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Graphs provide a key means to model relationships between entities.
They consist of vertices representing the entities,
and edges representing relationships between pairs of entities.
To make people conceive the structure of a graph,
it is almost inevitable to visualize the graph.
We call such a visualization a graph drawing.
Moreover, we have a straight-line graph drawing
if each vertex is represented as a point
(or a small geometric object, e.g., a rectangle)
and each edge is represented as a line segment between its two vertices.
A polyline is a very simple straight-line graph drawing,
where the vertices form a sequence according to which the vertices are connected by edges.
An example of a polyline in practice is a GPS trajectory.
The underlying road network, in turn, can be modeled as a graph.
This book addresses problems that arise
when working with straight-line graph drawings and polylines.
In particular, we study algorithms
for recognizing certain graphs representable with line segments,
for generating straight-line graph drawings,
and for abstracting polylines.
In the first part, we first examine,
how and in which time we can decide
whether a given graph is a stick graph,
that is, whether its vertices can be represented as
vertical and horizontal line segments on a diagonal line,
which intersect if and only if there is an edge between them.
We then consider the visual complexity of graphs.
Specifically, we investigate, for certain classes of graphs,
how many line segments are necessary for any straight-line graph drawing,
and whether three (or more) different slopes of the line segments
are sufficient to draw all edges.
Last, we study the question,
how to assign (ordered) colors to the vertices of a graph
with both directed and undirected edges
such that no neighboring vertices get the same color
and colors are ascending along directed edges.
Here, the special property of the considered graph is
that the vertices can be represented as intervals
that overlap if and only if there is an edge between them.
The latter problem is motivated by an application
in automated drawing of cable plans with vertical and horizontal line segments,
which we cover in the second part.
We describe an algorithm that
gets the abstract description of a cable plan as input,
and generates a drawing that takes into account
the special properties of these cable plans,
like plugs and groups of wires.
We then experimentally evaluate the quality of the resulting drawings.
In the third part, we study the problem of abstracting (or simplifying)
a single polyline and a bundle of polylines.
In this problem, the objective is to remove as many vertices as possible from the given polyline(s)
while keeping each resulting polyline sufficiently similar to its original course
(according to a given similarity measure).
The aim of the present work was to improve drug monitoring in patients with various diseases in the context of precision medicine. This was pursued through the development and validation of mass spectrometric methods for determining the drug concentrations of kinase inhibitors and their clinical application. Besides conventional approaches to determine plasma level concentrations, the focus was also on alternative sampling techniques using volumetric absorptive microsampling (VAMS).
A conventional LC-MS/MS method was developed for the determination of cabozantinib in human EDTA plasma and validated according to the guidelines of the European and United States drug authorities (EMA, FDA). The method met the required criteria for linearity, accuracy and precision, selectivity, sensitivity, and stability of the analyte. Validation was also performed for dilution integrity, matrix effect, recovery, and carry-over, with results also in accordance with the requirements. The importance of monitoring the exposure of cabozantinib was demonstrated by a clinical case report of a 34-year-old female patient with advanced adrenocortical carcinoma who also required hemodialysis due to chronic kidney failure. Expected cabozantinib plasma concentrations were simulated for this off-label use based on a population pharmacokinetic model. It was shown that the steady state trough levels were much lower than expected but could not be explained by hemodialysis. Considering the critical condition and potential drug-drug interaction with metyrapone, a substance the patient had taken among several others during the observation period, individual pharmacokinetics could consequently not be estimated without drug monitoring.
In addition, a VAMS method for simultaneous determination of ten kinase inhibitors from capillary blood was developed. This microsampling technique was mainly characterized by the collection of a defined volume of blood, which could be dried and subsequently analyzed. The guidelines for bioanalytical method validation of the EMA and FDA were also used for this evaluation. As the nature of dried blood samples differs from liquid matrices, further parameters were investigated. These include the investigation of the hematocrit effect, process efficiency, and various stability conditions, for example at increased storage temperatures. The validation showed that the developed method is suitable to analyze dried matrix samples accurate, precise, and selective for all analytes. Apart from the stability tests, all acceptance criteria were met. The decreased stability of two analytes was probably due to the reproducible but reduced recovery. In vitro studies provided results on the VAMS-to-plasma correlation to predict the analyte distribution between both matrices, at least in an exploratory manner. It revealed a heterogeneous picture of analytes with different VAMS-to-plasma distributions. Furthermore, the analysis of 24 patient samples indicated the applicability of at-home VAMS. Both should be confirmed later as part of the clinical validation.
