16S rRNA gene high-throughput sequencing data mining of microbial diversity and interactions

2015 ◽  
Vol 99 (10) ◽  
pp. 4119-4129 ◽  
Author(s):  
Feng Ju ◽  
Tong Zhang
2020 ◽  
Author(s):  
Andrés Vásquez-Domínguez ◽  
Luis Jaramillo-Valverde ◽  
Kelly S. Levano ◽  
Pedro Novoa-Bellota ◽  
Marco Machaguay-Romero ◽  
...  

ABSTRACTGenetic and microbiome studies of ancient Caral-Supe civilization have not yet been published. For this reason, the objective of this work is to identify the microorganisms and possible diseases that existed in this ancient civilization using coprolites samples. To do this, two coprolites samples were analyzing through high-throughput sequencing data of 16S rRNA gene and an intergenic region (ITS).


2020 ◽  
Vol 9 (10) ◽  
Author(s):  
Wilbert Serrano ◽  
Raul M. Olaechea ◽  
Ulrike I. Tarazona

Despite the importance of the Peruvian scallop Argopecten purpuratus as a major cultivated species, information on its microbiota is limited. Here, we provide a high-throughput sequencing data analysis of 16S rRNA gene amplicons from the distal intestine of A. purpuratus. Geographical and seasonal variation of the indigenous gut microbiota is shown.


2021 ◽  
Vol 9 ◽  
Author(s):  
Olivia N. Choi ◽  
Ammon Corl ◽  
Andrew Wolfenden ◽  
Avishai Lublin ◽  
Suzanne L. Ishaq ◽  
...  

Studies in both humans and model organisms suggest that the microbiome may play a significant role in host health, including digestion and immune function. Microbiota can offer protection from exogenous pathogens through colonization resistance, but microbial dysbiosis in the gastrointestinal tract can decrease resistance and is associated with pathogenesis. Little is known about the effects of potential pathogens, such as Salmonella, on the microbiome in wildlife, which are known to play an important role in disease transmission to humans. Culturing techniques have traditionally been used to detect pathogens, but recent studies have utilized high throughput sequencing of the 16S rRNA gene to characterize host-associated microbial communities (i.e., the microbiome) and to detect specific bacteria. Building upon this work, we evaluated the utility of high throughput 16S rRNA gene sequencing for potential bacterial pathogen detection in barn swallows (Hirundo rustica) and used these data to explore relationships between potential pathogens and microbiota. To accomplish this, we first compared the detection of Salmonella spp. in swallows using 16S rRNA data with standard culture techniques. Second, we examined the prevalence of Salmonella using 16S rRNA data and examined the relationship between Salmonella-presence or -absence and individual host factors. Lastly, we evaluated host-associated bacterial diversity and community composition in Salmonella-present vs. -absent birds. Out of 108 samples, we detected Salmonella in six (5.6%) samples based on culture, 25 (23.1%) samples with unrarefied 16S rRNA gene sequencing data, and three (2.8%) samples with both techniques. We found that sex, migratory status, and weight were correlated with Salmonella presence in swallows. In addition, bacterial community composition and diversity differed between birds based on Salmonella status. This study highlights the value of 16S rRNA gene sequencing data for monitoring pathogens in wild birds and investigating the ecology of host microbe-pathogen relationships, data which are important for prediction and mitigation of disease spillover into domestic animals and humans.


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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