Abstract
Antimicrobial resistance (AMR) reported to increase globally at alarming levels in the recent past. A number of potential alternative solutions discussed and implemented to control AMR in bacterial pathogens. Stringent control over the clinical application of antibiotics for a reduction in uses is a special consideration along with alternative solutions to fight against AMR. Although alternatives to conventional antibiotics like antimicrobial peptides (AMP) might warrant serious consideration to fight against AMR, there is a thriving recognition for vaccines in encountering the problem of AMR. Vaccines can reduce the prevalence of AMR by reducing the number of specific pathogens, which result in cutting down the antimicrobial need and uses. However, conventional vaccines produced using live or attenuated microorganisms while the presence of immunologically redundant biological components or impurities might cause major side effects and health related problems. Here we discussed AMPs based vaccination strategies as an emerging concept to overcome the disadvantages of traditional vaccines while boosting the AMPs to control multidrug resistant bacteria or AMR. Nevertheless, the poor immune response is a major challenge in the case of peptide vaccines as minimal antigenic epitopes used for immunization in peptide vaccines.
Keywords: Antimicrobial peptide, vaccine, antimicrobial resistance, epitope, adjuvants, immune response.
Graphical Abstract
[1]
Centers for Disease Control and Prevention. Antibiotic Resistance Threats in the United States, 2013.
[2]
Laxminarayan, R.; Bhutta, Z.A. Antimicrobial resistance a threat to neonate survival. Lancet Glob. Health, 2016, 4(10), e676-e677.
[3]
Roca, I.; Akova, M.; Baquero, F.; Carlet, J.; Cavaleri, M.; Coenen, S.; Cohen, J.; Findlay, D.; Gyssens, I.; Heure, O.E.; Kahlmeter, G.; Kruse, H.; Laxminarayan, R.; Liébana, E.; López-Cerero, L.; MacGowan, A.; Martins, M.; Rodríguez-Baño, J.; Rolain, J.M.; Segovia, C.; Sigauque, B.; Tacconelli, E.; Wellington, E.; Vila, J. The global threat of antimicrobial resistance: Science for intervention. New Microbes New Infect., 2015, 6, 22-29.
[4]
Laxminarayan, R.; Matsoso, P.; Pant, S.; Brower, C.; Røttingen, J.A.; Klugman, K.; Davies, S. Access to effective antimicrobials: A worldwide challenge. Lancet, 2016, 387(10014), 168-175.
[5]
Review on Antimicrobial Resistance. Antimicrobial Resistance: Tackling a Crisis for the Health and Wealth of Nations, 2014.
[6]
Laxminarayan, R.; Duse, A.; Wattal, C.; Zaidi, A.K.M.; Wertheim, H.F.L.; Sumpradit, N.; Vlieghe, E.; Hara, G.L.; Gould, I.M.; Goossens, H.; Greko, C.; So, A.D.; Bigdeli, M.; Tomson, G.; Woodhouse, W.; Ombaka, E.; Peralta, A.Q.; Qamar, F.N.; Mir, F.; Kariuki, S.; Bhutta, Z.A.; Coates, A.; Bergstrom, R.; Wright, G.D.; Brown, E.D.; Cars, O. Antibiotic resistance-the need for global solutions. Lancet Infect. Dis., 2013, 13(12), 1057-1098.
[7]
Potter, A.; Gerdts, V.; Littel-van den Hurk, Sv. Veterinary vaccines: Alternatives to antibiotics? Anim. Health Res. Rev., 2008, 9(2), 187-199.
[8]
Siegrist, C.A. Vaccine immunology. In: Vaccines; Plotkin, S.; Orenstein W.; Offit, P, 6th ed; Elsevier: Amsterdam, 2013; pp. 14-32.
[9]
Pasquale, A.; Preiss, S.; Silva, F.; Garçon, N. Vaccine adjuvants: From 1920 to 2015 and beyond. Vaccines, 2015, 3(2), 320-343.
[10]
Reed, S.G.; Orr, M.T.; Fox, C.B. Key roles of adjuvants in modern vaccines. Nat. Med., 2013, 19(12), 1597-1608.
