Saturnispora sinensis sp. nov., a new ascomycetous yeast species from soil and rotten wood.

A yeast strain (CGMCC 2.6937T) belonging to the ascomycetous yeast genus Saturnispora was recently isolated from soil collected in Xinghuacun, Shanxi Province, PR China. The strain produces one or two ellipsoid or spherical ascospores in asci formed by the conjugation between a cell and its bud. Phylogenetic analyses of the internal transcribed spacer (ITS) region and the D1/D2 domain of the large subunit rRNA gene suggest that this strain is conspecific with strains NYNU 14639 isolated from rotten wood collected in Funiu Mountain, Henan province and ES13S05 from soil collected in Nantou County, Taiwan. The CGMCC 2.6937T group is most closely related to Saturnispora dispora and Saturnispora zaruensis. However, strain CGMCC 2.6937T differs from S. dispora by 17 (3.2 %, 13 substitutions and four gaps) and 77 (18.8 %, 52 substitutions and 25 gaps) mismatches, and from S. zaruensis by 15 (2.9 %, 12 substitutions and three gaps) and 64 (15.6 %, 44 substitutions and 20 gaps) mismatches, in the D1/D2 domain and ITS region, respectively. The results suggest that the CGMCC 2.6937T group represents an undescribed species in the genus Saturnispora, for which the name Saturnispora sinensis sp. nov. is proposed. The holotype strain is CGMCC 2.6937T.

Microbial communities and their correlation with flavor compound formation during the mechanized production of light-flavor Baijiu.

Light-flavor Baijiu fermentation is a typical spontaneous solid-state fermentation process fueled by a variety of microorganisms. Mechanized processes have been increasingly employed in Baijiu production to replace traditional manual operation processes, however, the microbiological and physicochemical dynamics in mechanized processes remain largely unknown. Here, we investigated the microbial community succession and flavor compound formation during a whole mechanized fermentation process of light-flavor Baijiu using the conventional dilution plating method, PacBio single-molecule real-time (SMRT) sequencing and headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry. The results showed that largely different fungal and bacterial communities were involved in the soaking and fermentation processes. A clear succession from Pantoea agglomerans to Bacillus (B.) smithii and B. coagulans in dominant bacterial species and from Cladosporium exasperatum to Saccharomyces cerevisiae and Lichtheimia ramosa in dominant fungal species occurred in the soaking processes. In the fermentation process, the most dominant bacterial species was shifted from Pantoea agglomerans to Lactobacillus (La.) acetotolerans and the most dominant fungal species were shifted from Lichtheimia ramose and Rhizopus arrhizus to Saccharomyces cerevisiae. The bacterial and fungal species positively associated with acidity and the formation of ethanol and different flavor compounds were specified. The microbial species exhibited strong co-occurrence or co-exclusion relationships were also identified. The results are helpful for the improvement of mechanized fermentation process of light-flavor Baijiu production.

Microbial Community Affects Daqu Quality and the Production of Ethanol and Flavor Compounds in Baijiu Fermentation.

Daqu is a traditional starter for Baijiu fermentation and is produced by spontaneous fermentation of ground and moistened barley or wheat. The quality of Daqu is traditionally evaluated based on physicochemical and subjective sensory parameters without microbiological analysis. Here, we compared the physicochemical characteristics of qualified (QD) and inferior (ID) Daqu, their microbial communities based on plate counting and PacBio SMRT sequencing of rRNA gene libraries, and their impacts on Baijiu fermentation. The results showed that the glucoamylase and α-amylase activities of QD were significantly higher than those of ID. The counts of yeasts and relative abundances of functional microbes, especially the amylolytic bacterium Bacillus licheniformis and fungi Saccharomycopsis fibuligera and Lichtheimia ramosa, were significantly higher in QD than in ID. The laboratory-scale Baijiu fermentation tests showed that the relative abundances of the amylolytic microbes were higher in the QD than the ID fermentation set, resulting in more efficient fermentation, as indicated by more weight loss and higher moisture content in the former. Consequently, more glycerol, acetic acid, ethanol, and other volatile compounds were produced in the QD than in the ID fermentation set. The results suggest that Daqu quality is determined by, and can be evaluated based on, its microbial community.

Quantitative Detection of In Vivo Aggregation Degree for Enhanced M2 Macrophage MR Imaging.

In situ self-assembly in vivo can be used in the enhanced diagnosis and therapy of major diseases such as cancer and bacterial infections on the basis of an assembly/aggregation-induced-retention (AIR) effect. However, the aggregation degree (αagg) is a significant parameter for determining the delivery efficiency to lesions in a complex physiological environment and a real-time quantitative calculation of the aggregation degree in vivo is still a great challenge. Here, we developed a magnetic resonance imaging (MRI) method for sensitive and quantitative calculation of αagg with a detection limit of 10-4 M and a bioactivated in vivo assembly (BIVA) magnetic resonance (MR) probe was optimized for enhanced T1-weighted MR imaging of M2 macrophages in tumors. Our MRI quantitative calculation method had a high fitting degree (R2 = 0.987) with the gold standard fluorescence (FL) method. On the basis of the BIVA mechanism of CD206 active targeting and cathepsin B specific tailoring to induce an in situ nanofiber assembly, our optimized BIVA probe exhibited a high intracellular aggregation degree of over 70% and a high in vivo αagg value of over 55%. Finally, the aggregation-enhanced T1 MR signal and the AIR effect both contributed to enhanced T1-weighted MR imaging of M2 macrophages in triple-negative breast cancer. We believe that our αagg real-time quantitative calculation method of MRI will help to further screen and optimize the in vivo enhanced imaging and treatment of the BIVA drug.