The clinical investigation of the VAMS method pursued two objectives. On the one hand, the simultaneous collection of VAMS and serum samples should enable a conversion of the determined concentrations and, on the other hand, the feasibility of autonomous microsampling at home should be examined more closely. For the former, it could be shown that different conversion methods are suitable for converting VAMS concentrations into serum levels. The type of conversion was secondary for the prediction. However, the previously defined criteria could not be fulfilled for all five kinase inhibitors investigated. The framework conditions of the study led to increased variability, especially for analytes with short half-life. A low and varying hematocrit, caused by the underlying disease, also made prediction difficult for a specific patient collective. For the second objective, investigating the feasibility of VAMS, different aspects were considered. It could be shown that the majority of patients support home-based microsampling. The acceptance is likely to increase even further when microsampling is no longer part of a non-interventional study, but participation is accompanied by targeted monitoring and subsequent adjustment of the therapy. The fact that additional training increases understanding of the correct sampling procedure is also a source of confidence. Demonstrated stability during storage under real-life conditions underlines the practicality of this sampling technique.
Taken together, mass spectrometric methods for both plasma and VAMS could be developed and validated, and their clinical application could be successfully demonstrated. The availability of simple bioanalytical methods to determine kinase inhibitor exposure could improve access to prospective studies and thus facilitate the implementation of routine therapeutic drug monitoring.
Ischemia-reperfusion injury (I/R injury) is a common complication in ischemic stroke (IS) treatment, which is characterized by a paradoxical perpetuation of tissue damage despite the successful re-establishment of vascular perfusion. This phenomenon is known to be facilitated by the detrimental interplay of platelets and inflammatory cells at the vascular interface. However, the spatio-temporal and molecular mechanisms underlying these cellular interactions and their contribution to infarct progression are still incompletely understood. Therefore, this study intended to clarify the temporal mechanisms of infarct growth after cerebral vessel recanalization. The data presented here could show that infarct progression is driven by early blood-brain-barrier perturbation and is independent of secondary thrombus formation. Since previous studies unravelled the secretion of platelet granules as a molecular mechanism of how platelets contribute to I/R injury, special emphasis was placed on the role of platelet granule secretion in the process of barrier dysfunction. By combining an in vitro approach with a murine IS model, it could be shown that platelet α-granules exerted endothelial-damaging properties, whereas their absence (NBEAL2-deficiency) translated into improved microvascular integrity. Hence, targeting platelet α-granules might serve as a novel treatment option to reduce vascular integrity loss and diminish infarct growth despite recanalization.
Recent evidence revealed that pathomechanisms underlying I/R injury are already instrumental during large vessel occlusion. This indicates that penumbral tissue loss under occlusion and I/R injury during reperfusion share an intertwined relationship. In accordance with this notion, human observational data disclosed the presence of a neutrophil dominated immune response and local platelet activation and secretion, by the detection of the main components of platelet α-granules, within the secluded vasculature of IS patients. These initial observations of immune cells and platelets could be further expanded within this thesis by flow cytometric analysis of local ischemic blood samples. Phenotyping of immune cells disclosed a yet unknown shift in the lymphocyte population towards CD4+ T cells and additionally corroborated the concept of an immediate intravascular immune response that is dominated by granulocytes. Furthermore, this thesis provides first-time evidence for the increased appearance of platelet-leukocyte-aggregates within the secluded human vasculature. Thus, interfering with immune cells and/or platelets already under occlusion might serve as a potential strategy to diminish infarct expansion and ameliorate clinical outcome after IS.
