Predicting DNA duplex stability from the base sequence

Solvation free energy in governing equations for DNA hybridization, protein-ligand binding, and protein folding

This work examines the thermodynamics of model biomolecular interactions using a governing equation that accounts for the participation of bulk water in the equilibria. In the first example, the binding affinities of two DNA duplexes, one of nine and one of 10 base pairs in length, are measured and characterized by isothermal titration calorimetry (ITC) as a function of concentration. The results indicate that the change in solvation free energy that accompanies duplex formation (ΔGS) is large and unfavorable. The duplex with the larger number of G:C pairings yields the largest change in solvation free energy, ΔGS = +460 kcal·mol-1per base pair at 25 °C. A van't Hoff analysis of the data is complicated by the varying degree of intramolecular base stacking within each DNA strand as a function of temperature. A modeling study reveals how the solvation free energy alters the output of a typical ITC experiment and leads to a good, though misleading, fit to the classical equilibrium equation. The same thermodynamic framework is applied to a model protein-ligand interaction, the binding of ribonuclease A with the nucleotide inhibitor 3'-UMP, and to a conformational equilibrium, the change in tertiary structure of α-lactalbumin in molar guanidinium chloride solutions. The ribonuclease study yields a value of ΔGS = +160 kcal·mol-1, whereas the folding equilibrium yields ΔGS ≈ 0, an apparent characteristic of hydrophobic interactions. These examples provide insight on the role of solvation energy in binding equilibria and suggest a pivot in the fundamental application of thermodynamics to solution chemistry.

Generation of a plasmid series for rapid sub-cloning and use in various Enterobacteriaceae

Plasmids are molecular genetic tools used for trans-complementation and gene expression in bacteria. Challenges faced by researchers include limited repertoire of antibiotic resistance of plasmids, issues related to plasmid compatibility and restricted or incompatible multiple cloning sites when needing to change plasmid copy number to tune production of their protein of interest. In this study, a series of plasmids were generated with compatible multiple cloning sites and homologous DNA regions to allow for modular cloning for rapid exchange of antibiotic resistance and plasmid origin. Plasmids generated in this series have options for high, mid, and low plasmid copy number, and have either an integrated FLAG epitope in the multiple cloning site or possess an uninterrupted multiple cloning site with the option of using the common LacZ-based blue/white screening method. Low copy plasmids also have one of five antibiotic selection markers. To demonstrate functionality of these plasmids, a representative FLAG tagged protein and mCherry were cloned into the low copy plasmids and expressed in various bacteria belonging to the Enterobacteriaceae family. In conclusion, by creating a new plasmid series, we have expanded the toolkit of available molecular biology tools for bacterial work.

Maximal Genetic Code Symmetry Is a Physicochemical Purine-Pyrimidine Symmetry Language for Transcription and Translation in the Flow of Genetic Information from DNA to Proteins

Until now, research has not taken into consideration the physicochemical purine-pyrimidine symmetries of the genetic code in the transcription and translation processes of proteinogenesis. Our Supersymmetry Genetic Code table, developed in 2022, is common and unique for all RNA and DNA living species. Its basic structure is a purine-pyrimidine symmetry net with double mirror symmetry. Accordingly, the symmetry of the genetic code directly shows its organisation based on the principle of nucleotide Watson-Crick and codon-anticodon pairing. The maximal purine-pyrimidine symmetries of codons show that each codon has a strictly defined and unchangeable position within the genetic code. We discovered that the physicochemical symmetries of the genetic code play a fundamental role in recognising and differentiating codons from mRNA and the anticodon tRNA and aminoacyl-tRNA synthetases in the transcription and translation processes. These symmetries also support the wobble hypothesis with non-Watson-Crick pairing interactions between the translation process from mRNA to tRNA. The Supersymmetry Genetic Code table shows a specific arrangement of the second base of codons, according to which it is possible that an anticodon from tRNA recognises whether a codon from mRNA belongs to an amino acid with two or four codons, which is very important in the purposeful use of the wobble pairing process. Therefore, we show that canonical and wobble pairings essentially do not lead to misreading and errors during translation, and we point out the role of physicochemical purine-pyrimidine symmetries in decreasing disorder according to error minimisation and preserving the integrity of biological processes during proteinogenesis.

Identification of sepsis-causing bacteria from whole blood without culture using primers with no cross-reactivity to human DNA

Sepsis is a major health concern globally, and identification of the causative organism usually takes several days. Furthermore, molecular amplification using whole blood from patients with sepsis remains challenging because of primer cross-reactivity with human DNA, which can delay appropriate clinical intervention. To address these concerns, we designed primers that could reduce cross-reactivity. By evaluating these primers against human DNA, we confirmed that the cross-reactivity observed with conventional primers was notably absent. In silico PCR further demonstrated the specificity and efficiency of the designed primers across 23 bacterial species that are often associated with sepsis. When tested using blood samples from sepsis patients, the designed primers showed moderate sensitivity and high specificity. Surprisingly, our method identified bacteria even in samples that were detected at other sites but tested negative using conventional blood culture methods. Although we identified some challenges, such as contamination with Acetobacter aceti due to the saponin pretreatment of samples, the developed method demonstrates remarkable potential for rapid identification of the causative organisms of sepsis and provides a new avenue for diagnosis in clinical practice.

Nucleotide and dinucleotide preference of segmented viruses are shaped more by segment: In case study of tomato spotted wilt virus

Several studies have showed that the nucleotide and dinucleotide composition of viruses possibly follows their host species or protein coding region. Nevertheless, the influence of viral segment on viral nucleotide and dinucleotide composition is still unknown. Here, we explored through tomato spotted wilt virus (TSWV), a segmented virus that seriously threatens the production of tomatoes all over the world. Through nucleotide composition analysis, we found the same over-representation of A across all viral segments at the first and second codon position, but it exhibited distinct in segments at the third codon position. Interestingly, the protein coding regions which encoded by the same or different segments exhibit obvious distinct nucleotide preference. Then, we found that the dinucleotides UpG and CpU were overrepresented and the dinucleotides UpA, CpG and GpU were underrepresented, not only in the complete genomic sequences, but also in different segments, protein coding regions and host species. Notably, 100% of the data investigated here were predicted to the correct viral segment and protein coding region, despite the fact that only 67% of the data analyzed here were predicted to the correct viral host species. In conclusion, in case study of TSWV, nucleotide composition and dinucleotide preference of segment viruses are more strongly dependent on segment and protein coding region than on host species. This research provides a novel perspective on the molecular evolutionary mechanisms of TSWV and provides reference for future research on genetic diversity of segmented viruses.

DNASCANNER v2: A Web-Based Tool to Analyze the Characteristic Properties of Nucleotide Sequences

Throughout the process of evolution, DNA undergoes the accumulation of distinct mutations, which can often result in highly organized patterns that serve various essential biological functions. These patterns encompass various genomic elements and provide valuable insights into the regulatory and functional aspects of DNA. The physicochemical, mechanical, thermodynamic, and structural properties of DNA sequences play a crucial role in the formation of specific patterns. These properties contribute to the three-dimensional structure of DNA and influence their interactions with proteins, regulatory elements, and other molecules. In this study, we introduce DNASCANNER v2, an advanced version of our previously published algorithm DNASCANNER for analyzing DNA properties. The current tool is built using the FLASK framework in Python language. Featuring a user-friendly interface tailored for nonspecialized researchers, it offers an extensive analysis of 158 DNA properties, including mono/di/trinucleotide frequencies, structural, physicochemical, thermodynamics, and mechanical properties of DNA sequences. The tool provides downloadable results and offers interactive plots for easy interpretation and comparison between different features. We also demonstrate the utility of DNASCANNER v2 in analyzing splice-site junctions, casposon insertion sequences, and transposon insertion sites (TIS) within the bacterial and human genomes, respectively. We also developed a deep learning module for the prediction of potential TIS in a given nucleotide sequence. In the future, we aim to optimize the performance of this prediction model through extensive training on larger data sets.

