Biology subjects

Ackermann, J.

Publications and source records attributed to Ackermann, J..

13 recordsLinked to original sources

bioRxiv2024

Macrophages foster adaptive anti-tumor immunity by ZEB1-dependent cytotoxic T cell chemoattraction

Tumor-associated macrophages (TAMs) shape the tumor microenvironment (TME) and exert a decisive impact on anti-tumor immunity. Understanding TAM function is therefore critical to understand anti-tumor immune responses and to design immunotherapies. Here, we describe the transcription factor ZEB1, a well-known driver of epithelial-to-mesenchymal transition, as an intrinsic regulator of TAM function in adaptive anti-tumor immunity. By combining cell type-specific deletion of Zeb1 with syngeneic models of colorectal and pancreatic cancer, we discovered an unexpected function of ZEB1 in the TAM-mediated control of T cell trafficking. ZEB1 supports secretion of a subset of chemokines including CCL2 and CCL22 by promoting their transcription and translation as well as by safeguarding protein processing. ZEB1 thereby elevates cytotoxic T cell (CTL) recruitment in vitro and in vivo and fosters immunosurveillance during tumor as well as lung metastatic outgrowth. Our study spotlights ZEB1 as a crucial facilitator of adaptive anti-tumor immunity and uncovers a potential therapeutic window of opportunity for cytokine-guided enhancement of CTL infiltration into tumors and metastases.

cancer biology↗

bioRxiv2024

How cancer-associated fibroblasts promote T cell exclusion in human lung tumors: a physical perspective

The tumor stroma is a tissue composed primarily of extracellular matrix, fibroblasts, immune cells, and vasculature. Its structure and functions, such as nutrient support and waste removal, are altered during malignancy. Tumor cells transform fibroblasts into cancer-associated fibroblasts, which have important immunosuppressive activity on which growth, invasion, and metastasis depend. These activated fibroblasts prevent immune cell infiltration into the tumor nest, thereby promoting cancer progression and inhibiting T-cell-based immunotherapy. To understand these complex interactions, we measure the density of different cell types in the stroma using immunohistochemistry techniques on tumor samples from lung cancer patients. We incorporate these data, and also known information on cell proliferation rates and relevant biochemical interactions, into a minimal dynamical system with few parameters. A spatio-temporal approach to the inhomogeneous environment explains the cell distribution and fate of lung carcinomas. The model reproduces that cancer-associated fibroblasts act as a barrier to tumor growth, but also reduce the efficiency of the immune response. The final outcome depends on the parameter values for each patient and leads to either tumor invasion, persistence, or eradication as a result of the interplay between cancer cell growth, T-cell cytotoxic activity, and fibroblast attraction, activation, and spatial dynamics. Our conclusion is that a wide spectrum of scenarios exists as a result of the competition between the characteristic times of cancer cell growth and the activity rates of the other species. Nevertheless, distinct trajectories and patterns allow quantitative predictions that may help in the selection of new therapies and personalized protocols. We conclude with different options for further modeling. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/575824v3_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@156ac4forg.highwire.dtl.DTLVardef@14a9a19org.highwire.dtl.DTLVardef@cafebeorg.highwire.dtl.DTLVardef@11aa3bf_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

biophysics↗

bioRxiv2023

Aging and freezing of active nematic dynamics of cancer-associated fibroblasts by fibronectin matrix remodeling

Cancer-associated fibroblasts (CAFs) are one of the most abundant cell types in tumor stroma. Exhibiting an elongated morphology, CAFs align with each other, closely resembling nematic ordering in liquid crystal physics. CAFs play a pivotal role in the genesis and remodeling of the extracellular matrix (ECM), with ECM proteins, especially fibronectin, reciprocally modulating CAF alignment and coherence. Yet, the intricate feedback loops between fibronectin deposition and CAF structuring remain largely unexplored. Here, we combined CAF live imaging, traction force microscopy, ECM microfabrication, and theoretical modeling to assess how the ECM influences the dynamics of nematically ordered CAFs. We found that CAFs dynamically orchestrate a fibronectin network that mirrors their nematic ordering. Over time, this passive nematic ordering of fibronectin, in turn, steers CAF rearrangement. Contrary to most cellular systems, where defects remain dynamic at a steady state, the ECM/CAF interplay profoundly alters the behavior of both CAF and ECM nematics, leading to aging-massive slowdown, and even freezing of defect dynamics. This results in a CAFs capsule where aligned areas and defects are spatially and temporally fixed, yet active, exerting forces at the substate and transmitting forces between cells. Functionally, while defects may be permissive, it is the fibronectin loss-induced fluidization of the CAF capsule that critically undermines its barrier function.

