Loss of mouse Stmn2 function causes motor neuropathy.

Amyotrophic lateral sclerosis (ALS) is characterized by motor neuron degeneration accompanied by aberrant accumulation and loss of function of the RNA-binding protein TDP43. Thus far, it remains unresolved to what extent TDP43 loss of function directly contributes to motor system dysfunction. Here, we employed gene editing to find whether the mouse ortholog of the TDP43-regulated gene STMN2 has an important function in maintaining the motor system. Both mosaic founders and homozygous loss-of-function Stmn2 mice exhibited neuromuscular junction denervation and fragmentation, resulting in muscle atrophy and impaired motor behavior, accompanied by an imbalance in neuronal microtubule dynamics in the spinal cord. The introduction of human STMN2 through BAC transgenesis was sufficient to rescue the motor phenotypes observed in Stmn2 mutant mice. Collectively, our results demonstrate that disrupting the ortholog of a single TDP43-regulated RNA is sufficient to cause substantial motor dysfunction, indicating that disruption of TDP43 function is likely a contributor to ALS.

Craniofacial growth in infants with deformational plagiocephaly: does prematurity affect the duration of head orthosis therapy and the extent of the reduction in asymmetry during treatment?

OBJECTIVE: Although prematurity is a risk factor for developing deformational plagiocephaly (DP), to our knowledge, there are no studies that have analyzed the impact of a premature birth on the duration of head orthosis therapy and the extent of the reduction in asymmetry during treatment. MATERIALS AND METHODS: We examined 239 patients with DP who were undergoing head orthosis therapy. Depending on the gestational age, they were assigned to either a premature (gestational age of < 37 weeks) or a full-term (gestational age of ≥ 37 weeks) group. Head shape was analyzed using 3D-stereophotogrammetry at the start and end of treatment. We performed multiple linear regression analyses to evaluate the impact of prematurity on the duration of therapy and the extent of the reduction in asymmetry, taking age and the initial asymmetry of an infant's head into account. RESULTS: Head orthosis therapy led to a significant reduction in asymmetry in both groups. Using multiple linear regression analyses, we demonstrated that age at the start of treatment, the initial asymmetry and prematurity, significantly influenced the duration of therapy. Patients who were born at an earlier gestational age experienced a shorter treatment length. However, prematurity did not affect the extent of the reduction in cranial asymmetry that was achieved. CONCLUSIONS: Along with age at the start of treatment and the initial asymmetry, prematurity is significantly correlated with the duration of head orthosis therapy, but not with the extent of the reduction in asymmetry achieved. CLINICAL RELEVANCE: Knowledge of these findings is important for clinicians when planning treatment and discussing the effectiveness of head orthosis therapy with the parents of premature infants with DP.

Prediction and benefits of minimal disease activity in patients with psoriatic arthritis and active skin disease in the ADEPT trial.

OBJECTIVES: To determine the proportion of patients with psoriatic arthritis in the Adalimumab Effectiveness in Psoriatic Arthritis trial achieving minimal disease activity (MDA) and its individual components at 1 or more visits over 144 weeks, identify baseline predictors of MDA achievement, and evaluate the association of MDA status with independent quality of life (QoL)-related patient-reported outcomes (PROs). METHODS: Univariate and multivariate analyses were used to identify the baseline characteristics that predicted achievement of MDA at individual time points (weeks 12 through 144) or sustained MDA (achievement of MDA at 2 consecutive time points 12 weeks apart). The association of independent QoL-related PROs with MDA achievement was evaluated at weeks 24 and 144. RESULTS: In univariate analyses, higher baseline patient assessment of pain, tender joint count (TJC), enthesitis and Health Assessment Questionnaire-Disability Index (HAQ-DI) score were significantly associated with lower likelihood of achieving MDA at later time points. Multivariate analyses confirmed higher baseline HAQ-DI as a significant predictor for failure to achieve MDA at later time points. Achievement of sustained MDA was associated with lower baseline TJC and HAQ-DI score. Achievement of different MDA components appeared to be treatment dependent. MDA achievers had significantly better QoL-related PROs and greater improvements in PROs from baseline to week 24 compared with non-achievers. CONCLUSIONS: Higher HAQ-DI score was the most consistent baseline factor that decreased the likelihood of achieving MDA and sustained MDA at later time points. Achieving MDA was associated with better independent QoL-related PROs.

pROC-Chemotype Plots Enhance the Interpretability of Benchmarking Results in Structure-Based Virtual Screening.

