Peptides have great potential to combat antibiotic resistance. While many platforms can screen peptides for their ability to bind to target cells, there are virtually no platforms that directly assess the functionality of peptides. This limitation is exacerbated when identifying antimicrobial peptides because the phenotype, death, selects against itself and has caused a scientific bottleneck that confines research to a few naturally occurring classes of antimicrobial peptides. We have used this seeming dissonance to develop Surface Localized Antimicrobial Display (SLAY), a platform that allows screening of unlimited numbers of peptides of any length, composition, and structure in a single tube for antimicrobial activity. Using SLAY, we screened ∼800,000 random peptide sequences for antimicrobial function and identified thousands of active sequences, dramatically increasing the number of known antimicrobial sequences. SLAY hits present with different potential mechanisms of peptide action and access to areas of antimicrobial physicochemical space beyond what nature has evolved.

To overcome these roadblocks, we present Surface Localized Antimicrobial Display (SLAY), a high-throughput screening platform that rapidly identifies lead antimicrobial peptides to combat multi-drug-resistant gram-negative bacteria. SLAY drives bacteria to express and self-test peptides of any size, structure, or sequence complexity for antimicrobial activity through a physiologically and therapeutically meaningful interface and provides readout of the interactions via high-throughput DNA sequencing. Using SLAY, we quickly screened a library of approximately 800,000 20-mer peptides for antimicrobial activity and identified 7,968 fully synthetic sequences covering an unprecedented range of peptide physicochemical space. Selected peptides with properties far removed from CAMPs showed activity against multi-drug-resistant bacteria, different potential mechanisms of action, and low eukaryotic toxicity. SLAY offers a unique approach to peptide discovery and aims to revolutionize our understanding of antimicrobial peptide chemistry that can serve to supplement our antibiotic arsenal, generate antibiotic scaffolds, and expand our knowledge of potential antimicrobial targets to combat the spread of antibiotic-resistant bacteria.

With the near infinite possibilities of combinatorial sequence space and our limited understanding of peptide chemistry with antimicrobial activity, it is nearly impossible to predict bioactive sequences de novo (). This necessitates the development of functional approaches for peptide exploration if we hope to capitalize on their therapeutic potential. Many technologies, like phage display, allow screening or selecting for peptides that bind a molecule or cell but do not provide a means to directly assess the functionality and antimicrobial relevance of the peptides or their interactions. Antimicrobial peptide screening through these approaches is further confounded because an antimicrobial interaction eliminates the target bacteria and prevents recovery of the active peptide. Alternative molecular approaches express peptides intracellularly to identify sequences with antimicrobial activity. Unfortunately, peptides identified through these approaches often fail to show activity in synthetic form because they cannot pass through the cell membrane to reach their target. Current chemical synthesis approaches that do allow functional peptide screening are limited to a few thousand short, linear sequences at a time and require combinatorial chemistry and robotics for scale-up, which is beyond the reach of most research programs (). While marking an important advance in peptide screening, this capacity has not facilitated antimicrobial peptide exploration beyond naturally available templates, leaving the majority of potentially therapeutically valuable peptide chemical space undiscovered.

There has been a resurgence of interest in developing antimicrobial peptides to supplement our antibiotic arsenal, generate new scaffolds for antibiotic design, and expand our knowledge of antimicrobial action (). However, we lack simple, biologically relevant means to screen comprehensive peptide libraries and discover peptides with antimicrobial activity for development. This has limited antimicrobial peptide research to the few unique classes that have evolved in nature, with the majority of studies focusing on a single dominant class of naturally occurring cationic antimicrobial peptides (CAMPs) (). CAMPs are characterized by strong cationic charge and amphipathic properties with broad-spectrum activity and pore-forming mechanisms of action (). While CAMPs are successful in terms of their broad activity against pathogens in vitro, they have not been successful therapeutically (). Natural antimicrobial peptides beyond CAMPs have sequences of diverse length, chemistry, and structure, acting on a wide range of molecular targets (). This underscores that no single peptide sequence has evolved as singularly effective against all pathogens in all settings ().

