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Biology subjects

Tadesse, L. F.

Publications and source records attributed to Tadesse, L. F..

2 recordsLinked to original sources

Nucleic acid turnover and lipid remodeling distinguish T cell activation and exhaustion states via label-free Raman spectroscopy

T cell exhaustion impairs immune control of chronic diseases including tuberculosis, HIV, malaria, and cancer. Its clinical implications are vast, predicting HIV-associated malignancy and treatment response and limiting the efficacy of cell therapies. Despite the advantages of monitoring and removing exhausted T cells, current detection methods require expensive antibody labeling, destructive workflows, or days-long functional assays. Here, we introduce Raman spectroscopy as a label-free assay for distinguishing T cell states directly from culture while preserving viability for downstream use. We achieve >97% accuracy in discriminating unstimulated, activated, and exhausted T cells across three donors and multiple hardware setups. We identify vibrational modes associated with nucleic acid turnover and lipid remodeling as key features that distinguish T cell activation and exhaustion. In heterogeneous populations, we quantify exhaustion percentage with R2= 1 and strong correlation to adenine (r= -0.91) and amide II protein (r= 0.94) vibrational modes. This work establishes vibrational fingerprinting as a direct measure of T cell exhaustion beyond surface marker expression towards scalable immune diagnostics, in-line monitoring, and selective immunopheresis.

biophysics↗

Rapid residual bead quantification for cell therapy manufacturing using Raman spectroscopy

Adoptive cell therapies are transforming the treatment of cancer and autoimmunity by enhancing patients own immune cells to fight disease. In cell therapy manufacturing, immunomagnetic beads are used to isolate and activate target cells for gene transfer but must be removed downstream to [&le;]10 beads per 300,000 cells. Current quantification requires time-intensive and error-prone manual counting using brightfield microscopy, while existing automated approaches struggle with variable bead-cell morphology and tedious sample preparation steps. Raman spectroscopy offers rapid, morphology-independent detection using molecular signatures generated by inelastic light scattering. Here, we leverage immunomagnetic beads strong Raman signatures to quantify them in area scans from dried samples, achieving single bead resolution and accurate counting of bead clusters with and without cells. Using low power ([&le;]7 mW) and exposure times ([&ge;]0.5 s), the average area under 3 signature Raman peaks (1110 cm-1, 1346 cm-1, and 1595 cm-1) are measured and input to a linear regression model, achieving a mean squared error (MSE) of <0.2 beads. Our results show Raman spectroscopy as a robust, automated approach for bead counting in existing pipelines with potential to improve the safety and throughput of cell therapies.

bioengineering↗