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1. Cannabis sativa CBD Extract Shows Promising Antibacterial Activity against Salmonella typhimurium and S. newington

   https://doi.org/10.3390/molecules27092669  

   Gildea, Logan; Ayariga, Joseph Atia; Ajayi, Olufemi S.; Xu, Junhuan; Villafane, Robert; Samuel-Foo, Michelle (May 2022, Molecules)

   Products derived from Cannabis sativa L. have gained increased interest and popularity. As these products become common amongst the public, the health and potential therapeutic values associated with hemp have become a premier focus of research. While the psychoactive and medicinal properties of Cannabis products have been extensively highlighted in the literature, the antibacterial properties of cannabidiol (CBD) have not been explored in depth. This research serves to examine the antibacterial potential of CBD against Salmonella newington and S. typhimurium. In this study, we observed bacterial response to CBD exposure through biological assays, bacterial kinetics, and fluorescence microscopy. Additionally, comparative studies between CBD and ampicillin were conducted against S. typhimurium and S. newington to determine comparative efficacy. Furthermore, we observed potential resistance development of our Salmonella spp. against CBD treatment. 

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2. Photocatalytic and Photothermal Antimicrobial Mussel-Inspired Nanocomposites for Biomedical Applications

   https://doi.org/10.3390/ijms241713272  

   Soto-Garcia, Luis F.; Guerrero-Rodriguez, Ingrid D.; Hoang, Luu; Laboy-Segarra, Samantha Lauren; Phan, Ngan T.; Villafuerte, Enrique; Lee, Juhyun; Nguyen, Kytai T. (September 2023, International Journal of Molecular Sciences)

   Bacterial infection has traditionally been treated with antibiotics, but their overuse is leading to the development of antibiotic resistance. This may be mitigated by alternative approaches to prevent or treat bacterial infections without utilization of antibiotics. Among the alternatives is the use of photo-responsive antimicrobial nanoparticles and/or nanocomposites, which present unique properties activated by light. In this study, we explored the combined use of titanium oxide and polydopamine to create nanoparticles with photocatalytic and photothermal antibacterial properties triggered by visible or near-infrared light. Furthermore, as a proof-of-concept, these photo-responsive nanoparticles were combined with mussel-inspired catechol-modified hyaluronic acid hydrogels to form novel light-driven antibacterial nanocomposites. The materials were challenged with models of Gram-negative and Gram-positive bacteria. For visible light, the average percentage killed (PK) was 94.6 for E. coli and 92.3 for S. aureus. For near-infrared light, PK for E. coli reported 52.8 and 99.2 for S. aureus. These results confirm the exciting potential of these nanocomposites to prevent the development of antibiotic resistance and also to open the door for further studies to optimize their composition in order to increase their bactericidal efficacy for biomedical applications. 

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3. Horizontal Gene Transfer Is the Main Driver of Antimicrobial Resistance in Broiler Chicks Infected with Salmonella enterica Serovar Heidelberg

   https://doi.org/10.1128/mSystems.00729-21  

   Oladeinde, Adelumola; Abdo, Zaid; Press, Maximilian O.; Cook, Kimberly; Cox, Nelson A.; Zwirzitz, Benjamin; Woyda, Reed; Lakin, Steven M.; Thomas, Jesse C.; Looft, Torey; et al (August 2021, mSystems)

   Garrido, Daniel (Ed.)

   ABSTRACT The overuse and misuse of antibiotics in clinical settings and in food production have been linked to the increased prevalence and spread of antimicrobial resistance (AR). Consequently, public health and consumer concerns have resulted in a remarkable reduction in antibiotics used for food animal production. However, there are no data on the effectiveness of antibiotic removal in reducing AR shared through horizontal gene transfer (HGT). In this study, we used neonatal broiler chicks and Salmonella enterica serovar Heidelberg, a model food pathogen, to test if chicks raised antibiotic free harbor transferable AR. We challenged chicks with an antibiotic-susceptible S . Heidelberg strain using various routes of inoculation and determined if S . Heidelberg isolates recovered carried plasmids conferring AR. We used antimicrobial susceptibility testing and whole-genome sequencing (WGS) to show that chicks grown without antibiotics harbored an antimicrobial resistant S . Heidelberg population at 14 days after challenge and chicks challenged orally acquired AR at a higher rate than chicks inoculated via the cloaca. Using 16S rRNA gene sequencing, we found that S . Heidelberg infection perturbed the microbiota of broiler chicks, and we used metagenomics and WGS to confirm that a commensal Escherichia coli population was the main reservoir of an IncI1 plasmid acquired by S . Heidelberg. The carriage of this IncI1 plasmid posed no fitness cost to S . Heidelberg but increased its fitness when exposed to acidic pH in vitro . These results suggest that HGT of plasmids carrying AR shaped the evolution of S . Heidelberg and that antibiotic use reduction alone is insufficient to limit antibiotic resistance transfer from commensal bacteria to Salmonella enterica . IMPORTANCE The reported increase in antibiotic-resistant bacteria in humans has resulted in a major shift away from antibiotic use in food animal production. This shift has been driven by the assumption that removing antibiotics will select for antibiotic susceptible bacterial taxa, which in turn will allow the currently available antibiotic arsenal to be more effective. This change in practice has highlighted new questions that need to be answered to assess the effectiveness of antibiotic removal in reducing the spread of antibiotic resistance bacteria. This research demonstrates that antibiotic-susceptible Salmonella enterica serovar Heidelberg strains can acquire multidrug resistance from commensal bacteria present in the gut of neonatal broiler chicks, even in the absence of antibiotic selection. We demonstrate that exposure to acidic pH drove the horizontal transfer of antimicrobial resistance plasmids and suggest that simply removing antibiotics from food animal production might not be sufficient to limit the spread of antimicrobial resistance. 

