An Insight into the Genome of Pathogenic and Non-Pathogenic IAcanthamoeba/I

• Published in: Pathogens (Basel) 2022-12, Vol.11 (12)
• Main Authors: Sharma, Chayan, Khurana, Sumeeta, Arora, Amit, Bhatia, Alka, Gupta, Amit
• Format: Article
• Language: English
• Subjects: Analysis; Care and treatment; Control; Diagnosis; Encephalitis; Identification and classification; Keratitis; Protozoa; RNA sequencing; Virulence (Microbiology)
• ISSN: 2076-0817; 2076-0817
• DOI: 10.3390/pathogens11121558

Background: Acanthamoeba are amphizoic amoeba majorly responsible for causing Acanthamoeba keratitis (AK) and Granulomatous amoebic encephalitis (GAE). Despite its ubiquitous nature, the frequency of infections is not high, probably due to the existence of non-pathogenic isolates. The whole-genome sequencing and an annotated genome assembly can unravel the biological functions and help in identifying probable genes related to pathogenicity. Methods: Illumina and Nanopore sequencing were performed for keratitis, encephalitis, and non-pathogenic environmental isolates. Hybrid assembly was prepared for the AK and GAE isolates, while only the Illumina reads were utilized for a non-pathogenic environmental isolate. Protein coding genes were identified using the GeneMark-ES program and BLASTx module of Diamond used for gene prediction. Additionally, the Kyoto Encyclopedia of Genes and Genomes annotation and cluster of orthologous group’s annotation using RPS-blast against the CDD database was performed. The subsequent data analysis and validation will help identify probable pathogenic genes. Results: The genome assemblies of 9.67, 8.34, and 8.89 GBs were reported for GAE, AK, and non-pathogenic isolate, respectively. KEGG reported 22,946 in GAE, 24,231 in keratitis, and 9367 genes in the environmental isolate. The COG annotation revealed 3232 in GAE, 3403 in keratitis, and 1314 genes in the non-pathogenic isolate. Conclusion: The present study has attempted to generate de novo hybrid genome assemblies of Acanthamoeba that would help decode the genome of free-living amoeba and will provide genomic data for a better understanding of virulence-related factors.