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Radiation-induced immune suppression poses significant health challenges for millions of patients undergoing cancer chemotherapy and radiotherapy treatment, and astronauts and space tourists travelling to outer space. While a limited number of recombinant protein therapies, such a Sargramostim, are approved for accelerating hematologic recovery, the pronounced role of granulocyte-macrophage colony-stimulating factor (GM-CSF or CSF2) as a proinflammatory cytokine poses additional challenges in creating immune dysfunction towards pathogenic autoimmune diseases. Here we present an approach to high-throughput drug-discovery, target validation, and lead molecule identification using nucleic acid-based molecules. These Nanoligomer™ molecules are rationally designed using a bioinformatics and an artificial intelligence (AI)-based ranking method and synthesized as a single-modality combining 6-different design elements to up- or downregulate gene expression of target gene, resulting in elevated or diminished protein expression of intended target. This method additionally alters related gene network targets ultimately resulting in pathway modulation. This approach was used to perturb and identify the most effective upstream regulators and canonical pathways for therapeutic intervention to reverse radiation-induced immunosuppression. The lead Nanoligomer™identified in a screen of human donor derived peripheral blood mononuclear cells (PBMCs) upregulated Erythropoietin (EPO) and showed the greatest reversal of radiation induced cytokine changes. It was further testedin vivoin a mouse radiation-model with low-dose (3 mg/kg) intraperitoneal administration and was shown to regulate gene expression ofepoin lung tissue as well as counter immune suppression. These results point to the broader applicability of our approach towards drug-discovery, and potential for further investigation of lead molecule as reversible gene therapy to treat adverse health outcomes induced by radiation exposure.

Future lunar missions and beyond will require new and innovative approaches to radiation countermeasures. The Translational Research Institute for Space Health (TRISH) is focused on identifying and supporting unique approaches to reduce risks to human health and performance on future missions beyond low Earth orbit. This paper will describe three funded and complementary avenues for reducing the risk to humans from radiation exposure experienced in deep space. The first focus is on identifying new therapeutic targets to reduce the damaging effects of radiation by focusing on high throughput genetic screens in accessible, sometimes called lower, organism models. The second focus is to design innovative approaches for countermeasure development with special attention to nucleotide-based methodologies that may constitute a more agile way to design therapeutics. The final focus is to develop new and innovative ways to test radiation countermeasures in a human model system. While animal studies continue to be beneficial in the study of space radiation, they can have imperfect translation to humans. The use of three-dimensional (3D) complex in vitro models is a promising approach to aid the development of new countermeasures and personalized assessments of radiation risks. These three distinct and unique approaches complement traditional space radiation efforts and should provide future space explorers with more options to safeguard their short and long-term health.

The devastating effects of the coronavirus disease 2019 (COVID-19) pandemic have made clear a global necessity for antiviral strategies. Most fatalities associated with infection from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) result at least partially from uncontrolled host immune response. Here, we use an antisense compound targeting a previously identified microRNA (miRNA) linked to severe cases of COVID-19. The compound binds specifically to the miRNA in question, miR-2392, which is produced by human cells in several disease states. The safety and biodistribution of this compound were tested in a mouse model via intranasal, intraperitoneal, and intravenous administration. The compound did not cause any toxic responses in mice based on measured parameters, including body weight, serum biomarkers for inflammation, and organ histopathology. No immunogenicity from the compound was observed with any administration route. Intranasal administration resulted in excellent and rapid biodistribution to the lungs, the main site of infection for SARS-CoV-2. Pharmacokinetic and biodistribution studies reveal delivery to different organs, including lungs, liver, kidneys, and spleen. The compound was largely cleared through the kidneys and excreted via the urine, with no accumulation observed in first-pass organs. The compound is concluded to be a safe potential antiviral treatment for COVID-19.

Counting viable cells is a universal practice in microbiology. The colony forming unit (CFU) assay has remained the gold standard to measure viability across disciplines; however, it is time-intensive and resource-consuming. Herein, we describe the Geometric Viability Assay (GVA) that replicates CFU measurements over 6-orders of magnitude while reducing over 10-fold the time and consumables. GVA computes a sample’s viable cell count based on the distribution of embedded colonies growing inside a pipette tip. GVA is compatible with gram-positive and -negative planktonic bacteria, biofilms, and yeast. Laborious CFU experiments such as checkerboard assays, treatment time-courses, and drug screens against slow-growing cells are simplified by GVA. We therefore screened a drug library against exponential and stationary phaseE. colileading to the discovery of the ROS-mediated, bactericidal mechanism of diphenyliodonium. The ease and low cost of GVA evinces it can accelerate existing viability assays and enable measurements at previously impractical scales.

