From Genome to Drugs: New Approaches in Antimicrobial Discovery

Molecular and computational insights into algD biofilm genes in multi drug resistant and extensively drug resistant Pseudomonasaeruginosa

Antibiotic-resistance and biofilm formation are the main virulence factors and present a serious treatment challenge in Pseudomonas aeruginosa. This study aimed to investigate antimicrobial resistance, genetic diversity, biofilm-specific algD gene, and computational analysis of clinical isolates. Forty two isolates of P. aeruginosa were examined by PCR, ELISA, sangers sequencing, phylogenetic analysis, MolProbity score, 3D structural modelling, Ramachandran plot, multiple sequence alignment, and protein domain analysis. According to the results, PCR analysis revealed algD gene presence in all isolates. ELISA showed 55 % (n = 23) of the samples produced strong biofilms, 38 % (n = 16) produced moderate biofilms, and 7 % (3) produced weak biofilms. The evolutionary relationships of 8 (S1-S8) P. aeruginosa strains with 81 reference strains were illustrated by the phylogenetic tree. Samples S1-S8 showed excellent MolProbity score (<1.00), low clashed scores (0.67-0.70), most residues in the favored regions (∼96.2-96.5 %), low Ramachandran outliers (0.53-0.56 %), low Rotamer outlier (0.62 %), low bad angles (<2), indicated high-quality models and values preferred percentages showed excellent models with structural refinement. Over all samples S5 and S6 stood out as the top choices for high-confidence modeling and applications. The essential catalytic domain UDP-glucose/GDP-mannose dehydrogenase was identified that could be used as important therapeutic targets. High quality models indicated suitability for downstream applications, such as studying protein-ligand interactions, understanding structural aspects of biofilm-resistant bacteria. This study improved our knowledge of the mechanisms underlying P. aeruginosa biofilm resistance and sets the stage for the development of novel therapeutic and diagnostic strategies to combat multidrug resistant strains.

Progress in the Identification and Design of Novel Antimicrobial Peptides Against Pathogenic Microorganisms

The occurrence and spread of antimicrobial resistance (AMR) pose a looming threat to human health around the world. Novel antibiotics are urgently needed to address the AMR crisis. In recent years, antimicrobial peptides (AMPs) have gained increasing attention as potential alternatives to conventional antibiotics due to their abundant sources, structural diversity, broad-spectrum antimicrobial activity, and ease of production. Given its significance, there has been a tremendous advancement in the research and development of AMPs. Numerous AMPs have been identified from various natural sources (e.g., plant, animal, human, microorganism) based on either well-established isolation or bioinformatic pipelines. Moreover, computer-assisted strategies (e.g., machine learning (ML) and deep learning (DL)) have emerged as a powerful and promising technology for the accurate prediction and design of new AMPs. It may overcome some of the shortcomings of traditional antibiotic discovery and contribute to the rapid development and translation of AMPs. In these cases, this review aims to appraise the latest advances in identifying and designing AMPs and their significant antimicrobial activities against a wide range of bacterial pathogens. The review also highlights the critical challenges in discovering and applying AMPs.

Computational approach based on freely accessible tools for antimicrobial drug design

Antimicrobial drug development is crucial for public health, especially with the emergence of pandemics and drug resistance that prompts the search for new therapeutic resources. In this context, in silico assays consist of a valuable approach in the rational drug design because they enable a faster and more cost-effective identification of drug candidates compared to in vitro screening. However, once a potential drug is identified, in vitro and in vivo assays are essential to verify the expected activity of the compound and advance it through the subsequent stages of drug development. This work aims to outline an in silico protocol that utilizes only freely available computational tools for identifying new potential antimicrobial agents, which is also suitable in the broad spectrum of drug design. Additionally, this paper reviews relevant computational methods in this context and provides a summary of information concerning the protein-ligand interaction.

