Biological early warning system based on the responses of aquatic organisms to disturbances: a review

Aquatic ecosystems are subject to a number of anthropogenic disturbances, including environmental toxicants. The efficient monitoring of water resources is fundamental for effective management of water quality and aquatic ecosystems. Spot sampling and continuous water quality monitoring based on physicochemical factors are conducted to assess water quality. However, not all contaminants or synergistic and antagonistic toxic effects can be determined by solely analyzing the physicochemical factors. Thus, various biotests have been developed using long-term and automatic observation studies based on the ability of the aquatic organisms to continuously sense a wide range of pollutants. In addition, a biological early warning system (BEWS) has been developed based on the response behaviors of organisms to continuously detect a wide range of pollutants for effective water quality monitoring and management. However, large amounts of data exhibiting non-linearity and individual behavioral variation are continuously accumulated over long-term and continuous behavioral monitoring studies. Thus, appropriate mathematical and computational data analyses are necessary to manage and interpret such large datasets. Here, we review the development and application of BEWS by using various groups of organisms and the computational methods used to process the behavioral monitoring data.

Evidence for ligandable sites in structured RNA throughout the Protein Data Bank

RNA has attracted considerable attention as a target for small molecules. However, methods to identify, study, and characterize suitable RNA targets have lagged behind strategies for protein targets. One approach that has received considerable attention for protein targets has been to utilize computational analysis to investigate ligandable "pockets" on proteins that are amenable to small molecule binding. These studies have shown that selected physical properties of pockets are important parameters that govern the ability of a structure to bind to small molecules. This work describes a similar analysis to study pockets on all RNAs in the Protein Data Bank (PDB). Using parameters such as buriedness, hydrophobicity, volume, and other properties, the set of all RNAs is analyzed and compared to all proteins. Considerable overlap is observed between the properties of pockets on RNAs and proteins. Thus, many RNAs are capable of populating conformations with pockets that are likely suitable for small molecule binding. Further, principal moment of inertia (PMI) calculations reveal that liganded RNAs exist in diverse structural space, much of which overlaps with protein structural space. Taken together, these results suggest that complex folded RNAs adopt unique structures with pockets that may represent viable opportunities for small molecule targeting.

Genotype-phenotype correlation in 18 Egyptian patients with glutaric acidemia type I

Glutaric acidemia I (GAI) is an autosomal recessive metabolic disease caused by a deficiency of glutaryl-CoA dehydrogenase enzyme (GCDH). Patients with GAI are characterized by macrocephaly, acute encephalitis-like crises, dystonia and frontotemporal atrophy. In this study, we investigated 18 Egyptian patients that were diagnosed with GAI based on their clinical, neuroradiological, and biochemical profiles. Of the 18 patients, 16 had developmental delay and/or regression, dystonia was prominent in 75% of the cases, and three patients died. Molecular genetics analysis identified 14 different mutations in the GCDH gene in the 18 patients, of the 14 mutations, nine were missense, three were in the 3'-Untranslated Region (3'-UTR), one was nonsense, and one was a silent mutation. Four novel mutations were identified (c.148 T > A; p.Trp50Arg, c.158C > A; p.Pro53Gln, c.1284C > G; p.Ile428Met, and c.1189G > T; p.Glu397*) that were all absent in 300 normal chromosomes. The 3'-UTR mutation (c.*165A > G; rs8012), was the most frequent mutation observed (0.5; 18/36), followed by the most common mutation among Caucasian patients (p.Arg402Trp; rs121434369) with allele frequency of 0.36 (13/36), and the 3'-UTR mutation (c.*288G > T; rs9384, 0.22; 8/16). The p.Arg257Gln mutation was found with allele frequency of ~0.17 (6/36). The marked homozygosity observed in our patients is probably due to the high level of consanguinity that is observed in 100% of the cases. We used nine in silico prediction tools to predict the pathogenicity (SIFT, PhD-SNP, SNAP, Meta-SNP, PolyPhen2, and Align GVGD) and protein stability (I-Mutant2.0, Mupro, and istable) of the nine missense mutants. The mutant p.Arg402Trp was predicted to be most deleterious by all the six pathogenicity prediction tools and destabilizing by all the three-stability prediction tools, and highly conserved by the ConSurf server. Using the clinical, biochemical, family history of the 18 patients, and the in silico analysis of the missense mutations, our study showed a mix of conclusive and inconclusive genotype-phenotype correlations among our patient's cohort and suggests the usefulness of using various sophisticated computational analysis to be utilized for future variant classifications in the genetic clinics.

