https://researchdata.se/sv/catalogue Search results sv This repository contains analysis code related to the manuscript "Recovering membrane interaction kinetics of single molecules from 3D tracking data" by Lundin et al. (2026) Biophysical Journal Abstract Interactions between cytosolic biomolecules and the bacterial inner membrane are fundamental to many cellular processes, yet directly measuring their binding kinetics in living cells remains challenging. Conventional two‑dimensional single‑molecule tracking analyses can be insufficient, particularly when membrane association does not markedly alter the diffusion rate. Here, we present a method to recover membrane interaction kinetics from three‑dimensional single‑molecule trajectories in rod-shaped bacteria. Using simulated 3D tracking data, we identify membrane‑associated motion by quantifying how well short trajectory segments follow the circular curvature of the cell membrane. The resulting measure is further analyzed using a hidden Markov modeling framework, enabling robust discrimination between cytosolic and membrane‑bound states and capturing the dynamics of state transitions without requiring diffusion‑rate changes or direct colocalization with membrane markers. This work establishes a general framework for extracting membrane interaction kinetics from 3D single‑molecule tracking data in live bacteria, and highlights the value of realistic microscopy simulations for quantitative interpretation and systematic bias assessment. A detailed list of files and file organizations can be found in the readme file. Thu, 17 Sep 2026 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-32771763 https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-32771763 Uppsala universitet Erik Lundin Ivan Volkov Magnus Johansson This repository contains data related to the publication: "Optimization of the genetic code expansion technology for intracellular labelling and single-molecule tracking of proteins in genomically re-coded E. coli" by Ilievski et al. The study includes optimizations of genetic code expansion technology for bio-orthogonal click-labeling of proteins inside living E. coli cells. A detailed list of files and file organizations can be found in the readme file Mon, 08 Dec 2025 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-29939984 https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-29939984 Uppsala universitet Filip Ilievski Linnea Wikström Anneli Borg Ivan Volkov Gerrit Brandis Magnus Johansson This repository contains microscopy data and analysis code related to the publication: Metelev and Johansson, "A complex between IF2 and NusA suggests early coupling of transcription-translation". The study includes single-particle tracking of translation initiation factors and related compounds in live E. coli cells, for analysis of translation initiation kinetics. A detailed list of files and file organization can be found in the readme text file. Wed, 09 Jul 2025 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-28795805 https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-28795805 Uppsala universitet Mikhail Metelev Magnus Johansson This data set contains code and data needed to generate the figures and tables presented in "Pooled optical screening in bacteria using chromosomally expressed barcodes". See link to the publication in Related Material. Optical pooled screening is an important tool to study dynamic phenotypes for libraries of genetically engineered cells. However, the desired engineering often requires that the barcodes used for in situ genotyping are expressed from the chromosome. This has not previously been achieved in bacteria. Here we describe a method for in situ genotyping of libraries with genomic barcodes in Escherichia coli. The method is applied to measure the intracellular maturation time of 84 red fluorescent proteins. All microscopy images and the corresponding image analysis code and outputs are found on the BioImage Archive. See link in Related Material. Tue, 27 May 2025 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-26976952 https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-26976952 Uppsala universitet Ruben R. G. Soares Daniela A. García-Soriano Jimmy Larsson David Fange Dvir Schirman Marco Grillo Anna Knöppel Beer Chakra Sen Fabian Svahn Spartak Zikrin Michael Ratz Mats Nilsson Johan Elf This item is part of the Figshare Project: Early mitochondrial dysfunction revealed across FUS- and TARDBP-ALS at single cell resolution (https://su.figshare.com/projects/Early_mitochondrial_dysfunction_revealed_across_FUS-_and_TARDBP-ALS_at_single_cell_resolution/163252) From Data Availability Statement for the forthcoming paper in Nature Communications entitled: Single-cell RNA sequencing reveals early mitochondrial dysfunction unique to motor neurons shared across FUS- and TARDBP-ALS "We have deposited all raw and processed RNA sequencing data generated in this study on the NCBI Gene Expression Omnibus (GEO) under the accession number GSE226482. The C9orf72-ALS bulk RNA sequencing data was