scholarly journals Complementing 16S rRNA Gene Amplicon Sequencing with Total Bacterial Load To Infer Absolute Species Concentrations in the Vaginal Microbiome

mSystems ◽  
2020 ◽  
Vol 5 (2) ◽  
Author(s):  
Florencia A. Tettamanti Boshier ◽  
Sujatha Srinivasan ◽  
Anthony Lopez ◽  
Noah G. Hoffman ◽  
Sean Proll ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Relative Abundance ◽  
Bacterial Species ◽  
Bacterial Load ◽  
Amplicon Sequencing ◽  
Individual Species ◽  
Rrna Gene ◽  
Vaginal Microbiome ◽  
Bacterial Concentrations

ABSTRACT Whereas 16S rRNA gene amplicon sequencing quantifies relative abundances of bacterial taxa, variation in total bacterial load between samples restricts its ability to reflect absolute concentrations of individual bacterial species. Quantitative PCR (qPCR) can quantify individual species, but it is not practical to develop a suite of qPCR assays for every bacterium present in a diverse sample. We sought to determine the accuracy of an inferred measure of bacterial concentration using total bacterial load and relative abundance. We analyzed 1,320 samples from 20 women with a history of frequent bacterial vaginosis who self-collected vaginal swabs daily over 60 days. We inferred bacterial concentrations by taking the product of species relative abundance (assessed by 16S rRNA gene amplicon sequencing) and bacterial load (measured by broad-range 16S rRNA gene qPCR). Log10-converted inferred concentrations correlated with targeted qPCR (r = 0. 935, P < 2.2e–16) for seven key bacterial species. The mean inferred concentration error varied across bacteria, with rarer bacteria associated with larger errors. A total of 92% of the >0.5-log10 errors occurred when the relative abundance was <10%. Many errors occurred during early bacterial expansion from or late contraction to low abundance. When the relative abundance of a species is >10%, inferred concentrations are reliable proxies for targeted qPCR in the vaginal microbiome. However, targeted qPCR is required to capture bacteria at low relative abundance and is preferable for characterizing growth and decay kinetics of single species. IMPORTANCE Microbiome studies primarily use 16S rRNA gene amplicon sequencing to assess the relative abundance of bacterial taxa in a community. However, these measurements do not accurately reflect absolute taxon concentrations. We sought to determine whether the product of species’ relative abundance and total bacterial load measured by broad-range qPCR is an accurate proxy for individual species’ concentrations, as measured by taxon-specific qPCR assays. Overall, the inferred bacterial concentrations were a reasonable proxy of species-specific qPCR values, particularly when bacteria are present at a higher relative abundance. This approach offers an opportunity to assess the concentrations of bacterial species and how they change in a community over time without developing individual qPCR assays for each taxon.

scholarly journals Complementing 16S rRNA gene amplicon sequencing with estimates of total bacterial load to infer absolute species concentrations in the vaginal microbiome

2019 ◽  
Author(s):  
Florencia Tettamanti Boshier ◽  
Sujatha Srinivasan ◽  
Anthony Lopez ◽  
Noah G. Hoffman ◽  
Sean Proll ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Bacterial Vaginosis ◽  
Relative Abundance ◽  
Bacterial Species ◽  
Bacterial Load ◽  
Amplicon Sequencing ◽  
Individual Species ◽  
Rrna Gene ◽  
Associated Bacteria

Whereas 16S rRNA gene amplicon sequencing quantifies relative abundances of bacterial taxa, variation in total bacterial load between samples restricts its ability to reflect absolute concentration of individual species. Quantitative PCR (qPCR) can quantify individual species, but it is not practical to develop a suite of qPCR assays for every bacterium present in a diverse sample. We analyzed 1320 samples from 20 women with a history of frequent bacterial vaginosis, who self-collected vaginal swabs daily over 60 days. We inferred bacterial concentrations by taking the product of species relative abundance (assessed by 16S rRNA gene amplicon sequencing) and total bacterial load (measured by broad-range 16S rRNA gene qPCR). Log10-converted inferred concentrations correlated with targeted qPCR (r = 0. 935, p<2.2e-16) for seven key bacterial species. The mean inferred concentration error varied across bacteria, with rarer bacterial vaginosis-associated bacteria associated with larger errors. 92% of errors >0.5 log10 occurred when relative abundance was <10%. Many errors occurred during early bacterial expansion or late contraction. When relative abundance of a species is >10%, inferred concentrations are reliable proxies for targeted qPCR. However, targeted qPCR is required to capture bacteria at low relative abundance, particularly with BV-associated bacteria during the early onset of bacterial vaginosis.

