Reconstruction And Application Of Genome-scale Biological Models Of Candida Glabrata

In this dissertation, a pyruvate producer, Candida glabrata CCTCC M202019 was chosen as a model system to reconstruct the genome-scale metabolic model(GSMM) and transcriptional regulatory network(TRN) of C. glabrata, and the genome-scale cofactor metabolic model(GSCMM) of industrial microbes based on the whole genome sequencing, functional and comparative genomics analysis. Combined the above genome-scale biological models(GSBMs) with constraint-based optimization algorithm, the physiological characteristics such as pyruvate high-productivity and low pathogenicity associated biological safety in C. glabrata, and its production performance of pyruvate and other fine chemicals derived from pyruvate were analyzed and optimized in the respects of genes, transcription, metabolism, and cofactors. The main results were described as follows:1. The whole genome sequence of C. glabrata CCTCC M202019 was sequenced by the high-throughput sequencing technology. It gets a size of 12.1 Mbp, a GC content of 38.47%, 5345 genes, 191 t RNA, 6 r RNA, and 1.15% repeat sequences. Comparative genomics analysis with C. glabrata CBS138 revealed a high similarity between the two strains. However, genetic differences existed in central carbon metabolism(nutrient and dicarboxylic acid transport, oxidative phosphorylation, and pyruvate catabolism) and adhesion metabolism(the decreased amounts of adhesive proteins, and deletions or mutations of low-complexity repeats and functional domains). Furthermore, the pyruvate high-productivity and biological safety of strain M202019 was respectively validated by wet experiments of pyruvate fermentation on four kinds of medium, growth tests on Colombia agar base, and the adhesive capacity on the inner wall of 96-microwell plates and endothelial cells.2. According to protein sequences, literature information and professional database of C. glabrata, the GSMM i NX804 for C. glabrata was reconstructed including 804 genes, 1025 metabolites, and 1287 biochemical reactions in the cytosol, mitochondria, peroxisomes, Golgi apparatus, and vacuole. Physiological characteristics of C. glabrata were recognized using the GSMM i NX804. For example, C. glabrata has a narrower carbon source utilization but a wider nitrogen spectrum. The 130 and 74 essential genes were identified on synthetic complete medium and an analogous serum medium, respectively. High pyruvate accumulation was owing to a strong glucose transport capacity, three pyruvate biosynthetic pathways(glycolysis, pentose phosphate pathway and methylglyoxal degradation), and the weaken pyruvate catabolism. Furthermore, the production performance of C. glabrata was developed:(1) The in silico pyruvate production was improved in two double knockouts mutants(glucose-6-phosphate 1-dehydrogenase and transketolase, D-lactate dehydrogenase and L-lactate dehydrogenase);(2) The inhibited ?-ketoglutarate dehydrogenase, the increased thiamin and mitochondrial ATP level were appropriate for ?-ketoglutarate production;(3) Fumarate production was increased with the flux of glycolysis and cytosolic reductive pathway;(4) The expression of ?-acetolactate carboxy-lyase benefit to acetoin production. These above strategies have successfully validated or predicted the accumulation of most products such as fumarate and acetoin.3. Using transcriptome data of C. glabrata, the genome-scale transcriptional regulatory network was reconstructed by integrating de-novo reverse-engineering and homologous methods. The C. glabrata TRN covered 6655 kinds of interaction between 145 transcription factors and 3239 target genes, and had the typical topological structure and significant network cohesiveness. Combined with the GSMM i NX804, 6 essential metabolites and related 8 enzymes were systematically selected from transcriptional regulatory modules about the pathogenicity, and verified as drug targets in C. glabrata or other pathogenic microorganisms.4. Based on 14 industrial microbial GSMMs, the GSCMM, including 6434 genes, 1782 metabolites and 6877 reactions, was reconstructed by gene re-annotation, standardization and refinements of model contents, and filling gaps. Using the GSCMM icm NX6434, cofactor metabolic reactions were characterized by enzymatic function and cellular compartments. Cofactor-related gene coverages averaged 12.9% for prokaryotes and 4.8% for eukaryotes, respectively. The two shared 533 reactions were distributed in 63 metabolic subsystems. And validated specific reactions in the prokaryotic and eukaryotic cofactor models were 152 in 34 pathways and 77 in 20 pathways, respectively. Furthermore, ATP, NADH, NADPH, and acetyl-Co A could be produced by 12, 21, 18, and 15 reactions, and be consumed by 30, 7, 21, and 29 reactions. These reactions were mainly involved in the biomolecular biosynthesis and the connection between different metabolic pathways. The common cofactors could interact with each other including ATP-NAD, ATP-acetyl-Co A, ATP-NADP(H), Co A-NADH, Co A-NADPH, and NAD-NADP. The interaction between different couples of cofactors could be as global regulatory points of the level and form of the intracellular cofactors.5. Using the GSCMM icm NX6434, effects of cofactors on cell growth, product biosynthesis, and microbial robustness were analyzed including(1) Essentail cofactor metabolic modules involved 2480 genes and 2948 reactions. The 36 candidates(the 21 validated) for cell growth were predicted by improving the biosynthesis of ATP, NAD, NADPH, and acetyl-Co A, directing these cofactors into essential metabolic pathways, as well as avoiding cofactor utilization during byproduct biosynthesis and futile cycles.(2) According to cofactor requirements of 25 kinds of industrial products, these common cofactors regulated the distribution and rate of the carbon flux by affecting enzyme activity, substrate level, enzyme activity and substrates, and coupling with other cofactors, as well as an optimized metabolic flux, could be obtained by manipulating cofactor concentration, patterns, and balance.(3) Integrated with 28 transcriptional data under environmental stress, significant changes in the ATP, NAD(H), NADP(H), or acetyl-Co A concentrations was found to trigger relevant metabolic responses to acidic, oxidative, heat, and osmotic stress. Introducing carbon flux into certain cofactor synthetic pathways and stress response pathway could enhance the robustness of industrial microorganisms.