Proteomics for systems toxicology

Current toxicology studies frequently lack measurements at molecular resolution to enable a more mechanism-based and predictive toxicological assessment. Recently, a systems toxicology assessment framework has been proposed, which combines conventional toxicological assessment strategies with system-wide measurement methods and computational analysis approaches from the field of systems biology. Proteomic measurements are an integral component of this integrative strategy because protein alterations closely mirror biological effects, such as biological stress responses or global tissue alterations. Here, we provide an overview of the technical foundations and highlight select applications of proteomics for systems toxicology studies. With a focus on mass spectrometry-based proteomics, we summarize the experimental methods for quantitative proteomics and describe the computational approaches used to derive biological/mechanistic insights from these datasets. To illustrate how proteomics has been successfully employed to address mechanistic questions in toxicology, we summarized several case studies. Overall, we provide the technical and conceptual foundation for the integration of proteomic measurements in a more comprehensive systems toxicology assessment framework. We conclude that, owing to the critical importance of protein-level measurements and recent technological advances, proteomics will be an integral part of integrative systems toxicology approaches in the future.

A comprehensive in silico analysis of non-synonymous and regulatory SNPs of human MBL2 gene

Mannose binding lectin (MBL) is a liver derived protein which plays an important role in innate immunity. Mannose binding lectin gene 2 (MBL2) polymorphisms are reported to be associated with various diseases. In spite of being exhaustively studied molecule, no attempt has been made till date to comprehensively and systematically analyze the SNPs of MBL2 gene. The present study was carried out to identify and prioritize the SNPs of MBL2 gene for further genotyping and functional studies. To predict the possible impact of SNPs on MBL structure and function SNP data obtained from dbSNP database were analyzed using various bioinformatics tools. Out of total 661 SNPs, only 37 validated SNPs having minor allele frequency ≥0.10 were considered for the present study. These 37 SNPs includes one in 3' near gene, nine in 3' UTR, one non-synonymous SNP (nsSNP), thirteen intronic SNPs and thirteen in 5' near gene. From these 37 SNPs, 11 non-coding SNPs were identified to be of functional significance and evolutionary conserved. Out of these, 4 SNPs from 3' UTR were found to play role in miRNA binding, 7 SNPs from 5' near and intronic region were predicted to involve in transcription factor binding and expression of MBL2 gene. One nsSNP Gly54Asp (rs1800450) was found to be deleterious and damaging by both SIFT and Polyphen-2 servers and thus affecting MBL2 protein stability and expression. Protein structural analysis with this amino acid variant was performed by using I-TASSER, RAMPAGE, Swiss-PdbViewer, Chimera and I-mutant. Information regarding solvent accessibility, molecular dynamics and energy minimization calculations showed that this variant causes clashes with neighboring amino acids residues that must interfere in the normal triple helix formation of trimeric subunit and further with the normal assembly of MBL oligomeric form, hence decrease in stability. Thus, findings of the present study indicated 12 SNPs of MBL2 gene to be functionally important. Exploration of these variants may provide novel remedial markers for various diseases.

Adsorptive decontamination of antibiotics from livestock wastewater by using alkaline-modified biochar

Efficient abatement of antibiotics from livestock wastewater is in urgent demand, but still challenging. In this study, alkaline-modified biochar with larger surface area (130.520 m² g^-1) and pore volume (0.128 cm³ g^-1) was fabricated and explored for the adsorption of different types of antibiotics from livestock wastewater. Batch adsorption experiments demonstrated that the adsorption process was mainly determined by chemisorption and was heterogeneous, which could be moderately affected by the variations of solution pH (3-10). Furthermore, the computational analysis based on density functional theory (DFT) indicated that the -OH groups on biochar surface could serve as the dominant active sites for antibiotics adsorption due to the strongest adsorption energies between antibiotics and -OH groups. In addition, the antibiotics removal was also evaluated in multi-pollutants system, where biochar performed synergistic adsorption towards Zn²⁺/Cu²⁺ and antibiotics. Overall, these findings not only deepen our understandings on the adsorption mechanism between biochar and antibiotics, but also promote the application of biochar in the remediation of livestock wastewater.

