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Current Proteomics

Editor-in-Chief

ISSN (Print): 1570-1646
ISSN (Online): 1875-6247

Research Article

The Epidemiological and Pangenome Landscape of Staphylococcus aureus and Identification of Conserved Novel Candidate Vaccine Antigens

Author(s): Kanwal Naz , Nimat Ullah, Anam Naz, Sidra Irum, Hamza Arshad Dar, Tahreem Zaheer, Fatima Shahid and Amjad Ali *

Volume 19, Issue 1, 2022

Published on: 12 February, 2021

Page: [114 - 126] Pages: 13

DOI: 10.2174/1570164618666210212122847

Price: $65

Abstract

Background and Objective: Staphylococcus aureus (S. aureus) is a gram-positive bacterium and one of the major nosocomial pathogens. It has the ability to acquire resistance against almost all available classes of antibiotics; Methicillin-Resistant S. aureus (MRSA) is a well-known antibiotic-resistant pathogen. S. aureus is a globally distributed pathogen that needs in-depth epidemiological and genomic level investigation for proper treatment and prevention.

Methods: To explore the genomic epidemiology of S. aureus, in-silico Multi Locus Sequence Typing (MLST) was carried out for 355 complete genomes. Diversity within the species was investigated through pan-genome analysis and a subtractive genomic approach was employed for the identification of the core immunogenic targets.

Results: Epidemiological study identified 62 different sequence types (STs) of S. aureus distributed worldwide, in which ST-8, ST-5, ST-398, ST-239, and ST-30 were the most dominant STs comprising more than 50% of the isolates. The pan-genome of S. aureus is still open with 7,199 genes and there is a major contribution (80%) of MRSA strains in the S. aureus species pangenome. The core genome (2,025 genes) of S. aureus is almost stable (comprising 72% of S. aureus genome size), while accessory and unique genes (28% of S. aureus genome size) are gradually increasing. Screening of 2,025 core genes identified putative vaccine candidates. The best scoring and dominant B-cell and T-cell epitopes were predicted out of the selected potential vaccine candidate proteins with the help of a multi-step screening procedure.

Conclusion: We believe that the current study will provide insight into the genetic epidemiology and diversity of S. aureus, and the predicted epitopes against the pathogen can be tested further for their immunological responses within the host and may provide both humoral and cellular immunity against the disease.

Keywords: Epidemiology, Staphylococcus aureus, MLST, MRSA, pangenome, subtractive proteomics, vaccine candidates.