Antibiotic-resistant bacteria are projected to kill 30 million people by 2050 (). As emphasized by recent World Health Organization reports, antibiotics to treat gram-negative bacterial infections are needed most (). The path from antibiotic discovery to clinical therapy has a high attrition rate, with the last new class of antibiotics to combat gram-negative bacteria being discovered over 40 years ago (). Most antibiotic screening methods have not evolved far from the innovation of Waksman’s approach developed in the 1930s and are no longer able to quickly identify new lead compounds (). Necessitated by the lack of new leads and sources for natural products, companies are attempting to resurrect previously unsuccessful drug candidates (). Reliable and robust antibiotic discovery platforms are urgently needed to discover new leads against new microbial targets in our arms race against resistance.

Hemolysis is a known off-target effect of CAMPs, with peptides such as protegrin-1 showing marked hemolysis at therapeutically relevant concentrations (). The hemolytic activities of the peptides against human red blood cells were determined as an indication of their toxicity toward mammalian cells. The hemolytic activities of all peptides are summarized in Figure 5 C. PBS was used as a negative control and 1% triton was used as a positive control for 100% lysis. None of the peptides P3–P18 identified in our screen exhibited notable hemolytic activity, with all being well under 20% hemolysis. However, maximal tolerated dose testing in CD-1 mice with cationic peptide P1 and anionic peptide P7 revealed marked differences in toxic effects. Cationic peptide P1 showed toxic effects at 25 mg/kg (seizure-like activity) and caused immediate mortality at 35 mg/kg. This agrees with established literature that cationic peptides frequently have toxic effects (). On the other hand, the anionic peptide P7 did not show any toxic effects up to the maximum dose of 50 mg/kg.

We further probed the mechanism of SLAY peptides with time-dependent killing assays. While membrane-targeting CAMPs kill rapidly, antimicrobials targeting specific cellular processes tend to elicit their effect over a long period of time (). We selected our top five non-cationic peptides—P3 cyclic, P4, P5 cyclic, P6, and P7—for testing. We assayed all peptides at 4× MBC. In our time-kill assay, cecropin P1 killed >99.9% of bacteria in less than 30 min ( Figure 5 B). In contrast, our selected peptides acted over a longer time period. Peptides P3, P4, and P5 acted over 12 hr, while P6 and P7 acted over 18 hr. Additionally, development of resistance was not observed in W3110 during continuous serial passaging in the presence of subinhibitory concentration of the cationic peptide P1, while resistance could be generated against anionic P7 ( Figure S7 ). Combined with their non-pore forming action, these results suggest that peptides identified through SLAY may represent non-pore forming and diverse mechanism of action.

Serial passage of E. coli W3110 with 15 days of sub-inhibitory concentrations of peptides P1 and P7. Passages were done in triplicate. Resistance is not observed with cationic P1 peptide. One replicate of the anionic P7 peptide developed 64-fold resistance over the 15-day period.

Defining the target(s) and mechanism(s) of antibiotic action is challenging and still debated for many clinically used antibiotics (). To begin to explore the mechanism of action of peptides identified by SLAY, we compared their pore-forming activity and killing kinetics to the traditional CAMP cecropin P1. Peptide-dependent membrane damage is commonly assayed with propidium iodide (PI), which penetrates cells with compromised membranes to stain nucleic acids (). The effect of peptides on E. coli was probed by incubating peptide-treated cells with PI followed by flow cytometry analysis to determine peptide-induced membrane damage as previously described () ( Figure 5 A). Treatment of E. coli with cecropin P1, a known pore-forming peptide, resulted in 33.7% of the population staining PI positive, indicating membrane damage. Cationic peptides P1 and P2 identified by SLAY exhibited even stronger membrane damage compared to cecropin P1, with 85.3% and 71.6% PI-positive cells, respectively. Remarkably, peptides P3–P18 identified in our screen that contained atypically antimicrobial amino acid compositions compared to known CAMPs did not cause cell fluorescence over 4%, with majority under 1%. This indicates that peptides P3–P18 identified through SLAY do not damage bacterial membranes, suggesting they kill bacteria via alternative mechanism(s) of action.

