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  • 1
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    Online Resource
    From affinity selection to kinetic selection in Germinal Centre modelling
    Public Library of Science (PLoS) ; 2022
    In:  PLOS Computational Biology Vol. 18, No. 6 ( 2022-6-3), p. e1010168-
    Details
    In: PLOS Computational Biology, Public Library of Science (PLoS), Vol. 18, No. 6 ( 2022-6-3), p. e1010168-
    Abstract: Affinity maturation is an evolutionary process by which the affinity of antibodies (Abs) against specific antigens (Ags) increases through rounds of B-cell proliferation, somatic hypermutation, and positive selection in germinal centres (GC). The positive selection of B cells depends on affinity, but the underlying mechanisms of affinity discrimination and affinity-based selection are not well understood. It has been suggested that selection in GC depends on both rapid binding of B-cell receptors (BcRs) to Ags which is kinetically favourable and tight binding of BcRs to Ags, which is thermodynamically favourable; however, it has not been shown whether a selection bias for kinetic properties is present in the GC. To investigate the GC selection bias towards rapid and tight binding, we developed an agent-based model of GC and compared the evolution of founder B cells with initially identical low affinities but with different association/dissociation rates for Ag presented by follicular dendritic cells in three Ag collection mechanisms. We compared an Ag collection mechanism based on association/dissociation rates of B-cell interaction with presented Ag, which includes a probabilistic rupture of bonds between the B-cell and Ag (Scenario-1) with a reference scenario based on an affinity-based Ag collection mechanism (Scenario-0). Simulations showed that the mechanism of Ag collection affects the GC dynamics and the GC outputs concerning fast/slow (un)binding of B cells to FDC-presented Ags. In particular, clones with lower dissociation rates outcompete clones with higher association rates in Scenario-1, while remaining B cells from clones with higher association rates reach higher affinities. Accordingly, plasma cell and memory B cell populations were biased towards B-cell clones with lower dissociation rates. Without such probabilistic ruptures during the Ag extraction process (Scenario-2), the selective advantage for clones with very low dissociation rates diminished, and the affinity maturation level of all clones decreased to the reference level.
    Type of Medium: Online Resource
    ISSN: 1553-7358
    URL: Article
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    DOI: 10.1371/journal.pcbi.1010168
    DOI: 10.1371/journal.pcbi.1010168.g001
    DOI: 10.1371/journal.pcbi.1010168.g002
    DOI: 10.1371/journal.pcbi.1010168.g003
    DOI: 10.1371/journal.pcbi.1010168.g004
    DOI: 10.1371/journal.pcbi.1010168.g005
    DOI: 10.1371/journal.pcbi.1010168.t001
    DOI: 10.1371/journal.pcbi.1010168.s001
    DOI: 10.1371/journal.pcbi.1010168.s002
    DOI: 10.1371/journal.pcbi.1010168.s003
    DOI: 10.1371/journal.pcbi.1010168.s004
    DOI: 10.1371/journal.pcbi.1010168.s005
    DOI: 10.1371/journal.pcbi.1010168.s006
    DOI: 10.1371/journal.pcbi.1010168.s007
    DOI: 10.1371/journal.pcbi.1010168.s008
    DOI: 10.1371/journal.pcbi.1010168.s009
    DOI: 10.1371/journal.pcbi.1010168.s010
    Language: English
    Publisher: Public Library of Science (PLoS)
    Publication Date: 2022
    detail.hit.zdb_id: 2193340-6
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  • 2
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    DataSheet_1.docx
    Frontiers Media SA ; 2021
    In:  Frontiers in Immunology Vol. 12 ( 2021-8-17)
    Details
    In: Frontiers in Immunology, Frontiers Media SA, Vol. 12 ( 2021-8-17)
    Abstract: Memory B cells and antibody-secreting plasma cells are generated within germinal centers during affinity maturation in which B-cell proliferation, selection, differentiation, and self-renewal play important roles. The mechanisms behind memory B cell and plasma cell differentiation in germinal centers are not well understood. However, it has been suggested that cell fate is (partially) determined by asymmetric cell division, which involves the unequal distribution of cellular components to both daughter cells. To investigate what level and/or probability of asymmetric segregation of several fate determinant molecules, such as the antigen and transcription factors (BCL6, IRF4, and BLIMP1) recapitulates the temporal switch and DZ-to-LZ ratio in the germinal center, we implemented a multiscale model that combines a core gene regulatory network for plasma cell differentiation with a model describing the cellular interactions and dynamics in the germinal center. Our simulations show that BLIMP1 driven plasma cell differentiation together with coupled asymmetric division of antigen and BLIMP1 with a large segregation between the daughter cells results in a germinal center DZ-to-LZ ratio and a temporal switch from memory B cells to plasma cells that have been observed in experiments.
