Algae biomass and cellular exudated compounds have several biotechnological applications in various areas, such as agriculture, pharmaceutical, human and animal feed, and bioenergy, among others. However, many of these applications have not been developed to their full capability, in part due to the need to better understand the underlying principles of their cellular regulation of growth and metabolism. Recently, synthetic biology has been implemented as a new option to not only build new biological devices and systems but also comprehend the natural biochemical pathways present in living organisms. The use of this technology is still underdeveloped in algae research when compared to yeast and bacterial applications. Part of this effect is due to restraints on building multi-gene circuits, which are associated with the lack of controllable promoters and transcription factors in algae. This scenario could be improved by the development of orthogonal gene promoters, supported by the understanding of global biological responses related to their function in the host metabolism. With the integrative analysis of genomics, transcriptomics and proteomics, we may be able to find patterns of optimal orthogonality and address the rational design of optimal gene promoters that enhance algae biotechnological applications. In this paper, we will review the existing approaches and discuss future perspectives on the creation of orthogonal gene promoters in algae.
Cyanobacteria offer a sustainable and environmentally friendly method of light-driven biosynthesis of chemicals with minimal environmental impact, making them an extremely attractive proposition in alleviating society’s dependency on fossil fuels. To fully exploit cyanobacteria as a chassis to meet society’s demands for energy and chemical production, genetic modification is a crucial step in improving productivity through the expression of heterologous and novel biosynthetic pathways. Genome mining was carried out with the aim of identifying potential recE and recT homologues to improve the efficiency of genetic manipulation. Two promising candidate homologues of recT and cas4 (recE homologue) were identified from the cyanobacterium Aphanocapsa feldmanni. Expression of these candidates increased recombination efficiency 3-fold, generating mutants with the expected genotypes and phenotypes, which were comparable to mutants created with conventional knockout protocols using suicide vectors. These results indicate that cyanobacteria possess recombination homologues that can be re-purposed to improve the efficiency of genome engineering to accelerate cyanobacteria for strain development.
Studying the structure and dynamics of proteins and their complexes is essential for understanding biological processes and developing therapeutic strategies. Mutations in protein amino acid sequences can significantly alter their structure and function. However, the limited availability of experimentally characterized mutant protein structures makes comprehensive exploration challenging. The impact of mutations on proteins can also be analyzed in terms of several structural and physicochemical features. To overcome this limitation, we developed CHIMERA_AA, an integrated toolkit that allows researchers to modify and analyze protein structures and their complexes. This toolkit enables users to perform user-specified single or multiple amino acid mutations, as well as class-wise mutations, generating diverse structural combinations for further computational studies and generating initial coordinates of the mutated structures in user-specified formats (PDB, mmCIF, and mol2). The toolkit also generates minimized structures and facilitates the extraction and analysis of structural and physicochemical features of protein structures. The CHIMERA_AA toolkit empowers researchers to extend their studies beyond structural databases, offering an efficient method for investigating protein properties and dynamics.
Indole-3-acetic acid (IAA) is the main natural auxin and a key regulator of plant growth. However, most commercial auxins are synthetically produced from non-renewable resources. Here, we present a minimal synthetic biology platform for microbial IAA production that also serves as a teaching model for genetic circuit design and bioprocess development. We developed codon-optimized versions of the iaaM and iaaH genes, which encode tryptophan 2-monooxygenase and indole-3-acetamide hydrolase, and assembled them into a compact expression cassette in Escherichia coli TOP10. Correct expression of both enzymes was confirmed by SDS-PAGE. The engineered strain was cultivated in a low-cost medium made from avocado seed hydrolysate, an agro-industrial waste, supplemented with tryptophan as a precursor. IAA was quantified using the Salkowski colorimetric assay and further validated by HPLC, reaching approximately 303–313 µg/mL at 48 h, with the medium costing approximately fivefold cheaper locally than traditional LB. The supernatants containing biosynthetic IAA induced root formation in 100% of tobacco leaf explants, outperforming the commercial standard at the same concentration and confirming biological activity. Since this workflow follows the Design–Build–Test–Learn (DBTL) cycle, Design (pathway selection and codon optimization), Build (plasmid assembly), Test (protein expression, metabolite quantification, plant bioassays), and Learn (medium and process optimization), it provides a sustainable production method and an accessible educational platform for synthetic biology.
Gene therapy is an emerging approach for treating cancer by delivering therapeutic nucleic acids into malignant cells. However, tumor heterogeneity and the tumor microenvironment (TME) undermine the effectiveness of conventional gene therapy, which may lead to off-target activity in normal cells and limit therapeutic efficacy. Tumor-specific promoters (TSPs) provide transcription-level control by activating expression mainly in malignant cells through oncogenic signaling pathways or tumor-associated conditions such as hypoxia and inflammation. Recent work has demonstrated that gene therapy combined with suitable nanodelivery systems, including lipid-based, polymeric and inorganic systems, enables more precise tumor-restricted expression and enhanced antitumor effects. This review summarizes the current landscape of TSP discovery and engineering, and discusses considerations for their integration into emerging nanodelivery systems for cancer treatment.
