Relevant bibliographies by topics / Single cell proteomics

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  2. Dissertations / Theses
  3. Books
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Academic literature on the topic 'Single cell proteomics'

Author: Grafiati
Published: 5 June 2025
Last updated: 16 July 2025

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Journal articles on the topic "Single cell proteomics"

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Vistain, Luke F., and Savaş Tay. "Single-Cell Proteomics." Trends in Biochemical Sciences 46, no. 8 (2021): 661–72. http://dx.doi.org/10.1016/j.tibs.2021.01.013.

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Doerr, Allison. "Single-cell proteomics." Nature Methods 16, no. 1 (2018): 20. http://dx.doi.org/10.1038/s41592-018-0273-y.

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Suruchi, Sharma*1 And Sahil Sharma2. "Single Cell Proteomics (SCP): The Cell Analysis." Science World a monthly e magazine 3, no. 3 (2023): 413–17. https://doi.org/10.5281/zenodo.7762339.

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Cells from microbial cultures and mammalian cell cultures that have identical genomes and grow in the same environment do not have the same proteome. The distinctions Proteomes have important functional consequences. The proteome of each individual cell will be analysed using high throughput analytical platforms in Single Cell Proteomics; advanced isolation and sampling methods are required to minimize protein loss, and highly sensitive techniques are required for proteome analysis. Single Cell Proteomics can be used to create a proteome map of each type of cell in multicellular and single-cell organisms, interactions related to a biological process. This aids in the investigation of protein expression and modification under specific biological conditions, the characterization of protein functions in a genome, the identification of protein localization and compartmentalization at a given time, and the determination of protein-protein interactions related to a biological process.
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Senavirathna, Lakmini, Cheng Ma, Ru Chen, and Sheng Pan. "Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity." Cells 11, no. 15 (2022): 2450. http://dx.doi.org/10.3390/cells11152450.

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Dissecting the proteome of cell types and states at single-cell resolution, while being highly challenging, has significant implications in basic science and biomedicine. Mass spectrometry (MS)-based single-cell proteomics represents an emerging technology for system-wide, unbiased profiling of proteins in single cells. However, significant challenges remain in analyzing an extremely small amount of proteins collected from a single cell, as a proteome-wide amplification of proteins is not currently feasible. Here, we report an integrated spectral library-based single-cell proteomics (SLB-SCP) platform that is ultrasensitive and well suited for a large-scale analysis. To overcome the low MS/MS signal intensity intrinsically associated with a single-cell analysis, this approach takes an alternative approach by extracting a breadth of information that specifically defines the physicochemical characteristics of a peptide from MS1 spectra, including monoisotopic mass, isotopic distribution, and retention time (hydrophobicity), and uses a spectral library for proteomic identification. This conceptually unique MS platform, coupled with the DIRECT sample preparation method, enabled identification of more than 2000 proteins in a single cell to distinguish different proteome landscapes associated with cellular types and heterogeneity. We characterized individual normal and cancerous pancreatic ductal cells (HPDE and PANC-1, respectively) and demonstrated the substantial difference in the proteomes between HPDE and PANC-1 at the single-cell level. A significant upregulation of multiple protein networks in cancer hallmarks was identified in the PANC-1 cells, functionally discriminating the PANC-1 cells from the HPDE cells. This integrated platform can be built on high-resolution MS and widely accepted proteomic software, making it possible for community-wide applications.
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Chen, Kangfu, and Zongjie Wang. "A Micropillar Array Based Microfluidic Device for Rare Cell Detection and Single-Cell Proteomics." Methods and Protocols 6, no. 5 (2023): 80. http://dx.doi.org/10.3390/mps6050080.

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Advancements in single-cell-related technologies have opened new possibilities for analyzing rare cells, such as circulating tumor cells (CTCs) and rare immune cells. Among these techniques, single-cell proteomics, particularly single-cell mass spectrometric analysis (scMS), has gained significant attention due to its ability to directly measure transcripts without the need for specific reagents. However, the success of single-cell proteomics relies heavily on efficient sample preparation, as protein loss in low-concentration samples can profoundly impact the analysis. To address this challenge, an effective handling system for rare cells is essential for single-cell proteomic analysis. Herein, we propose a microfluidics-based method that offers highly efficient isolation, detection, and collection of rare cells (e.g., CTCs). The detailed fabrication process of the micropillar array-based microfluidic device is presented, along with its application for CTC isolation, identification, and collection for subsequent proteomic analysis.
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Krieg, Rene C., Cloud P. Paweletz, Lance A. Liotta, and Emanuel F. Petricoin. "Clinical Proteomics for Cancer Biomarker Discovery and Therapeutic Targeting." Technology in Cancer Research & Treatment 1, no. 4 (2002): 263–72. http://dx.doi.org/10.1177/153303460200100407.

