Anharmonic lattice dynamics and thermal transport in type-I inorganic clathrates

The anharmonic phonon properties of type-I filled inorganic clathrates Ba8Ga16Ge30 and Sr8Ga16Ge30 are obtained from the first-principles calculations by considering the temperature-dependent sampling of the potential energy surface and quartic phonon renormalization. Owing to the weak binding of guest atoms with the host lattice, the obtained guest modes undergo strong renormalization with temperature and become stiffer by up to 50% at room temperature in Sr8Ga16Ge30. The calculated phonon frequencies and associated thermal mean squared displace- ments are comparable with experiments despite the on-centering of guest atoms at cage centers in both clathrates. Lattice thermal conductivities are obtained in the temperature range of 50- 300 K accounting for three-phonon scattering processes and multi-channel thermal transport. The contribution of coherent transport channel is significant at room temperature (13% and 22% in Ba8Ga16Ge30 and Sr8Ga16Ge30) but is insufficient to explain the experimentally observed glass-like thermal transport in Sr8Ga16Ge30.

A Yeast-Based Functional Assay to Study Plant N-Degron – N-Recognin Interactions

The N-degron pathway is a branch of the ubiquitin-proteasome system where amino-terminal residues serve as degradation signals. In a synthetic biology approach, we expressed ubiquitin ligase PRT6 and ubiquitin conjugating enzyme 2 (AtUBC2) from Arabidopsis thaliana in a Saccharomyces cerevisiae strain with mutation in its endogenous N-degron pathway. The two enzymes re-constitute part of the plant N-degron pathway and were probed by monitoring the stability of co-expressed GFP-linked plant proteins starting with Arginine N-degrons. The novel assay allows for straightforward analysis, whereas in vitro interaction assays often do not allow detection of the weak binding of N-degron recognizing ubiquitin ligases to their substrates, and in planta testing is usually complex and time-consuming.

Neutrophil-mediated oxidative stress and albumin structural damage predict COVID-19-associated mortality

Human serum albumin (HSA) is the frontline antioxidant protein in blood with established anti-inflammatory and anticoagulation functions. Here we report that COVID-19-induced oxidative stress inflicts structural damages to HSA and is linked with mortality outcome in critically ill patients. We recruited 39 patients who were followed up for a median of 12.5 days (1-35 days), among them 23 had died. Analyzing blood samples from patients and healthy individuals (n=11), we provide evidence that neutrophils are major sources of oxidative stress in blood and that hydrogen peroxide is highly accumulated in plasmas of non-survivors. We then analyzed electron paramagnetic resonance (EPR) spectra of spin labelled fatty acids (SLFA) bound with HSA in whole blood of control, survivor, and non-survivor subjects (n=10-11). Non-survivor' HSA showed dramatically reduced protein packing order parameter, faster SLFA correlational rotational time, and smaller S/W ratio (strong-binding/weak-binding sites within HSA), all reflecting remarkably fluid protein microenvironments. Following loading/unloading of 16-DSA we show that transport function of HSA maybe impaired in severe patients. Stratified at the means, Kaplan–Meier survival analysis indicated that lower values of S/W ratio and accumulated H2O2 in plasma significantly predicted in-hospital mortality (S/W≤0.15, 81.8% (18/22) vs. S/W>0.15, 18.2% (4/22), p=0.023; plasma [H2O2]>8.6 mM, 65.2% (15/23) vs. 34.8% (8/23), p=0.043). When we combined these two parameters as the ratio ((S/W)/[H2O2]) to derive a risk score, the resultant risk score lower than the mean (< 0.019) predicted mortality with high fidelity (95.5% (21/22) vs. 4.5% (1/22), logrank c2 = 12.1, p=4.9x10-4). The derived parameters may provide a surrogate marker to assess new candidates for COVID-19 treatments targeting HSA replacements and/or oxidative stress.

Proteins mediating different DNA topologies block RNAP elongation with different efficiency

Many DNA-binding proteins induce topological structures such as loops or wraps through binding to two or more sites along the DNA. Such topologies may regulate transcription initiation and may also be roadblocks for elongating RNA polymerase (RNAP). Remarkably, a lac repressor protein bound to a weak binding site (O2) does not obstruct RNAP in vitro but becomes an effective roadblock when securing a loop of 400 bp between two widely separated binding sites. To investigate whether topological structures mediated by proteins bound to closely spaced binding sites and interacting cooperatively also represent roadblocks, we compared the effect of the lambda CI and 186 CI repressors on RNAP elongation. Dimers of lambda CI can bind to two sets of adjacent sites separated by hundreds of bp and form a DNA loop via the interaction between their C-terminal domains. The 186 CI protein can form a wheel of seven dimers around which specific DNA binding sequences can wrap. Atomic force microscopy (AFM) was used to image transcription elongation complexes of DNA templates that contained binding sites for either the lambda or 186 CI repressor. While RNAP elongated past lambda CI on unlooped DNA, as well as past 186 CI-wrapped DNA, it did not pass the lambda CI-mediated loop. These results may indicate that protein-mediated loops with widely separated binding sites more effectively block transcription than a wrapped topology with multiple, closely spaced binding sites.