[11]
Moyer, T.J.; Zmolek, A.C.; Irvine, D.J. Beyond antigens and adjuvants: Formulating future vaccines. J. Clin. Invest., 2016, 126(3), 799-808.
[13]
Haney, E.F.; Mansour, S.C.; Hancock, R.E.W. Antimicrobial peptides: An introduction. Methods Mol. Biol., 2017, 1548, 3-22.
[14]
Baindara, P.; Chaudhry, V.; Mittal, G.; Liao, L.M.; Matos, C.O.; Khatri, N.; Franco, O.L.; Patil, P.B.; Korpole, S. Characterization of the antimicrobial peptide penisin, a class Ia novel lantibiotic from paenibacillus sp. strain A3. Antimicrob. Agents Chemother., 2015, 60(1), 580-591.
[15]
Gordon, Y.J.; Romanowski, E.G.; McDermott, A.M. Mini review: A review of antimicrobial peptides and their therapeutic potential as anti-infective drugs. Curr. Eye Res., 2005, 30(7), 505-515.
[16]
Baindara, P.; Korpole, S. Lipopeptides: Status and strategies to control fungal infection. In: Recent Trends in Antifungal Agents and Antifungal Therapy; Basak, A.; Chakraborty, R.; Mandal, M.S., Eds.; Springer India: New Delhi, 2016; pp. 97-121.
[18]
Pinheiro Da Silva, F.; MacHado, M.C.C. Antimicrobial peptides: Clinical relevance and therapeutic implications. Peptides, 2012, 36(2), 308-314.
[19]
van Dissel, J.T.; Arend, S.M.; Prins, C.; Bang, P.; Tingskov, P.N.; Lingnau, K.; Nouta, J.; Klein, M.R.; Rosenkrands, I.; Ottenhoff, T.H.M. Ag85B–ESAT-6 adjuvanted with IC31® promotes strong and long-lived Mycobacterium tuberculosis specific T cell responses in naïve human volunteers. Vaccine, 2010, 28(20), 3571-3581.
[20]
Schellack, C.; Prinz, K.; Egyed, A.; Fritz, J.H.; Wittmann, B.; Ginzler, M.; Swatosch, G.; Zauner, W.; Kast, C.; Akira, S.; von Gabain, A.; Buschle, M.; Lingnau, K. IC31, a novel adjuvant signaling via TLR9, induces potent cellular and humoral immune responses. Vaccine, 2006, 24(26), 5461-5472.
[21]
Mandal, S.M.; Pati, B.R.; Chakraborty, R.; Franco, O.L. New insights into the bioactivity of peptides from probiotics. Front. Biosci., 2016, 8, 450.
[22]
Baindara, P.; Gautam, A.; Raghava, G.P.S.; Korpole, S. Anticancer properties of a defensin like class IId bacteriocin laterosporulin10. Sci. Rep., 2017, 7, 46541.
[23]
Baindara, P.; Singh, N.; Ranjan, M.; Nallabelli, N.; Chaudhry, V.; Pathania, G.L.; Sharma, N.; Kumar, A.; Patil, P.B.; Korpole, S. Laterosporulin10: A novel defensin like class IId bacteriocin from brevibacillus sp. Strain SKDU10 with inhibitory activity against microbial pathogens. Microbiology, 2016, 162(8), 1286-1299.
[24]
Baindara, P.; Kapoor, A.; Korpole, S.; Grover, V. Cysteine-rich low molecular weight antimicrobial peptides from brevibacillus and related genera for biotechnological applications. World J. Microbiol. Biotechnol., 2017, 33(6), 124.
[25]
Hancock, R.E.W.; Sahl, H-G. Antimicrobial and host-defense peptides as new anti-infective therapeutic strategies. Nat. Biotechnol., 2006, 24(12), 1551-1557.
[26]
Atkins, K.E.; Flasche, S. Vaccination to reduce antimicrobial resistance. Lancet Glob. Health, 2018, 6(3), 252.
[27]
Van De Sande-Bruinsma, N.; Grundmann, H.; Verloo, D.; Tiemersma, E.; Monen, J.; Goossens, H.; Ferech, M.; Mittermayer, H.; Metz, S.; Koller, W. European antimicrobial resistance surveillance system group; European surveillance of antimicrobial consumption project group. Antimicrobial drug use and resistance in europe. Emerg. Infect. Dis., 2008, 14(11), 1722-1730.
