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Electrophoresis. 1990 Jul;11(7):537-53.

Internal sequence analysis of proteins separated on polyacrylamide gels at the submicrogram level: improved methods, applications and gene cloning strategies.

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1
Howard Hughes Medical Institute, Department of Genetics, Harvard Medical School, Boston, MA 02115.

Abstract

The fields of protein chemistry and molecular biology are currently merging for study of biologically relevant events and conditions. To obtain partial sequences of microamounts of protein, efficient integration of high resolution separation and sequencing technologies is required. We report here on improved methods that allow extensive internal sequencing of 10 to 20 picomoles protein recovered from one- or two-dimensional gels. Each step of the standard protocol of Aebersold et al. (Proc. Natl. Acad. Sci. USA 1987, 84, 6970-6974) and the required instrumentation were examined and specifically adapted for use with submicrogram amounts of protein. Optimizations of in situ microdigests and liquid chromatography were needed for improved peptide recovery. Subsequent automated sequencing required subpicomole analysis. New methods for S-alkylation of gel-separated proteins and accurate identification of tryptophan-containing peptides were introduced to insure overall higher efficiencies. The acquired internal sequences facilitated cloning of the genes and several strategies are discussed. Applying our method, several proteins of unknown structure were sequenced and successfully identified or cloned. Internal sequences of submicrogram protein amounts, recovered from a single two-dimensional gel of Escherichia coli total protein (120 micrograms), allowed unambiguous identification of the spots but pre-gel enrichment will be required for analysis of most (90-95%) other spots. Integration of comprehensive two-dimensional gel protein databases with methods and strategies outlined here could potentially be an abundant source of DNA probes and markers useful for guidance of the human genome sequencing project and for analysis of the emerging vast amounts of data.

PMID:
2226409
DOI:
10.1002/elps.1150110704
[Indexed for MEDLINE]

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