Aspergillus fumigatus pan-genome analysis identifies genetic variants associated with human infection.
Journal
Nature microbiology
ISSN: 2058-5276
Titre abrégé: Nat Microbiol
Pays: England
ID NLM: 101674869
Informations de publication
Date de publication:
12 2021
12 2021
Historique:
received:
05
03
2021
accepted:
08
10
2021
entrez:
25
11
2021
pubmed:
26
11
2021
medline:
25
12
2021
Statut:
ppublish
Résumé
Aspergillus fumigatus is an environmental saprobe and opportunistic human fungal pathogen. Despite an estimated annual occurrence of more than 300,000 cases of invasive disease worldwide, a comprehensive survey of the genomic diversity present in A. fumigatus-including the relationship between clinical and environmental isolates and how this genetic diversity contributes to virulence and antifungal drug resistance-has been lacking. In this study we define the pan-genome of A. fumigatus using a collection of 300 globally sampled genomes (83 clinical and 217 environmental isolates). We found that 7,563 of the 10,907 unique orthogroups (69%) are core and present in all isolates and the remaining 3,344 show presence/absence of variation, representing 16-22% of the genome of each isolate. Using this large genomic dataset of environmental and clinical samples, we found an enrichment for clinical isolates in a genetic cluster whose genomes also contain more accessory genes, including genes coding for transmembrane transporters and proteins with iron-binding activity, and genes involved in both carbohydrate and amino-acid metabolism. Finally, we leverage the power of genome-wide association studies to identify genomic variation associated with clinical isolates and triazole resistance as well as characterize genetic variation in known virulence factors. This characterization of the genomic diversity of A. fumigatus allows us to move away from a single reference genome that does not necessarily represent the species as a whole and better understand its pathogenic versatility, ultimately leading to better management of these infections.
Identifiants
pubmed: 34819642
doi: 10.1038/s41564-021-00993-x
pii: 10.1038/s41564-021-00993-x
doi:
Substances chimiques
Fungal Proteins
0
Virulence Factors
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1526-1536Informations de copyright
© 2021. The Author(s), under exclusive licence to Springer Nature Limited.
Références
Latgé, J. P. and Chamilos, G. Aspergillus fumigatus and Aspergillosis in 2019. Clin. Microbiol. Rev. https://doi.org/10.1128/CMR.00140-18 (2019).
Invasive Aspergillosis. LIFE http://www.life-worldwide.org/fungal-diseases/invasive-aspergillosis (2020).
Harrison, N. et al. Incidence and characteristics of invasive fungal diseases in allogeneic hematopoietic stem cell transplant recipients: a retrospective cohort study. BMC Infect. Dis. 15, 584 (2015).
pubmed: 26715563
pmcid: 4696168
doi: 10.1186/s12879-015-1329-6
Kuster, S. et al. Incidence and outcome of invasive fungal diseases after allogeneic hematopoietic stem cell transplantation: a Swiss transplant cohort study. Transpl. Infect. Dis. 20, e12981 (2018).
pubmed: 30144374
doi: 10.1111/tid.12981
Heo, S. T. et al. Changes in in vitro susceptibility patterns of Aspergillus to triazoles and correlation with aspergillosis outcome in a tertiary care cancer center, 1999–2015. Clin. Infect. Dis. 65, 216–225 (2017).
pubmed: 28379304
pmcid: 5850538
doi: 10.1093/cid/cix297
Lestrade, P. P. et al. Voriconazole resistance and mortality in invasive aspergillosis: a multicenter retrospective cohort study. Clin. Infect. Dis. 68, 1463–1471 (2019).
pubmed: 30307492
doi: 10.1093/cid/ciy859
Snelders, E. et al. Emergence of azole resistance in Aspergillus fumigatus and spread of a single resistance mechanism. PLoS Med. 5, 1629–1637 (2008).
doi: 10.1371/journal.pmed.0050219
Rizzetto, L. et al. Strain dependent variation of immune responses to A. fumigatus: definition of pathogenic species. PLoS ONE 8, 2–14 (2013).
doi: 10.1371/journal.pone.0056651
Kowalski, C. H. et al. Heterogeneity among isolates reveals that fitness in low oxygen correlates with Aspergillus fumigatus virulence. mBio 7, e01515-16 (2016).
pubmed: 27651366
pmcid: 5040115
doi: 10.1128/mBio.01515-16
Alshareef, F. & Robson, G. D. Genetic and virulence variation in an environmental population of the opportunistic pathogen Aspergillus fumigatus. Microbiology 160, 742–751 (2014).
pubmed: 24464798
doi: 10.1099/mic.0.072520-0
Knox, B. P. et al. Characterization of Aspergillus fumigatus isolates from air and surfaces of the International Space Station. mSphere 1, e00227-16.
