No abstract

Bacillus cereus is widely distributed in different food products and can cause a variety of symptoms associated with food poisoning. Since ready-to-eat (RTE) foods are not commonly sterilized by heat treatment before consumption, B. cereus contamination may cause severe food safety problems. In this study, we investigated the prevalence of B. cereus in RTE food samples from different regions of China and evaluated the levels of bacterial contamination, antibiotic resistance, virulence gene distribution, and genetic polymorphisms of these isolates. Of the tested retail RTE foods, 35% were positive for B. cereus, with 39 and 83% of the isolated strains harboring the enterotoxin-encoding hblACD and nheABC gene clusters, respectively. The entFM gene was detected in all B. cereus strains. The cytK gene was present in 68% of isolates, but only 7% harbored the emetic toxin-encoding gene cesB. Antimicrobial susceptibility testing revealed that the majority of the isolates were resistant not only to most β-lactam antibiotics, but also to rifamycin. Multilocus sequence typing (MLST) revealed that the 368 isolates belonged to 192 different sequence types (STs) including 93 new STs, the most prevalent of which was ST26. Collectively, our study indicates the prevalence, bacterial contamination levels, and biological characteristics of B. cereus isolated from RTE foods in China and demonstrates the potential hazards of B. cereus in RTE foods.

No abstract

No abstract

Aspergillus niger is a primary cell factory for food-grade protein (enzyme) production due to its strong protein secretion capacity and unique safety characteristics. The bottleneck issue for the current A. niger expression system is the difference in expression yield of heterologous proteins of non-fungal origin compared to those of fungal origin, which is about three orders of magnitude. The sweet protein monellin, derived from West African plants, has the potential to become a food-grade sweetener due to its high sweetness and the benefit of not containing sugar itself, but it is extremely difficult to establish a research model for heterologous expression in A. niger, owing to extremely low expression, a small molecular weight, and being undetectable with conventional protein electrophoresis. HiBiT-Tag was fused with low-expressing monellin in this work to create a research model for heterologous protein expression in A. niger at ultra-low levels. We increased monellin expression by increasing the monellin copy number, fusing monellin with the endogenous highly expressed glycosylase glaA, and eliminating extracellular protease degradation, among other strategies. In addition, we investigated the effects of overexpression of molecular chaperones, inhibiting the ERAD pathway, and enhancing the synthesis of phosphatidylinositol, phosphatidylcholine, and diglycerides in the biomembrane system. Using medium optimization, we finally obtained 0.284 mg/L of monellin in the supernatant of the shake flask. This is the first time recombinant monellin has been expressed in A. niger, with the goal of investigating ways to improve the secretory expression of heterologous proteins at ultra-low levels, which can serve as a model for the expression of other heterologous proteins in A. niger.

Glucoamylase has a wide range of applications in the production of glucose, antibiotics, amino acids, and other fermentation industries. Fungal glucoamylase, in particular, has attracted much attention because of its wide application in different industries, among which Aspergillus niger is the popular strain producing glucoamylase. The low availability of NADPH was found to be one of the limiting factors for the overproduction of glucoamylase. In this study, three NADH kinases (AN03, AN14, AN17) and malic enzyme (maeA) were overexpressed in aconidial A. niger by CRISPR/Cas9 technology, significantly increasing the size of the NADPH pool, resulting in the activity of glucoamylase was improved by about 70%, 50%, 90%, and 70%, respectively; the total secreted protein was increased by about 25%, 22%, 52%, and 26%, respectively. Furthermore, the combination of the mitochondrial NADH kinase (AN17) and the malic enzyme (maeA) increased glucoamylase activity by a further 19%. This study provided an effective strategy for enhancing glucoamylase production of A. niger.

The complex morphological structure of Aspergillus niger influences its production of proteins, metabolites, etc., making the genetic manipulation and clonal purification of this species increasingly difficult, especially in aconidial Aspergillus niger. In this study, we found that N-acetyl-D-glucosamine (GlcNAc) could induce the formation of spore-like propagules in the aconidial Aspergillus niger SH2 strain. The spore-like propagules possessed life activities such as drug resistance, genetic transformation, and germination. Transcriptomic analysis indicated that the spore-like propagules were resting conidia entering dormancy and becoming more tolerant to environmental stresses. The Dac1 gene and the metabolic pathway of GlcNAc converted to glycolysis are related to the formation of the spore-like propagules, as evidenced by the CRISPRi system, qPCR, and semi-quantitative RT-PCR. Moreover, a method based on the CRISPR-Cas9 tool to rapidly recycle screening tags and recover genes was suitable for Aspergillus niger SH2. To sum up, this suggests that the spore-like propagules are resting conidia and the mechanism of their formation is the metabolic pathway of GlcNAc converted to glycolysis, particularly the Dac1 gene. This study can improve our understanding of the critical factors involved in mechanisms of phenotypic change and provides a good model for researching phenotypic change in filamentous fungi.

In order to cope with the environmental problems of climate deterioration, reduce carbon emissions and develop environmentally friendly energy sources without delay. The global energy system is undergoing tremendous changes, accelerating the transformation of the energy structure, and promoting the development of the energy structure to a low-carbon or even carbon-free direction. Renewable energy has received attention due to its clean and green characteristics. Wind power generation, as an important way to develop renewable energy, faces grid security challenges due to the volatility and uncontrollability of wind speed. In this paper, a systematic prediction method is proposed for wind speed: the wind speed sequence is decomposed by the variational modal decomposition method according to the principle of envelope entropy, and the extreme learning machine network optimized by the bat algorithm is used to predict the data after decomposing. Besides, error sequence correction method based on kernel density estimation is proposed to predict residual. The availability of the model proposed in this paper is proved by experiments, and a good prediction effect is obtained. In order to heighten the utilization of wind energy, the wind power dispatching of relevant departments provides a reference method.