Journal articles on the topic '16S amplicon analysis'
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Devloo-Delva, Floriaan, Roger Huerlimann, Gladys Chua, Jordan K. Matley, Michelle R. Heupel, Colin A. Simpfendorfer, and Gregory E. Maes. "How does marker choice affect your diet analysis: comparing genetic markers and digestion levels for diet metabarcoding of tropical-reef piscivores." Marine and Freshwater Research 70, no. 1 (2019): 8. http://dx.doi.org/10.1071/mf17209.
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Tropical reefs are highly diverse ecosystems, and reliable biomonitoring, through diet metabarcoding, is needed to understand present and future trophic relationships in this changing habitat. Several studies have assessed the reliability and effectiveness of single molecular markers; however, a cross-marker validation has rarely been performed. This study identified crucial properties for 12S rDNA, 16S rDNA and COI metabarcoding in tropical-reef piscivores (Plectropomus spp.). In addition, three new versatile primer sets for 16S were designed in silico for metabarcoding of reef fish. Results showed that COI was overall better at recovering true diversity because of a well-supported database. Second, optimal 16S amplicon sizes ranged between 160 and 440 base pairs for full diversity recovery, with increased species detection for the 270-base pairs region. Finally, blocking of predator-specific COI sequences was not equally effective in all host species, potentially introducing bias when diet compositions are directly compared. In conclusion, this novel study showed that marker success for prey identification is highly dependent on the reference database, taxonomic scope, DNA quality, amplicon length and sequencing platform. Results suggest that COI, complemented with 16S, yields the best outcome for diet metabarcoding in reef piscivores. Findings in this paper are relevant to other piscivores and other metabarcoding applications.
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Ansorge, Rebecca, Giovanni Birolo, Stephen A. James, and Andrea Telatin. "Dadaist2: A Toolkit to Automate and Simplify Statistical Analysis and Plotting of Metabarcoding Experiments." International Journal of Molecular Sciences 22, no. 10 (May 18, 2021): 5309. http://dx.doi.org/10.3390/ijms22105309.
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The taxonomic composition of microbial communities can be assessed using universal marker amplicon sequencing. The most common taxonomic markers are the 16S rDNA for bacterial communities and the internal transcribed spacer (ITS) region for fungal communities, but various other markers are used for barcoding eukaryotes. A crucial step in the bioinformatic analysis of amplicon sequences is the identification of representative sequences. This can be achieved using a clustering approach or by denoising raw sequencing reads. DADA2 is a widely adopted algorithm, released as an R library, that denoises marker-specific amplicons from next-generation sequencing and produces a set of representative sequences referred to as ‘Amplicon Sequence Variants’ (ASV). Here, we present Dadaist2, a modular pipeline, providing a complete suite for the analysis that ranges from raw sequencing reads to the statistics of numerical ecology. Dadaist2 implements a new approach that is specifically optimised for amplicons with variable lengths, such as the fungal ITS. The pipeline focuses on streamlining the data flow from the command line to R, with multiple options for statistical analysis and plotting, both interactive and automatic.
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Zhang, Ke, Rongnan Lin, Yujun Chang, Qing Zhou, and Zhi Zhang. "16S-FASAS: an integrated pipeline for synthetic full-length 16S rRNA gene sequencing data analysis." PeerJ 10 (September 23, 2022): e14043. http://dx.doi.org/10.7717/peerj.14043.
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Background The full-length 16S rRNA sequencing can better improve the taxonomic and phylogenetic resolution compared to the partial 16S rRNA gene sequencing. The 16S-FAS-NGS (16S rRNA full-length amplicon sequencing based on a next-generation sequencing platform) technology can generate high-quality, full-length 16S rRNA gene sequences using short-read sequencers, together with assembly procedures. However there is a lack of a data analysis suite that can help process and analyze the synthetic long read data. Results Herein, we developed software named 16S-FASAS (16S full-length amplicon sequencing data analysis software) for 16S-FAS-NGS data analysis, which provided high-fidelity species-level microbiome data. 16S-FASAS consists of data quality control, de novo assembly, annotation, and visualization modules. We verified the performance of 16S-FASAS on both mock and fecal samples. In mock communities, we proved that taxonomy assignment by MegaBLAST had fewer misclassifications and tended to find more low abundance species than the USEARCH-UNOISE3-based classifier, resulting in species-level classification of 85.71% (6/7), 85.71% (6/7), 72.72% (8/11), and 70% (7/10) of the target bacteria. When applied to fecal samples, we found that the 16S-FAS-NGS datasets generated contigs grouped into 60 and 56 species, from which 71.62% (43/60) and 76.79% (43/56) were shared with the Pacbio datasets. Conclusions 16S-FASAS is a valuable tool that helps researchers process and interpret the results of full-length 16S rRNA gene sequencing. Depending on the full-length amplicon sequencing technology, the 16S-FASAS pipeline enables a more accurate report on the bacterial complexity of microbiome samples. 16S-FASAS is freely available for use at https://github.com/capitalbio-bioinfo/FASAS.
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Leonard, Caroline, Damien Thiry, Bernard Taminiau, Georges Daube, and Jacques Fontaine. "External Ear Canal Evaluation in Dogs with Chronic Suppurative Otitis Externa: Comparison of Direct Cytology, Bacterial Culture and 16S Amplicon Profiling." Veterinary Sciences 9, no. 7 (July 18, 2022): 366. http://dx.doi.org/10.3390/vetsci9070366.
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A discrepancy between cytology and bacterial culture methods is sometimes observed in canine otitis externa. The objective of this study was to compare results from cytology, bacterial culture and 16S amplicon profiling. Twenty samples from 16 dogs with chronic suppurative otitis externa were collected. A direct cytological evaluation was carried out during the consultations. Aerobic bacterial culture and susceptibility were performed by an external laboratory used in routine practice. For 16S amplicon profiling, DNA was extracted and the hypervariable segment V1–V3 of the 16S rDNA was amplified and then sequenced with a MiSeq Illumina sequence carried out by the Mothur software using the SILVA database. A good correlation between cytology and bacterial culture was observed in 60% of the samples. Some bacterial species revealed by bacterial culture were present with low relative abundance (<10%) in 16S amplicon profiling. Some bacterial species revealed by the 16S amplicon profiling analysis were not identified with culture; most of the time, the offending species was a Corynebacterium. To conclude, a careful interpretation of the results of bacterial culture should be made and always be in agreement with the cytology. The 16S amplicon profiling method appears to be a more sensitive method for detecting strains present in suppurative otitis but does not provide information on bacterial susceptibility.
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Yu, Jeong suk, Minhee Kim, Il-Hoon Cho, Yu-Min Sim, and Young Sun Hwang. "Evidence Supporting Oral Hygiene Management by Owners through a Genetic Analysis of Dental Plaque Bacteria in Dogs." Veterinary Sciences 11, no. 2 (February 19, 2024): 96. http://dx.doi.org/10.3390/vetsci11020096.
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With the increase in the number of households raising dogs and the reports of human-to-dog transmission of oral bacteria, concerns about dogs’ oral health and the need for oral hygiene management are increasing. In this study, the owners’ perceptions about their dogs’ oral health and the frequency of oral hygiene were determined along with the analysis of dog dental plaque bacteria through metagenomic amplicon sequencing so as to support the need for oral hygiene management for dogs. Although the perception of 63.2% of the owners about their dogs’ oral health was consistent with the veterinarian’s diagnosis, the owners’ oral hygiene practices regarding their dogs were very poor. The calculi index (CI) and gingiva index (GI) were lower in dogs who had their teeth brushed more than once a week (57.89%) than in dogs brushed less than once a month (42.10%); however, the difference was nonsignificant (CI: p = 0.479, GI: p = 0.840). Genomic DNA was extracted from dental plaque bacteria removed during dog teeth scaling, and metagenomic amplicons were sequenced. The 16S amplicons of 73 species were identified from among the plaque bacteria of the dogs. These amplicons were of oral disease-causing bacteria in humans and dogs. The 16S amplicon of Streptococcus mutans matched that of the human S. mutans, with type c identified as the main serotype. This result suggests that human oral bacteria can be transmitted to dogs. Therefore, considering the high frequency of contact between dogs and humans because of communal living and the current poor oral health of dogs, owners must improve the oral hygiene management of their dogs.
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Theil, Sebastien, and Etienne Rifa. "rANOMALY: AmplicoN wOrkflow for Microbial community AnaLYsis." F1000Research 10 (January 7, 2021): 7. http://dx.doi.org/10.12688/f1000research.27268.1.
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Bioinformatic tools for marker gene sequencing data analysis are continuously and rapidly evolving, thus integrating most recent techniques and tools is challenging. We present an R package for data analysis of 16S and ITS amplicons based sequencing. This workflow is based on several R functions and performs automatic treatments from fastq sequence files to diversity and differential analysis with statistical validation. The main purpose of this package is to automate bioinformatic analysis, ensure reproducibility between projects, and to be flexible enough to quickly integrate new bioinformatic tools or statistical methods. rANOMALY is an easy to install and customizable R package, that uses amplicon sequence variants (ASV) level for microbial community characterization. It integrates all assets of the latest bioinformatics methods, such as better sequence tracking, decontamination from control samples, use of multiple reference databases for taxonomic annotation, all main ecological analysis for which we propose advanced statistical tests, and a cross-validated differential analysis by four different methods. Our package produces ready to publish figures, and all of its outputs are made to be integrated in Rmarkdown code to produce automated reports.
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Hjelmsø, Mathis Hjort, Lars Hestbjerg Hansen, Jacob Bælum, Louise Feld, William E. Holben, and Carsten Suhr Jacobsen. "High-Resolution Melt Analysis for Rapid Comparison of Bacterial Community Compositions." Applied and Environmental Microbiology 80, no. 12 (March 7, 2014): 3568–75. http://dx.doi.org/10.1128/aem.03923-13.
