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SynBio, Volume 3, Issue 4 (December 2025) – 7 articles

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15 pages, 1442 KB  
Review
Targeting Cancer-Associated Transcripts with Engineered RNase P Ribozymes
by Thomas Sorrell, Ethan Ou and Fenyong Liu
SynBio 2025, 3(4), 20; https://doi.org/10.3390/synbio3040020 - 8 Dec 2025
Viewed by 170
Abstract
Nucleic acid-based gene interfering and editing molecules, such as antisense oligonucleotides, ribozymes, small interfering RNAs (siRNAs), and CRISPR-Cas9-associated guide RNAs, are promising gene-targeting agents for therapeutic applications. Cancer’s heterogeneous and diverse nature demands gene-silencing technologies that are both specific and adaptable. RNase P [...] Read more.
Nucleic acid-based gene interfering and editing molecules, such as antisense oligonucleotides, ribozymes, small interfering RNAs (siRNAs), and CRISPR-Cas9-associated guide RNAs, are promising gene-targeting agents for therapeutic applications. Cancer’s heterogeneous and diverse nature demands gene-silencing technologies that are both specific and adaptable. RNase P ribozymes, called M1GS RNAs, are engineered constructs that link the catalytic M1 RNA from bacterial RNase P to a programmable guide sequence. This guide sequence directs the M1GS ribozyme to base-pair with a target RNA, inducing it to fold into a structure resembling pre-tRNA. Catalytic activity can be enhanced through in vitro selection strategies. In this review, we will discuss the application of M1GS ribozymes in targeting cancer-associated RNAs, focusing on the BCR-ABL transcript in leukemia, the internal ribosome entry site (IRES) of hepatitis C virus (HCV), and the replication and transcription activator (RTA) of Kaposi’s sarcoma-associated herpesvirus (KSHV). Together, these examples highlight the versatility of M1GS ribozymes across both viral and cellular oncogenic targets, underscoring their potential as a flexible synthetic biology platform for cancer therapy. Full article
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30 pages, 1321 KB  
Review
A Guide to Guides: An Overview of SpCas9 sgRNA Scaffold Variants and Modifications
by Jonas De Saeger
SynBio 2025, 3(4), 19; https://doi.org/10.3390/synbio3040019 - 20 Nov 2025
Viewed by 949
Abstract
The CRISPR/SpCas9 system has revolutionized biology by enabling precise and programmable genome modification. While substantial effort has focused on engineering the SpCas9 protein and spacer sequences, the single-guide RNA (sgRNA) scaffold is an equally critical determinant of activity. Since the canonical scaffold was [...] Read more.
The CRISPR/SpCas9 system has revolutionized biology by enabling precise and programmable genome modification. While substantial effort has focused on engineering the SpCas9 protein and spacer sequences, the single-guide RNA (sgRNA) scaffold is an equally critical determinant of activity. Since the canonical scaffold was introduced in 2012, numerous variants have been developed. Early designs sought to enhance editing efficiency; however, despite the first improved scaffold being reported in 2013, more than 80% of CRISPR plasmids deposited in the Addgene repository still use the original scaffold rather than an efficiency-optimized alternative, which may not provide optimal performance. Subsequent work has also addressed intra-sgRNA interactions that impair folding, as well as inter-sgRNA interactions that destabilize multiplexed arrays, yet these solutions remain largely overlooked. Beyond efficiency, scaffold engineering—and the inclusion of auxiliary RNA elements—has enabled new capabilities, including effector recruitment, conditional regulation, visualization, improved stability, and large-scale multiplexing. The main goal of this review is to (i) provide a structured overview of the diverse SpCas9 sgRNA scaffold variants and auxiliary RNA modifications developed to date, (ii) summarize their functional characteristics and contexts of use, thereby illustrating how scaffold engineering continues to expand the functional scope of CRISPR technologies, and (iii) present a curated sequence resource comprising more than 230 scaffold variants and 80 auxiliary modifications to support experimental design and benchmarking. Full article
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15 pages, 3161 KB  
Article
ChronoSort: Revealing Hidden Dynamics in AlphaFold3 Structure Predictions
by Matthew J. Argyle, William P. Heaps, Corbyn Kubalek, Spencer S. Gardiner, Bradley C. Bundy and Dennis Della Corte
SynBio 2025, 3(4), 18; https://doi.org/10.3390/synbio3040018 - 14 Nov 2025
Viewed by 602
Abstract
Protein function emerges from dynamic conformational changes, yet structure prediction methods provide only static snapshots. While AlphaFold3 (AF3) predicts protein structures, the potential for extracting dynamic information from its ensemble predictions has remained underexplored. Here, we demonstrate that AF3 structural ensembles contain substantial [...] Read more.
