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. Author manuscript; available in PMC: 2024 Mar 25.
Published in final edited form as: Methods Enzymol. 2021 Dec 28;663:259–271. doi: 10.1016/bs.mie.2021.09.008

Revealing AMP mechanisms of action through resistance evolution and quantitative proteomics

Samantha J Balboa 1, Leslie M Hicks 1
PMCID: PMC10961912  NIHMSID: NIHMS1972867  PMID: 35168792

Abstract

Antimicrobial resistance (AMR) is a significant public health issue that threatens our ability to treat common infections. AMR often emerges in bacteria through upregulation of proteins that allow a sub-population of resistant bacteria to proliferate through natural selection. Identifying these proteins is crucial for understanding how AMR develops in bacteria and is essential in developing novel therapeutics to combat the threat of widespread AMR. Mass spectrometry-based proteomics is a powerful tool for understanding the biochemical pathways of biological systems, lending remarkable insight into AMR mechanisms in bacteria through measuring the changing protein abundances as a result of antibiotic treatment. Herein, we describe a serial passaging method for evolving resistance in bacteria that implements quantitative proteomics to reveal the differential proteomes of resistant bacteria. The focus herein is on antimicrobial peptides (AMPs), but the approach can be generalized for any antimicrobial compound. Comparative proteomics of sensitive vs. resistance strains in response to AMP treatment reveals mechanisms to survive the bioactive compound and points to the mechanism of action for novel AMPs.

Keywords: Antimicrobial peptides, serial passaging, antimicrobial resistance, quantitative proteomics, mass spectrometry

1. Introduction

Antibiotic-resistant infections are a rising global health crisis with more than 2.8 million antibiotic resistant infections occurring each year in the U.S., resulting in >35,000 deaths (Centers for Disease Control, 2019). The World Health Organization (WHO) has published a list of priority pathogens, dubbed the ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.) pathogens, for which new antimicrobial strategies are urgently needed (Tacconelli et al., 2017). While drugs of last resort are prescribed in severe cases of multi-drug resistant (MDR) infections, the emergence of resistance to these last resort antibiotics is depleting effective therapeutic strategies. Novel antibiotics are therefore essential to treat MDR infections.

Antimicrobial peptides (AMPs) are small peptides (<50 amino acids) that are expressed throughout all kingdoms of life and can inhibit the growth of parasites, fungi, viruses, and bacteria (Wang et al. 2019). AMPs are an attractive class of antimicrobials due to their ubiquitous nature, broad-spectrum activity, and slower emergence of resistance (Brogden, 2005; Magana et al. 2020). Despite these advantages, AMPs can still confer antibiotic resistance in bacteria, especially when applied in sublethal concentrations that allow resistant sub-populations of bacteria to rapidly develop. Well-characterized bacterial mechanisms to achieve resistance to AMPs include modulation of efflux pumps and uptake transporters to decrease intracellular AMP concentration, expression of peptidases to proteolytically degrade AMPs, and modification of the cellular membrane to reduce electrostatic interactions (Wang et al., 2019).

Antibiotic stress has enormous implications on the proteomic landscape and bacterial phenotype (Fernández-Reyes et al., 2009; Sun et al., 2020; Janssen et al., 2020; Wong, Oliver, and Linington, 2012; Nonejuie et al., 2013). As such, understanding the proteomic response of bacteria to AMP exposure is crucial to understanding mechanisms of action and potential routes for resistance evolution. This can be readily studied in vitro through serial passaging experiments in which bacteria cultures are initially exposed to sublethal concentrations of AMP and continually passaged into increasing AMP concentration to select for resistant bacteria.(Sun et al. 2020). Mechanisms of action and resistance can then be informed through comparative quantitative proteomics of these resistant populations to those that are susceptible.

Herein, a method to induce AMR in bacteria and readout molecular phenotypic changes via quantitative proteomics is described. This includes a serial passaging method to induce AMP resistance in an example bacteria (Escherichia coli) followed by a detailed sample preparation and analysis protocol for label-free quantitative proteomics (Fig. 1A). Key considerations for implementation of this method include: 1) requirement for sufficient antibiotic/AMP to induce resistance in multiple replicates across multiple generations with increasing concentrations of antimicrobial compound, and 2) proteomics analysis will be most powerful with sequenced, well-annotated target bacterial strains.

Figure 1.

Figure 1.

