A Proteomic Analysis of Maize Chloroplast Biogenesis

Patricia M. Lonosky, Xiaosi Zhang, Vasant G. Honavar, Drena L. Dobbs, Aigen Fu, Steve R. Rodermel

Research output: Contribution to journalArticlepeer-review

93 Scopus citations


Proteomics studies to explore global patterns of protein expression in plant and green algal systems have proliferated within the past few years. Although most of these studies have involved mapping of the proteomes of various organs, tissues, cells, or organelles, comparative proteomics experiments have also led to the identification of proteins that change in abundance in various developmental or physiological contexts. Despite the growing use of proteomics in plant studies, questions of reproducibility have not generally been addressed, nor have quantitative methods been widely used, for example, to identify protein expression classes. In this report, we use the de-etiolation ("greening") of maize (Zea mays) chloroplasts as a model system to explore these questions, and we outline a reproducible protocol to identify changes in the plastid proteome that occur during the greening process using techniques of two-dimensional gel electrophoresis and mass spectrometry. We also evaluate hierarchical and nonhierarchical statistical methods to analyze the patterns of expression of 526 "high-quality," unique spots on the two-dimensional gels. We conclude that Adaptive Resonance Theory 2 - a nonhierarchical, neural clustering technique that has not been previously applied to gene expression data - is a powerful technique for discriminating protein expression classes during greening. Our experiments provide a foundation for the use of proteomics in the design of experiments to address fundamental questions in plant physiology and molecular biology.

Original languageEnglish (US)
Pages (from-to)560-574
Number of pages15
JournalPlant physiology
Issue number2
StatePublished - Feb 2004

All Science Journal Classification (ASJC) codes

  • Physiology
  • Genetics
  • Plant Science


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