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www.mashanov.uk

Dear Reader, 

You can use this website to download freeware applications (see links below) written by G. Mashanov (The Francis Crick Institute, UK). This software was developed for the detection/tracking, analysis, and modelling of single molecule dynamics (movement and binding kinetics) in live cells, but it can be used for other purposes. You can download our real and simulated data samples and ImageJ Plugins to import and export your data files.   

The software was compiled using CBuilder_XE7. It will run under Win32 or Win64 OS and does not require installation or registration:

1. Download required .zip file (see below). The archives contain ".exe" files (32 or 64 bit), and corresponding “.dll” files (“.bpl” libraries).

2.  Unzip these files into selected folder on your computer.

3.  Run the required “.exe” file.

You may manually associate “.gmv” data files (using Windows Explorer) with GMimPro and “.gmi” files with Motility to open data files by clicking on it. I am happy to answer your specific questions gmashanov@gmail.com but, please, read the help files (.pdf) (and corresponding publications) first.

Yours

Gregory Mashanov


GMvCell screenshotNew: GMvCell is a development of GMcellModel (see below). It is a combination of a 3D matrix and continuum space models used to simulate complicated, randomly shaped and placed cellular structures and some dynamic cellular structures (e.g., moving vesicles fusing with cell membrane). Single molecule objects (upto 50000 units of each class) move with floating-point precision in a continuum space but only in voxels of correct type in discrete space. Objects of the same or different classes can interact with each other according to the binding/dissociation rates set by operator - the probability of binding depends on the distance/mobility of eligible pair and continuity of the correct voxel space between these objects. During simulation model produces sequences of fluorescence light microscopy images built according to the simulated imaging conditions (e.g., illumination method, microscope magnification, objective numerical aperture, and camera settings) which can be used for data ananlysis. The model executable file (GMvCell.exe), required libraries, help file (GmvCell-Help.pdf), pre-defined scenarios, and satellite  software (GMimPro and Motility) can be downloaded below (64bit files). Please note, this is 64bit only software because it requires large memory volume to simulate virtual cell. 


GMimPro is an image sequence processor designed for automatic single particle/molecule detection and tracking. It can track up to 10000 objects for up to 10000 frames. You can use ImageJ Plugins to convert your data files into GMimPro format (“.gmv”) or import RAW data files in GMimPro (File/Import Data). You can export the results of tracking or other measurements using “.txt” or “.gmi” data format. See Biophysical Journal, 2007 publication for full description of the employed algorithms.
Update: New, 64-bit only version of GMimPro2023 is included in 64bit download file. This version works faster because it loads the whole record into RAM. GMimPro2023 has more features (e.g. analysis of two-colour pairs of records).

GMcellModel is a computer model simulating mobility and binding kinetics of the single fluorescent molecules (both cytoplasm and membrane associated) in a virtual cell. It generates a sequence of images (8-bit “.bmp” or “.gmv” format), each containing summed images of all fluorescent objects emitting light under given illumination conditions with realistic levels of noise and emission fluctuations. These sequences can be analysed by GMimPro or other imaging software (e.g., ImageJ). You can load few basic scenarios (downloaded folder GMcellModelScenario) and run the model to test it. See JRS Interface 2014 publication for full description of the employed algorithms.


Motility is a satellite software designed for statistical analysis of tracking data (.gmi) generated by GMimPro. You can add many individual “.gmi” files together and create distributions of: intensity, mobility, velocity, and other paprameters. You can create plots of average intensity, mobility, and "distance from the origin" versus time, generate MSD versus dT plots, and others. You can apply thresholds to separate slow-fast, dim-bright, short-long lived objects, and so on. The graphs can be printed, saved as “.bmp”, and exported as “.txt” files for future analysis or publishing.


ImageJ plug-ins are written by Prof. J.E. Molloy (University of Warwick, UK).

1.  Copy plugins into ImageJ plugins folder

2.  Open ImageJ and load your image sequence

3.  Input scales and time interval to the sequence properties if needed

4.  Use“GMV Writer” in “Plugins” menu to save your data as “.gmv” file.

Alternatively you can save your data as RAW data file and use File/Import Data in GMimPro to convert data into GMimPro format (".gmv").


About  Software  DataSamples  Movies  Publications

Download 32bit “.exe” files and libraries

Download 64bit “.exe” files and libraries

Download ImageJ Plugins for GMimPro

Download GMinfectionSpreadModel

(model simulating infection spread in a structured enviroment)


About  Software  DataSamples  Movies  Publications

Download Data samples

GFP_inVitro - single GFP molecules attached to glass via antiGFP ab (in vitro, TIRF microscopy)

Cy3B_inVitro - single fluorescent molecules of Cy3B dye attached to coverslip (in vitro, TIRF microscopy)

GFP_A1_HEK - Adenosine GPCR A1 receptors (GFP tagged) at plasma membrane of live HEK cell (37°C, TIRF microscopy)

Cy3B-Tz_M1_CHO - Muscarinic Acetylcholine GPCR M1 receptors at plasma membrane of live CHO cell (23°C, labelled with Cy3B-telenzepine, TIRF microscopy)

Cy3B-Tz_M2_CHO - Muscarinic Acetylcholine M2 receptors at plasma membrane of live CHO cell (23°C, labelled with Cy3B-telenzepine, TIRF microscopy)

