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

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.

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

2021 ◽  
Vol 12 ◽  
Author(s):  
Hannah E. Epstein ◽  
Alejandra Hernandez-Agreda ◽  
Samuel Starko ◽  
Julia K. Baum ◽  
Rebecca Vega Thurber
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Beta Diversity ◽  
Sequence Data ◽  
Alpha Diversity ◽  
Gene Profiling ◽  
Rrna Gene ◽  
Sequencing Platform ◽  
Alpha And Beta Diversity ◽  
Diversity Metrics

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.

scholarly journals PSVI-16 Fecal microbiome of nursery pigs fed phytogenics and antibiotics

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 203-203
Author(s):  
Huyen Tran ◽  
Timothy J Johnson
Keyword(s):  
Beta Diversity ◽  
Sequence Data ◽  
Alpha Diversity ◽  
Illumina Miseq ◽  
Amplicon Sequencing ◽  
Fecal Microbiome ◽  
Nursery Pigs ◽  
Alpha And Beta Diversity ◽  
Family Level ◽  
Dietary Treatments

Abstract The objective of this study was to evaluate effects of feeding two phytogenic products (PHY1 and PHY2; blends of essential oils and plant extracts) in diets with or without antibiotics (AureoMix S 10-10; AB) on fecal microbiome of nursery pigs. A total of 400 nursery pigs (6.8 kg BW; 20 d of age) were fed one of the six dietary treatments (9 pens/treatment), including: control (0% AB; 0% phytogenics), 0.5% AB, phytogenics (0.02% PHY1 or 0.03% PHY2) or the combination of phytogenic and AB (PHY1 x AB or PHY2 x AB). On d 46 postweaning, 48 fecal samples were collected (1 pig/pen; 7–9 pigs/treatment) and were subjected to the analyses of microbial communities by using 16S rRNA V4 amplicon sequencing with Illumina MiSeq. The sequence data were analyzed by using Qiime and the rarefied OTU table was submitted to Calypso to evaluate the alpha and beta diversity, taxonomic classification, and the differential taxa associated to the dietary treatments. There were differences among treatments on alpha diversity, where the control and PHY2 pigs had lower OTU richness (P = 0.05) and chao1 index (P &lt; 0.10) compared to pigs fed AB alone or AB with phytogenics. There were also differences among treatments on microbial beta diversity of pigs (P &lt; 0.01). The most abundant phyla included Firmicute, Bacteroidetes, Actinobacteria, Tenericutes, Proteobacteria, Spirochaetes, and TM7. At family level, pigs fed AB had greater Ruminococcaceae compared to the control, but lower Coriobacteriaceae and Erysipelotrichaceae compared to PHY1 or PHY2 group (P &lt; 0.05). Feature selection by LEfSe indicated that dominant genus associated to AB treatment was Unclassified RF39, while dominant genera associated to PHY2 treatment were Cantenibacterium, unclassified Coriobacteriaceae, Blautia, Eubacterium, and Collinsella. In conclusion, feeding AB and phytogenic products had different impacts on the fecal bacteria of nursery pigs.

Microbiological description of self-overgrowing spoil heaps and sand quarries in Nordwest Russia

2021 ◽  
Author(s):  
Aleksei Zverev ◽  
Anastasiia Kimeklis ◽  
Grigory Gladkov ◽  
Arina Kichko ◽  
Evgeny Andronov ◽  
...  
Keyword(s):  
Beta Diversity ◽  
Alpha Diversity ◽  
Illumina Miseq ◽  
Differential Abundance ◽  
Alpha And Beta Diversity ◽  
Technogenic Landscapes ◽  
Different Types ◽  
Undisturbed Soils ◽  
Disturbed Soils ◽  
Diversity Metrics

&lt;p&gt;Self-overgrowing recovery of disturbed soils is one of important processes in reclamation of disturbed soils. Different types of anthropogenic disturbances followed by variety of soil types and their genesis leads to different bacterial communities, envolved in reclamation processes. Here we describe regional self-overgrowing soils in two location (Novgorod region, Northwest Russia). We analyse top level of industrial disturbed soils after coil mining (spoil tips with extremely low pH, and &lt;span&gt;overburden &lt;/span&gt;soil) and sand quarry dumps followed by local undisturbed soils.&lt;/p&gt;&lt;p&gt;We perform 16s amplicone sequencind (v4-region) by Illumina MiSEQ and chemical routine analysis (pH, C, N and other). We provide alpha- and beta-diversity analysis, followed by CCA and analysis of differential abundance of taxa.&lt;/p&gt;&lt;p&gt;Sand quarry dumps and regional soils looks common on phyla level, and represent common soil phyla like &lt;em&gt;Proteobacteria&lt;/em&gt;, &lt;em&gt;Actinobacteria&lt;/em&gt; and &lt;em&gt;Verrucomicrobia&lt;/em&gt;. Alpha-diversity metrics aslo are similar, despite difference in beta-diversity. O&lt;span&gt;verburden soil and soil from spot tips, by contrast, is very different even in phylum level. Main intermediants here are &lt;em&gt;Actinobacteria&lt;/em&gt;, &lt;em&gt;Chloroflexi&lt;/em&gt; &amp;#1080; &lt;em&gt;Nitrospirae&lt;/em&gt;. Also they show extremely low alpha-diversity metrics.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;This work was supported by RSF 17-16-01030, &amp;#171;Dynamics of soil biota in chronoseries of post-technogenic landscapes: analysis of soil-ecological efficiency of ecosystem restoration processes&amp;#187;&lt;/span&gt;&lt;/p&gt;

scholarly journals 269 Influence of the maternal rumen microbiome on development of the calf meconium and rumen microbiome

