In:
Genome Research, Cold Spring Harbor Laboratory, Vol. 28, No. 9 ( 2018-09), p. 1383-1394
Kurzfassung:
African trypanosomes are vector-borne hemoparasites of humans and animals. In the mammal, parasites evade the immune response through antigenic variation. Periodic switching of the variant surface glycoprotein (VSG) coat covering their cell surface allows sequential expansion of serologically distinct parasite clones. Trypanosome genomes contain many hundreds of VSG genes, subject to rapid changes in nucleotide sequence, copy number, and chromosomal position. Thus, analyzing, or even quantifying, VSG diversity over space and time presents an enormous challenge to conventional techniques. Indeed, previous population genomic studies have overlooked this vital aspect of pathogen biology for lack of analytical tools. Here we present a method for analyzing population-scale VSG diversity in Trypanosoma congolense from deep sequencing data. Previously, we suggested that T. congolense VSGs segregate into defined “phylotypes” that do not recombine. In our data set comprising 41 T. congolense genome sequences from across Africa, these phylotypes are universal and exhaustive. Screening sequence contigs with diagnostic protein motifs accurately quantifies relative phylotype frequencies, providing a metric of VSG diversity, called the “variant antigen profile.” We applied our metric to VSG expression in the tsetse fly, showing that certain, rare VSG phylotypes may be preferentially expressed in infective, metacyclic-stage parasites. Hence, variant antigen profiling accurately and rapidly determines the T. congolense VSG gene and transcript repertoire from sequence data, without need for manual curation or highly contiguous sequences. It offers a tractable approach to measuring VSG diversity across strains and during infections, which is imperative to understanding the host–parasite interaction at population and individual scales.
Materialart:
Online-Ressource
ISSN:
1088-9051
,
1549-5469
DOI:
10.1101/gr.234146.118
Sprache:
Englisch
Verlag:
Cold Spring Harbor Laboratory
Publikationsdatum:
2018
ZDB Id:
1483456-X
SSG:
12
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