Biology subjects

Horn, H.

Publications and source records attributed to Horn, H..

13 recordsLinked to original sources

bioRxiv2026

Design and Validation of a 3D-Printed Motorized Biaxial Cell Stretching Device

Mechanical forces have a major effect on cell behavior. Most cells in vitro are grown under static conditions on hard tissue culture plastic, conditions that do not accurately reflect living tissues. The ability of cells to sense and respond to mechanical forces is essential for key biological processes, including development, proliferation, and migration. Disruption of the ability to respond to mechanical forces are known to be a critical factor in many diseases, including cardiovascular disease, progeria, and cancer. Here, we present the design, fabrication, and biological testing of a custom-built cell-stretching device that applies controlled biaxial strain to cells cultured on a polydimethylsiloxane (PDMS) membrane. We then used this device to examine how cells respond to strain. In response to biaxial strain, MCF-7 cells activated the mechanosensitive immediate early gene (IEX-1), with its expression increasing significantly after 1 and 3 hours of stretching. Cells exposed to mechanical strain also remodeled their cytoskeleton in a direction-dependent manner. Under uniaxial strain, actin filaments reoriented perpendicular to the stretch direction, whereas biaxially stretched cells do not promote directional reorientation, but instead appear to reinforce actin at the cell periphery. Similarly, cells under uniaxial strain exhibited changes in nuclear orientation and shape that were not observed under biaxial strain. Nuclear area remained unchanged in either strain condition. These results highlight that the biaxial stretcher can be used to apply strain to cells, and that cells respond differently to biaxial strain compared to what has been reported for uniaxial strain.

Cell Biology↗

bioRxiv2025

Impact of the rotational speed and counter electrode configuration on the performance of a rotating disc bioelectrochemical reactor (RDBER) operated as microbial electrolysis cell

A 10 L Rotating Disc Bioelectrochemical Reactor (RDBER) was operated as a microbial electrolysis cell (MEC) under different rotational speeds and counter electrode configurations. Increasing the anodes speed from 0.25 to 1 rpm raised the anodic current density from 55 {+/-} 14 to 100 {+/-} 7 A m-3 while increasing hydrogen production rates from 0.05 {+/-} 0.01 to 0.18 {+/-} 0.01 [Formula]. Higher speeds provided no further benefit. Moving the counter electrodes to the upper reactor half reduced observed hydrogen shuttling. The modified RDBER reached current densities of 1.98 {+/-} 0.11 A m-2 and 0.99 {+/-} 0.03 [Formula] hydrogen production. Optical coherence tomography confirmed biofilm morphology changes but no significant increase in biovolume or substratum coverage. Hydrogen recovery remained below 50%. While the RDBER achieved high volumetric current densities and volumetric hydrogen production rates compared to other MEC pilots, improvements in anodic current density and cathodic hydrogen recovery are required for practical application. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=87 SRC="FIGDIR/small/641858v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@f8e054org.highwire.dtl.DTLVardef@14fbaaeorg.highwire.dtl.DTLVardef@1692978org.highwire.dtl.DTLVardef@121b116_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LI10 L RDBER was operated as MEC in batch experiments at different rotational speeds C_LIO_LIhydrogen shuttling was reduced through cathode displacement C_LIO_LICurrent densities of 198 {+/-} 11 A m-3 and H2-production rates of 0.99 {+/-} 0.03 L LR-1 d-1 C_LIO_LIAnodic biofilm parameters were not significantly altered by cathode modification C_LI

bioengineering↗

bioRxiv2023

Oxic microbial electrosynthesis can be more energy efficient for biomass production than knallgas or photosynthesis based processes