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ABSTRACTIn the study of bacterial community composition, 16S rRNA gene amplicon sequencing is today among the preferred methods of analysis. The cost of nucleotide sequence analysis, including requisite computational and bioinformatic steps, however, takes up a large part of many research budgets. High-resolution melt (HRM) analysis is the study of the melt behavior of specific PCR products. Here we describe a novel high-throughput approach in which we used HRM analysis targeting the 16S rRNA gene to rapidly screen multiple complex samples for differences in bacterial community composition. We hypothesized that HRM analysis of amplified 16S rRNA genes from a soil ecosystem could be used as a screening tool to identify changes in bacterial community structure. This hypothesis was tested using a soil microcosm setup exposed to a total of six treatments representing different combinations of pesticide and fertilization treatments. The HRM analysis identified a shift in the bacterial community composition in two of the treatments, both including the soil fumigant Basamid GR. These results were confirmed with both denaturing gradient gel electrophoresis (DGGE) analysis and 454-based 16S rRNA gene amplicon sequencing. HRM analysis was shown to be a fast, high-throughput technique that can serve as an effective alternative to gel-based screening methods to monitor microbial community composition.
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Álvarez Narváez, Sonsiray, Megan S. Beaudry, Connor G. Norris, Paula B. Bartlett, Travis C. Glenn, and Susan Sanchez. "Improved Equine Fecal Microbiome Characterization Using Target Enrichment by Hybridization Capture." Animals 14, no. 3 (January 29, 2024): 445. http://dx.doi.org/10.3390/ani14030445.
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GITDs are among the most common causes of death in adult and young horses in the United States (US). Previous studies have indicated a connection between GITDs and the equine gut microbiome. However, the low taxonomic resolution of the current microbiome sequencing methods has hampered the identification of specific bacterial changes associated with GITDs in horses. Here, we have compared TEHC, a new approach for 16S rRNA gene selection and sequencing, with conventional 16S rRNA gene amplicon sequencing for the characterization of the equine fecal microbiome. Both sequencing approaches were used to determine the fecal microbiome of four adult horses and one commercial mock microbiome. Our results show that TEHC yielded significantly more operational taxonomic units (OTUs) than conventional 16S amplicon sequencing when the same number of reads were used in the analysis. This translated into a deeper and more accurate characterization of the fecal microbiome when the samples were sequenced with TEHC according to the relative abundance analysis. Alpha and beta diversity metrics corroborated these findings and demonstrated that the microbiome of the fecal samples was significantly richer when sequenced with TEHC compared to 16S amplicon sequencing. Altogether, our study suggests that the TEHC strategy provides a more extensive characterization of the fecal microbiome of horses than the current alternative based on the PCR amplification of a portion of the 16S rRNA gene.
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Tang, Jianming, John K. Moulton, Kenneth Pruess, Eddie W. Cupp, and Thomas R. Unnasch. "Genetic variation in North American black flies in the subgenus Psilopelmia (Simulium: Diptera: Simuliidae)." Canadian Journal of Zoology 76, no. 2 (February 1, 1998): 205–11. http://dx.doi.org/10.1139/z97-190.
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Resolution of the genetic heterogeneity of closely related insect species depends on the selection of reliable genetic markers derived from representative specimens. We report the results of a survey of genetic variability in nine species of black flies in the subgenusPsilopelmia Enderlein. Three regions of the mitochondrial genome and an amplicon including the internal transcribed spacer 1 of the nuclear ribosomal RNA gene cluster (ITS1) were amplified using the polymerase chain reaction (PCR), and the amplicons were examined for intraspecific and interspecific polymorphisms. Six of the seven Psilopelmia species that yielded PCR products in the ITS1 PCR reaction were found to generate products that were indistinguishable on the basis of size. Similarly, little interspecific variation was noted in the 16S rRNA amplicon among nine species of Psilopelmia assayed by heteroduplex analysis. In contrast, the remaining regions of the mitochondrial genome exhibited both intra- and inter-specific variation when analyzed by heteroduplex analysis. Information collected from the five amplicons could be employed to develop a classification scheme capable of distinguishing the nine species of Psilopelmia examined.
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Nelson, Michael C., Hilary G. Morrison, Jacquelynn Benjamino, Sharon L. Grim, and Joerg Graf. "Analysis, Optimization and Verification of Illumina-Generated 16S rRNA Gene Amplicon Surveys." PLoS ONE 9, no. 4 (April 10, 2014): e94249. http://dx.doi.org/10.1371/journal.pone.0094249.
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Planý, Matej, Tomáš Kuchta, Katarína Šoltýs, Tomáš Szemes, Domenico Pangallo, and Peter Siekel. "Metagenomic Analysis of Slovak Bryndza Cheese Using Next-Generation 16S rDNA Amplicon Sequencing." Nova Biotechnologica et Chimica 15, no. 1 (June 1, 2016): 23–34. http://dx.doi.org/10.1515/nbec-2016-0003.
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Abstract Knowledge about diversity and taxonomic structure of the microbial population present in traditional fermented foods plays a key role in starter culture selection, safety improvement and quality enhancement of the end product. Aim of this study was to investigate microbial consortia composition in Slovak bryndza cheese. For this purpose, we used culture-independent approach based on 16S rDNA amplicon sequencing using next generation sequencing platform. Results obtained by the analysis of three commercial (produced on industrial scale in winter season) and one traditional (artisanal, most valued, produced in May) Slovak bryndza cheese sample were compared. A diverse prokaryotic microflora composed mostly of the genera Lactococcus, Streptococcus, Lactobacillus, and Enterococcus was identified. Lactococcus lactis subsp. lactis and Lactococcus lactis subsp. cremoris were the dominant taxons in all tested samples. Second most abundant species, detected in all bryndza cheeses, were Lactococcus fujiensis and Lactococcus taiwanensis, independently by two different approaches, using different reference 16S rRNA genes databases (Greengenes and NCBI respectively). They have been detected in bryndza cheese samples in substantial amount for the first time. The narrowest microbial diversity was observed in a sample made with a starter culture from pasteurised milk. Metagenomic analysis by high-throughput sequencing using 16S rRNA genes seems to be a powerful tool for studying the structure of the microbial population in cheeses.
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da Silva, Cleiziane Bispo, Hellen Ribeiro Martins dos Santos, Phellippe Arthur Santos Marbach, Jorge Teodoro de Souza, Valter Cruz-Magalhães, Ronaldo Costa Argôlo-Filho, and Leandro Lopes Loguercio. "First-tier detection of intragenomic 16S rRNA gene variation in culturable endophytic bacteria from cacao seeds." PeerJ 7 (November 20, 2019): e7452. http://dx.doi.org/10.7717/peerj.7452.
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Background Intragenomic variability in 16S rDNA is a limiting factor for taxonomic and diversity characterization of Bacteria, and studies on its occurrence in natural/environmental populations are scarce. In this work, direct DNA amplicon sequencing coupled with frequent-cutter restriction analysis allowed detection of intragenomic 16S rDNA variation in culturable endophytic bacteria from cacao seeds in a fast and attractive manner. Methods Total genomic DNA from 65 bacterial strains was extracted and the 16S rDNA hyper variable V5–V9 regions were amplified for enzyme digestion and direct Sanger-type sequencing. The resulting electropherograms were visually inspected and compared to the corresponding AluI-restriction profiles, as well as to complete genome sequences in databases. Restriction analysis were employed to substitute the need of amplicon cloning and re-sequencing. A specifically improved polyacrylamide-gradient electrophoresis allowed to resolve 5-bp differences in restriction fragment sizes. Chi-square analysis on 2 × 2 contingency table tested for the independence between the ‘number of AluI bands’ and ‘type of eletropherogram’. Results Two types of electropherograms were obtained: unique template, with single peaks per base (clean chromatograms), and heterogeneous template, with various levels of multiple peaks per base (mixed chromatograms). Statistics revealed significant interaction between number of restriction fragments and type of electropherogram for the same amplicons: clean or mixed ones associated to ≤5 or ≥6 bands, respectively. The mixed-template pattern combined with the AluI-restriction profiles indicated a high proportion of 49% of the culturable endophytes from a tropical environment showing evidence of intragenomic 16S rDNA heterogeneity. Conclusion The approach presented here was useful for a rapid, first-tier detection of intragenomic variation in culturable isolates, which can be applied in studies of other natural populations; a preliminary view of intragenomic heterogeneity levels can complement culture-dependent and -independent methods. Consequences of these findings in taxonomic and diversity studies in complex bacterial communities are discussed.
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Sierra, Maria A., Qianhao Li, Smruti Pushalkar, Bidisha Paul, Tito A. Sandoval, Angela R. Kamer, Patricia Corby, et al. "The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community." Genes 11, no. 8 (August 3, 2020): 878. http://dx.doi.org/10.3390/genes11080878.
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There is currently no criterion to select appropriate bioinformatics tools and reference databases for analysis of 16S rRNA amplicon data in the human oral microbiome. Our study aims to determine the influence of multiple tools and reference databases on α-diversity measurements and β-diversity comparisons analyzing the human oral microbiome. We compared the results of taxonomical classification by Greengenes, the Human Oral Microbiome Database (HOMD), National Center for Biotechnology Information (NCBI) 16S, SILVA, and the Ribosomal Database Project (RDP) using Quantitative Insights Into Microbial Ecology (QIIME) and the Divisive Amplicon Denoising Algorithm (DADA2). There were 15 phyla present in all of the analyses, four phyla exclusive to certain databases, and different numbers of genera were identified in each database. Common genera found in the oral microbiome, such as Veillonella, Rothia, and Prevotella, are annotated by all databases; however, less common genera, such as Bulleidia and Paludibacter, are only annotated by large databases, such as Greengenes. Our results indicate that using different reference databases in 16S rRNA amplicon data analysis could lead to different taxonomic compositions, especially at genus level. There are a variety of databases available, but there are no defined criteria for data curation and validation of annotations, which can affect the accuracy and reproducibility of results, making it difficult to compare data across studies.