(A) The membrane damage of E. coli treated by peptides as measured by an increase in fluorescence intensity of PI. E. coli was treated with 25μM peptide. Controls were processed without peptides.

Traditional antimicrobial peptides are considered to act non-specifically through membrane disruption with extremely rapid killing. In addition to the chemical landscape SLAY provides access to, we hypothesized that peptides identified by SLAY might also act through different mechanisms of peptide action.

Cationic-hydrophobic peptide P1 showed universal activity, which is commonly associated with non-specific CAMP activity. Interestingly, P2, which is cationic but non-hydrophobic, showed a larger range of activity. Furthermore, many of our atypical, non-cationic, non-hydrophobic peptides (P3–P18) showed varying ranges in activity across the four gram-negative bacteria tested. For example, P6, P8, P13, and P16 showed antimicrobial action against some strains while having no activity (>128 μM) against others. This suggests many of our peptides may act through a more targeted mechanism.

We tested antimicrobial activity against our host strain used in the screen (E. coli W3110) and three multi-drug-resistant strains: A. baumannii (Ab 5075), P. aeruginosa (PA14), and E. coli conferring New Delhi metallo-beta-lactamase (NDM) resistance. Antimicrobial peptide activity is highly sensitive to medium conditions (). We first performed minimal inhibitory concentration (MIC) assays using Mueller-Hinton medium. Cationic peptides P1 and P2 showed robust activity, like that of our standard CAMP cecropin P1 ( Table S2 ). Peptides P3–P22 did not show activity in this medium (data not shown). We next assayed antimicrobial activity using a simple and defined tris-based medium. Since the bacteria did not grow robustly in this medium, we assayed the MBC of each peptide. In this medium, cationic peptides P1 and P2 had potent antibacterial activity, with MBC values of <2 μM for P1 for all bacteria tested. Peptides P3–P18, except for P3 and P5, had activity against the strain W3110. Both peptides P3 and P5 contained cysteine residues, suggesting possible cyclic formation is needed for activity. P5 contains two cysteine residues within its sequence, while P3 contains four. We had P5 synthesized as a cyclic peptide with a disulfide bond and retested its activity. This cyclic analog of P5 exhibited much higher antimicrobial activity, with MBC changing from >128 to ≤2–8 μM. Similarly, we tested a cyclic configuration of P3 with disulfides C2–C19 and C8–C17, and its antimicrobial activity increased from MBC of 128 μM to ≤2–4 μM. This further reiterates that SLAY can screen and select for cyclic peptides. Peptides P19–P22, as well as the control peptide C1, did not show activity in any medium we tested ( Table 2 and data not shown). Thus, 18 of 22 (∼80%) sequences identified by SLAY as active showed antimicrobial activity in at least one medium, indicating a high true-positive rate. Select peptides were assayed in two additional media ( Table S3 ).

To validate our hits, we selected 22 peptides based on chemical composition, predicted aqueous solubility ( pepcalc.com ), and clustering diversity for chemical synthesis and antimicrobial activity testing. This included two cationic peptides, P1 and P2, that we selected to show SLAY can identify antimicrobial sequences reminiscent of naturally occurring CAMPs. In contrast, the remaining peptides (P3–P18) were selected for opposing characteristics—low hydrophobicity and neutral to negative charge. We chose these sequences to test if SLAY could identify peptide chemistry not typically associated with antimicrobial activity. One control peptide (C1) that had a neutral log2 fold reduction in our screen was used. The peptide sequences that were synthesized and tested for antimicrobial activity are listed in Table 2

Minimal bactericidal concentrations (MBC) were determined as the lowest concentration of peptide that results in at least 99.9% killing of the initial inoculums. Data are representative of three independent experiments.

b Minimal bactericidal concentrations (MBC) were determined as the lowest concentration of peptide that results in at least 99.9% killing of the initial inoculums. Data are representative of three independent experiments.

