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   https://doi.org/10.3389/fcimb.2020.00326  

   Mercer, Derry K. ; Torres, Marcelo D. ; Duay, Searle S. ; Lovie, Emma ; Simpson, Laura ; von Köckritz-Blickwede, Maren ; de la Fuente-Nunez, Cesar ; O'Neil, Deborah A. ; Angeles-Boza, Alfredo M. ( July 2020 , Frontiers in Cellular and Infection Microbiology)
2. Deep Learning Analysis of Vibrational Spectra of Bacterial Lysate for Rapid Antimicrobial Susceptibility Testing

   https://doi.org/10.1021/acsnano.0c05693  

   Thrift, William John ; Ronaghi, Sasha ; Samad, Muntaha ; Wei, Hong ; Nguyen, Dean Gia ; Cabuslay, Antony Superio ; Groome, Chloe E. ; Santiago, Peter Joseph ; Baldi, Pierre ; Hochbaum, Allon I. ; et al ( November 2020 , ACS Nano)

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3. Antimicrobial and Antibiofilm Activities of Helical Antimicrobial Peptide Sequences Incorporating Metal-Binding Motifs

   https://doi.org/10.1021/acs.biochem.9b00440  

   Agbale, Caleb M. ; Sarfo, Justice K. ; Galyuon, Isaac K. ; Juliano, Samuel A. ; Silva, Gislaine G. ; Buccini, Danieli F. ; Cardoso, Marlon H. ; Torres, Marcelo D. ; Angeles-Boza, Alfredo M. ; de la Fuente-Nunez, Cesar ; et al ( August 2019 , Biochemistry)
4. Towards designing globular antimicrobial peptide mimics: role of polar functional groups in biomimetic ternary antimicrobial polymers

   https://doi.org/10.1039/D0SM01896A  

   Rani, Garima ; Kuroda, Kenichi ; Vemparala, Satyavani ( March 2021 , Soft Matter)

   null (Ed.)

   Using atomistic molecular dynamics simulations, we study the interaction of ternary methacrylate polymers, composed of charged cationic, hydrophobic and neutral polar groups, with model bacterial membrane. Our simulation data shows that the random ternary polymers can penetrate deep into the membrane interior and partitioning of even a single polymer has a pronounced effect on the membrane structure. Lipid reorganization, on polymer binding, shows a strong affinity of the ternary polymer for anionic POPG lipids and the same is compared with the control case of binary polymers (only cationic and hydrophobic groups). While binary polymers exhibit strong propensity of acquired amphiphilic conformations upon membrane insertion, our results strongly suggest that such amphiphilic conformations are absent in the case of random ternary polymers. The ternary polymers adopt a more folded conformation, staying aligned in the direction of the membrane normal and subsequently penetrating deeper into the membrane interior suggesting a novel membrane partitioning mechanism without amphiphilic conformations. Finally, we also examine the interactions of ternary polymer aggregates with model bacterial membranes, which show that replacing some of the hydrophobic groups by polar groups leads to weakly held ternary aggregates enabling them to undergo rapid partitioning and insertion into membrane interior. Our work thus underscores the role of inclusion of polar groups into the framework of traditional binary biomimetic antimicrobial polymers and suggests different mode of partitioning into bacterial membranes, mimicking antimicrobial mechanism of globular antimicrobial peptides like Defensin. 

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5. A tool to enhance antimicrobial stewardship using similarity networks to identify antimicrobial resistance patterns across farms

   https://doi.org/10.1038/s41598-023-29980-4  

   Aguilar-Vega, Cecilia ; Scoglio, Caterina ; Clavijo, María J. ; Robbins, Rebecca ; Karriker, Locke ; Liu, Xin ; Martínez-López, Beatriz ( December 2023 , Scientific Reports)

   Antimicrobial resistance (AMR) is one of the major challenges of the century and should be addressed with a One Health approach. This study aimed to develop a tool that can provide a better understanding of AMR patterns and improve management practices in swine production systems to reduce its spread between farms. We generated similarity networks based on the phenotypic AMR pattern for each farm with information on important bacterial pathogens for swine farming based on the Euclidean distance. We included seven pathogens:Actinobacillus suis,Bordetella bronchiseptica,Escherichia coli,Glaesserella parasuis,Pasteurella multocida,Salmonellaspp., andStreptococcus suis; and up to seventeen antibiotics from ten classes. A threshold criterion was developed to reduce the density of the networks and generate communities based on their AMR profiles. A total of 479 farms were included in the study although not all bacteria information was available on each farm. We observed significant differences in the morphology, number of nodes and characteristics of pathogen networks, as well as in the number of communities and susceptibility profiles of the pathogens to different antimicrobial drugs. The methodology presented here could be a useful tool to improve health management, biosecurity measures and prioritize interventions to reduce AMR spread in swine farming.

    

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