Enhanced function annotations for Drosophila serine proteases: a case study for systematic annotation of multi-member gene families.
Systematically annotating function of enzymes that belong to large protein families encoded in a single eukaryotic genome is a very challenging task. We carried out such an exercise to annotate function for serine-protease family of the trypsin fold in Drosophila melanogaster, with an emphasis on annotating serine-protease homologues (SPHs) that may have lost their catalytic function. Our approach involves data mining and data integration to provide function annotations for 190 Drosophila gene products containing serine-protease-like domains, of which 35 are SPHs. This was accomplished by analysis of structure-function relationships, gene-expression profiles, large-scale protein-protein interaction data, literature mining and bioinformatic tools. We introduce functional residue clustering (FRC), a method that performs hierarchical clustering of sequences using properties of functionally important residues and utilizes correlation co-efficient as a quantitative similarity measure to transfer in vivo substrate specificities to proteases. We show that the efficiency of transfer of substrate-specificity information using this method is generally high. FRC was also applied on Drosophila proteases to assign putative competitive inhibitor relationships (CIRs). Microarray gene-expression data were utilized to uncover a large-scale and dual involvement of proteases in development and in immune response. We found specific recruitment of SPHs and proteases with CLIP domains in immune response, suggesting evolution of a new function for SPHs. We also suggest existence of separate downstream protease cascades for immune response against bacterial/fungal infections and parasite/parasitoid infections. We verify quality of our annotations using information from RNAi screens and other evidence types. Utilization of such multi-fold approaches results in 10-fold increase of function annotation for Drosophila serine proteases and demonstrates value in increasing annotations in multiple genomes.
Shah
Parantu K
PK
European Molecular Biology Laboratory, Meyerhofstrasse 1, Heidelberg, Germany.
Tripathi
Lokesh P
LP
Jensen
Lars Juhl
LJ
Gahnim
Murad
M
Mason
Christopher
C
Furlong
Eileen E
EE
Rodrigues
Veronica
V
White
Kevin P
KP
Bork
Peer
P
Sowdhamini
R
R
D000818:Animals; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D029721:Drosophila Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D004331:Drosophila melanogaster / Q000196:embryology / Q000201:enzymology* / Q000235:genetics; D047108:Embryonic Development / Q000235:genetics; D020869:Gene Expression Profiling; D008969:Molecular Sequence Data; D025941:Protein Interaction Mapping; D017434:Protein Structure, Tertiary; D020539:Sequence Analysis, Protein / Q000379:methods*; D012697:Serine Endopeptidases / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D015842:Serine Proteinase Inhibitors / Q000494:pharmacology; D013379:Substrate Specificity
D029721:Drosophila Proteins; D015842:Serine Proteinase Inhibitors; D012697:Serine Endopeptidases