Cell systems最新文献

Robust and stable expression of genes of interest is crucial for studying and engineering biology. While expressing desired gene products in some microorganisms is well established, achieving stable expression in mammalian systems is still a complex task. Over the years, various methods have been developed to integrate transgenes into mammalian cells, including the use of viral vectors, transposases, nucleases, and recombinases. This review aims to provide an overview of some of the commonly used integration strategies in mammalian cells, with a particular focus on methods toward site-specific integration, highlighting respective advantages and limitations and providing a summary of recent advances. Additionally, it also explores some of the challenges in the field, offering insights into potential directions for future development.

Mammalian cells utilize intercellular signals to regulate physiological processes such as development and homeostasis. Synthetic signaling systems emulate these processes using orthogonal signals like small molecules, which offer benefits including rapid diffusion, controllability, and reduced immunogenicity compared with proteins. However, prior synthetic small molecule systems exhibited limited sensitivity (50% effective concentrations [EC₅₀] > 10^-7 mol/L) and imposed high metabolic burdens due to precursor biosynthesis. To address this, we engineered a super-sensitive (EC₅₀ ∼10^-9 mol/L) and low-burden cell-cell communication platform comprising de novo designed sender, receiver, and degrader modules. The sender produces signal molecules from the endogenous amino acid phenylalanine, the receiver integrates cis-regulatory elements from genomic data and AI-assisted trans-regulatory factor optimization to minimize leakage, and the degrader employs screened enzymes for highly efficient signal control. Finally, this precursor-free system facilitates robust, long-range morphogen gradient formation. The intercellular communication system reported herein holds great potential for future applications in tissue engineering.

Protein secretion in mammalian cells is the active transport of proteins from the cytoplasm to the extracellular space. It plays a fundamental role in mammalian physiology and signaling, as well as biotherapeutics production and cell and gene therapies. The efficacy of protein secretion, however, is impacted by features of the secreted protein itself, and the host-cell machinery that supports each step of the secretion process. High-throughput techniques such as microfluidics, cell display, and cell encapsulation assays for the study and engineering of secreted proteins are transforming biomedical knowledge and our ability to modulate protein secretion. In addition, computational advances, including signal peptide modeling, whole-protein machine learning models, and genome-scale simulations, are opening new pathways for rational design of protein secretion. Here, we highlight recent developments in secretion engineering that are leading to the convergence of high-throughput experimentation and machine learning methods and can help address current challenges in bioproduction and support future efforts in cell and gene therapy while enabling new modalities.

The secretory pathway processes >30% of mammalian proteins, orchestrating their synthesis, modification, trafficking, and quality control across multiple organelles via coordinated interactions, making its regulation difficult to decipher. To advance such research, we present secRecon, a reconstruction of the mammalian secretory pathway, comprising 1,127 manually curated genes organized within 77 secretory process terms, annotated with functional roles, subcellular localization, protein interactions, and complexes. Applying secRecon to omics data revealed distinct secretory topologies in antibody-producing plasma cells versus Chinese hamster ovary (CHO) cells, with CHO-specific deficiencies in proteostasis, translocation, and N-glycosylation genes, highlighting targets to enhance secretion. Analysis of single-cell SEC-seq data uncovered diversity in IgG-secreting plasma cells that is shaped by the unfolded protein response, endoplasmic reticulum (ER)-associated degradation, and vesicle trafficking and identified distinct secretory machinery genes as markers of plasma cell differentiation. These results show that secRecon enables the discovery of mechanisms controlling protein secretion and supports applications in both biomedical research and biotechnology. A record of this paper's transparent peer review process is included in the supplemental information.

A key challenge in synthetic biology is achieving durable amplification of low-level inputs in gene regulation systems. Current RNA-based tools primarily operate post-transcriptionally and often yield limited, transient responses. An underexplored feature of lowly expressed long non-coding RNAs (lncRNAs) is their ability to induce outsized effects on chromatin regulation across large genomic regions. Mechanistic insights from basic research are bringing the field closer to designing lncRNAs for epigenetic engineering. We review foundational studies on ectopic expression to uncover lncRNA-mediated epigenetic mechanisms and state-of-the-art transgenic systems for studying lncRNA-driven epigenetic regulation. We present perspectives on strategies for testing the composability of modular lncRNA elements to build rationally designed systems with programmable chromatin-modifying functions and potential biomedical applications such as gene dosage correction. Deepening mechanistic insights into lncRNA function, combined with the development of lncRNA-based technologies for genome regulation, will pave the way for significant advances in cell state control.

Owing to the complexity of living cells, multicellular systems exhibit heterogeneity at both the macro (different cell types) and the micro (molecular states within a cell type) levels. Traditionally, such heterogeneity has challenged the yield and quality of stem cell-derived cell therapy manufacturing. Here, we argue that heterogeneity can instead be harnessed as a design feature in the quality-by-design toolkit to optimize cell therapy yield and quality, thereby improving bioprocess robustness. We propose a framework for mapping input cell state to output cell fate using systems and synthetic biology tools. This framework can be used to define material and critical quality attributes at the molecular level that better predict drug safety and efficacy. By understanding the sources and consequences of heterogeneity, we can harness it to conquer complex cell therapy manufacturing and bring it to the level of robustness currently only achieved for biologics and small molecules.

Synthetic biology offers control over cellular and tissue functions. As it moves beyond microbes into humans, synthetic biology enables precise control over gene expression, cell fate, and tissue organization across heart, lung, blood, and sleep systems. By integrating genome engineering, dynamic gene circuits, and high-dimensional biosensors, these advances support scalable, quantitative models of multicellular biology, expanding the need for systems-level models and integration. We highlight emerging systems such as tunable transcriptional regulators, synthetic organizers, and feedback circuits that bridge molecular control with functional outcomes. Furthermore, by combining omics data with artificial intelligence (AI)-guided circuit design, synthetic biology enables high-resolution cellular and tissue-scale models of development, cellular interactions, drug development, gene therapy, and therapeutic response. Key challenges remain-including delivery, transgene stability, and robust spatiotemporal control in physiologically relevant models. This perspective synthesizes field-spanning progress and defines shared priorities for engineering cells and tissues that function reliably across dynamic, multi-organ environments.

DIAL is a novel framework for temporal control of transcript abundances in engineered cells. Targeted excision of DNA spacers in transgenic promoters permits controlled transitions of protein expression between setpoints. DIAL expands the repertoire of bioengineering tools for controlling protein expression, cell fates, and biological systems in general.

Synthetic gene circuits represent a transformative approach in gene- and cell-based therapies, offering dynamic and precise control of therapeutic functions to address the limitations inherent in conventional treatments. Despite significant preclinical advancements, their clinical translation has been predominantly confined to relatively simple circuit designs, with few complex systems progressing into clinical trials. This perspective discusses current clinical applications of synthetic gene circuits, particularly their roles in solid tumor therapy, T cell-mediated immunomodulation, and metabolic disease management. We outline the therapeutic potential of these circuits and address the challenges impeding their clinical applications, including safety, specificity, immunogenicity, and delivery efficiency. To advance translation, we emphasize the importance of the development of humanized animal models, advanced delivery platforms, AI-driven optimization of circuit components, and the strategic selection of clinically target scenarios. Furthermore, we highlight emerging cybergenetics principles-intelligent and programmable genetic control systems-as a cornerstone for future smart living therapeutics and cell-based therapies.