Hidden Markov Model Analysis of Multichromophore Photobleaching

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• 作者：Troy C. Messina ; Hiyun Kim ; Jason T. Giurleo ; David S. Talaga
• 刊名：Journal of Physical Chemistry B
• 出版年：2006
• 出版时间：August 24, 2006
• 年：2006
• 卷：110
• 期：33
• 页码：16366 - 16376
• 全文大小：459K
• 年卷期：v.110,no.33(August 24, 2006)
• ISSN：1520-5207

文摘

The interpretation of single-molecule measurements is greatly complicated by the presence of multiplefluorescent labels. However, many molecular systems of interest consist of multiple interacting components.We investigate this issue using multiply labeled dextran polymers that we intentionally photobleach to thebackground on a single-molecule basis. Hidden Markov models allow for unsupervised analysis of the datato determine the number of fluorescent subunits involved in the fluorescence intermittency of the 6-carboxy-tetramethylrhodamine labels by counting the discrete steps in fluorescence intensity. The Bayes informationcriterion allows us to distinguish between hidden Markov models that differ by the number of states, that is,the number of fluorescent molecules. We determine information-theoretical limits and show via Monte Carlosimulations that the hidden Markov model analysis approaches these theoretical limits. This technique hasresolving power of one fluorescing unit up to as many as 30 fluorescent dyes with the appropriate choice ofdye and adequate detection capability. We discuss the general utility of this method for determining aggregation-state distributions as could appear in many biologically important systems and its adaptability to generalphotometric experiments.