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Antimicrobial peptides (AMPs) preferentially permeate prokaryotic membranes via electrostatic binding and membrane remodeling. Such action is drastically suppressed by high salt due to increased electrostatic screening, thus it is puzzling how marine AMPs can possibly work. We examine as a model system, piscidin-1, a histidine-rich marine AMP, and show that ion-histidine interactions play unanticipated roles in membrane remodeling at high salt: Histidines can simultaneously hydrogen-bond to a phosphate and coordinate with an alkali metal ion to neutralize phosphate charge, thereby facilitating multidentate bonds to lipid headgroups in order to generate saddle-splay curvature, a prerequisite to pore formation. A comparison among Na + , K + , and Cs + indicates that histidine-mediated salt tolerance is ion specific. We conclude that histidine plays a unique role in enabling protein/peptide-membrane interactions that occur in marine or other high-salt environment., (© 2022 Wiley-VCH GmbH.)

It is unclear how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to the strong but ineffective inflammatory response that characterizes severe Coronavirus disease 2019 (COVID-19), with amplified immune activation in diverse cell types, including cells without angiotensin-converting enzyme 2 receptors necessary for infection. Proteolytic degradation of SARS-CoV-2 virions is a milestone in host viral clearance, but the impact of remnant viral peptide fragments from high viral loads is not known. Here, we examine the inflammatory capacity of fragmented viral components from the perspective of supramolecular self-organization in the infected host environment. Interestingly, a machine learning analysis to SARS-CoV-2 proteome reveals sequence motifs that mimic host antimicrobial peptides (xenoAMPs), especially highly cationic human cathelicidin LL-37 capable of augmenting inflammation. Such xenoAMPs are strongly enriched in SARS-CoV-2 relative to low-pathogenicity coronaviruses. Moreover, xenoAMPs from SARS-CoV-2 but not low-pathogenicity homologs assemble double-stranded RNA (dsRNA) into nanocrystalline complexes with lattice constants commensurate with the steric size of Toll-like receptor (TLR)-3 and therefore capable of multivalent binding. Such complexes amplify cytokine secretion in diverse uninfected cell types in culture (epithelial cells, endothelial cells, keratinocytes, monocytes, and macrophages), similar to cathelicidins role in rheumatoid arthritis and lupus. The induced transcriptome matches well with the global gene expression pattern in COVID-19, despite using

Antimicrobial peptides (AMPs) preferentially permeate prokaryotic membranes via electrostatic binding and membrane remodeling. Such action is drastically suppressed by high salt due to increased electrostatic screening, thus it is puzzling how marine AMPs can possibly work. We examine as a model system, piscidin-1, a histidine-rich marine AMP, and show that ion-histidine interactions play unanticipated roles in membrane remodeling at high salt: Histidines can simultaneously hydrogen-bond to a phosphate and coordinate with an alkali metal ion to neutralize phosphate charge, thereby facilitating multidentate bonds to lipid headgroups in order to generate saddle-splay curvature, a prerequisite to pore formation. A comparison among Na+ , K+ , and Cs+ indicates that histidine-mediated salt tolerance is ion specific. We conclude that histidine plays a unique role in enabling protein/peptide-membrane interactions that occur in marine or other high-salt environment.

Cathelicidins such as the human 37-amino acid peptide (LL-37) are peptides that not only potently kill microbes but also trigger inflammation by enabling immune recognition of endogenous nucleic acids. Here, a detailed structure-function analysis of LL-37 was performed to understand the details of this process. Alanine scanning of 34-amino acid peptide (LL-34) showed that some variants displayed increased antimicrobial activity against Staphylococcus aureus and group A Streptococcus. In contrast, different substitutions clustered on the hydrophobic face of the LL-34 alpha helix inhibited the ability of those variants to promote type 1 interferon expression in response to U1 RNA or to present U1 to the scavenger receptor (SR) B1 on the keratinocyte cell surface. Small-angle X-ray scattering experiments of the LL-34 variants LL-34, F5A, I24A, and L31A demonstrated that these peptides form cognate supramolecular structures with U1 characterized by inter-dsRNA spacings of approximately 3.5 nm, a range that has been previously shown to activate toll-like receptor 3 by the parent peptide LL-37. Therefore, while alanine substitutions on the hydrophobic face of LL-34 led to loss of binding to SRs and the complete loss of autoinflammatory responses in epithelial and endothelial cells, they did not inhibit the ability to organize with U1 RNA in solution to associate with toll-like receptor 3. These observations advance our understanding of how cathelicidin mediates the process of innate immune self-recognition to enable inert nucleic acids to trigger inflammation. We introduce the term "innate immune vetting" to describe the capacity of peptides such as LL-37 to enable certain nucleic acids to become an inflammatory stimulus through SR binding prior to cell internalization.