Recently, we have reported a systematic comparison of molecular preparation protocols (using MOE or Maestro) in combination with two docking tools (GOLD or Glide), employing our DEKOIS 2.0 benchmark sets. Herein, we demonstrate how comparable settings of data preparation protocols can affect the profile and AUC of pROC curves based on variations in chemotype enrichment. We show how the recognition of different classes of chemotypes can affect the docking performance, particularly in the early enrichment, and monitor changes in this recognition behavior based on score normalization and rescoring strategies. For this, we have developed "pROC-Chemotype", which is an automated protocol that matches and visualizes ligand chemotype information together with potency classes in the pROC profiles obtained by docking. This tool enhances the understanding of the influence of chemotype recognition in early enrichment, but also reveals trends of impaired recognition of chemotype classes at the end of the score-ordered rank. Identifying such issues helps to devise score-normalization strategies to overcome this potential bias in an intuitive manner. Furthermore, strong perturbations in chemotype ranking between different methods can help to identify the underlying reasons (e.g., changes in the protonation/tautomerization state). It also assists in the selection of appropriate scoring functions that are capable to retrieve more potent and diverse hits. In summary, we demonstrate how this new tool can be utilized to identify and highlight chemotype-specific behavior, e.g., in dataset preparation. This can help to overcome some chemistry-related bias in virtual screening campaigns. pROC-Chemotype is made freely available at www.dekois.com.

A ranking method for the concurrent learning of compounds with various activity profiles.

BACKGROUND: In this study, we present a SVM-based ranking algorithm for the concurrent learning of compounds with different activity profiles and their varying prioritization. To this end, a specific labeling of each compound was elaborated in order to infer virtual screening models against multiple targets. We compared the method with several state-of-the-art SVM classification techniques that are capable of inferring multi-target screening models on three chemical data sets (cytochrome P450s, dehydrogenases, and a trypsin-like protease data set) containing three different biological targets each. RESULTS: The experiments show that ranking-based algorithms show an increased performance for single- and multi-target virtual screening. Moreover, compounds that do not completely fulfill the desired activity profile are still ranked higher than decoys or compounds with an entirely undesired profile, compared to other multi-target SVM methods. CONCLUSIONS: SVM-based ranking methods constitute a valuable approach for virtual screening in multi-target drug design. The utilization of such methods is most helpful when dealing with compounds with various activity profiles and the finding of many ligands with an already perfectly matching activity profile is not to be expected.

Referral patterns, diagnosis, and disease management of patients with axial spondyloarthritis: results of an international survey.

BACKGROUND: Recognition, diagnosis, and management of axial spondyloarthritis (axial SpA) continue to advance. OBJECTIVES: The objectives of this study were to compare referrals, diagnosis, and management of axial SpA in Western Europe (WE), North America (US and Canada), and the rest of world (RoW) in academic and community rheumatology practices and to identify areas for further education. METHODS: Rheumatologists responded online to the MAXIMA (Management of Axial SpA International and Multicentric Approaches) survey. Questions pertained to referral, diagnosis, and management of axial SpA. RESULTS: Rheumatologists (N = 809) from 56 countries completed the survey about patients with chronic back pain (≥3 months) starting before age 45 years. Responses from academic and community practice rheumatologists were generally similar. Most referrals were from primary care providers. Symptom duration of 3 years or more at referral was reported more frequently by WE and RoW than US respondents. More WE and RoW than US rheumatologists referred to the Assessment of SpondyloArthritis International Society criteria for axial SpA in clinical practice. Rheumatologists reported prescribing disease-modifying antirheumatic drugs for the management of axial SpA. Sulfasalazine was frequently prescribed across regions; methotrexate was more commonly prescribed by US rheumatologists compared with other regions. CONCLUSIONS: Referral patterns, diagnosis, and disease management for axial SpA were similar among WE, North America, and RoW rheumatologists and in academic/community practices, although more WE and RoW rheumatologists referred to Assessment of SpondyloArthritis International Society criteria in clinical practice. Disease-modifying antirheumatic drugs were commonly prescribed for axial SpA patients, although it was unclear whether these were prescribed for axial or peripheral symptoms.

