Inconsistent Patterns of Microbial Diversity and Composition Between Highly Similar Sequencing Protocols: A Case Study With Reef-Building Corals

16S rRNA gene profiling (amplicon sequencing) is a popular technique for understanding host-associated and environmental microbial communities. Most protocols for sequencing amplicon libraries follow a standardized pipeline that can differ slightly depending on laboratory facility and user. Given that the same variable region of the 16S gene is targeted, it is generally accepted that sequencing output from differing protocols are comparable and this assumption underlies our ability to identify universal patterns in microbial dynamics through meta-analyses. However, discrepant results from a combined 16S rRNA gene dataset prepared by two labs whose protocols differed only in DNA polymerase and sequencing platform led us to scrutinize the outputs and challenge the idea of confidently combining them for standard microbiome analysis. Using technical replicates of reef-building coral samples from two species, Montipora aequituberculata and Porites lobata, we evaluated the consistency of alpha and beta diversity metrics between data resulting from these highly similar protocols. While we found minimal variation in alpha diversity between platform, significant differences were revealed with most beta diversity metrics, dependent on host species. These inconsistencies persisted following removal of low abundance taxa and when comparing across higher taxonomic levels, suggesting that bacterial community differences associated with sequencing protocol are likely to be context dependent and difficult to correct without extensive validation work. The results of this study encourage caution in the statistical comparison and interpretation of studies that combine rRNA gene sequence data from distinct protocols and point to a need for further work identifying mechanistic causes of these observed differences.

Download Full-text

Microbial community composition and diversity via 16S rRNA gene amplicons: evaluating the Illumina platform

10.1101/010058 ◽

2014 ◽

Cited By ~ 2

Author(s):

Lucas Sinclair ◽

Omneya Ahmed Osman ◽

Stefan Bertilsson ◽

Alexander Eiler

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Beta Diversity ◽

Sequence Data ◽

Soda Lakes ◽

Microbial Community Composition ◽

Rrna Gene ◽

Clustering Methods ◽

Illumina Platform ◽

Alpha And Beta Diversity

As new sequencing technologies become cheaper and older ones disappear, laboratories switch vendors and platforms. Validating the new setups is a crucial part of conducting rigorous scientific research. Here we report on the reliability and biases of performing bacterial 16S rRNA gene amplicon paired-end sequencing on the MiSeq Illumina platform. We designed a protocol using 50 barcode pairs to run samples in parallel and coded a pipeline to process the data. Sequencing the same sediment sample in 248 replicates as well as 70 samples from alkaline soda lakes, we evaluated the performance of the method with regards to estimates of alpha and beta diversity. Using different purification and DNA quantification procedures we always found up to 5-fold differences in the yield of sequences between individually barcodes samples. Using either a one-step or a two-step PCR preparation resulted in significantly different estimates in both alpha and beta diversity. Comparing with a previous method based on 454 pyrosequencing, we found that our Illumina protocol performed in a similar manner -- with the exception for evenness estimates where correspondence between the methods was low. We further quantified the data loss at every processing step eventually accumulating to 50\% of the raw reads. When evaluating different OTU clustering methods, we observed a stark contrast between the results of QIIME with default settings and the more recent UPARSE algorithm when it comes to the number of OTUs generated. Still, overall trends in alpha and beta diversity corresponded highly using both clustering methods. Our procedure performed well considering the precisions of alpha and beta diversity estimates, with insignificant effects of individual barcodes. Comparative analyses suggest that 454 and Illumina sequence data can be combined if the same PCR protocol and bioinformatic workflows are used for describing patterns in richness, beta-diversity and taxonomic composition. (version 1.1 resubmitted to PLOS one 2014-Sept-08)

Download Full-text

The power of microbiome studies: some considerations on which alpha and beta metrics to use and how to report analysis the results

10.21203/rs.3.rs-698991/v1 ◽

2021 ◽

Author(s):

Jannigje Gerdien Kers ◽

Edoardo Saccenti

Keyword(s):

