Unravelling the pathobiological role of the fungal KEOPS complex in Cryptococcus neoformans

The kinase, putative endopeptidase and other peptides of small size (KEOPS) complex plays critical cellular functions in eukaryotes, but its pathobiological roles remains elusive in fungal pathogens. Here we comprehensively analyze the pathobiological functions of the KEOPS complex in fungal meningoencephalitis pathogen Cryptococcus neoformans. The cryptococcal KEOPS complex appears to have a linear arrangement of Pcc1-Kae1-Bud32-Cgi121, supported by physical interaction between Pcc1-Kae1, Kae1-Bud32, and Bud32-Cgi121, but does not have Gon7 ortholog, which is the part of the S. cerevisiae KEOPS complex. Deletion of PCC1, KAE1, and BUD32 causes severe growth defects with perturbed cell cycle control. C. neoformans strains grown overnight in YPD medium weretransferred to 50 mL of fresh YPD medium and incubated at 30°C until the OD600 reached 0.6. The cells were then harvested by centrifugation and lyophilized. Total RNAs were isolated by Easy-BLUE (iNtRON), treated with DNase I (Qiagen), and purified with RNeasy MiniElute clean up kit (Qiagen) following the manufacturer’s instruction. Cultured samples were prepared independently three times for each strain, the cDNA library was constructed with the 1 µg of total RNAs for each sample by Illumina TruSeq mRNA library kit (Illumina) and sequenced by Illumina platform. The adapter sequences were trimmed from the sequencing reads by using Cutadpat v3.4 with Python 3.7.4. (1). The reference genome sequence of Cryptococcus neoformans H99 and annotation data were downloaded from the NCBI ftp server. The reads were aligned to the Cryptococcus neoformans H99 genome sequence using Hisat2 v2.2.1 with the Hisat and Bowtie2 algorithm and processed as previously reported (2). Hisat2 was performed with “-p 30”and “– dta -1”option and other parameters set as default. Aligned reads were converted and then sorted by Samtools v1.9 (3) with “-Sb -@ 8”option for converting, and “-@ 20 –m 2000000000” option for sorting and the other parameters set as default. Transcript assembly and abundance estimation were performed using Stringtie v2.1.1 by using “-p 12” option, and also “-B” option to run the Ballgown analysis (4). Assembled transcripts were merged to single GTF file, and the relative transcript abundances were calculated via Fragments Per Kilobase ofexon per Million fragments mapped (FPKM). The FPKM and readcount matrix was generated by R package “isoformswitchanalyzerR” and analyzed by DESeq2. Differentially expressed genes (DEG) analysis was performed using DESeq2 v1.24.0 with default sets with the Ballgown. Volcano plot was illustrated by using R v4.1.0, with the cutoff (more than two-fold changes with p< 0.05).