Development of self-compatible Chinese cabbage lines of Chiifu through marker-assisted selection

The continuously refined genome assembly of the Chinese cabbage accession Chiifu is widely recognized as the reference for Brassica rapa. However, the high self-incompatibility of Chiifu limits its broader utilization. In this study, we report the development of self-compatible Chiifu lines through a meticulous marker-assisted selection (MAS) strategy, involving the substitution of the Chiifu allele of MLPK (M-locus protein kinase) with that from the self-compatible Yellow Sarson (YS). A YS-based marker (SC-MLPK) was employed to screen 841 B. rapa accessions, confirming that all eight accessions with the mlpk/mlpk (mm) genotype exhibited self-compatibility. Additionally, we designed 131 High-Resolution Melting (HRM) markers evenly distributed across the B. rapa genome as genomic background selection (GBS) markers to facilitate the introgression of self-compatibility from YS into Chiifu along with SC-MLPK. Genome background screening revealed that the BC3S1 population had a proportion of the recurrent parent genome (PR) ranging from 93.9% to 98.5%. From this population, we identified self-compatible individuals exhibiting a high number of pollen tubes penetrating stigmas (NPT) (>25) and a maximum compatibility index (CI) value of 7.5. Furthermore, we selected two individuals demonstrating significant similarity to Chiifu in both genetic background and morphological appearance, alongside self-compatibility. These selected individuals were self-pollinated to generate two novel lines designated as SC-Chiifu Lines. The development of these self-compatible Chiifu lines, together with the SC-MLPK marker and the set of HRM markers, represents valuable tools for B. rapa genetics and breeding.

Unleashing inkjet-printed nanostructured electrodes and battery-free potentiostat for the DNA-based multiplexed detection of SARS-CoV-2 genes

Following the global COVID-19 pandemic triggered by SARS-CoV-2, the need for rapid, specific and cost-effective point-of-care diagnostic solutions remains paramount. Even though COVID-19 is no longer a public health emergency, the disease still poses a global threat leading to deaths, and it continues to change with the risk of new variants emerging causing a new surge in cases and deaths. Here, we address the urgent need for rapid, cost-effective and point-of-care diagnostic solutions for SARS-CoV-2. We propose a multiplexed DNA-based sensing platform that utilizes inkjet-printed nanostructured gold electrodes and an inkjet-printed battery-free near-field communication (NFC) potentiostat for the simultaneous quantitative detection of two SARS-CoV-2 genes, the ORF1ab and the N gene. The detection strategy based on the formation of an RNA-DNA sandwich structure leads to a highly specific electrochemical output. The inkjet-printed nanostructured gold electrodes providing a large surface area enable efficient binding and increase the sensitivity. The inkjet-printed battery-free NFC potentiostat enables rapid measurements and real-time data analysis via a smartphone application, making the platform accessible and portable. With the advantages of speed (5 min), simplicity, sensitivity (low pM range, ∼450% signal gain) and cost-effectiveness, the proposed platform is a promising alternative for point-of-care diagnostics and high-throughput analysis that complements the COVID-19 diagnostic toolkit.

Hydration Waters Make Up for the Missing Third Hydrogen Bond in the A·T Base Pair

Base pairing complementarity is central to DNA function. G·C and A·T pair specificity is thought to originate from the different number of hydrogen bonds the pairs make. Quantifying how many hydrogen bonds exist can be difficult because water molecules in the surrounding can make up for or disrupt direct hydrogen bonds, and the hydration structures around A·T and G·C pairs on duplex DNA are distinct. Large-scale computer simulations have been used here to create a detailed map for the hydration structure on A·T and G·C base pairs in water. The contributions of specific hydration waters to the free energy of each of the hydrogen bonds in the A·T and G·C pairs were computed. Using the equilibrium fractions of hydrated versus unhydrated states from the hydration profiles, the impact of specific bound waters on each hydrogen bond can be uniquely quantified using a thermodynamic construction. The findings suggest that hydration water in the minor groove of an A·T pair can provide up to about 2 kcal/mol of free energy advantage, effectively making up for the missing third hydrogen bond in the A·T pair compared to G·C, rendering the intrinsic thermodynamic stability of the A·T pair almost synonymous with G·C.

Diel Cycle Proteomics: Illuminating Molecular Dynamics in Purple Bacteria for Optimized Biotechnological Applications

Circadian rhythms, characterized by approximately 24 h cycles, play a pivotal role in enabling various organisms to synchronize their biological activities with daily variations. While ubiquitous in Eukaryotes, circadian clocks remain exclusively characterized in Cyanobacteria among Prokaryotes. These rhythms are regulated by a core oscillator, which is controlled by a cluster of three genes: kaiA, kaiB, and kaiC. Interestingly, recent studies revealed rhythmic activities, potentially tied to a circadian clock, in other Prokaryotes, including purple bacteria such as Rhodospirillum rubrum, known for its applications in fuel and plastic bioproduction. However, the pivotal question of how light and dark cycles influence protein dynamics and the expression of putative circadian clock genes remains unexplored in purple non-sulfur bacteria. Unraveling the regulation of these molecular clocks holds the key to unlocking optimal conditions for harnessing the biotechnological potential of R. rubrum. Understanding how its proteome responds to different light regimes-whether under continuous light or alternating light and dark cycles-could pave the way for precisely fine-tuning bioproduction processes. Here, we report for the first time the expressed proteome of R. rubrum grown under continuous light versus light and dark cycle conditions using a shotgun proteomic analysis. In addition, we measured the impact of light regimes on the expression of four putative circadian clock genes (kaiB1, kaiB2, kaiC1, kaiC2) at the transcriptional and translational levels using RT-qPCR and targeted proteomic (MRM-MS), respectively. The data revealed significant effects of light conditions on the overall differential regulation of the proteome, particularly during the early growth stages. Notably, several proteins were found to be differentially regulated during the light or dark period, thus impacting crucial biological processes such as energy conversion pathways and the general stress response. Furthermore, our study unveiled distinct regulation of the four kai genes at both the mRNA and protein levels in response to varying light conditions. Deciphering the impact of the diel cycle on purple bacteria not only enhances our understanding of their ecology but also holds promise for optimizing their applications in biotechnology, providing valuable insights into the origin and evolution of prokaryotic clock mechanisms.

Building an ab initio solvated DNA model using Euclidean neural networks

Accurately modeling large biomolecules such as DNA from first principles is fundamentally challenging due to the steep computational scaling of ab initio quantum chemistry methods. This limitation becomes even more prominent when modeling biomolecules in solution due to the need to include large numbers of solvent molecules. We present a machine-learned electron density model based on a Euclidean neural network framework that includes a built-in understanding of equivariance to model explicitly solvated double-stranded DNA. By training the machine learning model using molecular fragments that sample the key DNA and solvent interactions, we show that the model predicts electron densities of arbitrary systems of solvated DNA accurately, resolves polarization effects that are neglected by classical force fields, and captures the physics of the DNA-solvent interaction at the ab initio level.

Structure of the WYL-domain containing transcription activator, DriD, in complex with ssDNA effector and DNA target site

Transcription regulators play central roles in orchestrating responses to changing environmental conditions. Recently the Caulobacter crescentus transcription activator DriD, which belongs to the newly defined WYL-domain family, was shown to regulate DNA damage responses independent of the canonical SOS pathway. However, the molecular mechanisms by which DriD and other WYL-regulators sense environmental signals and recognize DNA are not well understood. We showed DriD DNA-binding is triggered by its interaction with ssDNA, which is produced during DNA damage. Here we describe the structure of the full-length C. crescentus DriD bound to both target DNA and effector ssDNA. DriD consists of an N-terminal winged-HTH (wHTH) domain, linker region, three-helix bundle, WYL-domain and C-terminal WCX-dimer domain. Strikingly, DriD binds DNA using a novel, asymmetric DNA-binding mechanism that results from different conformations adopted by the linker. Although the linker does not touch DNA, our data show that contacts it makes with the wHTH are key for specific DNA binding. The structure indicates how ssDNA-effector binding to the WYL-domain impacts wHTH DNA binding. In conclusion, we present the first structure of a WYL-activator bound to both effector and target DNA. The structure unveils a unique, asymmetric DNA binding mode that is likely conserved among WYL-activators.

