scholarly journals A comprehensive automated pipeline for human microbiome sampling, 16S rRNA gene sequencing and bioinformatics processing

2018 ◽  
Author(s):  
LW Hugerth ◽  
M Seifert ◽  
AAL Pennhag ◽  
J Du ◽  
MC Hamsten ◽  
...  
Keyword(s):  
Dna Extraction ◽  
Large Scale ◽  
Human Microbiome ◽  
Population Level ◽  
16S Rrna Gene Sequencing ◽  
Extraction Methods ◽  
Storage Conditions ◽  
Rrna Gene ◽  
Sample Collection ◽  
Dna Extraction Methods

ABSTRACTThe advent of affordable high-throughput DNA sequencing has opened up a golden age of studies in the human microbiome. In order to understand the role of the human microbiota, standardized methods for large-scale, population-level studies are needed to avoid underpowered or poorly designed studies. The biggest bottlenecks to population-level microbiomics are sample collection, storage and DNA extraction. Here, we describe a flexible automated approach to process intestinal biopsies, fecal samples and vaginal swabs from sample collection to OTU table. We have evaluated storage conditions, DNA extraction methods, PCR strategies and bioinformatic pipelines for these three sample types, and present here a set of guidelines and best practices for each of these steps.

scholarly journals Toward standards in clinical microbiome studies: comparison of three DNA extraction methods and two bioinformatic pipelines

2019 ◽  
Author(s):  
Q.R. Ducarmon ◽  
B.V.H. Hornung ◽  
A.R. Geelen ◽  
E.J. Kuijper ◽  
R.D. Zwittink
Keyword(s):  
Dna Extraction ◽  
Extraction Method ◽  
Bacterial Biomass ◽  
Extraction Methods ◽  
Rrna Gene ◽  
Method Choice ◽  
Advantages And Disadvantages ◽  
Dna Extraction Method ◽  
Dna Extraction Methods ◽  
Negative Controls

ABSTRACTWhen studying the microbiome using next generation sequencing, DNA extraction method, sequencing procedures and bioinformatic processing are crucial to obtain reliable data. Method choice has been demonstrated to strongly affect the final biological interpretation. We assessed the performance of three DNA extraction methods and two bioinformatic pipelines for bacterial microbiota profiling through 16S rRNA gene amplicon sequencing, using positive and negative controls for DNA extraction and sequencing, and eight different types of high- or low-biomass samples. Performance was evaluated based on quality control passing, DNA yield, richness, diversity and compositional profiles. All DNA extraction methods retrieved the theoretical relative bacterial abundance with maximum three-fold change, although differences were seen between methods, and library preparation and sequencing induced little variation. Bioinformatic pipelines showed different results for estimating richness, but diversity and compositional profiles were comparable. DNA extraction methods were successful for feces and oral swabs and variation induced by DNA extraction methods was lower than inter-subject (biological) variation. For low-biomass samples, a mixture of genera present in negative controls and sample-specific genera, possibly representing biological signal, were observed. We conclude that the tested bioinformatic pipelines perform equally with pipeline-specific advantages and disadvantages. Two out of three extraction methods performed equally well, while one method was less accurate regarding retrieval of compositional profiles. Lastly, we demonstrate the importance of including negative controls when analyzing low bacterial biomass samples.IMPORTANCEMethod choice throughout the workflow of a microbiome study, from sample collection to DNA extraction and sequencing procedures, can greatly affect results. This study evaluated three different DNA extraction methods and two bioinformatic pipelines by including positive and negative controls, and various biological specimens. By identifying an optimal combination of DNA extraction method and bioinformatic pipeline use, we hope to contribute to increased methodological consistency in microbiome studies. Our methods were not only applied to commonly studied samples for microbiota analysis, e.g. feces, but also for more rarely studied, low-biomass samples. Microbiota composition profiles of low-biomass samples (e.g. urine and tumor biopsies) were not always distinguishable from negative controls, or showed partial overlap, confirming the importance of including negative controls in microbiome studies, especially when low bacterial biomass is expected.

