Central dogma of molecular biology

Assessing how well students understand the molecular basis of evolution by natural selection

Researchers have called for undergraduate courses to update teaching frameworks based on the Modern Synthesis with insights from molecular biology, by stressing the molecular underpinnings of variation and adaptation. To support this goal, we developed a modified version of the widely used Assessing Conceptual Reasoning of Natural Selection (ACORNS) instrument. The expanded tool, called the E-ACORNS, is explicitly designed to test student understanding of the connections among genotypes, phenotypes, and fitness. E-ACORNS comprises a slight modification to the ACORNS open-response prompts and a new scoring rubric. The rubric is based on five core concepts in evolution by natural selection, with each concept broken into elements at the novice, intermediate, and expert-level understanding. Initial tests of the E-ACORNS showed that (1) upper-level undergraduates can score responses reliably and quickly, and (2) students who were just starting an introductory biology series for majors do not yet grasp the molecular basis of phenotypic variation and its connection to fitness.

The genome editing revolution

A series of spectacular scientific discoveries and technological advances in the second half of the 20th century have provided the basis for the ongoing genome editing revolution. The elucidation of structural and functional features of DNA and RNA was followed by pioneering studies on genome editing: Molecular biotechnology was born. Since then, four decades followed during which progress of scientific insights and technological methods continued at an overwhelming pace. Fundamental insights into microbial host-virus interactions led to the development of tools for genome editing using restriction enzymes or the revolutionary CRISPR-Cas technology. In this review, we provide a historical overview of milestones that led to the genome editing revolution and speculate about future trends in biotechnology.

Reverse Transcriptases: From Discovery and Applications to Xenobiology

Reverse transcriptases are DNA polymerases that can use RNA as a template for DNA synthesis. They thus catalyze the reverse of transcription. Although discovered in 1970, reverse transcriptases are still of great interest and are constantly being further developed for numerous modern research approaches. They are frequently used in biotechnological and molecular diagnostic applications. In this review, we describe the discovery of these fascinating enzymes and summarize research results and applications ranging from molecular cloning, direct virus detection, and modern sequencing methods to xenobiology.

IARA: a complete and curated atlas of the biogenesis of spliceosome machinery during RNA splicing

Splicing is one of the most important post-transcriptional processing systems and is responsible for the generation of transcriptome diversity in all living eukaryotes. Splicing is regulated by the spliceosome machinery, which is responsible for each step of primary RNA processing. However, current molecules and stages involved in RNA splicing are still spread over different studies. Thus, a curated atlas of spliceosome-related molecules and all involved stages during RNA processing can provide all researchers with a reliable resource to better investigate this important mechanism. Here, we present IARA (website access: https://pucpr-bioinformatics.github.io/atlas/), an extensively curated and constantly updated catalog of molecules involved in spliceosome machinery. IARA has a map of the steps involved in the human splicing mechanism, and it allows a detailed overview of the molecules involved throughout the distinct steps of splicing.

Epitranscriptomics in metabolic disease

While epigenetic modifications of DNA and histones play main roles in gene transcription regulation, recently discovered post-transcriptional RNA modifications, known as epitranscriptomic modifications, have been found to have a profound impact on gene expression by regulating RNA stability, localization and decoding efficiency. Importantly, genetic variations or environmental perturbations of epitranscriptome modifiers (that is, writers, erasers and readers) are associated with obesity and metabolic diseases, such as type 2 diabetes. The epitranscriptome is closely coupled to epigenetic signalling, adding complexity to our understanding of gene expression in both health and disease. Moreover, the epitranscriptome in the parental generation can affect organismal phenotypes in the next generation. In this Review, we discuss the relationship between epitranscriptomic modifications and metabolic diseases, their relationship with the epigenome and possible therapeutic strategies.

Mathematical and physical considerations indicating that the cell genome is a read-write memory

The molecular mechanisms that govern biological evolution have not been fully elucidated so far. Recent studies indicate that regulatory proteins, acting as decision-making complex devices, can accelerate or retard the evolution of cells. Such biochemically controlled evolution may be considered as an optimization process of logical nature aimed at developing fitter species that can better survive in a specific environment. Therefore, we may assume that new genetic information can be stored in the cell memory (i.e., genome) by a sophisticated biomolecular process that resembles writing in computer memory. Such a hypothesis is theoretically supported by a recent work showing that logic is a necessary component of life, so living systems process information in the same way as computers. The current study summarizes existing evidence showing that cells can intentionally modify their stored data by biochemical processes resembling stochastic algorithms to avoid environmental stress and increase their chances of survival. Furthermore, the mathematical and physical considerations that render a read-write memory a necessary component of biological systems are presented.

Transcriptomic, proteomic, and functional consequences of codon usage bias in human cells during heterologous gene expression

Differences in codon frequency between genomes, genes, or positions along a gene, modulate transcription and translation efficiency, leading to phenotypic and functional differences. Here, we present a multiscale analysis of the effects of synonymous codon recoding during heterologous gene expression in human cells, quantifying the phenotypic consequences of codon usage bias at different molecular and cellular levels, with an emphasis on translation elongation. Six synonymous versions of an antibiotic resistance gene were generated, fused to a fluorescent reporter, and independently expressed in HEK293 cells. Multiscale phenotype was analyzed by means of quantitative transcriptome and proteome assessment, as proxies for gene expression; cellular fluorescence, as a proxy for single-cell level expression; and real-time cell proliferation in absence or presence of antibiotic, as a proxy for the cell fitness. We show that differences in codon usage bias strongly impact the molecular and cellular phenotype: (i) they result in large differences in mRNA levels and protein levels, leading to differences of over 15 times in translation efficiency; (ii) they introduce unpredicted splicing events; (iii) they lead to reproducible phenotypic heterogeneity; and (iv) they lead to a trade-off between the benefit of antibiotic resistance and the burden of heterologous expression. In human cells in culture, codon usage bias modulates gene expression by modifying mRNA availability and suitability for translation, leading to differences in protein levels and eventually eliciting functional phenotypic changes.

