Search Results (23)

Over the past two decades, advances in the understanding of epigenetic mechanisms—driven by the rapid expansion of omics technologies—have catalyzed a major paradigm shift in biology: from the genetic determinism and linear causality of the Central Dogma toward the dynamic, networked complexity of systems biology and multilevel regulation. This reconceptualization extends to inheritance itself, highlighting the crucial role of the epigenome as a molecular interface between the genome and the exposome—the cumulative set of internal and external environmental influences experienced across the lifespan. Within this evolving framework, neurodevelopmental disorders exemplify the deep entanglement between genetic predisposition, environmental exposure, and epigenetic modulation. Their increasing global prevalence and frequent comorbidities underscore the need for an integrated etiological understanding that transcends reductionist models. This review tries to synthesize current evidence on the shared molecular and systemic mechanisms underlying neurodevelopmental spectrum disorders and examines how environmental and epigenetic factors jointly shape neurodevelopmental trajectories across generations. Finally, it discusses the broader implications of this paradigm shift for early diagnosis, prevention, and public health policies aimed at fostering healthy brain development in future generations. Full article

The conceptual understanding of genetic information has evolved from early philosophical speculation to the molecular precision of contemporary biology. Initial debates over the nature of heredity, including Mendel’s hereditary factors and the longstanding protein versus nucleic acid controversy, underscored the difficulty of identifying the true substrate of inheritance. Subsequent discoveries, including reverse transcription, protein-based infectivity (prions), transposable elements, and the regulatory functions of non-coding RNAs, revealed molecular processes that operate at the boundaries of, or alongside, Crick’s original formulation of the Central Dogma of Molecular Biology. Importantly, these findings do not violate the directional rules of information transfer defined by the Central Dogma (DNA → RNA → protein), but instead reshape how, when, and under what constraints these canonical flows are executed in living systems. Epigenetic and epigenetic-like mechanisms, including DNA methylation, histone modifications, chromatin topology, non-canonical DNA conformations, and cytoplasmic inheritance, introduce regulatory layers that modulate information flow without constituting independent information matrices. In parallel, genome innovation, through de novo gene birth, and genome erosion, through pseudogenization, demonstrate that the repertoire of DNA → RNA → protein pathways is itself evolutionarily dynamic. This narrative integrative review reconstructs the historical milestones that culminated in the Central Dogma and synthesizes subsequent discoveries that expand its functional realization. By revisiting the Central Dogma through an extended, holistic lens, this article argues that DNA, RNA, and proteins function not only as carriers of genetic information, but also as active participants in its regulation, contextualization, and evolutionary diversification, without departing from the core directional principles originally articulated by Crick. For reader convenience, a dedicated section entitled “Abbreviations and Key Molecular Terms” is provided at the end of the manuscript to facilitate navigation and interdisciplinary accessibility. Full article

RNA-targeting techniques have emerged as powerful tools in cancer research and therapeutics, offering precise and programmable control over gene expression at the post-transcriptional level. Once viewed as passive intermediates in the central dogma, RNA molecules are now recognized as dynamic regulators of cellular function, capable of influencing transcription, translation, and epigenetic regulation. Advances in high-throughput sequencing technologies, transcriptomics, and structural RNA biology have uncovered a diverse landscape of coding and non-coding RNAs involved in oncogenesis, drug resistance, and tumor progression. In response, several RNA-targeting strategies have been developed to modulate these transcripts, including antisense oligonucleotides (ASOs), RNA interference (RNAi), CRISPR-Cas13 systems, small molecules, and aptamers. This review provides a comparative analysis of these technologies, highlighting their molecular mechanisms, therapeutic potential, and current limitations. Emphasis is placed on the translational progress of RNA-targeting agents, including recent FDA approvals and ongoing clinical trials for cancer indications. Through a critical comparison of these strategies, this review underscores the growing significance of RNA-targeting technologies as a foundation for next-generation cancer therapeutics and precision oncology. Full article

