1. Flow Cytometry and Cell Sorting. My early publications pioneered the application of flow cytometry and cell sorting to higher plants.  I developed an internationally-adopted method for analysis of the cell cycle and genome sizes of plants using flow cytometry (reference [a]), methods for analysis and sorting of individual plant cells from which the cell wall had been removed (protoplasts; ref. [b]), and for regeneration of somatic hybrid plants following sorting of heterokaryons produced by protoplast fusion (ref. [c]). Our cell cycle work was the first to identify widespread somatic endoreduplication in the model plant Arabidopsis thaliana (ref. [d]).

a.    Galbraith, D.W. et al. (1983). Rapid flow cytometric analysis of the cell cycle in intact plant tissues. Science 220:1049-1051. 
b.    Harkins, K.R., and Galbraith, D.W. (1984). Flow sorting and culture of plant protoplasts. Physiologia Plantarum 60:43-52.
c.    Afonso, C.L. et al. (1985). Production of somatic hybrid plants through fluorescence activated sorting of protoplasts.  Nature Biotechnology 3:811-816. 
d.    Galbraith, D.W. et al. (1991).  Systemic endopolyploidy in Arabidopsis thaliana.  Plant Physiology 96:985-989.

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2. Digital Signal Processing and Artificial Intelligence.  We pioneered methods for flow cytometric analysis and sorting of large cells and other biological and non-biological cells (ref. [e]), and were the first to describe the application of digital signal processing in flow cytometric instrumentation (refs. [f], [g], [h]).  Reference [g] is the first description of the application of Artificial Intelligence methods (a multi-layer perceptron) to accurately classify cells based on their digitized pulse-waveforms.

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e.   Harkins, K.R., and Galbraith, D.W. (1987). Factors governing the flow cytometric analysis and sorting of large biological particles.  Cytometry 8:60-71. 

f.    Zilmer, N.A. et al. (1995).  Flow cytometric analysis using digital signal processing.  Cytometry 20:102-117.

g.    Godavarti M. et al. (1996). Automated particle classification based on digital acquisition and analysis of flow cytometric pulse waveforms. Cytometry 24:330-339.

h.    Murthi, S. et al. (2002). An improved data acquisition system for digital flow cytometry.  ISCAS 2002. IEEE International Symposium on Circuits and Systems 1:669-672.

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3. Cell Type-specific Gene Expression.  My laboratory pioneered analysis of the expression of specific genes within different cell types in plants using flow cytometry and sorting (ref. [i]). We were first to describe the expression of the Green Fluorescent Protein (GFP) in plants (refs. [j], [k]), and the directed transgenic targeting of GFP to nuclei (refs. [l], [m]). We, with collaborators, combined our methods for flow sorting protoplasts according to GFP expression to provide the first comprehensive description of global patterns of transcription within the arabidopsis root (refs. [n],[o]). We compared this to global patterns of gene expression derived from the analysis of polyadenylated RNA extracted from flow sorted, GFP-labeled nuclei (refs. [p], [q]), and this has led to the development of a general strategy for analysis of gene expression in complex tissues, including mammalian cells and organs, focusing on the flow sorted nucleus as the critical source of transcriptional information (ref. [r]). We extended this work to include successful demonstration of global analysis of transcription at the level of single sorted mammalian nuclei (ref. [s]), and have used it for characterization of the initial stages of oncogenesis in mouse pancreas (ref. [t]).  In parallel, my laboratory conceived and, with collaborators, developed methods for analysis of translation within specific cell types (refs. [u], [v]).

 

The ability to isolate nuclei from tissue homogenates using our methods for flow sorting led to an explosive expansion across the world of single-nucleus RNA-sequencing (sn-RNAseq) for all eukaryotic organisms.  In our case, we recently employed this for study of stomatal differentiation and function in maize (references [w1-2]).   

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i.   Harkins, K.R. et al. (1990).  Expression of photosynthesis related gene fusions is restricted by cell type in transgenic plants and in transfected protoplasts. Proceedings of the National Academy of Sciences U.S.A. 87:816-820.

j.   Sheen, J. et al. (1995).  Green fluorescent protein as a new vital marker in plant cells.  Plant Journal 8:777-784.

k.  Galbraith, D.W. et al. (1995).  Flow cytometric analysis of transgene expression in higher plants:  Green Fluorescent Protein. Methods in Cell Biology 50:3-12.

l.   Grebenok, R.J. et al. (1997). Green-Fluorescent Protein fusions for efficient characterization of nuclear localization signals. Plant Journal 11:573-586.

m. Grebenok, R.J. et al. (1997).  Characterization of the targeted nuclear accumulation of GFP within the cells of transgenic plants. Plant Journal 12:685-696.

n.  Birnbaum, K. et al. (2003). A gene expression map of the Arabidopsis root. Science 302:1956-1960. 

o.  Birnbaum, K. et al. (2005). Cell-type specific expression profiling in plants using fluorescent reporter lines, protoplasting, and cell sorting. Nature Methods 2:1-5.

p.  Zhang, C.Q. et al. (2005). Cell type-specific characterization of nuclear DNA contents within complex tissues and organs. Plant Methods 2005, 1:7 doi:10.1186/1746-4811-1-7.

q.  Zhang, C.Q. et al. (2008). Characterization of cell-specific gene expression through fluorescence-activated sorting of nuclei. Plant Physiology 147:30-40.

