scholarly journals HyperEx: A Tool to Extract Hypervariable Regions from 16S rRNA Sequencing Data

2021 ◽  
Author(s):  
Anicet Ebou ◽  
Dominique Koua ◽  
Adolphe Zeze
Keyword(s):  
16S Rrna ◽  
Ribosomal Rna ◽  
High Throughput Sequencing ◽  
16S Ribosomal Rna ◽  
16S Rrna Sequencing ◽  
Taxonomic Resolution ◽  
Sequencing Data ◽  
Pairwise Sequence Alignment ◽  
Hypervariable Regions ◽  
Rrna Sequencing

The 16S ribosomal RNA gene is one of the most studied genes in biology. This 16S ribosomal RNA importance is due to its wide application in phylogenetics and taxonomic elucidation of bacteria and archaea. Indeed, 16S ribosomal RNA is present in almost all bacteria and archaea and has, among many other useful characteristics, a low mutation rate. The 16S ribosomal RNA is composed of nine hypervariable regions which are commonly targeted by high throughput sequencing technologies in identification or community studies like metabarcoding studies. Unfortunately, the hypervariable regions do not have the same taxonomic resolution among all bacteria taxa. This requires a preliminary in silico analysis to determine the best hypervariable regions to target in a particular study. Nevertheless, to the best of our knowledge, no automated primer-based open-source tool exists to extract hypervariable regions from complete or near-complete 16S rRNA sequencing data. Here we present HyperEx which efficiently extracts the hypervariable region of interest based on embedded primers or user-given primers. HyperEx implements the Myers algorithm for the exact pairwise sequence alignment. HyperEx is freely available under the MIT license as an operating system independent Rust command-line tool at https://github.com/Ebedthan/hyperex and https://crates.io.

scholarly journals Excessive Unbalanced Meat Consumption in the First Year of Life Increases Asthma Risk in the PASTURE and LUKAS2 Birth Cohorts

2021 ◽  
Vol 12 ◽  
Author(s):  
Alexander J. Hose ◽  
Giulia Pagani ◽  
Anne M. Karvonen ◽  
Pirkka V. Kirjavainen ◽  
Caroline Roduit ◽  
...  
Keyword(s):  
16S Rrna ◽  
Meat Consumption ◽  
16S Rrna Sequencing ◽  
Atopic Asthma ◽  
First Year ◽  
Sequencing Data ◽  
Food Items ◽  
Asthma Risk ◽  
Rrna Sequencing ◽  
First Year Of Life

A higher diversity of food items introduced in the first year of life has been inversely related to subsequent development of asthma. In the current analysis, we applied latent class analysis (LCA) to systematically assess feeding patterns and to relate them to asthma risk at school age. PASTURE (N=1133) and LUKAS2 (N=228) are prospective birth cohort studies designed to evaluate protective and risk factors for atopic diseases, including dietary patterns. Feeding practices were reported by parents in monthly diaries between the 4th and 12th month of life. For 17 common food items parents indicated frequency of feeding during the last 4 weeks in 4 categories. The resulting 153 ordinal variables were entered in a LCA. The intestinal microbiome was assessed at the age of 12 months by 16S rRNA sequencing. Data on feeding practice with at least one reported time point was available in 1042 of the 1133 recruited children. Best LCA model fit was achieved by the 4-class solution. One class showed an elevated risk of asthma at age 6 as compared to the other classes (adjusted odds ratio (aOR): 8.47, 95% CI 2.52–28.56, p = 0.001) and was characterized by daily meat consumption and rare consumption of milk and yoghurt. A refined LCA restricted to meat, milk, and yoghurt confirmed the asthma risk effect of a particular class in PASTURE and independently in LUKAS2, which we thus termed unbalanced meat consumption (UMC). The effect of UMC was particularly strong for non-atopic asthma and asthma irrespectively of early bronchitis (aOR: 17.0, 95% CI 5.2–56.1, p < 0.001). UMC fostered growth of iron scavenging bacteria such as Acinetobacter (aOR: 1.28, 95% CI 1.00-1.63, p = 0.048), which was also related to asthma (aOR: 1.55, 95% CI 1.18-2.03, p = 0.001). When reconstructing bacterial metabolic pathways from 16S rRNA sequencing data, biosynthesis of siderophore group nonribosomal peptides emerged as top hit (aOR: 1.58, 95% CI 1.13-2.19, p = 0.007). By a data-driven approach we found a pattern of overly meat consumption at the expense of other protein sources to confer risk of asthma. Microbiome analysis of fecal samples pointed towards overgrowth of iron-dependent bacteria and bacterial iron metabolism as a potential explanation.