Neuroinflammation is a key factor in the development of neurodegenerative diseases, including prion disease. There are currently no effective treatments to halt pathogenesis and progression, which includes accumulation of misfolded proteins, neuroinflammation, and cognitive/behavioral deficits followed by irreversible neuronal death. We hypothesized that downregulation of two key neuroinflammatory targets would be neuroprotective. To test this, we utilized Nanoligomers™ in a prion-diseased mouse to assess the impact on glial inflammation, behavioral/cognition deficits, and loss of neurons. Nanoligomer™ treated mice displayed decreased numbers of glia, and improved behavior and cognitive tests. Critically, the Nanoligomer™ protected the brain from prion-induced spongiotic change, neuronal loss, and significantly increased life span, indicating that Nanoligomer™ inhibition of inflammatory pathways can prevent neuronal death and slow the progression of neurodegenerative diseases.One-Sentence SummaryImmunotherapeutic Nanoligomer™ in prion diseased mice opens new treatment avenues for other neurodegenerative diseases.

Acute activation of innate immune response in the brain, or neuroinflammation, protects this vital organ from a range of external pathogens and promotes healing after traumatic brain injury. However, chronic neuroinflammation leads to the activation of immune cells like microglia and astrocytes causes damage to the nervous tissue, and is causally linked to a range of neurodegenerative diseases such as Alzheimer’s diseases (AD), Multiple Sclerosis (MS), Parkinson’s diseases (PD), and many others. While neuroinflammation is a key target for a range of neuropathological diseases, there is a lack of effective countermeasures to tackle it, and existing experimental therapies require fairly invasive intracerebral and intrathecal delivery due to difficulty associated with the therapeutic crossover between the blood-brain barrier (BBB), making such treatments impractical to treat neuroinflammation long-term. Here, we present the development of an optimal neurotherapeutic using our Nanoligomer™ discovery engine, by screening downregulation of several proinflammatory cytokines (e.g., Interleukin-1β or IL-1β, tumor necrosis factor-alpha or TNF-α, TNF receptor 1 or TNFR1, Interleukin 6 or IL-6), inflammasomes (e.g., NLRP1), key transcription factors (e.g., nuclear factor kappa-B or NF-κβ) and their combinations, as upstream regulators and canonical pathway targets, to identify and validate the best-in-class treatment. Using our high-throughput drug discovery, target validation, and lead molecule identification via a bioinformatics and AI-based ranking method to design sequence-specific peptide molecules to up-or down-regulate gene expression of the targeted gene at will, we used our discovery engine to perturb and identify most effective upstream regulators and canonical pathways for therapeutic intervention to reverse neuroinflammation. The lead neurotherapeutic was a combination of Nanoligomers™ targeted to NF-κβ (SB.201.17D.8_ NF-κβ1) and TNFR1 (SB.201.18D.6_TNFR1), which were identified usingin vitrocell-based screening in donor-derived human astrocytes, and further validatedin vivousing a mouse model of lipopolysaccharide (LPS)-induced neuroinflammation. The combination treatment SB_NI_111 was delivered without any special formulation using a simple intraperitoneal injection of low-dose (5mg/kg) and was found to significantly suppress the expression of LPS-induced neuroinflammation in mouse hippocampus. These results point to the broader applicability of this approach towards the development of therapies for chronic neuroinflammation-linked neurodegenerative diseases, sleep countermeasures, and others, and the potential for further investigation of the lead neurotherapeutic molecule as reversible gene therapy.

Galactic cosmic rays (GCR) in space induce increase in cerebral amyloid-β levels and elevated levels of microgliosis and astrocytosis, causing accelerated neurodegeneration from this increased neuroinflammation. Even exposure to low-levels of high-Z high-energy (HZE) radiation (50 cGy) has been shown to induce biochemical and immunohistochemical changes in short-term leading to degradation in cognition, motor skills, and development of space-induced neuropathy. There is lack of effective neuroinflammation countermeasures, and current experimental therapies require invasive intracerebral and intrathecal delivery due to difficulty associated with therapeutic crossover between blood-brain barrier. Here, we present a new countermeasure development approach for neurotherapeutics using high-throughput drug-discovery, target validation, and lead molecule identification with nucleic acid-based molecules. These Nanoligomer™ molecules are rationally designed using a bioinformatics and AI-based ranking method and synthesized as a single-modality combining 6-different design elements to up- or down-regulate gene expression of target gene at will, resulting in elevated or diminished protein expression of intended target. This platform approach was used to perturb and identify most effective upstream regulators and canonical pathways for therapeutic intervention to reverse radiation-induced neuroinflammation. The lead Nanoligomer™ and corresponding target granulocyte-macrophage colony-stimulating factor (GM-CSF) were identified usingin vitrocell-based screening in human astrocytes and donor derived peripheral blood mononuclear cells (PBMCs) and further validatedin vivousing a mouse model of radiation-induced neuroinflammation. GM-CSF transcriptional downregulator Nanoligomer 30D.443_CSF2 downregulated proinflammatory cytokine GM-CSF (or CSF2) using simple intraperitoneal injection of low-dose (3mg/kg) and completely reversed expression of CSF2 in cortex tissue, as well as other neuroinflammation markers. These results point to the broader applicability of this approach towards space countermeasure development, and potential for further investigation of lead neurotherapeutic molecule as a reversible gene therapy.