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A) Overall workflow for in vitro evaluation of evolutionary antibiotic resistance via quantitative proteomics. Briefly, resistant cultures are generated through serial passaging in increasing concentrations of AMP. Then, the proteomes from the resistant cultures are harvested, extracted, reduced, alkylated, and digested with trypsin. The resulting peptides are then analyzed via LC-MS/MS. Data are then searched against a database to identify peptides. Peptides are assigned to proteins and quantified to determine changing protein abundances between conditions. B) General overview of a serial passaging experiment in which a parent culture is used to generate 3–5 replicates. Cultures are then passaged into increasing concentrations of AMP until desired resistance is observed. C) As the concentration of AMP increases in the bacterial culture, so do the incubation times to reach log-phase at OD600 = 0.5–0.7.

2. Materials

2.1. Serial passaging

  1. Bacterial strain: herein, Escherichia coli ATCC® 25922 will be used as an example.

  2. Mueller-Hinton agar/broth: Mueller-Hinton agar and broth can be readily purchased. To prepare agar plates, suspend 38 g of dehydrated agar medium in 1 L of Milli-Q water and sterilize by autoclaving. Cool media and pour approximately 20 mL into 100 × 15 mm petri dishes using aseptic technique. Allow plates to solidify overnight and store at 4 °C.

    To prepare liquid Mueller-Hinton broth, dissolve 21 g of dehydrated medium in 1 L of Milli-Q water and sterilize by autoclaving.

  3. Antimicrobial peptide sufficient for generation of at least three resistant lineages.

    Tip: From a single parent culture, three biological replicates can be produced. Once each biological replicate reaches log-phase, five technical replicates can be collected for robust label-free quantitation. In a single passaging experiment comparing the proteomic differences between wild-type and three replicates of AMP-resistant strains, 20 total samples will be generated. It is important to note that there must be sufficient AMP material to produce resistant strains. If the MIC for an AMP is 1 μg/mL, the starting AMP concentration in the serial passage experiment could be 0.5 μg/mL, which is 0.5xMIC. If performing three passages, the final concentration for generating resistant strains is 4 μg/mL. Thus, there must be enough material to passage in 0.5, 1, 2, and 4 μg/mL of AMP for three biological replicates.

  4. Shaking incubator at 37 °C, 250 rpm.

  5. 96-well plate UV/Vis spectrophotometer.

2.2. Protein extraction

  1. Lysis buffer: 100 mM Tris-HCl, pH 8, 0.1% Triton-X 100.
    1. Stock solutions can be made for easy preparation of lysis buffer. When preparing the lysis buffer, stir slowly when fully dissolving contents to minimize agitation and bubble formation from the Triton-X 100.
  2. Covaris 2 mL milliTUBEs and 24 Place milliTUBE rack.
    1. As an alternative, samples can be shaken for 15 min at RT, sonicated, or lysed using a French pressure cell press.

  3. 100 mM ammonium acetate in 100% methanol (MeOH), chilled.

  4. 100 mM TRIS, pH 8.0. Using a 1 M TRIS stock is recommended for ease of buffer preparation.

  5. Resuspension buffer: 8 M urea, 100 mM TRIS, pH 8.0.

  6. CB-X Protein Assay Kit (G-Biosciences, St. Louis, MO, USA) or equivalent protein quantification assay.

2.3. Reduction, alkylation, and digestion

  1. Reduction buffer: 500 mM dithiothreitol (DTT) in 100 mM TRIS, pH 8.0. Make fresh for each experiment and cover tube with aluminum foil or keep buffer in the dark to prevent degradation of light-sensitive DTT solution.

  2. Alkylation buffer: 500 mM iodoacetamide (IAM) in 100 mM TRIS, pH 8.0. Make fresh for each experiment and cover tube with aluminum foil or keep buffer in the dark to prevent degradation of light-sensitive IAM solution.

  3. Trypsin Gold, Mass Spectrometry grade, Promega (Madison, WI, USA), 0.5 μg/mL in 50 mM acetic acid.

  4. 20% trifluoroacetic acid (TFA).

  5. ThermoMixer, Eppendorf.

2.4. Desalting

  1. Sep-Pak C18 1 cc Vac Cartridge, 50 mg, 55–105 μm particle size (Waters, Milford, MA, USA).

  2. 0.1% TFA (LC-MS grade).

  3. 80% acetonitrile (ACN, LC-MS grade), 0.1% TFA (LC-MS grade).

  4. Vacuum manifold with 24-port cover (Phenomenex, Torrance, CA, USA) or equivalent setup.

  5. Vacuum centrifuge.

2.6. LC-MS/MS

  1. 5% ACN (LC-MS grade), 0.1% TFA (LC-MS grade).

