Mining human microbiomes reveals an untapped source of peptide antibiotics.

Drug-resistant bacteria are outpacing traditional antibiotic discovery efforts. Here, we computationally screened 444,054 previously reported putative small protein families from 1,773 human metagenomes for antimicrobial properties, identifying 323 candidates encoded in small open reading frames (smORFs). To test our computational predictions, 78 peptides were synthesized and screened for antimicrobial activity in vitro, with 70.5% displaying antimicrobial activity. As these compounds were different compared with previously reported antimicrobial peptides, we termed them smORF-encoded peptides (SEPs). SEPs killed bacteria by targeting their membrane, synergizing with each other, and modulating gut commensals, indicating a potential role in reconfiguring microbiome communities in addition to counteracting pathogens. The lead candidates were anti-infective in both murine skin abscess and deep thigh infection models. Notably, prevotellin-2 from Prevotella copri presented activity comparable to the commonly used antibiotic polymyxin B. Our report supports the existence of hundreds of antimicrobials in the human microbiome amenable to clinical translation.

Discovery of antimicrobial peptides in the global microbiome with machine learning.

Novel antibiotics are urgently needed to combat the antibiotic-resistance crisis. We present a machine-learning-based approach to predict antimicrobial peptides (AMPs) within the global microbiome and leverage a vast dataset of 63,410 metagenomes and 87,920 prokaryotic genomes from environmental and host-associated habitats to create the AMPSphere, a comprehensive catalog comprising 863,498 non-redundant peptides, few of which match existing databases. AMPSphere provides insights into the evolutionary origins of peptides, including by duplication or gene truncation of longer sequences, and we observed that AMP production varies by habitat. To validate our predictions, we synthesized and tested 100 AMPs against clinically relevant drug-resistant pathogens and human gut commensals both in vitro and in vivo. A total of 79 peptides were active, with 63 targeting pathogens. These active AMPs exhibited antibacterial activity by disrupting bacterial membranes. In conclusion, our approach identified nearly one million prokaryotic AMP sequences, an open-access resource for antibiotic discovery.

Hundreds of antimicrobial peptides create a selective barrier for insect gut symbionts.

The spatial organization of gut microbiota is crucial for the functioning of the gut ecosystem, although the mechanisms that organize gut bacterial communities in microhabitats are only partially understood. The gut of the insect Riptortus pedestris has a characteristic microbiota biogeography with a multispecies community in the anterior midgut and a monospecific bacterial population in the posterior midgut. We show that the posterior midgut region produces massively hundreds of specific antimicrobial peptides (AMPs), the Crypt-specific Cysteine-Rich peptides (CCRs) that have membrane-damaging antimicrobial activity against diverse bacteria but posterior midgut symbionts have elevated resistance. We determined by transposon-sequencing the genetic repertoire in the symbiont Caballeronia insecticola to manage CCR stress, identifying different independent pathways, including AMP-resistance pathways unrelated to known membrane homeostasis functions as well as cell envelope functions. Mutants in the corresponding genes have reduced capacity to colonize the posterior midgut, demonstrating that CCRs create a selective barrier and resistance is crucial in gut symbionts. Moreover, once established in the gut, the bacteria differentiate into a CCR-sensitive state, suggesting a second function of the CCR peptide arsenal in protecting the gut epithelia or mediating metabolic exchanges between the host and the gut symbionts. Our study highlights the evolution of an extreme diverse AMP family that likely contributes to establish and control the gut microbiota.

Viral afterlife: SARS-CoV-2 as a reservoir of immunomimetic peptides that reassemble into proinflammatory supramolecular complexes.

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 cathelicidin's role in rheumatoid arthritis and lupus. The induced transcriptome matches well with the global gene expression pattern in COVID-19, despite using <0.3% of the viral proteome. Delivery of these complexes to uninfected mice boosts plasma interleukin-6 and CXCL1 levels as observed in COVID-19 patients.

TP-LMMSG: a peptide prediction graph neural network incorporating flexible amino acid property representation.

