Automated and online characterization of adherent cell culture growth in a microfabricated bioreactor.
Automated and online characterization of adherent cell culture growth in a microfabricated bioreactor.
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DOI：
10.1177/2211068214529288
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发表时间：
2014-10
期刊：
影响因子：
--
通讯作者：
Szita N
中科院分区：
文献类型：
--
作者：
Jaccard N;Macown RJ;Super A;Griffin LD;Veraitch FS;Szita N
贴壁细胞系广泛应用于生物学的所有领域，包括药物发现，毒性研究和再生医学。然而，贴壁细胞过程通常受到细胞培养系统缺乏进展的限制。虽然悬浮培养过程受益于数十年的仪器化生物反应器的发展，但贴壁培养通常在静态的非仪器化烧瓶和孔板中进行。我们先前描述了一种微制造的生物反应器，其能够高度控制细胞的微环境，同时保持与标准细胞培养方案的兼容性。在本报告中，我们描述了其与自动图像处理功能的集成，允许连续监测关键细胞培养特征。基于机器学习的算法能够在共培养环境中特异性检测一种细胞类型，例如在成纤维细胞背景下的人类胚胎干细胞。此外，该算法不会混淆由微加工产生的图像伪影，例如表面上的划痕或灰尘颗粒与细胞特征。我们演示了如何自动化的流量控制，环境控制和图像采集可以采用整个培养区域的图像，并获得小鼠胚胎干细胞培养的时间过程数据，例如，融合。
Adherent cell lines are widely used across all fields of biology, including drug discovery, toxicity studies, and regenerative medicine. However, adherent cell processes are often limited by a lack of advances in cell culture systems. While suspension culture processes benefit from decades of development of instrumented bioreactors, adherent cultures are typically performed in static, noninstrumented flasks and well-plates. We previously described a microfabricated bioreactor that enables a high degree of control on the microenvironment of the cells while remaining compatible with standard cell culture protocols. In this report, we describe its integration with automated image-processing capabilities, allowing the continuous monitoring of key cell culture characteristics. A machine learning–based algorithm enabled the specific detection of one cell type within a co-culture setting, such as human embryonic stem cells against the background of fibroblast cells. In addition, the algorithm did not confuse image artifacts resulting from microfabrication, such as scratches on surfaces, or dust particles, with cellular features. We demonstrate how the automation of flow control, environmental control, and image acquisition can be employed to image the whole culture area and obtain time-course data of mouse embryonic stem cell cultures, for example, for confluency.
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影响因子：
2.8
作者：
Juneau, Pierre-Marc;Garnier, Alain;Duchesne, Carl
通讯作者：
Duchesne, Carl
一种具有稳定浓度梯度的新型微流体平台，用于芯片上细胞培养和筛选测定
影响因子：
6.1
作者：
Xu, Bi-Yi;Hu, Shan-Wen;Chen, Hong-Yuan
通讯作者：
Chen, Hong-Yuan
影响因子：
3.7
作者：
Reichen M;Macown RJ;Jaccard N;Super A;Ruban L;Griffin LD;Veraitch FS;Szita N
通讯作者：
Szita N
DOI：
10.1177/2211068213499917
发表时间：
2013-12
期刊：
Journal of laboratory automation
影响因子：
--
作者：
Reichen M;Veraitch FS;Szita N
通讯作者：
Szita N
影响因子：
3.7
作者：
Ker DF;Weiss LE;Junkers SN;Chen M;Yin Z;Sandbothe MF;Huh SI;Eom S;Bise R;Osuna-Highley E;Kanade T;Campbell PG
通讯作者：
Campbell PG