Altmetric

Gene Function Hypotheses for the Campylobacter jejuni Glycome Generated by a Logic-Based Approach

File Description SizeFormat 
1-s2.0-S0022283612008327-main.pdfPublished version1.12 MBAdobe PDFDownload
Title: Gene Function Hypotheses for the Campylobacter jejuni Glycome Generated by a Logic-Based Approach
Author(s): Sternberg, MJE
Tamaddoni-Nezhad, A
Lesk, VI
Kay, E
Hitchen, PG
Cootes, A
Van Alphen, LB
Lamoureux, MP
Jarrelle, HC
Rawlings, CJ
Soo, EC
Szymanski, CM
Dell, A
Wren, BW
Muggleton, SH
Item Type: Journal Article
Abstract: Increasingly, experimental data on biological systems are obtained from several sources and computational approaches are required to integrate this information and derive models for the function of the system. Here, we demonstrate the power of a logic-based machine learning approach to propose hypotheses for gene function integrating information from two diverse experimental approaches. Specifically, we use inductive logic programming that automatically proposes hypotheses explaining the empirical data with respect to logically encoded background knowledge. We study the capsular polysaccharide biosynthetic pathway of the major human gastrointestinal pathogen Campylobacter jejuni. We consider several key steps in the formation of capsular polysaccharide consisting of 15 genes of which 8 have assigned function, and we explore the extent to which functions can be hypothesised for the remaining 7. Two sources of experimental data provide the information for learning—the results of knockout experiments on the genes involved in capsule formation and the absence/presence of capsule genes in a multitude of strains of different serotypes. The machine learning uses the pathway structure as background knowledge. We propose assignments of specific genes to five previously unassigned reaction steps. For four of these steps, there was an unambiguous optimal assignment of gene to reaction, and to the fifth, there were three candidate genes. Several of these assignments were consistent with additional experimental results. We therefore show that the logic-based methodology provides a robust strategy to integrate results from different experimental approaches and propose hypotheses for the behaviour of a biological system.
Publication Date: 23-Oct-2012
Date of Acceptance: 17-Oct-2012
URI: http://hdl.handle.net/10044/1/40592
DOI: http://dx.doi.org/10.1016/j.jmb.2012.10.014
ISSN: 1089-8638
Publisher: Elsevier
Start Page: 186
End Page: 197
Journal / Book Title: Journal of Molecular Biology
Volume: 425
Issue: 1
Sponsor/Funder: Biotechnology and Biological Sciences Research Council (BBSRC)
Biotechnology and Biological Sciences Research Council (BBSRC)
Funder's Grant Number: BB/C519670/1
BB/F008309/1
Copyright Statement: © 2012 Elsevier Ltd. Open access under CC BY license.
Keywords: Science & Technology
Life Sciences & Biomedicine
Biochemistry & Molecular Biology
BIOCHEMISTRY & MOLECULAR BIOLOGY
systems biology
Campylobacter jejuni
machine learning
capsular polysaccharide
pathway modelling
PROTEIN FUNCTION
METABOLIC PATHWAYS
GENOME SEQUENCE
PREDICTION
POLYSACCHARIDE
INTEGRATION
ANNOTATION
KNOWLEDGE
NCTC11168
NETWORKS
Artificial Intelligence
Bacterial Capsules
Biosynthetic Pathways
Campylobacter jejuni
Gene Knockout Techniques
Genes, Bacterial
Glycomics
Logic
Metabolomics
Models, Biological
Molecular Sequence Annotation
Mutation
Oligonucleotide Array Sequence Analysis
Phenotype
Polysaccharides, Bacterial
Systems Biology
Campylobacter jejuni
Polysaccharides, Bacterial
Bacterial Capsules
Oligonucleotide Array Sequence Analysis
Systems Biology
Phenotype
Mutation
Genes, Bacterial
Models, Biological
Logic
Artificial Intelligence
Biosynthetic Pathways
Glycomics
Metabolomics
Gene Knockout Techniques
Molecular Sequence Annotation
Biochemistry & Molecular Biology
0601 Biochemistry And Cell Biology
Publication Status: Published
Appears in Collections:Faculty of Engineering
Computing
Faculty of Natural Sciences



Items in Spiral are protected by copyright, with all rights reserved, unless otherwise indicated.

Creative Commons