Object Coreference in German: The Reflexive sich as a Problem for Derivational Approaches to Binding

Despite Grewendorf’s well-known German binding data with the double-object verb zeigen ‘show’, where one object reflexively binds the other and which suggests that the direct object (DO) is generated higher than the indirect object (IO), this paper argues for the canonical surface order of IO > DO as base order. We highlight the exceptional status of Grewendorf’s examples, build on scope facts as well as a quantitative acceptability rating study, and exploit the fact that zeigen can also be used as inherently reflexive with idiomatic meaning. Appealing to the base configuration of the pieces of idiomatic expressions and considering different Spell-Out possibilities of coreferential objects in German, we show that the case, number, and gender underspecification of the anaphor sich poses a previously unnoticed problem for derivational approaches to binding.

The SARS-CoV-2 B.1.1.529 Omicron virus causes attenuated infection and disease in mice and hamsters

Despite the development and deployment of antibody and vaccine countermeasures, rapidly-spreading SARS-CoV-2 variants with mutations at key antigenic sites in the spike protein jeopardize their efficacy. The recent emergence of B.1.1.529, the Omicron variant1,2, which has more than 30 mutations in the spike protein, has raised concerns for escape from protection by vaccines and therapeutic antibodies. A key test for potential countermeasures against B.1.1.529 is their activity in pre-clinical rodent models of respiratory tract disease. Here, using the collaborative network of the SARS-CoV-2 Assessment of Viral Evolution (SAVE) program of the National Institute of Allergy and Infectious Diseases (NIAID), we evaluated the ability of multiple B.1.1.529 Omicron isolates to cause infection and disease in immunocompetent and human ACE2 (hACE2) expressing mice and hamsters. Despite modeling and binding data suggesting that B.1.1.529 spike can bind more avidly to murine ACE2, we observed attenuation of infection in 129, C57BL/6, and BALB/c mice as compared with previous SARS-CoV-2 variants, with limited weight loss and lower viral burden in the upper and lower respiratory tracts. Although K18-hACE2 transgenic mice sustained infection in the lungs, these animals did not lose weight. In wild-type and hACE2 transgenic hamsters, lung infection, clinical disease, and pathology with B.1.1.529 also were milder compared to historical isolates or other SARS-CoV-2 variants of concern. Overall, experiments from multiple independent laboratories of the SAVE/NIAID network with several different B.1.1.529 isolates demonstrate attenuated lung disease in rodents, which parallels preliminary human clinical data.

Alkali metal cations can inhibit non-covalent catalysis

The study concerns the effect of inorganic salts on supramolecular catalysis. The model reaction is the acid hydrolysis of the ammonium phenyl acetate derivative promoted by cucurbit[7]uril macrocycle. When salt is absent, the macrocycle is insensitive to the ionic strength of the solution, and the reaction rate linearly depends on the concentration of hydronium ions (H3O+). After the addition of inorganic salts, in particular, Na+ and K+ ions, the catalytic effect of the macrocycle is suppressed. The kinetic and binding data collected by us evidence the formation of the ternary complexes between the cations, macrocycle, and substrate, which are less prone to H3O+ attack. This type of inhibition corresponds to a rare uncompetitive model in contrast to a more common competitive one that relies on the displacement of the substrate. This study shows that special care must be taken when studying catalysis in solutions that contain metal cations, such as regular water and inorganic buffers.

TargetGeneReg 2.0: a comprehensive web-atlas for p53, p63, and cell cycle-dependent gene regulation

In recent years, our web-atlas at www.TargetGeneReg.org has enabled many researchers to uncover new biological insights and to identify novel regulatory mechanisms that affect p53 and the cell cycle – signaling pathways that are frequently dysregulated in diseases like cancer. Here, we provide a substantial upgrade of the database that comprises an extension to include non-coding genes and the transcription factors ΔNp63 and RFX7. TargetGeneReg 2.0 combines gene expression profiling and transcription factor DNA binding data to determine, for each gene, the response to p53, ΔNp63, and cell cycle signaling. It can be used to dissect common, cell type, and treatment-specific effects, identify the most promising candidates, and validate findings. We demonstrate the increased power and more intuitive layout of the resource using realistic examples.

