Na+-Mg2+ ion effects on conformation and translocation dynamics of single-stranded RNA: Cooperation and competition.

The nanopore-based translocation of a single-stranded RNA (ssRNA) in mixed salt solution has garnered increasing interest for its biological and technological significance. However, it is challenging to comprehensively understand the effects of the mixed ion species on the translocation dynamics due to their cooperation and competition, which can be directly reflected by the ion screening and neutralizing effects, respectively. In this study, Langevin dynamics simulation is employed to investigate the properties of ssRNA conformation and translocation in mixed Na+-Mg2+ ion environments. Simulation results reveal that the ion screening effect dominates the change in the ssRNA conformational size, the ion neutralizing effect controls the capture rate of the ssRNA by the nanopore, and both of them take charge of the different changes in translocation time of the ssRNA under various mixed ion environments. Under high Na+ ion concentration, as Mg2+ concentration increases, the ion neutralizing effect strengthens, weakening the driving force inside the nanopore, leading to longer translocation time. Conversely, at low Na+ concentration, an increase in Mg2+ concentration enhances the ion screening effect, aiding in faster translocation. Furthermore, these simulation results will be explained by quantitative analysis, advancing a deeper understanding of the complicated effects of the mixed Na+-Mg2+ ions.

Moving dynamics of a nanorobot with three DNA legs on nanopore-based tracks.

DNA nanorobots have garnered increasing attention in recent years due to their unique advantages of modularity and algorithm simplicity. To accomplish specific tasks in complex environments, various walking strategies are required for the DNA legs of the nanorobot. In this paper, we employ computational simulations to investigate a well-designed DNA-legged nanorobot moving along a nanopore-based track on a planar membrane. The nanorobot consists of a large nanoparticle as the robot core and three single-stranded DNAs (ssDNAs) as the robot legs. The nanopores linearly embedded in the membrane serve as the toeholds for the robot legs. A charge gradient along the pore distribution mainly powers the activation of the nanorobot. The nanorobot can move in two modes: a walking mode, where the robot legs sequentially enter the nanopores, and a jumping mode, where the robot legs may skip a nanopore to reach the next one. Moreover, we observe that the moving dynamics of the nanorobot on the nanopore-based tracks depends on pore-pore distance, pore charge gradient, external voltage, and leg length.

Mutual effects between single-stranded DNA conformation and Na+-Mg2+ ion competition in mixed salt solutions.

The ion-dependence of single-stranded DNA (ssDNA) conformational changes has attracted growing attention because of its biological and technological importance. Although single-species ion effects have been extensively explored, it is challenging to study the ssDNA conformational properties under mixed monovalent/divalent ion conditions due to the complications of ssDNA flexibility and ion-ion competition. In this study, we apply Langevin dynamics simulations to investigate mixed Na+/Mg2+ ion-dependent ssDNA conformations. The ssDNA structure is described using a coarse-grained model, in which the phosphate, base, and sugar of each nucleotide are represented by three different beads. A novel improvement in our simulation model is that mixed-salt-related electrostatic interactions are computed via combining Manning counterion condensation (MCC) theory with the Monte Carlo tightly bound ion (MCTBI) model. Based on this MCC-MCTBI combination, we report new empirical functions to describe the ion-concentration-dependent and ssDNA conformation/structure-dependent electrostatic effects. The calculation results relating to the ion binding properties and the simulation results relating to the ssDNA conformational properties are validated against experimental results. In addition, our simulation results suggest a quantitative relationship between the ssDNA conformation and Na+-Mg2+ competition; this in turn reveals their mutual impact in the ion atmosphere.

Dataset of normalized probability distributions of virtual bond lengths, bond angles, and dihedral angles for the coarse-grained single-stranded DNA structures.

The utility of the coarse-grained (CG) single-stranded DNA (ssDNA) model can drastically reduce the compute time for simulating the ssDNA dynamics. The model-matched CG potentials and the inherent potential constants can be derived by coarse-graining the experimentally measured ssDNA structures. A useful and widespread treatment of the CG model is to use three different pseudo-atoms P, S, and B to represent the atomic groups of phosphate, sugar, and base, respectively, in each nucleotide of the ssDNA structures. The three pseudo-atoms generate nine types of the structural parameters to characterize the unstructured ssDNA conformations, including three (virtual) bond lengths (P-S, S-B, and S-P) between two neighbouring beads, four bond angles (P-S-P, S-P-S, P-S-B, and B-S-P) between three adjacent bonds, and two dihedral angles (P-S-P-S and S-P-S-P) between three successive bonds. This paper mainly presents the data of normalized probability distributions of the bond lengths, bond angles, and dihedral angles for the CG ssDNAs.

