4 resultados para proteome

em CaltechTHESIS


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In natural environments, bacterial physiology is frequently characterized by slow metabolic rates and complex cellular heterogeneities. The opportunistic pathogen Pseudomonas aeruginosa provides one such example; P. aeruginosa forms untreatable chronic biofilm infections of the cystic fibrosis lung, where oxygen limitation can lead to states of metabolic dormancy. To better understand the biology of these states, in vitro experiments must be adapted to better recapitulate natural settings. However, low rates of protein turnover and cellular or phenotypic complexity make these systems difficult to study using established methods. Here we adapt the bioorthogonal noncanonical amino acid tagging (BONCAT) method for time- and cell-selective proteomic analysis to the study of P. aeruginosa. Analysis of proteins synthesized in an anoxic dormancy state led to the discovery of a new type of transcriptional regulator which we designated SutA. We performed detailed analyses of SutA’s role in transcription under slow growth states and we elucidated the structural basis for its regulatory behavior. Additionally, we used cell-selective targeting of BONCAT labeling to measure the dynamic proteomic response of an antibiotic-tolerant biofilm subpopulation. Overall this work shows the utility of selective proteomics as applied to bacterial physiology and describes the broad biological insight obtained from that application.

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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.

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.

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.

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Cdc48/p97 is an essential, highly abundant hexameric member of the AAA (ATPase associated with various cellular activities) family. It has been linked to a variety of processes throughout the cell but it is best known for its role in the ubiquitin proteasome pathway. In this system it is believed that Cdc48 behaves as a segregase, transducing the chemical energy of ATP hydrolysis into mechanical force to separate ubiquitin-conjugated proteins from their tightly-bound partners.

Current models posit that Cdc48 is linked to its substrates through a variety of adaptor proteins, including a family of seven proteins (13 in humans) that contain a Cdc48-binding UBX domain. As such, due to the complexity of the network of adaptor proteins for which it serves as the hub, Cdc48/p97 has the potential to exert a profound influence on the ubiquitin proteasome pathway. However, the number of known substrates of Cdc48/p97 remains relatively small, and smaller still is the number of substrates that have been linked to a specific UBX domain protein. As such, the goal of this dissertation research has been to discover new substrates and better understand the functions of the Cdc48 network. With this objective in mind, we established a proteomic screen to assemble a catalog of candidate substrate/targets of the Ubx adaptor system.

Here we describe the implementation and optimization of a cutting-edge quantitative mass spectrometry method to measure relative changes in the Saccharomyces cerevisiae proteome. Utilizing this technology, and in order to better understand the breadth of function of Cdc48 and its adaptors, we then performed a global screen to identify accumulating ubiquitin conjugates in cdc48-3 and ubxΔ mutants. In this screen different ubx mutants exhibited reproducible patterns of conjugate accumulation that differed greatly from each other, pointing to various unexpected functional specializations of the individual Ubx proteins.

As validation of our mass spectrometry findings, we then examined in detail the endoplasmic-reticulum bound transcription factor Spt23, which we identified as a putative Ubx2 substrate. In these studies ubx2Δ cells were deficient in processing of Spt23 to its active p90 form, and in localizing p90 to the nucleus. Additionally, consistent with reduced processing of Spt23, ubx2Δ cells demonstrated a defect in expression of their target gene OLE1, a fatty acid desaturase. Overall, this work demonstrates the power of proteomics as a tool to identify new targets of various pathways and reveals Ubx2 as a key regulator lipid membrane biosynthesis.

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Bio-orthogonal non-canonical amino acid tagging (BONCAT) is an analytical method that allows the selective analysis of the subset of newly synthesized cellular proteins produced in response to a biological stimulus. In BONCAT, cells are treated with the non-canonical amino acid L-azidohomoalanine (Aha), which is utilized in protein synthesis in place of methionine by wild-type translational machinery. Nascent, Aha-labeled proteins are selectively ligated to affinity tags for enrichment and subsequently identified via mass spectrometry. The work presented in this thesis exhibits advancements in and applications of the BONCAT technology that establishes it as an effective tool for analyzing proteome dynamics with time-resolved precision.

Chapter 1 introduces the BONCAT method and serves as an outline for the thesis as a whole. I discuss motivations behind the methodological advancements in Chapter 2 and the biological applications in Chapters 2 and 3.

Chapter 2 presents methodological developments that make BONCAT a proteomic tool capable of, in addition to identifying newly synthesized proteins, accurately quantifying rates of protein synthesis. I demonstrate that this quantitative BONCAT approach can measure proteome-wide patterns of protein synthesis at time scales inaccessible to alternative techniques.

In Chapter 3, I use BONCAT to study the biological function of the small RNA regulator CyaR in Escherichia coli. I correctly identify previously known CyaR targets, and validate several new CyaR targets, expanding the functional roles of the sRNA regulator.

In Chapter 4, I use BONCAT to measure the proteomic profile of the quorum sensing bacterium Vibrio harveyi during the time-dependent transition from individual- to group-behaviors. My analysis reveals new quorum-sensing-regulated proteins with diverse functions, including transcription factors, chemotaxis proteins, transport proteins, and proteins involved in iron homeostasis.

Overall, this work describes how to use BONCAT to perform quantitative, time-resolved proteomic analysis and demonstrates that these measurements can be used to study a broad range of biological processes.