PfAP2Tel, harbouring a non-canonical DNA-binding AP2 domain, binds to Plasmodium falciparum telomeres.
Miguel Sierra-MirandaShruthi-Sridhar VembarDulce María DelgadilloPedro Antonio Ávila-LópezAbril Marcela Herrera-SolorioDaniela Lozano AmadoMiguel VargasRosaura Hernandez-RivasPublished in: Cellular microbiology (2017)
The telomeres of the malaria parasite Plasmodium falciparum are essential not only for chromosome end maintenance during blood stage development in humans but also to generate genetic diversity by facilitating homologous recombination of subtelomeric, multigene virulence families such as var and rifin. However, other than the telomerase PfTERT, proteins that act at P. falciparum telomeres are poorly characterised. To isolate components that bind to telomeres, we performed oligonucleotide pulldowns and electromobility shift assays with a telomeric DNA probe and identified a non-canonical member of the ApiAP2 family of transcription factors, PfAP2Tel (encoded by PF3D7_0622900), as a component of the P. falciparum telomere-binding protein complex. PfAP2Tel is expressed throughout the intra-erythrocytic life cycle and localises to the nuclear periphery, co-localising with telomeric clusters. Furthermore, EMSAs using the recombinant protein demonstrated direct binding of PfAP2Tel to telomeric repeats in vitro, while genome-wide chromatin immunoprecipitation followed by next generation sequencing corroborated the high specificity of this protein to telomeric ends of all 14 chromosomes in vivo. Taken together, our data describe a novel function for ApiAP2 proteins at chromosome ends and open new avenues to study the molecular machinery that regulates telomere function in P. falciparum.
Keyphrases
- plasmodium falciparum
- dna binding
- transcription factor
- binding protein
- dna damage response
- genome wide
- genetic diversity
- copy number
- dna repair
- life cycle
- dna damage
- circulating tumor
- escherichia coli
- dna methylation
- cell free
- protein protein
- gene expression
- single molecule
- pseudomonas aeruginosa
- amino acid
- staphylococcus aureus
- high throughput
- quantum dots
- machine learning
- biofilm formation
- small molecule
- deep learning
- artificial intelligence