Solitary bees account for most described bee species worldwide, with many spinning silk fibers to form protective cocoons during development; however, solitary bee silk proteins remain largely unexplored in recombinant systems and biomaterial fabrication. Here, we report the first recombinant expression and biomaterial formation from a solitary bee silk protein. Osmia lignaria silk fibroin 2 (OligF2) was expressed in Escherichia coli BL21(DE3) using an expression and purification scheme adapted from a recombinant hagfish intermediate filament (rHIF) workflow, yielding 0.34 g/L at ~70% purity. The purified OligF2 protein was cast into films at 0.75% and 1% (w/v). Fourier-transform infrared attenuated total reflectance (FTIR-ATR) analysis estimated higher β-sheet content in 0.75% films (50.3%) than in 1% films (42.3%). Mechanical testing yielded elastic moduli of 7.83 ± 2.73 MPa and 6.80 ± 1.89 MPa for the 0.75% and 1% films, respectively. These results establish the first recombinant production and biomaterial formation of a solitary bee silk protein, providing a foundation for exploring this class of recombinant proteins for the development of tunable biomaterials.
Lipid nanodiscs are synthetic nanoparticles capable of solubilizing lipophilic drugs and have been shown to improve the potency of the antifungal Amphotericin B (AmphB) against various fungal pathogens. In this study, the SpyCatcher–SpyTag covalent labeling system was used to couple AmphB-loaded Apolipoprotein A1 (ApoA1) lipid nanodiscs to the receptor domain of Dectin-1, which binds to β-1,3/1,6 glucans present in many fungal cell walls. Denaturing protein gel electrophoresis demonstrated that ApoA1-SpyTag003 lipid nanodiscs could be covalently labeled with SpyCatcher003-Dectin-1-superfolder GFP (sfGFP). In microtiter growth assays with Saccharomyces cerevisiae, Dectin-1 AmphB nanodiscs displayed an IC50 1.5-fold lower than uncoupled AmphB nanodiscs and 2.8-fold lower than AmphB-only controls. Nanodiscs without AmphB and SpyCatcher003-Dectin-1-sfGFP themselves did not inhibit yeast growth. Fluorescence microscopy showed that SpyCatcher003-Dectin-1-sfGFP binds to yeast cell walls and accumulated at hot spots, matching the budding scar enrichment pattern previously described for other Dectin-1 fusion proteins. Together these results indicate that Dectin-1 fusions can target AmphB-loaded lipid nanodiscs to fungal cell walls and improve drug delivery. The results here establish the use of a modular SpyCatcher–SpyTag coupling system for targeting drug-loaded lipid nanodiscs to different cells or tissues, thereby increasing drug retention at infection sites, increasing drug potency, and reducing harmful side-effects.
Metabolic engineering presents the possibility of creating novel and practical whole-cell biocatalysts. The practice of metabolic engineering is achieved first by in vitro DNA assembly, followed by the introduction of the newly constructed DNA into industrial microorganisms to create a novel phenotype. Although this approach of in vitro DNA assembly has been studied extensively, generation of unwanted recombinant DNA products remains a possibility. In this study, a recombinant DNA, namely pGRN02, was constructed using the sequence- and ligation- independent cloning. However, this DNA assembly method had a low success rate (5%). Unexpectedly, we identified an un-wanted recombinant DNA product as a major recombinant product (70%). DNA sequencing of this product indicated that it should not have been formed during in vitro DNA assembly, but rather post in vitro assembly. This study aims to report and discuss profound results of the DNA assembly reaction. The standard SLIC design using 20 bp homology arms is theoretically sufficient for correct assembly under typical conditions. However, longer unexpected repeats, such as the 44 bp internal homology observed here, can outcompete the designed junctions and dominate the recombination outcome.
Agricultural systems face mounting pressures from climate change, as rising temperatures, elevated CO2, and shifting precipitation patterns intensify plant disease outbreaks worldwide. Conventional strategies, such as breeding for resistance, pesticides, and even transgenic approaches, are proving too slow or unsustainable to meet these challenges. Synthetic biology offers a transformative paradigm for reprogramming plant immunity through genetic circuits, RNA-based defences, epigenome engineering, engineered microbiomes, and artificial intelligence (AI). We introduce the concept of synthetic immunity, a unifying framework that extends natural defence layers, PAMP-triggered immunity (PTI), and effector-triggered immunity (ETI). While pests and pathogens continue to undermine global crop productivity, synthetic immunity strategies such as CRISPR-based transcriptional activation, synthetic receptors, and RNA circuit-driven defences offer promising new avenues for enhancing plant resilience. We formalize synthetic immunity as an emerging, integrative concept that unites molecular engineering, regulatory rewiring, epigenetic programming, and microbiome modulation, with AI and computational modelling accelerating their design and climate-smart deployment. This review maps the landscape of synthetic immunity, highlights technological synergies, and outlines a translational roadmap from laboratory design to field application. Responsibly advanced, synthetic immunity represents not only a scientific frontier but also a sustainable foundation for climate-resilient agriculture.
