Central dogma of molecular biology

Proteomics of the heart

Mass spectrometry-based proteomics is a sophisticated identification tool specializing in portraying protein dynamics at a molecular level. Proteomics provides biologists with a snapshot of context-dependent protein and proteoform expression, structural conformations, dynamic turnover, and protein-protein interactions. Cardiac proteomics can offer a broader and deeper understanding of the molecular mechanisms that underscore cardiovascular disease, and it is foundational to the development of future therapeutic interventions. This review encapsulates the evolution, current technologies, and future perspectives of proteomic-based mass spectrometry as it applies to the study of the heart. Key technological advancements have allowed researchers to study proteomes at a single-cell level and employ robot-assisted automation systems for enhanced sample preparation techniques, and the increase in fidelity of the mass spectrometers has allowed for the unambiguous identification of numerous dynamic posttranslational modifications. Animal models of cardiovascular disease, ranging from early animal experiments to current sophisticated models of heart failure with preserved ejection fraction, have provided the tools to study a challenging organ in the laboratory. Further technological development will pave the way for the implementation of proteomics even closer within the clinical setting, allowing not only scientists but also patients to benefit from an understanding of protein interplay as it relates to cardiac disease physiology.

Inteins: A Swiss army knife for synthetic biology

Inteins are proteins found in nature that execute protein splicing. Among them, split inteins stand out for their versatility and adaptability, presenting creative solutions for addressing intricate challenges in various biological applications. Their exquisite attributes, including compactness, reliability, orthogonality, low toxicity, and irreversibility, make them of interest to various fields including synthetic biology, biotechnology and biomedicine. In this review, we delve into the inherent challenges of using inteins, present approaches for overcoming these challenges, and detail their reliable use for specific cellular tasks. We will discuss the use of conditional inteins in areas like cancer therapy, drug screening, patterning, infection treatment, diagnostics and biocontainment. Additionally, we will underscore the potential of inteins in executing basic logical operations with practical implications. We conclude by showcasing their potential in crafting complex genetic circuits for performing computations and feedback control that achieves robust perfect adaptation.

Cooperative genes in smart systems: Toward an inclusive new synthesis in evolution

For more than half a century, biologist Julian Huxley's term, the "Modern Synthesis", has been used as a label for a model of biological evolution where genetic influences are viewed as a principal source of creativity and change. Over the years, as evidence has accumulated that there are many other, far more important factors at work in evolution, theoretical "compromises," such as the so-called "Extended Synthesis", have been proposed. This is no longer tenable. It is time to abandon the Modern Synthesis, and its doppelganger "The Selfish Gene". Here is the case for a new, multi-faceted, open-ended, "inclusive" evolutionary synthesis, where living systems themselves are recognized as purposeful (teleonomic) "agents" and cooperative effects (synergies) of various kinds are seen as all-important influences.

Insights into Error Control Mechanisms in Biological Processes: Copolymerization and Enzyme-Kinetics Revisited

The high fidelity observed in biological information processing ranging from replication to translation has stimulated significant research efforts to clarify the underlying microscopic picture. Theoretically, several approaches to analyze the error rates have been proposed. The copolymerization theory describes the addition and removal of monomers at the growing tip of a copolymer, leading to a closed set of nonlinear equations. On the other hand, enzyme-kinetics approaches formulate linear equations of biochemical networks, describing transitions between discrete chemical states. However, it is still unclear whether the error values computed by the two approaches agree. Moreover, there are conflicting interpretations on whether the error is under thermodynamic or kinetic discrimination control. In this work, we examine the error rate in persistent copying biochemical processes by specifically analyzing both theoretical approaches. The initial disagreement of the results between the two theories motivated us to rederive the formula for the error rate in the kinetic model. The error computed with the new method resulted in excellent agreement between both theoretical approaches and with Monte Carlo simulations. Furthermore, our theoretical analysis shows that the kinetic discrimination controls the error, even when the energy difference between adding the right and wrong products is very small. Our theoretical investigation gives important insights into the physical-chemical properties of complex biological processes by providing the quantitative framework to evaluate them.

Probing of nucleic acid compaction using low-frequency Raman spectroscopy

Compaction of nucleic acids, namely DNA and RNA, determines their functions and involvement in vital cell processes including transcription, replication, DNA repair and translation. However, experimental probing of the compaction of nucleic acids is not straightforward. In this study, we suggest an approach for this probing using low-frequency Raman spectroscopy. Specifically, we show theoretically, computationally and experimentally the quantifiable correlation between the low-frequency Raman intensity from nucleic acids, magnitude of thermal fluctuations of atomic positions, and the compaction state of biomolecules. Noteworthily, we highlight that the LF Raman intensity differs by an order of magnitude for different samples of DNA, and even for the same sample in the course of long-term storage. The feasibility of the approach is further shown by assessment of the DNA compaction in the nuclei of plant cells. We anticipate that the suggested approach will enlighten compaction of nucleic acids and their dynamics during the key processes of the cell life cycle and under various factors, facilitating advancement of molecular biology and medicine.

Protein translation rate determines neocortical neuron fate

The mammalian neocortex comprises an enormous diversity regarding cell types, morphology, and connectivity. In this work, we discover a post-transcriptional mechanism of gene expression regulation, protein translation, as a determinant of cortical neuron identity. We find specific upregulation of protein synthesis in the progenitors of later-born neurons and show that translation rates and concomitantly protein half-lives are inherent features of cortical neuron subtypes. In a small molecule screening, we identify Ire1α as a regulator of Satb2 expression and neuronal polarity. In the developing brain, Ire1α regulates global translation rates, coordinates ribosome traffic, and the expression of eIF4A1. Furthermore, we demonstrate that the Satb2 mRNA translation requires eIF4A1 helicase activity towards its 5'-untranslated region. Altogether, we show that cortical neuron diversity is generated by mechanisms operating beyond gene transcription, with Ire1α-safeguarded proteostasis serving as an essential regulator of brain development.

Futile cycles: Emerging utility from apparent futility

Futile cycles are biological phenomena where two opposing biochemical reactions run simultaneously, resulting in a net energy loss without appreciable productivity. Such a state was presumed to be a biological aberration and thus deemed an energy-wasting "futile" cycle. However, multiple pieces of evidence suggest that biological utilities emerge from futile cycles. A few established functions of futile cycles are to control metabolic sensitivity, modulate energy homeostasis, and drive adaptive thermogenesis. Yet, the physiological regulation, implication, and pathological relevance of most futile cycles remain poorly studied. In this review, we highlight the abundance and versatility of futile cycles and propose a classification scheme. We further discuss the energetic implications of various futile cycles and their impact on basal metabolic rate, their bona fide and tentative pathophysiological implications, and putative drug interactions.