Fusobacterium nucleatum is an emerging cancer-associated bacterium belonging to the Fusobacteriota phylum, which is evolutionary distant from all model bacteria. Recent analysis generated global fusobacterial RNA maps, which enabled the discovery of 24 small noncoding RNAs (sRNAs) in F. nucleatum. Notably, the σE-dependent sRNA FoxI and FoxJ act as a posttranscriptional regulator of several cell envelope proteins. The σE-dependent sRNAs in Escherichia coli and Salmonella require the RNA chaperone Hfq for their functions. Intriguingly, F. nucleatum seems to have no homologs of the three common RNA-binding proteins (RBPs) CsrA, Hfq and ProQ. However, it remains unclear if other families of RBPs act in concert with FoxI, FoxJ and other fusobacterial sRNAs.
This work has successfully established a 14-mer capture tagged-sRNA affinity purification procedure initially using 6S RNA as a proof-of-concept. Applying this method to 19 different F. nucleatum sRNAs led to a comprehensive mapping of sRNA-binding proteins in this bacterium. This screen identified a total of 75 proteins significantly enriched across all sRNAs and prominent in ribosomal proteins, uncharacterized proteins and enzymes associated with metabolism. This work further focused on the homologs of two KH domain proteins KhpA and KhpB, which were recently recognized as global RBPs in various Gram-positive bacteria such as Streptococcus pneumoniae, Clostridioides difficile, and Enterococcus faecalis.
Comparative analyses revealed conserved domain composition and gene synteny of KhpA and KhpB across F. nucleatum, S. pneumoniae, C. difficle and E. faecalis, indicating conserved roles of these proteins in bacteria. Further protein-protein interaction assays and global RNA targets profiling demonstrated that KhpA and KhpB form dimers and act together as broad RBPs, binding to sRNAs, mRNAs and tRNAs in F. nucleatum. Further functional characterizations unveiled that KhpA/B are required for the growth of F. nucleatum under nutrient limitation conditions and impact cell morphology. Additionally, the two RBPs also influence global gene expression in F. nucleatum affecting various bacterial physiological processes, including ethanolamine utilization.
In summary, this work established a sRNA-centric approach for screening sRNA-binding proteins in F. nucleatum. Further, the assay could be applied in other non-model organisms and is feasible to screen multiple sRNA baits in parallel for sRNA-interactors. By applying this procedure to nearly all known fusobacterial sRNAs, this work generated an extensive map of sRNA-interacting proteins in F. nucleatum. Molecular and genetic studies identified that KhpA/B act as major RBPs and gene regulators in F. nucleatum, representing important first steps in elucidating key players of post-transcriptional control at the root of the bacterial phylogenetic tree.
This thesis investigates the charged moments and the symmetry-resolved
entanglement entropy in the context of the AdS3/CFT2 duality. In the
first part, I focus on the holographic U(1) Chern-Simons-Einstein gravity,
a toy model of AdS3/CFT2 with U(1) Kac-Moody symmetry. I
start with the vacuum background with a single entangling interval. I
show that, apart from a partition function in the grand canonical ensemble,
the charged moments can also be interpreted as the two-point
function of vertex operators on the replica surface. For the holographic
description, I propose a duality between the bulk U(1) Wilson line and
the boundary vertex operators. I verify this duality by deriving the
effective action for the Chern-Simons fields and comparing the result
with the vertex correlator. In the twist field approach, I show that the
charged moments are given by the correlation function of the charged
twist operators and the additional background operators. To solve the
correlation functions involved, I prove the factorization of the U(1) extended
conformal block into a U(1) block and a Virasoro block. The
general expression for the U(1) block is derived by directly summing
over the current descendant states, and the result shows that it takes
an identical form as the vertex correlators. This leads to the conclusion
that the disjoint Wilson lines compute the neutral U(1) block. The final
result for the symmetry-resolved entanglement entropy shows that
it is always charge-independent in this model. In the second part, I
study charged moments in higher spin holography, where the boundary
theory is a CFT with W3 symmetry. I define the notion of the
higher spin charged moments by introducing a spin-3 modular charge
operator. Restricting to the vacuum background with a single entangling
interval, I employ the grand canonical ensemble interpretation
and calculate the charged moments via the known higher spin black
hole solution. On the CFT side, I perform a perturbative expansion for
the higher spin charged moments in terms of the connected correlation
functions of the spin-3 modular charge operators. Using the recursion
relation for the correlation functions of the W3 currents, I evaluate the
charged moments up to the quartic order of the chemical potential. The
final expression matches with the holographic result. My results both
for U(1) Chern-Simons Einstein gravity and W3 higher spin gravity
constitute novel checks of the AdS3/CFT2 correspondence.
