The dynamic organization of fungal acetyl-CoA carboxylase

Acetyl-CoA carboxylases (ACCs) catalyse the committed step in fatty-acid biosynthesis: the ATP-dependent carboxylation of acetyl-CoA to malonyl-CoA. They are important regulatory hubs for metabolic control and relevant drug targets for the treatment of the metabolic syndrome and cancer. Eukaryotic ACCs are single-chain multienzymes characterized by a large, non-catalytic central domain (CD), whose role in ACC regulation remains poorly characterized. Here we report the crystal structure of the yeast ACC CD, revealing a unique four-domain organization. A regulatory loop, which is phosphorylated at the key functional phosphorylation site of fungal ACC, wedges into a crevice between two domains of CD. Combining the yeast CD structure with intermediate and low-resolution data of larger fragments up to intact ACCs provides a comprehensive characterization of the dynamic fungal ACC architecture. In contrast to related carboxylases, large-scale conformational changes are required for substrate turnover, and are mediated by the CD under phosphorylation control

Structural studies on the target of rapamycin complex 1

Proteins are the functional units executing the genetic program of living cells. Protein activity has to be modulated and adapted to environmental and intracellular conditions throughout the life cycle of every cell. In higher eukaryotes, complex multidomain proteins and multisubunit complexes have evolved to integrate large numbers of input signals to control key steps in metabolism, growth and proliferation. Structural studies of authentic eukaryotic multidomain proteins are required to understand their emergent properties resulting from interdomain and intersubunit crosstalk and conformational dynamics. However, due to problems in sample preparation and characterization, resolving the structures of large eukaryotic protein assemblies remains a considerable challenge. This thesis provides novel structural and mechanistic insights to three highly relevant eukaryotic protein systems, based on integrative multimethod approaches to tackle the inherent complexity of each case. Mammalian target of rapamycin (mTOR) is the master regulator of growth and proliferation; it senses nutrient and growth signals and in response mediates the switch between anabolism and catabolism. Dysregulation of mTOR signaling is implicated in metabolic diseases and cancer, and mTOR is an established drug target. mTOR is comprised in two structurally and functionally distinct signaling complexes, mTORC1 and mTORC2. In Chapter 2, we determine the structure of the human mTORC1, containing the protein subunits mTOR, Raptor and mLST8, bound to FKBP12, by combining cryo-electron microscopy of the assembled complex at 5.9 Å resolution and crystallographic studies of the 149 kDa Raptor from Chaetomium thermophilum at 4.3 Å resolution. The core scaffold of the complex is formed by mTOR; the Raptor N-terminal conserved (RNC) domain is bound in vicinity to the mTOR catalytic site, suggesting a key role of the RNC in substrate recognition and delivery. Polo-like kinase 4 (PLK4) is a central controller of centriole duplication. Chapter 3 identifies a mechanism for PLK4 regulation by the partner protein STIL by using biochemical mapping, kinase assays, super resolution microscopy, isothermal calorimetry in combination with structural studies of the interaction of the PLK4- polobox 3 (PB3) domain with a coiled-coil region of STIL (STIL-CC). NMR 5 spectroscopy provides a solution structure of the isolated PLK4-PB3 and crystallographic structure determination reveals the mode of complex formation of PLK4-PB3 and STIL-CC. Mutations in STIL-CC abrogate the interaction to PB3 and diminish centriole duplication in cells, demonstrating the relevance of the PLK4-STIL interaction for centriole duplication. Acetyl-CoA carboxylase (ACC) catalyzes the conversion of acetyl-CoA to malonyl- CoA, providing the building blocks for fatty acid synthesis. Eukaryotic ACCs are large multidomain proteins, that comprise a unique 120 kDa regulatory central domain (CD) besides the N- and C-terminal catalytic domains biotin carboxylase (BC) and carboxyl transferase (CT). In chapter 4 we determine the structure of the human and yeast CD and provide intermediate resolution crystal structures of up to nearly full-length ACC from Chaetomium thermophilum. In combination with functional assays, these data reveal the structural basis for phosphorylation-dependent control of yeast ACC activity. In summary, the results presented in this thesis provide new structural and mechanistic insights into crucial eukaryote-specific regulatory properties of large multidomain proteins and protein complexes. These studies open important routes for further dissecting functional mechanisms by targeted biochemical and biophysical approaches. In particular for mTORC1, the current results provide a basis for analyzing the interactions with signaling partner proteins. Interdomain crosstalk and regulated protein conformational dynamics in these systems are closely linked to disease. Targeting interdomain interactions may serve as a relevant strategy for therapeutic intervention, e. g. in cancer therapy. The detailed depiction of intact assemblies of ACC and mTORC1 provides the structural groundworks for such approaches

