Historical Contingency and Compensatory Evolution Constrain the Path of Evolution in a Genome Shuffling Experiment with Saccharomyces cerevisiae

The research reported in this thesis builds on an evolutionary engineering experiment (Pinel 2011) that yielded strains of Saccharomyces cerevisiae tolerant to a lignocellulosic hydrolysate. A highly tolerant strain was later characterized by whole genome and transcriptome sequencing (Pinel 2015). The evolutionary trajectories of mutations identified by sequencing were probed by whole population amplicon sequencing, while their significance to the phenotype was assessed by genotyping of additional mutants. Results of this work suggested that our survey of mutations selected during evolutionary engineering was partial. I therefore hypothesized that a complete survey of mutational diversity by whole population genome sequencing would further refine our understanding of lignocellulosic hydrolysate tolerance in S. cerevisiae. I further conjectured that extending this survey to several time points would reveal some of the fundamental evolutionary mechanisms that shape the outcomes of genome shuffling experiments. In parallel, I hypothesized that phenotypic testing of reverse engineered point mutants would identify mutations responsible for lignocellulosic hydrolysate tolerance in our strains of S. cerevisiae. My data revealed that a stong founder effect and prevalent genetic hitchhiking during genome shuffling lead to the domination of compensatory patterns during evolution. Bias introduced by historical contingency lead to the selection of few genuinely beneficial mutations. In the specific context of lignocellulosic hydrolysate tolerance, mutations in genes NRG1 and GSH1, conferring tolerance to acetic acid, oxidative, and potentially other stresses most prominently enhanced the phenotype

Using advanced computational methods to model the binding of antibody complexes: a case study from the coagulation cascade

Haemophilia A is a congenital bleeding disorder affecting one in 5,000 to 10,000 males. To prevent symptomatic disease, injections of recombinant factor VIII (FVIII) are administered to compensate for insufficient levels of this essential clotting factor. Patients suffering from a severe form of haemophilia A are at increased risk of forming neutralising antibodies — known as inhibitors — against therapeutic FVIII. A better understanding of the binding characteristics of inhibitors may aid the selection of optimal haemophilia A therapies, lead to the development of new therapeutics that are less antigenic, and support future initiatives in personalised and precision medicine. With this goal in mind, Classical Molecular Dynamics (CMD) in conjunction with Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) free energy calculations, together with enhanced sampling techniques, have been used to investigate interactions and the dynamics of binding site residues of the human inhibitory antibody BO2C11 bound to the C2-domain of factor VIII. In parallel, recombinant bacterial expressions of the C2-domain were initiated with the aim to explore structural changes induced by mutations that abrogate binding as described previously in surface plasmon resonance experiments. Computational binding affinity predictions were generally shown to be in good agreement with experimental findings. Additionally, binding site dynamics were investigated in detail using customized visualization techniques and an interpretable machine learning approach. Nevertheless, CMD simulations were insufficient for gaining insights into structural changes induced by mutations that were determined experimentally to be non-binding, and for exploring the underlying differences between the bound and unbound structures of the FVIII-C2 domain. To this end, Accelerated Molecular Dynamics (AMD) and Umbrella Sampling (US) simulations proved to be appropriate additions to investigate the conformational changes and energetic differences associated with the binding of BO2C11

TNF-insulin crosstalk at the transcription factor GATA6 is revealed by a model that links signaling and transcriptomic data tensors

Signal -transduction networks coordinate transcriptional programs activated by diverse extracellular stimuli, such as growth factors and cytokines. Cells receive multiple stimuli simultaneously, and mapping how activation of the integrated signaling network affects gene expression is a challenge. We stimulated colon adenocarcinoma cells with various combinations of the cytokine tumor necrosis factor (TNF) and the growth factors insulin and epidermal growth factor (EGF) to investigate signal integration and transcriptional crosstalk. We quantitatively linked the proteomic and transcriptomic data sets by implementing a structured computational approach called tensor partial least squares regression. This statistical model accurately predicted transcriptional signatures from signaling arising from single and combined stimuli and also predicted time-dependent contributions of signaling events. Specifically, the model predicted that an early-phase, Akt-associated signal downstream of insulin repressed a set of transcripts induced by TNF. Through bioinformatics and cell-based experiments, we identified the Akt-repressed signal as glycogen synthase kinase 3 (GSK3)–catalyzed phosphorylation of Ser37 on the long form of the transcription factor GATA6. Phosphorylation of GATA6 on Ser37 promoted its degradation, thereby preventing GATA6 from repressing transcripts that are induced by TNF and attenuated by insulin. Our analysis showed that predictive tensor modeling of proteomic and transcriptomic data sets can uncover pathway crosstalk that produces specific patterns of gene expression in cells receiving multiple stimuli

Refractory sampling links efficiency and costs of sensory encoding to stimulus statistics.

