Probing RNA structures and functions by solvent accessibility: an overview from experimental and computational perspectives

Characterizing RNA structures and functions have mostly been focused on 2D, secondary and 3D, tertiary structures. Recent advances in experimental and computational techniques for probing or predicting RNA solvent accessibility make this 1D representation of tertiary structures an increasingly attractive feature to explore. Here, we provide a survey of these recent developments, which indicate the emergence of solvent accessibility as a simple 1D property, adding to secondary and tertiary structures for investigating complex structure–function relations of RNAs.

High-throughput split-protein profiling by combining transposon mutagenesis and regulated protein-protein interactions with deep sequencing

Splitting a protein at a position may lead to self- or assisted-complementary fragments depending on whether two resulting fragments can reconstitute to maintain the native function spontaneously or require assistance from two interacting molecules. Assisted complementary fragments with high contrast are an important tool for probing biological interactions. However, only a small number of assisted-complementary split-variants have been identified due to manual, labour-intensive optimization of a candidate gene. Here, we introduce a technique for high-throughput split-protein profiling (HiTS) that allows fast identification of self- and assisted complementary positions by transposon mutagenesis, a rapamycin-regulated FRB-FKBP protein interaction pair, and deep sequencing. We test this technique by profiling three antibiotic-resistant genes (fosfomycin-resistant gene, fosA3, erythromycin-resistant gene, ermB, and chloramphenicol-resistant gene, catI). Self- and assisted complementary fragments discovered by the high-throughput technique were subsequently confirmed by low-throughput testing of individual split positions. Thus, the HiTS technique provides a quicker alternative for discovering the proteins with suitable self- and assisted-complementary split positions when combining with a readout such as fluorescence, bioluminescence, cell survival, gene transcription or genome editing.

High-throughput mapping of RNA solvent accessibility at the single-nucleotide resolution by RtcB ligation between a fixed 5'-OH-end linker and unique 3'-P-end fragments from hydroxyl radical cleavage

Given the challenges for the experimental determination of RNA tertiary structures, probing solvent accessibility has become increasingly important to gain functional insights. Among various chemical probes developed, backbone-cleaving hydroxyl radical is the only one that can provide unbiased detection of all accessible nucleotides. However, the readouts have been based on reverse transcription (RT) stop at the cleaving sites, which are prone to false positives due to PCR amplification bias, early drop-off of reverse transcriptase, and the use of random primers in RT reaction. Here, we introduced a fixed-primer method called RL-Seq by performing RtcB Ligation (RL) between a fixed 5'-OH-end linker and unique 3'-P-end fragments from hydroxyl radical cleavage prior to high-throughput sequencing. The application of this method to E. coli ribosomes confirmed its ability to accurately probe solvent accessibility with high sensitivity (low required sequencing depth) and accuracy (strong correlation to structure-derived values) at the single-nucleotide resolution. Moreover, a near-perfect correlation was found between the experiments with and without using unique molecular identifiers, indicating negligible PCR biases in RL-Seq. Further improvement of RL-Seq and its potential transcriptome-wide applications are discussed.

Computational algorithmic and molecular dynamics study of functional and structural impacts of non-synonymous single nucleotide polymorphisms in human DHFR gene

Human dihydrofolate reductase (DHFR) is a conserved enzyme that is central to folate metabolism and is widely targeted in pathogenic diseases as well as cancers. Although studies have reported the fact that genetic mutations in DHFR leads to a rare autosomal recessive inborn error of folate metabolism and drug resistance, there is a lack of an extensive study on how the deleterious non-synonymous SNPs (nsSNPs) disrupt its phenotypic effects. In this study, we aim at discovering the structural and functional consequences of nsSNPs in DHFR by employing a combined computational approach consisting of ten recently developed in silico tools for identification of damaging nsSNPs and molecular dynamics (MD) simulation for getting deeper insights into the magnitudes of damaging effects. Our study revealed the presence of 12 most deleterious nsSNPs affecting the native phenotypic effects, with three (R71T, G118D, Y122D) identified in the co-factor and ligand binding active sites. MD simulations also suggested that these three SNPs particularly Y122D, alter the overall structural flexibility and dynamics of the native DHFR protein which can provide more understandings into the crucial roles of these mutants in influencing the loss of DHFR function.

5-Hydroxymethylfurfural (HMF) levels in honey and other food products: effects on bees and human health

An organic compound known as 5-hydroxymethylfurfural (HMF) is formed from reducing sugars in honey and various processed foods in acidic environments when they are heated through the Maillard reaction. In addition to processing, storage conditions affect the formation HMF, and HMF has become a suitable indicator of honey quality. HMF is easily absorbed from food through the gastrointestinal tract and, upon being metabolized into different derivatives, is excreted via urine. In addition to exerting detrimental effects (mutagenic, genotoxic, organotoxic and enzyme inhibitory), HMF, which is converted to a non-excretable, genotoxic compound called 5-sulfoxymethylfurfural, is beneficial to human health by providing antioxidative, anti-allergic, anti-inflammatory, anti-hypoxic, anti-sickling, and anti-hyperuricemic effects. Therefore, HMF is a neo-forming contaminant that draws great attention from scientists. This review compiles updated information regarding HMF formation, detection procedures, mitigation strategies and effects of HMF on honey bees and human health.