As the world braces to enter its third year in the coronavirus disease 2019 (COVID-19) pandemic, the need for accessible and effective antiviral therapeutics continues to be felt globally. The recent surge of Omicron variant cases has demonstrated that vaccination and prevention alone cannot quell the spread of highly transmissible variants. A safe and nontoxic therapeutic with an adaptable design to respond to the emergence of new variants is critical for transitioning to treatment of COVID-19 as an endemic disease. Here, we present a novel compound, called SBCoV202, that specifically and tightly binds the translation initiation site of RNA-dependent RNA polymerase within the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome, inhibiting viral replication. SBCoV202 is a Nanoligomer,™ a molecule that includes peptide nucleic acid sequences capable of binding viral RNA with single-base-pair specificity to accurately target the viral genome. The compound has been shown to be safe and nontoxic in mice, with favorable biodistribution, and has shown efficacy against SARS-CoV-2 in vitro. Safety and biodistribution were assessed after three separate administration methods, namely intranasal, intravenous, and intraperitoneal. Safety studies showed the Nanoligomer caused no outward distress, immunogenicity, or organ tissue damage, measured through observation of behavior and body weight, serum levels of cytokines, and histopathology of fixed tissue, respectively. SBCoV202 was evenly biodistributed throughout the body, with most tissues measuring Nanoligomer concentrations well above the compound KD of 3.37 nM. In addition to favorable availability to organs such as the lungs, lymph nodes, liver, and spleen, the compound circulated through the blood and was rapidly cleared through the renal and urinary systems. The favorable biodistribution and lack of immunogenicity and toxicity set Nanoligomers apart from other antisense therapies, while the adaptability of the nucleic acid sequence of Nanoligomers provides a defense against future emergence of drug resistance, making these molecules an attractive potential treatment for COVID-19.

Drug-resistant bacterial infections are a growing cause of illness and death globally. Current methods of treatment are not only proving less effective but also perpetuate evolution of new resistance. Here we propose, through an in vivo model, a new treatment for drug-resistant bacterial infection that uses semiconductor nanoparticles, called quantum dots (QDs), that can be activated by light to produce superoxide to specifically and effectively kill drug-resistant bacteria. We adapt this technology for in vivo assessment of toxicity and treatment of a subcutaneous infection in mice. As our cadmium telluride QDs with 2.4 eV band gap (CdTe-2.4 QDs) are activated by blue light, we engineered LED patches to adhere to the infection site on mice, thus providing the light necessary for the activity of injected QDs and treatment of the infection. We show, through assessment of body weight, histology, and inflammation and oxidative stress markers in serum, that the CdTe-2.4 QDs are nontoxic at concentrations that reduce drug-resistant bacterial viability in subcutaneous abscesses. Further, CdTe-2.4 QDs did not accumulate in the body and were safely excreted in urine via renal clearance. CdTe-2.4 QD treatment decreased abscess viability by as much as 7 orders of magnitude. We thus propose an alternative treatment approach for drug-resistant topical infections: the injection of a low concentration of QDs and the application of an adhesive patch comprising only an LED and a battery. This treatment could revolutionize last-resort treatments of burn wounds, cellulitis, and other skin infections.

CdTe-2.4 eV quantum dots (QDs) show excellent efficacy due to their tunability and photo-potentiation for sterilizing drug-resistant planktonic cultures without harming mammalian cells but this QD fabrication has not been tested against biofilms. While the QD attack mechanism—production of superoxide radicals—is known to stimulate biofilm formation, here we demonstrate that CdTe-2.4 eV QD-antibiotic combination therapy can nearly eradicate Escherichia coli, methicillin-resistant Staphylococcus aureus, and Pseudomonas aeruginosa biofilms. CdTe-2.4 eV QD versatility, safety, and ability to potentiate antibiotics makes them a potential treatment strategy for biofilm-associated infections.

