Molecular biotechnology

Permanent URI for this collectionhttps://digital.lib.washington.edu/handle/1773/4944

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    Implications of myelin basic protein processing and presentation on T cell activation and tolerance
    (2004) Seamons, Audrey
    Experimental autoimmune encephalomyelitis (EAE) is an animal model for multiple sclerosis which can be induced by immunization with myelin antigens such as myelin basic protein (MBP). Immune tolerance influences the repertoire of MBP-specific T cells in B10.PL mice. MBPAc1--11-specific T cells escape tolerance while MBP121--150-specific T cells undergo tolerance in vivo. This differential tolerance induction may reflect unstable binding of MBPAc1--11 to I-Au compared to stable binding of peptides within MBP121--150.To determine which MBP epitopes are naturally processed from whole MBP, peptides eluted from I-Au isolated from MBP-pulsed splenocytes were analyzed by mass spectrometry. Two nested sets of peptides were found, N-terminal MBP peptides and peptides containing MBP125--135. N-terminal peptides MBPAc1--18 and MBPAc1--17 were the most abundant peptides processed from whole MBP. Our investigations indicate that MBPAc1--18 can bind in the register that presents MBPAc1--11, however, most MBPAc1--18 binds in a more stable register, MBP5--16, allowing MBPAc1--11-specific T cells to escape tolerance. Additionally, endogenously derived MBP peptides are constitutively presented by B cells and dendritic cells (DCs) which are able to stimulate activated MBP121--150-specific T cells. However, only DCs are able to stimulate naive MBP121--150-specific T cells, implicating DCs as the antigen presenting cell involved in the maintenance of peripheral tolerance to MBP.To investigate why two different MBPAc1--11-specific T cell receptor transgenic mouse lines exhibit differences in spontaneous EAE incidence, T cell responses to MBP were compared between the two lines. While differences in T cell proliferative responses were not detected, T cells isolated from the Tg line with lower spontaneous EAE incidence did not produce IFN-gamma and lower percentages of T cells produced cytokines compared to the line with higher incidence of spontaneous EAE.We also analyzed the structural basis for cross-reactivity exhibited by T cells recognizing two distinct epitopes within MBP121--150. Mutational analysis of the CDRI and 3 regions of one cross-reactive T cell receptor indicated that the same amino acids within CDR1 and 3 are used to recognize both epitopes.
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    Genomic analysis by single cell flow sorting
    (2003) Choe, Juno
    The Human Genome Project has dramatically changed the landscape of biology. With the availability of genomic sequence from humans and many other organisms, new biological questions are being asked that involve the simultaneous study of thousands of genes or proteins. The invention of new technologies continues to be important for the timely investigation of many of these questions.In this work, we present new technologies that address several genomcs-level questions using electronic cell sorters. Because these machines are capable of examining and sorting tens of thousands of cells per second, they are potentially ideal platforms for investigating large systems. The challenge lies in converting biological attributes into readable physical attributes. In this work, we present the development of a series of plasmid vectors that encode biological states as the ratio of two fluorescent proteins in E. coli.Using this doctrine, we created the pGRFP series of vectors that can be used to rapidly isolate insert-bearing clones on an electronic cell sorter. This technique is a powerful alternative to traditional colony picking based on blue/white color selection. The speed of the electronic cell sorter allows us to deposit single cells into tubes as fast as the tubes can be transported. We validate this method's precision is selecting insert-bearing clones and show its usefulness in a small sequencing project.We also show how the pGRFP series vectors can be used to classify a large number of protein mutants. We sequenced hundreds of active mutants of a human enzyme. From these data, we introduce the concept of the "x-factor" that indicates a particular protein's tolerance to mutation. We are able to make striking correlations between the pattern of mutability throughout the enzyme and what is known about its 3D structure and mechanism of action.Finally, we present the pGFPpDsRed series of vectors that show promise in detecting DNA-Protein interactions. This might make a very useful tool for scanning genomic DNA for transcription factor binding sites on the road to solving regulatory networks. Conversely, a large number of protein mutants could be searched quickly to find variants that bind to a specific DNA sequence.
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    Bioinformatics of proteomic tandem mass spectra: selection, characterization, and identification
    (2003) Tabb, David L
    Tandem mass spectrometry is a powerful technology for proteomics. Quadrupole ion traps can isolate ions of a particular peptide, fragment them through collision-induced dissociation, and catalog the fragment ions in tandem mass spectra. Database search algorithms such as Mascot and SEQUEST can then identify the peptides represented by a collection of these spectra. These spectra, however, have not been extensively characterized, leading to inaccuracies in the ways these algorithms model fragment ions. In this body of research, a new algorithm, "DTASelect," was created to summarize, filter, and compare the identifications produced by database search algorithms. The extent and significance of spectral similarity in proteomic collections was explored. A set of well-identified peptides was statistically characterized to demonstrate the impact of peptide sequence on fragmentation. This information led to the creation of a new fragmentation model, which made possible a new algorithm, "GutenTag," to identify peptides via an automated, accurate sequence tagging approach. Taken together, this research shows that more accurate models of fragmentation can both improve existing algorithms and make new classes of algorithms feasible.