The research described in this thesis focused on the use of bioorthogonal antigens to investigate immunological processes in antigen presenting cells. Bioorthogonal antigens are antigenic proteins... Show moreThe research described in this thesis focused on the use of bioorthogonal antigens to investigate immunological processes in antigen presenting cells. Bioorthogonal antigens are antigenic proteins produced through recombinant expression in a methionine auxotrophic E. coli strain. This allows for the replacement of methionine residues with the bioorthogonal non-canonical amino acid, azidohomoalanine (Aha), that resembles methionine. Aha contains an azide group that enables the selective and rapid visualization or enrichment of the antigen after a biological experiment using alkyne-modified fluorophores or alkyne-containing resins, respectively, via copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC). The research involved studying the effects of post-translational modifications (PTMs), antigen complexation and glycosylation of antibodies in immune complexes on the uptake, proteolysis, and T cell activation by dendritic cells (DCs) of Aha-containing antigens. Additionally, a new method was developed to enrich low abundant bioorthogonal antigenic fragments from complex mixtures. This method can be used in future studies to identify processed Aha-containing fragments from immune cells that are preserved for T cell presentation. Show less
Isager, P.M.; Lakens, D.; Leeuwen, T. van; Veer, A.E. van 't 2023
Replication of published results is crucial for ensuring the robustness and self-correction of research, yet replications are scarce in many fields. Replicating researchers will therefore often... Show moreReplication of published results is crucial for ensuring the robustness and self-correction of research, yet replications are scarce in many fields. Replicating researchers will therefore often have to decide which of several relevant candidates to target for replication. Formal strategies for efficient study selection have been proposed, but none have been explored for practical feasibility - a prerequisite for validation. Here we move one step closer to efficient replication study selection by exploring the feasibility of a particular selection strategy that estimates replication value as a function of citation impact and sample size (Isager, van 't Veer, & Lakens, 2021). We tested our strategy on a sample of fMRI studies in social neuroscience. We first report our efforts to generate a representative candidate set of replication targets. We then explore the feasibility and reliability of estimating replication value for the targets in our set, resulting in a dataset of 1358 studies ranked on their value of prioritising them for replication. In addition, we carefully examine possible measures, test auxiliary assumptions, and identify boundary conditions of measuring value and uncertainty. We end our report by discussing how future validation studies might be designed. Our study demonstrates the importance of investigating how to implement study selection strategies in practice. Our sample and study design can be extended to explore the feasibility of other formal study selection strategies that have been proposed. Show less
Bioorthogonal deprotectionsare readily used to control biologicalfunction in a cell-specific manner. To further improve the spatialresolution of these reactions, we here present a lysosome... Show moreBioorthogonal deprotectionsare readily used to control biologicalfunction in a cell-specific manner. To further improve the spatialresolution of these reactions, we here present a lysosome-targetedtetrazine for an organelle-specific deprotection reaction. We showthat trans-cyclooctene deprotection with this reagentcan be used to control the biological activity of ligands for invariantnatural killer T cells in the lysosome to shed light on the processingpathway in antigen presenting cells. We then use the lysosome-targetedtetrazine to show that long peptide antigens used for CD8(+) T cell activation do not pass through this organelle, suggestinga role for the earlier endosomal compartments for their processing. Show less
Leeuwen, T. van; Doelman, W.; Kieboom, R.W.R. van den; Florea, B.I.; Kasteren, S.I. van 2023
Uptake and processing of antigens by antigen presenting cells (APCs) is a key step in the initiation of the adaptive immune response. Studying these processes is complex as the identification of... Show moreUptake and processing of antigens by antigen presenting cells (APCs) is a key step in the initiation of the adaptive immune response. Studying these processes is complex as the identification of low abundant exogenous antigens from complex cell extracts is difficult. Mass-spectrometry based proteomics - the ideal analysis tool in this case - requires methods to retrieve such molecules with high efficiency and low background. Here, we present a method for the selective and sensitive enrichment of antigenic peptides from APCs using click-antigens; antigenic proteins expressed with azidohomoalanine (Aha) in place of methionine residues. We here describe the capture of such antigens using a new covalent method namely, alkynyl functionalized PEG-based Rink amide resin, that enables capture of click-antigens via copper-catalyzed azide-alkyne [2 + 3] cycloaddition (CuAAC). The covalent nature of the thus formed linkage allows stringent washing to remove a-specific background material, prior to retrieval peptides by acid-mediated release. We successfully identified peptides from a tryptic digest of the full APC proteome containing femtomole amounts of Aha-labelled antigen, making this a promising approach for clean and selective enrichment of rare bioorthogonally modified peptides from complex mixtures. Show less
