Early selection of Chinese Hamster Ovary (CHO) cells using simultaneous label-free autofluorescence multi-harmonic (slam) microscopy and Fluorescence Lifetime Imaging Microscopy (FLIM) for biopharmaceutical cell line development
Ho, Alexander
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https://hdl.handle.net/2142/129578
Description
Title
Early selection of Chinese Hamster Ovary (CHO) cells using simultaneous label-free autofluorescence multi-harmonic (slam) microscopy and Fluorescence Lifetime Imaging Microscopy (FLIM) for biopharmaceutical cell line development
Author(s)
Ho, Alexander
Issue Date
2025-05-06
Director of Research (if dissertation) or Advisor (if thesis)
Efficient selection of high performing Chinese Hamster Ovary (CHO) clones remains a major bottleneck in biopharmaceutical development, requiring weeks to months of subculture and functional assays. Here, we introduce a label free, multimodal imaging pipeline that combines Simultaneous Label free Autofluorescence Multi-harmonic (SLAM) microscopy with Fluorescence Lifetime Imaging Microscopy (FLIM), coupled with a linear kernel Support Vector Machine (SVM) classifier, to enable early phenotypic classification of monoclonal CHO lines. By capturing endogenous two and three photon autofluorescence (NAD(P)H, FAD), second and third harmonic generation, and lifetime contrasts in a single acquisition, more 200 quantitative features, spanning intensity, shape, texture, and colocalization metrics, at the single cell level were extracted and analyzed. On a set of four producer clones (A–D), our SLAM + FLIM + SVM workflow achieves > 95 % balanced accuracy and per class AUC > 0.98 immediately at passage 2, vastly outperforming brightfield‐only models (≤ 0.6). The approach generalizes to an eight cell line panel (S1–S8), sustaining high (> 0.90) accuracy across passages P0–P5 and yielding robust unimodal benchmarks that confirm the synergy of combined multiphoton and lifetime contrasts. In addition, binning clones into low/medium/high classes for harvest titer, per‐cell productivity, maximum viable cell concentration, and long‐term stability, demonstrates early prediction of each critical quality attribute (CQA) (balanced accuracies 0.76–0.93) and identifies the most predictive features via permutation importance analysis. Importantly, rank weighted lifetime–lifetime and multiphoton–Redox colocalization metrics dominate, linking subcellular metabolic microarchitecture to functional performance. This study establishes the combination of SLAM and FLIM imaging as a high content phenotyping platform for label free CHO clone selection, with the potential to drastically shorten cell line development timelines.
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