single-molecule fluorescence in situ hybridization (smFISH) to localize mRNAs at subcellular resolution in the adult Drosophila brain. mRNAs for subunits of nicotinic acetylcholine receptors and kinases could be detected within the dendrites of co-labelled Mushroom Body Output Neurons (MBONs) and their relative abundance showed cell-specificity. Moreover, aversive olfactory learning produced a transient increase in the level of CaMKII mRNA within the dendritic compartments of the {gamma}5{beta}'2a MBONs. Localization of specific mRNAs in MBONs before and after learning represents a critical step towards deciphering the role of dendritic translation in the neuronal plasticity underlying behavioural change in Drosophila.

neuroscience↗

bioRxiv2020

Massive windborne migration of Sahelian insects: Diversity, seasonality, altitude, and direction

Knowledge on long-distance migration of insects is especially important for food security, public health, and conservation-issues that are especially significant in Africa. During the wet season, the Sahel nourishes diverse life forms which are soon purged by the long dry season. Windborne migration is a key strategy enabling exploitation of such ephemeral havens. However, our knowledge of these large-scale movements remains sparse due to the virtual invisibility of insects flying at altitude. In this first cross-season investigation (3 years) of the aerial insect fauna over Africa, we sampled crepuscular and nocturnal insects flying 40-290 m above ground in four Sahelian villages in Mali, using sticky nets mounted on tethered helium-filled balloons. Nearly half a million insects were caught, representing at least thirteen insect orders following preliminary sorting of the collections. At least 100 insect families were determined to have been captured at altitude in samples collected on 222 nets, obtained in 125 collections over 96 nights. Control nets (raised momentarily to >40 m during system launch and retrieval) confirmed that the insects were captured at altitude, not near the ground. Thirteen ecologically and phylogenetically diverse species were studied in detail. The flight activity of all species peaked during the wet season every year across localities up to ~100 km apart, and occurred over multiple nights, suggesting regular migrations. Species differed in flight altitude, seasonality, and correlations with aerial temperatures, humidity, and wind speed. All taxa exhibited frequent migrations on southerly winds, accounting for the recolonization of the Sahel from southern source populations. "Return" southward movement at the end of the wet season occurred in most taxa but no selectivity for such winds was detected. Extrapolation of aerial density to estimate the seasonal number of migrants crossing Mali at latitude 14{degrees}N suggested numbers in the trillions, even for the modestly abundant taxa. Assuming 2-10 hours of flight, the nightly distances traversed exceed tens and even hundreds of kilometers. Two migration strategies were proposed: "residential Sahelian migration" and "round trip migration". The unprecedented magnitude and diversity of long-range windborne insect migrations highlight the importance of this life strategy in their impact on Sahelian and neighboring ecosystems.

ecology↗

bioRxiv2019

Localization microscopy at doubled precision with patterned illumination

MINFLUX offers a breakthrough in single molecule localization precision, but suffers from a tiny field-of-view and a lack of practical parallelism. Here, we combine centroid estimation and illumination pattern induced photon count variations in a conventional widefield imaging setup to extract position information over a typical micron sized field-of-view. We show a near twofold improvement in precision over standard localization with the same photon count on DNA-origami nano-structures.

molecular biology↗

bioRxiv2018

An Automated Bayesian Pipeline for Rapid Analysis of Single-Molecule Binding Data

Single-molecule binding assays enable the study of how molecular machines assemble and function. Current algorithms can identify and locate individual molecules, but require tedious manual validation of each spot. Moreover, no solution for high-throughput analysis of single-molecule binding data exists. Here, we describe an automated pipeline to analyze single-molecule data over a wide range of experimental conditions. We benchmarked the pipeline by measuring the binding properties of the well-studied, DNA-guided DNA endonuclease, TtAgo, an Argonaute protein from the Eubacterium Thermus thermophilus. We also used the pipeline to extend our understanding of TtAgo by measuring the proteins binding kinetics at physiological temperatures and for target DNAs containing multiple, adjacent binding sites.

molecular biology↗

bioRxiv2017

Single-molecule FISH in Drosophila muscle reveals location dependent mRNA composition of megaRNPs

Single-molecule fluorescence in-situ hybridization (smFISH) provides direct access to the spatial relationship between nucleic acids and specific subcellular locations. The ability to precisely localize a messenger RNA can reveal key information about its regulation. Although smFISH is well established in cell culture or thin sections, methods for its accurate application to tissues are lacking. The utility of smFISH in thick tissue sections must overcome several challenges, including probe penetration of fixed tissue, accessibility of target mRNAs for probe hybridization, high fluorescent background, spherical aberration along the optical axis, and image segmentation of organelles. Here we describe how we overcame these obstacles to study mRNA localization in Drosophila larval muscle samples that approach 50 m thickness. We use sample-specific optimization of smFISH, particle identification based on maximum likelihood testing, and 3-dimensional multiple-organelle segmentation. The latter allows using independent thresholds for different regions of interest within an image stack. Our approach therefore facilitates accurate measurement of mRNA location in thick tissues.

cell biology↗