Prozessentwicklung und -übertragung vom 50-ml- auf den 10-l-Maßstab: Antikörper-Produktion in Pflanzenzellen

Engineered plant cells can be used in order to produce antibodies. Suitable methods for process development and scale-up allow fast production of pre-clinical antibody samples in single-use bioreactor

Tuning-Robust Initialization Methods for Speaker Diarization

This paper investigates a typical speaker diarization system regarding its robustness against initialization parameter variation and presents a method to reduce manual tuning of these values significantly. The behavior of an agglomerative hierarchical clustering system is studied to determine which initialization parameters impact accuracy most. We show that the accuracy of typical systems is indeed very sensitive to the values chosen for the initialization parameters and factors such as the duration of speech in the recording. We then present a solution that reduces the sensitivity of the initialization values and therefore reduces the need for manual tuning significantly while at the same time increasing the accuracy of the system. For short meetings extracted from the previous (2006, 2007, and 2009) National Institute of Standards and Technology (NIST) Rich Transcription (RT) evaluation data, the decrease of the diarization error rate is up to 50% relative. The approach consists of a novel initialization parameter estimation method for speaker diarization that uses agglomerative clustering with Bayesian information criterion (BIC) and Gaussian mixture models (GMMs) of frame-based cepstral features (MFCCs). The estimation method balances the relationship between the optimal value of the seconds of speech data per Gaussian and the duration of the speech data and is combined with a novel nonuniform initialization method. This approach results in a system that performs better than the current ICSI baseline engine on datasets of the NIST RT evaluations of the years 2006, 2007, and 2009

Robust Speaker Diarization for Short Speech Recordings

We investigate a state-of-the-art Speaker Diarization system regarding its behavior on meetings that are much shorter (from 500 seconds down to 100 seconds) than those typically analyzed in Speaker Diarization benchmarks. First, the problems inherent to this task are analyzed. Then, we propose an approach that consists of a novel initialization parameter estimation method for typical state-of-the-art diarization approaches. The estimation method balances the relationship between the optimal value of the duration of speech data per Gaussian and the duration of the speech data, which is verified experimentally for the first time in this article. As a result, the Diarization Error Rate for short meetings extracted from the 2006, 2007, and 2009 NIST RT evaluation data is decreased by up to 50% relative

Leveraging speaker diarization for meeting recognition from distant microphones

ABSTRACT We investigate using state-of-the-art speaker diarization output for speech recognition purposes. While it seems obvious that speech recognition could benefit from the output of speaker diarization ("Who spoke when") for effective feature normalization and model adaptation, such benefits have remained elusive in the very challenging domain of meeting recognition from distant microphones. In this study, we show that recognition gains are possible by careful postprocessing of the diarization output. Still, recognition accuracy may suffer when the underlying diarization system performs worse than expected, even compared to far less sophisticated speaker-clustering techniques. We obtain a more accurate and robust overall system by combining recognition output with multiple speaker segmentations and clusterings. We evaluate our methods on data from the 2009 NIST Rich Transcription meeting recognition evaluation