scholarly journals PSXIV-23 Characterization of microbial communities associated with the rumen lining, digesta and rumen fluid from beef cattle consuming a high energy diet using 16S rRNA gene amplicon sequencing

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 446-446
Author(s):  
Arquimides Reyes ◽  
Margaret Weinroth ◽  
Cory Wolfe ◽  
Robert Delmore ◽  
Terry Engle ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Beef Cattle ◽  
Microbial Communities ◽  
Relative Abundance ◽  
Rumen Fluid ◽  
Amplicon Sequencing ◽  
High Energy ◽  
Feedlot Cattle ◽  
Rrna Gene

Abstract The true etiology of liver abscesses is not well known. Therefore, the objective of this study was to characterize the microbial communities in the rumen lining, digesta, and rumen fluid from beef cattle consuming a high energy diet, using 16S rRNA gene amplicon sequencing. Twelve crossbred feedlot steers (450 ±10 kg; ~ 3.0 years of age) fitted with ruminal fistulas, consuming a high energy finishing diet (1.43 NEg, Mcal/kg DM) for 21 d were utilized in this experiment. Microbial DNA from three regions within the rumen [rumen lining (ventral/lateral), digesta (geometric center of the rumen), and rumen fluid] was extracted and the V4 region of the 16S rRNA gene was amplified and sequenced. Across all sample regions, bacterial sequences were classified into 34 phyla, 76 classes, 143 orders, and 254 families. Bacteroidetes and Firmicutes were the predominant phyla present across all samples. The relative abundance of Bacteroidetes detected in rumen fluid was lesser (P &lt; 0.05) when compared to bacteria sampled from the rumen lining and digesta. In contrast, the relative abundance of Firmicutes were greater (P &lt; 0.05) in rumen fluid and the rumen lining when compared to digesta samples. There are very few publications describing the complex community of the rumen microbiome. To our knowledge this is the first publication categorizing microbial populations in three distinct locations within the rumen using next generation sequencing in feedlot cattle.

scholarly journals Engineering CRISPR/Cas9 to mitigate abundant host contamination for 16S rRNA gene-based amplicon sequencing

Microbiome ◽  
2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Luyang Song ◽  
Kabin Xie
Keyword(s):  
Bacterial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
High Throughput Sequencing ◽  
Bacterial Species ◽  
Amplicon Sequencing ◽  
16S Rrna Genes ◽  
Rrna Genes ◽  
Rrna Gene ◽  
Plant Microbiota

Abstract Background High-throughput sequencing of bacterial 16S rRNA gene (16S-seq) is a useful and common method for studying bacterial community structures. However, contamination of the 16S rRNA genes from the mitochondrion and plastid hinders the sensitive bacterial 16S-seq in plant microbiota profiling, especially for some plant species such as rice. To date, efficiently mitigating such host contamination without a bias is challenging in 16S rRNA gene-based amplicon sequencing. Results We developed Cas-16S-seq method to reduce abundant host contamination for plant microbiota profiling. This method utilizes the Cas9 nuclease and specific guide RNA (gRNA) to cut 16S rRNA targets during library construction, thereby removing host contamination in 16S-seq. We used rice as an example to validate the feasibility and effectiveness of Cas-16S-seq. We established a bioinformatics pipeline to design gRNAs that specifically target rice 16S rRNA genes without bacterial 16S rRNA off-targets. We compared the effectiveness of Cas-16S-seq with that of the commonly used 16S-seq method for artificially mixed 16S rRNA gene communities, paddy soil, rice root, and phyllosphere samples. The results showed that Cas-16S-seq substantially reduces the fraction of rice 16S rRNA gene sequences from 63.2 to 2.9% in root samples and from 99.4 to 11.6% in phyllosphere samples on average. Consequently, Cas-16S-seq detected more bacterial species than the 16S-seq in plant samples. Importantly, when analyzing soil samples, Cas-16S-seq and 16S-seq showed almost identical bacterial communities, suggesting that Cas-16S-seq with host-specific gRNAs that we designed has no off-target in rice microbiota profiling. Conclusion Our Cas-16S-seq can efficiently remove abundant host contamination without a bias for 16S rRNA gene-based amplicon sequencing, thereby enabling deeper bacterial community profiling with a low cost and high flexibility. Thus, we anticipate that this method would be a useful tool for plant microbiomics.

