Reconstruction and in silico analysis of an Actinoplanes sp. SE50/110 genome-scale metabolic model for acarbose production

Complete genome sequence, metabolic model construction, and huangjiu application of Saccharopolyspora rosea A22, a thermophilic, high amylase and glucoamylase actinomycetes

Saccharopolyspora is an important microorganism in the fermentation process of wheat qu and huangjiu, yet the mechanisms by which it performs specific functions in huangjiu remain unclear. A strain with high amylase and glucoamylase activities was isolated from wheat qu and identified as Saccharopolyspora rosea (S. rosea) A22. We initially reported the whole genome sequence of S. rosea A22, which comprised a circular chromosome 6,562,638 bp in size with a GC content of 71.71%, and 6,118 protein-coding genes. A functional genomic analysis highlighted regulatory genes involved in adaptive mechanisms to harsh conditions, and in vitro experiments revealed that the growth of S. rosea A22 could be regulated in response to the stress condition. Based on whole-genome sequencing, the first genome-scale metabolic model of S. rosea A22 named iSR1310 was constructed to predict the growth ability on different media with 91% accuracy. Finally, S. rosea A22 was applied to huangjiu fermentation by inoculating raw wheat qu, and the results showed that the total higher alcohol content was reduced by 12.64% compared with the control group. This study has elucidated the tolerance mechanisms and enzyme-producing properties of S. rosea A22 at the genetic level, providing new insights into its application to huangjiu.

Genomic sequencing, genome-scale metabolic network reconstruction, and in silico flux analysis of the grape endophytic fungus Alternaria sp. MG1

BACKGROUND

Alternaria sp. MG1, an endophytic fungus isolated from grape, is a native producer of resveratrol, which has important application potential. However, the metabolic characteristics and physiological behavior of MG1 still remains mostly unraveled. In addition, the resveratrol production of the strain is low. Thus, the whole-genome sequencing is highly required for elucidating the resveratrol biosynthesis pathway. Furthermore, the metabolic network model of MG1 was constructed to provide a computational guided approach for improving the yield of resveratrol.

RESULTS

Firstly, a draft genomic sequence of MG1 was generated with a size of 34.7 Mbp and a GC content of 50.96%. Genome annotation indicated that MG1 possessed complete biosynthesis pathways for stilbenoids, flavonoids, and lignins. Eight secondary metabolites involved in these pathways were detected by GC-MS analysis, confirming the metabolic diversity of MG1. Furthermore, the first genome-scale metabolic network of Alternaria sp. MG1 (named iYL1539) was reconstructed, accounting for 1539 genes, 2231 metabolites, and 2255 reactions. The model was validated qualitatively and quantitatively by comparing the in silico simulation with experimental data, and the results showed a high consistency. In iYL1539, 56 genes were identified as growth essential in rich medium. According to constraint-based analysis, the importance of cofactors for the resveratrol biosynthesis was successfully demonstrated. Ethanol addition was predicted in silico to be an effective method to improve resveratrol production by strengthening acetyl-CoA synthesis and pentose phosphate pathway, and was verified experimentally with a 26.31% increase of resveratrol. Finally, 6 genes were identified as potential targets for resveratrol over-production by the recently developed methodology. The target-genes were validated using salicylic acid as elicitor, leading to an increase of resveratrol yield by 33.32% and the expression of gene 4CL and CHS by 1.8- and 1.6-fold, respectively.

CONCLUSIONS

This study details the diverse capability and key genes of Alternaria sp. MG1 to produce multiple secondary metabolites. The first model of the species Alternaria was constructed, providing an overall understanding of the physiological behavior and metabolic characteristics of MG1. The model is a highly useful tool for enhancing productivity by rational design of the metabolic pathway for resveratrol and other secondary metabolites.