On the origin and evolution of RNA editing in metazoans

Extensive adenosine-to-inosine (A-to-I) editing of nuclear-transcribed mRNAs is the hallmark of metazoan transcriptional regulation. Here, by profiling the RNA editomes of 22 species that cover major groups of Holozoa, we provide substantial evidence supporting A-to-I mRNA editing as a regulatory innovation originating in the last common ancestor of extant metazoans. This ancient biochemistry process is preserved in most extant metazoan phyla and primarily targets endogenous double-stranded RNA (dsRNA) formed by evolutionarily young repeats. We also find intermolecular pairing of sense-antisense transcripts as an important mechanism for forming dsRNA substrates for A-to-I editing in some but not all lineages. Likewise, recoding editing is rarely shared across lineages but preferentially targets genes involved in neural and cytoskeleton systems in bilaterians. We conclude that metazoan A-to-I editing might first emerge as a safeguard mechanism against repeat-derived dsRNA and was later co-opted into diverse biological processes due to its mutagenic nature.

Molecular elements: novel approaches for molecular building

Classically, a molecular element (ME) is a pure substance composed of two or more atoms of the same element. However, MEs, in the context of this review, can be any molecules as elements bonded together into the backbone of synthetic oligonucleotides (ONs) with designed sequences and functions, including natural A, T, C, G, U, and unnatural bases. The use of MEs can facilitate the synthesis of designer molecules and smart materials. In particular, we discuss the landmarks associated with DNA structure and related technologies, as well as the extensive application of ONs, the ideal type of molecules for intervention therapy aimed at correcting disease-causing genetic errors (indels). It is herein concluded that the discovery of ON therapeutics and the fabrication of designer molecules or nanostructures depend on the ME concept that we previously published. Accordingly, ME will be our focal point as we discuss related research directions and perspectives in making molecules and materials. This article is part of the theme issue 'Reactivity and mechanism in chemical and synthetic biology'.

Revealing the History and Mystery of RNA-Seq

Advances in RNA-sequencing technologies have led to the development of intriguing experimental setups, a massive accumulation of data, and high demand for tools to analyze it. To answer this demand, computational scientists have developed a myriad of data analysis pipelines, but it is less often considered what the most appropriate one is. The RNA-sequencing data analysis pipeline can be divided into three major parts: data pre-processing, followed by the main and downstream analyses. Here, we present an overview of the tools used in both the bulk RNA-seq and at the single-cell level, with a particular focus on alternative splicing and active RNA synthesis analysis. A crucial part of data pre-processing is quality control, which defines the necessity of the next steps; adapter removal, trimming, and filtering. After pre-processing, the data are finally analyzed using a variety of tools: differential gene expression, alternative splicing, and assessment of active synthesis, the latter requiring dedicated sample preparation. In brief, we describe the commonly used tools in the sample preparation and analysis of RNA-seq data.

Template-Assembled Synthetic G-Quartets (TASQs): multiTASQing Molecular Tools for Investigating DNA and RNA G-Quadruplex Biology

Biomimetics is defined as a "practice of making technological design that copies natural processes", with the idea that "nature has already solved the challenges we are trying to solve" (Cambridge Dictionary). The challenge we decided to address several years ago was the selective targeting of G quadruplexes (G4s) by small molecules (G4 ligands). Why? Because G4s, which are four-stranded DNA and RNA structures that fold from guanine (G)-rich sequences, are suspected to play key biological roles in human cells and diseases. Selective G4 ligands can thus be used as small-molecule modulators to gain a deep understanding of cell circuitry where G4s are involved, thus complying with the very definition of chemical biology (Stuart Schreiber) applied here to G4 biology. How? Following a biomimetic approach that hinges on the observation that G4s are stable secondary structures owing to the ability of Gs to self-associate to form G quartets, and then of G quartets to self-stack to form the columnar core of G4s. Therefore, using a synthetic G quartet as a G4 ligand represents a unique example of biomimetic recognition of G4s.We formulated this hypothesis more than a decade ago, stepping on years of research on Gs, G4s, and G4 ligands. Our approach led to the design, synthesis, and use of a broad family of synthetic G quartets, also referred to as TASQs for template-assembled synthetic G quartets (John Sherman). This quest led us across various chemical lands (organic and supramolecular chemistry, chemical biology, and genetics), along a route on which every new generation of TASQ was a milestone in the growing portfolio of ever smarter molecular tools to decipher G4 biology. As discussed in this Account, we detail how and why we successively develop the very first prototypes of (i) biomimetic ligands, which interact with G4s according to a bioinspired, like-likes-like interaction between two G quartets, one from the ligand, the other from the G4; (ii) smart ligands, which adopt their active conformation only in the presence of their G4 targets; (iii) twice-as-smart ligands, which act as both smart ligands and smart fluorescent probes, whose fluorescence is triggered (turned on) upon interaction with their G4 targets; and (iv) multivalent ligands, which display additional functionalities enabling the detection, isolation, and identification of G4s both in vitro and in vivo. This quest led us to gather a panel of 14 molecular tools which were used to investigate the biology of G4s at a cellular level, from basic optical imaging to multiomics studies.

Knotify+: Toward the Prediction of RNA H-Type Pseudoknots, Including Bulges and Internal Loops

The accurate "base pairing" in RNA molecules, which leads to the prediction of RNA secondary structures, is crucial in order to explain unknown biological operations. Recently, COVID-19, a widespread disease, has caused many deaths, affecting humanity in an unprecedented way. SARS-CoV-2, a single-stranded RNA virus, has shown the significance of analyzing these molecules and their structures. This paper aims to create a pioneering framework in the direction of predicting specific RNA structures, leveraging syntactic pattern recognition. The proposed framework, Knotify+, addresses the problem of predicting H-type pseudoknots, including bulges and internal loops, by featuring the power of context-free grammar (CFG). We combine the grammar's advantages with maximum base pairing and minimum free energy to tackle this ambiguous task in a performant way. Specifically, our proposed methodology, Knotify+, outperforms state-of-the-art frameworks with regards to its accuracy in core stems prediction. Additionally, it performs more accurately in small sequences and presents a comparable accuracy rate in larger ones, while it requires a smaller execution time compared to well-known platforms. The Knotify+ source code and implementation details are available as a public repository on GitHub.

