A protocol for constructing a domain-specific ontology for use in biomedical information extraction using lexical-chaining analysis

In order to do more semantics-based information extraction, we require specialized domain models. We develop a hybrid approach for constructing such a domain-specific ontology, which integrates key concepts from the protein-protein–interaction domain with the Gene Ontology. In addition, we present a method for using the domain-specific ontology in a discourse-based analysis module for analyzing full-text articles on protein interactions. The analysis module uses a lexical chaining technique to extract strings of semantically related words that represent the topic structure of the text. We show that the domain-specific ontology improved the performance of the lexical-chaining module. As well the topic structure as represented by the lexical chains contains important information on protein-protein interactions appearing in the same textual context

Interactions of AtRGL1, a negative regulator of gibberellic acid signalling : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Biochemistry, Massey University, Palmerston North, New Zealand

Arabidopsis thaliana AtRGL1 (repressor of ga1-3 like-1) is a negative regulator of the signal transduction pathway of the plant hormone gibberellin. AtRGL1 belongs to the DELLA subfamily within the GRAS family of plant regulatory proteins. There are four other DELLA proteins, including AtRGA (repressor of ga1-3) and AtRGL2, encoded by the A. thaliana genome. Previous studies provided evidence that the DELLA proteins are nuclear localised and are functionally divided into N- and C- terminal domains. The N-terminal domain perceives the gibberellin signal, while the C-terminal domain functions as a negative regulator of transcription and also as a possible dimerisation domain. Previous studies have also shown that AtRGA, AtRGL1, and AtRGL2 function together in the regulation of the development of the inflorescence and that AtRGL1 is primarily expressed in this tissue. To investigate how DELLA proteins function in gibberellin signalling. I sought plant proteins that interact with AtRGL1. Two proteins. p24 (24 kDa) and p64 (64 kDa), were isolated from wild-type plant nuclear extracts by affinity to the N-tenninal 121 amino acid residues of AtRGL1. The identity of these two proteins remains to be established. To investigate the interactions of the C-terminal domain of AtRGL1 an anti-AtRGL1 polyclonal antiserum was developed for co-immunoprecipitation experiments. However, AtRGL1 was not detectable in plant nuclear extracts from the inflorescence of wild-type plants, precluding this approach. The possibility of DELLA protein dimerisation was also investigated using AtRGA, AtRGL1, and AtRGL2 in yeast 2-hybrid experiments. Yeast 2-hybrid protein interaction results suggest that AtRGA, AtRGL1, and AtRGL2 do not form homo- or hetero-dimers. Complexities encountered with this approach could make these results invalid, so these interactions require further investigation

Applicability of tandem affinity purification MudPIT to pathway proteomics in yeast

A combined multidimensional chromatography-mass spectrometry approach known as "MudPIT" enables rapid identification of proteins that interact with a tagged bait while bypassing some of the problems associated with analysis of polypeptides excised from SDS-polyacrylamide gels. However, the reproducibility, success rate, and applicability of MudPIT to the rapid characterization of dozens of proteins have not been reported. We show here that MudPIT reproducibly identified bona fide partners for budding yeast Gcn5p. Additionally, we successfully applied MudPIT to rapidly screen through a collection of tagged polypeptides to identify new protein interactions. Twenty-five proteins involved in transcription and progression through mitosis were modified with a new tandem affinity purification (TAP) tag. TAP-MudPIT analysis of 22 yeast strains that expressed these tagged proteins uncovered known or likely interacting partners for 21 of the baits, a figure that compares favorably with traditional approaches. The proteins identified here comprised 102 previously known and 279 potential physical interactions. Even for the intensively studied Swi2p/Snf2p, the catalytic subunit of the Swi/Snf chromatin remodeling complex, our analysis uncovered a new interacting protein, Rtt102p. Reciprocal tagging and TAP-MudPIT analysis of Rtt102p revealed subunits of both the Swi/Snf and RSC complexes, identifying Rtt102p as a common interactor with, and possible integral component of, these chromatin remodeling machines. Our experience indicates it is feasible for an investigator working with a single ion trap instrument in a conventional molecular/cellular biology laboratory to carry out proteomic characterization of a pathway, organelle, or process (i.e. "pathway proteomics") by systematic application of TAP-MudPIT