Sample Size ◽

Beta Diversity ◽

Sequence Data ◽

Animal Experiments ◽

Simulated Data ◽

Alpha Diversity ◽

Data Sets ◽

Power Calculations ◽

Alpha And Beta Diversity ◽

Diversity Metrics

Abstract Since sequencing techniques become less expensive, larger sample sizes are applicable for microbiota studies. The aim of this study is to show how, and to what extent, different diversity metrics and different compositions of the microbiota influence the needed sample size to observed dissimilar groups. Empirical 16S rRNA amplicon sequence data obtained from animal experiments, observational human data, and simulated data was used to perform retrospective power calculations. A wide variation of alpha diversity and beta diversity metrics were used to compare the different microbiota data sets and the effect on the sample size. Our data showed that beta diversity metrics are most sensitive to observe differences compared to alpha diversity metrics. The structure of the data influenced which alpha metrics are most sensitive. Regarding beta diversity, the Bray-Curtis metric is in general most sensitive to observe differences between groups, resulting in lower sample size and potential publication bias. We recommend to perform power calculations and to use multiple diversity metrics as an outcome measure. To improve microbiota studies awareness needs to be raised on the sensitivity and bias for microbiota research outcomes created by the used metrics rather than biological differences. We have seen that different alpha and beta diversity metrics lead to different study power: on the basis of this observation, one could be naturally tempted to try all possible metrics until one or more are found that give a statistically significant test result, i.e. p-value < α. This way of proceeding is one of the many forms of the so-called p-value hacking. To this end, in our opinion, the only way to protect ourselves from (the temptation of) p-hacking would be to publish, and we stress here the word publish, a statistical plan before experiments are initiated: this practice is customary for clinical trials where a statistical plan describing the endpoints and the corresponding statistical analyses must be disclosed before the start of the study.

Download Full-text

Assessment of two DNA extraction kits for profiling poultry respiratory microbiota from multiple sample types

10.1101/2020.10.21.348508 ◽

2020 ◽

Author(s):

Michael E.C. Abundo ◽

John M. Ngunjiri ◽

Kara J.M. Taylor ◽

Hana Ji ◽

Amir Ghorbani ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Dna Extraction ◽

Extraction Process ◽

Production Performance ◽

Rrna Gene ◽

Sample Type ◽

Alpha And Beta Diversity ◽

Gene Copies ◽

Diversity Metrics

AbstractCharacterization of poultry microbiota is becoming increasingly important due to the growing need for microbiome-based interventions to improve poultry health and production performance. However, the lack of standardized protocols for sampling, sample processing, DNA extraction, sequencing, and bioinformatic analysis can hinder data comparison between studies. Here, we investigated how the DNA extraction process affects microbial community compositions and diversity metrics in different chicken respiratory sample types including choanal and tracheal swabs, nasal cavity and tracheal washes, and lower respiratory lavage. We did a side-by-side comparison of the performances of Qiagen DNeasy blood and tissue (BT) and ZymoBIOMICS DNA Miniprep (ZB) kits. In general, samples extracted with the BT kit yielded higher concentrations of total DNA while those extracted with the ZB kit contained higher numbers of bacterial 16S rRNA gene copies per unit volume. Therefore, the samples were normalized to equal amounts of 16S rRNA gene copies prior to sequencing. For each sample type, all predominant taxa detected in samples extracted with one kit were present in replicate samples extracted with the other kit and did not show significant differences at the class level. Furthermore, between-kit differences in alpha and beta diversity metrics were statistically indistinguishable. Therefore, both kits perform similarly with regard to 16S rRNA gene-based poultry microbiome analysis.

