Biology subjects

Koch, F.

Publications and source records attributed to Koch, F..

13 recordsLinked to original sources

bioRxiv2026

Stabilising effect of modularity in antagonistic networks depends on intraguild interactions

Existing literature on ecological networks provides valuable insights into the structure-stability relation of antagonistic, mutualistic or competitive systems, but it remains unclear whether these insights also apply to networks that contain a mix of different interaction types. Here, we study the effect of modularity on stability in systems that contain not only antagonistic interactions between two guilds, but also competition, facilitation or even antagonism within each guild, inspired by Ghanaian tree-liana interaction networks. We represent these systems as structured community matrices with random interaction strengths, in which we vary both the modularity within the antagonistic subnetwork and the type of intraguild interactions. Using the eigenvalues of the community matrix to assess stability, we find that modularity in antagonistic interactions generally has a stabilising effect, in line with results on single-interaction type networks. We furthermore find that the magnitude of this effect is modulated by the type of intra-guild interaction under consideration and is largest when these interactions describe facilitation. We explain these findings via a shift in the balance between self-reinforcing and self-damping feedback loops. Our results highlight the need to study how patterns in inter- and intraguild interactions jointly affect ecosystem stability.

ecology↗

bioRxiv2025

Forecasting bryozoan assemblage dynamics under simulated climate change

The shallow Antarctic continental shelf experiences strong physical disturbances in the form of ice-scour which play a key role in maintaining biodiversity. Due to climate change, both the extent and duration of sea ice cover is expected to rapidly decline, leading to complex shifts in disturbance regimes with unknown impacts on successional dynamics and biodiversity in benthic communities. We introduce a simulation model to study the assemblage dynamics of Bryozoa, which are sessile, suspension feeding animals and key pioneers in the shallows. The model captures colonisation events, colony growth as well as intra- and interspecific overgrowth competition for space between colonies. Mortality due to predation is modelled as the removal of zooids within small areas of the model world. Using the model, we simulate various disturbance regimes, e.g. by varying the timing of ice-scour events, the length of the growing season and the spatial distribution of predation events. We find that the timing of ice-scour events throughout the growing season has only minor short-term effects on successional dynamics in bryozoan assemblages, while an extended growing season substantially accelerates succession in the long term. We furthermore find that relatively rare but large predation events lead to a slower recovery, whereas relatively frequent but small events result in a faster succession with higher overall abundances. These results highlight that in order to understand how benthic biodiversity will be impacted by climate change, it is necessary to consider the interplay between biotic interactions and complex changes in physical disturbance regimes. HighlightsO_LIWe use an individual-based model to simulate climate change impacts on bryozoan assemblages. C_LIO_LIWarming leads to complex shifts in timing and spatial distribution of disturbances. C_LIO_LISuccessional dynamics are affected by changes in growing season and predation events. C_LIO_LIInterplay of biotic interactions and physical disturbances drives benthic biodiversity. C_LI

ecology↗

bioRxiv2025

Targeted sex ratio distortion in the mouse

In animal breeding, female or male progeny is preferred depending on the use of the animals. Especially in livestock, offspring with undesired sex is of low economic value and often culled. Here we achieve targeted sex ratio distortion in the mouse, leveraging components of a selfish supergene, the t-haplotype. Utilizing its central element, the t-responder, we generate a highly "selfless" genetic element disabling transgenic sperm. When integrated on the X or Y chromosome it results in a high prevalence of non-transgenic offspring of the desired sex. Our strategy overcomes key limitations of existing strategies, including compromised animal health, reduced fertility, and fully transgenic breeding stocks, which might foster acceptance of its application to livestock. The efficacy of our approach marks a groundbreaking advancement in animal breeding. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=130 HEIGHT=200 SRC="FIGDIR/small/660540v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1b11374org.highwire.dtl.DTLVardef@742ec5org.highwire.dtl.DTLVardef@1aaafc0org.highwire.dtl.DTLVardef@f87dac_HPS_FORMAT_FIGEXP M_FIG C_FIG Transgene integration on X or Y chromosome affects the motility of transgenic sperm resulting in a strong sex-bias towards non-transgenic/wildtype offspring. Application to livestock can reduce unwanted progeny and transform farm animal breeding.

