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. Author manuscript; available in PMC: 2025 Aug 2.
Published in final edited form as: J Proteome Res. 2024 Feb 17;23(8):2948–2960. doi: 10.1021/acs.jproteome.3c00597

Identification and characterization of CC-AMP1-like and CC-AMP2-like peptides in Capsicum spp

Kevin D Culver 1, Patric W Sadecki 1, Jessica K Jackson 2, Zoe A Brown 3, Megan E Hnilica 1, Jingyun Wu 1, Lindsey N Shaw 2, Andrew J Wommack 3, Leslie M Hicks 1,*
PMCID: PMC11296913  NIHMSID: NIHMS1972859  PMID: 38367000

Abstract

Antimicrobial peptides (AMPs) are compounds with a variety of bioactive properties. Especially promising are their antibacterial activities, often towards drug-resistant pathogens. Across different AMP sources, AMPs expressed within plants are relatively underexplored, with a limited number of plant AMP families identified. Recently, we identified the novel AMPs CC-AMP1 and CC-AMP2 in ghost pepper plants (Capsicum chinense × frutescens), exerting promising antibacterial activity and not classifying into any known plant AMP family. Herein, AMPs related to CC-AMP1 and CC-AMP2 were identified within both Capsicum annuum and Capsicum baccatum. In silico predictions throughout plants were utilized to illustrate that CC-AMP1-like and CC-AMP2-like peptides belong to two broader AMP families, with three-dimensional structural predictions indicating that CC-AMP1-like peptides comprise a novel subfamily of α-hairpinins. The antibacterial activities of several closely related CC-AMP1-like peptides were compared, with a truncated version of CC-AMP1 possessing significantly more activity than the full peptide. This truncated peptide was further characterized to possess broad-spectrum antibacterial activity against the clinically relevant ESKAPE pathogens. These findings illustrate the value in continued study of plant AMPs towards characterization of novel AMP families, with CC-AMP1-like peptides possessing promising bioactivity.

Keywords: Antimicrobial peptides, mass spectrometry, peppers, ESKAPE pathogens

Graphical Abstract:

graphic file with name nihms-1972859-f0001.jpg

Introduction

Antimicrobial peptides (AMPs) are host defense peptides expressed throughout all life,1–4 with a wide range of bioactivities such as antibacterial, antifungal, and antiviral.5–7 Plants as a source of AMPs are relatively underexplored compared to other kingdoms, and represent <1% of all naturally occurring AMPs deposited in the Antimicrobial Peptide Database.4 Within plants, seven major AMP families have been discovered including thionins, defensins, knottins, lipid transfer proteins, snakins, hevein-like peptides, and α-hairpinins.8–11 With increasingly available genomic and transcriptomic data within plants,12 widely available three-dimensional structural predictions,13 and development of high-throughput workflows for botanical AMP discovery,14 there is increased potential for discovery and characterization of novel AMPs within plants.

Classification of AMPs into AMP families is generally based on sequence similarity, cysteine motif, and overall tertiary structure.10,11 Cysteine motifs, consisting of defined numbers of cysteine residues and spacing between these cysteine residues, are highly conserved within these AMP families and form multiple disulfide bonds which confer stability as well as tertiary structure.11 Among plant AMP families, α-Hairpinins are relatively underexplored and are described as having a peculiar helix-loop-helix structure with two disulfide bonds that link the two helices.8 While maintaining a conserved cysteine motif and three-dimensional structure, these peptides often have highly heterologous primary sequences, with α-hairpinins displaying a range of differing bioactivities including antibacterial, antifungal, trypsin inhibitory, ribosome-inactivating, and DNA-binding.8,11,15–17

Recently, two novel AMPs with promising antibacterial activity were discovered in Capsicum chinense × frutescens (ghost pepper), CC-AMP1 and CC-AMP2, with each peptide displaying a unique cysteine motif not observed in any major plant AMP family.18 CC-AMP1 was characterized as possessing a membrane-lytic mechanism of action with low μM activity against Gram-negative bacteria including E. coli, K. pneumoniae, A. baumannii, and P. aeruginosa, while also being non-hemolytic against human erythrocytes. Though the low abundance of CC-AMP2 precluded extensive biological characterization, it was observed to have higher activity against E. coli than CC-AMP1. UniProt BLAST results indicated that peptides displaying these same novel cysteine motifs are likely expressed in closely related species,18 suggesting that CC-AMP1 and CC-AMP2 belong to two previously uncharacterized AMP families.

Herein, in silico predictions are employed to explore the pervasiveness of these two putative AMP families within Solanaceae. Structural predictions via AlphaFold13 point towards CC-AMP1-like peptides comprising a novel type of three disulfide bond α-hairpinin, while CC-AMP2-like peptides appear to be a small, highly unique AMP family. The presence of these AMP families is validated within Capsicum annuum and Capsicum baccatum, and the antibacterial properties of new CC-AMP1-like peptides are compared to CC-AMP1, providing insight into key structural features. A CC-AMP1 variant with significantly more antimicrobial activity than CC-AMP1 is characterized, and in silico predictions of both CC-AMP1-like and CC-AMP2-like peptides are further employed across all UniProt plants. Altogether, this work illustrates CC-AMP1-like peptides are likely widespread within plants and that α-hairpinins are more diverse than previously known.

Methods

In silico AMP Prediction.

For AMP prediction within Solanaceae, a fasta file of all proteins within the Solanaceae family on UniProt (taxonomy ID: 4070) was downloaded on March 25, 2022. SignalP 6.019 was used on this fasta file in fast mode with organism set to eukarya and format set to none. The results were further searched using Cysmotif Searcher20 with the option of skipping translation of input sequences. The motifs file used by Cysmotif Searcher was manually edited to search for only the CC-AMP1 and CC-AMP2 cysteine motifs, CX{3}CX{3}CX{5}CX{3}CX{3}CXX and CX{2}CX{2}CX{3}CX{2}CCX, respectively. Results were then parsed to manually apply additional putative cleavages. For CC-AMP1-like peptides, a C-terminal domain was removed at two residues after the CC-AMP1 cysteine motif. For CC-AMP2-like peptides, an N-terminal domain was removed by cleaving after the first observed lysine residue.

For prediction across all UniProt plants, a fasta file of all proteins within the Viridiplantae kingdom on UniProt (taxonomy ID: 33090) was downloaded on April 29, 2022. The file was split into 60 smaller files and each was subjected to the same SignalP 6.0 analysis that was done using Solanaceae proteins. The 60 result files were combined and subjected to the same Cysmotif Searcher analysis that was done using Solanaceae proteins, without applying the additional putative cleavages to predicted sequences. Sequences that had already been predicted from Solanaceae were disregarded.

All multiple sequence alignments were performed using the UniProt Align tool.26 The cladogram was generated from the alignment of CC-AMP1-like accessions across UniProt plants by selecting Guide tree, Circular, and Cladogram under the Trees tab from the alignment results.

Net charges at pH 7 for each predicted Solanaceae peptide were calculated using the Bachem peptide calculator (https://www.bachem.com/knowledge-center/peptide-calculator/).

Predicted three-dimensional structures generated via AlphaFold13 were downloaded via UniProt and viewed in ChimeraX 1.4.27 Expected cleaved regions were hidden (e.g. signal peptides) to generate final predicted structures.

Plant Material.

Aleppo pepper (Capsicum annuum) and Criolla Sella pepper (Capsicum baccatum) seeds were purchased from Strictly Medicinal Seeds (Williams, OR) and planted in nutrient rich soil. Plants were grown under controlled temperature (17.5–20.3°C) and light cycle (14 hours) conditions. The plants were grown for approximately 12 weeks and aerial tissue was harvested with immediate flash freezing and storage at −80°C until extraction.

