scholarly journals Cydrasil 3, a curated 16S rRNA gene reference package and web app for cyanobacterial phylogenetic placement

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Daniel Roush ◽  
Ana Giraldo-Silva ◽  
Ferran Garcia-Pichel
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Web Application ◽  
De Novo ◽  
Reference Sequence ◽  
Rrna Gene ◽  
Automated Classification ◽  
Reference Tree ◽  
Phylogenetic Placement ◽  
Routine Identification

AbstractCyanobacteria are a widespread and important bacterial phylum, responsible for a significant portion of global carbon and nitrogen fixation. Unfortunately, reliable and accurate automated classification of cyanobacterial 16S rRNA gene sequences is muddled by conflicting systematic frameworks, inconsistent taxonomic definitions (including the phylum itself), and database errors. To address this, we introduce Cydrasil 3 (https://www.cydrasil.org), a curated 16S rRNA gene reference package, database, and web application designed to provide a full phylogenetic perspective for cyanobacterial systematics and routine identification. Cydrasil 3 contains over 1300 manually curated sequences longer than 1100 base pairs and can be used for phylogenetic placement or as a reference sequence set for de novo phylogenetic reconstructions. The web application (utilizing PaPaRA and EPA-ng) can place thousands of sequences into the reference tree and has detailed instructions on how to analyze results. While the Cydrasil web application offers no taxonomic assignments, it instead provides phylogenetic placement, as well as a searchable database with curation notes and metadata, and a mechanism for community feedback.

scholarly journals Performance and Application of 16S rRNA Gene Cycle Sequencing for Routine Identification of Bacteria in the Clinical Microbiology Laboratory

2020 ◽  
Vol 33 (4) ◽  
Author(s):  
Deirdre L. Church ◽  
Lorenzo Cerutti ◽  
Antoine Gürtler ◽  
Thomas Griener ◽  
Adrian Zelazny ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Clinical Microbiology ◽  
Clinical Microbiology Laboratory ◽  
Rrna Gene ◽  
Microbiology Laboratory ◽  
Cycle Sequencing ◽  
16S Sequencing ◽  
Routine Identification ◽  
Identification Of Bacteria

SUMMARY This review provides a state-of-the-art description of the performance of Sanger cycle sequencing of the 16S rRNA gene for routine identification of bacteria in the clinical microbiology laboratory. A detailed description of the technology and current methodology is outlined with a major focus on proper data analyses and interpretation of sequences. The remainder of the article is focused on a comprehensive evaluation of the application of this method for identification of bacterial pathogens based on analyses of 16S multialignment sequences. In particular, the existing limitations of similarity within 16S for genus- and species-level differentiation of clinically relevant pathogens and the lack of sequence data currently available in public databases is highlighted. A multiyear experience is described of a large regional clinical microbiology service with direct 16S broad-range PCR followed by cycle sequencing for direct detection of pathogens in appropriate clinical samples. The ability of proteomics (matrix-assisted desorption ionization-time of flight) versus 16S sequencing for bacterial identification and genotyping is compared. Finally, the potential for whole-genome analysis by next-generation sequencing (NGS) to replace 16S sequencing for routine diagnostic use is presented for several applications, including the barriers that must be overcome to fully implement newer genomic methods in clinical microbiology. A future challenge for large clinical, reference, and research laboratories, as well as for industry, will be the translation of vast amounts of accrued NGS microbial data into convenient algorithm testing schemes for various applications (i.e., microbial identification, genotyping, and metagenomics and microbiome analyses) so that clinically relevant information can be reported to physicians in a format that is understood and actionable. These challenges will not be faced by clinical microbiologists alone but by every scientist involved in a domain where natural diversity of genes and gene sequences plays a critical role in disease, health, pathogenicity, epidemiology, and other aspects of life-forms. Overcoming these challenges will require global multidisciplinary efforts across fields that do not normally interact with the clinical arena to make vast amounts of sequencing data clinically interpretable and actionable at the bedside.

scholarly journals De novo clustering methods out-perform reference-based methods for assigning 16S rRNA gene sequences to operational taxonomic units

