Application of the omics sciences to the study of Naegleria fowleri, Acanthamoeba spp., and Balamuthia mandrillaris: current status and future projections.
Libia Zulema Rodriguez-AnayaÁngel Josué Félix-SastréFernando Lares-VillaLuis Fernando Lares-JiménezJose Reyes Gonzalez-GalavizPublished in: Parasite (Paris, France) (2021)
In this review, we focus on the sequenced genomes of the pathogens Naegleria fowleri, Acanthamoeba spp. and Balamuthia mandrillaris, and the remarkable discoveries regarding the pathogenicity and genetic information of these organisms, using techniques related to the various omics branches like genomics, transcriptomics, and proteomics. Currently, novel data produced through comparative genomics analyses and both differential gene and protein expression in these free-living amoebas have allowed for breakthroughs to identify genes unique to N. fowleri, genes with active transcriptional activity, and their differential expression in conditions of modified virulence. Furthermore, orthologous genes of the various nuclear genomes within the Naegleria and Acanthamoeba genera have been clustered. The proteome of B. mandrillaris has been reconstructed through transcriptome data, and its mitochondrial genome structure has been thoroughly described with a unique characteristic that has come to light: a type I intron with the capacity of interrupting genes through its self-splicing ribozymes activity. With the integration of data derived from the diverse omic sciences, there is a potential approximation that reflects the molecular complexity required for the identification of virulence factors, as well as crucial information regarding the comprehension of the molecular mechanisms with which these interact. Altogether, these breakthroughs could contribute to radical advances in both the fields of therapy design and medical diagnosis in the foreseeable future.
Keyphrases
- genome wide
- single cell
- bioinformatics analysis
- genome wide identification
- dna methylation
- escherichia coli
- electronic health record
- rna seq
- pseudomonas aeruginosa
- copy number
- biofilm formation
- gene expression
- antimicrobial resistance
- big data
- staphylococcus aureus
- genome wide analysis
- transcription factor
- healthcare
- mass spectrometry
- stem cells
- health information
- oxidative stress
- gram negative
- data analysis
- machine learning
- risk assessment
- multidrug resistant
- drug induced
- genetic diversity