Bioinspired computing methods, such as Artificial Neural Networks (ANNs), play a significant role in machine learning. This is particularly evident in smart manufacturing, where ANNs and their derivatives, like deep learning, are widely used for pattern recognition and adaptive control. However, ANNs sometimes fail to achieve the desired results, especially when working with small datasets. To address this limitation, this article presents the effectiveness of DNA-Based Computing (DBC) as a complementary approach. DBC is an innovative machine learning method rooted in the central dogma of molecular biology that deals with the genetic information of DNA/RNA to protein. In this article, two machine learning approaches are considered. In the first approach, an ANN was trained and tested using time series datasets driven by long and short windows, with features extracted from the time domain. Each long-window-driven dataset contained approximately 150 data points, while each short-window-driven dataset had approximately 10 data points. The results showed that the ANN performed well for long-window-driven datasets. However, its performance declined significantly in the case of short-window-driven datasets. In the last approach, a hybrid model was developed by integrating DBC with the ANN. In this case, the features were first extracted using DBC. The extracted features were used to train and test the ANN. This hybrid approach demonstrated robust performance for both long- and short-window-driven datasets. The ability of DBC to overcome the ANN’s limitations with short-window-driven datasets underscores its potential as a pragmatic machine learning solution for developing more effective smart manufacturing systems, such as digital twins. Full article

Cardiac physiology and pathology have been extensively explored at the transcriptional level. Still, they are less understood at the translational level, including three major knowledge gaps: pathophysiological impact, molecular mechanisms, and therapeutic implications of translational control in cardiac biology and heart disease. This review aims to provide a summary of the most recent key findings in this emerging field of translational control in heart health and disease, covering the physiological functions, disease pathogenesis, biochemical mechanisms, and development of potential RNA-based, translation-manipulating drugs. Translation of mRNA to protein is the final step in the central dogma for protein synthesis. Translation machinery includes a family of essential “housekeeping” factors and enzymes required for mRNA translation. These translation factors ensure the accurate processing of mRNA to protein according to the genetic code and maintain the optimal quality and quantity of cellular proteins for normal cardiac function. Translation factors also regulate the efficiency, speed, and fidelity of protein production and play a role in cardiac pathological remodeling under stress conditions. This review first introduces the techniques and methods used to study the translational regulation of gene expression in the cardiac system. We then summarize discoveries of a variety of pathophysiological functions and molecular mechanisms of translational control in cardiac health and disease, focusing on two primary symptoms, cardiac hypertrophy and fibrosis. In these sessions, we discuss the translational regulation directed by specific regulatory factors in cardiac physiology and how their genetic mutations, expression dysregulation, or functional alterations contribute to the etiology of heart disease. Notably, translational control exhibits extensive crosstalk with other processes, including transcriptional regulation, mitochondrial metabolism, and sarcomere homeostasis. Furthermore, recent findings have revealed the role of translational regulation in cardiomyocyte proliferation and heart regeneration, providing new approaches for creating regenerative medicine. Because transcript-specific translational regulation of both pathological and protective proteins occurs in heart disease, target-selective translation inhibitors and enhancers can be developed. These inhibitors and enhancers offer valuable insights into novel therapeutic targets and the development of RNA-based drugs for heart disease treatment. Full article

Human genome projects in the 1990s identified about 20,000 protein-coding sequences. We are now in the RNA revolution, propelled by the realization that genes determine phenotype beyond the foundational central molecular biology dogma, stating that inherited linear pieces of DNA are transcribed to RNAs and translated into proteins. Crucially, over 95% of the genome, initially considered junk DNA between protein-coding genes, encodes essential, functionally diverse non-protein-coding RNAs, raising the gene count by at least one order of magnitude. Most inherited phenotype-determining changes in DNA are in regulatory areas that control RNA and regulatory sequences. RNAs can directly or indirectly determine phenotypes by regulating protein and RNA function, transferring information within and between organisms, and generating DNA. RNAs also exhibit high structural, functional, and biomolecular interaction plasticity and are modified via editing, methylation, glycosylation, and other mechanisms, which bestow them with diverse intra- and extracellular functions without altering the underlying DNA. RNA is, therefore, currently considered the primary determinant of cellular to populational functional diversity, disease-linked and biomolecular structural variations, and cell function regulation. As demonstrated by RNA-based coronavirus vaccines’ success, RNA technology is transforming medicine, agriculture, and industry, as did the advent of recombinant DNA technology in the 1980s. Full article

