Intermuscular adipose tissue-free skeletal muscle mass: estimation by dual-energy X-ray absorptiometry in adults.

Skeletal muscle (SM) is a large and physiologically important compartment. Adipose tissue is found interspersed between and within SM groups and is referred to as intermuscular adipose tissue (IMAT). The study objective was to develop prediction models linking appendicular lean soft tissue (ALST) estimates by dual-energy X-ray absorptiometry (DXA) with whole body IMAT-free SM quantified by magnetic resonance imaging. ALST and total-body IMAT-free SM were evaluated in 270 healthy adults [body mass index (BMI) of <35 kg/m(2)]. The SM prediction models were then validated by the leave-one-out method and by application in a new group of subjects who varied in SM mass [anorexia nervosa (AN), n = 23; recreational athletes, n = 16; patients with acromegaly, n = 7]. ALST alone was highly correlated with whole body IMAT-free SM [model 1: R(2) = 0.96, standard error (SE) = 1.46 kg, P < 0.001]; age (model 2: R(2) = 0.97, SE = 1.38 kg, P < 0.001) and sex and race (model 3: R(2) = 0.97, SE = 1.06 kg, both P < 0.001) added significantly to the prediction models. All three models validated in the athletes and patients with acromegaly but significantly (P < 0.01-0.001) over-predicted SM in the AN group as a whole. However, model 1 was validated in AN patients with BMIs in the model-development group range (n = 11; BMI of >16 kg/m(2)) but not in those with a BMI of <16 kg/m(2) (n = 12). The DXA-based models are accurate for predicting IMAT-free SM in selected populations and thus provide a new opportunity for quantifying SM in physiological and epidemiological investigations.     

Microbial Community Metabolic Modeling: A Community Data‐Driven Network Reconstruction

Metabolic network modeling of microbial communities provides an in‐depth understanding of community‐wide metabolic and regulatory processes. Compared to single organism analyses, community metabolic network modeling is more complex because it needs to account for interspecies interactions. To date, most approaches focus on reconstruction of high‐quality individual networks so that, when combined, they can predict community behaviors as a result of interspecies interactions. However, this conventional method becomes ineffective for communities whose members are not well characterized and cannot be experimentally interrogated in isolation. Here, we tested a new approach that uses community‐level data as a critical input for the network reconstruction process. This method focuses on directly predicting interspecies metabolic interactions in a community, when axenic information is insufficient. We validated our method through the case study of a bacterial photoautotroph–heterotroph consortium that was used to provide data needed for a community‐level metabolic network reconstruction. Resulting simulations provided experimentally validated predictions of how a photoautotrophic cyanobacterium supports the growth of an obligate heterotrophic species by providing organic carbon and nitrogen sources. J. Cell. Physiol. 231: 2339–2345, 2016. © 2016 The Authors. Journal of Cellular Physiology Published by Wiley Periodicals, Inc.     

Global patterns and substrate‐based mechanisms of the terrestrial nitrogen cycle

Nitrogen (N) deposition is impacting the services that ecosystems provide to humanity. However, the mechanisms determining impacts on the N cycle are not fully understood. To explore the mechanistic underpinnings of N impacts on N cycle processes, we reviewed and synthesised recent progress in ecosystem N research through empirical studies, conceptual analysis and model simulations. Experimental and observational studies have revealed that the stimulation of plant N uptake and soil retention generally diminishes as N loading increases, while dissolved and gaseous losses of N occur at low N availability but increase exponentially and become the dominant fate of N at high loading rates. The original N saturation hypothesis emphasises sequential N saturation from plant uptake to soil retention before N losses occur. However, biogeochemical models that simulate simultaneous competition for soil N substrates by multiple processes match the observed patterns of N losses better than models based on sequential competition. To enable better prediction of terrestrial N cycle responses to N loading, we recommend that future research identifies the response functions of different N processes to substrate availability using manipulative experiments, and incorporates the measured N saturation response functions into conceptual, theoretical and quantitative analyses.     

Suppression of bacterial infection in rice by treatment with a sulfated peptide

The rice XA21 receptor kinase confers robust resistance to bacterial blight disease caused by Xanthomonas oryzae pv. oryzae (Xoo). A tyrosine‐sulfated peptide from Xoo, called RaxX, triggers XA21‐mediated immune responses, including the production of ethylene and reactive oxygen species and the induction of defence gene expression. It has not been tested previously whether these responses confer effective resistance to Xoo. Here, we describe a newly established post‐inoculation treatment assay that facilitates investigations into the effect of the sulfated RaxX peptide in planta. In this assay, rice plants were inoculated with a virulent strain of Xoo and then treated with the RaxX peptide 2 days after inoculation. We found that post‐inoculation treatment of XA21 plants with the sulfated RaxX peptide suppresses the development of Xoo infection in XA21 rice plants. The treated plants display restricted lesion development and reduced bacterial growth. Our findings demonstrate that exogenous application of sulfated RaxX activates XA21‐mediated immunity in planta, and provides a potential strategy for the control of bacterial disease in the field.