Graphical Abstract
[1]
Tong, S.Y.; Davis, J.S.; Eichenberger, E.; Holland, T.L.; Fowler, V.G., Jr Staphylococcus aureus infections: epidemiology, pathophysiology, clinical manifestations, and management. Clin. Microbiol. Rev., 2015, 28(3), 603-661.
[http://dx.doi.org/10.1128/CMR.00134-14] [PMID: 26016486]
[2]
Ullah, N.; Raza, T.; Dar, H.A.; Shehroz, M.; Zaheer, T.; Naz, K.; Ali, A. Whole-genome sequencing of a new sequence type (ST5352) strain of community-acquired methicillin-resistant Staphylococcus aureus from a hospital in Pakistan. J. Glob. Antimicrob. Resist., 2019, 19, 161-163.
[http://dx.doi.org/10.1016/j.jgar.2019.09.015] [PMID: 31557564]
[3]
Katayama, Y.; Ito, T.; Hiramatsu, K. A new class of genetic element, staphylococcus cassette chromosome mec, encodes methicillin resistance in Staphylococcus aureus. Antimicrob. Agents Chemother., 2000, 44(6), 1549-1555.
[http://dx.doi.org/10.1128/AAC.44.6.1549-1555.2000] [PMID: 10817707]
[4]
Tang, P.; Croxen, M.A.; Hasan, M.R.; Hsiao, W.W.; Hoang, L.M. Infection control in the new age of genomic epidemiology. Am. J. Infect. Control, 2017, 45(2), 170-179.
[http://dx.doi.org/10.1016/j.ajic.2016.05.015] [PMID: 28159067]
[5]
aStruelens, M.J.; De Gheldre, Y.; Deplano, A. Comparative and library epidemiological typing systems: outbreak investigations versus surveillance systems. Infect. Control Hosp. Epidemiol., 1998, 19(8), 565-569.
bMuellner, P.; Pleydell, E.; Pirie, R.; Baker, M.G.; Campbell, D.; Carter, P.E.; French, N.P. Molecular-based surveillance of campylobacteriosis in New Zealand- from source attribution to genomic epidemiology. Euro Surveill., 2013, 18(3), 20365.
cStruelens, M.J.; Brisse, S. From molecular to genomic epidemiology: transforming surveillance and control of infectious diseases. Euro Surveill., 2013, 18(4), 20386.
[http://dx.doi.org/10.2307/30141781] [PMID: 9758056] [PMID: 23351655] [http://dx.doi.org/10.2807/ese.18.04.20386-en] [PMID: 23369387]
[6]
Feil, E.J.; Li, B.C.; Aanensen, D.M.; Hanage, W.P.; Spratt, B.G. eBURST: inferring patterns of evolutionary descent among clusters of related bacterial genotypes from multilocus sequence typing data. J. Bacteriol., 2004, 186(5), 1518-1530.
[http://dx.doi.org/10.1128/JB.186.5.1518-1530.2004] [PMID: 14973027]
[7]
Tettelin, H.; Riley, D.; Cattuto, C.; Medini, D. Comparative genomics: the bacterial pan-genome. Curr. Opin. Microbiol., 2008, 11(5), 472-477.
[http://dx.doi.org/10.1016/j.mib.2008.09.006] [PMID: 19086349]
[8]
McInerney, J.O.; McNally, A.; O’Connell, M.J. Why prokaryotes have pangenomes. Nat. Microbiol., 2017, 2(4), 17040.
[http://dx.doi.org/10.1038/nmicrobiol.2017.40] [PMID: 28350002]
[9]
Tettelin, H.; Masignani, V.; Cieslewicz, M.J.; Donati, C.; Medini, D.; Ward, N.L.; Angiuoli, S.V.; Crabtree, J.; Jones, A.L.; Durkin, A.S.; Deboy, R.T.; Davidsen, T.M.; Mora, M.; Scarselli, M.; Margarit y Ros, I.; Peterson, J.D.; Hauser, C.R.; Sundaram, J.P.; Nelson, W.C.; Madupu, R.; Brinkac, L.M.; Dodson, R.J.; Rosovitz, M.J.; Sullivan, S.A.; Daugherty, S.C.; Haft, D.H.; Selengut, J.; Gwinn, M.L.; Zhou, L.; Zafar, N.; Khouri, H.; Radune, D.; Dimitrov, G.; Watkins, K.; O’Connor, K.J.; Smith, S.; Utterback, T.R.; White, O.; Rubens, C.E.; Grandi, G.; Madoff, L.C.; Kasper, D.L.; Telford, J.L.; Wessels, M.R.; Rappuoli, R.; Fraser, C.M. Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial “pan-genome”. Proc. Natl. Acad. Sci. USA, 2005, 102(39), 13950-13955.