cell biology↗

bioRxiv2023

Onsager's variational principle in proliferating biological tissues, in presenceof activity and anisotropy

A hallmark of biological cells is their ability to proliferate and of tissues their ability to grow. This is common in morphogenesis and embryogenesis but also in pathological conditions such as tumour growth. To consider these tissues from a physical point of view, it is necessary to derive fundamental relationships, in particular for velocities and density components, taking into account growth terms, chemical factors and the symmetry of cells and tissues. The aim is then to develop a consistent coarse-grained approach to these complex systems, which exhibit proliferation, disorder, anisotropy and activity at small scales. To this end, Onsagers variational principle allows the systematic derivation of flux-force relations in systems out of equilibrium and the principle of the extremum of dissipation, first formulated by Rayleigh and revisited by Onsager, finally leads to a consistent formulation for a continuous approach in terms of a coupled set of partial differential equations. Considering the growth and death rates as fluxes, as well as the chemical reactions driving the cellular activities, we derive the momentum equations based on a leading order physical expansion. Furthermore, we illustrate the different interactions for systems with nematic or polar order at small scales, and numerically solve the resulting system of partial differential equations in relevant biophysical growth examples. To conclude, we show that Onsagers variational principle is useful for systematically exploring the different scenarios in proliferating systems, and how morphogenesis depends on these interactions.

biophysics↗

bioRxiv2023

Smart Slides for Optical Monitoring of Cellular Processes

The molecules released by cells are a fingerprint of their current state. Methods that measure them with high spatial and temporal resolution would provide valuable insights into cell physiology and diseases. Here, we develop a nanosensor coating that transforms standard cell culture materials/dishes into "Smart Slides" capable of optically monitoring biochemical efflux from cells. For this purpose, we use single wall carbon nanotubes (SWCNTs) that are fluorescent in the beneficial near-infrared (NIR, 850 - 1700 nm) window. They are chemically tailored to detect the neurotransmitter dopamine by a change in fluorescence intensity. These nanosensors are spin-coated on glass substrates and we show that such sensor layers can be sterilized by UV light and can be stored in dry condition or buffer for at least 6 weeks. We also identify the optimal sensor density to maximize sensitivity. Finally, we use these materials to image dopamine release from neuronal cells cultivated on top in the presence of various psychotropic substances, which represents a system to test pharmaceuticals for neurological or neurodegenerative diseases. Therefore, Smart Slides are a powerful tool to monitor cellular processes in cell culture systems.

biochemistry↗

bioRxiv2023

Stochastic modeling of the dynamics of Salmonella infection of epithelial cells

Bacteria of the Salmonella genus are intracellular pathogens, which cause gastroenteritis and typhoid fever in animals and humans, and are responsible for millions of infections and thousands of deaths across the world every year. Furthermore, Salmonella has played the role of a model organism for studying host-pathogen interactions. Taking these two aspects into account, enormous efforts in the literature are devoted to study this intracellular pathogen. Within epithelial cells, there are two distinct subpopulations of Salmonella: (i) a large fraction of Salmonella, which are enclosed by vacuoles, and (ii) a small fraction of hyper-replicating cytosolic Salmonella. Here, by considering the infection of epithelial cells by Salmonella as a discrete-state, continuous-time Markov process, we propose a stochastic model of infection, which includes the invasion of Salmonella into the epithelial cells by a cooperative strategy, the replication inside the Salmonella-containing vacuole, and the bacterial proliferation in the cytosol. The xenophagic degradation of cytosolic bacteria is considered, too. The stochastic approach provides important insights into stochastic variation and heterogeneity of the vacuolar and cytosolic Salmonella populations on a single-cell level over time. Specifically, we predict the percentage of infected human epithelial cells depending on the incubation time and the multiplicity of infection, an d the bacterial load of the infected cells at different post-infection times.