Protein function emerges from dynamic conformational changes, yet structure prediction methods provide only static snapshots. While AlphaFold3 (AF3) predicts protein structures, the potential for extracting dynamic information from its ensemble predictions has remained underexplored. Here, we demonstrate that AF3 structural ensembles contain substantial dynamic information that correlates remarkably well with molecular dynamics simulations (MD). We developed ChronoSort, a novel algorithm that organizes static structure predictions into temporally coherent trajectories by minimizing structural differences between neighboring frames. Through systematic analysis of four diverse protein targets, we show that root-mean-square fluctuations derived from AF3 ensembles can correlate strongly with those from MD (r = 0.53 to 0.84). Principal component analysis reveals that AF3 predictions capture the same collective motion patterns observed in molecular dynamics trajectories, with eigenvector similarities significantly exceeding random distributions. ChronoSort trajectories exhibit structural evolution profiles comparable to MD. These findings suggest that modern AI-based structure prediction tools encode conformational flexibility information that can be systematically extracted without expensive MD. We provide ChronoSort as open-source software to enable broad community adoption. This work offers a novel approach to extracting functional insights from structure prediction tools in minutes, with significant implications for synthetic biology, protein engineering, drug discovery, and structure–function studies. Full article
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27 pages, 2271 KB  
Review
Digital to Biological Translation: How the Algorithmic Data-Driven Design Reshapes Synthetic Biology
by Abdul Manan, Nabila Qayyum, Rajath Ramachandran, Naila Qayyum and Sidra Ilyas
SynBio 2025, 3(4), 17; https://doi.org/10.3390/synbio3040017 - 7 Nov 2025
Viewed by 1554
Abstract
Synthetic biology, an emergent interdisciplinary field integrating principles from biology, engineering, and computer science, endeavors to rationally design and construct novel biological systems or reprogram extant ones to achieve predefined functionalities. The conventional approach relies on an iterative Design-Build-Test-Learn (DBTL) cycle, a process [...] Read more.
Synthetic biology, an emergent interdisciplinary field integrating principles from biology, engineering, and computer science, endeavors to rationally design and construct novel biological systems or reprogram extant ones to achieve predefined functionalities. The conventional approach relies on an iterative Design-Build-Test-Learn (DBTL) cycle, a process frequently hampered by the intrinsic complexity, non-linear interactions, and vast design space inherent to biological systems. The advent of Artificial Intelligence (AI), and particularly its subfields of Machine Learning (ML) and Deep Learning (DL), is fundamentally reshaping this paradigm by offering robust computational frameworks to navigate these formidable challenges. This review elucidates the strategic integration of AI/ML/DL across the synthetic biology workflow, detailing the specific algorithms and mechanisms that enable rational design, autonomous experimentation, and pathway optimization. Their advanced applications are specifically underscored across critical facets, including de novo rational design, enhanced predictive modeling, intelligent high-throughput data analysis, and AI-driven laboratory automation. Furthermore, pivotal challenges, such as data sparsity, model interpretability, the “black box” problem, computational resource demands, and ethical considerations, have been addressed, while concurrently forecasting future trajectories for this rapidly advancing and convergent domain. The synergistic convergence of these disciplines is demonstrably accelerating biological discovery, facilitating the creation of innovative and scalable biological solutions, and fostering a more predictable and efficient paradigm for biological engineering. Full article
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22 pages, 3055 KB  
Article
Stoichiometric Multiprotein Assembly Scaffolded by a Heterotrimeric DNA Clamp for Enzyme Colocalization and DNA Functionalization
by Arabella Essert and Kathrin Castiglione
SynBio 2025, 3(4), 16; https://doi.org/10.3390/synbio3040016 - 6 Nov 2025
Viewed by 411
Abstract
Researchers strive to exploit kinetic potentials of multistep reactions by positioning enzymes in a regulated fashion. Therein, the proliferating cell nuclear antigen (PCNA) from Sulfolobus solfataricus is a promising biomolecular tool due to its extraordinary architecture. PCNA is a circular DNA sliding clamp, [...] Read more.