Computational analysis of protein hotspots

Mapping protein hotspots and analysis of the binding free energy associated with each hotspot can provide critical information for drug design. In the present study, we have performed computational analysis for the two known hotspots in thermolysin. Our data showed that the free energy double-decoupling method can determine the binding free energy of different probe molecules associated with the same hotspot or different hotspots with the same probe molecule. The less expensive cosolvent mapping method can be used to readily identify known protein hotspots without prior knowledge and also provide a good estimate of the binding free energy, as compared to the more expensive free energy double-decoupling method. Hence, the combination of the cosolvent mapping method to identify potential protein hotspots followed by more rigorous calculation of the binding free energy associated with each hotspot using the double-decoupling method can provide very useful information for drug design.

Long term morphological characterization of mesenchymal stromal cells 3D spheroids built with a rapid method based on entry-level equipment

Three-dimensional (3D) spheroids of mesenchymal stromal cells (MSC) have been demonstrated to improve a wide range of MSC features, such as multilineage potential, secretion of therapeutic factors, and resistance against hypoxic condition. Accordingly, they represent a promising tool in regenerative medicine for several biological and clinical applications. Many approaches have been proposed to generate MSC spheroids. They usually require specific generation systems, such as rotatory bioreactors or low-attachment plates, and each approach has its own disadvantages. Furthermore, an over-time analysis of morphological homogeneity and architectural stability of the spheroids generated is rarely provided. In this work we adapted the "pellet culture" method to obtain homogenous spheroids of MSC and maintain them in vitro for long term studies. We analysed their outer and inner structure over a 2-month period to provide morphological and architectural information regarding the spheroids generated. Quantitative and qualitative data were obtained using brightfield and confocal microscope imaging coupled to a computational analysis to estimate volume, sphericity, and jagging degree. In addition, histological evaluation was performed to more thoroughly assess the cellular composition and the internal architecture of the 3D spheroids. The results provided show that MSC spheroids generated with the proposed approach are homogeneous and stable, from both morphological and architectural points of view, for a period of at least 15 days, approximately between day 15 and day 30 after their generation. Accordingly, the approach proposed serves as a rapid, cost-effective, and efficient method to generate and maintain MSC spheroids using common entry-level laboratory equipment only.

Detecting broad domains and narrow peaks in ChIP-seq data with hiddenDomains

Background

Correctly identifying genomic regions enriched with histone modifications and transcription factors is key to understanding their regulatory and developmental roles. Conceptually, these regions are divided into two categories, narrow peaks and broad domains, and different algorithms are used to identify each one. Datasets that span these two categories are often analyzed with a single program for peak calling combined with an ad hoc method for domains.

Results

We developed hiddenDomains, which identifies both peaks and domains, and compare it to the leading algorithms using H3K27me3, H3K36me3, GABP, ESR1 and FOXA ChIP-seq datasets. The output from the programs was compared to qPCR-validated enriched and depleted sites, predicted transcription factor binding sites, and highly-transcribed gene bodies. With every method, hiddenDomains, performed as well as, if not better than algorithms dedicated to a specific type of analysis.

Conclusions

hiddenDomains performs as well as the best domain and peak calling algorithms, making it ideal for analyzing ChIP-seq datasets, especially those that contain a mixture of peaks and domains.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-0991-z) contains supplementary material, which is available to authorized users.

Variability in static alignment and kinematics for kinematically aligned TKA

BACKGROUND

Total knee arthroplasty (TKA) significantly improves pain and restores a considerable degree of function. However, improvements are needed to increase patient satisfaction and restore kinematics to allow more physically demanding activities that active patients consider important. The aim of our study was to compare the alignment and motion of kinematically and mechanically aligned TKAs.

METHODS

A patient specific musculoskeletal computer simulation was used to compare the tibio-femoral and patello-femoral kinematics between mechanically aligned and kinematically aligned TKA in 20 patients.

RESULTS

When kinematically aligned, femoral components on average resulted in more valgus alignment to the mechanical axis and internally rotated to surgical transepicondylar axis whereas tibia component on average resulted in more varus alignment to the mechanical axis and internally rotated to tibial AP rotational axis. With kinematic alignment, tibio-femoral motion displayed greater tibial external rotation and lateral femoral flexion facet centre (FFC) translation with knee flexion than mechanical aligned TKA. At the patellofemoral joint, patella lateral shift of kinematically aligned TKA plateaued after 20 to 30° flexion while in mechanically aligned TKA it decreased continuously through the whole range of motion.