To further explore the composition of active sequences identified in our screen, we performed a clustering analysis based on amino acid side-chain properties to identify subclasses of peptide sequences that may be present in our hits. To facilitate our analysis, we simplified the amino acid sequence such that all the amino acids were grouped into the broad categories of polar positive, polar negative, polar uncharged, aromatic, nonpolar aliphatic, and cysteine. Supporting the breadth of antimicrobial sequences uncovered, we found large sequence differences between peptides, as measured by Levenshtein edit distances (minimum = 2, median = 13, maximum = 20). Using hierarchical clustering, we sub-divided the peptides into 81 clusters with group sizes ranging from 8–259 peptides and a median of 68 peptides. ( Figure S6 ). We performed multiple sequence alignments on the simplified sequences of each of the 81 clusters to look for potential signature motifs. In general, no strong motif could be identified for any cluster, although some clusters did have a simplified consensus sequence with an apparent hydrophobic domain in addition to variable domains that may facilitate membrane interactions. From the variance in cluster sizes and in the simplified consensus sequences outlined in Data S1 , it is evident that the peptides discovered in this screen are extremely diverse and represent a vast potential for research into unexplored antimicrobial peptides. These results further support that active antimicrobial sequences exist in a much wider range of peptide chemical space than previously recognized that extends far beyond what has evolved in nature.

Natural antimicrobial peptides are dominated by cationic and amphipathic composition. To begin to explore the range of hits identified by SLAY in the context of currently known antimicrobial chemistry, we plotted each active and inactive peptide from our screen by their charge and hydrophobicity. On average, the chemical composition of the library was centered near neutral charge and neutral hydrophobicity ( Figure 4 B). Remarkably, we observed no bias in these parameters between inactive and active sequences from our library, with the bulk of both peptide populations centered near neutral charge and neutral hydrophobicity ( Figure 4 B). Active sequences did not show a propensity toward any specific charge or hydrophobic character. This lack of selection is in sharp contrast to the bulk of naturally occurring antimicrobial peptides in current databases, which are dominated by positive charge and hydrophobic character ( Figure 4 C). Comparing amino acid frequency further highlights these observations ( Figure 4 D). When examining our library, we observed little enrichment of any specific amino acid in active versus inactive sequences. Meanwhile, positively charged lysine was found at a much higher frequency in known antimicrobial peptides compared to active sequences from our screen. Hydrophobic residues including alanine, isoleucine, leucine, and valine were also more frequent in known antimicrobial peptides compared to the active sequences from our screen. These results indicate that antimicrobial peptide sequence and chemical space extends far beyond what is known and has evolved in nature and can be functionally explored through SLAY.

Library samples were collected pre-induction and post-4-hr induction with 0.1 mM IPTG in duplicate. Sequencing read counts are listed in Table S1 . Peptides were taken through two triage stages to identify hits with a high likelihood of true activity. Peptides were first sorted by their log2 reduction values. Peptides with a significant decrease of at least log2 fold −1 were considered to be depleted from the input library and to have potential antimicrobial activity. Next, we removed peptides that had ≤50 reads in each replicate. While somewhat arbitrary, samples with fewer reads will be more affected by machine errors than those with larger read counts, so removing these decreases the overall noise in our analysis. As we anticipated from screening a random library, the vast majority (98.3%) of sequences showed no depletion following induction, indicating they had no antimicrobial activity ( Figure 4 A). However, due to the massive throughput of SLAY, the 1.7% of the peptide library that did show depletion and potential antimicrobial activity represents 7,968 peptides. This single screen nearly doubled the number of unique antimicrobial peptides reported in publicly available databases ().