Accurate Five-category Classification for Colorectal Cancer Using Gut Microbiome 16S rRNA Sequencing

2021 ◽  
Author(s):  
Liying Zhang ◽  
Jiaqi Zhu ◽  
Qiutao Ding ◽  
Yanqi Huang ◽  
Hongbo Zhang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
16S Rrna ◽  
Gut Microbiome ◽  
Large Scale ◽  
Operational Taxonomic Unit ◽  
16S Rrna Sequencing ◽  
Screening Tests ◽  
Advanced Adenoma ◽  
Sequencing Data ◽  
Rrna Sequencing

Abstract The association between the gut microbiome and the five stages of colorectal cancer (CRC) (healthy, polyposis, nonadvanced adenoma, advanced adenoma, and cancer) remains unclear. We performed 16S rRNA sequencing of the V3-V4 amplicon from 999 samples from subjects at various stages of CRC development and constructed an accurate predictive random forest model for CRC development. In the testing set, our five-category CRC prediction classifier had accuracies of 0.84 and 0.74 using the relative operational taxonomic unit (OTU) abundances and relative genus abundances, respectively. Specifically, the OTU-based classifier had a sensitivity of 0.97 and specificity of 0.97 for CRC samples, and the genus-based classifier had a sensitivity of 0.97 and specificity of 0.95 for CRC samples. Meanwhile, the gut microbiota was found to differ at all stages of CRC development. The differential abundances of closely related bacteria were used to accurately classify the five stages of CRC development. Additionally, both unannotated and annotated OTUs played important roles in classifier modelling. Our work not only provides valuable 16S rRNA sequencing data from patients and healthy individuals on a large scale but also identifies reproducible gut microbiome biomarkers for CRC staging and highlights their potential applications as noninvasive microbiome biomarkers for diagnosis and as predictive CRC screening tests.

scholarly journals Characterization of bacterial communities in wastewater with enhanced taxonomic resolution by full-length 16S rRNA sequencing

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Daniela Numberger ◽  
Lars Ganzert ◽  
Luca Zoccarato ◽  
Kristin Mühldorfer ◽  
Sascha Sauer ◽  
...  
Keyword(s):  
16S Rrna ◽  
Bacterial Communities ◽  
Full Length ◽  
16S Rrna Sequencing ◽  
Taxonomic Resolution ◽  
Rrna Sequencing

scholarly journals Characterization of Bacterial Community Dynamics of the Human Mouth Throughout Decomposition via Metagenomic, Metatranscriptomic, and Culturing Techniques

2021 ◽  
Vol 12 ◽  
Author(s):  
Emily C. Ashe ◽  
André M. Comeau ◽  
Katie Zejdlik ◽  
Seán P. O’Connell
Keyword(s):  
16S Rrna ◽  
Community Dynamics ◽  
Current Knowledge ◽  
16S Rrna Gene Sequencing ◽  
Oral Microbiome ◽  
16S Rrna Sequencing ◽  
Rrna Gene ◽  
Sequencing Data ◽  
Bacterial Community Dynamics ◽  
Rrna Sequencing

The postmortem microbiome has recently moved to the forefront of forensic research, and many studies have focused on the idea that predictable fluctuations in decomposer communities could be used as a “microbial clock” to determine time of death. Commonly, the oral microbiome has been evaluated using 16S rRNA gene sequencing to assess the changes in community composition throughout decomposition. We sampled the hard palates of three human donors over time to identify the prominent members of the microbiome. This study combined 16S rRNA sequencing with whole metagenomic (MetaG) and metatranscriptomic (MetaT) sequencing and culturing methodologies in an attempt to broaden current knowledge about how these postmortem microbiota change and might function throughout decomposition. In all four methods, Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes were the dominant phyla, but their distributions were insufficient in separating samples based on decomposition stage or time or by donor. Better resolution was observed at the level of genus, with fresher samples from decomposition clustering away from others via principal components analysis (PCA) of the sequencing data. Key genera in driving these trends included Rothia; Lysinibacillus, Lactobacillus, Staphylococcus, and other Firmicutes; and yeasts including Candida and Yarrowia. The majority of cultures (89%) matched to sequences obtained from at least one of the sequencing methods, while 11 cultures were found in the same samples using all three methods. These included Acinetobacter gerneri, Comamonas terrigena, Morganella morganii, Proteus vulgaris, Pseudomonas koreensis, Pseudomonas moraviensis, Raoutella terrigena, Stenotrophomonas maltophilia, Bacillus cereus, Kurthia zopfii, and Lactobacillus paracasei. MetaG and MetaT data also revealed many novel insects as likely visitors to the donors in this study, opening the door to investigating them as potential vectors of microorganisms during decomposition. The presence of cultures at specific time points in decomposition, including samples for which we have MetaT data, will yield future studies tying specific taxa to metabolic pathways involved in decomposition. Overall, we have shown that our 16S rRNA sequencing results from the human hard palate are consistent with other studies and have expanded on the range of taxa shown to be associated with human decomposition, including eukaryotes, based on additional sequencing technologies.