Rational Design of DNA Hydrogels Based on Molecular Dynamics of Polymers

In recent years, DNA has emerged as a fascinating building material to engineer hydrogel due to its excellent programmability, which has gained considerable attention in biomedical applications. Understanding the structure-property relationship and underlying molecular determinants of DNA hydrogel is essential to precisely tailor its macroscopic properties at molecular level. In this review, the rational design principles of DNA molecular networks based on molecular dynamics of polymers on the temporal scale, which can be engineered via the backbone rigidity and crosslinking kinetics, are highlighted. By elucidating the underlying molecular mechanisms and theories, it is aimed to provide a comprehensive overview of how the tunable DNA backbone rigidity and the crosslinking kinetics lead to desirable macroscopic properties of DNA hydrogels, including mechanical properties, diffusive permeability, swelling behaviors, and dynamic features. Furthermore, it is also discussed how the tunable macroscopic properties make DNA hydrogels promising candidates for biomedical applications, such as cell culture, tissue engineering, bio-sensing, and drug delivery.

Physical Peculiarity of Two Sites in Human Promoters: Universality and Diverse Usage in Gene Function

Since the discovery of physical peculiarities around transcription start sites (TSSs) and a site corresponding to the TATA box, research has revealed only the average features of these sites. Unsettled enigmas include the individual genes with these features and whether they relate to gene function. Herein, using 10 physical properties of DNA, including duplex DNA free energy, base stacking energy, protein-induced deformability, and stabilizing energy of Z-DNA, we clarified for the first time that approximately 97% of the promoters of 21,056 human protein-coding genes have distinctive physical properties around the TSS and/or position -27; of these, nearly 65% exhibited such properties at both sites. Furthermore, about 55% of the 21,056 genes had a minimum value of regional duplex DNA free energy within TSS-centered ±300 bp regions. Notably, distinctive physical properties within the promoters and free energies of the surrounding regions separated human protein-coding genes into five groups; each contained specific gene ontology (GO) terms. The group represented by immune response genes differed distinctly from the other four regarding the parameter of the free energies of the surrounding regions. A vital suggestion from this study is that physical-feature-based analyses of genomes may reveal new aspects of the organization and regulation of genes.

DNA superhelicity

Closing each strand of a DNA duplex upon itself fixes its linking number L. This topological condition couples together the secondary and tertiary structures of the resulting ccDNA topoisomer, a constraint that is not present in otherwise identical nicked or linear DNAs. Fixing L has a range of structural, energetic and functional consequences. Here we consider how L having different integer values (that is, different superhelicities) affects ccDNA molecules. The approaches used are primarily theoretical, and are developed from a historical perspective. In brief, processes that either relax or increase superhelicity, or repartition what is there, may either release or require free energy. The energies involved can be substantial, sufficient to influence many events, directly or indirectly. Here two examples are developed. The changes of unconstrained superhelicity that occur during nucleosome attachment and release are examined. And a simple theoretical model of superhelically driven DNA structural transitions is described that calculates equilibrium distributions for populations of identical topoisomers. This model is used to examine how these distributions change with superhelicity and other factors, and applied to analyze several situations of biological interest.

Competitive Influence of Alkali Metals in the Ion Atmosphere on Nucleic Acid Duplex Stability

The nonspecific atmosphere around nucleic acids, often termed the ion atmosphere, encompasses a collection of weak ion-nucleic acid interactions. Although nonspecific, the ion atmosphere has been shown to influence nucleic acid folding and structural stability. Studies investigating the composition of the ion atmosphere have shown competitive occupancy of the atmosphere between metal ions in the same solution. Many studies have investigated single ion effects on nucleic acid secondary structure stability; however, no comprehensive studies have investigated how the competitive occupancy of mixed ions in the ion atmosphere influences nucleic acid secondary structure stability. Here, six oligonucleotides were optically melted in buffers containing molar quantities, or mixtures, of either XCl (X = Li, K, Rb, or Cs) or NaCl. A correction factor was developed to better predict RNA duplex stability in solutions containing mixed XCl/NaCl. For solutions containing a 1:1 mixture of XCl/NaCl, one alkali metal chloride contributed more to duplex stability than the other. Overall, there was a 54% improvement in predictive capabilities with the correction factor compared with the standard 1.0 M NaCl nearest-neighbor models. This correction factor can be used in models to better predict RNA secondary structure in solutions containing mixed XCl/NaCl.

A novel method for automated crystal visualization and quantification in murine folic acid-induced acute kidney injury

Folic acid (FA)-induced acute kidney injury (FA-AKI) is an increasingly prevalent rodent disease model involving the injection of a high dose of FA that culminates in renal FA crystal deposition and injury. However, the literature characterizing the FA-AKI model is sparse and dated in part due to the absence of a well-described methodology for the visualization and quantification of renal FA crystals. Using widely available materials and tools, we developed a straightforward and crystal-preserving histological protocol that can be coupled with automated imaging for renal FA crystal visualization and generated an automated macro for downstream crystal content quantification. The applicability of the method was demonstrated by characterizing the model in male and female C57BL6/JRj mice after 3 and 30 h of FA treatment. Kidneys from both sexes and timepoints showed a bimodal distribution of FA crystal deposition in the cortical and medullary regions while, compared with males, females exhibited higher renal FA crystal content at the 30-h timepoint accompanied by greater kidney weight and higher plasma urea. Despite comparable plasma phosphate concentrations, FA-AKI resulted in a substantially more elevated plasma intact fibroblast growth factor 23 (FGF23) in females, reflected by a similar pattern in osseous Fgf23 mRNA expression. Therefore, the presented method constitutes a valuable tool for the quantification of renal FA crystals, which can aid the mechanistic characterization of the FA-AKI model and serves as a means to control for confounding changes in FA crystallization when using the model for investigating early and prophylactic AKI therapeutic interventions.NEW & NOTEWORTHY Here, we describe a novel method for the visualization and quantification of renal folic acid (FA) crystals in the rodent FA-induced acute kidney injury (FA-AKI) model. The protocol involves a straightforward histological approach followed by fully automated imaging and quantification steps. Applicability was confirmed by showing that the FA-AKI model is sex-dependent. The method can serve as a tool to aid in characterizing FA-AKI and to control for studies investigating prophylactic therapeutic avenues using FA-AKI.

Systematic analysis of the codon usage patterns of African swine fever virus genome coding sequences reveals its host adaptation phenotype

African swine fever (ASF) is a severe haemorrhagic disease caused by the African swine fever virus (ASFV), transmitted by ticks, resulting in high mortality among domestic pigs and wild boars. The global spread of ASFV poses significant economic threats to the swine industry. This study employs diverse analytical methods to explore ASFV's evolution and host adaptation, focusing on codon usage patterns and associated factors. Utilizing phylogenetic analysis methods including neighbour-joining and maximum-likelihood, 64 ASFV strains were categorized into four clades. Codon usage bias (CUB) is modest in ASFV coding sequences. This research identifies multiple factors - such as nucleotide composition, mutational pressures, natural selection and geographical diversity - contributing to the formation of CUB in ASFV. Analysis of relative synonymous codon usage reveals CUB variations within clades and among ASFVs and their hosts. Both Codon Adaptation Index and Similarity Index analyses confirm that ASFV strains are highly adapted to soft ticks (Ornithodoros moubata) but less so to domestic pigs, which could be a result of the long-term co-evolution of ASFV with ticks. This study sheds light on the factors influencing ASFV's codon usage and fitness dynamics, enriching our understanding of its evolution, adaptation and host interactions.