The error bars represent the SEM, and the asterisks correspond to Bonferroni-adjusted p values (, anddenote p values <0.05, <0.01, and <0.001, respectively) derived from Tukey’s range test performed in conjunction with an ANOVA. See also Figures S5 and S6

(C) A charge versus hydrophobicity plot comparing SLAY active peptides and known active peptides. Known antimicrobial peptides complied from six available online databases are colored in black, and active peptides from our screen are colored in green. Ellipses represent a 95% confidence interval assuming a t distribution.

(B) Screened peptides are plotted according to their hydrophobicity and charge properties. Active peptides are colored in green, and inactive peptides are colored in orange. Ellipses represent a 95% confidence interval assuming a t distribution.

(A) Mean normalized input and output counts of total peptide library. Peptides considered active with lfcMLE ≤−1 are plotted in green. Peptides with lfcMLE >−1 were considered inactive and are plotted in orange. Peptides removed from further analysis contained initial reads in either replicate of less than or equal to 50 and are plotted in yellow.

The breadth of peptide chemical space with antimicrobial and potential therapeutic value is likely much larger than current screening approaches allow us to assess (). To test this hypothesis, we applied SLAY to screen a massive and unbiased peptide library of fully random sequences for antimicrobial activity. We constructed a library of approximately 800,000 peptides in E. coli W3110 using NNB codons to produce random peptide sequences with a target length of 20 amino acids. We sequenced this library and generated a sequence logo based on all peptides in the library ( Figure S5 ). We also generated a sequence logo based on a similarly computationally generated random 20-mer peptide library ( Figure S5 ). The sequence logo generated in both analysis was nearly identical, indicating our ∼800,000-peptide library did indeed contain a random assortment of sequences.

Sequence logo comparison between a randomly generated 20 amino acid library, our library, and the top hits generated from our library. Sequence logos were generated from either the entire set of possible killing peptides (7,968 sequences), 10,000 randomly sampled sequences of the total library, or an amino acid translation of 10,000 randomly generated nucleotide sequences of a repeated “NNB” motif. All logos are plotted in units of probability.

To validate SLAY, a small library of three antimicrobial peptides and two control peptides ( Table 1 ) were transformed into E. coli and then pooled, induced, and harvested at 0 (input), 2, 3, and 4 hr. Following next-generation library construction and sequencing, reads were normalized to the input counts ( Figure 3 ). Log2 fold values, reported in Table 1 , indicate the degree to which the peptides were removed from the population. Control peptides 2xHA and defensin HNP-1 cysteine mutant showed a near-neutral log2 fold change over the time course examined. Meanwhile, the remaining antimicrobial peptides show a log2 fold change of −1 or lower, indicating they were removed from the population over the time course. From these data, we would conclude that protegrin 1, cecropin P1, and defensin HNP-1 have effective antimicrobial activity against our E. coli strain, with protegrin 1 exhibiting the strongest activity. Indeed, minimal bactericidal concentration (MBC) assays using synthesized peptides showed correlative bactericidal activity with log2 fold values, with MBCs of <0.125 μM, 1 μM, and 8 μM measured for protegrin 1, cecropin P1, and defensin HNP-1, respectively ( Table 1 ).

A defined set of 5 peptides were cloned and pooled into a small library. The library was tested as described in Figure 2 and STAR Methods over a period of 4 hr with plasmids isolation at 0-, 2-, 3-, and 4-hr time points in duplicate. Reads were normalized to the input counts and plotted as a function of time.

Our screening workflow for SLAY is shown in Figure 2 . Peptides are cloned into our surface display system and transformed into a gram-negative strain of interest. Peptide surface expression is then induced by IPTG. Bacteria expressing bactericidal or bacteriostatic peptides will decrease in abundance during the induction period. One PCR generates Illumina next-generation sequencing samples for sequencing from plasmid libraries pre- and post-induction. In silico translation and comparison identifies each peptide in the library and its abundance pre- and post-induction to identify potential antimicrobial hits.

