Quantitative Proteomics in Yeast : From bSLIM and Proteome Discoverer Outputs to Graphical Assessment of the Significance of Protein Quantification Scores

Multi-omics analyses of choroid plexus carcinoma cell lines reveal potential targetable pathways and alterations

PURPOSE

Choroid plexus carcinomas (CPCs) are extremely rare brain tumors and carry a dismal prognosis. Treatment options are limited and there is an urgent need to develop models to further research. In the present study, we established two CPC cell lines and performed multi-omics analyses. These cell lines serve as valuable models to propose new treatments in these rare but deadly brain tumors.

METHODS

Multi-omic profiling including, (i) methylation array (EPIC 850 K), (ii) whole genome sequencing (WGS), (iii) CANCERPLEX cancer genome panel testing, (iv) RNA sequencing (RNA-seq), and (v) proteomics analyses were performed in CCHE-45 and NGT131 cell lines.

RESULTS

Both cell lines were classified as methylation class B. Both harbored pathogenic TP53 point mutations; CCHE-45 additionally displayed TP53 loss. Furthermore, alterations of the NOTCH and WNT pathways were also detected in both cell lines. Two protein-coding gene fusions, BZW2-URGCP, and CTTNBP2-ERBB4, mutations of two oncodrivers, GBP-4 and KRTAP-12-2, and several copy number alterations were observed in CCHE-45, but not NGT131. Transcriptome and proteome analysis identified shared and unique signatures, suggesting that variability in choroid plexus carcinoma tumors may exist. The discovered difference's importance and implications highlight the possible diversity of choroid plexus carcinoma and call for additional research to fully understand disease pathogenesis.

CONCLUSION

Multi-omics analyses revealed that the two choroid plexus carcinoma cell lines shared TP53 mutations and other common pathway alterations and activation of NOTCH and WNT pathways. Noticeable differences were also observed. These cell lines can serve as valuable models to propose new treatments in these rare but deadly brain tumors.

3D models of fungal chromosomes to enhance visual integration of omics data

The functions of eukaryotic chromosomes and their spatial architecture in the nucleus are reciprocally dependent. Hi-C experiments are routinely used to study chromosome 3D organization by probing chromatin interactions. Standard representation of the data has relied on contact maps that show the frequency of interactions between parts of the genome. In parallel, it has become easier to build 3D models of the entire genome based on the same Hi-C data, and thus benefit from the methodology and visualization tools developed for structural biology. 3D modeling of entire genomes leverages the understanding of their spatial organization. However, this opportunity for original and insightful modeling is underexploited. In this paper, we show how seeing the spatial organization of chromosomes can bring new perspectives to omics data integration. We assembled state-of-the-art tools into a workflow that goes from Hi-C raw data to fully annotated 3D models and we re-analysed public omics datasets available for three fungal species. Besides the well-described properties of the spatial organization of their chromosomes (Rabl conformation, hypercoiling and chromosome territories), our results highlighted (i) in Saccharomyces cerevisiae, the backbones of the cohesin anchor regions, which were aligned all along the chromosomes, (ii) in Schizosaccharomyces pombe, the oscillations of the coiling of chromosome arms throughout the cell cycle and (iii) in Neurospora crassa, the massive relocalization of histone marks in mutants of heterochromatin regulators. 3D modeling of the chromosomes brings new opportunities for visual integration of omics data. This holistic perspective supports intuition and lays the foundation for building new concepts.

Extending the Range of SLIM-Labeling Applications: From Human Cell Lines in Culture to Caenorhabditis elegans Whole-Organism Labeling

The simple light isotope metabolic-labeling technique relies on the in vivo biosynthesis of amino acids from U-[¹²C]-labeled molecules provided as the sole carbon source. The incorporation of the resulting U-[¹²C]-amino acids into proteins presents several key advantages for mass-spectrometry-based proteomics analysis, as it results in more intense monoisotopic ions, with a better signal-to-noise ratio in bottom-up analysis. In our initial studies, we developed the simple light isotope metabolic (SLIM)-labeling strategy using prototrophic eukaryotic microorganisms, the yeasts Candida albicans and Saccharomyces cerevisiae, as well as strains with genetic markers that lead to amino-acid auxotrophy. To extend the range of SLIM-labeling applications, we evaluated (i) the incorporation of U-[¹²C]-glucose into proteins of human cells grown in a complex RPMI-based medium containing the labeled molecule, considering that human cell lines require a large number of essential amino-acids to support their growth, and (ii) an indirect labeling strategy in which the nematode Caenorhabditis elegans grown on plates was fed U-[¹²C]-labeled bacteria (Escherichia coli) and the worm proteome analyzed for ¹²C incorporation into proteins. In both cases, we were able to demonstrate efficient incorporation of ¹²C into the newly synthesized proteins, opening the way for original approaches in quantitative proteomics.