VarGibbs Usage in the Optimization of Nearest-Neighbor Parameters and Prediction of Melting Temperature of RNA Duplexes

The nearest-neighbor (NN) model is a general tool for the evaluation for oligonucleotide thermodynamic stability. It is primarily used for the prediction of melting temperatures but has also found use in RNA secondary structure prediction and theoretical models of hybridization kinetics. One of the key problems is to obtain the NN parameters from melting temperatures, and VarGibbs was designed to obtain those parameters directly from melting temperatures. Here we will describe the basic workflow from RNA melting temperatures to NN parameters with the use of VarGibbs. We start by a brief revision of the basic concepts of RNA hybridization and of the NN model and then show how to prepare the data files, run the parameter optimization, and interpret the results.

The Supersymmetry Genetic Code Table and Quadruplet Symmetries of DNA Molecules Are Unchangeable and Synchronized with Codon-Free Energy Mapping during Evolution

The Supersymmetry Genetic code (SSyGC) table is based on five physicochemical symmetries: (1) double mirror symmetry on the principle of the horizontal and vertical mirror symmetry axis between all bases (purines [A, G) and pyrimidines (U, C)] and (2) of bases in the form of codons; (3) direct-complement like codon/anticodon symmetry in the sixteen alternating boxes of the genetic code columns; (4) A + T-rich and C + G-rich alternate codons in the same row between both columns of the genetic code; (5) the same position between divided and undivided codon boxes in relation to horizontal mirror symmetry axis. The SSyGC table has a unique physicochemical purine-pyrimidine symmetry net which is as the core symmetry common for all, with more than thirty different nuclear and mitochondrial genetic codes. This net is present in the SSyGC table of all RNA and DNA living species. None of these symmetries are present in the Standard Genetic Code (SGC) table which is constructed on the alphabetic horizontal and vertical U-C-A-G order of bases. Here, we show that the free energy value of each codon incorporated as fundamentally mapping the "energy code" in the SSyGC table is compatible with mirror symmetry. On the other hand, in the SGC table, the same free energy values of codons are dispersed and a mirror symmetry between them is not recognizable. At the same time, the mirror symmetry of the SSyGC table and the DNA quadruplets together with our classification of codons/trinucleotides are perfectly imbedded in the mirror symmetry energy mapping of codons/trinucleotides and point out in favor of maintaining the integrity of the genetic code and DNA genome. We also argue that physicochemical symmetries of the SSyGC table in the manner of the purine-pyrimidine symmetry net, the quadruplet symmetry of DNA molecule, and the free energy of codons have remined unchanged during all of evolution. The unchangeable and universal symmetry properties of the genetic code, DNA molecules, and the energy code are decreasing disorder between codons/trinucleotides and shed a new light on evolution. Diversity in all living species on Earth is broad, but the symmetries of the Supersymmetry Genetic Code as the code of life and the DNA quadruplets related to the "energy code" are unique, unchangeable, and have the power of natural laws.

Single-molecule analysis of DNA base-stacking energetics using patterned DNA nanostructures

The DNA double helix structure is stabilized by base-pairing and base-stacking interactions. However, a comprehensive understanding of dinucleotide base-stacking energetics is lacking. Here we combined multiplexed DNA-based point accumulation in nanoscale topography (DNA-PAINT) imaging with designer DNA nanostructures and measured the free energy of dinucleotide base stacking at the single-molecule level. Multiplexed imaging enabled us to extract the binding kinetics of an imager strand with and without additional dinucleotide stacking interactions. The DNA-PAINT data showed that a single additional dinucleotide base stacking results in up to 250-fold stabilization for the DNA duplex nanostructure. We found that the dinucleotide base-stacking energies vary from -0.95 ± 0.12 kcal mol-1 to -3.22 ± 0.04 kcal mol-1 for C|T and A|C base-stackings, respectively. We demonstrate the application of base-stacking energetics in designing DNA-PAINT probes for multiplexed super-resolution imaging, and efficient assembly of higher-order DNA nanostructures. Our results will aid in designing functional DNA nanostructures, and DNA and RNA aptamers, and facilitate better predictions of the local DNA structure.

LAMPPrimerBank, a manually curated database of experimentally validated loop-mediated isothermal amplification primers for detection of respiratory pathogens

PURPOSE AND METHODS

The emergence of coronavirus disease 2019 (COVID-19) has once again affirmed the significant threat of respiratory infections to global public health and the utmost importance of prompt diagnosis in managing and mitigating any pandemic. The nucleic acid amplification test (NAAT) is the primary detection method for most pathogens. Loop-mediated isothermal amplification (LAMP) is a rapid, simple, sensitive, and specific epitome of isothermal NAAT performed using a set of four to six primers. Primer design is a fundamental step in LAMP assays, with several complexities and experimental screening requirements. To address this challenge, an online database is presented here. Its workflow comprises three steps: literature aggregation, data curation, and database and website implementation.

RESULTS

LAMPPrimerBank ( https://lampprimerbank.mathematik.uni-marburg.de ) is a manually curated database dedicated to experimentally validated LAMP primers, their peculiarities of assays, and accompanying literature, with a primary emphasis on respiratory pathogens. LAMPPrimerBank, with its user-friendly web interface and an open application programming interface, enables the accelerated and facile exploration, comparison, and exportation of LAMP primer sequences and their respective information from the massively scattered literature. LAMPPrimerBank currently comprises LAMP primers for diagnosing viral, bacterial, and fungal respiratory pathogens. Additionally, to address the challenge of false-positive results generated by nonspecific amplifications, LAMPPrimerBank computationally predicted and visualized the sizes of LAMP products for recorded primer sets in the database.

CONCLUSION

LAMPPrimerBank, as a pioneering database in the rapidly expanding field of isothermal NAAT, endeavors to confront the two challenges of the LAMP: primer design and discrimination of false-positive results.

Comparative study of encoded and alignment-based methods for virus taxonomy classification

The emergence of viruses and their variants has made virus taxonomy more important than ever before in controlling the spread of diseases. The creation of efficient treatments and cures that target particular virus properties can be aided by understanding virus taxonomy. Alignment-based methods are commonly used for this task, but are computationally expensive and time-consuming, especially when dealing with large datasets or when detecting new virus variants is time sensitive. An alternative approach, the encoded method, has been developed that does not require prior sequence alignment and provides faster results. However, each encoded method has its own claimed accuracy. Therefore, careful evaluation and comparison of the performance of different encoded methods are essential to identify the most accurate and reliable approach for virus taxonomy classification. This study aims to address this issue by providing a comprehensive and comparative analysis of the potential of encoded methods for virus classification and phylogenetics. We compared the vectors generated for each encoded method using distance metrics to determine their similarity to alignment-based methods. The results and their validation show that K-merNV followed by CgrDft encoded methods, perform similarly to state-of-the-art multi-sequence alignment methods. This is the first study to incorporate and compare encoded methods that will facilitate future research in making more informed decisions regarding selection of a suitable method for virus taxonomy.

RNA-Based Strategies for Cancer Therapy: In Silico Design and Evaluation of ASOs for Targeted Exon Skipping

Precision medicine in oncology has made significant progress in recent years by approving drugs that target specific genetic mutations. However, many cancer driver genes remain challenging to pharmacologically target ("undruggable"). To tackle this issue, RNA-based methods like antisense oligonucleotides (ASOs) that induce targeted exon skipping (ES) could provide a promising alternative. In this work, a comprehensive computational procedure is presented, focused on the development of ES-based cancer treatments. The procedure aims to produce specific protein variants, including inactive oncogenes and partially restored tumor suppressors. This novel computational procedure encompasses target-exon selection, in silico prediction of ES products, and identification of the best candidate ASOs for further experimental validation. The method was effectively employed on extensively mutated cancer genes, prioritized according to their suitability for ES-based interventions. Notable genes, such as NRAS and VHL, exhibited potential for this therapeutic approach, as specific target exons were identified and optimal ASO sequences were devised to induce their skipping. To the best of our knowledge, this is the first computational procedure that encompasses all necessary steps for designing ASO sequences tailored for targeted ES, contributing with a versatile and innovative approach to addressing the challenges posed by undruggable cancer driver genes and beyond.