Bioactive peptide therapeutics has been a long-standing research topic. Notably, the antimicrobial peptides (AMPs) have been extensively studied for its therapeutic potential. Meanwhile, the demand for annotating other therapeutic peptides, such as antiviral peptides (AVPs) and anticancer peptides (ACPs), also witnessed an increase in recent years. However, we conceive that the structure of peptide chains and the intrinsic information between the amino acids is not fully investigated among the existing protocols. Therefore, we develop a new graph deep learning model, namely TP-LMMSG, which offers lightweight and easy-to-deploy advantages while improving the annotation performance in a generalizable manner. The results indicate that our model can accurately predict the properties of different peptides. The model surpasses the other state-of-the-art models on AMP, AVP and ACP prediction across multiple experimental validated datasets. Moreover, TP-LMMSG also addresses the challenges of time-consuming pre-processing in graph neural network frameworks. With its flexibility in integrating heterogeneous peptide features, our model can provide substantial impacts on the screening and discovery of therapeutic peptides. The source code is available at https://github.com/NanjunChen37/TP_LMMSG.

Diff-AMP: tailored designed antimicrobial peptide framework with all-in-one generation, identification, prediction and optimization.

Antimicrobial peptides (AMPs), short peptides with diverse functions, effectively target and combat various organisms. The widespread misuse of chemical antibiotics has led to increasing microbial resistance. Due to their low drug resistance and toxicity, AMPs are considered promising substitutes for traditional antibiotics. While existing deep learning technology enhances AMP generation, it also presents certain challenges. Firstly, AMP generation overlooks the complex interdependencies among amino acids. Secondly, current models fail to integrate crucial tasks like screening, attribute prediction and iterative optimization. Consequently, we develop a integrated deep learning framework, Diff-AMP, that automates AMP generation, identification, attribute prediction and iterative optimization. We innovatively integrate kinetic diffusion and attention mechanisms into the reinforcement learning framework for efficient AMP generation. Additionally, our prediction module incorporates pre-training and transfer learning strategies for precise AMP identification and screening. We employ a convolutional neural network for multi-attribute prediction and a reinforcement learning-based iterative optimization strategy to produce diverse AMPs. This framework automates molecule generation, screening, attribute prediction and optimization, thereby advancing AMP research. We have also deployed Diff-AMP on a web server, with code, data and server details available in the Data Availability section.

Intestinal biofilms: pathophysiological relevance, host defense, and therapeutic opportunities.

SUMMARYThe human intestinal tract harbors a profound variety of microorganisms that live in symbiosis with the host and each other. It is a complex and highly dynamic environment whose homeostasis directly relates to human health. Dysbiosis of the gut microbiota and polymicrobial biofilms have been associated with gastrointestinal diseases, including irritable bowel syndrome, inflammatory bowel diseases, and colorectal cancers. This review covers the molecular composition and organization of intestinal biofilms, mechanistic aspects of biofilm signaling networks for bacterial communication and behavior, and synergistic effects in polymicrobial biofilms. It further describes the clinical relevance and diseases associated with gut biofilms, the role of biofilms in antimicrobial resistance, and the intestinal host defense system and therapeutic strategies counteracting biofilms. Taken together, this review summarizes the latest knowledge and research on intestinal biofilms and their role in gut disorders and provides directions toward the development of biofilm-specific treatments.

Regulatory interactions between daptomycin- and bacitracin-responsive pathways coordinate the cell envelope antibiotic resistance response of Enterococcus faecalis.

Enterococcal infections frequently show high levels of antibiotic resistance, including to cell envelope-acting antibiotics like daptomycin (DAP). While we have a good understanding of the resistance mechanisms, less is known about the control of such resistance genes in enterococci. Previous work unveiled a bacitracin resistance network, comprised of the sensory ABC transporter SapAB, the two-component system (TCS) SapRS and the resistance ABC transporter RapAB. Interestingly, components of this system have recently been implicated in DAP resistance, a role usually regulated by the TCS LiaFSR. To better understand the regulation of DAP resistance and how this relates to mutations observed in DAP-resistant clinical isolates of enterococci, we here explored the interplay between these two regulatory pathways. Our results show that SapR regulates an additional resistance operon, dltXABCD, a known DAP resistance determinant, and show that LiaFSR regulates the expression of sapRS. This regulatory structure places SapRS-target genes under dual control, where expression is directly controlled by SapRS, which itself is up-regulated through LiaFSR. The network structure described here shows how Enterococcus faecalis coordinates its response to cell envelope attack and can explain why clinical DAP resistance often emerges via mutations in regulatory components.

Allergic fungal rhinosinusitis linked to other hyper-IgE syndromes through defective TH17 responses.