Cell-type specific and differential expression of LINC-RSAS long noncoding RNA declines in the testes during ageing of the rat

Long noncoding RNAs (lncRNAs) have emerged as major regulators of gene expression, chromatin structure, epigenetic changes, post-transcriptional processing of RNAs, translation of mRNAs into proteins as well as contributing to the process of ageing. Ageing is a universal, slow, progressive change in almost all physiological processes of organisms after attaining reproductive maturity and often associated with age-related diseases. Mammalian testes contain various cell-types, vast reservoir of transcriptome complexity, produce haploid male gametes for reproduction and testosterone for development and maintenance of male sexual characters as well as contribute genetic variation to the species. We report age-related decline in expression and cellular localization of Long intergenic noncoding repeat-rich sense-antisense (LINC-RSAS) RNA in the testes and its major cell-types such as primary spermatocytes, Leydig cells and Sertoli cells during ageing of the rat. LINC-RSAS expression in testes increased from immature (4-weeks) to adult (16- and 44-weeks) and declined from adult (44-weeks) to nearly-old (70-weeks) rats. Genomic DNA methylation in the testes showed a similar pattern. Cell-type specific higher expression of LINC-RSAS was observed in primary spermatocytes (pachytene cells), Leydig cells and Sertoli cells of testes of adult rats. Over-expression of LINC-RSAS in cultured human cell lines revealed its possible role in cell-cycle control and apoptosis. We propose that LINC-RSAS expression is involved in molecular physiology of primary spermatocytes, Leydig cells and Sertoli cells of adult testes and its decline is associated with diminishing function of testes during ageing of the rat.

The mega-evolution of life with its three memory systems depends on sender-receiver communication and problem-solving. A narrative review

It should be the ultimate goal of any theory of evolution to delineate the contours of an integrative system to answer the question: How does life (in all its complexity) evolve (which can be called mega-evolution)? But how to plausibly define 'life'? My answer (1994-2023) is: 'life' sounds like a noun, but denotes an activity, and thus is a verb. Life (L) denotes nothing else than the total sum (∑) of all acts of communication (transfer of information) (C) executed by any type of senders-receivers at all their levels (up to at least 15) of compartmental organization: L = ∑C. The 'communicating compartment' is better suited to serve as the universal unit of structure, function and evolution than the cell, the smallest such unit. By paying as much importance to communication activity as to the Central Dogma of molecular biology, a wealth of new insights unfold. The major ones are as follows. (1) Living compartments have not only a genetic memory (DNA), but also a still enigmatic cognitive and an electrical memory system (and thus a triple memory system). (2) Complex compartments can have up to three types of progeny: genetic descendants/children, pupils/learners and electricians. (3) Of particular importance to adaptation, any act of communication is a problem-solving act because all messages need to be decoded. Hence through problem-solving that precedes selection, life itself is the driving force of its own evolution (a very clever but counterintuitive and unexpected logical deduction). Perhaps, this is the 'vital force' philosopher and Nobel laureate (in 1927) Henri Bergson searched for but did not find.

Noise robustness and metabolic load determine the principles of central dogma regulation

The processes of gene expression are inherently stochastic, even for essential genes required for growth. How does the cell maximize fitness in light of noise? To answer this question, we build a mathematical model to explore the trade-off between metabolic load and growth robustness. The model predicts novel principles of central dogma regulation: Optimal protein expression levels for many genes are in vast overabundance. Essential genes are transcribed above a lower limit of one message per cell cycle. Gene expression is achieved by load balancing between transcription and translation. We present evidence that each of these novel regulatory principles is observed. These results reveal that robustness and metabolic load determine the global regulatory principles that govern central dogma processes, and these principles have broad implications for cellular function.

Establishing a conceptual framework for holistic cell states and state transitions

Cell states were traditionally defined by how they looked, where they were located, and what functions they performed. In this post-genomic era, the field is largely focused on a molecular view of cell state. Moving forward, we anticipate that the observables used to define cell states will evolve again as single-cell imaging and analytics are advancing at a breakneck pace via the collection of large-scale, systematic cell image datasets and the application of quantitative image-based data science methods. This is, therefore, a key moment in the arc of cell biological research to develop approaches that integrate the spatiotemporal observables of the physical structure and organization of the cell with molecular observables toward the concept of a holistic cell state. In this perspective, we propose a conceptual framework for holistic cell states and state transitions that is data-driven, practical, and useful to enable integrative analyses and modeling across many data types.

Light Responsive DNA Nanomaterials and Their Biomedical Applications

DNA nanomaterials have been widely employed for various biomedical applications. With rapid development of chemical modification of nucleic acid, serials of stimuli-responsive elements are included in the multifunctional DNA nanomaterials. In this review, we summarize the recent advances in light responsive DNA nanomaterials based on photocleavage/photodecage, photoisomerization, and photocrosslinking for efficient bioimaging (including imaging of small molecule, microRNA, and protein) and drug delivery (including delivery of small molecule, nucleic acid, and gene editing system). We also discuss the remaining challenges and future perspectives of the light responsive DNA nanomaterials in biomedical applications.

Synthetic Peptides: Promising Modalities for the Targeting of Disease-Related Nucleic Acids

DNA and RNA play pivotal roles in life processes by storing and transferring genetic information, modulating gene expression, and contributing to essential cellular machinery such as ribosomes. Dysregulation and mutations in nucleic acid-related processes are implicated in numerous diseases. Despite the critical impact on health of nucleic acid mutations or dysregulation, therapeutic compounds addressing these biomolecules remain limited. Peptides have emerged as a promising class of molecules for biomedical research, offering potential solutions for challenging drug targets. This review focuses on the use of synthetic peptides to target disease-related nucleic acids. We discuss examples of peptides targeting double-stranded DNA, including the clinical candidate Omomyc, and compounds designed for regulatory G-quadruplexes. Further, we provide insights into both library-based screenings and the rational design of peptides to target regulatory human RNA scaffolds and viral RNAs, emphasizing the potential of peptides in addressing nucleic acid-related diseases.

Structure-based drug design of DNA minor groove binders and evaluation of their antibacterial and anticancer properties

Antimicrobial and chemotherapy resistance are escalating medical problem of paramount importance. Yet, research for novel antimicrobial and anticancer agents remains lagging behind. With their reported medical applications, DNA minor groove binders (MGBs) are worthy of exploration. In this study, the approach of structure-based drug design was implemented to generate 11 MGB compounds including a novel class of bioactive alkyne-linked MGBs. The NCI screening protocol was utilized to evaluate the antitumor activity of the target MGBs. Furthermore, a variety of bactericidal, cytopathogenicity, MIC90, and cytotoxicity assays were carried out using these MGBs against 6 medically relevant bacteria: Salmonella enterica, Escherichia coli, Serratia marcescens, Bacillus cereus, Streptococcus pneumoniae and Streptococcus pyogenes. Moreover, molecular docking, molecular dynamic simulations, DNA melting, and isothermal titration calorimetry (ITC) analyses were utilized to explore the binding mode and interactions between the most potent MGBs and the DNA duplex d(CGACTAGTCG)2. NCI results showed that alkyne-linked MGBs (26 & 28) displayed the most significant growth inhibition among the NCI-60 panel. In addition, compounds MGB3, MGB4, MGB28, and MGB32 showed significant bactericidal effects, inhibited B. cereus and S. enterica-mediated cytopathogenicity, and exhibited low cytotoxicity. MGB28 and MGB32 demonstrated significant inhibition of S. pyogenes, whereas MGB28 notably inhibited S. marcescens and all four minor groove binders significantly inhibited B. cereus. The ability of these compounds to bind with DNA and distort its groove dimensions provides the molecular basis for the allosteric perturbation of proteins-DNA interactions by MGBs. This study shed light on the mechanism of action of MGBs and revealed the important structural features for their antitumor and antibacterial activities, which are important to guide future development of MGB derivatives as novel antibacterial and anticancer agents.