Single mRNA Imaging with Fluorogenic RNA Aptamers and Small-molecule Fluorophores

Messenger RNA (mRNA) is the fundamental information transfer system in the cell. Tracking single mRNA from transcription to degradation with fluorescent probes provides spatiotemporal information in cells about how the genetic information is transferred from DNA to proteins. The traditional single mRNA imaging approach utilizes RNA hairpins (e.g. MS2) and tethered fluorescent protein as probes. As an exciting alternative, RNA aptamers: small-molecule fluorophores (SFs) systems have emerged as novel single mRNA imaging probes since 2019, exhibiting several advantages including fluorogenic ability and minimal perturbation. This review summarizes all five reported RNA aptamers: SFs systems for single mRNA imaging in living cells so far. It also discusses the challenges and provides prospects for single mRNA imaging applications. This review is expected to inspire researchers to develop RNA aptamers: SFs systems for studying gene expression at single-molecule resolution in cells.

Dealing with dimensionality: the application of machine learning to multi-omics data

MOTIVATION

Machine learning (ML) methods are motivated by the need to automate information extraction from large datasets in order to support human users in data-driven tasks. This is an attractive approach for integrative joint analysis of vast amounts of omics data produced in next generation sequencing and other -omics assays. A systematic assessment of the current literature can help to identify key trends and potential gaps in methodology and applications. We surveyed the literature on ML multi-omic data integration and quantitatively explored the goals, techniques and data involved in this field. We were particularly interested in examining how researchers use ML to deal with the volume and complexity of these datasets.

RESULTS

Our main finding is that the methods used are those that address the challenges of datasets with few samples and many features. Dimensionality reduction methods are used to reduce the feature count alongside models that can also appropriately handle relatively few samples. Popular techniques include autoencoders, random forests and support vector machines. We also found that the field is heavily influenced by the use of The Cancer Genome Atlas dataset, which is accessible and contains many diverse experiments.

AVAILABILITY AND IMPLEMENTATION

All data and processing scripts are available at this GitLab repository: https://gitlab.com/polavieja_lab/ml_multi-omics_review/ or in Zenodo: https://doi.org/10.5281/zenodo.7361807.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Deciphering the multi-scale, quantitative cis-regulatory code

Uncovering the cis-regulatory code that governs when and how much each gene is transcribed in a given genome and cellular state remains a central goal of biology. Here, we discuss major layers of regulation that influence how transcriptional outputs are encoded by DNA sequence and cellular context. We first discuss how transcription factors bind specific DNA sequences in a dosage-dependent and cooperative manner and then proceed to the cofactors that facilitate transcription factor function and mediate the activity of modular cis-regulatory elements such as enhancers, silencers, and promoters. We then consider the complex and poorly understood interplay of these diverse elements within regulatory landscapes and its relationships with chromatin states and nuclear organization. We propose that a mechanistically informed, quantitative model of transcriptional regulation that integrates these multiple regulatory layers will be the key to ultimately cracking the cis-regulatory code.

Emerging and established therapies for chemotherapy-induced ototoxicity

PURPOSE

Ototoxicity is considered a dose-limiting side effect of some chemotherapies. Hearing loss, in particular, can have significant implications for the quality of life for cancer survivors. Here, we review therapeutic approaches to mitigating ototoxicity related to chemotherapy.

METHODS

Literature review.

CONCLUSIONS

Numerous otoprotection strategies are undergoing active investigation. However, numerous challenges exist to confer adequate protection while retaining the anti-cancer efficacy of the chemotherapy.

IMPLICATIONS FOR CANCER SURVIVORS

Ototoxicity can have significant implications for cancer survivors, notably those receiving cisplatin. Clinical translation of multiple otoprotection approaches will aid in limiting these consequences.

Overview of gene expression techniques with an emphasis on vitamin D related studies

Each cell controls when and how its genes must be expressed for proper function. Every function in a cell is driven by signaling molecules through various regulatory cascades. Different cells in a multicellular organism may express very different sets of genes, even though they contain the same DNA. The set of genes expressed in a cell determines the set of proteins and functional RNAs it contains, giving it its unique properties. Malfunction in gene expression harms the cell and can lead to the development of various disease conditions. The use of rapid high-throughput gene expression profiling unravels the complexity of human disease at various levels. Peripheral blood mononuclear cells (PBMC) have been used frequently to understand gene expression homeostasis in various disease conditions. However, more studies are required to validate whether PBMC gene expression patterns accurately reflect the expression of other cells or tissues. Vitamin D, which is responsible for a multitude of health consequences, is also an immune modulatory hormone with major biological activities in the innate and adaptive immune systems. Vitamin D exerts its diverse biological effects in target tissues by regulating gene expression and its deficiency, is recognized as a public health problem worldwide. Understanding the genetic factors that affect vitamin D has the potential benefit that it will make it easier to identify individuals who require supplementation. Different technological advances in gene expression can be used to identify and assess the severity of disease and aid in the development of novel therapeutic interventions. This review focuses on different gene expression approaches and various clinical studies of vitamin D to investigate the role of gene expression in identifying the molecular signature of the disease.

