Inundation prediction in tropical wetlands from JULES-CaMa-Flood global land surface simulations

Wetlands play a key role in hydrological and biogeochemical cycles and provide multiple ecosystem services to society. However, reliable data on the extent of global inundated areas and the magnitude of their contribution to local hydrological dynamics remain surprisingly uncertain. Global hydrological models and land surface models (LSMs) include only the most major inundation sources and mechanisms; therefore, quantifying the uncertainties in available data sources remains a challenge. We address these problems by taking a leading global data product on inundation extents (Global Inundation Extent from Multi-Satellites, GIEMS) and matching against predictions from a global hydrodynamic model (Catchment-based Macro-scale Floodplain – CaMa-Flood) driven by runoff data generated by a land surface model (Joint UK Land and Environment Simulator, JULES). The ability of the model to reproduce patterns and dynamics shown by the observational product is assessed in a number of case studies across the tropics, which show that it performs well in large wetland regions, with a good match between corresponding seasonal cycles. At a finer spatial scale, we found that water inputs (e.g. groundwater inflow to wetland) became underestimated in comparison to water outputs (e.g. infiltration and evaporation from wetland) in some wetlands (e.g. Sudd, Tonlé Sap), and the opposite occurred in others (e.g. Okavango) in our model predictions. We also found evidence for an underestimation of low levels of inundation in our satellite-based inundation data (approx. 10 % of total inundation may not be recorded). Additionally, some wetlands display a clear spatial displacement between observed and simulated inundation as a result of overestimation or underestimation of overbank flooding upstream. This study provides timely information on inherent biases in inundation prediction and observation that can contribute to our current ability to make critical predictions of inundation events at both regional and global levels

Strategies for Conditional Regulation of Proteins.

Design of the next-generation of therapeutics, biosensors, and molecular tools for basic research requires that we bring protein activity under control. Each protein has unique properties, and therefore, it is critical to tailor the current techniques to develop new regulatory methods and regulate new proteins of interest (POIs). This perspective gives an overview of the widely used stimuli and synthetic and natural methods for conditional regulation of proteins

Strategies for Conditional Regulation of Proteins.

Design of the next-generation of therapeutics, biosensors, and molecular tools for basic research requires that we bring protein activity under control. Each protein has unique properties, and therefore, it is critical to tailor the current techniques to develop new regulatory methods and regulate new proteins of interest (POIs). This perspective gives an overview of the widely used stimuli and synthetic and natural methods for conditional regulation of proteins

Measuring and Managing Ratio Compression for Accurate iTRAQ/TMT Quantification

Isobaric mass tagging (e.g., TMT and iTRAQ) is a precise and sensitive multiplexed peptide/protein quantification technique in mass spectrometry. However, accurate quantification of complex proteomic samples is impaired by cofragmentation of peptides, leading to systematic underestimation of quantitative ratios. Label-free quantification strategies do not suffer from such an accuracy bias but cannot be multiplexed and are less precise. Here, we compared protein quantification results obtained with these methods for a chemoproteomic competition binding experiment and evaluated the utility of measures of spectrum purity in survey spectra for estimating the impact of cofragmentation on measured TMT-ratios. While applying stringent interference filters enables substantially more accurate TMT quantification, this came at the expense of 30%–60% fewer proteins quantified. We devised an algorithm that corrects experimental TMT ratios on the basis of determined peptide interference levels. The quantification accuracy achieved with this correction was comparable to that obtained with stringent spectrum filters but limited the loss in coverage to <10%. The generic applicability of the fold change correction algorithm was further demonstrated by spiking of chemoproteomics samples into excess amounts of <i>E. coli</i> tryptic digests

Systematic analysis of protein turnover in primary cells

The proteome-wide characterization of proteostasis depends on robust approaches to determine protein half-lives. Here, the authors improve the accuracy and precision of mass spectrometry-based quantification, enabling reliable protein half-life determination in several non-dividing cell types