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 195-195
Author(s):  
Kelly Woodruff ◽  
Gwendolynn Hummel ◽  
Kathleen Austin ◽  
Travis Smith ◽  
Hannah Cunningham
Keyword(s):  
Beta Diversity ◽  
Management Practices ◽  
Sequence Data ◽  
Rumen Fluid ◽  
Alpha Diversity ◽  
Illumina Miseq ◽  
Sample Type ◽  
Microbial Composition ◽  
Alpha And Beta Diversity ◽  
Rumen Microbiome

Abstract Optimization of host performance may be achieved through programming of the rumen microbiome. Thus, understanding maternal influences on the development of the calf rumen microbiome is critical. We hypothesized that the cow maternal rumen microbiome would influence colonization of the calf rumen microbiome. Our objective was to relate the microbiome of the cow rumen fluid prior to parturition (RFC) and at weaning (RFCw) to the calf’s meconium microbiome (M) and calf rumen fluid microbiome at birth (RFd1), d 2 (RFd2), d 28 (RFd28), and weaning (RFNw). Multiparous Angus crossbred cows (n = 10) from the University of Wyoming beef herd were used. Rumen fluid was collected from the cows prior to parturition and at weaning. Immediately following parturition, meconium and rumen fluid were collected from the calf. Rumen fluid was collected again at d 2, 28, and at weaning. Microbial DNA was isolated and 16S rRNA sequencing was completed on the Illumina MiSeq. Sequence data were analyzed with QIIME2 to determine both alpha and beta diversity by sample type and day. Alpha diversity metrics reported similarities in the early gut microbiome (M, RFd1, and RFD2; q ≥ 0.12) and between the cow and calf at weaning (q ≥ 0.06). Microbial composition as determined by beta diversity differed in the early rumen microbiome (RFd1, RFd2, and RFd28; q ≤ 0.04). There were similarities in composition between M, RFCw, and RFd1 (q ≥ 0.09). These data can be used to develop hypotheses for the pathway of colonization in the early gut and can provide insight into management practices affecting the microbiome, improving host performance.

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

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 &lt; 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).

scholarly journals Gut Microbiome in Psoriasis: An Updated Review

Pathogens ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 463
Author(s):  
Mariusz Sikora ◽  
Albert Stec ◽  
Magdalena Chrabaszcz ◽  
Aleksandra Knot ◽  
Anna Waskiel-Burnat ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Beta Diversity ◽  
Large Scale ◽  
Skin Diseases ◽  
Intestinal Barrier ◽  
Alpha Diversity ◽  
Current Data ◽  
Intestinal Microbiome ◽  
Microbial Composition ◽  
Alpha And Beta Diversity

(1) Background: A growing body of evidence highlights that intestinal dysbiosis is associated with the development of psoriasis. The gut–skin axis is the novel concept of the interaction between skin diseases and microbiome through inflammatory mediators, metabolites and the intestinal barrier. The objective of this study was to synthesize current data on the gut microbial composition in psoriasis. (2) Methods: We conducted a systematic review of studies investigating intestinal microbiome in psoriasis, using the PRISMA checklist. We searched MEDLINE, EMBASE, and Web of Science databases for relevant published articles (2000–2020). (3) Results: All of the 10 retrieved studies reported alterations in the gut microbiome in patients with psoriasis. Eight studies assessed alpha- and beta-diversity. Four of them reported a lack of change in alpha-diversity, but all confirmed significant changes in beta-diversity. At the phylum-level, at least two or more studies reported a lower relative abundance of Bacteroidetes, and higher Firmicutes in psoriasis patients versus healthy controls. (4) Conclusions: There is a significant association between alterations in gut microbial composition and psoriasis; however, there is high heterogeneity between studies. More unified methodological standards in large-scale studies are needed to understand microbiota’s contribution to psoriasis pathogenesis and its modulation as a potential therapeutic strategy.

