Rolling forms the diversities of small molecular nonvolatile metabolite profile and consequently shapes the bacterial community structure for Keemun black tea.

The detailed dynamics of small molecular nonvolatile chemical and bacterial diversities, as well as their relationship are still unclear in the manufacturing process of Keemun black tea (KMBT). Herein, mass spectrometry-based untargeted metabolomics, Feature-based Molecular Networking (FBMN) and bacterial DNA amplicon sequencing were used to investigate the dense temporal samples of the manufacturing process. For the first time, we reveal that the pyrogallol-type catechins are oxidized asynchronously before catechol-type catechins during the black tea processing. Rolling is the key procedure for forming the small molecular nonvolatile metabolite profile (SMNMetProf), increasing the metabolite richness, and then shaping the bacterial community structure in the KMBT manufacturing process, which decreases both molecular weight and molecular polarity of the small molecular nonvolatile metabolites. The SMNMetProf of black tea is formed by the endogenous enzymatic oxidation of tea leaves, rather than bacterial fermentation.

Dynamic Changes in the Microbial Community and Metabolite Profile during the Pile Fermentation Process of Fuzhuan Brick Tea.

The pile fermentation process of Fuzhuan brick tea is unique in that it involves preheating without the use of starter cultures. The detailed metabolite changes and their drivers during this procedure are not known. Characterizing these unknown changes that occur in the metabolites and microbes during pile fermentation of Fuzhuan brick tea is important for industrial modernization of this traditional fermented food. Using microbial DNA amplicon sequencing, mass spectrometry-based untargeted metabolomics, and feature-based molecular networking, we herein reveal that significant changes in the microbial community occur before changes in the metabolite profile. These changes were characterized by a decrease in Klebsiella and Aspergillus, alongside an increase in Bacillus and Eurotium. The decrease in lysophosphatidylcholines, unsaturated fatty acids, and some astringent flavan-3-ols and bitter amino acids, as well as the increase in some less astringent flavan-3-ols and sweet or umami amino acids, contributed importantly to the overall changes observed in the metabolite profile. The majority of these changes was caused by bacterial metabolism and the corresponding heat generated by it.

Microbial and Nonvolatile Chemical Diversities of Chinese Dark Teas Are Differed by Latitude and Pile Fermentation.

Understanding the microbial and chemical diversities, as well as what affects these diversities, is important for modern manufacturing of traditional fermented foods. In this work, Chinese dark teas (CDTs) that are traditional microbial fermented beverages with relatively high sample diversity were collected. Microbial DNA amplicon sequencing and mass spectrometry-based untargeted metabolomics show that the CDT microbial ß diversity, as well as the nonvolatile chemical α and ß diversities, is determined by the primary impact factors of geography and manufacturing procedures, in particular, latitude and pile fermentation after blending. A large number of metabolites sharing between CDTs and fungi were discovered by Feature-based Molecular Networking (FBMN) on the Global Natural Products Social Molecular Networking (GNPS) web platform. These molecules, such as prenylated cyclic dipeptides and B-vitamins, are functionally important for nutrition, biofunctions, and flavor. Molecular networking has revealed patterns in metabolite profiles on a chemical family level in addition to individual structures.

Feature-Based Molecular Networking Analysis of the Metabolites Produced by In Vitro Solid-State Fermentation Reveals Pathways for the Bioconversion of Epigallocatechin Gallate.

Dark teas are prepared by a microbial fermentation process. Flavan-3-ol B-ring fission analogues (FBRFAs) are some of the key bioactive constituents that characterize dark teas. The precursors and the synthetic mechanism involved in the formation of FBRFAs are not known. Using a unique solid-state fermentation system with ß-cyclodextrin inclusion complexation as well as targeted chromatographic isolation, spectroscopic identification, and Feature-based Molecular Networking on the Global Natural Products Social Molecular Networking web platform, we reveal that dihydromyricetin and the FBRFAs, including teadenol A and fuzhuanin A, are derived from epigallocatechin gallate upon exposure to fungal strains isolated from Fuzhuan brick tea. In particular, the strains from subphylum Pezizomycotina were key drivers for these B-/C-ring oxidation transformations. These are the same transformations seen during the fermentation process of dark teas. These discoveries set the stage to enrich dark teas and other food products for these health-promoting constituents.

A new anti-proliferative acylated flavonol glycoside from Fuzhuan brick-tea.

Fuzhuan brick-tea (FBT) is unique for a fungal fermentation stage in its manufacture process and is classified in dark tea. A new acylated flavonol glycoside, kaempferol 3-O-[E-p-coumaroyl-(→2)][α-l-arabinopyranosyl-(1→3)][α-l-rhamnopyranosyl(1→6)]-ß-d-glucopyranoside, which was trivially named as camellikaempferoside A (1), was isolated from FBT along with camelliquercetiside C (2). Their structures were unambiguously elucidated by combination of spectroscopic and chemical methods. Compound 1 showed anti-proliferative activity against MCF-7 and MDA-MB-231 cells with IC50 values of 7.83 and 19.16 µM, respectively.

Filled pause refinement based on the pronunciation probability for lecture speech.

Nowadays, although automatic speech recognition has become quite proficient in recognizing or transcribing well-prepared fluent speech, the transcription of speech that contains many disfluencies remains problematic, such as spontaneous conversational and lecture speech. Filled pauses (FPs) are the most frequently occurring disfluencies in this type of speech. Most recent studies have shown that FPs are widely believed to increase the error rates for state-of-the-art speech transcription, primarily because most FPs are not well annotated or provided in training data transcriptions and because of the similarities in acoustic characteristics between FPs and some common non-content words. To enhance the speech transcription system, we propose a new automatic refinement approach to detect FPs in British English lecture speech transcription. This approach combines the pronunciation probabilities for each word in the dictionary and acoustic language model scores for FP refinement through a modified speech recognition forced-alignment framework. We evaluate the proposed approach on the Reith Lectures speech transcription task, in which only imperfect training transcriptions are available. Successful results are achieved for both the development and evaluation datasets. Acoustic models trained on different styles of speech genres have been investigated with respect to FP refinement. To further validate the effectiveness of the proposed approach, speech transcription performance has also been examined using systems built on training data transcriptions with and without FP refinement.