Download Full-text

Assessment of two DNA extraction kits for profiling poultry respiratory microbiota from multiple sample types

PLoS ONE ◽

10.1371/journal.pone.0241732 ◽

2021 ◽

Vol 16 (1) ◽

pp. e0241732

Author(s):

Michael E. C. Abundo ◽

John M. Ngunjiri ◽

Kara J. M. Taylor ◽

Hana Ji ◽

Amir Ghorbani ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Dna Extraction ◽

Production Performance ◽

Rrna Gene ◽

Sequence Variant ◽

Sample Type ◽

Alpha And Beta Diversity ◽

Gene Copies ◽

Diversity Metrics

Characterization of poultry microbiota is becoming increasingly important due to the growing need for microbiome-based interventions to improve poultry health and production performance. However, the lack of standardized protocols for sampling, sample processing, DNA extraction, sequencing, and bioinformatic analysis can hinder data comparison between studies. Here, we investigated how the DNA extraction process affects microbial community compositions and diversity metrics in different chicken respiratory sample types including choanal and tracheal swabs, nasal cavity and tracheal washes, and lower respiratory lavage. We did a side-by-side comparison of the performances of Qiagen DNeasy blood and tissue (BT) and ZymoBIOMICS DNA Miniprep (ZB) kits. In general, samples extracted with the BT kit yielded higher concentrations of total DNA while those extracted with the ZB kit contained higher numbers of bacterial 16S rRNA gene copies per unit volume. Therefore, the samples were normalized to equal amounts of 16S rRNA gene copies prior to sequencing. For each sample type, all predominant bacterial taxa detected in samples extracted with one kit were present in replicate samples extracted with the other kit and did not show significant differences at the class level. However, a few differentially abundant shared taxa were observed at family and genus levels. Furthermore, between-kit differences in alpha and beta diversity metrics at the amplicon sequence variant level were statistically indistinguishable. Therefore, both kits perform similarly in terms of 16S rRNA gene-based poultry microbiome analysis for the sample types analyzed in this study.

Download Full-text

Stool metabolome-microbiota evaluation among children and adolescents with obesity, overweight, and normal-weight using 1H NMR and 16S rRNA gene profiling

PLoS ONE ◽

10.1371/journal.pone.0247378 ◽

2021 ◽

Vol 16 (3) ◽

pp. e0247378

Author(s):

José Diógenes Jaimes ◽

Andrea Slavíčková ◽

Jakub Hurych ◽

Ondřej Cinek ◽

Ben Nichols ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Alpha Diversity ◽

Study Groups ◽

Normal Weight ◽

Gene Profiling ◽

Energy Harvest ◽

Rrna Gene ◽

H Nmr ◽

Significant Difference

Characterization of metabolites and microbiota composition from human stool provides powerful insight into the molecular phenotypic difference between subjects with normal weight and those with overweight/obesity. The aim of this study was to identify potential metabolic and bacterial signatures from stool that distinguish the overweight/obesity state in children/adolescents. Using 1H NMR spectral analysis and 16S rRNA gene profiling, the fecal metabolic profile and bacterial composition from 52 children aged 7 to 16 was evaluated. The children were classified into three groups (16 with normal-weight, 17 with overweight, 19 with obesity). The metabolomic analysis identified four metabolites that were significantly different (p < 0.05) among the study groups based on one-way ANOVA testing: arabinose, butyrate, galactose, and trimethylamine. Significantly different (p < 0.01) genus-level taxa based on edgeR differential abundance tests were genus Escherichia and Tyzzerella subgroup 3. No significant difference in alpha-diversity was detected among the three study groups, and no significant correlations were found between the significant taxa and metabolites. The findings support the hypothesis of increased energy harvest in obesity by human gut bacteria through the growing observation of increased fecal butyrate in children with overweight/obesity, as well as an increase of certain monosaccharides in the stool. Also supported is the increase of trimethylamine as an indicator of an unhealthy state.

Download Full-text

Development of a Dual-Index Sequencing Strategy and Curation Pipeline for Analyzing Amplicon Sequence Data on the MiSeq Illumina Sequencing Platform

Applied and Environmental Microbiology ◽

10.1128/aem.01043-13 ◽

2013 ◽

Vol 79 (17) ◽

pp. 5112-5120 ◽

Cited By ~ 3102

Author(s):

