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Nucleic acid‐based therapeutics that regulate gene expression have been developed towards clinical use at a steady pace for several decades, but in recent years the field has been accelerating. To date, there are 11 marketed products based on antisense oligonucleotides, aptamers and small interfering RNAs, and many others are in the pipeline for both academia and industry. A major technology trigger for this development has been progress in oligonucleotide chemistry to improve the drug properties and reduce cost of goods, but the main hurdle for the application to a wider range of disorders is delivery to target tissues. The adoption of delivery technologies, such as conjugates or nanoparticles, has been a game changer for many therapeutic indications, but many others are still awaiting their eureka moment. Here, we cover the variety of methods developed to deliver nucleic acid‐based therapeutics across biological barriers and the model systems used to test them. We discuss important safety considerations and regulatory requirements for synthetic oligonucleotide chemistries and the hurdles for translating laboratory breakthroughs to the clinic. Recent advances in the delivery of nucleic acid‐based therapeutics and in the development of model systems, as well as safety considerations and regulatory requirements for synthetic oligonucleotide chemistries are discussed in this review on oligonucleotide‐based therapeutics. Graphical Abstract Recent advances in the delivery of nucleic acid‐based therapeutics and in the development of model systems, as well as safety considerations and regulatory requirements for synthetic oligonucleotide chemistries are discussed in this review on oligonucleotide‐based therapeutics.

The ecological forces that govern the assembly and stability of the human gut microbiota remain unresolved. We developed a generalizable model‐guided framework to predict higher‐dimensional consortia from time‐resolved measurements of lower‐order assemblages. This method was employed to decipher microbial interactions in a diverse human gut microbiome synthetic community. We show that pairwise interactions are major drivers of multi‐species community dynamics, as opposed to higher‐order interactions. The inferred ecological network exhibits a high proportion of negative and frequent positive interactions. Ecological drivers and responsive recipient species were discovered in the network. Our model demonstrated that a prevalent positive and negative interaction topology enables robust coexistence by implementing a negative feedback loop that balances disparities in monospecies fitness levels. We show that negative interactions could generate history‐dependent responses of initial species proportions that frequently do not originate from bistability. Measurements of extracellular metabolites illuminated the metabolic capabilities of monospecies and potential molecular basis of microbial interactions. In sum, these methods defined the ecological roles of major human‐associated intestinal species and illuminated design principles of microbial communities. Synopsis Analysis of microbial interactions in a synthetic human gut microbiome community shows that pairwise microbial interactions are major drivers of multi‐species community dynamics. The study reveals ecological drivers, metabolite hub species and ecologically sensitive organisms in the network. A data‐driven pipeline is used to construct a predictive dynamic model of a diverse anaerobic human gut microbiome community. Design principles of stable coexistence and history‐dependence are elucidated. Ecological roles and metabolite profiles are analyzed for each organism. The study highlights challenges in using phylogenetic and exo‐metabolomic “signals” to predict microbial interactions and community functions. Graphical Abstract Analysis of microbial interactions in a synthetic human gut microbiome community shows that pairwise microbial interactions are major drivers of multi‐species community dynamics. The study reveals ecological drivers, metabolite hub species and ecologically sensitive organisms in the network.

Antibiotic resistance threatens our ability to treat infectious diseases, spurring interest in alternative antimicrobial technologies. The use of bacterial conjugation to deliver CRISPR‐ cas systems programmed to precisely eliminate antibiotic‐resistant bacteria represents a promising approach but requires high in situ DNA transfer rates. We have optimized the transfer efficiency of conjugative plasmid TP114 using accelerated laboratory evolution. We hence generated a potent conjugative delivery vehicle for CRISPR‐ cas9 that can eliminate > 99.9% of targeted antibiotic‐resistant Escherichia coli in the mouse gut microbiota using a single dose. We then applied this system to a Citrobacter rodentium infection model, achieving full clearance within four consecutive days of treatment. SYNOPSIS A conjugative plasmid with high transfer rates is leveraged to deliver the CRISPR system into targeted bacteria. The resulting conjugative system can clear a C. rodentium infection in mice. Conjugative plasmid TP114 can be used for the delivery of CRISPR‐Cas systems by an engineered conjugative probiotic (COP) strain. Accelerated laboratory evolution was conducted to further increase TP114 transfer rates in the gut microbiota. The COP approach was able to knock down antibiotic‐resistant bacteria from a probed population in situ . The improved eB‐COP system enabled the complete clearance of a C. rodentium infection in mice with similar efficiency as a conventional antibiotic treatment. Graphical Abstract A conjugative plasmid with high transfer rates is leveraged to deliver the CRISPR system into targeted bacteria. The resulting conjugative system can clear a C. rodentium infection in mice.