16S rRNA gene microbial analysis of the skin of fleece rot resistant and susceptible sheep

2007 ◽  
Vol 58 (7) ◽  
pp. 739 ◽  
Author(s):  
T. J. Dixon ◽  
S. I. Mortimer ◽  
B. J. Norris
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Current Knowledge ◽  
Sequence Similarity ◽  
Bacterial Species ◽  
Bacterial Load ◽  
Molecular Genetic Analysis ◽  
Future Research ◽  
Rrna Gene ◽  
Major Interest

Fleece rot is a bacterial dermatitis that follows prolonged wetting of the sheep’s skin, and a major pre-disposing condition to body strike in the Australian Merino. Several studies have examined bacterial load of the fleece in relation to fleece rot using traditional culture-based techniques focussing on only a few bacterial species. We examined the natural bacterial diversity of the healthy sheep skin and changes that occurred in fleece-rot resistant and susceptible animals during fleece rot development. Presented is a preliminary molecular genetic analysis of the bacterial ecology of the sheep skin. Eight 16S rRNA gene libraries were constructed from susceptible and resistant sheep both before and after onset of the disease following induction by simulated rainfall. Approximately 75% of the sequences obtained in this study have not been previously identified in fleece-rot studies. Four operational taxonomic units (OTU; groups of >97% sequence similarity) of major interest were present on susceptible animals and absent from resistant animals. Data on these OTU expand current knowledge of bacteria involved in inflammation and wounding of sheep skin tissue, and provide direction for future research that may lead to new treatment options for fleece rot and body strike.

scholarly journals An inter-laboratory study to investigate the impact of the bioinformatics component on microbiome analysis using mock communities

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Denise M. O’Sullivan ◽  
Ronan M. Doyle ◽  
Sasithon Temisak ◽  
Nicholas Redshaw ◽  
Alexandra S. Whale ◽  
...  
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Relative Abundance ◽  
Amplicon Sequencing ◽  
16S Rrna Genes ◽  
Rrna Genes ◽  
Rrna Gene ◽  
Microbiome Analysis ◽  
The Impact

AbstractDespite the advent of whole genome metagenomics, targeted approaches (such as 16S rRNA gene amplicon sequencing) continue to be valuable for determining the microbial composition of samples. Amplicon microbiome sequencing can be performed on clinical samples from a normally sterile site to determine the aetiology of an infection (usually single pathogen identification) or samples from more complex niches such as human mucosa or environmental samples where multiple microorganisms need to be identified. The methodologies are frequently applied to determine both presence of micro-organisms and their quantity or relative abundance. There are a number of technical steps required to perform microbial community profiling, many of which may have appreciable precision and bias that impacts final results. In order for these methods to be applied with the greatest accuracy, comparative studies across different laboratories are warranted. In this study we explored the impact of the bioinformatic approaches taken in different laboratories on microbiome assessment using 16S rRNA gene amplicon sequencing results. Data were generated from two mock microbial community samples which were amplified using primer sets spanning five different variable regions of 16S rRNA genes. The PCR-sequencing analysis included three technical repeats of the process to determine the repeatability of their methods. Thirteen laboratories participated in the study, and each analysed the same FASTQ files using their choice of pipeline. This study captured the methods used and the resulting sequence annotation and relative abundance output from bioinformatic analyses. Results were compared to digital PCR assessment of the absolute abundance of each target representing each organism in the mock microbial community samples and also to analyses of shotgun metagenome sequence data. This ring trial demonstrates that the choice of bioinformatic analysis pipeline alone can result in different estimations of the composition of the microbiome when using 16S rRNA gene amplicon sequencing data. The study observed differences in terms of both presence and abundance of organisms and provides a resource for ensuring reproducible pipeline development and application. The observed differences were especially prevalent when using custom databases and applying high stringency operational taxonomic unit (OTU) cut-off limits. In order to apply sequencing approaches with greater accuracy, the impact of different analytical steps needs to be clearly delineated and solutions devised to harmonise microbiome analysis results.

scholarly journals Much ado about nothing? Off-target amplification can lead to false-positive bacterial brain microbiome detection in healthy and Parkinson’s disease individuals