Cy3B-Tz_M2_HL1 - Muscarinic Acetylcholine GPCR M2 receptors at plasma membrane of live HL1 cell @23˚C (37°C, labelled with Cy3B-telenzepine, TIRF microscopy)

Cy3B-Tz_M2_HeartSlice - Muscarinic Acetylcholine GPCR M2 receptors at plasma membrane of ex-vivo mice heart slice (23°C, labelled with Cy3B-telenzepine, TIRF microscopy)

GFP_KCNQ1_HEK - KCNQ1 potassium channels. GFP tagged at plasma membrane of live HEK cell (37°C, TIRF microscopy)

GFP_KIR6.2_HEK – KIR6.2 potassium channels. GFP tagged at plasma membrane of live HEK cell (37°C, TIRF microscopy)

Myosin-2b in HUVEC
– Myosin-2b molecules (GFP tagged) binding to stress fibres in Endothelial cell (37°C, TIRF microscopy)

Myosin-10 in HeLa – Myosin-10 molecules moving to the tips of filopodia in HeLa cell (37°C, TIRF microscopy)

Modelled Data - Few samples of GMcellModel output (.gmv files) made in different conditions.


About  Software  DataSamples  Movies  Publications

Here is a short list of YouTube movies - examples of real and modelled data
(use DataSamples to download non-compressed data or download GMcellModel to generate simulated data)
Single molecules of M1 muscarinic ACh (GPCR) receptor moving on the plasma membrane of CHO cell @23°C
Single molecules of KCNQ1 potassium channel in HEK293 cell (KCNQ1 containing vesicle fusing with membrane)
Molecules of potassium channel (KIR6.2-GFP) in HL1 cell @37°C
A1 (GPCR) receptors (A1-GFP) on the membrane of HEK293 cell @37°C
M2 receptors (labelled with Cy3B-Telenzepine). Adult mouse heart slice @23°C
PH12-GFP (domains of Myosin-10) in Endothelial cell@37°C
Myosin-10 (GFP tagged) in HeLa@37°C
Myosin-2b (GFP tagged) in HeLa@37°C
Amoeba cells moving in Dunn chamber (cAMP gradient). Low-mag, dark-field imaging and single cell tracking
Tracking individual aphids (insects) in a Petri dish
GMcellModel - virtual cell Z-scan in Confocal and Epi-Fluorescene mode
GMcellModel - tracking single molecules at cell membrane
GMcellModel - interaction of moving membrane molecules with "lipid rafts"
GMcellModel - molecules in tubular network
GMcellModel - Kinesin molecules stepping on microtubules in a virtual cell
GMvCell - Constructing virtual cell in 3D voxilated matrix
GMvCell - Simulation of single molecule movements and interactions in a virtual cell


About  Software  DataSamples  Movies  Publications

Mashanov, G.I., Tacon, D., Knight, A.E., Peckham, M., and J.E. Molloy. (2003) Visualizing single molecules inside living cells using total internal reflection fluorescence microscopy. Methods, Academ. Press., 29:142-152.

Mashanov, G.I., Tacon, D., Peckham, M., and J.E. Molloy. (2004) The spatial and temporal dynamics of pleckstrin homology domain binding at the plasma membrane measured by imaging single molecules in live mouse myoblasts. J. Biol. Chem., 279:15274-15280.

Mashanov G.I., Molloy J.E. (2007) Automatic detection of single fluorophores in live cells. Biophys.J., 92:2199-2211.

Mashanov G.I.,
Nobles M., Harmer S.C., Molloy J.E., Tinker A. (2010) Direct Observation of Individual KCNQ1 Potassium Channels Reveals Their Distinctive Diffusive Behavior, J. of Biol. Chem., 285:3664-3675

Nenasheva T.A., Carter T., Mashanov G.I. (2012) Automatic tracking of individual migrating cells using low-magnification dark-field microscopy. J. of Microscopy, 246:83–88.

Mashanov G.I.
(2014) Single molecule dynamics in a virtual cell: a three-dimensional model that produces simulated fluorescence video-imaging data, JRS Interface, 11:1-11

Baboolal T.G., Mashanov G.I., NenashevaT.A., Peckham M., Molloy J.E. (2016) A Combination of Diffusion and Active Translocation
Localizes Myosin 10 to the Filopodial Tip
J. Biol. Chem., 291:22373-22385

Mashanov G.I., NenashevaT.A., Mashanova T., Maclachlan C., Birdsall N.J.M., Molloy J.E. (2020) A method for imaging single molecules at the plasma membrane of live cells within tissue slices J.G.P., 153:1-11

Mashanov G.I., NenashevaT.A., Mashanova A., Lape R., Birdsall N.J.M. Sivilotti L., Molloy J.E. (2021) Heterogeneity of cell membrane structure studied by single molecule tracking Faraday Discussions

Hellen N., Mashanov G.I., Conte J.L., ...... Carter T. (2022) P-selectin mobility undergoes a sol-gel transition as it diffuses from exocytosis sites into the cell membrane Nature Comm., 13:1-11

Mashanov G.I., Molloy J.E. (2024) Single molecule dynamics in a virtual cell combining a 3‑dimensional matrix model with random walks Scientific Reports, 14:1-14