American dream and German nightmare? identity, gender, and memory in the autobiographic work of Esmeralda Santiago and Emine Sevgi Ozdamar

This thesis compares the autobiographic work of Esmeralda Santiago and Emine Sevgi Özdamar focusing on the aspects of ethnic identity, gender, as well as history and memory. The argument is that both authors' work not only reflects the cultural origins of each writer and her trauma of loss, but also each host country's social realities and conflicts. In spite of alienation and loss of home and language, both protagonists create "touching tales," a phrase coined by Leslie Adelson that refers to the entanglement between cultures, stressing more the common ground between them than the differences. Santiago's work stresses the dividedness of American society along racial and ethnic lines, but also the opportunity for the immigrant to reinvent herself and overcome racial and social boundaries. Özdamar on the other hand reflects on the dividedness and traumatization of Germany through World War II, the Holocaust, the East-West division, and the terrorism of the 1970s. She compares it to the political and social division within Turkey as results of the Armenian genocide and military coups. While Santiago views American culture with distance, Özdamar displays an enthusiastic reception of leftist writers like Bertolt Brecht and German literature in general. Both autobiographical subjects find a way to reconcile their own inner divisions through theater work, which combines universal and multicultural elements

Practical applications of genomics to natural product discovery and biosynthesis

Natural products, generally defined as metabolites of biotic origin, have a long history as medicines and have remained a fruitful source of new drug leads for multiple diseases in the modern age. Arguably the largest asset of natural products, and a pitfall of synthetic compound libraries, is the remarkable diversity of structure and chemical group functionality that discloses them as Nature’s handiwork and is critical for the bioactivities that many of them possess. Despite this precedent, characterization of new chemical entities is met with a significant challenge: rediscovery of known compounds. For compound discovery to continue translating to useful, practical chemical matter, it is essential that strides be made to streamline and augment current methodology to prioritize novelty. Modern genomics provides a potential resolution to these issues: as the financial and technical hurdles for whole-genome sequencing are reduced, annotating the biosynthetic capabilities of sequenced organisms becomes more accessible and reliable. It follows that gene clusters can be analyzed before undertaking efforts to isolate and characterize compounds, minimizing costs and resources. However, this approach is dependent upon a robust understanding of gene function as it translates to natural product structure, and assignment of biosynthetic enzyme/cluster function is drastically outpaced by the availability of genome sequences, leading to an excess of genomic data that cannot be optimally exploited. We describe the current state of these challenges as it relates to the discovery of new natural products in Chapter 1, and developments in “reverse genetics” techniques which seek to address these shortcomings. Our group has developed a platform to automate analysis of biosynthetic gene clusters and structure prediction, described in Chapter 2, which we applied to an understudied family of natural products. RODEO (Rapid ORF Description and Evaluation Online) was designed as a practical tool for high-throughput analysis of natural product gene clusters, and initially focused on lasso peptides, where our application of hidden Markov models, heuristic and sequence motif analysis, and machine learning revealed new scaffolds. This genome-mining approach enabled by RODEO prioritized strains with unique biosynthetic clusters and predicted lasso peptides, resulting in the isolation of six new compounds with unique structural features including one with a new ribosomal peptide post-translational modification and another with an unprecedented “handcuff” topology. In Chapter 3, a family of bioinformatically-identified prenyltransferases is investigated that has members in several bacterial pathogens. Starting from genomic data, these terpenoid synthase enzymes are biochemically characterized and found to be functionally divergent from previously identified examples. Sequence analysis suggests residues which are believed to influence activity, and mutagenesis was used to provide a starting point for correlating residues to catalysis. The enzyme family responsible for formation of azol(in)e heterocycles in ribosomal peptide natural products is revealed in Chapter 4 to have a new biosynthetic role. Characterization of the bottromycin heterocyclases suggest an instance of Nature using a common amide-backbone activation mechanism for different reactions - in this case a macroamidine heterocyclization. Substrate tolerance and recognition are explored for the unique substrate, which contains bipartite peptide regions for modification and binding by the enzymes. More broadly, the genomic distribution of atypical heterocyclases are investigated, indicating a high probability of discovering more examples of new biosynthetic chemistry and consequently, new natural product scaffolds. In Chapter 5, we extend this approach to a different area of YcaO biosynthetic enzymes which are implicated to not perform heterocyclizations at all, but instead appear to utilize this mechanism to induce thioamidation, an uncommon and divergent post-translational modification. Genetic evidence is found which supports the “TfuA-associated YcaOs” as a subfamily capable of thioamidation of ribosomal natural products. Whole genome sequencing of “orphan” natural products containing thioamides but no associated gene clusters revealed consistent presence of both TfuA-YcaO genes. The co-occurrence of the TfuA-YcaO pair were then used to guide screening for new natural products containing thioamides and aid in the structural identification of a novel thiopeptide with this post-translational modification

Progress Report on Study of Water in the Santa Cruz Valley Arizona

This item is part of the Agricultural Experiment Station archive. It was digitized from a physical copy provided by the University Libraries at the University of Arizona. For more information, please email CALS Publications at [email protected]

In vitro biosynthetic studies of bottromycin expand the enzymatic capabilities of the YcaO superfamily

