A divergent cyclin/cyclin-dependent kinase complex controls progression through the atypical replicative cycles during Plasmodium berghei gametogony

Cell-cycle transitions are generally triggered by variations in the activity of cyclin-dependent kinases (CDKs) bound to cyclins. Malaria-causing parasites have evolved unique cell-cycles with a repertoire of ancestral CDKs and cyclins whose functions and interdependency remain elusive. Here, we show that the divergent Plasmodium berghei CDK-related kinase 5 (CRK5), is a critical cell-cycle regulator of gametogony required for transmission to the mosquito. It phosphorylates canonical CDK motifs on components of the pre-replicative complex and is essential for DNA replication. We also provide evidence for indirect regulation of the concomitant progression through M-phase. Over a replicative cycle, CRK5 stably interacts with a single Plasmodium-specific cyclin (SOC2) with no evidence of SOC2 cycling through transcription, translation nor degradation. Our results present evidence that during Plasmodium gametogony, a unique and divergent cyclin/CDK pair evolved to fulfil the functional space of multiple eukaryotic cell-cycle kinases controlling S-phase entry and progression through M-phase. Overall design: Gametocytes (non-activated -0 min- and activated -15 min-) were collected from CRK5-KO and WT lines. Total RNA was isolated from purified parasites using an RNeasy purification kit (Qiagen). RNA was vacuum concentrated (SpeedVac) and transported using RNA stable tubes (Biomatrica). Strand-specific mRNA sequencing was performed from total RNA using TruSeq Stranded mRNA Sample Prep Kit LT (Illumina) according to the manufacturer's instructions. Briefly, polyA+ mRNA was purified from total RNA using oligo-dT dynabead selection. First strand cDNA was synthesised primed with random oligos followed by second strand synthesis where dUTPs were incorporated to achieve strand-specificity. The cDNA was adapter-ligated and the libraries amplified by PCR. Libraries were sequenced in an Illumina Hiseq machine with paired-end 100bp read chemistry. RNA-seq read alignments were mapped onto the P. berghei ANKA genome (May 2015 release in GeneDB—http://www.genedb.org/) using Tophat2 (version 2.0.13) with parameters “-library-type fr-firststrand–no-novel-juncs–r 60”. Transcript abundances were extracted as raw read counts using the Python script 'HTseq-count' (model type – union, http://www-huber.embl.de/users/anders/HTSeq/). Counts per million (cpm) values were obtained from count data and gene were filtered if they failed to achieve a cpm value of 1 in at least 30% of samples per condition. Library sizes were normalized by the TMM method using EdgeR software and further subjected to linear model analysis using the voom function in the limma package43. Differential expression analysis was performed using DESeq2 in R version 3.2.1. Genes with fold change greater than 2 and p-value less than 0.05 were considered as significantly differentially expressed. P. berghei GO terms (Gene Ontology) were downloaded from GeneDB (http://www.genedb.org/; May 2015 release) and gene ontology enrichment analysis was performed for the DEG lists using GOstats R package. All analyses and visualizations were done with R packages- cummeRbund and ggplot2.