CONCLUSIONS

Kinematic alignment resulted in greater variation than mechanical alignment for all tibio-femoral and patello-femoral motion. Kinematic alignment places TKA components patient specific alignment which depends on the preoperative state of the knee resulting in greater variation in kinematics. The use of computational models has the potential to predict which alignment based on native alignment, kinematic or mechanical, could improve knee function for patient's undergoing TKA.

Data-driven multiple-level analysis of gut-microbiome-immune-joint interactions in rheumatoid arthritis

Background

Rheumatoid arthritis (RA) is the most common autoimmune disease and affects about 1% of the population. The cause of RA remains largely unknown and could result from a complex interaction between genes and environment factors. Recent studies suggested that gut microbiota and their collective metabolic outputs exert profound effects on the host immune system and are implicated in RA. However, which and how gut microbial metabolites interact with host genetics in contributing to RA pathogenesis remains unknown. In this study, we present a data-driven study to understand how gut microbial metabolites contribute to RA at the genetic, functional and phenotypic levels.

Results

We used publicly available disease genetics, chemical genetics, human metabolome, genetic signaling pathways, mouse genome-wide mutation phenotypes, and mouse phenotype ontology data. We identified RA-associated microbial metabolites and prioritized them based on their genetic, functional and phenotypic relevance to RA. We evaluated the prioritization methods using short-chain fatty acids (SCFAs), which were previously shown to be involved in RA etiology. We validate the algorithms by showing that SCFAs are highly associated with RA at genetic, functional and phenotypic levels: SCFAs ranked at top 3.52% based on shared genes with RA, top 5.69% based on shared genetic pathways, and top 16.94% based on shared phenotypes. Based on the genetic-level analysis, human gut microbial metabolites directly interact with many RA-associated genes (as many as 18.1% of all 166 RA genes). Based on the functional-level analysis, human gut microbial metabolites participate in many RA-associated genetic pathways (as many as 71.4% of 311 genetic pathways significantly enriched for RA), including immune system pathways. Based on the phenotypic-level analysis, gut microbial metabolites affect many RA-related phenotypes (as many as 51.3% of 978 phenotypes significantly enriched for RA), including many immune system phenotypes.

Conclusions

Our study demonstrates strong gut-microbiome-immune-joint interactions in RA, which converged on both genetic, functional and phenotypic levels.

Network dynamics in the healthy and epileptic developing brain

Electroencephalography (EEG) allows recording of cortical activity at high temporal resolution. EEG recordings can be summarized along different dimensions using network-level quantitative measures, such as channel-to-channel correlation, or band power distributions across channels. These reveal network patterns that unfold over a range of different timescales and can be tracked dynamically. Here we describe the dynamics of network state transitions in EEG recordings of spontaneous brain activity in normally developing infants and infants with severe early infantile epileptic encephalopathies (n = 8, age: 1–8 months). We describe differences in measures of EEG dynamics derived from band power, and correlation-based summaries of network-wide brain activity. We further show that EEGs from different patient groups and controls may be distinguishable on a small set of the novel quantitative measures introduced here, which describe dynamic network state switching. Quantitative measures related to the sharpness of switching from one correlation pattern to another show the largest differences between groups. These findings reveal that the early epileptic encephalopathies are associated with characteristic dynamic features at the network level. Quantitative network-based analyses like the one presented here may in the future inform the clinical use of quantitative EEG for diagnosis.

Association analysis of rs1049255 and rs4673 transitions in p22phox gene with coronary artery disease: A case-control study and a computational analysis

BACKGROUND

The p22phox gene encodes the main subunit of NADH/NADPH-oxidase. This enzyme is expressed in smooth muscle cells of arteries, and it produces the reactive oxygen species. On the other hand, oxidative stress plays a main role in the pathogenesis of coronary artery disease (CAD).

AIM

The aim of this study is to evaluate the association between rs4673 and rs1049255 polymorphisms of p22phox gene with CAD in an Iranian population which was followed with a computational analysis approach.

METHODS

In a cross-sectional study, we collected blood samples of 302 Iranian Caucasian including 143 patients and 159 healthy controls. Genotype of the polymorphisms was detected through PCR-RFLP method. A computational analysis was also performed using SNAP, Polyphen-2, Chou-Fasman, RNAsnp, and miRNA SNP databases.

