A Deniable Encryption Method for Modulation-Based DNA Storage.

Recent advancements in synthesis and sequencing techniques have made deoxyribonucleic acid (DNA) a promising alternative for next-generation digital storage. As it approaches practical application, ensuring the security of DNA-stored information has become a critical problem. Deniable encryption allows the decryption of different information from the same ciphertext, ensuring that the "plausible" fake information can be provided when users are coerced to reveal the real information. In this paper, we propose a deniable encryption method that uniquely leverages DNA noise channels. Specifically, true and fake messages are encrypted by two similar modulation carriers and subsequently obfuscated by inherent errors. Experiment results demonstrate that our method not only can conceal true information among fake ones indistinguishably, but also allow both the coercive adversary and the legitimate receiver to decrypt the intended information accurately. Further security analysis validates the resistance of our method against various typical attacks. Compared with conventional DNA cryptography methods based on complex biological operations, our method offers superior practicality and reliability, positioning it as an ideal solution for data encryption in future large-scale DNA storage applications.

Biotransformation of ginsenoside compound K using ß-glucosidase in deep eutectic solvents.

Ginsenoside compound K (CK) holds significant potential for application in the pharmaceutical industry, which exhibits numerous pharmacological activity such as cardioprotective and antidiabetic. However, the difficult separation technique and limited yield of CK hinder its widespread use. The study investigated the process of converting ginsenoside CK using ß-glucosidase. It aimed to determine the specific site where the enzyme binds and the most favorable arrangement of the enzyme. Molecular docking was also employed to determine the interaction between ß-glucosidase and ginsenosides, indicating a strong and spontaneous contact force between them. The effectiveness of the conversion process was further improved using a "green" deep eutectic solvent (DES). A univariate experimental design was used to determine the composition of DES and the optimal hydrolysis conditions for ß-glucosidase to convert ginsenoside Rb1 into ginsenoside CK. The employment of ß-glucosidase enzymatic hydrolysis in the synthesis of rare ginsenoside CK applying the environmentally friendly solvent DES is not only viable and effective but also appropriate for industrial use. The characterization methods confirmed that DES did not disrupt the structure and conformation of ß-glucosidase. In ChCl:EG = 2:1 (30%, v/v), pH 5.0 of DES buffer, reaction temperature 50 ℃, enzyme substrate mass ratio 1:1, after 36 h of reaction, the CK yield was 1.24 times that in acetate buffer, which can reach 86.2%. In this study, the process of using ß-glucosidase enzymatic hydrolysis and producing rare ginsenoside CK in green solvent DES is feasible, efficient and suitable for industrial production and application.

Feedback regulation of the isoprenoid pathway by SsdTPS overexpression has the potential to enhance plant tolerance to drought stress.

In order to maintain the dynamic physiological balance, plants are compelled to adjust their energy metabolism and signal transduction to cope with the abiotic stresses caused by complex and changeable environments. The diterpenoid natural compound and secondary metabolites, sclareol, derived from Salvia sclarea, has gained significant attention owing to its economic value as a spice material and diverse physiological activities. Here, we focused on the roles and regulatory mechanisms of the sclareol diterpene synthase gene SsdTPS in the resistance of S. sclarea to abiotic stresses. Our results suggested that abiotic stresses could induce the response and upregulation of SsdTPS expression and isoprenoid pathway in S. sclarea. Ectopic expression of SsdTPS conferred drought tolerance in transgenic Arabidopsis, compared with wild-type. Overexpression of SsdTPS enhanced the transcription of ABA signal transduction synthetic regulators and induced the positive feedback upregulating key regulatory genes in the MEP pathway, thereby promoting the increase of ABA content and improving drought tolerance in transgenic plants. In addition, SsdTPS-overexpressed transgenic Arabidopsis improved the responses of stomatal regulatory genes and ROS scavenging enzyme activities and gene expression to drought stress. This promoted the stomatal closure and ROS reduction, thus enhancing water retention capacity and reducing oxidative stress damage. These findings unveil the potentially positive role of SsdTPS in orchestrating multiple regulatory mechanisms and maintaining homeostasis for improved abiotic stress resistance in S. sclarea, providing a novel insight into strategies for promoting drought resistance and cultivating highly tolerant plants.