[http://dx.doi.org/10.1073/pnas.0506758102] [PMID: 16172379]
[10]
aLu, Q.-F.; Cao, D.-M.; Su, L.-L.; Li, S.-B.; Ye, G.-B.; Zhu, X.-Y.; Wang, J.-P. Genus-wide comparative genomics analysis of Neisseria to identify new genes associated with pathogenicity and niche adaptation of Neisseria pathogens. International journal of genomics, 2019, 2019
bFreschi, L.; Vincent, A.T.; Jeukens, J.; Emond-Rheault, J-G.; Kukavica-Ibrulj, I.; Dupont, M-J.; Charette, S.J.; Boyle, B.; Levesque, R.C. The Pseudomonas aeruginosa pan-genome provides new insights on its population structure, horizontal gene transfer, and pathogenicity. Genome Biol. Evol., 2019, 11(1), 109-120.
[http://dx.doi.org/10.1155/2019/6015730] [http://dx.doi.org/10.1093/gbe/evy259] [PMID: 30496396]
[11]
Pinto, M.; González-Díaz, A.; Machado, M.P.; Duarte, S.; Vieira, L.; Carriço, J.A.; Marti, S.; Bajanca-Lavado, M.P.; Gomes, J.P. Insights into the population structure and pan-genome of Haemophilus influenzae. Infect. Genet. Evol., 2019, 67, 126-135.
[http://dx.doi.org/10.1016/j.meegid.2018.10.025] [PMID: 30391557]
[12]
Kiu, R.; Caim, S.; Alexander, S.; Pachori, P.; Hall, L.J. Probing genomic aspects of the multi-host pathogen Clostridium perfringens reveals significant pangenome diversity, and a diverse array of virulence factors. Front. Microbiol., 2017, 8, 2485.
[http://dx.doi.org/10.3389/fmicb.2017.02485] [PMID: 29312194]
[13]
Doron, S.; Melamed, S.; Ofir, G.; Leavitt, A.; Lopatina, A.; Keren, M.; Amitai, G.; Sorek, R. Systematic discovery of antiphage defense systems in the microbial pangenome. Science, 2018, 359(6379), eaar4120.
[http://dx.doi.org/10.1126/science.aar4120] [PMID: 29371424]
[14]
aKavvas, E.S.; Catoiu, E.; Mih, N.; Yurkovich, J.T.; Seif, Y.; Dillon, N.; Heckmann, D.; Anand, A.; Yang, L.; Nizet, V.; Monk, J.M.; Palsson, B.O. Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance. Nat. Commun., 2018, 9(1), 4306.
bZeng, L.; Wang, D.; Hu, N.; Zhu, Q.; Chen, K.; Dong, K.; Zhang, Y.; Yao, Y.; Guo, X.; Chang, Y-F.; Zhu, Y. A novel pan-genome reverse vaccinology approach employing a negative-selection strategy for screening surface-exposed antigens against leptospirosis. Front. Microbiol., 2017, 8, 396.
cBhardwaj, T.; Somvanshi, P. Pan-genome analysis of Clostridium botulinum reveals unique targets for drug development. Gene, 2017, 623, 48-62.
Naz, A.; Obaid, A.; Shahid, F.; Dar, H.A.; Naz, K.; Ullah, N.; Ali, A. Reverse vaccinology and drug target identification through pan-genomics Pan-genomics: Applications, Challenges, and Future Prospects Elsevier, 2020, pp. 317-333.
[http://dx.doi.org/10.1038/s41467-018-06634-y] [PMID: 30333483] [http://dx.doi.org/10.3389/fmicb.2017.00396] [PMID: 28352257] [http://dx.doi.org/10.1016/j.gene.2017.04.019] [PMID: 28450142] [http://dx.doi.org/10.1016/B978-0-12-817076-2.00016-0]
[15]