genetics↗

bioRxiv2025

Blastocoel fluid RNA predicts pregnancy outcome in assisted reproduction

Nearly one in eight couples are affected by infertility, with many relying on assisted reproductive technologies (ART) to conceive. However, selecting the highest-quality embryo in ART remains a major challenge, as current assessment methods are often subjective, or invasive, and lack precision. Here, we introduce a novel strategy that analyses embryo-derived polyadenylated RNA in blastocoel fluid to more accurately predict pregnancy outcomes. Elevated RNA levels were strongly associated with implantation failure, particularly in embryos from women over the age of 34. Our predictive model developed using our sample cohort, incorporating both RNA and maternal age, demonstrated exceptional performance, achieving 76% accuracy in the training set and 73% in independent validation in predicting implantation outcome-- highlighting a promising advancement in embryo selection and ART success.

molecular biology↗

bioRxiv2024

Skewness enables stabilising effect of hierarchy in complex competition networks

1Ecological networks tend to contain many weak and only few strong interactions. Furthermore, interaction strengths are often arranged or patterned in ways that enhance stability. However, little attention has been given to the relation between the "many weak and few strong links" distribution and the stabilising effect of patterning. Here, we focus on the stabilising effect of hierarchy in bryozoan competition networks, and demonstrate that it critically depends on a skewed distribution of interaction strengths. To this end, we first show that, in line with many other ecological networks, the empirically derived interaction strengths in competition networks were characterised by a high level of skewness, with many weak and few strong links. Then, we analysed the relationship between the interaction strength distributions, hierarchy and stability by comparing theoretical competition matrices with different distributions of interaction strengths. We found that the full stabilising effect of hierarchy only appeared when we used skewed interaction strengths produced by a gamma distribution, but not in matrices built with uniform or half-normal distributions. This has important methodological implications, since theoretical studies often assume normal or uniform distributions to study ecological stability, and therefore might overlook stabilising mechanisms. We conclude that since skewed interaction strengths are a common feature of ecological networks, they can be expected to play an important role in the relation between structure and stability in living systems.

ecology↗

bioRxiv2023

Genome-wide identification of notochord enhancers comprising the regulatory landscape of the Brachyury (T) locus in mouse

The node and notochord are important signaling centers organizing dorso-ventral patterning of cells arising from neuro-mesodermal progenitors forming the embryonic body anlage. Due to the scarcity of notochordal progenitors and notochord cells, a comprehensive identification of regulatory elements driving notochord-specific gene expression has been lacking. Here we have used ATAC-seq analysis of FACS-purified notochordal cells from TS12-13 mouse embryos to identify 8921 putative notochord enhancers. In addition, we established a new model for generating notochordal cells in culture, and found 3728 of these enhancers occupied by the essential notochordal regulators Brachyury (T) and/or Foxa2. We describe the regulatory landscape of the T locus comprising 10 putative enhancers occupied by these factors and confirmed the regulatory activity of 3 of these elements. Moreover, we characterized one new notochord enhancer, termed TNE2, in embryos. TNE2 complements the loss of TNE in the trunk notochord, and is essential for notochordal cell proliferation and differentiation in the tail. Our data demonstrate the essential role of Foxa2 in switching T expressing cells from a NMP/mesodermal trajectory to the notochordal fate. Summary statementCombining multi-omics assays of purified embryonic and in vitro generated cells we identified thousands of notochord enhancers comprising TNE2 essential for T expression and tail development of the mouse embryo.