An optimized energy potential can predict SH2 domain-peptide interactions

Peptide recognition modules (PRMs) are used throughout biology to mediate protein-protein interactions, and many PRMs are members of large protein domain families. Members of these families are often quite similar to each other, but each domain recognizes a distinct set of peptides, raising the question of how peptide recognition specificity is achieved using similar protein domains. The analysis of individual protein complex structures often gives answers that are not easily applicable to other members of the same PRM family. Bioinformatics-based approaches, one the other hand, may be difficult to interpret physically. Here we integrate structural information with a large, quantitative data set of SH2-peptide interactions to study the physical origin of domain-peptide specificity. We develop an energy model, inspired by protein folding, based on interactions between the amino acid positions in the domain and peptide. We use this model to successfully predict which SH2 domains and peptides interact and uncover the positions in each that are important for specificity. The energy model is general enough that it can be applied to other members of the SH2 family or to new peptides, and the cross-validation results suggest that these energy calculations will be useful for predicting binding interactions. It can also be adapted to study other PRM families, predict optimal peptides for a given SH2 domain, or study other biological interactions, e.g. protein-DNA interactions

Charting the protein complexome in yeast by mass spectrometry

It has become evident over the past few years that many complex cellular processes, including control of the cell cycle and ubiquitin-dependent proteolysis, are carried out by sophisticated multisubunit protein machines that are dynamic in abundance, post-translational modification state, and composition. To understand better the nature of the macromolecular assemblages that carry out the cell cycle and ubiquitin-dependent proteolysis, we have used mass spectrometry extensively over the past few years to characterize both the composition of various protein complexes and the modification states of their subunits. In this article we review some of our recent efforts, and describe a promising new approach for using mass spectrometry to dissect protein interaction networks

Interaction specificity of Arabidopsis 14-3-3 proteins with phototropin receptor kinases

Phototropin receptor kinases play an important roles in optimising plant growth in response to blue light. Much is known regarding their photochemical reactivity, yet little progress has been made to identify downstream signalling components. Here, we isolated several interacting proteins for Arabidopsis phototropin 1 (phot1) by yeast two-hybrid screening. These include members of the NPH3/RPT2 (NRL) protein family, proteins associated with vesicle trafficking, and the 14-3-3 lambda (?) isoform from Arabidopsis . 14-3-3? and phot1 were found to colocalise and interact in vivo. Moreover, 14-3-3 binding to phot1 was limited to non-epsilon 14-3-3 isoforms and was dependent on key sites of receptor autophosphorylation. No 14-3-3 binding was detected for Arabidopsis phot2, suggesting that 14-3-3 proteins represent specific mode of phot1 signalling

Novel cyclic di-GMP effectors of the YajQ protein family control bacterial virulence

Bis-(3 ',5 ') cyclic di-guanylate (cyclic di-GMP) is a key bacterial second messenger that is implicated in the regulation of many critical processes that include motility, biofilm formation and virulence. Cyclic di-GMP influences diverse functions through interaction with a range of effectors. Our knowledge of these effectors and their different regulatory actions is far from complete, however. Here we have used an affinity pull-down assay using cyclic di-GMP-coupled magnetic beads to identify cyclic di-GMP binding proteins in the plant pathogen Xanthomonas campestris pv. campestris (Xcc). This analysis identified XC_3703, a protein of the YajQ family, as a potential cyclic di-GMP receptor. Isothermal titration calorimetry showed that the purified XC_3703 protein bound cyclic di-GMP with a high affinity (K-d similar to 2 mu M). Mutation of XC_3703 led to reduced virulence of Xcc to plants and alteration in biofilm formation. Yeast two-hybrid and far-western analyses showed that XC_3703 was able to interact with XC_2801, a transcription factor of the LysR family. Mutation of XC_2801 and XC_3703 had partially overlapping effects on the transcriptome of Xcc, and both affected virulence. Electromobility shift assays showed that XC_3703 positively affected the binding of XC_2801 to the promoters of target virulence genes, an effect that was reversed by cyclic di-GMP. Genetic and functional analysis of YajQ family members from the human pathogens Pseudomonas aeruginosa and Stenotrophomonas maltophilia showed that they also specifically bound cyclic di-GMP and contributed to virulence in model systems. The findings thus identify a new class of cyclic di-GMP effector that regulates bacterial virulence