SBMLSimulator: A Java Tool for Model Simulation and Parameter Estimation in Systems Biology.

The identification of suitable model parameters for biochemical reactions has been recognized as a quite difficult endeavor. Parameter values from literature or experiments can often not directly be combined in complex reaction systems. Nature-inspired optimization techniques can find appropriate sets of parameters that calibrate a model to experimentally obtained time series data. We present SBMLsimulator, a tool that combines the Systems Biology Simulation Core Library for dynamic simulation of biochemical models with the heuristic optimization framework EvA2. SBMLsimulator provides an intuitive graphical user interface with various options as well as a fully-featured command-line interface for large-scale and script-based model simulation and calibration. In a parameter estimation study based on a published model and artificial data we demonstrate the capability of SBMLsimulator to identify parameters. SBMLsimulator is useful for both, the interactive simulation and exploration of the parameter space and for the large-scale model calibration and estimation of uncertain parameter values.

The systems biology simulation core algorithm.

BACKGROUND: With the increasing availability of high dimensional time course data for metabolites, genes, and fluxes, the mathematical description of dynamical systems has become an essential aspect of research in systems biology. Models are often encoded in formats such as SBML, whose structure is very complex and difficult to evaluate due to many special cases. RESULTS: This article describes an efficient algorithm to solve SBML models that are interpreted in terms of ordinary differential equations. We begin our consideration with a formal representation of the mathematical form of the models and explain all parts of the algorithm in detail, including several preprocessing steps. We provide a flexible reference implementation as part of the Systems Biology Simulation Core Library, a community-driven project providing a large collection of numerical solvers and a sophisticated interface hierarchy for the definition of custom differential equation systems. To demonstrate the capabilities of the new algorithm, it has been tested with the entire SBML Test Suite and all models of BioModels Database. CONCLUSIONS: The formal description of the mathematics behind the SBML format facilitates the implementation of the algorithm within specifically tailored programs. The reference implementation can be used as a simulation backend for Java™-based programs. Source code, binaries, and documentation can be freely obtained under the terms of the LGPL version 3 from http://simulation-core.sourceforge.net. Feature requests, bug reports, contributions, or any further discussion can be directed to the mailing list simulation-core-development@lists.sourceforge.net.

Inferring multi-target QSAR models with taxonomy-based multi-task learning.

BACKGROUND: A plethora of studies indicate that the development of multi-target drugs is beneficial for complex diseases like cancer. Accurate QSAR models for each of the desired targets assist the optimization of a lead candidate by the prediction of affinity profiles. Often, the targets of a multi-target drug are sufficiently similar such that, in principle, knowledge can be transferred between the QSAR models to improve the model accuracy. In this study, we present two different multi-task algorithms from the field of transfer learning that can exploit the similarity between several targets to transfer knowledge between the target specific QSAR models. RESULTS: We evaluated the two methods on simulated data and a data set of 112 human kinases assembled from the public database ChEMBL. The relatedness between the kinase targets was derived from the taxonomy of the humane kinome. The experiments show that multi-task learning increases the performance compared to training separate models on both types of data given a sufficient similarity between the tasks. On the kinase data, the best multi-task approach improved the mean squared error of the QSAR models of 58 kinase targets. CONCLUSIONS: Multi-task learning is a valuable approach for inferring multi-target QSAR models for lead optimization. The application of multi-task learning is most beneficial if knowledge can be transferred from a similar task with a lot of in-domain knowledge to a task with little in-domain knowledge. Furthermore, the benefit increases with a decreasing overlap between the chemical space spanned by the tasks.

Optimization and visualization of the edge weights in optimal assignment methods for virtual screening.

