Biology subjects

Matti, U.

Publications and source records attributed to Matti, U..

11 recordsLinked to original sources

bioRxiv2025

VMAT2 dysfunction impairs vesicular dopamine uptake, driving its oxidation and α-synuclein pathology in DJ-1-linked Parkinson's disease neurons

Parkinsons disease (PD) is characterized by -synuclein accumulation and dopaminergic neuron degeneration, with dopamine (DA) oxidation emerging as a key pathological driver. However, the mechanisms underlying this neurotoxic process remain unclear. Using PD patient-derived and CRISPR-engineered iPSC midbrain dopaminergic neurons lacking DJ-1, we identified defective sequestration of cytosolic DA into synaptic vesicles, which culminated in DA oxidation and -synuclein accumulation. In-depth proteomics, state-of-the-art imaging, and ultrasensitive DA probes uncovered that decreased VMAT2 protein and function impaired vesicular DA uptake, resulting in reduced vesicle availability and abnormal vesicle morphology. Furthermore, VMAT2 activity and vesicle endocytosis are processes dependent on ATP, which is notably reduced in DJ-1-deficient dopaminergic neurons. ATP supplementation restored vesicular function and alleviated DA-related pathologies in mutant dopaminergic neurons. This study reveals an ATP-sensitive mechanism that regulates DA homeostasis through VMAT2 and vesicle dynamics in midbrain dopaminergic neurons, highlighting enhanced DA sequestration as a promising therapeutic strategy for PD. TeaserLoss of DJ-1 interferes with VMAT2 function and vesicle dynamics, leading to DA oxidation and -synuclein pathology in PD neurons.

neuroscience↗

bioRxiv2025

Chlamydial membrane vesicles deliver the chlamydial porin OmpA to mitochondria to inhibit apoptosis

Chlamydiae are obligate intracellular bacteria that inhibit mitochondrial apoptosis to maintain integrity of the host cell. We have previously reported that a chlamydial outer membrane {beta}-barrel protein, the porin OmpA, can during ectopic expression inhibit mitochondrial apoptosis through direct interaction with the BCL-2-family effectors BAX and BAK. We here show that OmpA from Chlamydia trachomatis (Ctr) uses membrane vesicles for its delivery to the outer mitochondrial membrane during Ctr infection. Using a number of imaging and fractionation techniques, we show that OmpA during infection reaches mitochondria and is inserted into mitochondrial membranes. Purified membrane vesicles (MV) from Ctr-infected cells contained OmpA. When added to uninfected cells, MV fused with mitochondrial membranes, causing the interaction of OmpA with BAK and the cytosolic retro-translocation of BAX. MV addition to uninfected cells protected the cells against apoptosis. We propose a structural model of this BAK inhibition by OmpA that reenacts the inhibition of BAK by the mitochondrial porin VDAC2. The results provide evidence that the porin from Chlamydia, as well as the structurally similar porin from the related Simkania, specifically exploits its relationship to mitochondrial porins to protect the infected cell against apoptosis and to enable intracellular growth of the bacteria in human cells.

cell biology↗

bioRxiv2022

Assessment of 3D MINFLUX data for quantitative structural biology in cells revisited

Prakash and Curd provide a re-analysis1 of individual datasets taken from our report2 demonstrating MINFLUX 3D imaging in cells. Their evaluation confirms the unique localization precision provided by MINFLUX2,3 featuring a standard deviation of {sigma} = 1-3 nm. We appreciate their confirmation and also welcome the opportunity to clarify their remaining points. The hitherto almost unconceivable 3D localization precision attained by MINFLUX is likely to hold the key to an all-optical dynamical structural biology.

biophysics↗

bioRxiv2021

Global fitting for high-accuracy multi-channel single-molecule localization

Multi-channel detection in single-molecule localization microscopy (SMLM) greatly increases information content for various biological applications. Here, we present globLoc, a graphics processing unit (GPU) based global fitting algorithm with flexible PSF modeling and parameter sharing, to extract maximum information from multi-channel single molecule data. We show, both in simulations and experiments, that global fitting can substantially improve the 3D localization precision for biplane and 4Pi SMLM and color assignment for ratiometric multicolor imaging.

molecular biology↗

bioRxiv2021

Maximum-likelihood model fitting for quantitative analysis of SMLM data

Quantitative analysis is an important part of any single-molecule localization microscopy (SMLM) data analysis workflow to extract biological insights from the coordinates of the single fluorophores, but current approaches are restricted to simple geometries or do not work on heterogenous structures. Here, we present LocMoFit (Localization Model Fit), an open-source framework to fit an arbitrary model directly to the localization coordinates in SMLM data. Using maximum likelihood estimation, this tool extracts the most likely parameters for a given model that best describe the data, and can select the most likely model from alternative models. We demonstrate the versatility of LocMoFit by measuring precise dimensions of the nuclear pore complex and microtubules. We also use LocMoFit to assemble static and dynamic multi-color protein density maps from thousands of snapshots. In case an underlying geometry cannot be postulated, LocMoFit can perform single-particle averaging of super-resolution structures without any assumption about geometry or symmetry. We provide extensive simulation and visualization routines to validate the robustness of LocMoFit and tutorials based on example data to enable any user to increase the information content they can extract from their SMLM data.