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.

Responses to commentaries on "The gene: An appraisal"

The central conclusions of "The Gene: An Appraisal" are that genetic variance does not underpin biological evolution, and, therefore, that genes are not Mendel's units of inheritance. In this response, I will address the criticisms I have received via commentaries on that paper by defending the following statements: 1. Epistasis does not explain the power-law fitness profile of the Long-Term Evolution Experiment (LTEE). The data from the evolution of natural systems displays the power-law form ubiquitously. Epistasis plays no role in evolution. 2. The common characteristics of living things (natural systems) are described by the principle of least action in de Maupertuis's original form, which is synonymous with the 2nd law of thermodynamics and Newton's 2nd law of motion in its complete form, i.e., F = dp/dt. Organisms strive to achieve free energy balance with their environments. 3. Based on an appraisal of the scientific environment between 1880 and 1911, I conclude that Johannsen's genotype conception was perhaps, the only option available to him. 4. The power-law fitness profile of the LTEE falsifies Fisher's Genetical Theory of Natural Selection, Johannsen's genotype conception, and the idea that 'Darwinian evolution' is an exception to the generic thermodynamic process of evolution in natural systems. 5. The use of the technique of genome-wide association to identify the causes and the likelihoods of inherited common diseases and behavioural traits is a 'wild goose chase' because genes are not the units of inheritance.

Noncoding RNAs in skeletal development and disorders

Protein-encoding genes only constitute less than 2% of total human genomic sequences, and 98% of genetic information was previously referred to as "junk DNA". Meanwhile, non-coding RNAs (ncRNAs) consist of approximately 60% of the transcriptional output of human cells. Thousands of ncRNAs have been identified in recent decades, and their essential roles in the regulation of gene expression in diverse cellular pathways associated with fundamental cell processes, including proliferation, differentiation, apoptosis, and metabolism, have been extensively investigated. Furthermore, the gene regulation networks they form modulate gene expression in normal development and under pathological conditions. In this review, we integrate current information about the classification, biogenesis, and function of ncRNAs and how these ncRNAs support skeletal development through their regulation of critical genes and signaling pathways in vivo. We also summarize the updated knowledge of ncRNAs involved in common skeletal diseases and disorders, including but not limited to osteoporosis, osteoarthritis, rheumatoid arthritis, scoliosis, and intervertebral disc degeneration, by highlighting their roles established from in vivo, in vitro, and ex vivo studies.

Plasma metabolomic analysis reveals the metabolic characteristics and potential diagnostic biomarkers of spinal tuberculosis

Objectives

This study aimed to conduct a non-targeted metabolomic analysis of plasma from patients with spinal tuberculosis (STB) to systematically elucidate the metabolomic alterations associated with STB, and explore potential diagnostic biomarkers for STB.

Methods

From January 2020 to January 2022, 30 patients with spinal tuberculosis (STBs) clinically diagnosed at the General Hospital of Ningxia Medical University and 30 age- and sex-matched healthy controls (HCs) were selected for this study. Using ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) based metabolomics, we analyzed the metabolic profiles of 60 plasma samples. Statistical analyses, pathway enrichment, and receiver operating characteristic (ROC) analyses were performed to screen and evaluate potential diagnostic biomarkers.

Results

Metabolomic profiling revealed distinct alterations between the STBs and HCs cohorts. A total of 1635 differential metabolites were screened, functionally clustered, and annotated. The results showed that the differential metabolites were enriched in sphingolipid metabolism, tuberculosis, cutin, suberine and wax biosynthesis, beta-alanine metabolism, methane metabolism, and other pathways. Through the random forest algorithm, LysoPE (18:1(11Z)/0:0), 8-Demethyl-8-formylriboflavin 5'-phosphate, Glutaminyl-Gamma-glutamate, (2R)-O-Phospho-3-sulfolactate, and LysoPE (P-16:0/0:0) were determined to have high independent diagnostic value.

Conclusions

STBs exhibited significantly altered metabolite profiles compared with HCs. Here, we provide a global metabolomic profile and identify potential diagnostic biomarkers of STB. Five potential independent diagnostic biomarkers with high diagnostic value were screened. This study provides novel insights into the pathogenesis, diagnosis, and treatment strategies of STB.

Long non-coding RNAs and their role in muscle regeneration

In mammals, most of the genome is transcribed to generate a large and heterogeneous variety of non-protein coding RNAs, that are broadly grouped according to their size. Long noncoding RNAs include a very large and versatile group of molecules. Despite only a minority of them has been functionally characterized, there is emerging evidence indicating long noncoding RNAs as important regulators of expression at multiple levels. Several of them have been shown to be modulated during myogenic differentiation, playing important roles in the regulation of skeletal muscle development, differentiation and homeostasis, and contributing to neuromuscular diseases. In this chapter, we have summarized the current knowledge about long noncoding RNAs in skeletal muscle and discussed specific examples of long noncoding RNAs (lncRNAs and circRNAs) regulating muscle stem cell biology. We have also discussed selected long noncoding RNAs involved in the most common neuromuscular diseases.

An open source knowledge graph ecosystem for the life sciences

Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, and methods exist to construct them automatically. However, tackling complex biomedical integration problems requires flexibility in the way knowledge is modeled. Moreover, existing KG construction methods provide robust tooling at the cost of fixed or limited choices among knowledge representation models. PheKnowLator (Phenotype Knowledge Translator) is a semantic ecosystem for automating the FAIR (Findable, Accessible, Interoperable, and Reusable) construction of ontologically grounded KGs with fully customizable knowledge representation. The ecosystem includes KG construction resources (e.g., data preparation APIs), analysis tools (e.g., SPARQL endpoint resources and abstraction algorithms), and benchmarks (e.g., prebuilt KGs). We evaluated the ecosystem by systematically comparing it to existing open-source KG construction methods and by analyzing its computational performance when used to construct 12 different large-scale KGs. With flexible knowledge representation, PheKnowLator enables fully customizable KGs without compromising performance or usability.