In recent years, the prevalence of carbapenem-resistant Enterobacteriaceae (CRE) has risen substantially, and the study of CRE resistance mechanisms has become increasingly important for antibiotic development. Although much research has focused on genomic resistance factors, relatively few studies have examined CRE pathogens through changes in gene expression. In this study, we examined the gene expression profile of a CRE Escherichia coli clinical isolate that is sensitive to meropenem but resistant to ertapenem to explore transcriptomic contributions to resistance and to identify gene knockdown targets for carbapenem potentiation. We sequenced total and short RNA to analyze the gene expression response to ertapenem or meropenem treatment and found significant expression changes in genes related to motility, maltodextrin metabolism, the formate hydrogenlyase complex, and the general stress response. To validate these findings, we used our laboratory's Facile Accelerated Specific Therapeutic (FAST) platform to create antisense peptide nucleic acids (PNAs), gene-specific molecules designed to inhibit protein translation. PNAs were designed to inhibit the pathways identified in our transcriptomic analysis, and each PNA was then tested in combination with each carbapenem to assess its effect on the antibiotics' minimum inhibitory concentrations. We observed significant PNA-antibiotic interaction with five different PNAs across six combinations. Inhibition of the genes hycA, dsrB, and bolA potentiated carbapenem efficacy in CRE E. coli, whereas inhibition of the genes flhC and ygaC conferred added resistance. Our results identify resistance factors and demonstrate that transcriptomic analysis is a potent tool for designing antibiotic PNA.

The increasing prevalence of drug-resistant bacterial strains is causing illness and death in an unprecedented number of people around the globe. Currently implemented small-molecule antibiotics are both increasingly less efficacious and perpetuating the evolution of resistance. Here, we propose a new treatment for drug-resistant bacterial infection in the form of indium phosphide quantum dots (InP QDs), semiconductor nanoparticles that are activated by light to produce superoxide. We show that the superoxide generated by InP QDs is able to effectively kill drug-resistant bacteria in vivo to reduce subcutaneous abscess infection in mice without being toxic to the animal. Our InP QDs are activated by near-infrared wavelengths with high transmission through skin and tissues and are composed of biocompatible materials. Body weight and organ tissue histology show that the QDs are nontoxic at a macroscale. Inflammation and oxidative stress markers in serum demonstrate that the InP QD treatment did not result in measurable effects on mouse health at concentrations that reduce drug-resistant bacterial viability in subcutaneous abscesses. The InP QD treatment decreased bacterial viability by over 3 orders of magnitude in subcutaneous abscesses formed in mice. These InP QDs thus provide a promising alternative to traditional small-molecule antibiotics, with the potential to be applied to a wide variety of infection types, including wound, respiratory, and urinary tract infections.

Nanomaterials have been extensively used in the biomedical field and have recently garnered attention as potential antimicrobial agents. Cadmium telluride quantum dots (QDs) with a bandgap of 2.4 eV (CdTe-2.4) were previously shown to inhibit multidrug-resistant clinical isolates of bacterial pathogens via light-activated superoxide generation. Here we investigate the transcriptomic response of Escherichia coli to phototherapeutic CdTe-2.4 QDs both with and without illumination, as well as in comparison with the non-superoxide-generating cadmium selenide QDs (CdSe-2.4) as a negative control. Our analysis sought to separate the transcriptomic response of E. coli to the generation of superoxide by the CdTe-2.4 QDs from the presence of cadmium chalcogenide nanoparticles alone. We used comparisons between illuminated CdTe-2.4 conditions and all others to establish the superoxide generation response and used comparisons between all QD conditions and the no treatment condition to establish the cadmium chalcogen...

Quantum-confined states of semiconductor nanocrystals offer unique opportunities for selective light-activated photochemistry and generation of specific reactive oxygen (ROS) and nitrogen (RNS) spe...

MicroRNAs (miRNAs) are small non-coding RNAs involved in post-transcriptional gene regulation that have a major impact on many diseases and provide an exciting avenue toward antiviral therapeutics. From patient transcriptomic data, we determined that a circulating miRNA, miR-2392, is directly involved with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) machinery during host infection. Specifically, we show that miR-2392 is key in driving downstream suppression of mitochondrial gene expression, increasing inflammation, glycolysis, and hypoxia, as well as promoting many symptoms associated with coronavirus disease 2019 (COVID-19) infection. We demonstrate that miR-2392 is present in the blood and urine of patients positive for COVID-19 but is not present in patients negative for COVID-19. These findings indicate the potential for developing a minimally invasive COVID-19 detection method. Lastly, using in vitro human and in vivo hamster models, we design a miRNA-based antiviral therapeutic that targets miR-2392, significantly reduces SARS-CoV-2 viability in hamsters, and may potentially inhibit a COVID-19 disease state in humans., Graphical abstract, McDonald et al. uncover a role of a circulating microRNA, miR-2392, as a potential biomarker for COVID-19 and begin development of a potential COVID-19 therapeutic and antiviral to inhibit miR-2392.