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Yen, Sandi, Jethro Johnson, and Nicholas E. Ilott. "Streamlined processing and analysis of 16S rRNA amplicon sequencing data with OCMS_16S and OCMSlooksy." Wellcome Open Research 7 (February 23, 2022): 68. http://dx.doi.org/10.12688/wellcomeopenres.17632.1.
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16S rRNA gene sequencing is a cost-effective method for profiling the bacterial component of a microbiome. Nevertheless, processing and analysis of the resulting sequencing data is often constrained by the availability of dedicated bioinformaticians - creating a bottleneck for biological interpretation. Multiple visualisation and analysis tools now exist for downstream analysis of 16S rRNA data. These tools are designed with biological scientists in mind and therefore consist of a graphical user interface that interacts with taxonomic counts tables to perform tasks such as alpha- and beta-diversity analysis and differential abundance. However, generating the input to these applications still relies on bioinformatics experience, creating a disconnect between data processing and data analysis. We aimed to bridge the gap between data processing and data analysis. To do this we have created two tools - OCMS_16S and OCMSlooksy - that perform data processing and data visualisation/analysis, respectively. OCMS_16S is a cgat-core based pipeline that wraps DADA2 functionality in order to facilitate processing of raw sequence reads into tables of amplicon sequence variant (ASV) counts using a simple command line interface. OCMSlooksy is an RShiny application that takes an OCMS_16S-generated SQLite database as input to facilitate data exploration and analysis. Combining these tools provides a simple, user-friendly workflow to facilitate 16S rRNA gene amplicon sequencing data analysis from raw reads to results.
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Ranjan, Ravi, Asha Rani, Ahmed Metwally, Halvor S. McGee, and David L. Perkins. "Analysis of the microbiome: Advantages of whole genome shotgun versus 16S amplicon sequencing." Biochemical and Biophysical Research Communications 469, no. 4 (January 2016): 967–77. http://dx.doi.org/10.1016/j.bbrc.2015.12.083.
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Murovec, Boštjan, Leon Deutsch, and Blaž Stres. "General Unified Microbiome Profiling Pipeline (GUMPP) for Large Scale, Streamlined and Reproducible Analysis of Bacterial 16S rRNA Data to Predicted Microbial Metagenomes, Enzymatic Reactions and Metabolic Pathways." Metabolites 11, no. 6 (May 24, 2021): 336. http://dx.doi.org/10.3390/metabo11060336.
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General Unified Microbiome Profiling Pipeline (GUMPP) was developed for large scale, streamlined and reproducible analysis of bacterial 16S rRNA data and prediction of microbial metagenomes, enzymatic reactions and metabolic pathways from amplicon data. GUMPP workflow introduces reproducible data analyses at each of the three levels of resolution (genus; operational taxonomic units (OTUs); amplicon sequence variants (ASVs)). The ability to support reproducible analyses enables production of datasets that ultimately identify the biochemical pathways characteristic of disease pathology. These datasets coupled to biostatistics and mathematical approaches of machine learning can play a significant role in extraction of truly significant and meaningful information from a wide set of 16S rRNA datasets. The adoption of GUMPP in the gut-microbiota related research enables focusing on the generation of novel biomarkers that can lead to the development of mechanistic hypotheses applicable to the development of novel therapies in personalized medicine.
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Fujimoto, Naoshi, Keigo Mizuno, Tomoki Yokoyama, Akihiro Ohnishi, Masaharu Suzuki, Satoru Watanabe, Kenji Komatsu, et al. "Community analysis of picocyanobacteria in an oligotrophic lake by cloning 16S rRNA gene and 16S rRNA gene amplicon sequencing." Journal of General and Applied Microbiology 61, no. 5 (2015): 171–76. http://dx.doi.org/10.2323/jgam.61.171.
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Nakajima, Aruto, Keisuke Yoshida, Aina Gotoh, Toshihiko Katoh, Miriam N. Ojima, Mikiyasu Sakanaka, Jin-Zhong Xiao, Toshitaka Odamaki, and Takane Katayama. "A simple method that enhances minority species detection in the microbiota: 16S metagenome-DRIP (Deeper Resolution using an Inhibitory Primer)." Microbiome Research Reports 1, no. 3 (2022): 20. http://dx.doi.org/10.20517/mrr.2022.08.
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Aim: 16S rRNA gene-based microbiota analyses (16S metagenomes) using next-generation sequencing (NGS) technologies are widely used to examine the microbial community composition in environmental samples. However, the sequencing capacity of NGS is sometimes insufficient to cover the whole microbial community, especially when analyzing soil and fecal microbiotas. This limitation may have hampered the detection of minority species that potentially affect microbiota formation and structure. Methods: We developed a simple method, termed 16S metagenome-DRIP (Deeper Resolution using an Inhibitory Primer), that not only enhances minority species detection but also increases the accuracy of their abundance estimation. The method relies on the inhibition of normal amplicon formation of the 16S rRNA gene of a target major (abundant) species during the first PCR step. The addition of a biotinylated primer that is complementary to the variable sequence of the V3-V4 region of the target species inhibits a normal amplification process to form an aberrant short amplicon. The fragment is then captured by streptavidin beads for removal from the reaction mixture, and the resulting mixture is utilized for the second PCR with barcode-tag primers. Thus, this method only requires two additional experimental procedures to the conventional 16S metagenome analysis. A proof-of-concept experiment was first conducted using a mock sample consisting of the genomes of 14 bacterial species. Then, the method was applied to infant fecal samples using a Bifidobacterium-specific inhibitory primer (n = 11). Results: As a result, the reads assigned to the family Bifidobacteriaceae decreased on average from 16,657 to 1718 per sample without affecting the total read counts (36,073 and 34,778 per sample for the conventional and DRIP methods, respectively). Furthermore, the minority species detection rate increased with neither affecting Bray-Curtis dissimilarity calculated by omitting the target Bifidobacterium species (median: 0.049) nor changing the relative abundances of the non-target species. While 115 amplicon sequence variants (ASVs) were unique to the conventional method, 208 ASVs were uniquely detected for the DRIP method. Moreover, the abundance estimation for minority species became more accurate, as revealed thorough comparison with the results of quantitative PCR analysis. Conclusion: The 16S metagenome-DRIP method serves as a useful technique to grasp a deeper and more accurate microbiota composition when combined with conventional 16S metagenome analysis methods.
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Guo, Mengmeng, Xi Cao, Ke Zhang, Menghao Pan, Yujiang Wu, Suo Langda, Yuxin Yang, Yulin Chen, Ba Gui, and Baohua Ma. "16S rRNA Gene Sequencing Revealed Changes in Gut Microbiota Composition during Pregnancy and Lactation in Mice Model." Veterinary Sciences 9, no. 4 (April 1, 2022): 169. http://dx.doi.org/10.3390/vetsci9040169.
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The gut microbiota play a vital role in regulating endocrine-mediated metabolism, immunity, and energy metabolism. However, little is known about the gut microbiota and metabolite composition and development throughout pregnancy and lactation. Here, we used amplicon sequencing to analyze the gut microbiota composition of 35 female mice in five stages of pregnancy and lactation, namely, non-receptive (NR) stages, sexually-receptive (SR) stages, at day 15 of pregnancy (Pre_D15), at the day of birth (Del), and at day 10 of lactation (Lac_D10). The results revealed that the α diversity of gut microbiota was significantly increased during pregnancy and lactation. In addition, the principal coordinate analysis (PCoA) conducted on the amplicon sequence variants’ (ASVs’) distribution of the 16S rRNA amplicons indicated that the microbiota composition was significantly different among the five groups. Based on a random forest analysis, Oscillospira, Dehalobacterium, and Alistipes were the most important microbiota. The abundance of Allobaculum, Oscillospira, and Ruminococcus were negatively correlated with the serum progesterone concentration, while the abundance of Oscillospira was positively correlated with the propionate and valerate concentration in the caecal contents. Moreover, the concentration of acetate and propionate in the Del and Lac_D10 stages was significantly lower than in the SR and Pre_D15 stages. Our findings indicate that some gut microbes and metabolites vary considerably at the different stages of pregnancy and during lactation stages, which can potentially be used as microbial biomarkers. These results provide information on the potential use of the identified microbes as probiotics to maintain a healthy pregnancy and lactation.
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Torrell, Helena, Adrià Cereto-Massagué, Polina Kazakova, Lorena García, Héctor Palacios, and Núria Canela. "Multiomic Approach to Analyze Infant Gut Microbiota: Experimental and Analytical Method Optimization." Biomolecules 11, no. 7 (July 7, 2021): 999. http://dx.doi.org/10.3390/biom11070999.
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Background: The human intestinal microbiome plays a central role in overall health status, especially in early life stages. 16S rRNA amplicon sequencing is used to profile its taxonomic composition; however, multiomic approaches have been proposed as the most accurate methods for study of the complexity of the gut microbiota. In this study, we propose an optimized method for bacterial diversity analysis that we validated and complemented with metabolomics by analyzing fecal samples. Methods: Forty-eight different analytical combinations regarding (1) 16S rRNA variable region sequencing, (2) a feature selection approach, and (3) taxonomy assignment methods were tested. A total of 18 infant fecal samples grouped depending on the type of feeding were analyzed by the proposed 16S rRNA workflow and by metabolomic analysis. Results: The results showed that the sole use of V4 region sequencing with ASV identification and VSEARCH for taxonomy assignment produced the most accurate results. The application of this workflow showed clear differences between fecal samples according to the type of feeding, which correlated with changes in the fecal metabolic profile. Conclusion: A multiomic approach using real fecal samples from 18 infants with different types of feeding demonstrated the effectiveness of the proposed 16S rRNA-amplicon sequencing workflow.
