Biology subjects

Marin, Z.

Publications and source records attributed to Marin, Z..

13 recordsLinked to original sources

bioRxiv2026

Microscope control with a natural language agent

Microscopy underpins modern biology, but acquiring high-quality data from complex experiments at scale remains challenging. Smart microscopy can standardize and automate data collection, but each experiment-specific solution requires coding expertise and development time. To address this, we present MicroClaw, an AI agent that advises on experiment- and system-specific parameters and approaches and collaboratively plans and executes diverse, complex, and reusable imaging workflows across microscope platforms, without requiring expert knowledge.

biophysics↗

bioRxiv2026

Multi-channel high-density single-molecule localization

Deep learning has enabled single-molecule localization microscopy (SMLM) at high emitter densities, but only for single channel systems. Here we present DECODE-Plex, a deep-learning-based framework to localize dense single molecules with overlapping point spread functions simultaneously in multiple channels. We showcase DECODE-Plex on experimental ultra-high density dual-color and 3D live-cell data. Packaged for ease of use, it will enable many groups to improve imaging speed and quality of multi-channel SMLM.

biophysics↗

bioRxiv2025

A correlative quantitative phase contrast and fluorescence super-resolution microscope for imaging molecules in their cellular context

Fluorescence microscopy has been widely used to reveal the spatial distribution of specifically labeled molecules, but it is blind to cellular context. Quantitative phase contrast microscopy (QPC) provides such complementary information. Here we have developed a platform that combines the QPC technique of correlative orientation-independent differential interference contrast (OI-DIC) microscopy with single-molecule super-resolution fluorescence microscopy. We demonstrate a detection sensitivity of 0.05 nm optical path difference, sufficient to detect single microtubules, and show its capability of 3D super-resolution fluorescence imaging in the cellular context. Additionally, we report deep-learning enabled digital staining, identifying nuclei, mitochondria and lipid droplets from OI-DIC data and demonstrate the potential of this approach for long-term live-cell imaging of organelles of interest without the need for fluorescence. OI-DIC can be easily integrated into most fluorescence microscopes and is readily adoptable by microscopy labs. ONE-SENTENCE TEASERA highly sensitive technique to visualize sub-cellular structures, dynamics, and molecules in their cellular context.

cell biology↗

bioRxiv2025

Multiscale imaging of cytokinesis

After separation of duplicated genetic material, animal cells divide by cytokinesis. This process involves several simultaneous and successive steps of molecular reorganization at cell membrane, cortex and the spindle apparatus as the cleavage furrow ingresses and the spindle is transformed into the intercellular bridge. Dozens of proteins play a role in cytokinesis. However, a comprehensive view of their successive nanoscale reorganizations over cytokinesis remains untractable with current microscopy methods. Here, we developed a multimodal imaging and analysis framework to investigate the relative organization of key cytokinetic molecules over time. We extract cytokinetic hallmarks from live-cell lattice light-sheet and expansion microscopy (ExM) to computationally define pseudotime and align nanoscale ExM images of cytokinesis. We discover a cytokinetic substep and create nanoscale maps of the intercellular bridge and the midbody in 6 stages for 20 involved molecules. We thus provide a framework for nanoscale analysis of cytokinesis, a process fundamental to life.

cell biology↗

bioRxiv2025

Evaluating MINFLUX experimental performance in silico

MINFLUX is a super-resolution microscopy technique with remarkable resolution for imaging and tracking. Its optical resolution is well understood under idealized conditions, but because of system complexity and experimental imperfections, actual performance can be much worse. Here we present SimuFLUX, a comprehensive and realistic simulator for MINFLUX. We use it to investigate performance limits caused by fluorophore dynamics, background, estimators, and misalignment, and to simulate experiments to optimize parameters and assess feasibility.

biophysics↗

bioRxiv2025

Feature-Driven Whole-Tissue Imaging with Subcellular Resolution

Understanding how subcellular structures and events shape tissue-wide phenomena remains a central challenge in biology. We present Multiscale Cleared Tissue Axially Swept Light-Sheet Microscopy (MCT-ASLM), a platform combining cm-scale imaging with targeted high-resolution interrogation of intact tissues in human-guided or autonomous modes. Capable of capturing fields of view up to 21 mm at micron-scale resolution, MCT-ASLM can seamlessly transition to submicron (~300 nm) isotropic resolution for targeted imaging. This versatility enables comprehensive studies of hierarchical organization and spatially complex processes, including mapping neuronal circuits in rat brains, visualizing glomerular innervation in mouse kidneys, and examining metastatic tumor microenvironments. By bridging subcellular to tissue-level scales, MCT-ASLM offers a powerful method for unraveling how local events contribute to global biological phenomena.

biophysics↗

bioRxiv2024

A general algorithm for consensus 3D cell segmentation from 2D segmented stacks

Cell segmentation is the foundation of a wide range of microscopy-based biological studies. Deep learning has revolutionized 2D cell segmentation, enabling generalized solutions across cell types and imaging modalities. This has been driven by the ease of scaling up image acquisition, annotation, and computation. However, 3D cell segmentation, requiring dense annotation of 2D slices still poses significant challenges. Manual labeling of 3D cells to train broadly applicable segmentation models is prohibitive. Even in high- contrast images annotation is ambiguous and time-consuming. Here we develop a theory and toolbox, u- Segment3D, for 2D-to-3D segmentation, compatible with any 2D method generating pixel-based instance cell masks. u-Segment3D translates and enhances 2D instance segmentations to a 3D consensus instance segmentation without training data, as demonstrated on 11 real-life datasets, >70,000 cells, spanning single cells, cell aggregates, and tissue. Moreover, u-Segment3D is competitive with native 3D segmentation, even exceeding when cells are crowded and have complex morphologies.

