Egor Zindy, BSc PhD
Bioimaging and Data analysis
Answering biological questions requires the convergence of many scientific fields; from setting up biological constructs, to choosing appropriate imaging methods, onto mining the images and datasets for relevant quantities, to finally being able to model this data and generating new understandings.
Our role is to advise on which imaging modalities and data analysis method are best suited for a particular experiment. This is to ensure that relevant and quantifiable data can be extracted in a rigorous and reproducible manner.
Within our Core Facilities and other dedicated facilities in the Faculty of Life Sciences, we have access to state of the art imaging and non-imaging instruments and the extensive knowledge of their supporting staff. Some of the instruments we use are fluorescence and electron microscopes, high content systems capable of detecting and quantifying morphological changes on a large number of cells at once, and advanced techniques to measure molecular dynamics within cells.
With bio-informaticians and -statisticians, we then mine the (often huge) multi-dimensional datasets for specific patterns, and build computational models which best fit the data and explain the biology.
Software we use
The software we use loosely falls into three categories:- Image Acquisition, Image Processing and finally Data Analysis and Modelling.
Image acquisition software at the BioImaging facility includes Metamorph (Molecular Devices), NIS Elements and EZ-C1 (Nikon), Slidebook (Intelligent Imaging Innovations), LAS AF (Leica), Deltavision softWoRx (Applied Precision), Image-Pro Plus (MediaCybernetics), BD Attovision (BD Biosciences), Axiovision (Zeiss), Panoramic Viewer and HistoQuant (3DHISTECH).
Image Processing and Image analysis software includes FIJI and ImageJ (Opensource projects), AutoQuant Deconvolution Software (MediaCybernetics), Imaris (Bitplane Scientific Software), softWoRx Explorer (Applied Precision), Cellomics Arrayscan (Thermo Scientific), CellProfiler (Opensource project, Broad Institute).
Further Image analysis, Data Processing and Modelling may be programmed on platforms such as Matlab (MathWorks), Octave (GNU software), Python/NumPy/C/C++ (Opensource platforms), or R (Opensource project).
Human Umbilical Vein Endothelial Cells (HUVEC) above courtesy of Ayse Latif and Prof. Paul N. Bishop - Centre for Ophthalmology and Vision Research / Centre for Advanced Discovery and Experimental Therapeutics (CADET), Institute of Human Development, Faculty of Medical and Human Sciences. In order to improve the quantification of focal adhesion, a background correction must be applied to the green channel (Alexa 488). Ours is based on an Adaptive Histogram Equalization technique called Weighted Region Ranking (KUIM Image Processing System, John Gauch). High Content Screening can then quantify on a large number of cells parameters such as number of focal adhesion spots and changes in cell morphology (Cellomics Arrayscan, Centre of Excellence in Biopharmaceuticals).
Pilot experiments demonstrate feasibility of automated procedures.
A, B) High morphological resolution revealed by a representative image of Drosophila primary neurons cultured in a DB Pure Coat 398 well plate and scanned on our Thermo Scientific Cellomics Arrayscan; in contrast to previous screens, our cultures contain a high number of isolated neurons which display detailed anatomical readouts for cytoskeletal activity (blue, nucleus in cell bodies; green, microtubules in cell body and axon; red, actin in filopodia). C) Cellomics software reliably identifies isolated neurons (outlined in white). D) Branch analysis of a mouse cortical primary neuron using Cellomics software.
Recent key publications
Z. Hamrang, A. Pluen, E. Zindy and D. Clarke.(2012) Raster image correlation spectroscopy as a novel tool for the quantitative assessment of protein diffusional behaviour in solution. Journal of Pharmaceutical Sciences. 101(6), 2082-2093. eScholarID:159102106.
Ben Staley, Egor Zindy and Alain Pluen.(2010) Quantifying the uptake and distribution of arginine rich peptides at therapeutic concentrations using Fluorescence Correlation Spectroscopy and Image Correlation Spectroscopy techniques.Presented at 3rd Cellular Delivery of Therapeutic Macromolecules meeting. University of Cardiff.. eScholarID:93663.
Staley B, Zindy E , Pluen A. (2009) Observation of the uptake of TAT peptide at nanomolar concentrations.Presented at British Pharmaceutical Conference. MEN: PHARMACEUTICAL PRESS-ROYAL PHARMACEUTICAL SOC GREAT BRITIAN.. eScholarID:86001.