BioEssays最新文献

With the advent of gene editing technologies like CRISPR/Cas9, it has become possible to edit genomic regions of interest for research and therapeutic purposes. These technologies have also been adapted to alter gene expression without changing their DNA sequence, allowing epigenetic edits. While genetic editors make edits by cutting the genome at specified regions, epigenetic editors leverage the same targeting mechanism but act based on the epigenetic modifier fused to them, such as a methyltransferase. Here, we discuss two recently employed epigenetic editors (epi-editors) that silenced target genes involved in disease to mitigate their effects. Neumann et al. reported the construction of an epigenetic editor called CHARM that could methylate and silence the prion gene in mouse brains and subsequently switch itself off. Additionally, Capelluti et al. developed an epi-editor called EvoETR that knocked down Pcsk9 in the murine liver to reduce LDL levels. We aim to highlight the design principles underlying the design of these epi-editors to inform future editor designs.

The genome sequencing revolution has revealed that all species possess a large number of unique genes critical for trait variation, adaptation, and evolutionary innovation. One widely used approach to identify such genes consists of detecting protein-coding sequences with no homology in other genomes, termed orphan genes. These genes have been extensively studied, under the assumption that they represent valid proxies for species-specific genes. Here, we critically evaluate taxonomic, phylogenetic, and sequence evolution evidence showing that orphan genes belong to a range of evolutionary ages and thus cannot be assigned to a single lineage. Furthermore, we show that the processes generating orphan genes are substantially more diverse than generally thought and include horizontal gene transfer, transposable element domestication, and overprinting. Thus, orphan genes represent a heterogeneous collection of genes rather than a single biological entity, making them unsuitable as a subject for meaningful investigation of gene evolution and phenotypic innovation.

Fanconi anemia (FA) is generally classified as a DNA repair disorder, conferring a genetic predisposition to cancer and prominent bone marrow failure (BMF) in early childhood. Corroborative human and murine studies point to a fetal origin of hematopoietic stem cell (HSC) attrition under replicative stress. Along with intriguing recent insights into non-canonical roles and domain-specific functions of FA proteins, these studies have raised the possibility of a DNA repair-independent BMF etiology. However, deeper mechanistic insight is critical as current curative options of allogeneic stem cell transplantation and emerging gene therapy have limited eligibility, carry significant side effects, and involve complex procedures restricted to resource-rich environments. To develop rational and broadly accessible therapies for FA patients, the field will need more faithful disease models that overcome the scarcity of patient samples, leverage technological advances, and adopt investigational clinical trial designs tailored for rare diseases.

Plants are in intimate association with taxonomically structured microbial communities called the plant microbiota. There is growing evidence that the plant microbiota contributes to the holistic performance and general health of plants, especially under unfavorable situations. Despite the attached benefits, surprisingly, the plant microbiota in nature also includes potentially pathogenic strains, signifying that the plant hosts have tight control over these microbes. Despite the conceivable role of plant immunity in regulating its microbiota, we lack a complete understanding of its role in governing the assembly, maintenance, and function of the plant microbiota. Here, we highlight the recent progress on the mechanistic relevance of host immunity in orchestrating plant-microbiota dialogues and discuss the pluses and perils of these microbial assemblies.

The performance of deep Neural Networks (NNs) in the text (ChatGPT) and image (DALL-E2) domains has attracted worldwide attention. Convolutional NNs (CNNs), Large Language Models (LLMs), Denoising Diffusion Probabilistic Models (DDPMs)/Noise Conditional Score Networks (NCSNs), and Graph NNs (GNNs) have impacted computer vision, language editing and translation, automated conversation, image generation, and social network management. Proteins can be viewed as texts written with the alphabet of amino acids, as images, or as graphs of interacting residues. Each of these perspectives suggests the use of tools from a different area of deep learning for protein structural biology. Here, I review how CNNs, LLMs, DDPMs/NCSNs, and GNNs have led to major advances in protein structure prediction, inverse folding, protein design, and small molecule design. This review is primarily intended as a deep learning primer for practicing experimental structural biologists. However, extensive references to the deep learning literature should also make it relevant to readers who have a background in machine learning, physics or statistics, and an interest in protein structural biology.

A recent thought-provoking theory argues that complex organisms using epigenetic information for their normal development and functioning must irreversibly age as a result of epigenetic signal loss. Importantly, the scope of this theory could be considerably expanded, with scientific benefits, by analyzing epigenetic ageing beyond the borders of the Tree of Life. Viruses that use epigenetic signals for their normal functioning may also age, that is, present an increasing risk of failing to complete their individual life cycle and to disappear with time. As viruses are ancient, abundant, and infect a considerable diversity of hosts, the ageing virus hypothesis, if verified, would have important consequences for many fields of the Life sciences. Uncovering ageing viruses would integrate the most abundant and biologically central entities on Earth into theories of ageing, enhance virology, gerontology, evolutionary biology, molecular ecology, genomics, and possibly medicine through the development of new therapies manipulating viral ageing.