Synthesis of Silver Nanoparticles and Evaluation of Antimicrobial Activity Using the Aqueous Extract of Pterodon emarginatus Seeds

The decline in research for new antimicrobials, combined with the rise in bacterial resistance, has become a critical issue that is expected to worsen over time. As an alternative, health sciences have integrated materials engineering to develop new bioactive compounds through the interaction of nanoparticles with plant-derived compounds. These compounds offer advantages such as high bioavailability and low cost, exemplified by Pterodon emarginatus, a plant native to the Brazilian Cerrado. This study aimed to synthesize and stabilize silver nanoparticles (AgNPs) using the aqueous extract of Pterodon emarginatus seeds and evaluate their antimicrobial activity against fungal (Candida albicans) and bacterial (Escherichia coli) strains. The synthesis of AgNPs was performed using the aqueous plant extract as a stabilizing agent, with formation confirmed through UV-Vis spectroscopy, showing a characteristic absorbance peak at 400 nm. The resulting AgNPs were then tested for antimicrobial activity. While the aqueous extract of P. emarginatus alone showed no significant antimicrobial activity, the synthesized AgNPs demonstrated remarkable antifungal and antibacterial effects. These results highlight the synergistic interaction between the bactericidal properties of AgNPs and the bioactive compounds present in the plant extract. This approach offers a promising and sustainable alternative for the development of new antimicrobial agents, addressing the urgent need for effective solutions to combat microbial resistance.

A systematic overview of strategies for photosensitizer and light delivery in antibacterial photodynamic therapy for lung infections

Antimicrobial photodynamic therapy (aPDT) emerges as a viable treatment strategy for infections resistant to conventional antibiotics. A complex interplay of factors, including intracellular photosensitizer (PS) accumulation, photochemical reaction type, and oxygen levels, determines the efficacy of aPDT. Recent progress includes the development of modified PSs with enhanced lipophilicity and target-specific strategies to improve bacterial cell wall penetration and targeting. Nanotechnology-based approaches, such as using nanomaterials for targeted PS delivery, have shown promise in enhancing aPDT efficacy. Advancements in light delivery methods for aPDT, such as transillumination of large lesions and local light delivery using fiber optic techniques, are also being explored to optimize treatment efficacy in clinical settings. The limited number of animal models and clinical trials specifically designed to assess the efficacy of aPDT for lung infections highlights the need for further research in this critical area. The potential prospects of aPDT for lung tissue infections originating from antibiotic-resistant bacterial infections are also discussed in this review.

In silico approaches supporting drug repurposing for Leishmaniasis: a scoping review

The shortage of treatment options for leishmaniasis, especially those easy to administer and viable for deployment in the world's poorest regions, highlights the importance of employing these strategies to cost-effectively investigate repurposing candidates. This scoping review aims to map the studies using in silico methodologies for drug repurposing against leishmaniasis. This study followed JBI recommendations for scoping reviews. Articles were searched on PubMed, Scopus, and Web of Science databases using keywords related to leishmaniasis and in silico methods for drug discovery, without publication date restrictions. The selection was based on primary studies involving computational methods for antileishmanial drug repurposing. Information about methodologies, obtained data, and outcomes were extracted. After the full-text appraisal, 34 studies were included in this review. Molecular docking was the preferred method for evaluating repurposing candidates (n=25). Studies reported 154 unique ligands and 72 different targets, sterol 14-alpha demethylase and trypanothione reductase being the most frequently reported. In silico screening was able to correctly pinpoint some known active pharmaceutical classes and propose previously untested drugs. Fifteen drugs investigated in silico exhibited low micromolar inhibition (IC50 < 10 µM) of Leishmania spp. in vitro. In conclusion, several in silico repurposing candidates are yet to be investigated in vitro and in vivo. Future research could expand the number of targets screened and employ advanced methods to optimize drug selection, offering new starting points for treatment development. See also the graphical abstract(Fig. 1).

