Detecting protein and post-translational modifications in single cells with iDentification and qUantification sEparaTion (DUET)

While technologies for measuring transcriptomes in single cells have matured, methods for measuring proteins and their post-translational modification (PTM) states in single cells are still being actively developed. Unlike nucleic acids, proteins cannot be amplified, making detection of minute quantities from single cells difficult. Here, we develop a strategy to detect targeted protein and its PTM isoforms in single cells. We barcode the proteins from single cells by tagging them with oligonucleotides, pool barcoded cells together, run bulk gel electrophoresis to separate protein and its PTM isoform and quantify their abundances by sequencing the oligonucleotides associated with each protein species. We used this strategy, iDentification and qUantification sEparaTion (DUET), to measure histone protein H2B and its monoubiquitination isoform, H2Bub, in single yeast cells. Our results revealed the heterogeneities of H2B ubiquitination levels in single cells from different cell-cycle stages, which is obscured in ensemble measurements

Detecting protein and post-translational modifications in single cells with iDentification and qUantification sEparaTion (DUET)

While technologies for measuring transcriptomes in single cells have matured, methods for measuring proteins and their post-translational modification (PTM) states in single cells are still being actively developed. Unlike nucleic acids, proteins cannot be amplified, making detection of minute quantities from single cells difficult. Here, we develop a strategy to detect targeted protein and its PTM isoforms in single cells. We barcode the proteins from single cells by tagging them with oligonucleotides, pool barcoded cells together, run bulk gel electrophoresis to separate protein and its PTM isoform and quantify their abundances by sequencing the oligonucleotides associated with each protein species. We used this strategy, iDentification and qUantification sEparaTion (DUET), to measure histone protein H2B and its monoubiquitination isoform, H2Bub, in single yeast cells. Our results revealed the heterogeneities of H2B ubiquitination levels in single cells from different cell-cycle stages, which is obscured in ensemble measurements

Inversion of thermal properties of lunar soil from penetration heat of projectile using a 2D axisymmetric model and optimized PSO algorithm

The thermophysical parameters of lunar soil can be inferred from the temperature field during the invasion process of reconnaissance projectile. This paper adopts a two-dimensional axisymmetric model to reconstruct the projectile invasion process. An optimized particle swarm optimization method is then used to retrieve the thermophysical parameters of lunar soil. When the reconnaissance projectile penetrates the lunar interior, it rubs against the lunar soil and generates heat, which diffuses between the projectile body and the lunar soil. The sensors inside the reconnaissance projectile measure the temperature variation of the projectile body to inverse the thermophysical parameters. This paper carried out physical modeling of the penetration process of reconnaissance projectile. A two-dimensional axisymmetric simulation model is constructed for the physical process, and the adaptive inertial weight particle swarm algorithm is adopted. The inversion experiment of lunar soil thermophysical parameters based on the simulation model shows that the inversion error is less than 10%, which verifies the feasibility of this method

Structural and kinetic analysis of the COP9-Signalosome activation and the cullin-RING ubiquitin ligase deneddylation cycle

The COP9-Signalosome (CSN) regulates cullin–RING ubiquitin ligase (CRL) activity and assembly by cleaving Nedd8 from cullins. Free CSN is autoinhibited, and it remains unclear how it becomes activated. We combine structural and kinetic analyses to identify mechanisms that contribute to CSN activation and Nedd8 deconjugation. Both CSN and neddylated substrate undergo large conformational changes upon binding, with important roles played by the N-terminal domains of Csn2 and Csn4 and the RING domain of Rbx1 in enabling formation of a high affinity, fully active complex. The RING domain is crucial for deneddylation, and works in part through conformational changes involving insert-2 of Csn6. Nedd8 deconjugation and re-engagement of the active site zinc by the autoinhibitory Csn5 glutamate-104 diminish affinity for Cul1/Rbx1 by ~100-fold, resulting in its rapid ejection from the active site. Together, these mechanisms enable a dynamic deneddylation-disassembly cycle that promotes rapid remodeling of the cellular CRL network

