Browsing by Subject "Single cell analysis"

Cancer comprises a collection of diseases, all of which begin with abnormal tissue growth from various stimuli, including (but not limited to): heredity, genetic mutation, exposure to harmful substances, radiation as well as poor dieting and lack of exercise. The early detection of cancer is vital to providing life-saving, therapeutic intervention. However, current methods for detection (e.g., tissue biopsy, endoscopy and medical imaging) often suffer from low patient compliance and an elevated risk of complications in elderly patients. As such, many are looking to “liquid biopsies” for clues into presence and status of cancer due to its minimal invasiveness and ability to provide rich information about the native tumor. In such liquid biopsies, peripheral blood is drawn from patients and is screened for key biomarkers, chiefly circulating tumor cells (CTCs). Capturing, enumerating and analyzing the genetic and metabolomic characteristics of these CTCs may hold the key for guiding doctors to better understand the source of cancer at an earlier stage for more efficacious disease management.

The isolation of CTCs from whole blood, however, remains a significant challenge due to their (i) low abundance, (ii) lack of a universal surface marker and (iii) epithelial-mesenchymal transition that down-regulates common surface markers (e.g., EpCAM), reducing their likelihood of detection via positive selection assays. These factors potentiate the need for an improved cell isolation strategy that can collect CTCs via both positive and negative selection modalities as to avoid the reliance on a single marker, or set of markers, for more accurate enumeration and diagnosis.

The technologies proposed herein offer a unique set of strategies to focus, sort and template cells in three independent microfluidic modules. The first module exploits ultrasonic standing waves and a class of elastomeric particles for the rapid and discriminate sequestration of cells. This type of cell handling holds promise not only in sorting, but also in the isolation of soluble markers from biofluids. The second module contains components to focus (i.e., arrange) cells via forces from acoustic standing waves and separate cells in a high throughput fashion via free-flow magnetophoresis. The third module uses a printed array of micromagnets to capture magnetically labeled cells into well-defined compartments, enabling on-chip staining and single cell analysis. These technologies can operate in standalone formats, or can be adapted to operate with established analytical technologies, such as flow cytometry. A key advantage of these innovations is their ability to process erythrocyte-lysed blood in a rapid (and thus high throughput) fashion. They can process fluids at a variety of concentrations and flow rates, target cells with various immunophenotypes and sort cells via positive (and potentially negative) selection. These technologies are chip-based, fabricated using standard clean room equipment, towards a disposable clinical tool. With further optimization in design and performance, these technologies might aid in the early detection, and potentially treatment, of cancer and various other physical ailments.

Droplet microfluidics technology holds immense potential for single-cell level biomedical engineering studies, motivating the study of cellular immunotherapy, cell interactions, drug screening, and single-cell dynamics. However, existing droplet microfluidics have limited pairing efficiency, complex manual operation procedures, and low in-droplet cell manipulation capacity, which hinder their potential application in single-cell analyses with high sample purity or uniformity requirements. Several efforts, such as electrophoretic, magnetic, and optical droplet sorters, have been used to overcome some limitations. Still, they need the all-powerful capability of acoustics to solve all the problems. As a dynamic, precise, contact-free, and biocompatible force, acoustics can improve pairing efficiency in droplets and provide an ideal tool for active droplet manipulation. In this dissertation, I demonstrate the reinvention of droplet microfluidics, reporting the multifunctionality of acoustics for high throughput, high-precision droplet sorting, and active droplet manipulation. I propose a modular acoustofluidics platform designed for the streamlined sorting and collection of effector-target (i.e., NK92-K562) cell pairs, facilitating efficient monitoring of the real-time dynamics of immunological response formation. Coupled with transcriptional and protein expression analyses, I evaluated the synergistic effect of doxorubicin on the cellular immune response. In addition, because of the non-contact nature of acoustics, I can actively and simultaneously manipulate multiple cell-encapsulated droplets, which other methods cannot achieve. The proposed acoustofluidic platform can provide promising building blocks for high-throughput quantitative single-cell level coculture to understand intercellular communication while empowering immunotherapy through precision manipulation and analysis of immunological synapses.

Control of E2F transcription factor activity, regulated by the action of the retinoblastoma tumor suppressor, is critical for determining cell cycle entry and cell proliferation. However, an understanding of the precise determinants of this control, including the role of other cell cycle regulatory activities, has not been clearly defined.

Recognizing that the contributions of individual regulatory components could be masked by heterogeneity in populations of cells, we made use of an integrated system to follow E2F transcriptional dynamics at the single cell level and in real time. We measured and characterized E2F temporal dynamics in the first cell cycle where cells enter the cell cycle after a period of quiescence. Quantitative analyses revealed that crossing a threshold of amplitude of E2F transcriptional activity serves as the critical determinant of cell-cycle commitment and division.

By using a developed ordinary differential equation model for Rb/E2F network, we performed simulations and predicted that Myc and cyclin D/E activities have distinct roles in modulating E2F transcriptional dynamics. Myc is critical in modulating the amplitude whereas cyclin D/E activities have little effect on the amplitude but do contribute to the modulation of duration of E2F transcriptional activation. These predictions were validated through the analysis of E2F dynamics in single cells under the conditions that cyclin D/E or Myc activities are perturbed by small molecule inhibitors or RNA interference.