Peptide Extraction and Creation of Peptide Library.

122 grams of Capsicum annuum leaf tissue and 102 grams of Capsicum baccatum leaf tissue were separately extracted in an acetic acid solution as previously described,28 with size exclusion steps to remove large proteins (>30 kDa) and small molecules. Neutral and negatively charged molecules were removed through SCX chromatography, desalted, and fractionated using reversed-phase chromatography as previously described.18 Fractions were collected every minute, dried in a vacuum centrifuge, and resuspended in 100 μL of LC-MS grade water.

Additional Reversed-Phase LC Separations.

Fractions 26–27 of Capsicum annuum, as well as fractions 26–29 and 30–34 of Capsicum baccatum were each separately re-combined into three samples. These samples were subjected to a reversed-phase chromatographic separation with mobile phase A consisting of water with 0.1% formic acid and mobile phase B consisting of acetonitrile with 0.1% formic acid. The samples were injected at 500 μL and a linear gradient of increasing mobile phase B was used at a flow rate of 1.0 mL/min. Mobile phase B was held at 5% for 1 min before being increased from 5% to 50% in 30 min and ramping to 85% in 2 min, where it was held for 3 min before returning to 5% in 1 min and re-equilibrating for 8 min. Fractions were collected every 30 seconds, dried in a vacuum centrifuge, and resuspended in 50 μL of LC-MS water.

Antimicrobial Assays.

E. coli ATCC 25922, K. pneumoniae VK148, A. baumannii 5075, P. aeruginosa 1423, and E. cloacae 1454 were streaked on LB plates and incubated at 37°C for 16 hours. E. faecium 1450 and S. aureus 635 were streaked on TSA and incubated at 37°C for 16 hours. The assay was performed as previously described.28 Briefly, assays were performed using a 96-well plate in 1xMHB combining 10 μL peptide fraction with 40 μL 0.125 OD600 bacterial culture. Ampicillin (0.1 mg/mL) was used as the positive control for E. coli, erythromycin (0.1 mg/mL) was used as the positive control for K. pneumoniae, and erythromycin (1mg/mL) was used as the positive control for E. faecium, S. aureus, A. baumannii, P. aeruginosa, and E. cloacae. Water was used as the negative control for E. coli assays, 0.1% DMSO was used for K. pneumoniae assays, and PBS was used for the remaining strains tested. Assays were incubated for 4 hours at 37°C at 250 rpm and OD600 was measured before adding 1 μL of 50 mM resazurin to each well. After 1 additional hour of incubation at 37°C at 250 rpm, a fluorescence measurement with 544 nm (ex) and 590 nm (em) was collected. Assays for E. faecium, S. aureus, A. baumannii, P. aeruginosa, and E. cloacae were incubated in a BioTek Cytation 5 plate reader (Agilent) at 37°C with double orbital shaking for 4 hours and OD600 was measured. Calculation of percent activity was done as previously described.18 Two-tailed t-tests were performed on the K. pneumoniae data using Excel 2019. All IC50 were calculated using GraphPad Prism (v5; GraphPad Software) as previously described.18

Reduction, Alkylation and Protease Digestion.

For peptides which were reduced and alkylated, peptide sample aliquots of 10 μL were reduced with 10 mM dithiothreitol (Millipore-Sigma) at 45°C at 850 rpm for 30 minutes, and alkylated with 16 mM iodoacetamide (Millipore-Sigma) at 25°C at 850 rpm for 15 minutes. For trypsin digested samples, 10 μL of reduced and alkylated peptide was digested with trypsin gold (Promega) with an enzyme/protein ratio of approximately 1:50 (w/w) and incubated at 37°C at 850 rpm overnight. For chymotrypsin digested samples, 10 μL of reduced and alkylated peptide was digested with chymotrypsin, sequencing grade (Promega), with an enzyme/protein ratio of approximately 1:20 (w/w) and incubated at 25°C at 850 rpm for 4 hours. All samples were desalted with C18 ZipTips prior to LC-MS/MS analysis.

LC-MS/MS Analysis.

All samples utilized in the identification of CC-AMP1-like and CC-AMP2-like masses, as well as the tryptic digest of CA-AMP1 and the reduced and alkylated CC-AMP1 (D5-C30) sample used for sequencing, were analyzed using a nano-LC-ESI-MS/MS platform as previously described28 with the following specifications: 0.1% formic acid in all mobile phases and a trapping mobile phase composition of 1% MeCN/0.1% formic acid. The MS was operated in positive-ion, high-sensitivity mode with the MS survey spectrum using a mass range of m/z 350–1600 in 250 ms and information-dependent acquisition (IDA) of MS/MS data using an eight second dynamic exclusion window. The first 20 features above an intensity threshold of 150 counts and having a charge state of +2 to +5 were fragmented using rolling collision energy (CE) (±5%). For reduced and alkylated CC-AMP1 (D5-C30), targeted MS/MS data was acquired on the +5 charge state using a CE of 35 and CE spread of 5. Peptide abundance for C. baccatum bioactive region 2 was quantified using Progenesis QI for Proteomics software (Nonlinear Dynamics, v. 2.0) as previously described28 to create a list of mass spectrometric species. Default peak picking settings were used with the exception that a minimum peak width of 0.05 min was required. Mass spectrometric features with identical charge states, masses within 0.05 Da, and retention times within 5 min of each other were binned.

All samples utilized in the sequencing of CC-AMP1-like peptides, except for the inactive CC-AMP1-like peptide and CC-AMP1 (D5-C30), were analyzed using a nanoAcquity UPLC System (Waters) coupled to a Q Exactive HF‐X mass spectrometer (Thermo Fisher Scientific). Mobile phase A consisted of water with 0.1% formic acid and mobile phase B consisted of acetonitrile with 0.1% formic acid. Injections were made to a Symmetry C18 trap column (100 Å, 5 μm, 180 μm × 20 mm; Waters) with a flow rate of 5 μL/min for 3 min using 99% A and 1% B. Peptides were then separated on an HSS T3 C18 column (100 Å, 1.8 μm, 75 μm × 250 mm; Waters) at 40°C using a linear gradient of increasing mobile phase B at a flow rate of 300 nL/min. Mobile phase B was held at 5% for 1 min before being increased from 5% to 50% in 30 min and ramping to 85% in 2 min, where it was held for 3 min before returning to 5% in 1 min and re-equilibrating for 23 min. The mass spectrometer was operated in positive polarity and the Nanospray Flex source had spray voltage floating at 2.2 kV, capillary temperature at 275°C, except for the chymotryptic digest of CA-AMP1 which used a capillary temperature of 325°C, and funnel RF level at 40. For CC-AMP1, CB-AMP1, CC-AMP1 (L4-C30), and CC-AMP1 (Z1-C30), targeted SIM scans were acquired at a scan range of 150–2000 m/z at a resolving power of 120000 and an AGC target of 5 × 104 with a maximum injection time of 100 ms. MS/MS scans were performed at a resolving power of 60000 and an AGC target of 1 × 105 with a maximum injection time of 100 ms. For CC-AMP1, CB-AMP1, and CC-AMP1 (Z1-C30), a CE of 30 was used, while CC-AMP1 (L4-C30) was analyzed with a CE of 35. For the chymotryptic digest of CA-AMP1, MS survey scans were collected with a range of 350–2000 m/z at a resolution of 120000 and AGC target of 3 × 106 with a maximum injection time of 100 ms. Top 20 data-dependent acquisition was used, selecting precursors from +2 to +7 charge state and using a normalized collision energy of 28. MS/MS scans were performed at a resolving power of 30000 and an AGC target of 5 × 103 with a maximum injection time of 100 ms. Dynamic exclusion of 10 s was used.

