GSMN-ML- a genome scale metabolic network reconstruction of the obligate human pathogenMycobacterium leprae

Abstract

22 Leprosy, caused by Mycobacterium leprae, has plagued humanity for thousands 23 of years and continues to cause morbidity, disability and stigmatization in two 24 to three million people today. Although effective treatment is available, the 25 disease incidence has remained approximately constant for decades so new 26 approaches, such as vaccine or new drugs, are urgently needed for control.27 Research is however hampered by the pathogen's obligate intracellular lifestyle 28 and the fact that it has never been grown in vitro. Consequently, despite the 29 availability of its complete genome sequence, fundamental questions regarding 30 the biology of the pathogen, such as its metabolism, remain largely unexplored.31 In order to explore the metabolism of the leprosy bacillus with a long-term aim 32 of developing a medium to grow the pathogen in vitro, we reconstructed an in 33 silico genome scale metabolic model of the bacillus, GSMN-ML. The model was 2 34 used to explore the growth and biomass production capabilities of the pathogen 35 with a range of nutrient sources, such as amino acids, glucose, glycerol and 36 metabolic intermediates. We also used the model to analyze RNA-seq data 37 from M. leprae grown in mouse foot pads, and performed Differential Producibility 38 Analysis (DPA) to identify metabolic pathways that appear to be active during 39 intracellular growth of the pathogen, which included pathways for central carbon 40 metabolism, co-factor, lipids, amino acids, nucleotides and cell wall synthesis. 41The GSMN-ML model is thereby a useful in silico tool that can be used to 42 explore the metabolism of the leprosy bacillus, analyze functional genomic 43 experimental data, generate predictions of nutrients required for growth of the 44 bacillus in vitro and identify novel drug targets. 46Author Summary 47 Mycobacterium leprae, the obligate human pathogen is uncultivable in axenic 48 growth medium, and this hinders research on this pathogen, and the 49 pathogenesis of leprosy. The development of novel therapeutics relies on the 50 understanding of growth, survival and metabolism of this bacterium in the host, 51 the knowledge of which is currently very limited. Here we reconstructed a 52 metabolic network of M. leprae-GSMN-ML, a powerful in silico tool to study 53 growth and metabolism of the leprosy bacillus. We demonstrate the application 54 of GSMN-ML to identify the metabolic pathways, and metabolite classes that 55 M. leprae utilizes during intracellular growth. 56 57 Key words 58 Mycobacterium leprae; metabolism; metabolic network; genome scale model; 59 flux balance analysis; differential producibility analysis 60 61 Introduction 62 The mycobacterial genus includes two of the greatest scourges of humanity:63 Mycobacterium tuberculosis and M. leprae, responsible for tuberculosis (TB) and 64 leprosy respectively. Leprosy is one of the oldest plagues of mankind yet 65 remains prevalent in developing countries. In 1981, the World Health 66 Organization (WHO) recommended multidrug treatment (MDT) of d...

Metabolic flux partitioning between the TCA cycle and glyoxylate shunt combined with a reversible methyl citrate cycle provide nutritional flexibility forMycobacterium tuberculosis

“…S4), raising doubts over the annotated function of this protein. Mycobacterium bovis, Mycobacterium bovis BCG and Mycobacterium leprae encode similar “PPDK” genes lacking PEP/pyruvate binding domains (33, 51–52). Although it is possible that the mycobacterial PEP/pyruvate binding domain is encoded on another Mtb gene, in silico searches have not identified any genes Mtb protein homologous to the C-terminal PEP/pyruvate-binding domain of typical PPDK’s.…”