[28]
O’Neill, J. Tackling drug-resistant infections globally: Final report and recommendations. Rev. Antimicrob. Resist., 2016, 1, 84.
[29]
Heinsen, F.A.; Knecht, H.; Neulinger, S.C.; Schmitz, R.A.; Knecht, C.; Kühbacher, T.; Rosenstiel, P.C.; Schreiber, S.; Friedrichs, A.K.; Ott, S.J. Dynamic changes of the luminal and mucosaassociated gut microbiota during and after antibiotic therapy with paromomycin. Gut Microbes, 2015, 6(4), 243-254.
[30]
Ferrer, M.; Martins dos Santos, V.A.P.; Ott, S.J.; Moya, A. Gut microbiota disturbance during antibiotic therapy: A multi-omic approach. Gut Microbes, 2014, 5(1), 64-70.
[31]
Iizumi, T.; Battaglia, T.; Ruiz, V.; Perez Perez, G.I. Gut microbiome and antibiotics. Arch. Med. Res., 2017, 48, 727-734.
[32]
Olekhnovich, E.I.; Vasilyev, A.T.; Ulyantsev, V.I.; Kostryukova, E.S.; Tyakht, A.V. MetaCherchant: Analyzing genomic context of antibiotic resistance genes in gut microbiota. Bioinformatics, 2018, 34(3), 434-444.
[33]
Van Schaik, W. The human gut resistome. Philos. Trans. R. Soc. Biol. Sci., 2015, 370(1670), 20140087-20140087.
[34]
García-Quintanilla, M.; Pulido, M.R.; Carretero-Ledesma, M.; McConnell, M.J. Vaccines for antibiotic-resistant bacteria: Possibility or pipe dream? Trends Pharmacol. Sci., 2016, 37(2), 143-152.
[35]
Jansen, K.U.; Knirsch, C.; Anderson, A.S. The role of vaccines in preventing bacterial antimicrobial resistance. Nat. Med., 2018, 24(1), 10-20.
[37]
Metcalf, C.J.E.; Ferrari, M.; Graham, A.L.; Grenfell, B.T. Understanding herd immunity. Trends Immunol., 2015, 36(12), 753-755.
[38]
Siefert, A.L.; Caplan, M.J.; Fahmy, T.M. Artificial bacterial biomimetic nanoparticles synergize pathogen-associated molecular patterns for vaccine efficacy. Biomaterials, 2016, 97, 85-96.
[39]
Demento, S.L.; Siefert, A.L.; Bandyopadhyay, A.; Sharp, F.A.; Fahmy, T.M. Pathogen-associated molecular patterns on biomaterials: A paradigm for engineering new vaccines. Trends Biotechnol., 2011, 29(6), 294-306.
[40]
Testa, J.S.; Philip, R. Role of T-cell epitope-based vaccine in prophylactic and therapeutic applications. Future Virol., 2012, 7(11), 1077-1088.
[41]
Kuo, T.; Wang, C.; Badakhshan, T.; Chilukuri, S.; BenMohamed, L. The challenges and opportunities for the development of a T-cell epitope-based herpes simplex vaccine. Vaccine, 2014, 32(50), 6733-6745.
[42]
Li, L.; Yin, H.; An, Z.; Feng, Z. Considerations for developing an immunization strategy with enterovirus 71 vaccine. Vaccine, 2015, 33(9), 1107-1112.
[43]
Corti, D.; Voss, J.; Gamblin, S.J.; Codoni, G.; Macagno, A.; Jarrossay, D.; Vachieri, S.G.; Pinna, D.; Minola, A.; Vanzetta, F.; Silacci, C.; Fernandez-Rodriguez, B.M.; Agatic, G.; Bianchi, S.; Giacchetto-Sasselli, I.; Calder, L.; Sallusto, F.; Collins, P.; Haire, L.F.; Temperton, N.; Langedijk, J.P.; Skehel, J.J.; Lanzavecchia, A. A neutralizing antibody selected from plasma cells that binds to group 1 and group 2 influenza A hemagglutinins. Science, 2011, 333(6044), 850-856.