There is a groundswell of interest in using genetically engineered sensor bacteria to study gut microbiota pathways, and diagnose or treat associated diseases. Here, we computationally identify the first biological thiosulfate sensor and an improved tetrathionate sensor, both two‐component systems from marine Shewanella species, and validate them in laboratory Escherichia coli . Then, we port these sensors into a gut‐adapted probiotic E. coli strain, and develop a method based upon oral gavage and flow cytometry of colon and fecal samples to demonstrate that colon inflammation (colitis) activates the thiosulfate sensor in mice harboring native gut microbiota. Our thiosulfate sensor may have applications in bacterial diagnostics or therapeutics. Finally, our approach can be replicated for a wide range of bacterial sensors and should thus enable a new class of minimally invasive studies of gut microbiota pathways. Synopsis A sensor bacterium that uses a novel two‐component signaling system is engineered to detect thiosulfate and colon inflammation. This work suggests thiosulfate as a novel biomarker of colon inflammation and demonstrates the potential of engineered bacteria in disease diagnostics. Novel two‐component system sensors of thiosulfate and tetrathionate from marine Shewanella species are identified computationally. Both sensors are characterized in laboratory Escherichia coli and then ported to the gut‐adapted probiotic strain Nissle 1917. A flow cytometry protocol is developed for identifying the engineered bacteria in the colon contents or feces of mice with intact microbiota. The thiosulfate sensor has elevated output in inflamed mice, suggesting thiosulfate as a novel biomarker of inflammation. Graphical Abstract A sensor bacterium that uses a novel two‐component signaling system is engineered to detect thiosulfate and colon inflammation. This work suggests thiosulfate as a novel biomarker of colon inflammation and demonstrates the potential of engineered bacteria in disease diagnostics.

Direct reprogramming based on genetic factors resembles a promising strategy to replace lost cells in degenerative diseases such as Parkinson's disease. For this, we developed a knock‐in mouse line carrying a dual dCas9 transactivator system (dCAM) allowing the conditional in vivo activation of endogenous genes. To enable a translational application, we additionally established an AAV‐based strategy carrying intein‐split‐dCas9 in combination with activators (AAV‐dCAS). Both approaches were successful in reprogramming striatal astrocytes into induced GABAergic neurons confirmed by single‐cell transcriptome analysis of reprogrammed neurons in vivo . These GABAergic neurons functionally integrate into striatal circuits, alleviating voluntary motor behavior aspects in a 6‐OHDA Parkinson's disease model. Our results suggest a novel intervention strategy beyond the restoration of dopamine levels. Thus, the AAV‐dCAS approach might enable an alternative route for clinical therapies of Parkinson's disease. Synopsis GABAergic neurons generated by CRISPR‐mediated direct reprogramming of striatal astrocytes rescue voluntary motor behavior in a toxin‐induced murine model for Parkinson's disease, suggesting a novel intervention strategy beyond the restoration of dopamine levels. A novel CRISPRa mouse line dCAM is developed for the conditional induction of endogenous target genes. An AAV‐based split‐dCas9‐activator system is established for translational applications of CRISPRa. Direct reprogramming of murine striatal astrocytes using the factor combination Ascl1 , Lmx1a , and Nr4a2 results in induced GABAergic neurons in vivo . Induced GABAergic neurons are capable of ameliorating specific motor symptoms of Parkinson's disease. Graphical Abstract GABAergic neurons generated by CRISPR‐mediated direct reprogramming of striatal astrocytes rescue voluntary motor behavior in a toxin‐induced murine model for Parkinson's disease, suggesting a novel intervention strategy beyond the restoration of dopamine levels.