scholarly journals Bacterial communities associated with cell phones and shoes

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9235
Author(s):  
David A. Coil ◽  
Russell Y. Neches ◽  
Jenna M. Lang ◽  
Guillaume Jospin ◽  
Wendy E. Brown ◽  
...  
Keyword(s):  
Large Scale ◽  
Cell Phones ◽  
Human Microbiome ◽  
16S Rrna Gene Sequencing ◽  
The United States ◽  
Oral Microbiome ◽  
Rrna Gene ◽  
Sporting Events ◽  
Rrna Gene Sequencing ◽  
Source And Sink

Background Every human being carries with them a collection of microbes, a collection that is likely both unique to that person, but also dynamic as a result of significant flux with the surrounding environment. The interaction of the human microbiome (i.e., the microbes that are found directly in contact with a person in places such as the gut, mouth, and skin) and the microbiome of accessory objects (e.g., shoes, clothing, phones, jewelry) is of potential interest to both epidemiology and the developing field of microbial forensics. Therefore, the microbiome of personal accessories are of interest because they serve as both a microbial source and sink for an individual, they may provide information about the microbial exposure experienced by an individual, and they can be sampled non-invasively. Findings We report here a large-scale study of the microbiome found on cell phones and shoes. Cell phones serve as a potential source and sink for skin and oral microbiome, while shoes can act as sampling devices for microbial environmental experience. Using 16S rRNA gene sequencing, we characterized the microbiome of thousands of paired sets of cell phones and shoes from individuals at sporting events, museums, and other venues around the United States. Conclusions We place this data in the context of previous studies and demonstrate that the microbiome of phones and shoes are different. This difference is driven largely by the presence of “environmental” taxa (taxa from groups that tend to be found in places like soil) on shoes and human-associated taxa (taxa from groups that are abundant in the human microbiome) on phones. This large dataset also contains many novel taxa, highlighting the fact that much of microbial diversity remains uncharacterized, even on commonplace objects.

scholarly journals DNA extraction for human microbiome studies: the issue of standardization

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
K. Leigh Greathouse ◽  
Rashmi Sinha ◽  
Emily Vogtmann
Keyword(s):  
Dna Extraction ◽  
Human Microbiome ◽  
Extraction Methods ◽  
Minimum Standard ◽  
Dna Extraction Methods ◽  
Processing Steps

Abstract Among the laboratory and bioinformatic processing steps for human microbiome studies, a lack of consistency in DNA extraction methodologies is hindering the ability to compare results between studies and sometimes leading to errant conclusions. The purpose of this article is to highlight the issues related to DNA extraction methods and to suggest minimum standard requirements that should be followed to ensure consistency and reproducibility.

scholarly journals Development and Evaluation of PCR Assays for the Detection of Paenibacillus larvae in Honey Samples: Comparison with Isolation and Biochemical Characterization

2003 ◽  
Vol 69 (3) ◽  
pp. 1504-1510 ◽  
Author(s):  
Tamás Bakonyi ◽  
Irmgard Derakhshifar ◽  
Elvira Grabensteiner ◽  
Norbert Nowotny
Keyword(s):  
Dna Extraction ◽  
Large Scale ◽  
Biochemical Characterization ◽  
Direct Detection ◽  
Extraction Methods ◽  
Proteinase K ◽  
Paenibacillus Larvae ◽  
Lower Sensitivity ◽  
Pcr Assays ◽  
Dna Extraction Methods

