Confidence intervals of evolutionary distances between sequences and comparison with usual approaches including the bootstrap method.

Two methods are commonly employed for evaluating the extent of the uncertainty of evolutionary distances between sequences: either some estimator of the variance of the distance estimator, or the bootstrap method. However, both approaches can be misleading, particularly when the evolutionary distance is small. We propose using another statistical method which does not have the same defect: interval estimation. We show how confidence intervals may be constructed for the Jukes and Cantor (1969) and Kimura two-parameter (1980) estimators. We compare the exact confidence intervals thus obtained with the approximate intervals derived by the two previous methods, using artificial and biological data. The results show that the usual methods clearly underestimate the variability when the substitution rate is low and when sequences are short. Moreover, our analysis suggests that similar results may be expected for other evolutionary distance estimators.

A specialised proteomic database for comparing matrix-assisted laser desorption/ionization-time of flight mass spectrometry data of tryptic peptides with corresponding sequence database segments.

We have developed a specialised proteomic database for the analysis of matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) data derived from tryptic peptides of Sinorhizobium meliloti proteins. This database currently contains the amino acid sequence data of the proteins predicted from the complete chromosome, MALDI-TOF MS data from proteolytic peptides of about 400 tryptically digested proteins, and the results of a search of the MALDI-TOF MS spectra against the chromosomal amino acid sequences. The database made it possible to access and compare the sequences of theoretical tryptic peptides that correspond to MALDI-TOF peaks in the mass spectrum with predicted tryptic peptides from identified proteins that could not be matched to MALDI-TOF peaks. A comparison of the molecular weights, isoelectric points and amino acid compositions of the identified and nonidentified peptides is presented. We also show how the system can assist in the development of an automated scoring function that facilitates and consolidates protein identification.