key: cord-312602-855n5av1
authors: Chen, Min; Hong, Nan; Hu, Shan; Wang, Peng; Guan, HongZhi; Xiao, Meng; Zhu, Xinlin; Al-Hatmi, Abdullah M.S.; Zhou, Zhe; Gao, Lei; Boekhout, Teun; Xu, Jianping; Xu, Yingchun; Liao, Wanqing; Yang, Ying
title: Molecular identification of Cryptococcus gattii from cerebrospinal fluid using single-cell sequencing: a case study
date: 2020-06-23
journal: J Infect
DOI: 10.1016/j.jinf.2020.06.040
sha: 
doc_id: 312602
cord_uid: 855n5av1

A 31-year-old man presented with cryptococcal meningitis (CM) without typical clinical characteristics, but with abnormal walking, difficult leg lifting and frequent falling. He was admitted to a hospital in Beijing for two months and then transferred to Peking Union Medical College Hospital. After multiple tests failed to identify the pathogen, single-cell sequencing (scS) was used to test the cerebrospinal fluid (CSF). Comparing the sequence obtained from single-cell sequencing with the reference database, it was found that the infection was caused by Cryptococcus gattii sensu stricto (AFLP4/VGI genotype). Cryptococcus is difficult to cultivate from complex body fluids. The etiological agent of this patient was identified and the patient was treated. This case is the first case in which scS was used to detect and identify fungal pathogen after conventional testing failed to identify the cause of the disease. This report demonstrates that the scS approach can be used to generate fungal genome sequences directly from the CSF of a CM patient. The scS technology could become a powerful tool to precise detect microscopically visible but uncultured pathogens in clinical samples.

The etiological agent of this patient was identified and the patient was treated. This case is the first case in which scS was used to detect and identify fungal pathogen after conventional testing failed to identify the cause of the disease. This report demonstrates that the scS approach can be used to generate fungal genome sequences directly from the CSF of a CM patient. The scS technology could become a powerful tool to precise detect microscopically visible but uncultured pathogens in clinical samples. infection is crucial for targeted treatment and patient survival [1, 2] . A considerable proportion of the etiologic agents of CNS-related mycoses remains unidentified [3, 4] .

Cryptococcal meningitis (CM) is a life-threatening fungal infection associated with the human central nervous system (CNS), which is mainly caused by yeasts of the basidiomycetous genus Cryptococcus, particularly species that belong to the Cryptococcus neoformans and Cryptococcus gattii complexes [5] . The taxonomy and nomenclature of C. neoformans and C. gattii species complexes have undergone several changes and remain a subject of controversy [6] .

Compared to the high incidence rate of CM caused by C. neoformans sensu stricto, the incidence of the C. gattii complex is significantly less at a global level, but can be found more frequently in specific geographic or climatic zones [7, 8] . The five genotype groups within C. gattii sensu lato identified based on their amplified fragment length polymorphism (AFLP) banding patterns were proposed as five separate species, including C. gattii (genotype AFLP4/VGI), C. bacillisporus (genotype AFLP5/VGIII), C.

deuterogattii (genotype AFLP6/VGII), C. tetragattii (genotype AFLP7/VGIV), and C. decagattii (genotype AFLP10/VGIV) [9, 10] . Isolates of C. gattii s.s. and C. deuterogattii are the most frequently encountered globally, whereas C. bacillisporus and C. decagattii are mostly reported from the American continents, and C. tetragattii and VGV isolates of C. gattii seem to be restricted to southern Africa and India, respectively [7, 8, 11] .

Clinical symptoms and radiological signs of CM are notoriously non-specific, variable, and often absent [12] . Laboratory assays, such as Indian Ink staining and cryptococcal antigen (Cr-Ag) detection fulfill an important role for the diagnosis of CM in clinics worldwide [13] . However, these conventional diagnostic assays are generally used to target the cryptococcal capsule. This can be problematic if CM is caused by capsule-deficient Cryptococcus isolates [13] [14] [15] . Furthermore, the overwhelming majority of conventional assays on CM without pure cultures cannot distinguish members of the C. neoformans/C. gattii species complexes. As a result, proper treatments against C. gattii sensu lato may not be achieved [8, 16] .