developmental biology↗

bioRxiv2022

Protein secretion zones within the Gram-positive cell wall

Whereas the translocation of proteins across the cell membrane has been thoroughly investigated, it is still unclear how proteins cross the cell wall in Gram positive bacteria, which are widely used for industrial applications. We have studied secretion of -amylase AmyE within two different Bacillus strains. We show that a C-terminal fusion of AmyE with the fluorescent reporter mCherry is secreted via discrete patches with very low dynamics that are visible at many places within the lateral cell wall, for many minutes. Expression from a high copy number plasmid was required to be able to see these structures we term "secretion zones". Zones corresponded to visualized AmyE activity on the surface of cells, and frequently overlapped with SecA signals, but did not necessarily co-localize with the secretion ATPase. Single particle tracking showed much higher dynamics of SecA and of SecDF, involved in AmyE secretion, at the cell membrane than AmyE. These experiments suggest that SecA initially translocates AmyE molecules through the cell membrane, and then diffuses to a different translocon. Single molecule tracking of SecA show changes in distinct diffusion states of SecA, but suggest that AmyE overexpression does not overwhelm the system. Because secretion zones were only found during the transition to and within stationary phase, diffusion rather than passive transport based on cell wall growth from inside to outside, releases AmyE and thus probably secreted proteins in general. Our findings suggest active transport through the cell membrane and slow, passive transition through the cell wall in Gram positive bacteria.

microbiology↗

bioRxiv2022

A drop-on-demand bioprinting approach to spatially arrange multiple cell types and monitor their cell-cell interactions towards vascularization based on endothelial cells and mesenchymal stem cells

Spheroids, organoids, or highly-dense cell-laden droplets are often used as building blocks for bioprinting, but so far little is known about the spatio-temporal cellular interactions post printing. We present a drop-on-demand approach to study the biological interactions of such building blocks in micrometer dimensions. Droplets (containing approximately 700 cells in 10 nl) of multiple cell types are patterned in a 3D hydrogel matrix with a precision of less than 70 m. It is applied to investigate interactions of cell types relevant for vascularization approaches. We show that a gap of 200 m between droplets containing endothelial cells (HUVECs) and adipose-derived mesenchymal stem cells (ASCs) leads to decreased sprouting of HUVECs towards ASCs and increased growth from ASCs towards HUVECs. For mixed aggregates containing both cell types, cellular interconnections of ASCs with up to approximately 0.8 millimeter length and inhibition of HUVEC sprouting are observed. When ASCs are differentiated into smooth muscle cells (SMCs), HUVECs display decreased sprouting towards SMCs in separate aggregates, whereas no cellular interconnections or inhibition of HUVEC sprouting are detected for mixed aggregates. These findings demonstrate that this approach acts as a new tool to investigate cell-cell interactions of different cell types in 3D bioprinted constructs.

bioengineering↗

bioRxiv2022

dSeqSb: A systems biology approach to decipher dynamics of 1 host-pathogen interactions using temporal dual RNA-seq data

Infection triggers a dynamic cascade of reciprocal events between host and pathogen wherein the host activates complex mechanisms to recognise and kill pathogens while the pathogen adjusts its virulence and fitness to avoid eradication by the host. The interaction between the pathogen and the host results in large-scale changes in gene expression in both organisms. Dual RNA-seq, the simultaneous detection of host and pathogen transcripts, has become a leading approach to unravel complex molecular interactions between the host and the pathogen and is particularly informative for intracellular organisms. The amount of in vitro and in vivo dual RNA-seq data is rapidly growing which demands computational pipelines to effectively analyse such data. In particular, holistic, systems-level, and temporal analyses of dual RNA-seq data are essential to enable further insights into the host-pathogen transcriptional dynamics and potential interactions. Here, we developed an integrative network-driven bioinformatics pipeline, dRNASb, a systems biology-based computational pipeline to analyse temporal transcriptional clusters, incorporate molecular interaction networks (e.g., protein-protein interactions), identify topologically and functionally key transcripts in host and pathogen, and associate host and pathogen temporal transcriptome to decipher potential between-species interactions. The pipeline is applicable to various dual RNA-seq data from different species and experimental conditions. As a case study, we applied dRNASb to analyse temporal dual RNA-seq data of Salmonella-infected human cells, which enabled us to uncover genes contributing to the infection process and their potential functions and to identify potential host-pathogen interactions between host and pathogen genes. Overall, dRNASb has the potential to identify key genes involved in bacterial growth or host defence mechanisms for future uses as therapeutic targets.