In this study, we developed an innovative nanoparticle formulation to facilitate the delivery of antitumor antibodies to tumor sites. The study commenced with the utilization of 13 bispecific antibody fusion proteins, which targeted the Fn14 receptor, thereby validating the pivotal role of crosslinking in Fn14 receptor activation. Subsequently, gold nanoparticles were activated using COOH-PEG-SH in combination with EDC/NHS, and subsequently conjugated with two Fn14-targeting antibodies, PDL192 and 5B6. Following this, a pH-sensitive shell was generated on the outer layer of the antibody-coupled gold nanoparticles through the application of chemically modified polylysine. The resultant complexes, termed MPL-antibody-AuNP, demonstrated a release profile reminiscent of the tumor microenvironment (TME). Notably, these complexes released antibody-AuNPs only in slightly acidic conditions while remaining intact in neutral or basic environments. Functionality analysis further affirmed the pH-sensitive property of MPL-antibody-AuNPs, demonstrating that the antibodies only initiated potent Fn14 activation in slightly acidic environments. This formulation holds potential for applicability to antibodies or ligands targeting the 80 TNFRSF family, given that gold nanoparticles successfully served as platforms for antibody crosslinking, thereby transforming these antibodies into potent agonists. Moreover, the TME disintegration profile of MPL mitigates the potential cytotoxic effects of antibodies, thereby circumventing associated adverse side effects. This study not only showcases the potential of nanoparticle formulations in targeted therapy, but also provides a solid foundation for further investigations on their clinical application in the context of targeting category II TNFRSF receptors with antibodies or ligands.
Among the defense strategies developed in microbes over millions of years, the innate adaptive CRISPR-Cas immune systems have spread across most of bacteria and archaea. The flexibility, simplicity, and specificity of CRISPR-Cas systems have laid the foundation for CRISPR-based genetic tools. Yet, the efficient administration of CRISPR-based tools demands rational designs to maximize the on-target efficiency and off-target specificity. Specifically, the selection of guide RNAs (gRNAs), which play a crucial role in the target recognition of CRISPR-Cas systems, is non-trivial. Despite the fact that the emerging machine learning techniques provide a solution to aid in gRNA design with prediction algorithms, design rules for many CRISPR-Cas systems are ill-defined, hindering their broader applications.
CRISPR interference (CRISPRi), an alternative gene silencing technique using a catalytically dead Cas protein to interfere with transcription, is a leading technique in bacteria for functional interrogation, pathway manipulation, and genome-wide screens. Although the application is promising, it also is hindered by under-investigated design rules. Therefore, in this work, I develop a state-of-art predictive machine learning model for guide silencing efficiency in bacteria leveraging the advantages of feature engineering, data integration, interpretable AI, and automated machine learning. I first systematically investigate the influential factors that attribute to the extent of depletion in multiple CRISPRi genome-wide essentiality screens in Escherichia coli and demonstrate the surprising dominant contribution of gene-specific effects, such as gene expression level. These observations allowed me to segregate the confounding gene-specific effects using a mixed-effect random forest (MERF) model to provide a better estimate of guide efficiency, together with the improvement led by integrating multiple screens. The MERF model outperformed existing tools in an independent high-throughput saturating screen. I next interpret the predictive model to extract the design rules for robust gene silencing, such as the preference for cytosine and disfavoring for guanine and thymine within and around the protospacer adjacent motif (PAM) sequence. I further incorporated the MERF model in a web-based tool that is freely accessible at www.ciao.helmholtz-hiri.de.