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As we emerge into the post-genome era, proteomics finds itself as the driving force field as we translate the nucleic acid information archive into understanding how the cell actually works and how disease processes operate. Even so, the traditionally held view of proteomics as simply cataloging and developing lists of the cellular protein repertoire of a cell are now changing, especially in the sub-discipline of clinical proteomics. The most relevant information archive to clinical applications and drug development involves the elucidation of the information flow of the cell; the “software” of protein pathway networks and circuitry. The deranged circuitry of the cell as the drug target itself as well as the effect of the drug on not just the target, but also the entire network, is what we now are striving towards. Clinical proteomics, as a new and most exciting sub-discipline of proteomics, involves the bench-to-bedside clinical application of proteomic tools. Unlike the genome, there are potentially thousands of proteomes: each cell type has its own unique proteome. Moreover, each cell type can alter its proteome depending on the unique tissue microenvironment in which it resides, giving rise to multiple permutations of a single proteome. Since there is no polymerase chain reaction equivalent to proteomics- identifying and discovering the “wiring diagram” of a human diseased cell in a biopsy specimen remains a daunting challenge. New micro-proteomic technologies are being and still need to be developed to drill down into the proteomes of clinically relevant material. Cancer, as a model disease, provides a fertile environment to study the application of proteomics at the bedside. The promise of clinical proteomics and the new technologies that are developed is that we will detect cancer earlier through discovery of biomarkers, we will discover the next generation of targets and imaging biomarkers, and we can then apply this knowledge to patient-tailored therapy.
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Orsburn, Benjamin C. "Evaluation of the Sensitivity of Proteomics Methods Using the Absolute Copy Number of Proteins in a Single Cell as a Metric." Proteomes 9, no. 3 (2021): 34. http://dx.doi.org/10.3390/proteomes9030034.

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Proteomic technology has improved at a staggering pace in recent years, with even practitioners challenged to keep up with new methods and hardware. The most common metric used for method performance is the number of peptides and proteins identified. While this metric may be helpful for proteomics researchers shopping for new hardware, this is often not the most biologically relevant metric. Biologists often utilize proteomics in the search for protein regulators that are of a lower relative copy number in the cell. In this review, I re-evaluate untargeted proteomics data using a simple graphical representation of the absolute copy number of proteins present in a single cancer cell as a metric. By comparing single-shot proteomics data to the coverage of the most in-depth proteomic analysis of that cell line acquired to date, we can obtain a rapid metric of method performance. Using a simple copy number metric allows visualization of how proteomics has developed in both sensitivity and overall dynamic range when using both relatively long and short acquisition times. To enable reanalysis beyond what is presented here, two available web applications have been developed for single- and multi-experiment comparisons with reference protein copy number data for multiple cell lines and organisms.
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Slavov, Nikolai. "Scaling Up Single-Cell Proteomics." Molecular & Cellular Proteomics 21, no. 1 (2022): 100179. http://dx.doi.org/10.1016/j.mcpro.2021.100179.

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Ctortecka, Claudia, and Karl Mechtler. "The rise of single‐cell proteomics." Analytical Science Advances 2, no. 3-4 (2021): 84–94. http://dx.doi.org/10.1002/ansa.202000152.

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Petelski, Aleksandra A., Edward Emmott, Andrew Leduc, et al. "Multiplexed single-cell proteomics using SCoPE2." Nature Protocols 16, no. 12 (2021): 5398–425. http://dx.doi.org/10.1038/s41596-021-00616-z.

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Dissertations / Theses on the topic "Single cell proteomics"

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Salehi-Reyhani, Ali. "Tools for single cell proteomics." Thesis, Imperial College London, 2011. http://hdl.handle.net/10044/1/9280.

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Despite recent advances that offer control of single cells, in terms of manipulation and sorting and the ability to measure gene expression, the need to measure protein copy number remains unmet. Measuring protein copy number in single cells and related quantities such as levels of phosphorylation and protein-protein interaction is the basis of single cell proteomics. A technology platform to undertake the analysis of protein copy number from single cells has been developed. The approach described is ‘all-optical’ whereby single cells are manipulated into separate analysis chambers using an optical trap; single cells are lysed by mechanical shearing caused by laser-induced microcavitation; and the protein released from a single cell is measured by total internal reflection microscopy as it is bound to micro-printed antibody spots within the device. The platform was tested using GFP transfected cells and the relative precision of the measurement method was determined to be 88%. Single cell measurements were also made on a breast cancer cell line to measure the relative levels of unlabelled human tumour suppressor protein p53 using a chip incorporating an antibody sandwich assay format. This demonstrates the ability count protein copy number from single cells in a manner which could be applied in principle to any set of proteins and for any cell type without the need for genetic engineering. Metabolism can undergo alteration in diseases such as cancer and heart failure and also as cells differentiate during development. In order to assess how it may inform a proteomic measurement, multidimensional two-photon fluorescence metabolic imaging is conducted on a cultured cancer cell line, primary adult rat cardiomyocytes and human embryonic stem cells. By measuring the parameters of fluorescence such as intensity and lifetime of the autofluorescent metabolic co-factors NADH and FAD, it was found to be possible to contrast cells under various conditions and metabolic stimuli. In particular, human embryonic stem cells were able to be contrasted at 3 stages of development as they underwent differentiation into embryonic stem cell derived cardiomyocytes. Metabolic imaging provides a non-destructive method to monitor cellular metabolic activity with high resolution. This is complimentary to the single cell proteomic platform and the convergence of both techniques holds promise in future investigations into how metabolism influences cell function and the proteome in development and disease.
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Bano, Fouzia. "Towards single cell genomics and proteomics: new methods in nanoscale surface biochemistry." Doctoral thesis, SISSA, 2009. http://hdl.handle.net/20.500.11767/4754.