Using transcriptomics, proteomics and phosphoproteomics as new approach methodology (NAM) to define biological responses for chemical safety assessment

Omic-based technologies are of particular interest and importance for hazard identification and health risk characterization of chemicals. Their application in the new approach methodologies (NAMs) anchored on cellular toxicity pathways is based on the premise that any apical health endpoint change must be underpinned by some alterations at the omic levels. In the present study we examined the cellular responses to two chemicals, caffeine and coumarin, by generating and integrating multi-omic data from multi-dose and multi-time point transcriptomic, proteomic and phosphoproteomic experiments. We showed that the methodology presented here was able to capture the complete chain of events from the first chemical-induced changes at the phosphoproteome level, to changes in gene expression, and lastly to changes in protein abundance, each with vastly different points of departure (PODs). In HepG2 cells we found that the metabolism of lipids and general cellular stress response to be the dominant biological processes in response to caffeine and coumarin exposure, respectively. The phosphoproteomic changes were detected early in time, at very low doses and provided a fast, adaptive cellular response to chemical exposure with 7-37-fold lower points of departure comparing to the transcriptomics. Changes in protein abundance were found much less frequently than transcriptomic changes. While challenges remain, our study provides strong and novel evidence supporting the notion that these three omic technologies can be used in an integrated manner to facilitate a more complete understanding of pathway perturbations and POD determinations for risk assessment of chemical exposures.

Cells as the first data scientists

The concepts that we generally associate with the field of data science are strikingly descriptive of the way that life, in general, processes information about its environment. The 'information life cycle', which enumerates the stages of information treatment in data science endeavours, also captures the steps of data collection and handling in biological systems. Similarly, the 'data-information-knowledge ecosystem', developed to illuminate the role of informatics in translating raw data into knowledge, can be a framework for understanding how information is constantly being transferred between life and the environment. By placing the principles of data science in a broader biological context, we see the activities of data scientists as the latest development in life's ongoing journey to better understand and predict its environment. Finally, we propose that informatics frameworks can be used to understand the similarities and differences between abiotic complex evolving systems and life.

Biophysical Reviews: Turning the page from 2022 to 2023

This Editorial (vol. 15 issue 1-Regular Issue featuring an Issue Focus on the "100th Anniversary of Har Gobind Khorana") first describes the issue contents before providing both, a look back at some journal highlights from 2022, and a look forward to what we can expect from 2023. The Editorial closes with a roundup of new journal access features and an acknowledgement of those supporting the journal.

Yet Another Similarity between Mitochondrial and Bacterial Ribosomal Small Subunit Biogenesis Obtained by Structural Characterization of RbfA from S. aureus

Ribosome biogenesis is a complex and highly accurate conservative process of ribosomal subunit maturation followed by association. Subunit maturation comprises sequential stages of ribosomal RNA and proteins' folding, modification and binding, with the involvement of numerous RNAses, helicases, GTPases, chaperones, RNA, protein-modifying enzymes, and assembly factors. One such assembly factor involved in bacterial 30S subunit maturation is ribosomal binding factor A (RbfA). In this study, we present the crystal (determined at 2.2 Å resolution) and NMR structures of RbfA as well as the 2.9 Å resolution cryo-EM reconstruction of the 30S-RbfA complex from Staphylococcus aureus (S. aureus). Additionally, we show that the manner of RbfA action on the small ribosomal subunit during its maturation is shared between bacteria and mitochondria. The obtained results clarify the function of RbfA in the 30S maturation process and its role in ribosome functioning in general. Furthermore, given that S. aureus is a serious human pathogen, this study provides an additional prospect to develop antimicrobials targeting bacterial pathogens.

LncReader: identification of dual functional long noncoding RNAs using a multi-head self-attention mechanism

Long noncoding ribonucleic acids (RNAs; LncRNAs) endowed with both protein-coding and noncoding functions are referred to as 'dual functional lncRNAs'. Recently, dual functional lncRNAs have been intensively studied and identified as involved in various fundamental cellular processes. However, apart from time-consuming and cell-type-specific experiments, there is virtually no in silico method for predicting the identity of dual functional lncRNAs. Here, we developed a deep-learning model with a multi-head self-attention mechanism, LncReader, to identify dual functional lncRNAs. Our data demonstrated that LncReader showed multiple advantages compared to various classical machine learning methods using benchmark datasets from our previously reported cncRNAdb project. Moreover, to obtain independent in-house datasets for robust testing, mass spectrometry proteomics combined with RNA-seq and Ribo-seq were applied in four leukaemia cell lines, which further confirmed that LncReader achieved the best performance compared to other tools. Therefore, LncReader provides an accurate and practical tool that enables fast dual functional lncRNA identification.

RNA Nanostructures: From Structure to Function

Nucleic-acid nanostructures, which have been designed and constructed with atomic precision, have been used as scaffolds for different molecules and proteins, as nanomachines, as computational components, and more. In particular, RNA has garnered tremendous interest as a building block for the self-assembly of sophisticated and functional nanostructures by virtue of its ease of synthesis by in vivo or in vitro transcription, its superior mechanical and thermodynamic properties, and its functional roles in nature. In this Topical Review, we describe recent developments in the use of RNA for the design and construction of nanostructures. We discuss the differences between RNA and DNA that make RNA attractive as a building block for the construction of nucleic-acid nanostructures, and we present the uses of different nanostructures─RNA alone, RNA-DNA, and functional RNA nanostructures.

Elastic Fluorescent Protein-Based Down-Converting Optical Films for Flexible Display

Protein-based material design provides great advantages to developing smart biomaterials with tunable structures and desired functions. They have been widely used in many biomedical applications including tissue engineering and drug delivery. However, protein-based materials are not yet widely used in optoelectronic materials despite their excellent optical and tunable mechanical properties. Here, we synthesized engineered fluorescent proteins (FPs) fused with elastic protein for the development of optoelectrical down-converting optical filters for flexible display materials. We synthesized sequence-specific FPs to tune blue, green, yellow, and red colors and fused them with elastic protein to tune mechanical properties. We fabricated flexible self-supporting film materials and characterized mechanical properties and down-converting optical properties. We also fabricated a hybrid light-emitting diode (LED) to down convert blue to desired green, red, and white colors. Furthermore, we constructed a flexible white LED using organic LED as a flexible substrate. Our modular synthesis approach of tunable bio-optoelectrical material approaches will be useful to design future biocompatible and flexible display materials and technologies.