BACKGROUND: In a gene expression analysis comparing sinus mucosa samples from allergic fungal rhinosinusitis (AFRS) patients with samples from non-AFRS chronic rhinosinusitis with nasal polyp (CRSwNP) patients, the antimicrobial peptide (AMP) histatin 1 (HTN1) was found to be the most differentially downregulated gene in AFRS. OBJECTIVE: We sought to identify the molecular etiology of the downregulated expression of HTN1. METHODS: We used RT-PCR to compare the expression of AMPs and a fungistasis assay to evaluate the antifungal activity of sinus secretions. Using flow cytometry, we characterized the presence of TH17/TH22 cells and signal transducer and activator of transcription (STAT) signaling from AFRS patients, non-AFRS CRSwNP patients, and healthy controls. RESULTS: We confirmed decreased expression of AMPs in AFRS sinus mucosa with concordant decrease in antifungal activity in sinus secretions. IL-22 and IL-22-producing T cells were deficient within sinus mucosa of AFRS patients. In vitro studies demonstrated a defect in IL-6/STAT3 signaling critical for TH17/TH22 differentiation. Epithelial cells from AFRS patients could express AMPs when stimulated with exogenous IL-22/IL-17 and circulating TH17 cell abundance was normal. CONCLUSIONS: Similar to other hyper-IgE syndromes, but distinct from CRSwNP, AFRS patients express a defect in STAT3 activation limited to IL-6-dependent STAT3 phosphorylation that is critical for TH17/TH22 differentiation. This defect leads to a local deficiency of IL-17/IL-22 cytokines and deficient AMP expression within diseased sinus mucosa of AFRS patients. Our findings support evaluation of therapeutic approaches that enhance airway AMP production in AFRS.

Osteopontin Depletion in Non-haematopoietic Cells Improves Outcomes in Septic Mice by Enhancing Antimicrobial Peptide Production.

Osteopontin (Opn) depletion can improve septic outcomes, but the underlying mechanism remains unknown. In this study, we demonstrated that non-haematopoietic but not haematopoietic Opn depletion improved septic outcomes. Compared to wild-type (WT) mice, co-housed Opn-/- mice displayed enhanced production of antibacterial peptides (AMPs), decreased bacterial loads, and a distinct bacterial composition of gut microbiota. Fecal microbiota transplantation (FMT) and OPN neutralization assay showed that Opn depletion could reduce the bacterial loads and improve septic inflammation. By employing an intestinal organoid culture system, we proved that OPN neutralization in WT organoids could inactivate AKT and decrease FOXO3a phosphorylation, resulting in enhanced AMP production, whereas OPN treatment in OPN deficient organoids could activate AKT and increase FOXO3a phosphorylation, leading to reduced AMP production. Our findings identified OPN as a novel regulatory factor of AMP production to modulate bacterial loads and composition of gut microbiota, in turn affecting sepsis outcomes.

Membrane Lipids Augment Cell Envelope Stress Signaling via the MadRS System to Defend Against Antimicrobial Peptides and Antibiotics in Enterococcus faecalis.

Enterococci have evolved resistance mechanisms to protect their cell envelopes against bacteriocins and host cationic antimicrobial peptides (CAMPs) produced in the gastrointestinal environment. Activation of the membrane stress response has also been tied to resistance to the lipopeptide antibiotic daptomycin. However, the actual effectors mediating resistance have not been elucidated. Here, we show that the MadRS (formerly YxdJK) membrane antimicrobial peptide defense system controls a network of genes, including a previously uncharacterized three gene operon (madEFG) that protects the E. faecalis cell envelope from antimicrobial peptides. Constitutive activation of the system confers protection against CAMPs and daptomycin in the absence of a functional LiaFSR system and leads to persistence of cardiac microlesions in vivo. Moreover, changes in the lipid cell membrane environment alter CAMP susceptibility and expression of the MadRS system. Thus, we provide a framework supporting a multilayered envelope defense mechanism for resistance and survival coupled to virulence.

An efficient hybrid deep learning architecture for predicting short antimicrobial peptides.