2015 ◽  
Author(s):  
Sarah L Westcott ◽  
Patrick Schloss
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
De Novo ◽  
Rrna Gene ◽  
Clustering Methods ◽  
Gene Sequences ◽  
16S Rrna Gene Sequences ◽  
Reference Methods ◽  
Reference Sequences

Background. 16S rRNA gene sequences are routinely assigned to operational taxonomic units (OTUs) that are then used to analyze complex microbial communities. A number of methods have been employed to carry out the assignment of 16S rRNA gene sequences to OTUs leading to confusion over which method is optimal. A recent study suggested that a clustering method should be selected based on its ability to generate stable OTU assignments that do not change as additional sequences are added to the dataset. In contrast, we contend that the quality of the OTU assignments, the ability of the method to properly represent the distances between the sequences, is more important.Methods. Our analysis implemented six de novo clustering algorithms including the single linkage, complete linkage, average linkage, abundance-based greedy clustering, distance-based greedy clustering, and Swarm and the open and closed-reference methods. Using two previously published datasets we used the Matthew’s Correlation Coefficient (MCC) to assess the stability and quality of OTU assignments.Results. The stability of OTU assignments did not reflect the quality of the assignments. Depending on the dataset being analyzed, the average linkage and the distance and abundance-based greedy clustering methods generated OTUs that were more likely to represent the actual distances between sequences than the open and closed-reference methods. We also demonstrated that for the greedy algorithms VSEARCH produced assignments that were comparable to those produced by USEARCH making VSEARCH a viable free and open source alternative to USEARCH. Further interrogation of the reference-based methods indicated that when USEARCH or VSEARCH were used to identify the closest reference, the OTU assignments were sensitive to the order of the reference sequences because the reference sequences can be identical over the region being considered. More troubling was the observation that while both USEARCH and VSEARCH have a high level of sensitivity to detect reference sequences, the specificity of those matches was poor relative to the true best match.Discussion. Our analysis calls into question the quality and stability of OTU assignments generated by the open and closed-reference methods as implemented in current version of QIIME. This study demonstrates that de novo methods are the optimal method of assigning sequences into OTUs and that the quality of these assignments needs to be assessed for multiple methods to identify the optimal clustering method for a particular dataset.

scholarly journals Cutibacterium modestum and “Propionibacterium humerusii” represent the same species that is commonly misidentified as Cutibacterium acnes

2021 ◽  
Author(s):  
Daniel Goldenberger ◽  
Kirstine K. Søgaard ◽  
Aline Cuénod ◽  
Helena Seth-Smith ◽  
Daniel de Menezes ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Reference Sequence ◽  
Rrna Gene ◽  
Correct Identification ◽  
Skin Microbiome ◽  
Isolation And Identification ◽  
Important Species ◽  
Cutibacterium Acnes ◽  
The 16S Rrna Gene

AbstractCutibacterium spp. play an increasing role in soft tissue and implant-associated infections. We isolated a novel Cutibacterium spp. from an implant and investigated this isolate using multiple identification approaches. Correct identification was hampered by inconsistent reference data. The isolate was characterised using conventional methods such as Gram stain, MALDI-TOF MS, and antimicrobial susceptibility testing against multiple antimicrobials. Partial 16S rRNA gene sequencing and whole genome sequencing were also performed. In addition, we summarised the available published sequence data and compared prior data to our strain. Conventional phenotypic identification of our isolate resulted in Cutibacterium spp. After analysis of 16S rRNA gene and genome sequences, our isolate was identified as C. modestum, a very recently described species. The 16S rRNA gene analysis was hampered by three incorrect nucleotides within the 16S rRNA gene reference sequence of C. modestum M12T (accession no. LC466959). We also clearly demonstrate that this novel species is identical to tentatively named “Propionibacterium humerusii”. Retrospective data analysis indicates that C. modestum is a clinically important Cutibacterium species often misidentified as C. acnes. The isolation and identification of Cutibacterium spp. is still a challenge. The correct description of very recently named C. modestum and the availability of a correct 16S rRNA sequence of the type strain may help to clarify the taxonomical uncertainty concerning “P. humerusii”. The novel C. modestum is an additional, clinically important species within the genus Cutibacterium and may represent a new member of the human skin microbiome.