Smart manufacturing needs cognitive computing methods to make the relevant systems more intelligent and autonomous. In this respect, bio-inspired cognitive computing methods (i.e., biologicalization) can play a vital role. This article is written from this perspective. In particular, this article provides a general overview of the bio-inspired computing method called DNA-Based Computing (DBC), including its theory and applications. The main theme of DBC is the central dogma of molecular biology (once information of DNA/RNA has got into a protein, it cannot get out again), i.e., DNA to RNA (sequences of four types of nucleotides) and DNA/RNA to protein (sequence of twenty types of amino acids) are allowed, but not the reverse ones. Thus, DBC transfers few-element information (DNA/RAN-like) to many-element information (protein-like). This characteristic of DBC can help to solve cognitive problems (e.g., pattern recognition). DBC can take many forms; this article elucidates two main forms, denoted as DBC-1 and DBC-2. Using arbitrary numerical examples, we demonstrate that DBC-1 can solve various cognitive problems, e.g., “similarity indexing between seemingly different but inherently identical objects” and “recognizing regions of an image separated by a complex boundary.” In addition, using an arbitrary numerical example, we demonstrate that DBC-2 can solve the following cognitive problem: “pattern recognition when the relevant information is insufficient.” The remarkable thing is that smart manufacturing-based systems (e.g., digital twins and big data analytics) must solve the abovementioned problems to make the manufacturing enablers (e.g., machine tools and monitoring systems) more self-reliant and autonomous. Consequently, DBC can improve the cognitive problem-solving ability of smart manufacturing-relevant systems and enrich their biologicalization. Full article

With more than 466 million people affected, hearing loss represents the most common sensory pathology worldwide. Despite its widespread occurrence, much remains to be explored, particularly concerning the intricate pathogenic mechanisms underlying its diverse phenotypes. In this context, metabolomics emerges as a promising approach. Indeed, lying downstream from molecular biology’s central dogma, the metabolome reflects both genetic traits and environmental influences. Furthermore, its dynamic nature facilitates well-defined changes during disease states, making metabolomic analysis a unique lens into the mechanisms underpinning various hearing impairment forms. Hence, these investigations may pave the way for improved diagnostic strategies, personalized interventions and targeted treatments, ultimately enhancing the clinical management of affected individuals. In this comprehensive review, we discuss findings from 20 original articles, including human and animal studies. Existing literature highlights specific metabolic changes associated with hearing loss and ototoxicity of certain compounds. Nevertheless, numerous critical issues have emerged from the study of the current state of the art, with the lack of standardization of methods, significant heterogeneity in the studies and often small sample sizes being the main limiting factors for the reliability of these findings. Therefore, these results should serve as a stepping stone for future research aimed at addressing the aforementioned challenges. Full article

The disciplinary identity of molecular biology has frequently been called into question. Although the debates might sometimes have been more about creating or debunking myths, defending intellectual territory and the distribution of resources, there are interesting underlying questions about this area of biology and how it is conceptually organized. By looking at the history of molecular biology, its origins and development, I examine the possible criteria for its status as a scientific discipline. Doing so allows us to answer the title question in such a way that offers a reasonable middle ground, where molecular biology can be properly viewed as a viable interdisciplinary program that can very well be called a discipline in its own right, even if no strict boundaries can be established. In addition to this historical analysis, a couple of systematic issues from a philosophy of science perspective allow for some assessment of the current situation and the future of molecular biology. Full article

