Adaptability of metabolic networks in evolution and disease

There are 114.101 small molecule metabolites currently annotated in the Human Metabolome Database, which are highly connected amongst each other, with a few metabolites exhibiting an estimated number of more than 103 connections. Redundancy and plasticity are essential features of metabolic networks enabling cells to respond to fluctuating environments, presence of toxic molecules, or genetic perturbations like mutations. These system-level properties are inevitably linked to all aspects of biological systems ensuring cell viability by enabling processes like adaption and differentiation. To this end, the ability to interrogate molecular changes at omics level has opened new opportunities to study the cell at its different layers from the epigenome and transcriptome to its proteome and metabolome. In this thesis, I tackled the question how redundancy and plasticity shape adaptation in metabolic networks in evolutionary and disease contexts. I utilize a multi-omics approach to study comprehensively the metabolic state of a cell and its regulation at the transcriptional and proteomic level. One of the challenges with multi-omics approaches is the integration and interpretation of multi-layered data sets. To approach this challenge, I use genome scale metabolic models as a knowledge-based scaffold to overlay omics data and thereby to enable biological interpretation beyond statistical correlation. This integrative methodology has been applied to two different projects, namely the evolutionary adaptation towards a nutrient source in yeast and the metabolic adaptations following disease progression. For the latter, I also curated a current human genome-scale metabolic model and made it more suitable for flux predictions. In the yeast case study, I investigate the metabolic network adaptations enabling yeast to grow on an alternative carbon source – glycerol. I could show that network redundancy is one of the key features of fast adaptation of the yeast metabolic network to the new nutrient environment. Genomics, transcriptomics, proteomics, metabolomics and metabolic modeling together revealed a shift of the organism’s redox-balance under glycerol consumption as a driving force of adaption, which can be linked to the causal mutation in the enzyme Kgd1. On the other hand, the limitations of metabolic network adaptation also became apparent since all evolved and adapted strains exhibited metabolic trade-offs in other environmental conditions than the adaptation niche. Either an impaired diauxic shift (as in the case of the glycerol mutant) or an increased sensitivity towards osmotic stress (caused by mutations in the HOG pathway) was coupled with efficient use of glycerol. In the second project, the molecular phenotype of regressed breast cancer cells was studied to identify what differentiates these cells from healthy breast tissue and to characterize the potential source of tumor recurrence. Using a breast cancer mouse model with inducible oncogenes, transcriptomics together with an extensive set of different types of metabolomics (targeted and untargeted metabolomics, lipidomics and fluxomics) could show that regressed cancer cells, albeit their apparently normal morphology, possess a highly altered molecular phenotype with an oncogenic memory. While in cancer redundancy and plasticity enable the adaptation towards a proliferative state, in regressed cells, on the contrary, prolonged oncogenic signaling leads to a loss of metabolic network regulation and the entering of an irreversible metabolic state. This state appears to be insensitive to adaptation mechanisms as transcripts and metabolites reciprocally enhance each other to maintain the tumor-like metabolic phenotype. In conclusion, this work demonstrates how genome scale metabolic models can help identifying functional mechanisms from complex and multi-layered omics data. Appropriate genome scale metabolic models combined with metabolite measurements have proven particularly useful in this context. The comprehensive understanding of all integrated aspects of a cell’s physiology is a challenging endeavor and the results of this thesis might stimulate further research towards this goal

Parakriner Einfluss von Osteoarthroseknorpel auf die chondrogene Differenzierung humaner RS-Zellen