[44]
Marco, M.D.; Peper, J.K.; Rammensee, H.G. Identification of immunogenic epitopes by MS/MS. Cancer J., 2017, 23(2), 102-107.
[45]
Hager-Braun, C.; Tomer, K.B. Determination of protein-derived epitopes by mass spectrometry. Expert Rev. Proteomics, 2005, 2(5), 745-756.
[46]
Chen, W.H.; Sun, P.P.; Lu, Y.; Guo, W.W.; Huang, Y.X.; Ma, Z.Q. MimoPro: A more efficient web-based tool for epitope prediction using phage display libraries. BMC Bioinformatics, 2011, 12, 199.
[47]
Huang, J.; Gutteridge, A.; Honda, W.; Kanehisa, M. MIMOX: A web tool for phage display based epitope mapping. BMC Bioinformatics, 2006, 7, 451.
[48]
Mayrose, I.; Penn, O.; Erez, E.; Rubinstein, N.D.; Shlomi, T.; Freund, N.T.; Bublil, E.M.; Ruppin, E.; Sharan, R.; Gershoni, J.M.; Martz, E.; Pupko, T. Pepitope: Epitope mapping from affinity-selected peptides. Bioinformatics, 2007, 23(23), 3244-3246.
[49]
Huang, J.; Ru, B.; Zhu, P.; Nie, F.; Yang, J.; Wang, X.; Dai, P.; Lin, H.; Guo, F.B.; Rao, N. MimoDB 2.0: A mimotope database and beyond. Nucleic Acids Res., 2012, 40, D271-D277.
[50]
Skwarczynski, M.; Toth, I.; Andersen, P.; Doherty, T.M.; Wallach, J.C.; Ferrero, M.C.; Delpino, M.V.; Fossati, C.A.; Baldi, P.C.; Steer, A.C. Peptide-based synthetic vaccines. Chem. Sci., 2016, 7(2), 842-854.
[51]
Robinson, J.; Halliwell, J.A.; McWilliam, H.; Lopez, R.; Parham, P.; Marsh, S.G.E. The IMGT/HLA database. Nucleic Acids Res., 2013, 41(Database issue), D1222-D1227.
[52]
Robinson, J.; Halliwell, J.A.; Marsh, S.G.E. IMGT/HLA and the immuno polymorphism database. Methods Mol. Biol., 2014, 1184, 109-121.
[53]
Andersen, H.P.; Nielsen, M.; Lund, O. Prediction of residues in discontinuous B-cell epitopes using protein 3D structures. Protein Sci., 2006, 15(11), 2558-2567.
[54]
Kulkarni-Kale, U.; Bhosle, S.; Kolaskar, A.S. CEP: A conformational epitope prediction server. Nucleic Acids Res, 2005, 33(Web Server issue), W168-W171.
[55]
Nielsen, M.; Lundegaard, C.; Lund, O. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method. BMC Bioinformatics, 2007, 8, 238.
[56]
Liang, S.; Liu, S.; Zhang, C.; Zhou, Y. A Simple reference state makes a significant improvement in near-native selections from structurally refined docking decoys. Proteins Struct. Funct. Genet., 2007, 69(2), 244-253.
[57]
Sweredoski, M.J.; Baldi, P. PEPITO: Improved discontinuous B-cell epitope prediction using multiple distance thresholds and half sphere exposure. Bioinformatics, 2008, 24(12), 1459-1460.
[58]
Qi, T.; Qiu, T.; Zhang, Q.; Tang, K.; Fan, Y.; Qiu, J.; Wu, D.; Zhang, W.; Chen, Y.; Gao, J.; Zhu, R.; Cao, Z. SEPPA 2.0 - more
refined server to predict spatial epitope considering species of
immune host and subcellular localization of protein antigen. Nucleic Acids Res, 2014, 42(Web Server issue), W59-W63.
[59]
Liang, S.; Zheng, D.; Standley, D.M.; Yao, B.; Zacharias, M.; Zhang, C. EPSVR and EPMeta: Prediction of antigenic epitopes using support vector regression and multiple server results. BMC Bioinformatics, 2010, 11, 381.