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Chan, Kher Xing. "Morphological and physiological studies of the carbon concentrating mechanism in Chlamydomonas reinhardtii." Thesis, University of Cambridge, 2019. https://www.repository.cam.ac.uk/handle/1810/276829.

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Chlamydomonas reinhardtii possesses a single-cell-based CO2-concentrating mechanism (CCM). The CCM is an important element of algal photosynthesis, metabolism, growth and biomass production, which works by increasing the concentration of inorganic carbon (Ci) in the pyrenoid, a dense RuBisCO-packed structure within the chloroplast. This suppresses RuBisCO oxygenase activity and associated photorespiration. The enhanced efficiency of CO2 assimilation in the pyrenoid via CCM had been modelled theoretically as a requirement for successful CCM in higher plant systems. The ultimate aim of my research is to understand the biogenesis of the pyrenoid using a set of CCM mutants with pyrenoidal defects. Immunofluorescence methods and spot growth tests under different CO2 concentrations were performed on mutants with CCM defects generated by an insertional mutagenesis screen. Morphological and physiological characterisation of these mutants revealed differences in the pyrenoid morphology, the ability for RuBisCO to aggregate into the pyrenoid and the formation of thylakoidal tubule network associated with the pyrenoid. The thylakoid tubule network may be linked to the transport of inorganic carbon into the pyrenoid as part of the CCM. Further characterisation of one of the mutants gave rise to the hypothesis that the gene of interest, Cre11.g467712 (SAGA), is a multi-functional anchor protein related to the structural formation of the pyrenoid and may be another essential component of the pyrenoid.
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Spiteri, Alanna Gabrielle. "Tracking microglia response kinetics with high dimensional proteomic and genomic analysis in neuroinflammation." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/29746.

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Microglia are the resident myeloid population of the central nervous system (CNS), crucial for homeostasis and implicated in almost every defined neuropathology, many of which result in severe debilitation and/or death. Understanding the precise contributions of these cells to disease can thus inform effective therapeutic intervention, particularly in acute neurotropic infectious diseases, such as West Nile virus encephalitis (WNE), which can be fatal, where no licensed vaccine or therapy is available. In a murine model of WNE, widespread neuronal infection drives substantial CNS infiltration of inflammatory monocyte-derived cells (MC), causing severe lethal neuroinflammation. However, the contribution of microglia to this response is largely unknown, since in the severely inflamed CNS it has been impossible to distinguish microglia from MCs accurately. Using high-dimensional cytometry, single-cell RNA sequencing and computational analysis, we detailed the proteomic and transcriptomic programs adopted by microglia and MCs in WNE, elucidating their temporal- and disease-specific functions. Microglia downregulated CX3CR1, F4/80, CD68 and TMEM119 and upregulated CD45, CD64, CD81, MHC-I and IL-12 with disease progression, corresponding to an anti-viral and immune cell-recruiting transcriptomic program at dpi 5 and 7, respectively. Conversely, MC adopted antigen-presenting, immune-cell recruiting and Nos-producing phenotypes, which all had anti-viral function. Functional enrichment profiles were investigated by differentially depleting microglia or MCs in the CNS, where we serendipitously uncovered the therapeutic potential of the microglia-depleting agent, PLX5622, by its off-target inhibition of bone marrow monocyte proliferation and CNS infiltration. Further integrative analysis across 8 neuropathology models demonstrated differential disease-specific transcriptomic responses of microglia vs MCs, uncovering the microglia-enriched, inflammatory stable marker, Cd81, which accurately identifies microglia in neuroinflammation. In connecting transcriptomic and proteomic profiles to better understand resident and infiltrating myeloid responses across CNS pathology, we have identified both therapeutic targets and broader effects of microglial-specific tools.
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"Multiplexed Single-cell Spatial Proteomics and Transcriptomics." Doctoral diss., 2018. http://hdl.handle.net/2286/R.I.51771.

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abstract: Single-cell proteomics and transcriptomics analysis are crucial to gain insights of healthy physiology and disease pathogenesis. The comprehensive profiling of biomolecules in individual cells of a heterogeneous system can provide deep insights into many important biological questions, such as the distinct cellular compositions or regulation of inter- and intracellular signaling pathways of healthy and diseased tissues. With multidimensional molecular imaging of many different biomarkers in patient biopsies, diseases can be accurately diagnosed to guide the selection of the ideal treatment. As an urgent need to advance single-cell analysis, imaging-based technologies have been developed to detect and quantify multiple DNA, RNA and protein molecules in single cell in situ. Novel fluorescent probes have been designed and synthesized, which targets specifically either their nucleic acid counterpart or protein epitopes. These highly multiplexed imaging-based platforms have the potential to detect and quantify 100 different protein molecules and 1000 different nucleic acids in a single cell. Using novel fluorescent probes, a large number of biomolecules have been detected and quantified in formalin-fixed paraffin-embedded (FFPE) brain tissue at single-cell resolution. By studying protein expression levels, neuronal heterogeneity has been revealed in distinct subregions of human hippocampus.<br>Dissertation/Thesis<br>Doctoral Dissertation Chemistry 2018
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Narayanaswamy, Rammohan 1978. "Genome-wide analyses of single cell phenotypes using cell microarrays." Thesis, 2008. http://hdl.handle.net/2152/3967.

