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Soil microbiomes are heterogeneous, complex microbial communities. Metagenomic analysis is generating vast amounts of data, creating immense challenges in sequence assembly and analysis. Although advances in technology have resulted in the ability to easily collect large amounts of sequence data, soil samples containing thousands of unique taxa are often poorly characterized. These challenges reduce the usefulness of genome-resolved metagenomic (GRM) analysis seen in other fields of microbiology, such as the creation of high quality metagenomic assembled genomes and the adoption of genome scale modeling approaches. The absence of these resources restricts the scale of future research, limiting hypothesis generation and the predictive modeling of microbial communities. Creating publicly available databases of soil MAGs, similar to databases produced for other microbiomes, has the potential to transform scientific insights about soil microbiomes without requiring the computational resources and domain expertise for assembly and binning.

Bisphenol A (BPA) is a polymer used in the production of polycarbonate plastics and epoxy resins. An estrogen mimic, prenatal BPA exposure has been associated with several behavioral outcomes in children; however, the impact of maternal demographic and economic factors on associations between BPA and child behavioral outcomes have not been examined. The objective of this study was to examine associations between prenatal maternal urinary BPA and behavior in 4-5 year old girls, and to assess whether socio-demographic factors modify this relationship. Mothers enrolled in The Infant Development and Environment Study (TIDES) provided a single spot urine at enrollment (median gestational age 11 weeks) and completed the Behavior Assessment System for Children-2 (BASC-2) and Social Responsiveness Scale-2 (SRS-2) when their daughters were 4-5 years of age. Mother-daughter pairs with complete phthalate, BASC-2, SRS-2, and covariate data were included in this analysis (N = 244). BPA was detectable in 93 % of urine samples. We used multivariable linear regression analyses to estimate associations between maternal urinary log10-transformed BPA concentration and BASC-2 subscale and composite scores and SRS-2 Total Score. To examine the role of socioeconomic and demographic factors associated with study site, we stratified by TIDES center, comparing those enrolled at University of Rochester Medical Center (URMC), a predominately lower socioeconomic population, and those enrolled elsewhere: University of Washington, University of Minnesota, and University of California San Francisco, whose populations share similar higher socioeconomic demographic characteristics. Across all centers, no associations were seen between BPA and BASC-2 or SRS-2 scores. When stratifying by center, BPA was significantly associated with greater social impairment as measured by the SRS-2 Total Score (β-coefficient [95 % confidence intervals]: 5.1 [1.0, 9.2]) in URMC participants (N = 61). In non-URMC participants (N = 183), BPA was significantly associated with lower BASC-2 Internalizing composite (-3.3 [-6.7, 0.0]) and Depression subscale scores (-3.4 [-6.7, 0.0]) while no associations were seen between BPA and SRS-2 scores. Our findings suggest that sociodemographic factors may modify the impacts of maternal prenatal BPA on developmental endpoints.

Soil moisture is a major driver of microbial activity and thus, of the release of carbon (C) into the Earth's atmosphere. Yet, there is no consensus on the relationship between soil moisture and microbial respiration, and as a result, moisture response functions are a poorly constrained aspect of C models. In addition, models assume that the response of microbial respiration to moisture is the same for all ecosystems, regardless of climate history, an assumption that many empirical studies have challenged. These gaps in understanding of the microbial respiration response to moisture contribute to uncertainty in model predictions. We review our understanding of what drives microbial moisture response, highlighting evidence that historical precipitation can influence both responses to moisture and sensitivity to drought. We present two hypotheses, the ‘climate history hypothesis’, where we predict that baseline moisture response functions change as a function of precipitation history, and the ‘drought legacy hypothesis’, in which we suggest that the intensity and frequency of historical drought have shaped microbial communities in ways that will control moisture responses to contemporary drought. Underlying mechanisms include biological selection and filtering of the microbial community by rainfall regimes, which result in microbial traits and trade-offs that shape function. We present an integrated modelling and empirical approach for understanding microbial moisture responses and improving models. Standardized measures of moisture response (respiration rate across a range of moistures) and accompanying microbial properties are needed across sites. These data can be incorporated into trait-based models to produce generalized moisture response functions, which can then be validated and incorporated into conventional and microbially explicit ecosystem models of soil C cycling. Future studies should strive to analyse realistic moisture conditions and consider the role of environmental factors and soil structure in microbial response. Microbes are the engines that drive C storage and are sensitive to changes in rainfall. A greater understanding of the factors that govern this sensitivity could be a key part of improving predictions of soil C dynamics, climate change and C-climate feedbacks. Read the free Plain Language Summary for this article on the Journal blog.