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Janis R. Bedarf ◽  
Naiara Beraza ◽  
Hassan Khazneh ◽  
Ezgi Özkurt ◽  
David Baker ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
False Positive ◽  
Gene Sequencing ◽  
Bacterial Biomass ◽  
16S Rrna Gene Sequencing ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Rrna Gene Sequencing

Abstract Background Recent studies suggested the existence of (poly-)microbial infections in human brains. These have been described either as putative pathogens linked to the neuro-inflammatory changes seen in Parkinson’s disease (PD) and Alzheimer’s disease (AD) or as a “brain microbiome” in the context of healthy patients’ brain samples. Methods Using 16S rRNA gene sequencing, we tested the hypothesis that there is a bacterial brain microbiome. We evaluated brain samples from healthy human subjects and individuals suffering from PD (olfactory bulb and pre-frontal cortex), as well as murine brains. In line with state-of-the-art recommendations, we included several negative and positive controls in our analysis and estimated total bacterial biomass by 16S rRNA gene qPCR. Results Amplicon sequencing did detect bacterial signals in both human and murine samples, but estimated bacterial biomass was extremely low in all samples. Stringent reanalyses implied bacterial signals being explained by a combination of exogenous DNA contamination (54.8%) and false positive amplification of host DNA (34.2%, off-target amplicons). Several seemingly brain-enriched microbes in our dataset turned out to be false-positive signals upon closer examination. We identified off-target amplification as a major confounding factor in low-bacterial/high-host-DNA scenarios. These amplified human or mouse DNA sequences were clustered and falsely assigned to bacterial taxa in the majority of tested amplicon sequencing pipelines. Off-target amplicons seemed to be related to the tissue’s sterility and could also be found in independent brain 16S rRNA gene sequences. Conclusions Taxonomic signals obtained from (extremely) low biomass samples by 16S rRNA gene sequencing must be scrutinized closely to exclude the possibility of off-target amplifications, amplicons that can only appear enriched in biological samples, but are sometimes assigned to bacterial taxa. Sequences must be explicitly matched against any possible background genomes present in large quantities (i.e., the host genome). Using close scrutiny in our approach, we find no evidence supporting the hypothetical presence of either a brain microbiome or a bacterial infection in PD brains.

scholarly journals Handling of spurious sequences affects the outcome of high-throughput 16S rRNA gene amplicon profiling

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Sandra Reitmeier ◽  
Thomas C. A. Hitch ◽  
Nicole Treichel ◽  
Nikolaos Fikas ◽  
Bela Hausmann ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Diversity Analysis ◽  
Careful Attention ◽  
Operational Taxonomic Units ◽  
Basic Concepts ◽  
Gnotobiotic Mice ◽  
Mock Communities

Abstract16S rRNA gene amplicon sequencing is a popular approach for studying microbiomes. However, some basic concepts have still not been investigated comprehensively. We studied the occurrence of spurious sequences using defined microbial communities based on data either from the literature or generated in three sequencing facilities and analyzed via both operational taxonomic units (OTUs) and amplicon sequence variants (ASVs) approaches. OTU clustering and singleton removal, a commonly used approach, delivered approximately 50% (mock communities) to 80% (gnotobiotic mice) spurious taxa. The fraction of spurious taxa was generally lower based on ASV analysis, but varied depending on the gene region targeted and the barcoding system used. A relative abundance of 0.25% was found as an effective threshold below which the analysis of spurious taxa can be prevented to a large extent in both OTU- and ASV-based analysis approaches. Using this cutoff improved the reproducibility of analysis, i.e., variation in richness estimates was reduced by 38% compared with singleton filtering using six human fecal samples across seven sequencing runs. Beta-diversity analysis of human fecal communities was markedly affected by both the filtering strategy and the type of phylogenetic distances used for comparison, highlighting the importance of carefully analyzing data before drawing conclusions on microbiome changes. In summary, handling of artifact sequences during bioinformatic processing of 16S rRNA gene amplicon data requires careful attention to avoid the generation of misleading findings. We propose the concept of effective richness to facilitate the comparison of alpha-diversity across studies.

scholarly journals Detection of Legionella species, the influence of precipitation on the amount of Legionella DNA, and bacterial microbiome in aerosols from outdoor sites near asphalt roads in Toyama Prefecture, Japan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jun-ichi Kanatani ◽  
Masanori Watahiki ◽  
Keiko Kimata ◽  
Tomoko Kato ◽  
Kaoru Uchida ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Indoor Environment ◽  
Geometric Mean ◽  
Amplicon Sequencing ◽  
Positive Sample ◽  
Outdoor Environment ◽  
Rrna Gene ◽  
Total Precipitation ◽  
Monthly Total Precipitation