L-Type Ca2+ Channel Regulation by Calmodulin and CaBP1

L-type voltage-gated Ca2+ channels (CaV1.2 and CaV1.3, called CaV) interact with the Ca2+ sensor proteins, calmodulin (CaM) and Ca2+ binding Protein 1 (CaBP1), that oppositely control Ca2+-dependent channel activity. CaM and CaBP1 can each bind to the IQ-motif within the C-terminal cytosolic domain of CaV, which promotes increased channel open probability under basal conditions. At elevated cytosolic Ca2+ levels (caused by CaV channel opening), Ca2+-bound CaM binding to CaV is essential for promoting rapid Ca2+-dependent channel inactivation (CDI). By contrast, CaV binding to CaBP1 prevents CDI and promotes Ca2+-induced channel opening (called CDF). In this review, I provide an overview of the known structures of CaM and CaBP1 and their structural interactions with the IQ-motif to help understand how CaM promotes CDI, whereas CaBP1 prevents CDI and instead promotes CDF. Previous electrophysiology studies suggest that Ca2+-free forms of CaM and CaBP1 may pre-associate with CaV under basal conditions. However, previous Ca2+ binding data suggest that CaM and CaBP1 are both calculated to bind to Ca2+ with an apparent dissociation constant of ~100 nM when CaM or CaBP1 is bound to the IQ-motif. Since the neuronal basal cytosolic Ca2+ concentration is ~100 nM, nearly half of the neuronal CaV channels are suggested to be bound to Ca2+-bound forms of either CaM or CaBP1 under basal conditions. The pre-association of CaV with calcified forms of CaM or CaBP1 are predicted here to have functional implications. The Ca2+-bound form of CaBP1 is proposed to bind to CaV under basal conditions to block CaV binding to CaM, which could explain how CaBP1 might prevent CDI.

Processing binding data using an open-source workflow

The thermal shift assay (TSA)—also known as differential scanning fluorimetry (DSF), thermofluor, and Tm shift—is one of the most popular biophysical screening techniques used in fragment-based ligand discovery (FBLD) to detect protein–ligand interactions. By comparing the thermal stability of a target protein in the presence and absence of a ligand, potential binders can be identified. The technique is easy to set up, has low protein consumption, and can be run on most real-time polymerase chain reaction (PCR) instruments. While data analysis is straightforward in principle, it becomes cumbersome and time-consuming when the screens involve multiple 96- or 384-well plates. There are several approaches that aim to streamline this process, but most involve proprietary software, programming knowledge, or are designed for specific instrument output files. We therefore developed an analysis workflow implemented in the Konstanz Information Miner (KNIME), a free and open-source data analytics platform, which greatly streamlined our data processing timeline for 384-well plates. The implementation is code-free and freely available to the community for improvement and customization to accommodate a wide range of instrument input files and workflows. Graphical Abstract

target: an R package to predict combined function of transcription factors

Researchers use ChIP binding data to identify potential transcription factor binding sites. Similarly, they use gene expression data from sequencing or microarrays to quantify the effect of the transcription factor overexpression or knockdown on its targets. Therefore, the integration of the binding and expression data can be used to improve the understanding of a transcription factor function. Here, we implemented the binding and expression target analysis (BETA) in an R/Bioconductor package. This algorithm ranks the targets based on the distances of their assigned peaks from the transcription factor ChIP experiment and the signed statistics from gene expression profiling with transcription factor perturbation. We further extend BETA to integrate two sets of data from two transcription factors to predict their targets and their combined functions. In this article, we briefly describe the workings of the algorithm and provide a workflow with a real dataset for using it. The gene targets and the aggregate functions of transcription factors YY1 and YY2 in HeLa cells were identified. Using the same datasets, we identified the shared targets of the two transcription factors, which were found to be, on average, more cooperatively regulated.

target: an R package to predict combined function of transcription factors

Researchers use ChIP binding data to identify potential transcription factor binding sites. Similarly, they use gene expression data from sequencing or microarrays to quantify the effect of the factor overexpression or knockdown on its targets. Therefore, the integration of the binding and expression data can be used to improve the understanding of a transcription factor function. Here, we implemented the binding and expression target analysis (BETA) in an R/Bioconductor package. This algorithm ranks the targets based on the distances of their assigned peaks from the factor ChIP experiment and the signed statistics from gene expression profiling with factor perturbation. We further extend BETA to integrate two sets of data from two factors to predict their targets and their combined functions. In this article, we briefly describe the workings of the algorithm and provide a workflow with a real dataset for using it. The gene targets and the aggregate functions of transcription factors YY1 and YY2 in HeLa cells were identified. Using the same datasets, we identified the shared targets of the two factors, which were found to be, on average, more cooperatively regulated.

A comprehensive thermodynamic model for RNA binding by the Saccharomyces cerevisiae Pumilio protein PUF4

Genomic methods have been valuable for identifying RNA-binding proteins (RBPs) and the genes, pathways, and processes they regulate. Nevertheless, standard motif descriptions cannot be used to predict all RNA targets or test quantitative models for cellular interactions and regulation. We present a complete thermodynamic model for RNA binding to the S. cerevisiae Pumilio protein PUF4 derived from direct binding data for 6180 RNAs measured using the RNA on a massively parallel array (RNA-MaP) platform. The PUF4 model is highly similar to that of the related RBPs, human PUM2 and PUM1, with one marked exception: a single favorable site of base flipping for PUF4, such that PUF4 preferentially binds to a non-contiguous series of residues. These results are foundational for developing and testing cellular models of RNA-RBP interactions and function, for engineering RBPs, for understanding the biophysical nature of RBP binding and the evolutionary landscape of RNAs and RBPs.