Sensing nucleotide composition in virus RNA

Nucleotide composition plays a crucial role in the structure, function and recognition of RNA molecules. During infection, virus RNA is exposed to multiple endogenous proteins that detect local or global compositional biases and interfere with virus replication. Recent advancements in RNA:protein mapping technologies have enabled the identification of general RNA-binding preferences in the human proteome at basal level and in the context of virus infection. In this review, we explore how cellular proteins recognise nucleotide composition in virus RNA and the impact these interactions have on virus replication. Protein-binding G-rich and C-rich sequences are common examples of how host factors detect and limit infection, and, in contrast, viruses may have evolved to purge their genomes from such motifs. We also give examples of how human RNA-binding proteins inhibit virus replication, not only by destabilising virus RNA, but also by interfering with viral protein translation and genome encapsidation. Understanding the interplay between cellular proteins and virus RNA composition can provide insights into host-virus interactions and uncover potential targets for antiviral strategies.

Mechanical codes of chemical-scale specificity in DNA motifs

In gene transcription, certain sequences of double-stranded (ds)DNA play a vital role in nucleosome positioning and expression initiation. That dsDNA is deformed to various extents in these processes leads us to ask: Could the genomic DNA also have sequence specificity in its chemical-scale mechanical properties? We approach this question using statistical machine learning to determine the rigidity between DNA chemical moieties. What emerges for the polyA, polyG, TpA, and CpG sequences studied here is a unique trigram that contains the quantitative mechanical strengths between bases and along the backbone. In a way, such a sequence-dependent trigram could be viewed as a DNA mechanical code. Interestingly, we discover a compensatory competition between the axial base-stacking interaction and the transverse base-pairing interaction, and such a reciprocal relationship constitutes the most discriminating feature of the mechanical code. Our results also provide chemical-scale understanding for experimental observables. For example, the long polyA persistence length is shown to have strong base stacking while its complement (polyAc) exhibits high backbone rigidity. The mechanical code concept enables a direct reading of the physical interactions encoded in the sequence which, with further development, is expected to shed new light on DNA allostery and DNA-binding drugs.

Two are not enough: synthetic strategies and applications of unnatural base pairs

Nucleic acid chemistry is a rapidly evolving field, and the need for novel nucleotide modifications and artificial nucleotide building blocks for diagnostic and therapeutic use, material science or for studying cellular processes continues unabated. This review focusses on the development and application of unnatural base pairs as part of an expanded genetic alphabet. Not only recent developments in "nature-like" artificial base pairs are presented, but also current synthetic methods to get access to C-glycosidic nucleotides. Wide-ranging viability in synthesis is a prerequisite for the successful use of unnatural base pairs in a broader spectrum and will be discussed.

A novel rapid detection method for a single-nucleotide substitution mutation derived from canine urothelial and prostatic carcinoma cells present in small amounts in urine sediments

For early detection of canine urothelial and prostatic carcinoma, we intend to develop and commercialize a simple and rapid detection method for the BRAF V595E mutation, a known mutation in this cancer. Detection of the single-nucleotide substitution in cancer cells contained in urine sediments is effective for early cancer diagnosis. However, urine sediment also contains many normal cells, and when there is a small relative composition of cancer cells, the mutation is difficult to detect by conventional methods other than next-generation sequencing. Our new detection method enables reliable discrimination with the same labor and cost as the PCR method. We compared the results of our new method with the results of the conventional Sanger method for 38 canine urine sediment samples, and the results of 34 samples were consistent between both methods. The remaining four results were all determined to be negative by the Sanger method and positive by our new method. For these four samples, the ratio of the mutated gene to the wild-type gene was estimated using a third-generation sequencer, and the ratio of the mutated gene was 0.1%-1.4%. We postulate that the Sanger method gave a negative result because of the low abundance of the mutated gene in these samples, proving the high sensitivity of our new method.

Direct detection of drug-resistant Mycobacterium tuberculosis using targeted next generation sequencing

Mycobacterium tuberculosis complex (MTBC) infections are treated with combinations of antibiotics; however, these regimens are not as efficacious against multidrug and extensively drug resistant MTBC. Phenotypic (growth-based) drug susceptibility testing on slow growing bacteria like MTBC requires many weeks to months to complete, whereas sequencing-based approaches can predict drug resistance (DR) with reduced turnaround time. We sought to develop a multiplexed, targeted next generation sequencing (tNGS) assay that can predict DR and can be performed directly on clinical respiratory specimens. A multiplex PCR was designed to amplify a group of thirteen full-length genes and promoter regions with mutations known to be involved in resistance to first- and second-line MTBC drugs. Long-read amplicon libraries were sequenced with Oxford Nanopore Technologies platforms and high-confidence resistance mutations were identified in real-time using an in-house developed bioinformatics pipeline. Sensitivity, specificity, reproducibility, and accuracy of the tNGS assay was assessed as part of a clinical validation study. In total, tNGS was performed on 72 primary specimens and 55 MTBC-positive cultures and results were compared to clinical whole genome sequencing (WGS) performed on paired patient cultures. Complete or partial susceptibility profiles were generated from 82% of smear positive primary specimens and the resistance mutations identified by tNGS were 100% concordant with WGS. In addition to performing tNGS on primary clinical samples, this assay can be used to sequence MTBC cultures mixed with other mycobacterial species that would not yield WGS results. The assay can be effectively implemented in a clinical/diagnostic laboratory with a two to three day turnaround time and, even if batched weekly, tNGS results are available on average 15 days earlier than culture-derived WGS results. This study demonstrates that tNGS can reliably predict MTBC drug resistance directly from clinical specimens or cultures and provide critical information in a timely manner for the appropriate treatment of patients with DR tuberculosis.

Transcriptome-wide selection and validation of a solid set of reference genes for gene expression studies in the cephalopod mollusk Octopus vulgaris

Octopus vulgaris is a cephalopod mollusk and an active marine predator that has been at the center of a number of studies focused on the understanding of neural and biological plasticity. Studies on the machinery involved in e.g., learning and memory, regeneration, and neuromodulation are required to shed light on the conserved and/or unique mechanisms that these animals have evolved. Analysis of gene expression is one of the most essential means to expand our understanding of biological machinery, and the selection of an appropriate set of reference genes is the prerequisite for the quantitative real-time polymerase chain reaction (qRT-PCR). Here we selected 77 candidate reference genes (RGs) from a pool of stable and relatively high-expressed transcripts identified from the full-length transcriptome of O. vulgaris, and we evaluated their expression stabilities in different tissues through geNorm, NormFinder, Bestkeeper, Delta-CT method, and RefFinder. Although various algorithms provided different assemblages of the most stable reference genes for the different kinds of tissues tested here, a comprehensive ranking revealed RGs specific to the nervous system (Ov-RNF7 and Ov-RIOK2) and Ov-EIF2A and Ov-CUL1 across all considered tissues. Furthermore, we validated RGs by assessing the expression profiles of nine target genes (Ov-Naa15, Ov-Ltv1, Ov-CG9286, Ov-EIF3M, Ov-NOB1, Ov-CSDE1, Ov-Abi2, Ov-Homer2, and Ov-Snx20) in different areas of the octopus nervous system (gastric ganglion, as control). Our study allowed us to identify the most extensive set of stable reference genes currently available for the nervous system and appendages of adult O. vulgaris.