scholarly journals EzTaxon: a web-based tool for the identification of prokaryotes based on 16S ribosomal RNA gene sequences

2007 ◽  
Vol 57 (10) ◽  
pp. 2259-2261 ◽  
Author(s):  
Jongsik Chun ◽  
Jae-Hak Lee ◽  
Yoonyoung Jung ◽  
Myungjin Kim ◽  
Seil Kim ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Phylogenetic Analyses ◽  
Rrna Gene ◽  
Gene Sequences ◽  
16S Rrna Gene Sequences ◽  
Multiple Sequence ◽  
Web Based ◽  
Routine Identification ◽  
Type Strains

16S rRNA gene sequences have been widely used for the identification of prokaryotes. However, the flood of sequences of non-type strains and the lack of a peer-reviewed database for 16S rRNA gene sequences of type strains have made routine identification of isolates difficult and labour-intensive. In the present study, we generated a database containing 16S rRNA gene sequences of all prokaryotic type strains. In addition, a web-based tool, named EzTaxon, for analysis of 16S rRNA gene sequences was constructed to achieve identification of isolates based on pairwise nucleotide similarity values and phylogenetic inference methods. The system developed provides users with a similarity-based search, multiple sequence alignment and various phylogenetic analyses. All of these functions together with the 16S rRNA gene sequence database of type strains can be successfully used for automated and reliable identification of prokaryotic isolates. The EzTaxon server is freely accessible over the Internet at http://www.eztaxon.org/

scholarly journals HashSeq: A Simple, Scalable, and Conservative De Novo Variant Caller for 16S rRNA Gene Datasets

2021 ◽  
Author(s):  
Farnaz Fouladi ◽  
Jacqueline B Young ◽  
Anthony A Fodor
Keyword(s):  
High Resolution ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
De Novo ◽  
16S Rrna Gene Sequencing ◽  
Error Rates ◽  
Sequencing Error ◽  
Rrna Gene ◽  
Sequence Variants ◽  
Background Error

16S rRNA gene sequencing is a common and cost-effective technique for characterization of microbial communities. Recent bioinformatics methods enable high-resolution detection of sequence variants of only one nucleotide difference. In this manuscript, we utilize a very fast HashMap-based approach to detect sequence variants in six publicly available 16S rRNA gene datasets. We then use the normal distribution combined with LOESS regression to estimate background error rates as a function of sequencing depth for individual clusters of sequences. This method is computationally efficient and produces inference that yields sets of variants that are conservative and well supported by reference databases. We argue that this approach to inference is fast, simple, scalable to large datasets, and provides a high-resolution set of sequence variants which are less likely to be the result of sequencing error.

scholarly journals Metagenomic 16S rRNA gene sequencing survey of Borrelia species in Irish samples of Ixodes ricinus ticks

2018 ◽  
Author(s):  
John S Lambert ◽  
Michael John Cook ◽  
John Eoin Healy ◽  
Ross Murtagh ◽  
Gordana Avramovic ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Ixodes Ricinus ◽  
Sanger Sequencing ◽  
Reference Sequence ◽  
Borrelia Burgdorferi Sensu Lato ◽  
Tick Population ◽  
Rrna Gene ◽  
Ixodes Ricinus Ticks ◽  
The 16S Rrna Gene

