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1.
BMC Bioinformatics ; 25(1): 189, 2024 May 14.
Article in English | MEDLINE | ID: mdl-38745271

ABSTRACT

BACKGROUND: The selection of primer pairs in sequencing-based research can greatly influence the results, highlighting the need for a tool capable of analysing their performance in-silico prior to the sequencing process. We therefore propose PrimerEvalPy, a Python-based package designed to test the performance of any primer or primer pair against any sequencing database. The package calculates a coverage metric and returns the amplicon sequences found, along with information such as their average start and end positions. It also allows the analysis of coverage for different taxonomic levels. RESULTS: As a case study, PrimerEvalPy was used to test the most commonly used primers in the literature against two oral 16S rRNA gene databases containing bacteria and archaea. The results showed that the most commonly used primer pairs in the oral cavity did not match those with the highest coverage. The best performing primer pairs were found for the detection of oral bacteria and archaea. CONCLUSIONS: This demonstrates the importance of a coverage analysis tool such as PrimerEvalPy to find the best primer pairs for specific niches. The software is available under the MIT licence at https://gitlab.citius.usc.es/lara.vazquez/PrimerEvalPy .


Subject(s)
Archaea , Bacteria , DNA Primers , Microbiota , RNA, Ribosomal, 16S , Software , Microbiota/genetics , RNA, Ribosomal, 16S/genetics , Bacteria/genetics , Bacteria/classification , Archaea/genetics , DNA Primers/metabolism , DNA Primers/genetics , Humans , Mouth/microbiology , Computer Simulation
3.
Microbiome ; 11(1): 58, 2023 03 23.
Article in English | MEDLINE | ID: mdl-36949474

ABSTRACT

BACKGROUND: Sequencing has been widely used to study the composition of the oral microbiome present in various health conditions. The extent of the coverage of the 16S rRNA gene primers employed for this purpose has not, however, been evaluated in silico using oral-specific databases. This paper analyses these primers using two databases containing 16S rRNA sequences from bacteria and archaea found in the human mouth and describes some of the best primers for each domain. RESULTS: A total of 369 distinct individual primers were identified from sequencing studies of the oral microbiome and other ecosystems. These were evaluated against a database reported in the literature of 16S rRNA sequences obtained from oral bacteria, which was modified by our group, and a self-created oral archaea database. Both databases contained the genomic variants detected for each included species. Primers were evaluated at the variant and species levels, and those with a species coverage (SC) ≥75.00% were selected for the pair analyses. All possible combinations of the forward and reverse primers were identified, with the resulting 4638 primer pairs also evaluated using the two databases. The best bacteria-specific pairs targeted the 3-4, 4-7, and 3-7 16S rRNA gene regions, with SC levels of 98.83-97.14%; meanwhile, the optimum archaea-specific primer pairs amplified regions 5-6, 3-6, and 3-6, with SC estimates of 95.88%. Finally, the best pairs for detecting both domains targeted regions 4-5, 3-5, and 5-9, and produced SC values of 95.71-94.54% and 99.48-96.91% for bacteria and archaea, respectively. CONCLUSIONS: Given the three amplicon length categories (100-300, 301-600, and >600 base pairs), the primer pairs with the best coverage values for detecting oral bacteria were as follows: KP_F048-OP_R043 (region 3-4; primer pair position for Escherichia coli J01859.1: 342-529), KP_F051-OP_R030 (4-7; 514-1079), and KP_F048-OP_R030 (3-7; 342-1079). For detecting oral archaea, these were as follows: OP_F066-KP_R013 (5-6; 784-undefined), KP_F020-KP_R013 (3-6; 518-undefined), and OP_F114-KP_R013 (3-6; 340-undefined). Lastly, for detecting both domains jointly they were KP_F020-KP_R032 (4-5; 518-801), OP_F114-KP_R031 (3-5; 340-801), and OP_F066-OP_R121 (5-9; 784-1405). The primer pairs with the best coverage identified herein are not among those described most widely in the oral microbiome literature. Video Abstract.