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The past few decades have witnessed a revolution in recombinant DNA and nucleic acid sequencing technologies. Recently however, technologies capable of massively high-throughout, genome-wide data collection, combined with computational and statistical tools for data mining, integration and modeling have enabled the construction of predictive networks that capture cellular regulatory states, paving the way for ‘Systems biology’. Consequently, protein interactions can be captured in the context of a cellular interaction network and emergent ‘system’ properties arrived at, that may not have been possible by conventional biology. The ability to generate data from multiple, non-redundant experimental sources is one of the important facets to systems biology. Towards this end, we have established a novel platform called ‘spotted cell microarrays’ for conducting image-based genetic screens. We have subsequently used spotted cell microarrays for studying multidimensional phenotypes in yeast under different regulatory states. In particular, we studied the response to mating pheromone using a cell microarray comprised of the yeast non-essential deletion library and analyzed morphology changes to identify novel genes that were involved in mating. An important aspect of the mating response pathway is large-scale spatiotemporal changes to the proteome, an aspect of proteomics, still largely obscure. In our next study, we used an imaging screen and a computational approach to predict and validate the complement of proteins that polarize and change localization towards the mating projection tip. By adopting such hybrid approaches, we have been able to, not only study proteins involved in specific pathways, but also their behavior in a systemic context, leading to a broader comprehension of cell function. Lastly, we have performed a novel metabolic starvation-based screen using the GFP-tagged collection to study proteome dynamics in response to nutrient limitation and are currently in the process of rationalizing our observations through follow-up experiments. We believe this study to have implications in evolutionarily conserved cellular mechanisms such as protein turnover, quiescence and aging. Our technique has therefore been applied towards addressing several interesting aspects of yeast cellular physiology and behavior and is now being extended to mammalian cells.<br>text
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"Highly Multiplexed Single Cell in situ Protein Analysis with Cleavable Fluorescent Probes." Doctoral diss., 2019. http://hdl.handle.net/2286/R.I.53605.

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abstract: Measurements of different molecular species from single cells have the potential to reveal cell-to-cell variations, which are precluded by population-based measurements. An increasing percentage of researches have been focused on proteins, for its central roles in biological processes. Immunofluorescence (IF) has been a well-established protein analysis platform. To gain comprehensive insights into cell biology and diagnostic pathology, a crucial direction would be to increase the multiplexity of current single cell protein analysis technologies. An azide-based chemical cleavable linker has been introduced to design and synthesis novel fluorescent probes. These probes allow cyclic immunofluorescence staining which leads to the feasibility of highly multiplexed single cell in situ protein profiling. These highly multiplexed imaging-based platforms have the potential to quantify more than 100 protein targets in cultured cells and more than 50 protein targets in single cells in tissues. This approach has been successfully applied in formalin-fixed paraffin-embedded (FFPE) brain tissues. Multiplexed protein expression level results reveal neuronal heterogeneity in the human hippocampus.<br>Dissertation/Thesis<br>Doctoral Dissertation Chemistry 2019
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Ma, Chao. "Single Cell Proteomics Microchip to Profile Immune Function, with Applications in Stem Cell Biology, Translational Disease Mechanism Study and Clinical Therapeutics Monitoring." Thesis, 2013. https://thesis.library.caltech.edu/7527/13/Thesis%20submit%20by%20Chao%20Ma%2004012013.pdf.

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<p>In response to infection or tissue dysfunction, immune cells develop into highly heterogeneous repertoires with diverse functions. Capturing the full spectrum of these functions requires analysis of large numbers of effector molecules from single cells. However, currently only 3-5 functional proteins can be measured from single cells. We developed a single cell functional proteomics approach that integrates a microchip platform with multiplex cell purification. This approach can quantitate 20 proteins from >5,000 phenotypically pure single cells simultaneously. With a 1-million fold miniaturization, the system can detect down to ~100 molecules and requires only ~104 cells. Single cell functional proteomic analysis finds broad applications in basic, translational and clinical studies. In the three studies conducted, it yielded critical insights for understanding clinical cancer immunotherapy, inflammatory bowel disease (IBD) mechanism and hematopoietic stem cell (HSC) biology.</p> <p>To study phenotypically defined cell populations, single cell barcode microchips were coupled with upstream multiplex cell purification based on up to 11 parameters. Statistical algorithms were developed to process and model the high dimensional readouts. This analysis evaluates rare cells and is versatile for various cells and proteins. (1) We conducted an immune monitoring study of a phase 2 cancer cellular immunotherapy clinical trial that used T-cell receptor (TCR) transgenic T cells as major therapeutics to treat metastatic melanoma. We evaluated the functional proteome of 4 antigen-specific, phenotypically defined T cell populations from peripheral blood of 3 patients across 8 time points. (2) Natural killer (NK) cells can play a protective role in chronic inflammation and their surface receptor – killer immunoglobulin-like receptor (KIR) – has been identified as a risk factor of IBD. We compared the functional behavior of NK cells that had differential KIR expressions. These NK cells were retrieved from the blood of 12 patients with different genetic backgrounds. (3) HSCs are the progenitors of immune cells and are thought to have no immediate functional capacity against pathogen. However, recent studies identified expression of Toll-like receptors (TLRs) on HSCs. We studied the functional capacity of HSCs upon TLR activation. The comparison of HSCs from wild-type mice against those from genetics knock-out mouse models elucidates the responding signaling pathway.</p> <p>In all three cases, we observed profound functional heterogeneity within phenotypically defined cells. Polyfunctional cells that conduct multiple functions also produce those proteins in large amounts. They dominate the immune response. In the cancer immunotherapy, the strong cytotoxic and antitumor functions from transgenic TCR T cells contributed to a ~30% tumor reduction immediately after the therapy. However, this infused immune response disappeared within 2-3 weeks. Later on, some patients gained a second antitumor response, consisted of the emergence of endogenous antitumor cytotoxic T cells and their production of multiple antitumor functions. These patients showed more effective long-term tumor control. In the IBD mechanism study, we noticed that, compared with others, NK cells expressing KIR2DL3 receptor secreted a large array of effector proteins, such as TNF-α, CCLs and CXCLs. The functions from these cells regulated disease-contributing cells and protected host tissues. Their existence correlated with IBD disease susceptibility. In the HSC study, the HSCs exhibited functional capacity by producing TNF-α, IL-6 and GM-CSF. TLR stimulation activated the NF-κB signaling in HSCs. Single cell functional proteome contains rich information that is independent from the genome and transcriptome. In all three cases, functional proteomic evaluation uncovered critical biological insights that would not be resolved otherwise. The integrated single cell functional proteomic analysis constructed a detail kinetic picture of the immune response that took place during the clinical cancer immunotherapy. It revealed concrete functional evidence that connected genetics to IBD disease susceptibility. Further, it provided predictors that correlated with clinical responses and pathogenic outcomes.</p>
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Ooi, Amanda. "Characterization of Plant Growth under Single-Wavelength Laser Light Using the Model Plant Arabidopsis Thaliana." Diss., 2016. http://hdl.handle.net/10754/621945.