Limit and screen sequences with high degree of secondary structures in DNA storage by deep learning method.

BACKGROUND: In single-stranded DNAs/RNAs, secondary structures are very common especially in long sequences. It has been recognized that the high degree of secondary structures in DNA sequences could interfere with the correct writing and reading of information in DNA storage. However, how to circumvent its side-effect is seldom studied. METHOD: As the degree of secondary structures of DNA sequences is closely related to the magnitude of the free energy released in the complicated folding process, we first investigate the free-energy distribution at different encoding lengths based on randomly generated DNA sequences. Then, we construct a bidirectional long short-term (BiLSTM)-attention deep learning model to predict the free energy of sequences. RESULTS: Our simulation results indicate that the free energy of DNA sequences at a specific length follows a right skewed distribution and the mean increases as the length increases. Given a tolerable free energy threshold of 20 kcal/mol, we could control the ratio of serious secondary structures in the encoding sequences to within 1% of the significant level through selecting a feasible encoding length of 100 nt. Compared with traditional deep learning models, the proposed model could achieve a better prediction performance both in the mean relative error (MRE) and the coefficient of determination (R2). It achieved MRE = 0.109 and R2 = 0.918 respectively in the simulation experiment. The combination of the BiLSTM and attention module can handle the long-term dependencies and capture the feature of base pairing. Further, the prediction has a linear time complexity which is suitable for detecting sequences with severe secondary structures in future large-scale applications. Finally, 70 of 94 predicted free energy can be screened out on a real dataset. It demonstrates that the proposed model could screen out some highly suspicious sequences which are prone to produce more errors and low sequencing copies.

A Robust and Efficient DNA Storage Architecture Based on Modulation Encoding and Decoding.

Synthetic DNA has been widely considered an attractive medium for digital data storage. However, the random insertion-deletion-substitution (IDS) errors in the sequenced reads still remain a critical challenge to reliable data recovery. Motivated by the modulation technique in the communication field, we propose a new DNA storage architecture to solve this problem. The main idea is that all binary data are modulated into DNA sequences with the same AT/GC patterns, which facilitate the detection of indels in noisy reads. The modulation signal could not only satisfy the encoding constraints but also serve as prior information to detect the potential positions of errors. Experiments on simulation and real data sets demonstrate that modulation encoding provides a simple way to comply with biological constraints for sequence encoding (i.e., balanced GC content and avoiding homopolymers). Furthermore, modulation decoding is highly efficient and extremely robust, which can correct up to ∼40% of errors. In addition, it is robust to imperfect clustering reconstruction, which is very common in practice. Although our method has a relatively low logical density of 1.0 bits/nt, its high robustness may provide a wide space for developing low-cost synthetic technologies. We believe this new architecture may boost the early coming of large-scale DNA storage applications in the future.

Alleviation of cadmium-induced photoinhibition and oxidative stress by melatonin in Chlamydomonas reinhardtii.