Data on the efficiency and development of continuous processes are scarce in the emerging field of oxic microbial electrosynthesis (OMES). Therefore, the recently isolated knallgas bacterium Kyrpidia spormannii was observed in a bioelectrochemical flow cell setup to study biomass formation and energy efficiency of cathode dependent growth. The study revealed that a potential of -500 mV vs. the standard hydrogen electrode (SHE) caused differences in the structure of the biofilm developing on the cathode, but had almost no impact on biomass growth behavior compared to -375 mV vs. SHE. No growth was observed at 0 mV vs SHE. Coulombic efficiency (CE) was calculated for the cultivation at -500 mV vs. SHE. The process can be conducted with the same electron efficiency as traditional gas fermentation. The solar energy demand with 67.89 kWh kg-1 dry biomass is highly competitive to alternative and already established processes for converting (solar) energy to biomass. Additionally, with suggestions for a biomass harvesting method and subsequent recultivation, proof of principle for a continuously operable process was provided. The results pave the way for a new concept in carbon dioxide-based biotechnology. Significance statementTo mitigate global climate change, it is imperative to transition the human economy to a different resource foundation, moving away from fossil fuels and reducing atmospheric carbon dioxide levels. Biotechnological production based on CO2 necessitates a supply of energy and electrons. This study reveals that an oxic process, wherein bacteria are directly cultivated as a biofilm on the cathode surface of a bioelectrochemical system, can exhibit higher energy efficiency than plant-based systems or systems reliant on hydrogen generated through water electrolysis. This technology could be instrumental in establishing carbon dioxide and renewable energy as the foundation for feed, food, and platform chemical production.

bioengineering↗

bioRxiv2022

A scalable, Rotating Disc Bioelectrochemical Reactor (RDBER) suitable for the cultivation of both cathodic and anodic biofilms

This study discusses the construction and operation of a membrane-less bioelectrochemical reactor that employs rotating working electrodes with a surface area of up to 1 m2. As a proof-of-principle for an aerobic microbial electrosynthesis process, Kyrpidia spormannii was cultivated in the reactor. Optical coherence tomography was used to examine the spatial distribution of the cathodic biofilm. After 24 days 87% of the cathode surface was covered with biofilm that was characterized by a radial increase in its biovolume towards the circumcenter of the electrodes reaching up to 92.13 m3 m-2. To demonstrate the versatility of the system, we further operated the reactor as a microbial electrolysis cell employing a co-culture of Shewanella oneidensis and Geobacter sulfurreducens. Anodic current densities of up to 130 A cm-2 were measured during these batch experiments. This resulted in a maximum production rate of 0.43 liters of pure hydrogen per liter reactor volume and day. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=161 SRC="FIGDIR/small/507646v3_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@102fbecorg.highwire.dtl.DTLVardef@e96345org.highwire.dtl.DTLVardef@7476aaorg.highwire.dtl.DTLVardef@1ac358_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIConstruction of a 10 L membrane-less, pressurizable bioelectrochemical reactor C_LIO_LIRotating working electrodes with up to 1 m2 electrode surface C_LIO_LIElectroautotrophic cultivation and quantification of K. spormannii biofilms C_LIO_LIInitial cell density crucial for successful K. spormannii biofilm formation C_LIO_LIAnodic operation as MEC with Shewanella / Geobacter coculture C_LI

microbiology↗

bioRxiv2021

Extracellular riboflavin induces anaerobic biofilm formation in Shewanella oneidensis

Some microorganisms can respire with extracellular electron acceptors using an extended electron transport chain to the cell surface. These organisms apply flavin molecules as cofactors to facilitate one-electron transfer catalysed by the terminal reductases and as endogenous electron shuttles. In the model organism Shewanella oneidensis, riboflavin production and excretion triggers a specific biofilm formation response that is initiated at a specific threshold concentration, similar to canonical quorum sensing molecules. Riboflavin-mediated messaging is based on the overexpression of the gene encoding the putrescin decarboxylase speC which leads to posttranscriptional overproduction of proteins involved in biofilm formation. Using a model of growth-dependent riboflavin production under batch and biofilm growth conditions, the number of cells necessary to produce the threshold concentration per time was deduced. Furthermore, our results indicate that specific retention of riboflavin in the biofilm matrix leads to localized concentrations which by far exceed the necessary threshold value. ImportanceFerric iron is the fourth most abundant element of the earth crust. It occurs at neutral pH in the form insoluble iron minerals. The dissimilatory reduction of these minerals is an import part of global geological cycles and is catalyzed by microorganisms through extended respiratory chains to the cell surface. Shewanella oneidensis is one of the best understood model organisms for this kind of extracellular respiration. Flavins are important for the reduction of extracellular electron acceptors by S. oneidensis. since they have a function as (I) cofactors of the terminal reductases and (II) electron shuttles. In this study we reveal that flavin molecules are further employed as quorum sensing molecules. They are excreted by the organisms in a growth dependent manner and lead to anaerobic biofilm formation as a specific response at a certain threshold concentration. Although we know multiple examples of quorum sensing mechanisms, the use of riboflavin was so far not described and at least in S. oneidensis proceeds via a new regulatory routine that proceeds on the trancriptomic and posttranscriptomic level.