A common belief among pre-medical and medical students is that biochemistry is not relevant to practicing medicine. The problem-based approach of case studies has been used in medical education to scaffold the application of content to clinical cases, but few studies report on a similar use in undergraduate biochemistry. Case studies in biochemistry and related disciplines have been previously reported as increasing learning motivation and supporting depth of knowledge. Additionally, students engaging in case studies outperform students in traditional instruction. The objective of this qualitative case study was to find how the timing of a medical case study within the instructional sequence in an undergraduate biochemistry course supported students in applying the central dogma of molecular biology to explain the transfer of Huntington’s disease from parent to child. The CBL+ group reviewed the case study before class while the CBL− group was presented with the case study during class. Analysis of open response tasks added to the pre- and post-surveys suggested that the case study supported both groups in applying the central dogma to the case, but the earlier presentation of the case to the CBL+ group promoted deeper thinking about the mechanistic causation of the transfer of the disease. Full article

The central dogma of genetics, which outlines the flow of genetic information from DNA to RNA to protein, has long been the guiding principle in molecular biology. In fact, more than three-quarters of the RNAs produced by transcription of the plant genome are not translated into proteins, and these RNAs directly serve as non-coding RNAs in the regulation of plant life activities at the molecular level. The breakthroughs in high-throughput transcriptome sequencing technology and the establishment and improvement of non-coding RNA experiments have now led to the discovery and confirmation of the biogenesis, mechanisms, and synergistic effects of non-coding RNAs. These non-coding RNAs are now predicted to play important roles in the regulation of gene expression and responses to stress and evolution. In this review, we focus on the synthesis, and mechanisms of non-coding RNAs, and we discuss their impact on gene regulation in plants. Full article

Breast cancer (BC) is characterized by an extensive genotypic and phenotypic heterogeneity. In-depth investigations into the molecular bases of BC phenotypes, carcinogenesis, progression, and metastasis are necessary for accurate diagnoses, prognoses, and therapy assessments in predictive, precision, and personalized oncology. This review discusses both classic as well as several novel omics fields that are involved or should be used in modern BC investigations, which may be integrated as a holistic term, onco-breastomics. Rapid and recent advances in molecular profiling strategies and analytical techniques based on high-throughput sequencing and mass spectrometry (MS) development have generated large-scale multi-omics datasets, mainly emerging from the three ”big omics”, based on the central dogma of molecular biology: genomics, transcriptomics, and proteomics. Metabolomics-based approaches also reflect the dynamic response of BC cells to genetic modifications. Interactomics promotes a holistic view in BC research by constructing and characterizing protein–protein interaction (PPI) networks that provide a novel hypothesis for the pathophysiological processes involved in BC progression and subtyping. The emergence of new omics- and epiomics-based multidimensional approaches provide opportunities to gain insights into BC heterogeneity and its underlying mechanisms. The three main epiomics fields (epigenomics, epitranscriptomics, and epiproteomics) are focused on the epigenetic DNA changes, RNAs modifications, and posttranslational modifications (PTMs) affecting protein functions for an in-depth understanding of cancer cell proliferation, migration, and invasion. Novel omics fields, such as epichaperomics or epimetabolomics, could investigate the modifications in the interactome induced by stressors and provide PPI changes, as well as in metabolites, as drivers of BC-causing phenotypes. Over the last years, several proteomics-derived omics, such as matrisomics, exosomics, secretomics, kinomics, phosphoproteomics, or immunomics, provided valuable data for a deep understanding of dysregulated pathways in BC cells and their tumor microenvironment (TME) or tumor immune microenvironment (TIMW). Most of these omics datasets are still assessed individually using distinct approches and do not generate the desired and expected global-integrative knowledge with applications in clinical diagnostics. However, several hyphenated omics approaches, such as proteo-genomics, proteo-transcriptomics, and phosphoproteomics-exosomics are useful for the identification of putative BC biomarkers and therapeutic targets. To develop non-invasive diagnostic tests and to discover new biomarkers for BC, classic and novel omics-based strategies allow for significant advances in blood/plasma-based omics. Salivaomics, urinomics, and milkomics appear as integrative omics that may develop a high potential for early and non-invasive diagnoses in BC. Thus, the analysis of the tumor circulome is considered a novel frontier in liquid biopsy. Omics-based investigations have applications in BC modeling, as well as accurate BC classification and subtype characterization. The future in omics-based investigations of BC may be also focused on multi-omics single-cell analyses. Full article