Effects of electrostatic interactions on global folding and local conformational dynamics of a multidomain Y-family DNA polymerase.

The Y-family DNA polymerases specialize in translesion DNA synthesis, which is essential for replicating damaged DNA. The Y-family polymerases, which are made up of four stable domains, exhibit extensive distributions of charged residues, and are responsible for the tight formation of the protein-DNA complex. However, it is still unclear how the electrostatic interactions influence the conformational dynamics of the polymerases. Here, we focus on the case of a prototype Y-family DNA polymerase, Dpo4. Using coarse-grained models including a salt-dependent electrostatic potential, we investigate the effects of the electrostatic interactions on the folding process of Dpo4. Our simulations show that strong electrostatic interactions result in a three-state folding of Dpo4, consistent with the experimental observations. This folding process exhibits low cooperativity led by low salt concentration, where the individual domains fold one by one through one single pathway. Since the refined folding order of domains in multidomain proteins can shrink the configurational space, we suggest that the electrostatic interactions facilitate the Dpo4 folding. In addition, we study the local conformational dynamics of Dpo4 in terms of fluctuation and frustration analyses. We show that the electrostatic interactions can exaggerate the local conformational properties, which are in favor of the large-scale conformational transition of Dpo4 during the functional DNA binding. Our results underline the importance of electrostatic interactions in the conformational dynamics of Dpo4 at both the global and local scale, providing useful guidance in protein engineering at the multidomain level.

Translocation of a looped polymer threading through a nanopore.

Recent experiments reported that the complicated translocation dynamics of a looped DNA chain through a nanopore can be detected by ionic current blockade profiles. Inspired by the experimental results, we systematically study the translocation dynamics of a looped polymer, formed by three building blocks of a loop in the middle and two tails of the same length connected with the loop, by using Langevin dynamics simulations. Based on two entering modes (tail-leading and loop-leading) and three translocation orders (loop-tail-tail, tail-loop-tail, and tail-tail-loop), the translocation of the looped polymer is classified into six translocation pathways, corresponding to different current blockade profiles. The probabilities of the six translocation pathways are dependent on the loop length, polymer length, and pore radius. Moreover, the translocation times of the entire polymer and the loop are investigated. We find that the two translocation times show different dependencies on the translocation pathways and on the lengths of the loop and the entire polymer.

Identification of Inflammatory Genes, Pathways, and Immune Cells in Necrotizing Enterocolitis of Preterm Infant by Bioinformatics Approaches.

BACKGROUND: Necrotizing enterocolitis (NEC) is one of the most serious gastrointestinal disease-causing high morbidity and mortality in premature infants. However, the underlying mechanism of the pathogenesis of NEC is still not fully understood. METHODS: RNA sequencing of intestinal specimens from 9 NEC and 5 controls was employed to quantify the gene expression levels. RNA sequencing was employed to quantify the gene expression levels. DESeq2 tool was used to identify the differentially expressed genes. The biological function, pathways, transcription factors, and immune cells dysregulated in NEC were characterized by gene set enrichment analysis. RESULTS: In the present study, we analyzed RNA sequencing data of NECs and controls and revealed that immune-related pathways were highly activated, while some cellular responses to external stimuli-related pathways were inactivated in NEC. Moreover, B cells, macrophages M1, and plasma cells were identified as the major cell types involved in NEC. Furthermore, we also found that inflammation-related transcription factor genes, such as STAT1, STAT2, and IRF2, were significantly activated in NEC, further suggesting that these TFs might play critical roles in NEC pathogenesis. In addition, NEC samples exhibited heterogeneity to some extent. Interestingly, two subgroups in the NEC samples were identified by hierarchical clustering analysis. Notably, B cells, T cells, Th1, and Tregs involved in adaptive immune were predicted to highly infiltrate into subgroup I, while subgroup II was significantly infiltrated by neutrophils. The heterogeneity of immune cells in NEC indicated that both innate and adaptive immunes might induce NEC-related inflammatory response. CONCLUSIONS: In summary, we systematically analyzed inflammation-related genes, signaling pathways, and immune cells to characterize the NEC pathogenesis and samples, which greatly improved our understanding of the roles of inflammatory responses in NEC.

