Biology subjects

Larabell, C.

Publications and source records attributed to Larabell, C..

8 recordsLinked to original sources

bioRxiv2026

Reverse engineering Lewy bodies suggests alpha-synuclein pathology as condensatopathy

Understanding how soluble monomeric alpha-synuclein transitions into pathological alpha-synuclein (Lewy bodies) has remained a central challenge in neurodegeneration. Existing models, largely based on treating cells and animals with pre-formed alpha-synuclein fibrils cannot account for the emergence of the first inclusion without pre-existing seeds. Here, we combine in vitro reconstitutions, computational modeling and a minimal cellular system to show that phase separation of alpha-synuclein with an interacting scaffold can recapitulate Lewy body-like structures. An unbiased proteomics screen, live-cell imaging, correlative light-electron microscopy, and soft X-ray tomography show that Lewy body-like structures are associated with redistribution of actin and membrane-bound organelles, with mitochondria accumulating at their periphery in an actin-dependent manner. Structural analyses further indicate that alpha-synuclein condensates provide local environments in which the insoluble beta-sheets can form. Together, these findings support a seed-independent trajectory from soluble alpha-synuclein through condensation and progressive immobilization to Lewy body-like assemblies and, subsequently, insoluble beta-sheet fibrils. This framework offers a new mechanistic route for understanding the disease progression and promises to guide the design of innovative therapeutic interventions.

neuroscience↗

bioRxiv2025

Interior soft x-ray tomography with sparse global sampling

Objective. To investigate the feasibility of interior imaging reconstruction in soft X-ray tomography to achieve higher spatial resolution cellular imaging, including whole-cell imaging. Approach. We develop an alignment and reconstruction algorithm that enables a combination of a low number of images from sparse whole-cell imaging with a high-resolution local interior scan. Based on numerical simulations, we demonstrate that combined reconstructions mitigate the depth of field limitation in high-resolution scans, enable radiation dose optimization, and yield quantitative X-ray absorption values with sparse sampling. Furthermore, we validate our numerical approach using experimental data from two different cell types and demonstrate that combined reconstruction is a reliable method for obtaining high and local spatial resolution within the volume of a whole cell. Significance. The developed sparse reconstruction algorithm provides a robust and faithful visualization of cellular organelles with soft X-ray tomography. A mesoscale imaging approach, such as an interior tomography scan, enables one to "scout" and zoom into the volumes of interest that contain organelles of interest. Utilizing sparse reconstructions, this increase in spatial resolution is achieved without sacrificing larger volume imaging, providing information on the relative position of all organelles within a cell.

cell biology↗

bioRxiv2024

Automated segmentation of soft X-ray tomography: native cellular structure with sub-micron resolution at high throughput for whole-cell quantitative imaging in yeast

Soft X-ray tomography (SXT) is an invaluable tool for quantitatively analyzing cellular structures at sub-optical isotropic resolution. However, it has traditionally depended on manual segmentation, limiting its scalability for large datasets. Here, we leverage a deep learning-based auto-segmentation pipeline to segment and label cellular structures in hundreds of cells across three Saccharomyces cerevisiae strains. This task-based pipeline employs manual iterative refinement to improve segmentation accuracy for key structures, including the cell body, nucleus, vacuole, and lipid droplets, enabling high-throughput and precise phenotypic analysis. Using this approach, we quantitatively compared the 3D whole-cell morphometric characteristics of wild-type, VPH1-GFP, and vac14 strains, uncovering detailed strain-specific cell and organelle size and shape variations. We show the utility of SXT data for precise 3D curvature analysis of entire organelles and cells and detection of fine morphological features using surface meshes. Our approach facilitates comparative analyses with high spatial precision and statistical throughput, uncovering subtle morphological features at the single cell and population level. This workflow significantly enhances our ability to characterize cell anatomy and supports scalable studies on the mesoscale, with applications in investigating cellular architecture, organelle biology, and genetic research across diverse biological contexts. Significance StatementO_LISoft X-ray tomography offers many powerful features for whole-cell multi-organelle imaging, but, like other high resolution volumetric imaging modalities, is typically limited by low throughput due to laborious segmentation. C_LIO_LIAuto-segmentation for soft X-ray tomography overcomes this limitation, enabling statistical 3D morphometric analysis of multiple organelles in whole cells across cell populations. C_LIO_LIThe combination of high 3D resolution of SXT data with statistically useful throughput represents an avenue for more thorough characterizations of cells in toto and opens new mesoscale biological questions and statistical whole-cell modeling of organelle and cell morphology, interactions, and responses to perturbations. C_LI

cell biology↗

bioRxiv2023

Ensemble and Iterative Engineering for Maximized Bioconversion to the Blue Pigment, Indigoidine from Non-Canonical Sustainable Carbon Sources