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Yaman, Belma Nural. "Metagenomics (16S Amplicon Sequencing) and DGGE Analysis of Bacterial Diversity of Acid Mine Drainage." Journal of Microbiology, Biotechnology and Food Sciences 9, no. 5 (April 2020): 932–36. http://dx.doi.org/10.15414/jmbfs.2020.9.5.932-936.
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Gonzalez, Emmanuel, Frederic E. Pitre, and Nicholas J. B. Brereton. "ANCHOR: a 16S rRNA gene amplicon pipeline for microbial analysis of multiple environmental samples." Environmental Microbiology 21, no. 7 (May 21, 2019): 2440–68. http://dx.doi.org/10.1111/1462-2920.14632.
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Sibanda, Timothy, Ramganesh Selvarajan, and Memory Tekere. "Targeted 16S rRNA amplicon analysis reveals the diversity of bacterial communities in carwash effluents." International Microbiology 22, no. 2 (October 26, 2018): 181–89. http://dx.doi.org/10.1007/s10123-018-00038-0.
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Ramiro-Garcia, Javier, Gerben D. A. Hermes, Christos Giatsis, Detmer Sipkema, Erwin G. Zoetendal, Peter J. Schaap, and Hauke Smidt. "NG-Tax, a highly accurate and validated pipeline for analysis of 16S rRNA amplicons from complex biomes." F1000Research 5 (November 23, 2018): 1791. http://dx.doi.org/10.12688/f1000research.9227.2.
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Background: Massive high-throughput sequencing of short, hypervariable segments of the 16S ribosomal RNA (rRNA) gene has transformed the methodological landscape describing microbial diversity within and across complex biomes. However, several studies have shown that the methodology rather than the biological variation is responsible for the observed sample composition and distribution. This compromises meta-analyses, although this fact is often disregarded. Results: To facilitate true meta-analysis of microbiome studies, we developed NG-Tax, a pipeline for 16S rRNA gene amplicon sequence analysis that was validated with different mock communities and benchmarked against QIIME as a frequently used pipeline. The microbial composition of 49 independently amplified mock samples was characterized by sequencing two variable 16S rRNA gene regions, V4 and V5-V6, in three separate sequencing runs on Illumina’s HiSeq2000 platform. This allowed for the evaluation of important causes of technical bias in taxonomic classification: 1) run-to-run sequencing variation, 2) PCR–error, and 3) region/primer specific amplification bias. Despite the short read length (~140 nt) and all technical biases, the average specificity of the taxonomic assignment for the phylotypes included in the mock communities was 97.78%. On average 99.95% and 88.43% of the reads could be assigned to at least family or genus level, respectively, while assignment to ‘spurious genera’ represented on average only 0.21% of the reads per sample. Analysis of α- and β-diversity confirmed conclusions guided by biology rather than the aforementioned methodological aspects, which was not achieved with QIIME. Conclusions: Different biological outcomes are commonly observed due to 16S rRNA region-specific performance. NG-Tax demonstrated high robustness against choice of region and other technical biases associated with 16S rRNA gene amplicon sequencing studies, diminishing their impact and providing accurate qualitative and quantitative representation of the true sample composition. This will improve comparability between studies and facilitate efforts towards standardization.
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Chun, Jongsik, Anwarul Huq, and Rita R. Colwell. "Analysis of 16S-23S rRNA Intergenic Spacer Regions of Vibrio cholerae and Vibrio mimicus." Applied and Environmental Microbiology 65, no. 5 (May 1, 1999): 2202–8. http://dx.doi.org/10.1128/aem.65.5.2202-2208.1999.
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ABSTRACT Vibrio cholerae identification based on molecular sequence data has been hampered by a lack of sequence variation from the closely related Vibrio mimicus. The two species share many genes coding for proteins, such as ctxAB, and show almost identical 16S DNA coding for rRNA (rDNA) sequences. Primers targeting conserved sequences flanking the 3′ end of the 16S and the 5′ end of the 23S rDNAs were used to amplify the 16S-23S rRNA intergenic spacer regions of V. cholerae and V. mimicus. Two major (ca. 580 and 500 bp) and one minor (ca. 750 bp) amplicons were consistently generated for both species, and their sequences were determined. The largest fragment contains three tRNA genes (tDNAs) coding for tRNAGlu, tRNALys, and tRNAVal, which has not previously been found in bacteria examined to date. The 580-bp amplicon contained tDNAIle and tDNAAla, whereas the 500-bp fragment had single tDNA coding either tRNAGlu or tRNAAla. Little variation, i.e., 0 to 0.4%, was found among V. cholerae O1 classical, O1 El Tor, and O139 epidemic strains. Slightly more variation was found against the non-O1/non-O139 serotypes (ca. 1% difference) and V. mimicus (2 to 3% difference). A pair of oligonucleotide primers were designed, based on the region differentiating all of V. cholerae strains from V. mimicus. The PCR system developed was subsequently evaluated by using representatives of V. cholerae from environmental and clinical sources, and of other taxa, including V. mimicus. This study provides the first molecular tool for identifying the species V. cholerae.
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Barak, Noga, Eduard Fadeev, Vera Brekhman, Dikla Aharonovich, Tamar Lotan, and Daniel Sher. "Selecting 16S rRNA Primers for Microbiome Analysis in a Host–Microbe System: The Case of the Jellyfish Rhopilema nomadica." Microorganisms 11, no. 4 (April 6, 2023): 955. http://dx.doi.org/10.3390/microorganisms11040955.
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Amplicon sequencing of the 16S rRNA gene is extensively used to characterize bacterial communities, including those living in association with eukaryotic hosts. Deciding which region of the 16S rRNA gene to analyze and selecting the appropriate PCR primers remains a major decision when initiating any new microbiome study. Based on a detailed literature survey of studies focusing on cnidarian microbiomes, we compared three commonly used primers targeting different hypervariable regions of the 16S rRNA gene, V1V2, V3V4, and V4V5, using the jellyfish Rhopilema nomadica as a model. Although all primers exhibit a similar pattern in bacterial community composition, the performance of the V3V4 primer set was superior to V1V2 and V4V5. The V1V2 primers misclassified bacteria from the Bacilli class and exhibited low classification resolution for Rickettsiales, which represent the second most abundant 16S rRNA gene sequence in all the primers. The V4V5 primer set detected almost the same community composition as the V3V4, but the ability of these primers to also amplify the eukaryotic 18S rRNA gene may hinder bacterial community observations. However, after overcoming the challenges possessed by each one of those primers, we found that all three of them show very similar bacterial community dynamics and compositions. Nevertheless, based on our results, we propose that the V3V4 primer set is potentially the most suitable for studying jellyfish-associated bacterial communities. Our results suggest that, at least for jellyfish samples, it may be feasible to directly compare microbial community estimates from different studies, each using different primers but otherwise similar experimental protocols. More generally, we recommend specifically testing different primers for each new organism or system as a prelude to large-scale 16S rRNA gene amplicon analyses, especially of previously unstudied host–microbe associations.
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Bergsten, Pauline, Pauline Vannier, Julie Frion, Alan Mougeolle, and Viggó Þór Marteinsson. "Culturable Bacterial Diversity from the Basaltic Subsurface of the Young Volcanic Island of Surtsey, Iceland." Microorganisms 10, no. 6 (June 8, 2022): 1177. http://dx.doi.org/10.3390/microorganisms10061177.
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The oceanic crust is the world’s largest and least explored biosphere on Earth. The basaltic subsurface of Surtsey island in Iceland represents an analog of the warm and newly formed-oceanic crust and offers a great opportunity for discovering novel microorganisms. In this study, we collected borehole fluids, drill cores, and fumarole samples to evaluate the culturable bacterial diversity from the subsurface of the island. Enrichment cultures were performed using different conditions, media and temperatures. A total of 195 bacterial isolates were successfully cultivated, purified, and identified based on MALDI-TOF MS analysis and by 16S rRNA gene sequencing. Six different clades belonging to Firmicutes (40%), Gammaproteobacteria (28.7%), Actinobacteriota (22%), Bacteroidota (4.1%), Alphaproteobacteria (3%), and Deinococcota (2%) were identified. Bacillus (13.3%) was the major genus, followed by Geobacillus (12.33%), Enterobacter (9.23%), Pseudomonas (6.15%), and Halomonas (5.64%). More than 13% of the cultured strains potentially represent novel species based on partial 16S rRNA gene sequences. Phylogenetic analyses revealed that the isolated strains were closely related to species previously detected in soil, seawater, and hydrothermal active sites. The 16S rRNA gene sequences of the strains were aligned against Amplicon Sequence Variants (ASVs) from the previously published 16S rRNA gene amplicon sequence datasets obtained from the same samples. Compared with the culture-independent community composition, only 5 out of 49 phyla were cultivated. However, those five phyla accounted for more than 80% of the ASVs. Only 121 out of a total of 5642 distinct ASVs were culturable (≥98.65% sequence similarity), representing less than 2.15% of the ASVs detected in the amplicon dataset. Here, we support that the subsurface of Surtsey volcano hosts diverse and active microbial communities and that both culture-dependent and -independent methods are essential to improving our insight into such an extreme and complex volcanic environment.
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McAdams, Zachary, Kevin Gustafson, and Aaron Ericsson. "The Effect of Common Viral Inactivation Techniques on 16S rRNA Amplicon-Based Analysis of the Gut Microbiota." Microorganisms 9, no. 8 (August 17, 2021): 1755. http://dx.doi.org/10.3390/microorganisms9081755.