RESULTS

Data of case control study demonstrated that CT genotype (R = 1.84, 95% CI = 1.13-3.00, p = 0.014) and T allele (OR = 1.53, 95% CI = 1.09-2.15, p = 0.013) of rs4673 polymorphism, have a significant association with enhanced risk of CAD. But rs1049255 analysis demonstrated the absence of such an association with CAD. Indeed, in silico data analysis demonstrated that rs4673 transition could impact on function of p22phox protein (SNAP score 56, expected accuracy 75%; Polyphen-2 score 0.99, sensitivity 0.09, specificity 0.99). Data derived from miRNA SNP database demonstrated that rs1049255 polymorphism increases the affinity of attachment between has-miR-3689a-3b with 3'-UTR of p22phox gene.

CONCLUSION

Our data demonstrated that rs4673 transition may be involved in susceptibility to CAD and could be applied as a potential biomarker for this disease.

Theoretical analysis of bacterial efflux pumps inhibitors: Strategies in-search of competent molecules and develop next

Multi-drug resistance (MDR) bacteria pose a significant threat to our ability to effectively treat infections due to the development of several antibiotic resistant mechanisms. A major component in the development of the MDR phenotype in MDR bacteria is over expression of different-type of efflux pumps, which actively pump out antibacterial agents and biocides from the periplasm to the outside of the cell. Consequently, bacterial efflux pumps are an important target for developing novel antibacterial treatments. Potent efflux pump inhibitors (EPIs) could be used as adjunctive therapies that would increase the potency of existing antibiotics and decrease the emergence of MDR bacteria. Several potent inhibitors of efflux pumps have been reported which has been summarized here. All the natural and synthetic EPIs were optimized with Gaussian and Avogadro software. The optimized structures were docked with each class of efflux pumps and their bonding parameters were computed. The theoretical analyses were performed with density functional theory (DFT). Overall, computational study revealed a good trend of electrophilicity and ionization potential of the EPIs, the obtained average values are within in the range of 0.001414 AU ± 0.00032 and 0.208821 AU ± 0.015545, respectively. Interestingly, cathinone interacts with most of the efflux pumps among the tested inhibitors. The electrophilicity and ionization potential of cathinone are 0.00198 and 0.2388 AU, respectively. The study opens a new road for designing future-generation target-specific efflux pump inhibitors, as well as one molecule with multiple inhibition abilities.

Endoperoxide polyketides from a Chinese Plakortis simplex: further evidence of the impact of stereochemistry on antimalarial activity of simple 1,2-dioxanes

Chemical investigation of the organic extract obtained from the sponge Plakortis simplex collected in the South China Sea afforded five new polyketide endoperoxides (2 and 4-7), along with two known analogues (1 and 3). The stereostructures of these metabolites have been deduced on the basis of spectroscopic analysis and chemical conversion. The isolated endoperoxide derivatives have been tested for their in vitro antimalarial activity against Plasmodium falciparum strains, showing IC50 values in the low micromolar range. The structure-activity relationships were analyzed by means of a detailed computational investigation and rationalized in the light of the mechanism of action proposed for this class of simple antimalarials. The relative orientation of the atoms involved in the putative radical generation and transfer reaction was demonstrated to have a great impact on the antimalarial activity. The resulting 3D pharmacophoric model can be a useful guide to design simple and effective antimalarial lead compounds belonging to the class of 1,2-dioxanes.

Fatigue of Metallic Stents: From Clinical Evidence to Computational Analysis

The great success of stents in treating cardiovascular disease is actually undermined by their long-term fatigue failure. The high variability of stent failure incidence suggests that it is due to several correlated aspects, such as loading conditions, material properties, component design, surgical procedure, and patient functional anatomy. Numerical and experimental non-clinical assessments are included in the recommendations and requirements of several regulatory bodies and they are thus exploited in the analysis of stent fatigue performance. Optimization-based simulation methodologies have been developed as well, to improve the fatigue endurance of novel designs. This paper presents a review on the fatigue issue in metallic stents, starting from a description of clinical evidence about stent fracture up to the analysis of computational approaches available from the literature. The reported discussion on both the experimental and numerical framework aims at providing a general insight into stent lifetime prediction as well as at understanding the factors which affect stent fatigue performance for the design of novel components.