Andriiashen, V.; Liere, R. van; Leeuwen, T. van; Batenburg, K.J. 2023
Although X-ray imaging is used routinely in industry for high-throughput product quality control, its capability to detect internal defects has strong limitations. The main challenge stems from the... Show moreAlthough X-ray imaging is used routinely in industry for high-throughput product quality control, its capability to detect internal defects has strong limitations. The main challenge stems from the superposition of multiple object features within a single X-ray view. Deep Convolutional neural networks can be trained by annotated datasets of X-ray images to detect foreign objects in real-time. However, this approach depends heavily on the availability of a large amount of data, strongly hampering the viability of industrial use with high variability between batches of products. We present a computationally efficient, CT-based approach for creating artificial single-view X-ray data based on just a few physically CT-scanned objects. By algorithmically modifying the CT-volume, a large variety of training examples is obtained. Our results show that applying the generative model to a single CT-scanned object results in image analysis accuracy that would otherwise be achieved with scans of tens of real-world samples. Our methodology leads to a strong reduction in training data needed, improved coverage of the combinations of base and foreign objects, and extensive generalizability to additional features. Once trained on just a single CT-scanned object, the resulting deep neural network can detect foreign objects in real-time with high accuracy. Show less
Detection of unwanted ('foreign') objects within products is a common procedure in many branches of industry for maintaining production quality. X-ray imaging is a fast, non-invasive and widely... Show moreDetection of unwanted ('foreign') objects within products is a common procedure in many branches of industry for maintaining production quality. X-ray imaging is a fast, non-invasive and widely applicable method for foreign object detection. Deep learning has recently emerged as a powerful approach for recognizing patterns in radiographs (i.e., X-ray images), enabling automated X-ray based foreign object detection. However, these methods require a large number of training examples and manual annotation of these examples is a subjective and laborious task. In this work, we propose a Computed Tomography (CT) based method for producing training data for supervised learning of foreign object detection, with minimal labor requirements. In our approach, a few representative objects are CT scanned and reconstructed in 3D. The radiographs that are acquired as part of the CT-scan data serve as input for the machine learning method. High-quality ground truth locations of the foreign objects are obtained through accurate 3D reconstructions and segmentations. Using these segmented volumes, corresponding 2D segmentations are obtained by creating virtual projections. We outline the benefits of objectively and reproducibly generating training data in this way. In addition, we show how the accuracy depends on the number of objects used for the CT reconstructions. The results show that in this workflow generally only a relatively small number of representative objects (i.e., fewer than 10) are needed to achieve adequate detection performance in an industrial setting. Show less
Zeegers, M.T.; Kadu, A.; Leeuwen, T. van; Batenburg, K.J. 2022
Advances in multi-spectral detectors are causing a paradigm shift in x-ray computed tomography (CT). Spectral information acquired from these detectors can be used to extract volumetric material... Show moreAdvances in multi-spectral detectors are causing a paradigm shift in x-ray computed tomography (CT). Spectral information acquired from these detectors can be used to extract volumetric material composition maps of the object of interest. If the materials and their spectral responses are known a priori, the image reconstruction step is rather straightforward. If they are not known, however, the maps as well as the responses need to be estimated jointly. A conventional workflow in spectral CT involves performing volume reconstruction followed by material decomposition, or vice versa. However, these methods inherently suffer from the ill-posedness of the joint reconstruction problem. To resolve this issue, we propose 'A Dictionary-based Joint reconstruction and Unmixing method for Spectral