Cut-insert-stitch editing reaction (CIStER) sequence for surgical chemical glycan editing

Post-synthetic surgical editing enables synthesizing diverse molecules from a common scaffold. Editing carbohydrates by inserting a foreign glycan is still a far-reaching goal for synthetic chemists. In this study, a one-pot-three-step chemical approach was employed to edit glycoconjugates. It is comprised of three steps: the first is a 'cut' step, cleaving one of the interglycosidic bonds and producing an intermediate that could be intercepted with 4-mercaptotoluene; second step activates the thiotolyl glycoside in the presence of an aglycon containing an orthogonally activatable ethynylcycloxyl carbonate moiety; and the third step involves 'stitching' by activating the carbonate donor. The cut-insert stitch-editing reaction (CIStER) is demonstrated by inserting branched and linear arabinans reminiscent of M. tuberculosis cell wall from the same designer trimannoside. Glycosylating an activated hydroxyacid (serinyl, steroidal, and lipid) after cutting the interglycosidic bond and stitching in the presence of base extendes the CIStER approach to the synthesis of glycohybrids.

The roles of non-coding RNAs in male reproductive development and abiotic stress responses during this unique process in flowering plants

Successful male reproductive development is the guarantee for sexual reproduction of flowering plants. Male reproductive development is a complicated and multi-stage process that integrates physiological processes and adaptation and tolerance to a myriad of environmental stresses. This well-coordinated process is governed by genetic and epigenetic machineries. Non-coding RNAs (ncRNAs) play pleiotropic roles in the plant growth and development. The identification, characterization and functional analysis of ncRNAs and their target genes have opened a new avenue for comprehensively revealing the regulatory network of male reproductive development and its response to environmental stresses in plants. This review briefly addresses the types, origin, biogenesis and mechanisms of ncRNAs in plants, highlights important updates on the roles of ncRNAs in regulating male reproductive development and emphasizes the contribution of ncRNAs, especially miRNAs and lncRNAs, in responses to abiotic stresses during this unique process in flowering plants.

Protein structure-function continuum model: Emerging nexuses between specificity, evolution, and structure

The rationale for replacing the old binary of structure-function with the trinity of structure, disorder, and function has gained considerable ground in recent years. A continuum model based on the expanded form of the existing paradigm can now subsume importance of both conformational flexibility and intrinsic disorder in protein function. The disorder is actually critical for understanding the protein-protein interactions in many regulatory processes, formation of membrane-less organelles, and our revised notions of specificity as amply illustrated by moonlighting proteins. While its importance in formation of amyloids and function of prions is often discussed, the roles of intrinsic disorder in infectious diseases and protein function under extreme conditions are also becoming clear. This review is an attempt to discuss how our current understanding of protein function, specificity, and evolution fit better with the continuum model. This integration of structure and disorder under a single model may bring greater clarity in our continuing quest for understanding proteins and molecular mechanisms of their functionality.

Etiopathogenesis of Psoriasis: Integration of Proposed Theories

Psoriasis is a chronic inflammatory disease characterized by squamous and erythematous plaques on the skin and the involvement of the immune system. Global prevalence for psoriasis has been reported around 1-3% with a higher incidence in adults and similar proportions between men and women. The risk factors associated with psoriasis are both extrinsic and intrinsic, out of which a polygenic predisposition is a highlight out of the latter. Psoriasis etiology is not yet fully described, but several hypothesis have been proposed: 1) the autoimmunity hypothesis is based on the over-expression of antimicrobial peptides such as LL-37, the proteins ADAMTSL5, K17, and hsp27, or lipids synthesized by the PLA2G4D enzyme, all of which may serve as autoantigens to promote the differentiation of autoreactive lymphocytes T and unleash a chronic inflammatory response; 2) dysbiosis of skin microbiota hypothesis in psoriasis has gained relevance due to the observations of a loss of diversity and the participation of pathogenic bacteria such as Streptococcus spp. or Staphylococcus spp. the fungi Malassezia spp. or Candida spp. and the virus HPV, HCV, or HIV in psoriatic plaques; 3) the oxidative stress hypothesis, the most recent one, describes that the cell injury and the release of proinflammatory mediators and antimicrobial peptides that leads to activate of the Th1/Th17 axis observed in psoriasis is caused by a higher release of reactive oxygen species and the imbalance between oxidant and antioxidant mechanisms. This review aims to describe the mechanisms involved in the three hypotheses on the etiopathogeneses of psoriasis.

Multimodal Analytical Tools to Enhance Mechanistic Understanding of Aortic Valve Calcification

This review focuses on technologies at the core of calcific aortic valve disease (CAVD) and drug target research advancement, including transcriptomics, proteomics, and molecular imaging. We examine how bulk RNA sequencing and single-cell RNA sequencing have engendered organismal genomes and transcriptomes, promoting the analysis of tissue gene expression profiles and cell subpopulations, respectively. We bring into focus how the field is also largely influenced by increasingly accessible proteome profiling techniques. In unison, global transcriptional and protein expression analyses allow for increased understanding of cellular behavior and pathogenic pathways under pathologic stimuli including stress, inflammation, low-density lipoprotein accumulation, increased calcium and phosphate levels, and vascular injury. We also look at how direct investigation of protein signatures paves the way for identification of targetable pathways for pharmacologic intervention. Here, we note that imaging techniques, once a clinical diagnostic tool for late-stage CAVD, have since been refined to address a clinical need to identify microcalcifications using positron emission tomography/computed tomography and even detect in vivo cellular events indicative of early stage CAVD and map the expression of identified proteins in animal models. Together, these techniques generate a holistic approach to CAVD investigation, with the potential to identify additional novel regulatory pathways.

Engineering transcriptional regulation for cell-based therapies

A major aim in the field of synthetic biology is developing tools capable of responding to user-defined inputs by activating therapeutically relevant cellular functions. Gene transcription and regulation in response to external stimuli are some of the most powerful and versatile of these cellular functions being explored. Motivated by the success of chimeric antigen receptor (CAR) T-cell therapies, transmembrane receptor-based platforms have been embraced for their ability to sense extracellular ligands and to subsequently activate intracellular signal transduction. The integration of transmembrane receptors with transcriptional activation platforms has not yet achieved its full potential. Transient expression of plasmid DNA is often used to explore gene regulation platforms in vitro. However, applications capable of targeting therapeutically relevant endogenous or stably integrated genes are more clinically relevant. Gene regulation may allow for engineered cells to traffic into tissues of interest and secrete functional proteins into the extracellular space or to differentiate into functional cells. Transmembrane receptors that regulate transcription have the potential to revolutionize cell therapies in a myriad of applications, including cancer treatment and regenerative medicine. In this review, we will examine current engineering approaches to control transcription in mammalian cells with an emphasis on systems that can be selectively activated in response to extracellular signals. We will also speculate on the potential therapeutic applications of these technologies and examine promising approaches to expand their capabilities and tighten the control of gene regulation in cellular therapies.