Integrative proteomics and metabolomics profiling to understand the biochemical basis of beef muscle darkening at a slightly elevated pH

Previous studies investigated the biochemical basis of dark-cutting conditions at elevated muscle pH (above 6), but the molecular basis at slightly above normal pH (between 5.6 and 5.8) is still unclear. The objective was to determine protein and metabolite profiles to elucidate postmortem muscle darkening at slightly elevated pH. Loins were selected based on the criteria established in our laboratory before sample collections, such as pH less than 5.8, L* values (muscle lightness) less than 38, and not discounted by the grader (high-pH beef with dark color are discounted and not sold in retail stores). Six bright red loins (longissimus lumborum) at normal-pH (average pH = 5.57) and six dark-colored strip loins at slightly elevated pH (average pH = 5.70) from A maturity carcasses were obtained within 72-h postmortem from a commercial beef purveyor. Surface color, oxygen consumption, metmyoglobin reducing activity, protein, and metabolite profiles were determined on normal-pH and dark-colored steaks at slightly elevated pH. Enzymes related to glycogen metabolism and glycolytic pathways were more differently abundant than metabolites associated with these pathways. The results indicated that oxygen consumption and metmyoglobin reducing activity were greater (P < 0.05) in darker steaks than normal-pH steaks. Enzymes involved with glycogen catabolic pathways and glycogen storage disease showed lower abundance in dark beef. The tricarboxylic acid metabolite, aconitic acid, was overabundant in darker-colored beef than normal-pH beef, but glucose derivative metabolites were less abundant. The majority of glycogenolytic proteins and metabolites reported as overabundant in the previous dark-cutting studies at high pH (>6.4) also did not show significant differences in the current study. Therefore, our data suggest enzymes involved in glycogen metabolism, in part, create a threshold for muscle darkening than metabolites.

RNA-targeting strategies as a platform for ocular gene therapy

Genetic medicine is offering hope as new therapies are emerging for many previously untreatable diseases. The eye is at the forefront of these advances, as exemplified by the approval of Luxturna® by the United States Food and Drug Administration (US FDA) in 2017 for the treatment of one form of Leber Congenital Amaurosis (LCA), an inherited blindness. Luxturna® was also the first in vivo human gene therapy to gain US FDA approval. Numerous gene therapy clinical trials are ongoing for other eye diseases, and novel delivery systems, discovery of new drug targets and emerging technologies are currently driving the field forward. Targeting RNA, in particular, is an attractive therapeutic strategy for genetic disease that may have safety advantages over alternative approaches by avoiding permanent changes in the genome. In this regard, antisense oligonucleotides (ASO) and RNA interference (RNAi) are the currently popular strategies for developing RNA-targeted therapeutics. Enthusiasm has been further fuelled by the emergence of clustered regularly interspersed short palindromic repeats (CRISPR)-CRISPR associated (Cas) systems that allow targeted manipulation of nucleic acids. RNA-targeting CRISPR-Cas systems now provide a novel way to develop RNA-targeted therapeutics and may provide superior efficiency and specificity to existing technologies. In addition, RNA base editing technologies using CRISPR-Cas and other modalities also enable precise alteration of single nucleotides. In this review, we showcase advances made by RNA-targeting systems for ocular disease, discuss applications of ASO and RNAi technologies, highlight emerging CRISPR-Cas systems and consider the implications of RNA-targeting therapeutics in the development of future drugs to treat eye disease.

Bottom-Up Synthetic Biology Using Cell-Free Protein Synthesis

Technical advances in biotechnology have greatly accelerated the development of bottom-up synthetic biology. Unlike top-down approaches, bottom-up synthetic biology focuses on the construction of a minimal cell from scratch and the application of these principles to solve challenges. Cell-free protein synthesis (CFPS) systems provide minimal machinery for transcription and translation, from either a fractionated cell lysate or individual purified protein elements, thus speeding up the development of synthetic cell projects. In this review, we trace the history of the cell-free technique back to the first in vitro fermentation experiment using yeast cell lysate. Furthermore, we summarized progresses of individual cell mimicry modules, such as compartmentalization, gene expression regulation, energy regeneration and metabolism, growth and division, communication, and motility. Finally, current challenges and future perspectives on the field are outlined.

Intercepting biological messages: Antibacterial molecules targeting nucleic acids during interbacterial conflicts

Bacteria live in polymicrobial communities and constantly compete for resources. These organisms have evolved an array of antibacterial weapons to inhibit the growth or kill competitors. The arsenal comprises antibiotics, bacteriocins, and contact-dependent effectors that are either secreted in the medium or directly translocated into target cells. During bacterial antagonistic encounters, several cellular components important for life become a weak spot prone to an attack. Nucleic acids and the machinery responsible for their synthesis are well conserved across the tree of life. These molecules are part of the information flow in the central dogma of molecular biology and mediate long- and short-term storage for genetic information. The aim of this review is to summarize the diversity of antibacterial molecules that target nucleic acids during antagonistic interbacterial encounters and discuss their potential to promote the emergence antibiotic resistance.

Protein dynamics: The future is bright and complicated!

Biological life depends on motion, and this manifests itself in proteins that display motion over a formidable range of time scales spanning from femtoseconds vibrations of atoms at enzymatic transition states, all the way to slow domain motions occurring on micro to milliseconds. An outstanding challenge in contemporary biophysics and structural biology is a quantitative understanding of the linkages among protein structure, dynamics, and function. These linkages are becoming increasingly explorable due to conceptual and methodological advances. In this Perspective article, we will point toward future directions of the field of protein dynamics with an emphasis on enzymes. Research questions in the field are becoming increasingly complex such as the mechanistic understanding of high-order interaction networks in allosteric signal propagation through a protein matrix, or the connection between local and collective motions. In analogy to the solution to the "protein folding problem," we argue that the way forward to understanding these and other important questions lies in the successful integration of experiment and computation, while utilizing the present rapid expansion of sequence and structure space. Looking forward, the future is bright, and we are in a period where we are on the doorstep to, at least in part, comprehend the importance of dynamics for biological function.