The translocation dynamics of the polymer through a conical pore: Non-stuck, weak-stuck, and strong-stuck modes.

The external voltage-driven polymer translocation through a conical pore (with a large opening at the entry and a small tip at the exit) is studied by using the Langevin dynamics simulation in this paper. The entire translocation process is divided into an approaching stage and a threading stage. First, the approaching stage starts from the polymer entering the large opening and ends up at a terminal monomer reaching the pore tip. In this stage, the polymer will undergo the conformation adjustment to fit the narrowed cross-sectional area of the pore, leading to three approaching modes: the non-stuck mode with a terminal monomer arriving at the pore tip smoothly, the weak-stuck mode for the polymer stuck inside the pore for a short duration with minor conformational adjustments, and the strong-stuck mode with major conformational changes and a long duration. The approaching times (the duration of the approaching stage) of the three approaching modes show different behavior as a function of the pore apex angle. Second, the threading stage describes that the polymer threads through the pore tip with a linear fashion. In this stage, an increase in the apex angle causes the reduction of the threading time (the duration of the threading stage) due to the increase in the driving force with the apex angle at the tip. Moreover, we also find that with the increase in the apex angle or the polymer length, the polymer threading dynamics will change from the quasi-equilibrium state to the non-equilibrium state.

RLDOCK: A New Method for Predicting RNA-Ligand Interactions.

The ability to accurately predict the binding site, binding pose, and binding affinity for ligand-RNA binding is important for RNA-targeted drug design. Here, we describe a new computational method, RLDOCK, for predicting the binding site and binding pose for ligand-RNA binding. By developing an energy-based scoring function, we sample exhaustively all of the possible binding sites with flexible ligand conformations for a ligand-RNA pair based on the geometric and energetic scores. The model distinguishes from other approaches in three notable features. First, the model enables exhaustive scanning of all of the possible binding sites, including multiple alternative or coexisting binding sites, for a given ligand-RNA pair. Second, the model is based on a new energy-based scoring function developed here. Third, the model employs a novel multistep screening algorithm to improve computational efficiency. Specifically, first, for each binding site, we use a gird-based energy map to rank the binding sites according to the minimum Lennard-Jones potential energy for the different ligand poses. Second, for a given selected binding site, we predict the ligand pose using a two-step algorithm. In the first step, we quickly identify the probable ligand poses using a coarse-grained simplified energy function. In the second step, for each of the probable ligand poses, we predict the ligand poses using a refined energy function. Tests of the RLDOCK for a set of 230 RNA-ligand-bound structures indicate that RLDOCK can successfully predict ligand poses for 27.8, 58.3, and 69.6% of all of the test cases with the root-mean-square deviation within 1.0, 2.0, and 3.0 Å, respectively, for the top three predicted docking poses. The computational method presented here may enable the development of a new, more comprehensive framework for the prediction of ligand-RNA binding with an ensemble of RNA conformations and the metal-ion effects.

RNA-Puzzles Round IV: 3D structure predictions of four ribozymes and two aptamers.

RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA 3D structure prediction. With agreement from crystallographers, the RNA structures are predicted by various groups before the publication of the crystal structures. We now report the prediction of 3D structures for six RNA sequences: four nucleolytic ribozymes and two riboswitches. Systematic protocols for comparing models and crystal structures are described and analyzed. In these six puzzles, we discuss (i) the comparison between the automated web servers and human experts; (ii) the prediction of coaxial stacking; (iii) the prediction of structural details and ligand binding; (iv) the development of novel prediction methods; and (v) the potential improvements to be made. We show that correct prediction of coaxial stacking and tertiary contacts is essential for the prediction of RNA architecture, while ligand binding modes can only be predicted with low resolution and simultaneous prediction of RNA structure with accurate ligand binding still remains out of reach. All the predicted models are available for the future development of force field parameters and the improvement of comparison and assessment tools.

[Determination of diazepam in aquatic products by ultra performance liquid chromatography-tandem mass spectrometry with pass-through solid phase extraction].

A method was developed for the determination of diazepam in aquatic products by pass-through solid phase extraction-ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The analyte was extracted with acetonitrile directly and purified on a Prime HLB solid phase extraction column (60 mg/3 mL). The separation was performed on an Acquity UPLC BEH C18 column (100 mm×2.1 mm, 1.7 µm)using methanol-0.1% (v/v) formic acid aqueous solution as the mobile phase in gradient elution mode. Qualitative analysis was performed in the multiple reaction monitoring (MRM) mode. The analyte was quantified by matrix-matched external standard curves. The results showed good linear relationship in the range of 0.1-10 ng/mL, and the correlation coefficient (r2) was greater than 0.99. The spiked recoveries of diazepam were 88.2%-101.1% at the spiked levels of 1.5, 3.0 and 15.0 µg/kg, and both the intra-and inter-day precisions were less than 10%. The developed method is simple, rapid and accurate, and it can meet the requirements for diazepam determination in aquatic product samples.

