Targeted NGS-Based Analysis of Pneumocystis jirovecii Reveals Novel Genotypes.
Dora PunganTaylor EddensKejing SongMeredith A LakeyNicolle S CrovettoSimran K AroraShahid HusainJay K KollsPublished in: Journal of fungi (Basel, Switzerland) (2022)
Pneumocystis jirovecii is an important etiological agent of pneumonia that is underdiagnosed due to the inability to culture the organism. The 2019 PERCH study identified Pneumocystis as the top fungal cause of pneumonia in HIV-negative children using a PCR cutoff of 10 4 copies of Pneumocystis per mL of sample in nasopharyngeal/oropharyngeal (NP/OP) specimens. Given that Pneumocystis consists of an environmental ascus form and a trophic from (the latter is the form that attaches to the lung epithelium), it is possible that life-form-specific molecular assays may be useful for diagnosis. However, to accomplish this goal, these assays require genotypic information, as the current fungal genomic data are largely from the US and Europe. To genotype Pneumocystis across the globe, we developed an NGS-based genotyping assay focused on genes expressed in asci as well as trophs using PERCH throat swabs from Africa, Bangladesh, and Thailand, as well as North American samples. The NGS panel reliably detected 21 fungal targets in these samples and revealed unique genotypes in genes expressed in trophs, including Meu10, an ascospore assembly gene; two in mitochondrial gene ATP8, and the intergenic region between COX1 and ATP8. This assay can be used for enhanced Pneumocystis epidemiology to study outbreaks but also permits more accurate RT-CPR- or CRISPR-based assays to be performed to improve the non-bronchoscopic diagnosis of this under-reported fungal pathogen.
Keyphrases
- genome wide
- high throughput
- copy number
- genome wide identification
- dna methylation
- young adults
- risk factors
- oxidative stress
- human immunodeficiency virus
- genome wide analysis
- crispr cas
- single cell
- gene expression
- antiretroviral therapy
- hiv positive
- high resolution
- mass spectrometry
- transcription factor
- drug delivery
- risk assessment
- machine learning
- hiv aids
- cancer therapy
- human health
- acute respiratory distress syndrome
- mechanical ventilation