Im Rahmen dieser Doktorarbeit sollte ein potentiell regulierender Einfluss von löslichen, parakrinen Faktoren, produziert von reifen Chondrozyten auf die chondrogene Differenzierung von humanen, mesenchymalen Stammzellen nachgewiesen werden. Hierfür wurde ein Zellkulturmodell etabliert, in dem Chondrozyten und hRS getrennt voneinander kultiviert wurden und der Kontakt zwischen beiden Zelltypen auf lösliche Faktoren beschränkt war. Dies wird durch die Zugabe des bei den Chondrozyten konditionierten Zellkulturüberstandes zu den MSCs erreicht. Das etablierte Zellkultursystem ist gut dazu geeignet die chondrogene Differenzierung von humanen RS-Zellen zu unterstützen, da in beiden Kulturansätzen typische chondrogene Markerproteine in den Zellkulturüberstand nachgewiesen werden konnten. Die Ergebnisse zeigen weiterhin, dass lösliche Faktoren die chondrogene Differenzierung der hRS fördern. Eine Schlüsselrolle in diesem System könnten die beiden Matrixmetalloproteinasen MMP-2 und MMP-13 einnehmen. Beide Proteinasen besitzen zahlreiche wichtige Funktionen im Prozess der chondrogenen Differenzierung. Ein wichtiges Beispiel ist die Fähigkeit, von MMPs latentes TGF-ß aus der extrazellulären Matrix freizusetzen, um auf diesem Weg die Chondrogenese zu fördern. Dies korreliert auch gut mit den Ergebnissen dieser Arbeit, da im Zellkulturüberstand der konditionierten Pellets signifikant höhere Mengen an TGF-ß1 nachgewiesen wurden. Zusammen mit dem exogen zugeführten TGF-ß3 ist dieser Wachstumsfaktor in der Lage die Genexpression der chondrogenen Markergene wie COL2A1 und Aggrecan zu steigern. Dass auf Ebene der Proteinsekretion keine Unterschiede zwischen den beiden Kulturbedingungen bestehen, liegt in erster Linie an der Dauer der Zellkulturperiode, die zu kurz ist, um die langwierigen Veränderungen auf Ebene der Proteinsekretion darzustellen. Analog zu vergangenen Studien mit artikulären Chondrozyten, wie zum Beispiel die Studien von Jikko et al.,konnte auch im Rahmen dieser Arbeit keine hypertrophe Differenzierung der Chondrozyten nachgewiesen werden

Trajectories to reconcile sharing and commercialization in the maker movement

Maker technologies, including collaborative digital fabrication tools like 3-D printers, enable entrepreneurial opportunities and new business models. To date, relatively few highly successful maker startups have emerged, possibly due to the dominant mindset of the makers being one of cooperation and sharing. However, makers also strive for financial stability and many have profit motives. We use a multiple case study approach to explore makers' experiences regarding the tension between sharing and commercialization and their ways of dealing with it. We conducted interviews with maker initiatives across Europe including Fab Labs, a maker REtD center, and other networks of makers. We unpack and contextualize the concepts of sharing and commercialization. Our cross-case analysis leads to a new framework for understanding these entrepreneurs' position with respect to common good versus commercial offerings. Using the framework, we describe archetypal trajectories that maker initiatives go through in the dynamic transition from makers to social enterprises and social entrepreneurs. (C) 2017 Kelley School of Business, Indiana University. Published by Elsevier Inc. All rights reserved

Fast and slow light in zig-zag microring resonator chains

We analyze fast and slow light transmission in a zig-zag microring resonator chain. This novel device permits the operation in both regimes. In the superluminal case, a new ubiquitous light transmission effect is found whereby the input optical pulse is reproduced in an almost simultaneous manner at the various system outputs. When the input carrier is tuned to a different frequency, the system permits to slow down the propagating optical signal. Between these two extreme cases, the relative delay can be tuned within a broad range

Rusty Clusters? Dusting an IPv6 Research Foundation

The long-running IPv6 Hitlist service is an important foundation for IPv6 measurement studies. It helps to overcome infeasible, complete address space scans by collecting valuable, unbiased IPv6 address candidates and regularly testing their responsiveness. However, the Internet itself is a quickly changing ecosystem that can affect longrunning services, potentially inducing biases and obscurities into ongoing data collection means. Frequent analyses but also updates are necessary to enable a valuable service to the community. In this paper, we show that the existing hitlist is highly impacted by the Great Firewall of China, and we offer a cleaned view on the development of responsive addresses. While the accumulated input shows an increasing bias towards some networks, the cleaned set of responsive addresses is well distributed and shows a steady increase. Although it is a best practice to remove aliased prefixes from IPv6 hitlists, we show that this also removes major content delivery networks. More than 98% of all IPv6 addresses announced by Fastly were labeled as aliased and Cloudflare prefixes hosting more than 10M domains were excluded. Depending on the hitlist usage, e.g., higher layer protocol scans, inclusion of addresses from these providers can be valuable. Lastly, we evaluate different new address candidate sources, including target generation algorithms to improve the coverage of the current IPv6 Hitlist. We show that a combination of different methodologies is able to identify 5.6M new, responsive addresses. This accounts for an increase by 174% and combined with the current IPv6 Hitlist, we identify 8.8M responsive addresses

