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. 2021 Dec 19;22(24):13606.
doi: 10.3390/ijms222413606.

NMR Hydrophilic Metabolomic Analysis of Bacterial Resistance Pathways Using Multivalent Antimicrobials with Challenged and Unchallenged Wild Type and Mutated Gram-Positive Bacteria

Affiliations

NMR Hydrophilic Metabolomic Analysis of Bacterial Resistance Pathways Using Multivalent Antimicrobials with Challenged and Unchallenged Wild Type and Mutated Gram-Positive Bacteria

Michelle L Aries et al. Int J Mol Sci. .

Abstract

Multivalent membrane disruptors are a relatively new antimicrobial scaffold that are difficult for bacteria to develop resistance to and can act on both Gram-positive and Gram-negative bacteria. Proton Nuclear Magnetic Resonance (1H NMR) metabolomics is an important method for studying resistance development in bacteria, since this is both a quantitative and qualitative method to study and identify phenotypes by changes in metabolic pathways. In this project, the metabolic differences between wild type Bacillus cereus (B. cereus) samples and B. cereus that was mutated through 33 growth cycles in a nonlethal dose of a multivalent antimicrobial agent were identified. For additional comparison, samples for analysis of the wild type and mutated strains of B. cereus were prepared in both challenged and unchallenged conditions. A C16-DABCO (1,4-diazabicyclo-2,2,2-octane) and mannose functionalized poly(amidoamine) dendrimer (DABCOMD) were used as the multivalent quaternary ammonium antimicrobial for this hydrophilic metabolic analysis. Overall, the study reported here indicates that B. cereus likely change their peptidoglycan layer to protect themselves from the highly positively charged DABCOMD. This membrane fortification most likely leads to the slow growth curve of the mutated, and especially the challenged mutant samples. The association of these sample types with metabolites associated with energy expenditure is attributed to the increased energy required for the membrane fortifications to occur as well as to the decreased diffusion of nutrients across the mutated membrane.

Keywords: Bacillus cereus; DABCO; Gram-positive bacteria; antibiotic resistance; dendrimers; membrane disruption; metabolomics; nuclear magnetic resonance; quaternary ammonium compounds.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
C16-DABCO Mannose Functionalized Dendrimer (DABCOMD) Structure.
Figure 2
Figure 2
Hierarachical Clustering showing that WT ML and WT D ML cluster together, WT D S and Mut D S cluster together, and all other sample types are separate. Full names of sample groups are given in Table 1.
Figure 3
Figure 3
2D sPLS–DA (a) Contains all sample types: showing overlap of WT ML with WT D ML and the overlap of all stationary phases. Mut ML is separate, and Mut D ML is separate. (b) Contains only mid log samples, showing slight overlap of WT ML with WT D ML and complete separation of Mut ML and Mut D ML. (c) Contains only stationary phase samples, showing slight overlap of WT D S and Mut D S, and complete separation of WT S and Mut S. (d) Contains unchallenged samples, showing a complete separation of Mut ML and Mut S samples and a 2D overlap of the WT ML with WT S (overlap not present in the 3D plot (Figure S7d)). (e) Contains only DABCOMD challenged samples, showing complete separation of all sample types. (f) 2D ortho PLS–DA containing all sample types: demonstrates the greatest degree of separation with all sample types together, with only an overlap of the oval of WT ML with the oval of WT D ML, and an overlap of the oval of Mut D S with the ovals of WT S and Mut ML.
Figure 4
Figure 4
PCA biplot showing the distribution samples (blue dots) with color coordinated sample labels and circles and the distribution of metabolites (red dots).
Figure 5
Figure 5
PCA biplots showing the distribution samples (blue dots) with color coordinated sample labels and circles and the distribution of metabolites (red dots). (a) Mid log phase samples showing WT ML and WT D ML very close together, Mut ML separated, and Mut D ML separated. (b) Stationary phase samples showing complete separation.
Figure 6
Figure 6
PCA biplots showing the distribution samples (blue dots) with color coordinated sample labels and circles and the distribution of metabolites (red dots). (a) Mut ML, Mut S, WT ML, and WT S samples showing complete separation. (b) DABCOMD-challenged samples showing complete separation of WT D ML and Mut D ML, and the overlap of WT D S and Mut D S.
Figure 7
Figure 7
Box and whisker plots to show the differences in fold changes and the fold change ranges for example metabolites involved in peptidoglycan synthesis, membrane permeability and energy associated pathways. (AM) Mid Log Phase Sample Comparisons. (NT) Stationary Phase Sample Comparisons. (UAB) Unchallenged Sample Comparisons. (ACAJ) Challenged Sample Comparisons.
Figure 8
Figure 8
Overview of the protocol from the start of the cultures to the hydrophilic metabolite samples ready to be pelleted, frozen at −80 °C, and put in NMR buffer. The processes for unchallenged and challenged samples are the same except for the inclusion of DABCOMD in the challenged sample media.

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References

    1. Mintzer M.A., Dane E.L., O’Toole G.A., Grinstaff M.W. Exploiting Dendrimer Multivalency to Combat Emerging and Re-Emerging Infectious Diseases. Mol. Pharm. 2012;9:342–354. doi: 10.1021/mp2005033. - DOI - PMC - PubMed
    1. Alanis A.J. Resistance to antibiotics: Are we in the post-antibiotic era? Arch. Med. Res. 2005;36:697–705. doi: 10.1016/j.arcmed.2005.06.009. - DOI - PubMed
    1. Hoerr V., Duggan G.E., Zbytnuik L., Poon K.K.H., Grosse C., Neugebauer U., Methling K., Loeffler B., Vogel H.J. Characterization and prediction of the mechanism of action of antibiotics through NMR metabolomics. BMC Microbiol. 2016;16:82. doi: 10.1186/s12866-016-0696-5. - DOI - PMC - PubMed
    1. Gonzalez-Bello C. Antibiotic adjuvants—A strategy to unlock bacterial resistance to antibiotics. Bioorg. Med. Chem. Lett. 2017;27:4221–4228. doi: 10.1016/j.bmcl.2017.08.027. - DOI - PubMed
    1. Todar K. Textbook of Bacteriology. University of Wisconsin; Madison, WI, USA: 2020. [(accessed on 10 November 2021)]. Available online: http://textbookofbacteriology.net.

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