scholarly journals A Comprehensive Evaluation of Enterobacteriaceae Primer Sets for Analysis of Host-Associated Microbiota

Pathogens ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 17
Author(s):  
Carolina N. Resendiz-Nava ◽  
Hilda V. Silva-Rojas ◽  
Angel Rebollar-Alviter ◽  
Dulce M. Rivera-Pastrana ◽  
Edmundo M. Mercado-Silva ◽  
...  
Keyword(s):  
Performance Analysis ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Comprehensive Evaluation ◽  
Data Interpretation ◽  
Rrna Gene ◽  
Lack Of Information ◽  
Primer Sets ◽  
The Impact ◽  
Bacterial Groups

Enterobacteriaceae is one of the most important bacterial groups within the Proteobacteria phylum. This bacterial group includes pathogens, commensal and beneficial populations. Numerous 16S rRNA gene PCR-based assays have been designed to analyze Enterobacteriaceae diversity and relative abundance, and, to the best of our knowledge, 16 primer pairs have been validated, published and used since 2003. Nonetheless, a comprehensive performance analysis of these primer sets has not yet been carried out. This information is of particular importance due to the recent taxonomic restructuration of Enterobacteriaceae into seven bacterial families. To overcome this lack of information, the identified collection of primer pairs (n = 16) was subjected to primer performance analysis using multiple bioinformatics tools. Herein it was revealed that, based on specificity and coverage of the 16S rRNA gene, these 16 primer sets could be divided into different categories: Enterobacterales-, multi-family-, multi-genus- and Enterobacteriaceae-specific primers. These results highlight the impact of taxonomy changes on performance of molecular assays and data interpretation. Moreover, they underline the urgent need to revise and update the molecular tools used for molecular microbial analyses.

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

BMC Genomics ◽  
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.

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

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

<p>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).</p><p>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.</p><p>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.</p><p>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.</p><p>References</p><p>(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, 833–842.</p><p>(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</p><p>(3) Vetterlein D et al. (2020) Experimental platforms for the investigation of spatiotemporal patterns in the rhizosphere – laboratory and field scale. J. Plant Nutr. Soil Sci., 000, 1–16 DOI: 10.1002/jpln.202000079</p>

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

2020 ◽  
Vol 8 (1) ◽  
pp. 131 ◽  
Author(s):  
Leonardo Mancabelli ◽  
Christian Milani ◽  
Gabriele Andrea Lugli ◽  
Federico Fontana ◽  
Francesca Turroni ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
In Silico ◽  
In Silico Analysis ◽  
Amplification Efficiency ◽  
Rrna Gene ◽  
Test Case ◽  
Bacterial Populations ◽  
Taxonomic Marker ◽  
The Impact

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.

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

2017 ◽  
Vol 28 (1) ◽  
pp. 19-30 ◽  
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

A PCR-based specific assay reveals a population of bacteria within the Chloroflexi associated with the reductive dehalogenation of polychlorinated biphenyls

Microbiology ◽  
2005 ◽  
Vol 151 (6) ◽  
pp. 2039-2046 ◽  
Author(s):  
Joy E. M. Watts ◽  
Sonja K. Fagervold ◽  
Harold D. May ◽  
Kevin R. Sowers
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Polychlorinated Biphenyls ◽  
Reductive Dehalogenation ◽  
Rrna Gene ◽  
Gene Sequences ◽  
16S Rrna Gene Sequences ◽  
Specific Pcr ◽  
Pure Cultures ◽  
Primer Sets

Polychlorinated biphenyls (PCBs) accumulate and persist in sediments posing a risk to human health and the environment. Highly chlorinated PCBs are reductively dechlorinated in anaerobic sediments and two bacteria, designated o-17 and DF-1, from a novel phylogenetic group that reductively dechlorinate PCBs have recently been identified. However, there is a paucity of knowledge about the distribution, diversity and ecology of PCB-dechlorinating bacteria due to difficulty in obtaining pure cultures and the lack of detection by universal PCR 16S rRNA gene primer sets in sediments. A specific PCR primer was developed and optimized for detection of o-17/DF-1 and other closely related bacteria in the environment. Using this primer set it was determined that bacteria of this group were enriched in sediment microcosms from Baltimore Harbour concurrent with active dechlorination of 2,2′,3,4,4′,5′-hexachlorobiphenyl. Additional 16S rRNA gene sequences that had high levels of similarity to described PCB dechlorinators were detected in sediments from the Elizabeth River tributary of Chesapeake Bay, which had confirmed PCB-dechlorinating activities. Phylogenetic comparison of these detected 16S rRNA gene sequences revealed a relatively diverse group of organisms within the dehalogenating Chloroflexi that are distinct from the Dehalococcoides spp. Results from this study indicate that reductive PCB dechlorination activity may be catalysed by a previously undescribed group of micro-organisms that appear to be prevalent in PCB-impacted sites.

scholarly journals Quantitative Real-Time Legionella PCR for Environmental Water Samples: Data Interpretation

2006 ◽  
Vol 72 (4) ◽  
pp. 2801-2808 ◽  
Author(s):  
Philippe Joly ◽  
Pierre-Alain Falconnet ◽  
Janine André ◽  
Nicole Weill ◽  
Monique Reyrolle ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Legionella Pneumophila ◽  
Cooling Tower ◽  
Water System ◽  
Data Interpretation ◽  
Environmental Water ◽  
Hot Water ◽  
Rrna Gene ◽  
Conventional Culture