Short-length antimicrobial peptides (AMPs) have been demonstrated to have intensified antimicrobial activities against a wide spectrum of microbes. Therefore, exploration of novel and promising short AMPs is highly essential in developing various types of antimicrobial drugs or treatments. In addition to experimental approaches, computational methods have been developed to improve screening efficiency. Although existing computational methods have achieved satisfactory performance, there is still much room for model improvement. In this study, we proposed iAMP-DL, an efficient hybrid deep learning architecture, for predicting short AMPs. The model was constructed using two well-known deep learning architectures: the long short-term memory architecture and convolutional neural networks. To fairly assess the performance of the model, we compared our model with existing state-of-the-art methods using the same independent test set. Our comparative analysis shows that iAMP-DL outperformed other methods. Furthermore, to assess the robustness and stability of our model, the experiments were repeated 10 times to observe the variation in prediction efficiency. The results demonstrate that iAMP-DL is an effective, robust, and stable framework for detecting promising short AMPs. Another comparative study of different negative data sampling methods also confirms the effectiveness of our method and demonstrates that it can also be used to develop a robust model for predicting AMPs in general. The proposed framework was also deployed as an online web server with a user-friendly interface to support the research community in identifying short AMPs.

Identification and Characterization of CC-AMP1-like and CC-AMP2-like Peptides in Capsicum spp.

Antimicrobial peptides (AMPs) are compounds with a variety of bioactive properties. Especially promising are their antibacterial activities, often toward 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 x 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 clinically relevant ESKAPE pathogens. These findings illustrate the value in continued study of plant AMPs toward characterization of novel AMP families, with CC-AMP1-like peptides possessing promising bioactivity.

IL-22-dependent responses and their role during Citrobacter rodentium infection.

The mouse pathogen Citrobacter rodentium is utilized as a model organism for studying infections caused by the human pathogens enteropathogenic Escherichia coli (EPEC) and enterohemorrhagic E. coli (EHEC) and to elucidate mechanisms of mucosal immunity. In response to C. rodentium infection, innate lymphoid cells and T cells secrete interleukin (IL)-22, a cytokine that promotes mucosal barrier function. IL-22 plays a pivotal role in enabling mice to survive and recover from C. rodentium infection, although the exact mechanisms involved remain incompletely understood. Here, we investigated whether particular components of the host response downstream of IL-22 contribute to the cytokine's protective effects during C. rodentium infection. In line with previous research, mice lacking the IL-22 gene (Il22-/- mice) were highly susceptible to C. rodentium infection. To elucidate the role of specific antimicrobial proteins modulated by IL-22, we infected the following knockout mice: S100A9-/- (calprotectin), Lcn2-/- (lipocalin-2), Reg3b-/- (Reg3ß), Reg3g-/- (Reg3γ), and C3-/- (C3). All knockout mice tested displayed a considerable level of resistance to C. rodentium infection, and none phenocopied the lethality observed in Il22-/- mice. By investigating another arm of the IL-22 response, we observed that C. rodentium-infected Il22-/- mice exhibited an overall decrease in gene expression related to intestinal barrier integrity as well as significantly elevated colonic inflammation, gut permeability, and pathogen levels in the spleen. Taken together, these results indicate that host resistance to lethal C. rodentium infection may depend on multiple antimicrobial responses acting in concert, or that other IL-22-regulated processes, such as tissue repair and maintenance of epithelial integrity, play crucial roles in host defense to attaching and effacing pathogens.

The transcriptional response in mosquitoes distinguishes between fungi and bacteria but not Gram types.

Mosquitoes are prolific vectors of human pathogens, therefore a clear and accurate understanding of the organization of their antimicrobial defenses is crucial for informing the development of transmission control strategies. The canonical infection response in insects, as described in the insect model Drosophila melanogaster, is pathogen type-dependent, with distinct stereotypical responses to Gram-negative bacteria and Gram-positive bacteria/fungi mediated by the activation of the Imd and Toll pathways, respectively. To determine whether this pathogen-specific discrimination is shared by mosquitoes, we used RNAseq to capture the genome-wide transcriptional response of Aedes aegypti and Anopheles gambiae (s.l.) to systemic infection with Gram-negative bacteria, Gram-positive bacteria, yeasts, and filamentous fungi, as well as challenge with heat-killed Gram-negative, Gram-positive, and fungal pathogens. From the resulting data, we found that Ae. aegypti and An. gambiae both mount a core response to all categories of infection, and this response is highly conserved between the two species with respect to both function and orthology. When we compared the transcriptomes of mosquitoes infected with different types of bacteria, we observed that the intensity of the transcriptional response was correlated with both the virulence and growth rate of the infecting pathogen. Exhaustive comparisons of the transcriptomes of Gram-negative-challenged versus Gram-positive-challenged mosquitoes yielded no difference in either species. In Ae. aegypti, however, we identified transcriptional signatures specific to bacterial infection and to fungal infection. The bacterial infection response was dominated by the expression of defensins and cecropins, while the fungal infection response included the disproportionate upregulation of an uncharacterized family of glycine-rich proteins. These signatures were also observed in Ae. aegypti challenged with heat-killed bacteria and fungi, indicating that this species can discriminate between molecular patterns that are specific to bacteria and to fungi.