Phospholipase A2 enzymes differently impact PUFA release and oxylipin formation ex vivo in rat hearts

Phospholipase A2 (PLA2) enzymes cleave cell membrane phospholipids and release polyunsaturated fatty acids (PUFA), which can be converted into oxylipins. However, little is known about PLA2 preference for PUFA, and even less is known about how this further impacts oxylipin formation. Therefore, we investigated the role of different PLA2 groups in PUFA release and oxylipin formation in rat hearts. Sprague-Dawley rat heart homogenates were incubated without or with varespladib (VAR), methyl arachidonyl fluorophosphonate (MAFP) or EDTA. Free PUFA and oxylipins were determined by HPLC-MS/MS, and isoform expressions by RT-qPCR. Inhibition of sPLA2 IIA and/or V by VAR reduced the release of ARA and DHA, but only DHA oxylipins were inhibited. MAFP reduced the release of ARA, DHA, ALA, and EPA, and the formation of ARA, LA, DGLA, DHA, ALA, and EPA oxylipins. Interestingly, cyclooxygenase and 12-lipoxygenase oxylipins were not inhibited. mRNA expression levels of sPLA2 and iPLA2 isoforms were highest whereas levels of cPLA2 were low, consistent with activity. In conclusion, sPLA2 enzymes lead to the formation of DHA oxylipins, while iPLA2 is likely responsible for the formation of most other oxylipins in healthy rat hearts. Oxylipin formation cannot be implied from PUFA release, thus, both should be evaluated in PLA2 activity studies.

RT-LAMP as Diagnostic Tool for Influenza—A Virus Detection in Swine

Point-of-care diagnostic technologies are becoming more widely available for production species. Here, we describe the application of reverse transcription loop-mediated isothermal amplification (RT-LAMP) to detect the matrix (M) gene of influenza A virus in swine (IAV-S). M-specific LAMP primers were designed based on M gene sequences from IAV-S isolated in the USA between 2017 and 2020. The LAMP assay was incubated at 65 °C for 30 min, with the fluorescent signal read every 20 s. The assay’s limit of detection (LOD) was 20 M gene copies for direct LAMP of the matrix gene standard, and 100 M gene copies when using spiked extraction kits. The LOD was 1000 M genes when using cell culture samples. Detection in clinical samples showed a sensitivity of 94.3% and a specificity of 94.9%. These results show that the influenza M gene RT-LAMP assay can detect the presence of IAV in research laboratory conditions. With the appropriate fluorescent reader and heat block, the assay could be quickly validated as a low-cost, rapid, IAV-S screening tool for use on farms or in clinical diagnostic labs.

Machine learning-aided scoring of synthesis difficulties for designer chromosomes

Designer chromosomes are artificially synthesized chromosomes. Nowadays, these chromosomes have numerous applications ranging from medical research to the development of biofuels. However, some chromosome fragments can interfere with the chemical synthesis of designer chromosomes and eventually limit the widespread use of this technology. To address this issue, this study aimed to develop an interpretable machine learning framework to predict and quantify the synthesis difficulties of designer chromosomes in advance. Through the use of this framework, six key sequence features leading to synthesis difficulties were identified, and an eXtreme Gradient Boosting model was established to integrate these features. The predictive model achieved high-quality performance with an AUC of 0.895 in cross-validation and an AUC of 0.885 on an independent test set. Based on these results, the synthesis difficulty index (S-index) was proposed as a means of scoring and interpreting synthesis difficulties of chromosomes from prokaryotes to eukaryotes. The findings of this study emphasize the significant variability in synthesis difficulties between chromosomes and demonstrate the potential of the proposed model to predict and mitigate these difficulties through the optimization of the synthesis process and genome rewriting.

Cation valence dependence of hydrogen bond and stacking potentials in DNA mesoscopic models

Monovalent and divalent cations play a crucial role in living cells and for molecular techniques such as PCR. Here we evaluate DNA melting temperatures in magnesium (Mg²⁺) and magnesium‑potassium (Mg²⁺+ K⁺) buffers with a mesoscopic model that allows us to estimate hydrogen bonds and stacking interaction potentials. The Mg²⁺ and Mg²⁺+ K⁺ results are compared to previous calculations for sodium ions (Na⁺), in terms of equivalent sodium concentration and ionic strength. Morse potentials, related to hydrogen bonding, were found to be essentially constant and unaffected by cation conditions. However, for stacking interactions we find a clear dependence with ionic strength and cation valence. The highest ionic strength variations, for both hydrogen bonds and stacking interactions, was found at the sequence terminals. This suggests that end-to-end interactions in DNA will be strongly dependent on cation valence and ionic strength.

The 2Ih and OXOG Proximity Consequences on Charge Transfer through ds-DNA: Theoretical Studies of Clustered DNA Damage

Genetic information is continuously exposed to harmful factors, both intra- and extracellular. Their activity can lead to the formation of different types of DNA damage. Clustered lesions (CDL) are problematic for DNA repair systems. In this study, the short ds-oligos with a CDL containing (R) or (S) 2Ih and OXOG in their structure were chosen as the most frequent in vitro lesions. In the condensed phase, the spatial structure was optimized at the M062x/D95**:M026x/sto-3G level of theory, while the electronic properties were optimized at the M062x/6-31++G** level. The influence of equilibrated and non-equilibrated solvent-solute interactions was then discussed. It was found that the presence of (R)2Ih in the ds-oligo structure causes a greater increase in structure sensitivity towards charge adoption than (S)2Ih, while OXOG shows high stability. Moreover, the analysis of charge and spin distribution reveals the different effects of 2Ih diastereomers. Additionally, the adiabatic ionization potential was found as follows for (R)-2Ih and (S)-2Ih in eV: 7.02 and 6.94. This was in good agreement with the AIP of the investigated ds-oligos. It was found that the presence of (R)-2Ih has a negative influence on excess electron migration through ds-DNA. Finally, according to the Marcus theory, the charge transfer constant was calculated. The results presented in the article show that both diastereomers of 5-carboxamido-5-formamido-2-iminohydantoin should play a significant role in the CDL recognition process via electron transfer. Moreover, it should be pointed out that even though the cellular level of (R and S)-2Ih has been obscured, their mutagenic potential should be at the same level as other similar guanine lesions found in different cancer cells.

Thermodynamic determination of RNA duplex stability in magnesium solutions

The prediction of RNA secondary structure and thermodynamics from sequence relies on free energy minimization and nearest neighbor parameters. Currently, algorithms used to make these predictions are based on parameters from optical melting studies performed in 1 M NaCl. However, many physiological and biochemical buffers containing RNA include much lower concentrations of monovalent cations and the presence of divalent cations. In order to improve these algorithms, thermodynamic data was previously collected for RNA duplexes in solutions containing 71, 121, 221, and 621 mM Na+. From this data, correction factors for free energy (ΔG°37) and melting temperature (Tm) were derived. Despite these newly derived correction factors for sodium, the stabilizing effects of magnesium have been ignored. Here, the same RNA duplexes were melted in solutions containing 0.5, 1.5, 3.0, and 10.0 mM Mg2+ in the absence of monovalent cations. Correction factors for Tm and ΔG°37 were derived to scale the current parameters to a range of magnesium concentrations. The Tm correction factor predicts the melting temperature within 1.2°C, and the ΔG°37 correction factor predicts the free energy within 0.30 kcalmol. These newly derived magnesium correction factors can be incorporated into algorithms that predict RNA secondary structure and stability from sequence.