James J. Kozich ◽

Sarah L. Westcott ◽

Nielson T. Baxter ◽

Sarah K. Highlander ◽

Patrick D. Schloss

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Sequence Data ◽

Error Rates ◽

Rrna Gene ◽

Variable Regions ◽

Sequencing Platform ◽

Sequencing Technologies ◽

Sequencing Strategy ◽

The 16S Rrna Gene

ABSTRACTRapid advances in sequencing technology have changed the experimental landscape of microbial ecology. In the last 10 years, the field has moved from sequencing hundreds of 16S rRNA gene fragments per study using clone libraries to the sequencing of millions of fragments per study using next-generation sequencing technologies from 454 and Illumina. As these technologies advance, it is critical to assess the strengths, weaknesses, and overall suitability of these platforms for the interrogation of microbial communities. Here, we present an improved method for sequencing variable regions within the 16S rRNA gene using Illumina's MiSeq platform, which is currently capable of producing paired 250-nucleotide reads. We evaluated three overlapping regions of the 16S rRNA gene that vary in length (i.e., V34, V4, and V45) by resequencing a mock community and natural samples from human feces, mouse feces, and soil. By titrating the concentration of 16S rRNA gene amplicons applied to the flow cell and using a quality score-based approach to correct discrepancies between reads used to construct contigs, we were able to reduce error rates by as much as two orders of magnitude. Finally, we reprocessed samples from a previous study to demonstrate that large numbers of samples could be multiplexed and sequenced in parallel with shotgun metagenomes. These analyses demonstrate that our approach can provide data that are at least as good as that generated by the 454 platform while providing considerably higher sequencing coverage for a fraction of the cost.

Download Full-text

Effect of Bovine MFGM and LF in Infant Formula on Gut Microbiome and Metabolome at Four Months of Age

Current Developments in Nutrition ◽

10.1093/cdn/nzab027 ◽

2021 ◽

Author(s):

Maciej Chichlowski ◽

Nicholas Bokulich ◽

Cheryl L Harris ◽

Jennifer L Wampler ◽

Fei Li ◽

...

Keyword(s):

Infant Formula ◽

Beta Diversity ◽

Milk Fat ◽

Alpha Diversity ◽

Illumina Miseq ◽

Rrna Gene ◽

Term Infants ◽

Linear Discriminant ◽

Alpha And Beta Diversity ◽

Metabolite Profiles

Abstract Background Milk fat globule membrane (MFGM) and lactoferrin (LF) are human milk bioactive components demonstrated to support gastrointestinal (GI) and immune development. Significantly fewer diarrhea and respiratory-associated adverse events through 18 months of age were previously reported in healthy term infants fed a cow's milk-based infant formula with added source of bovine MFGM and bovine LF through 12 months of age. Objectives To compare microbiota and metabolite profiles in a subset of study participants. Methods Stool samples were collected at Baseline (10–14 days of age) and Day 120 (MFGM + LF: 26, Control: 33). Bacterial community profiling was performed via16S rRNA gene sequencing (Illumina MiSeq) and alpha and beta diversity were analyzed (QIIME 2). Differentially abundant taxa were determined using Linear discriminant analysis effect size (LefSE) and visualized (Metacoder). Untargeted stool metabolites were analyzed (HPLC/mass spectroscopy) and expressed as the fold-change between group means (Control: MFGM + LF ratio). Results Alpha diversity increased significantly in both groups from baseline to 4 months. Subtle group differences in beta diversity were demonstrated at 4 months (Jaccard distance; R2 = 0.01, P = 0.042). Specifically, Bacteroides uniformis and Bacteroides plebeius were more abundant in the MFGM + LF group at 4 months. Metabolite profile differences for MFGM + LF vs Control included: lower fecal medium chain fatty acids, deoxycarnitine, and glycochenodeoxycholate, and some higher fecal carbohydrates and steroids (P < 0.05). After applying multiple test correction, the differences in stool metabolomics were not significant. Conclusions Addition of bovine MFGM and LF in infant formula was associated with subtle differences in stool microbiome and metabolome by four months of age, including increased prevalence of Bacteroides species. Stool metabolite profiles may be consistent with altered microbial metabolism. Trial registration: https://clinicaltrials.gov/ct2/show/NCT02274883).