Bacterial pneumonia-induced shedding of epithelial heparan sulfate inhibits the bactericidal activity of cathelicidin in a murine model.

Bacterial pneumonia is a common clinical syndrome leading to significant morbidity and mortality worldwide. In the current study, we investigate a novel, multidirectional relationship between the pulmonary epithelial glycocalyx and antimicrobial peptides in the setting of methicillin-resistant Staphylococcus aureus (MRSA) pneumonia. Using an in vivo pneumonia model, we demonstrate that highly sulfated heparan sulfate (HS) oligosaccharides are shed into the airspaces in response to MRSA pneumonia. In vitro, these HS oligosaccharides do not directly alter MRSA growth or gene transcription. However, in the presence of an antimicrobial peptide (cathelicidin), increasing concentrations of HS inhibit the bactericidal activity of cathelicidin against MRSA as well as other nosocomial pneumonia pathogens (Klebsiella pneumoniae and Pseudomonas aeruginosa) in a dose-dependent manner. Surface plasmon resonance shows avid binding between HS and cathelicidin with a dissociation constant of 0.13 µM. These findings highlight a complex relationship in which shedding of airspace HS may hamper host defenses against nosocomial infection via neutralization of antimicrobial peptides. These findings may inform future investigation into novel therapeutic targets designed to restore local innate immune function in patients suffering from primary bacterial pneumonia.NEW & NOTEWORTHY Primary Staphylococcus aureus pneumonia causes pulmonary epithelial heparan sulfate (HS) shedding into the airspace. These highly sulfated HS fragments do not alter bacterial growth or transcription, but directly bind with host antimicrobial peptides and inhibit the bactericidal activity of these cationic polypeptides. These findings highlight a complex local interaction between the pulmonary epithelial glycocalyx and antimicrobial peptides in the setting of bacterial pneumonia.

Antimalarial activity of cecropin antimicrobial peptides derived from Anopheles mosquitoes.

The emergence of clinically drug-resistant malaria parasites requires the urgent development of new drugs. Mosquitoes are vectors of multiple pathogens and have developed resistance mechanisms against them, which often involve antimicrobial peptides (AMPs). An-cecB is an AMP of the malaria-transmitting mosquito genus Anopheles, and we herein report its antimalarial activity against Plasmodium falciparum 3D7, the artemisinin-resistant strain 803, and the chloroquine-resistant strain Dd2 in vitro. We also demonstrate its anti-parasite activity in vivo, using the rodent malaria parasite Plasmodium berghei (ANKA). We show that An-cecB displays potent antimalarial activity and that its mechanism of action may occur through direct killing of the parasite or through interaction with infected red blood cell membranes. Unfortunately, An-cecB was found to be cytotoxic to mammalian cells and had poor antimalarial activity in vivo. However, its truncated peptide An-cecB-1 retained most of its antimalarial activity and avoided its cytotoxicity in vitro. An-cecB-1 also showed better antimalarial activity in vivo. Mosquito-derived AMPs may provide new ideas for the development of antimalarial drugs against drug-resistant parasites, and An-cecB has potential use as a template for antimalarial peptides.

First vertebrate BRICHOS antimicrobial peptides: ß-hairpin host defense peptides in limbless amphibia lung resemble those of marine worms.