When comparing the MERF model with existing tools, the performance of the alternative gRNA design tool optimized for CRISPRi in eukaryotes when applied to bacteria was far from satisfying, questioning the robustness of prediction algorithms across organisms. In addition, the CRISPR-Cas systems exhibit diverse mechanisms albeit with some similarities. The captured predictive patterns from one dataset thereby are at risk of poor generalization when applied across organisms and CRISPR-Cas techniques. To fill the gap, the machine learning approach I present here for CRISPRi could serve as a blueprint for the effective development of prediction algorithms for specific organisms or CRISPR-Cas systems of interest. The explicit workflow includes three principle steps: 1) accommodating the feature set for the CRISPR-Cas system or technique; 2) optimizing a machine learning model using automated machine learning; 3) explaining the model using interpretable AI. To illustrate the applicability of the workflow and diversity of results when applied across different bacteria and CRISPR-Cas systems, I have applied this workflow to analyze three distinct CRISPR-Cas genome-wide screens. From the CRISPR base editor essentiality screen in E. coli, I have determined the PAM preference and sequence context in the editing window for efficient editing, such as A at the 2nd position of PAM, A/TT/TG downstream of PAM, and TC at the 4th to 5th position of gRNAs. From the CRISPR-Cas13a screen in E. coli, in addition to the strong correlation with the guide depletion, the target expression level is the strongest predictor in the model, supporting it as a main determinant of the activation of Cas13-induced immunity and better characterizing the CRISPR-Cas13 system. From the CRISPR-Cas12a screen in Klebsiella pneumoniae, I have extracted the design rules for robust antimicrobial activity across K. pneumoniae strains and provided a predictive algorithm for gRNA design, facilitating CRISPR-Cas12a as an alternative technique to tackle antibiotic resistance.
Overall, this thesis presents an accurate prediction algorithm for CRISPRi guide efficiency in bacteria, providing insights into the determinants of efficient silencing and guide designs. The systematic exploration has led to a robust machine learning approach for effective model development in other bacteria and CRISPR-Cas systems. Applying the approach in the analysis of independent CRISPR-Cas screens not only sheds light on the design rules but also the mechanisms of the CRISPR-Cas systems. Together, I demonstrate that applied machine learning paves the way to a deeper understanding and a broader application of CRISPR-Cas systems.
Ecophysiological adaptations of the cuticular water permeability within the Solanaceae family
(2024)
The cuticle, a complex lipidic layer synthesized by epidermal cells, covers and protects primary organs of all land plants. Its main function is to avoid plant desiccation by limiting non-stomatal water loss. The cuticular properties vary widely among plant species. So far, most of the cuticle-related studies have focused on a limited number of species, and studies addressing phylogenetically related plant species are rare. Moreover, comparative studies among organs from the same plant species are still scarce.
Thus, this study focus on organ-specificities of the cuticle within and between plant species of the Solanaceae family. Twenty-seven plant species of ten genera, including cultivated and non- cultivated species, were investigated to identify potential cuticular similarities. Structural, chemical and functional traits of fully expanded leaves, inflated fruiting calyces, and ripe fruits were analyzed.
The surface morphology was investigated by scanning electron microscopy. Leaves were mainly amphistomatic and covered by an epicuticular wax film. The diversity and distribution of trichomes varied among species. Only the leaves of S. grandiflora were glabrous. Plant species of the Leptostemonum subgenus had numerous prickles and non-glandular stellate trichomes. Fruits were stomata-free, except for S. muricatum, and a wax film covered their surface. Last, lenticel- like structures and remaining scars of broken trichomes were found on the surface of some Solanum fruits.
Cuticular water permeability was used as indicators of the cuticular transpiration barrier efficiency. The water permeability differed among plant species, organs and fruit types with values ranging up to one hundred-fold. The minimum leaf conductance ranged from 0.35 × 10-5 m s-1 in S. grandiflora to 31.54 × 10-5 m s-1 in S. muricatum. Cuticular permeability of fruits ranged from 0.64 × 10-5 m s-1 in S. dulcamara (fleshy berry) to 34.98 × 10-5 m s-1 in N. tabacum (capsule). Generally, the cuticular water loss of dry fruits was about to 5-fold higher than that of fleshy fruits.
Interestingly, comparisons between cultivated and non-cultivated species showed that wild species have the most efficient cuticular transpiration barrier in leaves and fruits. The average permeability of leaves and fruits of wild plant species was up to three-fold lower in comparison to the cultivated ones. Moreover, ripe fruits of P. ixocarpa and P. peruviana showed two-times lower cuticular transpiration when enclosed by the inflated fruiting calyx.
