High-resolution mycobiota analysis reveals dynamic intestinal translocation preceding invasive candidiasis

Abstract

The intestinal microbiota is a complex community of bacteria, archaea, viruses, protists and fungi1,2. Although the composition of bacterial constituents has been linked to immune homeostasis and infectious susceptibility3,4,5,6,7, the role of non-bacterial constituents and cross-kingdom microbial interactions in these processes is poorly understood2,8. Fungi represent a major cause of infectious morbidity and mortality in immunocompromised individuals, although the relationship of intestinal fungi (that is, the mycobiota) with fungal bloodstream infections remains undefined9. We integrated an optimized bioinformatics pipeline with high-resolution mycobiota sequencing and comparative genomic analyses of fecal and blood specimens from recipients of allogeneic hematopoietic cell transplant. Patients with Candida bloodstream infection experienced a prior marked intestinal expansion of pathogenic Candida species; this expansion consisted of a complex dynamic between multiple species and subspecies with a stochastic translocation pattern into the bloodstream. The intestinal expansion of pathogenic Candida spp. was associated with a substantial loss in bacterial burden and diversity, particularly in the anaerobes. Thus, simultaneous analysis of intestinal fungi and bacteria identifies dysbiosis states across kingdoms that may promote fungal translocation and facilitate invasive disease. These findings support microbiota-driven approaches to identify patients at risk of fungal bloodstream infections for pre-emptive therapeutic intervention.

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Fig. 1: Intestinal fungal burden in allo-HCT patients.
Fig. 2: Mycobiota dynamics in allo-HCT patients.
Fig. 3: High-resolution mycobiota analysis in allo-HCT patients with fungal BSI.
Fig. 4: Characterization of bacteria in fecal samples with high and low levels of pathogenic Candida spp.

Data availability

The data that support the findings of the present study are available from the corresponding author upon request. All sequencing data generated in this study have been deposited in the Sequence Read Archive under BioProject PRJNA579121. Accession numbers of entries under this BioProject and previously submitted bacterial 16S rDNA-sequencing data7,20 are listed in Supplementary Table 4.

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Acknowledgements

We thank E. Pamer, I. Iliev, J. Xavier, J. Heitman and R. Rao for discussions, I. Leiner, M. Gjonbalaj, R. Seok and MSKCC Integrated Genomics Operation Facility for technical assistance. The studies were supported by a Geoffrey Beene Foundation Award (to T.M.H.), a Burroughs Wellcome Fund Investigator in the Pathogenesis of Infectious Diseases Award (to T.M.H.), National Institutes of Health grants (nos. P30 CA008748 to the MSKCC, R01 AI093808 to T.M.H., R01 AI 139632 to T.M.H., R01 AI137269 to Y.T. and K08HL143189 to J.U.P.), a Deutsche Forschungsgemeinschaft (German Research Foundation) fellowship grant (no. RO5328/2-1 to T.R.) and the Science Foundation Ireland (grant no. 12/IA/1343 to G.B.).

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Authors

Contributions

T.M.H. and B.Z. conceived of this project. B.Z., N.L.T. and S.J. generated the fungal ITS1 sequencing library and fungal burden quantification. B.Z. isolated the fecal strains and prepared samples for the whole-genome sequencing. M.O. and G.B. performed the comparative genomic analyses of fecal and blood strains. T.R., Y.T. and B.Z. performed the bacterial–fungal interaction analyses. T.R., N.L.T. and E.R.L. contributed to the data interpretation and statistical analyses. E.R.L., Y.T. and T.M.H. acquired the clinical data. L.A.A. performed the 16S rDNA quantification. L.A.A., E.F. and R.J.W. generated the 16S rDNA-sequencing library and supported the fecal specimen collection and storage. E.M., S.M.M. and N.E.B. provided the bloodstream strains. C.A.V. assisted B.Z. with the isolation of C. orthopsilosis strains from fecal specimens. J.U.P. and M.R.M.v.d.B. provided helpful discussions on the study design. Y.T. developed the DADA2 algorithm-based ITS1 and 16S rDNA-sequencing pipeline and analyzed the amplicon-based sequencing data. B.Z. and T.M.H. wrote the manuscript. T.R., J.U.P., M.R.M.v.d.B., G.B. and Y.T. edited the manuscript. All authors read and approved the manuscript.

Corresponding authors

Correspondence to Ying Taur or Tobias M. Hohl.

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Competing interests

T.M.H. has participated in scientific advisory boards for Merck & Co, Inc. and Partner Therapeutics. J.U.P. reports research funding, intellectual property fees and travel reimbursement from Seres Therapeutics. M.R.M.v.d.B. has received research support from Seres Therapeutics, consulted, received honoraria from or participated in advisory boards for Seres Therapeutics, Flagship Ventures, Novartis, Evelo, Jazz Pharmaceuticals, Therakos, Amgen, Magenta Therapeutics, Merck & Co, Inc., Acute Leukemia Forum and the DKMS Medical Council (Board), and IP Licensing with Seres Therapeutics and Juno Therapeutics. All other authors have no competing interests.

