Peroxisomal polyhydroxyalkanoate biosynthesis is a promising strategy for bioplastic production in high biomass crops.

Polyhydroxyalkanoates (PHAs) are bacterial carbon storage polymers with diverse plastic-like properties. PHA biosynthesis in transgenic plants is being developed as a way to reduce the cost and increase the sustainability of industrial PHA production. The homopolymer polyhydroxybutyrate (PHB) is the simplest form of these biodegradable polyesters. Plant peroxisomes contain the substrate molecules and necessary reducing power for PHB biosynthesis, but peroxisomal PHB production has not been explored in whole soil-grown transgenic plants to date. We generated transgenic sugarcane (Saccharum sp.) with the three-enzyme Ralstonia eutropha PHA biosynthetic pathway targeted to peroxisomes. We also introduced the pathway into Arabidopsis thaliana, as a model system for studying and manipulating peroxisomal PHB production. PHB, at levels up to 1.6%-1.8% dry weight, accumulated in sugarcane leaves and A. thaliana seedlings, respectively. In sugarcane, PHB accumulated throughout most leaf cell types in both peroxisomes and vacuoles. A small percentage of total polymer was also identified as the copolymer poly (3-hydroxybutyrate-co-3-hydroxyvalerate) in both plant species. No obvious deleterious effect was observed on plant growth because of peroxisomal PHA biosynthesis at these levels. This study highlights how using peroxisomal metabolism for PHA biosynthesis could significantly contribute to reaching commercial production levels of PHAs in crop plants.

Light receptor action is critical for maintaining plant biomass at warm ambient temperatures.

The ability to withstand environmental temperature variation is essential for plant survival. Former studies in Arabidopsis revealed that light signalling pathways had a potentially unique role in shielding plant growth and development from seasonal and daily fluctuations in temperature. In this paper we describe the molecular circuitry through which the light receptors cry1 and phyB buffer the impact of warm ambient temperatures. We show that the light signalling component HFR1 acts to minimise the potentially devastating effects of elevated temperature on plant physiology. Light is known to stabilise levels of HFR1 protein by suppressing proteasome-mediated destruction of HFR1. We demonstrate that light-dependent accumulation and activity of HFR1 are highly temperature dependent. The increased potency of HFR1 at warmer temperatures provides an important restraint on PIF4 that drives elongation growth. We show that warm ambient temperatures promote the accumulation of phosphorylated PIF4. However, repression of PIF4 activity by phyB and cry1 (via HFR1) is critical for controlling growth and maintaining physiology as temperatures rise. Loss of this light-mediated restraint has severe consequences for adult plants which have greatly reduced biomass.

Optimizing a remotely sensed proxy for plankton biomass in Lake Kivu

Many regions of the world, including inland lakes, present with suboptimal conditions for the remotely sensed retrieval of optical signals, thus challenging the limits of available satellite data-processing tools, such as atmospheric correction models (ACM) and water constituent-retrieval (WCR) algorithms. Working in such regions, however, can improve our understanding of remote-sensing tools and their applicabil- ity in new contexts, in addition to potentially offering useful information about aquatic ecology. Here, we assess and compare 32 combinations of two ACMs, two WCRs, and three binary categories of data quality standards to optimize a remotely sensed proxy of plankton biomass in Lake Kivu. Each parameter set is compared against the available ground-truth match-ups using Spearman's right-tailed ρ. Focusing on the best sets from each ACM-WCR combination, their performances are discussed with regard to data distribution, sample size, spatial completeness, and seasonality. The results of this study may be of interest both for ecological studies on Lake Kivu and for epidemio- logical studies of disease, such as cholera, the dynamics of which has been associated with plankton biomass in other regions of the world.

Role of bacterial biomass in the sorption of Ni by biomass-birnessite assemblages

Birnessites precipitated by bacteria are typically poorly crystalline Mn(IV) oxides enmeshed within biofilms to form complex biomass-birnessite assemblages. The strong sorption affinity of bacteriogenic birnessites for environmentally important trace metals is relatively well understood mechanistically, but the role of bacterial cells and extracellular polymeric substances appears to vary among trace metals. To assess the role of biomass definitively, comparison between metal sorption by biomass at high metal loadings in the presence and absence of birnessite is required. We investigated the biomass effect on Ni sorption through laboratory experiments utilizing the birnessite produced by the model bacterium, Pseudomonas putida. Surface excess measurements at pH 6?8 showed that birnessite significantly enhanced Ni sorption at high loadings (up to nearly 4-fold) relative to biomass alone. This apparent large difference in affinity for Ni between the organic and mineral components was confirmed by extended X-ray absorption fine structure spectroscopy, which revealed preferential Ni binding to birnessite cation vacancy sites. At pH >= 7, Ni sorption involved both adsorption and precipitation reactions. Our results thus support the view that the biofilm does not block reactive mineral surface sites; instead, the organic material contributes to metal sorption once high-affinity sites on the mineral are saturated.

A spatial modelling framework for assessing climate change impacts on freshwater ecosystems: Response of brown trout (Salmo trutta L.) biomass to warming water temperature

Mountain regions worldwide are particularly sensitive to on-going climate change. Specifically in the Alps in Switzerland, the temperature has increased twice as fast than in the rest of the Northern hemisphere. Water temperature closely follows the annual air temperature cycle, severely impacting streams and freshwater ecosystems. In the last 20 years, brown trout (Salmo trutta L) catch has declined by approximately 40-50% in many rivers in Switzerland. Increasing water temperature has been suggested as one of the most likely cause of this decline. Temperature has a direct effect on trout population dynamics through developmental and disease control but can also indirectly impact dynamics via food-web interactions such as resource availability. We developed a spatially explicit modelling framework that allows spatial and temporal projections of trout biomass using the Aare river catchment as a model system, in order to assess the spatial and seasonal patterns of trout biomass variation. Given that biomass has a seasonal variation depending on trout life history stage, we developed seasonal biomass variation models for three periods of the year (Autumn-Winter, Spring and Summer). Because stream water temperature is a critical parameter for brown trout development, we first calibrated a model to predict water temperature as a function of air temperature to be able to further apply climate change scenarios. We then built a model of trout biomass variation by linking water temperature to trout biomass measurements collected by electro-fishing in 21 stations from 2009 to 2011. The different modelling components of our framework had overall a good predictive ability and we could show a seasonal effect of water temperature affecting trout biomass variation. Our statistical framework uses a minimum set of input variables that make it easily transferable to other study areas or fish species but could be improved by including effects of the biotic environment and the evolution of demographical parameters over time. However, our framework still remains informative to spatially highlight where potential changes of water temperature could affect trout biomass. (C) 2015 Elsevier B.V. All rights reserved.-