Ries, L. N. A. et al. Nutritional heterogeneity among Aspergillus fumigatus strains has consequences for virulence in a strain- and host-dependent manner. Front. Microbiol. 10, 854 (2019).
pubmed: 31105662
pmcid: 6492530
doi: 10.3389/fmicb.2019.00854
Steenwyk, J. L. et al. Variation among biosynthetic gene clusters, secondary metabolite profiles, and cards of virulence across Aspergillus species. Genetics 216, 481–497 (2020).
pubmed: 32817009
pmcid: 7536862
doi: 10.1534/genetics.120.303549
Dos Santos, R. A. C. et al. Genomic and phenotypic heterogeneity of clinical isolates of the human pathogens Aspergillus fumigatus, Aspergillus lentulus, and Aspergillus fumigatiaffinis. Front. Genet. 11, 459 (2020).
pubmed: 32477406
pmcid: 7236307
doi: 10.3389/fgene.2020.00459
Fedorova, N. D. et al. Genomic islands in the pathogenic filamentous fungus Aspergillus fumigatus. PLoS Genet. 4, e1000046 (2008).
Abdolrasouli, A. et al. Genomic context of azole-resistance mutations in Aspergillus fumigatus using whole-genome sequencing. mBio 6, e00536 (2015).
pubmed: 26037120
pmcid: 4453006
Garcia-Rubio, R. et al. Genome-wide comparative analysis of Aspergillus fumigatus strains: the reference genome as a matter of concern. Genes 9, 363 (2018).
pmcid: 6071029
doi: 10.3390/genes9070363
Fan, Y., Wang Y. and Xu, J. Comparative genome sequence analyses of geographic samples of Aspergillus fumigatus—relevance for amphotericin B resistance. Microorganisms 8, 1673 (2020).
Puértolas-Balint, F. et al. Revealing the virulence potential of clinical and environmental Aspergillus fumigatus isolates using whole-genome sequencing. Front. Microbiol. 10, 1970 (2019).
Barber, A. E. et al. Effects of agricultural fungicide use on Aspergillus fumigatus abundance, antifungal susceptibility, and population structure. mBio 11, e02213-20 (2020).
Arendrup, M. C. et al. Method for the determination of broth dilution minimum inhibitory concentrations of antifungal agents for conidia forming moulds. E.DEF 9.3.2. EUCAST https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/AFST/Files/EUCAST_E_Def_9.3.2_Mould_testing_definitive_revised_2020.pdf (2020).
Jombart, T., Devillard, S. & Balloux, F. Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet. 11, 94 (2010).
pubmed: 20950446
pmcid: 2973851
doi: 10.1186/1471-2156-11-94
Nierman, W. C. et al. Genomic sequence of the pathogenic and allergenic filamentous fungus Aspergillus fumigatus. Nature 438, 1151–1156 (2005).
pubmed: 16372009
doi: 10.1038/nature04332
Steenwyk, J. L. et al. Genomic and phenotypic analysis of COVID-19-associated pulmonary aspergillosis isolates of Aspergillus fumigatus. Microbiol. Spectr. 9, e0001021 (2021).
pubmed: 34106569
doi: 10.1128/Spectrum.00010-21
Abad, A. et al. What makes Aspergillus fumigatus a successful pathogen? Genes and molecules involved in invasive aspergillosis. Rev. Iberoam. Micol. 27, 155–82 (2010).
pubmed: 20974273
doi: 10.1016/j.riam.2010.10.003
Bignell, E., et al. Secondary metabolite arsenal of an opportunistic pathogenic fungus. Philos. Trans. R Soc. B 371, 20160023 (2016).
Kjaerbolling, I. et al. Linking secondary metabolites to gene clusters through genome sequencing of six diverse Aspergillus species. Proc. Natl Acad. Sci. USA 115, E753–E761 (2018).
pubmed: 29317534
pmcid: 5789934
doi: 10.1073/pnas.1715954115
Urban, M. et al. PHI-base: the pathogen-host interactions database. Nucleic Acids Res. 48, D613–D620 (2020).
pubmed: 31733065
O’Hanlon, K. A. et al. Targeted disruption of nonribosomal peptide synthetase pes3 augments the virulence of Aspergillus fumigatus. Infect. Immun. 79, 3978–3992 (2011).
pubmed: 21746855
pmcid: 3187245
doi: 10.1128/IAI.00192-11
Sugui, J. A. et al. Genes differentially expressed in conidia and hyphae of Aspergillus fumigatus upon exposure to human neutrophils. PLoS ONE 3, e2655 (2008).