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Peer review information A. Farrell is the primary editor on this article, and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Quantitative Candida genus-specific 18S rDNA levels in fecal samples of candidemic patients.

The grey shade indicates the time range of first positive fungal blood cultures. N.D.: not detected.

Extended Data Fig. 2 Quantitation of relative abundance of pathogenic Candida species in patients without candidemia.

The solid line represents the dynamic trend, with the shaded area indicating the 95% confidence intervals, n = 57.

Extended Data Fig. 3 C. parapsilosis ASV1 and ASV2 sequence alignment.

The box indicates the single nucleotide difference between ASV1 and ASV2. This level of variation (1/279) cannot be differentiated with methods based on OTU clustering.

Extended Data Fig. 4 Patient example with C. metapsilosis BSI.

a, The panel shows clinical data, ITS rDNA sequencing results, quantification of amplicons of 5 different ASVs, and genotyping results of fecal and blood strains from patient 5. b, Phylogenic trees of C. metapsilosis strains from patient 5 and from other institutions. Solid lines indicate the calculated distance between strains (bootstrap support of 100%, or otherwise labeled). Dashed lines indicate the bootstrap value of 0, suggesting that the fecal and blood strains are highly similar.

Extended Data Fig. 5 SNP trees of C. parapsilosis and C. orthopsilosis strains with complete information on previously sequenced strains.

The bootstrap values are 100% for all the solid lines and 0% for all the dashed lines in the C. parapsilosis tree. For the C. orthopsilosis tree, the bootstrap values are 100% for the lines except those with specific bootstrap value labeled.

Extended Data Fig. 6 The amplification of RTA3 and the adjacent region on the genomics sequences of C. parapsilosis cluster II strains.

a, The graph shows the enrichment of reads aligned with RTA3 and the adjacent region of chromosome 1 in the genome of cluster II strains, compared to cluster I strains and strain Pt3.fecal.day2. b, Quantitation of RTA3 copy number of all sequenced C. parapsilosis strains from this study (cluster I strains and the strain from patient 2: n = 8; cluster II strains: n = 23).

Extended Data Fig. 7 Bacterial 16S rDNA sequencing data of candidemic and non-candidemic patients.

The grey dashed line and arrow indicate the day of transplant. The grey box indicates day -10 to day +30 of transplant. The black dashed line and arrow indicate the day of the first positive bacterial blood culture. Five samples (one from patient 3, four from patient 5) failed 16S rDNA sequencing and were excluded from the bacterial diversity or LEfSe analysis. A subset of the 16S rDNA sequencing data has been previously reported7,20.

Extended Data Fig. 8 Bacterial 16S rDNA burden and α-diversity in patient fecal samples.

a, Quantitative bacterial 16S rDNA levels in candidemic (red, n = 38) and non-candidemic (green, n = 54) patient groups at indicated time points during allo-HCT. Ten samples were further excluded from Fig. 7 since they failed the 16S rDNA qPCR reaction. b, α-diversity of bacterial 16S rDNA in candidemic (red, n = 45) and non-candidemic (green, n = 57) patient groups, measured by Inverse Simpson index. The solid line represents the dynamic trend, with the shaded area indicating the 95% confidence intervals. The grey shaded area indicates the day of first positive fungal blood culture. The y-axis in panel (b) is rescaled with Logε. A subset of the 16S rDNA sequencing data has been previously reported7,20.

Extended Data Fig. 9 Full bacterial sequencing data aligned according to Candida relative abundance.

Alignment of bacterial (16S) rDNA sequencing data from all 15 study patients, according to the relative abundance of pathogenic Candida species. The bacterial 16S rDNA sequencing data of each sample are presented in the bottom row. A subset of the 16S rDNA sequencing data has been previously reported7,20.

Extended Data Fig. 10 Characterization of intestinal bacterial microbiota with high Saccharomyces cerevisiae relative abundance.

a, 16S rDNA Alignment of bacterial (16S) rDNA sequencing data from all 15 study patients, according to the relative abundance of S. cerevisiae. b, quantification of bacterial burden (two-sided Wilcoxon rank sum p = 0.36) in samples with high (n = 29) and low (n = 64) S. cerevisiae relative abundance. Box plots represent median, IQR and range. c, quantification of bacterial diversity (two-sided Wilcoxon rank sum p = 0.87) in samples with high (n = 32) and low (n = 71) S. cerevisiae relative abundance. Box plots represent median, IQR and range. A subset of the 16S rDNA sequencing data has been previously reported7,20.

Supplementary information

Supplementary Information

Supplementary Table 1.

Reporting Summary

Supplementary Tables 2–4

Supplementary Table 2 Information of whole-genome sequencing data. Supplementary Table 3a, List of high-quality SNPs of C. parapsilosis cluster II strains. b, The matrix for PCA. Supplementary Table 4 SRA accessions of original ITS/16S/genome sequencing data included in the present study.

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Zhai, B., Ola, M., Rolling, T. et al. High-resolution mycobiota analysis reveals dynamic intestinal translocation preceding invasive candidiasis. Nat Med 26, 59–64 (2020). https://doi.org/10.1038/s41591-019-0709-7

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