Batch screening of peptides using our surface display system can be achieved by first constructing a random library using random PCR primers that flank the peptide region (i), followed by collection of transformants, plasmid isolation, and subsequent transformation into a bacterial strain of interest. Next, the library is grown in culture and induced (ii). Peptides with antimicrobial activity (red) will drop out of the population (iii). Next-generation sequencing of the initial input at time zero and output (iv) at a pre-defined number of hours provides a read out of sequencing counts (v). From this information, top hits can be identified and tested. Further libraries can be constructed based on the identified top hits and the process can be repeated.

While the full-length tether (2×) is required for the spatial freedom of a peptide to interact with its host bacterium, it is short enough to prevent an antimicrobial peptide from exerting an effect on neighbor cells in culture. We co-cultured W3110 surface-expressing cecropin P1, which shows potent CAMP activity, with W3110 containing only the empty plasmid pMMB67EH. When co-cultured in a 1:1 ratio and induced, cecropin P1 only affects the viability of cells expressing it ( Figure 1 G). Thus, multiple peptides can be assayed for activity in a single tube.

To ensure the application of our system in a wide range of gram-negative bacteria, we engineered expression and replication of ubiquitous OmpA surface localization on a broad RSF1010 origin-based plasmid. Without any change to our system, we demonstrated that it was transferable and functional in a broad range of gram-negative bacteria, including ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Psuedomonas aeruginosa, and Enterobacter species) pathogens, like Acinetobacter baumannii and Pseudomonas aeruginosa ( Figure 1 F).

In addition to cecropin P1, antimicrobial peptides dermaseptin, protegrin 1, and defensin HNP-1 showed strong antimicrobial activity against W3110 in our system ( Figures 1 E and S4 ). Defensin HNP-1 and protegrin 1 were particularly interesting because they require disulfide bonds for activity. We reconstructed defensin HNP-1 without disulfides and demonstrated that its activity was dramatically reduced, in agreement with biochemical studies (). This indicates that our system supports the formation of cyclic, disulfide-bond-dependent antimicrobial peptides.

Dermaseptin S4L7K is displayed on the surface. IPTG concentrations tested were 0mM, 0.01mM, 0.1mM and 1mM. Growth curves were performed in triplicate over 6 hours. Data are represented as mean ± SEM.

The action of peptides displayed by our platform is also sensitive to relevant environmental conditions. CAMP activity is decreased by the addition of magnesium ions that fortify bacterial cell surfaces and are also sensitive to trypsin degradation due the large numbers of arginine and lysine residues they contain. Addition of up to 2 mM magnesium to the growth medium greatly reduced the antimicrobial action of surface-displayed cecropin P1, and addition of trypsin to the culture medium greatly lessened cecropin P1-induced growth effects ( Figure S3 ).

Cecropin P1 is displayed with increasing concentrations of magnesium and trypsin. Controls were cecropin P1 expressed with no added magnesium or trypsin enzyme. Growth curves were performed in triplicate over 6 hours. Data are represented as mean ± SEM.

To further demonstrate bacterium-relevant physiological interactions recapitulated through our approach, we introduced the 2× tether cecropin P1 construct in E. coli strain WD101 (). WD101 is a derivate of strain W3110 and carries a mutation that decreases its overall surface charge through the addition of amine-containing residues to lipopolysaccharide (LPS) that makes it resistant to CAMPs, like cecropin P1. Consistent with the ability of our engineered system to recapitulate natural interactions, WD101 was more resistant to antimicrobial activity of surface-expressed cecropin P1 compared to the parent CAMP sensitive strain W3110 ( Figure 1 D). Furthermore, deletion of the eptA gene, which is required for the LPS modification conferring CAMP resistance, sensitized WD101 to surface-displayed cecropin P1 ().

The length of the flexible tether strongly influenced cecropin-P1-dependent growth effects. In addition to the full-length tether (2×), we also cloned cecropin P1 with a half-length tether (1×) and no tether (0×). Induction of each construct at 0.1 mM IPTG showed that cecropin P1 displayed with the full 2× tether length had the strongest activity ( Figure S2 ).