Lyme borreliosis is a systemic infection caused by tick-borne pathogenic borreliae of the Borrelia burgdorferi sensu lato complex or of the more heterogeneous relapsing fever borrelia group. Clinical distinction of the infections due to different borrelia species is difficult. Accurate knowledge of the prevalence and the species of borreliae in the infected ticks in the endemic areas is valuable for formulating appropriate guidelines for proper management of this infectious disease. The purpose of this research was to design a readily implementable protocol to detect the divergent species of borreliae known to exist in Europe, using Irish samples of Ixodes ricinus ticks as the subject for study. Questing I. ricinus nymph samples were taken at six localities within Ireland. The crude DNA of each dried tick was extracted by hot NH4OH and used to initiate a same-nested PCR with a pair of borrelial genus-specific primers to amplify a highly conserved 357/358 bp segment of the 16S rRNA gene for detection and as the template for Sanger sequencing. To distinguish B. garinii from B. burgdorferi and to discriminate the various strains of B. garinii, a second 282 bp segment of the 16S rRNA gene was amplified for Sanger sequencing. A signature segment of the DNA sequence excised from the computer-generated electropherogram was submitted to the GenBank for BLAST alignment analysis. A 100% ID match with the unique reference sequence in the GenBank was required for the molecular diagnosis of the borrelial species or strain. We found the overall rate of borrelial infection in the Irish tick population to be 5%, with a range from 2% to 12% depending on the locations of tick collection. At least 3 species, namely B. garinii, B. valaisiana and B. miyamotoi, are infecting the ticks collected in Ireland. The isolates of B. garinii were confirmed to be strain BgVir, strain Bernie or strain T25. Since antigens for diagnostic serology tests may be species- or even strain-specific, expanded surveillance of the species and strains of the borreliae among human-biting ticks in Ireland is needed to ensure that the antigens used for the serology tests do contain the epitopes matching the antibodies elicited by the borrelial species and strains in the ticks cohabitating in the same environment.

scholarly journals First report of strains related to the phytoplasma associated with Tanzanian Lethal Decline on Cocos nucifera on the western coast of Madagascar

Plant Disease ◽  
2021 ◽  
Author(s):  
Fabian Pilet ◽  
Emilson Rakotoarisoa ◽  
M. R. Rakotomalala ◽  
Sabine Sisteron ◽  
Harisoa Nirina Razakamanana ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Cocos Nucifera ◽  
Reference Sequence ◽  
Rrna Gene ◽  
Western Coast ◽  
Gene Sequences ◽  
16S Rrna Gene Sequences ◽  
Seca Gene ◽  
Lethal Yellowing

Madagascar is a high diversity hotspot in the world, and palms are highly represented with nearly 200 endemic species (Rakotoarinivo et al., 2014). Coconut tree (Cocos nucifera) could have been introduced in Madagascar by Austronesians around AD 400 or 700 (Beaujard, 2011). Sporadic coconut trees showing very severe wilt were observed in 2016 in three localities of the western and northern coast of the island: Katsepy (Sample MG16-001), Antsohyhi (MG16-004 and MG16-005) and Ambaritsatrana (MG16-010). Symptoms correspond on a severe ascendant wilt of the leaves, associated with necrosis of the inflorescences and absence of nuts and death of all trees was confirmed eventually. We investigated the implication of phytoplasma because of the apparent similarity in the symptomatology with Coconut Lethal Yellowing Disease and Coconut Lethal Decline occurring in East Africa (Mpunami et al., 1999), and because the western coast of Madagascar faces the Mozambican channel only 400 km apart from areas along the East African coast where those two diseases occur. Symptomatic (n=4) and asymptomatic (n=6) coconut trees were sampled by stem drilling. DNA was extracted from sawdust samples using a modified CTAB protocol (Mpunami et al., 1999). A direct polymerase chain reaction (PCR) targeting the 16S rRNA gene plus Internal transcribed spacer with the P1-1T (AAGAGTTTGATCCTGGCTCAGGAT)/P7 primers (Schneider et al., 1998) amplified a product of about 1.8 kb for MG16-001 and MG16-005 samples only, while the four DNA extracts from symptomatic trees showed a 1.2 kb amplicon by nested PCR using R16F2n/R16R2 primer pairs in the second round (Lee et al., 1998). Amplification of the secA gene using the primer pair secAFor1/secARev3 (Hodgetts et al., 2008) was performed in a single round and gave a product of 850 bp exclusively for the symptomatic tree DNAs. All amplicons were double strand sequenced (Genewiz, UK). Corresponding high quality sequences were deposited in GenBank and submitted to Blastn on NCBI. The partial 16S rRNA gene sequences (accessions MN264629 to MN264632) obtained using R16F2n/R16R2 primers presented the highest similarity (from 99.47 to 99.56%) to the reference sequence for the phytoplasma associated with the Tanzanian Lethal Decline (GenBank accession X80117). This genetic proximity of the Malagasy strains was confirmed by the partial secA gene sequences (accessions MN267853 to MN267856) presenting the highest similarity (from 89.92 to 90.70%) to the Tanzanian Lethal Decline phytoplasma secA gene partial sequence (Genbank accession KJ462071). Full-length 16S rRNA gene sequences of MG16-001 and MG16-005 strains (accessions MN388765 and MN388766) were submitted to iPhyClassifier virtual RFLP tool (Zhao et al., 2009). The iPhyClassifier tool confirmed that Malagasy strains are related to the reference strain X80117 but belong to a different 16Sr subgroup (similarity coefficient from 0.90 to 0.93, Dev. 1). Both Malagassy strains and LDT phytoplasma should be assigned to a new 16Sr group since X80117 is itself erroneously assigned to 16SrIV group while the closest reference sequence AF509322, 16SrXXIV-A, shared only a similarity of 0.83 (Dev. 1). Occurrence of a phytoplasma associated with a lethal yellowing type syndrome in Madagascar could represent a dangerous threat to coconut crops that play an important socio-economic role in the coastal areas, but also to the many endemic palm species already on high extinction risk.