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Indoor horticulture offers a promising solution for sustainable food production and is becoming increasingly widespread. However, it incurs high energy and cost due to the use of artificial lighting such as high-pressure sodium lamps, fluorescent light or increasingly, the light-emitting diodes (LEDs). The energy efficiency and light quality of currently available lighting is suboptimal, therefore less than ideal for sustainable and cost-effective large-scale plant production. Here, we demonstrate the use of high-powered single-wavelength lasers for indoor horticulture. Lasers are highly energy-efficient and can be remotely guided to the site of plant growth, thus reducing on-site heat accumulation. Besides, laser beams can be tailored to match the absorption profiles of different plants. We have developed a prototype laser growth chamber and demonstrate that laser-grown plants can complete a full growth cycle from seed to seed with phenotypes resembling those of plants grown under LEDs. Importantly, the plants have lower expression of proteins diagnostic for light and radiation stress. The phenotypical, biochemical and proteomic data show that the singlewavelength laser light is suitable for plant growth and therefore, potentially able to unlock the advantages of this next generation lighting technology for highly energy-efficient horticulture. Furthermore, stomatal movement partly determines the plant productivity and stress management. Abscisic acid (ABA) induces stomatal closure by promoting net K+-efflux from guard cells through outwardrectifying K+ (K+ out) channels to regulate plant water homeostasis. Here, we show that the Arabidopsis thaliana guard cell outward-rectifying K+ (ATGORK) channel is a direct target for ABA in the regulation of stomatal aperture and hence gas exchange and transpiration. Addition of (±)-ABA, but not the biologically inactive (−)-isomer, increases K+ out channel activity in Vicia faba guard cell protoplast. A similar ABA-modulated K+ channel conductance was observed when ATGORK was heterologously expressed in human embryonic kidney 293 (HEK-293) cells. Alignment of ATGORK with known PYR/PYL/RCARs ABA receptors revealed that ATGORK harbors amino acid residues that are similar to those at the latchlike region of the ABA-binding sites. In ATGORK, the double mutations K559A and Y562A at the predicted ABA-interacting site impaired ABA-dependent channel activation and reduced the affinity for ABA in vitro.
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Wei, Wei. "Microfluidics-Based Single-Cell Functional Proteomics Microchip for Portraying Protein Signal Transduction Networks within the Framework of Physicochemical Principles, with Applications in Fundamental and Translational Cancer Research." Thesis, 2014. https://thesis.library.caltech.edu/8112/1/Wei_Wei_2014_thesis.pdf.

