The Impact of Primer Design on Amplicon-Based Metagenomic Profiling Accuracy: Detailed Insights into Bifidobacterial Community Structure

Next Generation Sequencing (NGS) technologies have overcome the limitations of cultivation-dependent approaches and allowed detailed study of bacterial populations that inhabit the human body. The consortium of bacteria residing in the human intestinal tract, also known as the gut microbiota, impacts several physiological processes important for preservation of the health status of the host. The most widespread microbiota profiling method is based on amplification and sequencing of a variable portion of the 16S rRNA gene as a universal taxonomic marker among members of the Bacteria domain. Despite its popularity and obvious advantages, this 16S rRNA gene-based approach comes with some important limitations. In particular, the choice of the primer pair for amplification plays a major role in defining the accuracy of the reconstructed bacterial profiles. In the current study, we performed an in silico PCR using all currently described 16S rRNA gene-targeting primer pairs (PP) in order to assess their efficiency. Our results show that V3, V4, V5, and V6 were the optimal regions on which to design 16S rRNA metagenomic primers. In detail, PP39 (Probio_Uni/Probio_Rev), PP41 (341F/534R), and PP72 (970F/1050R) were the most suitable primer pairs with an amplification efficiency of >98.5%. Furthermore, the Bifidobacterium genus was examined as a test case for accurate evaluation of intra-genus performances at subspecies level. Intriguingly, the in silico analysis revealed that primer pair PP55 (527f/1406r) was unable to amplify the targeted region of any member of this bacterial genus, while several other primer pairs seem to rather inefficiently amplify the target region of the main bifidobacterial taxa. These results highlight that selection of a 16S rRNA gene-based PP should be done with utmost care in order to avoid biases in microbiota profiling results.

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Empirical Testing of 16S rRNA Gene PCR Primer Pairs Reveals Variance in Target Specificity and Efficacy Not Suggested by In Silico Analysis

Applied and Environmental Microbiology ◽

10.1128/aem.02166-08 ◽

2009 ◽

Vol 75 (9) ◽

pp. 2677-2683 ◽

Cited By ~ 58

Author(s):

Sergio E. Morales ◽

William E. Holben

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Quantitative Pcr ◽

In Silico ◽

In Silico Analysis ◽

Rrna Genes ◽

Rrna Gene ◽

Empirical Testing ◽

Specific Target ◽

Silico Analysis

ABSTRACT Phylogenetic and “fingerprinting” analyses of the 16S rRNA genes of prokaryotes have been a mainstay of microbial ecology during the last two decades. However, many methods and results from studies that rely on the 16S rRNA gene for detection and quantification of specific microbial taxa have seemingly received only cursory or even no validation. To directly examine the efficacy and specificity of 16S rRNA gene-based primers for phylum-, class-, and operational taxonomic unit-specific target amplification in quantitative PCR, we created a collection of primers based solely on an extensive soil bacterial 16S rRNA gene clone library containing ∼5,000 sequences from a single soil sample (i.e., a closed site-specific library was used to create PCR primers for use at this site). These primers were initially tested in silico prior to empirical testing by PCR amplification of known target sequences and of controls based on disparate phylogenetic groups. Although all primers were highly specific according to the in silico analysis, the empirical analyses clearly exhibited a high degree of nonspecificity for many of the phyla or classes, while other primers proved to be highly specific. These findings suggest that significant care must be taken when interpreting studies whose results were obtained with target specific primers that were not adequately validated, especially where population densities or dynamics have been inferred from the data. Further, we suggest that the reliability of quantification of specific target abundance using 16S rRNA-based quantitative PCR is case specific and must be determined through rigorous empirical testing rather than solely in silico.

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In silico analysis of the 16S rRNA gene of endophytic bacteria, isolated from the aerial parts and seeds of important agricultural crops

Genetics and Molecular Research ◽

10.4238/2015.august.19.3 ◽

2015 ◽

Vol 14 (3) ◽

pp. 9703-9721 ◽

Cited By ~ 10

Author(s):

C. Bredow ◽

J.L. Azevedo ◽

J.A. Pamphile ◽

C.A. Mangolin ◽

S.A. Rhoden

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

In Silico ◽

Endophytic Bacteria ◽

In Silico Analysis ◽

Rrna Gene ◽

Agricultural Crops ◽

Aerial Parts ◽

The 16S Rrna Gene ◽

Silico Analysis

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Exploring protocol bias in airway microbiome studies: one versus two PCR steps and 16S rRNA gene region V3 V4 versus V4

