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Functionally important positions can comprise the majority of a protein's architecture.

ABSTRACT: Concomitant with the genomic era, many bioinformatics programs have been developed to identify functionally important positions from sequence alignments of protein families. To evaluate these analyses, many have used the LacI/GalR family and determined whether positions predicted to be "important" are validated by published experiments. However, we previously noted that predictions do not identify all of the experimentally important positions present in the linker regions of these homologs. In an attempt to reconcile these differences, we corrected and expanded the LacI/GalR sequence set commonly used in sequence/function analyses. Next, a variety of analyses were carried out (1) for the entire LacI/GalR sequence set and (2) for a subset of homologs with functionally-important "YxPxxxAxxL" motifs in their linkers. This strategy was devised to determine whether predictions could be improved by knowledge-based sequence sorting and-for some analyses-did increase the number of linker positions identified. However, two functionally important linker positions were not reliably identified by any analysis. Finally, we compared the new predictions to all known experimental data for E. coli LacI and three homologous linkers. From these, we estimate that >50% of positions are important to the functions of the LacI/GalR homologs. In corollary, neutral positions might occur less frequently and might be easier to detect in sequence analyses. Although analyses have successfully guided mutations that partially exchange protein functions, a better experimental understanding of the sequence/function relationships in protein families would be helpful for uncovering the remaining rules used by nature to evolve new protein functions.

SUBMITTER: Tungtur S

PROVIDER: S-EPMC3076786 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

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Functionally important positions can comprise the majority of a protein's architecture.

Tungtur Sudheer S Parente Daniel J DJ Swint-Kruse Liskin L

Proteins 20110304 5

Concomitant with the genomic era, many bioinformatics programs have been developed to identify functionally important positions from sequence alignments of protein families. To evaluate these analyses, many have used the LacI/GalR family and determined whether positions predicted to be "important" are validated by published experiments. However, we previously noted that predictions do not identify all of the experimentally important positions present in the linker regions of these homologs. In a ...[more]

PMID: 21374721

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Project description:BackgroundThe identification of functionally important residue positions is an important task of computational biology. Methods of correlation analysis allow for the identification of pairs of residue positions, whose occupancy is mutually dependent due to constraints imposed by protein structure or function. A common measure assessing these dependencies is the mutual information, which is based on Shannon's information theory that utilizes probabilities only. Consequently, such approaches do not consider the similarity of residue pairs, which may degrade the algorithm's performance. One typical algorithm is H2r, which characterizes each individual residue position k by the conn(k)-value, which is the number of significantly correlated pairs it belongs to.ResultsTo improve specificity of H2r, we developed a revised algorithm, named H2rs, which is based on the von Neumann entropy (vNE). To compute the corresponding mutual information, a matrix A is required, which assesses the similarity of residue pairs. We determined A by deducing substitution frequencies from contacting residue pairs observed in the homologs of 35 809 proteins, whose structure is known. In analogy to H2r, the enhanced algorithm computes a normalized conn(k)-value. Within the framework of H2rs, only statistically significant vNE values were considered. To decide on significance, the algorithm calculates a p-value by performing a randomization test for each individual pair of residue positions. The analysis of a large in silico testbed demonstrated that specificity and precision were higher for H2rs than for H2r and two other methods of correlation analysis. The gain in prediction quality is further confirmed by a detailed assessment of five well-studied enzymes. The outcome of H2rs and of a method that predicts contacting residue positions (PSICOV) overlapped only marginally. H2rs can be downloaded from http://www-bioinf.uni-regensburg.de.ConclusionsConsidering substitution frequencies for residue pairs by means of the von Neumann entropy and a p-value improved the success rate in identifying important residue positions. The integration of proven statistical concepts and normalization allows for an easier comparison of results obtained with different proteins. Comparing the outcome of the local method H2rs and of the global method PSICOV indicates that such methods supplement each other and have different scopes of application.

Project description:BackgroundThe population of Atlantic cod (Gadus morhua), also known as Northeast Arctic cod, migrating Atlantic cod, or simply "skrei," lives mainly in the Barents Sea and Svalbard waters and migrates in annual cycles to the Norwegian coast in order to spawn eggs during late winter. It is the world's largest population of Atlantic cod, and the population is distinct from the Norwegian coastal cod (or "fjord" cod). Despite the biological, economic, and cultural importance of migrating Atlantic cod, current knowledge on the associated microbiota is very limited. Using shotgun metagenomics and metaproteomics approaches, we present here the gut microbiota, metagenome-assembled genomes (MAGs) of the most abundant bacterial species, DNA-based functional profile, and the metaproteome of Atlantic cod specimens caught at a spawning area in an open ocean outside of Tromsø, Norway.ResultsOur analyses identified 268 bacterial families in DNA isolated from feces of 6 individual migrating Atlantic cod. The most abundant family was Vibrionaceae (52%; 83% if unclassified reads are excluded), with Photobacterium (genus) representing the vast majority. The recovery of metagenome-assembled genomes provided further details and suggests that several closely related Photobacterium strains from the Photobacterium phosphoreum clade are the most abundant. A genomic-based functional profiling showed that the most abundant functional subsystems are "Carbohydrates"; "Amino Acids and Derivatives"; "Protein Metabolism"; "Cofactors, Vitamins, Prosthetic, Groups, and Pigments"; and "DNA Metabolism," which is in agreement with other studies of gut microbiomes of marine organisms. Finally, the MS-based metaproteomic dataset revealed that the functional category "Protein Metabolism" is highly overrepresented (3×) when compared to the genome-based functional profile, which shows that ribosomal proteins are rich in the bacterial cytosol.ConclusionWe present here the first study of bacterial diversity of the gut of migrating Atlantic cod using shotgun sequencing and metagenome-assembled genomes (MAGs). The most abundant bacteria belong to the Photobacterium genus (Vibrionaceae family). We also constructed functional profiles of the gut microbiome. These may be used in future studies as a platform for mining of commercially interesting cold-active enzymes.

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Functionally important positions can comprise the majority of a protein's architecture.

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Functionally important positions can comprise the majority of a protein's architecture.

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