title: An orthology-based analysis of pathogenic protozoa impacting global health: an improved comparative genomics approach with prokaryotes and model eukaryote orthologs.
abstract: A key focus in 21(st) century integrative biology and drug discovery for neglected tropical and other diseases has been the use of BLAST-based computational methods for identification of orthologous groups in pathogenic organisms to discern orthologs, with a view to evaluate similarities and differences among species, and thus allow the transfer of annotation from known/curated proteins to new/non-annotated ones. We used here a profile-based sensitive methodology to identify distant homologs, coupled to the NCBI's COG (Unicellular orthologs) and KOG (Eukaryote orthologs), permitting us to perform comparative genomics analyses on five protozoan genomes. OrthoSearch was used in five protozoan proteomes showing that 3901 and 7473 orthologs can be identified by comparison with COG and KOG proteomes, respectively. The core protozoa proteome inferred was 418 Protozoa-COG orthologous groups and 704 Protozoa-KOG orthologous groups: (i) 31.58% (132/418) belongs to the category J (translation, ribosomal structure, and biogenesis), and 9.81% (41/418) to the category O (post-translational modification, protein turnover, chaperones) using COG; (ii) 21.45% (151/704) belongs to the categories J, and 13.92% (98/704) to the O using KOG. The phylogenomic analysis showed four well-supported clades for Eukarya, discriminating Multicellular [(i) human, fly, plant and worm] and Unicellular [(ii) yeast, (iii) fungi, and (iv) protozoa] species. These encouraging results attest to the usefulness of the profile-based methodology for comparative genomics to accelerate semi-automatic re-annotation, especially of the protozoan proteomes. This approach may also lend itself for applications in global health, for example, in the case of novel drug target discovery against pathogenic organisms previously considered difficult to research with traditional drug discovery tools.
authors: 1 Computational and Systems Biology Laboratory, Computational and Systems Biology Pole, Oswaldo Cruz Institute , Fiocruz, Brazil .
authors: Rafael R C
authors: RR
authors: Cuadrat
authors: Sérgio Manuel
authors: SM
authors: da Serra Cruz
authors: Diogo Antônio
authors: DA
authors: Tschoeke
authors: Edno
authors: E
authors: Silva
authors: Frederico
authors: F
authors: Tosta
authors: Henrique
authors: H
authors: Jucá
authors: Rodrigo
authors: R
authors: Jardim
authors: Maria Luiza M
authors: ML
authors: Campos
authors: Marta
authors: M
authors: Mattoso
authors: Alberto M R
authors: AM
authors: Dávila
mesh_terms: D001105:Archaea / Q000235:genetics; D001419:Bacteria / Q000235:genetics; D030562:Databases, Protein; D004748:Entamoeba histolytica / Q000235:genetics; D017125:Genes, Protozoan; D023281:Genomics; D014943:Global Health; D006801:Humans; D018320:Leishmania major / Q000235:genetics; D058977:Molecular Sequence Annotation; D010802:Phylogeny; D010963:Plasmodium falciparum / Q000235:genetics; D015800:Protozoan Proteins / Q000235:genetics*; D012689:Sequence Homology, Nucleic Acid; D014346:Trypanosoma brucei brucei / Q000235:genetics; D014349:Trypanosoma cruzi / Q000235:genetics
chemical_list: D015800:Protozoan Proteins