Defense of the central nervous system (CNS) against infection must be accomplished without generation of potentially injurious immune cell-mediated or off-target inflammation which could impair key functions. As the CNS is an immune-privileged compartment, inducible innate defense mechanisms endogenous to the CNS likely play an essential role in this regard. Pituitary adenylate cyclase-activating polypeptide (PACAP) is a neuropeptide known to regulate neurodevelopment, emotion, and certain stress responses. While PACAP is known to interact with the immune system, its significance in direct defense of brain or other tissues is not established. Here, we show that our machine-learning classifier can screen for immune activity in neuropeptides, and correctly identified PACAP as an antimicrobial neuropeptide in agreement with previous experimental work. Furthermore, synchrotron X-ray scattering, antimicrobial assays, and mechanistic fingerprinting provided precise insights into how PACAP exerts antimicrobial activities vs. pathogens via multiple and synergistic mechanisms, including dysregulation of membrane integrity and energetics and activation of cell death pathways. Importantly, resident PACAP is selectively induced up to 50-fold in the brain in mouse models of Staphylococcus aureus or Candida albicans infection in vivo, without inducing immune cell infiltration. We show differential PACAP induction even in various tissues outside the CNS, and how these observed patterns of induction are consistent with the antimicrobial efficacy of PACAP measured in conditions simulating specific physiologic contexts of those tissues. Phylogenetic analysis of PACAP revealed close conservation of predicted antimicrobial properties spanning primitive invertebrates to modern mammals. Together, these findings substantiate our hypothesis that PACAP is an ancient neuro-endocrine-immune effector that defends the CNS against infection while minimizing potentially injurious neuroinflammation.

All antibiotics have to engage bacterial amphiphilic barriers such as the lipopolysaccharide-rich outer membrane or the phospholipid-based inner membrane in some manner, either by disrupting them outright and/or permeating them and thereby allow the antibiotic to get into bacteria. There is a growing class of cyclic antibiotics, many of which are of bacterial origin, that exhibit activity against Gram-negative bacteria, which constitute an urgent problem in human health. We examine a diverse collection of these cyclic antibiotics, both natural and synthetic, which include bactenecin, polymyxin B, octapeptin, capreomycin, and Kirshenbaum peptoids, in order to identify what they have in common when they interact with bacterial lipid membranes. We find that they virtually all have the ability to induce negative Gaussian curvature (NGC) in bacterial membranes, the type of curvature geometrically required for permeation mechanisms such as pore formation, blebbing, and budding. This is interesting since permeation of membranes is a function usually ascribed to antimicrobial peptides (AMPs) from innate immunity. As prototypical test cases of cyclic antibiotics, we analyzed amino acid sequences of bactenecin, polymyxin B, and capreomycin using our recently developed machine-learning classifier trained on α-helical AMP sequences. Although the original classifier was not trained on cyclic antibiotics, a modified classifier approach correctly predicted that bactenecin and polymyxin B have the ability to induce NGC in membranes, while capreomycin does not. Moreover, the classifier was able to recapitulate empirical structure-activity relationships from alanine scans in polymyxin B surprisingly well. These results suggest that there exists some common ground in the sequence design of hybrid cyclic antibiotics and linear AMPs.