Cecropin P1 is displayed with no tether, 1x tether and a 2x at 0 mM and 0.1 mM IPTG. Growth curves were performed in triplicate over 6 hours. Data are represented as mean ± SEM.

Cecropin P1 is a well-studied CAMP that acts by binding and disrupting the structure of the bacterial outer membrane (). As a test case, cecropin P1 was cloned as the C-terminal peptide and the construct was expressed in wild-type E. coli K-12 strain W3110. A tandem influenza hemagglutinin peptide (2xHA) was cloned as a C-terminal peptide control. We induced expression with increasing concentrations of IPTG and monitored optical density as an initial measure of cell growth and viability. The cultures expressing the control 2xHA peptide grew similarly at all isopropyl-beta-D-thiogalactopyranoside (IPTG) concentrations ( Figure 1 B). The cultures expressing cecropin P1 showed an induction-dependent decrease in optical density ( Figure 1 B). We measured colony-forming units (CFUs) for cecropin P1 cultures and found a correlative decrease in viable cells following induction ( Figure 1 C). Cytosolic expression of cecropin P1 alone did not affect W3110 growth or viability ( Figure S1 ).

Cecropin P1 is expressed intracellularly with the 2x tether (without lpp-ompA for localization to the cell surface) at 0 mM, 0.01 mM, 0.1 mM and 1 mM IPTG. Growth curves were performed in triplicate over 6 hours. Data are represented as mean ± SEM.

During infection treatment, drugs first interact with a bacterium at its cell surface and then migrate to their target. To recapitulate this scenario during screening, SLAY localizes peptides on the gram-negative bacterial cell surface as part of a fusion protein consisting of (1) a murein lipoprotein (lpp) signal sequence that directs proteins for export from the cytoplasm and is subsequently cleaved, (2) five transmembrane domains (residues 46–159) of the OmpA membrane protein for outer membrane localization (), (3) a flexible tether that allows spatial freedom (), and (4) a C-terminal peptide. We engineered the tether to extend up to 180 Å from its fusion to OmpA, enabling the C-terminal peptide flexibility to interact with the growth environment, the outer membrane, and periplasmic components. With the fluid nature of periplasmic space ranging anywhere from 106–253 Å, peptides have the potential to penetrate as far as the cytoplasmic membrane () ( Figure 1 A).

(G) Neighboring cells are unaffected by surface expression of antimicrobial peptides. White and blue cells with empty plasmid and cecropin P1, respectively, are displayed. Input cultures (left) were collected, serial diluted, and spotted before induction of 1 mM IPTG. Cells were induced at a total starting OD 600 nm of 0.01. After 3 hr of surface expression, cells were collected, serial diluted, and spotted (right). All growth curves were performed in triplicate.

(F) The surface display system functions across many gram-negative species, such as Acinetobacter baumannii and Pseudomonas aeruginosa. Each strain is displaying protegrin 1 at 0 mM, 0.1 mM, and 1 mM IPTG. Plotted are recorded as optical density over 6 hr.

(A) Diagram of surface display system. Antimicrobial peptide surface display system composed of (1) Lpp signal sequence, (2) OmpA (46–159) transmembrane protein, (3) flexible tether, (4) C-terminal peptide. The Lpp signal sequence is shown for clarity but is removed prior to insertion into the outer membrane.

Discussion

SLAY presents a unique approach that challenges current drug discovery paradigms by replacing robotics, synthetic chemistry, and individual well reactions with molecular and computational techniques in a simple cell-based system for immediate biological relevance. Our screen of ∼800,000 unique sequences revealed the untapped potential of peptide chemical space with antimicrobial activity. As anticipated from a random peptide screen, the vast majority of sequences screened (98.3%) showed no activity. However, with the efficient throughput of SLAY, the 1.7% of active sequences still represents several thousand potential unique hits. Synthesis and testing of selected hits indicates a high true-positive rate for SLAY with ∼80% of sequences tested having antimicrobial activity in synthetic form. Furthermore, since SLAY mounts peptides directly at the bacterial cell surface, it effectively increases their local concentration near potential targets. This may facilitate discovery of peptides with initially weak target interactions or poor medium solubility that can then be developed into more potent analogs.