In silico analysis of nonsynonymous single nucleotide polymorphisms of the human adiponectin receptor 2 (ADIPOR2) gene

Polymorphisms of the ADIPOR2 gene are frequently linked to a higher risk of developing diseases including obesity, type 2 diabetes and cardiovascular diseases. Though mutations of the ADIPOR2 gene are detrimental, there is a lack of comprehensive in silico analyses of the functional and structural impacts at the protein level. Considering the involvement of ADIPOR2 in glucose uptake and fatty acid oxidation, an in silico functional analysis was conducted to explore the possible association between genetic mutations and phenotypic variations. A genomic analysis of 82 nonsynonymous SNPs in ADIPOR2 was initiated using SIFT followed by the SNAP2, nsSNPAnalyzer, PolyPhen-2, SNPs&GO, FATHMM and PROVEAN servers. A total of 10 mutations (R126W, L160Q, L195P, F201S, L235R, L235P, L256R, Y328H, E334K and Q349H) were predicted to have deleterious effects on the ADIPOR2 protein and were therefore selected for further analysis. Theoretical models of the variants were generated by comparative modeling via MODELLER 9.16. A protein structural analysis of these amino acid variants was performed using SNPeffect, I-Mutant, ConSurf, Swiss-PDB Viewer and NetSurfP to explore their solvent accessibility, molecular dynamics and energy minimization calculations. In addition, FTSite was used to predict the ligand binding sites, while NetGlycate, NetPhos2.0, UbPerd and SUMOplot were used to predict post-translational modification sites. All of the variants showed increased free energy, though F201S exhibited the highest energy increase. The root mean square deviation values of the modeled mutants strongly indicated likely pathogenicity. Remarkably, three binding sites were detected on ADIPOR2, and two mutations at positions 328 and 201 were found in the first and second binding pockets, respectively. Interestingly, no mutations were found at the post-translational modification sites. These genetic variants can provide a better understanding of the wide range of disease susceptibility associated with ADIPOR2 and aid the development of new molecular diagnostic markers for these diseases. The findings may also facilitate the development of novel therapeutic elements for associated diseases.

Polyphenols: Potential Future Arsenals in the Treatment of Diabetes

Diabetes mellitus (DM) is one of the most common endocrine metabolic disorders. In addition to exercise and diet, oral anti-diabetic drugs have been used as a part of the management strategy worldwide. Unfortunately, none of the conventional anti-diabetic drugs are without side effects, and these drugs pose an economic burden. Therefore, the investigation of novel anti-diabetic regimens is a major challenge for researchers, in which nature has been the primary resource for the discovery of potential therapeutics. Many plants have been shown to act as anti-diabetic agents, in which the main active constituents are believed to be polyphenols. Natural products containing high polyphenol levels can control carbohydrate metabolism by various mechanisms, such as protecting and restoring beta-cell integrity, enhancing insulin releasing activity, and increasing cellular glucose uptake. Blackberries, red grapes, apricots, eggplant and popular drinks such as coffee, cocoa and green tea are all rich in polyphenols, which may dampen insulin resistance and be natural alternatives in the treatment of diabetes. Therefore, the aim of this review is to report on the available anti-diabetic polyphenols (medicinal plants, fruits and vegetables), their mechanisms in the various pathways of DM and their correlations with DM. Additionally, this review emphasizes the types of polyphenols that could be potential future resources in the treatment of DM via either novel regimens or as supplementary agents.

Physicochemical Properties, Minerals, Trace Elements, and Heavy Metals in Honey of Different Origins: A Comprehensive Review

Honey is a popular natural food product with a very complex composition mainly consisting of both organic and inorganic constituents. The composition of honey is strongly influenced by both natural and anthropogenic factors, which vary based on its botanical and geographical origins. Although minerals and heavy metals are minor constituents of honey, they play vital role in determining its quality. There are several different analytical methods used to determine the chemical elements in honey. These methods are typically based on spectroscopy or spectrometry techniques (including atomic absorption spectrometry, atomic emission spectrometry, inductively coupled plasma mass spectrometry, and inductively coupled plasma optical emission spectrometry). This review compiles available scientific information on minerals and heavy metals in honey reported from all over the world. To date, 54 chemical elements in various types of honey have been identified and can be divided into 3 groups: major or macroelements (Na, K, Ca, Mg, P, S, Cl), minor or trace elements (Al, Cu, Pb, Zn, Mn, Cd, Tl, Co, Ni, Rb, Ba, Be, Bi, U, V, Fe, Pt, Pd, Te, Hf, Mo, Sn, Sb, La, I, Sm, Tb, Dy, Sd, Th, Pr, Nd, Tm, Yb, Lu, Gd, Ho, Er, Ce, Cr, As, B, Br, Cd, Hg, Se, Sr), and heavy metals (trace elements that have a specific gravity at least 5 times higher than that of water and inorganic sources). Chemical elements in honey samples throughout the world vary in terms of concentrations and are also influenced by environmental pollution.