Muhammad, S.A.; Ahmed, S.; Ali, A.; Huang, H.; Wu, X.; Yang, X.F.; Naz, A.; Chen, J. Prioritizing drug targets in Clostridium botulinum with a computational systems biology approach. Genomics, 2014, 104(1), 24-35.
[http://dx.doi.org/10.1016/j.ygeno.2014.05.002] [PMID: 24837790]
[16]
Naz, A.; Awan, F.M.; Obaid, A.; Muhammad, S.A.; Paracha, R.Z.; Ahmad, J.; Ali, A. Identification of putative vaccine candidates against Helicobacter pylori exploiting exoproteome and secretome: a reverse vaccinology based approach. Infect. Genet. Evol., 2015, 32, 280-291.
[http://dx.doi.org/10.1016/j.meegid.2015.03.027] [PMID: 25818402]
[17]
Uddin, R.; Siddiqui, Q.N.; Azam, S.S.; Saima, B.; Wadood, A. Identification and characterization of potential druggable targets among hypothetical proteins of extensively drug resistant Mycobacterium tuberculosis (XDR KZN 605) through subtractive genomics approach. Eur. J. Pharm. Sci., 2018, 114, 13-23.
[http://dx.doi.org/10.1016/j.ejps.2017.11.014] [PMID: 29174549]
[18]
Zhang, X.; Marichannegowda, M.H.; Rakesh, K.P.; Qin, H-L. Master mechanisms of Staphylococcus aureus: consider its excellent protective mechanisms hindering vaccine development! Microbiol. Res., 2018, 212-213, 59-66.
[http://dx.doi.org/10.1016/j.micres.2018.05.002] [PMID: 29853168]
[19]
Wattam, A.R.; Abraham, D.; Dalay, O.; Disz, T.L.; Driscoll, T.; Gabbard, J.L.; Gillespie, J.J.; Gough, R.; Hix, D.; Kenyon, R.; Machi, D.; Mao, C.; Nordberg, E.K.; Olson, R.; Overbeek, R.; Pusch, G.D.; Shukla, M.; Schulman, J.; Stevens, R.L.; Sullivan, D.E.; Vonstein, V.; Warren, A.; Will, R.; Wilson, M.J.; Yoo, H.S.; Zhang, C.; Zhang, Y.; Sobral, B.W. PATRIC, the bacterial bioinformatics database and analysis resource. Nucleic Acids Res., 2014, 42(Database issue), D581-D591.
[http://dx.doi.org/10.1093/nar/gkt1099] [PMID: 24225323]
[20]
Seemann, T. Prokka: rapid prokaryotic genome annotation. Bioinformatics, 2014, 30(14), 2068-2069.
[http://dx.doi.org/10.1093/bioinformatics/btu153] [PMID: 24642063]
[21]
Zankari, E.; Hasman, H.; Cosentino, S.; Vestergaard, M.; Rasmussen, S.; Lund, O.; Aarestrup, F.M.; Larsen, M.V. Identification of acquired antimicrobial resistance genes. J. Antimicrob. Chemother., 2012, 67(11), 2640-2644.
[http://dx.doi.org/10.1093/jac/dks261] [PMID: 22782487]
[22]
Larsen, M.V.; Cosentino, S.; Rasmussen, S.; Friis, C.; Hasman, H.; Marvig, R.L.; Jelsbak, L.; Sicheritz-Pontén, T.; Ussery, D.W.; Aarestrup, F.M.; Lund, O. Multilocus sequence typing of total-genome-sequenced bacteria. J. Clin. Microbiol., 2012, 50(4), 1355-1361.
[http://dx.doi.org/10.1128/JCM.06094-11] [PMID: 22238442]
[23]
Kumar, S.; Stecher, G.; Li, M.; Knyaz, C.; Tamura, K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol., 2018, 35(6), 1547-1549.
[http://dx.doi.org/10.1093/molbev/msy096] [PMID: 29722887]
[24]
Letunic, I.; Bork, P. Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation. Bioinformatics, 2007, 23(1), 127-128.
[http://dx.doi.org/10.1093/bioinformatics/btl529] [PMID: 17050570]
[25]
Naz, K.; Naz, A.; Ashraf, S.T.; Rizwan, M.; Ahmad, J.; Baumbach, J.; Ali, A.; Pan, R.V. PanRV: Pangenome-reverse vaccinology approach for identifications of potential vaccine candidates in microbial pangenome. BMC Bioinformatics, 2019, 20(1), 123.