Sensory neurons integrate information about the world, adapting their sampling to its changes. However, little is understood mechanistically how this primary encoding process, which ultimately limits perception, depends upon stimulus statistics. Here, we analyze this open question systematically by using intracellular recordings from fly (Drosophila melanogaster and Coenosia attenuata) photoreceptors and corresponding stochastic simulations from biophysically realistic photoreceptor models. Recordings show that photoreceptors can sample more information from naturalistic light intensity time series (NS) than from Gaussian white-noise (GWN), shuffled-NS or Gaussian-1/f stimuli; integrating larger responses with higher signal-to-noise ratio and encoding efficiency to large bursty contrast changes. Simulations reveal how a photoreceptor's information capture depends critically upon the stochastic refractoriness of its 30,000 sampling units (microvilli). In daylight, refractoriness sacrifices sensitivity to enhance intensity changes in neural image representations, with more and faster microvilli improving encoding. But for GWN and other stimuli, which lack longer dark contrasts of real-world intensity changes that reduce microvilli refractoriness, these performance gains are submaximal and energetically costly. These results provide mechanistic reasons why information sampling is more efficient for natural/naturalistic stimulation and novel insight into the operation, design, and evolution of signaling and code in sensory neurons

Protein Structure

Since the dawn of recorded history, and probably even before, men and women have been grasping at the mechanisms by which they themselves exist. Only relatively recently, did this grasp yield anything of substance, and only within the last several decades did the proteins play a pivotal role in this existence. In this expose on the topic of protein structure some of the current issues in this scientific field are discussed. The aim is that a non-expert can gain some appreciation for the intricacies involved, and in the current state of affairs. The expert meanwhile, we hope, can gain a deeper understanding of the topic

Lipid bilayer phase separations, cholesterol, and their effect on the amyloid precursor protein C99

The Amyloid Cascade hypothesis provides a molecular-level mechanism for the etiology of Alzheimer’s Disease (AD) and proposes a central role for the genesis and aggregation of Aβ protein. Aβ protein is the product of cleavage of the amyloid precursor protein (APP), a single pass transmembrane protein, by secretases and is found in a variety of isoforms, with longer isoforms being linked to the early onset of AD. The isoform distribution is dependent on membrane environment, mutations, and post-translational modifications. Lipid rafts are characterized by lipids induced into the liquid ordered phase by cholesterol, enhancing membrane thickness and lateral lipid density. Protein preference for rafts can control protein kinetics, and has been implicated in determining whether APP is processed by α– or β-secretase in the plasma membrane. In addition to inducing lipid rafts, cholesterol is hypothesized to directly modulate APP, the C-terminal fragment of APP (C99), and γ-secretase structure and function via direct interaction. To date, the molecular details involved in these fundamental events involved in Aβ genesis have yet to be resolved using experimental approaches, suggesting a critical role for computation. This thesis presents the results of investigations of lipid phase separation and cholesterol and their effects on C99 using molecular dynamics simulation. To gain insight into the nature of lipid rafts, studies characterizing the simulation system sizes required for observation of phase separation, exploring the effect of cholesterol concentration on phase separation and lipid phases, and examining the applicability of different lipid and cholesterol models for the simulation of lipid phases and protein structure were performed. To gain insight into the fundamental properties of C99, studies exploring the structure of full-length C99, the interaction of cholesterol with C99 in various mutational states, the effect of membrane thickness on the C99 extramembrane domains, and the structure of C99 monomer and dimer were performed. Taken together these studies advance our molecular-level understanding of the nature of cholesterol, the role of cholesterol in lipid phase separation, the effect of cholesterol on C99, and the structure of the full-sequence C99 monomer and dimer that play a critical role in the evolution of AD

A Bioinformatics Study of Protein Conformational Flexibility and Misfolding: a Sequence, Structure and Dynamics Approach

This PhD Thesis titled "A Bioinformatics Study of Protein Conformational Flexibility and Misfolding: a Sequence, Structure and Dynamics Approach" comprises the results and conclusions obtained by us from the study of three different but somehow related research projects, covering aspects of the phenomenon of protein local conformational instability, its relationship with protein function, evolvability and aggregation, and the effect of genetic variations on protein conformational instability related to Conformational Diseases. These projects include the prediction of putative prion proteins in complete proteomes and the study of prion biology from a genomic perspective, the prediction of conformationally unstable protein regions and the existence of a structural framework for linking conformational instability to folding and function, and the establishment of a rationale for assessing the connection among mutations and disease phenotypes in Conformational Diseases.Esta tesis doctoral comprende los resultados y conclusiones obtenidos por nosotros a partir del estudio de tres proyectos de investigación diferentes pero de alguna manera relacionados, cubriendo los aspectos del fenómeno de la inestabilidad conformacional local de la proteína, su relación con la función de la proteína, la capacidad de evolución y agregación, y el efecto de las variaciones genéticas en la inestabilidad conformacional de la proteína relacionados con las enfermedades conformacionales. Estos proyectos incluyen la predicción de presuntas proteínas priónicas en proteomas complejos y el estudio de la biología de priones desde una perspectiva genómica, la predicción de las regiones de proteínas conformacionalmente inestables y la existencia de un marco estructural para la vinculación de la inestabilidad conformacional del plegado y la función, y el establecimiento de una razón fundamental para la evaluación de la relación entre las mutaciones y fenotipos de la enfermedad en enfermedades conformacionales