biophysics↗

bioRxiv2021

Photon-free (s)CMOS camera characterization for artifact reduction in high- and super-resolution microscopy

Modern implementations of widefield fluorescence microscopy often rely on sCMOS cameras, but this camera architecture inherently features pixel-to-pixel variations. Such variations lead to image artifacts and render quantitative image interpretation difficult. Although a variety of algorithmic corrections exists, they require a thorough characterization of the camera, which typically is not easy to access or perform. Here, we developed a fully automated pipeline for camera characterization based solely on thermally generated signal, and implemented it in the popular open-source software Micro-Manager and ImageJ/Fiji. Besides supplying the conventional camera maps of noise, offset and gain, our pipeline also gives access to dark current and thermal noise as functions of the exposure time. This allowed us to avoid structural bias in single-molecule localization microscopy (SMLM), which without correction is substantial even for scientific-grade, cooled cameras. In addition, our approach enables high-quality 3D super-resolution as well as live-cell time-lapse microscopy with cheap, industry-grade cameras. As our approach for camera characterization does not require any user interventions or additional hardware implementations, numerous correction algorithms demanding camera characterization become easily applicable.

biophysics↗

bioRxiv2020

Deep learning enables fast and dense single-molecule localization with high accuracy

Single-molecule localization microscopy (SMLM) has had remarkable success in imaging cellular structures with nanometer resolution, but the need for activating only single isolated emitters limits imaging speed and labeling density. Here, we overcome this major limitation using deep learning. We developed DECODE, a computational tool that can localize single emitters at high density in 3D with highest accuracy for a large range of imaging modalities and conditions. In a public software benchmark competition, it outperformed all other fitters on 12 out of 12 data-sets when comparing both detection accuracy and localization error, often by a substantial margin. DECODE allowed us to take live-cell SMLM data with reduced light exposure in just 3 seconds and to image microtubules at ultra-high labeling density. Packaged for simple installation and use, DECODE will enable many labs to reduce imaging times and increase localization density in SMLM.

biophysics↗

bioRxiv2020

Direct Supercritical Angle Localization Microscopy for Nanometer 3D Superresolution

3D single molecule localization microscopy (SMLM) is an emerging superresolution method for structural cell biology, as it allows probing precise positions of proteins in cellular structures. Supercritical angle fluorescence strongly depends on the z-position of the fluorophore and can be used for z localization in a method called supercritical angle localization microscopy (SALM). Here, we realize the full potential of SALM by directly splitting supercritical and undercritical emission, using an ultra-high NA objective, and applying new fitting routines to extract precise intensities of single emitters, resulting in a four-fold improved z-resolution compared to the state of the art. We demonstrate nanometer isotropic localization precision on DNA origami structures, and on clathrin coated vesicles and microtubules in cells, illustrating the potential of SALM for cell biology.

biophysics↗

bioRxiv2019

A cost-efficient open source laser engine for microscopy

Scientific-grade lasers are costly components of modern microscopes. For high-power applications, such as single-molecule localization microscopy, their price can become prohibitive. Here, we present an open-source high-power laser engine that can be built for a fraction of the cost. It uses affordable, yet powerful laser diodes at wavelengths of 405 nm, 488 nm and 640 nm and optionally a 561 nm diode-pumped solid-state laser. The light is delivered to the microscope via an agitated multimode fiber in order to suppress speckles. We provide the part lists, CAD files and detailed descriptions, allowing any research group to build their own laser engine.

biophysics↗

bioRxiv2019

Nuclear pores as versatile reference standards for quantitative superresolution microscopy

Quantitative fluorescence and superresolution microscopy are often limited by insufficient data quality or artifacts. In this context, it is essential to have biologically relevant control samples to benchmark and optimize the quality of microscopes, labels and imaging conditions.\n\nHere we exploit the stereotypic arrangement of proteins in the nuclear pore complex as in situ reference structures to characterize the performance of a variety of microscopy modalities. We created four genome edited cell lines in which we endogenously labeled the nucleoporin Nup96 with mEGFP, SNAP-tag or HaloTag or the photoconvertible fluorescent protein mMaple. We demonstrate their use a) as 3D resolution standards for calibration and quality control, b) to quantify absolute labeling efficiencies and c) as precise reference standards for molecular counting.\n\nThese cell lines will enable the broad community to assess the quality of their microscopes and labels, and to perform quantitative, absolute measurements.

biophysics↗

bioRxiv2017

Fast, robust and precise 3D localization for arbitrary point spread functions

We present a fitter for 3D single-molecule localization of arbitrary, experimental point spread functions (PSFs) that reaches minimum uncertainty for EMCCD and sCMOS cameras, and achieves more than 105 fits/s. We provide tools to robustly model experimental PSFs and correct for depth induced aberrations, which allowed us to achieve an unprecedented 3D resolution with engineered astigmatic PSFs, and acquire high quality 3D superresolution images even on standard microscopes without 3D optics.

biophysics↗