Nonlinearity of root trait relationships and the root economics spectrum

The root economics spectrum (RES), a common hypothesis postulating a tradeoff between resource acquisition and conservation traits, is being challenged by conflicting relationships between root diameter, tissue density (RTD) and root nitrogen concentration (RN). Here, we analyze a global trait dataset of absorptive roots for over 800 plant species. For woody species (but not for non-woody species), we find nonlinear relationships between root diameter and RTD and RN, which stem from the allometric relationship between stele and cortical tissues. These nonlinear relationships explain how sampling bias from different ends of the nonlinear curves can result in conflicting trait relationships. Further, the shape of the relationships varies depending on evolutionary context and mycorrhizal affiliation. Importantly, the observed nonlinear trait relationships do not support the RES predictions. Allometry-based nonlinearity of root trait relationships improves our understanding of the ecology, physiology and evolution of absorptive roots

RORγ is a targetable master regulator of cholesterol biosynthesis in a cancer subtype.

Tumor subtype-specific metabolic reprogrammers could serve as targets of therapeutic intervention. Here we show that triple-negative breast cancer (TNBC) exhibits a hyper-activated cholesterol-biosynthesis program that is strongly linked to nuclear receptor RORγ, compared to estrogen receptor-positive breast cancer. Genetic and pharmacological inhibition of RORγ reduces tumor cholesterol content and synthesis rate while preserving host cholesterol homeostasis. We demonstrate that RORγ functions as an essential activator of the entire cholesterol-biosynthesis program, dominating SREBP2 via its binding to cholesterol-biosynthesis genes and its facilitation of the recruitment of SREBP2. RORγ inhibition disrupts its association with SREBP2 and reduces chromatin acetylation at cholesterol-biosynthesis gene loci. RORγ antagonists cause tumor regression in patient-derived xenografts and immune-intact models. Their combination with cholesterol-lowering statins elicits superior anti-tumor synergy selectively in TNBC. Together, our study uncovers a master regulator of the cholesterol-biosynthesis program and an attractive target for TNBC

Precipitation change affects forest soil carbon inputs and pools : a global meta-analysis

The impacts of precipitation change on forest carbon (C) storage will have global consequences, as forests play a major role in sequestering anthropogenic CO . Although forest soils are one of the largest terrestrial C pools, there is great uncertainty around the response of forest soil organic carbon (SOC) to precipitation change, which limits our ability to predict future forest C storage. To address this, we conducted a meta-analysis to determine the effect of drought and irrigation experiments on SOC pools, plant C inputs and the soil environment based on 161 studies across 139 forest sites worldwide. Overall, forest SOC content was not affected by precipitation change, but both drought and irrigation altered plant C inputs and soil properties associated with SOC formation and storage. Drought may enhance SOC stability by altering soil aggregate fractions, but the effect of irrigation on SOC fractions remains unexplored. The apparent insensitivity of SOC to precipitation change can be explained by the short duration of most experiments and by biome-specific responses of C inputs and pools to drought or irrigation. Importantly, we demonstrate that SOC content is more likely to decline under irrigation at drier temperate sites, but that dry forests are currently underrepresented across experimental studies. Thus, our meta-analysis advances research into the impacts of precipitation change in forests by revealing important differences among forest biomes, which are likely linked to plant adaptation to extant conditions. We further demonstrate important knowledge gaps around how precipitation change will affect SOC stability, as too few studies currently consider distinct soil C pools. To accurately predict future SOC storage in forests, there is an urgent need for coordinated studies of different soil C pools and fractions across existing sites, as well as new experiments in underrepresented forest types