ABSTRACT PCR assays were developed for the direct detection of Paenibacillus larvae in honey samples and compared with isolation and biochemical characterization procedures. Different primer pairs, designed from the 16S rRNA and the metalloproteinase precursor gene regions, and different DNA extraction methods were tested and compared. The sensitivity of the reactions was evaluated by serial dilutions of DNA extracts obtained from P. larvae cultures. The specificity of the primers was assessed by analyzing related Paenibacillus and Bacillus strains isolated from honey. The PCR assays also amplified these related bacteria, but at lower sensitivity. In the next step, the PCR assays were applied to contaminated honey and other bee products originating from 15 countries. Lysozyme treatment followed by proteinase K digestion was determined to be the best DNA extraction method for P. larvae spores. The most sensitive primer pair detected P. larvae in 18 of 23 contaminated honey samples, as well as in pollen, wax, and brood. Honey specimens containing saprophyte bacilli and paenibacilli, but not P. larvae, were PCR negative. Although the isolation and biochemical identification method (BioLog) showed higher sensitivity and specificity, PCR proved to be a valuable technique for large-scale screening of honey samples for American foulbrood, especially considering its rapidity and moderate costs.

scholarly journals Toward Standards in Clinical Microbiota Studies: Comparison of Three DNA Extraction Methods and Two Bioinformatic Pipelines

mSystems ◽  
2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Q. R. Ducarmon ◽  
B. V. H. Hornung ◽  
A. R. Geelen ◽  
E. J. Kuijper ◽  
R. D. Zwittink
Keyword(s):  
Dna Extraction ◽  
Extraction Method ◽  
Bacterial Biomass ◽  
Extraction Methods ◽  
Rrna Gene ◽  
Method Choice ◽  
Advantages And Disadvantages ◽  
Dna Extraction Method ◽  
Dna Extraction Methods ◽  
Negative Controls

ABSTRACT When studying the microbiome using next-generation sequencing, the DNA extraction method, sequencing procedures, and bioinformatic processing are crucial to obtain reliable data. Method choice has been demonstrated to strongly affect the final biological interpretation. We assessed the performance of three DNA extraction methods and two bioinformatic pipelines for bacterial microbiota profiling through 16S rRNA gene amplicon sequencing, using positive and negative controls for DNA extraction and sequencing and eight different types of high- or low-biomass samples. Performance was evaluated based on quality control passing, DNA yield, richness, diversity, and compositional profiles. All DNA extraction methods retrieved the theoretical relative bacterial abundance with a maximum 3-fold change, although differences were seen between methods, and library preparation and sequencing induced little variation. Bioinformatic pipelines showed different results for observed richness, but diversity and compositional profiles were comparable. DNA extraction methods were successful for feces and oral swabs, and variation induced by DNA extraction methods was lower than intersubject (biological) variation. For low-biomass samples, a mixture of genera present in negative controls and sample-specific genera, possibly representing biological signal, were observed. We conclude that the tested bioinformatic pipelines perform equally, with pipeline-specific advantages and disadvantages. Two out of three extraction methods performed equally well, while one method was less accurate regarding retrieval of compositional profiles. Lastly, we again demonstrate the importance of including negative controls when analyzing low-bacterial-biomass samples. IMPORTANCE Method choice throughout the workflow of a microbiome study, from sample collection to DNA extraction and sequencing procedures, can greatly affect results. This study evaluated three different DNA extraction methods and two bioinformatic pipelines by including positive and negative controls and various biological specimens. By identifying an optimal combination of DNA extraction method and bioinformatic pipeline use, we hope to contribute to increased methodological consistency in microbiota studies. Our methods were applied not only to commonly studied samples for microbiota analysis, e.g., feces, but also to more rarely studied, low-biomass samples. Microbiota composition profiles of low-biomass samples (e.g., urine and tumor biopsy specimens) were not always distinguishable from negative controls, or showed partial overlap, confirming the importance of including negative controls in microbiota studies, especially when low bacterial biomass is expected.

scholarly journals Comparative investigation of DNA extraction methods in black gram (Vigna mungo (L.)

