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Assessing the Microbial Communities in Four Different Daqus by Using PCR-DGGE, PLFA, and Biolog Analyses Cover

Assessing the Microbial Communities in Four Different Daqus by Using PCR-DGGE, PLFA, and Biolog Analyses

Open Access
|Feb 2020

Figures & Tables

Fig. 1.

PCR-DGGE profiles (A) and clustering analysis (B) of the bacterial communities in four typical Daqu samples. (a-m represent the specific bands excised; 1–4 represent Wuling Daqu, Baisha Daqu, Deshan Daqu, and Niulanshan Daqu, respectively.
PCR-DGGE profiles (A) and clustering analysis (B) of the bacterial communities in four typical Daqu samples. (a-m represent the specific bands excised; 1–4 represent Wuling Daqu, Baisha Daqu, Deshan Daqu, and Niulanshan Daqu, respectively.

Fig. 2.

Total biomass, bacterial biomass, fungi biomass (A) and the ratio of fungi biomass to bacteria biomass (B) of Daqu samples.
Total biomass, bacterial biomass, fungi biomass (A) and the ratio of fungi biomass to bacteria biomass (B) of Daqu samples.

Fig. 3.

Principal component analysis (PCA) showing variations in the PLFA pattern in different types of Daqu (A); clustering analysis (B) of the four Daqus on PLFAs content.
Principal component analysis (PCA) showing variations in the PLFA pattern in different types of Daqu (A); clustering analysis (B) of the four Daqus on PLFAs content.

Fig. 4.

The AWCD of five types of carbon sources in four Daqus communities, including all carbon sources (A), monosaccharides and their derivatives (B), disaccharides and polysaccharides (C), amino acid substrate and its derivatives (D), fatty acids and lipids (E), and metabolites and secondary metabolites (F).
The AWCD of five types of carbon sources in four Daqus communities, including all carbon sources (A), monosaccharides and their derivatives (B), disaccharides and polysaccharides (C), amino acid substrate and its derivatives (D), fatty acids and lipids (E), and metabolites and secondary metabolites (F).

Fig. 5.

Principal component analysis (A) and clustering analysis (B) based carbon source utilization patterns of microbial communities.
Principal component analysis (A) and clustering analysis (B) based carbon source utilization patterns of microbial communities.

Summary of the identification of bands in Fig_ 1_

Band No. a Related GenBank sequenceClosest relatives (accession no.)Identity (%) b
aMN857671Uncultured bacterium (AB441615.1)100
bMN857663 Weissella confuse (GU049413.1)99
cMN857670 Pediococcus pentosaceus (AB481102.1)100
dMN857669 Lactobacillus sanfranciscensis (EU350220.1)99
eMN857662Uncultured Lactobacillus sp. (FJ982856.1)100
fMN857666Uncultured bacterium (AB441567.1)100
g MN857665 Pediococcus acidilactici (FJ751795.1)99
hMN857667 Bacillus thermoamylovorans (GU067470.1)99
iMN857672Uncultured bacterium (FJ235654.1)100
jMN857673Uncultured bacterium (GQ076030.1)96
kMN857664Uncultured bacterium (GQ505035.1)100
lMN857661Uncultured Lactobacillus sp. (GQ999780.1)98
mMN857668 Thermoactinomyces sanguinis (AJ251778.1)95

The concentration of the PLFAs in different Daqu samples_

PLFA (nmol/g dry matter)Wuling DaquBaisha DaquDeshan DaquNiulanshan Daqu
A11:0000105.36
A13:0327.32297.50153.9599.80
15:00294.13475.82189.3124.35
Me14:0133.5300217.31
I14:0117.820054.73
I15:000034.62
A15:0102.960044.73
16:1W9Z121.91083.490
16:004.15194.314.005.45
I16:095.05220.5900
A16:0113.83166.872.86142.79
17:00112.01250.3461.090
Cy17:00076.790
18:3W6,9,12t216.8101.580
18:3W3,6,9zzz0066.790
18:2W6.9tt1.763.0302.66
18:2W6.9zz234.2030.460186.88
18:2W6.8zz00051.43
18:2W7.10tt000315.07
18:2W5.8tt248.8803.180
18:1W9t5.898.9714.187.36
18:1W10t45.45000
18:1W9z00068.80
18:0024.9268.6014.5526.90
Cy18:0149.68000
20:00152.12000

Samples of four typical Daqus of Chinese spirits_

NameFlavour typeHighest temperature inside the Daqu pile (°C)Region (city and geographic coordinates)
WulingSauce-flavour65Changde, Hunan (29°05′N, 111°39′E)
BaishaSauce- and strong-flavour60Changsha, Changsha (28°11′N, 112°58′E)
DeshanStrong-flavour55Changde, Hunan (29°05′N, 111°39′E)
NiulanshanLight-flavour50Beijing (39°56′N, 116°20′E)

Comparison of the carbon utilization of different samples_

WellCarbon SourcesWuling DaquBaisha DaquDeshan DaquNiulanshan Daqu
A2 β-Methyl-D-glucoside0.55900.0011.445
A3D-Galactonic acid-γ-Lactone0.5260.0261.1991.028
A4L-Arginine0.3830.0190.3160.063
B1Pyruvic acid Methyl ester0.75900.3830.444
B2D-Xylose1.1150.0250.0671.500
B3D-Galacturonic acid1.48400.7541.391
B4L-Asparagine0.1460.0330.0350.919
C1Tween 400.8720.3560.3990.399
C2i-Erythritol0.1130.0020.210.263
C32-Hydroxy benzoic acid0.00400.1760
C4L-Phenylalanine0.0850.1210.0990.132
D1Tween 800.5580.2510.81.037
D2D-Mannitol0.8450.0080.3991.789
D34-Hydroxy benzoic acid0.0190.0200.3020.076
D4L-Serine1.1290.0310.0490.626
E1 α-Cyclodextrin0.0010.04800.007
E2N-Acetyl-D-glucosamine0.9270.1710.1461.844
E3 γ-Hydroxybutyric acid0.1180.1020.1390.042
E4L-Threonine0.031000.019667
F1Glycogen0.19200.1430.163
F2D-Glucosaminic acid0.29800.9670.023
F3Itaconic acid00.04400
F4Glucose-L-glutamic acid0.0210.00900.132
G1D-Cellobiose G20.9200.1220.4221.538
G2Glucose-1-phosphate0.1090.03301.255
G3a-Ketobutyric acid000.0040
G4Phenylethylamine0.00100.5340
H1a-D-Lactose0.6120.0130.1891.404
H2D,L-a-Glycerol phosphate0.1620.0090.2430.275
H3D-Malic acid0.3490.0090.4310.944
H4Putrescine0.2930.0530.1330.639
DOI: https://doi.org/10.33073/pjm-2020-004 | Journal eISSN: 2544-4646 | Journal ISSN: 1733-1331
Language: English
Page range: 27 - 37
Submitted on: Oct 10, 2019
Accepted on: Jan 7, 2020
Published on: Feb 18, 2020
Published by: Polish Society of Microbiologists
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2020 YUXI LING, WENYING LI, TONG TONG, ZUMING LI, QIAN LI, ZHIHUI BAI, GUIJUN WANG, JIAHAO CHEN, YUGUANG WANG, published by Polish Society of Microbiologists
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.