Probing the interaction of 2,4-dichlorophenoxyacetic acid with human serum albumin as studied by experimental and computational approaches

To characterize the binding of a widely used herbicide, 2,4-dichlorophenoxyacetic acid (2,4-D) to the major transporter in human circulation, human serum albumin (HSA), multi-spectroscopic approaches such as fluorescence, absorption and circular dichroism along with computational methods were employed. Analysis of the fluorescence and absorption spectroscopic data confirmed the 2,4-D-HSA complex formation. A static quenching mechanism was evident from the inverse temperature dependence of the K_SV values. The complex was stabilized by a weak binding affinity (K_a = 5.08 × 10³ M^-1 at 298 K). Quantitative analysis of thermodynamic data revealed participation of hydrophobic and van der Waals interactions as well as hydrogen bonds in the binding process. Circular dichroism and three-dimensional fluorescence spectral results showed structural (secondary and tertiary) changes in HSA as well as microenvironmental perturbation around protein fluorophores (Trp and Tyr residues) upon 2,4-D binding. Addition of 2,4-D to HSA was found to improve protein's thermal stability. Competitive displacement results as well as computational analyses suggested preferred location of the 2,4-D binding site as Sudlow's site I (subdomain IIA) in HSA.

Identification and characterization of a novel nanobody against human placental growth factor to modulate angiogenesis

Placental growth factor (PlGF), a member of vascular endothelial growth factors (VEGF) family, is considered as an important antigen associated with pathological conditions such as cancer cell growth, and metastasis. PlGF-targeting via nanobody (Nb) therefore could be beneficial to modulate these pathologies. In this work, phage-display and computational approach was employed to develop a high affinity PlGF-specific Nb. An Nb library was constructed against human recombinant PlGF (rPlGF). After panning on immobilized rPlGF the periplasmic-extract (PE) of individual colonies were screened by ELISA (PE-ELISA). The 3D structures of selected Nbs were then homology modeled and energy minimized using the AMBER force field. Binding score calculations were also assessed to reveal possible Nb-PlGF interactions. Via ELISA-based affinity/specificity determinations, the best-qualified Nb was further evaluated by proliferation, migration, 3D capillary formation, invasion assays and on Chick chorioallantoic membrane (CAM) model. An immune library of 1.5×10⁷ individual Nb clones was constructed. By PE-ELISA 12 clones with strong signals were selected. Three out of 12 sequenced Nbs (Nb-C13, Nb-C18 and Nb-C62) showed high binding scores ranging between -378.7 and -461kcal/mol. Compared to a control Nb, Nb-C18 significantly inhibited proliferation, migration and the 3D-capillary formation of HUVEC cells (p<0.05) with an EC₅₀ of 35nM, 42nM and 24nM and invasion of MDA-MB231was significantly suppressed (p<0.05) with an EC₅₀ of57nM. The result of the CAM assay shows that Nb-C18 could inhibit the vascular formation in the chicken chorioallantoic membrane. This Nb can be used as anti-angiogenesis agent in future.

Human breast and melanoma cancer stem cells biomarkers

Cancer progression in humans is difficult to infer because we do not routinely sample patients at multiple stages of their disease. The identification cancer stem cell (CSC) subpopulations inside tumor opens a new view of cancer development, since it implies that tumors can only be eradicated by targeting CSCs. Several markers have been proposed in the literature to identify CSCs both in breast and melanoma but no consensus has been reached, leading to the hypothesis that the CSC phenotype might be dynamically switched. Herein we provide a critical discussion of the biological markers described in the literature for breast cancer and melanoma. Due to its complexity the field would benefit from an interdisciplinary approach to investigate tumor heterogeneity and its progression. Similar considerations could also be relevant for normal tissue stem cells.

Fluctuating expression of miR-584 in primary and high-grade gastric cancer

Background

Gastric cancer is the fifth most common cancer worldwide. Along with environmental factors, such as Helicobacter pylori (H. pylori) infection, genetic changes play important roles in gastric tumor formations. miR-584 is a less well-characterized microRNA (miRNA), with apparent activity in human cancers. However, miR-584 expression pattern in gastric cancer development has remained unclear. This study aims to analyze the expression of miR-584 in gastric cancer samples and investigates the associations between this miRNA and H. pylori infection and clinical characteristics.

Methods

The expression level of miR-584 was studied in primary gastric cancers versus healthy control gastric mucosa samples using the RT-qPCR method. The clinical data were analyzed statistically in terms of miR-584 expression. In silico studies were employed to study miR-584 more broadly in order to assess its expression and find new potential target genes.