The proteolytic digestions of the inactive CC-AMP1-like peptide were analyzed an Acquity UPLC M-Class system (Waters) coupled to a ZenoTOF 7600 mass spectrometer (Sciex). Injections were made to a Symmetry C18 trap column (100 Å, 5 μm, 180 μm × 20 mm; Waters) with a flow rate of 5 μL/min for 3 min using 99% A and 1% B. Peptides were then separated on an HSS T3 C18 column (100 Å, 1.8 μm, 75 μm × 250 mm; Waters) at 45°C using a linear gradient of increasing mobile phase B at a flow rate of 375 nL/min. Mobile phase B was held at 3% for 1 min before being increased from 3% to 50% in 35 min and ramping to 80% in 3 min, where it was held for 5 min before returning to 3% in 1 min and re-equilibrating for 15 min. The instrument was operated in positive mode and, for the tryptic digest, MS survey scans were collected from 300–1500 m/z at an accumulation time of 200 ms. MS/MS data was acquired at 100–1800 m/z using a top 45 IDA method with an accumulation time of 20 ms, selecting precursors from +1 to +3 charge state with intensity greater than 120. For the chymotryptic digest, MS survey scans were collected from 400–1500 m/z at an accumulation time of 200 ms. MS/MS data was acquired at 100–1800 m/z using a top 45 IDA method with an accumulation time of 20 ms, selecting precursors from +2 to +5 charge state with intensity greater than 120. For both samples, an exclusion window of 6 s after 2 occurrences was used and Zeno pulsing was turned on, with Zeno threshold set to 500000.

Hemolytic Assay.

The hemolytic assay of CC-AMP1 (L4-C30) was performed as previously described.18 Briefly, aliquots of 20 μL of peptide sample were added to 80 μL aliquots of 10% human red blood cell suspension (Rockland Immunochemicals). Triton x-100 at a final concentration of 2% was used as the positive control and 0.1% DMSO was used as the negative control. All samples were incubated at 37°C for 1 h before being centrifuged at 10,000 RCF for 5 min. Supernatant aliquots of 50 μL were moved to a 96 well plate to measure absorbance at 570 nm and hemolytic activity was calculated as follows: ((Asample – Anegative)/(Apositive – Anegative)) × 100, where Asample is the absorbance of the peptide sample, Anegative is the absorbance of the water negative control and Apositive is the absorbance of the Triton x-100 positive control.

Peptide Synthesis.

Peptide synthesis was performed as previously reported using a semi-automated flow chemistry instrument built in-house.29,30 Fmoc-amino acids were loaded onto 2-chlorotrityl resin (0.80 mmol/g, 200–400 mesh). Synthesis used Fmoc-deprotection with 20% piperidine in DMF, followed by coupling of each Fmoc amino acid (1 mmol) as a 0.38 M HBTU in DMF (2.5 mL) solution with 450 mL of DIPEA (or 250 mL with His, Cys, or Trp). DMF was used for resin washing between deprotection and coupling steps.

Completed synthetic peptide was cleaved using a TFA/EDT/TIPS/H2O (94:2.5:2.5:1.0) cleavage mixture (10 mL) with a 10-min incubation at 60 °C. The solution was filtered and reduced under a stream of N2 gas, followed by precipitation with diethyl ether at 4 °C. The crude peptide pellet was collect by centrifugation (3000 rpm, 4 °C, 10 min) and further purified by semi preparative HPLC (10–60% B over 20 min, 5 mL/min). Oxidative folding was performed by dissolving reduced peptide (0.1 mg/mL) in 0.1% acetic acid with 5% DMSO (v/v) and adjusting to pH 8.0 for gentle mixing with analytical HPLC monitoring.31 Upon completion, the peptide solution was changed to pH 4.0 with 1.0% aqueous TFA and purified by reverse-phase preparative HPLC.

Peptide Concentration Determination.

Concentration of isolated peptides was determined as previously described,18 using a NanoDrop 1000 (Thermo Fisher Scientific) at an absorbance of 280 nm. Expasy ProParam was used to estimate extincation coefficients.32

Spectral Annotation.

Annotation of MS/MS spectra was performed using the Interactive Peptide Spectral Annotator.33 Data generated from the Q Exactive HF-X mass spectrometer were annotated using a fragment tolerance of 5 ppm and matching threshold of 1% base peak, while all other data used a fragment tolerance of 10 ppm and matching threshold of 1% base peak. All fragment ion assignments were manually verified, with erroneous assignments removed.

Results and Discussion

In silico predictions within Solanaceae

To reveal conservation of CC-AMP1-like and CC-AMP2-like peptides throughout Solanaceae, all proteins within this plant family from UniProt were subjected to an in siliico prediction pipeline modified to search for these specific motifs (Table S1). First, SignalP 6.019 was used to identify and remove any signal peptides, which are expected to be present in AMP precursors.11 Peptides revealed by SignalP were then mined for either the CC-AMP1 or CC-AMP2 cysteine motif utilizing Cysmotif Searcher.20 Then, expected additional proteolytic processing based on observed mature CC-AMP1 and CC-AMP2 sequences18 was manually applied to arrive at a predicted mature AMP sequence (i.e. the removal of a C-terminal pro-domain in CC-AMP1-like peptides and the removal of an additional N-terminal domain in CC-AMP2-like peptides).

The CC-AMP1 motif was observed in peptides throughout nine genome-sequenced Solanaceae species across three genera on UniProt (Figure 1a). In total, 24 protein accessions were predicted to give rise to AMP sequences. Clustering based on sequence similarity illustrates divergence into three groups within mature CC-AMP1-like peptides, with one group predicted solely in Solanum, one group predicted solely in Nicotiana, and the third group predicted throughout all three genera (Solanum, Nicotiana, and Capsicum) (Figure 1a). While AMPs are generally found to be highly basic,10,11 group I peptides are overall anionic, with acidic residues outnumbering basic residues (Figure 1b). As with other, known anionic AMPs, these may require metal ions21 or be pH-dependent22 in order to effectively interact with bacterial pathogens. Group II peptides are generally neutral at pH 7, though they do contain charged residues and may similarly be pH-dependent for antibacterial activity (Figure 1b). Group III peptides are overall slightly basic (Figure 1b) and are the largest group predicted within Solanaceae.

Figure 1.

Figure 1.

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In silico predictions within Solanaceae proteins from UniProt. (a) Alignment of CC-AMP1-like peptides, with CC-AMP1 shown above (Z=pyroglutamic acid). Sequences are divided into three groups based on overall similarity and sub-alignments within each group are included. Positions in which positive charge is conserved are highlighted in pink, while negative charge conservation is highlighted in green. Cysteine residues are shown in red and their conservation throughout is highlighted in blue. Fully conserved residues are marked with “*”, conservation of residues with highly similar properties are marked with “:”, and conservation of residues with weakly similar properties are marked with “.”.(b) CC-AMP2-like peptides, with CC-AMP2 shown above, where highlighting and labeling are analogous to (a). (c) Box and whisker plot of charge at pH 7 for each group of predicted peptide sequences. (d) AlphaFold predicted structures of representative CC-AMP1-like peptides from each group in (a), as well as a representative CC-AMP2-like peptide from (b), where cysteine residues are shown in blue.

