Evaluation of chloroform/methanol extraction to facilitate the study of membrane proteins of non-model plants

Membrane proteins are of great interest to plant physiologists because of their important function in many physiological processes. However, their study is hampered by their low abundance and poor solubility in aqueous buffers. Proteomics studies of non-model plants are generally restricted to gel-based methods. Unfortunately, all gel-based techniques for membrane proteomics lack resolving power. Therefore, a very stringent enrichment method is needed before protein separation. In this study, protein extraction in a mixture of chloroform and methanol in combination with gel electrophoresis is evaluated as a method to study membrane proteins in non-model plants. Benefits as well as disadvantages of the method are discussed. To demonstrate the pitfalls of working with non-model plants and to give a proof of principle, the method was first applied to whole leaves of the model plant Arabidopsis. Subsequently, a comparison with proteins extracted from leaves of the non-model plant, banana, was made. To estimate the tissue and organelle specificity of the method, it was also applied on banana meristems. Abundant membrane or lipid-associated proteins could be identified in both tissues, with the leaf extract yielding a higher number of membrane proteins.     

Plant-water regime management in a wetland: consequences for a floating vegetation-nesting bird, whiskered tern Chlidonias hybridus

In this study we investigated the interplay between water level management, floating macrophytic vegetation and nesting whiskered tern (Chlidonias hybridus) during 8 years (1995–2002) at a shallow macrophyte-dominated lake in western France. The specific question was to see if slight increases in the water regime of the lake (three scenarios), as part of a restoration programme, affect the timing of nesting and occupation of colonies by whiskered terns by way of changes in biomass of waterlily (Nymphaea alba) beds where colonies always establish. During the study period, egg-laying dates were progressively delayed up to 40–50 days (mid-May to early July) in relation to late appearance of suitable waterlily biomass (R ² = 0.67, p = 0.01) associated with high spring water levels (1.10–1.25 m vs. 0.95 m). Simultaneously some nesting attempts were observed in sub-optimal habitats (adjacent wet grasslands) in high flooding conditions leading either to poor breeding success or colony desertion. We concluded that there is a need for compromise between the experimental water levels used to control waterlily biomass and the nesting requirements of the whiskered tern population in this lake of international importance (260–510 pairs in 1995–2002, ≥ 1% Ramsar level).     

Value Choices in Life Cycle Impact Assessment of Stressors Causing Human Health Damage

This article investigates how value choices in life cycle impact assessment can influence characterization factors (CFs) for human health (expressed as disability‐adjusted life years [DALYs]). The Cultural Theory is used to define sets of value choices in the calculation of CFs, reflecting the individualist, hierarchist, and egalitarian perspectives. CFs were calculated for interventions related to the following impact categories: water scarcity, tropospheric ozone formation, particulate matter formation, human toxicity, ionizing radiation, stratospheric ozone depletion, and climate change. With the Cultural Theory as a framework, we show that individualist, hierarchist, and egalitarian perspectives can lead to CFs that vary up to six orders of magnitude. For persistent substances, the choice in time horizon explains the differences among perspectives, whereas for nonpersistent substances, the choice in age weighting and discount rate of DALY and the type of effects or exposure routes account for differences in CFs. The calculated global impact varies by two orders of magnitude, depending on the perspective selected, and derives mainly from particulate matter formation and water scarcity for the individualist perspective and from climate change for the egalitarian perspective. Our results stress the importance of dealing with value choices in life cycle impact assessment and suggest further research for analyzing the practical consequences for life cycle assessment results.     

4-Phenyl-7-azaindoles as potent and selective IKK2 inhibitors

The synthesis and SAR of a novel series of IKK2 inhibitors are described. Modification around the hinge binding region of the 7-azaindole led to a series of potent and selective inhibitors with good cellular activity.     

Generating functional protein variants with variational autoencoders

The vast expansion of protein sequence databases provides an opportunity for new protein design approaches which seek to learn the sequence-function relationship directly from natural sequence variation. Deep generative models trained on protein sequence data have been shown to learn biologically meaningful representations helpful for a variety of downstream tasks, but their potential for direct use in the design of novel proteins remains largely unexplored. Here we show that variational autoencoders trained on a dataset of almost 70000 luciferase-like oxidoreductases can be used to generate novel, functional variants of the luxA bacterial luciferase. We propose separate VAE models to work with aligned sequence input (MSA VAE) and raw sequence input (AR-VAE), and offer evidence that while both are able to reproduce patterns of amino acid usage characteristic of the family, the MSA VAE is better able to capture long-distance dependencies reflecting the influence of 3D structure. To confirm the practical utility of the models, we used them to generate variants of luxA whose luminescence activity was validated experimentally. We further showed that conditional variants of both models could be used to increase the solubility of luxA without disrupting function. Altogether 6/12 of the variants generated using the unconditional AR-VAE and 9/11 generated using the unconditional MSA VAE retained measurable luminescence, together with all 23 of the less distant variants generated by conditional versions of the models; the most distant functional variant contained 35 differences relative to the nearest training set sequence. These results demonstrate the feasibility of using deep generative models to explore the space of possible protein sequences and generate useful variants, providing a method complementary to rational design and directed evolution approaches.     

The Past and Future of Tuberculosis Research

Renewed efforts in tuberculosis (TB) research have led to important new insights into the biology and epidemiology of this devastating disease. Yet, in the face of the modern epidemics of HIV/AIDS, diabetes, and multidrug resistance—all of which contribute to susceptibility to TB—global control of the disease will remain a formidable challenge for years to come. New high-throughput genomics technologies are already contributing to studies of TB''s epidemiology, comparative genomics, evolution, and host–pathogen interaction. We argue here, however, that new multidisciplinary approaches—especially the integration of epidemiology with systems biology in what we call “systems epidemiology”—will be required to eliminate TB.