Reduction of diffusion broadening in flow by analysis of time-gated single-molecule data.

We describe the application of Extreme Value Statistics to the analysis of discrete species that possess distinguishable properties (fluorescence wavelength, fluorescence intensity, light scattering, etc.) as they cross a well-defined observation/probe region. Time-gated selection and extreme value data analysis result in increased resolution in analytical determinations. When only the data corresponding to the smallest crossing times are selected for analysis, the width of the diffusion band decreases for the measured parameter. The molecules with the smallest crossing times diffuse preferentially along the flow direction. A Monte Carlo technique and the probability density function (pdf) for a freely diffusing species are used to generate data streams to provide a theoretical basis for the aforementioned phenomenon. These calculations are included to characterize the effect of the average flow rate and the diffusion constant. We have also included a procedure for extracting the normal diffusion constant (D) from the Extreme Value Distribution. In contrast to standard flow analysis, which requires long path lengths, our approach is particularly suited for measurements in picolitre and nanolitre volumes and provides another dimension to single-molecule measurements in cellular size volumes. We believe that this is a general phenomenon that depends upon the details of the pdf, which can be complex.

Statistics of single-molecule measurements: applications in flow-cytometry sizing of DNA fragments.

BACKGROUND: The measurement of physical properties from single molecules has been demonstrated. However, the majority of single-molecule studies report values based on relatively large data sets (e.g., N > 50). While there are studies that report physical quantities based on small sample sets, there has not been a detailed statistical analysis relating sample size to the reliability of derived parameters. METHODS: Monte Carlo simulations and multinomial analysis, dependent on quantifiable experimental parameters, were used to determine the minimum number of single-molecule measurements required to produce an accurate estimate of a population mean. Simulation results were applied to the fluorescence-based sizing of DNA fragments by ultrasensitive flow cytometry (FCM). RESULTS: Our simulations show, for an analytical technique with a 10% CV, that the average of as few as five single-molecule measurements would provide a mean value within one SD of the population mean. Additional simulations determined the number of measurements required to obtain the desired number of replicates for each subpopulation within a mixture. Application of these results to flow cytometry data for lambda/HindIII and S. aureus Mu50/SmaI DNA digests produced accurate DNA fingerprints from as few as 98 single-molecule measurements. CONCLUSIONS: A surprisingly small number of single-molecule measurements are required to obtain a mean measurement descriptive of a normally-distributed parent population.

Performance assessment of DNA fragment sizing by high-sensitivity flow cytometry and pulsed-field gel electrophoresis.

The sizing of restriction fragments is the chief analytical technique utilized in the production of DNA fingerprints. Few techniques have been able to compete with pulsed-field gel electrophoresis (PFGE), which is capable of discriminating among bacteria at species and strain levels by resolving restriction fragments. However, an ultrasensitive flow cytometer (FCM) developed in our lab has also demonstrated the ability to discriminate bacteria at species and strain levels. The abilities of FCM warrant a quantitative parallel comparison with PFGE to assess and evaluate the accuracy and precision of DNA fragment sizing by both techniques. Replicate samples of Staphylococcus aureus Mu50 were analyzed along with two clinical S. aureus isolates. The absolute fragment sizing accuracy was determined for PFGE (5% +/- 2%) and FCM (4% +/- 4%), with sequence-predicted Mu50 SmaI fragment sizes used as a reference. Precision was determined by simple arithmetic methods (relative standard deviation for PFGE [RSD(PFGE) ] = 3% +/- 2% and RSD(FCM) = 1.2% +/- 0.8%) as well as by the use of dendrograms derived from Dice coefficient-unweighted pair group method with arithmetic averages (UPGMA) and Pearson-UPGMA analyses. All quantitative measures of PFGE and FCM precision were equivalent, within error. The precision of both methods was not limited by any single sample preparation or analysis step that was tracked in this study. Additionally, we determined that the curve-based clustering of fingerprint data provided a more informative and useful assessment than did traditional band-based methods.