The significance of non-histone lysine methylation in cell biology and human disease is an emerging area of research exploration. The development of small molecule inhibitors that selectively and potently target enzymes that catalyze the addition of methyl-groups to lysine residues, such as the protein lysine mono-methyltransferase SMYD2, is an active area of drug discovery. Critical to the accurate assessment of biological function is the ability to identify target enzyme substrates and to define enzyme substrate specificity within the context of the cell. Here, using stable isotopic labeling with amino acids in cell culture (SILAC) coupled with immunoaffinity enrichment of mono-methyl-lysine (Kme1) peptides and mass spectrometry, we report a comprehensive, large-scale proteomic study of lysine mono-methylation, comprising a total of 1032 Kme1 sites in esophageal squamous cell carcinoma (ESCC) cells and 1861 Kme1 sites in ESCC cells overexpressing SMYD2. Among these Kme1 sites is a subset of 35 found to be potently down-regulated by both shRNA-mediated knockdown of SMYD2 and LLY-507, a selective small molecule inhibitor of SMYD2. In addition, we report specific protein sequence motifs enriched in Kme1 sites that are directly regulated by endogenous SMYD2 activity, revealing that SMYD2 substrate specificity is more diverse than expected. We further show direct activity of SMYD2 toward BTF3-K2, PDAP1-K126 as well as numerous sites within the repetitive units of two unique and exceptionally large proteins, AHNAK and AHNAK2. Collectively, our findings provide quantitative insights into the cellular activity and substrate recognition of SMYD2 as well as the global landscape and regulation of protein mono-methylation. Protein lysine methyltransferases (PKMTs) 1 catalyze the sequence-specific transfer of one, two, or three methyl groups to the side chains of lysine residues (1-4). In addition to the extensively studied lysine methylation on histones, PKMTs can modify non-histone proteins (3,(5)(6)(7)(8)). An increasing number of non-histone proteins have been reported as PKMT substrates, and, as a result, potential roles for the dysregulation of non-histone lysine methylation in cancer development and progression have been proposed (9). The majority of PKMT substrates have been identified based on biochemical methylation assays using recombinant enzyme and substrate, followed by cell-based assays typically requiring overexpression of enzyme and/or substrate to maximize signal detection (10 -13). However, it is difficult to discern whether these substrates are bona fide physiological substrates of endogenous PKMT activity. With the development of PKMT-targeted drugs emerging as a key area of drug discovery (14 -18), unbiased and quantitative methods enabling the comprehensive identification of histone and non-histone substrates in cells are critical to clarifying the cell-relevant substrates of these enzymes and to more accurately understand the functions of non-histone methylation.Progressing from targeted biochemical...

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Satellite gravimetry data acquired by the Gravity Recovery and Climate Experiment (GRACE) allows to derive the temporal evolution in ice mass for both the Antarctic Ice Sheet (AIS) and the Greenland Ice Sheet (GIS). Various algorithms have been used in a wide range of studies to generate Gravimetric Mass Balance (GMB) products. Results from different studies may be affected by substantial differences in the processing, including the applied algorithm, the utilised background models and the time period under consideration. This study gives a detailed description of an assessment of the performance of GMB algorithms using actual GRACE monthly solutions for a prescribed period as well as synthetic data sets. The inter-comparison exercise was conducted in the scope of the European Space Agency’s Climate Change Initiative (CCI) project for the AIS and GIS, and was, for the first time, open to everyone. GMB products generated by different groups could be evaluated and directly compared against each other. For the period from 2003-02 to 2013-12, estimated linear trends in ice mass vary between −99 Gt/yr and −108 Gt/yr for the AIS and between −252 Gt/yr and −274 Gt/yr for the GIS, respectively. The spread between the solutions is larger if smaller drainage basins or gridded GMB products are considered. Finally, findings from the exercise formed the basis to select the algorithms used for the GMB product generation within the AIS and GIS CCI project.

In this study the feasibility and performance of time variable decorrelation (VADER) filters derived from covariance information on decadal Gravity Recovery and Climate Experiment (GRACE) time series are investigated. The VADER filter is based on publicly available data that are provided by several GRACE processing centers, and does not need its own Level-2 processing chain. Numerical closed loop simulations, incorporating stochastic and deterministic error budgets, serve as basis for the design of the filter setup, and the resulting filters are subsequently applied for real data processing. The closed loop experiments demonstrate the impact of temporally varying error and signal covariance matrices that are used for the design of decorrelation filters. The results indicate an average reduction of cumulative geoid height errors of 15% using time-variable instead of static decorrelation. Based on the simulation experience, a real data filtering procedure is designed and set up. It is applied to the ITSG-Grace2014 time variable gravity field time series with its associated full monthly covariance matrices. To assess the validity of the approach, linear mass trend estimates for the Antarctic Peninsula are computed using VADER filters and compared to previous estimates from both, GRACE and other mass balance estimation techniques. The mass change results obtained show very good agreement with other estimates and are robust against variations of the filter strength. The DDK decorrelation filter serves as main benchmark for the assessment of the VADER filter. For comparable filter strengths the VADER filters achieve a better de-striping and deliver smaller formal errors than static filters like the DDK.

Abstract. The poorly known correction for the ongoing deformation of the solid Earth caused by glacial isostatic adjustment (GIA) is a major uncertainty in determining the mass balance of the Antarctic ice sheet from measurements of satellite gravimetry and to a lesser extent satellite altimetry. In the past decade, much progress has been made in consistently modeling ice sheet and solid Earth interactions; however, forward-modeling solutions of GIA in Antarctica remain uncertain due to the sparsity of constraints on the ice sheet evolution, as well as the Earth's rheological properties. An alternative approach towards estimating GIA is the joint inversion of multiple satellite data -namely, satellite gravimetry, satellite altimetry and GPS, which reflect, with different sensitivities, trends in recent glacial changes and GIA. Crucial to the success of this approach is the accuracy of the spacegeodetic data sets. Here, we present reprocessed rates of surface-ice elevation change (Envisat/Ice,