In Silico Study on a Binding Mechanism of ssDNA Aptamers Targeting Glycosidic Bond-Containing Small Molecules

Aptamer-based detection targeting glycoconjugates has attracted significant attention for its remarkable potential in identifying structural changes in saccharides in different stages of various diseases. However, the challenges in screening aptamers for small carbohydrates or glycoconjugates, which contain highly flexible and diverse glycosidic bonds, have hindered their application and commercialization. In this study, we investigated the binding conformations between three glycosidic bond-containing small molecules (GlySMs; glucose, N-acetylneuraminic acid, and neomycin) and their corresponding aptamers in silico, and analyzed factors contributing to their binding affinities. Based on the findings, a novel binding mechanism was proposed, highlighting the central role of the stem structure of the aptamer in binding and recognizing GlySMs and the auxiliary role of the mismatched bases in the adjacent loop. Guided by this binding mechanism, an aptamer with a higher 6'-sialyllactose binding affinity was designed, achieving a KD value of 4.54 ± 0.64 μM in vitro through a single shear and one mutation. The binding mechanism offers crucial guidance for designing high-affinity aptamers, enhancing the virtual screening efficiency for GlySMs. This streamlined workflow filters out ineffective binding sites, accelerating aptamer development and providing novel insights into glycan-nucleic acid interactions.

Comprehensive Comparison and Critical Assessment of RNA-Specific Force Fields

Molecular dynamics simulations play a pivotal role in elucidating the dynamic behaviors of RNA structures, offering a valuable complement to traditional methods such as nuclear magnetic resonance or X-ray. Despite this, the current precision of RNA force fields lags behind that of protein force fields. In this work, we systematically compared the performance of four RNA force fields (ff99bsc0χOL3, AMBERDES, ff99OL3_CMAP1, AMBERMaxEnt) across diverse RNA structures. Our findings highlight significant challenges in maintaining stability, particularly with regard to cross-strand and cross-loop hydrogen bonds. Furthermore, we observed the limitations in accurately describing the conformations of nonhelical structural motif, terminal nucleotides, and also base pairing and base stacking interactions by the tested RNA force fields. The identified deficiencies in existing RNA force fields provide valuable insights for subsequent force field development. Concurrently, these findings offer recommendations for selecting appropriate force fields in RNA simulations.

RNA-Small-Molecule Interaction: Challenging the "Undruggable" Tag

RNA targeting, specifically with small molecules, is a relatively new and rapidly emerging avenue with the promise to expand the target space in the drug discovery field. From being "disregarded" as an "undruggable" messenger molecule to FDA approval of an RNA-targeting small-molecule drug Risdiplam, a radical change in perspective toward RNA has been observed in the past decade. RNAs serve important regulatory functions beyond canonical protein synthesis, and their dysregulation has been reported in many diseases. A deeper understanding of RNA biology reveals that RNA molecules can adopt a variety of structures, carrying defined binding pockets that can accommodate small-molecule drugs. Due to its functional diversity and structural complexity, RNA can be perceived as a prospective target for therapeutic intervention. This perspective highlights the proof of concept of RNA-small-molecule interactions, exemplified by targeting of various transcripts with functional modulators. The advent of RNA-oriented knowledge would help expedite drug discovery.

Stereoselective Amine Synthesis Mediated by a Zirconocene Hydride to Accelerate a Drug Discovery Program

Chiral amine synthesis remains a significant challenge in accelerating the design cycle of drug discovery programs. A zirconium hydride, due to its high oxophilicity and lower reactivity, gave highly chemo- and stereoselective reductions of sulfinyl ketimines. The development of this zirconocene-mediated reduction helped to accelerate our drug discovery efforts and is applicable to several motifs commonly used in medicinal chemistry. Computational investigation supported a cyclic half-chair transition state to rationalize the high selectivity in benzyl systems.

Recent advances in the investigation of fusion RNAs and their role in molecular pathology of cancer

Gene fusions have had a significant role in the development of various types of cancer, oftentimes involved in oncogenic activities through dysregulation of gene expression or signalling pathways. Some cancer-associated chromosomal translocations can undergo backsplicing, resulting in fusion-circular RNAs, a more stable isoform immune to RNase degradation. This stability makes fusion circular RNAs a promising diagnostic biomarker for cancer. While the detection of linear fusion RNAs and their function in certain cancers have been described in literature, fusion circular RNAs lag behind due to their low abundance in cancer cells. This review highlights current literature on the role of linear and circular fusion transcripts in cancer, tools currently available for detecting of these chimeric RNAs and their function and how they play a role in tumorigenesis.

Uncovering the mechanism of mitochondrial translation initiation in plants

Mitochondrial translation differs significantly from that conducted in bacteria and plastids. Recent research conducted by Tran and colleagues has unveiled the plant-specific mechanisms of mitochondrial translation initiation. The authors identified two Arabidopsis thaliana (arabidopsis) mTRAN proteins that may bind to the 5' untranslated region (UTR) of mitochondrial mRNAs by recognising newly discovered A/U-rich motifs.

Performance analysis of data resampling on class imbalance and classification techniques on multi-omics data for cancer classification

Cancer, in any of its forms, remains a significant public health concern worldwide. Advances in early detection and treatment could lead to a decline in the overall death rate from cancer in recent decades. Therefore, tumor prediction and classification play an important role in fighting cancer. This study built computational models for a joint analysis of RNA seq, copy number variation (CNV), and DNA methylation to classify normal and tumor samples across liver cancer, breast cancer, and colon adenocarcinoma from The Cancer Genome Atlas (TCGA) dataset. Total of 18 machine learning methods were evaluated based on the AUC, precision, recall, and F-measure. Besides, five techniques were compared to ameliorate problems of class imbalance in the cancer datasets. Synthetic Minority Oversampling Technique (SMOTE) demonstrated the best performance. The results indicate that the model applying Stochastic Gradient Descent (SGD) for learning binary class SVM with hinge loss has the highest classification results on liver cancer and breast cancer datasets, with accuracy over 99% and AUC greater than or equal to 0.999. For colon adenocarcinoma dataset, both SGD and Sequential Minimal Optimization (SMO) that implements John Platt's sequential minimal optimization algorithm for training a support vector machine shows an outstanding classification performance with accuracy of 100%, AUC, precision, recall, and F-measure all at 1.000.