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

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

scholarly journals Diversity Indices of Plant Communities and Their Rhizosphere Microbiomes: An Attempt to Find the Connection

2021 ◽  
Vol 9 (11) ◽  
pp. 2339
Author(s):  
Aleksei O. Zverev ◽  
Arina A. Kichko ◽  
Aleksandr G. Pinaev ◽  
Nikolay A. Provorov ◽  
Evgeny E. Andronov
Keyword(s):  
Microbial Communities ◽  
Plant Communities ◽  
Plant Diversity ◽  
Beta Diversity ◽  
Mutual Influence ◽  
Plant Root ◽  
Alpha Diversity ◽  
Diversity Indices ◽  
Alpha And Beta Diversity ◽  
Highly Correlated

The rhizosphere community represents an “ecological interface” between plant and soil, providing the plant with a number of advantages. Despite close connection and mutual influence in this system, the knowledge about the connection of plant and rhizosphere diversity is still controversial. One of the most valuable factors of this uncertainty is a rough estimation of plant diversity. NGS sequencing can make the estimations of the plant community more precise than classical geobotanical methods. We investigate fallow and crop sites, which are similar in terms of environmental conditions and soil legacy, yet at the same time are significantly different in terms of plant diversity. We explored amplicons of both the plant root mass (ITS1 DNA) and the microbial communities (16S rDNA); determined alpha- and beta-diversity indices and their correlation, and performed differential abundance analysis. In the analysis, there is no correlation between the alpha-diversity indices of plants and the rhizosphere microbial communities. The beta-diversity between rhizosphere microbial communities and plant communities is highly correlated (R = 0.866, p = 0.01). ITS1 sequencing is effective for the description of plant root communities. There is a connection between rhizosphere communities and the composition of plants, but on the alpha-diversity level we found no correlation. In the future, the connection of alpha-diversities should be explored using ITS1 sequencing, even in more similar plant communities—for example, in different synusia.

scholarly journals Limits and Convergence properties of the Sequentially Markovian Coalescent

2020 ◽  
Author(s):  
Thibaut Sellinger ◽  
Diala Abu Awad ◽  
Aurélien Tellier
Keyword(s):  
Sequence Data ◽  
Demographic History ◽  
Simulated Data ◽  
Simultaneous Estimation ◽  
Data Sets ◽  
Performance Limits ◽  
Biological Variables ◽  
Convergence Proofs ◽  
New Interpretation ◽  
Population Demographic

AbstractMany methods based on the Sequentially Markovian Coalescent (SMC) have been and are being developed. These methods make use of genome sequence data to uncover population demographic history. More recently, new methods have extended the original theoretical framework, allowing the simultaneous estimation of the demographic history and other biological variables. These methods can be applied to many different species, under different model assumptions, in hopes of unlocking the population/species evolutionary history. Although convergence proofs in particular cases have been given using simulated data, a clear outline of the performance limits of these methods is lacking. We here explore the limits of this methodology, as well as present a tool that can be used to help users quantify what information can be confidently retrieved from given datasets. In addition, we study the consequences for inference accuracy violating the hypotheses and the assumptions of SMC approaches, such as the presence of transposable elements, variable recombination and mutation rates along the sequence and SNP call errors. We also provide a new interpretation of the SMC through the use of the estimated transition matrix and offer recommendations for the most efficient use of these methods under budget constraints, notably through the building of data sets that would be better adapted for the biological question at hand.

Impact of intrapartum antibiotics on the infant gastrointestinal microbiome: a narrative review

2021 ◽  
pp. archdischild-2021-322590
Author(s):  
Laura Diamond ◽  
Rachel Wine ◽  
Shaun K Morris
Keyword(s):  
Gestational Age ◽  
Beta Diversity ◽  
Mode Of Delivery ◽  
Alpha Diversity ◽  
First Year ◽  
Feeding Method ◽  
Alpha And Beta Diversity ◽  
Ovid Medline ◽  
First Year Of Life ◽  
The Impact

BackgroundThe composition of the infant gastrointestinal (GI) microbiome has been linked to adverse long-term health outcomes and neonatal sepsis. Several factors are known to impact the composition of the microbiome, including mode of delivery, gestational age, feeding method and exposure to antibiotics. The impact of intrapartum antibiotics (IPAs) on the infant microbiome requires further research.ObjectiveWe aimed to evaluate the impact of IPAs on the infant GI microbiome.MethodsWe searched Ovid MEDLINE and Embase Classic+Embase for articles in English reporting on the microbiome of infants exposed to IPAs from the date of inception to 3 January 2021. Primary outcomes included abundance and colonisation of Bifidobacterium and Lactobacillus, as well as alpha and beta diversity.Results30 papers were included in this review. In the first year of life, following exposure to IPAs, 30% (6/20) of infant cohorts displayed significantly reduced Bifidobacterium, 89% (17/19) did not display any significant differences in Lactobacillus colonisation, 21% (7/34) displayed significantly reduced alpha diversity and 35% (12/34) displayed alterations in beta diversity. Results were further stratified by delivery, gestational age (preterm or full term) and feeding method.ConclusionsIPAs impact the composition of the infant GI microbiome, resulting in possible reductions Bifidobacterium and alpha diversity, and possible alterations in beta diversity. Our findings may have implications for maternal and neonatal health, including interventions to prevent reductions in health-promoting bacteria (eg, probiotics) and IPA class selection.

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