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<p>Single-cell functional proteomics assays can connect genomic information to biological function through quantitative and multiplex protein measurements. Tools for single-cell proteomics have developed rapidly over the past 5 years and are providing unique opportunities. This thesis describes an emerging microfluidics-based toolkit for single cell functional proteomics, focusing on the development of the single cell barcode chips (SCBCs) with applications in fundamental and translational cancer research.</p> <p>The microchip designed to simultaneously quantify a panel of secreted, cytoplasmic and membrane proteins from single cells will be discussed at the beginning, which is the prototype for subsequent proteomic microchips with more sophisticated design in preclinical cancer research or clinical applications. The SCBCs are a highly versatile and information rich tool for single-cell functional proteomics. They are based upon isolating individual cells, or defined number of cells, within microchambers, each of which is equipped with a large antibody microarray (the barcode), with between a few hundred to ten thousand microchambers included within a single microchip. Functional proteomics assays at single-cell resolution yield unique pieces of information that significantly shape the way of thinking on cancer research. An in-depth discussion about analysis and interpretation of the unique information such as functional protein fluctuations and protein-protein correlative interactions will follow.</p> <p>The SCBC is a powerful tool to resolve the functional heterogeneity of cancer cells. It has the capacity to extract a comprehensive picture of the signal transduction network from single tumor cells and thus provides insight into the effect of targeted therapies on protein signaling networks. We will demonstrate this point through applying the SCBCs to investigate three isogenic cell lines of glioblastoma multiforme (GBM).</p> <p>The cancer cell population is highly heterogeneous with high-amplitude fluctuation at the single cell level, which in turn grants the robustness of the entire population. The concept that a stable population existing in the presence of random fluctuations is reminiscent of many physical systems that are successfully understood using statistical physics. Thus, tools derived from that field can probably be applied to using fluctuations to determine the nature of signaling networks. In the second part of the thesis, we will focus on such a case to use thermodynamics-motivated principles to understand cancer cell hypoxia, where single cell proteomics assays coupled with a quantitative version of Le Chatelier's principle derived from statistical mechanics yield detailed and surprising predictions, which were found to be correct in both cell line and primary tumor model.</p> <p>The third part of the thesis demonstrates the application of this technology in the preclinical cancer research to study the GBM cancer cell resistance to molecular targeted therapy. Physical approaches to anticipate therapy resistance and to identify effective therapy combinations will be discussed in detail. Our approach is based upon elucidating the signaling coordination within the phosphoprotein signaling pathways that are hyperactivated in human GBMs, and interrogating how that coordination responds to the perturbation of targeted inhibitor. Strongly coupled protein-protein interactions constitute most signaling cascades. A physical analogy of such a system is the strongly coupled atom-atom interactions in a crystal lattice. Similar to decomposing the atomic interactions into a series of independent normal vibrational modes, a simplified picture of signaling network coordination can also be achieved by diagonalizing protein-protein correlation or covariance matrices to decompose the pairwise correlative interactions into a set of distinct linear combinations of signaling proteins (i.e. independent signaling modes). By doing so, two independent signaling modes – one associated with mTOR signaling and a second associated with ERK/Src signaling have been resolved, which in turn allow us to anticipate resistance, and to design combination therapies that are effective, as well as identify those therapies and therapy combinations that will be ineffective. We validated our predictions in mouse tumor models and all predictions were borne out.</p> <p>In the last part, some preliminary results about the clinical translation of single-cell proteomics chips will be presented. The successful demonstration of our work on human-derived xenografts provides the rationale to extend our current work into the clinic. It will enable us to interrogate GBM tumor samples in a way that could potentially yield a straightforward, rapid interpretation so that we can give therapeutic guidance to the attending physicians within a clinical relevant time scale. The technical challenges of the clinical translation will be presented and our solutions to address the challenges will be discussed as well. A clinical case study will then follow, where some preliminary data collected from a pediatric GBM patient bearing an EGFR amplified tumor will be presented to demonstrate the general protocol and the workflow of the proposed clinical studies.</p>
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Books on the topic "Single cell proteomics"

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Vegvari, Akos, Jaakko Teppo, and Roman A. Zubarev, eds. Mass Spectrometry Based Single Cell Proteomics. Springer US, 2024. http://dx.doi.org/10.1007/978-1-0716-3934-4.

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Proserpio, Valentina. Single Cell Methods: Sequencing and Proteomics. Springer New York, 2019.

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Proserpio, Valentina. Single Cell Methods: Sequencing and Proteomics. Springer New York, 2020.

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Vegvari, Akos, Jaakko Teppo, and Roman A. Zubarev. Mass Spectrometry Based Single Cell Proteomics. Springer, 2024.

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Shah, Haroun N., and Saheer E. Gharbia. Mass Spectrometry for Microbial Proteomics. Wiley & Sons, Limited, John, 2010.

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Shah, Haroun N., and Saheer E. Gharbia. Mass Spectrometry for Microbial Proteomics. Wiley & Sons, Incorporated, John, 2010.

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Shah, Haroun N., and Saheer E. Gharbia. Mass Spectrometry for Microbial Proteomics. Wiley & Sons, Incorporated, John, 2010.

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Shah, Haroun N., and Saheer E. Gharbia. Mass Spectrometry for Microbial Proteomics. Wiley & Sons, Incorporated, John, 2010.

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Shah, Haroun N., and Saheer E. Gharbia. Mass Spectrometry for Microbial Proteomics. Wiley & Sons, Incorporated, John, 2010.

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Shah, Haroun N., and Saheer E. Gharbia. Mass Spectrometry for Microbial Proteomics. Wiley & Sons, Incorporated, John, 2011.

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Book chapters on the topic "Single cell proteomics"

1

Dovichi, Norman J., Shen Hu, David Michels, Danqian Mao, and Amy Dambrowitz. "Single Cell Proteomics." In Proteomics for Biological Discovery. John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0470007745.ch12.

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Xu, Xiangdong, and Shen Hu. "Single-Cell Proteomics." In Handbook of Single Cell Technologies. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-10-4857-9_1-1.

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Xu, Xiangdong, and Shen Hu. "Single-Cell Proteomics." In Handbook of Single-Cell Technologies. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-10-8953-4_1.