Routine molecular methods, such as multiple PCR-based assays, have not shown advantages when compared to Cr-Ag detection to diagnose CM [17] . Recently, nextgeneration sequencing (NGS) of CSF has been shown some potential advantages over traditional methods to identify culture-negative organisms among patients with CNS infections [3, 18] . However, the effectiveness of NGS for identification of fungal pathogens can be challenging. Because fungi have hard cell walls different from other pathogens, making it difficult to extract their DNA from small quantities of complex clinical specimens. This is especially the case when there are questions related to whether the identified microbe represents a true pathogen or a contaminant. In addition, NGS data require appropriately trained personnel to interpret the results [18] .

Although the majority of human fungal pathogens are culturable, clinical specimens often contain visible spores or hyphae, but may fail to yield viable cultures in many clinical cases [19] . Thus, molecular identification of visible spores or hyphae from clinical specimens, such as CSF, can provide critical information for a reliable diagnosis of CNS-related mycoses. Notably, single-cell sequencing (scS) recently has been shown to be a powerful approach for exploring biological systems with unprecedented resolution.

For example, the scS technology has been successfully used to do pre-implantation genetic diagnosis and analysis of circulating tumor cells [20] . Moreover, scS technology was used to analyze the convalescent patients' B cells and identify potent neutralizing antibodies against SARS-CoV-2 during the COVID-19 pandemic in 2020 [21] . This is helpful for prescribing specific targeted therapy on diseases. Although scS has demonstrated a broad potential, it has seldomly applied to detect pathogens. As mentioned above, due to the hard fungal cell wall, it is typically more difficult to extracted DNA from a small number of pathogen cells than the mammalian cells associated with clinical specimens. Here, we firstly used scS and laser dissection technology to directly identify C. gattii from CSF from a CM patient with atypical clinical characteristics.

An otherwise healthy 31-year-old man with a 1-month history of intermittent fever showed that the pathogen belonged to C. gattii sensu stricto. Because the patient could not tolerate side effects of AMB, the patient was treated with voriconazole (VOR, 400 mg/day) and 5-FC (6.0 g/day) for nearly 7 months when both CSF pleocytosis and head MRI examinations showed that the patient was recovered. The details of this case history are summarized in Figure 1 .

For scS, we first isolated the yeast cells from the CSF using laser microdissection. 

Approximately 40 μL of the reaction solution was added to the amplification reaction mixture (prepared according to the instruction as specified in the REPLI-g Single Cell kit), which consisted of the following: 9 μL of ddH 2 O, 29 μL of the REPLI-gsc Reaction Buffer REPLI-g, and 2 μL of the REPLI-g scDNA polymerase. Following incubation for 8 h at 30°C, REPLI-g DNA polymerase was inactivated by incubating at 

The trimming of reads and the removal of Illumina adapters were performed by Trimmomatic 0.36. The leading and trailing bases with a quality value below 5 were removed and a sliding window trimming was performed with a window size of 15 bp. An average quality value threshold of 4 and reads with length above 60 bp were kept for further analyses. After trimming and filtering, a total of 6,925,939 read pairs (94.95%, 6,925,939/7,294,295) fulfilled our criteria. The filtered reads were then assembled de novo using SPAdes 3.10.1 with metagenomic assembly mode and Kmers of 21, 33, and 55 were tested to achieve the best assembly effect [20] . The assembled contigs were then identified by Kraken2 [22] using a combined genome database of Archaea, Bacteria, Fungi, Homo sapiens (GRCh38.p13), Protozoa and Viruses. The assembly sequence has been submitted to the NCBI SAR database, with the accession number of SRX6952669.