    Type of Medium: Online Resource
    ISSN: 1664-3224
    URL: Article
    URL: Article
    DOI: 10.3389/fimmu.2021.716240
    DOI: 10.3389/fimmu.2021.716240.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2606827-8
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  • 3
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    Exploring dynamic metabolomics data with multiway data analysis: a simulation study
    Springer Science and Business Media LLC ; 2022
    In:  BMC Bioinformatics Vol. 23, No. 1 ( 2022-12)
    Details
    In: BMC Bioinformatics, Springer Science and Business Media LLC, Vol. 23, No. 1 ( 2022-12)
    Abstract: Analysis of dynamic metabolomics data holds the promise to improve our understanding of underlying mechanisms in metabolism. For example, it may detect changes in metabolism due to the onset of a disease. Dynamic or time-resolved metabolomics data can be arranged as a three-way array with entries organized according to a subjects mode, a metabolites mode and a time mode. While such time-evolving multiway data sets are increasingly collected, revealing the underlying mechanisms and their dynamics from such data remains challenging. For such data, one of the complexities is the presence of a superposition of several sources of variation: induced variation (due to experimental conditions or inborn errors), individual variation, and measurement error. Multiway data analysis (also known as tensor factorizations) has been successfully used in data mining to find the underlying patterns in multiway data. To explore the performance of multiway data analysis methods in terms of revealing the underlying mechanisms in dynamic metabolomics data, simulated data with known ground truth can be studied. Results We focus on simulated data arising from different dynamic models of increasing complexity, i.e., a simple linear system, a yeast glycolysis model, and a human cholesterol model. We generate data with induced variation as well as individual variation. Systematic experiments are performed to demonstrate the advantages and limitations of multiway data analysis in analyzing such dynamic metabolomics data and their capacity to disentangle the different sources of variations. We choose to use simulations since we want to understand the capability of multiway data analysis methods which is facilitated by knowing the ground truth. Conclusion Our numerical experiments demonstrate that despite the increasing complexity of the studied dynamic metabolic models, tensor factorization methods CANDECOMP/PARAFAC(CP) and Parallel Profiles with Linear Dependences (Paralind) can disentangle the sources of variations and thereby reveal the underlying mechanisms and their dynamics.