Clinical translation of nanomedicine with integrated digital medicine and machine learning interventions

Nanomaterials based therapeutics transform the ways of disease prevention, diagnosis and treatment with increasing sophistications in nanotechnology at a breakneck pace, but very few could reach to the clinic due to inconsistencies in preclinical studies followed by regulatory hinderances. To tackle this, integrating the nanomedicine discovery with digital medicine provide technologies as tools of specific biological activity measurement. Hence, overcome the redundancies in nanomedicine discovery by the on-site data acquisition and analytics through integrating intelligent sensors and artificial intelligence (AI) or machine learning (ML). Integrated AI/ML wearable sensors directly gather clinically relevant biochemical information from the subject's body and process data for physicians to make right clinical decision(s) in a time and cost-effective way. This review summarizes insights and recommend the infusion of actionable big data computation enabled sensors in burgeoning field of nanomedicine at academia, research institutes, and pharmaceutical industries, with a potential of clinical translation. Furthermore, many blind spots are present in modern clinically relevant computation, one of which could prevent ML-guided low-cost new nanomedicine development from being successfully translated into the clinic was also discussed.

From Data to Decisions: Leveraging Artificial Intelligence and Machine Learning in Combating Antimicrobial Resistance - a Comprehensive Review

The emergence of drug-resistant bacteria poses a significant challenge to modern medicine. In response, Artificial Intelligence (AI) and Machine Learning (ML) algorithms have emerged as powerful tools for combating antimicrobial resistance (AMR). This review aims to explore the role of AI/ML in AMR management, with a focus on identifying pathogens, understanding resistance patterns, predicting treatment outcomes, and discovering new antibiotic agents. Recent advancements in AI/ML have enabled the efficient analysis of large datasets, facilitating the reliable prediction of AMR trends and treatment responses with minimal human intervention. ML algorithms can analyze genomic data to identify genetic markers associated with antibiotic resistance, enabling the development of targeted treatment strategies. Additionally, AI/ML techniques show promise in optimizing drug administration and developing alternatives to traditional antibiotics. By analyzing patient data and clinical outcomes, these technologies can assist healthcare providers in diagnosing infections, evaluating their severity, and selecting appropriate antimicrobial therapies. While integration of AI/ML in clinical settings is still in its infancy, advancements in data quality and algorithm development suggest that widespread clinical adoption is forthcoming. In conclusion, AI/ML holds significant promise for improving AMR management and treatment outcome.

An insight into MDR Acinetobacter baumannii infection and its pathogenesis: Potential therapeutic targets and challenges

Acinetobacter baumannii is observed as a common species of Gram-negative bacteria that exist in soil and water. Despite being accepted as a typical component of human skin flora, it has become an important opportunistic pathogen, especially in healthcare settings. The pathogenicity of A. baumannii is attributed to its virulence factors, which include adhesins, pili, lipopolysaccharides, outer membrane proteins, iron uptake systems, autotransporter, secretion systems, phospholipases etc. These elements provide the bacterium the ability to cling to and penetrate host cells, get past the host immune system, and destroy tissue. Its infection is a major contributor to human pathophysiological conditions including pneumonia, bloodstream infections, urinary tract infections, and surgical site infections. It is challenging to treat infections brought on by this pathogen since this bacterium has evolved to withstand numerous drugs and further emergence of drug-resistant A. baumannii results in higher rates of morbidity and mortality. The long-term survival of this bacterium on surfaces of medical supplies and hospital furniture facilitates its frequent spread in humans from one habitat to another. There is a need for urgent investigations to find effective drug targets for A. baumannii as well as designing novel drugs to reduce the survival and spread of infection. In the current review, we represent the specific features, pathogenesis, and molecular intricacies of crucial drug targets of A. baumannii. This would also assist in proposing strategies and alternative therapies for the prevention and treatment of A. baumannii infections and their spread.