BMC Genomics ◽

10.1186/s12864-020-07252-z ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Christine Drengenes ◽

Tomas M. L. Eagan ◽

Ingvild Haaland ◽

Harald G. Wiker ◽

Rune Nielsen

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Bacterial Load ◽

Marker Gene ◽

Gene Region ◽

Lower Airway ◽

Rrna Gene ◽

Wide Range ◽

Airway Microbiome ◽

The Impact

Abstract Background Studies on the airway microbiome have been performed using a wide range of laboratory protocols for high-throughput sequencing of the bacterial 16S ribosomal RNA (16S rRNA) gene. We sought to determine the impact of number of polymerase chain reaction (PCR) steps (1- or 2- steps) and choice of target marker gene region (V3 V4 and V4) on the presentation of the upper and lower airway microbiome. Our analyses included lllumina MiSeq sequencing following three setups: Setup 1 (2-step PCR; V3 V4 region), Setup 2 (2-step PCR; V4 region), Setup 3 (1-step PCR; V4 region). Samples included oral wash, protected specimen brushes and protected bronchoalveolar lavage (healthy and obstructive lung disease), and negative controls. Results The number of sequences and amplicon sequence variants (ASV) decreased in order setup1 > setup2 > setup3. This trend appeared to be associated with an increased taxonomic resolution when sequencing the V3 V4 region (setup 1) and an increased number of small ASVs in setups 1 and 2. The latter was considered a result of contamination in the two-step PCR protocols as well as sequencing across multiple runs (setup 1). Although genera Streptococcus, Prevotella, Veillonella and Rothia dominated, differences in relative abundance were observed across all setups. Analyses of beta-diversity revealed that while oral wash samples (high biomass) clustered together regardless of number of PCR steps, samples from the lungs (low biomass) separated. The removal of contaminants identified using the Decontam package in R, did not resolve differences in results between sequencing setups. Conclusions Differences in number of PCR steps will have an impact of final bacterial community descriptions, and more so for samples of low bacterial load. Our findings could not be explained by differences in contamination levels alone, and more research is needed to understand how variations in PCR-setups and reagents may be contributing to the observed protocol bias.

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Soil aggregate-based nucleic acid analyses of the impact of maize roots and their root hairs on the structural diversity of microbial communities

10.5194/egusphere-egu21-7620 ◽

2021 ◽

Author(s):

Christoph Tebbe ◽

Damini Damini ◽

Damien Finn ◽

Nataliya Bilyera ◽

Minh Ganther ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Root Hair ◽

Soil Aggregates ◽

Root Hairs ◽

Soil Samples ◽

Plant Roots ◽

Bulk Soil ◽

Rrna Gene ◽

The Impact

The deposition of energy rich carbon sources released by plant roots during their growth fuels microbially driven ecosystem processes in soil, but there is a lack of understanding how microorganisms interact and collaborate. The objective of this research was therefore to characterize microbial networks as they assemble under the influence of plant roots. To identify the specific importance of root hairs, we compared the impact of a maize wild-type to a root-air defective mutant (rth3; (1).The microbial community structure was analyzed by qPCR and 16S rRNA gene amplicon sequencing from soil DNA. In order to increase the probability of detecting truly interacting microbial partners as a basis for network analyses, we first evaluated a new protocol to obtain DNA from as little as 1 mg instead of the usual 250 mg soil samples, thereby approaching the aggregate level (2). While the diversity of bacterial 16S rRNA gene amplicons of 250-mg samples taken from the same soil was not distinct, DNA analyses from individual aggregates clearly differed from each other underlining that soil aggregates represent distinct microbial habitats.Soil column experiments with maize grown in a loam soil (3) revealed distinct communities between rhizosphere and bulk soil. The community composition of individual aggregates showed more differences in bulk soil compared to rhizosphere. Less elaborated networks were seen in bulk soil and a profound effect of root hairs could be unravelled. Null model testing demonstrated that Actinobacteria were equally important for network connectivity independent of the root hair mutation, but for networks of the wildtype, Acidobacteria were essential for synergistic interactions and overall network structure. In contrast, Proteobacteria and Firmicutes connectivity became more important. The observed differences in community composition and interactions suggests carbon cycling, and perhaps other microbially-driven functions, are markedly affected by the presence of root hairs.Utilizing maize root soil microcosms for studying soil zymography in the rhizosphere allowed to obtain soil samples from regions with distinct specific enzyme activities. In order to enhance the detection of actively metabolizing bacterial community members, we studied rRNA sequences and compared it to rRNA gene sequences from the same samples. Currently the data are under analysis.References(1) Wen, T-J, Schnable PS (1994) Analyses of mutants of three genes that influence root hair development in Zea mays (Gramineae) suggest that root hairs are dispensable. Am. J. Bot. 81, 833&#8211;842.(2) Szoboszlay M, Tebbe CC (2020) Hidden heterogeneity and co-occurrence networks of soil prokaryotic communities revealed at the scale of individual soil aggregates. Microbiol. Open, e1144. DOI: 10.1002/mbo3.1144(3) Vetterlein D et al. (2020) Experimental platforms for the investigation of spatiotemporal patterns in the rhizosphere &#8211; laboratory and field scale. J. Plant Nutr. Soil Sci., 000, 1&#8211;16 DOI: 10.1002/jpln.202000079