Results

Both experimental and in silico studies showed up-regulation of miR-584 in patients with gastric cancer. This up-regulation seems to be induced by H. pylori infection since the infected samples showed increased levels of miR-584 expression. Deeper analyses revealed that miR-584 undergoes a dramatic down-regulation in late stages, invasive and lymph node-metastatic gastric tumors. Bioinformatics studies demonstrated that miR-584 has a substantial role in cancer pathways and has the potential to target STAT1 transcripts. Consistent with the inverse correlation between TCGA RNA-seq data of miR-584 and STAT1 transcripts, the qPCR analysis showed a significant negative correlation between these two RNAs in a set of clinical samples.

Conclusion

miR-584 undergoes up-regulation in the stage of primary tumor formation; however, becomes down-regulated upon the progression of gastric cancer. These findings suggest the potential of miR-584 as a diagnostic or prognostic biomarker in gastric cancer.

Molecular docking and network connections of active compounds from the classical herbal formula Ding Chuan Tang

BACKGROUND

Ding Chuan Tang (DCT), a traditional Chinese herbal formula, has been consistently prescribed for the therapeutic management of wheezing and asthma-related indications since the Song Dynasty (960-1279 AD). This study aimed to identify molecular network pharmacology connections to understand the biological asthma-linked mechanisms of action of DCT and potentially identify novel avenues for asthma drug development.

METHODS

Employing molecular docking (AutoDock Vina) and computational analysis (Cytoscape 3.6.0) strategies for DCT compounds permitted examination of docking connections for proteins that were targets of DCT compounds and asthma genes. These identified protein targets were further analyzed to establish and interpret network connections associated with asthma disease pathways.

RESULTS

A total of 396 DCT compounds and 234 asthma genes were identified through database search. Computational molecular docking of DCT compounds identified five proteins (ESR1, KDR, LTA4H, PDE4D and PPARG) mutually targeted by asthma genes and DCT compounds and 155 docking connections associated with cellular pathways involved in the biological mechanisms of asthma.

CONCLUSIONS

DCT compounds directly target biological pathways connected with the pathogenesis of asthma including inflammatory and metabolic signaling pathways.

Physiological and genetic analysis of multiple sodium channel variants in a model of genetic absence epilepsy

In excitatory neurons, SCN2A (NaV1.2) and SCN8A (NaV1.6) sodium channels are enriched at the axon initial segment. NaV1.6 is implicated in several mouse models of absence epilepsy, including a missense mutation identified in a chemical mutagenesis screen (Scn8a(V929F)). Here, we confirmed the prior suggestion that Scn8a(V929F) exhibits a striking genetic background-dependent difference in phenotypic severity, observing that spike-wave discharge (SWD) incidence and severity are significantly diminished when Scn8a(V929F) is fully placed onto the C57BL/6J strain compared with C3H. Examination of sequence differences in NaV subunits between these two inbred strains suggested NaV1.2(V752F) as a potential source of this modifier effect. Recognising that the spatial co-localisation of the NaV channels at the axon initial segment (AIS) provides a plausible mechanism for functional interaction, we tested this idea by undertaking biophysical characterisation of the variant NaV channels and by computer modelling. NaV1.2(V752F) functional analysis revealed an overall gain-of-function and for NaV1.6(V929F) revealed an overall loss-of-function. A biophysically realistic computer model was used to test the idea that interaction between these variant channels at the AIS contributes to the strain background effect. Surprisingly this modelling showed that neuronal excitability is dominated by the properties of NaV1.2(V752F) due to "functional silencing" of NaV1.6(V929F) suggesting that these variants do not directly interact. Consequent genetic mapping of the major strain modifier to Chr 7, and not Chr 2 where Scn2a maps, supported this biophysical prediction. While a NaV1.6(V929F) loss of function clearly underlies absence seizures in this mouse model, the strain background effect is apparently not due to an otherwise tempting Scn2a variant, highlighting the value of combining physiology and genetics to inform and direct each other when interrogating genetic complex traits such as absence epilepsy.