Lichtgesteuerte Translation von mRNA in Eukaryoten

Messenger RNA (mRNA) shows great potential for medical applications, as recently demonstrated by the mRNA-based vaccines against the coronavirus. In addition, it has long been used for ectopic gene expression in cells and model organisms. While numerous methodologies are available for controlling gene expression at the level of transcription, approaches to control translation are scarce. Here we review strategies for direct light-mediated activation of mRNA translation via photocleavable groups and their potential to achieve spatial and temporal control of protein production.

Strategy for RNA-Seq Experimental Design and Data Analysis

Ribonucleic acids (RNAs) are fundamental molecules that control regulation and expression of the genome and therefore the function of a cell. Robust analysis and quantification of RNA transcripts hold critical importance in understanding cell function, altered phenotypes in different biological context, for understanding and targeting diseases. The development of RNA-sequencing (RNA-Seq) now provides opportunities to analyze the expression and function of RNA molecules at an unprecedented scale. However, the strategy for RNA-Seq experimental design and data analysis can substantially differ depending on the biological application. The design choice could also have significant impact for downstream results and interpretation of data. Here we describe key critical considerations required for RNA-Seq experimental design and also describe a step-by-step bioinformatics workflow detailing the different steps required for RNA-Seq data analysis. We believe this article will be a valuable guide for designing and analyzing RNA-Seq data to address a wide range of different biological questions.

Potential Impact of Preoperative Circulating Biomarkers on Individual Escalating/de-Escalating Strategies in Early Breast Cancer

The research on non-invasive circulating biomarkers to guide clinical decision is in wide expansion, including the earliest disease settings. Several new intensification/de-intensification strategies are approaching clinical practice, personalizing the treatment for each patient. Moreover, liquid biopsy is revealing its potential with multiple techniques and studies available on circulating biomarkers in the preoperative phase. Inflammatory circulating cells, circulating tumor cells (CTCs), cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), and other biological biomarkers are improving the armamentarium for treatment selection. Defining the escalation and de-escalation of treatments is a mainstay of personalized medicine in early breast cancer. In this review, we delineate the studies investigating the possible application of these non-invasive tools to give a more enlightened approach to escalating/de-escalating strategies in early breast cancer.

Epitranscriptome changes triggered by ammonium nutrition regulate the proteome response of maritime pine roots

Epitranscriptome constitutes a gene expression checkpoint in all living organisms. Nitrogen is an essential element for plant growth and development that influences gene expression at different levels such as epigenome, transcriptome, proteome, and metabolome. Therefore, our hypothesis is that changes in the epitranscriptome may regulate nitrogen metabolism. In this study, epitranscriptomic modifications caused by ammonium nutrition were monitored in maritime pine roots using Oxford Nanopore Technology. Transcriptomic responses mainly affected transcripts involved in nitrogen and carbon metabolism, defense, hormone synthesis/signaling, and translation. Global detection of epitranscriptomic marks was performed to evaluate this posttranscriptional mechanism in un/treated seedlings. Increased N⁶-methyladenosine (m⁶A) deposition in the 3'-UTR was observed in response to ammonium, which seems to be correlated with poly(A) lengths and changes in the relative abundance of the corresponding proteins. The results showed that m⁶A deposition and its dynamics seem to be important regulators of translation under ammonium nutrition. These findings suggest that protein translation is finely regulated through epitranscriptomic marks likely by changes in mRNA poly(A) length, transcript abundance and ribosome protein composition. An integration of multiomics data suggests that the epitranscriptome modulates responses to nutritional, developmental and environmental changes through buffering, filtering, and focusing the final products of gene expression.

RNA-guided DNA base damage repair via DNA polymerase-mediated nick translation

DNA repair is mediated by DNA synthesis guided by a DNA template. Recent studies have shown that DNA repair can also be accomplished by RNA-guided DNA synthesis. However, it remains unknown how RNA can guide DNA synthesis to repair DNA damage. In this study, we revealed the molecular mechanisms underlying RNA-guided DNA synthesis and base damage repair mediated by human repair DNA polymerases. We showed that pol β, pol κ, and pol ι predominantly synthesized one nucleotide, and pol η, pol ν, and pol θ synthesized multi-nucleotides during RNA-guided DNA base damage repair. The steady-state kinetics showed that pol η exhibited more efficient RNA-guided DNA synthesis than pol β. Using molecular dynamics simulation, we further revealed dynamic conformational changes of pol β and pol η and their structural basis to accommodate the RNA template and misoriented triphosphates of an incoming nucleotide. We demonstrated that RNA-guided base damage repair could be accomplished by the RNA-guided DNA strand-displacement synthesis and nick translation leading to nick ligation in a double-strand DNA region. Our study revealed a novel RNA-guided base damage repair pathway during transcription and DNA replication.

Biological soft matter: intrinsically disordered proteins in liquid-liquid phase separation and biomolecular condensates

The facts that many proteins with crucial biological functions do not have unique structures and that many biological processes are compartmentalized into the liquid-like biomolecular condensates, which are formed via liquid-liquid phase separation (LLPS) and are not surrounded by the membrane, are revolutionizing the modern biology. These phenomena are interlinked, as the presence of intrinsic disorder represents an important requirement for a protein to undergo LLPS that drives biogenesis of numerous membrane-less organelles (MLOs). Therefore, one can consider these phenomena as crucial constituents of a new IDP-LLPS-MLO field. Furthermore, intrinsically disordered proteins (IDPs), LLPS, and MLOs represent a clear link between molecular and cellular biology and soft matter and condensed soft matter physics. Both IDP and LLPS/MLO fields are undergoing explosive development and generate the ever-increasing mountain of crucial data. These new data provide answers to so many long-standing questions that it is difficult to imagine that in the very recent past, protein scientists and cellular biologists operated without taking these revolutionary concepts into account. The goal of this essay is not to deliver a comprehensive review of the IDP-LLPS-MLO field but to provide a brief and rather subjective outline of some of the recent developments in these exciting fields.