We extracted the internal transcribed spacer (ITS) sequences from the obtained sequence and compared the ITS sequences with those present in GenBank. Our comparison showed that the yeast-like cells belonged to the human pathogenic The extracted sequences were concatenated by FASconCAT-G v1.0 [24] and further aligned by Mafft 7.271 [25] . A phylogenetic tree subsequently was constructed based on the alignment of the DNA obtained in this study. The 10 reference strains were analyzed using MEGA 7.0.21 with the neighbor joining (NJ) method with 1000 bootstraps [26] .

A total of 12,384 contigs with a contig N50 of 1151bp were obtained by SPAdes using Kmer of 55. This has a better assembly effect than when using the Kmers of 21 and Table S1 . The complete Kraken identification results are shown in Table S2 .

A total of 2,963 contigs in our assembly were found to have consistent matches with the 10 reference strain genomes. These contigs were further used to construct the phylogenetic tree. The 2,963 contigs accounted for 70.3% (3,004,566 bp / 4,274,048 bp) of the 4,575 contigs identified by Kraken2 as C. gatti sensu stricto. The phylogenetic analysis revealed that the yeast-like cells in this patient belonged to the genotype AFLP4/VGI of the C. gattii species complex, closely related to C. gattii sensu stricto.

strain E566 (Figure 2 ). Following this deduction, we could identify the suspected pathogenic isolate as C. gattii sensu stricto with a high level of confidence. As mentioned above, the routine clinical diagnostic tests of our CSF samples obtained initially from this patient failed to identify the etiological agent responsible for his condition. In contrast, scS in combination with a bioinformatics pipeline allowed us to confirm that the infection was caused by C. gattii sensu stricto which equals the the AFLP4/VGI genotype.

Compared to CM caused by C. neoformans sensu stricto, CM caused by C. gattii sensu lato is often associated with cerebral cryptococomma [27] and elevated CSF opening pressure [28, 29] . However, our case did not exhibit these clinical characteristics Notably, the scS technology in our study effectively and accurately generated enough sequence reads to facilitate direct detection and phylogenetic analysis of the cells of C. gattii sensu stricto in clinical CSF samples. The majority (approximately 82%) of the classified contigs (n=5,644) in our study were identified as fungi (81.73%, 4,438/5,644). Among all the classified contigs, 4438 of them were identified as C. gattii sensu stricto. This accounted for approximately 83% of the total length of the classified contigs (83.23%, 4,274,048 bp/5,135,098 bp). In our opinion, the scS technology is more effective than routine metagenome sequencing for identifying unexpected pathogens in clinical specimens. This is particularly true for the biopsy containing microscopically visible cells that fail to grow viable colonies onto standard laboratory media. One key reason is that the laser microdissection and scS technologies allow the end users to isolate and analyze individual pathogen cells directly from the clinical samples. In contrast, metagenome sequencing only yields a small fraction of the obtained sequences from the putative pathogen, with the majority sequences coming from the host cells.

We successfully isolated ample target cells following Indian ink staining using laser capture microdissection (LCM) [30, 31] . This provided the basis for us to successfully extract cryptococcal genomic DNA from the CSF and generate a genomic DNA library using a combination of snail enzyme, lysozyme and the REPLI-g Single Cell kit. In our opinion, the present study clearly provides a suitable basis to make additional refinements for extraction of fungal DNA from other clinical sample types. This will allow molecular identification of the etiologic agents of CNS-related and other invasive mycoses.

Efficient methods for the extraction of fungal DNA from clinical specimens are urgently required for pathogen detection using molecular assays [32] .

The generated sequence reads facilitated our phylogenetic analyses to identify the targeted yeast cells as a specific lineage of C. gattii sensu lato. These were derived from the genotype AFLP4/VGI representing C. gattii sensu stricto, which is the primary DNA of C. gattii sensu stricto in our study showed a close phylogenetic relationship with that of strain E566 originating from Australia. This suggests that VGI isolates from China have a close genetic relationship with those from Australia [33, 34] . The environmental source of them could be related to wood production and the introduction of foreign tree species, such as Eucalyptus species, into China from Australia [35, 36] .