Tomography' (ADJUST). Our formulation relies on forming a dictionary of spectral signatures of materials common in CT and prior knowledge of the number of materials present in an object. In particular, we decompose the spectral volume linearly in terms of spatial material maps, a spectral dictionary, and the indicator of materials for the dictionary elements. We propose a memory-efficient accelerated alternating proximal gradient method to find an approximate solution to the resulting bi-convex problem. From numerical demonstrations on several synthetic phantoms, we observe that ADJUST performs exceedingly well compared to other state-of-the-art methods. Additionally, we address the robustness of ADJUST against limited and noisy measurement patterns. The demonstration of the proposed approach on a spectral micro-CT dataset shows its potential for real-world applications. Code is available at https://github.com/mzeegers/ADJUST. Show less
Torres-Garcia, D.; Plassche, M.A.T. van de; Boven, E. van; Leeuwen, T. van; Groenewold, M.G.J.; Sarris, A.J.C.; ... ; Kasteren, S.I. van 2022
Bioorthogonal chemistry combines well with activity-based protein profiling, as it allows for the introduction of detection tags without significantly influencing the physiochemical and biological... Show moreBioorthogonal chemistry combines well with activity-based protein profiling, as it allows for the introduction of detection tags without significantly influencing the physiochemical and biological functions of the probe. In this work, we introduced methyltetrazinylalanine (MeTz-Ala), a close mimic of phenylalanine, into a dipeptide fluoromethylketone cysteine protease inhibitor. Following covalent and irreversible inhibition, the tetrazine allows vizualisation of the captured cathepsin activity by means of inverse electron demand Diels Alder ligation in cell lysates and live cells, demonstrating that tetrazines can be used as live cell compatible, minimal bioorthogonal tags in activity-based protein profiling. Show less
Proteolysis is fundamental to many biological processes. In the immune system, it underpins the activation of the adaptive immune response: degradation of antigenic material into short peptides and... Show moreProteolysis is fundamental to many biological processes. In the immune system, it underpins the activation of the adaptive immune response: degradation of antigenic material into short peptides and presentation thereof on major histocompatibility complexes, leads to activation of T-cells. This initiates the adaptive immune response against many pathogens. Studying proteolysis is difficult, as the oft-used polypeptide reporters are susceptible to proteolytic sequestration themselves. Here we present a new approach that allows the imaging of antigen proteolysis throughout the processing pathway in an unbiased manner. By incorporating bioorthogonal functionalities into the protein in place of methionines, antigens can be followed during degradation, whilst leaving reactive sidechains open to templated and non-templated post-translational modifications, such as citrullination and carbamylation. Using this approach, we followed and imaged the post-uptake fate of the commonly used antigen ovalbumin, as well as the post-translationally citrullinated and/or carbamylated auto-antigen vinculin in rheumatoid arthritis, revealing differences in antigen processing and presentation. Show less
Leeuwen, T. van; Araman, C.; Pournara, L.P.; Kampstra, A.S.B.; Bakkum, T.; Marqvorsen, M.H.S.; ... ; Kasteren, S.I. van 2021
Proteolysis is fundamental to many biological processes. In the immune system, it underpins the activation of the adaptive immune response: degradation of antigenic material into short peptides and... Show moreProteolysis is fundamental to many biological processes. In the immune system, it underpins the activation of the adaptive immune response: degradation of antigenic material into short peptides and presentation thereof on major histocompatibility complexes, leads to activation of T-cells. This initiates the adaptive immune response against many pathogens. Studying proteolysis is difficult, as the oft-used polypeptide reporters are susceptible to proteolytic sequestration themselves. Here we present a new approach that allows the imaging of antigen proteolysis throughout the processing pathway in an unbiased manner. By incorporating bioorthogonal functionalities into the protein in place of methionines, antigens can be followed during degradation, whilst leaving reactive sidechains open to templated and non-templated post-translational modifications, such as citrullination and carbamylation. Using this approach, we followed and imaged the post-uptake fate of the commonly used antigen ovalbumin, as well as the post-translationally citrullinated and/or carbamylated auto-antigen vinculin in rheumatoid arthritis, revealing differences in antigen processing and presentation. Show less
Dalen, F.J. van; Bakkum, T.; Leeuwen, T. van; Groenewold, G.J.M.; Deu, E.; Koster, A.J.; ... ; Verdoes, M. 2021