The holm oak (Quercus ilex L.) is the dominant tree species of the Mediterranean forest and the Spanish agrosilvopastoral ecosystem, “dehesa.” It has been, since the prehistoric period, an important part of the Iberian population from a social, cultural, and religious point of view, providing an ample variety of goods and services, and forming the basis of the economy in rural areas. Currently, there is renewed interest in its use for dietary diversification and sustainable food production. It is part of cultural richness, both economically (tangible) and environmentally (intangible), and must be preserved for future generations. However, a worrisome degradation of the species and associated ecosystems is occurring, observed in an increase in tree decline and mortality, which requires urgent action. Breeding programs based on the selection of elite genotypes by molecular markers is the only plausible biotechnological approach. To this end, the authors’ group started, in 2004, a research line aimed at characterizing the molecular biology of Q. ilex. It has been a challenging task due to its biological characteristics (long life cycle, allogamous, high phenotypic variability) and recalcitrant nature. The biology of this species has been characterized following the central dogma of molecular biology using the omics cascade. Molecular responses to biotic and abiotic stresses, as well as seed maturation and germination, are the two main objectives of our research. The contributions of the group to the knowledge of the species at the level of DNA-based markers, genomics, epigenomics, transcriptomics, proteomics, and metabolomics are discussed here. Moreover, data are compared with those reported for Quercus spp. All omics data generated, and the genome of Q. ilex available, will be integrated with morphological and physiological data in the systems biology direction. Thus, we will propose possible molecular markers related to resilient and productive genotypes to be used in reforestation programs. In addition, possible markers related to the nutritional value of acorn and derivate products, as well as bioactive compounds (peptides and phenolics) and allergens, will be suggested. Subsequently, the selected molecular markers will be validated by both genome-wide association and functional genomic analyses. Full article

Eliminating the risk of bugs and external decryption in cryptographic keys has always been a challenge for researchers. The current research is based on a new design that uses an Omega network-based pseudorandom DNA key generation method to produce cryptographic keys for symmetric key systems. The designed algorithm initially takes two random binary numbers as inputs to the Omega network design, generating an output of 256 symmetric keys. The Omega network uses the concept of the central dogma of molecular biology (DNA and RNA properties), including DNA replication (for DNA) and the transcription process (for RNA). The NIST test suite is applied to test the security properties of the proposed design. According to the study’s findings, the suggested design is significantly suited to achieve the NIST test security properties and passes all of the NIST recommended tests. Full article

Info-autopoiesis or the self-referenced, recursive, interactive process of information self-production that engages all living beings in their efforts to satisfy their physiological and/or relational needs relies on Bateson’s difference which makes a difference. Living beings, as active manipulators/observers of their environment, derive meaning from the sensorially detected motion of matter and/or energy in the Universe. The process of info-autopoiesis in humans is found to be triadic in nature and incorporates the simultaneity of a quantitative/objective perspective with a qualitative/subjective perspective. In this process of meaningful engagement with the environment, humans create and transform endogenous semantic information into countless expressions of exogeneous syntactic information, which is synonymous with ordered material structure and artificial creation. Other humans can interpret exogeneous syntactic information and uniquely transform it into semantic information that can take multifarious forms. This asymmetrical process is the basis to postulate the central dogma of information that states ‘info-autopoiesis results in endogenous semantic information that irreversibly becomes exogeneous syntactic information’. In other words, once the artificial, syntactic world, including machines, created by humans comes into being it can only be interpreted by others, i.e., it does not necessarily convey the same intended meaning to all. Additionally, these artificial creations only recognize, extract, create, transmit, preserve, store, and utilize syntactic information, unable to transform syntactic information into semantic information. In other words, our resourceful capacity for syntactic creation does not allow for creation of artificial beings with comparable capabilities as us for meaning making. It suggests that our dreams for sentient artificial general intelligence and superintelligence are misguided and parallel the central dogma of molecular biology which states that ‘once (sequential) information has passed into protein it cannot get out again’. Full article