Developing defined starter culture for reproducible profile of flavour compound in Chinese xiaoqu baijiu fermentation.

Defined starter cultures, containing selected microbes could reduce the complexity of natural starter, are beneficial for controllable food fermentations. However, there are challenges in identifying key microbiota and constructing synthetic microbiota for traditional food fermentations. Here, we aimed to develop a defined starter culture for reproducible profile of flavour compounds, using Chinese Xiaoqu Baijiu fermentation as a case. We classified all microbes into 4 modules using weighted correlation network analysis. Module 3 presented significant correlations with flavour compounds (P < 0.05) and the highest gene abundance related with flavour compound production. 13 dominant species in module 3 were selected for mixed culture fermentation, and each species was individually deleted to analyse the effect on flavour compound production. Ten species, presenting significant effects (P < 0.05) on flavour compound production, were selected for developing the starter culture, including Rhizopus oryzae, Rhizopus microsporus, Saccharomyces cerevisiae, Pichia kudriavzevii, Wickerhamomyces anomalus, Lactobacillus acetotolerans, Levilactobacillus brevis, Weissella paramesenteroides, Pediococcus acidilactici, and Leuconostoc pseudomesenteroides. After optimising the structure of the starter culture, the profile similarity of flavour compounds produced by the starter culture reached 81.88% with that by the natural starter. This work indicated feasibility of reproducible profile of flavour compounds with defined starter culture for food fermentations.

Unraveling multifunction of low-temperature Daqu in simultaneous saccharification and fermentation of Chinese light aroma type liquor.

Chinese liquor is produced by a representative simultaneous saccharification and fermentation process. Daqu, as a starter of Chinese liquor fermentation, affects both saccharification and fermentation. However, it is still unclear how Daqu contributed to the simultaneous saccharification and fermentation process. Here, using Chinese light aroma type liquor as a case, we identified low-temperature Daqu-originated enzymes and microorganisms that contributed to the simultaneous saccharification and fermentation using metaproteomic analysis combined with amplicon sequencing analysis. α-Amylase and glucoamylase accounted for 95 % of total saccharifying enzymes and were identified as key saccharifying enzymes. Lichtheimia was the key producer of these two enzymes (> 90 %) in low-temperature Daqu. Daqu contributed 90 % α-amylase and 99 % glucoamylase to the initial liquor fermentation. These two enzymes decreased by 35 % and 49 % until day 15 in liquor fermentation. In addition, Daqu contributed key microbial genera (91 % Saccharomyces, 6.5 % Companilactobacillus) and key enzymes (37 % alcohol dehydrogenase, 40 % lactic acid dehydrogenase, 56 % aldehyde dehydrogenase) related with formations of ethanol, lactic acid and flavour compounds to the initial liquor fermentation. The average relative abundances of these fermentation-related key microorganisms and enzymes increased by 2.78 times and 1.29 times till day 15 in liquor fermentation, respectively. It indicated that Daqu provided saccharifying enzymes for starch hydrolysis, and provided both enzymes and microorganisms associated with formations of ethanol, lactic acid and flavour compounds for liquor fermentation. This work illustrated the multifunction of low-temperature Daqu in the simultaneous saccharification and fermentation of Chinese light aroma type liquor. It would facilitate improving liquor fermentation by producing high-quality Daqu.

Identification of multi-target anti-cancer agents from TCM formula by in silico prediction and in vitro validation.

Cancer is a complex disease associated with multiple gene mutations and malignant phenotypes, and multi-target drugs provide a promising therapy idea for the treatment of cancer. Natural products with abundant chemical structure types and rich pharmacological characteristics could be ideal sources for screening multi-target antineoplastic drugs. In this paper, 50 tumor-related targets were collected by searching the Therapeutic Target Database and Thomson Reuters Integrity database, and a multi-target anti-cancer prediction system based on mt-QSAR models was constructed by using naïve Bayesian and recursive partitioning algorithm for the first time. Through the multi-target anti-cancer prediction system, some dominant fragments that act on multiple tumor-related targets were analyzed, which could be helpful in designing multi-target anti-cancer drugs. Anti-cancer traditional Chinese medicine (TCM) and its natural products were collected to form a TCM formula-based natural products library, and the potential targets of the natural products in the library were predicted by multi-target anti-cancer prediction system. As a result, alkaloids, flavonoids and terpenoids were predicted to act on multiple tumor-related targets. The predicted targets of some representative compounds were verified according to literature review and most of the selected natural compounds were found to exert certain anti-cancer activity in vitro biological experiments. In conclusion, the multi-target anti-cancer prediction system is very effective and reliable, and it could be further used for elucidating the functional mechanism of anti-cancer TCM formula and screening for multi-target anti-cancer drugs. The anti-cancer natural compounds found in this paper will lay important information for further study.

Fabrication of a Tyrosine-Responsive Liquid Quantum Dots Based Biosensor through Host-Guest Chemistry.

Design and fabrication of smart liquid quantum dots (LQDs) with high biomolecule selectivity and specificity remains a challenge. Herein, a multifunctional calix[4]arene derivative (PCAD) was rationally designed and applied to fabricate a Tyr-responsive CdSe-LQD system through host-guest chemistry. Such a biosensor displays an outstanding fluorescence/macroscopic response for Tyr and reversible fluidic features due to the hydrogen interaction between the PCAD of CdSe-LQDs and Tyr. These excellent results highlighted CdSe-LQDs as a promising platform for biological molecule recognition and separation in the future.

Improved Formula for the Stress Intensity Factor of Semi-Elliptical Surface Cracks in Welded Joints under Bending Stress.

Welded joints are prone to fatigue cracking with the existence of welding defects and bending stress. Fracture mechanics is a useful approach in which the fatigue life of the welded joint can be predicted. The key challenge of such predictions using fracture mechanics is how to accurately calculate the stress intensity factor (SIF). An empirical formula for calculating the SIF of welded joints under bending stress was developed by Baik, Yamada and Ishikawa based on the hybrid method. However, when calculating the SIF of a semi-elliptical crack, this study found that the accuracy of the Baik-Yamada formula was poor when comparing the benchmark results, experimental data and numerical results. The reasons for the reduced accuracy of the Baik-Yamada formula were identified and discussed in this paper. Furthermore, a new correction factor was developed and added to the Baik-Yamada formula by using theoretical analysis and numerical regression. Finally, the predictions using the modified Baik-Yamada formula were compared with the benchmark results, experimental data and numerical results. It was found that the accuracy of the modified Baik-Yamada formula was greatly improved. Therefore, it is proposed that this modified formula is used to conveniently and accurately calculate the SIF of semi-elliptical cracks in welded joints under bending stress.