Viroids, Satellite RNAs and Prions: Folding of Nucleic Acids and Misfolding of Proteins

Theodor ("Ted") Otto Diener (* 28 February 1921 in Zürich, Switzerland; † 28 March 2023 in Beltsville, MD, USA) pioneered research on viroids while working at the Plant Virology Laboratory, Agricultural Research Service, USDA, in Beltsville. He coined the name viroid and defined viroids' important features like the infectivity of naked single-stranded RNA without protein-coding capacity. During scientific meetings in the 1970s and 1980s, viroids were often discussed at conferences together with other "subviral pathogens". This term includes what are now called satellite RNAs and prions. Satellite RNAs depend on a helper virus and have linear or, in the case of virusoids, circular RNA genomes. Prions, proteinaceous infectious particles, are the agents of scrapie, kuru and some other diseases. Many satellite RNAs, like viroids, are non-coding and exert their function by thermodynamically or kinetically controlled folding, while prions are solely host-encoded proteins that cause disease by misfolding, aggregation and transmission of their conformations into infectious prion isoforms. In this memorial, we will recall the work of Ted Diener on subviral pathogens.

Nudt21-mediated alternative polyadenylation of MZT1 3'UTR contributes to pancreatic cancer progression

Alternative polyadenylation (APA) is an important post-transcriptional regulatory mechanism and is involved in many diseases, but its function and mechanism in regulating pancreatic cancer (PC) pathogenesis remain unclear. In this study, we found that the 3' UTR shortening of MZT1 was the most prominent APA event in PC liver metastases. The short-3'UTR isoform exerted a stronger effect in promoting cell proliferation and migration both in vitro and in vivo. NUDT21, a core cleavage factor involved in APA, promoted the usage of proximal polyadenylation sites (PASs) on MZT1 mRNA by binding to the UGUA element located upstream of the proximal PAS. High percentage of distal polyA site usage index of MZT1 was significantly associated with a better prognosis. These findings demonstrate a crucial mechanism that NUDT21-mediated APA of MZT1 could promote the progression of PC. Our findings provided a better understanding of the connection between PC progression and APA machinery.

Late-Stage Functionalization of Living Organisms: Rethinking Selectivity in Biology

With unlimited selectivity, full post-translational chemical control of biology would circumvent the dogma of genetic control. The resulting direct manipulation of organisms would enable atomic-level precision in "editing" of function. We argue that a key aspect that is still missing in our ability to do this (at least with a high degree of control) is the selectivity of a given chemical reaction in a living organism. In this Review, we systematize existing illustrative examples of chemical selectivity, as well as identify needed chemical selectivities set in a hierarchy of anatomical complexity: organismo- (selectivity for a given organism over another), tissuo- (selectivity for a given tissue type in a living organism), cellulo- (selectivity for a given cell type in an organism or tissue), and organelloselectivity (selectivity for a given organelle or discrete body within a cell). Finally, we analyze more traditional concepts such as regio-, chemo-, and stereoselective reactions where additionally appropriate. This survey of late-stage biomolecule methods emphasizes, where possible, functional consequences (i.e., biological function). In this way, we explore a concept of late-stage functionalization of living organisms (where "late" is taken to mean at a given state of an organism in time) in which programmed and selective chemical reactions take place in life. By building on precisely analyzed notions (e.g., mechanism and selectivity) we believe that the logic of chemical methodology might ultimately be applied to increasingly complex molecular constructs in biology. This could allow principles developed at the simple, small-molecule level to progress hierarchically even to manipulation of physiology.

Differentiable partition function calculation for RNA

Ribonucleic acid (RNA) is an essential molecule in a wide range of biological functions. In 1990, McCaskill introduced a dynamic programming algorithm for computing the partition function of an RNA sequence. McCaskill's algorithm is widely used today for understanding the thermodynamic properties of RNA. In this work, we introduce a generalization of McCaskill's algorithm that is well-defined over continuous inputs. Crucially, this enables us to implement an end-to-end differentiable partition function calculation. The derivative can be computed with respect to the input, or to any other fixed values, such as the parameters of the energy model. This builds a bridge between RNA thermodynamics and the tools of differentiable programming including deep learning as it enables the partition function to be incorporated directly into any end-to-end differentiable pipeline. To demonstrate the effectiveness of our new approach, we tackle the inverse folding problem directly using gradient optimization. We find that using the gradient to optimize the sequence directly is sufficient to arrive at sequences with a high probability of folding into the desired structure. This indicates that the gradients we compute are meaningful.

The mRNA-LNP vaccines - the good, the bad and the ugly?

The mRNA-LNP vaccine has received much attention during the COVID-19 pandemic since it served as the basis of the most widely used SARS-CoV-2 vaccines in Western countries. Based on early clinical trial data, these vaccines were deemed safe and effective for all demographics. However, the latest data raise serious concerns about the safety and effectiveness of these vaccines. Here, we review some of the safety and efficacy concerns identified to date. We also discuss the potential mechanism of observed adverse events related to the use of these vaccines and whether they can be mitigated by alterations of this vaccine mechanism approach.

Significant Prognostic Factor at Age Cut-off of 73 Years for Advanced Ovarian Serous Cystadenocarcinoma Patients: Insights from Real-World Study

Objective

The objective of this research was to determine the age cut-off for worse prognosis and investigate age-related differentially expressed genes (DEGs) in patients with advanced ovarian serous cystadenocarcinoma (AOSC).

Methods

In this research, we included a cohort of 20,846 patients diagnosed with AOSC, along with RNA-seq data from 374 patients in publicly available databases. Then we used the X-tile software to determine the age cut-off and stratified the patients into young and old groups. We utilized propensity score matching (PSM) to balance baseline between the young and old groups. Furthermore, we conducted an enrichment analysis of DEGs between the two age groups using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and gene ontology (GO) to identify dysregulated pathways. To evaluate the potential prognostic value of the DEGs, we performed survival analysis, such as Kaplan-Meier analysis and Log rank test.

Results

We stratified the patients into young group (n=16,336) and old group (n=4510) based on the cut-off age of 73 years by X-tile software. Age over 73 years was identified as an independent risk factor for overall survival (OS) and cancer-specific survival (CSS). Next, we identified 436 DEGs and found that the neurotrophin signaling pathway and translation factor activity were associated with prognosis outcomes. Among the top 10 hub genes (RELA, NFKBIA, TRAF6, IRAK2, TAB3, AKT1, TBP, EIF2S2, MAPK10, and SUPT3H), RELA, TAB3, AKT1, TBP, and SUPT3H were found to be significantly associated with poor prognosis in old patients with AOSC.

Conclusion

Our study determined 73 years as the cutoff value for age in patients with AOSC. RELA, TAB3, AKT1, TBP, and SUPT3H were identified as age-related DEGs that could contribute to the poor prognosis of older patients with AOSC.