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Gut Microbiota Analysis Results Are Highly Dependent on the 16S rRNA Gene Target Region, Whereas the Impact of DNA Extraction Is Minor

Journal of Biomolecular Techniques JBT ◽

10.7171/jbt.17-2801-003 ◽

2017 ◽

Vol 28 (1) ◽

pp. 19-30 ◽

Cited By ~ 64

Author(s):

Anniina Rintala ◽

Sami Pietilä ◽

Eveliina Munukka ◽

Erkki Eerola ◽

Juha-Pekka Pursiheimo ◽

...

Keyword(s):

16S Rrna ◽

Gut Microbiota ◽

16S Rrna Gene ◽

Dna Extraction ◽

Rrna Gene ◽

Gene Target ◽

Target Region ◽

Microbiota Analysis ◽

The Impact ◽

The 16S Rrna Gene

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Direct Quantification of Campylobacter jejuni and Campylobacter lanienae in Feces of Cattle by Real-Time Quantitative PCR

Applied and Environmental Microbiology ◽

10.1128/aem.70.4.2296-2306.2004 ◽

2004 ◽

Vol 70 (4) ◽

pp. 2296-2306 ◽

Cited By ~ 77

Author(s):

G. Douglas Inglis ◽

Lisa D. Kalischuk

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Real Time ◽

Campylobacter Jejuni ◽

Single Copy ◽

Mitigation Strategies ◽

Rrna Gene ◽

Limit Of Quantification ◽

Cattle Feces ◽

The Impact

ABSTRACT Campylobacter species are fastidious to culture, and the ability to directly quantify biomass in microbiologically complex substrates using real-time quantitative (RTQ) PCR may enhance our understanding of their biology and facilitate the development of efficacious mitigation strategies. This study reports the use of nested RTQ-PCR to directly quantify Campylobacter jejuni and Campylobacter lanienae in cattle feces. For C. jejuni, the single-copy mapA gene was selected. For C. lanienae, the three-copy 16S rRNA gene was targeted. RTQ-PCR primers were tested alone or they were nested with species-specific primers, and amplification products were detected using the intercalating dye SYBR Green. Nesting did not increase the specificity or sensitivity of C. jejuni quantification, and the limit of quantification was 19 to 25 genome copies (≈3 × 103 CFU/g of feces). In contrast, nested RTQ-PCR was necessary to confer specificity on C. lanienae by targeting the 16S rRNA gene. The limit of quantification was 1.8 genome copies (≈250 CFU/g of feces), and there was no discernible difference between the two C. lanienae secondary primer sets evaluated. Detection and quantification of C. jejuni in naturally infested cattle feces by RTQ-PCR were comparable to the results of culture-based methods. In contrast, culturing did not detect C. lanienae in 6 of 10 fecal samples positive for the bacterium and substantially underestimated cell densities relative to nested RTQ-PCR. The results of this study illustrate that RTQ-PCR can be used to directly quantify campylobacters, including very fastidious species, in a microbiologically and chemically complex substrate. Furthermore, targeting of a multicopy universal gene provided highly sensitive quantification of C. lanienae, but nested RTQ-PCR was necessary to confer specificity. This method will facilitate subsequent studies to elucidate the impact of this group of bacteria within the gastrointestinal tracts of livestock and studies of the factors that influence colonization success and shedding.

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