scholarly journals Rumen Epithelial Communities Share a Core Bacterial Microbiota: A Meta-Analysis of 16S rRNA Gene Illumina MiSeq Sequencing Datasets

2021 ◽  
Vol 12 ◽  
Author(s):  
Chiron J. Anderson ◽  
Lucas R. Koester ◽  
Stephan Schmitz-Esser
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Host Species ◽  
De Novo ◽  
Management Practice ◽  
Meta Analysis ◽  
Illumina Miseq ◽  
Rumen Content ◽  
Rrna Gene ◽  
The Core

In this meta-analysis, 17 rumen epithelial 16S rRNA gene Illumina MiSeq amplicon sequencing data sets were analyzed to identify a core rumen epithelial microbiota and core rumen epithelial OTUs shared between the different studies included. Sequences were quality-filtered and screened for chimeric sequences before performing closed-reference 97% OTU clustering, and de novo 97% OTU clustering. Closed-reference OTU clustering identified the core rumen epithelial OTUs, defined as any OTU present in ≥ 80% of the samples, while the de novo data was randomly subsampled to 10,000 reads per sample to generate phylum- and genus-level distributions and beta diversity metrics. 57 core rumen epithelial OTUs were identified including metabolically important taxa such as Ruminococcus, Butyrivibrio, and other Lachnospiraceae, as well as sulfate-reducing bacteria Desulfobulbus and Desulfovibrio. Two Betaproteobacteria OTUs (Neisseriaceae and Burkholderiaceae) were core rumen epithelial OTUs, in contrast to rumen content where previous literature indicates they are rarely found. Two core OTUs were identified as the methanogenic archaea Methanobrevibacter and Methanomethylophilaceae. These core OTUs are consistently present across the many variables between studies which include different host species, geographic region, diet, age, farm management practice, time of year, hypervariable region sequenced, and more. When considering only cattle samples, the number of core rumen epithelial OTUs expands to 147, highlighting the increased similarity within host species despite geographical location and other variables. De novo OTU clustering revealed highly similar rumen epithelial communities, predominated by Firmicutes, Bacteroidetes, and Proteobacteria at the phylum level which comprised 79.7% of subsampled sequences. The 15 most abundant genera represented an average of 54.5% of sequences in each individual study. These abundant taxa broadly overlap with the core rumen epithelial OTUs, with the exception of Prevotellaceae which were abundant, but not identified within the core OTUs. Our results describe the core and abundant bacteria found in the rumen epithelial environment and will serve as a basis to better understand the composition and function of rumen epithelial communities.

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