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Single molecule transcription profiling with AFM.

ABSTRACT: Established techniques for global gene expression profiling, such as microarrays, face fundamental sensitivity constraints. Due to greatly increasing interest in examining minute samples from micro-dissected tissues, including single cells, unorthodox approaches, including molecular nanotechnologies, are being explored in this application. Here, we examine the use of single molecule, ordered restriction mapping, combined with AFM, to measure gene transcription levels from very low abundance samples. We frame the problem mathematically, using coding theory, and present an analysis of the critical error sources that may serve as a guide to designing future studies. We follow with experiments detailing the construction of high density, single molecule, ordered restriction maps from plasmids and from cDNA molecules, using two different enzymes, a result not previously reported. We discuss these results in the context of our calculations.

SUBMITTER: Reed J

PROVIDER: S-EPMC2922717 | biostudies-literature | 2007 May

REPOSITORIES: biostudies-literature

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Single molecule transcription profiling with AFM.

Reed Jason J Mishra Bud B Pittenger Bede B Magonov Sergei S Troke Joshua J Teitell Michael A MA Gimzewski James K JK

Nanotechnology 20070501 4

Established techniques for global gene expression profiling, such as microarrays, face fundamental sensitivity constraints. Due to greatly increasing interest in examining minute samples from micro-dissected tissues, including single cells, unorthodox approaches, including molecular nanotechnologies, are being explored in this application. Here, we examine the use of single molecule, ordered restriction mapping, combined with AFM, to measure gene transcription levels from very low abundance samp ...[more]

PMID: 20721301

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Project description:The formation of hemostatic plugs at sites of vascular injury crucially involves the multimeric glycoprotein von Willebrand factor (VWF). VWF multimers are linear chains of N-terminally linked dimers. The latter are formed from monomers via formation of the C-terminal disulfide bonds Cys2771-Cys2773', Cys2773-Cys2771', and Cys2811-Cys2811'. Mutations in VWF that impair multimerization can lead to subtype 2A of the bleeding disorder von Willebrand Disease (VWD). Commonly, the multimer size distribution of VWF is assessed by electrophoretic multimer analysis. Here, we present atomic force microscopy (AFM) imaging as a method to determine the size distribution of VWF variants by direct visualization at the single-molecule level. We first validated our approach by investigating recombinant wildtype VWF and a previously studied mutant (p.Cys1099Tyr) that impairs N-terminal multimerization. We obtained excellent quantitative agreement with results from earlier studies and with electrophoretic multimer analysis. We then imaged specific mutants that are known to exhibit disturbed C-terminal dimerization. For the mutants p.Cys2771Arg and p.Cys2773Arg, we found the majority of monomers (87 ± 5% and 73 ± 4%, respectively) not to be C-terminally dimerized. While these results confirm that Cys2771 and Cys2773 are crucial for dimerization, they additionally provide quantitative information on the mutants' different abilities to form alternative C-terminal disulfides for residual dimerization. We further mutated Cys2811 to Ala and found that only 23 ± 3% of monomers are not C-terminally dimerized, indicating that Cys2811 is structurally less important for dimerization. Furthermore, for mutants p.Cys2771Arg, p.Cys2773Arg, and p.Cys2811Ala we found 'even-numbered' non-native multimers, i.e. multimers with monomers attached on both termini; a multimer species that cannot be distinguished from native multimers by conventional multimer analysis. Summarizing, we demonstrate that AFM imaging can provide unique insights into VWF processing defects at the single-molecule level that cannot be gained from established methods of multimer analysis.

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Single molecule transcription profiling with AFM.

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Single molecule transcription profiling with AFM.

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