RNA-based regulation of pluripotency and differentiation

RNA-bindende Proteine sind zentrale Regulatoren der Genexpression, aber ihre Funktionen bei der Koordinierung von Zellschicksalsentscheidungen sind unzureichend verstanden. In dieser Studie haben wir RNA interactome capture angewandt, um die globalen Dynamiken des RNA-gebundenen Proteoms während der Auflösung der Pluripotenz und neuronaler Differenzierung zu bestimmen. Wir haben entdeckt, dass 30-40% der RNA-bindenden Proteine sehr dynamisch während der Zellschicksalentscheidungen sind, die Abundanzdynamiken dieser Proteine aber nicht hauptursächlich dafür zu sein scheinen. Basierend auf unseren Daten haben wir ZAP (ZC3HAV1) als einen Faktor identifiziert, der mit Pluripotenz assoziiert ist. Um die Rolle von ZAP in der Stammzellbiologie zu analysieren, haben wir PAR-CLIP, SLAMseq und einen Differenzierungsassay angewandt. Unsere Daten haben gezeigt, dass ZAP mehr als 2,000 mRNA-Transkripte innerhalb des murinen Stammzelltranskriptoms in Abhängigkeit von CG-Dinukleotiden bindet. Zieltranskripte sind angereichert mit Genfunktionen in Zell-Zell-Interaktionen, Gewebemorphogenese und Pluripotenzregulation und werden in Abwesenheit von ZAP stabilisiert. Auβerdem haben wir herausgefunden, dass Depletion von ZAP zu flacherer und breiterer Koloniemorphologie von Stammzellen bei gleichzeitiger Fehlexpression von hunderten von Genen inklusive Lineage-Faktoren führt. Desweiteren führt Abwesenheit von ZAP zu erhöhter Geschwindigkeit bei der Auflösung der Pluripotenz. Zusammengefasst stellen wir die These auf, dass ZAP ein multi-modaler Regulator der Pluripotenz ist. ZAP agiert als positiver Regulator während Aufrechterhaltung der Pluripotenz, während es am Anfang der Pluripotenzauflösung pluripotenz-fördernde Faktoren herunterreguliert. Schlussendlich demonstriert diese Studie, wie die Erforschung von Dynamiken des RNA-gebundenen Proteoms während Zellschicksalsentscheidungen neue Wege öffnet, um die Funktion von RNA-bindenden Proteinen im entwicklungsbiologischen Kontext zu analysieren.RNA-binding proteins are key regulators of gene expression, but their functions in coordinating cell fate transitions are poorly understood. In this study, we applied RNA interactome capture to determine the global dynamics of the RNA-bound proteome during dissolution of pluripotency and neuronal differentiation. We discovered that 30-40% of RNA-binding proteins are highly dynamic during cell fate transitions and that these dynamics do not appear to be predominantly governed by alterations in their abundance. Based on our data, we identified ZAP (ZC3HAV1) as a factor highly associated with pluripotency. In order to dissect the role of ZAP in mESC biology, we applied a variety of approaches including PAR-CLIP, SLAMseq and pluripotency exit reporter assays. We found that ZAP binds more than 2,000 mRNAs in the mESC transcriptome in a CG dinucleotide-dependent manner. Targets are enriched for transcripts encoding cell-cell adhesion, tissue morphogenesis and pro-pluripotency regulators and stabilized in absence of ZAP. Furthermore, we found that ZAP depletion leads to flattened and spreading stem cell colony morphology, concomitant misexpression of hundreds of transcripts including lineage factors and accelerated early dissolution of pluripotency. In conclusion, we propose that ZAP is a multi-modal stem cell RNA-binding protein acting as a positive regulator in maintenance of pluripotency while aiding downregulation of pro-pluripotent factors at the onset of differentiation. Ultimately, this study demonstrates how exploration of RNA-bound proteome dynamics during cell fate transitions can open paths to dissecting functions of RNA-binding proteins in a developmental context

Biophysical Chemistry

Biophysical chemistry is one of the most interesting interdisciplinary research fields. Some of its different subjects have been intensively studied for decades. Now the field attracts not only scientists from chemistry, physics, and biology backgrounds but also those from medicine, pharmacy, and other sciences. We aimed to start this version of the book Biophysical Chemistry from advanced principles, as we include some of the most advanced subject matter, such as advanced topics in catalysis applications (first section) and therapeutic applications (second section). This led us to limit our selection to only chapters with high standards, therefore there are only six chapters, divided into two sections. We have assumed that the interested readers are familiar with the fundamentals of some advanced topics in mathematics such as integration, differentiation, and calculus and have some knowledge of organic and physical chemistry, biology, and pharmacy. We hope that the book will be valuable to graduate and postdoctoral students with the requisite background, and by some advanced researchers active in chemistry, biology, biochemistry, medicine, pharmacy, and other sciences