Our understanding of complex living systems is limited by our capacity to perform experiments in high throughput. While robotic systems have automated many traditional hand‐pipetting protocols, software limitations have precluded more advanced maneuvers required to manipulate, maintain, and monitor hundreds of experiments in parallel. Here, we present Pyhamilton, an open‐source Python platform that can execute complex pipetting patterns required for custom high‐throughput experiments such as the simulation of metapopulation dynamics. With an integrated plate reader, we maintain nearly 500 remotely monitored bacterial cultures in log‐phase growth for days without user intervention by taking regular density measurements to adjust the robotic method in real‐time. Using these capabilities, we systematically optimize bioreactor protein production by monitoring the fluorescent protein expression and growth rates of a hundred different continuous culture conditions in triplicate to comprehensively sample the carbon, nitrogen, and phosphorus fitness landscape. Our results demonstrate that flexible software can empower existing hardware to enable new types and scales of experiments, empowering areas from biomanufacturing to fundamental biology. SYNOPSIS An open‐source Python platform enables advanced liquid handling robots to perform a variety of complex high‐throughput experiments that could never be performed manually. Bioautomation can benefit from flexible, easily shared protocols in a widely used language. Custom techniques such as plaque assays can be readily automated. 480 bacterial turbidostats using 100 different media compositions areused to map the metabolic fitness landscape for recombinant protein production. Graphical Abstract An open‐source Python platform enables advanced liquid handling robots to perform a variety of complex high‐throughput experiments that could never be performed manually.

Enteric hyperoxaluria (EH) is a metabolic disease caused by excessive absorption of dietary oxalate leading to the formation of chronic kidney stones and kidney failure. There are no approved pharmaceutical treatments for EH. SYNB8802 is an engineered bacterial therapeutic designed to consume oxalate in the gut and lower urinary oxalate as a potential treatment for EH. Oral administration of SYNB8802 leads to significantly decreased urinary oxalate excretion in healthy mice and non‐human primates, demonstrating the strain's ability to consume oxalate in vivo . A mathematical modeling framework was constructed that combines in vitro and in vivo preclinical data to predict the effects of SYNB8802 administration on urinary oxalate excretion in humans. Simulations of SYNB8802 administration predict a clinically meaningful lowering of urinary oxalate excretion in healthy volunteers and EH patients. Together, these findings suggest that SYNB8802 is a promising treatment for EH. SYNOPSIS SYNB8802 is an engineered probiotic designed to metabolize oxalate in patients with enteric hyperoxaluria. The strain shows significant oxalate degradation in vitro and in vivo , and in silico modeling predicts that it can lower urinary oxalate in patients. Enteric hyperoxaluria is a metabolic disorder where oxalate overabsorption can lead to chronic kidney stones and ultimately kidney failure. SYNB8802 is an engineered probiotic, derived from Escherichia coli Nissle capable of degrading oxalate. SYNB8802 lowers urinary oxalate, a disease biomarker, as shown in preclinical data from mice and non‐human primates. In silico modeling predicts that SYNB8802 lowers urinary oxalate up to 71% in patients. Graphical Abstract SYNB8802 is an engineered probiotic designed to metabolize oxalate in patients with enteric hyperoxaluria. The strain shows significant oxalate degradation in vitro and in vivo , and in silico modeling predicts that it can lower urinary oxalate in patients.