Predicted three-dimensional structures via AlphaFold13 were downloaded from UniProt using a representative peptide from each of the three CC-AMP1-like groups, with both the signal peptides and putative C-terminal pro-domains removed from the precursor structures to arrive at a mature AMP structure (Figure 1c). Interestingly, all three peptides demonstrated a structure highly similar to α-hairpinins, a known plant AMP family with a characteristic helix-loop-helix structure.8 α-hairpinins are described as having a cysteine motif of CX3CXnCX3C, forming two disulfide bonds which link the helices. The predicted CC-AMP1-like peptides contain a motif of CX3CX3CX5CX3CX3C (Figure 1a), with the cysteine residues along the helices having identical spacing to those of α-hairpinins. Furthermore, α-hairpinin precursors often contain multiple α-hairpinin domains,8 which is observed in CC-AMP1-like precursors such as accession A0A0V0IS39 in which a second three disulfide bond hairpin-like structure is found within the C-terminal domain (Supplementary Figure S1). These results suggest that CC-AMP1-like peptides comprise a novel sub-family of α-hairpinin, with three disulfide bonds instead of two.

The CC-AMP2 motif was only observed in peptides from Solanum and Capsicum, and not Nicotiana (Figure 1d). High levels of sequence similarity are observed throughout these CC-AMP2-like peptides and five positions maintain basic residues throughout all sequences, possibly indicating the importance of positive charge in these locations to facilitate interaction with bacteria.23 When comparing overall charge, CC-AMP2-like peptides are much more cationic (Figure 1b) and may result in a general increase in potency, as was observed for CC-AMP2 which is approximately 2x more potent against E. coli.18 As with CC-AMP1-like peptides, the three dimensional structure predicted by AlphaFold for CC-AMP2-like peptides was explored using accession A0A2G3CEJ1 as a representative peptide with both the signal peptide and additional N-terminal domain removed. The predicted structure is unique among known AMP families and consists of an alpha-helix with a C-terminal disordered region, made up of the cysteine motif (Figure 1c). While the proximities of cysteine residues in this predicted structure suggest different disulfide bond linkages as to what has been experimentally shown18 (Figure 1c and d), this is a relatively low confidence structure (Supplementary Figure S2) and the C-terminal disordered region would likely fold differently than what is predicted here. As both the cysteine motif and predicted three-dimensional structure of CC-AMP2-like peptides are novel among AMP families, these peptides likely correspond to an undiscovered AMP family with proliferation across Solanum and Capsicum species.

Identification of bioactive peptides within C. annuum and C. baccatum

While in silico predictions of CC-AMP1-like and CC-AMP2-like peptides are useful in illustrating their likely proliferation throughout related plant species, production and accumulation is difficult to predict. Further, it is often difficult to predict a mature AMP sequence with certainty due to factors such as additional cleavages from proteolytic processing and post-translational modifications (PTMs).14 The plant species Capsicum annuum (Aleppo pepper) and Capsicum baccatum (Criolla sella pepper) were thus investigated in order to validate that CC-AMP1-like and CC-AMP2-like peptides accumulated in plant tissue. Exploration of these peptides from closely related Capsicum species allowed for antimicrobial comparison of highly similar sequences, yielding insights into key features that modulate antibacterial activity.

C. annuum antibacterial activity

C. annuum leaf extract was subjected to reversed-phase LC separation, with fractions collected every minute, before being assayed against E. coli ATCC 25922 (Figure 2a). Two regions of 100% inhibition were observed in fractions 26–27 (region 1) and fractions 29–31 (region 2). These correlated with bioactivity regions observed from C. chinense × frutescens (ghost pepper),18 where an identical RPLC separation yielded two regions of activity attributed to CC-AMP1 (fractions 31–32) and CC-AMP2 (fractions 27–30). This suggested that CC-AMP2-like peptides may be attributed to activity in region 1 and CC-AMP1-like peptides may be attributed to activity in region 2.

Figure 2.

Figure 2.

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Identification of CC-AMP1-like and CC-AMP2-like peptides in C. annuum. (a) Overlay of C. annuum reversed-phase chromatogram and percent activity against E. coli ATCC 25922. Two regions of high antimicrobial activity are observed, with region 1 (fractions 26–27) in green and region 2 (fractions 29–31) in red. (b) Mass spectrum of isolated CA-AMP1 in fraction 29, attributed to the activity in region 2, with the assigned sequence above. (c) Overlay of the reversed-phase chromatogram of an additional fractionation of region 1 with the antimicrobial activities of the fractions against E. coli ATCC 25922. (d) Mass spectrum of isolated CA-AMP2 in fraction 18.5, attributed to the activity in region 1, with the assigned sequence above.

C. annuum: region 1 contains CA-AMP2

Although the high antibacterial activity observed in region 1 (fractions 26–27) within C. annuum was expected to result from CC-AMP2-like AMPs (Figure 2a), LC-MS analysis revealed these fractions to be complex peptide mixtures. Thus, fractions in this region were combined and subjected to an additional, modified reversed-phase separation with new fractions collected every 30 s to further simplify mixtures. These fractions were concentrated and again assayed against E. coli ATCC 25922 (Figure 2c). Bioactivity was exclusively observed within fractions eluting from 18, 18.5, and 19 min. LC-MS analysis revealed a highly abundant peptide with a mass of 4065.1 Da observed within all active fractions that was isolated within fraction 18.5 (Figure 2d). This mass matched the predicted mature CC-AMP2-like sequence from both accessions Q947G5 and Q947G6 (Figure 1d) with a ppm error of 4.9 (MWtheo: 4065.0 Da) and was deemed CA-AMP2. The identification was further confirmed with LC-MS/MS (Supplemental Figure S3).

C. annuum region 2 contains CA-AMP1

Region 2 within C. annuum contained a highly abundant mass of 3484.8 Da within all three fractions and was isolated in fraction 29, indicating this as the bioactive compound, deemed CA-AMP1 (Figure 2b). Among predicted CC-AMP1-like peptides within C. annuum (Figure 1a), accession A0A1U8EF54 had a relatively close mass of 3418.7 Da (Supplementary Figure S4). Thus, additional characterization was needed to account for the 66.1 Da mass difference and determine sequence variations and/or post-translational modifications (PTMs). CA-AMP1 was subjected to reduction and alkylation followed by two separate proteolytic digestions with trypsin and chymotrypsin in order to obtain adequate MS/MS fragmentation. Through de novo sequencing of two tryptic and two chymotryptic peptides (Supplementary Figure S4), the full sequence of CA-AMP1 was determined with a theoretical mass of 3484.8 Da matching the observed mass (Figure 1b).

C. baccatum antibacterial activity

C. baccatum leaf extract was also assayed against E. coli ATCC 25922 following reversed-phase separation, with fractions collected every minute (Figure 3a). Two regions of 100% inhibition were observed in fractions 26–29 (region 1) and 30–34 (region 2), correlating to the two bioactive regions identified in C. annuum. As in C. annuum, region 1 within C. baccatum was expected to contain CC-AMP2-like peptides and region 2 was expected to contain CC-AMP1-like peptides.

Figure 3.

Figure 3.

