Structural and biochemical studies of zinc finger-DNA complexes

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 1998.Vita.Includes bibliographical references.by Monica Elrod-Erickson.Ph.D

Regulation of COPII vesicle formation and protein sorting by the BST genes in Saccharomyces cerevisiae

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 1998.Includes bibliographical references.by Matthew J. Elrod-Erickson.Ph.D

Assessment of the optimization of affinity and specificity at protein–DNA interfaces

The biological functions of DNA-binding proteins often require that they interact with their targets with high affinity and/or high specificity. Here, we describe a computational method that estimates the extent of optimization for affinity and specificity of amino acids at a protein–DNA interface based on the crystal structure of the complex, by modeling the changes in binding-free energy associated with all individual amino acid and base substitutions at the interface. The extent to which residues are predicted to be optimal for specificity versus affinity varies within a given protein–DNA interface and between different complexes, and in many cases recapitulates previous experimental observations. The approach provides a complement to traditional methods of mutational analysis, and should be useful for rapidly formulating hypotheses about the roles of amino acid residues in protein–DNA interfaces

Optimization of minimum set of protein–DNA interactions: a quasi exact solution with minimum over-fitting

Motivation: A major limitation in modeling protein interactions is the difficulty of assessing the over-fitting of the training set. Recently, an experimentally based approach that integrates crystallographic information of C2H2 zinc finger–DNA complexes with binding data from 11 mutants, 7 from EGR finger I, was used to define an improved interaction code (no optimization). Here, we present a novel mixed integer programming (MIP)-based method that transforms this type of data into an optimized code, demonstrating both the advantages of the mathematical formulation to minimize over- and under-fitting and the robustness of the underlying physical parameters mapped by the code

The Emp24 Complex Recruits a Specific Cargo Molecule into Endoplasmic Reticulum–Derived Vesicles

Members of the yeast p24 family, including Emp24p and Erv25p, form a heteromeric complex required for the efficient transport of selected proteins from the endoplasmic reticulum (ER) to the Golgi apparatus. The specific functions and sites of action of this complex are unknown. We show that Emp24p is directly required for efficient packaging of a lumenal cargo protein, Gas1p, into ER-derived vesicles. Emp24p and Erv25p can be directly cross-linked to Gas1p in ER-derived vesicles. Gap1p, which was not affected by emp24 mutation, was not cross-linked. These results suggest that the Emp24 complex acts as a cargo receptor in vesicle biogenesis from the ER

Impact of Software Modeling on the Accuracy of Perfusion MRI in Glioma

PURPOSE: To determine whether differences in modeling implementation will impact the correction of leakage effects (from blood brain barrier disruption) and relative cerebral blood volume (rCBV) calculations as measured on T2*-weighted dynamic susceptibility-weighted contrast-enhanced (DSC)-MRI at 3T field strength. MATERIALS AND METHODS: This HIPAA-compliant study included 52 glioma patients undergoing DSC-MRI. Thirty-six patients underwent both non Preload Dose (PLD) and PLD-corrected DSC acquisitions, with sixteen patients undergoing PLD-corrected acquisitions only. For each acquisition, we generated two sets of rCBV metrics using two separate, widely published, FDA-approved commercial software packages: IB Neuro (IBN) and NordicICE (NICE). We calculated 4 rCBV metrics within tumor volumes: mean rCBV, mode rCBV, percentage of voxels with rCBV > 1.75 (%>1.75), and percentage of voxels with rCBV > 1.0 (Fractional Tumor Burden or FTB). We determined Pearson (r) and Spearman (ρ) correlations between non-PLD- and PLD-corrected metrics. In a subset of recurrent glioblastoma patients (n=25), we determined Receiver Operator Characteristic (ROC) Areas-Under-Curve (AUC) for FTB accuracy to predict the tissue diagnosis of tumor recurrence versus post-treatment effect (PTRE). We also determined correlations between rCBV and microvessel area (MVA) from stereotactic biopsies (n=29) in twelve patients. RESULTS: Using IBN, rCBV metrics correlated highly between non-PLD- and PLD-corrected conditions for FTB (r=0.96, ρ=0.94), %>1.75 (r=0.93, ρ=0.91), mean (r=0.87, ρ=0.86) and mode (r=0.78, ρ=0.76). These correlations dropped substantially with NICE. Using FTB, IBN was more accurate than NICE in diagnosing tumor vs PTRE (AUC=0.85 vs 0.67) (p<0.01). The highest rCBV-MVA correlations required PLD and IBN (r=0.64, ρ=0.58, p=0.001). CONCLUSIONS: Different implementations of perfusion MRI software modeling can impact the accuracy of leakage correction, rCBV calculation, and correlations with histologic benchmarks