Genetic circuits require many regulatory parts in order to implement signal processing or execute algorithms in cells. A potentially scalable approach is to use dCas9, which employs small guide RNAs (sgRNAs) to repress genetic loci via the programmability of RNA:DNA base pairing. To this end, we use dCas9 and designed sgRNAs to build transcriptional logic gates and connect them to perform computation in living cells. We constructed a set of NOT gates by designing five synthetic Escherichia coli σ 70 promoters that are repressed by corresponding sgRNAs, and these interactions do not exhibit crosstalk between each other. These sgRNAs exhibit high on‐target repression (56‐ to 440‐fold) and negligible off‐target interactions (< 1.3‐fold). These gates were connected to build larger circuits, including the Boolean‐complete NOR gate and a 3‐gate circuit consisting of four layered sgRNAs. The synthetic circuits were connected to the native E. coli regulatory network by designing output sgRNAs to target an E. coli transcription factor ( malT ). This converts the output of a synthetic circuit to a switch in cellular phenotype (sugar utilization, chemotaxis, phage resistance). Synopsis Genetic gates are assembled based on dCas9 and engineered small guide RNAs (sgRNAs) that drive Cas9 to target promoters. These transcriptional gates are linked to build larger genetic circuits that are connected to the natural regulatory network of the cell. Synthetic promoters and cognate sgRNAs exhibit large dynamic range and negligible crosstalk. sgRNA‐based NOT gate response functions are non‐cooperative and quantitatively different from those based on transcriptional repressors. Multi‐input logic gates are constructed by layering orthogonal sgRNAs. Host regulatory networks can be interfaced through the design of sgRNA circuit outputs targeted to native transcription factors. Graphical Abstract Genetic gates are assembled based on dCas9 and engineered small guide RNAs (sgRNAs) that drive Cas9 to target promoters. These transcriptional gates are linked to build larger genetic circuits that are connected to the natural regulatory network of the cell.

Cochlear implants (CIs) are considered the most successful neuroprosthesis as they enable speech comprehension in the majority of half a million CI users suffering from sensorineural hearing loss. By electrically stimulating the auditory nerve, CIs constitute an interface re‐connecting the brain and the auditory scene, providing the patient with information regarding the latter. However, since electric current is hard to focus in conductive environments such as the cochlea, the precision of electrical sound encoding—and thus quality of artificial hearing—is limited. Recently, optogenetic stimulation of the cochlea has been suggested as an alternative approach for hearing restoration. Cochlear optogenetics promises increased spectral selectivity of artificial sound encoding, hence improved hearing, as light can conveniently be confined in space to activate the auditory nerve within smaller tonotopic ranges. In this review, we discuss the latest experimental and technological developments of cochlear optogenetics and outline the remaining challenges on the way to clinical translation. Graphical Abstract In this review, A. Dieter, D. Keppeler and T. Moser summarize the state of the art and progresses made in optical cochlear implantation using ontogenetic technology and discuss the challenges for translation into patients with hearing loss.

The formation of spatiotemporal patterns of gene expression is frequently guided by gradients of diffusible signaling molecules. The toggle switch subnetwork, composed of two cross‐repressing transcription factors, is a common component of gene regulatory networks in charge of patterning, converting the continuous information provided by the gradient into discrete abutting stripes of gene expression. We present a synthetic biology framework to understand and characterize the spatiotemporal patterning properties of the toggle switch. To this end, we built a synthetic toggle switch controllable by diffusible molecules in Escherichia coli . We analyzed the patterning capabilities of the circuit by combining quantitative measurements with a mathematical reconstruction of the underlying dynamical system. The toggle switch can produce robust patterns with sharp boundaries, governed by bistability and hysteresis. We further demonstrate how the hysteresis, position, timing, and precision of the boundary can be controlled, highlighting the dynamical flexibility of the circuit. Synopsis Toggle switch is a common subnetwork of gene regulatory networks in charge of pattern formation. This study combines a synthetic biology framework and mathematical modeling to characterize the spatiotemporal properties of toggle switch in Escherichia coli . A synthetic toggle switch network in E. coli interprets a signal concentration gradient into bistable and hysteretic spatial patterns. Combining quantitative measurements with a mathematical model allows reconstructing the underlying bifurcation diagram. Modulating the repression strength of the mutual repressing nodes allows to control the hysteresis, position, timing, and precision of the pattern boundary. Graphical Abstract Toggle switch is a common subnetwork of gene regulatory networks in charge of pattern formation. This study combines a synthetic biology framework and mathematical modeling to characterize the spatiotemporal properties of toggle switch in E. coli .