As one of the most threatening challenges to the natural environment and human health, cadmium (Cd) pollution has seriously impacted natural organisms. Green algae, such as Chlamydomonas reinhardtii (C. reinhardtii), can provide a safer, lower cost, and more effective ecological approach to the treatment of heavy metal ions in wastewater due to their sorption properties. However, heavy metal ions affect C. reinhardtii when adsorbed. Melatonin is able to protect the plant body from damage when the plant is under biotic/abiotic stress. Therefore, we investigated the effects of melatonin on the cell morphology, chlorophyll content, chlorophyll fluorescence parameters, enzymatic activity of the antioxidant system, gene expression, and the ascorbic acid (AsA)-glutathione (GSH) cycle of C. reinhardtii under the stress of Cd (13 mg/L). Our results indicated that Cd significantly induced photoinhibition and overaccumulation of reactive oxygen species (ROS). By application with the concentration of 1.0 µM melatonin, the algal solute of C. reinhardtii under the Cd stress gradually regained its green color, the cell morphology became intact, and the photosynthetic electron transport function was retained. However, in the melatonin-silenced strain, there was a significant decrease in all of the above indicators. In addition, the use of exogenous melatonin or the expression of endogenous melatonin genes could enhance the intracellular enzyme activities of catalase (CAT), peroxidase (POD), superoxide dismutase (SOD), ascorbate peroxidase (APX), and glutathione reductase (GR). It also upregulated the expression of active enzyme genes such as SOD1, CAT1, FSD1, GSH1, GPX5, and GSHR1. These results indicate that the presence of melatonin effectively protects the activity of photosynthetic system II in C. reinhardtii, enhances antioxidant activity, upregulates gene expression in the AsA-GSH cycle, and reduces the level of ROS, thereby alleviating the damage caused by Cd toxicity.

An image cryptography method by highly error-prone DNA storage channel.

Introduction: Rapid development in synthetic technologies has boosted DNA as a potential medium for large-scale data storage. Meanwhile, how to implement data security in the DNA storage system is still an unsolved problem. Methods: In this article, we propose an image encryption method based on the modulation-based storage architecture. The key idea is to take advantage of the unpredictable modulation signals to encrypt images in highly error-prone DNA storage channels. Results and Discussion: Numerical results have demonstrated that our image encryption method is feasible and effective with excellent security against various attacks (statistical, differential, noise, and data loss). When compared with other methods such as the hybridization reactions of DNA molecules, the proposed method is more reliable and feasible for large-scale applications.

A Novel Image Encryption Scheme for DNA Storage Systems Based on DNA Hybridization and Gene Mutation.

With the rapid development of DNA (deoxyribonucleic acid) storage technologies, storing digital images in DNA is feasible. Meanwhile, the information security in DNA storage system is still a problem to solve. Therefore, in this paper, we propose a DNA storage-oriented image encryption algorithm utilizing the information processing mechanisms in molecule biology. The basic idea is to perform pixel replacement by gene hybridization, and implement dual diffusion by pixel diffusion and gene mutation. The ciphertext DNA image can be synthesized and stored in DNA storage system after encryption. Experimental results demonstrate it can resist common attacks, and shows a strong robustness against sequence loss and base substitution errors in the DNA storage channel. A DNA storage-oriented image encryption algorithm based on gene hybridization and gene mutation, First, we scramble rows and columns of the plaintext image by dynamic Josephus traversing. Second, we replace the pixels by gene hybridization. Finally, we diffuse the image matrix in binary domain and encode pixels into 8-base strands which are later further diffused by gene mutation. The ciphertext image can be synthesized according to the mutant gene codes and stored in any DNA storage system.

A highly sensitive bead-based flow cytometric competitive binding assay to detect SARS-CoV-2 neutralizing antibody activity.

