Estimation of errors introduced by confocal imaging into the data on segmentation gene expression in Drosophila

MOTIVATION Currently the confocal scanning microscopy of fluorescently tagged molecules is extensively employed to acquire quantitative data on gene expression at cellular resolution. Following this approach, we generated a large dataset on the expression of segmentation genes in the Drosophila blastoderm, that is widely used in systems biology studies. As data accuracy is of critical importance for the success of studies in this field, we took a shot to evaluate possible errors introduced in the data by acquisition and processing methods. This article deals with errors introduced by confocal microscope. RESULTS In confocal imaging, the inevitable photon noise is commonly reduced by the averaging of multiple frames. The averaging may introduce errors into the data, if single frames are clipped by microscope hardware. A method based on censoring technique is used to estimate and correct this type of errors. Additional source of errors is the quantification of blurred images. To estimate and correct these errors, the Richardson-Lucy deconvolution method was modified to provide the higher accuracy of data read off from blurred images of the Drosophila blastoderm. We have found that the sizes of errors introduced by confocal imaging make up approximately 5-7% of the mean intensity values and do not disguise the dynamic behavior and characteristic features of gene expression patterns. We also defined a range of microscope parameters for the acquisition of sufficiently accurate data. AVAILABILITY http://urchin.spbcas.ru/downloads/step/step.htm

[1]  J. Reinitz,et al.  Rapid preparation of a panel of polyclonal antibodies to Drosophila segmentation proteins , 1998, Development Genes and Evolution.

[2]  P. Ingham The molecular genetics of embryonic pattern formation in Drosophila , 1988, Nature.

[3]  D Kosman,et al.  Automated assay of gene expression at cellular resolution. , 1998, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.

[4]  Ernst Wit,et al.  Statistical Adjustment of Signal Censoring in Gene Expression Experiments , 2003, Bioinform..

[5]  Johannes Jaeger,et al.  A high-throughput method for quantifying gene expression data from early Drosophila embryos , 2005, Development Genes and Evolution.

[6]  J. Pawley,et al.  Handbook of Biological Confocal Microscopy , 1990, Springer US.

[7]  B. Alberts,et al.  Studies of nuclear and cytoplasmic behaviour during the five mitotic cycles that precede gastrulation in Drosophila embryogenesis. , 1983, Journal of cell science.

[8]  William H. Press,et al.  Numerical Recipes in FORTRAN - The Art of Scientific Computing, 2nd Edition , 1987 .

[9]  John Reinitz,et al.  A database for management of gene expression data in situ , 2004, Bioinform..

[10]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Shuo-Jye Wu ESTIMATIONS OF THE PARAMETERS OF THE WEIBULL DISTRIBUTION WITH PROGRESSIVELY CENSORED DATA , 2002 .

[12]  L. Shepp,et al.  Maximum Likelihood Reconstruction for Emission Tomography , 1983, IEEE Transactions on Medical Imaging.

[13]  Claus Thorn Ekstrøm,et al.  Spot shape modelling and data transformations for microarrays , 2004, Bioinform..

[14]  Ilan Davis,et al.  Transcribed genes are localized according to chromosomal position within polarized Drosophila embryonic nuclei , 1999, Current Biology.

[15]  Thorsten Forster,et al.  Statistical Applications in Genetics and Molecular Biology Estimation of Expression Levels in Spotted Microarrays with Saturated Pixels , 2011 .

[16]  James B. Pawley,et al.  Points, Pixels, and Gray Levels: Digitizing Image Data , 2006 .

[17]  Geert M. P. van Kempen,et al.  Background estimation in nonlinear image restoration , 2000 .

[18]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

[19]  R. Zucker,et al.  Statistical evaluation of confocal microscopy images. , 2001, Cytometry.

[20]  Josiane Zerubia,et al.  Richardson–Lucy algorithm with total variation regularization for 3D confocal microscope deconvolution , 2006, Microscopy research and technique.

[21]  James B. Pawley,et al.  Fundamental Limits in Confocal Microscopy , 2006 .

[22]  Robert M Zucker,et al.  Evaluation of confocal microscopy system performance. , 2001, Methods in molecular biology.

[23]  R. Zucker,et al.  Evaluation of confocal microscopy system performance. , 2001, Cytometry.