Antisense transcription is widespread in all kingdoms of life and has been shown to influence gene expression through transcriptional interference (TI), a phenomenon in which one transcriptional process negatively influences another in cis. The processivity, or uninterrupted transcription, of an RNA Polymerase (RNAP) is closely tied to levels of antisense transcription in bacterial genomes, but its influence on TI, while likely important, is not well-characterized. Here we show that TI can be tuned through processivity control via three distinct antitermination strategies: the antibiotic bicyclomycin, phage protein Psu, and ribosome-RNAP coupling. We apply these methods toward TI and tune ribosome-RNAP coupling to produce 38-fold gene repression due to RNAP collisions. We then couple protein roadblock and RNAP collisions to design minimal genetic NAND and NOR logic gates. Together these results show the importance of processivity control for strong TI and demonstrate the potential for TI to create sophisticated switching responses.

Nanomaterials have been extensively used in the biomedical field and have recently garnered attention as potential antimicrobial agents. Cadmium telluride quantum dots (QDs) with a bandgap of 2.4 eV (CdTe-2.4) were previously shown to inhibit multidrug-resistant clinical isolates of bacterial pathogens via light-activated superoxide generation. Here we investigate the transcriptomic response of

Quantum-confined states of semiconductor nanocrystals offer unique opportunities for selective light-activated photochemistry and generation of specific reactive oxygen (ROS) and nitrogen (RNS) species. Recently, assessment of different ROS and RNS species identified intracellular light-activated superoxide as the prime candidate for selective nanotherapeutic treatments in countering the threat of multidrug-resistant (MDR) pathogens. Here, we show that by carefully tuning the composition of ternary zinc cadmium telluride (Zn

In recent years, the prevalence of carbapenem-resistant Enterobacteriaceae (CRE) has risen substantially, and the study of CRE resistance mechanisms has become increasingly important for antibiotic development. Although much research has focused on genomic resistance factors, relatively few studies have examined CRE pathogens through changes in gene expression. In this study, we examined the gene expression profile of a CRE Escherichia coli clinical isolate that is sensitive to meropenem but resistant to ertapenem to explore transcriptomic contributions to resistance and to identify gene knockdown targets for carbapenem potentiation. We sequenced total and short RNA to analyze the gene expression response to ertapenem or meropenem treatment and found significant expression changes in genes related to motility, maltodextrin metabolism, the formate hydrogenlyase complex, and the general stress response. To validate these findings, we used our laboratory’s Facile Accelerated Specific Therapeutic (FAST) platform to create antisense peptide nucleic acids (PNAs), gene-specific molecules designed to inhibit protein translation. PNAs were designed to inhibit the pathways identified in our transcriptomic analysis, and each PNA was then tested in combination with each carbapenem to assess its effect on the antibiotics’ minimum inhibitory concentrations. We observed significant PNA–antibiotic interaction with five different PNAs across six combinations. Inhibition of the genes hycA, dsrB, and bolA potentiated carbapenem efficacy in CRE E. coli, whereas inhibition of the genes flhC and ygaC conferred added resistance. Our results identify resistance factors and demonstrate that transcriptomic analysis is a potent tool for designing antibiotic PNA.

Proliferation of multidrug-resistant (MDR) bacteria poses a threat to human health, requiring new strategies. Here we propose using fitness neutral gene expression perturbations to potentiate antibiotics. We systematically explored 270 gene knockout-antibiotic combinations in Escherichia coli, identifying 90 synergistic interactions. Identified gene targets were subsequently tested for antibiotic synergy on the transcriptomic level via multiplexed CRISPR-dCas9 and showed successful sensitization of E. coli without a separate fitness cost. These fitness neutral gene perturbations worked as co-therapies in reducing a Salmonella enterica intracellular infection in HeLa. Finally, these results informed the design of four antisense peptide nucleic acid (PNA) co-therapies, csgD, fnr, recA and acrA, against four MDR, clinically isolated bacteria. PNA combined with sub-minimal inhibitory concentrations of trimethoprim against two isolates of Klebsiella pneumoniae and E. coli showed three cases of re-sensitization with minimal fitness impacts. Our results highlight a promising approach for extending the utility of current antibiotics., Otoupal et al. use a systematic approach to investigate the effects of fitness neutral gene perturbations and antibiotic synergy in Escherichia coli. These neutral fitness interactions worked as co-therapies in a Salmonella enterica infection and informed the design of re-sensitization therapies in multi-drug resistant E. coli and Klebisiella pneumoniae clinical isolates.