Machine learning in the estimation of CRISPR-Cas9 cleavage sites for plant system

CRISPR-Cas9 system is one of the recent most used genome editing techniques. Despite having a high capacity to alter the precise target genes and genomic regions that the planned guide RNA (or sgRNA) complements, the off-target effect still exists. But there are already machine learning algorithms for people, animals, and a few plant species. In this paper, an effort has been made to create models based on three machine learning-based techniques [namely, artificial neural networks (ANN), support vector machines (SVM), and random forests (RF)] for the prediction of the CRISPR-Cas9 cleavage sites that will be cleaved by a particular sgRNA. The plant dataset was the sole source of inspiration for all of these machine learning-based algorithms. 70% of the on-target and off-target dataset of various plant species that was gathered was used to train the models. The remaining 30% of the data set was used to evaluate the model's performance using a variety of evaluation metrics, including specificity, sensitivity, accuracy, precision, F1 score, F2 score, and AUC. Based on the aforementioned machine learning techniques, eleven models in all were developed. Comparative analysis of these produced models suggests that the model based on the random forest technique performs better. The accuracy of the Random Forest model is 96.27%, while the AUC value was found to be 99.21%. The SVM-Linear, SVM-Polynomial, SVM-Gaussian, and SVM-Sigmoid models were trained, making a total of six ANN-based models (ANN1-Logistic, ANN1-Tanh, ANN1-ReLU, ANN2-Logistic, ANN2-Tanh, and ANN-ReLU) and Support Vector Machine models (SVM-Linear, SVM-Polynomial, SVM-Gaussian However, the overall performance of Random Forest is better among all other ML techniques. ANN1-ReLU and SVM-Linear model performance were shown to be better among Artificial Neural Network and Support Vector Machine-based models, respectively.

Thermodynamic Characterization of Nucleic Acid Nanoparticles Hybridization by UV Melting

The advances in nucleic acid nanotechnology have given rise to various elegantly designed structural complexes fabricated from DNA, RNA, chemically modified RNA strands, and their mixtures. The structural properties of NA nanoparticles (NANP) generally dictate and significantly impact biological function; and thus, it is critical to extract information regarding relative stabilities of the different structural forms. The adequate stability assessment requires knowledge of thermodynamic parameters that can be empirically derived using conventional UV-melting technique. The focus of this chapter is to describe methodology to evaluate thermodynamic data of NANPs complexation based on DNA 12 base-pair (bp) duplex formation as an example.

Structure- and Content-Dependent Efficiency of Cas9-Assisted DNA Cleavage in Genome-Editing Systems

Genome-editing systems, being some of the key tools of molecular biologists, represent a reasonable hope for progress in the field of personalized medicine. A major problem with such systems is their nonideal accuracy and insufficient selectivity. The selectivity of CRISPR-Cas9 systems can be improved in several ways. One efficient way is the proper selection of the consensus sequence of the DNA to be cleaved. In the present work, we attempted to evaluate the effect of formed non-Watson-Crick pairs in a DNA duplex on the efficiency of DNA cleavage in terms of the influence of the structure of the formed partially complementary pairs. We also studied the effect of the location of such pairs in DNA relative to the PAM (protospacer-adjacent motif) on the cleavage efficiency. We believe that the stabilization of the Cas9-sgRNA complex with a DNA substrate containing noncomplementary pairs is due to loop reorganization in the RuvC domain of the enzyme. In addition, PAM-proximal mismatches in the DNA substrate lower enzyme efficiency because the "seed" region is involved in binding and cleavage, whereas PAM-distal mismatches have no significant impact on target DNA cleavage. Our data suggest that in the case of short duplexes with mismatches, the stages of recognition and binding of dsDNA substrates by the enzyme determine the reaction rate and time rather than the thermodynamic parameters affected by the "unwinding" of DNA. The results will provide a theoretical basis for predicting the efficiency and accuracy of CRISPR-Cas9 systems at cleaving target DNA.

An Explanation of Exceptions from Chargaff's Second Parity Rule/Strand Symmetry of DNA Molecules

In this article, we show that mono/oligonucleotide quadruplets, as basic structures of DNA, along with our classification of trinucleotides, disclose an organization of genomes based on purine-pyrimidine symmetry. Moreover, the structure and stability of DNA are influenced by the Watson-Crick pairing and the natural law of DNA creation and conservation, according to which the same mono- or oligonucleotide insertion must be inserted simultaneously into both strands of DNA. Taken together, they lead to quadruplets with central mirror symmetry and bidirectional DNA strand orientation and are incorporated into Chargaff's second parity rule (CSPR). Performing our quadruplet frequency analysis of all human chromosomes and of Neuroblastoma BreakPoint Family (NBPF) genes, which code Olduvai protein domains in the human genome, we show that the coding part of DNA violates CSPR. This may shed new light and give rise to a novel hypothesis on DNA creation and its evolution. In this framework, the logarithmic relationship between oligonucleotide order and minimal DNA sequence length, to establish the validity of CSPR, automatically follows from the quadruplet structure of the genomic sequence. The problem of the violation of CSPR in rare symbionts is discussed.

Forces Driving a Magic Bullet to Its Target: Revisiting the Role of Thermodynamics in Drug Design, Development, and Optimization

Drug discovery strategies have advanced significantly towards prioritizing target selectivity to achieve the longstanding goal of identifying "magic bullets" amongst thousands of chemical molecules screened for therapeutic efficacy. A myriad of emerging and existing health threats, including the SARS-CoV-2 pandemic, alarming increase in bacterial resistance, and potentially fatal chronic ailments, such as cancer, cardiovascular disease, and neurodegeneration, have incentivized the discovery of novel therapeutics in treatment regimens. The design, development, and optimization of lead compounds represent an arduous and time-consuming process that necessitates the assessment of specific criteria and metrics derived via multidisciplinary approaches incorporating functional, structural, and energetic properties. The present review focuses on specific methodologies and technologies aimed at advancing drug development with particular emphasis on the role of thermodynamics in elucidating the underlying forces governing ligand-target interaction selectivity and specificity. In the pursuit of novel therapeutics, isothermal titration calorimetry (ITC) has been utilized extensively over the past two decades to bolster drug discovery efforts, yielding information-rich thermodynamic binding signatures. A wealth of studies recognizes the need for mining thermodynamic databases to critically examine and evaluate prospective drug candidates on the basis of available metrics. The ultimate power and utility of thermodynamics within drug discovery strategies reside in the characterization and comparison of intrinsic binding signatures that facilitate the elucidation of structural-energetic correlations which assist in lead compound identification and optimization to improve overall therapeutic efficacy.

Photophysical Properties and DNA Binding of Two Intercalating Osmium Polypyridyl Complexes Showing Light-Switch Effects

The synthesis and photophysical characterization of two osmium(II) polypyridyl complexes, [Os(TAP)₂dppz]²⁺ (1) and [Os(TAP)₂dppp2]²⁺ (2) containing dppz (dipyrido[3,2-a:2′,3′-c]phenazine) and dppp2 (pyrido[2′,3′:5,6]pyrazino[2,3-f][1,10]phenanthroline) intercalating ligands and TAP (1,4,5,8-tetraazaphenanthrene) ancillary ligands, are reported. The complexes exhibit complex electrochemistry with five distinct reductive redox couples, the first of which is assigned to a TAP-based process. The complexes emit in the near-IR (1 at 761 nm and 2 at 740 nm) with lifetimes of >35 ns with a low quantum yield of luminescence in aqueous solution (∼0.25%). The Δ and Λ enantiomers of 1 and 2 are found to bind to natural DNA and with AT and GC oligodeoxynucleotides with high affinities. In the presence of natural DNA, the visible absorption spectra are found to display significant hypochromic shifts, which is strongly evident for the ligand-centered π–π* dppp2 transition at 355 nm, which undergoes 46% hypochromism. The emission of both complexes increases upon DNA binding, which is observed to be sensitive to the Δ or Λ enantiomer and the DNA composition. A striking result is the sensitivity of Λ-2 to the presence of AT DNA, where a 6-fold enhancement of luminescence is observed and reflects the nature of the binding for the enantiomer and the protection from solution. Thermal denaturation studies show that both complexes are found to stabilize natural DNA. Finally, cellular studies show that the complexes are internalized by cultured mammalian cells and localize in the nucleus.