BACKGROUND: Ligand-based virtual screening plays a fundamental part in the early drug discovery stage. In a virtual screening, a chemical library is searched for molecules with similar properties to a query molecule by means of a similarity function. The optimal assignment of chemical graphs has proven to be a valuable similarity function for many cheminformatic tasks, such as virtual screening. The optimal assignment assumes all atoms of a query molecule to be equally important, which is not realistic depending on the binding mode of a ligand. The importance of a query molecule's atoms can be integrated in the optimal assignment by weighting the assignment edges. We optimized the edge weights with respect to the virtual screening performance by means of evolutionary algorithms. Furthermore, we propose a visualization approach for the interpretation of the edge weights. RESULTS: We evaluated two different evolutionary algorithms, differential evolution and particle swarm optimization, for their suitability for optimizing the assignment edge weights. The results showed that both optimization methods are suited to optimize the edge weights. Furthermore, we compared our approach to the optimal assignment with equal edge weights and two literature similarity functions on a subset of the Directory of Useful Decoys using sophisticated virtual screening performance metrics. Our approach achieved a considerably better overall and early enrichment performance. The visualization of the edge weights enables the identification of substructures that are important for a good retrieval of ligands and for the binding to the protein target. CONCLUSIONS: The optimization of the edge weights in optimal assignment methods is a valuable approach for ligand-based virtual screening experiments. The approach can be applied to any similarity function that employs the optimal assignment method, which includes a variety of similarity measures that have proven to be valuable in various cheminformatic tasks. The proposed visualization helps to get a better understanding of the binding mode of the analyzed query molecule.

JSBML: a flexible Java library for working with SBML.

SUMMARY: The specifications of the Systems Biology Markup Language (SBML) define standards for storing and exchanging computer models of biological processes in text files. In order to perform model simulations, graphical visualizations and other software manipulations, an in-memory representation of SBML is required. We developed JSBML for this purpose. In contrast to prior implementations of SBML APIs, JSBML has been designed from the ground up for the Java programming language, and can therefore be used on all platforms supported by a Java Runtime Environment. This offers important benefits for Java users, including the ability to distribute software as Java Web Start applications. JSBML supports all SBML Levels and Versions through Level 3 Version 1, and we have strived to maintain the highest possible degree of compatibility with the popular library libSBML. JSBML also supports modules that can facilitate the development of plugins for end user applications, as well as ease migration from a libSBML-based backend. AVAILABILITY: Source code, binaries and documentation for JSBML can be freely obtained under the terms of the LGPL 2.1 from the website http://sbml.org/Software/JSBML.

Genotypic features of lentivirus transgenic mice.

Lentivector-mediated transgenesis is increasingly used, whether for basic studies as an alternative to pronuclear injection of naked DNA or to test candidate gene therapy vectors. In an effort to characterize the genetic features of this approach, we first measured the frequency of germ line transmission of individual proviruses established by infection of fertilized mouse oocytes. Seventy integrants from 11 founder (G0) mice were passed to 111 first generation (G1) pups, for a total of 255 events corresponding to an average rate of transmission of 44%. This implies that integration had most often occurred at the one- or two-cell stage and that the degree of genotypic mosaicism in G0 mice obtained through this approach is generally minimal. Transmission analysis of eight individual proviruses in 13 G2 mice obtained by a G0-G1 cross revealed only 8% of proviral homozygosity, significantly below the 25% expected from purely Mendelian transmission, suggesting counter-selection due to interference with the functions of targeted loci. Mapping of 239 proviral integration sites in 49 founder animals revealed that about 60% resided within annotated genes, with a marked tendency for clustering in the middle of the transcribed region, and that integration was not influenced by the transcriptional orientation. Transcript levels of a set of arbitrarily chosen target genes were significantly higher in two-cell embryos than in embryonic stem cells or adult somatic cells, suggesting that, as previously noted in other settings, lentiviral vectors integrate preferentially into regions of the genome that are transcriptionally active or poised for activation.

SIRT1 regulates HIV transcription via Tat deacetylation.

The human immunodeficiency virus (HIV) Tat protein is acetylated by the transcriptional coactivator p300, a necessary step in Tat-mediated transactivation. We report here that Tat is deacetylated by human sirtuin 1 (SIRT1), a nicotinamide adenine dinucleotide-dependent class III protein deacetylase in vitro and in vivo. Tat and SIRT1 coimmunoprecipitate and synergistically activate the HIV promoter. Conversely, knockdown of SIRT1 via small interfering RNAs or treatment with a novel small molecule inhibitor of the SIRT1 deacetylase activity inhibit Tat-mediated transactivation of the HIV long terminal repeat. Tat transactivation is defective in SIRT1-null mouse embryonic fibroblasts and can be rescued by expression of SIRT1. These results support a model in which cycles of Tat acetylation and deacetylation regulate HIV transcription. SIRT1 recycles Tat to its unacetylated form and acts as a transcriptional coactivator during Tat transactivation.

