Biology subjects

Siggel, M.

Publications and source records attributed to Siggel, M..

10 recordsLinked to original sources

bioRxiv2025

Helfrich Monte Carlo Flexible Fitting: physics-based, data-driven cell-scale simulations

Simulating entire cells represents the next frontier of computational biology. Achieving this goal requires methods that accurately describe cellular membranes across spatial and temporal scales. Although three-dimensional electron microscopy enables detailed membrane visualization, limitations on acquisition geometry, data quality, and field-of-view often result in fragmented membrane representations incompatible with simulations. To resolve this, here we introduce Helfrich Monte Carlo Flexible Fitting (HMFF), an approach that integrates experimental density data into physical simulations to determine membrane structure. Through the accompanying Mosaic software platform, we apply HMFF to influenza virus particles, Mycoplasma pneumoniae cells, and entire eukaryotic organelles. The resulting models enable multi-scale simulations spanning millions of lipids and proteins at experimentally determined positions, support quantitative morphological analysis, assess uncertainty in membrane localization, and reveal physical effects implicit in the data. Together, these capabilities establish a foundation for data-driven whole-cell simulations.

biophysics↗

bioRxiv2023

PyTME (Python Template Matching Engine): A fast, flexible, and multi-purpose template matching library for cryogenic electron microscopy data

Cryogenic electron microscopy (cryo-EM) is a key method in structural and cell biology. Analysis of cryo-EM images requires interpretation of noisy, low-resolution densities which relies on identifying the most probable orientation of macromolecules in a target using template matching. Many method-specific template matching software exist for single-particle cryo-EM, cryo-electron tomography (cryo-ET), or fitting atomic structures into averaged 3D maps of macromolecules. Here, we report the Python Template Matching Engine (pyTME), a software engine that consolidates method-specific template matching problems. The underlying library provides highly efficient template-matching implementation and abstract data structures for storing and manipulating input and output data. It scales favorable to large datasets, both with multiple CPUs and GPUs, compared to existing software enabling template matching of even unbinned cryo-ET data in hours, which was previously nearly impossible due to technical restraints. Any hardware-specific optimization needed for dealing with large data is automatically performed to increase ease of use and minimize user intervention. The efficiency and simplicity of pyTME will enable high throughput mining of a variety of cryo-EM and ET datasets in the future.

bioinformatics↗

bioRxiv2023

The Shape of Things in Cryo-ET: Why Emojis Aren't Just for Texts

Detecting specific biological macromolecules in cryogenic electron tomography (cryo-ET) data is frequently approached by applying cross-correlation-based 3D template matching. To reduce computational cost and noise, high binning is used to aggregate voxels before template matching. This remains a prevalent practice in both practical applications and method development. Here, we systematically evaluate the relation between template size, shape, and angular sampling to identify ribosomes in a ground truth annotated dataset. We show that at the commonly used binning, a detailed subtomogram average, a sphere, and the heart emoji [Formula] results in near-identical performance. Our findings indicate that with current template-matching practices, macromolecules can only be detected with high precision if their shape and size are sufficiently different from the background. Using theoretical considerations we rationalize our experimental results and discuss why at high binning, primarily low-frequency information remains and that template matching fails to be accurate because similarly shaped and sized macromolecules have similar low-frequency spectrums. We discuss these challenges and propose potential enhancements for future template-matching methodologies.

biophysics↗

bioRxiv2023

ColabSeg: An interactive tool for editing, processing, and visualizing membrane segmentations from cryo-ET data

Cellular cryo-electron tomography (cryo-ET) has emerged as a key method to unravel the spatial and structural complexity of cells in their near-native state at unprecedented molecular resolution. To enable quantitative analysis of the complex shapes and morphologies of lipid membranes, the noisy three-dimensional (3D) volumes must be segmented. Despite recent advances, this task often requires considerable user intervention to curate the resulting seg-mentations. Here, we present ColabSeg, a Python-based tool for processing, visualizing, cleaning, and fitting membrane segmentations from cryo-ET data for downstream analysis. ColabSeg makes many well-established algorithms for point-cloud processing easily available to the broad community of structural biologists for applications in cryo-ET through its graphical user interface (GUI). We demonstrate the usefulness of the tool with a range of use cases and biological examples. Finally, for a large Mycoplasma pneumoniae dataset of 50 tomograms, we show how ColabSeg enables high-throughput membrane segmentation, which can be used as valuable training dataset for fully automated convolutional neural network (CNN)-based segmentation.

bioinformatics↗

bioRxiv2023

The distance between the plasma membrane and the actomyosin cortex acts as a nanogate to control cell surface mechanics

Animal cell shape changes are controlled by the actomyosin cortex, a peripheral actin network tethered to the plasma membrane by membrane-to-cortex attachment (MCA) proteins. Previous studies have focused on how myosin motors or actin turnover can generate the local deformations required for morphogenesis. However, how the cell controls local actin nucleation remains poorly understood. By combining molecular engineering with biophysical approaches and in situ characterization of cortical actin network architecture, we show that membrane-to-cortex tethering determines the distance between the plasma membrane and the actomyosin cortex at the nanoscale of single actin nucleators. In turn, the size of this gap dictates actin filament production and the mechanical properties of the cell surface. Specifically, it tunes formin activity, controlling actin bundling and cortical tension. Our study defines the membrane-to-cortex distance as a nanogate that cells can open or close by MCA proteins to control the activity of key molecules at the cell surface.