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Identification of CC-AMP1-like and CC-AMP2-like peptides in C. baccatum. (a) Overlay of C. baccatum reversed-phase chromatogram and percent activity against E. coli ATCC 25922. Two regions of high antimicrobial activity are observed, with region 1 (fractions 26–29) in green and region 2 (fractions 30–34) in red. (b) Antimicrobial activities of fractions collected from an additional reversed-phase separation of region 2 against E. coli ATCC 25922, overlayed with the abundances of observed CC-AMP1-like peptides. Each peptide’s maximum abundance is normalized to 1 for visualization. The determined sequences of each peptide are listed to the right of the plot. (c) Overlay of the reversed-phase chromatogram of an additional fractionation of region 1 with the antimicrobial activities of the fractions against E. coli ATCC 25922. (d) Mass spectrum of CC-AMP1 (D5-C30), attributed to the activity of fraction 24, with the assigned sequence above. (e) Mass spectrum of observed CC-AMP2-like peptides, attributed to the activity of fractions 18–19.5. The determined sequences are listed to the right of the spectrum.

C. baccatum region 1 contains both CC-AMP-2-like and CC-AMP-1-like peptides

As observed in C. annuum region 1, C. baccatum region 1 contained complex mixtures of peptides and was subjected to an identical separation and bioassay (Figure 3b). Fractions 17.5–19.5 and 24 demonstrated robust bioactivity against E. coli. Two CC-AMP2-like peptides were found within fractions 18–19.5, with masses of 4093.1 Da and 4136.1 Da (Figure 3c). These masses were matched to predicted mature CC-AMP2-like sequences found in C. baccatum: accession A0A2G2X990 (MWtheo: 4093.0 Da) and accession A0A2G2X9U8 (MWtheo: 4136.1 Da) (Figure 1d). These putative sequences were further confirmed with LC-MS/MS (Supplementary Figures S5 and S6). One CC-AMP1-like peptide was identified in fraction 24 with a mass of 2779.3 Da, determined to be a truncated sequence of CC-AMP1 (CC-AMP1 (D5-C30)) (Figure 3d) and confirmed via LC-MS/MS (Supplementary Figure S7). While fraction 17.5 displayed antimicrobial activity, no CC-AMP1-like or CC-AMP2-like peptides were observed.

C. baccatum region 2 contains CC-AMP1-like peptides

Predictions within C. baccatum revealed three potential CC-AMP1-like peptides (Figure 1a) from accessions A0A2G2VRW2 (MWtheo: 3432.6 Da), A0A2G2VS94 (MWtheo: 3446.7 Da), and A0A2G2VRJ9 (MWtheo: 3364.6 Da). While similar masses were noted following LC-MS analysis of region 2, none of these predicted CC-AMP1-like masses were observed, suggesting potential sequence differences and/or PTMs. Further, the fractions were relatively complex and single peptides could not be attributed to activity within each fraction. Thus, further separation followed by bioactivity screening was employed to decrease the complexity of this bioactive region (Figure 3e), identical to the separation used in region 1 (Figure 3b). Activity was observed across fractions 24 to 29.5 min (Figure 3e). The activity profile contained several maxima suggesting three overlapping peaks and multiple activity contributors throughout this region. Fractions 22.5–31.5 were therefore analyzed via LC-MS to fit peptide abundances to antibacterial activity and elucidate the most likely peptides responsible for this activity. Four peptides were identified whose abundance profiles correlated with the observed bioactivity (Figure 3e), with masses 2892.4, 3498.7, 3445.7, and 3233.5 Da, all of which were targeted for further analysis.

All four peptides sequences were determined via targeted LC-MS/MS analyses (Supplementary Figures S8–S11). Interestingly, the peptide of mass 3445.7 Da was identified as CC-AMP1, despite relatively different CC-AMP1-like peptides predicted in C. baccatum (Figure 1a). Two of the other peptides, 2892.4 Da and 3233.5 Da, were identified as truncated CC-AMP1 sequences (CC-AMP1 (L4-C30) and CC-AMP1 (Z1-C30), respectively), indicating that the first three and last two residues in CC-AMP1 are not necessary for antibacterial activity. Finally, the peptide of mass 3498.7 Da was found to correspond to CC-AMP1 with two amino acid substitutions, T3 to K3 and A10 to P10, and was deemed CB-AMP1.

Interestingly, a fifth CC-AMP1-like mass of 3443.7 Da was observed that was inactive (Figure 3e). This peptide was subjected to LC-MS/MS analysis following separate digestions with chymotrypsin and trypsin (Supplementary Figure S12). Four amino acid substitutions were observed from the CC-AMP1 sequence to this peptide. Most notably, a loss of positive charge occurred with a K18 to T18 substitution. If positive charge at this position is essential for bacterial interaction, a loss of that charge would explain the loss of bioactivity.

In total, three CC-AMP2-like peptides and seven CC-AMP1-like peptides were identified across C. annuum and C. baccatum. While in silico AMP predictions provided insight into putative CC-AMP1-like and CC-AMP2-like peptides (Figure 1a and 1d), a large amount of sequence diversity was encountered within the identified peptides (Figure 2c–d, Figure 3c–e), relative to those that were predicted. This disparity highlights the need for targeted mass spectrometric characterization of these peptides.

Antibacterial comparison of CC-AMP1-like peptides

While bioactivity screenings against E. coli ATCC 25922 were useful in the identification of CC-AMP1-like and CC-AMP2-like peptides within the C. annuum and C. baccatum extracts, we wanted to explore the capacity for bioactivity against the more biologically relevant human pathogen K. pneumoniae VK148. Three CC-AMP1-like peptides including CC-AMP1, CA-AMP1, CB-AMP1 were synthesized, and all displayed similar levels of activity (Figure 4a). Additionally, three variants of CC-AMP1 were synthesized (Figure 4b). Several significant differences in antimicrobial activity observed as a result of their slight sequence differences allowed us to begin to determine the structure-activity relationship (SAR) of CC-AMP1 as follows.

Figure 4.

Figure 4.

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Activity comparisons of different CC-AMP1-like peptides against K. pneumoniae VK148, in which * corresponds to p<0.05, ** corresponds to p<0.01, and *** corresponds to p<0.001, resulting from two-tailed t-tests. (a) Activity comparison of CC-AMP1, CA-AMP1, and CB-AMP1. (b) Primary sequences of all assayed peptides and representative AlphaFold-predicted structure of CC-AMP1 in two different orientations, in which hydrophobic residues are red, charged lysine residues are purple, the acetylated lysine residue is green, and disulfide-bound cysteine residues are blue. (c) Activity comparison of CC-AMP1 variants, including Z1-C30, L4-C30, and K18 acetylated.

Acetylation of K18 significantly reduces activity

Acetylation of K18 resulted in a significant loss of CC-AMP1 activity (Figure 4c). The Alphafold-predicted structure from UniProt accession A0A2G3BCB3 (Figure 1a) was used as a proxy for the structure of CC-AMP1 (Figure 4b), as the only sequence difference from this accession to CC-AMP1 is a K3 to T3 substitution. When viewing the lysine residues in this structure, there is a clear difference in directionality between K18 and the other lysine residues (Figure 4b). We hypothesize that these four positive charges are used in the initial interaction of the peptide with the negative charges of the bacterial membrane. The lysine at position 18, which is facing the same direction as the majority of the hydrophobic residues within the peptide, is then utilized to re-orient the peptide for hydrophobic interactions within the membrane. When K18 is acetylated, removing that charge, it is likely that this re-orientation is too difficult to occur.

N-terminal and C-terminal hydrophobicity significantly increase activity

It is clear that a large amount of hydrophobicity is required within these peptides in order to maximize antibacterial activity. Significantly higher activity was observed with CC-AMP1 (L4-C30) relative to CC-AMP1 across all concentrations (Figure 4c). Truncation of the first three residues in CC-AMP1 results in the N-terminal tail having a higher overall hydrophobicity (Figure 4c), likely increasing its ability for hydrophobic interactions within the bacterial membrane. Conversely, significantly lower activity was observed with CC-AMP1 (Z1-C30) relative to CC-AMP1 at 20, 15, and 10 μM concentrations (Figure 4c). As the two C-terminal residues are hydrophobic (Figure 4b), truncation of these likely decreases the peptide’s ability for hydrophobic interactions. As CC-AMP1 (L4-C30) also has the C-terminal truncation of these two hydrophobic residues, it is expected that a variant which includes those residues would result in even higher activity.