In an ongoing study, we also measured E2F dynamics in cycling cells. We provide preliminary results showing robust oscillatory E2F expression at the single-cell level that aligns with the progression of continuous cell division. The temporal characteristics of the dynamics trajectories deserve further quantitative investigations.

Taken together, our results establish a strict relationship between E2F dynamics and cell fate decision at the single-cell level, providing a refined model for understanding the control logic of cell cycle entry.

Single-cell analysis (SCA) tools have important applications in the analysis of phenotypic heterogeneity, which is difficult or impossible to analyze in bulk cell culture or patient samples. SCA tools thus have a myriad of applications ranging from better credentialing of drug therapies to the analysis of rare latent cells harboring HIV infection or in Cancer. However, existing SCA systems usually lack the required combination of programmability, flexibility, and scalability necessary to enable the study of cell behaviors and cell-cell interactions at the scales sufficient to analyze extremely rare events. To advance the field, I have developed a novel, programmable, and massively-parallel SCA tool which is based on the principles of computer circuits. By integrating these magnetic circuits with microfluidics channels, I developed a platform that can organize a large number of single particles into an array in a controlled manner.

My magnetophoretic circuits use passive elements constructed in patterned magnetic thin films to move cells along programmed tracks with an external rotating magnetic field. Cell motion along these tracks is analogous to the motion of charges in an electrical conductor, following a rule similar to Ohm’s law. I have also developed asymmetric conductors, similar to electrical diodes, and storage sites for cells that behave similarly to electrical capacitors. I have also developed magnetophoretic circuits which use an overlaid pattern of microwires to switch single cells between different tracks. This switching mechanism, analogous to the operation of electronic transistors, is achieved by establishing a semiconducting gap in the magnetic pattern which can be changed from an insulating state to a conducting state by application of electrical current to an overlaid electrode. I performed an extensive study on the operation of transistors to optimize their geometry and minimize the required gate currents.

By combining these elements into integrated circuits, I have built devices which are capable of organizing a precise number of cells into individually addressable array sites, similar to how a random access memory (RAM) stores electronic data. My programmable magnetic circuits allow for the organization of both cells and single-cell pairs into large arrays. Single cells can also potentially be retrieved for downstream high-throughput genomic analysis.

In order to enhance the efficiency of the tool and to increase the delivery speed of the particles, I have also developed microfluidics systems that are combined with the magnetophoretic circuits. This hybrid system, called magnetomicrofluidics, is capable of rapidly organizing an array of particles and cells with the high precision and control. I have also shown that cells can be grown inside these chips for multiple days, enabling the long-term phenotypic analysis of rare cellular events. These types of studies can reveal important insights about the intercellular signaling networks and answer crucial questions in biology and immunology.

The ability to convert sensory stimuli into long-lasting changes in brain function is essential for animals to interact with and learn from their environment. This process is achieved by encoding sensory stimuli into temporal patterns of neuronal activity, which in turn modulate the connectivity and strength of neural circuits in the brain. These long-term plastic changes in the brain are known to depend on the neuronal activity-regulated transcription of new gene products. My dissertation research sought to elucidate how the timing and level of transcriptional responses following neuronal activity can be precisely regulated to form proper neuronal connections. In the first part of this dissertation, I investigated the role of the developmentally regulated GluN3A subunit in NMDAR-induced transcription. I observed that neurons lacking the transcription factor CaRF showed enhanced NMDAR-induced expression of Bdnf and Arc both in cultured neurons and following sensory stimulation in the developing brain in vivo. I identified GluN3A as a regulatory target of CaRF and found that neurons lacking GluN3A showed selective enhancement of NMDAR-induced transcription. GluN3A limited synaptic activity-induced transcription by inhibiting both NMDAR-induced nuclear translocation of the p38 MAP kinase and activation of the transcription factor MEF2C. These data demonstrate that GluN3A negatively regulates NMDAR-dependent activation of gene transcription and reveal a novel mechanism that regulates the level of NMDAR-induced transcriptional response in the developing brain. In the second part of my dissertation, I examined the role of enhancer histone acetylation in neuronal activity-regulated gene transcription. I applied quantitative single-molecule fluorescence in situ hybridization to measure neuronal activity-induced gene transcription at the single neuron level, taking advantage of the intrinsic stochasticity of transcription to quantify the effects of enhancer regulation on the dynamics of promoter state transitions. Locally-induced enhancer histone acetylation by CRISPR-mediated epigenome editing was sufficient to increase Fos mRNA expression both under basal conditions and following membrane depolarization in primary hippocampal neurons, via a mechanism that involves enhancer recruitment of Brd4, increased transcriptional elongation by the release of paused polymerase, and prolonged activation of Fos promoters. These data indicate that enhancer histone acetylation plays a causative role in the induction of neuronal activity-regulated gene transcription and open up the possibility to specifically control the level and timing of the neuronal activity-induced transcriptional response. Taken together my dissertation works elucidate mechanisms that control the specificity, timing, and amplitude of transcriptional responses to neuronal activity, revealing novel information about the dynamic range of this fundamental cellular process.