bioinformatics↗

bioRxiv2024

Mechanically Sheared Axially Swept Light-Sheet Microscopy

We present a mechanically sheared image acquisition format for upright and open-top light-sheet microscopes that automatically places data in its proper spatial context. This approach, which reduces computational post-processing and eliminates unnecessary interpolation or duplication of the data, is demonstrated on an upright variant of Axially Swept Light-Sheet Microscopy (ASLM) that achieves a field of view, measuring 774 x 435 microns, that is 3.2-fold larger than previous models and a raw and isotropic resolution of [~]420 nm. Combined, we demonstrate the power of this approach by imaging sub-diffraction beads, cleared biological tissues, and expanded specimens.

biophysics↗

bioRxiv2024

Adaptive Optics in an Oblique Plane Microscope

Adaptive optics (AO) can restore diffraction limited performance when imaging beyond superficial cell layers in vivo and in vitro, and as such is of interest for advanced 3D microscopy methods such as light-sheet fluorescence microscopy (LSFM). In a typical LSFM system, the illumination and detection paths are separate and subject to different optical aberrations. To achieve optimal microscope performance, it is necessary to sense and correct these aberrations in both light paths, resulting in a complex microscope system. Here, we show that in an oblique plane microscope (OPM), a type of LSFM with a single primary objective lens, the same deformable mirror can correct both the illumination and fluorescence detection. Besides reducing the complexity, we show that AO in OPM also restores the relative alignment of the light-sheet and focal plane, and that a projection imaging mode can stabilize and improve the wavefront correction in a sensorless AO format. We demonstrate OPM with AO on fluorescent nanospheres and by imaging the vasculature and cancer cells in zebrafish embryos embedded in a glass capillary, restoring diffraction limited resolution and improving the signal strength twofold.

cell biology↗

bioRxiv2024

navigate: an open-source platform for smart light-sheet microscopy.

navigate is a turnkey, open-source software solution designed to enhance light-sheet fluorescence microscopy (LSFM) by integrating smart microscopy techniques into a user-friendly framework. It enables automated, intelligent imaging with a Python-based control system that supports GUI-reconfigurable acquisition routines and the integration of diverse hardware sets. As a comprehensive package, navigate democratizes access to advanced LSFM capabilities, facilitating the development and implementation of smart microscopy workflows without requiring deep programming knowledge or specialized expertise in light-sheet microscopy.

biophysics↗

bioRxiv2023

The nanoscale organization of reticulon 4 shapes local endoplasmic reticulum structure in situ

The endoplasmic reticulums (ER) structure is directly linked to the many functions of the ER but its formation is not fully understood. We investigate how the ER-membrane curving protein reticulon 4 (Rtn4) localizes to and organizes in the membrane and how that affects local ER structure. We show a strong correlation between the local Rtn4 density and the local ER membrane curvature. Our data further reveal that the typical ER tubule possesses an elliptical cross-section with Rtn4 enriched at either end of the major axis. Rtn4 oligomers are linear-shaped, contain about five copies of the protein, and preferentially orient parallel to the tubule axis. Our observations support a mechanism in which oligomerization leads to an increase of the local Rtn4 concentration with each molecule increasing membrane curvature through a hairpin wedging mechanism. This quantitative analysis of Rtn4 and its effects on the ER membrane result in a new model of tubule shape as it relates to Rtn4. SummaryRtn4 forms linear-shaped oligomers that contain an average of five Rtn4 proteins, localize to the sides of elliptical tubules, prefer orientations near parallel to the tubule axis, and increase local curvature of the ER membrane by increasing local Rtn4 density.

cell biology↗

bioRxiv2023

Extracting nanoscale morphology from localizations

Membrane surface reconstruction at the nanometer scale is required for understanding mechanisms of subcellular shape change. This historically has been the domain of electron microscopy, but extraction of surfaces from specific labels is a difficult task in this imaging modality. Existing methods for extracting surfaces from fluorescence microscopy have poor resolution or require high-quality super-resolution data that is manually cleaned and curated. Here we present NanoWrap, a new method for extracting surfaces from generalized single-molecule localization microscopy (SMLM) data. This makes it possible to study the shape of specifically-labelled membraneous structures inside of cells. We validate NanoWrap using simulations and demonstrate its reconstruction capabilities on SMLM data of the endoplasmic reticulum and mitochondria. NanoWrap is implemented in the open-source Python Microscopy Environment. SIGNIFICANCEWe introduce a novel tool for reconstruction of subcellular membrane surfaces from single-molecule localization microscopy data and use it to visualize and quantify local shape and membrane-membrane interactions. We benchmark its performance on simulated data and demonstrate its fidelity to experimental data.

biophysics↗

bioRxiv2020

PYMEVisualize: an open-source tool for exploring 3D super-resolution data

Localization-based super-resolution microscopy techniques such as PALM, STORM, and PAINT are increasingly critical tools for biological discovery. These methods generate lists of single fluorophore positions that capture nanoscale structural details of subcellular organisation, but to develop biological insight, we must post-process and visualize this data in a meaningful way. A large number of algorithms have been developed for localization post-processing, transforming point data into representations which approximate traditional microscopy images, and performing specific quantitative analysis directly on points. Implementations of these algorithms typically stand in isolation, necessitating complex workflows involving multiple different software packages. Here we present PYMEVisualize, an open-source tool for the interactive exploration and analysis of 3D, multicolor, single-molecule localization data. PYMEVisualize brings together a broad range of the most commonly used post-processing, density mapping, and direct quantification tools in an easy-to-use and extensible package. This software is one component of the PYthon Microscopy Environment (python-microscopy.org), an integrated application suite for light microscopy acquisition, data storage, visualization, and analysis built on top of the scientific Python environment.

biophysics↗