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Research investigating the gut microbiome (GM) during a viral infection may necessitate inactivation of the fecal viral load. Here, we assess how common viral inactivation techniques affect 16S rRNA-based analysis of the gut microbiome. Five common viral inactivation methods were applied to cross-matched fecal samples from sixteen female CD-1 mice of the same GM background prior to fecal DNA extraction. The V4 region of the 16S rRNA gene was amplified and sequenced from extracted DNA. Treatment-dependent effects on DNA yield, genus-level taxonomic abundance, and alpha and beta diversity metrics were assessed. A sodium dodecyl sulfate (SDS)-based inactivation method and Holder pasteurization had no effect on measures of microbial richness, while two Buffer AVL-based inactivation methods resulted in a decrease in detected richness. SDS inactivation, Holder pasteurization, and the AVL-based inactivation methods had no effect on measures of alpha diversity within samples or beta diversity between samples. Fecal DNA extracted with TRIzol-treated samples failed to amplify and sequence, making it unsuitable for microbiome analysis. These results provide guidance in the 16S rRNA microbiome analysis of fecal samples requiring viral inactivation.
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Forero-Becerra, Elkin, Jignesh Patel, Heidy-C. Martínez-Díaz, Paola Betancourt-Ruiz, Efraín Benavides, Steven Durán, Luz-A. Olaya-Másmela, Eliana Bolaños, Marylin Hidalgo, and Jere W. McBride. "Seroprevalence and Genotypic Analysis of Ehrlichia canis Infection in Dogs and Humans in Cauca, Colombia." American Journal of Tropical Medicine and Hygiene 104, no. 5 (May 5, 2021): 1771–76. http://dx.doi.org/10.4269/ajtmh.20-0965.
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ABSTRACTEhrlichia canis infections have been reported in humans in Venezuela and Costa Rica. In this study, 506 healthy residents and 114 dogs from four municipalities (Cauca, Colombia) were surveyed and blood samples collected. Antibodies to E. canis in human and canine sera were evaluated using the Tandem repeat protein 19 (TRP19) peptide ELISA and indirect immunofluorescence assay (IFA). Ehrlichia canis TRP19 antibodies were detected in only 1/506 human sera, but the single positive sample was negative by IFA. The majority (75/114; 66%) of dogs surveyed had antibodies to the E. canis TRP19 peptide by ELISA, and eight randomly selected sera were further confirmed by E. canis IFA. Genomic DNA samples obtained from 73 E. canis TRP19 ELISA–positive dog blood samples were examined by PCR targeting the 16S ribosomal ribonucleic acid (rRNA) gene. Ehrlichia canis 16S rRNA was amplified in 30 (41%) of the dogs, and 16 amplicons were selected for DNA sequencing, which confirmed that all were E. canis. A second PCR was performed on the 16 confirmed E. canis 16S rRNA PCR–positive samples to determine the TRP36 genotype by amplifying the trp36 gene. TRP36 PCR amplicon sequencing identified nine dogs infected with the U.S. E. canis TRP36 genotype (56%), one dog with the Brazilian genotype (6%), and six dogs with the Costa Rican genotype (38%). Moreover, these molecular genotype signatures were consistent with serologic analysis using TRP36 genotype–specific peptides. Notably, there was no serologic evidence of E. canis infection in humans, suggesting that E. canis infection in dogs in Cauca is not associated with zoonotic human infection.
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Ramiro-Garcia, Javier, Gerben D. A. Hermes, Christos Giatsis, Detmer Sipkema, Erwin G. Zoetendal, Peter J. Schaap, and Hauke Smidt. "NG-Tax, a highly accurate and validated pipeline for analysis of 16S rRNA amplicons from complex biomes." F1000Research 5 (July 22, 2016): 1791. http://dx.doi.org/10.12688/f1000research.9227.1.
Full textAbstract:
Background Massive high-throughput sequencing of short, hypervariable segments of the 16S ribosomal RNA (rRNA) gene has transformed the methodological landscape describing microbial diversity within and across complex biomes. However, several studies have shown that the methodology rather than the biological variation is responsible for the observed sample composition and distribution. This compromises true meta-analyses, although this fact is often disregarded. Results To facilitate true meta-analysis of microbiome studies, we developed NG-Tax, a pipeline for 16S rRNA gene amplicon sequence analysis that was validated with different mock communities and benchmarked against QIIME as the currently most frequently used pipeline. The microbial composition of 49 independently amplified mock samples was characterized by sequencing two variable 16S rRNA gene regions, V4 and V5-V6, in three separate sequencing runs on Illumina’s HiSeq2000 platform. This allowed evaluating important factors of technical bias in taxonomic classification: 1) run-to-run sequencing variation, 2) PCR–error, and 3) region/primer specific amplification bias. Despite the short read length (~140 nt) and all technical biases, the average specificity of the taxonomic assignment for the phylotypes included in the mock communities was 96%. On average 99.94% and 92.02% of the reads could be assigned to at least family or genus level, respectively, while assignment to ‘spurious genera’ represented on average only 0.02% of the reads per sample. Analysis of α- and β-diversity confirmed conclusions guided by biology rather than the aforementioned methodological aspects, which was not the case when samples were analysed using QIIME. Conclusions Different biological outcomes are commonly observed due to 16S rRNA region-specific performance. NG-Tax demonstrated high robustness against choice of region and other technical biases associated with 16S rRNA gene amplicon sequencing studies, diminishing their impact and providing accurate qualitative and quantitative representation of the true sample composition. This will improve comparability between studies and facilitate efforts towards standardization.
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NAKAYAMA, Jiro, Jiahui JIANG, Koichi WATANABE, Kangting CHEN, Huang NINXIN, Kazunori MATSUDA, Takashi KURAKAWA, Hirokazu TSUJI, Kenji SONOMOTO, and Yuan-Kun LEE. "Up to Species-level Community Analysis of Human Gut Microbiota by 16S rRNA Amplicon Pyrosequencing." Bioscience of Microbiota, Food and Health 32, no. 2 (2013): 69–76. http://dx.doi.org/10.12938/bmfh.32.69.
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Roberto, Frank F. "16S-rRNA gene-targeted amplicon sequence analysis of an enargite-dominant bioleach demonstration in Peru." Hydrometallurgy 180 (September 2018): 271–76. http://dx.doi.org/10.1016/j.hydromet.2018.08.005.
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Barret, Maialen, Nathalie Gagnon, Martin L. Kalmokoff, Edward Topp, Yris Verastegui, Stephen P. J. Brooks, Fernando Matias, Josh D. Neufeld, and Guylaine Talbot. "Identification of Methanoculleus spp. as Active Methanogens during Anoxic Incubations of Swine Manure Storage Tank Samples." Applied and Environmental Microbiology 79, no. 2 (October 26, 2012): 424–33. http://dx.doi.org/10.1128/aem.02268-12.
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ABSTRACTMethane emissions represent a major environmental concern associated with manure management in the livestock industry. A more thorough understanding of how microbial communities function in manure storage tanks is a prerequisite for mitigating methane emissions. Identifying the microorganisms that are metabolically active is an important first step. Methanogenic archaea are major contributors to methanogenesis in stored swine manure, and we investigated active methanogenic populations by DNA stable isotope probing (DNA-SIP). Following a preincubation of manure samples under anoxic conditions to induce substrate starvation, [U-13C]acetate was added as a labeled substrate. Fingerprint analysis of density-fractionated DNA, using length-heterogeneity analysis of PCR-amplifiedmcrAgenes (encoding the alpha subunit of methyl coenzyme M reductase), showed that the incorporation of13C into DNA was detectable atin situacetate concentrations (∼7 g/liter). Fingerprints of DNA retrieved from heavy fractions of the13C treatment were primarily enriched in a 483-bp amplicon and, to a lesser extent, in a 481-bp amplicon. Analyses based on clone libraries of themcrAand 16S rRNA genes revealed that both of these heavy DNA amplicons corresponded toMethanoculleusspp. Our results demonstrate that uncultivated methanogenic archaea related toMethanoculleusspp. were major contributors to acetate-C assimilation during the anoxic incubation of swine manure storage tank samples. Carbon assimilation and dissimilation rate estimations suggested thatMethanoculleusspp. were also major contributors to methane emissions and that the hydrogenotrophic pathway predominated during methanogenesis.
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Murphy, Robert, and Mikael Lenz Strube. "RibDif2: Expanding amplicon analysis to full genomes." Bioinformatics Advances, August 21, 2023. http://dx.doi.org/10.1093/bioadv/vbad111.
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Abstract Motivation As previously described, amplicon analysis of the bacterial 16S gene has several limitations owing to fundamental characteristics of both the 16S gene and technological restrictions. Previously, RibDif was introduced to help quantify these limitations by detailed analysis of a given genera and the 16S gene profile of its members, notably multiplicity and divergence of 16S alleles within genomes as well as shared alleles between species. Apart from using amplicon-analysis for only the 16S gene, amplicons derived from genus-specific genes or even functional genes are increasingly being utilized. Moreover, long-read technologies are progressively being used to sequence longer amplicons, and since these inherently contain more information, they may likely alleviate the issues proposed in RibDif. Results Taking these phenomena into account, we here propose RibDif2. RibDif2 retains the 16S-optimized functionality of the original RibDif but can now run any set of primers on any part of the genome in any set of organisms, be it prokaryote, eukaryote or archaea. We demonstrate this new functionality by showing full species resolution of Pseudoalteromonas using complete rRNA-operon amplicons, as well as selection of optimally discriminatory primers for Staphylococcus and Pseudomonas. Moreover, we show a potential bias towards terrestrial bacteria relative to marine ones for primers amplifying biosynthetic gene clusters and lastly suggest optimal primers to differentiate the members of the insect genus Drosophila. We believe RibDif2 will facilitate the work of all scientists using amplicon sequencing, especially in the era of long-read sequencing. Availability Ribdif2 is freely available at https://github.com/Rob-murphys/ribdif Supplementary information Supplementary data are available at Bioinformatics Advances online.
