A longstanding challenge in gene therapy is expressing a dosage-sensitive gene within a tight therapeutic window. For example, loss of MECP2 function causes Rett syndrome, while its duplication causes MECP2 duplication syndrome. Viral gene delivery methods generate variable numbers of gene copies in individual cells, creating a need for gene dosage-invariant expression systems. Here, we introduce a compact miRNA-based, incoherent feed-forward loop circuit that achieves precise control of Mecp2 expression in cells and brains, and improves outcomes in an AAV-based mouse model of Rett syndrome gene therapy. Single molecule analysis of endogenous and ectopic Mecp2 mRNA revealed precise, sustained expression across a broad range of gene dosages. Delivered systemically in a brain-targeting AAV capsid, the circuit strongly suppressed Rett behavioral symptoms for over 24 weeks, outperforming an unregulated gene therapy. These results demonstrate that synthetic miRNA-based regulatory circuits can enable precise in vivo expression to improve the safety and efficacy of gene therapy.
", "doi": "10.1101/2024.03.13.584179", "pmcid": "PMC10980028", "issn": "2692-8205", "publisher": "Cold Spring Harbor", "publication": "bioRxiv", "publication_date": "2024-03-14", "pages": "2024.03.13.584179" }, { "id": "authors:9dhkn-8g759", "collection": "authors", "collection_id": "9dhkn-8g759", "cite_using_url": "https://authors.library.caltech.edu/records/9dhkn-8g759", "type": "monograph", "title": "miRNA circuit modules for precise, tunable control of gene expression", "author": [ { "family_name": "Du", "given_name": "Rongrong", "orcid": "0009-0003-4942-3020", "clpid": "Du-Rongrong" }, { "family_name": "Flynn", "given_name": "Michael J.", "orcid": "0009-0003-1186-957X", "clpid": "Flynn-Michael-J" }, { "family_name": "Honsa", "given_name": "Monique", "clpid": "Honsa-Monique" }, { "family_name": "Jungmann", "given_name": "Ralf", "orcid": "0000-0003-4607-3312", "clpid": "Jungmann-Ralf" }, { "family_name": "Elowitz", "given_name": "Michael B.", "orcid": "0000-0002-1221-0967", "clpid": "Elowitz-M-B" } ], "abstract": "The ability to express transgenes at specified levels is critical for understanding cellular behaviors, and for applications in gene and cell therapy. Transfection, viral vectors, and other gene delivery methods produce varying protein expression levels, with limited quantitative control, while targeted knock-in and stable selection are inefficient and slow. Active compensation mechanisms can improve precision, but the need for additional proteins or lack of tunability have prevented their widespread use. Here, we introduce a toolkit of compact, synthetic miRNA-based circuit modules that provide precise, tunable control of transgenes across diverse cell types. These circuits, termed DIMMERs (Dosage-Invariant miRNA-Mediated Expression Regulators) use multivalent miRNA regulatory interactions within an incoherent feed-forward loop architecture to achieve nearly uniform protein expression over more than two orders of magnitude variation in underlying gene dosages or transcription rates. They also allow coarse and fine control of expression, and are portable, functioning across diverse cell types. In addition, a heuristic miRNA design algorithm enables the creation of orthogonal circuit variants that independently control multiple genes in the same cell. These circuits allowed dramatically improved CRISPR imaging, and super-resolution imaging of EGFR receptors with transient transfections. The toolbox provided here should allow precise, tunable, dosage-invariant expression for research, gene therapy, and other biotechnology applications.
", "doi": "10.1101/2024.03.12.583048", "pmcid": "PMC10979901", "issn": "2692-8205", "publisher": "Cold Spring Harbor Laboratory Press", "publication": "bioRxiv", "publication_date": "2024-03-12", "pages": "2024.03.12.583048" }, { "id": "authors:p39kv-fgh08", "collection": "authors", "collection_id": "p39kv-fgh08", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20230725-706037000.28", "type": "monograph", "title": "Lineage motifs: developmental modules for control of cell type proportions", "author": [ { "family_name": "Tran", "given_name": "Martin", "orcid": "0000-0001-9882-7230", "clpid": "Tran-Martin" }, { "family_name": "Askary", "given_name": "Amjad", "orcid": "0000-0002-2913-8498", "clpid": "Askary-Amjad" }, { "family_name": "Elowitz", "given_name": "Michael B.", "orcid": "0000-0002-1221-0967", "clpid": "Elowitz-M-B" } ], "abstract": "In multicellular organisms, cell types must be produced and maintained in appropriate proportions. One way this is achieved is through committed progenitor cells that produce specific sets of descendant cell types. However, cell fate commitment is probabilistic in most contexts, making it difficult to infer progenitor states and understand how they establish overall cell type proportions. Here, we