The cuticular chemical composition was examined using gas chromatography. Very-long-chain aliphatic compounds primarily composed the cuticular waxes, being mostly dominated by n- alkanes (up to 80% of the total wax load). Primary alkanols, alkanoic acids, alkyl esters and branched iso- and anteiso-alkanes were also frequently found. Although in minor amounts, sterols, pentacyclic triterpenoids, phenylmethyl esters, coumaric acid esters, and tocopherols were identified in the cuticular waxes. Cuticular wax coverages highly varied in solanaceous (62- fold variation). The cuticular wax load of fruits ranged from 0.55 μg cm−2 (Nicandra physalodes) to 33.99 μg cm−2 (S. pennellii), whereas the wax amount of leaves varied from 0.90 μg cm−2 (N. physalodes) to 28.42 μg cm−2 (S. burchellii). Finally, the wax load of inflated fruiting calyces ranged from 0.56 μg cm−2 in P. peruviana to 2.00 μg cm−2 in N. physalodes.
For the first time, a comparative study on the efficiency of the cuticular transpiration barrier in different plant organs of closely related plant species was conducted. Altogether, the cuticular chemical variability found in solanaceous species highlight species-, and organ-specific wax biosynthesis. These chemical variabilities might relate to the waterproofing properties of the plant cuticle, thereby influencing leaf and fruit performances. Additionally, the high cuticular water permeabilities of cultivated plant species suggest a potential existence of a trade-off between fruit organoleptic properties and the efficiency of the cuticular transpiration barrier. Last, the high cuticular water loss of the solanaceous dry fruits might be a physiological adaptation favouring seed dispersion.
In DNA-encoded library synthesis, amine-substituted building blocks are prevalent. We explored isocyanide multicomponent reactions to diversify DNA-tagged amines and reported the Ugi-azide reaction with high yields and a good substrate scope. In addition, the Ugi-aza-Wittig reaction and the Ugi-4-center-3-component reaction, which used bifunctional carboxylic acids to provide lactams, were explored. Five-, six-, and seven-membered lactams were synthesized from solid support-coupled DNA-tagged amines and bifunctional building blocks, providing access to structurally diverse scaffolds.
Glycine receptor β–targeting autoantibodies contribute to the pathology of autoimmune diseases
(2024)
Background and Objectives
Stiff-person syndrome (SPS) and progressive encephalomyelitis with rigidity and myoclonus (PERM) are rare neurologic disorders of the CNS. Until now, exclusive GlyRα subunit–binding autoantibodies with subsequent changes in function and surface numbers were reported. GlyR autoantibodies have also been described in patients with focal epilepsy. Autoimmune reactivity against the GlyRβ subunits has not yet been shown. Autoantibodies against GlyRα1 target the large extracellular N-terminal domain. This domain shares a high degree of sequence homology with GlyRβ making it not unlikely that GlyRβ-specific autoantibody (aAb) exist and contribute to the disease pathology.
Methods
In this study, we investigated serum samples from 58 patients for aAb specifically detecting GlyRβ. Studies in microarray format, cell-based assays, and primary spinal cord neurons and spinal cord tissue immunohistochemistry were performed to determine specific GlyRβ binding and define aAb binding to distinct protein regions. Preadsorption approaches of aAbs using living cells and the purified extracellular receptor domain were further used. Finally, functional consequences for inhibitory neurotransmission upon GlyRβ aAb binding were resolved by whole-cell patch-clamp recordings.
Results
Among 58 samples investigated, cell-based assays, tissue analysis, and preadsorption approaches revealed 2 patients with high specificity for GlyRβ aAb. Quantitative protein cluster analysis demonstrated aAb binding to synaptic GlyRβ colocalized with the scaffold protein gephyrin independent of the presence of GlyRα1. At the functional level, binding of GlyRβ aAb from both patients to its target impair glycine efficacy.
Discussion
Our study establishes GlyRβ as novel target of aAb in patients with SPS/PERM. In contrast to exclusively GlyRα1-positive sera, which alter glycine potency, aAbs against GlyRβ impair receptor efficacy for the neurotransmitter glycine. Imaging and functional analyses showed that GlyRβ aAbs antagonize inhibitory neurotransmission by affecting receptor function rather than localization.