Hidden Markov model analysis of multichromophore photobleaching

Troy C. Messina, Hiyun Kim, Jason T. Giurleo, David Talaga

Research output: Contribution to journalArticleResearchpeer-review

24 Citations (Scopus)

Abstract

The interpretation of single-molecule measurements is greatly complicated by the presence of multiple fluorescent 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 the background on a single-molecule basis. Hidden Markov models allow for unsupervised analysis of the data to determine the number of fluorescent subunits involved in the fluorescence intermittency of the 6-carboxytetramethylrhodamine labels by counting the discrete steps in fluorescence intensity. The Bayes information criterion 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 Carlo simulations that the hidden Markov model analysis approaches these theoretical limits. This technique has resolving power of one fluorescing unit up to as many as 30 fluorescent dyes with the appropriate choice of dye 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 general photometric experiments.

Original languageEnglish
Pages (from-to)16366-16376
Number of pages11
JournalJournal of Physical Chemistry B
Volume110
Issue number33
DOIs
StatePublished - 24 Aug 2006

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Photobleaching
Hidden Markov models
Molecules
Labels
Dyes
dyes
Fluorescence
molecules
fluorescence
dextrans
Dextran
Optical resolving power
intermittency
Dextrans
Fluorescent Dyes
counting
Polymers
Coloring Agents
Agglomeration
polymers

Cite this

Messina, Troy C. ; Kim, Hiyun ; Giurleo, Jason T. ; Talaga, David. / Hidden Markov model analysis of multichromophore photobleaching. In: Journal of Physical Chemistry B. 2006 ; Vol. 110, No. 33. pp. 16366-16376.
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Hidden Markov model analysis of multichromophore photobleaching. / Messina, Troy C.; Kim, Hiyun; Giurleo, Jason T.; Talaga, David.

In: Journal of Physical Chemistry B, Vol. 110, No. 33, 24.08.2006, p. 16366-16376.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Kim, Hiyun

AU - Giurleo, Jason T.

AU - Talaga, David

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AB - The interpretation of single-molecule measurements is greatly complicated by the presence of multiple fluorescent 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 the background on a single-molecule basis. Hidden Markov models allow for unsupervised analysis of the data to determine the number of fluorescent subunits involved in the fluorescence intermittency of the 6-carboxytetramethylrhodamine labels by counting the discrete steps in fluorescence intensity. The Bayes information criterion 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 Carlo simulations that the hidden Markov model analysis approaches these theoretical limits. This technique has resolving power of one fluorescing unit up to as many as 30 fluorescent dyes with the appropriate choice of dye 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 general photometric experiments.

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