ABSTRACT
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 104 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.
ABSTRACT
MicroRNAs (miRNAs) can regulate nearly all biological processes and their dysregulation is implicated in various complex diseases and pathological conditions. Recent years have seen a growing number of functional studies of miRNAs using high-throughput experimental technologies, which have produced a large amount of high-quality data regarding miRNA target genes and their interactions with small molecules, long non-coding RNAs, epigenetic modifiers, disease associations, etc These rich sets of information have enabled the creation of comprehensive networks linking miRNAs with various biologically important entities to shed light on their collective functions and regulatory mechanisms. Here, we introduce miRNet, an easy-to-use web-based tool that offers statistical, visual and network-based approaches to help researchers understand miRNAs functions and regulatory mechanisms. The key features of miRNet include: (i) a comprehensive knowledge base integrating high-quality miRNA-target interaction data from 11 databases; (ii) support for differential expression analysis of data from microarray, RNA-seq and quantitative PCR; (iii) implementation of a flexible interface for data filtering, refinement and customization during network creation; (iv) a powerful fully featured network visualization system coupled with enrichment analysis. miRNet offers a comprehensive tool suite to enable statistical analysis and functional interpretation of various data generated from current miRNA studies. miRNet is freely available at http://www.mirnet.ca.