scholarly journals Analysis of the Bacterial Communities in Two Liquors of Soy Sauce Aroma as Revealed by High-Throughput Sequencing of the 16S rRNA V4 Hypervariable Region

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Jing Tang ◽  
Xiaoxin Tang ◽  
Ming Tang ◽  
Ximin Zhang ◽  
Xiaorong Xu ◽  
...  

Chinese liquor is one of the world’s oldest distilled alcoholic beverages and an important commercial fermented product in China. The Chinese liquor fermentation process has three stages: making Daqu (the starter), stacking fermentation on the ground, and liquor fermentation in pits. We investigated the bacterial diversity of Maotai and Guotai Daqu and liquor fermentation using high-throughput sequencing of the V4 hypervariable region of the 16S rRNA gene. A total of 70,297 sequences were obtained from the Daqu samples and clustered into 17 phyla. The composition of the bacterial communities in the Daqu from these two soy sauce aroma-style Chinese liquors was the same, although some bacterial species changed in abundance. Between the Daqu and liquor fermentation samples, 12 bacterial phyla increased. The abundance of Lactobacillus and Pseudomonas increased in the liquor fermentation. This study has used high-throughput sequencing to provide new insights into the bacterial composition of the Chinese liquor Daqu and fermentation. Similarities in the distribution of bacteria in the soy sauce aroma-style Chinese liquors Daqu suggest that the abundance of bacteria might be generally concerned to other liquor.

2013 ◽  
Vol 80 (2) ◽  
pp. 478-485 ◽  
Author(s):  
Yue Tang ◽  
Anthony Underwood ◽  
Adriana Gielbert ◽  
Martin J. Woodward ◽  
Liljana Petrovska

ABSTRACTThe animal gastrointestinal tract houses a large microbial community, the gut microbiota, that confers many benefits to its host, such as protection from pathogens and provision of essential metabolites. Metagenomic approaches have defined the chicken fecal microbiota in other studies, but here, we wished to assess the correlation between the metagenome and the bacterial proteome in order to better understand the healthy chicken gut microbiota. Here, we performed high-throughput sequencing of 16S rRNA gene amplicons and metaproteomics analysis of fecal samples to determine microbial gut composition and protein expression. 16 rRNA gene sequencing analysis identifiedClostridiales,Bacteroidaceae, andLactobacillaceaespecies as the most abundant species in the gut. For metaproteomics analysis, peptides were generated by using the Fasp method and subsequently fractionated by strong anion exchanges. Metaproteomics analysis identified 3,673 proteins. Among the most frequently identified proteins, 380 proteins belonged toLactobacillusspp., 155 belonged toClostridiumspp., and 66 belonged toStreptococcusspp. The most frequently identified proteins were heat shock chaperones, including 349 GroEL proteins, from many bacterial species, whereas the most abundant enzymes were pyruvate kinases, as judged by the number of peptides identified per protein (spectral counting). Gene ontology and KEGG pathway analyses revealed the functions and locations of the identified proteins. The findings of both metaproteomics and 16S rRNA sequencing analyses are discussed.


2021 ◽  
Author(s):  
Artur Trzebny ◽  
Anna Slodkowicz-Kowalska ◽  
Johanna Björkroth ◽  
Miroslawa Dabert

AbstractThe animal gut microbiota consist of many different microorganisms, mainly bacteria, but archaea, fungi, protozoans, and viruses may also be present. This complex and dynamic community of microorganisms may change during parasitic infection. In the present study, we investigated the effect of the presence of microsporidians on the composition of the mosquito gut microbiota and linked some microbiome taxa and functionalities to infections caused by these parasites. We characterised bacterial communities of 188 mosquito females, of which 108 were positive for microsporidian DNA. To assess how bacterial communities change during microsporidian infection, microbiome structures were identified using 16S rRNA microbial profiling. In total, we identified 46 families and four higher taxa, of which Comamonadaceae, Enterobacteriaceae, Flavobacteriaceae and Pseudomonadaceae were the most abundant mosquito-associated bacterial families. Our data suggest that the mosquito gut microbial composition varies among host species. In addition, we found a correlation between the microbiome composition and the presence of microsporidians. The prediction of metagenome functional content from the 16S rRNA gene sequencing suggests that microsporidian infection is characterised by some bacterial species capable of specific metabolic functions, especially the biosynthesis of ansamycins and vancomycin antibiotics and the pentose phosphate pathway. Moreover, we detected a positive correlation between the presence of microsporidian DNA and bacteria belonging to Spiroplasmataceae and Leuconostocaceae, each represented by a single species, Spiroplasma sp. PL03 and Weissella cf. viridescens, respectively. Additionally, W. cf. viridescens was observed only in microsporidian-infected mosquitoes. More extensive research, including intensive and varied host sampling, as well as determination of metabolic activities based on quantitative methods, should be carried out to confirm our results.