[60]
Ponomarenko, J.; Bui, H.H.; Li, W.; Fusseder, N.; Bourne, P.E.; Sette, A.; Peters, B. ElliPro: A new structure-based tool for the prediction of antibody epitopes. BMC Bioinformatics, 2008, 9(1), 514.
[61]
Rubinstein, N.D.; Mayrose, I.; Martz, E.; Pupko, T. Epitopia: A web-server for predicting B-cell epitopes. BMC Bioinformatics, 2009, 10, 287.
[62]
Ansari, H.R.; Raghava, G.P. Identification of conformational B-Cell epitopes in an antigen from its primary sequence. Immunome Res., 2010, 6(Suppl. 2), S2.
[63]
Schuler, M.M.; Nastke, M.D.; Stevanovikć, S. SYFPEITHI: Database for searching and T-cell epitope prediction. Methods Mol. Biol., 2007, 409, 75-93.
[64]
Azmi, F.; Fuaad, A.A.H.A.; Skwarczynski, M.; Toth, I. Recent progress in adjuvant discovery for peptide-based subunit vaccines. Hum. Vaccin. Immunother., 2014, 10(3), 778-796.
[65]
Petrovsky, N.; Aguilar, J.C. Vaccine adjuvants: Current state and future trends. Immunol. Cell Biol., 2004, 82(5), 488-496.
[66]
Awate, S.; Babiuk, L.A.; Mutwiri, G. Mechanisms of action of adjuvants. Front. Immunol., 2013, 4, 114.
[67]
Excler, J.L.; Kim, J.H. Accelerating the development of a group A streptococcus vaccine: An urgent public health need. Clin. Exp. Vaccine Res., 2016, 5(2), 101-107.
[68]
Kao, D.J.; Churchill, M.E.A.; Irvin, R.T.; Hodges, R.S. Animal protection and structural studies of a consensus sequence vaccine targeting the receptor binding domain of the type IV pilus of pseudomonas aeruginosa. J. Mol. Biol., 2007, 374(2), 426-442.
[69]
Hussein, W.M.; Liu, T.Y.; Skwarczynski, M.; Toth, I. Toll-like receptor agonists: A patent review (2011 -2013). Expert Opin. Ther. Pat., 2014, 24(4), 453-470.
[70]
Marasini, N.; Skwarczynski, M.; Toth, I. Oral delivery of nanoparticle-based vaccines. Expert Rev. Vaccines, 2014, 13(11), 1361-1376.
[71]
Dürr, U.H.N.; Sudheendra, U.S.; Ramamoorthy, A. LL-37, the only
human member of the cathelicidin family of antimicrobial peptides. Biochim. Biophys. Acta - Biomembr, 2006, 1758(9), 1408-1425.
[72]
De Yang; Chen, Q.; Schmidt, A.P.; Anderson, G.M.; Wang, J.M.; Wooters, J.; Oppenheim, J.J.; Chertov, O. Ll-37, the neutrophil granule–and epithelial cell–derived cathelicidin, utilizes formyl peptide receptor-like 1 (Fprl1) as a receptor to chemoattract human peripheral blood neutrophils, monocytes, and T cells. J. Exp. Med., 2000, 192(7), 1069-1074.
[73]
Zheng, Y.; Niyonsaba, F.; Ushio, H.; Nagaoka, I.; Ikeda, S.; Okumura, K.; Ogawa, H. Cathelicidin LL-37 induces the generation of reactive oxygen species and release of human α-defensins from neutrophils. Br. J. Dermatol., 2007, 157(6), 1124-1131.
[74]
Mookherjee, N.; Brown, K.L.; Bowdish, D.M.E.; Doria, S.; Falsafi, R.; Hokamp, K.; Roche, F.M.; Mu, R.; Doho, G.H.; Pistolic, J.; Powers, J.P.; Bryan, J.; Brinkman, F.S.; Hancock, R.E. Modulation of the TLR-mediated inflammatory response by the endogenous human host defense peptide LL-37. J. Immunol., 2006, 176(4), 2455-2464.
[75]
Nijnik, A.; Pistolic, J.; Wyatt, A.; Tam, S.; Hancock, R.E.W. Human cathelicidin peptide LL-37 modulates the effects of IFN- on APCs. J. Immunol., 2009, 183(9), 5788-5798.