Exploring CC-AMP1 (L4-C30) bioactivity

CC-AMP1 has been shown to possess activity against several Gram-negative ESKAPE pathogens at low micromolar concentrations, with 50% inhibitory concentrations (IC50) of 13.2, 6.9, and 4.0 μM against K. pneumoniae VK148, and P. aeruginosa 1423, A. baumannii 5075, respectively.18 The ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter species) are particularly relevant human pathogens due to their pathogenicity and multi-drug resistances.24 The significant enhancement in activity of CC-AMP1 (L4-C30) against K. pneumoniae relative to CC-AMP1 (Figure 4c) led to the further examination of antimicrobial activity of this variant against all other ESKAPE pathogens. CC-AMP1 (L4-C30) displayed broad-spectrum activity against a full ESKAPE pathogens panel (Figure 5a). Unlike CC-AMP1,18 the truncated peptide was active against Gram-positive E. faecium and S. aureus, with IC50 values of 4.6 and 20.7 μM, respectively (Figure 5a). This is likely due to the increased hydrophobicity of the N-terminal region as discussed above. Further, activity of the truncated peptide was generally higher than that of CC-AMP1, with IC50 values of 7.9, 6.2, and 2.6 μM for K. pneumoniae, P. aeruginosa, and A. baumannii, respectively (Figure 5a). However, despite high activity against other Gram-negative pathogens, CC-AMP1 (L4-C30) activity against Gram-negative E. cloaceae only reached ~60% at the highest concentration tested of 40 μM (Figure 5a).

Figure 5.

Figure 5.

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Additional assays of CC-AMP1 (L4-C30). (a) ESKAPE pathogen assays, with 50% inhibitory concentrations (IC50) calculated for each bacteria except for E. cloaceae. The K. pneumoniae data is taken from Figure 4A, with two additional concentrations at 5 and 2.5 μM of CC-AMP1 (L4-C30). (b) Hemolytic assay against human red blood cells.

Additionally, CC-AMP1(L4-C30) was assessed for hemolytic activity against human erythrocytes, as CC-AMP1 was previously shown to be non-hemolytic. Despite the increase observed in antimicrobial activity (Figure 4c and 5a) due to the higher hydrophobicity of the N-terminal region, CC-AMP1 (L4-C30) was also non-hemolytic towards human erythrocytes (Figure 5b).

Prediction of CC-AMP1-like and CC-AMP2-like peptides across all plants

In silico prediction of CC-AMP1-like and CC-AMP2-like peptides was expanded to cover all UniProt Viridiplantae proteins, approximately 13 million sequences at the time of download, utilizing SignalP 6.019 and Cysmotif Searcher20 as was implemented with Solanaceae proteins. Prediction of CC-AMP2-like peptides yielded no additional results beyond those observed within Solanaceae, indicating that these peptides likely belong to a smaller AMP family only found within a select number of closely related species. However, 44 accessions across 10 genera were predicted to contain at least one CC-AMP1-like peptide (Figure 6). Highly heterologous sequences were observed, with precursors containing variable numbers of putative α-hairpinin domains, as is observed across known α-hairpinins.8

Figure 6.

Figure 6.

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Guide tree cladogram of predicted CC-AMP1-like precursors across all UniProt plants, with signal peptides removed. Clades containing highly similar sequences and predicted three-dimensional structures are color coded, with the number of circles next to accessions corresponding to the number of observed α-hairpinin domains. A representative AlphaFold predicted structure with the highest number of observed α-hairpinin domains is shown for each of these groupings, where the domains are colored in purple and the cysteine residues expected to be disulfide-bound within these domains are colored in blue.

Interestingly, many of these α-hairpinin domains contained differing cysteine motifs to those that have thus far been seen in CC-AMP1-like peptides, with some domains differing within the same precursor. For example, accession A0A5E4FH28 from Prunus dulcis contained two α-hairpinin domains with one displaying the CC-AMP1-like motif of CX3CX3CX5CX3CX3C and the other displaying the traditional α-hairpinin motif of CX3CXnCX3C (Supplementary Figure S13). Additionally, some putative α-hairpinins showed differential spacing between cysteine residues within the motif, contrasting the three residue spacing between all helix cysteines that is generally observed. Accession A0A0D3BUV1 from Brassica oleracea consists of three α-hairpinin domains, one of which contained a peculiar cysteine motif of CX4CX3CX7CX2CX3C while still maintaining a three disulfide bond helix-loop-helix predicted three dimensional structure (Figure 6 and Supplementary Figure S13).

While this prediction workflow was able to generate results indicating 44 putative CC-AMP1-like peptides, there are some limitations. Several proteins predicted by Cysmotif Searcher did not appear to be CC-AMP1-like despite containing the cysteine motif (Supplementary Table S2). For example, accession A0A0B0MHC7 from Gossypium arboreum is annotated as a cytochrome b-c1 complex subunit and is not predicted to form the hairpin-like helix-loop-helix structure (Supplementary Figure S14a). Accession A0A1S3TZS3 from Vigna radiata, annotated as loricrin-like is also not predicted to form the CC-AMP1-like structure (Supplementary Figure S14e). While accession A0A835TCJ4 from Chlamydomonas incerta does not have an associated AlphaFold prediction, this is a large protein of approximately 3,000 amino acids which is annotated as a cytochrome P450 (Supplementary Table S2) and likely does not contain any AMP domains. Finally, two proteins from Digitaria exilis with accessions A0A835AK19 and A0A835AMY7 were annotated as keratin associated protein-like, with elongated structures that did not appear to be CC-AMP1-like (Supplementary Figure S14b and d); a third protein from the same species with accession A0A835A1E1 had a similar predicted AlphaFold structure (Supplementary Figure S14c). Incorporation of AlphaFold structures into large-scale AMP predictions in silico can be an extremely valuable tool to eliminate erroneous predictions and hone in on likely AMP targets.

Overall, based on these results it is clear that the prevalence and structural diversity of the α-hairpinin AMP family is much greater than previously thought. It is likely that many of these predicted peptides have a wide range of bioactive functions similar to those that have been described in other α-hairpinins such as antibacterial and antifungal.15,17,25 The promising antibacterial results in characterizing the CC-AMP1-like peptides discovered within Capsicum spp. demonstrate the value in further investigation of this intriguing AMP family. Beyond this, continued discovery and characterization of entirely new AMP families, such as the CC-AMP2-like peptides, is necessary in realizing the potential of plant AMPs, which remain underexplored.

Supplementary Material

Supplementary Figures

Figure S1–2: AlphaFold predicted structures of CC-AMP1 and CC-AMP2-like proteins. Figure S3–12: Annotated MS/MS spectra of identified peptides. Figure S13: In silico alignment of predicted proteins. Figure S14: AlphaFold structures of predicted CC-AMP1-like proteins.

Supplementary Tables

Table S1: Cysmotif Searcher results from Solanaceae proteins. Table S2: Cysmotif Searcher results from all Uniprot plants.

Acknowledgments

This work was supported by NIH-NIGMS under award number R01GM125814 to L.M.H.

Footnotes

Competing interests

The authors declare no competing interests.