systems biology↗

bioRxiv2021

Mathematical modeling of the molecular switch of TNFR1-mediated signaling pathways using Petri nets

The paper describes a mathematical model of the molecular switch of cell survival, apoptosis, and necroptosis in cellular signaling pathways initiated by tumor necrosis factor 1. Based on experimental findings in the current literature, we constructed a Petri net model in terms of detailed molecular reactions for the molecular players, protein complexes, post-translational modifications, and cross talk. The model comprises 118 biochemical entities, 130 reactions, and 299 connecting edges. Applying Petri net analysis techniques, we found 279 pathways describing complete signal flows from receptor activation to cellular response, representing the combinatorial diversity of functional pathways.120 pathways steered the cell to survival, whereas 58 and 35 pathways led to apoptosis and necroptosis, respectively. For 65 pathways, the triggered response was not deterministic, leading to multiple possible outcomes. Based on the Petri net, we investigated the detailed in silico knockout behavior and identified important checkpoints of the TNFR1 signaling pathway in terms of ubiquitination within complex I and the gene expression dependent on NF-{kappa}B, which controls the caspase activity in complex II and apoptosis induction.

systems biology↗

bioRxiv2021

Modeling the mechanics of growing epithelia with a bilayer plate theory

Epithelia, which consists of cell sheets lying on a substrate, are prevalent structures of multi-cellular organisms. The physical basis of epithelial morphogenesis has been intensely investigated in recent years. However, as 2D mechanics focused most attention, we still lack a rigorous description of how the mechanical interactions between the cell layer and its substrate can lead to 3D distortions. This work provides a complete description of epithelial mechanics using the most straightforward model of an epithelium: a thin elastic bilayer. We first provide experimental evidence in Drosophila tissues that localized alterations of the cell-substrate (the extracellular matrix) can lead to profound 3D shape changes in epithelia. We then develop an analytical model modifying the Foppl-von Karman equation with growth for bilayers. We provide a complete description of all contributions from biophysical characteristics of epithelia. We show how any localized inhomogeneity of stiffness or thickness drastically changes the bending process when the two layers grow differently. Comparison with finite-element simulations and experiments performed on Drosophila wing imaginal discs validate this approach for thin epithelia.

biophysics↗

bioRxiv2021

Identification of Leucinostatins from Ophiocordyceps sp. as Antiparasitic Agents Against Trypanosoma cruzi

Safe and effective treatments for Chagas disease, a potentially fatal parasitic infection associated with cardiac and gastrointestinal pathology and caused by the kinetoplastid parasite Trypanosoma cruzi, have yet to be developed. Benznidazole and nifurtimox, which are currently the only available drugs against T. cruzi, are associated with severe adverse effects and questionable efficacy in the late stage of the disease. Natural products have proven to be a rich source of new chemotypes for other infectious agents. We utilized a microscopy-based high-throughput phenotypic screen to identify inhibitors of T. cruzi from a library of natural product samples obtained from fungi procured through a Citizen Science Soil Collection Program (https://whatsinyourbackyard.org/), and the Great Lakes (USA) benthic environment. We identified five leucinostatins (A, B, F, NPDG C and NPDG D) as potent inhibitors of the intracellular amastigote form of T. cruzi. Leucinostatin B also showed in vivo efficacy in a mouse model of Chagas disease. Given prior reports that leucinostatins A and B have antiparasitic activity against the related kinetoplastid T. brucei, our findings suggest a potential cross-trypanocidal compound class and provide a platform for further chemical derivatization of a potent chemical scaffold against T. cruzi.

microbiology↗

bioRxiv2018

Mapping the genetics of neuropsychological traits to the molecular network of the human brain using a data integrative approach