[http://dx.doi.org/10.1186/s12859-019-2713-9] [PMID: 30871454]
[26]
Huerta-Cepas, J.; Forslund, K.; Coelho, L.P.; Szklarczyk, D.; Jensen, L.J.; von Mering, C.; Bork, P. Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Mol. Biol. Evol., 2017, 34(8), 2115-2122.
[http://dx.doi.org/10.1093/molbev/msx148] [PMID: 28460117]
[27]
Pruitt, K. D.; Tatusova, T.; Maglott, D. R. NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic acids research, 2006, 2006(35)(suppl_1), D61-D65.
[28]
Boutet, E.; Lieberherr, D.; Tognolli, M.; Schneider, M.; Bairoch, A. Uniprotkb/swiss-prot. Plant bioinformatics; Springer, 2007, pp. 89-112.
[http://dx.doi.org/10.1007/978-1-59745-535-0_4]
[29]
Luo, H.; Lin, Y.; Gao, F.; Zhang, C-T.; Zhang, R. DEG 10, an update of the database of essential genes that includes both protein- coding genes and noncoding genomic elements. Nucleic Acids Res., 2014, 42(Database issue), D574-D580.
[http://dx.doi.org/10.1093/nar/gkt1131] [PMID: 24243843]
[30]
Lacey, K.A.; Geoghegan, J.A.; McLoughlin, R.M. The role of Staphylococcus aureus virulence factors in skin infection and their potential as vaccine antigens. Pathogens, 2016, 5(1), 22.
[http://dx.doi.org/10.3390/pathogens5010022] [PMID: 26901227]
[31]
Tusnády, G.E.; Simon, I. The HMMTOP transmembrane topology prediction server. Bioinformatics, 2001, 17(9), 849-850.
[http://dx.doi.org/10.1093/bioinformatics/17.9.849] [PMID: 11590105]
[32]
Yu, N.Y.; Wagner, J.R.; Laird, M.R.; Melli, G.; Rey, S.; Lo, R.; Dao, P.; Sahinalp, S.C.; Ester, M.; Foster, L.J.; Brinkman, F.S. PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes. Bioinformatics, 2010, 26(13), 1608-1615.
[http://dx.doi.org/10.1093/bioinformatics/btq249] [PMID: 20472543]
[33]
Saha, S.; Raghava, G.P. Prediction of continuous B-cell epitopes in an antigen using recurrent neural network. Proteins, 2006, 65(1), 40-48.
[http://dx.doi.org/10.1002/prot.21078] [PMID: 16894596]
[34]
Singh, H.; Raghava, G.P. ProPred: prediction of HLA-DR binding sites. Bioinformatics, 2001, 17(12), 1236-1237.
[http://dx.doi.org/10.1093/bioinformatics/17.12.1236] [PMID: 11751237]
[35]
Singh, H.; Raghava, G.P. ProPred1: prediction of promiscuous MHC Class-I binding sites. Bioinformatics, 2003, 19(8), 1009-1014.
[http://dx.doi.org/10.1093/bioinformatics/btg108] [PMID: 12761064]
[36]
Yu, C-S.; Cheng, C-W.; Su, W-C.; Chang, K-C.; Huang, S-W.; Hwang, J-K.; Lu, C-H. CELLO2GO: a web server for protein subCELlular LOcalization prediction with functional gene ontology annotation. PLoS One, 2014, 9(6), e99368.
[http://dx.doi.org/10.1371/journal.pone.0099368] [PMID: 24911789]
[37]
Liu, J.; Zeng, Q.; Wang, M.; Cheng, A.; Liu, M.; Zhu, D.; Chen, S.; Jia, R.; Zhao, X.X.; Wu, Y.; Yang, Q.; Zhang, S.; Liu, Y.; Yu, Y.; Zhang, L.; Chen, X. Comparative genome-scale modelling of the pathogenic Flavobacteriaceae species Riemerella anatipestifer in China. Environ. Microbiol., 2019, 21(8), 2836-2851.
[http://dx.doi.org/10.1111/1462-2920.14635] [PMID: 31004458]
[38]
aRamadurai, L.; Jayaswal, R.K. Molecular cloning, sequencing, and expression of lytM, a unique autolytic gene of Staphylococcus aureus. J. Bacteriol., 1997, 179(11), 3625-3631.