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Thielert, Marvin, Caroline A. M. Weiss, Matthias Mann, and Florian A. Rosenberger. "Spatial Proteomics of Single Hepatocytes with Multiplexed Data-Independent Acquisition (mDIA)." In Mass Spectrometry Based Single Cell Proteomics. Springer US, 2024. http://dx.doi.org/10.1007/978-1-0716-3934-4_9.

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AbstractSpatially resolved mass spectrometry-based proteomics at single-cell resolution promises to provide insights into biological heterogeneity. We describe a protocol based on multiplexed data-independent acquisition (mDIA) with dimethyl labeling to enhance proteome depth, accuracy, and throughput while minimizing costs. It enables high-quality proteome analysis of single isolated hepatocytes and utilizes liver zonation for single-cell proteomics benchmarking. This adaptable, modular protocol will promote the use of single-cell proteomics in spatial biology.
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Mailloux, Shay, Lisa Ramirez, and Jun Wang. "Microfluidic Single-Cell Functional Proteomics." In Microfluidic Methods for Molecular Biology. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30019-1_7.

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Wang, Zheng, and Xiaoju Zhang. "Single Cell Proteomics for Molecular Targets in Lung Cancer: High-Dimensional Data Acquisition and Analysis." In Single Cell Biomedicine. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0502-3_7.

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Hartlmayr, David, Claudia Ctortecka, Rupert Mayer, Karl Mechtler, and Anjali Seth. "Label-Free Sample Preparation for Single-Cell Proteomics." In Mass Spectrometry Based Single Cell Proteomics. Springer US, 2024. http://dx.doi.org/10.1007/978-1-0716-3934-4_1.

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Lewandowski, Michael, Shad Morton, Matthew Blake, et al. "Single-Cell Proteomics Analysis with Tecan Uno and SCREEN Workflow." In Mass Spectrometry Based Single Cell Proteomics. Springer US, 2024. http://dx.doi.org/10.1007/978-1-0716-3934-4_13.

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Orsburn, Benjamin C. "Analyzing Posttranslational Modifications in Single Cells." In Mass Spectrometry Based Single Cell Proteomics. Springer US, 2024. http://dx.doi.org/10.1007/978-1-0716-3934-4_12.

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Marín-Vicente, Consuelo, Enrique Calvo, José Manuel Rodríguez, et al. "A Sample Preparation Procedure for Isobaric Labeling-Based Single-Cell Proteomics." In Mass Spectrometry Based Single Cell Proteomics. Springer US, 2024. http://dx.doi.org/10.1007/978-1-0716-3934-4_4.

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Conference papers on the topic "Single cell proteomics"

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Liu, Qiaoming, Yadong Wang, and Guohua Wang. "scEAGC: an efficient anchor graph clustering for single-cell transcriptomics and proteomics data." In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024. https://doi.org/10.1109/bibm62325.2024.10821751.

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Xu, Yan. "Nanofluidics for Single-Cell Proteomics with Single-Molecule Sensitivity." In The 7th International Multidisciplinary Conference on Optofluidics 2017. MDPI, 2017. http://dx.doi.org/10.3390/optofluidics2017-04528.

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Paryavi, Mohsen, Richie Chio, M. Rifur Rahman, Iain MacPherson, and Aaron T. Ohta. "Towards High-Throughput Single-Cell Proteomics Using Droplet Microfluidics." In 2020 IEEE 15th International Conference on Nano/Micro Engineered and Molecular System (NEMS). IEEE, 2020. http://dx.doi.org/10.1109/nems50311.2020.9419479.

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Bendall, Sean. "Abstract IA22: Single cell proteomics to capture human dysplasia and dysfunction." In Abstracts: AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; September 17-18, 2020. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.tumhet2020-ia22.

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Fava, A., C. Y. Lee, M. C. Marlin, et al. "OP0176 SINGLE-CELL SPATIAL PROTEOMICS IDENTIFIES INTRAGLOMERULAR MYELOID CELLS IN MEMBRANOUS LUPUS NEPHRITIS." In EULAR 2024 European Congress of Rheumatology, 12-15 June. Vienna, Austria. BMJ Publishing Group Ltd and European League Against Rheumatism, 2024. http://dx.doi.org/10.1136/annrheumdis-2024-eular.5685.

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Heath, James R., Wei Wei, Young Shik Shin, et al. "Abstract SY23-02: Nanotechnology and single cell proteomics as a diagnostic tool." In Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA. American Association for Cancer Research, 2014. http://dx.doi.org/10.1158/1538-7445.am2014-sy23-02.

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Liu, Yang, and Amy Herr. "DROPBLOT DESIGN INTEGRATES DROPLET MICROFLUIDICS WITH SINGLE-CELL ELECTROPHORESIS FOR TARGETED PROTEOMICS." In 2022 Solid-State, Actuators, and Microsystems Workshop. Transducer Research Foundation, 2022. http://dx.doi.org/10.31438/trf.hh2022.29.

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Heath, James R. "Abstract IA07: Single cell functional proteomics and metabolomics: A conduit to physicochemical models of tumor biology." In Abstracts: AACR Special Conference: Engineering and Physical Sciences in Oncology; June 25-28, 2016; Boston, MA. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.epso16-ia07.