Download Full-text

AB1232 ORAL DYSBIOSIS REFLECTS THE IMMUNOLOGICAL ALTERATION OF RA REGARDING TO ACPA AND HLA DRB1*SE: NAGASAKI ISLAND STUDY

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-eular.5147 ◽

2020 ◽

Vol 79 (Suppl 1) ◽

pp. 1907.2-1907

Author(s):

Y. Tsuji ◽

M. Tamai ◽

S. Morimoto ◽

D. Sasaki ◽

M. Nagayoshi ◽

...

Keyword(s):

Beta Diversity ◽

Healthy Subjects ◽

Microbial Community Composition ◽

Alpha Diversity ◽

Enzyme Linked Immunosorbent Assay ◽

Rrna Gene ◽

Oral Microbiota ◽

Unifrac Distance ◽

Alpha And Beta Diversity ◽

The Difference

Background:Anti-citrullinated protein antibody (ACPA) production is observed in several organs even prior to the onset of rheumatoid arthritis (RA), and oral mucosa is considered to be one of the important tissues. The presence of HLA-DRB1*SE closely associates with ACPA production. Saliva is considered to reflect the oral microbiota including periodontal disease. Alteration of oral microbiota of RA becomes to be normalized by DMARDs treatment, however, the interaction of HLA-DRB1*SE, ACPA and oral microbiota of RA patients remains to be elucidated.Objectives:The Nagasaki Island Study, which had started in 2014 collaborating with Goto City, is intended for research of the preclinical stage of RA, including ACPA/HLA genotype screening and ultrasound and magnetic resonance imaging examinations in high-risk subjects. Using the samples accumulated in this cohort, we have tried to investigate the difference of oral microbiota among RA patients and healthy subjects regarding to ACPA and HLA-DRB1*SE.Methods:Blood and salivary samples were obtained from 1422 subjects out of 4276 who have participated in the Nagasaki Island Study from 2016 to 2018. ACPA positivity was 1.7 % in total. Some of RA patients resided in Goto City participated in the Nagasaki Island Study. At this point, we selected 291 subjects, who were ACPA positive non-RA healthy subjects (n=22) and patients with RA (n=33, 11 subjects were ACPA positive and 22 ACPA negative respectively) as the case, age and gender matched ACPA negative non-RA healthy subjects (n=236) as the control. ACPA was measured by an enzyme-linked immunosorbent assay, and HLA genotyping was quantified by next-generation sequencing (Ref.1). The operational taxonomic unit (OUT) analysis using 16S rRNA gene sequencing were performed. The richness of microbial diversity within-subject (alpha diversity) was scaled via Shannon entropy. The dissimilarity between microbial community composition was calculated using Bray-Curtis distance as a scale, and differences between groups (beta diversity) were tested by permutational multivariate analysis of variance (PERMANOVA). In addition, UniFrac distance calculated in consideration of the distance on the phylogenetic tree were performed.Results:Median age 70 y.o., % Female 58.8 %. Among RA and non-RA subjects, not alpha diversity but beta diversity was statistically significance (p=0.022, small in RA). In RA subjects, both alpha and beta diversity is small (p<0.0001), especially significant in ACPA positive RA (Figure 1). Amongt RA subjects, presence of HLA-DRB1*SE did not show the difference but the tendency of being small of alpha diversity (p=0.29).Conclusion:Our study has suggested for the first time the association of oral microbiota alteration with the presence of ACPA and HLA-DRB1*SE. Oral dysbiosis may reflect the immunological status of patients with RA.References:[1]Kawaguchi S, et al. Methods Mol Biol 2018;1802: 22Disclosure of Interests:None declared

Download Full-text

PSIX-3 Comparison of 16S rRNA gene profiles of rumen microbiome from Raramuri Criollo, European and Criollo x European lineages

Journal of Animal Science ◽

10.1093/jas/skab235.789 ◽

2021 ◽

Vol 99 (Supplement_3) ◽

pp. 441-442

Author(s):

Adrian Maynez-Perez ◽

Francisco Jahuey-Martinez ◽

Jose A Martinez-Quintana ◽

Michael E Hume ◽

Robin C Anderson ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Beta Diversity ◽

