Scholarlink

<p>Time-kill curve (TKC) experiments are widely used to assess antifungal activity against <i>Candida spp</i>. However, this method only quantifies fungi able to grow on agar plates, fails to capture real-time dynamic changes, and cannot distinguish individual cells from aggregates. Flow cytometry (FCM) enables instantaneous single-cell analysis and could overcome these limitations. The aim of this study was to develop a new FCM strategy to characterize subpopulations during TKC experiments. <i>C. auris</i> B11221 and <i>C. glabrata</i> ATCC MYA-2950 strains were used. TKC experiments were performed on YPD agar plates and by FCM using voriconazole, micafungin and amphotericin B. FCM analysis quantified and classified yeast cells based on CFDA-AM (carboxyfluorescein diacetate, acetoxymethyl ester), PI (propidium iodide) staining and morphological features. Post-antifungal effect of treatment, carry-over effect and medium effect were also assessed. Finally, aggregate formation and reversibility after treatment removal were evaluated. For fungicidal profiles, PI-negative counts were more consistent with colony forming unit counts than CFDA-AM-positive counts. The remaining discrepancies could be attributed to real-time measurement of FCM compared with the delayed response of agar-based methods. FCM detected aggregate formation following micafungin and voriconazole exposure in <i>C. auris</i>. Aggregation appeared reversible following treatment removal. FCM enabled real-time monitoring of antifungal dynamics and analysis of aggregates during TKC experiments.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Flow cytometry as a tool for real-time monitoring of antifungal activity and aggregation in Candida auris

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月26日

查看全文
  • Adrien Baillod,
  • Jonathan Clarhaut,
  • Jérémy Moreau,
  • Léa Morin,
  • Lucas Keomany,
  • Laure Prouvensier,
  • Julien Buyck,
  • Sandrine Marchand,
  • Kévin Brunet

摘要

Time-kill curve (TKC) experiments are widely used to assess antifungal activity against Candida spp. However, this method only quantifies fungi able to grow on agar plates, fails to capture real-time dynamic changes, and cannot distinguish individual cells from aggregates. Flow cytometry (FCM) enables instantaneous single-cell analysis and could overcome these limitations. The aim of this study was to develop a new FCM strategy to characterize subpopulations during TKC experiments. C. auris B11221 and C. glabrata ATCC MYA-2950 strains were used. TKC experiments were performed on YPD agar plates and by FCM using voriconazole, micafungin and amphotericin B. FCM analysis quantified and classified yeast cells based on CFDA-AM (carboxyfluorescein diacetate, acetoxymethyl ester), PI (propidium iodide) staining and morphological features. Post-antifungal effect of treatment, carry-over effect and medium effect were also assessed. Finally, aggregate formation and reversibility after treatment removal were evaluated. For fungicidal profiles, PI-negative counts were more consistent with colony forming unit counts than CFDA-AM-positive counts. The remaining discrepancies could be attributed to real-time measurement of FCM compared with the delayed response of agar-based methods. FCM detected aggregate formation following micafungin and voriconazole exposure in C. auris. Aggregation appeared reversible following treatment removal. FCM enabled real-time monitoring of antifungal dynamics and analysis of aggregates during TKC experiments.