microbiology↗

bioRxiv2020

Using protein interaction networks to identify cancer dependencies from tumor genome data

Genes required for tumor proliferation and survival (dependencies) are challenging to predict from cancer genome data, but are of high therapeutic value. We developed an algorithm (network purifying selection [NPS]) that aggregates weak signals of purifying selection across a genes first order protein-protein interaction network. We applied NPS to 4,742 tumor genomes to show that a genes NPS score is predictive of whether it is a dependency and validated 58 NPS-predicted dependencies in six cancer cell lines. Importantly, we demonstrate that leveraging NPS predictions to execute targeted CRISPR screens is a powerful, highly cost-efficient approach for identifying and validating dependencies quickly, because it eliminates the substantial experimental overhead required for whole-genome screening.

cancer biology↗

bioRxiv2018

Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight novel adipocyte biology

To characterize latent components of genetic associations, we applied truncated singular value decomposition (DeGAs) to matrices of summary statistics derived from genome-wide association analyses across 2,138 phenotypes measured in 337,199 White British individuals in the UK Biobank study. We systematically identified key components of genetic associations and the contributions of variants, genes, and phenotypes to each component. As an illustration of the utility of the approach to inform downstream experiments, we report putative loss of function variants, rs114285050 (GPR151) and rs150090666 (PDE3B), that substantially contribute to obesity-related traits, and experimentally demonstrate the role of these genes in adipocyte biology. Our approach to dissect components of genetic associations across human phenotypes will accelerate biomedical hypothesis generation by providing insights on previously unexplored latent structures.

genetics↗

bioRxiv2018

Macrophages protect against loss of adipose tissue during cancer cachexia

Cancer cachexia represents a central obstacle in medical oncology as it is associated with poor therapy response and reduced overall survival. Systemic inflammation is considered to be a key driver of cancer cachexia, however, clinical studies with anti-inflammatory drugs failed to show a robust cachexia-inhibiting effect. To address this contradiction, we investigated the functional importance of innate immune cells for hepatocellular carcinoma (HCC)-associated cachexia. To this end, we used a transgenic HCC mouse model intercrossed with mice harboring a defect in myeloid cell-mediated inflammation. We identified robust cachexia in the HCC mouse model as evidenced by a marked loss of visceral fat and lean mass. Computed tomography-based analyses demonstrated that a subgroup of human HCC patients displays reduced visceral fat mass, complementing the murine data. While the myeloid cell-mediated inflammation defect resulted in reduced expression of pro-inflammatory cytokines in the serum of HCC-bearing mice, this unexpectedly did not translate into diminished, but rather enhanced cachexia-associated fat loss. Defective myeloid cell-mediated inflammation was associated with decreased macrophage abundance in visceral adipose tissue, suggesting a role for local macrophages in the regulation of cancer-induced fat loss. Taken together, myeloid cell-mediated inflammation displays a rather unexpected beneficial function in a murine HCC model. These results demonstrate that immune cells are capable of protecting the host against cancer-induced tissue wasting, adding a further layer of complexity to the pathogenesis of cachexia and providing a potential explanation for the contradictory results of clinical studies with anti-inflammatory drugs.

cancer biology↗

bioRxiv2017

Detecting cancer vulnerabilities through gene networks under purifying selection in 4,700 cancer genomes

Large-scale cancer sequencing studies have uncovered dozens of mutations critical to cancer initiation and progression. However, a significant proportion of genes linked to tumor propagation remain hidden, often due to noise in sequencing data confounding low frequency alterations. Further, genes in networks under purifying selection (NPS), or those that are mutated in cancers less frequently than would be expected by chance, may play crucial roles in sustaining cancers but have largely been overlooked. We describe here a statistical framework that identifies genes that have a first order protein interaction network significantly depleted for mutations, to elucidate key genetic contributors to cancers. Not reliant on and thus, unbiased by, the gene of interests mutation rate, our approach has identified 685 putative genes linked to cancer development. Comparative analysis indicates statistically significant enrichment of NPS genes in previously validated cancer vulnerability gene sets, while further identifying novel cancer-specific candidate gene targets. As more tumor genomes are sequenced, integrating systems level mutation data through this network approach should become increasingly useful in pinpointing gene targets for cancer diagnosis and treatment.

