In Vitro Enzyme Self-Selection Using Molecular Programs

Cell-free systems: A synthetic biology tool for rapid prototyping in metabolic engineering

Microbial cell factories provide sustainable alternatives to petroleum-based chemical production using cost-effective substrates. A deep understanding of their metabolism is essential to harness their potential along with continuous efforts to improve productivity and yield. However, the construction and evaluation of numerous genetic variants are time-consuming and labor-intensive. Cell-free systems (CFSs) serve as powerful platforms for rapid prototyping of genetic circuits, metabolic pathways, and enzyme functionality. They offer numerous advantages, including minimizing unwanted metabolic interference, precise control of reaction conditions, reduced labor, and shorter Design-Build-Test-Learn cycles. Additionally, the introduction of in vitro compartmentalization strategies in CFSs enables ultra-high-throughput screening in physically separated spaces, which significantly enhances prototyping efficiency. This review highlights the latest examples of using CFS to overcome prototyping limitations in living cells with a focus on rapid prototyping, particularly regarding gene regulation, enzymes, and multienzymatic reactions in bacteria. Finally, this review evaluates CFSs as a versatile prototyping platform and discusses its future applications, emphasizing its potential for producing high-value chemicals through microbial biosynthesis.

Harnessing DNA computing and nanopore decoding for practical applications: from informatics to microRNA-targeting diagnostics

DNA computing represents a subfield of molecular computing with the potential to become a significant area of next-generation computation due to the high programmability inherent in the sequence-dependent molecular behaviour of DNA. Recent studies in DNA computing have extended from mathematical informatics to biomedical applications, with a particular focus on diagnostics that exploit the biocompatibility of DNA molecules. The output of DNA computing devices is encoded in nucleic acid molecules, which must then be decoded into human-recognizable signals for practical applications. Nanopore technology, which utilizes an electrical and label-free decoding approach, provides a unique platform to bridge DNA and electronic computing for practical use. In this tutorial review, we summarise the fundamental knowledge, technologies, and methodologies of DNA computing (logic gates, circuits, neural networks, and non-DNA input circuity). We then focus on nanopore-based decoding, and highlight recent advances in medical diagnostics targeting microRNAs as biomarkers. Finally, we conclude with the potential and challenges for the practical implementation of these techniques. We hope that this tutorial will provide a comprehensive insight and enable the general reader to grasp the fundamental principles and diverse applications of DNA computing and nanopore decoding, and will inspire a wide range of scientists to explore and push the boundaries of these technologies.

Robust Sequence Design Space for the Isothermal Exponential Amplification of Short Oligonucleotides

Advances in isothermal amplification techniques have accelerated development in biosensing applications and the design of complex molecular devices. The exponential amplification reaction technique, or EXPAR, is uniquely positioned to process molecular information from short oligonucleotide strands (≈10 nucleotides length) typically encountered in molecular computing or microRNA detection. Despite its conceptual simplicity (requiring only a template strand and two enzymes), the issue of nonspecific background amplification has hindered broader adoption. In this work, a new system configuration is established at 37 °C to achieve significantly improved performance. Critical sequence motifs responsible for the excellent signal-to-background profile are identified and generalized as a universal adapter design framework. Orthogonal template sequences generated from the framework are implemented for a triplex reaction and successfully evaluated mixtures of multiple-target inputs in a single-step, one-pot format without the need for exogenous agents.

DNA circuit-based immunoassay for ultrasensitive protein pattern classification

Cytokines are important immune modulators, and pivotal biomarkers for the diagnostic of various diseases. In standard analytical procedure, each protein is detected individually, using for instance gold standard ELISA protocols or nucleic acid amplification-based immunoassays. In recent years, DNA nanotechnology has been employed for creating sophisticated biomolecular systems that perform neuromorphic computing on molecular inputs, opening the door to concentration pattern recognition for biomedical applications. This work introduces immuno-PUMA (i-PUMA), an isothermal amplification-based immunoassay for ultrasensitive protein detection. The assay couples the convenience of supported format of an ELISA protocol with the computing capabilities of a DNA/enzyme circuit. We demonstrate a limit of detection of 2.1 fM, 8.7 fM and 450 aM for IL12, IL4 and IFNγ cytokines, respectively, outperforming the traditional ELISA format. i-PUMA's versatility extends to molecular computation, allowing the creation of 2-input perceptron-like classifiers for IL12 and IL4, with tunable weight sign and amplitude. Overall, i-PUMA represents a sensitive, low-cost, and versatile immunoassay with potential applications in multimarker-based sample classification, complementing existing molecular profiling techniques.

Functional analysis of single enzymes combining programmable molecular circuits with droplet-based microfluidics

The analysis of proteins at the single-molecule level reveals heterogeneous behaviours that are masked in ensemble-averaged techniques. The digital quantification of enzymes traditionally involves the observation and counting of single molecules partitioned into microcompartments via the conversion of a profluorescent substrate. This strategy, based on linear signal amplification, is limited to a few enzymes with sufficiently high turnover rate. Here we show that combining the sensitivity of an exponential molecular amplifier with the modularity of DNA-enzyme circuits and droplet readout makes it possible to specifically detect, at the single-molecule level, virtually any D(R)NA-related enzymatic activity. This strategy, denoted digital PUMA (Programmable Ultrasensitive Molecular Amplifier), is validated for more than a dozen different enzymes, including many with slow catalytic rate, and down to the extreme limit of apparent single turnover for Streptococcus pyogenes Cas9. Digital counting uniquely yields absolute molar quantification and reveals a large fraction of inactive catalysts in all tested commercial preparations. By monitoring the amplification reaction from single enzyme molecules in real time, we also extract the distribution of activity among the catalyst population, revealing alternative inactivation pathways under various stresses. Our approach dramatically expands the number of enzymes that can benefit from quantification and functional analysis at single-molecule resolution. We anticipate digital PUMA will serve as a versatile framework for accurate enzyme quantification in diagnosis or biotechnological applications. These digital assays may also be utilized to study the origin of protein functional heterogeneity.