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Raimo, Monica, Amanda van Vliet, Denise Vodegel, et al. "384 Single-cell transcriptomics, proteomics and in vitro cytotoxicity of allogeneic cryopreserved natural killer cell therapy GTA002 identify potent effector signatures." In SITC 38th Annual Meeting (SITC 2023) Abstracts. BMJ Publishing Group Ltd, 2023. http://dx.doi.org/10.1136/jitc-2023-sitc2023.0384.

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SU, Yapeng, Wei Wei, Lidia Robert, et al. "Abstract 2069: Overcoming drug resistance by targeting melanoma dedifferentiation through information-theoretic analysis and single cell proteomics." In Proceedings: AACR Annual Meeting 2017; April 1-5, 2017; Washington, DC. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.am2017-2069.

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Reports on the topic "Single cell proteomics"

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Frank, M. Single Cell Proteomics with Ultra-High Sensitivity Mass Spectrometry. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/15011526.

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Fulcher, James, Lye Meng Markillie, Hugh Mitchell, et al. Parallel measurement of transcriptomes and proteomes from same single cells using nanodroplet splitting. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/1998955.

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Epel, Bernard, and Roger Beachy. Mechanisms of intra- and intercellular targeting and movement of tobacco mosaic virus. United States Department of Agriculture, 2005. http://dx.doi.org/10.32747/2005.7695874.bard.

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To cause disease, plant viruses must replicate and spread locally and systemically within the host. Cell-to-cell virus spread is mediated by virus-encoded movement proteins (MPs), which modify the structure and function of plasmodesmata (Pd), trans-wall co-axial membranous tunnels that interconnect the cytoplasm of neighboring cells. Tobacco mosaic virus (TMV) employ a single MP for cell- cell spread and for which CP is not required. The PIs, Beachy (USA) and Epel (Israel) and co-workers, developed new tools and approaches for study of the mechanism of spread of TMV that lead to a partial identification and molecular characterization of the cellular machinery involved in the trafficking process. Original research objectives: Based on our data and those of others, we proposed a working model of plant viral spread. Our model stated that MPᵀᴹⱽ, an integral ER membrane protein with its C-terminus exposed to the cytoplasm (Reichel and Beachy, 1998), alters the Pd SEL, causes the Pd cytoplasmic annulus to dilate (Wolf et al., 1989), allowing ER to glide through Pd and that this gliding is cytoskeleton mediated. The model claimed that in absence of MP, the ER in Pd (the desmotubule) is stationary, i.e. does not move through the Pd. Based on this model we designed a series of experiments to test the following questions: -Does MP potentiate ER movement through the Pd? - In the presence of MP, is there communication between adjacent cells via ER lumen? -Does MP potentiate the movement of cytoskeletal elements cell to cell? -Is MP required for cell-to-cell movement of ER membranes between cells in sink tissue? -Is the binding in situ of MP to RNA specific to vRNA sequences or is it nonspecific as measured in vitro? And if specific: -What sequences of RNA are involved in binding to MP? And finally, what host proteins are associated with MP during intracellular targeting to various subcellular targets and what if any post-translational modifications occur to MP, other than phosphorylation (Kawakami et al., 1999)? Major conclusions, solutions and achievements. A new quantitative tool was developed to measure the "coefficient of conductivity" of Pd to cytoplasmic soluble proteins. Employing this tool, we measured changes in Pd conductivity in epidermal cells of sink and source leaves of wild-type and transgenic Nicotiana benthamiana (N. benthamiana) plants expressing MPᵀᴹⱽ incubated both in dark and light and at 16 and 25 ᵒC (Liarzi and Epel, 2005 (appendix 1). To test our model we measured the effect of the presence of MP on cell-to-cell spread of a cytoplasmic fluorescent probe, of two ER intrinsic membrane protein-probes and two ER lumen protein-probes fused to GFP. The effect of a mutant virus that is incapable of cell-to-cell spread on the spread of these probes was also determined. Our data shows that MP reduces SEL for cytoplasmic molecules, dilates the desmotubule allowing cell-cell diffusion of proteins via the desmotubule lumen and reduces the rate of spread of the ER membrane probes. Replicase was shown to enhance cell-cell spread. The data are not in support of the proposed model and have led us to propose a new model for virus cell-cell spread: this model proposes that MP, an integral ER membrane protein, forms a MP:vRNAER complex and that this ER-membrane complex diffuses in the lipid milieu of the ER into the desmotubule (the ER within the Pd), and spreads cell to cell by simple diffusion in the ER/desmotubule membrane; the driving force for spread is the chemical potential gradient between an infected cell and contingent non-infected neighbors. Our data also suggests that the virus replicase has a function in altering the Pd conductivity. Transgenic plant lines that express the MP gene of the Cg tobamovirus fused to YFP under the control the ecdysone receptor and methoxyfenocide ligand were generated by the Beachy group and the expression pattern and the timing and targeting patterns were determined. A vector expressing this MPs was also developed for use by the Epel lab . The transgenic lines are being used to identify and isolate host genes that are required for cell-to-cell movement of TMV/tobamoviruses. This line is now being grown and to be employed in proteomic studies which will commence November 2005. T-DNA insertion mutagenesis is being developed to identify and isolate host genes required for cell-to-cell movement of TMV.
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