Department of Chemistry, Texas A&M University , College Station, Texas 77843-3255, United States.
Biochemistry. 2013 Dec 31;52(52):9413-25. doi: 10.1021/bi4010304. Epub 2013 Dec 17.
Fermenting cells growing exponentially on rich (YPAD) medium underwent a transition to a slow-growing state as glucose levels declined and their metabolism shifted to respiration. During exponential growth, Fe import and cell-growth rates were matched, affording an approximately invariant cellular Fe concentration. During the transition period, the high-affinity Fe import rate declined slower than the cell-growth rate declined, causing Fe to accumulate, initially as Fe(III) oxyhydroxide nanoparticles but eventually as mitochondrial and vacuolar Fe. Once the cells had reached slow-growth mode, Fe import and cell-growth rates were again matched, and the cellular Fe concentration was again approximately invariant. Fermenting cells grown on minimal medium (MM) grew more slowly during the exponential phase and underwent a transition to a true stationary state as glucose levels declined. The Fe concentration of MM cells that just entered the stationary state was similar to that of YPAD cells, but MM cells continued to accumulate Fe in the stationary state. Fe initially accumulated as nanoparticles and high-spin Fe(II) species, but vacuolar Fe(III) also eventually accumulated. Surprisingly, Fe-packed 5-day-old MM cells suffered no more reactive oxygen species (ROS) damage than younger cells, suggesting that the Fe concentration alone does not accurately predict the extent of ROS damage. The mode and rate of growth at the time of harvesting dramatically affected cellular Fe content. A mathematical model of Fe metabolism in a growing cell was developed. The model included the import of Fe via a regulated high-affinity pathway and an unregulated low-affinity pathway. The import of Fe from the cytosol to vacuoles and mitochondria and nanoparticle formation were also included. The model captured essential trafficking behavior, demonstrating that cells regulate Fe import in accordance with their overall growth rate and that they misregulate Fe import when nanoparticles accumulate. The lack of regulation of Fe in yeast is perhaps unique compared to the tight regulation of other cellular metabolites. This phenomenon likely derives from the unique chemistry associated with Fe nanoparticle formation.
在丰富（YPAD）培养基中指数生长的发酵细胞随着葡萄糖水平的下降和代谢向呼吸转变，经历了向缓慢生长状态的转变。在指数生长期间，铁的摄取和细胞生长速度相匹配，使细胞内铁浓度保持大致不变。在转变期间，高亲和力铁摄取率的下降速度比细胞生长速度的下降速度慢，导致铁积累，最初是作为 Fe(III) 氧氢氧化物纳米颗粒，但最终是作为线粒体和液泡铁。一旦细胞进入缓慢生长模式，铁摄取和细胞生长速度再次匹配，细胞内铁浓度再次保持大致不变。在指数期，在最低培养基（MM）上生长的发酵细胞生长速度较慢，随着葡萄糖水平的下降，它们进入真正的静止状态。刚刚进入静止状态的 MM 细胞的铁浓度与 YPAD 细胞相似，但 MM 细胞在静止状态下仍在继续积累铁。铁最初作为纳米颗粒和高自旋 Fe(II) 物质积累，但最终液泡铁(III)也积累。令人惊讶的是，与年轻细胞相比，装满铁的 5 天龄 MM 细胞没有遭受更多的活性氧（ROS）损伤，这表明铁浓度本身并不能准确预测 ROS 损伤的程度。收获时的生长方式和速度对细胞内铁含量有显著影响。开发了一个用于生长细胞中铁代谢的数学模型。该模型包括通过受调控的高亲和力途径和不受调控的低亲和力途径摄取铁。还包括将铁从细胞质摄取到液泡和线粒体以及纳米颗粒形成。该模型捕捉到了基本的运输行为，表明细胞根据其总体生长速度调节铁摄取，并且当纳米颗粒积累时，它们会错误地调节铁摄取。与其他细胞代谢物的严格调节相比，酵母中铁的缺乏调节可能是独特的。这种现象可能源于与铁纳米颗粒形成相关的独特化学性质。