bioinformatics↗

bioRxiv2017

Machine-assisted cultivation and analysis of biofilms

Biofilms are the natural form of life of the majority of microorganisms. These multispecies consortia are intensively studied not only for their effects on health and environment but also because they have an enormous potential as tools for biotechnological processes. Further exploration and exploitation of these complex systems will benefit from technical solutions that enable integrated, machine-assisted cultivation and analysis. We here introduce a microfluidic platform, where readily available microfluidic chips are connected by automated liquid handling with analysis instrumentation, such as fluorescence detection, microscopy, chromatography and optical coherence tomography. The system is operable under oxic and anoxic conditions, allowing for different gases as feeding sources and offers high spatiotemporal resolution in the analysis of metabolites and biofilm composition. We demonstrate the platforms performance by monitoring the self-organized separation of mixed cultures along autonomously created gradients, the productivity of biofilms along the microfluidic channel and the enrichment of microbial nanoorganisms.

microbiology↗

bioRxiv2017

A unified web platform for network-based analyses of genomic data

Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to quantitatively compare the signal-to-noise ratio of different networks, the biology they describe, and to identify the optimal network to interpret a particular genetic dataset. Via GeNets users can train a machine-learning model (Quack) to make such comparisons; and they can execute, store, and share analyses of genetic and RNA sequencing datasets.

genomics↗

bioRxiv2017

Expanding discovery from cancer genomes by integrating protein network analyses with in vivo tumorigenesis assays

Approaches that integrate molecular network information and tumor genome data could complement gene-based statistical tests to identify likely new cancer genes, but are challenging to validate at scale and their predictive value remains unclear. We developed a robust statistic (NetSig) that integrates protein interaction networks and data from 4,742 tumor exomes and used it to accurately classify known driver genes in 60% of tested tumor types and to predict 62 new candidates. We designed a quantitative experimental framework to compare the in vivo tumorigenic potential of NetSig candidates, known oncogenes and random genes in mice showing that NetSig candidates induce tumors at rates comparable to known oncogenes and 10-fold higher than random genes. By reanalyzing nine tumor-inducing NetSig candidates in 242 patients with oncogene-negative lung adenocarcinomas, we find that two (AKT2 and TFDP2) are significantly amplified. Overall, we illustrate a scalable integrated computational and experimental workflow to expand discovery from cancer genomes.

cancer biology↗

bioRxiv2017

Heterogeneous Contribution of Microdeletions in the Development of Common Generalized and Focal epilepsies

BackgroundMicrodeletions are known to confer risk to epilepsy, particularly at genomic rearrangement \"hotspot\" loci. However, deciphering their role outside hotspots and risk assessment by epilepsy sub-type has not been conducted.\n\nMethodsWe assessed the burden, frequency and genomic content of rare, large microdeletions found in a previously published cohort of 1,366 patients with Genetic Generalized Epilepsy (GGE) plus two sets of additional unpublished genome-wide microdeletions found in 281 Rolandic Epilepsy (RE) and 807 Adult Focal Epilepsy (AFE) patients, totaling 2,454 cases. These microdeletion sets were assessed in a combined analysis and in sub-type specific approaches against 6,746 ethnically matched controls.\n\nResultsWhen hotspots are considered, we detected an enrichment of microdeletions in the combined epilepsy analysis (adjusted-P= 2.00x10-7; OR = 1.89; 95%-CI: 1.51-2.35), where the implicated microdeletions overlapped with rarely deleted genes and those involved in neurodevelopmental processes. Sub-type specific analyses showed that hotspot deletions in the GGE subgroup contribute most of the signal (adjusted-P = 1.22x10-12; OR = 7.45; 95%-CI = 4.20-11.97). Outside hotspot loci, microdeletions were enriched in the GGE cohort for neurodevelopmental genes (adjusted-P = 4.78x10-3; OR = 2.30; 95%-CI = 1.42-3.70), whereas no additional signal was observed for RE and AFE. Still, gene content analysis was able to identify known (NRXN1, RBFOX1 and PCDH7) and novel (LOC102723362) candidate genes affected in more than one epilepsy sub-type but not in controls.\n\nConclusionsOur results show a heterogeneous effect of recurrent and non-recurrent microdeletions as part of the genetic architecture of GGE and a minor to negligible contribution in the etiology of RE and AFE.

genetics↗