Comparative functional genomics of the acarbose producers reveals potential targets for metabolic engineering

The α-glucosidase inhibitor acarbose is produced in large-scale by strains derived from Actinoplanes sp. SE50 and used widely for the treatment of type-2 diabetes. Compared with the wild-type SE50, a high-yield derivative Actinoplanes sp. SE50/110 shows 2-fold and 3–7-fold improvement of acarbose yield and acb cluster transcription, respectively. The genome of SE50 was fully sequenced and compared with that of SE50/110, and 11 SNVs and 4 InDels, affecting 8 CDSs, were identified in SE50/110. The 8 CDSs were individually inactivated in SE50. Deletions of ACWT_4325 (encoding alcohol dehydrogenase) resulted in increases of acarbose yield by 25% from 1.87 to 2.34 g/L, acetyl-CoA concentration by 52.7%, and PEP concentration by 22.7%. Meanwhile, deletion of ACWT_7629 (encoding elongation factor G) caused improvements of acarbose yield by 36% from 1.87 to 2.54 g/L, transcription of acb cluster, and ppGpp concentration to 2.2 folds. Combined deletions of ACWT_4325 and ACWT_7629 resulted in further improvement of acarbose to 2.83 g/L (i.e. 76% of SE50/110), suggesting that the metabolic perturbation and improved transcription of acb cluster caused by these two mutations contribute substantially to the acarbose overproduction. Enforced application of similar strategies was performed to manipulate SE50/110, resulting in a further increase of acarbose titer from 3.73 to 4.21 g/L. Therefore, the comparative genomics approach combined with functional verification not only revealed the acarbose overproduction mechanisms, but also guided further engineering of its high-yield producers.

Genome-Scale Metabolic Model of Actinosynnema pretiosum ATCC 31280 and Its Application for Ansamitocin P-3 Production Improvement

Actinosynnema pretiosum ATCC 31280 is the producer of antitumor agent ansamitocin P-3 (AP-3). Understanding of the AP-3 biosynthetic pathway and the whole metabolic network in A. pretiosum is important for the improvement of AP-3 titer. In this study, we reconstructed the first complete Genome-Scale Metabolic Model (GSMM) Aspm1282 for A. pretiosum ATCC 31280 based on the newly sequenced genome, with 87% reactions having definite functional annotation. The model has been validated by effectively predicting growth and the key genes for AP-3 biosynthesis. Then we built condition-specific models for an AP-3 high-yield mutant NXJ-24 by integrating Aspm1282 model with time-course transcriptome data. The changes of flux distribution reflect the metabolic shift from growth-related pathway to secondary metabolism pathway since the second day of cultivation. The AP-3 and methionine metabolisms were both enriched in active flux for the last two days, which uncovered the relationships among cell growth, activation of methionine metabolism, and the biosynthesis of AP-3. Furthermore, we identified four combinatorial gene modifications for overproducing AP-3 by in silico strain design, which improved the theoretical flux of AP-3 biosynthesis from 0.201 to 0.372 mmol/gDW/h. Upregulation of methionine metabolic pathway is a potential strategy to improve the production of AP-3.

Genome-scale biological models for industrial microbial systems

The primary aims and challenges associated with microbial fermentation include achieving faster cell growth, higher productivity, and more robust production processes. Genome-scale biological models, predicting the formation of an interaction among genetic materials, enzymes, and metabolites, constitute a systematic and comprehensive platform to analyze and optimize the microbial growth and production of biological products. Genome-scale biological models can help optimize microbial growth-associated traits by simulating biomass formation, predicting growth rates, and identifying the requirements for cell growth. With regard to microbial product biosynthesis, genome-scale biological models can be used to design product biosynthetic pathways, accelerate production efficiency, and reduce metabolic side effects, leading to improved production performance. The present review discusses the development of microbial genome-scale biological models since their emergence and emphasizes their pertinent application in improving industrial microbial fermentation of biological products.

Chemical and Biological Aspects of Extracts from Medicinal Plants with Antidiabetic Effects

Diabetes mellitus is a chronic disease and a leading cause of death in western countries. Despite advancements in the clinical management of the disease, it is not possible to control the late complications of diabetes. The main characteristic feature of diabetes is hyperglycemia, which reflects the deterioration in the use of glucose due to a faulty or poor response to insulin secretion. Alloxan and streptozotocin (STZ) are the chemical tools that are most commonly used to study the disease in rodents. Many plant species have been used in ethnopharmacology or to treat experimentally symptoms of this disease. When evaluated pharmacologically, most of the plants employed as antidiabetic substances have been shown to exhibit hypoglycemic and antihyperglycemic activities, and to contain chemical constituents that may be used as new antidiabetic agents. There are many substances extracted from plants that offer antidiabetic potential, whereas others may result in hypoglycemia as a side effect due to their toxicity, particularly their hepatotoxicity. In this article we present an updated overview of the studies on extracts from medicinal plants, relating the mechanisms of action by which these substances act and the natural principles of antidiabetic activity.