
Use of systems biology to decipher host microbial interactions and predict pathological consequences


In systems biology, researchers aim to understand complex biological systems as a whole, which is often achieved by mathematical modelling and the analyses of high-throughput data. In this review, we give an overview of medical applications of systems biology approaches with special focus on host-pathogen interactions. After introducing general ideas of systems biology, we focus on (1) the detection of putative biomarkers for improved diagnosis and support of therapeutic decisions; (2) network modelling for the identification of regulatory interactions between cellular molecules to reveal putative drug targets; (3) module discovery for the detection of phenotype-specific modules in molecular interaction networks. Biomarker detection applies supervised machine learning methods utilising high-throughput data (e.g. SNP detection, RNA-seq, proteomics) and clinical data. We demonstrate structural analysis of molecular networks, especially by identification of disease modules as novel strategy, and discuss possible applications to host-pathogen interactions. Pioneering work was done to predict molecular host-pathogen interactions networks based on dual RNA-seq data. However, currently this network modelling is restricted to a small number of genes. With increasing number and quality of databases and data repositories, also the prediction of large-scale networks will be feasible that can used for multi-dimensional diagnosis and decision support for prevention and therapy of diseases. Finally, we outline further perspective issues such as support of personalised medicine with high-throughput data and generation of multi-scale host-pathogen interaction models.
SEEK ID: https://funginet.hki-jena.de/publications/67
PubMed ID: 27113568
Projects: B3 (E), FungiNet B - Bioinformatics projects, INF
Publication type: Not specified
Journal: Clin Microbiol Infect
Citation:
Date Published: 27th Apr 2016
Registered Mode: Not specified

Views: 2904
Created: 10th May 2016 at 08:23
Last updated: 17th Jan 2024 at 10:24

This item has not yet been tagged.

None