Knowledge mapping of alternative splicing of cancer from 2012 to 2021: A bibliometric analysis

Background

As a processing method of RNA precursors, alternative splicing (AS) is critical to normal cellular activities. Aberrant AS events are associated with cancer development and can be promising targets to treat cancer. However, no detailed and unbiased study describes the current state of AS of cancer research. We aim to measure and recognize the current state and trends of AS cancer research in this study.

Methods

The Web of Science Core Collection was used to acquire the articles. Utilizing three bibliometric tools (CiteSpace, VOSviewer, R-bibliometrix), we were able to measure and recognize the influence and collaboration data of individual articles, journals, and co-citations. Analysis of co-occurrence and burst information helped us identify the trending research areas related to AS of cancer.

Results

From 2012 to 2021, the total number of papers on AS of cancer published in 766 academic journals was 3,507, authored by 20,406 researchers in 405 institutions from 80 countries/regions. Research involving AS of cancer genes was primarily conducted in the United States and China; simultaneously, the Chinese Academy of Sciences, Fudan University, and National Cancer Institute were the institutions with strong research capabilities. Scorilas Andreas is the scholar with the most publications, while the most co-citations were generated by Wang, Eric T. Plos One published the most papers on AS of cancer, while J Biol Chem was the most co-cited academic journal in this field. The results of keyword co-occurrence analysis can be divided into three types: molecular (P53, CD44, androgen receptor, srsf3, esrp1), pathological process (apoptosis, EMT, metastasis, angiogenesis, proliferation), and disease (breast cancer, colorectal cancer, prostate cancer, hepatocellular carcinoma, gastric cancer).

Conclusion

Research on AS of cancer has been increasing in intensity over the past decade. Current AS of cancer studies focused on the hallmarks of AS in cancer and AS signatures including diagnostic and therapeutic targets. Among them, the current trends are splicing factors regulating epithelial-mesenchymal transition and other hallmarks, aberrant splicing events in tumors, and further mechanisms. These might give researchers interested in this field a forward-looking perspective and inform further research.

Engineering exosomes for bone defect repair

Currently, bone defect repair is still an intractable clinical problem. Numerous treatments have been performed, but their clinical results are unsatisfactory. As a key element of cell-free therapy, exosome is becoming a promising tool of bone regeneration in recent decades, because of its promoting osteogenesis and osteogenic differentiation function in vivo and in vitro. However, low yield, weak activity, inefficient targeting ability, and unpredictable side effects of natural exosomes have limited the clinical application. To overcome the weakness, various approaches have been applied to produce engineering exosomes by regulating their production and function at present. In this review, we will focus on the engineering exosomes for bone defect repair. By summarizing the exosomal cargos affecting osteogenesis, the strategies of engineering exosomes and properties of exosome-integrated biomaterials, this work will provide novel insights into exploring advanced engineering exosome-based cell-free therapy for bone defect repair.

Optimization and compartmentalization of a cell-free mixture of DNA amplification and protein translation

Recent studies have shown that the reconstituted cell-free DNA replisome and in vitro transcription and translation systems from Escherichia coli are highly important in applied and synthetic biology. To date, no attempt has been made to combine those two systems. Here, we study the performance of the mixed two separately exploited systems commercially available as RCR and PURE systems. Regarding the genetic information flow from DNA to proteins, mixtures with various ratios of RCR/PURE gave low protein expression, possibly due to the well-known conflict between replication and transcription or inappropriate buffer conditions. To further increase the compatibility of the two systems, rationally designed reaction buffers with a lower concentration of nucleoside triphosphates in 50 mM HEPES (pH7.6) were evaluated, showing increased performance from RCR/PURE (85%/15%) in a time-dependent manner. The compatibility was also validated in compartmentalized cell-sized droplets encapsulating the same RCR/PURE soup. Our findings can help to better fine-tune the reaction conditions of RCR-PURE systems and provide new avenues for rewiring the central dogma of molecular biology as self-sustaining systems in synthetic cell models. KEY POINTS: • Commercial reconstituted DNA amplification (RCR) and transcription and translation (PURE) systems hamper each other upon mixing. • A newly optimized buffer with a low bias for PURE was formulated in the RCR-PURE mixture. • The performance and dynamics of RCR-PURE were investigated in either bulk or compartmentalized droplets.

Relative importance of genotype, gene expression, and DNA methylation on complex traits in perennial ryegrass

The growing demand for food and feed crops in the world because of growing population and more extreme weather events requires high-yielding and resilient crops. Many agriculturally important traits are polygenic, controlled by multiple regulatory layers, and with a strong interaction with the environment. In this study, 120 F₂ families of perennial ryegrass (Lolium perenne L.) were grown across a water gradient in a semifield facility with subsoil irrigation. Genomic (single-nucleotide polymorphism [SNP]), transcriptomic (gene expression [GE]), and DNA methylomic (MET) data were integrated with feed quality trait data collected from control and drought sections in the semifield facility, providing a treatment effect. Deep root length (DRL) below 110 cm was assessed with convolutional neural network image analysis. Bayesian prediction models were used to partition phenotypic variance into its components and evaluated the proportion of phenotypic variance in all traits captured by different regulatory layers (SNP, GE, and MET). The spatial effects and effects of SNP, GE, MET, the interaction between GE and MET (GE × MET) and GE × treatment (GE_Control and GE_Drought ) interaction were investigated. Gene expression explained a substantial part of the genetic and spatial variance for all the investigated phenotypes, whereas MET explained residual variance not accounted for by SNPs or GE. For DRL, MET also contributed to explaining spatial variance. The study provides a statistically elegant analytical paradigm that integrates genomic, transcriptomic, and MET information to understand the regulatory mechanisms of polygenic effects for complex traits.

