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Whole-genome sequencing rule-out of suspected hospital-onset Rhizopus outbreaks

Published online by Cambridge University Press:  13 June 2023

Victoria T. Chu
Affiliation:
Division of Infectious Diseases and Global Health, Department of Pediatrics, University of California–San Francisco, San Francisco, California
Saba Nafees
Affiliation:
Chan Zuckerberg Biohub, San Francisco, California
Eric Waltari
Affiliation:
Chan Zuckerberg Biohub, San Francisco, California
Nicole McNeil
Affiliation:
Department of Hospital Epidemiology and Infection Prevention, University of California–San Francisco, San Francisco, California
Carolyn Caughell
Affiliation:
Department of Hospital Epidemiology and Infection Prevention, University of California–San Francisco, San Francisco, California
Estella Sanchez-Guerrero
Affiliation:
Division of Infectious Diseases, Department of Medicine, University of California–San Francisco, San Francisco, California
Lusha Wang
Affiliation:
Department of Hospital Epidemiology and Infection Prevention, University of California–San Francisco, San Francisco, California
Kim Stanley
Affiliation:
Department of Hospital Epidemiology and Infection Prevention, University of California–San Francisco, San Francisco, California
Gail Cunningham
Affiliation:
Department of Laboratory Medicine, University of California–San Francisco, San Francisco, California
Joan Wong
Affiliation:
Chan Zuckerberg Biohub, San Francisco, California
Maíra Phelps
Affiliation:
Chan Zuckerberg Biohub, San Francisco, California
Cristina M. Tato
Affiliation:
Chan Zuckerberg Biohub, San Francisco, California
Steve Miller
Affiliation:
Illumina, Inc, Foster City, California
Joseph L. DeRisi
Affiliation:
Chan Zuckerberg Biohub, San Francisco, California Department of Biochemistry and Biophysics, University of California–San Francisco, San Francisco, California
Deborah S. Yokoe
Affiliation:
Department of Hospital Epidemiology and Infection Prevention, University of California–San Francisco, San Francisco, California Division of Infectious Diseases, Department of Medicine, University of California–San Francisco, San Francisco, California
Lynn Ramirez-Avila
Affiliation:
Division of Infectious Diseases and Global Health, Department of Pediatrics, University of California–San Francisco, San Francisco, California Department of Hospital Epidemiology and Infection Prevention, University of California–San Francisco, San Francisco, California
Charles R. Langelier*
Affiliation:
Chan Zuckerberg Biohub, San Francisco, California Department of Hospital Epidemiology and Infection Prevention, University of California–San Francisco, San Francisco, California Division of Infectious Diseases, Department of Medicine, University of California–San Francisco, San Francisco, California
*
Corresponding author: Charles Langelier; Email: chaz.langelier@ucsf.edu
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Abstract

Two independent temporal-spatial clusters of hospital-onset Rhizopus infections were evaluated using whole-genome sequencing (WGS). Phylogenetic analysis confirmed that isolates within each cluster were unrelated despite epidemiological suspicion of outbreaks. The ITS1 region alone was insufficient for accurate analysis. WGS has utility for rapid rule-out of suspected nosocomial Rhizopus outbreaks.

Type
Concise Communication
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America

Rhizopus spp are a common etiology of mucormycosis, an invasive fungal infection that affects individuals who are immunocompromised or have diabetes mellitus. Hospital outbreaks secondary to contaminated medical equipment or airborne dissemination of fungal spores have been reported. Reference Hartnett, Jackson and Perkins1 From 2020 to 2022, 2 independent temporospatial clusters of hospital-onset Rhizopus infections were identified. We used whole-genome sequencing (WGS) to evaluate the genetic similarity of patient isolates and to assess whether the clusters represented hospital outbreaks.

Methods

Electronic medical records were reviewed for patient history. Hospital-onset was defined as fungal infection diagnosed ≥7 days after admission. Cultures were performed on bronchial alveolar lavage (BAL) or tissue specimens. DNA extraction, library preparation, and Illumina sequencing were performed according to established protocols. Reference Crawford, Kamm and Millert2 Sequencing reads were assembled and categorized using the Chan Zuckerberg identification (CZID) pipeline. Reference Ramesh, Nakielny and Hsu3 Alignment of reads to a reference and calculation of distance matrices was performed using the SPID pipeline Reference Kamm4 with a reference genome from Rhizopus microsporus var rhizopodiformis strain B11533 (Genbank accession SMRR00000000.1) spanning 27.7 megabases (Mbp) and representing all 27 contigs. Maximum likelihood phylogenetic analysis was performed using Randomized Axelerated Maximum Likelihood (RAxML) Reference Kozlov, Darriba, Flouri, Morel and Stamatakis5 following described methods. Reference Crawford, Kamm and Millert2 Because ITS1 amplicon sequencing has historically been used to evaluate suspected outbreaks of fungal pathogens, Reference Garcia-Hermoso, Criscuolo and Lee6 we assessed whether phylogenetic analysis performed exclusively on this region would yield the same conclusions as WGS. Lastly, we reviewed hospital-onset invasive fungal infection surveillance data from 2018 to 2022 to assess whether there was an increase in fungal infections during this period. The University of California–San Francisco Institutional Review Board granted a waiver of consent for this study, which was part of a larger ongoing surveillance study of patients with outbreak-associated infections (IRB protocol no. 17-24056).