Accurate detection of SARS-CoV-2 neutralizing antibody (nAb) is critical for assessing the immunity levels after virus infection or vaccination. As fast, cost-effective alternatives to viral infection-based assays, competitive binding (CB) assays were developed to quantitate nAb by monitoring the ability of sera to inhibit the binding of viral spike (S) protein to the angiotensin converting enzyme 2 (ACE2) receptor. Herein, we established a bead-based flow cytometric CB assay and tested the detection performance of six combination models, i.e. immobilized ACE2 and soluble Fc-tagged S1 subunit of S protein (iACE2/S1-Fc), immobilized ACE2 and soluble Fc-tagged receptor binding domain (RBD) of S protein (iACE2/RBD-Fc), immobilized S1 and soluble Fc-tagged ACE2 (iS1/ACE2-Fc), immobilized S1 and soluble His-tagged ACE2 (iS1/ACE2-His), immobilized RBD and soluble Fc-tagged ACE2 (iRBD/ACE2-Fc), and immobilized RBD and soluble His-tagged ACE2 (iRBD/ACE2-His). Using SARS-CoV-2 monoclonal antibodies and sera of convalescent COVID-19 patients and vaccinated subjects, the combination models iACE2/RBD-Fc, iACE2/S1-Fc and iS1/ACE2-His were identified to be able to specifically detect SARS-CoV-2 nAb, among which iACE2/RBD-Fc model showed the highest sensitivity, superior to a commercial SARS-CoV-2 surrogate virus neutralization test (sVNT) ELISA kit. Further studies demonstrated that the sensitivity and specificity of CB assays were affected by the tag of ACE2, type of spike and method of measuring binding rate between ACE2 and spike. Moreover, the iACE2/RBD-Fc model showed good performance in detecting kinetic development of nAb against both the prototype SARS-CoV-2 strain and an omicron variant of SARS-CoV-2 in people immunized by an inactivated SARS-CoV-2 vaccine, and the results of iACE2/RBD-Fc model are correlated well with those of live virus-based and pseudovirus-based neutralization tests, demonstrating the potential to be developed into a highly sensitive, specific, versatile and high-throughput method for detecting SARS-CoV-2 nAb in clinical practice.

Bioluminescence imaging of mouse monocyte chemoattractant protein-1 expression in inflammatory processes.

Monocyte chemoattractant protein-1 (MCP-1) plays a crucial role in various inflammatory diseases. To reveal the impact of MCP-1 during diseases and to develop anti-inflammatory agents, we establish a transgenic mouse line. The firefly luciferase gene is incorporated into the mouse genome and driven by the endogenous MCP-1 promoter. A bioluminescence photographing system is applied to monitor luciferase levels in live mice during inflammation, including lipopolysaccharide-induced sepsis, concanavalin A-induced T cell-dependent liver injury, CCl 4-induced acute hepatitis, and liver fibrosis. The results demonstrate that the luciferase signal induced in inflammatory processes is correlated with endogenous MCP-1 expression in mice. Furthermore, the expressions of MCP-1 and the luciferase gene are dramatically inhibited by administration of the anti-inflammatory drug dexamethasone in a septicemia model. Our results suggest that the transgenic MCP-1-Luc mouse is a useful model to study MCP-1 expression in inflammation and disease and to evaluate the efficiency of anti-inflammatory drugs in vivo.

Molecular Cloning and Analysis of an Acetyl-CoA C-acetyltransferase Gene (EkAACT) from Euphorbia kansui Liou.

Terpenoids are the largest class of natural products and are essential for cell functions in plants and their interactions with the environment. Acetyl-CoA acetyltransferase (AACT, EC2.3.1.9) can catalyze a key initiation step of the mevalonate pathway (MVA) for terpenoid biosynthesis and is modulated by many endogenous and external stimuli. Here, the function and expression regulation activities of AACT in Euphorbia kansui Liou (EkAACT) were reported. Compared with wild-type Arabidopsis, the root length, whole seedling fresh weight and growth morphology of EkAACT-overexpressing plants were slightly improved. The transcription levels of AtAACT, AtMDC, AtMK, AtHMGR, and AtHMGS in the MVA pathway and total triterpenoid accumulation increased significantly in transgenic Arabidopsis. Under NaCl and PEG treatment, EkAACT-overexpressing Arabidopsis showed a higher accumulation of total triterpenoids, higher enzyme activity of peroxidase (POD) and superoxide dismutase (SOD), increased root length and whole seedling fresh weight, and a decrease in the proline content, which indicated that plant tolerance to abiotic stress was enhanced. Thus, AACT, as the first crucial enzyme, plays a major role in the overall regulation of the MVA pathway.