Researchers strive to exploit kinetic potentials of multistep reactions by positioning enzymes in a regulated fashion. Therein, the proliferating cell nuclear antigen (PCNA) from Sulfolobus solfataricus is a promising biomolecular tool due to its extraordinary architecture. PCNA is a circular DNA sliding clamp, which can bind and move along DNA and thus, be applied for the immobilization and transport of biomolecules on versatile DNA scaffolds. Additionally, its heterotrimeric character facilitates the colocalization of enzyme cascades with defined stoichiometry. This study provides insights into the in vitro binding behavior of PCNA and its potential as protein scaffold for DNA functionalization and controlled biocatalysis: (1) PCNA was capable of binding circular DNA and wireframe DNA nanostructures. (2) DNA binding was predominantly mediated by the PCNA1 subunit. (3) PCNA assembly around DNA was compromised when cysteines were introduced at the PCNA–PCNA interfaces to stabilize the ring via disulfide bonds. (4) A two-enzyme cascade, comprising a pseudo-monomeric cytochrome P450 BM3 monooxygenase and a monomeric alcohol dehydrogenase (ADH), was successfully fused to PCNA, retaining catalytic activity. (5) When immobilized on DNA, the cascade performance was not assessable, due to nearly complete loss of ADH activity in proximity to DNA. Full article
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21 pages, 2596 KB  
Article
Self-Energy-Harvesting Pacemakers: An Example of Symbiotic Synthetic Biology
by Kuntal Kumar Das, Ashutosh Kumar Dubey, Bikramjit Basu and Yogendra Narain Srivastava
SynBio 2025, 3(4), 15; https://doi.org/10.3390/synbio3040015 - 4 Oct 2025
Viewed by 1080
Abstract
While synthetic biology has traditionally focused on creating biological systems often through genetic engineering, emerging technologies, for example, implantable pacemakers with integrated piezo-electric and tribo-electric materials are beginning to enlarge the classical domain into what we call symbiotic synthetic biology. These devices are [...] Read more.
While synthetic biology has traditionally focused on creating biological systems often through genetic engineering, emerging technologies, for example, implantable pacemakers with integrated piezo-electric and tribo-electric materials are beginning to enlarge the classical domain into what we call symbiotic synthetic biology. These devices are permanently attached to a body, although non-living or genetically unaltered, and closely mimic biological behavior by harvesting biomechanical energy and providing functions, such as autonomous heart pacing. They form active interfaces with human tissues and operate as hybrid systems, similar to synthetic organs. In this context, the present paper first presents a short summary of previous in vivo studies on piezo-electric composites in relation to their deployment as battery-less pacemakers. This is then followed by a summary of a recent theoretical work using a damped harmonic resonance model, which is being extended to mimic the functioning of such devices. We then extend the theoretical study further to include new solutions and obtain a sum rule for the power output per cycle in such systems. In closing, we present our quantitative understanding to explore the modulation of the quantum vacuum energy (Casimir effect) by periodic body movements to power pacemakers. Taken together, the present work provides the scientific foundation of the next generation bio-integrated intelligent implementation. Full article
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15 pages, 2082 KB  
Article
Analysis and Application of Translation-Enhancing Peptides for Improved Production of Proteins Containing Polyproline
by Akimichi Yoshino, Riko Shimoji, Yuma Nishikawa, Hideo Nakano and Teruyo Ojima-Kato
SynBio 2025, 3(4), 14; https://doi.org/10.3390/synbio3040014 - 3 Oct 2025
Viewed by 831
Abstract
Polyproline residues are well known to induce ribosomal stalling during translation. Our previous work demonstrated that inserting a short translation-enhancing peptide, Ser-Lys-Ile-Lys (SKIK), immediately upstream of such difficult-to-translate sequences can significantly alleviate ribosomal stalling in Escherichia coli. In this study, we provide [...] Read more.
Polyproline residues are well known to induce ribosomal stalling during translation. Our previous work demonstrated that inserting a short translation-enhancing peptide, Ser-Lys-Ile-Lys (SKIK), immediately upstream of such difficult-to-translate sequences can significantly alleviate ribosomal stalling in Escherichia coli. In this study, we provide a quantitative evaluation of its translational effect by kinetically analyzing the influence of the SKIK peptide on polyproline motifs using a reconstituted E. coli in vitro translation system. Translation rates estimated under reasonable assumptions fitted well to a Hill equation within a Michaelis–Menten-like kinetic framework. We further revealed that repetition of the SKIK tag did not provide any positive effect on translation. Moreover, introduction of the SKIK tag increased the production of polyproline-containing proteins, including human interleukin 11, human G protein signaling modulator 3, and DUF58 domain–containing protein from Streptomyces sp. in E. coli cell-free protein synthesis. These findings not only provide new insight into the fundamental regulation of translation by nascent peptides but also demonstrate the potential of the SKIK peptide as a practical tool for synthetic biology, offering a strategy to improve the production of difficult-to-express proteins. Full article
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