Carbapenems are a powerful class of antibiotics, often used as a last-resort treatment to eradicate multidrug-resistant infections. In recent years, however, the incidence of carbapenem-resistantEnterobacteriaceae(CRE) has risen substantially, and the study of bacterial resistance mechanisms has become increasingly important for antibiotic development. Although much research has focused on genomic contributors to carbapenem resistance, relatively few studies have examined CRE pathogens through changes in gene expression. In this research, we used transcriptomics to study a CREEscherichia coliclinical isolate that is sensitive to meropenem but resistant to ertapenem, to both explore carbapenem resistance and identify novel gene knockdown targets for carbapenem re-sensitization. We sequenced total and small RNA to analyze gene expression changes in response to treatment with ertapenem or meropenem, as compared to an untreated control. Significant expression changes were found in genes related to motility, maltodextrin metabolism, the formate hydrogenlyase complex, and the general stress response. To validate these transcriptomic findings, we used our lab’s Facile Accelerated Specific Therapeutic (FAST) platform to create antisense peptide nucleic acids (PNA), gene-specific molecules designed to inhibit protein translation. FAST PNA were designed to inhibit the pathways identified in our transcriptomic analysis, and each PNA was then tested in combination with each carbapenem to assess its effect on the antibiotics’ minimum inhibitory concentrations. We observed significant treatment interaction with five different PNAs across six PNA-antibiotic combinations. Inhibition of the geneshycA,dsrB, andbolAwere found to re-sensitize CREE. colito carbapenems, whereas inhibition of the genesflhCandygaCwas found to confer added resistance. Our results identify new resistance factors that are regulated at the level of gene expression, and demonstrate for the first time that transcriptomic analysis is a potent tool for designing antibiotic PNA.

Multidrug-resistant (MDR) bacteria pose a grave concern to global health, which is perpetuated by a lack of new treatments and countermeasure platforms to combat outbreaks or antibiotic resistance. To address this, we have developed a Facile Accelerated Specific Therapeutic (FAST) platform that can develop effective peptide nucleic acid (PNA) therapies against MDR bacteria within a week. Our FAST platform uses a bioinformatics toolbox to design sequence-specific PNAs targeting non-traditional pathways/genes of bacteria, then performs in-situ synthesis, validation, and efficacy testing of selected PNAs. As a proof of concept, these PNAs were tested against five MDR clinical isolates: carbapenem-resistant Escherichia coli, extended-spectrum beta-lactamase Klebsiella pneumoniae, New Delhi Metallo-beta-lactamase-1 carrying Klebsiella pneumoniae, and MDR Salmonella enterica. PNAs showed significant growth inhibition for 82% of treatments, with nearly 18% of treatments leading to greater than 97% decrease. Further, these PNAs are capable of potentiating antibiotic activity in the clinical isolates despite presence of cognate resistance genes. Finally, the FAST platform offers a novel delivery approach to overcome limited transport of PNAs into mammalian cells by repurposing the bacterial Type III secretion system in conjunction with a kill switch that is effective at eliminating 99.6% of an intracellular Salmonella infection in human epithelial cells., Eller et al. develop a Facile Accelerated Specific Therapeutic (FAST) platform of antisense therapeutics that targets MDR bacterial pathogens with peptide nucleic acids (PNAs). This platform designs species and/or sequence specific PNAS based on a bioinformatics toolbox and offers a new delivery approach by repurposing the bacterial Type III secretion system in conjunction with a kill switch to overcome limited transport of PNAs into mammalian cells.

Several nanoscale electronic methods have been proposed for high-throughput single-molecule nucleic acid sequence identification. While many studies display a large ensemble of measurements as "electronic fingerprints" with some promise for distinguishing the DNA and RNA nucleobases (adenine, guanine, cytosine, thymine, and uracil), important metrics such as accuracy and confidence of base calling fall well below the current genomic methods. Issues such as unreliable metal-molecule junction formation, variation of nucleotide conformations, insufficient differences between the molecular orbitals responsible for single-nucleotide conduction, and lack of rigorous base calling algorithms lead to overlapping nanoelectronic measurements and poor nucleotide discrimination, especially at low coverage on single molecules. Here, we demonstrate a technique for reproducible conductance measurements on conformation-constrained single nucleotides and an advanced algorithmic approach for distinguishing the nucleobases. Our quantum point contact single-nucleotide conductance sequencing (QPICS) method uses combed and electrostatically bound single DNA and RNA nucleotides on a self-assembled monolayer of cysteamine molecules. We demonstrate that by varying the applied bias and pH conditions, molecular conductance can be switched ON and OFF, leading to reversible nucleotide perturbation for electronic recognition (NPER). We utilize NPER as a method to achieve99.7% accuracy for DNA and RNA base calling at low molecular coverage (∼12×) using unbiased single measurements on DNA/RNA nucleotides, which represents a significant advance compared to existing sequencing methods. These results demonstrate the potential for utilizing simple surface modifications and existing biochemical moieties in individual nucleobases for a reliable, direct, single-molecule, nanoelectronic DNA and RNA nucleotide identification method for sequencing.