Cathepsin S is a lysosomal cysteine protease highly expressed in immune cells such as dendritic cells, B cells and macrophages. Its functions include extracellular matrix breakdown and cleavage of... Show moreCathepsin S is a lysosomal cysteine protease highly expressed in immune cells such as dendritic cells, B cells and macrophages. Its functions include extracellular matrix breakdown and cleavage of cell adhesion molecules to facilitate immune cell motility, as well as cleavage of the invariant chain during maturation of major histocompatibility complex II. The identification of these diverse specific functions has brought the challenge of delineating cathepsin S activity with great spatial precision, relative to related enzymes and substrates. Here, the development of a potent and highly selective two-step activity-based probe for cathepsin S and the application in multicolor bio-orthogonal correlative light-electron microscopy is presented. LHVS, which has been reported as a selective inhibitor of cathepsin S with nanomolar potency, formed the basis for our probe design. However, in competitive activity-based protein profiling experiments LHVS showed significant cross-reactivity toward Cat L. Introduction of an azide group in the P2 position expanded the selectivity window for cathepsin S, but rendered the probe undetectable, as demonstrated in bio-orthogonal competitive activity-based protein profiling. Incorporation of an additional azide handle for click chemistry on the solvent-exposed P1 position allowed for selective labeling of cathepsin S. This highlights the influence of click handle positioning on probe efficacy. This probe was utilized in multicolor bio-orthogonal confocal and correlative light-electron microscopy to investigate the localization of cathepsin S activity at an ultrastructural level in bone marrow-derived dendritic cells. The tools developed in this study will aid the characterization of the variety of functions of cathepsin S throughout biology. Show less
Dalen, F.J. van; Bakkum, T.; Leeuwen, T. van; Groenewold, M.; Deu, E.; Koster, A.J.; ... ; Verdoes, M. 2021
Cathepsin S is a lysosomal cysteine protease highly expressed in immune cells such as dendritic cells, B cells and macrophages. Its functions include extracellular matrix breakdown and cleavage of... Show moreCathepsin S is a lysosomal cysteine protease highly expressed in immune cells such as dendritic cells, B cells and macrophages. Its functions include extracellular matrix breakdown and cleavage of cell adhesion molecules to facilitate immune cell motility, as well as cleavage of the invariant chain during maturation of major histocompatibility complex II. The identification of these diverse specific functions has brought the challenge of delineating cathepsin S activity with great spatial precision, relative to related enzymes and substrates. Here, the development of a potent and highly selective two-step activity-based probe for cathepsin S and the application in multicolor bio-orthogonal correlative light-electron microscopy is presented. LHVS, which has been reported as a selective inhibitor of cathepsin S with nanomolar potency, formed the basis for our probe design. However, in competitive activity-based protein profiling experiments LHVS showed significant cross-reactivity toward Cat L. Introduction of an azide group in the P2 position expanded the selectivity window for cathepsin S, but rendered the probe undetectable, as demonstrated in bio-orthogonal competitive activity-based protein profiling. Incorporation of an additional azide handle for click chemistry on the solvent-exposed P1 position allowed for selective labeling of cathepsin S. This highlights the influence of click handle positioning on probe efficacy. This probe was utilized in multicolor bio-orthogonal confocal and correlative light-electron microscopy to investigate the localization of cathepsin S activity at an ultrastructural level in bone marrow-derived dendritic cells. The tools developed in this study will aid the characterization of the variety of functions of cathepsin S throughout biology. Show less
Zeegers, M.T.; Pelt, D.M.; Leeuwen, T. van; Liere, R. van; Batenburg, K.J. 2020
An important challenge in hyperspectral imaging tasks is to cope with the large number of spectral bins. Common spectral data reduction methods do not take prior knowledge about the task into... Show moreAn important challenge in hyperspectral imaging tasks is to cope with the large number of spectral bins. Common spectral data reduction methods do not take prior knowledge about the task into account. Consequently, sparsely occurring features that may be essential for the imaging task may not be preserved in the data reduction step. Convolutional neural network (CNN) approaches are capable of learning the specific features relevant to the particular imaging task, but applying them directly to the spectral input data is constrained by the computational efficiency. We propose a novel supervised deep learning approach for combining data reduction and image analysis in an end-to-end architecture. In our approach, the neural network component that performs the reduction is trained such that image features most relevant for the task are preserved in the reduction step. Results for two convolutional neural network architectures and two types of generated datasets show that the proposed Data Reduction CNN (DRCNN) approach can produce more accurate results than existing popular data reduction methods, and can be used in a wide range of problem settings. The integration of knowledge about the task allows for more image compression and higher accuracies compared to standard data reduction methods. Show less