Characterizing cell state and cell fate by high-throughput single cell genomics

Thesis (Ph.D.)--University of Washington, 2019Animal development is one of the greatest sources of wonders in science. Development of multicellular organism is characterized by the differentiation of a fertilized egg into diverse cell types of the body in a programed temporal spatial order. The process of development includes fertilization, cleavage, gastrulation, organogenesis, metamorphosis, regeneration, and senescence. Characterizing cell differentiation in each step, by resolving the cell state diversity and cell fate dynamics, is the key to fully understanding developmental process. The expression levels of mRNA species are readily linked to cellular function, and therefore profiling the transcriptome of individual cells has emerged as a powerful strategy for resolving cell state heterogeneity. However, current methods for single cell RNA sequencing all rely on the isolation of individual cells within physical compartments and thus have problems such as low throughput, high cost, and information lost from other molecular layers. During the three and half years of my graduate study, I developed four novel high-throughput single cell genomic techniques to get over these limitations and applied them to profiling cell state heterogeneity and dynamics in development at single cell resolution. To resolve cellular state heterogeneity, I developed a combinatorial indexing strategy to profile the transcriptome across tens of thousands of single cells (sci-RNA-seq: Single cell Combinatorial Indexing RNA sequencing), and applied sci-RNA-seq to generate the first catalog of single cell transcriptomes at the scale of whole organism Caenorhabditis elegans (Cao. J., Jonathan. P., et al, Comprehensive single-cell transcriptional profiling of a multicellular organism, Science, 2017). I profiled over 50,000 cells from the nematode C. elegans at the L2 stage, which is over 50-fold “shotgun cellular coverage” of its somatic cell composition. This is the first study to show that single cell transcriptome alone is sufficient to separate all major cell types from whole animal. Cell type specific genes for 27 distinct cell types are identified, including for some fine-grained cell types that are present in only one or two cells per individual. Given that C.elegans is the only organism with a fully mapped cellular lineage, these data represent a rich resource for future research aimed at defining cell types and states. The dataset will advance our understanding of developmental biology, and constitute a major step towards a comprehensive, single-cell molecular atlas of a whole animal. To further characterize cellular state across multiple molecular layers, I developed sci-CAR, the first high throughput single cell genomic approach that can jointly profile epigenome (chromatin accessibility) and transcriptome in each of 1000s of single cells (Cao. J. et al, Joint profiling of chromatin accessibility and gene expression in thousands of single cells, Science, 2018). I applied sci-CAR to 11,233 cells from whole mouse kidney and linked cis-regulatory sites to their putative target genes based on the covariance of chromatin accessibility and transcription at the single-cell level. To the best of our knowledge, this represents the first joint profiling of the epigenome and transcriptome in individual cells at the scale and complexity of a whole mammalian organ. One critical challenge in development is to characterize the cell differentiation path for all major cell types forming our body. During mammalian organogenesis, the cells of the three germ layers transform into an embryo that includes most major internal and external organs. The key regulators of developmental defects can be studied during this critical window, but conventional approaches lack the throughput and resolution to obtain a global view of the molecular states and trajectories of a rapidly diversifying and expanding number of cell types. To investigate cell state dynamics in this critical window, I developed another single cell transcriptome profiling technique (sci-RNA-seq3), the first single cell RNA-seq technique capable of profiling millions of single cells in a single experiment, with over one hundred times higher throughput and lower cost compared with conventional approaches. I applied sci-RNA-seq3 to profiling ~ 2 million cells derived from 61 mouse embryos staged between 9.5 and 13.5 days of gestation (Cao. J., Spielmann. M., et al, The single-cell transcriptional landscape of mammalian organogenesis, Nature, 2018). This is by far the most comprehensive cell atlas of mammalian development as well as the largest single cell RNA-seq data set in the world. By unsupervised clustering analysis, I characterized hundreds of expanding, contracting and transient cell types, many of which are only detected because of the depth of cellular coverage obtained here, and defined the corresponding sets of cell type-specific marker genes, several of which are validated by whole mount in situ hybridization. With a new single cell RNA-seq analysis package Monocle 3, I further delineated and annotated 56 single cell developmental trajectories of mouse organogenesis, spanning all major systems such as central nervous system and reproductive system. The dynamics of cell proliferation and key gene regulators within each cell lineage are further identified. These data comprise a foundational resource for single cell genomic field and mammalian developmental biology. To further characterizing the mechanism regulating cell state dynamics, I developed sci-fate, the first strategy to recover whole transcriptome temporal dynamics across thousands of single cells (Cao. J., et al, Characterizing single cell temporal dynamics with sci-fate, manuscript in preparation, 2019). I applied sci-fate to a model system of cortisol response and developed a computation strategy to identify key driving transcription factors regulating cell state changes. Based on the data, I built a cell state transition network for future cell state prediction, and illustrate key factors regulating cell state transition dynamics. This is the first study to quantitatively characterize cell state dynamics at whole transcriptome level and constitutes a major step to fully understanding mechanisms in cell fate determination