Helix-Based RNA Landscape Partition and Alternative Secondary Structure Determination.

RNA is a versatile macromolecule with the ability to fold into and interconvert between multiple functional conformations. The elucidation of the RNA folding landscape, especially the knowledge of alternative structures, is critical to uncover the physical mechanism of RNA functions. Here, we introduce a helix-based strategy for RNA folding landscape partition and alternative secondary structure determination. The benchmark test of 27 RNAs involving alternative stable structures shows that the model has the ability to divide the whole landscape into distinct partitions at the secondary structure level and predict the representative structures for each partition. Furthermore, the predicted structures and equilibrium populations of metastable conformations for the 2'dG-sensing riboswitch reveal the allosteric conformational switch on transcript length, which is consistent with the experimental study, indicating the importance of metastable states for RNA-based gene regulation. The model delivers a starting point for the landscape-based strategy toward the RNA folding mechanism and functions.

Kinetic Mechanism of RNA Helix-Terminal Basepairing-A Kinetic Minima Network Analysis.

RNA functions are often kinetically controlled. The folding kinetics of RNAs involves global structural changes and local nucleotide movement, such as base flipping. The most elementary step in RNA folding is the closing and opening of a basepair. By integrating molecular dynamics simulation, master equation, and kinetic Monte Carlo simulation, we investigate the kinetics mechanism of RNA helix-terminal basepairing. The study reveals a six-state folding scheme with three dominant folding pathways of tens, hundreds, and thousands of nanoseconds of folding timescales, respectively. The overall kinetics is rate limited by the detrapping of a misfolded state with the overall folding time of 10-5 s. Moreover, the analysis examines the different roles of the various driving forces, such as the basepairing and stacking interactions and the ion binding/dissociation effects on structural changes. The results may provide useful insights for developing a basepair opening/closing rate model and further kinetics models of large RNAs.

Predicting Monovalent Ion Correlation Effects in Nucleic Acids.

Ion correlation and fluctuation can play a potentially significant role in metal ion-nucleic acid interactions. Previous studies have focused on the effects for multivalent cations. However, the correlation and fluctuation effects can be important also for monovalent cations around the nucleic acid surface. Here, we report a model, gMCTBI, that can explicitly treat discrete distributions of both monovalent and multivalent cations and can account for the correlation and fluctuation effects for the cations in the solution. The gMCTBI model enables investigation of the global ion binding properties as well as the detailed discrete distributions of the bound ions. Accounting for the ion correlation effect for monovalent ions can lead to more accurate predictions, especially in a mixed monovalent and multivalent salt solution, for the number and location of the bound ions. Furthermore, although the monovalent ion-mediated correlation does not show a significant effect on the number of bound ions, the correlation may enhance the accumulation of monovalent ions near the nucleic acid surface and hence affect the ion distribution. The study further reveals novel ion correlation-induced effects in the competition between the different cations around nucleic acids.

[Determination of streptomycin and dihydrostreptomycin residues in honey by hydrophilic interaction liquid chromatography-tandem mass spectrometry].

An analytical method was developed for the determination of streptomycin and dihydrostreptomycin in honey using hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS). The streptomycin and dihydrostreptomycin residues in the test samples were extracted with 20 g/L trichloroacetic acid aqueous solution (including 50 mmol/L phosphate, pH 6.8) and cleaned on an Oasis HLB solid phase extraction column. The products were separated on a SIELC Obelisc R column with gradient elution using 0.5% (v/v) formic acid aqueous solution and acetonitrile as mobile phases. Streptomycin and dihydrostreptomycin were detected by liquid chromatography-tandem mass spectrometry in the positive ion mode using the external standard method. Under the optimal conditions, streptomycin and dihydrostreptomycin showed good linearity (r>0.99) in the range of 2.5-100 µg/L. The LOD and LOQ of the method was 2.0 µg/kg and 5.0 µg/kg, respectively. The spiked recoveries of the analytes from blank honey samples at the three levels of 5.0, 20.0 and 100.0 µg/kg were in the range of 86.9%-113.2% with the relative standard deviations less than 10%. With the advantages of convenience, rapidity, sensitivity and good repeatability, the method is suitable for the detection of streptomycin and dihydrostreptomycin in honey.

