Using Raman spectroscopy and chemometrics to identify the growth phase of Lactobacillus casei Zhang during batch culture at the single-cell level.
Using Raman spectroscopy and chemometrics to identify the growth phase of Lactobacillus casei Zhang during batch culture at the single-cell level.
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使用拉曼光谱和化学计量学在单细胞水平上鉴定干酪乳杆菌张在分批培养过程中的生长阶段
DOI：
10.1186/s12934-017-0849-8
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发表时间：
2017-12-23
影响因子：
6.4
通讯作者：
Zhang H
中科院分区：
文献类型：
--
作者：
Ren Y;Ji Y;Teng L;Zhang H
背景：由于微生物培养是由异质性细胞组成的，这些细胞根据其大小和细胞内DNA、蛋白质和其他成分的浓度而不同，因此批量培养中细菌群体生长阶段的详细鉴定和区分是具有挑战性的。细胞分析对于质量控制和细胞富集是必不可少的。方法：本文报道了利用单细胞拉曼光谱（SCRS）实时分析和预测干酪乳杆菌（Lactobacillus (L.) casei Zhang）分批培养过程中不同生长阶段细胞数量的研究结果。SCRS可以在单细胞水平上对确定的细胞生长阶段进行有针对性的分析，包括滞后期、对数期和平稳期。结果：在细胞生长的不同状态下发现了光谱位移，反映了每个细胞生长阶段特有的生化变化。随着时间的推移，与DNA和RNA相关的拉曼峰值的强度会下降，而蛋白质特异性和脂质特异性的拉曼振动则以不同的速率增加。基于SCRS，采用监督分类模型（Random Forest）对细胞的滞后期、对数期和平稳期进行分类，平均灵敏度为90.7%，平均特异性为90.8%。此外，正确的细胞类型预测精度约为91.2%。结论：综上所述，拉曼光谱可以实现无标记、连续监测细胞生长，这可能有助于更准确地估计工业发酵间歇培养过程中乳酸菌群体的生长状态。
Background:As microbial cultures are comprised of heterogeneous cells that differ according to their size and intracellular concentrations of DNA, proteins, and other constituents, the detailed identification and discrimination of the growth phases of bacterial populations in batch culture is challenging. Cell analysis is indispensable for quality control and cell enrichment.Methods:In this paper, we report the results of our investigation on the use of single-cell Raman spectrometry (SCRS) for real-time analysis and prediction of cells in different growth phases during batch culture of Lactobacillus (L.) casei Zhang. A targeted analysis of defined cell growth phases at the level of the single cell, including lag phase, log phase, and stationary phase, was facilitated by SCRS.Results:Spectral shifts were identified in different states of cell growth that reflect biochemical changes specific to each cell growth phase. Raman peaks associated with DNA and RNA displayed a decrease in intensity over time, whereas protein-specific and lipid-specific Raman vibrations increased at different rates. Furthermore, a supervised classification model (Random Forest) was used to specify the lag phase, log phase, and stationary phase of cells based on SCRS, and a mean sensitivity of 90.7% and mean specificity of 90.8% were achieved. In addition, the correct cell type was predicted at an accuracy of approximately 91.2%.Conclusions:To conclude, Raman spectroscopy allows label-free, continuous monitoring of cell growth, which may facilitate more accurate estimates of the growth states of lactic acid bacterial populations during fermented batch culture in industry.
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影响因子：
4.2
作者：
Neugebauer, U.;Bocklitz, T.;Popp, J.
通讯作者：
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影响因子：
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影响因子：
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作者：
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通讯作者：
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