Tat acetylation: a regulatory switch between early and late phases in HIV transcription elongation.

The HIV transcriptional activator Tat enhances the processivity of RNA polymerase II by recruiting the CyclinT1/CDK9 complex to the TAR RNA element. In addition, Tat synergizes with the histone acetyltransferase p300 and is acetylated by p300 at a single lysine residue (K50) in the TAR RNA binding domain. We have recently reported that this post-translational modification is necessary for the interaction and transcriptional synergy of Tat with the transcriptional coactivator PCAF. We have further studied the relevance of Tat acetylation during HIV transcription and generated antibodies specific for acetylated Tat (AcTat). Microinjection of anti-AcTat antibodies inhibited Tat-mediated transactivation in cells. Similarly, the specific p300 inhibitor Lys-CoA and short inhibitory RNAs specific for p300 suppressed Tat transcriptional activity. Full-length synthetic AcTat bound to TAR RNA and CyclinT1 with high affinity, but formation of the Tat-TAR-CyclinT1 ternary complex was inhibited when K50 was acetylated. Our data collectively show that Tat acetylation by p300 defines a critical step in Tat transactivation that serves to disrupt the Tat/TAR/CyclinT1 complex and helps in recruiting PCAF to the elongating RNA polymerase II.

Acetylation of the HIV-1 Tat protein: an in vitro study.

In the last few years, the understanding of lysine acetylation as a regulatory post-translational modification of proteins in cell signalling cascades has increased. It is now known that not only histones but also non-histone factors can serve as substrates of different acetyltransferase enzymes. Acetylated lysine residues in non-histone factors are often identified using radioactive labelling experiments and immunochemical analysis of synthetic peptides. In this study of the human immunodeficiency virus 1 (HIV-1) Tat protein, we demonstrate the benefits of matrix-assisted laser desorption/ionisation mass spectrometry, proteolytic digestion and Edman sequencing for the mapping of acetylation sites. We confirmed that the HIV-1 Tat protein is acetylated in vitro by the acetyltransferase p300 at a specific lysine residue at position 50 in its RNA binding region. Furthermore, we showed that the Tat cysteine-rich region is acetylated at multiple cysteine residues in the absence of enzyme. Since this non-enzymatic cysteine acetylation occurs independently from the surrounding peptide sequence, we consider the presence of cysteine residues in acetylated peptides an important factor for the interpretation of in vitro acetylation assays in general.

Acetylation of Tat defines a cyclinT1-independent step in HIV transactivation.

The HIV transcriptional activator Tat is acetylated by p300 at a single lysine residue in the TAR RNA binding domain. We have generated monoclonal and polyclonal antibodies specific for the acetylated form of Tat (AcTat). Microinjection of anti-AcTat antibodies inhibited Tat-mediated transactivation in cells. Similarly, the p300 inhibitor Lys-CoA and siRNA specific for p300 suppressed Tat transcriptional activity. Full-length synthetic AcTat bound to TAR RNA with the same affinity as unacetylated Tat, but formation of a Tat-TAR-CyclinT1 ternary complex was completely inhibited in the presence of AcTat. We propose that Tat acetylation may help in dissociating the Tat cofactor CyclinT1 from TAR RNA and serve to transfer Tat onto the elongating RNA polymerase II.

Transcriptional synergy between Tat and PCAF is dependent on the binding of acetylated Tat to the PCAF bromodomain.

The human immunodeficiency virus (HIV) Tat protein plays an essential role in promoting efficient transcriptional elongation of viral transcripts. We report that the transcriptional co-activator PCAF and Tat interact and synergize to activate the HIV promoter. The binding of Tat and PCAF in vitro and in vivo is dependent on the acetylated state of Lys50 of Tat and on the PCAF bromodomain. Structural analysis of the acetylated Tat peptide bound to the PCAF bromodomain defined amino acids Y47 and R53 in Tat and V763, Y802, and Y809 in PCAF as critical interaction points between the two proteins. Mutation of each of these residues in either Tat or PCAF inhibited in a cumulative manner the Tat-PCAF interaction in vitro and in vivo, and abrogated the synergistic activation of the HIV promoter by both proteins. These observations demonstrate that acetylation of Tat establishes a novel protein-protein interaction domain at the surface of Tat that is necessary for the transcriptional activation of the HIV promoter.