Data availability

The mass spectrometry data have been deposited at the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository34 with the data set identifier PXD041035.

References

  • (1).Bin Hafeez A; Jiang X; Bergen PJ; Zhu Y Antimicrobial Peptides: An Update on Classifications and Databases. Int. J. Mol. Sci. 2021, 22 (21). 10.3390/ijms222111691. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (2).Campos ML; de Souza CM; de Oliveira KBS; Dias SC; Franco OL The Role of Antimicrobial Peptides in Plant Immunity. J. Exp. Bot. 2018, 69 (21), 4997–5011. 10.1093/jxb/ery294. [DOI] [PubMed] [Google Scholar]
  • (3).Mahlapuu M; Håkansson J; Ringstad L; Björn C Antimicrobial Peptides: An Emerging Category of Therapeutic Agents. Front. Cell. Infect. Microbiol. 2016, 6, 194. 10.3389/fcimb.2016.00194. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (4).Wang G; Li X; Wang Z APD3: The Antimicrobial Peptide Database as a Tool for Research and Education. Nucleic Acids Res. 2015, 44 (D1), D1087–D1093. 10.1093/nar/gkv1278. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (5).Li C; Wang D; Zhou Y; Kang K; Ge Y Antifungal Activity of Camelus-Derived LFA-LFC Chimeric Peptide Gelatin Film and Effect on Oral Bacterial Biofilm. Appl. Biochem. Biotechnol. 2022. 10.1007/s12010-022-04248-1. [DOI] [PubMed] [Google Scholar]
  • (6).Songnaka N; Lertcanawanichakul M; Hutapea AM; Krobthong S; Yingchutrakul Y; Atipairin A Purification and Characterization of Novel Anti-MRSA Peptides Produced by Brevibacillus Sp. SPR-20. Molecules 2022, 27 (23). 10.3390/molecules27238452. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (7).Chia LY; Kumar PV; Maki MAA; Ravichandran G; Thilagar S A Review: The Antiviral Activity of Cyclic Peptides. Int. J. Pept. Res. Ther 2023, 29 (1), 7. 10.1007/s10989-022-10478-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (8).Slavokhotova AA; Rogozhin EA Defense Peptides From the α-Hairpinin Family Are Components of Plant Innate Immunity. Front. Plant Sci. 2020, 11, 465. 10.3389/fpls.2020.00465. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (9).Li J; Hu S; Jian W; Xie C; Yang X Plant Antimicrobial Peptides: Structures, Functions, and Applications. Bot. Stud. 2021, 62 (1), 5. 10.1186/s40529-021-00312-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (10).Nawrot R; Barylski J; Nowicki G; Broniarczyk J; Buchwald W; Goździcka-Józefiak A Plant Antimicrobial Peptides. Folia Microbiol. (Praha). 2014, 59 (3), 181–196. 10.1007/s12223-013-0280-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (11).Tam J; Wang S; Wong K; Tan W Antimicrobial Peptides from Plants. Pharmaceuticals 2015, 8 (4), 711–757. 10.3390/ph8040711. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (12).Leebens-Mack JH; Barker MS; Carpenter EJ; Deyholos MK; Gitzendanner MA; Graham SW; Grosse I; Li Z; Melkonian M; Mirarab S; Porsch M; Quint M; Rensing SA; Soltis DE; Soltis PS; Stevenson DW; Ullrich KK; Wickett NJ; DeGironimo L; Edger PP; Jordon-Thaden IE; Joya S; Liu T; Melkonian B; Miles NW; Pokorny L; Quigley C; Thomas P; Villarreal JC; Augustin MM; Barrett MD; Baucom RS; Beerling DJ; Benstein RM; Biffin E; Brockington SF; Burge DO; Burris JN; Burris KP; Burtet-Sarramegna V; Caicedo AL; Cannon SB; Çebi Z; Chang Y; Chater C; Cheeseman JM; Chen T; Clarke ND; Clayton H; Covshoff S; Crandall-Stotler BJ; Cross H; dePamphilis CW; Der JP; Determann R; Dickson RC; Di Stilio VS; Ellis S; Fast E; Feja N; Field KJ; Filatov DA; Finnegan PM; Floyd SK; Fogliani B; García N; Gâteblé G; Godden GT; Goh F Qi Y.; Greiner S; Harkess A; Heaney JM; Helliwell KE; Heyduk K; Hibberd JM; Hodel RGJ; Hollingsworth PM; Johnson MTJ; Jost R; Joyce B; Kapralov MV; Kazamia E.; Kellogg EA; Koch MA; Von Konrat M; Könyves K; Kutchan TM; Lam V; Larsson A; Leitch AR; Lentz R; Li F-W; Lowe AJ; Ludwig M; Manos PS; Mavrodiev E; McCormick MK; McKain M; McLellan T; McNeal JR; Miller RE; Nelson MN; Peng Y; Ralph P; Real D; Riggins CW; Ruhsam M; Sage RF; Sakai AK; Scascitella M; Schilling EE; Schlösser E-M; Sederoff H; Servick S; Sessa EB; Shaw AJ; Shaw SW; Sigel EM; Skema C; Smith AG; Smithson A; Stewart CN; Stinchcombe JR; Szövényi P; Tate JA; Tiebel H; Trapnell D; Villegente M; Wang C-N; Weller SG; Wenzel M; Weststrand S; Westwood JH; Whigham DF; Wu S; Wulff AS; Yang Y; Zhu D; Zhuang C; Zuidof J; Chase MW; Pires JC; Rothfels CJ; Yu J; Chen C; Chen L; Cheng S; Li J; Li R; Li X; Lu H; Ou Y; Sun X; Tan X; Tang J; Tian Z; Wang F; Wang J; Wei X; Xu X; Yan Z; Yang F; Zhong X; Zhou F; Zhu Y; Zhang Y; Ayyampalayam S; Barkman TJ; Nguyen N; Matasci N; Nelson DR; Sayyari E; Wafula EK; Walls RL; Warnow T; An H; Arrigo N; Baniaga AE; Galuska S; Jorgensen SA; Kidder TI; Kong H; Lu-Irving P; Marx HE; Qi X; Reardon CR; Sutherland BL; Tiley GP; Welles SR; Yu R; Zhan S; Gramzow L; Theißen G; Wong GK-S; Initiative OTPT One Thousand Plant Transcriptomes and the Phylogenomics of Green Plants. Nature 2019, 574 (7780), 679–685. 10.1038/s41586-019-1693-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (13).Varadi M; Anyango S; Deshpande M; Nair S; Natassia C; Yordanova G; Yuan D; Stroe O; Wood G; Laydon A; Žídek A; Green T; Tunyasuvunakool K; Petersen S; Jumper J; Clancy E; Green R; Vora A; Lutfi M; Figurnov M; Cowie A; Hobbs N; Kohli P; Kleywegt G; Birney E; Hassabis D; Velankar S AlphaFold Protein Structure Database: Massively Expanding the Structural Coverage of Protein-Sequence Space with High-Accuracy Models. Nucleic Acids Res. 2022, 50 (D1), D439–D444. 10.1093/nar/gkab1061. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (14).Culver KD; Hicks LM In Silico Prediction and Mass Spectrometric Characterization of Botanical Antimicrobial Peptides. Methods Enzymol. 2022, 663, 157–175. 10.1016/bs.mie.2021.11.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (15).Slavokhotova AA; Rogozhin EA; Musolyamov AK; Andreev YA; Oparin PB; Berkut AA; Vassilevski AA; Egorov TA; Grishin E V; Odintsova, T. I. Novel Antifungal α-Hairpinin Peptide from Stellaria Media Seeds: Structure, Biosynthesis, Gene Structure and Evolution. Plant Mol. Biol. 2014, 84 (1), 189–202. 10.1007/s11103-013-0127-z. [DOI] [PubMed] [Google Scholar]