The bottromycins belong to the ribosomally synthesized and posttranslationally modified peptide (RiPP) family of natural products. Bottromycins exhibit unique structural features, including a hallmark macrolactamidine ring and thiazole heterocycle for which divergent members of the YcaO superfamily have been biosynthetically implicated. Here we report the in vitro reconstitution of two YcaO proteins, BmbD and BmbE, responsible for the ATP-dependent cyclodehydration reactions that yield thiazoline- and macrolactamidine-functionalized products, respectively. We also establish the substrate tolerance for BmbD and BmbE and systematically dissect the role of the follower peptide, which we show serves a purpose similar to canonical leader peptides in directing the biosynthetic enzymes to the substrate. Lastly, we leverage the expanded capabilities of YcaO proteins to conduct an extensive bioinformatic survey to classify known YcaO chemistry. This analysis predicts new functions remain to be uncovered within the superfamily

antiSMASH 4.0—improvements in chemistry prediction and gene cluster boundary identification

Many antibiotics, chemotherapeutics, crop protection agents and food preservatives originate from molecules produced by bacteria, fungi or plants. In recent years, genome mining methodologies have been widely adopted to identify and characterize the biosynthetic gene clusters encoding the production of such compounds. Since 2011, the ‘antibiotics and secondary metabolite analysis shell—antiSMASH’ has assisted researchers in efficiently performing this, both as a web server and a standalone tool. Here, we present the thoroughly updated antiSMASH version 4, which adds several novel features, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CASSIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, improved predictions for terpene and ribosomally synthesized and post-translationally modified peptides cluster products, reporting of sequence similarity to proteins encoded in experimentally characterized gene clusters on a per-protein basis and a domain-level alignment tool for comparative analysis of trans-AT polyketide synthase assembly line architectures. Additionally, several usability features have been updated and improved. Together, these improvements make antiSMASH up-to-date with the latest developments in natural product research and will further facilitate computational genome mining for the discovery of novel bioactive molecules

An antibiotic from an uncultured bacterium binds to an immutable target

Antimicrobial resistance is a leading mortality factor worldwide. Here, we report the discovery of clovibactin, an antibiotic isolated from uncultured soil bacteria. Clovibactin efficiently kills drug-resistant Gram-positive bacterial pathogens without detectable resistance. Using biochemical assays, solid-state nuclear magnetic resonance, and atomic force microscopy, we dissect its mode of action. Clovibactin blocks cell wall synthesis by targeting pyrophosphate of multiple essential peptidoglycan precursors (C 55PP, lipid II, and lipid III WTA). Clovibactin uses an unusual hydrophobic interface to tightly wrap around pyrophosphate but bypasses the variable structural elements of precursors, accounting for the lack of resistance. Selective and efficient target binding is achieved by the sequestration of precursors into supramolecular fibrils that only form on bacterial membranes that contain lipid-anchored pyrophosphate groups. This potent antibiotic holds the promise of enabling the design of improved therapeutics that kill bacterial pathogens without resistance development. </p

Ex Vivo Metrics™, a preclinical tool in new drug development

Among the challenges facing translational medicine today is the need for greater productivity and safety during the drug development process. To meet this need, practitioners of translational medicine are developing new technologies that can facilitate decision making during the early stages of drug discovery and clinical development. Ex Vivo Metrics™ is an emerging technology that addresses this need by using intact human organs ethically donated for research. After hypothermic storage, the organs are reanimated by blood perfusion, providing physiologically and biochemically stable preparations. In terms of emulating human exposure to drugs, Ex Vivo Metrics is the closest biological system available for clinical trials. Early application of this tool for evaluating drug targeting, efficacy, and toxicity could result in better selection among promising drug candidates, greater drug productivity, and increased safety

Gene expression profiling for molecular distinction and characterization of laser captured primary lung cancers

<p>Abstract</p> <p>Methods</p> <p>We examined gene expression profiles of tumor cells from 29 untreated patients with lung cancer (10 adenocarcinomas (AC), 10 squamous cell carcinomas (SCC), and 9 small cell lung cancer (SCLC)) in comparison to 5 samples of normal lung tissue (NT). The European and American methodological quality guidelines for microarray experiments were followed, including the stipulated use of laser capture microdissection for separation and purification of the lung cancer tumor cells from surrounding tissue.</p> <p>Results</p> <p>Based on differentially expressed genes, different lung cancer samples could be distinguished from each other and from normal lung tissue using hierarchical clustering. Comparing AC, SCC and SCLC with NT, we found 205, 335 and 404 genes, respectively, that were at least 2-fold differentially expressed (estimated false discovery rate: < 2.6%). Different lung cancer subtypes had distinct molecular phenotypes, which also reflected their biological characteristics. Differentially expressed genes in human lung tumors which may be of relevance in the respective lung cancer subtypes were corroborated by quantitative real-time PCR.</p> <p>Genetic programming (GP) was performed to construct a classifier for distinguishing between AC, SCC, SCLC, and NT. Forty genes, that could be used to correctly classify the tumor or NT samples, have been identified. In addition, all samples from an independent test set of 13 further tumors (AC or SCC) were also correctly classified.</p> <p>Conclusion</p> <p>The data from this research identified potential candidate genes which could be used as the basis for the development of diagnostic tools and lung tumor type-specific targeted therapies.</p