2019 ◽  
Author(s):  
Creciana Maria Endres ◽  
Ícaro Maia Santos de Castro ◽  
Laura Delpino Trevisol ◽  
Michele Bertoni Mann ◽  
Ana Paula Muterle Varela ◽  
...  

AbstractThe production of sheep’s milk cheese has grown in recent years since it is a high value-added product with excellent properties. As such, it is necessary to provide data on the microbiota and organoleptic characteristics of this product, as well as the influence of these microorganisms on public health. Thus, the aim of the present study was to characterize the microbial community of different types of sheep cheeses using high-throughput sequencing of the 16S rRNA gene. The study was conducted with four groups of cheese: colonial, fresh, feta, and pecorino (n = 5 samples per group). The high-throughput 16S rRNA amplicon sequencing revealed 55 operational taxonomic units in the 20 samples, representing 9 genera of the two bacterial phyla Firmicutes and Proteobacteria. The predominant genera in the samples were Streptococcus and Lactobacillus. When evaluating alpha diversity by the indexes of Simpson, Chao1, Shannon, and Skew no significant differences were observed between the groups. Evaluating of the beta diversity using Bray-Curtis dissimilarity, the group of colonial cheeses presented a significant difference when compared to the feta (q = 0.030) and pecorino groups (q = 0.030). Additionally, the fresh group differed from the pecorino group (q = 0.030). The unweighted Unifrac distance suggests that the colonial cheese group differed from the others. Moreover, the feta cheese group differed from the fresh group. The distance-weighted Unifrac suggests that no significance exists between the groups. According to this information, the microbiota characterization of these cheese groups was useful in demonstrating the bacterial communities belonging to each group, its effects on processing, elaboration, maturation, and public health.


2016 ◽  
Vol 82 (12) ◽  
pp. 3525-3536 ◽  
Author(s):  
Nikea Ulrich ◽  
Abigail Rosenberger ◽  
Colin Brislawn ◽  
Justin Wright ◽  
Collin Kessler ◽  
...  

ABSTRACTBacterial community composition and longitudinal fluctuations were monitored in a riverine system during and after Superstorm Sandy to better characterize inter- and intracommunity responses associated with the disturbance associated with a 100-year storm event. High-throughput sequencing of the 16S rRNA gene was used to assess microbial community structure within water samples from Muddy Creek Run, a second-order stream in Huntingdon, PA, at 12 different time points during the storm event (29 October to 3 November 2012) and under seasonally matched baseline conditions. High-throughput sequencing of the 16S rRNA gene was used to track changes in bacterial community structure and divergence during and after Superstorm Sandy. Bacterial community dynamics were correlated to measured physicochemical parameters and fecal indicator bacteria (FIB) concentrations. Bioinformatics analyses of 2.1 million 16S rRNA gene sequences revealed a significant increase in bacterial diversity in samples taken during peak discharge of the storm. Beta-diversity analyses revealed longitudinal shifts in the bacterial community structure. Successional changes were observed, in whichBetaproteobacteriaandGammaproteobacteriadecreased in 16S rRNA gene relative abundance, while the relative abundance of members of theFirmicutesincreased. Furthermore, 16S rRNA gene sequences matching pathogenic bacteria, including strains ofLegionella,Campylobacter,Arcobacter, andHelicobacter, as well as bacteria of fecal origin (e.g.,Bacteroides), exhibited an increase in abundance after peak discharge of the storm. This study revealed a significant restructuring of in-stream bacterial community structure associated with hydric dynamics of a storm event.IMPORTANCEIn order to better understand the microbial risks associated with freshwater environments during a storm event, a more comprehensive understanding of the variations in aquatic bacterial diversity is warranted. This study investigated the bacterial communities during and after Superstorm Sandy to provide fine time point resolution of dynamic changes in bacterial composition. This study adds to the current literature by revealing the variation in bacterial community structure during the course of a storm. This study employed high-throughput DNA sequencing, which generated a deep analysis of inter- and intracommunity responses during a significant storm event. This study has highlighted the utility of applying high-throughput sequencing for water quality monitoring purposes, as this approach enabled a more comprehensive investigation of the bacterial community structure. Altogether, these data suggest a drastic restructuring of the stream bacterial community during a storm event and highlight the potential of high-throughput sequencing approaches for assessing the microbiological quality of our environment.


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