retrieved directly from the authors of the study. [Items under this Figshare Project contain:] "Scans of fluorescent western blots, raw imaging files from confocal microscopy, the analysis files from Opera Phenix, qPCR data sets, and Seahorse assay result files." -------------------------------------------- [Item specific description:] This data belong to Supplementary Fig. 5 and 6. Western blots in iPSC lines with various FUS and TARDBP M337V mutations for FUS and TDP-43 protein expression. The assembled western blots are presented in the PPTX file. The fluorescent signal were scanned on a Odyssey CLx scanner (LI-COR) and exported as Image Studio ZIP archives. More information about the Image Studio software can be obtained here: https://www.licorbio.com/image-studio The raw images are given as TIF files, thumbnails as PNG, and aquisition meta information as TXT files within the exported archives. Mon, 28 Apr 2025 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-17045-sthlmuni-22555525 https://researchdata.se/sv/catalogue/dataset/doi-10-17045-sthlmuni-22555525 Stockholms universitet Christoph Schweingruber Jonas Mechtersheimer Marc-David Ruepp Stefan Reber Data to accompany the manuscript "Deep learnings models for lipid-nanoparticle-based drug delivery" Abstract:Large-scale time-lapse microscopy experiments are useful to understand delivery and expression in RNA-based therapeutics. The resulting data has high dimensionality and high (but sparse) information content, making it challenging and costly to store and process. Early prediction of experimental outcome enables intelligent data management and decision making. We start from time-lapse data of HepG2 cells exposed to lipid-nanoparticles loaded with mRNA for expression of green fluorescent protein (GFP). We hypothesize that it is possible to predict if a cell will express GFP or not based on cell morphology at time-points prior to GFP expression. Here we present results on per-cell classification (GFP expression/no GFP expression) and regression (level of GFP expression) using three different approaches. In the first approach we use a convolutional neural network extracting per-cell features at each time point. We then utilize the same features combined with: a long-short-term memory (LSTM) network encoding temporal dynamics (approach 2); and time-series feature extraction using the python package tsfresh followed by principal component analysis and gradient boosting machines (approach 3), to reach a final classification or regression result. Application of the three approaches to a previously unanalyzed test set of cells showed good predictive performance of all three approaches but that accounting for the temporal dynamics via LSTMs or tsfresh led to significantly improved performance. The predictions made by the LSTM and tsfresh applications were not significantly different. The results highlight the benefit of accounting for temporal dynamics when studying drug delivery using high content imaging. Python code:https://github.com/pharmbio/phil_LNP_modelling Tue, 04 Feb 2025 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-12482183 https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-12482183 Uppsala universitet Philip Harrison Håkan Wieslander Alan Sabirsh Johan Karlsson Victor Malmsjö Andreas Hellender Carolina Wählby Ola Spjuth A test dataset for MUSCLE (MUltiplexed Single-molecule Characterization at the Library scalE) data analysis. See "\Python codes for MUSCLE data analysis\README.txt" for the instructions on running the data analysis codes. Use the files in the "Test MUSCLE dataset" folder as input for the codes. "Test MUSCLE dataset\Output_tile1\" contains the code output for the test dataset. The example dataset corresponds to one MiSeq tile in an experiment analyzing dCas9-induced R-loop formation for a library of 256 different target sequences. The latest version of the Python codes for matching single-molecule FRET traces with sequenced clusters is available at https://github.com/deindllab/MUSCLE/. Tue, 14 Jan 2025 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-28008872 https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-28008872 Uppsala universitet Mikhail Panfilov Guanzhong Mao Jianfeng Guo Javier Aguirre Rivera Anton Sabantcev Sebastian Deindl Data and codes underlying the findings of the manuscript "Massively parallel analysis of single-molecule dynamics on next generation sequencing chips". Please see the Materials and Methods section of the manuscript for the description of experimental procedures. For every figure in the paper a README file is provided, listing the datasets used for the figure, as well as the MATLAB analysis codes used to generate the respective plots. The latest version of the Python codes for matching single-molecule FRET traces with sequenced clusters is available at https://github.com/deindllab/MUSCLE/. The abstract of the manuscript: "Single-molecule techniques are ideally poised to characterize complex dynamics but are typically limited to investigating a small number of different