黑龙江4种铁线莲色谱指纹特征比较分析

运用化学计量学方法,比较分析黑龙江4种铁线莲植物,辣蓼铁线莲、棉团铁线莲、褐毛铁线莲、齿叶铁线莲根及根茎石油醚提取物的色谱指纹特征。色谱-光谱数据的多元分辨结果表明4种铁线莲的色谱指纹特征中,总计至少有45种化学成分存在,共有的化学成分为14种,单独的化学成分分别为3、6、2及2种。聚类分析显示,辣蓼铁线莲与棉团铁线莲间的相似程度在4种铁线莲全部两-两组合的相似程度中最小。     

OpenAWSEM with Open3SPN2: A fast,flexible, and accessible framework for large-scale coarse-grained biomolecular simulations

We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM’s Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM’s Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen’s early Nobel prize winning experiments by using OpenMM’s Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.     

O-antigen modulates infection-induced pain States

The molecular initiators of infection-associated pain are not understood. We recently found that uropathogenic E. coli (UPEC) elicited acute pelvic pain in murine urinary tract infection (UTI). UTI pain was due to E. coli lipopolysaccharide (LPS) and its receptor, TLR4, but pain was not correlated with inflammation. LPS is known to drive inflammation by interactions between the acylated lipid A component and TLR4, but the function of the O-antigen polysaccharide in host responses is unknown. Here, we examined the role of O-antigen in pain using cutaneous hypersensitivity (allodynia) to quantify pelvic pain behavior and using sacral spinal cord excitability to quantify central nervous system manifestations in murine UTI. A UPEC mutant defective for O-antigen biosynthesis induced chronic allodynia that persisted long after clearance of transient infections, but wild type UPEC evoked only acute pain. E. coli strains lacking O-antigen gene clusters had a chronic pain phenotype, and expressing cloned O-antigen gene clusters altered the pain phenotype in a predictable manner. Chronic allodynia was abrogated in TLR4-deficient mice, but inflammatory responses in wild type mice were similar among E. coli strains spanning a wide range of pain phenotypes, suggesting that O-antigen modulates pain independent of inflammation. Spinal cords of mice with chronic allodynia exhibited increased spontaneous firing and compromised short-term depression, consistent with centralized pain. Taken together, these findings suggest that O-antigen functions as a rheostat to modulate LPS-associated pain. These observations have implications for an infectious etiology of chronic pain and evolutionary modification of pathogens to alter host behaviors.     

Downregulation of USP4 Promotes Activation of Microglia and Subsequent Neuronal Inflammation in Rat Spinal Cord After Injury

Neurochemical Research - NF-κB is involved in the activation of microglia, which induces secondary spinal cord injury (SCI). This process involves the activation of NF-κB signaling...     

The Biological Significance of Multi-copy Regions and Their Impact on Variant Discovery

Identification of genetic variants via high-throughput sequencing (HTS) technologies has been essential for both fundamental and clinical studies. However, to what extent the genome sequence composition affects variant calling remains unclear. In this study, we identified 63,897 multi-copy sequences (MCSs) with a minimum length of 300 bp, each of which occurs at least twice in the human genome. The 151,749 genomic loci (multi-copy regions, or MCRs) harboring these MCSs account for 1.98% of the genome and are distributed unevenly across chromosomes. MCRs containing the same MCS tend to be located on the same chromosome. Gene Ontology (GO) analyses revealed that 3800 genes whose UTRs or exons overlap with MCRs are enriched for Golgi-related cellular component terms and various enzymatic activities in the GO biological function category. MCRs are also enriched for loci that are sensitive to neocarzinostatin-induced double-strand breaks. Moreover, genetic variants discovered by genome-wide association studies and recorded in dbSNP are significantly underrepresented in MCRs. Using simulated HTS datasets, we show that false variant discovery rates are significantly higher in MCRs than in other genomic regions. These results suggest that extra caution must be taken when identifying genetic variants in the MCRs via HTS technologies.     

Lactic and hydrochloric acids induce different patterns of inflammatory response in LPS-stimulated RAW 264.7 cells

Metabolic acidosis frequently complicates sepsis and septic shock and may be deleterious to cellular function. Different types of metabolic acidosis (e.g., hyperchloremic and lactic acidosis) have been associated with different effects on the immune response, but direct comparative studies are lacking. Murine macrophage-like RAW 264.7 cells were cultured in complete medium with lactic acid or HCl to adjust the pH between 6.5 and 7.4 and then stimulated with LPS (Escherichia coli 0111:B4; 10 ng/ml). Nitric oxide (NO), IL-6, and IL-10 levels were measured in the supernatants. RNA was extracted from the cell pellets, and RT-PCR was performed to amplify corresponding mediators. Gel shift assay was also performed to assess NF-kappa B DNA binding. Inc easing concentrations of acid caused increasing acidification of the media. Trypan blue exclusion and lactate dehydrogenase release demonstrated that acidification did not reduce cell viability. HCl significantly increased LPS-induced NO release and NF-kappa B DNA binding at pH 7.0 but not at pH 6.5. IL-6 and IL-10 expression (RNA and protein) were reduced with HCl-induced acidification, but IL-10 was reduced much more than IL-6 at low pH. By contrast, lactic acid significantly decreased LPS-induced NO, IL-6, and IL-10 expression in a dose-dependent manner. Lactic acid also inhibited LPS-induced NF-kappa B DNA binding. Two common forms of metabolic acidosis (hyperchloremic and lactic acidosis) are associated with dramatically different patterns of immune response in LPS-stimulated RAW 264.7 cells. HCl is essentially proinflammatory as assessed by NO release, IL-6-to-IL-10 ratios, and NF-kappa B DNA binding. By contrast, lactic acidosis is anti-inflammatory.     

DNA aptamers specific for Legionella pneumophila: systematic evolution of ligands by exponential enrichment in whole bacterial cells

Biotechnology Letters - Legionella pneumophila is the major causative agent of Legionnaires’ disease and Pontiac fever, which pose major public health problems. Rapid detection of L....     

High-Throughput-Methyl-Reading (HTMR) assay: a solution based on nucleotide methyl-binding proteins enables large-scale screening for DNA/RNA methyltransferases and demethylases

Epigenetic therapy has significant potential for cancer treatment. However, few small potent molecules have been identified against DNA or RNA modification regulatory proteins. Current approaches for activity detection of DNA/RNA methyltransferases and demethylases are time-consuming and labor-intensive, making it difficult to subject them to high-throughput screening. Here, we developed a fluorescence polarization-based ‘High-Throughput Methyl Reading’ (HTMR) assay to implement large-scale compound screening for DNA/RNA methyltransferases and demethylases-DNMTs, TETs, ALKBH5 and METTL3/METTL14. This assay is simple to perform in a mix-and-read manner by adding the methyl-binding proteins MBD1 or YTHDF1. The proteins can be used to distinguish FAM-labelled substrates or product oligonucleotides with different methylation statuses catalyzed by enzymes. Therefore, the extent of the enzymatic reactions can be coupled with the variation of FP binding signals. Furthermore, this assay can be effectively used to conduct a cofactor competition study. Based on the assay, we identified two natural products as candidate compounds for DNMT1 and ALKBH5. In summary, this study outlines a powerful homogeneous approach for high-throughput screening and evaluating enzymatic activity for DNA/RNA methyltransferases and demethylases that is cheap, easy, quick, and highly sensitive.