2019 ◽  
Author(s):  
M. . Prakash ◽  
B. . Priyadharshini ◽  
M. . Vignesh ◽  
R. . Anandan
Keyword(s):  
Dna Extraction ◽  
Extraction Method ◽  
Large Scale ◽  
Dna Isolation ◽  
Extraction Methods ◽  
Comparative Investigation ◽  
Black Gram ◽  
Dna Extraction Method ◽  
Ctab Method ◽  
Dna Extraction Methods

Isolation of intact, double stranded, pure and non- contaminated genomic DNA is prerequisite for large scale genotyping analysis including DNA-banks. Three methods of DNA isolation (Dellaporta, CTAB and Hi-PurAg DNA isolation kits) from 25 black gram genotypes were compared in terms of the yield, purity, integrity, and stability of extracted DNA. Purity and quantification of isolated DNA samples was confirmed by using the UV nano-spectrophotometer at OD260/280 and the same is confirmed based by agarose gel electrophoresis. The CTAB method showed the best results followed by Hi-PurAg and Dellaporta method. The CTAB DNA extraction method was found to be the most efficient DNA extraction method, capable of providing high quality, pure and stable DNA and could be used for various molecular related works. All the 25 black gram genotypes for this research gave good yield of DNA from the established modified CTAB protocol.

scholarly journals The colorectal cancer-associated faecal microbiome of developing countries resembles that of developed countries

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Caroline Young ◽  
Henry M. Wood ◽  
Ramakrishnan Ayloor Seshadri ◽  
Pham Van Nang ◽  
Carlos Vaccaro ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Developing Countries ◽  
Large Scale ◽  
Room Temperature ◽  
16S Rrna Gene Sequencing ◽  
Occult Blood ◽  
Developed Countries ◽  
Rrna Gene ◽  
Sample Collection ◽  
Faecal Microbiome

Abstract Background The incidence of colorectal cancer (CRC) is increasing in developing countries, yet limited research on the CRC- associated microbiota has been conducted in these areas, in part due to scarce resources, facilities, and the difficulty of fresh or frozen stool storage/transport. Here, we aimed (1) to establish a broad representation of diverse developing countries (Argentina, Chile, India, and Vietnam); (2) to validate a ‘resource-light’ sample-collection protocol translatable in these settings using guaiac faecal occult blood test (gFOBT) cards stored and, importantly, shipped internationally at room temperature; (3) to perform initial profiling of the collective CRC-associated microbiome of these developing countries; and (4) to compare this quantitatively with established CRC biomarkers from developed countries. Methods We assessed the effect of international storage and transport at room temperature by replicating gFOBT from five UK volunteers, storing two in the UK, and sending replicates to institutes in the four countries. Next, to determine the effect of prolonged UK storage, DNA extraction replicates for a subset of samples were performed up to 252 days apart. To profile the CRC-associated microbiome of developing countries, gFOBT were collected from 41 treatment-naïve CRC patients and 40 non-CRC controls from across the four institutes, and V4 16S rRNA gene sequencing was performed. Finally, we constructed a random forest (RF) model that was trained and tested against existing datasets from developed countries. Results The microbiome was stably assayed when samples were stored/transported at room temperature and after prolonged UK storage. Large-scale microbiome structure was separated by country and continent, with a smaller effect from CRC. Importantly, the RF model performed similarly to models trained using external datasets and identified similar taxa of importance (Parvimonas, Peptostreptococcus, Fusobacterium, Alistipes, and Escherichia). Conclusions This study demonstrates that gFOBT, stored and transported at room temperature, represents a suitable method of faecal sample collection for amplicon-based microbiome biomarkers in developing countries and suggests a CRC-faecal microbiome association that is consistent between developed and developing countries.

scholarly journals Associations Between Dysmenorrhea Symptom-Based Phenotypes and Vaginal Microbiome: A Pilot Study

