Casein kinase 2 complex: a central regulator of multiple pathobiological signaling pathways in Cryptococcus neoformans
Casein kinase 2 (CK2) is a potential therapeutic target for several human diseases due to its crucial roles in growth, differentiation, and metabolic homeostasis. This study delves into the role of the CK2 complex in Cryptococcus neoformans, a key fungal pathogen causing meningitis. In C. neoformans, the CK2 complex is made up of a main catalytic subunit (Cka1) and two regulatory subunits (Ckb1 and Ckb2). The primary role of Cka1 is as a protein kinase, while Ckb1/2 assist in various cellular functions. Triple mutants without all three subunits exhibited more pronounced defects than mutants lacking only Cka1, hinting at potential independent functions of Ckb1/2. In animal studies, mutants without these subunits showed a sharp decline in virulence. Moreover, CK2 disruption affected many effector proteins and disrupted key signaling pathways crucial for the pathogenicity of C. neoformans. Overall, the findings highlight the importance of the CK2 complex in fungal biology and its potential as a target for new antifungal treatments. Overall design: The wild-type, cka1?, and ckb1? ckb2? cka1? strains were first cultured overnight at 30°C and then transferred to fresh YPD medium until they reached an OD600 of 0.8. Cells were collected, flash-frozen, and lyophilized. Total RNA was extracted using Easy-BLUE (17061, iNtRON, South Korea) and further purified with an RNeasy minikit (74106, Qiagen, Germany). This process was repeated for three independent cultures of each strain. Using 1 ?g of total RNA, cDNA libraries were prepared with the TruSeq mRNA library kit (Illumina, USA) and sequenced on an Illumina platform.  Post-sequencing, reads were processed to remove adaptor and low-quality sequences using Cutadpat v2.4 with Python 3.7.4 with adapter sequence (64). The reads were processed as previously described (65) and aligned to the C. neoformans H99 reference genome using Hisat2 v2.2.1 and the Hisat and Bowtie2 algorithm. Annotation data were obtained from the NCBI FTP server. The “-p 30” and “—dta -1” options, along with other default settings, were used to run Hisat2. Aligned reads were converted and sorted using Samtools v0.1.19 with default parameters except for the “-Sb -@ 8” option for converting and the “-@ 20 –m 2000000000” option for sorting (66). The “-p 12” option was used by Stringtie v1.3.6 to perform transcript assembly and abundance estimation. Transcript abundance was quantified using FPKM (Fragments Per Kilobase of Exon per Million Fragments Mapped) values (66). Data matrices were generated and analyzed using the R package “isoformswitchanalyzerR”. Quality control was assessed through DEBrowser (67). The analysis of differentially expressed genes (DEGs) was conducted with DESeq2 v1.24 (68, 69), and results were visualized using the Enhanced Volcano package in R v4.1.0 (70), with a cutoff of more than two-fold changes and a P-value of less than 0.05.