Results

Investigation A

Two adult patients (patients A1 and A2) who underwent outpatient bronchoscopy on the same day in October 2020 had rare Rhizopus spp in their BAL cultures (Table 1). Patient A1 had diabetes mellitus type 2 and a history of bilateral lung transplantation; patient A2 had a history of lung radiation therapy for gastric cancer and treated pulmonary tuberculosis. BALs were performed for noninfectious evaluations of worsening lung function (patient A1) and mechanical dilation of a chronic airway stricture (patient A2).

Table 1. Demographic, Microbiologic, and Sequencing Data for Two Clusters of Patients With Mucormycosis

Note. WGS, whole-genome sequencing.

The unusual occurrence of Rhizopus spp in 2 BAL specimens collected on the same day at the same hospital raised concern for a nosocomial infection or contamination in the collection process from a common environmental source that could place other immunocompromised patients undergoing the same procedure at risk for infection. Initial review of the operating room and clinical microbiology laboratory procedures was uninformative other than confirming that the same laboratory staff member plated both BAL samples for culture. WGS and phylogenetic analyses were performed within 48 hours. The isolates were identified as different species: R. microsporus (patient A1) and R. oryzae (patient A2). They differed by 1,688 single-nucleotide polymorphisms (SNPs) over a shared genome alignment of 0.41 Mbp (Fig. 1). Because WGS identified different Rhizopus spp, no further environmental investigation was conducted. Given low clinical suspicion for infection, therapy was not initiated, and no subsequent cultures were obtained.

Figure 1. (A) Maximum likelihood phylogenetic tree of all 5 patients from Rhizopus clusters A and B, based on whole-genome sequencing (WGS), created with RAxML. An historical control (HCtrl) R. microsporus isolate was also included. Scale bar represents 1 SNP/kb. (B) Heatmap demonstrating WGS-derived single-nucleotide polymorphism (SNP) distances between isolates. (C) Heatmap demonstrating ITS1-derived SNP distances between isolates, with a R. oryzae ITS1 reference.

Investigation B

Cluster B comprised 3 pediatric patients hospitalized between November 2020 and March 2022 with cutaneous mucormycosis (Table 1). Patients B1 and B2 were autologous stem-cell transplant recipients who developed cheek cutaneous mucormycosis under medical adhesive for a nasogastric tube and an endotracheal tube, respectively. One month after the diagnosis of patient B2 diagnosis, an extremely preterm infant (patient B3) kept in a humidified incubator developed a cutaneous abdominal eschar. Tissue cultures from all 3 patients grew Rhizopus spp.

An infection control investigation for each case was launched. It included environmental assessments of the heating and ventilation systems, construction projects, and fungal air sampling. A review of equipment and items with direct contact to the patients’ skin, surface, and bulk cultures of patient-care items was conducted, as well as an analysis of geospatial relationships between the involved patients. The investigations resulted in deep cleaning of patient rooms, changes in equipment maintenance workflow, and a switch in linen vendors after a site visit revealed a lapse in the current vendor’s TRSA certification. However, a common source for the Rhizopus was not identified.

WGS was ultimately performed on four isolates among the 3 patients; patient B2 had 2 tissue culture isolates. All 3 patients had distinct Rhizopus infections identified as Rhizopus oryzae (patient B1, patient B2 isolate 1 and patient B2 isolate 2) and Rhizopus microsporus (patient B3) (Fig. 1A). Isolates 1 and 2 from patient B2 each differed from patient B1’s isolate by >600 SNPs over an average shared genome alignment of 0.77 Mbp. Isolates from patients B1 and B2 differed from patient B3’s isolate by >30,000 SNPs over an average shared genome alignment of 3.3 Mbp.

The 2 isolates from patient B2 (obtained independently on the same day) served as a positive control; they were confirmed to be genetically identical (Fig. 1B). An historical isolate from a community-onset R. microsporus infection in the same hospital served as a negative control and differed by >2,000 SNPs from the closest investigated isolate (Fig. 1B). The ITS1 region alone distinguished infections from different Rhizopus spp. in cluster A, but ITS1 lacked resolution to differentiate between isolates of the same Rhizopus spp. in cluster B (Fig. 1C).

Lastly, we asked whether there was an increase in the number of invasive fungal infections at the study site institution between 2018 and 2022. We identified no significant change in the incidence (median, 5 cases per quarter; interquartile range, 4–5 cases per quarter).

Discussion

An increase in hospital-onset Rhizopus cases can reflect sporadic environmental acquisition or active hospital transmission from a point source. Despite epidemiologic, clinical, and microbiologic correlations concerning for nosocomial Rhizopus outbreaks or a common environmental source, WGS confirmed that the cases within both clusters were phylogenetically distinct and were likely a result of stochastic occurrences.

