David W Galbraith

David W Galbraith

Professor, Plant Science
Professor, Biomedical Engineering
Professor, BIO5 Institute
Primary Department
Department Affiliations
Contact
(520) 621-9153

Work Summary

I examine the molecular functions of the different cells found in the tissues and organs of plants and animals and how they combine these functions to optimize the health and vigor of the organism.

Research Interest

David Galbraith obtained undergraduate and graduate degrees in Biochemistry from the University of Cambridge, and postdoctoral training as a NATO Fellow at Stanford University. His first academic appointment was at the University of Nebraska Lincoln, and he became Professor of Plant Sciences at the University of Arizona in 1989. His research has focused on the development of instrumentation and methods for the analysis of biological cells, organs, and systems. He is internationally recognized as a pioneer in the development and use of flow cytometry and sorting in plants, developing widely-used methods for the analysis of genome size and cell cycle status, and for the production of somatic hybrids. He also was among the first to develop methods for the analysis of gene expression within specific cell types, using markers based on Fluorescent Protein expression for flow sorting these cells, and microarray platforms for analysis of their transcriptional activities and protein complements. Current interests include applications of highly parallel platforms for transcript and protein profiling of minimal sample sizes, and for analysis of genetic and epigenetic mechanisms that regulate gene expression during normal development and in diseased states, specifically pancreatic cancer. He is also funded to study factors involved in the regulation of bud dormancy in Vitis vinifera, and has interests in biodiversity and improvement of third-world agriculture. He has published more than 180 scholarly research articles, holds several patents, was elected a Fellow of the American Association for Advancement of Science in 2002, and serves on the editorial board of Cytometry Part A. He is widely sought as a speaker, having presented over 360 seminars in academic, industrial and conference settings. He was elected Secretary of the International Society for Advancement of Cytometry in 2016. Keywords: Plant and Animal Cellular Engineering; Biological Instrumentation; Flow Cytometry and Sorting

Publications

Song, C. P., Guo, Y., Qiu, Q. S., Lambert, G., Galbraith, D. W., Jagendorf, A., & Zhu, J. K. (2004). A probable Na+(K+)/H+ exchanger on the chloroplast envelope functions in pH homeostasis and chloroplast development in Arabidopsis thaliana. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 101(27), 10211-10216.
Galbraith, D. W., Samadder, P., & Sliwinska, E. (2018). Nuclear Cytometry: Analysis of the patterns of DNA synthesis and transcription using flow cytometry, confocal microscopy, and RNA sequencing.. Methods in Molecular Biology, 1678, 371-392. doi:doi: 10.1007/978-1-4939-7346-0_16.
Wang, Z., Hobson, N., Galindo, L., Zhu, S., Shi, D., McDill, J., Yang, L., Hawkins, S., Neutelings, G., Datla, R., Lambert, G., Galbraith, D. W., Grassa, C. J., Geraldes, A., Cronk, Q. C., Cullis, C., Dash, P. K., Kumar, P. A., Cloutier, S., , Sharpe, A. G., et al. (2012). The genome of flax (Linum usitatissimum) assembled de novo from short shotgun sequence reads. PLANT JOURNAL, 72(3), 461-473.
Zheng, C., Acheampong, A., Shi, Z., Mugzech, A., Halaly, T., Shaya, F., Colova, V., Ophir, R., Galbraith, D. W., & Or, E. (2017). ABA catabolism enhances dormancy release of grapevine buds.. Plant Cell & Environment.
Galbraith, D., Godavarti, M., Rodriguez, J. J., Yopp, T. A., Lambert, G. M., & Galbraith, D. W. (1996). Automated particle classification based on digital acquisition and analysis of flow cytometric pulse waveforms. Cytometry, 24(4).

In flow cytometry, the typical use of front-end analog processing limits the pulse waveform features that can be measured to pulse integral, height, and width. Direct digitizing of the waveforms provides a means for the extraction of additional features, for example, pulse skewness and kurtosis, and Fourier properties. In this work, we have first demonstrated that the Fourier properties of the pulse can be employed usefully for discrimination between different types of cells that otherwise cannot be classified by using only time-domain features of the pulse. We then implemented and evaluated automatic procedures for cell classification based on neural networks. We established that neural networks could provide an efficient means of classification of cell types without the need for user interaction. The neural networks were also employed in an innovative manner for analysis of the digital flow cytometric data without feature extraction. The performance of the neural networks was compared with that of a more conventional means of classification, the K-means clustering algorithm. Neural networks can be realized in hardware, and this, in addition to their highly parallel architecture, makes them an important potential part of real-time analysis systems. These results are discussed in terms of the design of a real-time digital data acquisition system for flow cytometry.