Molecular BioSystems最新文献

Type 1 diabetes is associated with such complications as blindness, kidney failure, and nerve damage. Replacing C-peptide, a hormone normally co-secreted with insulin, has been shown to reduce diabetes-related complications. Interestingly, after nearly 30 years of positive research results, C-peptide is still not being co-administered with insulin to diabetic patients. The following review discusses the potential of C-peptide as an auxilliary replacement therapy and why it's not currently being used as a therapeutic.

The current therapies for treating tumors are lacking in efficacy and specificity. Synthetic biology principles may bring some new possible methods for curing cancer. Here we present a synthetic logic circuit based on the CRISPR/Cas9 system. The CRISPR/Cas9 technology has been applied in many biological fields, including cancer research. In this study, the expression of Cas9 nuclease was controlled indirectly by an enhanced hTERT promoter using the GAL4/upstream activating sequence (UAS) binding system. Cas9 was driven by 5XUAS, single guide RNA (sgRNA) was used to target mutant or wild-type HRAS, and the fusion gene GAL4-P65 was driven by the enhanced hTERT promoter. The system was tested in bladder cancer cells (T24 and 5637) and the results showed that the enhanced hTERT promoter could drive the expression of GAL4-P65 in these bladder cancer cell lines. Then all these devices were packed into lentivirus and the results of quantitative real-time PCR showed that the mRNA expression level of HRAS was selectively inhibited in the T24 and 5637 cells. The results of functional experiments suggested that the proliferation, cell migration and invasion were selectively suppressed, and that the apoptosis rate was increased in bladder cancer cells but not in human foreskin fibroblasts (HFF). In conclusion, we successfully constructed an enhanced hTERT promoter-driven CRISPR/Cas9 system and data showed that it could selectively suppress the progression of bladder cancer cells.

A huge number of G-rich sequences forming quadruplexes are found in the human genome, especially in telomeric regions, UTRs, and the promoter regions of a number of genes. One such gene is GRIN1 encoding the NR1 subunit of the N-methyl-D-aspartate receptor (NMDA). Several lines of reports have implicated that attenuated function of NMDA results in schizophrenia, a genetic disorder characterized by hallucinations, delusions, and psychosis. Involvement of the GRIN1 gene in the pathogenesis of schizophrenia has been extensively analysed. Recent reports have demonstrated that polymorphism in the promoter region of GRIN1 at position ?855 (G/C) has a possible association with schizophrenia. The binding site for the NF-κB transcription factor gets altered due to this mutation, resulting in reduced gene expression as well as NMDA activity. By combining gel electrophoresis (PAGE), circular dichroism (CD) and CD melting techniques, the G → C single nucleotide polymorphism (SNP) at the G-rich sequence (d-CTTAGCCCGAGGAGGGGGTCCCAAGT; GRIN1) was investigated. We report that the GRIN1 sequence can form an octameric/multistranded quadruplex structure with parallel conformation in the presence of K⁺ as well as Na⁺. CD and gel studies are in good correlation in order to detect molecularity and strand conformation. The parallel G-quadruplex species was hypothesized to be octameric in K⁺/Na⁺ salts. The mutated sequence (d-CTTAGCCCGAGGAGGGGGTCCCAAGT; GRIN1M) remained single stranded under physiological conditions. CD melting studies support the formation of an interstranded G-quadruplex structure by the GRIN1 sequence. Two structural models are propounded for a multistranded parallel G-quadruplex conformation which might be responsible for regulating the gene expression normally underlying memory and learning.

Hydrogen sulfide, an important gaseous signaling molecule in the human body, is known to protect cardiomyocytes from ischemia, a condition characterized by insufficient oxygen supply to the cells. Here we show that a nanosized H₂S donor micelle releases H₂S intracellularly and prevents cardiomyocyte apoptosis in an in vitro ischemia model.

The collapsin response mediator protein CRMP2 (gene: DPYSL2) is crucial for neuronal development. The homotetrameric CRMP2 complex is regulated via two mechanisms: first by phosphorylation and second by the reduction and oxidation of the Cys504 residues of two adjacent subunits. Here, we have analysed the effects of this redox switch on the protein in vitro combined with force field molecular dynamics (MD). Earlier X-ray data reveal the structure of the rigid body of the molecule but lack the flexible C-terminus with the important sites for phosphorylation and redox regulation. An in silico model for this part was established by replica exchange simulations and homology modelling, which is consistent with the CD spectroscopy results of the recombinant protein. Thermofluor data indicated that the protein aggregates at bivalent ion concentrations below 200 mM. In simulations the protein surface was covered under these conditions by a large number of ions, which most likely prevent aggregation. A tryptophan residue (Trp295) in close proximity to the forming disulphide allowed the measurement of the structural relaxation of the rigid body upon reduction by fluorescence quenching. We were also able to determine the second-order rate constant of CRMP2 oxidation by H₂O₂. The simulated solvent accessible surface of the hydroxyl group of Ser518 significantly increased upon reduction of the disulphide bond. Our results give the first detailed insight into the profound structural changes of the tetrameric CRMP2 due to oxidation and indicate a tightly connected regulation by phosphorylation and redox modification.