introduce Lineage Motif Analysis (LMA), a method that recursively identifies statistically overrepresented patterns of cell fates on lineage trees as potential signatures of committed progenitor states. Applying LMA to published datasets reveals spatial and temporal organization of cell fate commitment in zebrafish and rat retina and early mouse embryo development. Comparative analysis of vertebrate species suggests that lineage motifs facilitate adaptive evolutionary variation of retinal cell type proportions. LMA thus provides insight into complex developmental processes by decomposing them into simpler underlying modules.", "doi": "10.1101/2023.06.06.543925", "pmcid": "PMC10274800", "publication_date": "2023-06-07" }, { "id": "authors:mt2za-c6023", "collection": "authors", "collection_id": "mt2za-c6023", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20230322-368481000.42", "type": "monograph", "title": "Combinatorial expression motifs in signaling pathways", "author": [ { "family_name": "Granados", "given_name": "Alejandro A.", "orcid": "0000-0002-6275-9800", "clpid": "Granados-Alejandro-A" }, { "family_name": "Kanrar", "given_name": "Nivedita", "clpid": "Kanrar-Nivedita" }, { "family_name": "Elowitz", "given_name": "Michael B.", "orcid": "0000-0002-1221-0967", "clpid": "Elowitz-M-B" } ], "abstract": "Cell-cell signaling pathways comprise sets of variant receptors that are expressed in different combinations in different cell types. This architecture allows one pathway to be used in a variety of configurations, which could provide distinct functional capabilities, such as responding to different ligand variants. While individual pathways have been well-studied, we have lacked a comprehensive understanding of what receptor combinations are expressed and how they are distributed across cell types. Here, combining data from multiple single-cell gene expression atlases, we analyzed the expression profiles of core signaling pathways, including TGF-\u03b2, Notch, Wnt, and Eph-ephrin, as well as non-signaling pathways. In many pathways, a limited set of receptor expression profiles are used recurrently in many distinct cell types. While some recurrent profiles are restricted to groups of closely related cells, others, which we term pathway expression motifs, reappear in distantly related cell types spanning diverse tissues and organs. Motif usage was generally uncorrelated between pathways, remained stable in a given cell type during aging, but could change in sudden punctuated transitions during development. These results suggest a mosaic view of pathway usage, in which the same core pathways can be active in many or most cell types, but operate in one of a handful of distinct modes.", "doi": "10.1101/2022.08.21.504714", "publication_date": "2022-08-22" }, { "id": "authors:a7vwv-mhw66", "collection": "authors", "collection_id": "a7vwv-mhw66", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20220712-283791000", "type": "monograph", "title": "A synthetic protein-level neural network in mammalian cells", "author": [ { "family_name": "Chen", "given_name": "Zibo", "orcid": "0000-0003-2990-2895", "clpid": "Chen-Zibo" }, { "family_name": "Linton", "given_name": "James M.", "clpid": "Linton-James-M" }, { "family_name": "Zhu", "given_name": "Ronghui", "orcid": "0000-0001-8171-482X", "clpid": "Zhu-Ronghui" }, { "family_name": "Elowitz", "given_name": "Michael B.", "orcid": "0000-0002-1221-0967", "clpid": "Elowitz-M-B" } ], "abstract": "Artificial neural networks provide a powerful paradigm for information processing that has transformed diverse fields. Within living cells, genetically encoded synthetic molecular networks could, in principle, harness principles of neural computation to classify molecular signals. Here, we combine de novo designed protein heterodimers and engineered viral proteases to implement a synthetic protein circuit that performs winner-take-all neural network computation. This \"perceptein\" circuit includes modules that compute weighted sums of input protein concentrations through reversible binding interactions, and allow for self-activation and mutual inhibition of protein components using irreversible proteolytic cleavage reactions. Altogether, these interactions comprise a network of 310 chemical reactions stemming from 8 expressed protein species. The complete system achieves signal classification with tunable decision boundaries in mammalian cells. These results demonstrate how engineered protein-based networks can enable programmable signal classification in living cells.", "doi": "10.1101/2022.07.10.499405", "publication_date": "2022-07-12" }, { "id": "authors:ernz6-2xp43", "collection": "authors", "collection_id": "ernz6-2xp43", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20220328-182609385", "type": "monograph", "title": "Periodic spatial patterning with a single morphogen", "author": [ { "family_name": "Wang", "given_name": "Sheng", "clpid": "Wang-Sheng" }, { "family_name": "Garcia-Ojalvo", "given_name": "Jordi", "orcid": "0000-0002-3716-7520", "clpid": "Garcia-Ojalvo" }, { "family_name": "Elowitz", "given_name": "Michael B.", "orcid": "0000-0002-1221-0967", "clpid": "Elowitz-M-B" } ], "abstract": "Multicellular development employs periodic spatial patterning to generate repetitive structures such as digits, vertebrae, and teeth. Turing patterning has long provided a key paradigm for understanding such systems. The simplest Turing systems are believed to require at least two signals, or morphogens, that diffuse and react to spontaneously generate periodic patterns. Here, using mathematical modeling, we show that a minimal circuit comprising an intracellular positive feedback loop and a single diffusible morphogen is sufficient to generate stable, long-range spatially periodic cellular patterns. The model considers cells as discrete entities as a key feature, and incorporates transient boundary conditions. Linear stability analysis reveals that this single-morphogen Turing circuit can support a broad range of spatial wavelengths, including fine-grain patterns similar to those generated by classic lateral inhibition systems. Further, signals emanating from a boundary can initiate and stabilize propagating modes with a well-defined spatial wavelength. Once formed, patterns are self-sustaining and robust to noise. Finally, while noise can disrupt patterning in pre-patterned regions, its disruptive effect can be overcome by a bistable intracellular circuit loop, or by considering patterning in the context of growing tissue. Together, these results show that a single morphogen can be sufficient for robust spatial pattern formation, and should provide a foundation for engineering pattern formation in the emerging field of synthetic developmental biology.", "doi": "10.1101/2022.03.21.484932", "publication_date": "2022-03-22" }, { "id": "authors:qz3hc-zsb05", "collection": "authors", "collection_id": "qz3hc-zsb05", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20210929-151425994", "type": "monograph", "title": "Ratiometric RNA labeling allows dynamic multiplexed analysis of gene circuits in single cells", "author": [ { "family_name": "Xu", "given_name": "Shuhui", "clpid": "Xu-Shuhui" }, { "family_name": "Li", "given_name": "Kai", "clpid": "Li-Kai" }, { "family_name": "Ma", "given_name": "Liang", "clpid": "Ma-Liang" }, { "family_name": "Zhang", "given_name": "Jianhan", "clpid": "Zhang-Jianhan" }, { "family_name": "Yoon", "given_name": "Shinae", "clpid": "Yoon-Shinae" }, { "family_name": "Elowitz", "given_name": "Michael B.", "orcid": "0000-0002-1221-0967", "clpid": "Elowitz-M-B" }, { "family_name": "Lin", "given_name": "Yihan", "orcid": "0000-0002-2763-5538", "clpid": "Lin-Yihan" } ], "abstract": "Biological processes are highly dynamic and are regulated by genes that connect with one and another, forming regulatory circuits and networks. Understanding how gene regulatory circuits operate dynamically requires monitoring the expression of multiple genes in the same cell. However, it is limited by the relatively few distinguishable fluorescent proteins. Here, we developed a multiplexed real-time transcriptional imaging method based on two RNA stem-loop binding proteins, and employed it to analyze the temporal dynamics of synthetic gene circuits. By incorporating different ratios of MS2 and PP7 stem-loops, we were able to monitor the real-time nascent transcriptional activities of up to five genes in the same cell using only two fluorescent proteins. Applying this multiplexing capability to synthetic linear or branched gene regulatory cascades revealed that propagation of transcriptional dynamics is enhanced by non-stationary dynamics and is dictated by the slowest regulatory branch in the presence of combinatorial regulation. Mathematical modeling provided further insight into temporal multi-gene interactions and helped to understand potential challenges in regulatory inference using snapshot single-cell data. Ratiometric multiplexing should scale exponentially with additional labelling channels, providing a way to track the dynamics of larger circuits.", "doi": "10.1101/2021.09.23.461487", "publication_date": "2021-09-24" }, { "id": "authors:2z0dm-q9917", "collection": "authors", "collection_id": "2z0dm-q9917", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20201123-140413855", "type": "monograph", "title": "A simple direct RT-LAMP SARS-CoV-2 saliva diagnostic", "author": [ { "family_name": "Flynn", "given_name": "Michael J.", "clpid": "Flynn-Michael-J" }, { "family_name": "Snitser", "given_name": "Olga", "clpid": "Snitser-Olga" }, { "family_name": "Flynn", "given_name": "James", "clpid": "Flynn-James" }, { "family_name": "Green", "given_name": "Samantha", "clpid": "Green-Samantha" }, { "family_name": "Yelin", "given_name": "Idan", "orcid": "0000-0003-2515-4113", "clpid": "Yelin-Idan" }, { "family_name": "Szwarcwort-Cohen", "given_name": "Moran", "clpid": "Szwarcwort-Cohen-Moran" }, { "family_name": "Kishony", "given_name": "Roy", "clpid": "Kishony-Roy" }, { "family_name": "Elowitz", "given_name": "Michael