DivNet: Estimating diversity in networked communities

Willis, Amy; Bd, Martin

doi:10.1101/305045

Cited by 32 publications

(30 citation statements)

References 38 publications

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“…However, these approaches typically cannot be applied to zero-valued observations (Aitchison, 1986;McMurdie and Holmes, 2014;Willis and Martin, 2018). Since many taxa are typically unobserved in each sample, these methods commonly make use of pseudo-counts to replace zeros, or incorporate a zero-inflation component into their model (Xia and others, 2013;Mandal and others, 2015;Li and others, 2018;Willis and Martin, 2018). In the case of pseudo-counts, parameter estimation depends on an arbitrarily chosen hyperparameter, while zero-inflated models may lack interpretability.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling microbial abundances and dysbiosis with beta-binomial regression

Martin¹,

Witten²,

Willis³

2020

Ann. Appl. Stat.

304

266

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Using a sample from a population to estimate the proportion of the population with a certain category label is a broadly important problem. In the context of microbiome studies, this problem arises when researchers wish to use a sample from a population of microbes to estimate the population proportion of a particular taxon, known as the taxon's relative abundance. In this paper, we propose a beta-binomial model for this task. Like existing models, our model allows for a taxon's relative abundance to be associated with covariates of interest. However, unlike existing models, our proposal also allows for the overdispersion in the taxon's counts to be associated with covariates of interest. We exploit this model in order to propose tests not only for differential relative abundance, but also for differential variability. The latter is particularly valuable in light of speculation that dysbiosis, the perturbation from a normal microbiome that can occur in certain disease conditions, may manifest as a loss of stability, or increase in variability, of the counts associated with each taxon. We demonstrate the performance of our proposed model using a simulation study and an application to soil microbial data. *

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Section: Literature Reviewmentioning

confidence: 99%

Modeling microbial abundances and dysbiosis with beta-binomial regression

Martin¹,

Witten²,

Willis³

2020

Ann. Appl. Stat.

304

266

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“…We used ecological network regression models to estimate Shannon diversity with the R package DivNet [66]. We then tested for differences in Shannon diversity using the hierarchical model Betta, which accounts for incomplete community sampling and allows for multivariable adjustment [67].…”

Section: Alpha Diversity Analysismentioning

confidence: 99%

Timing of complementary feeding is associated with gut microbiota diversity and composition and short chain fatty acid concentrations over the first year of life

et al. 2020

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Background: Early introduction of complementary foods has been associated with various immune disorders, oxidative stress, and obesity in childhood. The gut microbiota and the short chain fatty acids (SCFAs) they produce are postulated to be on the causal pathway. The objective of this study was to determine if early complementary feeding (i.e. consumption of solids or non-water/formula liquids at or before 3 months) is prospectively associated with infant gut microbiota composition, diversity and SCFAs at 3 and 12 months of age in the Nurture birth cohort. Results: Mother-infant dyads in the early complementary feeding group (n = 18) had similar baseline characteristics to those in the later feeding group (n = 49). We assessed differential abundance of microbial taxa (measured by 16S rRNA gene sequencing of the V4 region) by timing of complementary feeding using beta-binomial regression models (considering a two-sided FDR corrected p-value of < 0.05 as significant), and we fittted linear regression models to assess the association between early complementary feeding and SCFA concentrations (quantified using gas chromatography). After multivariable adjustment for breastfeeding, delivery method, birth weight, and gestational age, there were 13 differentially abundant microbial amplicon sequence variants (ASVs) by timing of introduction to complementary foods at 3 months and 20 ASVs at 12 months. Infants introduced to complementary foods early (vs. later) had higher concentrations of the SCFA butyric acid (mean difference = 0.65, 95% CI: 0.27, 1.04, p < 0.01) and total SCFAs (mean difference = 38.8, 95% CI: 7.83, 69.7) at 12 months. Bilophila wadsworthia and Lachnospiraceae Roseburia were associated with early (vs. later) complementary feeding and with higher butyric acid concentrations at 3 and 12 months, respectively. Conclusions: Our findings are consistent with the hypothesis that early (vs. later) introduction to complementary foods is associated with altered gut microbiota composition and butyric acid concentrations measured in stool until at least 1 year of age. Further research is needed to determine if these changes mediate future development of metabolic and immune conditions.

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“…These reads were 220 analyzed using the DADA2 ) pipeline implemented in QIIME 2 (Bolyen et al 2018). ASVs with low prevalence (< 0.01) were removed and alphadiversity was measured by Shannon-diversity Index that accounts for both species abundance and evenness (Willis & Martin 2018). The association between bacterial alphadiversity and artificial selection regime was tested via the adonis function in vegan R 225 package (Oksanen et al 2015), with alpha-diversity as dependent variable and diet, round, selection pressure as explanatory variables.…”

Section: S Analysis Of Microbiome Compositionmentioning

confidence: 99%

The microbiome wants what it wants: microbial evolution overtakes experimental host-mediated indirect selection

Arora

Brisbin

Mikheyev

2019

Preprint

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Microbes ubiquitously inhabit animals and plants, often affecting their host's phenotype. 10 As a result, even in a constant genetic background, the host's phenotype may evolve through indirect selection on the microbiome. 'Microbiome engineering' offers a promising novel approach for attaining desired host traits but has been attempted only a few times.Building on the known role of the microbiome on development in fruit flies, we attempted to evolve earlier eclosing flies by selecting on microbes in the growth media. We carried 15 out parallel evolution experiments in no-and high-sugar diets by transferring media associated with fast-developing fly lines over the course of four rounds of selection. In each round, we used sterile eggs from the same inbred population, and assayed fly mean eclosion times. Ultimately, flies eclosed seven to twelve hours earlier, depending on the diet, but selection had no effect. 16S sequencing showed that the microbiome did evolve, 20 particularly in the no sugar diet, with an increase in alpha diversity over time. Thus, while microbiome evolution did affect host eclosion times, these effects were incidental. Instead, any experimentally enforced selection effects were swamped by independent microbial evolution. These results imply that selection on host phenotypes must be strong enough to overcome other selection pressures simultaneously operating on the microbiome. The 25 independent evolutionary trajectories of the host and the microbiome may limit the extent to which indirect selection on the microbiome can ultimately affect host phenotype.Random-selection lines accounting for independent microbial evolution are essential for experimental microbiome engineering studies. 30

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DivNet: Estimating diversity in networked communities

Cited by 32 publications

References 38 publications

Modeling microbial abundances and dysbiosis with beta-binomial regression

Modeling microbial abundances and dysbiosis with beta-binomial regression

Timing of complementary feeding is associated with gut microbiota diversity and composition and short chain fatty acid concentrations over the first year of life

The microbiome wants what it wants: microbial evolution overtakes experimental host-mediated indirect selection

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