Mathematical analysis of robustness of oscillations in models of the mammalian circadian clock.

Circadian rhythms in a wide range of organisms are mediated by molecular mechanisms based on transcription-translation feedback. In this paper, we use bifurcation theory to explore mathematical models of genetic oscillators, based on Kim & Forger's interpretation of the circadian clock in mammals. At the core of their models is a negative feedback loop whereby PER proteins (PER1 and PER2) bind to and inhibit their transcriptional activator, BMAL1. For oscillations to occur, the dissociation constant of the PER:BMAL1 complex, [Formula: see text], must be ≤ 0.04 nM, which is orders of magnitude smaller than a reasonable expectation of 1-10 nM for this protein complex. We relax this constraint by two modifications to Kim & Forger's 'single negative feedback' (SNF) model: first, by introducing a multistep reaction chain for posttranscriptional modifications of Per mRNA and posttranslational phosphorylations of PER, and second, by replacing the first-order rate law for degradation of PER in the nucleus by a Michaelis-Menten rate law. These modifications increase the maximum allowable [Formula: see text] to ~2 nM. In a third modification, we consider an alternative rate law for gene transcription to resolve an unrealistically large rate of Per2 transcription at very low concentrations of BMAL1. Additionally, we studied extensions of the SNF model to include a second negative feedback loop (involving REV-ERB) and a supplementary positive feedback loop (involving ROR). Contrary to Kim & Forger's observations of these extended models, we find that, with our modifications, the supplementary positive feedback loop makes the oscillations more robust than observed in the models with one or two negative feedback loops. However, all three models are similarly robust when accounting for circadian rhythms (~24 h period) with [Formula: see text] ≥ 1 nM. Our results provide testable predictions for future experimental studies.

Modeling the temporal dynamics of master regulators and CtrA proteolysis in Caulobacter crescentus cell cycle.

The cell cycle of Caulobacter crescentus involves the polar morphogenesis and an asymmetric cell division driven by precise interactions and regulations of proteins, which makes Caulobacter an ideal model organism for investigating bacterial cell development and differentiation. The abundance of molecular data accumulated on Caulobacter motivates system biologists to analyze the complex regulatory network of cell cycle via quantitative modeling. In this paper, We propose a comprehensive model to accurately characterize the underlying mechanisms of cell cycle regulation based on the study of: a) chromosome replication and methylation; b) interactive pathways of five master regulatory proteins including DnaA, GcrA, CcrM, CtrA, and SciP, as well as novel consideration of their corresponding mRNAs; c) cell cycle-dependent proteolysis of CtrA through hierarchical protease complexes. The temporal dynamics of our simulation results are able to closely replicate an extensive set of experimental observations and capture the main phenotype of seven mutant strains of Caulobacter crescentus. Collectively, the proposed model can be used to predict phenotypes of other mutant cases, especially for nonviable strains which are hard to cultivate and observe. Moreover, the module of cyclic proteolysis is an efficient tool to study the metabolism of proteins with similar mechanisms.

A Hierarchical Error Correction Strategy for Text DNA Storage.

DNA storage has been a thriving interdisciplinary research area because of its high density, low maintenance cost, and long durability for information storage. However, the complexity of errors in DNA sequences including substitutions, insertions and deletions hinders its application for massive data storage. Motivated by the divide-and-conquer algorithm, we propose a hierarchical error correction strategy for text DNA storage. The basic idea is to design robust codes for common characters which have one-base error correction ability including insertion and/or deletion. The errors are gradually corrected by the codes in DNA reads, multiple alignment of character lines, and finally word spelling. On one hand, the proposed encoding method provides a systematic way to design storage friendly codes, such as 50% GC content, no more than 2-base homopolymers, and robustness against secondary structures. On the other hand, the proposed error correction method not only corrects single insertion or deletion, but also deals with multiple insertions or deletions. Simulation results demonstrate that the proposed method can correct more than 98% errors when error rate is less than or equal to 0.05. Thus, it is more powerful and adaptable to the complicated DNA storage applications.