Abstract Background Legionellosis is caused by the inhalation of aerosolized water contaminated with Legionella bacteria. In this study, we investigated the prevalence of Legionella species in aerosols collected from outdoor sites near asphalt roads, bathrooms in public bath facilities, and other indoor sites, such as buildings and private homes, using amoebic co-culture, quantitative PCR, and 16S rRNA gene amplicon sequencing. Results Legionella species were not detected by amoebic co-culture. However, Legionella DNA was detected in 114/151 (75.5%) air samples collected near roads (geometric mean ± standard deviation: 1.80 ± 0.52 log10 copies/m3), which was comparable to the numbers collected from bathrooms [15/21 (71.4%), 1.82 ± 0.50] but higher than those collected from other indoor sites [11/30 (36.7%), 0.88 ± 0.56] (P < 0.05). The amount of Legionella DNA was correlated with the monthly total precipitation (r = 0.56, P < 0.01). It was also directly and inversely correlated with the daily total precipitation for seven days (r = 0.21, P = 0.01) and one day (r = − 0.29, P < 0.01) before the sampling day, respectively. 16S rRNA gene amplicon sequencing revealed that Legionella species were detected in 9/30 samples collected near roads (mean proportion of reads, 0.11%). At the species level, L. pneumophila was detected in 2/30 samples collected near roads (the proportion of reads, 0.09 and 0.11% of the total reads number in each positive sample). The three most abundant bacterial genera in the samples collected near roads were Sphingomonas, Streptococcus, and Methylobacterium (mean proportion of reads; 21.1%, 14.6%, and 1.6%, respectively). In addition, the bacterial diversity in outdoor environment was comparable to that in indoor environment which contains aerosol-generating features and higher than that in indoor environment without the features. Conclusions DNA from Legionella species was widely present in aerosols collected from outdoor sites near asphalt roads, especially during the rainy season. Our findings suggest that there may be a risk of exposure to Legionella species not only in bathrooms but also in the areas surrounding asphalt roads. Therefore, the possibility of contracting legionellosis in daily life should be considered.

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.

scholarly journals Phylogenetic Diversity and Molecular Detection of Bacteria in Gull Feces

2008 ◽  
Vol 74 (13) ◽  
pp. 3969-3976 ◽  
Author(s):  
Jingrang Lu ◽  
Jorge W. Santo Domingo ◽  
Regina Lamendella ◽  
Thomas Edge ◽  
Stephen Hill
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Phylogenetic Diversity ◽  
Bacterial Species ◽  
Rrna Gene ◽  
Fecal Dna ◽  
Environmental Waters ◽  
Potential Risks ◽  
Species Specific ◽  
Gut Microbial Community

ABSTRACT In spite of increasing public health concerns about the potential risks associated with swimming in waters contaminated with waterfowl feces, little is known about the composition of the gut microbial community of aquatic birds. To address this, a gull 16S rRNA gene clone library was developed and analyzed to determine the identities of fecal bacteria. Analysis of 282 16S rRNA gene clones demonstrated that the gull gut bacterial community is mostly composed of populations closely related to Bacilli (37%), Clostridia (17%), Gammaproteobacteria (11%), and Bacteriodetes (1%). Interestingly, a considerable number of sequences (i.e., 26%) were closely related to Catellicoccus marimammalium, a gram-positive, catalase-negative bacterium. To determine the occurrence of C. marimammalium in waterfowl, species-specific 16S rRNA gene PCR and real-time assays were developed and used to test fecal DNA extracts from different bird (n = 13) and mammal (n = 26) species. The results showed that both assays were specific to gull fecal DNA and that C. marimammalium was present in gull fecal samples collected from the five locations in North America (California, Georgia, Ohio, Wisconsin, and Toronto, Canada) tested. Additionally, 48 DNA extracts from waters collected from six sites in southern California, Great Lakes in Michigan, Lake Erie in Ohio, and Lake Ontario in Canada presumed to be impacted with gull feces were positive by the C. marimammalium assay. Due to the widespread presence of this species in gulls and environmental waters contaminated with gull feces, targeting this bacterial species might be useful for detecting gull fecal contamination in waterfowl-impacted waters.

Sign in / Sign up

Export Citation Format

Share Document