Abstract
We propose a Bayesian sparse multivariate regression method to model the relationship between microbe abundance and environmental factors for microbiome data. We model abundance counts of operational taxonomic units (OTUs) with a negative binomial distribution and relate covariates to the counts through regression. Extending conventional nonlocal priors, we construct asymmetric nonlocal priors for regression coefficients to efficiently identify relevant covariates and their effect directions. We build a hierarchical model to facilitate pooling of information across OTUs that produces parsimonious results with improved accuracy. We present simulation studies that compare variable selection performance under the proposed model to those under Bayesian sparse regression models with asymmetric and symmetric local priors and two frequentist models. The simulations show the proposed model identifies important covariates and yields coefficient estimates with favorable accuracy compared with the alternatives. The proposed model is applied to analyze an ocean microbiome dataset collected over time to study the association of harmful algal bloom conditions with microbial communities.
Highlights
Daphnia is a ubiquitous keystone zooplankton species found in many aquatic ecosystems, capable of growing in both pristine and polluted environments
We investigated the role of microbiomes on host fitness under mercury stress
We found that Daphnia is an environmental reservoir of mercurytolerant bacteria that could potentially biotransform mercury into less-toxic form by up-regulating the expression of merA gene upon exposure to elevated levels of mercury and reducing the concentration of mercury in the medium
Summary
Daphnia is a ubiquitous keystone zooplankton species found in many aquatic ecosystems, capable of growing in both pristine and polluted environments. It can withstand many environmental stressors, is widely used as a model organism for numerous research [1,2,3,4,5,6,7], including studies on the effects of temperature fluctuations [8, 9], food availability Inorganic Hg 2+ can be further converted into the less toxic, extremely volatile Hg 0 by microorganisms expressing the merA gene that encodes a mercury reductase [40,41,42,43] Microorganisms harboring these mercurybiotransformation genes have the potential to impact mercury speciation, cycling and concentration in the environment. We found that a daphnid microbiota member can aid in the host survival and allow the host to produce viable offspring even when exposed to mercury contamination
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