Simulation study on the migration of diblock copolymers in periodically patterned slits.

The forced migration of diblock copolymers (ANABNB) in periodically patterned slits was investigated by using Langevin dynamics simulation. The lower surface of the slit consists of stripe α and stripe ß distributed in alternating sequence, while the upper one is formed only by stripe ß. The interaction between block A and stripe α is strongly attractive, while all other interactions are purely repulsive. Simulation results show that the migration of the diblock copolymer is remarkably dependent on the driving force and there is a transition region at moderate driving force. The transition driving force ft, where the transition region occurs, decreases monotonously with increasing length of block B (NB) but is independent of the polymer length and the periodic length of the slit, which is interpreted from the free energy landscape of diblock copolymer migration. The results also show that periodic slits could be used to separate diblock polymers with different NB by tuning the external driving force.

Predicting RNA-Metal Ion Binding with Ion Dehydration Effects.

Metal ions play essential roles in nucleic acids folding and stability. The interaction between metal ions and nucleic acids can be highly complicated because of the interplay between various effects such as ion correlation, fluctuation, and dehydration. These effects may be particularly important for multivalent ions such as Mg2+ ions. Previous efforts to model ion correlation and fluctuation effects led to the development of the Monte Carlo tightly bound ion model. Here, by incorporating ion hydration/dehydration effects into the Monte Carlo tightly bound ion model, we develop a, to our knowledge, new approach to predict ion binding. The new model enables predictions for not only the number of bound ions but also the three-dimensional spatial distribution of the bound ions. Furthermore, the new model reveals several intriguing features for the bound ions such as the mutual enhancement/inhibition in ion binding between the fully hydrated (diffuse) ions, the outer-shell dehydrated ions, and the inner-shell dehydrated ions and novel features for the monovalent-divalent ion interplay due to the hydration effect.

Trapped and non-trapped polymer translocations through a spherical pore.

The polymer translocation through a spherical pore is studied using the Langevin dynamics simulation. The translocation events are classified into two types: one is the trapped translocation in which the entire polymer is trapped in the pore and the other is the non-trapped translocation where the pore cannot hold the whole polymer. We find that the trapped translocation is favored at large spheres and small external voltages. However, the monomer-pore attraction would lead to the non-monotonic behavior of the trapped translocation possibility out of all translocation events. Moreover, both the trapped and non-trapped translocation times are dependent on the polymer length, pore size, external voltage, and the monomer-pore attraction. There exist two pathways for the polymer in the trapped translocation: an actively trapped pathway for the polymer trapped in the pore before the head monomer arrives at the pore exit, and a passively trapped pathway for the polymer trapped in the pore while the head monomer is struggling to move out of the pore. The studies of trapped pathways can provide a deep understanding of the polymer translocation behavior.

Randomness of Eigenstates of Many-Body Quantum Systems.

The emergence of random eigenstates of quantum many-body systems in integrable-chaos transitions is the underlying mechanism of thermalization for these quantum systems. We use fidelity and modulus fidelity to measure the randomness of eigenstates in quantum many-body systems. Analytic results of modulus fidelity between random vectors are obtained to be a judge for the degree of randomness. Unlike fidelity, which just refers to a kind of criterion of necessity, modulus fidelity can measure the degree of randomness in eigenstates of a one-dimension (1D) hard-core boson system and identifies the integrable-chaos transition in this system.

Simulation study on the translocation of polyelectrolyte through conical nanopores.

Experiments have suggested that the conical nanopore may be a reasonable sensor for the biopolymer analysis as it can provide high-resolution current signal. In this paper, we use Langevin dynamics simulation to study the translocation of charged polymer (polyelectrolyte) through three different conical nanopores, a single-conical nanopore with large entry and small exit (pore I), a single-conical nanopore with small entry and large exit (pore II), and a double-conical nanopore with the tip (narrowest place) at the middle (pore III). Simulation shows that the detailed translocation behaviors are of pore structure dependence. Pore I might be the most reasonable one for the polyelectrolyte analysis, especially at strong monomer-pore attraction, since it can efficiently reduce the polyelectrolyte speed at the tip. The simulation results are interpreted by the free energy profiles of the polyelectrolyte translocation through different pores and the time of individual monomer passing through the tips.