samples. However, a large sequence or chemical space often needs to be explored to derive a comprehensive understanding of complex biological processes. Here we describe MUltiplexed Single-molecule Characterization at the Library scalE (MUSCLE), a method that combines single-molecule fluorescence microscopy with next-generation sequencing to enable highly multiplexed observations of complex dynamics. We comprehensively profile the sequence dependence of DNA hairpin properties and Cas9-induced target DNA unwinding/rewinding dynamics. For Cas9, the ability to explore a large sequence space allowed us to identify a number of target sequences with unexpected behaviors. We envision that MUSCLE will enable the mechanistic exploration of many fundamental biological processes." To download the data file (279.41 GB) in this item, use: wget --content-disposition https://ndownloader.figshare.com/files/47434699 Mon, 26 Aug 2024 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-25705512 https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-25705512 Uppsala universitet Javier Aguirre Rivera Guanzhong Mao Anton Sabantcev Mikhail Panfilov Magnus Lindell Christelle Chanez Felix Ritort Martin Jinek Sebastian Deindl Qinhan Hou Single-molecule Förster resonance energy transfer (FRET) data supporting the findings of the paper titled "Asymmetric nucleosome PARylation at DNA breaks mediates directional nucleosome sliding by ALC1" in Nature Communications. The data mainly pertain to the remodeling directionality of ALC1 as a function of the PARylation state of a nucleosome. The initial remodeling directionality was measured based on the direction of the initial FRET change upon remodeling. The biotinylated FRET-labeled nucleosomes were immobilized on a PEG (poly[ethylene glycol])-coated quartz slide saturated with streptavidin. Cy3 and Cy5 fluorophores were excited with 532 nm Nd:YAG and 638 nm diode lasers, respectively, and fluorescence emissions from Cy3 and Cy5 fluorophores were detected using a custom-built prism-based TIRF microscope. To check the presence of an intact donor fluorophore, the sample was alternately excited with 532 nm and 638 nm lasers during the experiment. Tue, 19 Dec 2023 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-24764697 https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-24764697 Uppsala universitet Anton Sabantcev Luka Bacic Guillaume Gaullier Guanzhong Mao Klaus Brackmann Mikhail Panfilov Jugal Mohapatra Glen Liszczak Sebastian Deindl General Description It contains data sets from Ragaller et al, Open Biology, 2022 (https://doi.org/10.1098/rsob.220175). It contains Generalized Polarization (GP) values, GP profiles, GP maps, raw spectral images, MD Simulation snapshots, tilt angle distributions, partial density profiles, relaxation time and stokes shift Abstract The plasma membrane serves as a crucial platform for a multitude of cellular processes. Its collective biophysical properties are largely determined by the structural diversity of the different lipid species it accommodates. Therefore, a detailed investigation of biophysical properties of the plasma membrane is of utmost importance for a comprehensive understanding of biological processes occurring therein. During the past two decades several environment-sensitive probes have been popular tools to investigate membrane properties. Although these probes are assumed to report on membrane order in similar ways, their individual mechanisms remain to be elucidated. In this study, using model membrane systems, we studied the probes Pro12A, NR12S and NR12A in depth and examined their sensitivity to parameters with potential biological implications, such as the degree of lipid saturation, double bond position and configuration, phospholipid headgroup and cholesterol content. Applying spectral imaging together with atomistic molecular dynamics simulations and time-dependent fluorescent shift analyses, we unravelled individual sensitivities of these probes to different biophysical properties, their distinct localizations and specific relaxation processes in membranes. Overall, Pro12A, NR12S and NR12A serve together as a toolbox with a wide range of applications allowing to select the most appropriate probe for each specific research question.  Data usage Researchers  are welcome to use the data contained in the dataset for any projects.  Please cite this item upon use or when published. We  encourage reuse using the same CC BY 4.0 License. Data Content Excel files for graphs Microscopy Images Software to open files .csv - Microsoft Excel .tif, .lsm - Fiji (https://imagej.net/Fiji.html#Downloads) .pzfx - GraphPad Prism .svg - Inkscape (https://inkscape.org/) Thu, 15 Sep 2022 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-20509362 https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-20509362 Karolinska Institutet Franziska Ragaller Luca Andronico Jan Sykora Waldemar Kulig Tomasz Róg Yagmur Balim Urem Abhinav Abhinav Dmytro I. Danylchuk Martin Hof Andrey S. Klymchenko Mariana Amaro Ilpo Vattulainen Erdinc Sezgin