Event-Triggered Consensus Control for Networked Underactuated Robotic Systems.

In this article, the consensus of networked underactuated robotic systems subject to fixed and switched communication networks is discussed by developing some novel event-triggered control algorithms, which can synchronously guarantee the convergence of the active states, the boundedness of the velocities of passive actuators, and the exclusion of Zeno behaviors. In the cases of fixed networks, the sufficient criteria are established for the presented distributed event-triggered mechanisms with and without using neighbors' velocities, in order to achieve a better tradeoff between the communication load and system performance. Besides, in the situation of switched networks, the sufficient criterion is established by assuming that the union of the network has a spanning tree. A distributed sampled-data rule is constructed to decide when to update its own and neighbors' estimated positions, and thus further reduces the unnecessary control cost. Finally, by further extending the main results to three other sampled-data control algorithms, several examples with performance comparisons are provided to validate the efficiency and advantages of the theoretical results.

Rapid Detection of Multiple Classes of ß-Lactam Antibiotics in Blood Using an NDM-1 Biosensing Assay.

Currently, assays for rapid therapeutic drug monitoring (TDM) of ß-lactam antibiotics in blood, which might be of benefit in optimizing doses for treatment of critically ill patients, remain challenging. Previously, we developed an assay for determining the penicillin-class antibiotics in blood using a thermometric penicillinase biosensor. The assay eliminates sample pretreatment, which makes it possible to perform semicontinuous penicillin determinations in blood. However, penicillinase has a narrow substrate specificity, which makes it unsuitable for detecting other classes of ß-lactam antibiotics, such as cephalosporins and carbapenems. In order to assay these classes of clinically useful antibiotics, a novel biosensor was developed using New Delhi metallo-ß-lactamase-1 (NDM-1) as the biological recognition layer. NDM-1 has a broad specificity range and is capable of hydrolyzing all classes of ß-lactam antibiotics in high efficacy with the exception of monobactams. In this study, we demonstrated that the NDM-1 biosensor was able to quantify multiple classes of ß-lactam antibiotics in blood plasma at concentrations ranging from 6.25 mg/L or 12.5 mg/L to 200 mg/L, which covered the therapeutic concentration windows of the tested antibiotics used to treat critically ill patients. The detection of ceftazidime and meropenem was not affected by the presence of the ß-lactamase inhibitors avibactam and vaborbactam, respectively. Furthermore, both free and protein-bound ß-lactams present in the antibiotic-spiked plasma samples were detected by the NDM-1 biosensor. These results indicated that the NDM-1 biosensor is a promising technique for rapid TDM of total ß-lactam antibiotics present in the blood of critically ill patients.

Correction: Critical role of deadenylation in regulating poly(A) rhythms and circadian gene expression.

[This corrects the article DOI: 10.1371/journal.pcbi.1007842.].

EkFLS overexpression promotes flavonoid accumulation and abiotic stress tolerance in plant.

Flavonoids with great medicinal value play an important role in plant individual growth and stress resistance. Flavonol synthetase (FLS) is one of the key enzymes to synthesize flavonoids. However, the role of the FLS gene in flavonoid accumulation and tolerance to abiotic stresses, as well as its mechanism has not yet been investigated systematically in plants. The aim of this research is to evaluate the effect of FLS overexpression on the accumulation of active ingredients and stress resistance in Euphorbia kansui Liou. The results showed that when the EkFLS gene was overexpressed in Arabidopsis thaliana, the accumulation of flavonoids was improved. In addition, when the wild-type and EkFLS overexpressed Arabidopsis plants were treated with ABA and MeJA, compared with WT Arabidopsis, EkFLS overexpressed Arabidopsis promoted stomatal aperture to influence photosynthesis of the plants, which in turn can promote stress resistance. Meanwhile, under MeJA, NaCl, and PEG treatment, EkFLS overexpressed in Arabidopsis induced higher accumulation of flavonoids, which significantly enhanced peroxidase (POD) and superoxide dismutase (SOD) activities that can scavenge reactive oxygen species in cells to protect the plant. These results indicated that EkFLS overexpression is strongly correlated to the increase of flavonoid synthesis and therefore the tolerance to abiotic stresses in plants, providing a theoretical basis for further improving the quality of medicinal plants and their resistance to abiotic stresses simultaneously.