Ketocarotenoid production in tomato triggers metabolic reprogramming and cellular adaptation: The quest for homeostasis

Plants are sessile and therefore have developed an extraordinary capacity to adapt to external signals. Here, the focus is on the plasticity of the plant cell to respond to new intracellular cues. Ketocarotenoids are high-value natural red pigments with potent antioxidant activity. In the present study, system-level analyses have revealed that the heterologous biosynthesis of ketocarotenoids in tomato initiated a series of cellular and metabolic mechanisms to cope with the formation of metabolites that are non-endogenous to the plant. The broad multilevel changes were linked to, among others, (i) the remodelling of the plastidial membrane, where the synthesis and storage of ketocarotenoids occurs; (ii) the recruiting of core metabolic pathways for the generation of metabolite precursors and energy; and (iii) redox control. The involvement of the metabolites as regulators of cellular processes shown here reinforces their pivotal role suggested in the remodelled 'central dogma' concept. Furthermore, the role of metabolic reprogramming to ensure cellular homeostasis is proposed.

Whole Blood Transcriptome Analysis in Patients with Trigeminal Neuralgia: a Prospective Clinical Study

Trigeminal neuralgia (TN) brings a huge burden to patients, without long-term effective treatment. This study aimed to explore the differentially expressed genes (DEGs) and related enrichment pathways in patients with TN. This was a study of transcriptome sequencing and bioinformatics analysis of human samples. Whole blood samples were collected from the TN patients and pain-free controls. RNA was extracted to conduct the RNA-sequencing and the subsequent bioinformatics analysis. DEGs between the two groups were derived. Kyoto encyclopedia of genes and genomes (KEGG) and Gene ontology (GO) was used to find the enrichment pathways of DEGs. Protein protein interaction (PPI) network was used to depict the interaction between DEGs and find the most important gene, hub gene. Compared with the control group, there were 117 up-regulated DEGs and 103 down-regulated DEGs in the whole blood of patients in the TN group. Pathway enrichment analysis showed that DEGs were mainly enriched in the neuroimmune and metabolic pathways. The PPI network demonstrated that colony stimulating factor 2 (CSF2) was the most important hub gene in the whole blood of TN patients. This study shows the expression of the transcriptome in the whole blood samples of TN patients. The neuroimmune responses and key hub gene CSF2 in the whole blood cells play a vital role in the occurrence of TN. Our research provides a theoretical basis for the diagnosis and treatments of TN. This study was registered at clinicaltrials.gov in June 2021 (No. NCT04923399).

An emerging paradigm in epigenetic marking: coordination of transcription and replication

DNA replication and RNA transcription both utilize DNA as a template and therefore need to coordinate their activities. The predominant theory in the field is that in order for the replication fork to proceed, transcription machinery has to be evicted from DNA until replication is complete. If that does not occur, these machineries collide, and these collisions elicit various repair mechanisms which require displacement of one of the enzymes, often RNA polymerase, in order for replication to proceed. This model is also at the heart of the epigenetic bookmarking theory, which implies that displacement of RNA polymerase during replication requires gradual re-building of chromatin structure, which guides recruitment of transcriptional proteins and resumption of transcription. We discuss these theories but also bring to light newer data that suggest that these two processes may not be as detrimental to one another as previously thought. This includes findings suggesting that these processes can occur without fork collapse and that RNA polymerase may only be transiently displaced during DNA replication. We discuss potential mechanisms by which RNA polymerase may be retained at the replication fork and quickly rebind to DNA post-replication. These discoveries are important, not only as new evidence as to how these two processes are able to occur harmoniously but also because they have implications on how transcriptional programs are maintained through DNA replication. To this end, we also discuss the coordination of replication and transcription in light of revising the current epigenetic bookmarking theory of how the active gene status can be transmitted through S phase.

Advances in brain epitranscriptomics research and translational opportunities

Various chemical modifications of all RNA transcripts, or epitranscriptomics, have emerged as crucial regulators of RNA metabolism, attracting significant interest from both basic and clinical researchers due to their diverse functions in biological processes and immense clinical potential as highlighted by the recent profound success of RNA modifications in improving COVID-19 mRNA vaccines. Rapid accumulation of evidence underscores the critical involvement of various RNA modifications in governing normal neural development and brain functions as well as pathogenesis of brain disorders. Here we provide an overview of RNA modifications and recent advancements in epitranscriptomic studies utilizing animal models to elucidate important roles of RNA modifications in regulating mammalian neurogenesis, gliogenesis, synaptic formation, and brain function. Moreover, we emphasize the pivotal involvement of RNA modifications and their regulators in the pathogenesis of various human brain disorders, encompassing neurodevelopmental disorders, brain tumors, psychiatric and neurodegenerative disorders. Furthermore, we discuss potential translational opportunities afforded by RNA modifications in combatting brain disorders, including their use as biomarkers, in the development of drugs or gene therapies targeting epitranscriptomic pathways, and in applications for mRNA-based vaccines and therapies. We also address current limitations and challenges hindering the widespread clinical application of epitranscriptomic research, along with the improvements necessary for future progress.

Identification of the consistently differential expressed hub mRNAs and proteins in lung adenocarcinoma and construction of the prognostic signature: a multidimensional analysis

BACKGROUND

This study aimed to elucidate the consistency of differentially expressed hub mRNAs and proteins in lung adenocarcinoma (LUAD) across populations and to construct a comprehensive LUAD prognostic signature.

METHODS

The transcriptomic and proteomics data from different populations were standardized and analyzed using the same criteria to identify the consistently differential expressed mRNAs and proteins across genders and races. We then integrated prognosis-related mRNAs with clinical, pathological, and EGFR (epidermal growth factor receptor) mutation data to construct a survival model, subsequently validating it across populations. Through plasma proteomics, plasma proteins that consistently differential expressed with LUAD tissues were screened and validated, with their associations discerned by measuring expressions in tumor tissues and tumor vascular normalization.

RESULTS

The consistency rate of differentially expressed mRNAs and proteins was ~20-40%, with ethnic factors leading to about 40-60% consistency of differentially expressed mRNA or protein across populations. The survival model based on the identified eight hub mRNAs as well as stage, smoking status, and EGFR mutations, demonstrated good prognostic prediction capabilities in both Western and East Asian populations, with a higher number of unfavorable variables indicating poorer LUAD prognosis. Notably, GPI expression in tumor tissues was inversely correlated with vascular normalization and positively correlated with plasma GPI expression.

CONCLUSION

Our study underscores the significance of integrating transcriptomics and proteomics data, emphasizing the need to account for genetic diversity among ethnic groups. The developed survival model may offer a holistic perspective on LUAD progression, enhancing prognosis and therapeutic strategies.