    Type of Medium: Online Resource
    ISSN: 1471-2105
    URL: Article
    DOI: 10.1186/s12859-021-04550-5
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2041484-5
    SSG: 12
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  • 4
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    Understanding repertoire sequencing data through a multiscale computational model of the germinal center
    Springer Science and Business Media LLC ; 2023
    In:  npj Systems Biology and Applications Vol. 9, No. 1 ( 2023-03-16)
    Details
    In: npj Systems Biology and Applications, Springer Science and Business Media LLC, Vol. 9, No. 1 ( 2023-03-16)
    Abstract: Sequencing of B-cell and T-cell immune receptor repertoires helps us to understand the adaptive immune response, although it only provides information about the clonotypes (lineages) and their frequencies and not about, for example, their affinity or antigen (Ag) specificity. To further characterize the identified clones, usually with special attention to the particularly abundant ones (dominant), additional time-consuming or expensive experiments are generally required. Here, we present an extension of a multiscale model of the germinal center (GC) that we previously developed to gain more insight in B-cell repertoires. We compare the extent that these simulated repertoires deviate from experimental repertoires established from single GCs, blood, or tissue. Our simulations show that there is a limited correlation between clonal abundance and affinity and that there is large affinity variability among same-ancestor (same-clone) subclones. Our simulations suggest that low-abundance clones and subclones, might also be of interest since they may have high affinity for the Ag. We show that the fraction of plasma cells (PCs) with high B-cell receptor (BcR) mRNA content in the GC does not significantly affect the number of dominant clones derived from single GCs by sequencing BcR mRNAs. Results from these simulations guide data interpretation and the design of follow-up experiments.
    Type of Medium: Online Resource
    ISSN: 2056-7189
    URL: Article
    DOI: 10.1038/s41540-023-00271-y
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2841868-2
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  • 5
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    Integrative Analysis of Proteome and Transcriptome Dynamics during Bacillus subtilis Spore Revival
    American Society for Microbiology ; 2020
    In:  mSphere Vol. 5, No. 4 ( 2020-08-26)
    Details
    In: mSphere, American Society for Microbiology, Vol. 5, No. 4 ( 2020-08-26)
    Abstract: Bacillus subtilis spores can reactivate their metabolism through germination upon contact with germinants and can develop into vegetative cells upon outgrowth. However, the mechanisms at the basis of the molecular machinery that triggers the spore germination and outgrowth processes are still largely unclear. To gain further insights into these processes, the transcriptome and proteome changes occurring during the conversion of spores to vegetative cells were analyzed in the present study. For each time point sampled, the changes in the spore proteome were quantitatively monitored relative to the proteome of metabolically 15 N-labeled vegetative cells. Of the quantified proteins, 60% are shared by vegetative cells and spores, indicating that the spores have a minimal protein set, sufficient to resume metabolism upon completion of germination. These shared proteins thus represent the most basic “survival kit” for spore-based life. We observed no significant change in the proteome or the transcriptome until the spore’s completion of germination. Our analysis identified 34 abundant mRNA transcripts in the dormant spores, 31 of which are rapidly degraded after germination. In outgrowing spores, we identified 3,152 differentially expressed genes and have demonstrated the differential expression of 322 proteins with our mass spectrometry analyses. Our data also showed that 173 proteins from dormant spores, including both proteins unique to spores and proteins shared with vegetative cells, were lost after completion of germination. The observed diverse timings of synthesis of different protein sets in spore outgrowth revealed a putative core strategy underlying the revival of ‘life’ from the B. subtilis spore. IMPORTANCE This study demonstrated the progress of macromolecular synthesis during Bacillus subtilis spore germination and outgrowth. The transcriptome analysis has additionally allowed us to trace gene expression during this transformation process. For the first time, the basic survival kit for spore-based life has been identified. In addition, in this analysis based on monitoring of protein levels in germinating and outgrowing spores, the transition from (ribo)nucleotide and amino acid biosynthesis to the restoration of all metabolic pathways can be clearly seen. The integrative multi-omics approach applied in this study thus has helped us to achieve a comprehensive overview of the molecular mechanisms at the basis of spore germination and outgrowth as well as to identify important knowledge gaps in need of further study.