Cas12a/Guide RNA-Based Platform for Rapidly and Accurately Detecting blaKPC Gene in Carbapenem-Resistant Enterobacterales

Purpose

Accurate detection and identification of pathogens and their associated resistance mechanisms are essential prerequisites for implementing precision medicine in the management of Carbapenem-resistant Enterobacterales (CRE). Among the various resistance mechanisms, the production of KPC carbapenemase is the most prevalent worldwide. Consequently, this study aims to develop a convenient and precise nucleic acid detection platform specifically for the blaKPC gene.

Methods

The initial phase of our research methodology involved developing a CRISPR/Cas12a detection framework, which was achieved by designing highly specific single-guide RNAs (sgRNAs) targeting the blaKPC gene. To enhance the sensitivity of this system, we incorporated three distinct amplification techniques-polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), and recombinase polymerase amplification (RPA)-into the CRISPR/Cas12a framework. Subsequently, we conducted a comparative analysis of the sensitivity and specificity of these three amplification methods when used in combination with the CRISPR/Cas12a system. Additionally, we assessed the clinical applicability of the methodologies by evaluating fluorescence readouts from 80 different clinical isolates. Furthermore, we employed lateral flow assay technology to provide a visual representation of the results, facilitating point-of-care testing.

Results

Following a comparative analysis of the sensitivity and specificity of the three methods, we identified the RPA-Cas12a approach as the optimal detection technique. Our findings demonstrated that the limit of detection (LoD) of the RPA-Cas12a platform was 1 aM (~1 copy/µL) for plasmid DNA and 5 × 10³ fg/µL for genomic DNA. Furthermore, both the sensitivity and specificity of the platform achieved 100% upon validation with 80 clinical isolates.

Conclusion

These findings suggest that the developed RPA-Cas12a platform represents a promising tool for the cost-effective, convenient, and accurate detection of the blaKPC gene.

Bacterial cytochrome P450s: a bioinformatics odyssey of substrate discovery

Bacterial P450 cytochromes (BacCYPs) are versatile heme-containing proteins responsible for oxidation reactions on a wide range of substrates, contributing to the production of valuable natural products with limitless biotechnological potential. While the sequencing of microbial genomes has provided a wealth of BacCYP sequences, functional characterization lags behind, hindering our understanding of their roles. This study employs a comprehensive approach to predict BacCYP substrate specificity, bridging the gap between sequence and function. We employed an integrated approach combining sequence and functional data analysis, genomic context exploration, 3D structural modeling with molecular docking, and phylogenetic clustering. The research begins with an in-depth analysis of BacCYP sequence diversity and structural characteristics, revealing conserved motifs and recurrent residues in the active site. Phylogenetic analysis identifies distinct groups within the BacCYP family based on sequence similarity. However, our study reveals that sequence alone does not consistently predict substrate specificity, necessitating additional perspectives. The study delves into the genetic context of BacCYPs, utilizing neighboring gene information to infer potential substrates, a method proven very effective in many cases. Molecular docking is employed to assess BacCYP-substrate interactions, confirming potential substrates and providing insights into selectivity. Finally, a comprehensive strategy is proposed for predicting BacCYP substrates, involving all the evaluated approaches. The effectiveness of this strategy is demonstrated with two case studies, highlighting its potential for substrate discovery.

The role and potential of computer-aided drug discovery strategies in the discovery of novel antimicrobials

Antimicrobial resistance (AMR) has become more of a concern in recent decades, particularly in infections associated with global public health threats. The development of new antibiotics is crucial to ensuring infection control and eradicating AMR. Although drug discovery and development are essential processes in the transformation of a drug candidate from the laboratory to the bedside, they are often very complicated, expensive, and time-consuming. The pharmaceutical sector is continuously innovating strategies to reduce research costs and accelerate the development of new drug candidates. Computer-aided drug discovery (CADD) has emerged as a powerful and promising technology that renews the hope of researchers for the faster identification, design, and development of cheaper, less resource-intensive, and more efficient drug candidates. In this review, we discuss an overview of AMR, the potential, and limitations of CADD in AMR drug discovery, and case studies of the successful application of this technique in the rapid identification of various drug candidates. This review will aid in achieving a better understanding of available CADD techniques in the discovery of novel drug candidates against resistant pathogens and other infectious agents.