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et al. A new antibiotic kills pathogens without detectable resistance. We showed that SLAY can identify peptides similar to naturally occurring CAMPs and that these peptides have the expected pore-forming activity and mammalian toxicity. Importantly, we show that SLAY can identify peptide chemistry not typically associated with antimicrobial activity. For this purpose, we tested diverse sequences with hydrophilic character and neutral-to-negative charge and showed they could still kill several types of bacteria. The lack of detectable membrane activity among these peptides suggests that they act through different mechanisms of action yet to be explored. The cell envelope of gram-negative bacteria has many potential targets, including essential protein complexes, like the Bam, Lpt, and Lol systems (). Alternatively, peptides discovered through SLAY may target and sequester essential metabolites, as was suggested for the mechanism of action of teixobactin (). Natural antimicrobial peptides evolved in the context of a complex immune system and were likely selected for more than their antimicrobial activity. Indeed, many naturally occurring CAMPs have been shown to have immune modulatory activity. Thus, while nature has provided predominantly one scaffold and target for antimicrobial peptide chemistry, our results with SLAY highlight the diversity of untapped antimicrobial peptide chemical space that can be explored for therapeutic value.

The power of SLAY lies in the high-throughput molecular foundation of the platform and opens the door for countless iterations. Our pipeline allows for progression from library construction through sequencing-based identification of antimicrobial leads that can then be validated synthetically and tested for in vivo effects. With this framework, peptide libraries of any size and composition can be easily screened in a broad range of gram-negative bacteria, facilitating a wide range of uses. Analysis of our screen indicated no strong compositional bias between active and inactive peptide sequences. Thus, any area of antimicrobial peptide space can be explored by biasing the sequence composition of the initial library. In addition to composition, we demonstrated that SLAY can be used to explore structure with easy identification of cyclic peptides, which have many positive pharmacokinetic properties. Once a lead sequence is identified, SLAY can be used to explore its sequence-function relationship by generating and testing a library of sequence derivatives. Furthermore, screens can be performed under any condition, such as in serum or in the presence of proteases, to study the effects of these environmental changes on sequence activity. The unprecedented sequence-activity relationship data of functional and non-functional antimicrobial sequences gained through these screens will facilitate rational development of therapeutic peptides and the ability to broadly understand peptide chemical space with effects on bacterial physiology.

As with all screening procedures, SLAY can generate false-positive hits. False positives could arise from peptide-fusion proteins that are toxic to the cell because they cause deleterious protein aggregates, stall translation, block essential secretion systems, or inhibit other essential functions during secretion to the cell surface. Some peptides may utilize the tether in their activity on the cell surface and would arise as false positives when synthesized and tested without the tether. Peptides identified by SLAY may not be soluble in synthetic form, limiting their potential use. Thus, it is important to validate hits as synthetic peptides.

Bacteria have gained resistance to every antibiotic clinically used. There is no doubt they would gain resistance to any antimicrobial peptide discovered. However, the facile implementation of SLAY allows for continual iteration of peptide screens to identify leads as resistance arises. Thus, SLAY allows us to continuously spin the wheel and identify additional sets of antimicrobial peptides to thwart the inevitable rise of resistance. Conventional antibiotics that drive the problem of resistance are broad spectrum. While powerful, these drugs cannot distinguish between a target pathogen and a harmless commensal, and this collateral damage can further spur the development of antibiotic resistance. By screening the same peptide library in multiple gram-negative bacteria, SLAY could allow for the identification of targeted peptides to eliminate only invading pathogens and reduce off-target consequences. SLAY allows us to enter previously unexplored chemical space for the first time and will facilitate the discovery of antibiotic scaffolds poised for further development.