Antimicrobial peptides (AMPs) are typically thought of as molecular hole punchers that directly kill pathogens by membrane permeation. However, recent work has shown that AMPs are pleiotropic, multifunctional molecules that can strongly modulate immune responses. In this review, we provide a historical overview of the immunomodulatory properties of natural and synthetic antimicrobial peptides, with a special focus on human cathelicidin and defensins. We also summarize the various mechanisms of AMP immune modulation and outline key structural rules underlying the recently-discovered phenomenon of AMP-mediated Toll-like receptor (TLR) signaling. In particular, we describe several complementary studies demonstrating how AMPs self-assemble with nucleic acids to form nanocrystalline complexes that amplify TLR-mediated inflammation. In a broader scope, we discuss how this new conceptual framework allows for the prediction of immunomodulatory behavior in AMPs, how the discovery of hidden antimicrobial activity in known immune signaling proteins can inform these predictions, and how these findings reshape our understanding of AMPs in normal host defense and autoimmune disease.

Antimicrobial peptides are a class of membrane-active peptides that form a critical component of innate host immunity and possess a diversity of sequence and structure. Machine learning approaches have been profitably employed to efficiently screen sequence space and guide experiment towards promising candidates with high putative activity. In this mini-review, we provide an introduction to antimicrobial peptides and summarize recent advances in machine learning-enabled antimicrobial peptide discovery and design with a focus on a recent work Lee et al. Proc. Natl. Acad. Sci. USA 2016;113(48):13588-13593. This study reports the development of a support vector machine classifier to aid in the design of membrane active peptides. We use this model to discover membrane activity as a multiplexed function in diverse peptide families and provide interpretable understanding of the physicochemical properties and mechanisms governing membrane activity. Experimental validation of the classifier reveals it to have learned membrane activity as a unifying signature of antimicrobial peptides with diverse modes of action. Some of the discriminating rules by which it performs classification are in line with existing "human learned" understanding, but it also unveils new previously unknown determinants and multidimensional couplings governing membrane activity. Integrating machine learning with targeted experimentation can guide both antimicrobial peptide discovery and design and new understanding of the properties and mechanisms underpinning their modes of action.

Double-stranded RNA (dsRNA) induces production of pro-inflammatory cytokines in normal human epidermal keratinocytes (NHEK) by specific binding to endosomal Toll-like receptor-3 (TLR3). Recently, it has been shown that hyperactivation of TLR3 in psoriatic keratinocytes by dsRNA can occur in the presence of human antimicrobial peptide (AMP) LL37. Here, we combine synchrotron X-ray scattering, microscopy, computer simulations, and measurements of NHEK cytokine production to elucidate a previously unanticipated form of specific molecular pattern recognition. LL37 and similar α-helical AMPs can form pro-inflammatory nanocrystalline complexes with dsRNA that are recognized by TLR3 differently than dsRNA alone. dsRNA complexes that activate IL-6 production in NHEK and those that do not are both able to enter cells and co-localize with TLR3. However, the crystallinity of these AMP-dsRNA complexes, specifically the geometric spacing between parallel dsRNA and the repeat number of ordered dsRNA, strongly influences the level of TLR3 activation. Crystalline complexes that present dsRNA at a spacing that matches with the steric size of TLR3 can recruit and engage multiple TLR3 receptors, driving receptor clustering and immune amplification, whereas crystalline complexes that exhibit poor steric matching do not. Reverse-transcription quantitative PCR of IL-6 during siRNA knockdown of TLR3 confirms that cytokine production is due to TLR3: High levels of IL-6 transcription are observed for sterically matched complexes without TLR3 knockdown, whereas such activity is abrogated with TLR3 knockdown.