Multidrug-resistant (MDR) bacteria pose a grave concern to global health. This problem is further aggravated by a lack of new and effective antibiotics and countermeasure platforms that can sustain the creation of novel antimicrobials in the wake of new outbreaks or evolution of resistance to antibiotics. To address this, we have developed a Facile Accelerated Specific Therapeutic (FAST) platform that can develop effective therapies against MDR bacteria within a week. Our FAST platform combines four essential modules- design, build, test, and delivery-of drug development cycle. The design module comprises a bioinformatics toolbox that predicts sequence-specific peptide nucleic acids (PNAs) that target non-traditional pathways and genes of bacteria in minutes. The build module constitutes in-situ synthesis and validation of selected PNAs in less than four days and efficacy testing within a day. As a proof of concept, these PNAs were tested against MDR clinical isolates. Here we tested Enterobacteriaceae including carbapenem-resistant Escherichia coli, extended-spectrum beta-lactamase (ESBL) Klebsiella pneumoniae, New Delhi Metallo-beta-lactamase-1 carrying Klebsiella pneumoniae and MDR Salmonella enterica. PNAs showed significant growth inhibition for 82% of treatments, with nearly 18% of the treatments leading to more than 97% decrease. Further, these PNAs are capable of potentiating antibiotic activity in the clinical isolates despite presence of cognate resistance genes. Finally, FAST offers a novel delivery approach to overcome limited transport of PNAs into mammalian cells to clear intracellular infections. This method relies on repurposing the bacterial Type III secretion system in conjunction with a kill switch that is effective at eliminating 99.6% of an intracellular Salmonella infection in human epithelial cells. Our findings demonstrate the potential of the FAST platform in treating MDR bacteria in a rapid and effective manner.

The rapid proliferation of multidrug-resistant (MDR) bacteria poses a critical threat to human health, for which new antimicrobial strategies are desperately needed. Here we outline a strategy for combating bacterial infections by administering fitness neutral gene expression perturbations as co-therapies to potentiate antibiotic lethality. We systematically explored the fitness of 270 gene knockout-drug combinations in Escherichia coli, identifying 114 synergistic interactions. Genes revealed in this screen were subsequently perturbed at the transcriptome level via multiplexed CRISPR-dCas9 interference to induce antibiotic synergy. These perturbations successfully sensitized E. coli to antibiotic treatment without imposing a separate fitness cost. We next administered these fitness neutral gene perturbations as co-therapies to potentiate antibiotic killing of Salmonella enterica in intracellular infections of HeLa epithelial cells, demonstrating therapeutic applicability. Finally, we utilized these results to design peptide nucleic acid (PNA) co-therapies for targeted gene expression reduction in four MDR, clinically isolated bacteria. Two isolates of Klebsiella pneumoniae and E. coli were each exposed to PNAs targeting homologs of the genes csgD, fnr, recA and acrA in the presence of sub-minimal inhibitory concentrations of trimethoprim. We successfully increased each strain’s susceptibility to trimethoprim treatment and identified eight cases in which re-sensitization occurred without a direct fitness impact of the PNA on MDR strains. Our results highlight a promising approach for combating MDR bacteria which could extend the utility of our current antibiotic arsenal.

Transcriptional Interference (TI) has been shown to regulate gene expression at the DNA level via different molecular mechanisms. The obstacles present on the DNA that a transcribing RNA polymerase might encounter, e.g. a DNA bound protein or another RNA polymerase, can result in TI causing termination of transcription, thus reducing gene expression. However, the potential of TI as a new strategy to engineer complex gene expression modules has not been fully explored yet. Here we created a series of two-input devices using the presence of a roadblocking protein using both experimental and mathematical modeling approaches. We explore how multiple characteristics affect the response of genetic devices engineered to act like either AND, OR, or Single Input logic gates. We show that the dissociation constant of the roadblocking protein, inducer activation of promoter and operator sites, and distance between tandem promoters tune gate behavior. Our results demonstrate that controlling RNAP traffic using the TI mechanism of roadblock can generate genetic devices capable of more diverse gene expression patterns than traditional single input promoters. This work highlights the potential of rationally creating different types of genetic responses using the same transcription factors in subtly different genetic architectures.

The emergence of multidrug-resistant (MDR) pathogens represents one of the most urgent global public health crises. Light-activated quantum dots (QDs) are alternative antimicrobials, with efficient transport, low cost, and therapeutic efficacy, and they can act as antibiotic potentiators, with a mechanism of action orthogonal to small-molecule drugs. Furthermore, light-activation enhances control over the spatiotemporal release and dose of the therapeutic superoxide radicals from QDs. However, the limited deep-tissue penetration of visible light needed for QD activation, and concern over trace heavy metals, have prevented further translation. Herein, we report two indium phosphide (InP) QDs that operate in the near-infrared and deep-red light window, enabling deeper tissue penetration. These heavy-metal-free QDs eliminate MDR pathogenic bacteria, while remaining non-toxic to host human cells. This work provides a pathway for advancing QD nanotherapeutics to combat MDR superbugs.