B.", "orcid": "0000-0002-1221-0967", "clpid": "Elowitz-M-B" } ], "abstract": "Widespread, frequent testing is essential for curbing the ongoing COVID-19 pandemic. Because its simplicity makes it ideal for widely distributed, high throughput testing, RT-LAMP provides an attractive alternative to RT-qPCR. However, most RT-LAMP protocols require the purification of RNA, a complex and low-throughput bottleneck that has often been subject to reagent supply shortages. Here, we report an optimized RT-LAMP-based SARS-CoV-2 diagnostic protocol for saliva and swab samples. In the protocol we replace RNA purification with a simple sample preparation step using a widely available chelating agent, as well as optimize key protocol parameters. When tested on clinical swab and saliva samples, this assay achieves a limit of detection of 105 viral genomes per ml, with sensitivity close to 90% and specificity close to 100%, and takes 45 minutes from sample collection to result, making it well suited for a COVID-19 surveillance program.", "doi": "10.1101/2020.11.19.20234948", "publication_date": "2020-11-22" }, { "id": "authors:91hvf-49c47", "collection": "authors", "collection_id": "91hvf-49c47", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20200529-070622811", "type": "monograph", "title": "Engineering multiple levels of specificity in an RNA viral vector", "author": [ { "family_name": "Gao", "given_name": "Xiaojing J.", "orcid": "0000-0002-3094-1456", "clpid": "Gao-Xiaojing-J" }, { "family_name": "Chong", "given_name": "Lucy S.", "orcid": "0000-0002-5858-9984", "clpid": "Chong-Lucy-S" }, { "family_name": "Ince", "given_name": "Michaela H.", "orcid": "0000-0002-8997-3188", "clpid": "Ince-M-H" }, { "family_name": "Kim", "given_name": "Matthew S.", "orcid": "0000-0002-5836-8874", "clpid": "Kim-M-S" }, { "family_name": "Elowitz", "given_name": "Michael B.", "orcid": "0000-0002-1221-0967", "clpid": "Elowitz-M-B" } ], "abstract": "Synthetic molecular circuits could provide powerful therapeutic capabilities, but delivering them to specific cell types and controlling them remains challenging. An ideal \"smart\" viral delivery system would enable controlled release of viral vectors from \"sender\" cells, conditional entry into target cells based on cell-surface proteins, conditional replication specifically in target cells based on their intracellular protein content, and an evolutionarily robust system that allows viral elimination with drugs. Here, combining diverse technologies and components, including pseudotyping, engineered bridge proteins, degrons, and proteases, we demonstrate each of these control modes in a model system based on the rabies virus. This work shows how viral and protein engineering can enable delivery systems with multiple levels of control to maximize therapeutic specificity.", "publisher": "Caltech Library", "publication_date": "2020-05-27" }, { "id": "authors:425pg-3wb39", "collection": "authors", "collection_id": "425pg-3wb39", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20200601-094106134", "type": "monograph", "title": "Quantitative single-cell splicing analysis reveals an 'economy of scale' filter for gene expression", "author": [ { "family_name": "Ding", "given_name": "Fangyuan", "orcid": "0000-0003-0118-5441", "clpid": "Ding-Fangyuan" }, { "family_name": "Elowitz", "given_name": "Michael B.", "orcid": "0000-0002-1221-0967", "clpid": "Elowitz-M-B" } ], "abstract": "In eukaryotic cells, splicing affects the fate of each pre-mRNA transcript, helping to determine whether it is ultimately processed into an mRNA, or degraded. The efficiency of splicing plays a key role in gene expression. However, because it depends on the levels of multiple isoforms at the same transcriptional active site (TAS) in the same cell, splicing efficiency has been challenging to measure. Here, we introduce a quantitative single-molecule FISH-based method that enables determination of the absolute abundances of distinct RNA isoforms at individual TASs. Using this method, we discovered that splicing efficiency behaves in an unexpected 'economy of scale' manner, increasing, rather than decreasing, with gene expression levels, opposite to a standard enzymatic process. This behavior could result from an observed correlation between splicing efficiency and spatial proximity to nuclear speckles. Economy of scale splicing represents a non-linear filter that amplifies the expression of genes when they are more strongly transcribed. This method will help to reveal the roles of splicing in the quantitative control of gene expression.", "doi": "10.1101/457432", "publication_date": "2018-10-30" } ]