MotivationComplex neuropsychiatric conditions including autism spectrum disorders are among the most heritable neurodevelopmental disorders with distinct profiles of neuropsychological traits. A variety of genetic factors modulate these traits (phenotypes) underlying clinical diagnoses. To explore the associations between genetic factors and phenotypes, genome-wide association studies are broadly applied. Stringent quality checks and thorough downstream analyses for in-depth interpretation of the associations are an indispensable prerequisite. However, in the area of neuropsychology there is no framework existing, which besides performing association studies also affiliates genetic variants at the brain and gene network level within a single framework.\n\nResultsWe present a novel bioinformatics approach in the field of neuropsychology that integrates current state-of-the-art tools, algorithms and brain transcriptome data to elaborate the association of phenotype and genotype data. The integration of transcriptome data gives an advantage over the existing pipelines by directly translating genetic associations to brain regions and developmental patterns. Based on our data integrative approach, we identify genetic variants associated with Intelligence Quotient (IQ) in an autism cohort and found their respective genes to be expressed in specific brain areas.\n\nConclusionOur data integrative approach revealed that IQ is related to early down-regulated and late up-regulated gene modules implicated in frontal cortex and striatum, respectively. Besides identifying new gene associations with IQ we also provide a proof of concept, as several of the identified genes in our analysis are candidate genes related to intelligence in autism, intellectual disability, and Alzheimers disease. The framework provides a complete extensive analysis starting from a phenotypic trait data to its association at specific brain areas at vulnerable time points within a timespan of four days.\n\nAvailability and ImplementationOur framework is implemented in R and Python. It is available as an in-house script, which can be provided on demand.\n\nContactafsheen.yousaf@kgu.de

bioinformatics↗

bioRxiv2018

isiKnock: in silico knockouts in biochemical pathways

SummaryisiKnock is a new software that automatically conducts in silico knockouts for mathematical models of biochemical pathways. The software allows for the prediction of the behavior of biological systems after single or multiple knockout. The implemented algorithm applies transition invariants and the novel concept of Manatee invariants. A knockout matrix visualizes the results. The tool enables the analysis of dependencies, for example, in signal flows from the receptor activation to the cell response at steady state.\n\nAvailability and ImplementationisiKnock is an open-source tool, freely available at http://www.bioinformatik.uni-frankfurt.de/tools/isiKnock/index.php. It requires at least Java 8 and runs under Microsoft Windows, Linux, and Mac OS.\n\nContactina.koch@bioinformatik.uni-frankfurt.de

bioinformatics↗

bioRxiv2017

Bioinformatics analysis quantifies neighborhood preferences of cancer cells in Hodgkin lymphoma.

MotivationHodgkin lymphoma is a tumor of the lymphatic system and represents one of the most frequent lymphoma in the Western world. It is characterized by Hodgkin cells and Reed-Sternberg cells, which exhibit a broad morphological spectrum. The cells are visualized by immunohistochemical staining of tissue sections. In pathology, tissue images are mainly manually evaluated, relying on the expertise and experience of pathologists. Computational quantification methods become more and more essential to evaluate tissue images. In particular, the distribution of cancer cells is of great interest.\n\nResultsHere, we systematically quantified and investigated cancer cell properties and their spatial neighborhood relations by applying statistical analyses to whole slide images of Hodgkin lymphoma and lymphadenitis, which describes a non-cancerous inflammation of the lymph node. We differentiated cells by their morphology and studied the spatial neighborhood relation of more than 400,000 immunohistochemically stained cells. We found that, according to their morphological features, the cells exhibited significant preferences for and aversions to cells of specific profiles as nearest neighbor. We quantified differences between Hodgkin lymphoma and lymphadenitis concerning the neighborhood relations of cells and the sizes of cells. The approach can easily be applied to other cancer types.\n\nContactina.koch@bioinformatik.uni-frankfurt.de

bioinformatics↗

bioRxiv2017

Reversed depth in anti-correlated random dot stereograms and central-peripheral difference in visual inference

1Two images of random black and white dots, one for each eye, can represent object surfaces in a threedimensional scene when the dots correspond interocularly in a random dot stereogram (RDS). The spatial disparities between the corresponding dots represent depths of object surfaces. If the dots become anti-correlated such that a black dot in one monocular image corresponds to a white dot in the other, disparity-tuned neurons in the primary visual cortex (V1) respond as if their preferred disparities become non-preferred and vice versa, thereby reversing the disparity signs reported to higher visual areas. Humans have great difficulty perceiving the reversed depth, or any depth at all, in anti-correlated RDSs. We report that the reversed depth is more easily perceived when the RDSs are viewed in peripheral visual field, supporting a recently proposed central-peripheral dichotomy in mechanisms of feedback from higher to lower visual cortical areas for visual inference.

neuroscience↗