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In silico ionomics segregates parasitic from free-living eukaryotes.

Greganova E, Steinmann M, Mäser P, Fankhauser N - Genome Biol Evol (2013)

Bottom Line: Concentrating on unicellular eukaryotes (n = 37), we demonstrate that clustering of species according to their repertoire of ion transporters segregates obligate endoparasites (n = 23) on the one hand, from free-living species and facultative parasites (n = 14) on the other hand.Random forest classification identifies transporters of ammonia, plus transporters of iron and other transition metals, as the most informative for distinguishing the obligate parasites.Thus, in silico ionomics further underscores the importance of iron in infection biology and suggests access to host sources of nitrogen and transition metals to be selective forces in the evolution of parasitism.

View Article: PubMed Central - PubMed

Affiliation: Swiss Tropical and Public Health Institute, Basel, Switzerland.

ABSTRACT
Ion transporters are fundamental to life. Due to their ancient origin and conservation in sequence, ion transporters are also particularly well suited for comparative genomics of distantly related species. Here, we perform genome-wide ion transporter profiling as a basis for comparative genomics of eukaryotes. From a given predicted proteome, we identify all bona fide ion channels, ion porters, and ion pumps. Concentrating on unicellular eukaryotes (n = 37), we demonstrate that clustering of species according to their repertoire of ion transporters segregates obligate endoparasites (n = 23) on the one hand, from free-living species and facultative parasites (n = 14) on the other hand. This surprising finding indicates strong convergent evolution of the parasites regarding the acquisition and homeostasis of inorganic ions. Random forest classification identifies transporters of ammonia, plus transporters of iron and other transition metals, as the most informative for distinguishing the obligate parasites. Thus, in silico ionomics further underscores the importance of iron in infection biology and suggests access to host sources of nitrogen and transition metals to be selective forces in the evolution of parasitism. This finding is in agreement with the phenomenon of iron withholding as a primordial antimicrobial strategy of infected mammals.

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Hierarchical clustering of ionomic landscapes segregates obligate parasites from eukaryotes with free-living life stages. The tree was produced with pvclust using Canberra distance and McQuitty’s similarity analysis. au are shown in gray, where P = (100 − au)/100.
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evt134-F4: Hierarchical clustering of ionomic landscapes segregates obligate parasites from eukaryotes with free-living life stages. The tree was produced with pvclust using Canberra distance and McQuitty’s similarity analysis. au are shown in gray, where P = (100 − au)/100.

Mentions: The above profile libraries were used to screen predicted proteomes with hmmscan. When counting the number of hits per profile (fig. 2), every protein in a given proteome was allowed to score only once, that is, with the profile against which it had the highest score. A cutoff E-value of <10−10 was used to call a hit. For clustering (fig. 4), a 65-tuple vector was constructed for each proteome which consisted of the respective best scores to each profile. Hierarchical clustering of these vectors was performed with the R library (R Core Team 2013) Pvclust which implements multiscale bootstrap resampling (n = 10,000) to estimate “approximately unbiased” (au) errors, where P = (100 − au)/100 (Suzuki and Shimodaira 2006). Distance metric (Canberra) and clustering algorithm (McQuitty) were chosen as to maximize the number of species in significant clusters (au ≥ 95).Fig. 2.—


In silico ionomics segregates parasitic from free-living eukaryotes.

Greganova E, Steinmann M, Mäser P, Fankhauser N - Genome Biol Evol (2013)

Hierarchical clustering of ionomic landscapes segregates obligate parasites from eukaryotes with free-living life stages. The tree was produced with pvclust using Canberra distance and McQuitty’s similarity analysis. au are shown in gray, where P = (100 − au)/100.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3814192&req=5

evt134-F4: Hierarchical clustering of ionomic landscapes segregates obligate parasites from eukaryotes with free-living life stages. The tree was produced with pvclust using Canberra distance and McQuitty’s similarity analysis. au are shown in gray, where P = (100 − au)/100.
Mentions: The above profile libraries were used to screen predicted proteomes with hmmscan. When counting the number of hits per profile (fig. 2), every protein in a given proteome was allowed to score only once, that is, with the profile against which it had the highest score. A cutoff E-value of <10−10 was used to call a hit. For clustering (fig. 4), a 65-tuple vector was constructed for each proteome which consisted of the respective best scores to each profile. Hierarchical clustering of these vectors was performed with the R library (R Core Team 2013) Pvclust which implements multiscale bootstrap resampling (n = 10,000) to estimate “approximately unbiased” (au) errors, where P = (100 − au)/100 (Suzuki and Shimodaira 2006). Distance metric (Canberra) and clustering algorithm (McQuitty) were chosen as to maximize the number of species in significant clusters (au ≥ 95).Fig. 2.—

Bottom Line: Concentrating on unicellular eukaryotes (n = 37), we demonstrate that clustering of species according to their repertoire of ion transporters segregates obligate endoparasites (n = 23) on the one hand, from free-living species and facultative parasites (n = 14) on the other hand.Random forest classification identifies transporters of ammonia, plus transporters of iron and other transition metals, as the most informative for distinguishing the obligate parasites.Thus, in silico ionomics further underscores the importance of iron in infection biology and suggests access to host sources of nitrogen and transition metals to be selective forces in the evolution of parasitism.

View Article: PubMed Central - PubMed

Affiliation: Swiss Tropical and Public Health Institute, Basel, Switzerland.

ABSTRACT
Ion transporters are fundamental to life. Due to their ancient origin and conservation in sequence, ion transporters are also particularly well suited for comparative genomics of distantly related species. Here, we perform genome-wide ion transporter profiling as a basis for comparative genomics of eukaryotes. From a given predicted proteome, we identify all bona fide ion channels, ion porters, and ion pumps. Concentrating on unicellular eukaryotes (n = 37), we demonstrate that clustering of species according to their repertoire of ion transporters segregates obligate endoparasites (n = 23) on the one hand, from free-living species and facultative parasites (n = 14) on the other hand. This surprising finding indicates strong convergent evolution of the parasites regarding the acquisition and homeostasis of inorganic ions. Random forest classification identifies transporters of ammonia, plus transporters of iron and other transition metals, as the most informative for distinguishing the obligate parasites. Thus, in silico ionomics further underscores the importance of iron in infection biology and suggests access to host sources of nitrogen and transition metals to be selective forces in the evolution of parasitism. This finding is in agreement with the phenomenon of iron withholding as a primordial antimicrobial strategy of infected mammals.

Show MeSH
Related in: MedlinePlus