    Type of Medium: Online Resource
    ISSN: 2379-5042
    URL: Article
    DOI: 10.1128/mSphere.00463-20
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2020
    detail.hit.zdb_id: 2844248-9
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  • 6
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    RNA Sequencing Elucidates Drug-Specific Mechanisms of Antibiotic Tolerance and Resistance in Mycobacterium abscessus
    American Society for Microbiology ; 2022
    In:  Antimicrobial Agents and Chemotherapy Vol. 66, No. 1 ( 2022-01-18)
    Details
    In: Antimicrobial Agents and Chemotherapy, American Society for Microbiology, Vol. 66, No. 1 ( 2022-01-18)
    Abstract: Mycobacterium abscessus is an opportunistic pathogen notorious for its resistance to most classes of antibiotics and low cure rates. M. abscessus carries an array of mostly unexplored defense mechanisms. A deeper understanding of antibiotic resistance and tolerance mechanisms is pivotal in development of targeted therapeutic regimens. We provide the first description of all major transcriptional mechanisms of tolerance to all antibiotics recommended in current guidelines, using RNA sequencing-guided experiments. M. abscessus ATCC 19977 bacteria were subjected to subinhibitory concentrations of clarithromycin (CLR), amikacin (AMK), tigecycline (TIG), cefoxitin (FOX), and clofazimine (CFZ) for 4 and 24 h, followed by RNA sequencing. To confirm key mechanisms of tolerance suggested by transcriptomic responses, we performed time-kill kinetic analysis using bacteria after preexposure to CLR, AMK, or TIG for 24 h and constructed isogenic knockout and knockdown strains. To assess strain specificity, pan-genome analysis of 35 strains from all three subspecies was performed. Mycobacterium abscessus shows both drug-specific and common transcriptomic responses to antibiotic exposure. Ribosome-targeting antibiotics CLR, AMK, and TIG elicit a common response characterized by upregulation of ribosome structural genes, the WhiB7 regulon and transferases, accompanied by downregulation of respiration through NuoA-N. Exposure to any of these drugs decreases susceptibility to ribosome-targeting drugs from multiple classes. The cytochrome bd-type quinol oxidase contributes to CFZ tolerance in M. abscessus , and the sigma factor sigH but not antisigma factor MAB_3542c is involved in TIG resistance. The observed transcriptomic responses are not strain-specific, as all genes involved in tolerance, except erm(41) , are found in all included strains.
    Type of Medium: Online Resource
    ISSN: 0066-4804 , 1098-6596
    URL: Article
    DOI: 10.1128/AAC.01509-21
    RVK:
    XA 24552
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2022
    detail.hit.zdb_id: 1496156-8
    SSG: 12
    SSG: 15,3
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  • 7
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    Table1.docx
    Frontiers Media SA ; 2022
    In:  Frontiers in Systems Biology Vol. 2 ( 2022-4-27)
    Details
    In: Frontiers in Systems Biology, Frontiers Media SA, Vol. 2 ( 2022-4-27)
    Abstract: Diffuse large B-cell lymphoma is the most common subtype of non-Hodgkin’s lymphoma. It is a germinal center (GC)–derived, aggressive, and heterogeneous disease. Several transcription factors and signaling pathways that play a central role in the progression of the GC reaction and B-cell differentiation have been shown to play an oncogenic role in diffuse large B-cell lymphoma. B-cell lymphoma 6 (BCL6) is a transcriptional repressor that induces the GC B-cell phenotype and blocks plasma cell (PC) differentiation, while interferon regulatory factor 4 (IRF4) and B lymphocyte-induced maturation protein 1 (BLIMP1), a transcriptional promoter, both mediate PC differentiation and exit from the GC (1). Computational models are useful alternatives to trial-and-error experimental investigation. Ordinary differential equation (ODE) models have been used to study different known mechanisms of lymphomagenesis and suggest candidate tumorigenic alterations (2). Furthermore, multi-scale models (MSMs) have been used to study the role of cellular and molecular mechanisms involved in tumor growth (3–6). In this study, we used an existing MSM of PC differentiation in the GC to simulate eight different models with several candidate genetic alterations of the BCL6-IRF4-BLIMP1 regulatory network that lead to transcription factor deregulation and could explain the onset of diffuse large B-cell lymphoma and recapitulate the GC dynamics observed in such conditions. We observed that models with loss of BLIMP1 function (BLIMP loss and BLIMP loss IRF inc ) result in an accumulation of B cells in the GC and a block of PC differentiation and thus correctly recapitulate the observed GC and transcription factor dynamics. Models with constitutive activation of the nuclear factor kappa-light-chain-enhancer of activated B-cell (NF-kB) pathway alone and in codominance or co-expression with the enforced BCL6 expression (IRF inc and BCL inc IRF inc ) result in a decrease of GC B cells and unaltered PC production at early stages of the GC reaction, as observed experimentally. Interestingly, we also found that in IRF inc and BCL inc IRF inc models, an increase in PC production could happen at later stages of the GC reaction. Nevertheless, models with enforced BCL6 expression (BCL auto and BCL inc ) result in an expansion of GC B cell population and a block in the PC production that was not observed experimentally. Finally, models with loss of IRF4- and BLIMP1-mediated silencing of BCL6 (IRF sil and BLIMP sil ) did not affect GC and transcription factor dynamics.