pubmed: 18648542
pmcid: 2481287
doi: 10.1371/journal.pone.0002655
Willger, S. D. et al. A sterol-regulatory element binding protein is required for cell polarity, hypoxia adaptation, azole drug resistance, and virulence in Aspergillus fumigatus. PLoS Pathog. 4, e1000200 (2008).
pubmed: 18989462
pmcid: 2572145
doi: 10.1371/journal.ppat.1000200
Blatzer, M., et al. SREBP coordinates iron and ergosterol homeostasis to mediate triazole drug and hypoxia responses in the human fungal pathogen Aspergillus fumigatus. PLoS Genet. 7, e1002374 (2011).
Bertuzzi, M. et al. The pH-responsive PacC transcription factor of Aspergillus fumigatus governs epithelial entry and tissue invasion during pulmonary aspergillosis. PLoS Pathog. 10, e1004413 (2014).
pubmed: 25329394
pmcid: 4199764
doi: 10.1371/journal.ppat.1004413
Bignell, E. et al. The Aspergillus pH-responsive transcription factor PacC regulates virulence. Mol. Microbiol. 55, 1072–1084 (2005).
pubmed: 15686555
doi: 10.1111/j.1365-2958.2004.04472.x
Pongpom, M. et al. Divergent targets of Aspergillus fumigatus AcuK and AcuM transcription factors during growth in vitro versus invasive disease. Infect. Immun. 83, 923–933 (2015).
pubmed: 25534941
pmcid: 4333448
doi: 10.1128/IAI.02685-14
Camps, S. M. T. et al. Molecular epidemiology of Aspergillus fumigatus isolates harboring the TR34/L98H azole resistance mechanism. J. Clin. Microbiol. 50, 2674–2680 (2012).
pubmed: 22675126
pmcid: 3421523
doi: 10.1128/JCM.00335-12
McCarthy, C. G. P. & Fitzpatrick, D. A. Pan-genome analyses of model fungal species. Microb. Genom. 5, e000243 (2019).
pmcid: 6421352
Lind, A. L. et al. Drivers of genetic diversity in secondary metabolic gene clusters within a fungal species. PLoS Biol. 15, e2003583 (2017).
pubmed: 29149178
pmcid: 5711037
doi: 10.1371/journal.pbio.2003583
Rybak, J. Mutations in hmg1, challenging the paradigm of clinical triazole resistance in Aspergillus fumigatus. mBio 10, e00437-19 (2019).
pubmed: 30940706
pmcid: 6445940
doi: 10.1128/mBio.00437-19
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
pubmed: 19451168
pmcid: 2705234
doi: 10.1093/bioinformatics/btp324
McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
pubmed: 20644199
pmcid: 2928508
doi: 10.1101/gr.107524.110
Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly 6, 80–92 (2012).
pubmed: 22728672
pmcid: 3679285
doi: 10.4161/fly.19695
Varga, J. Mating type gene homologues in Aspergillus fumigatus. Microbiology 149, 816–819 (2003).
pubmed: 12686624
doi: 10.1099/mic.0.C0113-0
Paoletti, M. et al. Evidence for sexuality in the opportunistic fungal pathogen Aspergillus fumigatus. Curr. Biol. 15, 1242–1248 (2005).
pubmed: 16005299
doi: 10.1016/j.cub.2005.05.045
Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).
pubmed: 21653522
pmcid: 3137218
doi: 10.1093/bioinformatics/btr330
Peng, Y., et al. IDBA—a practical iterative de Bruijn graph de novo assembler. In Proc. Research in Computational Molecular Biology. RECOMB 2010. (ed. Berger, B.) 426–440 (Springer, 2010).
Gurevich, A. et al. QUAST: quality assessment tool for genome assemblies. Bioinformatics 29, 1072–1075 (2013).
pubmed: 23422339
pmcid: 3624806
doi: 10.1093/bioinformatics/btt086
Palmer, J & Stajich J. Funannotate v.1.5.3. Zenodo https://zenodo.org/record/2604804 (2019).