  2. LC-MS Total Recovery Vials.

  3. Symmetry C18 trap column (100 Å, 5 μm, 180 μm x 20 mm; Waters).

  4. HSS T3 C18 column (100 Å, 1.8 μm, 75 μm x 250 mm; Waters).

  5. Mobile Phase A: 0.1% formic acid. Add 1 mL of Optima LC-MS grade formic acid to 1 L of Optima LC-MS grade water.

  6. Mobile Phase B: 0.1% FA in ACN (LC-MS grade).

  7. Acquity UPLC M-Class system (Waters).

  8. Q Exactive HF-X Hybrid Quadrupole Orbitrap mass spectrometer (ThermoFisher, Waltham, MA, USA).

2.7. Data analysis

  1. Progenesis QI for Proteomics v2.0 (Nonlinear Dynamics, Durham, NC, USA).

    Tip: Freeware options include MaxQuant, msInspect, and Skyline (Tyanova, 2016; Bellew, 2006; Maclean, 2010).

  2. Mascot Daemon v3.5.1 (Matrix Science, Boston, MA, USA).

  3. R script for processing proteomic data. The code used for processing these data is available on GitHub (https://github.com/hickslab/ProgenesisLFQ).

3. Methods

3.1. In vitro evolution of antibiotic resistance via serial passaging

  1. Streak E. coli onto Mueller-Hinton agar plates and incubate for 12–18 h at 37 °C.

  2. Inoculate 5 mL of Mueller-Hinton broth with a single bacterial colony swabbed from the agar plate and incubate for 12–18 h at 37 °C, 250 rpm.

  3. From a single parent culture, back-dilute to an OD600 = 0.01 into three different culture tubes containing 7 mL of Muller-Hinton broth and 0.5 μg/mL of AMP, or a sub-MIC value, to create three lineages and a fourth tube for the untreated culture as a control.

  4. Grow cultures at 37 °C, 250 rpm to an OD600 of 0.5 – 0.7 (log-phase) as determined by growth curves.

  5. Once log-phase has been reached, aliquot five replicates of 1 mL of bacterial culture and centrifuge for 5 min at 13,400 rcf, flash freeze, and store at −80 °C for proteomics analysis. Then, inoculate ~100 μL of the remaining log-phase culture into a fresh 5 mL of Mueller-Hinton broth containing 100% increased concentration of antibiotic to a final OD600 = 0.01 (Fig. 1B).

  6. Repeat steps 4–5 iteratively to the desired increase in the MIC of AMP is observed, indicating significant resistance.

    Tip: Typically, a minimum of three passages of increasing AMP concentration is needed to induce AMP resistance from 0.5xMIC to 4xMIC, but this timeline is AMP and pathogen dependent as shown in several studies (Samuelsen et al., 2005; Blanco et al., 2020; Tambe, Sampath, and Modak, 2001). Sub-MIC treatment can also be adapted for this method by treating cultures with sub-MIC of AMP and measuring the proteomic differences. Note that AMP treatment of these cultures may increase incubation times to reach the desired OD600, thus cultures must be continuously monitored (Fig. 1C).

3.2. Protein extraction

  1. Resuspend bacterial pellets in 1 mL lysis buffer and transfer to Covaris 2 mL tubes. Keep samples on ice during resuspension.

    Tip: Alternative cell lysis options include probe sonication, French cell press, manual grinding with a mortar and pestle, and freeze/thaw cycles. Reagent-based methods have advantages such as quick, mild, efficient, and reproducible results at the cost of introducing high concentrations of salt and detergents to the sample which are not compatible with mass spectrometry and may need further processing strategies. Physical disruption methods have the advantage of lysing cells without the addition of salts and detergents, but with the loss of ease and reproducibility.

  2. Sonicate bacterial pellets for 3 min in a 4 °C water bath at 200 cycles/burst, 100 W power, and 13% duty cycle using an E220 focused ultrasonicator (Covaris, Woburn, MA, USA).

  3. Transfer samples from Covaris tubes to 2-mL centrifuge tubes, keeping the samples on ice.

  4. Centrifuge cell lysates at 16,000 rcf for 10 min at 4 °C and collect the supernatant into a 15-mL conical tube.

  5. Precipitate proteins by adding 5x volume (about 30 mL) of cold 100 mM ammonium acetate in MeOH.

  6. Incubate samples for 30 min at −20 °C.

  7. Collect protein pellet by centrifuging for 10 min at 3,200 rcf, 4 °C. Decant the supernatant without disturbing the pellet.