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Izak, D., A. Gromadka, and S. Kaczanowski. "Mothulity Facilitates 16S/ITS Amplicon Diversity Analysis." Current Protocols in Bioinformatics 69, no. 1 (February 24, 2020). http://dx.doi.org/10.1002/cpbi.94.
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Zorz, Jackie, Carmen Li, Anirban Chakraborty, Daniel A. Gittins, Taylor Surcon, Natasha Morrison, Robbie Bennett, Adam MacDonald, and Casey R. J. Hubert. "SituSeq: an offline protocol for rapid and remote Nanopore 16S rRNA amplicon sequence analysis." ISME Communications 3, no. 1 (April 20, 2023). http://dx.doi.org/10.1038/s43705-023-00239-3.
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AbstractMicrobiome analysis through 16S rRNA gene sequencing is a crucial tool for understanding the microbial ecology of any habitat or ecosystem. However, workflows require large equipment, stable internet, and extensive computing power such that most of the work is performed far away from sample collection in both space and time. Performing amplicon sequencing and analysis at sample collection would have positive implications in many instances including remote fieldwork and point-of-care medical diagnoses. Here we present SituSeq, an offline and portable workflow for the sequencing and analysis of 16S rRNA gene amplicons using Nanopore sequencing and a standard laptop computer. SituSeq was validated by comparing Nanopore 16S rRNA gene amplicons, Illumina 16S rRNA gene amplicons, and Illumina metagenomes, sequenced using the same environmental DNA. Comparisons revealed consistent community composition, ecological trends, and sequence identity across platforms. Correlation between the abundance of taxa in each taxonomic level in Illumina and Nanopore data sets was high (Pearson’s r > 0.9), and over 70% of Illumina 16S rRNA gene sequences matched a Nanopore sequence with greater than 97% sequence identity. On board a research vessel on the open ocean, SituSeq was used to analyze amplicon sequences from deep sea sediments less than 2 h after sequencing, and 8 h after sample collection. The rapidly available results informed decisions about subsequent sampling in near real-time while the offshore expedition was still underway. SituSeq is a portable and user-friendly workflow that helps to bring the power of microbial genomics and diagnostics to many more researchers and situations.
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Strube, Mikael Lenz. "RibDif: Can individual species be differentiated by 16S sequencing?" Bioinformatics Advances, September 6, 2021. http://dx.doi.org/10.1093/bioadv/vbab020.
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Abstract Metataxonomic analysis is now routinely used to profile the microbiome of virtually every ecological niche on planet Earth. The use of Amplicon Sequence Variants (ASVs), proposing to be the exact biological 16S rRNA amplicon sequences of a given biological system, is now considered the gold standard. However, the 16S rRNA genes, and in particular the amplicons derived from it, are not unique for most species nor are they necessarily unique within individual genomes. Despite these restrictions, individual ASVs are often used to make inferences on the state of a given ecosystem which may cause erroneous conclusions on the effects of a given species on a specific host phenotype or ecosystem. To support researchers working with metataxonomics, we have developed RibDif which easily and rapidly evaluates the feasibility of using metataxonomics to profile individual species. We use RibDif to demonstrate that the genus Pseudoalteromonas contain species that are impossible to distinguish with 16S amplicons and that this is a common motif in bacterial genera. We propose that researchers consult RibDif when making conclusions on individual species from metataxonomic data. Availability Ribdif is freely available along with source code and detailed documentation at https://github.com/mikaells/RibDif
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Zhang, Tianyuan, Hanzhou Li, Silin Ma, Jian Cao, Hao Liao, Qiaoyun Huang, and Wenli Chen. "The newest Oxford Nanopore R10.4.1 full-length 16S rRNA sequencing enables the accurate resolution of species-level microbial community profiling." Applied and Environmental Microbiology, October 6, 2023. http://dx.doi.org/10.1128/aem.00605-23.
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ABSTRACT The long-read amplicon provides a species-level solution for the community. With the improvement of nanopore flowcells, the accuracy of Oxford Nanopore Technologies (ONT) R10.4.1 has been substantially enhanced, with an average of approximately 99%. To evaluate its effectiveness on amplicons, three types of microbiomes were analyzed by 16S ribosomal RNA (hereinafter referred to as “16S”) amplicon sequencing using Novaseq, Pacbio sequel II, and Nanopore PromethION platforms (R9.4.1 and R10.4.1) in the current study. We showed the error rate, recall, precision, and bias index in the mock sample. The error rate of ONT R10.4.1 was greatly reduced, with a better recall in the case of the synthetic community. Meanwhile, in different types of environmental samples, ONT R10.4.1 analysis resulted in a composition similar to Pacbio data. We found that classification tools and databases influence ONT data. Based on these results, we conclude that the ONT R10.4.1 16S amplicon can also be used for application in environmental samples. IMPORTANCE The long-read amplicon supplies the community with a species-level solution. Due to the high error rate of nanopore sequencing early on, it has not been frequently used in 16S studies. Oxford Nanopore Technologies (ONT) introduced the R10.4.1 flowcell with Q20+ reagent to achieve more than 99% accuracy as sequencing technology advanced. However, there has been no published study on the performance of commercial PromethION sequencers with R10.4.1 flowcells on 16S sequencing or on the impact of accuracy improvement on taxonomy (R9.4.1 to R10.4.1) using 16S ONT data. In this study, three types of microbiomes were investigated by 16S ribosomal RNA (rRNA) amplicon sequencing using Novaseq, Pacbio sequel II, and Nanopore PromethION platforms (R9.4.1 and R10.4.1). In the mock sample, we displayed the error rate, recall, precision, and bias index. We observed that the error rate in ONT R10.4.1 is significantly lower, especially when deletions are involved. First and foremost, R10.4.1 and Pacific Bioscience platforms reveal a similar microbiome in environmental samples. This study shows that the R10.4.1 full-length 16S rRNA sequences allow for species identification of environmental microbiota.
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Tremblay, Julien, and Etienne Yergeau. "Systematic processing of ribosomal RNA gene amplicon sequencing data." GigaScience 8, no. 12 (December 1, 2019). http://dx.doi.org/10.1093/gigascience/giz146.
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Abstract Background With the advent of high-throughput sequencing, microbiology is becoming increasingly data-intensive. Because of its low cost, robust databases, and established bioinformatic workflows, sequencing of 16S/18S/ITS ribosomal RNA (rRNA) gene amplicons, which provides a marker of choice for phylogenetic studies, has become ubiquitous. Many established end-to-end bioinformatic pipelines are available to perform short amplicon sequence data analysis. These pipelines suit a general audience, but few options exist for more specialized users who are experienced in code scripting, Linux-based systems, and high-performance computing (HPC) environments. For such an audience, existing pipelines can be limiting to fully leverage modern HPC capabilities and perform tweaking and optimization operations. Moreover, a wealth of stand-alone software packages that perform specific targeted bioinformatic tasks are increasingly accessible, and finding a way to easily integrate these applications in a pipeline is critical to the evolution of bioinformatic methodologies. Results Here we describe AmpliconTagger, a short rRNA marker gene amplicon pipeline coded in a Python framework that enables fine tuning and integration of virtually any potential rRNA gene amplicon bioinformatic procedure. It is designed to work within an HPC environment, supporting a complex network of job dependencies with a smart-restart mechanism in case of job failure or parameter modifications. As proof of concept, we present end results obtained with AmpliconTagger using 16S, 18S, ITS rRNA short gene amplicons and Pacific Biosciences long-read amplicon data types as input. Conclusions Using a selection of published algorithms for generating operational taxonomic units and amplicon sequence variants and for computing downstream taxonomic summaries and diversity metrics, we demonstrate the performance and versatility of our pipeline for systematic analyses of amplicon sequence data.
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Kinoshita, Yuta, Hidekazu Niwa, Eri Uchida-Fujii, and Toshio Nukada. "Establishment and assessment of an amplicon sequencing method targeting the 16S-ITS-23S rRNA operon for analysis of the equine gut microbiome." Scientific Reports 11, no. 1 (June 4, 2021). http://dx.doi.org/10.1038/s41598-021-91425-7.
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AbstractMicrobial communities are commonly studied by using amplicon sequencing of part of the 16S rRNA gene. Sequencing of the full-length 16S rRNA gene can provide higher taxonomic resolution and accuracy. To obtain even higher taxonomic resolution, with as few false-positives as possible, we assessed a method using long amplicon sequencing targeting the rRNA operon combined with a CCMetagen pipeline. Taxonomic assignment had > 90% accuracy at the species level in a mock sample and at the family level in equine fecal samples, generating similar taxonomic composition as shotgun sequencing. The rRNA operon amplicon sequencing of equine fecal samples underestimated compositional percentages of bacterial strains containing unlinked rRNA genes by a fourth to a third, but unlinked rRNA genes had a limited effect on the overall results. The rRNA operon amplicon sequencing with the A519F + U2428R primer set was able to detect some kind of archaeal genomes such as Methanobacteriales and Methanomicrobiales, whereas full-length 16S rRNA with 27F + 1492R could not. Therefore, we conclude that amplicon sequencing targeting the rRNA operon captures more detailed variations of equine microbiota.
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Xue, Zhengyao, Mary E. Kable, and Maria L. Marco. "Impact of DNA Sequencing and Analysis Methods on 16S rRNA Gene Bacterial Community Analysis of Dairy Products." mSphere 3, no. 5 (October 17, 2018). http://dx.doi.org/10.1128/msphere.00410-18.