Bakkum, T.; Heemskerk, M.T.; Bos, E.; Groenewold, M.; Oikonomeas-Koppasis, N.; Walburg, K.V.; ... ; Kasteren, S.I. van 2020
Bioorthogonal correlative light-electron microscopy (BCLEM) can give a detailed overview of multicomponent biological systems. It can provide information on the ultrastructural context of... Show moreBioorthogonal correlative light-electron microscopy (BCLEM) can give a detailed overview of multicomponent biological systems. It can provide information on the ultrastructural context of bioorthogonal handles and other fluorescent signals, as well as information about subcellular organization. We have here applied B-CLEM to the study of the intracellular pathogen Mycobacterium tuberculosis (Mtb) by generating a triply labeled Mtb through combined metabolic labeling of the cell wall and the proteome of a DsRed-expressing Mtb strain. Study of this pathogen in a B-CLEM setting was used to provide information about the intracellular distribution of the pathogen, as well as its in situ response to various clinical antibiotics, supported by flow cytometric analysis of the bacteria, after recovery from the host cell (ex cellula). The RNA polymerase-targeting drug rifampicin displayed the most prominent effect on subcellular distribution, suggesting the most direct effect on pathogenicity and/or viability, while the cell wall synthesis-targeting drugs isoniazid and ethambutol effectively rescued bacterial division-induced loss of metabolic labels. The three drugs combined did not give a more pronounced effect but rather an intermediate response, whereas gentamicin displayed a surprisingly strong additive effect on subcellular distribution. Show less
Ellemers, N.; Toorn, J. van der; Paunov, Y.; Leeuwen, T. van 2019
We review empirical research on (social) psychology of morality to identify which issues and relations are well documented by existing data and which areas of inquiry are in need of further... Show moreWe review empirical research on (social) psychology of morality to identify which issues and relations are well documented by existing data and which areas of inquiry are in need of further empirical evidence. An electronic literature search yielded a total of 1,278 relevant research articles published from 1940 through 2017. These were subjected to expert content analysis and standardized bibliometric analysis to classify research questions and relate these to (trends in) empirical approaches that characterize research on morality. We categorize the research questions addressed in this literature into five different themes and consider how empirical approaches within each of these themes have addressed psychological antecedents and implications of moral behavior. We conclude that some key features of theoretical questions relating to human morality are not systematically captured in empirical research and are in need of further investigation. Show less
A long tradition of sociological research aims to understand the differences in the organizational and cognitive structure of scientific fields. This sociological tradition was in its earlier years... Show moreA long tradition of sociological research aims to understand the differences in the organizational and cognitive structure of scientific fields. This sociological tradition was in its earlier years intimately connected with the emerging field of bibliometric methods and applications, originated in the 1960s with the work of Storer and Price. However, the sociology of science and scientometrics have since the early 1980s drifted apart and attempts to reconcile them, or to reconcile the more theoretically inclined field of science and technology studies with scientometrics, have not had the desired effect. Recently, scholars have again argued for the need for interdisciplinary work bridging the sociology of science or science and technology studies with scientometrics. We take up these calls and explore ways to bridge the sociology of science with scientometrics by offering an operationalisation and empirical assessment of the rural and urban sociological framework by Becker and Trowler (2001). We compare ten specialisms from five disciplines: history, computer science, astrophysics, literature and biology, and study the connectivity properties of the bibliographic coupling networks of each. Our results show that the specialisms in the humanities possess a much lower connectivity, organising in many, smaller topics of research. They also show a lower reliance on shared core sources, contrary to the framework's predictions, suggesting that more theoretical and empirical work is required in order to fully characterise different specialisms of research. Show less