The open access journal SynBio [...]
Wildfires are increasingly frequent and intense due to climate change, resulting in degraded soils with diminished microbial activity, reduced water retention, and low nutrient availability. In many regions, previously restored areas face repeated burning events, which further exhaust soil fertility and limit the potential for natural regeneration. Traditional reforestation approaches such as seed scattering or planting seedlings often fail in these conditions due to extreme aridity, erosion, and lack of biological support. To address this multifaceted problem, this study proposes a living, biodegradable hydrogel that integrates an engineered soil-beneficial microorganism consortium, designed to deliver beneficial compounds and nutrients combined with endemic plant seeds into a single biopolymeric matrix. Acting simultaneously as a biofertilizer, soil conditioner, and reforestation aid, this 3-in-1 system provides a microenvironment that retains moisture, supports microbial diversity restoration, and facilitates plant germination even in nutrient-poor, arid soils. The concept is rooted in circular economy principles, utilizing polysaccharides from food industry by-products for biopolymer formation, thereby ensuring environmental compatibility and minimizing waste. The encapsulated microorganisms, a Bacillus subtilis strain and a Nostoc oryzae strain, are intended to enrich the soil with useful compounds. They are engineered based on synthetic biology principles to incorporate specific genetic modules. The B. subtilis strain is engineered to break down large polyphenolic compounds through laccase overexpression, thus increasing soil bioavailable organic matter. The cyanobacterium strain is modified to enhance its nitrogen-fixing capacity, supplying fixed nitrogen directly to the soil. After fulfilling its function, the matrix naturally decomposes, returning organic matter, while the incorporation of a quorum sensing-based kill-switch system is designed to prevent the environmental escape of the engineered microorganisms. This sustainable approach aims to transform post-wildfire landscapes into self-recovering ecosystems, offering a scalable and eco-friendly alternative to conventional restoration methods while advancing the integration of synthetic biology and environmental engineering for climate resilience.
Therapeutic proteins face a critical pharmacokinetic challenge: rapid clearance from circulation limits their clinical efficacy. Albumin-binding domains (ABDs) offer an elegant solution by enabling therapeutic proteins to “hitchhike” on serum albumin’s favorable 19-day half-life through FcRn-mediated recycling. Clinical validation through approved therapeutics like ozoralizumab demonstrates the success of this approach, with preclinical studies showing fusion to an ABD extended half-life to 18 days. This review provides an analysis of ABD-fusion protein design, integrating structural biology, computational prediction, and rational engineering principles. We catalog the major classes of albumin-binding modalities, including bacterial three-helix bundle domains, engineered peptides, antibody-derived binders, and alternative scaffolds, comparing their binding properties, size contributions, cross-species reactivity, and production cost. Critical examination of linker architectures reveals that flexible glycine-serine linkers (particularly the widely successful (GGGGS)3 motif) provide optimal balance between domain independence and molecular economy, though linker choice profoundly influences not only spatial separation but also binding affinity, folding, stability, and pharmacokinetics. We evaluate the utility and limitations of the structure prediction tools for ABD-fusion design. We establish practical guidelines for integrating computational screening with experimental validation. This review provides protein engineers and synthetic biologists with a comprehensive framework for rational design of albumin-binding therapeutics, emphasizing the synergistic integration of structural insight, computational prediction, and systematic experimental validation to accelerate development of next-generation long-acting biotherapeutics.
Synthetic RNA has become an essential modality in therapeutic development. Linear mRNA is already clinically validated, which demonstrated that in vitro-transcribed (IVT) RNA can achieve robust protein expression in humans and can be manufactured at a large scale. Circular RNA (circRNA) represents a more recent format characterized by a covalently closed backbone that confers enhanced resistance to exonucleases and supports sustained translation when paired with appropriate regulatory elements. Although both formats are produced through cell-free synthesis, their manufacturing pathways are distinct. Linear mRNA synthesis requires transcription, capping, polyadenylation, and stringent removal of double-stranded RNA contaminants. circRNA production generally proceeds through transcription of a linear precursor followed by enzymatic or ribozyme-mediated circularization, with emerging strategies such as permuted intron-exon designs improving efficiency and reducing extraneous sequence content. This review summarizes the principal methods used to generate linear and circRNA and identifies the technical barriers that must be overcome during the manufacturing process.
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.
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.
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.
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.
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.
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.
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.