Base Pairing Promoted the Self-Organization of Genetic Coding, Catalysis, and Free-Energy Transduction

How Nature discovered genetic coding is a largely ignored question, yet the answer is key to explaining the transition from biochemical building blocks to life. Other, related puzzles also fall inside the aegis enclosing the codes themselves. The peptide bond is unstable with respect to hydrolysis. So, it requires some form of chemical free energy to drive it. Amino acid activation and acyl transfer are also slow and must be catalyzed. All living things must thus also convert free energy and synchronize cellular chemistry. Most importantly, functional proteins occupy only small, isolated regions of sequence space. Nature evolved heritable symbolic data processing to seek out and use those sequences. That system has three parts: a memory of how amino acids behave in solution and inside proteins, a set of code keys to access that memory, and a scoring function. The code keys themselves are the genes for cognate pairs of tRNA and aminoacyl-tRNA synthetases, AARSs. The scoring function is the enzymatic specificity constant, kcat/kM, which measures both catalysis and specificity. The work described here deepens the evidence for and understanding of an unexpected consequence of ancestral bidirectional coding. Secondary structures occur in approximately the same places within antiparallel alignments of their gene products. However, the polar amino acids that define the molecular surface of one are reflected into core-defining non-polar side chains on the other. Proteins translated from base-paired coding strands fold up inside out. Bidirectional genes thus project an inverted structural duality into the proteome. I review how experimental data root the scoring functions responsible for the origins of coding and catalyzed activation of unfavorable chemical reactions in that duality.

Regulation of bacterial gene expression by non-coding RNA: It is all about time!

Commensal and pathogenic bacteria continuously evolve to survive in diverse ecological niches by efficiently coordinating gene expression levels in their ever-changing environments. Regulation through the RNA transcript itself offers a faster and more cost-effective way to adapt than protein-based mechanisms and can be leveraged for diagnostic or antimicrobial purposes. However, RNA can fold into numerous intricate, not always functional structures that both expand and obscure the plethora of roles that regulatory RNAs serve within the cell. Here, we review the current knowledge of bacterial non-coding RNAs in relation to their folding pathways and interactions. We posit that co-transcriptional folding of these transcripts ultimately dictates their downstream functions. Elucidating the spatiotemporal folding of non-coding RNAs during transcription therefore provides invaluable insights into bacterial pathogeneses and predictive disease diagnostics. Finally, we discuss the implications of co-transcriptional folding andapplications of RNAs for therapeutics and drug targets.

Harnessing non-Watson-Crick's base pairing to enhance CRISPR effectors cleavage activities and enable gene editing in mammalian cells

Genomic DNA of the cyanophage S-2L virus is composed of 2-aminoadenine (Z), thymine (T), guanine (G), and cytosine (C), forming the genetic alphabet ZTGC, which violates Watson-Crick base pairing rules. The Z-base has an extra amino group on the two position that allows the formation of a third hydrogen bond with thymine in DNA strands. Here, we explored and expanded applications of this non-Watson-Crick base pairing in protein expression and gene editing. Both ZTGC-DNA (Z-DNA) and ZUGC-RNA (Z-RNA) produced in vitro show detectable compatibility and can be decoded in mammalian cells, including Homo sapiens cells. Z-crRNA can guide CRISPR-effectors SpCas9 and LbCas12a to cleave specific DNA through non-Watson-Crick base pairing and boost cleavage activities compared to A-crRNA. Z-crRNA can also allow for efficient gene and base editing in human cells. Together, our results help pave the way for potential strategies for optimizing DNA or RNA payloads for gene editing therapeutics and give insights to understanding the natural Z-DNA genome.

Strain in the Midbrain: Impact of Traumatic Brain Injury on the Central Serotonin System

Traumatic brain injury (TBI) is a pervasive public health crisis that severely impacts the quality of life of affected individuals. Like peripheral forms of trauma, TBI results from extraordinarily heterogeneous environmental forces being imparted on the cranial space, resulting in heterogeneous disease pathologies. This has made therapies for TBI notoriously difficult to develop, and currently, there are no FDA-approved pharmacotherapies specifically for the acute or chronic treatment of TBI. TBI is associated with changes in cognition and can precipitate the onset of debilitating psychiatric disorders like major depressive disorder (MDD), generalized anxiety disorder (GAD), and post-traumatic stress disorder (PTSD). Complicating these effects of TBI, FDA-approved pharmacotherapies utilized to treat these disorders often fail to reach the desired level of efficacy in the context of neurotrauma. Although a complicated association, decades of work have linked central serotonin (5-HT) neurotransmission as being involved in the etiology of a myriad of neuropsychiatric disorders, including MDD and GAD. 5-HT is a biogenic monoamine neurotransmitter that is highly conserved across scales of biology. Though the majority of 5-HT is isolated to peripheral sites such as the gastrointestinal (GI) tract, 5-HT neurotransmission within the CNS exerts exquisite control over diverse biological functions, including sleep, appetite and respiration, while simultaneously establishing normal mood, perception, and attention. Although several key studies have begun to elucidate how various forms of neurotrauma impact central 5-HT neurotransmission, a full determination of precisely how TBI disrupts the highly regulated dynamics of 5-HT neuron function and/or 5-HT neurotransmission has yet to be conceptually or experimentally resolved. The purpose of the current review is, therefore, to integrate the disparate bodies of 5-HT and TBI research and synthesize insight into how new combinatorial research regarding 5-HT neurotransmission and TBI may offer an informed perspective into the nature of TBI-induced neuropsychiatric complications.

Liver cancer-specific mutations in functional domains of ADAR2 lead to the elevation of coding and non-coding RNA editing in multiple tumor-related genes

Mutation is the major cause of phenotypic innovations. Apart from DNA mutations, the alteration on RNA such as the ADAR-mediated A-to-I RNA editing could also shape the phenotype. These two layers of variations have not been systematically combined to study their collective roles in cancers. We collected the high-quality transcriptomes of ten hepatocellular carcinoma (HCC) and the matched control samples. We systematically identified HCC-specific mutations in the exonic regions and profiled the A-to-I RNA editome in each sample. All ten HCC samples had mutations in the CDS of ADAR2 gene (dsRNA-binding domain or catalytic domain). The consequence of these mutations converged to the elevation of ADAR2 efficiency as reflected by the global increase of RNA editing levels in HCC. The up-regulated editing sites (UES) were enriched in the CDS and UTR of oncogenes and tumor suppressor genes (TSG), indicating the possible roles of these target genes in HCC oncogenesis. We present the mutation-ADAR2-UES-oncogene/TSG-HCC axis that explains how mutations at different layers would finally lead to abnormal phenotype. In the light of central dogma, our work provides novel insights into how to fully take advantage of the transcriptome data to decipher the consequence of mutations.

Novel Perspectives for the Diagnosis and Treatment of Gynecological Cancers using Dysregulation of PIWI Protein and PiRNAs as Biomarkers

The term "gynecological cancer" is used for a group of cancers occurring in the female reproductive system. Some of these cancers are ranked as the leading causes of death in developed and developing countries. The lack of proper diagnostic strategies is one of the most important reasons that make them lethal. PIWI-interacting RNAs or piRNAs are a class of small non-coding RNAs, which contain 24-32 nucleotides. These RNAs take part in some cellular mechanisms, and their role in diverse kinds of cancer is confirmed by accumulative evidence. In this review, we gather some information on the roles of these RNAs and members of the PIWI protein family to provide new insight into accurate diagnostic biomarkers and more effective anti-cancer drugs with fewer side effects.