Abnormal regulation of signaling pathways is the key causative factor in several diseases. Although many methods have been proposed to identify significantly differential pathways between two conditions via microarray gene expression datasets, most of them concentrate on differences in the pathway components—either the differential expression or the correlation of genes in a given pathway. However, as biological functional units, signaling pathways may have diverse activity patterns across different biological contexts. In order to detect overall changes in pathways, we propose an analysis model called SPAID (Signaling Pathway Analysis based on Information Divergence). SPAID is based on the concept of information divergence, which can be used to compare two conditions by computing the differential probability distribution of the regulation capacity. We compared SPAID with several classical algorithms using different datasets, and the results indicate that SPAID produces higher repeatability, has better performance and universality, and extracts more comprehensive information regarding the underlying biological processes. In conclusion, by introducing the idea of information divergence, our study measures differences in pathways from an overall perspective and will provide a complementary analysis framework for pathway analysis.

Cardiomyocyte (CM) differentiation techniques for generating adult-like mature CMs remain imperfect, and the plausible underlying mechanisms remain unclear; however, there are a number of current protocols available. Here, to explore the mechanisms controlling cardiac differentiation, we analyzed the genome-wide transcription dynamics occurring during the differentiation of human pluripotent stem cells (hPSCs) into CMs using embryoid body (EB) formation. We optimized and updated the protocol to efficiently generate contracting CMs from hPSCs by adding fetal bovine serum (FBS) as a medium supplement, which could have a significant impact on the efficiency of cardiac differentiation. To identify genes, biological processes, and pathways involved in the cardiac differentiation of hPSCs, integrative and comparative analyses of the transcriptome profiles of differentiated CMs from hPSCs and of control CMs of the adult human heart (CM-AHH) were performed using gene ontology, functional annotation clustering, and pathway analyses. Several genes commonly regulated in the differentiated CMs and CM-AHH were enriched in pathways related to cell cycle and nucleotide metabolism. Strikingly, we found that current differentiation protocols did not promote sufficient expression of genes involved in oxidative phosphorylation to differentiate CMs from hPSCs compared to the expression levels in CM-AHH. Therefore, to obtain mature CMs similar to CM-AHH, these deficient pathways in CM differentiation, such as energy-related pathways, must be augmented prior to use for in vitro and in vivo applications. This approach opens up new avenues for facilitating the utilization of hPSC-derived CMs in biomedical research, drug evaluation, and clinical applications for patients with cardiac failure.

RNA–protein interactions are essential for understanding many important cellular processes. In particular, lncRNA–protein interactions play important roles in post-transcriptional gene regulation, such as splicing, translation, signaling and even the progression of complex diseases. However, the experimental validation of lncRNA–protein interactions remains time-consuming and expensive, and only a few theoretical approaches are available for predicting potential lncRNA–protein associations. Here, we presented eigenvalue transformation-based semi-supervised link prediction (LPI-ETSLP) to uncover the relationship between lncRNAs and proteins. Moreover, it is semi-supervised and does not need negative samples. Based on 5-fold cross validation, an AUC of 0.8876 and an AUPR of 0.6438 have demonstrated its reliable performance compared with three other computational models. Furthermore, the case study demonstrated that many lncRNA–protein interactions predicted by our method can be successfully confirmed by experiments. It is indicated that LPI-ETSLP would be a useful bioinformatics resource for biomedical research studies.

Protein intrinsic disorder is an important characteristic commonly detected in multifunctional or RNA- and DNA-binding proteins. Due to their high conformational flexibility and solvent accessibility, intrinsically disordered proteins (IDPs) and IDP regions (IDPRs) execute diverse functions including interaction with multiple partners, and are frequently subjected to various post-translational modifications. Recent studies on the components comprising the CRISPR (clustered regularly interspaced short palindromic repeats) system have elucidated the crystal structure of Cas9 proteins and the mechanism by which the Cas9–sgRNA complex recognizes and cleaves its target DNA. Yet the extent and functional implications of intrinsic disorder in the Cas9 protein have never been fully assessed. Here, we present a comprehensive computational analysis based on both sequence and structural data in an attempt to investigate the roles of IDPRs in the functioning of Cas9 proteins of different origin. We conclude that among the functional roles of IDPRs in Cas9 proteins are recognition of the target DNA and mediation of nucleic acid and protein binding.

Adverse drug reactions (ADRs) are one of the major concerns threatening public health and have resulted in failures in drug development. Thus, predicting ADRs and discovering the mechanisms underlying ADRs have become important tasks in pharmacovigilance. Identification of potential ADRs by computational approaches in the early stages would be advantageous in drug development. Here we propose a computational method that elucidates the action mechanisms of ADRs and predicts potential ADRs by utilizing ADR genes, drug features, and protein–protein interaction (PPI) networks. If some ADRs share similar features, there is a high possibility that they may appear together in a drug and share analogous mechanisms. Proceeding from this assumption, we clustered ADRs according to interactions of ADR genes in the PPI networks and the frequency of co-occurrence of ADRs in drugs. ADR clusters were verified based on a side effect database and literature data regarding whether ADRs have relevance to other ADRs in the same cluster. Gene networks shared by ADRs in each cluster were constructed by cumulating the shortest paths between drug target genes and ADR genes in the PPI network. We developed a classification model to predict potential ADRs using these gene networks shared by ADRs and calculated cross-validation AUC (area under the curve) values for each ADR cluster. In addition, in order to demonstrate correlations between gene networks shared by ADRs and ADRs in a cluster, we applied the Wilcoxon rank sum statistical test to the literature data and results of a Google query search. We attained statistically meaningful p-values (<0.05) for every ADR cluster. The results suggest that our approach provides insights into discovering the action mechanisms of ADRs and is a novel attempt to predict ADRs in a biological aspect.