Genome-scale metabolic models as platforms for identification of novel genes as antimicrobial drug targets

被引:17
作者
Mienda, Bashir Sajo [1 ]
Salihu, Rabiu [1 ]
Adamu, Aliyu [2 ]
Idris, Shehu [3 ]
机构
[1] Fed Univ Dutse, Dept Microbiol & Biotechnol, Fac Sci, PMB 7156 Ibrahim Aliyu Bypass, Dutse, Jigawa State, Nigeria
[2] Univ Teknol Malaysia, Fac Biosci & Med Engn, Dept Biotechnol & Med Engn, Johor Baharu 81310, Malaysia
[3] Kaduna State Univ, Dept Microbiol, Fac Sci, Tafawa Balewa Way,PMB 2339, Kaduna, Kaduna State, Nigeria
关键词
antimicrobial drug targets; essential genes; genome-scale metabolic models (GEMs); identification of novel genes; BRANCHED-CHAIN AMINOTRANSFERASE; CONSTRAINT-BASED MODELS; FLUX BALANCE ANALYSIS; MYCOBACTERIUM-TUBERCULOSIS; STAPHYLOCOCCUS-AUREUS; ESCHERICHIA-COLI; PSEUDOMONAS-AERUGINOSA; DRIVEN DISCOVERY; RESISTANCE; RECONSTRUCTION;
D O I
10.2217/fmb-2017-0195
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
The growing number of multidrug-resistant pathogenic bacteria is becoming a world leading challenge for the scientific community and for public health. However, advances in high-throughput technologies and whole-genome sequencing of bacterial pathogens make the construction of bacterial genome-scale metabolic models (GEMs) increasingly realistic. The use of GEMs as an alternative platforms will expedite identification of novel unconditionally essential genes and enzymes of target organisms with existing and forthcoming GEMs. This approach will follow the existing protocol for construction of high-quality GEMs, which could ultimately reduce the time, cost and labor-intensive processes involved in identification of novel antimicrobial drug targets in drug discovery pipelines. We discuss the current impact of existing GEMs of selected multidrug-resistant pathogenic bacteria for identification of novel antimicrobial drug targets and the challenges of closing the gap between genome-scale metabolic modeling and conventional experimental trial-and-error approaches in drug discovery pipelines. [GRAPHICS] .
引用
收藏
页码:455 / 467
页数:13
相关论文
共 50 条
[41]   Exploring the metabolic profile of A. baumannii for antimicrobial development using genome-scale modeling [J].
Leonidou, Nantia ;
Xia, Yufan ;
Friedrich, Lea ;
Schuetz, Monika S. ;
Draeger, Andreas .
PLOS PATHOGENS, 2024, 20 (09)
[42]   Genome-scale metabolic networks [J].
Terzer, Marco ;
Maynard, Nathaniel D. ;
Covert, Markus W. ;
Stelling, Joerg .
WILEY INTERDISCIPLINARY REVIEWS-SYSTEMS BIOLOGY AND MEDICINE, 2009, 1 (03) :285-297
[43]   A workflow for generating multi-strain genome-scale metabolic models of prokaryotes [J].
Norsigian, Charles J. ;
Fang, Xin ;
Seif, Yara ;
Monk, Jonathan M. ;
Palsson, Bernhard O. .
NATURE PROTOCOLS, 2020, 15 (01) :1-14
[44]   Logical transformation of genome-scale metabolic models for gene level applications and analysis [J].
Zhang, Cheng ;
Ji, Boyang ;
Mardinoglu, Adil ;
Nielsen, Jens ;
Hua, Qiang .
BIOINFORMATICS, 2015, 31 (14) :2324-2331
[45]   Leveraging genome-scale metabolic models for human health applications [J].
Chowdhury, Shomeek ;
Fong, Stephen S. .
CURRENT OPINION IN BIOTECHNOLOGY, 2020, 66 :267-276
[46]   Comprehensive Evaluation of Two Genome-Scale Metabolic Network Models for Scheffersomyces Stipitis [J].
Damiani, Andrew L. ;
He, Q. Peter ;
Jeffries, Thomas W. ;
Wang, Jin .
BIOTECHNOLOGY AND BIOENGINEERING, 2015, 112 (06) :1250-1262
[47]   Progress on genome-scale metabolic models integrated with multi-omics data [J].
Wang, Xueliang ;
Zhang, Yun ;
Wen, Tingyi .
CHINESE SCIENCE BULLETIN-CHINESE, 2021, 66 (19) :2393-2404
[48]   CycSim-an online tool for exploring and experimenting with genome-scale metabolic models [J].
Le Fevre, F. ;
Smidtas, S. ;
Combe, C. ;
Durot, M. ;
d'Alche-Buc, Florence ;
Schachter, V. .
BIOINFORMATICS, 2009, 25 (15) :1987-1988
[49]   MetaboTools: A Comprehensive Toolbox for Analysis of Genome-Scale Metabolic Models [J].
Aurich, Maike K. ;
Fleming, Ronan M. T. ;
Thiele, Ines .
FRONTIERS IN PHYSIOLOGY, 2016, 7
[50]   Applicatons of Genome-Scale Metabolic Models in Biotechnology and Systems Medicine [J].
Zhang, Cheng ;
Hua, Qiang .
FRONTIERS IN PHYSIOLOGY, 2016, 6