PO.MCB09.04 · 分子与细胞生物学

Integrated metabolic and cell-health profiling as a framework for defining cellular state

海报缩略图:Integrated metabolic and cell-health profiling as a framework for defining cellular state
编号 3271 展板 3 时间 4/20 02:00–05:00 区域 Section 23 主讲 Kayla Sylvester, BS;PhD
分会场 Metabolic Studies in Brain, Pediatric, and Hematologic Cancers
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作者与单位

Kayla Sylvester, Anthony C. Lauer, Gediminas Vidugiris, Donna Leippe, Jolanta Vidugiriene

Promega, Madison, WI

摘要 Abstract

Defining cellular state requires understanding how multiple metabolic features change together, yet most assays capture only single parameters. We developed an integrated bioluminescent profiling strategy that measures coordinated metabolic and cell-health indicators from the same low-input sample, providing a practical way to resolve early pathway activity and cellular condition across immune and cancer systems. The approach uses a suite of luminescent assays to quantify ATP, NAD, total NADP(H), metabolic activity, and nutrient utilization including glucose consumption, lactate secretion, and malate accumulation. Together, these features report on glycolytic engagement, mitochondrial contribution, and redox balance, generating compact multiparametric profiles not achievable with isolated assays. In primary T cells, the integrated profiles distinguished early glycolytic, NAD-rich states linked to rapid expansion from more oxidative states associated with memory-biased phenotypes. These early metabolic patterns emerged within the first 72 hours of activation and aligned with later differences in proliferation and T cell-subset composition, demonstrating that early metabolic signatures capture functional trajectories beyond initial activation markers. In cancer-cell models, the same measurements resolved nutrient-dependent shifts in metabolic balance and stress adaptation, illustrating how environmental composition shapes pathway use and overall cellular fitness. The workflow uses standard luminescent instrumentation, minimal material, and is adaptable to additional metabolic markers as the platform evolves. By capturing coordinated metabolic and cell-health features within a scalable framework, this approach provides a practical way to define cellular state and relate early metabolic patterns to later functional behavior across diverse experimental contexts.
利益披露 Disclosure
K. Sylvester, None.. A. C. Lauer, None.. G. Vidugiris, None.. D. Leippe, None.. J. Vidugiriene, None.

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