N6-methyladenosine Modification of Noncoding RNAs: Mechanisms and Clinical Applications in Cancer

N6-methyladenosine (m6A) modification remains the most pivotal epigenetic modification on RNA. As we know, m6A not only affects physiological processes but is also involved in carcinoma. Noncoding RNAs play an indispensable role in the occurrence and development of carcinoma. However, a large amount of research is focused on mRNA currently. Insufficient research has been done on the relationship between noncoding RNA (ncRNA) methylation and cancer. Therefore, this review aims to introduce the theoretical knowledge of m6A modification in noncoding RNA, discuss its function in tumorigenesis and progression, and ultimately summarize its potential clinical applications.

Circ_0007534 as new emerging target in cancer: Biological functions and molecular interactions

Circular RNA (circRNAs), an important member of the non-coding RNA (ncRNA) family, are widely expressed in a variety of biological cells. Owing to their stable structures, sequence conservations, and cell- or tissue-specific expressions, these RNA have become a popular subject of scientific research. With the development of sequencing methods, it has been revealed that circRNAs exert their biological function by sponging microRNAs (miRNAs), regulating transcription, or binding to proteins. Humans have historically been significantly impacted by various types of cancer. Studies have shown that circRNAs are abnormally expressed in various cancers and are involved in the occurrence and development of malignant tumors, such as tumor cell proliferation, migration, and invasion. As one of its star molecules, circ_0007534 is upregulated in colorectal, cervical, and pancreatic cancers; is closely related to the occurrence, development, and prognosis of tumors; and is expected to become a novel tumor marker and therapeutic target. This article briefly reviews the expression and mechanism of circ_0007534 in malignant tumors based on the domestic and foreign literature.

Emerging Role of Interferon-Induced Noncoding RNA in Innate Antiviral Immunity

Thousands of unique noncoding RNAs (ncRNAs) exist within the genomes of higher eukaryotes. Upon virus infection, the host generates interferons (IFNs), which initiate the expression of hundreds of interferon-stimulated genes (ISGs) through IFN receptors on the cell surface, establishing a barrier as the host's antiviral innate immunity. With the development of novel RNA-sequencing technology, many IFN-induced ncRNAs have been identified, and increasing attention has been given to their functions as regulators involved in the antiviral innate immune response. IFN-induced ncRNAs regulate the expression of viral proteins, IFNs, and ISGs, as well as host genes that are critical for viral replication, cytokine and chemokine production, and signaling pathway activation. This review summarizes the complex regulatory role of IFN-induced ncRNAs in antiviral innate immunity from the above aspects, aiming to improve understanding of ncRNAs and provide reference for the basic research of antiviral innate immunity.

Interactions of small molecules with DNA junctions

The four natural DNA bases (A, T, G and C) associate in base pairs (A=T and G≡C), allowing the attached DNA strands to assemble into the canonical double helix of DNA (or duplex-DNA, also known as B-DNA). The intrinsic supramolecular properties of nucleobases make other associations possible (such as base triplets or quartets), which thus translates into a diversity of DNA structures beyond B-DNA. To date, the alphabet of DNA structures is ripe with approximately 20 letters (from A- to Z-DNA); however, only a few of them are being considered as key players in cell biology and, by extension, valuable targets for chemical biology intervention. In the present review, we summarise what is known about alternative DNA structures (what are they? When, where and how do they fold?) and proceed to discuss further about those considered nowadays as valuable therapeutic targets. We discuss in more detail the molecular tools (ligands) that have been recently developed to target these structures, particularly the three- and four-way DNA junctions, in order to intervene in the biological processes where they are involved. This new and stimulating chemical biology playground allows for devising innovative strategies to fight against genetic diseases.

DNA opening during transcription initiation by RNA polymerase II in atomic detail

RNA polymerase II (RNAP II) synthesizes RNA by reading the DNA code. During transcription initiation, RNAP II opens the double-stranded DNA to expose the DNA template to the active site. The molecular interactions driving and controlling DNA opening are not well understood. We used all-atom steered molecular dynamics simulations to derive a continuous pathway of DNA opening in human RNAP II, involving a 55 Å DNA strand displacement and a nearly 360° DNA helix rotation. To drive such large-scale transitions, we used a combination of RMSD-based collective variables, a newly designed rotational coordinate, and a path collective variable. The simulations reveal extensive interactions of the DNA with three conserved protein loops near the active site, namely with the rudder, fork loop 1, and fork loop 2. According to the simulations, DNA-protein interactions support DNA opening by a twofold mechanism; they catalyze DNA opening by attacking Watson-Crick hydrogen bonds, and they stabilize the open DNA bubble by the formation of a wide set of DNA-protein salt bridges.

Clinical detection, diagnosis and treatment of morphological abnormalities of sperm flagella: A review of literature

Sperm carries male genetic information, and flagella help move the sperm to reach oocytes. When the ultrastructure of the flagella is abnormal, the sperm is unable to reach the oocyte and achieve insemination. Multiple morphological abnormalities of sperm flagella (MMAF) is a relatively rare idiopathic condition that is mainly characterized by multiple defects in sperm flagella. In the last decade, with the development of high-throughput DNA sequencing approaches, many genes have been revealed to be related to MMAF. However, the differences in sperm phenotypes and reproductive outcomes in many cases are attributed to different pathogenic genes or different pathogenic mutations in the same gene. Here, we will review information about the various phenotypes resulting from different pathogenic genes, including sperm ultrastructure and encoding proteins with their location and functions as well as assisted reproductive technology (ART) outcomes. We will share our clinical detection and diagnosis experience to provide additional clinical views and broaden the understanding of this disease.