  8. Allow protein pellets to dry for 20 min in a fume hood at room temperature.

  9. Resuspend the pellets in 400 μL of 4 M urea, 100 mM Tris, pH 8.0.

  10. Use a 10 μL aliquot of each replicate to perform protein quantification using the CB-X Protein Assay using manufacturer’s protocol.

  11. Normalize each replicate to ~50–100 μg of total protein in 200 μL.

3.3. Reduction, alkylation, and digestion

  1. Reduce samples using 10 mM DTT. Incubate for 30 min at room temperature while shaking at 850 rpm.

  2. Alkylate samples using 40 mM IAM. Incubate for 45 min in the dark by covering samples with aluminum foil at RT while shaking.

  3. Precipitate proteins with 10x volume of chilled 100% acetone and incubate for 30 min at −20°C. Then, centrifuge for 10 min at 4 °C, 20,000 rcf. Remove supernatant and dry under N2 in a fume hood.

  4. Resuspend protein pellets in 100 μL 8 M urea, 100 mM Tris, pH 8.0 and dilute to 2 M urea using 300 μL of 100 mM Tris pH 8.0.

  5. Perform overnight (12–18 hrs) digestion using mass spectrometry-grade trypsin (Trypsin Gold from Promega is recommended) at a protease to protein ratio of 1:50 (w/w) at 25°C. Gently invert or shake the samples using a Thermomixer at 850 rpm during digestion.

  6. Following digestion, quench the reaction by adding 10% TFA to the samples until pH is less than 3 when measured with a pH test strip. Typically, 10–20 μL of 10% TFA is sufficient for 400 μL samples.

  7. (Optional) Samples can be stored at −80°C until the next processing step is performed.

3.4. Desalting

  1. Set up one Waters™ Sep-Pak C18 SPE cartridge for each sample on a vacuum manifold using test tubes to collect the flow through from the cartridges.

  2. Wet cartridges by adding 1 mL of 80% ACN, 0.1% TFA.

  3. Equilibrate cartridges using 2 mL of 0.1% TFA.

  4. Load peptide samples onto the cartridge and recover the flow-through no faster than 1 drop/second in a new test tube.

  5. Reapply this flow through to the cartridge to ensure all peptides in the sample bind to the resin in the cartridge.

  6. Once the flow-through passes through, switch to a new test tube and flow 2 mL of 0.1% TFA through the cartridges to remove salts.

  7. Slowly elute desalted peptides at less than 1 drop/second into new 2-mL tubes by adding 1 mL of 50% ACN, 0.1% TFA to the cartridge. Once the samples finish eluting, apply vacuum for about 5 seconds to collect the remaining solvent from the packed bed.

  8. Following peptide elution, freeze the samples and vacuum centrifuge to dryness.

3.7. LC-MS/MS

  1. Resuspend peptide samples to 1 μg/μL in LC-MS water and dilute in LC-MS water + 0.1% TFA to a final concentration of 0.25 μg/mL in Total Recovery Vials (Waters).

  2. For each sample, inject 5 μL and perform LC-MS/MS analysis. Five technical replicates are injected for each biological replicate.

    • 2.1

      Acquity UPLC M-Class system (Waters): Inject the peptide mixture to a Symmetry C18 trap column (100 Å, 5 μm, 180 μm x 20 mm; Waters) with a flow rate of 5 μL/min for 3 min using 99% A and 1% B, then separate on a HSS T3 C18 column (100 Å, 1.8 μm, 75 μm x 250 mm; Waters) using a gradient of increasing mobile phase B at a flow rate of 300 nL/min for 120 min total. Increase mobile phase B from 5–35% in 90 min, ramp to 85% in 5 min, hold for 5 min, return to 5% mobile phase B in 2 min, and re-equilibrate for 13 min. This eluate is coupled directly to the subsequent ESI-MS/MS system.

    • 2.2.

      The ESI-MS/MS system consists of a Q Exactive HF-X Hybrid Quadrupole Orbitrap mass spectrometer (ThermoFisher). Use the following MS parameters: use a tune file set with positive polarity, 2.2 kV spray voltage, 325°C capillary temperature, and 40 S-lens RF level. Select full MS/DD-MS2 scan type and set method duration to 120 min and default charge state to 2. Perform MS survey scan in profile mode across 350–2000 m/z at 120,000 resolution until 50 ms maximum IT or 3×106 AGC target is reached. Select the top 20 features above 5000 counts excluding ions with unassigned, +1, or > +8 charge state. Collect MS2 scans at 30,000 resolution with NCE at 28 until 100 ms maximum IT or 1×105 AGC target. Set the dynamic exclusion window for precursor m/z to 10 s and an isolation window of 0.7 m/z.