Haemophilus parainfluenzaeInfective Endocarditis Diagnosed by Direct 16S rRNA Sequencing of Vegetation

2012 ◽  
Vol 2 (2) ◽  
pp. 111
Author(s):  
Sung-Hee Oh ◽  
Min-Chul Cho ◽  
Jae-Wook Kim ◽  
Dongheui An ◽  
Mun-Hui Jeong ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Sequencing ◽  
Rrna Sequencing

Full-length versus short amplicon 16S rRNA sequencing: benefits, drawbacks and risks

2020 ◽  
Author(s):  
Isabel Abellan-Schneyder ◽  
Andrea Janina Bayer ◽  
Sandra Reitmeier ◽  
Klaus Neuhaus
Keyword(s):  
16S Rrna ◽  
Full Length ◽  
16S Rrna Sequencing ◽  
Rrna Sequencing

Full-length versus short amplicon 16S rRNA sequencing: benefits, drawbacks and risks

2020 ◽  
Author(s):  
Andrea Janina Bayer ◽  
Sandra Reitmeier ◽  
Klaus Neuhaus ◽  
Isabel Abellan-Schneyder
Keyword(s):  
16S Rrna ◽  
Full Length ◽  
16S Rrna Sequencing ◽  
Rrna Sequencing

scholarly journals Phenotypic and phylogenetic characterization of Lactobacillus species isolated from traditional Lighvan cheese

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Haleh Forouhandeh ◽  
Sepideh Zununi Vahed ◽  
Hossein Ahangari ◽  
Vahideh Tarhriz ◽  
Mohammad Saeid Hejazi
Keyword(s):  
16S Rrna ◽  
Random Amplified Polymorphic Dna ◽  
Bacterial Species ◽  
16S Rrna Sequencing ◽  
Lactobacillus Species ◽  
Culture Methods ◽  
Phylogenetic Characterization ◽  
Rrna Sequencing ◽  
Specific Culture ◽  
Lighvan Cheese

Abstract Lighvan cheese (Lighvan panir) is among the most famous traditional cheese in Iran for its desired aroma and flavor. Undoubtedly, the lactic acid bacteria especially the genus Lactobacillus are the critical factors in developing the aroma, flavor, and texture in Lighvan cheese. In this study, the Lactobacillus population of the main Lighvan cheese was investigated. The Lactobacillus of the main Lighvan cheese was isolated using specific culture methods according to previously published Guidelines. Then, the phylogenetic features were investigated and the phenotypic characteristics were examined using specific culture methods. Twenty-eight Gram-positive bacterial species were identified belonged to the genus Lactobacillus. According to the same sequences as each other, three groups (A, B, and C) of isolates were categorized with a high degree of similarity to L. fermentum (100%) and L. casei group (L. casei, L. paracasei, and L. rhamnosus) (99.0 to 100%). Random amplified polymorphic DNA (RAPD) fingerprint analysis manifested the presence of three clusters that were dominant in traditional Lighvan cheese. Cluster І was divided into 4 sub-clusters. By the result of carbohydrate fermentation pattern and 16S rRNA sequencing, isolates were identified as L. rhamnosus. The isolates in clusters II and III represented L. paracasei and L. fermentum, respectively as they were identified by 16S rRNA sequencing and fermented carbohydrate patterns. Our result indicated that the specific aroma and flavor of traditional Lighvan cheese can be related to its Lactobacillus population including L. fermentum, L. casei, L. paracasei, and L. rhamnosus. Graphical abstract

scholarly journals Coupled DNA-labeling and sequencing approach enables the detection of viable-but-non-culturable Vibrio spp. in irrigation water sources in the Chesapeake Bay watershed

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Leena Malayil ◽  
Suhana Chattopadhyay ◽  
Emmanuel F. Mongodin ◽  
Amy R. Sapkota
Keyword(s):  
16S Rrna ◽  
Irrigation Water ◽  
Brackish Water ◽  
Water Sources ◽  
16S Rrna Sequencing ◽  
Vbnc State ◽  
Recycled Water ◽  
Dna Labeling ◽  
Rrna Sequencing ◽  
Brdu Labeling

AbstractNontraditional irrigation water sources (e.g., recycled water, brackish water) may harbor human pathogens, including Vibrio spp., that could be present in a viable-but-nonculturable (VBNC) state, stymieing current culture-based detection methods. To overcome this challenge, we coupled 5-bromo-2′-deoxyuridine (BrdU) labeling, enrichment techniques, and 16S rRNA sequencing to identify metabolically-active Vibrio spp. in nontraditional irrigation water (recycled water, pond water, non-tidal freshwater, and tidal brackish water). Our coupled BrdU-labeling and sequencing approach revealed the presence of metabolically-active Vibrio spp. at all sampling sites. Whereas, the culture-based method only detected vibrios at three of the four sites. We observed the presence of V. cholerae, V. vulnificus, and V. parahaemolyticus using both methods, while V. aesturianus and V. shilonii were detected only through our labeling/sequencing approach. Multiple other pathogens of concern to human health were also identified through our labeling/sequencing approach including P. shigelloides, B. cereus and E. cloacae. Most importantly, 16S rRNA sequencing of BrdU-labeled samples resulted in Vibrio spp. detection even when our culture-based methods resulted in negative detection. This suggests that our novel approach can effectively detect metabolically-active Vibrio spp. that may have been present in a VBNC state, refining our understanding of the prevalence of vibrios in nontraditional irrigation waters.

Sign in / Sign up

Export Citation Format

Share Document