Studies On Single-cell Dynamics Using Multi-trap Laser Tweezers Raman Spectroscopy

Studies on the componential changes of biological cells,particularly during their growth,development as well as their responses to external stimuli,can improve our understandings of the fundamental laws of life activities.To date,methods for cellular dynamics monitoring are primarily focused on the observation of the collective behaviors of a cell population;consequently the information obtained is averaged over a large number of cells,concealing their heterogeneity.Laser Tweezers Raman spectroscopy(LTRS)is a non-destructive and label-free technique for single-cell analysis and has been used for the monitoring of cellular dynamic processes,uncovering the molecular mechanisms behind the heterogeneity.However,as only one cell is analyzed at each time,the analytical efficiency of a single-trap LTRS is very low.In this thesis,a parallelized single-cell spectroscopic method is proposed.The method combines multi-trap LTRS and compressive sensing and is capable of simultaneously monitoring the dynamics of multiple biological cells.Both numerical simulation and dynamical experiments are performed to validate the proposed method.The thesis is divided into two parts:(1)In the first part,the working principles of the parallelized single-cell analytical method is introduced,which combines multi-trap LTRS and compressive sensing.A spectral reconstruction model is then built,which incorporates the collaboratively hierarchical sparsity.Two algorithms in compressed sensing,collaborative hierarchical Lasso(C-Hi Lasso)and weighted hierarchical Lasso(W-Hi Lasso),are introduced for the accurate reconstruction of the Raman spectra of individual cells at different time intervals.Superimposed spectra of multiple cells during their dynamics are numerically simulated,which are then used for substantiating the feasibility and accuracy of the proposed method from both qualitative and quantitative aspects.(2)In the second part,an experimental system of multi-trap LTRS is built.By using our proposed compressive detection scheme,the system is used to monitor the dynamical germination processes of multiple bacterial spores,which are triggered by the external calcium dipicolinate(Ca DPA).The C-Hi Lasso and W-Hi Lasso algorithms are then used to recover the Raman spectra of the individual spores at different time intervals.The reconstructed spectra are compared to the ground-truth that is obtained in the y-projection mode as well as the spectra reconstructed by Hi Lasso algorithm that does not include the collaborative sparsity.The results indicate that the algorithm incorporating collaborative sparsity yields higher spectral reconstruction fidelity and quantification accuracy.Moreover,the experimental results demonstrate that our proposed method also achieves higher signal-to-noise ratios.In summary,the combination of multi-trap LTRS and compressive sensing can accurately quantify the cellular dynamics of multiple biological cells,significantly improving the detection throughput of single-cell Raman spectroscopy.