Resequencing and characterization of the first Corynebacterium pseudotuberculosis genome isolated from camel

Background

Corynebacterium pseudotuberculosis is a zoonotic Gram-positive bacterial pathogen known to cause different diseases in many mammals, including lymph node abscesses in camels. Strains from biovars equi and ovis of C. pseudotuberculosis can infect camels. Comparative genomics could help to identify features related to host adaptation, and currently strain Cp162 from biovar equi is the only one from camel with a sequenced genome.

Methods

In this work, we compared the quality of three genome assemblies of strain Cp162 that used data from the DNA sequencing platforms SOLiD v3 Plus, IonTorrent PGM, and Illumina HiSeq 2500 with an optical map and investigate the unique features of this strain. For this purpose, we applied comparative genomic analysis on the different Cp162 genome assembly versions and included other 129 genomes from the same species.

Results

Since the first version of the genome, there was an increase of 88 Kbp and 121 protein-coding sequences, a decrease of pseudogenes from 139 to 53, and two inversions and one rearrangement corrected. We identified 30 virulence genes, none associated to the camel host, and the genes rpob2 and rbpA predicted to confer resistance to rifampin. In comparison to 129 genomes of the same species, strain Cp162 has four genes exclusively present, two of them code transposases and two truncated proteins, and the three exclusively absent genes lysG, NUDIX domain protein, and Hypothetical protein. All 130 genomes had the rifampin resistance genes rpob2 and rbpA. Our results found no unique gene that could be associated with tropism to camel host, and further studies should include more genomes and genome-wide association studies testing for genes and SNPs.

Unrealized targets in the discovery of antibiotics for Gram-negative bacterial infections

Advances in areas that include genomics, systems biology, protein structure determination and artificial intelligence provide new opportunities for target-based antibacterial drug discovery. The selection of a 'good' new target for direct-acting antibacterial compounds is the first decision, for which multiple criteria must be explored, integrated and re-evaluated as drug discovery programmes progress. Criteria include essentiality of the target for bacterial survival, its conservation across different strains of the same species, bacterial species and growth conditions (which determines the spectrum of activity of a potential antibiotic) and the level of homology with human genes (which influences the potential for selective inhibition). Additionally, a bacterial target should have the potential to bind to drug-like molecules, and its subcellular location will govern the need for inhibitors to penetrate one or two bacterial membranes, which is a key challenge in targeting Gram-negative bacteria. The risk of the emergence of target-based drug resistance for drugs with single targets also requires consideration. This Review describes promising but as-yet-unrealized targets for antibacterial drugs against Gram-negative bacteria and examples of cognate inhibitors, and highlights lessons learned from past drug discovery programmes.

Repurposing Selamectin as an Antimicrobial Drug against Hospital-Acquired Staphylococcus aureus Infections

The emergence of multidrug-resistant strains requires the urgent discovery of new antibacterial drugs. In this context, an antibacterial screening of a subset of anthelmintic avermectins against gram-positive and gram-negative strains was performed. Selamectin completely inhibited bacterial growth at 6.3 μg/mL concentrations against reference gram-positive strains, while no antibacterial activity was found against gram-negative strains up to the highest concentration tested of 50 μg/mL. Given its relevance as a community and hospital pathogen, further studies have been performed on selamectin activity against Staphylococcus aureus (S. aureus), using clinical isolates with different antibiotic resistance profiles and a reference biofilm-producing strain. Antibacterial studies have been extensive on clinical S. aureus isolates with different antibiotic resistance profiles. Mean MIC90 values of 6.2 μg/mL were reported for all tested S. aureus strains, except for the macrolide-resistant isolate with constitutive macrolide-lincosamide-streptogramin B resistance phenotype (MIC90 9.9 μg/mL). Scanning Electron Microscopy (SEM) showed that selamectin exposure caused relevant cell surface alterations. A synergistic effect was observed between ampicillin and selamectin, dictated by an FIC value of 0.5 against methicillin-resistant strain. Drug administration at MIC concentration reduced the intracellular bacterial load by 81.3%. The effect on preformed biofilm was investigated via crystal violet and confocal laser scanning microscopy. Selamectin reduced the biofilm biomass in a dose-dependent manner with minimal biofilm eradication concentrations inducing a 50% eradication (MBEC50) at 5.89 μg/mL. The cytotoxic tests indicated that selamectin exhibited no relevant hemolytic and cytotoxic activity at active concentrations. These data suggest that selamectin may represent a timely and promising macrocyclic lactone for the treatment of S. aureus infections.

Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections

Introduction:Trypanosoma cruzi, Trypanosoma brucei, and Leishmania spp., commonly referred to as TriTryps, are a group of protozoan parasites that cause important human diseases affecting millions of people belonging to the most vulnerable populations worldwide. Current treatments have limited efficiencies and can cause serious side effects, so there is an urgent need to develop new control strategies. Presently, the identification and prioritization of appropriate targets can be aided by integrative genomic and computational approaches.

Methods: In this work, we conducted a genome-wide multidimensional data integration strategy to prioritize drug targets. We included genomic, transcriptomic, metabolic, and protein structural data sources, to delineate candidate proteins with relevant features for target selection in drug development.

Results and Discussion: Our final ranked list includes proteins shared by TriTryps and covers a range of biological functions including essential proteins for parasite survival or growth, oxidative stress-related enzymes, virulence factors, and proteins that are exclusive to these parasites. Our strategy found previously described candidates, which validates our approach as well as new proteins that can be attractive targets to consider during the initial steps of drug discovery.

Microbial Genomics: Innovative Targets and Mechanisms

Multidrug resistance (MDR) has become an increasing threat to global health because bacteria can develop resistance to antibiotics over time. Scientists worldwide are searching for new approaches that go beyond traditional antibiotic discovery and development pipelines. Advances in genomics, however, opened up an unexplored therapeutic opportunity for the discovery of new antibacterial agents. Genomic approaches have been used to discover several novel antibiotics that target critical processes for bacterial growth and survival, including histidine kinases (HKs), LpxC, FabI, peptide deformylase (PDF), and aminoacyl-tRNA synthetases (AaRS). In this review, we will discuss the use of microbial genomics in the search for innovative and promising drug targets as well as the mechanisms of action for novel antimicrobial agents. We will also discuss future directions on how the utilization of the microbial genomics approach could improve the odds of antibiotic development having a more successful outcome.

In vitro antimicrobial activity and resistance mechanisms of the new generation tetracycline agents, eravacycline, omadacycline, and tigecycline against clinical Staphylococcus aureus isolates

In this study, we investigated the in vitro activity and resistance mechanisms of the new generation tetracycline agents, namely eravacycline, omadacycline, and tigecycline, against Staphylococcus aureus isolates. A total of 1,017 non-duplicate S. aureus isolates were collected and subjected to susceptibility testing against eravacycline, omadacycline, and tigecycline using the broth microdilution method. Tetracyclines-resistant (eravacycline/omadacycline/tigecycline-resistant) isolates were selected to elucidate the resistance mechanisms using polymerase chain reaction (PCR), cloning experiment, efflux pump inhibition, and quantitative real-time PCR. The results of the antibacterial susceptibility testing showed that compared with omadacycline, eravacycline and tigecycline had superior antibacterial activity against S. aureus isolates. Among 1,017 S. aureus, 41 tetracyclines-resistant isolates were identified. These resistant isolates possessed at least one tetracycline resistance gene and genetic mutation in the MepRAB efflux pump and 30S ribosome units. A frameshift mutation in mepB was detected in most tetracyclines-resistant strains (except for JP3349) compared with tetracyclines-susceptible (eravacycline/omadacycline/tigecycline-susceptible) strains. This was first shown to decrease susceptibility to omadacycline, but not to eravacycline and tigecycline. After treatment with eravacycline, omadacycline or tigecycline, overexpression of mepA, tet38, tet(K) and tet(L) was detected. Moreover, multi-locus sequence typing showed a major clonal dissemination type, ST5, and its variant ST764 were seen in most tetracyclines-resistant strains. To conclude, eravacycline and tigecycline exhibited better activity against S. aureus including tetracycline-resistant isolates than omadacycline. The resistance to these new generation tetracyclines due to an accumulation of many resistance mechanisms.