[76]
Steinstraesser, L.; Hirsch, T.; Schulte, M.; Kueckelhaus, M.; Jacobsen, F.; Mersch, E.A.; Stricker, I.; Afacan, N.; Jenssen, H.; Hancock, R.E.W.; Kindrachuk, J. Innate defense regulator peptide 1018 in wound healing and wound infection. PLoS One, 2012, 7(8), e39373.
[77]
Cirioni, O.; Giacometti, A.; Ghiselli, R.; Bergnach, C.; Orlando, F.; Silvestri, C.; Mocchegiani, F.; Licci, A.; Skerlavaj, B.; Rocchi, M.; Saba, V.; Zanetti, M.; Scalise, G. LL-37 protects rats against lethal sepsis caused by gram-negative bacteria. Antimicrob. Agents Chemother., 2006, 50(5), 1672-1679.
[78]
Faber, C.; Stallmann, H.P.; Lyaruu, D.M.; Joosten, U.; Von Eiff, C.; Van Nieuw, A.A.; Wuisman, P.I.J.M. Comparable efficacies of the antimicrobial peptide human lactoferrin 1-11 and gentamicin in a chronic methicillin-resistant Staphylococcus aureus osteomyelitis model. Antimicrob. Agents Chemother., 2005, 49(6), 2438-2444.
[79]
Papareddy, P.; Kalle, M.; Sørensen, O.E.; Malmsten, M.; Mörgelin, M.; Schmidtchen, A. The TFPI-2 derived peptide EDC34 improves outcome of gram-negative sepsis. PLoS Pathog., 2013, 9(12), e1003803.
[80]
Huang, H.N.; Rajanbabu, V.; Pan, C.Y.; Chan, Y.L.; Hui, C.F.; Chen, J.Y.; Wu, C.J. Modulation of the immune-related gene responses to protect mice against Japanese encephalitis virus using the antimicrobial peptide, tilapia hepcidin 1-5. Biomaterials, 2011, 32(28), 6804-6814.
[81]
Huang, H.N.; Rajanbabu, V.; Pan, C.Y.; Chan, Y.L.; Wu, C.J.; Chen, J.Y. A cancer vaccine based on the marine antimicrobial peptide pardaxin (GE33) for control of bladder-associated tumors. Biomaterials, 2013, 34(38), 10151-10159.
[82]
Baindara, P.; Korpole, S.; Grover, V. Bacteriocins: Perspective for the development of novel anticancer drugs. Appl. Microbiol. Biotechnol., 2018, 102(24), 10393-10408.
[84]
Cotter, P.D.; Ross, R.P.; Hill, C. Bacteriocins-a viable alternative to antibiotics? Nat. Rev. Microbiol., 2013, 11(2), 95-105.
[85]
Hancock, R.E.W.; Nijnik, A.; Philpott, D.J. Modulating immunity as a therapy for bacterial infections. Nat. Rev. Microbiol., 2012, 10(4), 243-254.
[86]
Ageitos, J.M.; Sánchez-Pérez, A.; Calo-Mata, P.; Villa, T.G. Antimicrobial Peptides (AMPs): Ancient compounds that represent novel weapons in the fight against bacteria. Biochem. Pharmacol., 2017, 133, 117-138.
[87]
Bechinger, B.; Gorr, S.U. Antimicrobial peptides: Mechanisms of action and resistance. J. Dent. Res., 2017, 96(3), 254-260.
Related Books
In Vitro Propagation and Secondary Metabolite Production from Medicinal Plants: Current Trends (Part 2)
Micropropagation of Medicinal Plants
Software and Programming Tools in Pharmaceutical Research
Biotechnology and Drug Development for Targeting Human Diseases
In Vitro Propagation and Secondary Metabolite Production from Medicinal Plants: Current Trends (Part 1)
Molecular and Physiological Insights into Plant Stress Tolerance and Applications in Agriculture- Part 2
Micropropagation of Medicinal Plants
Genome Editing in Bacteria (Part 1)
Data Science for Agricultural Innovation and Productivity
Animal Models In Experimental Medicine
Article Metrics
36
10