3.8. Data Analysis

  1. Upload the acquired LC-MS/MS spectral files (*.raw) into Progenesis QI for Proteomics (Nonlinear Dynamics). While the files are importing, start automatic processing to allow Progenesis to select an alignment reference to align the total ion chromatograms to minimize LC-MS/MS between-run differences in retention time and normalize peak abundances. Review the alignment score to ensure that all “Score” values are >80%. Design the experiment so that replicates are grouped together as one subject and export the aligned runs as a combined peak list (*.mgf).

    Tip: Low alignment scores are often a result of drifting LC retention times and/or fluctuating MS mass accuracy between-runs during LC-MS/MS acquisition. Should a run fail to align during the automatic processing procedure, repeating the process with this failed run will often produce successful alignment but with overall lower alignment scores across the runs.

  2. Perform Mascot (Matrix Science) database searching using the .mgf peak list to determine peptide sequence and identify proteins. Use the following search parameters: Search against the database containing the proteome for the organism of interest, in this case the Escherichia coli (strain 25922) proteome along with the sequence for common laboratory contaminants (www.thegpm.org/cRAP; 116 entries). Use a target decoy MS/MS search with trypsin protease specificity with up to two missed cleavages, a peptide mass tolerance of 15 ppm, and a fragment mass tolerance of 0.1 Da. Set a fixed modification of carbamidomethylation at cysteine and include the following variable modifications: acetylation at the protein N-terminus. After the search is complete, adjust the false discovery rate of the significant peptide identifications to be less than 1% using the embedded Percolator algorithm. Export matches the matches into a result file (*.xml).

  3. Import the Mascot search results into Progenesis to perform peptide feature mapping. Export the “Protein Measurements” as an Excel document from the “Review Proteins” tab.

  4. Parse the “Protein Measurements” data file using the QuantifyR package developed by our lab (https://github.com/hickslab/ProgenesisLFQ) or using a similar parsing technique. This script groups together features identified in Progenesis and matches identical sequence, modifications, and score with differing protein accessions. These features are then represented by the protein accession with the highest number of unique peptides and largest confidence score assigned by Progenesis. Features duplicated by multiple peptide identifications are reduced to a single peptide with the highest Mascot ion score. Identifiers are made by joining the protein accession of each feature with the single-letter amino acid code of the modified residue and location of the modification. The data are then reduced to unique identifiers by summing the abundance of all contributing features (charge states, missed cleavages, etc.). Each identifier group is represented in the final dataset by the peptide with the highest Mascot score.

  5. To determine whether there is a significant difference in resistant and wild-type strains, the “Analyze” module of the QuantifyR package is used to perform two-sided, equal-variance t-tests and one-way ANOVA. The false discovery rate (FDR) is controlled in both analyses by using the Benjamini-Hochberg FDR correction and is used to determine proteins that were significantly changing between wild-type and resistant conditions (q-value < 0.05). Using this workflow, a volcano plot displaying significantly changing proteins can be generated (Fig. 2) from the “Plot” function of the QuantifyR package. These changing protein abundances can then be used to inform further experiments to study the altered processes in the bacteria such as phenotypic assays, motility studies, and cell membrane permeability assays.

Figure 2.

Figure 2.

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Volcano plot showing changing protein abundances between parent cultures, serial passage 1, serial passage 4, and serial passage 9. The x-axis represents log2-transformed fold changes, with dashed lines indicating expected fold changes in E. coli background proteins. The y-axis represents the –log10-transformed FDR-adjusted p-values (q-values), with the dashed lines indicating the untransformed significance level, 0.05. Proteins in increasing abundance are shown in red while proteins decreasing in abundance are shown in blue.

4. Summary

Antimicrobial resistance is a challenging global health issue with enormous implications in human health. Recent studies highlight the importance of proteomic responses to AMP stress (Sadecki et al., 2021; Sun et al., 2020; Janssen et al., 2020). Interestingly, Sadecki et al., 2021 showed that polymyxin B, an AMP antibiotic, enhances the production of a genotoxic metabolite called colibactin in E. coli NC101, a commensal gut microbe, through the increase of proteins involved in the biosynthesis of colibactin. This study highlights the importance of understanding how AMP resistance can have immense implications to their target organism. This chapter outlines a method to induce AMR in bacteria through serial passaging and measuring the resulting proteomic changes via quantitative proteomics to inform further studies.

5. Acknowledgements

This research was supported by the NIH-NIGMS under award R01 GM125814 to L.M.H., and S.J.B acknowledges NIH Biophysics training grant support (T32 GM008570) and P.W.S. for their development of this method.

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