Biaryl scaffold-focused virtual screening for anti-aggregatory and neuroprotective effects in Alzheimer's disease

Background

Alzheimer’s disease (AD) is a primary cause of dementia in ageing population affecting more than 35 million people around the globe. It is a chronic neurodegenerative disease caused by defected folding and aggregation of amyloid beta (Aβ) protein. Aβ is formed by the cleavage of membrane embedded amyloid precursor protein (APP) by using enzyme ‘transmembrane aspartyl protease, β-secretase’. Inhibition of β-secretase is a viable strategy to prevent neurotoxicity in AD. Another strategy in the treatment of AD is inhibition of acetylcholinesterase. This inhibition reduces the degradation of acetylcholine and temporarily restores the cholinergic function of neurons and improves cognitive function. Monoamine oxidase and higher glutamate levels are also found to be linked with Aβ peptide related oxidative stress. Oxidative stress leads to reduced activity of glutamate synthase resulting in significantly higher level of glutamate in brain. The aim of this study is to perform in silico screening of a virtual library of biaryl scaffold containing compounds potentially used for the treatment of AD. Screening was done against the primary targets of AD therapeutics, acetylcholinesterase, β-secretase (BACE1), Monoamine oxidases (MAO) and N-Methyl-D-aspartate (NMDA) receptor. Compounds were screened for their inhibitory potential by employing molecular docking approach using AutoDock vina. Binding energy scores were embodied in the heatmap to display varies strengths of interactions of the ligands targeting AD.

Results

Several ligands showed notable interaction with at least two targets, but the strong interaction with all the targets is shown by very few ligands. The pharmacokinetics of the interacting ligands was also predicted. The interacting ligands have good drug-likeness and brain availability essential for drugs with intracranial targets.

Conclusion

These results suggest that biaryl scaffold may be pliable to drug development for neuroprotection in AD and that the synthesis of further analogues to optimize these properties should be considered.

Electronic supplementary material

The online version of this article (10.1186/s12868-018-0472-6) contains supplementary material, which is available to authorized users.

Screening and structural evaluation of deleterious Non-Synonymous SNPs of ePHA2 gene involved in susceptibility to cataract formation

Age-related cataract is clinically and genetically heterogeneous disorder affecting the ocular lens, and the leading cause of vision loss and blindness worldwide. Here we screened nonsynonymous single nucleotide polymorphisms (nsSNPs) of a novel gene, EPHA2 responsible for age related cataracts. The SNPs were retrieved from dbSNP. Using I-Mutant, protein stability change was calculated. The potentially functional nsSNPs and their effect on protein was predicted by PolyPhen and SIFT respectively. FASTSNP was used for functional analysis and estimation of risk score. The functional impact on the EPHA2 protein was evaluated by using SWISSPDB viewer and NOMAD-Ref server. Our analysis revealed 16 SNPs as nonsynonymous out of which 6 nsSNPs, namely rs11543934, rs2291806, rs1058371, rs1058370, rs79100278 and rs113882203 were found to be least stable by I-Mutant 2.0 with DDG value of > -1.0. nsSNPs, namely rs35903225, rs2291806, rs1058372, rs1058370, rs79100278 and rs113882203 showed a highly deleterious tolerance index score of 0.00 by SIFT server. Four nsSNPs namely rs11543934, rs2291806, rs1058370 and rs113882203 were found to be probably damaging with PSIC score of ≥ 2. 0 by Polyp hen server. Three nsSNPs namely, rs11543934, rs2291806 and rs1058370 were found to be highly polymorphic with a risk score of 3-4 with a possible effect of Non-conservative change and splicing regulation by FASTSNP. The total energy and RMSD value was higher for the mutant-type structure compared to the native type structure. We concluded that the nsSNP namely rs2291806 as the potential functional polymorphic that is likely to have functional impact on the EPHA2 gene.

Novel biospectroscopy sensor technologies towards environmental health monitoring in urban environments

Biospectroscopy is an emerging inter-disciplinary field that exploits the application of sensor technologies [e.g., Fourier-transform infrared spectroscopy, Raman spectroscopy] to lend novel insights into biological questions. Methods involved are relatively non-destructive so samples can subsequently be analysed by more conventional approaches, facilitating deeper mechanistic insights. Fingerprint spectra are derived and these consist of wavenumber-absorbance intensities; within a typical biological experiment, a complex dataset is quickly generated. Biological samples range from biofluids to cytology to tissues derived from human or sentinel sources, and analyses can be carried out ex vivo or in situ in living tissue. A reference range of a designated normal state can be derived; anything outside this is potentially atypical and discriminating chemical entities identified. Computational approaches allow one to minimize within-category confounding factors. Because of ease of sample preparation, low-cost and high-throughput capability, biospectroscopy approaches herald a new greener means of environmental health monitoring in urban environments.