  • (16).Sousa DA; Porto WF; Silva MZ; da Silva TR; Franco OL Influence of Cysteine and Tryptophan Substitution on DNA-Binding Activity on Maize α-Hairpinin Antimicrobial Peptide. Molecules 2016, 21 (8). 10.3390/molecules21081062. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (17).Barashkova AS; Ryazantsev DY; Rogozhin EA Rational Design of Plant Hairpin-like Peptide EcAMP1: Structural-Functional Correlations to Reveal Antibacterial and Antifungal Activity. Molecules 2022, 27 (11). 10.3390/molecules27113554. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (18).Culver KD; Allen JL; Shaw LN; Hicks LM Too Hot to Handle: Antibacterial Peptides Identified in Ghost Pepper. J. Nat. Prod. 2021, 84 (8), 2200–2208. 10.1021/acs.jnatprod.1c00281. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (19).Teufel F; Almagro Armenteros JJ; Johansen AR; Gíslason MH; Pihl SI; Tsirigos KD; Winther O; Brunak S; von Heijne G; Nielsen H SignalP 6.0 Predicts All Five Types of Signal Peptides Using Protein Language Models. Nat. Biotechnol. 2022. 10.1038/s41587-021-01156-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (20).Shelenkov AA; Slavokhotova AA; Odintsova TI Cysmotif Searcher Pipeline for Antimicrobial Peptide Identification in Plant Transcriptomes. Biochem. 2018, 83 (11), 1424–1432. 10.1134/S0006297918110135. [DOI] [PubMed] [Google Scholar]
  • (21).Łoboda D; Kozłowski H; Rowińska-Żyrek M Antimicrobial Peptide–Metal Ion Interactions – a Potential Way of Activity Enhancement. New J. Chem. 2018, 42 (10), 7560–7568. 10.1039/C7NJ04709F. [DOI] [Google Scholar]
  • (22).Malik E; Dennison SR; Harris F; Phoenix DA PH Dependent Antimicrobial Peptides and Proteins, Their Mechanisms of Action and Potential as Therapeutic Agents. Pharmaceuticals (Basel). 2016, 9 (4). 10.3390/ph9040067. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (23).Zhang Q-Y; Yan Z-B; Meng Y-M; Hong X-Y; Shao G; Ma J-J; Cheng X-R; Liu J; Kang J; Fu C-Y Antimicrobial Peptides: Mechanism of Action, Activity and Clinical Potential. Mil. Med. Res. 2021, 8 (1), 48. 10.1186/s40779-021-00343-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (24).Aloke C; Achilonu I Coping with the ESKAPE Pathogens: Evolving Strategies, Challenges and Future Prospects. Microb. Pathog. 2023, 175, 105963. 10.1016/j.micpath.2022.105963. [DOI] [PubMed] [Google Scholar]
  • (25).Nolde SB; Vassilevski AA; Rogozhin EA; Barinov NA; Balashova TA; Samsonova OV; Baranov YV; Feofanov AV; Egorov TA.; Arseniev AS.; Grishin EV. Disulfide-Stabilized Helical Hairpin Structure and Activity of a Novel Antifungal Peptide EcAMP1 from Seeds of Barnyard Grass (Echinochloa Crus-Galli). J. Biol. Chem. 2011, 286 (28), 25145–25153. 10.1074/jbc.M110.200378. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (26).Pundir S; Martin MJ; O’Donovan C; Consortium U UniProt Tools. Curr. Protoc. Bioinforma. 2016, 53, 1.29.1–1.29.15. 10.1002/0471250953.bi0129s53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (27).Pettersen EF; Goddard TD; Huang CC; Couch GS; Greenblatt DM; Meng EC; Ferrin TE UCSF Chimera—A Visualization System for Exploratory Research and Analysis. J. Comput. Chem. 2004, 25 (13), 1605–1612. 10.1002/jcc.20084. [DOI] [PubMed] [Google Scholar]
  • (28).Kirkpatrick CL; Broberg CA; McCool EN; Lee WJ; Chao A; McConnell EW; Pritchard DA; Hebert M; Fleeman R; Adams J; Jamil A; Madera L; Strömstedt AA; Göransson U; Liu Y; Hoskin DW; Shaw LN; Hicks LM The “PepSAVI-MS” Pipeline for Natural Product Bioactive Peptide Discovery. Anal. Chem. 2017, 89 (2), 1194–1201. 10.1021/acs.analchem.6b03625. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (29).Simon MD; Heider PL; Adamo A; Vinogradov AA; Mong SK; Li X; Berger T; Policarpo RL; Zhang C; Zou Y; Liao X; Spokoyny AM; Jensen KF; Pentelute BL Rapid Flow-Based Peptide Synthesis. Chembiochem 2014, 15 (5), 713–720. 10.1002/cbic.201300796. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (30).Moyer TB; Purvis AL; Wommack AJ; Hicks LM Proteomic Response of Escherichia Coli to a Membrane Lytic and Iron Chelating Truncated Amaranthus Tricolor Defensin. BMC Microbiol. 2021, 21 (1), 110. 10.1186/s12866-021-02176-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (31).Tam JP; Wu CR; Liu W; Zhang JW Disulfide Bond Formation in Peptides by Dimethyl Sulfoxide. Scope and Applications. J. Am. Chem. Soc. 1991, 113 (17), 6657–6662. 10.1021/ja00017a044. [DOI] [Google Scholar]
  • (32).Gasteiger E; Hoogland C; Gattiker A; Duvaud S; Wilkins MR; Appel RD; Bairoch A Protein Identification and Analysis Tools on the ExPASy Server BT - The Proteomics Protocols Handbook; Walker JM., Ed.; Humana Press: Totowa, NJ, 2005; pp 571–607. 10.1385/1-59259-890-0:571. [DOI] [Google Scholar]
  • (33).Brademan DR; Riley NM; Kwiecien NW; Coon JJ Interactive Peptide Spectral Annotator: A Versatile Web-Based Tool for Proteomic Applications. Mol. Cell. Proteomics 2019, 18 (8 suppl 1), S193–S201. 10.1074/mcp.TIR118.001209. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (34).Vizcaíno JA; Csordas A; del-Toro N; Dianes JA; Griss J; Lavidas I; Mayer G; Perez-Riverol Y; Reisinger F; Ternent T; Xu Q-W; Wang R; Hermjakob H 2016 Update of the PRIDE Database and Its Related Tools. Nucleic Acids Res. 2016, 44 (D1), D447–D456. 10.1093/nar/gkv1145. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Figures

Figure S1–2: AlphaFold predicted structures of CC-AMP1 and CC-AMP2-like proteins. Figure S3–12: Annotated MS/MS spectra of identified peptides. Figure S13: In silico alignment of predicted proteins. Figure S14: AlphaFold structures of predicted CC-AMP1-like proteins.

NIHMS1972859-supplement-Supplementary_Figures.docx (1.4MB, docx)
Supplementary Tables

Table S1: Cysmotif Searcher results from Solanaceae proteins. Table S2: Cysmotif Searcher results from all Uniprot plants.

NIHMS1972859-supplement-Supplementary_Tables.xlsx (22KB, xlsx)

Data Availability Statement

The mass spectrometry data have been deposited at the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository34 with the data set identifier PXD041035.

RESOURCES