biophysics↗

bioRxiv2022

Deciphering the conformations and dynamics of FG-nucleoporins in situ

The [~]120 MDa nuclear pore complex (NPC) acts as a gatekeeper for the molecular traffic between the nucleus and the cytosol. Small cargo readily passes through the transport channel, yet large cargo requires specialized nuclear transport receptors. While the scaffold structure that anchors the NPC in the double-layered nuclear envelope has been resolved to remarkable details, the spatial organization of intrinsically disordered nucleoporins (NUPs) within the central channel remains enigmatic. These so-called FG-NUPs account for about one-third of the total mass of the NPC and form the actual transport barrier. Here we combined site-specific fluorescent labeling in non-fixed cells and fluorescent lifetime imaging microscopy (FLIM) to directly decipher the conformations of an essential constituent of the permeability barrier, NUP98, inside the functioning NPCs using Fluorescence resonance energy transfer (FRET). With detailed measurements of the distance distribution of eighteen NUP98 segments combined with coarse-grained modeling, we mapped the uncharted biochemical environment inside the nanosized transport channel. We found that good-solvent conditions for a polymer dominate the inside of the nanosized NPC, expand the FG-domain in situ and facilitate nuclear transport, in sharp contrast to the collapsed NUP98 FG-chain in aqueous solution. The combination of fluorescence microscopy, high-resolution electron tomography, and molecular simulation opens a window into the so-far unresolved organization of the FG-NUPs at the center of NPC function, allowing us to reconcile scientific models of nuclear transport.

biophysics↗

bioRxiv2022

TriMem: A Parallelized Hybrid Monte Carlo Software for Efficient Simulations of Lipid Membranes

Lipid membranes are integral building blocks of living cells and perform a multitude of biological functions. Currently, molecular simulations of cellular-scale membrane structures at atomic resolution are nearly impossible, due to their size, complexity, and the large times-scales required. Instead, elastic membrane models are used to simulate membrane topologies and transitions between them, and to infer their properties and functions. Unfortunately, efficiently parallelized open-source simulation code to do so has been lacking. Here, we present TriMem, a parallel hybrid Monte Carlo simulation engine for triangulated lipid membranes. The kernels are efficiently coded in C++ and wrapped with Python for ease-of-use. The parallel implementation of the energy and gradient calculations and of Monte Carlo flip moves of edges in the triangulated membrane enable us to simulate also large and highly curved sub-cellular structures. For validation, we reproduce phase diagrams of vesicles with varying surface-to-volume ratios and area difference. The software can tackle a range of membrane remodelling processes on sub-cellular and cellular scales. Additionally, extensive documentation make the software accessible to the broad biophysics and computational cell biology communities.

biophysics↗

bioRxiv2022

Form follows function: Variable microtubule architecture in the malaria parasite

The malaria parasite undergoes a series of extensive morphological changes within its human host and mosquito vector. A scaffold of microtubules beneath a peripheral double membrane establishes and maintains the distinct shapes of all infectious forms, but the underlying structural basis remains unknown. Here we applied in situ electron cryo-tomography after focused ion beam milling to follow changes in the microtubule cytoskeleton throughout the Plasmodium life cycle. This revealed an unexpected level of structural and architectural diversity so far not observed in other organisms. Microtubules in migrating mosquito forms consist of 13 protofilaments reinforced by interrupted luminal helices. Conversely, gametocyte microtubules consist of 13 to 18 protofilaments with doublets, triplets and quadruplets of varying arrangements. We show the microtubule cytoskeleton within the native cellular context, highlighting structurally diverse apical rings which act as microtubule organising centres. This provides a unique view into a relevant human pathogen with an unusual microtubule cytoskeleton.

microbiology↗

bioRxiv2021

Artificial intelligence reveals nuclear pore complexity

Nuclear pore complexes (NPCs) mediate nucleocytoplasmic transport. Their intricate 120 MDa architecture remains incompletely understood. Here, we report a near-complete structural model of the human NPC scaffold with explicit membrane and in multiple conformational states. We combined AI-based structure prediction with in situ and in cellulo cryo-electron tomography and integrative modeling. We show that linker Nups spatially organize the scaffold within and across subcomplexes to establish the higher-order structure. Microsecond-long molecular dynamics simulations suggest that the scaffold is not required to stabilize the inner and outer nuclear membrane fusion, but rather widens the central pore. Our work exemplifies how AI-based modeling can be integrated with in situ structural biology to understand subcellular architecture across spatial organization levels. One sentence summaryAn AI-based, dynamic model of the human nuclear pore complex reveals how the protein scaffold and the nuclear envelope are coupled inside cells.

molecular biology↗

bioRxiv2021

FAM134B-RHD Protein Clustering Drives Spontaneous Budding of Asymmetric Membranes

Living cells constantly remodel the shape of their lipid membranes. In the endo-plasmic reticulum (ER), the reticulon homology domain (RHD) of the reticulophagy regulator 1 (RETR1/FAM134B) forms dense autophagic puncta that are associated with membrane removal by ER-phagy. In molecular dynamics (MD) simulations, we find that FAM134B-RHD spontaneously forms clusters, driven in part by curvature-mediated attraction. At a critical size, the FAM134B-RHD clusters induce the formation of membrane buds. The kinetics of budding depends sensitively on protein concentration and bilayer asymmetry. Our MD simulations shed light on the role of FAM134B-RHD in ER-phagy and show that membrane asymmetry can be used to modulate the kinetics barrier for membrane remodeling. Graphical TOC Entry O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

biophysics↗