Inhibition of coronavirus infection by a synthetic STING agonist in primary human airway system.

The newly emerged severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) coronavirus initiated a pneumonia outbreak (COVID-19) that rapidly spread worldwide and quickly became a public health emergency of international concern; However to date, except Remdesivir, there are no clinically approved specific or effective medicines to prevent or treat COVID-19. Therefore, the development of novel treatments against coronavirus infections caused by the current SARS-CoV-2 virus, as well as other highly pathogenic human coronaviruses, represents an urgent unmet need. Stimulator of interferon genes (STING) plays a central role in host defense mechanisms against microbial infections. STING activation leads to the induction of both type I interferon and autophagy responses, which elicit strong inhibitory effect against the infections caused by a broad range of microbial pathogens. However, whether STING activation can impact infections from SARS-CoV-2 or other coronaviruses remains largely unknown. In this study, we investigated the anti-coronavirus activity triggered by STING activation. We discovered that dimeric amidobenzimidazole (diABZI), a synthetic small molecule STING receptor agonist, showed potent anti-coronavirus activity against both the common cold human coronavirus 229E (HCoV-229E) and SARS-CoV-2 in cell culture systems. In addition, we demonstrated that the antiviral activity of diABZI was dependent on the interferon pathway in HCoV-229E infected normal human fibroblast lung cells (MRC-5) and reconstituted primary human airway air-liquid interface (ALI) cultures. Furthermore, low-dose of diABZI treatment at 0.1 µM effectively reduced the SARS-CoV-2 viral load at the epithelial apical surface and prevented epithelial damage in the reconstituted primary human bronchial airway epithelial ALI system. Our findings have thus revealed the therapeutic potential of STING agonists, such as diABZI, as treatments for SARS-CoV-2 and other human coronavirus infections.

Discovery of Pyrido[2,3-b]indole Derivatives with Gram-Negative Activity Targeting Both DNA Gyrase and Topoisomerase IV.

The rise of multidrug resistant (MDR) Gram-negative (GN) pathogens and the decline of available antibiotics that can effectively treat these severe infections are a major threat to modern medicine. Developing novel antibiotics against MDR GN pathogens is particularly difficult as compounds have to permeate the GN double membrane, which has very different physicochemical properties, and have to circumvent a plethora of resistance mechanisms such as multiple efflux pumps and target modifications. The bacterial type II topoisomerases DNA gyrase (GyrA2B2) and Topoisomerase IV (ParC2E2) are highly conserved targets across all bacterial species and validated in the clinic by the fluoroquinolones. Dual inhibitors targeting the ATPase domains (GyrB/ParE) of type II topoisomerases can overcome target-based fluoroquinolone resistance. However, few ATPase inhibitors are active against GN pathogens. In this study, we demonstrated a successful strategy to convert a 2-carboxamide substituted azaindole chemical scaffold with only Gram-positive (GP) activity into a novel series with also potent activity against a range of MDR GN pathogens. By systematically fine-tuning the many physicochemical properties, we identified lead compounds such as 17r with a balanced profile showing potent GN activity, high aqueous solubility, and desirable PK features. Moreover, we showed the bactericidal efficacy of 17r using a neutropenic mouse thigh infection model.