Hidden Markov model analysis of multichromophore photobleaching.
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-carboxy-tetramethylrhodamine 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.
Messina
Troy C
TC
Department of Chemistry and Chemical Biology and BioMaPS Institute, Rutgers, the State University of New Jersey, Piscataway, New Jersey 08854, USA.
Kim
Hiyun
H
Giurleo
Jason T
JT
Talaga
David S
DS
D002863:Chromogenic Compounds / Q000737:chemistry*; D003911:Dextrans / Q000737:chemistry; D005456:Fluorescent Dyes / Q000737:chemistry; D008390:Markov Chains; D008954:Models, Biological; D015233:Models, Statistical; D009010:Monte Carlo Method; D038761:Photobleaching; D012235:Rhodamines / Q000737:chemistry
C106141:6-carboxytetramethylrhodamine; D002863:Chromogenic Compounds; D003911:Dextrans; D005456:Fluorescent Dyes; D012235:Rhodamines