Antibacterial resistance necessitates the development of novel treatment methods for infections. Protein aggregates have recently been applied as antimicrobials to disrupt bacterial homeostasis. Past work on protein aggregates has focused on genome mining for aggregation-prone sequences in bacterial genomes rather than on rational design of aggregating antimicrobial peptides. Here, we use a synthetic biology approach to design an artificial gene encoding a de novo aggregating antimicrobial peptide. This artificial gene, opaL (overexpressed protein aggregator lipophilic), disrupts bacterial homeostasis by expressing extremely hydrophobic peptides. When this hydrophobic sequence is disrupted by acidic residues, consequent aggregation and antimicrobial effect decrease. Further, we developed a probiotic delivery system using the broad-host range conjugative plasmid RK2 to transfer the gene from donor to recipient bacteria. We utilize RK2 to mobilize a shuttle plasmid carrying opaL by adding the RK2 origin of transfer. We show that opaL is nontoxic to the donor, allowing for maintenance and transfer since its expression is under control of a promoter with a recipient-specific T7 RNA polymerase. Upon mating of donor and recipient Escherichia coli, we observe selective growth repression in T7 polymerase-expressing recipients. This technique could be used to target desired pathogens by selecting pathogen-specific promoters to control T7 RNA polymerase expression and provides a basis for the design and delivery of aggregating antimicrobial peptides.

We describe a nanoelectronic method for identifying single ribonucleotides and structural modifications, laying groundwork for single-molecule RNA sequencing/structural mapping., Although a number of advances have been made in RNA sequencing and structural characterization, the lack of a method for directly determining the sequence and structure of single RNA molecules has limited our ability to probe heterogeneity in gene expression at the level of single cells. Here we present a method for direct nucleotide identification and structural label mapping of single RNA molecules via Quantum Molecular Sequencing (QMSeq). The method combines non-perturbative quantum tunneling spectroscopy to probe the molecular orbitals of ribonucleotides, new experimental biophysical parameters that fingerprint these molecular orbitals, and a machine learning classification algorithm to distinguish between the ribonucleotides. The algorithm uses tunneling spectroscopy measurements on an unknown ribonucleotide to determine its chemical identity and the presence of local chemical modifications. Combining this with structure-dependent chemical labeling presents the possibility of mapping both the sequence and local structure of individual RNA molecules. By optimizing the base-calling algorithm, we show a high accuracy for both ribonucleotide discrimination (>99.8%) and chemical label identification (>98%) with a relatively modest molecular coverage (35 repeat measurements). This lays the groundwork for simultaneous sequencing and structural mapping of single unknown RNA molecules, and paves the way for probing the sequence–structure–function relationship within the transcriptome at an unprecedented level of detail.

Hepatitis C virus (HCV) infection is a global health problem, with nearly 2 million new infections occurring every year and up to 85% of these infections becoming chronic infections that pose serious long-term health risks. To effectively reduce the prevalence of HCV infection and associated diseases, it is important to understand the intracellular dynamics of the viral life cycle. Here, we present a detailed mathematical model that represents the full hepatitis C virus life cycle. It is the first full HCV model to be fit to acute intracellular infection data and the first to explore the functions of distinct viral proteins, probing multiple hypotheses of cis - and trans -acting mechanisms to provide insights for drug targeting. Model parameters were derived from the literature, experiments, and fitting to experimental intracellular viral RNA, extracellular viral titer, and HCV core and NS3 protein kinetic data from viral inoculation to steady state. Our model predicts higher rates for protein translation and polyprotein cleavage than previous replicon models and demonstrates that the processes of translation and synthesis of viral RNA have the most influence on the levels of the species we tracked in experiments. Overall, our experimental data and the resulting mathematical infection model reveal information about the regulation of core protein during infection, produce specific insights into the roles of the viral core, NS5A, and NS5B proteins, and demonstrate the sensitivities of viral proteins and RNA to distinct reactions within the life cycle. IMPORTANCE We have designed a model for the full life cycle of hepatitis C virus. Past efforts have largely focused on modeling hepatitis C virus replicon systems, in which transfected subgenomic HCV RNA maintains autonomous replication in the absence of virion production or spread. We started with the general structure of these previous replicon models and expanded it to create a model that incorporates the full virus life cycle as well as additional intracellular mechanistic detail. We compared several different hypotheses that have been proposed for different parts of the life cycle and applied the corresponding model variations to infection data to determine which hypotheses are most consistent with the empirical kinetic data. Because the infection data we have collected for this study are a more physiologically relevant representation of a viral life cycle than data obtained from a replicon system, our model can make more accurate predictions about clinical hepatitis C virus infections.