In spite of much progress on its mechanism, diagnosis and treatment, diabetes mellitus remains a public health challenge. The harm of diabetes is not significantly reduced, instead shows an increasing tendency year by year. To achieve an in?depth and comprehensive understanding of the underlying mechanism, and to develop efficacious, stable and hypoglycemia?risk free drugs, it is crucial to gain more knowledge about diabetes from animal models. In this review, the types of diabetes animal models, modeling methods, the advantages and disadvantages, their applicable scope are discussed aiming to provide a reference for researchers to choose appropriate animal models.

Objective To investigate the influence of tissue-specific growth hormone receptor (GHR)deficiency in type 1 diabetes in the mice at the gene level using pancreaticβcells combined with streptozotocin (STZ)-induced type 1 diabetes model.Methods The experiment was divided into four groups:knockout mice group (LLc knockout group), using the homozygotes (LLc:LL+Cre) producted by pancreaticβ cell-specific expressed recombinant enzyme mice (RIP-Cre)and Cre-LoxP system modified GHR mice (Floxed,LL);LL control group, containing Floxed GHR allele homozygous mice (LL);LLc STZ group and LL STZ group (STZ was used for inducing type 1 diabetes model mice). The mice with feeding glucose≥25 mmol · L-1 were considered to be successful models.The Glucose Tolerance Test (GTT),pancreas tissue HE staining and immunohistochemistry were performed in the mice.Results The blood glucose of the mice in LL STZ group and LLc STZ group and LLc STZ group were increased after inj ection of STZ and the models achieved the diagnostic criteria for diabetes 1 6 d later.The results of GTT showed that compared with LLc control group and LLc knockout group, the blood glucose levels of the mice in LL STZ and LLc STZ groups were increased (P<0.05).There was no significant change of morphology and structure of islets between LL control group and LLc knockout group detected by HE staining. The immunohistochemistry results showed that the insulin level of the mice in LL STZ group was significantly reduced compared with LL control group;the insulin level of the mice in LLc STZ group was reduced compared with LLc control group.Conclusion Pancreaticβcell GHR gene knockout has no effect on the blood glucose and the function ofβcells in the mice with STZ-induced type 1 diabetes.

Directed evolution, which is also called molecular evolution, or artificial evolution, combines random mutagenesis and directed selection. In previous studies, it has been extensively applied for the improvement of enzyme catalytic properties and stability, as well as the expanding of substrate specificity. In recent years, directed evolution was also employed in metabolic engineering of promoters for improving their strength and function, and the engineering of global transcription machinery. These techniques contribute to breeding more tolerant strains against environmental stress, as well as strains with improved fermentation efficiency. In this article, we reviewed the applications of directed evolution in the metabolic engineering of promoters and global transcription machinery. These techniques enabled fine-tuning of gene expression and simultaneous alternation of multiple gene transcription inside the cells, and thus are powerful new tools for metabolic engineering.
Directed Molecular Evolution ; Genetic Engineering ; Industrial Microbiology ; methods ; Metabolism ; Promoter Regions, Genetic ; genetics ; Saccharomyces cerevisiae ; genetics ; Transcription, Genetic ; genetics

Improvement of stress tolerance to various adverse environmental conditions (such as toxic products, high temperature) of the industrial microorganisms is important for industrial applications. Ethanol produced by yeast fermentation is inhibitory to both yeast cell growth and metabolisms, and consequently is one of the key stress elements of brewer's yeast. Research on the biochemical and molecular mechanism of the tolerance of yeast can provide basis for breeding of yeast strain with improved ethanol tolerance. In recent years, employing global gene transcriptional analysis and functional analysis, new knowledge on the biochemical and molecular mechanisms of yeast ethanol tolerance has been accumulated, and novel genes and biochemical parameters related to ethanol tolerance have been revealed. Based on these studies, the overexpression and/or disruption of the related genes have successfully resulted in the breeding of new yeast strains with improved ethanol tolerance. This paper reviewed the recent research progress on the molecular mechanism of yeast ethanol tolerance, as well as the genetic engineering manipulations to improve yeast ethanol tolerance. The studies reviewed here not only deepened our knowledge on yeast ethanol tolerance, but also provided basis for more efficient bioconversion for bio-energy production.
Drug Tolerance ; genetics ; Ethanol ; metabolism ; pharmacology ; Fermentation ; Genetic Engineering ; methods ; Industrial Microbiology ; methods ; Saccharomyces cerevisiae ; drug effects ; genetics ; Saccharomyces cerevisiae Proteins ; genetics

Directed evolution of transcription factors can be employed to effectively improve the phenotypes which are controlled by multiple genetic loci. In this study, we used error-prone PCR for the directed evolution of SPT3, which is the component of yeast Spt-Ada-Gcn5-acetyltransferase (SAGA) complex responsible for the transcription of stress-related genes, and studied its effect on the improvement of ethanol tolerance. Mutant library was constructed by ligating the error-prone PCR products with a modified pYES2.0 plasmid, and the expression plasmids were subsequently transformed to yeast industrial strain Saccharomyces cerevisiae 4126. One mutant strain M25 showing superior growth in presence of 10% ethanol was selected. M25 produced 11.7% more ethanol than the control strain harboring the empty vector when 125 g/L glucose was used as substrate. This study revealed that SPT3 is an important transcription factor for the metabolic engineering of yeast ethanol tolerance.
Directed Molecular Evolution ; methods ; Drug Resistance, Fungal ; Drug Tolerance ; Ethanol ; metabolism ; pharmacology ; Industrial Microbiology ; methods ; Saccharomyces cerevisiae ; drug effects ; genetics ; metabolism ; Saccharomyces cerevisiae Proteins ; genetics ; Trans-Activators ; genetics ; Transcription Factors ; genetics

On January 22, 2020, China National Center for Bioinformation (CNCB) released the 2019 Novel Coronavirus Resource (2019nCoVR), an open-access information resource for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). 2019nCoVR features a comprehensive integra-tion of sequence and clinical information for all publicly available SARS-CoV-2 isolates, which are manually curated with value-added annotations and quality evaluated by an automated in-house pipeline. Of particular note, 2019nCoVR offers systematic analyses to generate a dynamic landscape of SARS-CoV-2 genomic variations at a global scale. It provides all identified variants and their detailed statistics for each virus isolate, and congregates the quality score, functional annotation,and population frequency for each variant. Spatiotemporal change for each variant can be visualized and historical viral haplotype network maps for the course of the outbreak are also generated based on all complete and high-quality genomes available. Moreover, 2019nCoVR provides a full collection of SARS-CoV-2 relevant literature on the coronavirus disease 2019 (COVID-19), including published papers from PubMed as well as preprints from services such as bioRxiv and medRxiv through Europe PMC. Furthermore, by linking with relevant databases in CNCB, 2019nCoVR offers data submission services for raw sequence reads and assembled genomes, and data sharing with NCBI. Collectively, SARS-CoV-2 is updated daily to collect the latest information on genome sequences, variants, hap-lotypes, and literature for a timely reflection, making 2019nCoVR a valuable resource for the global research community. 2019nCoVR is accessible at https://bigd.big.ac.cn/ncov/.