2020 ◽  
pp. 109980042097960
Author(s):  
Chen X. Chen ◽  
Janet S. Carpenter ◽  
Tabitha Murphy ◽  
Patricia Brooks ◽  
J. Dennis Fortenberry
Keyword(s):  
Young Adults ◽  
Gut Microbiome ◽  
Treatment Options ◽  
Human Microbiome ◽  
16S Rrna Gene Sequencing ◽  
Adolescents And Young Adults ◽  
Rrna Gene ◽  
Sample Collection ◽  
Microbiome Research ◽  
Prospective Longitudinal

Human microbiome research provides rich opportunities to elucidate factors influencing health, uncover novel biomarkers, and expand disease treatment options. A well-conducted microbiome study depends not only on a rigorous design but also on successfully engaging participants in collecting quality samples. In this paper, we aim to describe (1) strategies our team used to engage adolescents and young adults in vaginal and gut microbiome sample self-collection and (2) their effectiveness. In our prospective, longitudinal, feasibility study of 20 female adolescents and young adults, research participants self-collected vaginal and gut microbiome samples at home. Using a participatory and iterative process, we developed strategies to engage participants in sample self-collection, including (1) providing clear instructions to ensure comprehension and buy-in, (2) providing a user-friendly take-home package, (3) minimizing disgust/embarrassment associated with sample collection, and (4) follow-up communications to facilitate sample collections and return. With these strategies, we achieved 100% participant retention and 100% sample return rates. All samples ( n = 80, 100%) were usable for downstream 16s rRNA gene sequencing and analysis. All participants rated the study procedures as acceptable, and qualitative data showed that strategies were well received by participants. This study suggests that carefully planning and implementing strategies to engage participants in sample self-collection can result in high degrees of participant compliance, sample quality, and participant satisfaction in microbiome research.

Quantifying technical confounders in microbiome studies

2020 ◽  
Author(s):  
Theda U P Bartolomaeus ◽  
Till Birkner ◽  
Hendrik Bartolomaeus ◽  
Ulrike Löber ◽  
Ellen G Avery ◽  
...  
Keyword(s):  
Dna Extraction ◽  
Human Microbiome ◽  
Alpha Diversity ◽  
Extraction Methods ◽  
Intestinal Microbiome ◽  
Interindividual Differences ◽  
Microbiome Composition ◽  
Technical Developments ◽  
Dna Extraction Methods ◽  
The Impact

Abstract Aims Recent technical developments have allowed the study of the human microbiome to accelerate at an unprecedented pace. Methodological differences may have considerable impact on the results obtained. Thus, we investigated how different storage, isolation, and DNA extraction methods can influence the characterization of the intestinal microbiome, compared to the impact of true biological signals such as intraindividual variability, nutrition, health, and demographics. Methods and results An observative cohort study in 27 healthy subjects was performed. Participants were instructed to collect stool samples twice spaced by a week, using six different methods (naive and Zymo DNA/RNA Shield on dry ice, OMNIgene GUT, RNALater, 95% ethanol, Zymo DNA/RNA Shield at room temperature). DNA extraction from all samples was performed comparatively using QIAamp Power Fecal and ZymoBIOMICS DNA Kits. 16S rRNA sequencing of the gut microbiota as well as qPCRs were performed on the isolated DNA. Metrics included alpha diversity as well as multivariate and univariate comparisons of samples, controlling for covariate patterns computationally. Interindividual differences explained 7.4% of overall microbiome variability, whereas the choice of DNA extraction method explained a further 5.7%. At phylum level, the tested kits differed in their recovery of Gram-positive bacteria, which is reflected in a significantly skewed enterotype distribution. Conclusion DNA extraction methods had the highest impact on observed microbiome variability, and were comparable to interindividual differences, thus may spuriously mimic the microbiome signatures of various health and nutrition factors. Conversely, collection methods had a relatively small influence on microbiome composition. The present study provides necessary insight into the technical variables which can lead to divergent results from seemingly similar study designs. We anticipate that these results will contribute to future efforts towards standardization of microbiome quantification procedures in clinical research.

Sign in / Sign up

Export Citation Format

Share Document