In summary, using a scS approach, we successfully identified a C. gattii sensu stricto strain that causes CNS infection. To our knowledge, this is the first time that this technology has been used to diagnose a case of CNS-related mycosis caused by pathogenic fungi that could not be cultured. After further optimization of clinical sample separation, the scS technology will have great potential to accurately identify the etiologic agents of CNS-related mycoses, as well as other disease-causing fungal pathogens. bootstraps test. One reference C. deneoformans strain JEC21 was used as outgroup.

Tab. S1: Spades assembling effect with different Kmers Tab. S2: Kraken identification report of all classified contigs Acknowledgements:

We thank Dr. Ferry Hagen (Westerdijk Fungal Biodiversity Institute

is the recipient of Major Infectious Diseases Such as AIDS and Viral Hepatitis Prevention and Control Technology Major Projects (2018ZX10712001 and 2018ZX10101003). M.C. is the recipient of National Natural Science Foundation of China

Neuroinfections caused by fungi

The spectrum of fungi that infects humans. Cold Spring Harbor perspectives in medicine

Actionable diagnosis of neuroleptospirosis by next-generation sequencing

Chronic Meningitis Investigated via Metagenomic Next-Generation Sequencing

Cryptococcus: from environmental saprophyte to global pathogen

Importance of Resolving Fungal Nomenclature: the Case of Multiple Pathogenic Species in the Cryptococcus Genus

Global Molecular Epidemiology of Cryptococcus neoformans and Cryptococcus gattii: An Atlas of the Molecular Types

Cryptococcus gattii infections

Recognition of seven species in the Cryptococcus gattii/Cryptococcus neoformans species complex. Fungal genetics and biology

A New Lineage of Cryptococcus gattii (VGV) Discovered in the Central Zambezian Miombo Woodlands

Autochthonous and dormant Cryptococcus gattii infections in Europe

Clinical practice guidelines for the management of cryptococcal disease: 2010 update by the infectious diseases society of america. Clinical infectious diseases : an official publication of the Infectious Diseases Society of

Evaluation of a newly developed lateral flow immunoassay for the diagnosis of cryptococcosis

Difficulty in diagnosing chronic meningitis caused by capsule-deficient Cryptococcus neoformans

False-negative cerebrospinal fluid cryptococcal latex agglutination tests for patients with culture-positive cryptococcal meningitis

Antifungal therapy and management of complications of cryptococcosis due to Cryptococcus gattii

Evaluation of five conventional and molecular approaches for diagnosis of cryptococcal meningitis in non-HIV-infected patients

Illuminating uveitis: metagenomic deep sequencing identifies common and rare pathogens

British Society for Medical Mycology best practice recommendations for the diagnosis of serious fungal diseases

SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing

Potent neutralizing antibodies against SARS-CoV-2 identified by high-throughput single-cell sequencing of convalescent patients' B cells

Kraken: ultrafast metagenomic sequence classification using exact alignments

BEDTools: The Swiss-Army Tool for Genome Feature Analysis

FASconCAT-G: extensive functions for multiple sequence alignment preparations concerning phylogenetic studies

MAFFT multiple sequence alignment software version 7: improvements in performance and usability

MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets

Cryptococcus gattii genotype VGIIa infection in man

Clinical and host differences between infections with the two varieties of Cryptococcus neoformans

Clinical manifestations of Cryptococcus gattii infection: determinants of neurological sequelae and death. Clinical infectious diseases : an official publication of the Infectious Diseases Society of

Future medical applications of single-cell sequencing in cancer

Laser microdissection of fungal septa as visualised by scanning electron microscopy. Fungal genetics and biology

Enhancing molecular approaches for diagnosis of fungal infections

Epidemiology of fungal infections in China

Epidemiology of Cryptococcus and cryptococcosis in China. Fungal genetics and biology

Cryptococcus gattii infections in China: extent of the problem?

Taxonomic analysis of cryptococcus species complex strain S8012 revealed Cryptococcus gattii with high heterogeneity on the genetics

The authors declared that they have no conflicts of interest.