Osmium(II) polypyridyl complexes comprising extended dipyrido[3,2-a:2′,3′-c]phenazine (1) and pyrido[2′,3′:5,6]pyrazino[2,3-f][1,10]phenanthroline (2) intercalating ligands are shown to be effective DNA binders accompanied by enhanced near-IR emission. The emission response to B-DNA is found to be sensitive to the enantiomer and the composition of DNA, with greater emission observed for AT-rich sequences. Thermal denaturation studies show that both complexes stabilize natural DNA. Cellular studies show that the complexes are internalized by cultured mammalian cells and localize in the nucleus.

The stability and number of nucleating interactions determine DNA hybridization rates in the absence of secondary structure

The kinetics of DNA hybridization are fundamental to biological processes and DNA-based technologies. However, the precise physical mechanisms that determine why different DNA sequences hybridize at different rates are not well understood. Secondary structure is one predictable factor that influences hybridization rates but is not sufficient on its own to fully explain the observed sequence-dependent variance. In this context, we measured hybridization rates of 43 different DNA sequences that are not predicted to form secondary structure and present a parsimonious physically justified model to quantify our observations. Accounting only for the combinatorics of complementary nucleating interactions and their sequence-dependent stability, the model achieves good correlation with experiment with only two free parameters. Our results indicate that greater repetition of Watson-Crick pairs increases the number of initial states able to proceed to full hybridization, with the stability of those pairings dictating the likelihood of such progression, thus providing new insight into the physical factors underpinning DNA hybridization rates.

Nucleic Acid Thermodynamics Derived from Mechanical Unzipping Experiments

Force-spectroscopy techniques have led to significant progress in studying the physicochemical properties of biomolecules that are not accessible in bulk assays. The application of piconewton forces with laser optical tweezers to single nucleic acids has permitted the characterization of molecular thermodynamics and kinetics with unprecedented accuracy. Some examples are the hybridization reaction between complementary strands in DNA and the folding of secondary, tertiary, and other heterogeneous structures, such as intermediate and misfolded states in RNA. Here we review the results obtained in our lab on deriving the nearest-neighbor free energy parameters in DNA and RNA duplexes from mechanical unzipping experiments. Remarkable nonequilibrium effects are also observed, such as the large irreversibility of RNA unzipping and the formation of non-specific secondary structures in single-stranded DNA. These features originate from forming stem-loop structures along the single strands of the nucleic acid. The recently introduced barrier energy landscape model quantifies kinetic trapping effects due to stem-loops being applicable to both RNA and DNA. The barrier energy landscape model contains the essential features to explain the many behaviors observed in heterogeneous nucleic-acid folding.

Codon Usage Provides Insights into the Adaptive Evolution of Mycoviruses in Their Associated Fungi Host

Codon usage bias (CUB) could reflect co-evolutionary changes between viruses and hosts in contrast to plant and animal viruses, and the systematic analysis of codon usage among the mycoviruses that infect plant pathogenic fungi is limited. We performed an extensive analysis of codon usage patterns among 98 characterized RNA mycoviruses from eight phytopathogenic fungi. The GC and GC3s contents of mycoviruses have a wide variation from 29.35% to 64.62% and 24.32% to 97.13%, respectively. Mycoviral CUB is weak, and natural selection plays a major role in the formation of mycoviral codon usage pattern. In this study, we demonstrated that the codon usage of mycoviruses is similar to that of some host genes, especially those involved in RNA biosynthetic process and transcription, suggesting that CUB is a potential evolutionary mechanism that mycoviruses adapt to in their hosts.

Genetic dissection of the RNA polymerase II transcription cycle

How DNA sequence affects the dynamics and position of RNA Polymerase II (Pol II) during transcription remains poorly understood. Here, we used naturally occurring genetic variation in F1 hybrid mice to explore how DNA sequence differences affect the genome-wide distribution of Pol II. We measured the position and orientation of Pol II in eight organs collected from heterozygous F1 hybrid mice using ChRO-seq. Our data revealed a strong genetic basis for the precise coordinates of transcription initiation and promoter proximal pause, allowing us to redefine molecular models of core transcriptional processes. Our results implicate DNA sequence, including both known and novel DNA sequence motifs, as key determinants of the position of Pol II initiation and pause. We report evidence that initiation site selection follows a stochastic process similar to Brownian motion along the DNA template. We found widespread differences in the position of transcription termination, which impact the primary structure and stability of mature mRNA. Finally, we report evidence that allelic changes in transcription often affect mRNA and ncRNA expression across broad genomic domains. Collectively, we reveal how DNA sequences shape core transcriptional processes at single nucleotide resolution in mammals.

Development of Breeder-Friendly KASP Markers from Genome-Wide Association Studies Results

Array-based SNP markers are commonly used in genome-wide association studies (GWAS) to identify genomic regions involved in important agronomical traits. However, conversion of these SNP markers into breeder-friendly kompetitive allele-specific PCR (KASP) markers for use in marker-assisted selection is often challenging. In this chapter we describe general considerations and successfully applied protocols for the conversion of Illumina array SNP markers into locus-specific KASP markers with a special emphasis and examples on how to overcome difficulties in polyploid wheat.

A successful hybrid deep learning model aiming at promoter identification

BACKGROUND

The zone adjacent to a transcription start site (TSS), namely, the promoter, is primarily involved in the process of DNA transcription initiation and regulation. As a result, proper promoter identification is critical for further understanding the mechanism of the networks controlling genomic regulation. A number of methodologies for the identification of promoters have been proposed. Nonetheless, due to the great heterogeneity existing in promoters, the results of these procedures are still unsatisfactory. In order to establish additional discriminative characteristics and properly recognize promoters, we developed the hybrid model for promoter identification (HMPI), a hybrid deep learning model that can characterize both the native sequences of promoters and the morphological outline of promoters at the same time. We developed the HMPI to combine a method called the PSFN (promoter sequence features network), which characterizes native promoter sequences and deduces sequence features, with a technique referred to as the DSPN (deep structural profiles network), which is specially structured to model the promoters in terms of their structural profile and to deduce their structural attributes.

RESULTS

The HMPI was applied to human, plant and Escherichia coli K-12 strain datasets, and the findings showed that the HMPI was successful at extracting the features of the promoter while greatly enhancing the promoter identification performance. In addition, after the improvements of synthetic sampling, transfer learning and label smoothing regularization, the improved HMPI models achieved good results in identifying subtypes of promoters on prokaryotic promoter datasets.

CONCLUSIONS

The results showed that the HMPI was successful at extracting the features of promoters while greatly enhancing the performance of identifying promoters on both eukaryotic and prokaryotic datasets, and the improved HMPI models are good at identifying subtypes of promoters on prokaryotic promoter datasets. The HMPI is additionally adaptable to different biological functional sequences, allowing for the addition of new features or models.

Developing predictive hybridization models for phosphorothioate oligonucleotides using high-resolution melting

The ability to predict nucleic acid hybridization energies has been greatly enabling for many applications, but predictive models require painstaking experimentation, which may limit expansion to non-natural nucleic acid analogues and chemistries. We have assessed the utility of dye-based, high-resolution melting (HRM) as an alternative to UV-Vis determinations of hyperchromicity in order to more quickly acquire parameters for duplex stability prediction. The HRM-derived model for phosphodiester (PO) DNA can make comparable predictions to previously established models. Using HRM, it proved possible to develop predictive models for DNA duplexes containing phosphorothioate (PS) linkages, and we found that hybridization stability could be predicted as a function of sequence and backbone composition for a variety of duplexes, including PS:PS, PS:PO, and partially modified backbones. Individual phosphorothioate modifications destabilize helices by around 0.12 kcal/mol on average. Finally, we applied these models to the design of a catalytic hairpin assembly circuit, an enzyme-free amplification method used for nucleic acid-based molecular detection. Changes in PS circuit behavior were consistent with model predictions, further supporting the addition of HRM modeling and parameters for PS oligonucleotides to the rational design of nucleic acid hybridization.