Subject(s)
Archaea , Microbiota , Humans , Archaea/genetics , RNA, Ribosomal, 16S/genetics , Genes, rRNA , DNA Primers/genetics , Bacteria/genetics , Microbiota/genetics , High-Throughput Nucleotide Sequencing/methods , Phylogeny
4.
Microbiol Spectr ; : e0439822, 2023 Feb 13.
Article in English | MEDLINE | ID: mdl-36779795

ABSTRACT

This study aimed to evaluate the number of 16S rRNA genes in the complete genomes of the bacterial and archaeal species inhabiting the human mouth and to assess how the use of different primer pairs would affect the detection and classification of redundant amplicons and matching amplicons (MAs) from different taxa. A total of 518 oral-bacterial and 191 oral-archaeal complete genomes were downloaded from the NCBI database, and their complete 16S rRNA genes were extracted. The numbers of genes and variants per genome were calculated. Next, 39 primer pairs were used to search for matches in the genomes and obtain amplicons. For each primer, we calculated the number of gene amplicons, variants, genomes, and species detected and the percentage of coverage at the species level with no MAs (SC-NMA). The results showed that 94.09% of oral bacteria and 52.59% of oral archaea had more than one intragenomic 16S rRNA gene. From 1.29% to 46.70% of bacterial species and from 4.65% to 38.89% of archaea detected by the primers had MAs. The best primers were the following (SC-NMA; region; position for Escherichia coli [GenBank version no. J01859.1]): KP_F048-OP_R030 for bacteria (93.55%; V3 to V7; 342 to 1079), KP_F018-KP_R063 for archaea (89.63%; V3 to V9; undefined to 1506), and OP_F114-OP_R121 for both domains (92.52%; V3 to V9; 340 to 1405). In addition to 16S rRNA gene redundancy, the presence of MAs must be controlled to ensure an accurate interpretation of microbial diversity data. The SC-NMA is a more useful parameter than the conventional coverage percentage for selecting the best primer pairs. The pairs used the most in the oral microbiome literature were not among the best performers. IMPORTANCE Hundreds of publications have studied the oral microbiome through 16S rRNA gene sequencing. However, none have assessed the number of 16S rRNA genes in the genomes of oral microbes, or how the use of primer pairs targeting different regions affects the detection of MAs from different taxa. Here, we found that almost all oral bacteria and more than half of oral archaea have more than one intragenomic 16S rRNA gene. The performance of the primer pairs in not detecting MAs increases as the length of the amplicon augments. As none of those most employed in the oral literature were among the best performers, we selected a series of primers to detect bacteria and/or archaea based on their percentage of species detected without MAs. The intragenomic 16S rRNA gene redundancy and the presence of MAs between distinct taxa need to be considered to ensure an accurate interpretation of microbial diversity data.

5.
Front Cell Infect Microbiol ; 11: 770668, 2021.
Article in English | MEDLINE | ID: mdl-35223533

ABSTRACT

Although clustering by operational taxonomic units (OTUs) is widely used in the oral microbial literature, no research has specifically evaluated the extent of the limitations of this sequence clustering-based method in the oral microbiome. Consequently, our objectives were to: 1) evaluate in-silico the coverage of a set of previously selected primer pairs to detect oral species having 16S rRNA sequence segments with ≥97% similarity; 2) describe oral species with highly similar sequence segments and determine whether they belong to distinct genera or other higher taxonomic ranks. Thirty-nine primer pairs were employed to obtain the in-silico amplicons from the complete genomes of 186 bacterial and 135 archaeal species. Each fasta file for the same primer pair was inserted as subject and query in BLASTN for obtaining the similarity percentage between amplicons belonging to different oral species. Amplicons with 100% alignment coverage of the query sequences and with an amplicon similarity value ≥97% (ASI97) were selected. For each primer, the species coverage with no ASI97 (SC-NASI97) was calculated. Based on the SC-NASI97 parameter, the best primer pairs were OP_F053-KP_R020 for bacteria (region V1-V3; primer pair position for Escherichia coli J01859.1: 9-356); KP_F018-KP_R002 for archaea (V4; undefined-532); and OP_F114-KP_R031 for both (V3-V5; 340-801). Around 80% of the oral-bacteria and oral-archaea species analyzed had an ASI97 with at least one other species. These very similar species play different roles in the oral microbiota and belong to bacterial genera such as Campylobacter, Rothia, Streptococcus and Tannerella, and archaeal genera such as Halovivax, Methanosarcina and Methanosalsum. Moreover, ~20% and ~30% of these two-by-two similarity relationships were established between species from different bacterial and archaeal genera, respectively. Even taxa from distinct families, orders, and classes could be grouped in the same possible OTU. Consequently, regardless of the primer pair used, sequence clustering with a 97% similarity provides an inaccurate description of oral-bacterial and oral-archaeal species, which can greatly affect microbial diversity parameters. As a result, OTU clustering conditions the credibility of associations between some oral species and certain health and disease conditions. This significantly limits the comparability of the microbial diversity findings reported in oral microbiome literature.


Subject(s)
Microbiota , Archaea/genetics , High-Throughput Nucleotide Sequencing/methods , Humans , Microbiota/genetics , Phylogeny , RNA, Ribosomal, 16S/genetics , Sequence Analysis, DNA/methods
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