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4. Modification of narrow‐spectrum peptidomimetic polyurethanes with fatty acid chains confers broad‐spectrum antibacterial activity

   https://doi.org/10.1002/pi.5773  

   Peng, Chao; Zhang, Tian; Ortiz‐Ortiz, Deliris_N; Vishwakarma, Apoorva; Barton, Hazel_A; Joy, Abraham (February 2019, Polymer International)

   Abstract Each year, thousands of patients die from antimicrobial‐resistant bacterial infections that fail to respond to conventional antibiotic treatment. Antimicrobial polymers are a promising new method of combating antibiotic‐resistant bacterial infections. We have previously reported the synthesis of a series of narrow‐spectrum peptidomimetic antimicrobial polyurethanes that are effective against Gram‐negative bacteria, such asEscherichia coli; however, these polymers are not effective against Gram‐positive bacteria, such asStaphylococcus aureus. With the aim of understanding the correlation between chemical structure and antibacterial activity, we have subsequently developed three structural variants of these antimicrobial polyurethanes using post‐polymerization modification with decanoic acid and oleic acid. Our results show that such modifications converted the narrow‐spectrum antibacterial activity of these polymers into broad‐spectrum activity against Gram‐positive species such asS. aureus, however, also increasing their toxicity to mammalian cells. Mechanistic studies of bacterial membrane disruption illustrate the differences in antibacterial action between the various polymers. The results demonstrate the challenge of balancing antimicrobial activity and mammalian cell compatibility in the design of antimicrobial polymer compositions. © 2019 Society of Chemical Industry 

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5. DeepMRG: a multi-label deep learning classifier for predicting bacterial metal resistance genes

   https://doi.org/10.1101/2023.11.14.566903  

   Emon, Muhit Islam; Zhang, Liqing (November 2023, bioRxiv)

   Abstract The widespread misuse of antibiotics has escalated antibiotic resistance into a critical global public health concern. Beyond antibiotics, metals function as antibacterial agents. Metal resistance genes (MRGs) enable bacteria to tolerate metal-based antibacterials and may also foster antibiotic resistance within bacterial communities through co-selection. Thus, predicting bacterial MRGs is vital for elucidating their involvement in antibiotic resistance and metal tolerance mechanisms. The “best hit” approach is mainly utilized to identify and annotate MRGs. This method is sensitive to cutoff values and produces a high false negative rate. Other than the best hit approach, only a few antimicrobial resistance (AMR) detection tools exist for predicting MRGs. However, these tools lack comprehensive annotation for MRGs conferring resistance to multiple metals. To address such limitations, we introduce DeepMRG, a deep learning-based multi-label classifier, to predict bacterial MRGs. Because a bacterial MRG can confer resistance to multiple metals, DeepMRG is designed as a multi-label classifier capable of predicting multiple metal labels associated with an MRG. It leverages bit score-based similarity distribution of sequences with experimentally verified MRGs. To ensure unbiased model evaluation, we employed a clustering method to partition our dataset into six subsets, five for cross-validation and one for testing, with non-homologous sequences, mitigating the impact of sequence homology. DeepMRG consistently achieved high overall F1-scores and significantly reduced false negative rates across a wide range of datasets. It can be used to predict bacterial MRGs in metagenomic or isolate assemblies. The web server of DeepMRG can be accessed athttps://deepmrg.cs.vt.edu/deepmrgand the source code is available athttps://github.com/muhit-emon/DeepMRGunder the MIT license. 

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