Aspartate α-decarboxylase a new therapeutic target in the fight against Helicobacter pylori infection

Effective eradication therapy for Helicobacter pylori is a worldwide demand. Aspartate α-decarboxylase (ADC) was reported as a drug target in H. pylori, in an in silico study, with malonic acid (MA) as its inhibitor. We evaluated eradicating H. pylori infection through ADC inhibition and the possibility of resistance development. MA binding to ADC was modeled via molecular docking. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of MA were determined against H. pylori ATCC 43504, and a clinical H. pylori isolate. To confirm selective ADC inhibition, we redetermined the MIC in the presence of products of the inhibited enzymatic pathway: β-alanine and pantothenate. HPLC was used to assay the enzymatic activity of H. pylori 6x-his tagged ADC in the presence of different MA concentrations. H. pylori strains were serially exposed to MA for 14 passages, and the MICs were determined. Cytotoxicity in different cell lines was tested. The efficiency of ADC inhibition in treating H. pylori infections was evaluated using a Sprague–Dawley (SD) rat infection model. MA spectrum of activity was determined in different pathogens. MA binds to H. pylori ADC active site with a good docking score. The MIC of MA against H. pylori ranged from 0.5 to 0.75 mg/mL with MBC of 1.5 mg/mL. Increasing β-alanine and pantothenate concentrations proportionally increased MA MIC. The 6x-his tagged ADC activity decreased by increasing MA concentration. No resistance to ADC inhibition was recorded after 14 passages; MA lacked cytotoxicity in all tested cell lines. ADC inhibition effectively eradicated H. pylori infection in SD rats. MA had MIC between 0.625 to 1.25 mg/mL against the tested bacterial pathogens. In conclusion, ADC is a promising target for effectively eradicating H. pylori infection that is not affected by resistance development, besides being of broad-spectrum presence in different pathogens. MA provides a lead molecule for the development of an anti-helicobacter ADC inhibitor. This provides hope for saving the lives of those at high risk of infection with the carcinogenic H. pylori.

Antibacterial Theranostic Agents with Negligible Living Cell Invasiveness: AIE-Active Cationic Amphiphiles Regulated by Alkyl Chain Engineering

To address the threat of bacterial infection in the following post-antibiotic era, developing effective antibacterial approaches is of utmost urgency. Theranostic medicine integrating diagnosis and therapy is a promising protocol to fight against pathogenic bacteria. But numerous reported antibacterial theranostic materials are disclosed to be trapped in the excessive invasiveness to living mammal cells, leading to false positives and possible biosafety risks. Herein, a series of cationic pyridinium-substituted phosphindole oxide derivatives featuring aggregation-induced emission are designed, and alkyl chain engineering is conducted to finely tune their hydrophobicity and investigate their bioaffinity preference for living mammal cells and pathogenic bacteria. Most importantly, an efficient theranostic agent (PyBu-PIO) is acquired that is free from living cell invasiveness with negligible cytotoxicity and yet holds a good affinity for Gram-positive bacteria, including drug-resistant strains, with a superior inactivating effect. Externally applying PyBu-PIO onto Gram-positive bacteria-infected skin wounds can achieve creditable imaging effects and successfully accelerate the healing processes with reliable biosafety. This work proposes living cell invasiveness as a criterion for antibacterial theranostic materials and provides important enlightenment for the design of antibacterial theranostic materials.