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ABSTRACT DNA sequencing and analysis methods were compared for 16S rRNA V4 PCR amplicon and genomic DNA (gDNA) mock communities encompassing nine bacterial species commonly found in milk and dairy products. The two communities comprised strain-specific DNA that was pooled before (gDNA) or after (PCR amplicon) the PCR step. The communities were sequenced on the Illumina MiSeq and Ion Torrent PGM platforms and then analyzed using the QIIME 1 (UCLUST) and Divisive Amplicon Denoising Algorithm 2 (DADA2) analysis pipelines with taxonomic comparisons to the Greengenes and Ribosomal Database Project (RDP) databases. Examination of the PCR amplicon mock community with these methods resulted in operational taxonomic units (OTUs) and amplicon sequence variants (ASVs) that ranged from 13 to 118 and were dependent on the DNA sequencing method and read assembly steps. The additional 4 to 109 OTUs/ASVs (from 9 OTUs/ASVs) included assignments to spurious taxa and sequence variants of the 9 species included in the mock community. Comparisons between the gDNA and PCR amplicon mock communities showed that combining gDNAs from the different strains prior to PCR resulted in up to 8.9-fold greater numbers of spurious OTUs/ASVs. However, the DNA sequencing method and paired-end read assembly steps conferred the largest effects on predictions of bacterial diversity, with effect sizes of 0.88 (Bray-Curtis) and 0.32 (weighted Unifrac), independent of the mock community type. Overall, DNA sequencing performed with the Ion Torrent PGM and analyzed with DADA2 and the Greengenes database resulted in the most accurate predictions of the mock community phylogeny, taxonomy, and diversity. IMPORTANCE Validated methods are urgently needed to improve DNA sequence-based assessments of complex bacterial communities. In this study, we used 16S rRNA PCR amplicon and gDNA mock community standards, consisting of nine, dairy-associated bacterial species, to evaluate the most commonly applied 16S rRNA marker gene DNA sequencing and analysis platforms used in evaluating dairy and other bacterial habitats. Our results show that bacterial metataxonomic assessments are largely dependent on the DNA sequencing platform and read curation method used. DADA2 improved sequence annotation compared with QIIME 1, and when combined with the Ion Torrent PGM DNA sequencing platform and the Greengenes database for taxonomic assignment, the most accurate representation of the dairy mock community standards was reached. This approach will be useful for validating sample collection and DNA extraction methods and ultimately investigating bacterial population dynamics in milk- and dairy-associated environments.
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Miura, Hiroto, Masayuki Takeda, Megumi Yamaguchi, Yoshihisa Ohtani, Go Endo, Yasuhisa Masuda, Kaede Ito, et al. "Application of MinION Amplicon Sequencing to Buccal Swab Samples for Improving Resolution and Throughput of Rumen Microbiota Analysis." Frontiers in Microbiology 13 (March 24, 2022). http://dx.doi.org/10.3389/fmicb.2022.783058.
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The Illumina MiSeq platform has been widely used as a standard method for studying the rumen microbiota. However, the low resolution of taxonomic identification is the only disadvantage of MiSeq amplicon sequencing, as it targets a part of the 16S rRNA gene. In the present study, we performed three experiments to establish a high-resolution and high-throughput rumen microbial profiling approach using a combination of MinION platform and buccal swab sample, which is a proxy for rumen contents. In experiment 1, rumen contents and buccal swab samples were collected simultaneously from cannulated cattle (n = 6) and used for microbiota analysis using three different analytical workflows: amplicon sequencing of the V3–V4 region of the 16S rRNA gene using MiSeq and amplicon sequencing of near full-length 16S rRNA gene using MinION or PacBio Sequel II. All reads derived from the MinION and PacBio platforms were classified at the species-level. In experiment 2, rumen fluid samples were collected from beef cattle (n = 28) and used for 16S rRNA gene amplicon sequencing using the MinION platform to evaluate this sequencing platform for rumen microbiota analysis. We confirmed that the MinION platform allowed species-level taxa assignment for the predominant bacterial groups, which were previously identified at the family- and genus-level using the MiSeq platform. In experiment 3, buccal swab samples were collected from beef cattle (n = 30) and used for 16S rRNA gene amplicon sequencing using the MinION platform to validate the applicability of a combination of the MinION platform and buccal swab samples for rumen microbiota analysis. The distribution of predominant bacterial taxa in the buccal swab samples was similar to that in the rumen samples observed in experiment 2. Based on these results, we concluded that the combination of the MinION platform and buccal swab samples may be potentially applied for rumen microbial analysis in large-scale studies.
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Zheng, Jun-Jie, Po-Wen Wang, Tzu-Wen Huang, Yao-Jong Yang, Hua-Sheng Chiu, Pavel Sumazin, and Ting-Wen Chen. "MOCHI, a comprehensive cross-platform tool for amplicon-based microbiota analysis." Bioinformatics, July 25, 2022. http://dx.doi.org/10.1093/bioinformatics/btac494.
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Abstract Motivation Microbiota analyses have important implications for health and science. These analyses make use of 16S/18S rRNA gene sequencing to identify taxa and predict species diversity. However, most available tools for analyzing microbiota data require adept programming skills and in-depth statistical knowledge for proper implementation. While long-read amplicon sequencing can lead to more accurate taxa predictions and is quickly becoming more common, practitioners have no easily accessible tools with which to perform their analyses. Results We present MOCHI, a GUI tool for microbiota amplicon sequencing analysis. MOCHI preprocesses sequences, assigns taxonomy, identifies different abundant species and predicts species diversity and function. It takes either taxonomic count table or FASTQ of partial 16S/18S rRNA or full-length 16S rRNA gene as input. It performs analyses in real-time and visualizes data in both tabular and graphical formats. Availability MOCHI can be installed to run locally or accessed as a web tool at https://mochi.life.nctu.edu.tw. Supplementary information Supplementary data are available at Bioinformatics online.
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Umbach, Alexander K., Champika Fernando, Janet E. Hill, and Josh D. Neufeld. "Evaluating cpn60 for high-resolution profiling of the mammalian skin microbiome and detection of phylosymbiosis." ISME Communications 3, no. 1 (July 7, 2023). http://dx.doi.org/10.1038/s43705-023-00276-y.
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AbstractDespite being the most widely used phylogenetic marker for amplicon-based profiling of microbial communities, limited phylogenetic resolution of the 16S rRNA gene limits its use for studies of host-microbe co-evolution. In contrast, the cpn60 gene is a universal phylogenetic marker with greater sequence variation capable of species-level resolution. This research compared mammalian skin microbial profiles generated from cpn60 and 16S rRNA gene sequencing approaches, testing for patterns of phylosymbiosis that suggest co-evolutionary host-microbe associations. An ~560 bp fragment of the cpn60 gene was amplified with universal primers and subjected to high-throughput sequencing. Taxonomic classification of cpn60 sequences was completed using a naïve-Bayesian QIIME2 classifier created for this project, trained with an NCBI-supplemented curated cpn60 database (cpnDB_nr). The cpn60 dataset was then compared to published 16S rRNA gene amplicon data. Beta diversity comparisons of microbial community profiles generated with cpn60 and 16S rRNA gene amplicons were not significantly different, based on Procrustes analysis of Bray-Curtis and UniFrac distances. Despite similar relationships among skin microbial profiles, improved phylogenetic resolution provided by the cpn60 gene sequencing permitted observations of phylosymbiosis between microbial community profiles and their mammalian hosts that were not previously observed with 16S rRNA gene profiles. Subsequent investigation of Staphylococcaceae taxa using the cpn60 gene showed increased phylogenetic resolution compared the 16S rRNA gene profiles, revealing potential co-evolutionary host-microbe associations. Overall, our results demonstrate that 16S rRNA and cpn60 marker genes generate comparable microbial community composition patterns while cpn60 better facilitates analyses, such as phylosymbiosis, that require increased phylogenetic resolution.
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Odom, Aubrey R., Tyler Faits, Eduardo Castro-Nallar, Keith A. Crandall, and W. Evan Johnson. "Metagenomic profiling pipelines improve taxonomic classification for 16S amplicon sequencing data." Scientific Reports 13, no. 1 (August 26, 2023). http://dx.doi.org/10.1038/s41598-023-40799-x.
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AbstractMost experiments studying bacterial microbiomes rely on the PCR amplification of all or part of the gene for the 16S rRNA subunit, which serves as a biomarker for identifying and quantifying the various taxa present in a microbiome sample. Several computational methods exist for analyzing 16S amplicon sequencing. However, the most-used bioinformatics tools cannot produce high quality genus-level or species-level taxonomic calls and may underestimate the potential accuracy of these calls. We used 16S sequencing data from mock bacterial communities to evaluate the sensitivity and specificity of several bioinformatics pipelines and genomic reference libraries used for microbiome analyses, concentrating on measuring the accuracy of species-level taxonomic assignments of 16S amplicon reads. We evaluated the tools DADA2, QIIME 2, Mothur, PathoScope 2, and Kraken 2 in conjunction with reference libraries from Greengenes, SILVA, Kraken 2, and RefSeq. Profiling tools were compared using publicly available mock community data from several sources, comprising 136 samples with varied species richness and evenness, several different amplified regions within the 16S rRNA gene, and both DNA spike-ins and cDNA from collections of plated cells. PathoScope 2 and Kraken 2, both tools designed for whole-genome metagenomics, outperformed DADA2, QIIME 2 using the DADA2 plugin, and Mothur, which are theoretically specialized for 16S analyses. Evaluations of reference libraries identified the SILVA and RefSeq/Kraken 2 Standard libraries as superior in accuracy compared to Greengenes. These findings support PathoScope and Kraken 2 as fully capable, competitive options for genus- and species-level 16S amplicon sequencing data analysis, whole genome sequencing, and metagenomics data tools.
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Matsuo, Yoshiyuki, Shinnosuke Komiya, Yoshiaki Yasumizu, Yuki Yasuoka, Katsura Mizushima, Tomohisa Takagi, Kirill Kryukov, et al. "Full-length 16S rRNA gene amplicon analysis of human gut microbiota using MinION™ nanopore sequencing confers species-level resolution." BMC Microbiology 21, no. 1 (January 26, 2021). http://dx.doi.org/10.1186/s12866-021-02094-5.