Rescuing Biologically Relevant Consensus Regions Across Replicated Samples

Motivation Protein-DNA binding sites of ChIP-seq experiments are identified where the binding affinity is significant based on a given threshold. The choice of the threshold is a trade-off between conservative region identification and discarding weak, but true binding sites. Results We argue the biological relevance of weak binding sites and the information they add when rescued. The sites are rescued using MSPC, which exploits replicates to lower the threshold required to identify a binding site while keeping a low false-positive rate. We extend MSPC to call consensus regions across any number of replicated samples, accounting for differences between biological and technical replicates. We observed several master transcription regulators (e.g., SP1 and GATA3) and HDAC2-GATA1 regulatory networks on rescued regions. Availability and implementation An implementation of the proposed method and the scripts to reproduce the performed analysis are freely available at https://genometric.github.io/MSPC/, MSPC is distributed as a command-line application, an R package available from Bioconductor (https://doi.org/doi:10.18129/B9.bioc.rmspc), and a C# library.

Binding methylarginines and methyllysines as free amino acids: a comparative study of multiple supramolecular host classes

Methylated free amino acids are an important class of targets for host-guest chemistry that have recognition properties distinct from those of methylated peptides and proteins. We present comparative binding studies for three different host classes that are each studied with multiple methylated arginines and lysines to determine fundamental structure-function relationships. The hosts studied are all anionic and include three calixarenes, two acyclic cucurbiturils, and two cleft-like hosts. We determined the binding association constants for a panel of methylated amino acids using indicator displacement assays. The calixarene hosts show weak binding that favours the higher methylation states, with the strongest binding observed for trimethyllysine. The acyclic cucurbiturils display stronger binding to the methylated amino acids, and some unique patterns of selectivity. The cleft-like hosts follow two different trends, one shallow host following similar trends to the calixarenes, and the other more closed host binding certain less-methylated amino acids stronger than their per-methylated counterparts. Molecular modeling sheds some light on the different preferences of different hosts. The results identify hosts with selectivities that will be useful for certain biomedical applications. The overall selectivity patterns are explained by a common framework that considers the topology, depth of binding pockets, and functional group participation across all host classes.

The Association of Human Leukocyte Antigen and COVID-19 in Southern China

HLA polymorphism is hypothesized to be associated with diverse immune responses towards infectious diseases. Herein, by comparing against multiple subpopulation groups as control, we confirmed that HLA-B*15:27 and HLA-DRB1*04:06 were associated with COVID-19 susceptibility in China. Both alleles were predicted to have weak binding affinities towards viral proteins.

ChIP-GSM: Inferring active transcription factor modules to predict functional regulatory elements

Transcription factors (TFs) often function as a module including both master factors and mediators binding at cis-regulatory regions to modulate nearby gene transcription. ChIP-seq profiling of multiple TFs makes it feasible to infer functional TF modules. However, when inferring TF modules based on co-localization of ChIP-seq peaks, often many weak binding events are missed, especially for mediators, resulting in incomplete identification of modules. To address this problem, we develop a ChIP-seq data-driven Gibbs Sampler to infer Modules (ChIP-GSM) using a Bayesian framework that integrates ChIP-seq profiles of multiple TFs. ChIP-GSM samples read counts of module TFs iteratively to estimate the binding potential of a module to each region and, across all regions, estimates the module abundance. Using inferred module-region probabilistic bindings as feature units, ChIP-GSM then employs logistic regression to predict active regulatory elements. Validation of ChIP-GSM predicted regulatory regions on multiple independent datasets sharing the same context confirms the advantage of using TF modules for predicting regulatory activity. In a case study of K562 cells, we demonstrate that the ChIP-GSM inferred modules form as groups, activate gene expression at different time points, and mediate diverse functional cellular processes. Hence, ChIP-GSM infers biologically meaningful TF modules and improves the prediction accuracy of regulatory region activities.