QUIC on the Highway: Evaluating Performance on High-rate Links

QUIC is a new protocol standardized in 2021 designed to improve on the widely used TCP / TLS stack. The main goal is to speed up web traffic via HTTP, but it is also used in other areas like tunneling. Based on UDP it offers features like reliable in-order delivery, flow and congestion control, streambased multiplexing, and always-on encryption using TLS 1.3. Other than with TCP, QUIC implements all these features in user space, only requiring kernel interaction for UDP. While running in user space provides more flexibility, it profits less from efficiency and optimization within the kernel. Multiple implementations exist, differing in programming language, architecture, and design choices. This paper presents an extension to the QUIC Interop Runner, a framework for testing interoperability of QUIC implementations. Our contribution enables reproducible QUIC benchmarks on dedicated hardware. We provide baseline results on 10G links, including multiple implementations, evaluate how OS features like buffer sizes and NIC offloading impact QUIC performance, and show which data rates can be achieved with QUIC compared to TCP. Our results show that QUIC performance varies widely between client and server implementations from 90 Mbit/s to 4900 Mbit/s. We show that the OS generally sets the default buffer size too small, which should be increased by at least an order of magnitude based on our findings. Furthermore, QUIC benefits less from NIC offloading and AES NI hardware acceleration while both features improve the goodput of TCP to around 8000 Mbit/s. Our framework can be applied to evaluate the effects of future improvements to the protocol or the OS.Comment: Presented at the 2023 IFIP Networking Conference (IFIP Networking

Evaluating the Benefits: Quantifying the Effects of TCP Options, QUIC, and CDNs on Throughput

To keep up with increasing demands on quality of experience, assessing and understanding the performance of network connections is crucial for web service providers. While different measures, like TCP options, alternative transport layer protocols like QUIC, or the hosting of services in CDNs, are expected to improve connection performance, no studies are quantifying such impacts on connections on the Internet. This paper introduces an active Internet measurement approach to assess the impacts of mentioned measures on connection performance. We conduct downloads from public web servers considering different vantage points, extract performance indicators like throughput, RTT, and retransmission rate, and survey speed-ups due to TCP option usage. Further, we compare the performance of QUIC-based downloads to TCP-based downloads considering different option configurations. Next to significant throughput improvements due to TCP option usage, in particular TCP window scaling, and QUIC, our study shows significantly increased performance for connections to domains hosted by different giant CDNs.Comment: Presented at the ACM/IRTF Applied Networking Research Workshop 2023 (ANRW23

Hydrogen-activation mechanism of [Fe] hydrogenase revealed by multi-scale modeling

When investigating the mode of hydrogen activation by [Fe] hydrogenases, not only the chemical reactivity at the active site is of importance but also the large-scale conformational change between the so-called open and closed conformations, which leads to a special spatial arrangement of substrate and iron cofactor. To study H2 activation, a complete model of the solvated and cofactor-bound enzyme in complex with the substrate methenyl-H4MPT+ was constructed. Both the closed and open conformations were simulated with classical molecular dynamics on the 100 ns time scale. Quantum-mechanics/molecular-mechanics calculations on snapshots then revealed the features of the active site that enable the facile H2 cleavage. The hydroxyl group of the pyridinol ligand can easily be deprotonated. With the deprotonated hydroxyl group and the structural arrangement in the closed conformation, H2 coordinated to the Fe center is subject to an ionic and orbital push-pull effect and can be rapidly cleaved with a concerted hydride transfer to methenyl-H4MPT+. An intermediary hydride species is not formed