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Abstract Background Species-level genetic characterization of complex bacterial communities has important clinical applications in both diagnosis and treatment. Amplicon sequencing of the 16S ribosomal RNA (rRNA) gene has proven to be a powerful strategy for the taxonomic classification of bacteria. This study aims to improve the method for full-length 16S rRNA gene analysis using the nanopore long-read sequencer MinION™. We compared it to the conventional short-read sequencing method in both a mock bacterial community and human fecal samples. Results We modified our existing protocol for full-length 16S rRNA gene amplicon sequencing by MinION™. A new strategy for library construction with an optimized primer set overcame PCR-associated bias and enabled taxonomic classification across a broad range of bacterial species. We compared the performance of full-length and short-read 16S rRNA gene amplicon sequencing for the characterization of human gut microbiota with a complex bacterial composition. The relative abundance of dominant bacterial genera was highly similar between full-length and short-read sequencing. At the species level, MinION™ long-read sequencing had better resolution for discriminating between members of particular taxa such as Bifidobacterium, allowing an accurate representation of the sample bacterial composition. Conclusions Our present microbiome study, comparing the discriminatory power of full-length and short-read sequencing, clearly illustrated the analytical advantage of sequencing the full-length 16S rRNA gene.
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Beaudry, Megan S., Jincheng Wang, Troy J. Kieran, Jesse Thomas, Natalia J. Bayona-Vásquez, Bei Gao, Alison Devault, et al. "Improved Microbial Community Characterization of 16S rRNA via Metagenome Hybridization Capture Enrichment." Frontiers in Microbiology 12 (April 27, 2021). http://dx.doi.org/10.3389/fmicb.2021.644662.
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Environmental microbial diversity is often investigated from a molecular perspective using 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics. While amplicon methods are fast, low-cost, and have curated reference databases, they can suffer from amplification bias and are limited in genomic scope. In contrast, shotgun metagenomic methods sample more genomic regions with fewer sequence acquisition biases, but are much more expensive (even with moderate sequencing depth) and computationally challenging. Here, we develop a set of 16S rRNA sequence capture baits that offer a potential middle ground with the advantages from both approaches for investigating microbial communities. These baits cover the diversity of all 16S rRNA sequences available in the Greengenes (v. 13.5) database, with no sequence having <78% sequence identity to at least one bait for all segments of 16S. The use of our baits provide comparable results to 16S amplicon libraries and shotgun metagenomic libraries when assigning taxonomic units from 16S sequences within the metagenomic reads. We demonstrate that 16S rRNA capture baits can be used on a range of microbial samples (i.e., mock communities and rodent fecal samples) to increase the proportion of 16S rRNA sequences (average > 400-fold) and decrease analysis time to obtain consistent community assessments. Furthermore, our study reveals that bioinformatic methods used to analyze sequencing data may have a greater influence on estimates of community composition than library preparation method used, likely due in part to the extent and curation of the reference databases considered. Thus, enriching existing aliquots of shotgun metagenomic libraries and obtaining modest numbers of reads from them offers an efficient orthogonal method for assessment of bacterial community composition.
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Olivier, Sandra A., Michelle K. Bull, Mikael Lenz Strube, Robert Murphy, Tom Ross, John P. Bowman, and Belinda Chapman. "Long-read MinION™ sequencing of 16S and 16S-ITS-23S rRNA genes provides species-level resolution of Lactobacillaceae in mixed communities." Frontiers in Microbiology 14 (December 7, 2023). http://dx.doi.org/10.3389/fmicb.2023.1290756.
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The Lactobacillaceae are lactic acid bacteria harnessed to deliver important outcomes across numerous industries, and their unambiguous, species-level identification from mixed community environments is an important endeavor. Amplicon-based metataxonomics using short-read sequencing of partial 16S rRNA gene regions is widely used to support this, however, the high genetic similarity among Lactobacillaceae species restricts our ability to confidently describe these communities even at genus level. Long-read sequencing (LRS) of the whole 16S rRNA gene or the near complete rRNA operon (16S-ITS-23S) has the potential to improve this. We explored species ambiguity amongst Lactobacillaceae using in-silico tool RibDif2, which identified allele overlap when various partial and complete 16S rRNA gene and 16S-ITS-23S rRNA regions were amplified. We subsequently implemented LRS by MinION™ to compare the capacity of V3–V4, 16S and 16S-ITS-23S rRNA amplicons to accurately describe the diversity of a 20-species Lactobacillaceae mock community in practice. In-silico analysis identified more instances of allele/species overlap with V3–V4 amplicons (n = 43) compared to the 16S rRNA gene (n = 11) and partial (n = up to 15) or complete (n = 0) 16S-ITS-23S rRNA amplicons. With subsequent LRS of a DNA mock community, 80% of target species were identified using V3–V4 amplicons whilst the 16S rRNA gene and 16S-ITS-23S rRNA region amplicons resulted in 95 and 100% of target species being identified. A considerable reduction in false-positive identifications was also seen with 16S rRNA gene (n = 3) and 16S-ITS-23S rRNA region (n = 9) amplicons compared with V3–V4 amplicons (n = 43). Whilst the target species affected by allele overlap in V3–V4 and 16S rRNA gene sequenced mock communities were predicted by RibDif2, unpredicted species ambiguity was observed in 16S-ITS-23S rRNA sequenced communities. Considering the average nucleotide identity (ANI) between ambiguous species (~97%) and the basecall accuracy of our MinION™ sequencing protocol (96.4%), the misassignment of reads between closely related taxa is to be expected. With basecall accuracy exceeding 99% for recent MinION™ releases, the increased species-level differentiating power promised by longer amplicons like the 16S-ITS-23S rRNA region, may soon be fully realized.
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Molano, Leidy-Alejandra G., Sara Vega-Abellaneda, and Chaysavanh Manichanh. "GSR-DB: a manually curated and optimized taxonomical database for 16S rRNA amplicon analysis." mSystems, January 8, 2024. http://dx.doi.org/10.1128/msystems.00950-23.
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ABSTRACT Amplicon-based 16S ribosomal RNA sequencing remains a widely used method to profile microbial communities, especially in low biomass samples, due to its cost-effectiveness and low-complexity approach. Reference databases are a mainstay for taxonomic assignments, which typically rely on popular databases such as SILVA, Greengenes, Genome Taxonomy Database (GTDB), or Ribosomal Database Project (RDP). However, the inconsistency of the nomenclature across databases and the presence of shortcomings in the annotation of these databases are limiting the resolution of the analysis. To overcome these limitations, we created the GSR database (Greengenes, SILVA, and RDP database), an integrated and manually curated database for bacterial and archaeal 16S amplicon taxonomy analysis. Unlike previous integration approaches, this database creation pipeline includes a taxonomy unification step to ensure consistency in taxonomical annotations. The database was validated with three mock communities, two real data sets, and a 10-fold cross-validation method and compared with existing 16S databases such as Greengenes, Greengenes 2, GTDB, ITGDB, SILVA, RDP, and MetaSquare. Results showed that the GSR database enhances taxonomical annotations of 16S sequences, outperforming current 16S databases at the species level, based on the evaluation of the mock communities. This was confirmed by the 10-fold cross-validation, except for Greengenes 2. The GSR database is available for full-length 16S sequences and the most commonly used hypervariable regions: V4, V1–V3, V3–V4, and V3–V5. IMPORTANCE Taxonomic assignments of microorganisms have long been hindered by inconsistent nomenclature and annotation issues in existing databases like SILVA, Greengenes, Greengenes2, Genome Taxonomy Database, or Ribosomal Database Project. To overcome these issues, we created Greengenes-SILVA-RDP database (GSR-DB), accurate and comprehensive taxonomic annotations of 16S amplicon data. Unlike previous approaches, our innovative pipeline includes a unique taxonomy unification step, ensuring consistent and reliable annotations. Our evaluation analyses showed that GSR-DB outperforms existing databases in providing species-level resolution, especially based on mock-community analysis, making it a game-changer for microbiome studies. Moreover, GSR-DB is designed to be accessible to researchers with limited computational resources, making it a powerful tool for scientists across the board. Available for full-length 16S sequences and commonly used hypervariable regions, including V4, V1–V3, V3–V4, and V3–V5, GSR-DB is a go-to database for robust and accurate microbial taxonomy analysis.
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Ziesemer, Kirsten A., Allison E. Mann, Krithivasan Sankaranarayanan, Hannes Schroeder, Andrew T. Ozga, Bernd W. Brandt, Egija Zaura, et al. "Intrinsic challenges in ancient microbiome reconstruction using 16S rRNA gene amplification." Scientific Reports 5, no. 1 (November 13, 2015). http://dx.doi.org/10.1038/srep16498.
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Abstract To date, characterization of ancient oral (dental calculus) and gut (coprolite) microbiota has been primarily accomplished through a metataxonomic approach involving targeted amplification of one or more variable regions in the 16S rRNA gene. Specifically, the V3 region (E. coli 341–534) of this gene has been suggested as an excellent candidate for ancient DNA amplification and microbial community reconstruction. However, in practice this metataxonomic approach often produces highly skewed taxonomic frequency data. In this study, we use non-targeted (shotgun metagenomics) sequencing methods to better understand skewed microbial profiles observed in four ancient dental calculus specimens previously analyzed by amplicon sequencing. Through comparisons of microbial taxonomic counts from paired amplicon (V3 U341F/534R) and shotgun sequencing datasets, we demonstrate that extensive length polymorphisms in the V3 region are a consistent and major cause of differential amplification leading to taxonomic bias in ancient microbiome reconstructions based on amplicon sequencing. We conclude that systematic amplification bias confounds attempts to accurately reconstruct microbiome taxonomic profiles from 16S rRNA V3 amplicon data generated using universal primers. Because in silico analysis indicates that alternative 16S rRNA hypervariable regions will present similar challenges, we advocate for the use of a shotgun metagenomics approach in ancient microbiome reconstructions.