Smit, A., Hubley, R. & Green, P. RepeatMasker Open-4.0. (2013–2015); http://www.repeatmasker.org
Bao, W., Kojima, K. K. & Kohany, O. Repbase Update, a database of repetitive elements in eukaryotic genomes. Mobile DNA 6, 11 (2015).
pubmed: 26045719
pmcid: 4455052
doi: 10.1186/s13100-015-0041-9
Haas, B. J. et al. Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments. Genome Biol. 9, R7 (2008).
pubmed: 18190707
pmcid: 2395244
doi: 10.1186/gb-2008-9-1-r7
Ter-Hovhannisyan, V. et al. Gene prediction in novel fungal genomes using an ab initio algorithm with unsupervised training. Genome Res. 18, 1979–1990 (2008).
pubmed: 18757608
pmcid: 2593577
doi: 10.1101/gr.081612.108
Stanke, M. et al. Using native and syntenically mapped cDNA alignments to improve de novo gene finding. Bioinformatics 24, 637–644 (2008).
pubmed: 18218656
doi: 10.1093/bioinformatics/btn013
Lowe, T. M. & Chan, P. P. tRNAscan-SE On-line: integrating search and context for analysis of transfer RNA genes. Nucleic Acids Res. 44, W54–W57 (2016).
pubmed: 27174935
pmcid: 4987944
doi: 10.1093/nar/gkw413
Finn, R. D. et al. Pfam: clans, web tools and services. Nucleic Acids Res. 34, D247–D251 (2006).
doi: 10.1093/nar/gkj149
Rawlings, N. D., Barrett, A. J. & Bateman, A. MEROPS: the database of proteolytic enzymes, their substrates and inhibitors. Nucleic Acids Res. 40, D343–D350 (2012).
pubmed: 22086950
doi: 10.1093/nar/gkr987
Zhang, H. et al. dbCAN2: a meta server for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 46, W95–W101 (2018).
pubmed: 29771380
pmcid: 6031026
doi: 10.1093/nar/gky418
Simao, F. A. et al. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210–3212 (2015).
pubmed: 26059717
doi: 10.1093/bioinformatics/btv351
Aramaki, T. et al. KofamKOALA: KEGG ortholog assignment based on profile HMM and adaptive score threshold. Bioinformatics 36, 2251–2252 (2020).
pubmed: 31742321
doi: 10.1093/bioinformatics/btz859
Jones, P. et al. InterProScan 5: genome-scale protein function classification. Bioinformatics 30, 1236–1240 (2014).
pubmed: 24451626
pmcid: 3998142
doi: 10.1093/bioinformatics/btu031
Emms, D. M. & Kelly, S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 20, 238 (2019).
pubmed: 31727128
pmcid: 6857279
doi: 10.1186/s13059-019-1832-y
Edgar, R. C. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinform. 5, 113 (2004).
doi: 10.1186/1471-2105-5-113
Suyama, M., Torrents, D. & Bork, P. PAL2NAL: robust conversion of protein sequence alignments into the corresponding codon alignments. Nucleic Acids Res. 34, W609–W612 (2006).
pubmed: 16845082
pmcid: 1538804
doi: 10.1093/nar/gkl315
Minh, B. Q. et al. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol. Biol. Evol. 37, 1530–1534 (2020).
pubmed: 32011700
pmcid: 7182206
doi: 10.1093/molbev/msaa015
Hoang, D. T. et al. UFBoot2: improving the ultrafast bootstrap approximation. Mol. Biol. Evol. 35, 518–522 (2018).
pubmed: 29077904
doi: 10.1093/molbev/msx281
Didelot, X. & Wilson, D. J. ClonalFrameML: efficient inference of recombination in whole bacterial genomes. PLoS Comput. Biol. 11, e1004041 (2015).
pubmed: 25675341
pmcid: 4326465
doi: 10.1371/journal.pcbi.1004041
Schliep, K. P. phangorn: Phylogenetic analysis in R. Bioinformatics 27, 592–593 (2011).
pubmed: 21169378
doi: 10.1093/bioinformatics/btq706
Yu, G. et al. Two methods for mapping and visualizing associated data on phylogeny using Ggtree. Mol. Biol. Evol. 35, 3041–3043 (2018).
pubmed: 30351396
pmcid: 6278858
doi: 10.1093/molbev/msy194
Yang, Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 24, 1586–1591 (2007).
pubmed: 17483113
doi: 10.1093/molbev/msm088
Whelan, F. J., Rusilowicz, M. and McInerney, J. O. Coinfinder: detecting significant associations and dissociations in pangenomes. Microb. Genom. 6, e000338 (2020).
Kang, H. M. et al. Variance component model to account for sample structure in genome-wide association studies. Nat. Genet. 42, 348–354 (2010).
pubmed: 20208533
pmcid: 3092069
doi: 10.1038/ng.548
Brynildsrud, O. et al. Rapid scoring of genes in microbial pan-genome-wide association studies with Scoary. Genome Biol. 17, 238 (2016).
pubmed: 27887642
pmcid: 5124306
doi: 10.1186/s13059-016-1108-8