A tunable zinc finger-based framework for Boolean logic computation in mammalian cells

The ability to perform molecular-level computation in mammalian cells has the potential to enable a new wave of sophisticated cell-based therapies and diagnostics. To this end, we developed a Boolean logic framework utilizing artificial Cys2–His2 zinc finger transcription factors (ZF-TFs) as computing elements. Artificial ZFs can be designed to specifically bind different DNA sequences and thus comprise a diverse set of components ideal for the construction of scalable networks. We generate ZF-TF activators and repressors and demonstrate a novel, general method to tune ZF-TF response by fusing ZF-TFs to leucine zipper homodimerization domains. We describe 15 transcriptional activators that display 2- to 463-fold induction and 15 transcriptional repressors that show 1.3- to 16-fold repression. Using these ZF-TFs, we compute OR, NOR, AND and NAND logic, employing hybrid promoters and split intein-mediated protein splicing to integrate signals. The split intein strategy is able to fully reconstitute the ZF-TFs, maintaining them as a uniform set of computing elements. Together, these components comprise a robust platform for building mammalian synthetic gene circuits capable of precisely modulating cellular behavior

ZiFiT (Zinc Finger Targeter): an updated zinc finger engineering tool

ZiFiT (Zinc Finger Targeter) is a simple and intuitive web-based tool that provides an interface to identify potential binding sites for engineered zinc finger proteins (ZFPs) in user-supplied DNA sequences. In this updated version, ZiFiT identifies potential sites for ZFPs made by both the modular assembly and OPEN engineering methods. In addition, ZiFiT now integrates additional tools and resources including scoring schemes for modular assembly, an interface with the Zinc Finger Database (ZiFDB) of engineered ZFPs, and direct querying of NCBI BLAST servers for identifying potential off-target sites within a host genome. Taken together, these features facilitate design of ZFPs using reagents made available to the academic research community by the Zinc Finger Consortium. ZiFiT is freely available on the web without registration at http://bindr.gdcb.iastate.edu/ZiFiT/

DLocalMotif: a discriminative approach for discovering local motifs in protein sequences

Motivation: Local motifs are patterns of DNA or protein sequences that occur within a sequence interval relative to a biologically defined anchor or landmark. Current protein motif discovery methods do not adequately consider such constraints to identify biologically significant motifs that are only weakly over-represented but spatially confined. Using negatives, i.e. sequences known to not contain a local motif, can further increase the specificity of their discovery

Secreted Bacterial Effectors and Host-Produced Eiger/TNF Drive Death in a Salmonella-Infected Fruit Fly

Death by infection is often as much due to the host's reaction as it is to the direct result of microbial action. Here we identify genes in both the host and microbe that are involved in the pathogenesis of infection and disease in Drosophila melanogaster challenged with Salmonella enterica serovartyphimurium (S. typhimurium). We demonstrate that wild-type S. typhimurium causes a lethal systemic infection when injected into the hemocoel of D. melanogaster. Deletion of the gene encoding the secreted bacterial effector Salmonella leucine-rich (PslrP) changes an acute and lethal infection to one that is persistent and less deadly. We propose a model in which Salmonella secreted effectors stimulate the fly and thus cause an immune response that is damaging both to the bacteria and, subsequently, to the host. In support of this model, we show that mutations in the fly gene eiger, a TNF homolog, delay the lethality of Salmonella infection. These results suggest that S. typhimurium-infected flies die from a condition that resembles TNF-induced metabolic collapse in vertebrates. This idea provides us with a new model to study shock-like biology in a genetically manipulable host. In addition, it allows us to study the difference in pathways followed by a microbe when producing an acute or persistent infection