Analysis of microbial diversity in Shenqu with different fermentation times by PCR-DGGE

Liu, Tengfei; Tian-zhu, Jia; Chen, Jiangning; Liu, Xiaoyu; Zhao, Minjie; Liu, Pengpeng

doi:10.1016/j.bjm.2017.01.002

Cited by 13 publications

(5 citation statements)

References 17 publications

(15 reference statements)

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“…This method can solve the phenomenon of “local optimal value” . It has been widely used in water quality evaluation, classification, short-term load charge, prediction, the consumption of natural gas and other fields. − However, there have been no reports on modeling fermentation prediction of BA based on LS-SVM. Therefore, our present study is designed to investigate an effective and rapid strategy for discriminating the fermentation time and bile species for BA based on odor.…”

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confidence: 99%

Identification of Different Bile Species and Fermentation Times of Bile Arisaema Based on an Intelligent Electronic Nose and Least Squares Support Vector Machine

et al. 2018

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Fermentation is one of the most traditionally utilized methods to process the raw materials of traditional Chinese medicine (TCM). Bile Arisaema (BA) is produced by the fermentation of the roots of Arisaema heterophyllum with bile. Fermentation time and bile species are the key factors in producing BA. The study was aimed to develop a new and rapid method for the identification of different fermentation times and bile species of BA. The polysaccharide content (PC), protease activity (PA), and amylase activity (AC) of BA were determined. The changes of PC, PA, and AC were significant indicators for the evaluation of different fermentation times. On the basis of the odor data of BA obtained by electronic nose technology (E-nose), the principal component analysis (PCA) was used to identify bile species. The results were further verified by the least squares support vector machine (LS-SVM). The trained LS-SVM was also used to predict the PC, PA, and AC of the samples to identify fermentation time. The present study indicated that E-nose combined with LS-SVM could effectively predict the PC, PA, and AC of the samples and identify the bile species and fermentation time of BA, and it was proved to be a useful strategy for quality control of fermented products of TCMs.

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confidence: 99%

Identification of Different Bile Species and Fermentation Times of Bile Arisaema Based on an Intelligent Electronic Nose and Least Squares Support Vector Machine

et al. 2018

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“…A vital challenge in CF is to determine bacterial members of the respiratory microbiota, but it mostly consisted of a small group of bacterial species, the majority of which could be readily isolated by conventional aerobic culture-based approaches ( 6 , 8 ). There are two major types of methods for evaluating microbial diversity, culture-dependent and culture-independent methods ( 9 ).…”

Section: Introductionmentioning

confidence: 99%

Comparison of culture and PCR-DGGE methods to evaluate the airways of cystic fibrosis patients and determination of their antibiotic resistance profile

Moazami Goudarzi,

Arani,

Ali

et al. 2023

IJM

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Background and Objectives: Respiratory infections are the most serious condition in cystic fibrosis (CF) patients; there- fore, a thorough comprehension of the diversity and dominant microbial species in CF airways has a crucial role in treatment. Our objective was to determine the antibiotic resistance profile of CF airways microbiota and compare culture methods and PCR-DGGE to evaluate bacterial diversity. Materials and Methods: Pharyngeal swabs from 121 CF patients were collected. The samples were then cultured, identified and antibiotic resistance testing was performed. Thirty samples were subjected to further molecular surveys. DNA contents of these samples were extracted and amplified using nested-PCR technique and their bacterial diversity was assessed by DGGE. The DGGE patterns were visualized and certain bands were excised and purified. Next, the DNA was amplified by another round of PCR and sent out for sequencing. Results: Staphylococcus aureus, Pseudomonas aeruginosa, and Klebsiella pneumoniae were the most prevalent species isolated using culture methods. S. aureus was the most common bacteria among 6 years and younger patients; while, P. aeruginosa had more prevalence among older ones. The PCR-DGGE results showed more diversity than culture methods, particularly in younger patients who exhibited more bacterial diversity than the older groups. Sequencing results unveiled the presence of certain bacterial species including Haemophilus parainfluenzae and Stenotrophomonas maltophilia which were completely missed in culture. Conclusion: Even though culture-dependent methods are cost-effective, PCR-DGGE appeared to be more efficient to de- termine bacterial diversity. PCR-DGGE detects less abundant species, though their viability could not be determined using this method.

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“…In recent years, studies on the effect of fermentation on the microecological community structure of TCM have also been reported ( Shimoyama et al, 2015 ; Huang et al, 2020 ; Qu et al, 2021 ). For example, some scholars have analyzed the microbial diversity of Shenqu at different fermentation times by PCR-DGGE ( Liu et al, 2017 ). Some scholars have also used Aspergillus spp.…”

Section: Introductionmentioning

confidence: 99%

Screening of Key Fungal Strains in the Fermentation Process of the Chinese Medicinal Preparation “Lianzhifan Solution” Based on Metabolic Profiling and High-Throughput Sequencing Technology

Xie

Yang

et al. 2021

Front. Microbiol.

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“Lianzhifan solution” (LZF) is produced by the natural fermentation of coptis root and gardenia fruit, and it is a classic prescription for external use in anorectal department. During the fermentation process, the structural evolution of microbial communities led to significant changes in the chemical profile. In this study, we first analyzed the dynamic changes of chemical components as well as the composition and succession of microbial community during the whole fermentation process of LZF, and confirmed the changes of characteristics of nine compounds during the whole fermentation process by metabolic profile. Further analysis found that there was no significant change of alkaloids in all stages of fermentation of LZF, but there were significant changes of iridoids in the middle and late stage of fermentation by deglycosylation. Genipin gentiobioside and geniposide were converted to genipin by biotransformation, showing that deglycosylation was the main event occurring in the fermentation. The community composition and abundance of species in 10 and 19days LZF fermentation broth were analyzed with high-throughput sequencing technology, and 16 dominant bacterial genera and 15 dominant fungal genera involved in the fermentation process were identified. Correlation analysis revealed that Penicillium expansum and Aspergillus niger involved in the fermentation were the dominant genera closely related to the dynamic changes of the deglycosylation of the main chemical components, and P. expansum YY-46 and A. niger YY-9 strains were obtained by the further fractionation. Then the monoculture fermentation process was evaluated, whereby we found that the deglycoside conversion rate of iridoid glycosides was greatly improved and the fermentation cycle was shortened by 3–4 times. This finding combined with equivalence evaluation of chemical component and pharmacodynamics to confirm that P. expansum YY-46 and A. niger YY-9 strains were key strains for fermentation concoction. This study established an efficient and practical screening strategy “Microfauna communities-Chemical component-Pharmacodynamic” axis for key strain, to improve the production process and formulating good manufacturing practice (GMP) work, and it is also applicable to the whole fermentation drugs industry.Graphical AbstractThe figure highly summarizes the research content of this study and shows the screening process of key strains in LZF fermentation.

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Analysis of microbial diversity in Shenqu with different fermentation times by PCR-DGGE

Cited by 13 publications

References 17 publications

Identification of Different Bile Species and Fermentation Times of Bile Arisaema Based on an Intelligent Electronic Nose and Least Squares Support Vector Machine

Identification of Different Bile Species and Fermentation Times of Bile Arisaema Based on an Intelligent Electronic Nose and Least Squares Support Vector Machine

Comparison of culture and PCR-DGGE methods to evaluate the airways of cystic fibrosis patients and determination of their antibiotic resistance profile

Screening of Key Fungal Strains in the Fermentation Process of the Chinese Medicinal Preparation “Lianzhifan Solution” Based on Metabolic Profiling and High-Throughput Sequencing Technology

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