    Type of Medium: Online Resource
    ISSN: 2674-0702
    URL: Article
    URL: Article
    DOI: 10.3389/fsysb.2022.864690
    DOI: 10.3389/fsysb.2022.864690.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 3106041-9
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  • 8
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    Human Blood Lipoprotein Predictions from 1H NMR Spectra: Protocol, Model Performances, and Cage of Covariance
    American Chemical Society (ACS) ; 2022
    In:  Analytical Chemistry Vol. 94, No. 2 ( 2022-01-18), p. 628-636
    Details
    In: Analytical Chemistry, American Chemical Society (ACS), Vol. 94, No. 2 ( 2022-01-18), p. 628-636
    Type of Medium: Online Resource
    ISSN: 0003-2700 , 1520-6882
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.1021/acs.analchem.1c01654
    DOI: 10.1021/acs.analchem.1c01654.s001
    DOI: 10.1021/acs.analchem.1c01654.s002
    DOI: 10.1021/acs.analchem.1c01654.s003
    Language: English
    Publisher: American Chemical Society (ACS)
    Publication Date: 2022
    detail.hit.zdb_id: 1483443-1
    detail.hit.zdb_id: 1508-8
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  • 9
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    Table_1.xlsx
    Frontiers Media SA ; 2021
    In:  Frontiers in Immunology Vol. 11 ( 2021-2-5)
    Details
    In: Frontiers in Immunology, Frontiers Media SA, Vol. 11 ( 2021-2-5)
    Abstract: Germinal centers play a key role in the adaptive immune system since they are able to produce memory B cells and plasma cells that produce high affinity antibodies for an effective immune protection. The mechanisms underlying cell-fate decisions are not well understood but asymmetric division of antigen, B-cell receptor affinity, interactions between B-cells and T follicular helper cells (triggering CD40 signaling), and regulatory interactions of transcription factors have all been proposed to play a role. In addition, a temporal switch from memory B-cell to plasma cell differentiation during the germinal center reaction has been shown. To investigate if antigen affinity-based Tfh cell help recapitulates the temporal switch we implemented a multiscale model that integrates cellular interactions with a core gene regulatory network comprising BCL6, IRF4, and BLIMP1. Using this model we show that affinity-based CD40 signaling in combination with asymmetric division of B-cells result in switch from memory B-cell to plasma cell generation during the course of the germinal center reaction. We also show that cell fate division is unlikely to be (solely) based on asymmetric division of Ag but that BLIMP1 is a more important factor. Altogether, our model enables to test the influence of molecular modulations of the CD40 signaling pathway on the production of germinal center output cells.
    Type of Medium: Online Resource
    ISSN: 1664-3224
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fimmu.2020.620716
    DOI: 10.3389/fimmu.2020.620716.s001
    DOI: 10.3389/fimmu.2020.620716.s002
    DOI: 10.3389/fimmu.2020.620716.s003
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2606827-8
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