r.   Barthelson, R.A. et al. (2007). Comparison of the contributions of the nuclear and cytoplasmic compartments to global gene expression in human cells. B.M.C. Genomics 8:340.

s.   Grindberg, R.V. et al. (2013). RNA-Seq from single nuclei. Proceedings of the National Academy of Sciences U.S.A. 110:19802-19807.

t.    Samadder, P. et al. (2016). Flow cytometry and single nucleus sorting for Cre-based analysis of changes in transcriptional states. Cytometry 89:430-442.

u.   Zanetti, M.E. et al. (2005). Immunopurification of polyribosomal complexes of arabidopsis for global analysis of gene expression. Plant Physiology 138:624-635. 

v.   Mustroph, A. et al. (2009). Profiling translatomes of discrete cell populations resolves altered cellular priorities during hypoxia in Arabidopsis. Proceedings of the National Academy of Sciences U.S.A.106:18849-18854.

w1. Sun, G. et al. (2022).  Single-nucleus transcriptome landscapes of the maize epidermis comprehensively reconstitute signaling networks governing the movement and development of grass stomata. Plant Cell 34 (5):1890-1911. https://doi.org/10.1093/plcell/koac047.

w2. Song, C.P. et al. (2023). A maize epimerase modulates cell wall synthesis and glycosylation during stomatal morphogenesis. Nature Communications 14: 4384. https://doi.org/10.1038/s41467-023-40013-6. 

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4. Organelle Engineering. As part of our work in targeting marker proteins to various subcellular compartments, we demonstrated the first example of production of novel subcellular organelles through transgenic engineering (ref. [x]).

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x.  Gong, F.-C. et al. (1996).  Z-membranes: artificial organelles for over-expressing recombinant integral membrane proteins. Proceedings of the National Academy of Sciences U.S.A. 93:2219-2223.

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5. Microarray Platforms. We were very early adopters of microarray technologies, and produced and distributed over 60,000 microarrays during the period of 2000-2011. We also provided ten instructional workshops during this period, training approximately 350 scientists. Publications emerging from this work relate to analysis of gene expression, genotyping, and novel expression platforms form both DNA and protein based microarrays (see for example, refs. [y]-[gg]).

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y.  Macas, J. et al. (1998). Adapting the Biomek 2000 Laboratory Automation Workstation for printing DNA microarrays. BioTechniques 25:106-110.

z.  Nouzová, M. et al. (2001). Microarray-based survey of repetitive genomic sequences in Vicia spp. Plant Molecular Biology 45:229-244.

aa.  Kawasaki, S. et al. (2001).  Gene expression profiles during the initial phase of salt stress in rice (Oryza sativa L.). Plant Cell 13:889-906.

bb.  Xu, W. et al. (2001). Microarray-based analysis of gene expression in very large gene families: the Cytochrome P450 gene superfamily of Arabidopsis thaliana. Gene 272:61-74.

cc.  Fernandes, J. et al. (2002). Comparison of RNA expression profiles based on maize EST frequency analysis and microarray hybridization. Plant Physiology 128:896-910.

dd.  Kris, R.M. et al. (2007). High-throughput, high-sensitivity analysis of gene expression in Arabidopsis thaliana. Plant Physiology 144:1256-1266. 

ee.  Edwards, J.D. et al. (2008). Development of a high-throughput, low-cost genotyping platform based on oligonucleotide microarrays, and its evaluation in rice. Plant Methods 2008, 4:13.

ff.  Bourzac, K.M. et al. (2011). A high-density quantitative nuclease protection microarray platform for high throughput analysis of gene expression. Journal of Biotechnology 154:68-75.

gg.  Kimzey, M.J. et al. (2011). Optimizing microarray-based in situ transcription-translation of proteins for MALDI mass spectrometry. Analytical Biochemistry 414:282-286.

hh.  Cantu-Bustosa, J.E. et al. (2016). Expression and purification of recombinant proteins in Escherichia coli tagged with the metal-binding protein CusF. Protein Expression and Purification 121:61-5 doi: 10.1016/j.pep.2016.01.007.

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6.  Pathogen Detection Devices. We devised a portable instrument that is capable of detecting the presence of microbial organisms (jj). It involved, for the first time, the rapid, real-time Mie-scatter sensing of colloidal emulsion nucleic acid amplification directly from emulsion droplets, using Loop-mediated isothermal amplification (LAMP). Interfacial tension values show characteristic changes in the absence or presence of amplification. This method was validated for detection of bacteria and viruses suspended in water, buffer, or serum‐like matrices. The unique benefits of this method are that it is very cost-effective as compared to existing methods, is field-deployable, and adaptable to a multitude of targets, sample matrices, and nucleic acid amplification tests. LAMP amplification is being employed for COVID-19 monitoring, and elsewhere developed for detection of other diseases of concern.   

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jj. Nicolini, A.M. et al. (2017). Mie scatter and interfacial tension based real-time quantification of colloidal emulsion nucleic acid amplification. Advanced Biosystems DOI: 10.1002/adbi. 201700098.

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7.   COVID-19/SARS-CoV-2 Coronavirus Detection and Pathogenesis. Working with BioSpyder (https://www.biospyder.com/), we are establishing a comprehensive assay platform for simultaneous detection of the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), the viral strain responsible for the coronavirus disease 2019 (COVID-19) pandemic, and of the cellular and molecular responses of the infected person during disease establishment and progression.    

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