Isolates within the suspected clusters differed by >600 SNPs over 3.3 Mbp. Although the number of SNPs needed to distinguish Rhizopus strains is undefined, prior studies have suggested that >60 SNPs may reliably distinguish Rhizopus strains. Reference Bowers, Monroy-Nieto and Gade7 Independent sequencing of 2 positive control isolates from patient B2 showed no SNPs over the shared genome alignment, indicating high analytic reproducibility of the WGS methods used. These investigations support increasing evidence that WGS can be performed rapidly Reference Crawford, Kamm and Millert2 and can lend clarity to suspected mucormycosis clusters Reference Garcia-Hermoso, Criscuolo and Lee6 as well as other invasive fungal outbreaks. Reference Bagal, Ireland and Gross8

Classically, Rhizopus outbreak investigations rely on conventional microbiological methods for species identification. Reference Hartnett, Jackson and Perkins1 When sequencing has been employed, it has been primarily restricted to short regions of the genome containing both conserved and variable sequences, such as the ITS1 or 18S regions. Reference Llata, Blossom and Khoury9 In our study, ITS1 sequencing alone led to a false determination of genetic relatedness between cases, and WGS was needed for the most accurate conclusion.

Using WGS, we were able to conclude that the cases within 2 clusters were unrelated. Prompt resolution of the suspected outbreak in cluster A avoided closure of bronchoscopy suites, sequestration and culturing of bronchoscopes, environmental and air sampling, and time-consuming investigations by hospital infection control personnel. In summary, precision infection control methods incorporating WGS can enable rapid rule-out of suspected Rhizopus hospital outbreaks and can complement traditional epidemiologic tools.

Data availability

The Rhizopus genome sequences associated with this study are publicly available under NCBI BioProject ID PRJNA905128.

Acknowledgments

We thank the members of the UCSF Health Hospital Epidemiology and Infection Prevention team as well as the professional microbiologists at UCSF clinical laboratories.

Financial support

Funding for this study was provided by the Chan Zuckerberg Biohub and the National Heart, Lung, and Blood Institute.

Competing interest

All authors report no conflicts of interest relevant to this article.

Footnotes

a

Authors of equal contribution.

References

Hartnett, KP, Jackson, BR, Perkins, KM, et al. A guide to investigating suspected outbreaks of mucormycosis in healthcare. J Fungi 2019;5:69.10.3390/jof5030069CrossRefGoogle ScholarPubMed
Crawford, E, Kamm, J, Millert, S, al. Investigating transfusion-related sepsis using culture-independent metagenomic sequencing. Clin Infect Dis 2022;71:11791185.10.1093/cid/ciz960CrossRefGoogle Scholar
Ramesh, A, Nakielny, S, Hsu, J, et al. Metagenomic next-generation sequencing of samples from pediatric febrile illness in Tororo, Uganda. PLoS One 2019;14:e0218318.10.1371/journal.pone.0218318CrossRefGoogle ScholarPubMed
Kamm, J. SPID: SNP pipeline for infectious disease. Github website. https://github.com/czbiohub/Spid.jl/blob/master/Readme.md. Published 2020. Accessed April 25, 2023.Google Scholar
Kozlov, AM, Darriba, D, Flouri, T, Morel, B, Stamatakis, A. RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference. Bioinformatics 2019;35:44534455.10.1093/bioinformatics/btz305CrossRefGoogle ScholarPubMed
Garcia-Hermoso, D, Criscuolo, A, Lee, SC, et al. Outbreak of invasive wound mucormycosis in a burn unit due to multiple strains of Mucor circinelloides f. circinelloides resolved by whole-genome sequencing. mBio 2018;9:e0057318.10.1128/mBio.00573-18CrossRefGoogle Scholar
Bowers, JR, Monroy-Nieto, J, Gade, L, et al. Rhizopus microsporus infections associated with surgical procedures, Argentina, 2006–2014. Emerg Infect Dis 2020;26:937944.10.3201/eid2605.191045CrossRefGoogle ScholarPubMed
Bagal, UR, Ireland, M, Gross, A, et al. Molecular epidemiology of Blastomyces gilchristii clusters, Minnesota, USA. Emerg Infect Dis 2022;28:19241926.10.3201/eid2809.220392CrossRefGoogle ScholarPubMed
Llata, E, Blossom, DB, Khoury, HJ, et al. A cluster of mucormycosis infections in hematology patients: challenges in investigation and control of invasive mold infections in high-risk patient populations. Diagn Microbiol Infect Dis 2011;71:7280.10.1016/j.diagmicrobio.2010.12.022CrossRefGoogle Scholar
Figure 0

Table 1. Demographic, Microbiologic, and Sequencing Data for Two Clusters of Patients With Mucormycosis

Figure 1

Figure 1. (A) Maximum likelihood phylogenetic tree of all 5 patients from Rhizopus clusters A and B, based on whole-genome sequencing (WGS), created with RAxML. An historical control (HCtrl) R. microsporus isolate was also included. Scale bar represents 1 SNP/kb. (B) Heatmap demonstrating WGS-derived single-nucleotide polymorphism (SNP) distances between isolates. (C) Heatmap demonstrating ITS1-derived SNP distances between isolates, with a R. oryzae ITS1 reference.