There are some ∼1,100 known antimicrobial peptides (AMPs), which permeabilize microbial membranes but have diverse sequences. Here, we develop a support vector machine (SVM)-based classifier to investigate ⍺-helical AMPs and the interrelated nature of their functional commonality and sequence homology. SVM is used to search the undiscovered peptide sequence space and identify Pareto-optimal candidates that simultaneously maximize the distance σ from the SVM hyperplane (thus maximize its "antimicrobialness") and its ⍺-helicity, but minimize mutational distance to known AMPs. By calibrating SVM machine learning results with killing assays and small-angle X-ray scattering (SAXS), we find that the SVM metric σ correlates not with a peptide's minimum inhibitory concentration (MIC), but rather its ability to generate negative Gaussian membrane curvature. This surprising result provides a topological basis for membrane activity common to AMPs. Moreover, we highlight an important distinction between the maximal recognizability of a sequence to a trained AMP classifier (its ability to generate membrane curvature) and its maximal antimicrobial efficacy. As mutational distances are increased from known AMPs, we find AMP-like sequences that are increasingly difficult for nature to discover via simple mutation. Using the sequence map as a discovery tool, we find a unexpectedly diverse taxonomy of sequences that are just as membrane-active as known AMPs, but with a broad range of primary functions distinct from AMP functions, including endogenous neuropeptides, viral fusion proteins, topogenic peptides, and amyloids. The SVM classifier is useful as a general detector of membrane activity in peptide sequences.

Novel synthetic mimics of antimicrobial peptides have been developed to exhibit structural properties and antimicrobial activity similar to those of natural antimicrobial peptides (AMPs) of the innate immune system. These molecules have a number of potential advantages over conventional antibiotics, including reduced bacterial resistance, cost-effective preparation, and customizable designs. In this study, we investigate a family of nylon-3 polymer-based antimicrobials. By combining vesicle dye leakage, bacterial permeation, and bactericidal assays with small-angle X-ray scattering (SAXS), we find that these polymers are capable of two interdependent mechanisms of action: permeation of bacterial membranes and binding to intracellular targets such as DNA, with the latter necessarily dependent on the former. We systemically examine polymer-induced membrane deformation modes across a range of lipid compositions that mimic both bacteria and mammalian cell membranes. The results show that the polymers' ability to generate negative Gaussian curvature (NGC), a topological requirement for membrane permeation and cellular entry, in model Escherichia coli membranes correlates with their ability to permeate membranes without complete membrane disruption and kill E. coli cells. Our findings suggest that these polymers operate with a concentration-dependent mechanism of action: at low concentrations permeation and DNA binding occur without membrane disruption, while at high concentrations complete disruption of the membrane occurs. This article is part of a Special Issue entitled: Interfacially Active Peptides and Proteins. Guest Editors: William C. Wimley and Kalina Hristova.

Pathological self-assembly is a concept that is classically associated with amyloids, such as amyloid-β (Aβ) in Alzheimer's disease and α-synuclein in Parkinson's disease. In prokaryotic organisms, amyloids are assembled extracellularly in a similar fashion to human amyloids. Pathogenicity of amyloids is attributed to their ability to transform into several distinct structural states that reflect their downstream biological consequences. While the oligomeric forms of amyloids are thought to be responsible for their cytotoxicity via membrane permeation, their fibrillar conformations are known to interact with the innate immune system to induce inflammation. Furthermore, both eukaryotic and prokaryotic amyloids can self-assemble into molecular chaperones to bind nucleic acids, enabling amplification of Toll-like receptor (TLR) signaling. Recent work has shown that antimicrobial peptides (AMPs) follow a strikingly similar paradigm. Previously, AMPs were thought of as peptides with the primary function of permeating microbial membranes. Consistent with this, many AMPs are facially amphiphilic and can facilitate membrane remodeling processes such as pore formation and fusion. We show that various AMPs and chemokines can also chaperone and organize immune ligands into amyloid-like ordered supramolecular structures that are geometrically optimized for binding to TLRs, thereby amplifying immune signaling. The ability of amphiphilic AMPs to self-assemble cooperatively into superhelical protofibrils that form structural scaffolds for the ordered presentation of immune ligands like DNA and dsRNA is central to inflammation. It is interesting to explore the notion that the assembly of AMP protofibrils may be analogous to that of amyloid aggregates. Coming full circle, recent work has suggested that Aβ and other amyloids also have AMP-like antimicrobial functions. The emerging perspective is one in which assembly affords a more finely calibrated system of recognition and response: the detection of single immune ligands, immune ligands bound to AMPs, and immune ligands spatially organized to varying degrees by AMPs, result in different immunologic outcomes. In this framework, not all ordered structures generated during multi-stepped AMP (or amyloid) assembly are pathological in origin. Supramolecular structures formed during this process serve as signatures to the innate immune system to orchestrate immune amplification in a proportional, situation-dependent manner. [ABSTRACT FROM AUTHOR]