While many heterologous molecules can be produced via microbial bioconversion processes, maximizing their titers, rates, and yields from lignin-derived carbon streams remains challenging. Growth coupling can not only increase titers and yields but also shift the production period from stationary phase to growth phase. These methods for designing growth-coupling strains however require multi-gene edits for implementation which may be perceived as impractical. Here, we computationally evaluated 4,114 potential solutions for growth coupling para-coumarate to indigoidine production and prototype two cut sets in Pseudomonas putida KT2440. We used adaptive laboratory evolution (ALE) on the initial triple deletion strain to restore growth on p-CA. Using X-ray tomography on this post-ALE strain we revealed increased cell density and decreased cell volume. Proteomics identified upregulated peroxidases that mitigate reactive oxygen species formation. Nine iterative stepwise modifications further informed by model-guided and rational approaches realized a growth coupled strain that produced 7.3 g/L indigoidine at 77% MTY in para-coumarate minimal medium. These ensemble strategies provide a blueprint for producing target molecules at high product titers, rates, and yields. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/532821v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@f0754aorg.highwire.dtl.DTLVardef@a45d24org.highwire.dtl.DTLVardef@df0596org.highwire.dtl.DTLVardef@1e7e140_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2023

Aberrant phase separation is a common killing strategy of positively charged peptides in biology and human disease

Positively charged repeat peptides are emerging as key players in neurodegenerative diseases. These peptides can perturb diverse cellular pathways but a unifying framework for how such promiscuous toxicity arises has remained elusive. We used mass-spectrometry-based proteomics to define the protein targets of these neurotoxic peptides and found that they all share similar sequence features that drive their aberrant condensation with these positively charged peptides. We trained a machine learning algorithm to detect such sequence features and unexpectedly discovered that this mode of toxicity is not limited to human repeat expansion disorders but has evolved countless times across the tree of life in the form of cationic antimicrobial and venom peptides. We demonstrate that an excess in positive charge is necessary and sufficient for this killer activity, which we name polycation poisoning. These findings reveal an ancient and conserved mechanism and inform ways to leverage its design rules for new generations of bioactive peptides.

cell biology↗

bioRxiv2022

An ESCRT-dependent pathway of Nuclear and Cytoplasmic Spatial PQC is coordinated at Nuclear Vacuolar Junctions

Effective Protein Quality Control (PQC), essential for cellular health, relies on spatial sequestration of misfolded proteins into defined inclusions. Here we elucidate the coordination of nuclear and cytoplasmic spatial PQC. While cytoplasmic misfolded proteins concentrate in a cytoplasmic, perinuclear Juxta Nuclear Quality control compartment (JUNQ), nuclear misfolded proteins sequester into a perinucleolar IntraNuclear Quality control compartment (INQ). Particle tracking reveals the INQ and JUNQ converge to face each other across the nuclear envelope at a site proximal to the Nuclear-Vacuolar Junction (NVJ) marked by perinuclear ESCRT-II/-III protein Chm7. Strikingly, this ESCRT-dependent convergence facilitates VPS4-dependent vacuolar clearance of misfolded cytoplasmic and nuclear proteins, the latter entailing extrusion of nuclear INQ into the vacuole. We propose perinuclear ESCRT coordinates spatial PQC at nuclear-vacuolar contacts to facilitate vacuolar clearance of nuclear and cytoplasmic misfolded proteins.

biochemistry↗

bioRxiv2018

Spontaneous driving forces give rise to protein-RNA condensates with coexisting phases and complex material properties

Collective phase transitions, including phase separation and gelation of multivalent protein and RNA molecules appears to underlie the biogenesis of biomolecular condensates such as membraneless organelles. In vivo, these condensates encompass hundreds of distinct types of molecules that are often organized into multi-layered structures supporting the differential partitioning of molecules into distinct regions with distinct material properties. The interplay between driven (active) versus spontaneous (passive) processes that are required for enabling the formation of condensates with coexisting layers of distinct material properties remains unclear. Here, we investigate the role of spontaneous driving forces as determinants of protein-RNA condensates with complex morphologies and distinct material properties. Through the use of systematic in vitro experiments and simulations based on coarse-grained models we find that that the collective interactions among the simplest, biologically relevant proteins and archetypal RNA molecules are sufficient for driving the spontaneous emergence of multi-layered condensates with distinct material properties. Our results demonstrate that key properties of protein-RNA condensates such as their overall morphologies, internal dynamics, and the selective partitioning of substrates are governed specific amino acid chemistries as well as RNA sequence and secondary structure. Our findings yield a clear set of heuristics regarding homo- and heterotypic interactions that are likely to be relevant for understanding the interplay between active and passive processes that control the formation of functional biomolecular condensates.

biophysics↗

bioRxiv2018

PSF correction in soft x-ray tomography

In this manuscript, we introduce a linear approximation of the forward model of soft x-ray tomography (SXT), such that the reconstruction is solvable by standard iterative schemes. This linear model takes into account the three-dimensional point spread function (PSF) of the optical system, which consequently enhances the reconstruction data. The feasibility of the model is demonstrated on both simulated and experimental data, based on theoretically estimated and experimentally measured PSFs.

cell biology↗