Chihuahuan Desert ◽

Reference Database ◽

Rrna Gene ◽

Linear Discriminant ◽

Microbiome Composition ◽

Northern Mexico ◽

Rumen Microbiome

Abstract Raramuri Criollo cattle from the Chihuahuan desert in northern Mexico have been described as an ecological ecotype due to their enormous advantage in land grass utilization and their capacity to diversify their diet with cacti, forbs and woody plants. This diversification in diet utilization, could reflect upon their microbiome composition. The aim of this study was to characterize the rumen microbiome of Raramuri criollo cattle and to compare it to other lineages that graze in the same area. A total of 28 cows representing three linages [Criollo (n = 13), European (n = 9) and Criollo x European Crossbred (n = 6)] were grazed without supplementation for 45 days. DNA was extracted from ruminal samples and the V4 region of the 16S rRNA gene was sequenced on an Illumina platform. Data were analyzed with the QIIME2 software package and DADA2 plugin and the amplicon sequence variants were taxonomically classified with naïve Bayesian using the SILVA 16S rRNA gene reference database (version 132). Statistical analysis was performed by ANOVA and PERMANOVA for alpha and beta diversity indexes, respectively, and the non-strict version of linear discriminant analysis effect size (LEfSe) was used to determine significantly different taxa among lineages. Differences in beta diversity indexes (P < 0.05) were found in ruminal microbiome composition between Criollo and European groups, whereas the Crossbred showed intermediate values when compared to the pure breeds (Table 1). LEfSe analysis identified a total of 20 bacterial groups that explained differences between lineages, including one for Crossbreed, ten for European and nine for Criollo. These results show ruminal microbiome differences between Raramuri criollo cattle and the mainstream European breeds used in the northern Mexico Chihuahuan desert and reflect that those differences could be a consequence of dissimilar grazing behavior.

Download Full-text

Epipelic cyanobacterial diversity in Pinang River basin, Malaysia, revealed by 16S-based metagenomic approach

Algologia ◽

10.15407/alg31.01.093 ◽

2021 ◽

Vol 31 (1) ◽

pp. 93-113

Author(s):

A.R. Nur Fadzliana ◽

◽

W.O. Wan Maznah ◽

S.A.M. Nor ◽

Choon Pin Foong ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

River Basin ◽

Sequence Data ◽

Diversity Index ◽

Saline Water ◽

Illumina Miseq ◽

Rrna Gene ◽

Cyanobacterial Community ◽

Upstream Station

Cyanobacteria are the most widespread group of photosynthetic prokaryotes. They are primary producers in a wide variety of habitats and are able to thrive in harsh environments, including polluted waters; therefore, this study was conducted to explore the cyanobacterial populations inhabiting river tributaries with different levels of pollution. Sediment samples (epipelon) were collected from selected tributaries of the Pinang River basin. Air Terjun (T1) and Air Itam rivers (T2) represent the upper streams of Pinang River basin, while Dondang (T3) and Jelutong rivers (T4) are located at in the middle of the river basin. The Pinang River (T5) is located near the estuary and is subjected to saline water intrusion during high tides. Cyanobacterial community was determined by identifying the taxa via 16S rRNA gene amplicon sequence data. 16S rRNA gene amplicons generated from collected samples were sequenced using illumina Miseq, with the targeted V3 and V4 regions yielding approximately 1 mln reads per sample. Synechococcus, Phormidium, Arthronema and Leptolyngbya were found in all samples. Shannon-Weiner diversity index was highest (H’ = 1.867) at the clean upstream station (T1), while the moderately polluted stream (T3) recorded the lowest diversity (H’ = 0.399), and relatively polluted stations (T4 and T5) recorded fairly high values of H’. This study provides insights into the cyanobacterial community structure in Pinang River basin via cultivation-independent techniques using 16S rRNA gene amplicon sequence. Occurrence of some morphospecies at specific locations showed that the cyanobacterial communities are quite distinct and have specific ecological demands. Some species which were ubiquitous might be able to tolerate varied environmental conditions.

Download Full-text