Double-stranded DNA (dsDNA) can trigger the production of type I interferon (IFN) in plasmacytoid dendritic cells (pDCs) by binding to endosomal Toll-like receptor-9 (TLR9; refs , , , , ). It is also known that the formation of DNA-antimicrobial peptide complexes can lead to autoimmune diseases via amplification of pDC activation. Here, by combining X-ray scattering, computer simulations, microscopy and measurements of pDC IFN production, we demonstrate that a broad range of antimicrobial peptides and other cationic molecules cause similar effects, and elucidate the criteria for amplification. TLR9 activation depends on both the inter-DNA spacing and the multiplicity of parallel DNA ligands in the self-assembled liquid-crystalline complex. Complexes with a grill-like arrangement of DNA at the optimum spacing can interlock with multiple TLR9 like a zipper, leading to multivalent electrostatic interactions that drastically amplify binding and thereby the immune response. Our results suggest that TLR9 activation and thus TLR9-mediated immune responses can be modulated deterministically. [ABSTRACT FROM AUTHOR]

Highlights: [•] AMPs are multifunctional molecules that selectively permeate microbial membranes. [•] Negative Gaussian curvature (NGC) enables many types of membrane permeation. [•] NGC generation by AMPs constrains their compositions in the form of a general rule. [•] We show that the sequences of known cationic AMPs are consistent with this rule. [ABSTRACT FROM AUTHOR]

Abstract Antimicrobial peptides (AMPs) are typically thought of as molecular hole punchers that directly kill pathogens by membrane permeation. However, recent work has shown that AMPs are pleiotropic, multifunctional molecules that can strongly modulate immune responses. In this review, we provide a historical overview of the immunomodulatory properties of natural and synthetic antimicrobial peptides, with a special focus on human cathelicidin and defensins. We also summarize the various mechanisms of AMP immune modulation and outline key structural rules underlying the recently-discovered phenomenon of AMP-mediated Toll-like receptor (TLR) signaling. In particular, we describe several complementary studies demonstrating how AMPs self-assemble with nucleic acids to form nanocrystalline complexes that amplify TLR-mediated inflammation. In a broader scope, we discuss how this new conceptual framework allows for the prediction of immunomodulatory behavior in AMPs, how the discovery of hidden antimicrobial activity in known immune signaling proteins can inform these predictions, and how these findings reshape our understanding of AMPs in normal host defense and autoimmune disease. [ABSTRACT FROM AUTHOR]

Abstract Antimicrobial peptides (AMPs) collectively constitute a key component of the host innate immune system. They span a diverse space of sequences and can be α-helical, β-sheet, or unfolded in structure. Despite a wealth of knowledge about them from decades of experiments, it remains difficult to articulate general principles governing such peptides. How are they different from other molecules that are also cationic and amphiphilic? What other functions, in immunity and otherwise, are enabled by these simple sequences? In this short review, we present some recent work that engages these questions using methods not usually applied to AMP studies, such as machine learning. We find that not only do AMP-like sequences confer membrane remodeling activity to an unexpectedly broad range of protein classes, their cationic and amphiphilic signature also allows them to act as meta-antigens and self-assemble with immune ligands into nanocrystalline complexes for multivalent presentation to Toll-like receptors. Graphical abstract Image 1 [ABSTRACT FROM AUTHOR]