A Descent Conjugate Gradient Algorithm for Optimization Problems and Its Applications in Image Restoration and Compression Sensing

It is well known that the nonlinear conjugate gradient algorithm is one of the effective algorithms for optimization problems since it has low storage and simple structure properties. This motivates us to make a further study to design a modified conjugate gradient formula for the optimization model, and this proposed conjugate gradient algorithm possesses several properties: (1) the search direction possesses not only the gradient value but also the function value; (2) the presented direction has both the sufficient descent property and the trust region feature; (3) the proposed algorithm has the global convergence for nonconvex functions; (4) the experiment is done for the image restoration problems and compression sensing to prove the performance of the new algorithm

Proteotoxic stress of cancer: implication of the heat-shock response in oncogenesis.

Organisms frequently encounter a wide variety of proteotoxic stressors. The heat-shock response, an ancient cytoprotective mechanism, has evolved to augment organismal survival and longevity in the face of proteotoxic stress from without and within. These broadly recognized beneficial effects, ironically, contrast sharply with its emerging role as a culprit in the pathogenesis of cancers. Here, we present an overview of the normal biology of the heat-shock response and highlight its implications in oncogenic processes, including the proteotoxic stress phenotype of cancer; the function of this stress response in helping cancer survive and adapt to proteotoxic stress; and perturbation of proteome homeostasis in cancer as a potential therapeutic avenue

Mesh-Based 3D MEC Modeling of a Novel Hybrid Claw Pole Generator

A brushless parallel hybrid excitation claw pole generator (HECPG) is proposed for electric vehicle (EV) application. Permanent magnet (PM) excitation method can reduce the volume of the machine and improve the power density and efficiency. Moreover, the voltage regulation can be ensured by field excitation. The flux path of the proposed HECPG is complex, and it will take a long time for 3D finite element analysis (FEA) to process it. To reduce simulation time, the mathematical model of the generator is given by a mesh-based 3D magnet equivalent circuit (MEC) network method considering radial and axial flux, magnetic saturation, and magnetic flux leakage. The performance of the generator is analyzed by FEA and prototype experiment. Finally, the results of 3D MEC, FEA, and experiment are compared. There is little difference between the three results, so 3D MEC can ensure the accuracy and significantly reduce the simulation time. The efficiency of the proposed HECPG is 90%, and the DC-Bus voltage can be modulated by changing the amplitude of field current

Mesh-Based 3D MEC Modeling of a Novel Hybrid Claw Pole Generator

A brushless parallel hybrid excitation claw pole generator (HECPG) is proposed for electric vehicle (EV) application. Permanent magnet (PM) excitation method can reduce the volume of the machine and improve the power density and efficiency. Moreover, the voltage regulation can be ensured by field excitation. The flux path of the proposed HECPG is complex, and it will take a long time for 3D finite element analysis (FEA) to process it. To reduce simulation time, the mathematical model of the generator is given by a mesh-based 3D magnet equivalent circuit (MEC) network method considering radial and axial flux, magnetic saturation, and magnetic flux leakage. The performance of the generator is analyzed by FEA and prototype experiment. Finally, the results of 3D MEC, FEA, and experiment are compared. There is little difference between the three results, so 3D MEC can ensure the accuracy and significantly reduce the simulation time. The efficiency of the proposed HECPG is 90%, and the DC-Bus voltage can be modulated by changing the amplitude of field current