ABSTRACT Quantitative Legionella PCRs targeting the 16S rRNA gene (specific for the genus Legionella) and the mip gene (specific for the species Legionella pneumophila) were applied to a total of 223 hot water system samples (131 in one laboratory and 92 in another laboratory) and 37 cooling tower samples (all in the same laboratory). The PCR results were compared with those of conventional culture. 16S rRNA gene PCR results were nonquantifiable for 2.8% of cooling tower samples and up to 39.1% of hot water system samples, and this was highly predictive of Legionella CFU counts below 250/liter. PCR cutoff values for identifying hot water system samples containing >103 CFU/liter legionellae were determined separately in each laboratory. The cutoffs differed widely between the laboratories and had sensitivities from 87.7 to 92.9% and specificities from 77.3 to 96.5%. The best specificity was obtained with mip PCR. PCR cutoffs could not be determined for cooling tower samples, as the results were highly variable and often high for culture-negative samples. Thus, quantitative Legionella PCR appears to be applicable to samples from hot water systems, but the positivity cutoff has to be determined in each laboratory.

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

2004 ◽  
Vol 70 (4) ◽  
pp. 2296-2306 ◽  
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.

scholarly journals 16S rRNA Gene Metabarcoding Indicates Species-Characteristic Microbiomes in Deep-Sea Benthic Foraminifera

2021 ◽  
Vol 12 ◽  
Author(s):  
Iines S. Salonen ◽  
Panagiota-Myrsini Chronopoulou ◽  
Hidetaka Nomaki ◽  
Dewi Langlet ◽  
Masashi Tsuchiya ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Deep Sea ◽  
Benthic Fauna ◽  
Rrna Gene ◽  
Symbiotic Relationships ◽  
Foraminiferal Species ◽  
Trophic Preferences ◽  
The Family ◽  
Bacterial Groups

Foraminifera are unicellular eukaryotes that are an integral part of benthic fauna in many marine ecosystems, including the deep sea, with direct impacts on benthic biogeochemical cycles. In these systems, different foraminiferal species are known to have a distinct vertical distribution, i.e., microhabitat preference, which is tightly linked to the physico-chemical zonation of the sediment. Hence, foraminifera are well-adapted to thrive in various conditions, even under anoxia. However, despite the ecological and biogeochemical significance of foraminifera, their ecology remains poorly understood. This is especially true in terms of the composition and diversity of their microbiome, although foraminifera are known to harbor diverse endobionts, which may have a significant meaning to each species’ survival strategy. In this study, we used 16S rRNA gene metabarcoding to investigate the microbiomes of five different deep-sea benthic foraminiferal species representing differing microhabitat preferences. The microbiomes of these species were compared intra- and inter-specifically, as well as with the surrounding sediment bacterial community. Our analysis indicated that each species was characterized with a distinct, statistically different microbiome that also differed from the surrounding sediment community in terms of diversity and dominant bacterial groups. We were also able to distinguish specific bacterial groups that seemed to be strongly associated with particular foraminiferal species, such as the family Marinilabiliaceae for Chilostomella ovoidea and the family Hyphomicrobiaceae for Bulimina subornata and Bulimina striata. The presence of bacterial groups that are tightly associated to a certain foraminiferal species implies that there may exist unique, potentially symbiotic relationships between foraminifera and bacteria that have been previously overlooked. Furthermore, the foraminifera contained chloroplast reads originating from different sources, likely reflecting trophic preferences and ecological characteristics of the different species. This study demonstrates the potential of 16S rRNA gene metabarcoding in resolving the microbiome composition and diversity of eukaryotic unicellular organisms, providing unique in situ insights into enigmatic deep-sea ecosystems.

scholarly journals Quantitative PCR provides a simple and accessible method for quantitative microbiome profiling

2018 ◽  
Author(s):  
Ching Jian ◽  
Panu Luukkonen ◽  
Hannele Yki-Järvinen ◽  
Anne Salonen ◽  
Katri Korpela
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Quantitative Pcr ◽  
Rrna Gene ◽  
Microbial Community Structures ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Bacterial Groups ◽  
Microbiome Profiling ◽  
Generation Sequencing

AbstractThe use of relative next generation sequencing (NGS) abundance data can lead to misinterpretations of microbial community structures as the increase of one taxon leads to concurrent decrease of the other(s). To overcome compositionality, we provide a quantitative NGS solution, which is achieved by adjusting the relative 16S rRNA gene amplicon NGS data with quantitative PCR (qPCR-based) total bacterial counts. By comparing the enumeration of dominant bacterial groups on different taxonomic levels in human fecal samples using taxon-specific 16S rRNA gene-targeted qPCR we show that quantitative NGS is able to estimate absolute bacterial abundances accurately. We also observed a higher degree of correspondence in the estimated microbe-metabolite relationship when quantitative NGS was applied. Being conceptually and methodologically analogous to amplicon-based NGS, our qPCR-based method can be readily incorporated into the standard, high-throughput NGS sample processing pipeline for more accurate description of interactions within and between the microbes and host.

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