Polymeric synthetic mimics of antimicrobialpeptides (SMAMPs) haverecently demonstrated similar antimicrobial activity as natural antimicrobialpeptides (AMPs) from innate immunity. This is surprising, since polymericSMAMPs are heterogeneous in terms of chemical structure (random sequence)and conformation (random coil), in contrast to defined amino acidsequence and intrinsic secondary structure. To understand this better,we compare AMPs with a “minimal” mimic, a well-characterizedfamily of polydisperse cationic methacrylate-based random copolymerSMAMPs. Specifically, we focus on a comparison between the quantifiablemembrane curvature generating capacity, charge density, and hydrophobicityof the polymeric SMAMPs and AMPs. Synchrotron small-angle X-ray scattering(SAXS) results indicate that typical AMPs and these methacrylate SMAMPsgenerate similar amounts of membrane negative Gaussian curvature (NGC),which is topologically necessary for a variety of membrane-destabilizingprocesses. Moreover, the curvature generating ability of SMAMPs ismore tolerant of changes in the lipid composition than that of naturalAMPs with similar chemical groups, consistent with the lower specificityof SMAMPs. We find that, although the amount of NGC generated by theseSMAMPs and AMPs are similar, the SMAMPs require significantly higherlevels of hydrophobicity and cationic charge to achieve the same levelof membrane deformation. We propose an explanation for these differences,which has implications for new synthetic strategies aimed at improvedmimesis of AMPs. [ABSTRACT FROM AUTHOR]

Defensins comprise a potent class of membrane disruptive antimicrobial peptides (AMPs) with well-characterized broad spectrum and selective microbicidal effects. By using high-resolution synchrotron small-angle X-ray scattering to investigate interactions between heterogeneous membranes and members of the defensin subfamilies, α-defensins (Crp-4),β-defensins (HBD- 2, HBD-3), and θ-defensins (RTD-1, BTD-7), we show how these peptides all permeabilize model bacterial membranes but not model eukaryotic membranes: defensins selectively generate saddle- splay ("negative Gaussian") membrane curvature in model membranes rich in negative curvature lipids such as those with pbosphoethanolamine (PE) headgroups. These results are shown to be consistent with vesicle leakage assays. A mechanism of action based on saddle-splay membrane curvature generation is broadly enabling, because it is a necessary condition for processes such as pore formation, blebbing, budding, and vesicularization, all of which destabilize the barrier function of cell membranes. Importantly, saddle-splay membrane curvature generation places constraints on tbe amino acid composition of membrane disruptive peptides. For example, we show that the requirement for generating saddle-splay curvature implies that a decrease in arginine content in an AMP can be offset by an increase in both lysine and hydrophobic content. This "design rule" is consistent with the amino acid compositions of 1080 known cationic AMPs. [ABSTRACT FROM AUTHOR]

All antibiotics have to engage bacterial amphiphilic barriers such as the lipopolysaccharide-rich outer membrane or the phospholipid-based inner membrane in some manner, either by disrupting them outright and/or permeating them and thereby allow the antibiotic to get into bacteria. There is a growing class of cyclic antibiotics, many of which are of bacterial origin, that exhibit activity against Gram-negative bacteria, which constitute an urgent problem in human health. We examine a diverse collection of these cyclic antibiotics, both natural and synthetic, which include bactenecin, polymyxin B, octapeptin, capreomycin, and Kirshenbaum peptoids, in order to identify what they have in common when they interact with bacterial lipid membranes. We find that they virtually all have the ability to induce negative Gaussian curvature (NGC) in bacterial membranes, the type of curvature geometrically required for permeation mechanisms such as pore formation, blebbing, and budding. This is interesting since permeation of membranes is a function usually ascribed to antimicrobial peptides (AMPs) from innate immunity. As prototypical test cases of cyclic antibiotics, we analyzed amino acid sequences of bactenecin, polymyxin B, and capreomycin using our recently developed machine-learning classifier trained on α-helical AMP sequences. Although the original classifier was not trained on cyclic antibiotics, a modified classifier approach correctly predicted that bactenecin and polymyxin B have the ability to induce NGC in membranes, while capreomycin does not. Moreover, the classifier was able to recapitulate empirical structure–activity relationships from alanine scans in polymyxin B surprisingly well. These results suggest that there exists some common ground in the sequence design of hybrid cyclic antibiotics and linear AMPs. Unlabelled Image • Many cyclic antibiotics (CAs) exhibit potent activity against Gram-negative bacteria. • CAs interact with membranes in a manner cognate to antimicrobial peptides (AMPs). • Both groups induce negative Gaussian curvature (NGC) to permeate bacterial membranes. • CAs induce magnitudes of NGC typical for AMPs rather than cell-penetrating peptides. • Machine-learning classifier trained on AMPs predicts activity for polymyxin variants. [ABSTRACT FROM AUTHOR]