bSugai, M.; Fujiwara, T.; Ohta, K.; Komatsuzawa, H.; Ohara, M.; Suginaka, H. epr, which encodes glycylglycine endopeptidase resistance, is homologous to femAB and affects serine content of peptidoglycan cross bridges in Staphylococcus capitis and Staphylococcus aureus. J. Bacteriol., 1997, 179(13), 4311-4318.
cOdintsov, S.G.; Sabala, I.; Marcyjaniak, M.; Bochtler, M. Latent LytM at 1.3A resolution. J. Mol. Biol., 2004, 335(3), 775-785.
[http://dx.doi.org/10.1128/JB.179.11.3625-3631.1997] [PMID: 9171409] [http://dx.doi.org/10.1128/JB.179.13.4311-4318.1997] [PMID: 9209049] [http://dx.doi.org/10.1016/j.jmb.2003.11.009] [PMID: 14687573]
[39]
Schleifer, K.H.; Kandler, O. Peptidoglycan types of bacterial cell walls and their taxonomic implications. Bacteriol. Rev., 1972, 36(4), 407-477.
[http://dx.doi.org/10.1128/BR.36.4.407-477.1972] [PMID: 4568761]
[40]
Pieper, R.; Gatlin-Bunai, C.L.; Mongodin, E.F.; Parmar, P.P.; Huang, S.T.; Clark, D.J.; Fleischmann, R.D.; Gill, S.R.; Peterson, S.N. Comparative proteomic analysis of Staphylococcus aureus strains with differences in resistance to the cell wall-targeting antibiotic vancomycin. Proteomics, 2006, 6(15), 4246-4258.
[http://dx.doi.org/10.1002/pmic.200500764] [PMID: 16826566]
[41]
Lang, S.; Livesley, M.A.; Lambert, P.A.; Littler, W.A.; Elliott, T.S. Identification of a novel antigen from Staphylococcus epidermidis. FEMS Immunol. Med. Microbiol., 2000, 29(3), 213-220.
[http://dx.doi.org/10.1111/j.1574-695X.2000.tb01525.x] [PMID: 11064268]
[42]
Pastrana, F.R.; Neef, J.; Koedijk, D.G.; de Graaf, D.; Duipmans, J.; Jonkman, M.F.; Engelmann, S.; van Dijl, J.M.; Buist, G. Human antibody responses against non-covalently cell wall-bound Staphylococcus aureus proteins. Sci. Rep., 2018, 8(1), 1-11.
[http://dx.doi.org/10.1038/s41598-018-21724-z] [PMID: 29311619]
[43]
Etz, H.; Minh, D.B.; Henics, T.; Dryla, A.; Winkler, B.; Triska, C.; Boyd, A.P.; Söllner, J.; Schmidt, W.; von Ahsen, U.; Buschle, M.; Gill, S.R.; Kolonay, J.; Khalak, H.; Fraser, C.M.; von Gabain, A.; Nagy, E.; Meinke, A. Identification of in vivo expressed vaccine candidate antigens from Staphylococcus aureus. Proc. Natl. Acad. Sci. USA, 2002, 99(10), 6573-6578.
[http://dx.doi.org/10.1073/pnas.092569199] [PMID: 11997460]
[44]
aKajimura, J.; Fujiwara, T.; Yamada, S.; Suzawa, Y.; Nishida, T.; Oyamada, Y.; Hayashi, I.; Yamagishi, J.; Komatsuzawa, H.; Sugai, M. Identification and molecular characterization of an N-acetylmuramyl-L-alanine amidase Sle1 involved in cell separation of Staphylococcus aureus. Mol. Microbiol., 2005, 58(4), 1087-1101.
bFrankel, M.B.; Schneewind, O. Determinants of murein hydrolase targeting to cross-wall of Staphylococcus aureus peptidoglycan. J. Biol. Chem., 2012, 287(13), 10460-10471.
[http://dx.doi.org/10.1111/j.1365-2958.2005.04881.x] [PMID: 16262792] [http://dx.doi.org/10.1074/jbc.M111.336404] [PMID: 22303016]
[45]
Wang, X.; Thompson, C.D.; Weidenmaier, C.; Lee, J.C. Release of Staphylococcus aureus extracellular vesicles and their application as a vaccine platform. Nat. Commun., 2018, 9(1), 1379.
[http://dx.doi.org/10.1038/s41467-018-03847-z] [PMID: 29643357]

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