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Species, Sequence Types and Alleles: Dissecting Genetic Variation in Acanthamoeba.

Paul A FuerstGregory C Booton
Published in: Pathogens (Basel, Switzerland) (2020)
Species designations within Acanthamoeba are problematic because of pleomorphic morphology. Molecular approaches, including DNA sequencing, hinted at a resolution that has yet to be fully achieved. Alternative approaches were required. In 1996, the Byers/Fuerst lab introduced the concept of sequence types. Differences between isolates of Acanthamoeba could be quantitatively assessed by comparing sequences of the nuclear 18S rRNA gene, ultimately producing 22 sequence types, designated T1 through T22. The concept of sequence types helps our understanding of Acanthamoeba evolution. Nevertheless, substantial variation in the 18S rRNA gene differentiates many isolates within each sequence type. Because the majority of isolates with sequences in the international DNA databases have been studied for only a small segment of the gene, designated ASA.S1, genetic variation within this hypervariable region of the 18S rRNA gene has been scrutinized. In 2002, we first categorized variation in this region in a sample of T3 and T4 isolates from Hong Kong, observing ten "alleles" within type T4 and five "alleles" within T3. Subsequently, confusion occurred when different labs applied redundant numerical labels to identify different alleles. A more unified approach was required. We have tabulated alleles occurring in the sequences submitted to the international DNA databases, and determined their frequencies. Over 150 alleles have occurred more than once within 3500+ isolates of sequence type T4. Results from smaller samples of other sequence types (T3, T5, T11 and T15, and supergroup T2/6) have also been obtained. Our results provide new insights into the evolutionary history of Acanthamoeba, further illuminating the degree of genetic separation between significant taxonomic units within the genus, perhaps eventually elucidating what constitutes a species of Acanthamoeba.
Keyphrases
  • genetic diversity
  • genome wide
  • copy number
  • single molecule
  • circulating tumor
  • cell free
  • amino acid
  • gene expression
  • machine learning
  • dna methylation
  • big data
  • genome wide analysis