ABSTRACT Retroviruses and retrotransposons, collectively referred to here as retroelements, rely on reverse transcription for their propagation. These elements play important roles in viral infection, genome evolution, gene regulation, and disease. Human immunodeficiency virus type 1 (HIV‐1) and long interspersed nuclear element‐1 (LINE‐1) represent two well‐characterized systems, whereas endogenous retroviruses (ERVs) provide additional insights into the regulation of retroelement‐derived RNAs. Beyond element‐encoded proteins, host RNA‐binding proteins (RBPs) regulate multiple stages of retroelement RNA metabolism, including RNA processing, localization, translation, stability, and ribonucleoprotein (RNP) assembly, thereby influencing productive propagation or restriction. In this review, we use an RNP‐state framework to compare how RBPs and related RNA‐associated factors regulate HIV‐1 and LINE‐1, from early RNA processing and RNP assembly to reverse transcription, innate immune sensing, nuclear trafficking, and genome integration or insertion. We also incorporate evidence from ERVs and other retroviral systems, including human T‐cell leukemia virus type 1 (HTLV‐1), Moloney murine leukemia virus (MLV), and foamy viruses. Finally, we discuss experimental approaches for investigating RBP–retroelement interactions and highlight outstanding questions concerning RBP specificity, biomolecular condensates, context‐dependent regulation, evolutionary conservation, and potential therapeutic applications.
ABSTRACT Fecal virome transplantation (FVT) is an emerging microbiome‐based intervention that transfers donor‐derived virus‐like particles, predominantly phages, while minimizing the transfer of viable donor bacteria. By modifying interactions between phages and their bacterial hosts, FVT may reshape recipient bacterial communities and thereby influence microbial metabolism and host immune responses. Current evidence supports the biological plausibility of this approach but does not yet demonstrate consistent therapeutic efficacy. Human studies remain few and heterogeneous, with mixed efficacy findings and insufficient evidence to establish long‐term safety. Preclinical studies suggest potential effects on metabolic, inflammatory and early‐life intestinal phenotypes, whereas evidence in livestock remains preliminary. Major knowledge gaps include inconsistent definitions and preparation methods, incomplete demonstration of viral sufficiency, uncertain engraftment and relationships between dose and response, compatibility between donors and recipients, and the potential transfer or mobilization of undesirable genetic material. This mini‐review summarizes the biological rationale and current evidence for FVT, evaluates methodological challenges and difficulties in establishing causality, and discusses the standardization and safety requirements needed to advance interventions based on the virome in human medicine and animal agriculture.
ABSTRACT Meat quality is a critical economic trait in ruminant production because it directly influences consumer acceptability, market value, and the long‐term sustainability of the livestock industry. Amino acids (AAs) have traditionally been regarded primarily as substrates for protein synthesis. However, growing evidence indicates that they also regulate multiple aspects of meat quality. Given the increasing demand for high‐quality ruminant meat and the growing interest in nutritional regulation of carcass traits, this review synthesizes current evidence on how functional amino acids (FAAs) modulate meat quality in ruminants, including cattle, sheep, and goats. We first summarize the core indicators of meat quality—including color, water‐holding capacity, tenderness, marbling, and flavor—and the current understanding of how these attributes are regulated by AA metabolism. We then review the specific effects and underlying mechanisms of key FAAs and their derivatives in ruminants: Lysine improves carcass leanness and nitrogen utilization efficiency; methionine enhances antioxidant capacity and exerts programming effects on fetal development; tryptophan regulates stress responses and digestive physiology via neuroendocrine pathways; branched‐chain amino acids (BCAAs) activate the mTOR signaling pathway and promote muscle protein synthesis; glutamate and glutamine support intestinal health, immunity, and reproductive performance; arginine and its derivatives (citrulline, guanidinoacetic acid, and N‐carbamoylglutamate) regulate vasodilation, energy metabolism, and endogenous arginine synthesis; and other functional AAs (glycine, serine, β‐alanine, histidine, betaine, and taurine) contribute to collagen stability, methyl‐group metabolism, meat color stability, and antioxidant defense. We further discuss strategies for practical application, including rumen‐protected delivery technologies, utilization of sustainable forage resources, and systematic evaluation of AA requirements for precision supplementation. Collectively, this review highlights the mechanisms through which FAAs regulate meat quality and identifies key research gaps and future directions in this field. The synthesized evidence provides a theoretical basis for developing nutritional strategies that simultaneously improve meat quality, production efficiency, and environmental sustainability in ruminant production systems.
ABSTRACT Accurate and scalable evaluation of gene‐editing efficiency is crucial for the development of novel editing tools. However, conventional methods are laborious, costly, and low‐throughput. Here, we developed an artificial intelligence (AI)‐driven fluorescent reporter (AR) platform, an integrated system that automates and streamlines the entire evaluation workflow. The AR platform combines an enhanced fluorescent reporter with an AI‐driven analytical pipeline. The dual‐fluorescence reporter system, in which mCherry carrying a PEST domain is paired with GFP, supports Cas variants with diverse PAM requirements and quantifies editing efficiency as the proportion of GFP‐only cells. The platform's AI module, EasyReporter, integrates a deep learning model for automated cell segmentation and quantification with a large language model (LLM)‐based agent for intelligent data interpretation and comprehensive report generation. Editing efficiencies measured by AR correlated with those measured by flow cytometry (Spearman ρ = 0.77) and amplicon sequencing (Spearman ρ = 0.83). The AR platform provides a high‐throughput and automated workflow that accelerates gene‐editing research. In the future, it will be particularly effective for quantifying the efficiency of large‐fragment gene editing, offering a new framework for AI‐empowered biological laboratories.