Innate immunity of invertebrates offers potent antimicrobial peptides (AMPs) against drug-resistant infections. To identify new worm ß-hairpin AMPs, we explored the sequence diversity of proteins with a BRICHOS domain, which comprises worm AMP precursors. Strikingly, we discovered new BRICHOS AMPs not in worms, but in caecilians, the least studied clade of vertebrates. Two precursor proteins from Microcaecilia unicolor and Rhinatrema bivittatum resemble SP-C lung surfactants and bear worm AMP-like peptides at C-termini. The analysis of M. unicolor tissue transcriptomes shows that the AMP precursor is highly expressed in the lung along with regular SP-C, suggesting a different, protective function. The peptides form right-twisted ß-hairpins, change conformation upon lipid binding, and rapidly disrupt bacterial membranes. Both peptides exhibit broad-spectrum activity against multidrug-resistant ESKAPE pathogens with 1-4 µM MICs and remarkably low toxicity, giving 40-70-fold selectivity towards bacteria. These BRICHOS AMPs, previously unseen in vertebrates, reveal a novel lung innate immunity mechanism and offer a promising antibiotics template.

Effect of membrane tension on antimicrobial peptide PGLa-induced pore formation in lipid bilayers.

The osmotic pressure (Π) method has recently been developed to quantitatively examine the effect of membrane tension (σ) on pore formation in giant unilamellar vesicles (GUVs) induced by antimicrobial peptides (AMPs). Here, we used the Π method to reveal the effect of σ on the interaction of an AMP, PGLa, with lipid bilayers comprising dioleoylphosphatidylglycerol (DOPG) and dioleoylphosphatidylcholine (DOPC) (4/6). PGLa induced leakage of fluorescent probes from single GUVs under Π, indicating nanopore formation. Membrane tension did not transform a PGLa-induced nanopore into a micropore nor cause GUV burst up to 3.4 mN/m, which is in contrast with the effect of σ on another AMP, magainin 2-induced pore formation, where lower σ resulted in GUV burst. The fraction of leaking GUVs at a specific time increased with increasing σ, indicating that the rate of PGLa-induced pore formation increases with increasing σ. The rate of transfer of fluorescent probe-labeled PGLa across the lipid bilayer without pore formation also increased with increasing σ. PGLa-induced pore formation requires a symmetric distribution of peptides in both leaflets of the GUV bilayer, and thus we infer that the increase in the rate of PGLa transfer from the outer leaflet to the inner leaflet underlies the increase in the rate of pore formation with increasing σ. On the basis of these results, we discuss the difference between the effect of σ on nanopore formation in GUV membranes induced by PGLa and that by magainin 2.

Derivation of a novel antimicrobial peptide from the Red Sea Brine Pools modified to enhance its anticancer activity against U2OS cells.

Cancer associated drug resistance is a major cause for cancer aggravation, particularly as conventional therapies have presented limited efficiency, low specificity, resulting in long term deleterious side effects. Peptide based drugs have emerged as potential alternative cancer treatment tools due to their selectivity, ease of design and synthesis, safety profile, and low cost of manufacturing. In this study, we utilized the Red Sea metagenomics database, generated during AUC/KAUST Red Sea microbiome project, to derive a viable anticancer peptide (ACP). We generated a set of peptide hits from our library that shared similar composition to ACPs. A peptide with a homeodomain was selected, modified to improve its anticancer properties, verified to maintain high anticancer properties, and processed for further in-silico prediction of structure and function. The peptide's anticancer properties were then assessed in vitro on osteosarcoma U2OS cells, through cytotoxicity assay (MTT assay), scratch-wound healing assay, apoptosis/necrosis detection assay (Annexin/PI assay), RNA expression analysis of Caspase 3, KI67 and Survivin, and protein expression of PARP1. L929 mouse fibroblasts were also assessed for cytotoxicity treatment. In addition, the antimicrobial activity of the peptide was also examined on E coli and S. aureus, as sample representative species of the human bacterial microbiome, by examining viability, disk diffusion, morphological assessment, and hemolytic analysis. We observed a dose dependent cytotoxic response from peptide treatment of U2OS, with a higher tolerance in L929s. Wound closure was debilitated in cells exposed to the peptide, while annexin fluorescent imaging suggested peptide treatment caused apoptosis as a major mode of cell death. Caspase 3 gene expression was not altered, while KI67 and Survivin were both downregulated in peptide treated cells. Additionally, PARP-1 protein analysis showed a decrease in expression with peptide exposure. The peptide exhibited minimal antimicrobial activity on critical human microbiome species E. coli and S. aureus, with a low inhibition rate, maintenance of structural morphology and minimal hemolytic impact. These findings suggest our novel peptide displayed preliminary ACP properties against U2OS cells, through limited specificity, while triggering apoptosis as a primary mode of cell death and while having minimal impact on the microbiological species E. coli and S. aureus.