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An improved staining method of cell cycle analysis with Sybr Green I for fungi: Cryptococcus neoformans and Saccharomyces cerevisiae.

ABSTRACT: Cryptococcus neoformans is a pathogenic fungus which causes millions of deaths and infections, especially threatening immunocompromised individuals. During the development of new drugs, the ubiquitination has been found to play an important role in the regulation of the virulence and cell cycle of this fungus. Based on this mechanism, ubiquitination-related mutant strains exhibiting cell cycle arrest have been established for drug development for the fungus. However, flow cytometry detection of the cell cycle in fungi is generally difficult because the thick cell wall and capsule of fungi generally contribute to a nonspecific signal of cytometry. In this study, an improved method, derived from Saccharomyces cerevisiae assays, is developed to specifically stain C. neoformans, in whose cell cycle the G1 and G2 peaks are separated enough to be allowed for cell cycle analysis. As a result, the improved method facilitates the detection of the alterations in the cell cycle of C. neoformans with a mutation that results in cell cycle arrest, which distinctly delays the cell division of C. neoformans. Thus, the improved method reported here provides detailed technical information regarding assays on C. neoformans and, more importantly, offers a solution for assessing the cell cycle in other fungi in the future. Abbreviation: PI: propidium iodide.

SUBMITTER: Gu Z

PROVIDER: S-EPMC7889188 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:DNA damage has been considered to be the universal critical lesion in cells after exposure to ionizing radiation. Measuring radiation-induced DNA damage is important to understand the mechanisms of radiation-induced toxicity and monitor DNA damage repairs. Currently the most widely used methods to measure DNA damage are pulsed-field gel electrophoresis (PFGF) and single-cell gel electrophoresis (also known as the comet assay), both of which are technically challenging and time consuming. Long range quantitative polymerase chain reaction (LR-QPCR) has been used successfully to measure nuclear and mitochondrial DNA damage in mammalian and several model organism cells. The principle of this assay is that DNA lesions will slow down or block the progression of DNA polymerase. Therefore, the amplification efficiency of DNA with fewer lesions will be higher than DNA with more lesions under the same reaction condition. Here, we developed the LR-QPCR assay primers and reaction conditions to quantify DNA damage in Cryptococcus neoformans (C. neoformans) and Saccharomyces cerevisiae (S. cerevisiae) after gamma ray exposure. Under these conditions, long DNA targets of C. neoformans H99 and S. cerevisiae BY4741 (17.6 and 16.4 kb for nuclear DNA and 15.3 and 14.6 kb for mitochondrial DNA) were quantitatively amplified using extracted DNA templates, respectively. Two short mitochondrial DNA targets of these two species (207 bp and 154 bp) were also quantitatively amplified and used to monitor the number of mitochondria. Using the LR-QPCR method, we showed that the frequency of radiation-induced mitochondrial and nuclear DNA lesions had a significant linear correlation with the radiation doses (from 500 Gy to 3000 Gy) in both species. Furthermore, the faster disappearance of DNA damage detected in C. neoformans H99S strain compared to H99 strain may help to explain the different radiation sensitivity of these two strains. In summary, we developed a simple, sensitive method to measure radiation-induced DNA damage, which can greatly facilitate the study of radiation-induced toxicity and can be widely used as a dosimetry in radiation-induced cell damage.

Project description:UnlabelledThe fungal pathogen Cryptococcus neoformans has several virulence factors, among which the most important is a polysaccharide capsule. The size of the capsule is variable and can increase significantly during infection. In this work, we investigated the relationship between capsular enlargement and the cell cycle. Capsule growth occurred primarily during the G1 phase. Real-time visualization of capsule growth demonstrated that this process occurred before the appearance of the bud and that capsule growth arrested during budding. Benomyl, which arrests the cells in G2/M, inhibited capsule growth, while sirolimus (rapamycin) addition, which induces G1 arrest, resulted in cells with larger capsule. Furthermore, we have characterized a mutant strain that lacks a putative G1/S cyclin. This mutant showed an increased capacity to enlarge the capsule, both in vivo (using Galleria mellonella as the host model) and in vitro. In the absence of Cln1, there was a significant increase in the production of extracellular vesicles. Proteomic assays suggest that in the cln1 mutant strain, there is an upregulation of the glyoxylate acid cycle. Besides, this cyclin mutant is avirulent at 37°C, which correlates with growth defects at this temperature in rich medium. In addition, the cln1 mutant showed lower intracellular replication rates in murine macrophages. We conclude that cell cycle regulatory elements are involved in the modulation of the expression of the main virulence factor in C. neoformans.ImportanceCryptococcus neoformans is a pathogenic fungus that has significant incidence worldwide. Its main virulence factor is a polysaccharide capsule that can increase in size during infection. In this work, we demonstrate that this process occurs in a specific phase of the cell cycle, in particular, in G1. In agreement, mutants that have an abnormal longer G1 phase show larger capsule sizes. We believe that our findings are relevant because they provide a link between capsule growth, cell cycle progression, and virulence in C. neoformans that reveals new aspects about the pathogenicity of this fungus. Moreover, our findings indicate that cell cycle elements could be used as antifungal targets in C. neoformans by affecting both the growth of the cells and the expression of the main virulence factor of this pathogenic yeast.

Project description:BACKGROUND:Gene expression is regulated by DNA-binding transcription factors (TFs). Together with their target genes, these factors and their interactions collectively form a gene regulatory network (GRN), which is responsible for producing patterns of transcription, including cyclical processes such as genome replication and cell division. However, identifying how this network regulates the timing of these patterns, including important interactions and regulatory motifs, remains a challenging task. RESULTS:We employed four in vivo and in vitro regulatory data sets to investigate the regulatory basis of expression timing and phase-specific patterns cell-cycle expression in Saccharomyces cerevisiae. Specifically, we considered interactions based on direct binding between TF and target gene, indirect effects of TF deletion on gene expression, and computational inference. We found that the source of regulatory information significantly impacts the accuracy and completeness of recovering known cell-cycle expressed genes. The best approach involved combining TF-target and TF-TF interactions features from multiple datasets in a single model. In addition, TFs important to multiple phases of cell-cycle expression also have the greatest impact on individual phases. Important TFs regulating a cell-cycle phase also tend to form modules in the GRN, including two sub-modules composed entirely of unannotated cell-cycle regulators (STE12-TEC1 and RAP1-HAP1-MSN4). CONCLUSION:Our findings illustrate the importance of integrating both multiple omics data and regulatory motifs in order to understand the significance regulatory interactions involved in timing gene expression. This integrated approached allowed us to recover both known cell-cycles interactions and the overall pattern of phase-specific expression across the cell-cycle better than any single data set. Likewise, by looking at regulatory motifs in the form of TF-TF interactions, we identified sets of TFs whose co-regulation of target genes was important for cell-cycle expression, even when regulation by individual TFs was not. Overall, this demonstrates the power of integrating multiple data sets and models of interaction in order to understand the regulatory basis of established biological processes and their associated gene regulatory networks.

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An improved staining method of cell cycle analysis with Sybr Green I for fungi: Cryptococcus neoformans and Saccharomyces cerevisiae.

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