ArticleACS synthetic biology2023
Protein-Specific Signal Peptides for Mammalian Vector Engineering.
Article in ACS synthetic biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed, 31 citations in OpenAlex.
- Differential Assembly of Native Epithelial Sodium Channel Complexes Across Mouse Epithelial Tissues.Kidney360 · 2026Article
- Improving recombinant protein productivity in CHO cells via multi-omics data integration.Bioresources and bioprocessing · 2026Review
- UniSePT: an engineered broadly applicable Unique Secretory signal PepTide for high-yield biotherapeutic production in mammalian cell-based expression systems.Journal of biological engineering · 2026Article
- Protein-inducible ribosomal frameshifting enables programmable translational control for genetic circuit design in Escherichia coli.Journal of biological engineering · 2026Article
- Direct Cytoplasmic Transcription and Trimeric RBD Design Synergize to Enhance DNA Vaccine Potency Against SARS-CoV-2.Pharmaceutics · 2026Article
- Systematic Evaluation of Vector Sequence Elements in Isogenic CHO Cells for Improved Antibody Production.ACS synthetic biology · 2026Article
- The landscape of antibody production systems: recombinant expression for research, diagnostics and therapy.Frontiers in bioengineering and biotechnology · 2026Review
- Genetic Engineering of Umbilical Cord-Derived Mesenchymal Stem Cells to Enhance BMP-2 Secretion via Signal Peptide Optimization.Biomedicines · 2025Article
- Engineering mammalian protein secretion: Toward the convergence of high-throughput biology and computational methods.Cell systems · 2025Review
- Synthetic G-quadruplex components for predictable, precise two-level control of mammalian recombinant protein expression.Nucleic acids research · 2025Article
- Signal Peptides: From Molecular Mechanisms to Applications in Protein and Vaccine Engineering.Biomolecules · 2025Review
- Advances in the biological production of sugar alcohols from biomass-derived xylose.World journal of microbiology & biotechnology · 2025Review
- Vaccinia growth factor-dependent modulation of the mTORC1-CAD axis upon nutrient restriction.Journal of virology · 2025Article
- Article
- Glycan masking in immunogen design: computational and experimental methods.Frontiers in immunology · 2025Review
- Simple improvements in vector design afford substantial gains in AAV delivery of aggregation-slowing Aβ variants.Molecular therapy. Nucleic acids · 2024Article
- Improvement strategies for transient gene expression in mammalian cells.Applied microbiology and biotechnology · 2024Review
- Development of a Mammalian Cell Line for Stable Production of Anti-PD-1.Antibodies (Basel, Switzerland) · 2024Article
- Episomal Vectors for Stable Production of Recombinant Proteins and Engineered Antibodies.Antibodies (Basel, Switzerland) · 2024Article
- Artificial intelligence-driven systems engineering for next-generation plant-derived biopharmaceuticals.Frontiers in plant science · 2023Review
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
Abstract
Expression of recombinant proteins in mammalian cell factories relies on synthetic assemblies of genetic parts to optimally control flux through the product biosynthetic pathway. In comparison to other genetic part-types, there is a relative paucity of characterized signal peptide components, particularly for mammalian cell contexts. In this study, we describe a toolkit of signal peptide elements, created using bioinformatics-led and synthetic design approaches, that can be utilized to enhance production of biopharmaceutical proteins in Chinese hamster ovary cell factories. We demonstrate, for the first time in a mammalian cell context, that machine learning can be used to predict how discrete signal peptide elements will perform when utilized to drive endoplasmic reticulum (ER) translocation of specific single chain protein products. For more complex molecular formats, such as multichain monoclonal antibodies, we describe how a combination of in silico and targeted design rule-based in vitro testing can be employed to rapidly identify product-specific signal peptide solutions from minimal screening spaces. The utility of this technology is validated by deriving vector designs that increase product titers ≥1.8×, compared to standard industry systems, for a range of products, including a difficult-to-express monoclonal antibody. The availability of a vastly expanded toolbox of characterized signal peptide parts, combined with streamlined in silico/in vitro testing processes, will permit efficient expression vector re-design to maximize titers of both simple and complex protein products.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.