microbiology↗

bioRxiv2021

Disentangling single-cell omics representation with a power spectral density-based feature extraction

Emerging single-cell technologies provide high-resolution measurements of distinct cellular modalities opening new avenues for generating detailed cellular atlases of many and diverse tissues. The high dimensionality, sparsity, and inaccuracy of single cell sequencing measurements, however, can obscure discriminatory information, mask cellular subtype variations and complicate downstream analyses which can limit our understanding of cell function and tissue heterogeneity. Here, we present a novel pre-processing method (scPSD) inspired by power spectral density analysis that enhances the accuracy for cell subtype separation from large-scale single-cell omics data. We comprehensively benchmarked our method on a wide range of single-cell RNA-sequencing datasets and showed that scPSD pre-processing, while being fast and scalable, significantly reduces data complexity, enhances cell-type separation, and enables rare cell identification. Additionally, we applied scPSD to transcriptomics and chromatin accessibility cell atlases and demonstrated its capacity to discriminate over 100 cell types across the whole organism and across different modalities of single-cell omics data.

bioinformatics↗

bioRxiv2020

Novel genetic variants associated with brain functional networks in 18,445 adults from the UK Biobank

This is the first study investigating the genetics of weighted functional brain network graph theory measures from 18,445 participants of the UK Biobank (44-80 years). The eighteen measures studied showed low heritability (mean h2SNP =0.12) and were highly genetically correlated. Genome-wide association studies for these measures observed 14 significant variants associated with strength of somatomotor and limbic networks. These intergenic variants were located near the PAX8 gene on chromosome 2. Gene-based analyses identified five significantly associated genes for five of the network measures, which have been implicated in sleep duration, neuronal differentiation/development, cancer, and susceptibility to neurodegenerative diseases. Genetic correlations with other traits were examined and significant correlations were observed with sleep measures and psychiatric symptoms. Further analysis found that somatomotor network strength was phenotypically associated with sleep duration and insomnia. Single nucleotide polymorphism (SNP) and gene level associations with functional network measures were identified, which may help uncover novel biological pathways relevant to human brain functional network integrity and diseases that affect it.

neuroscience↗

bioRxiv2020

Titan Mice are Unique Short-Lived Mammalian Model of Metabolic Syndrome and Aging

Suitable animal models are essential for translational research, especially in the case of complex, multifactorial conditions, such as obesity. The outbred mouse line Titan (DU6) results from the worlds longest selection experiment for high body mass and was previously described as a model for metabolic healthy (benign) obesity. The present study deeper characterized the geno- and phenotypes of this outbred mouse line and tested its suitability as an interventional obesity model. In contrast to previous findings, our data suggests that Titan mice are metabolically unhealthy obese and short-lived. Line-specific patterns of genetic invariability are in accordance with observed phenotypic traits. Titan mice show modifications in the liver transcriptome, proteome and epigenome that are linked to metabolic (dys)regulations. However, dietary intervention partially reversed the metabolic phenotype in Titan mice and significantly extended their life expectancy. Therefore, the Titan mouse line is a valuable resource for translational and interventional obesity research.

biochemistry↗

bioRxiv2020

Mouse embryonic stem cells self-organize into trunk-like structures with neural tube and somites

Post-implantation embryogenesis is a highly dynamic process comprising multiple lineage decisions and morphogenetic changes inaccessible to deep analysis in vivo. Mouse embryonic stem cells (mESCs) can form aggregates reflecting the post-occipital embryo (gastruloids), but lacking proper morphogenesis. Here we show that embedding of aggregates derived from mESCs in an extracellular matrix compound results in Trunk-Like-Structures (TLS) with a high level of organization comprising a neural tube and somites. Comparative single-cell RNA-seq analysis demonstrates that TLS execute gene-regulatory programs in an embryo-like order, and generate primordial germ cell like cells (PGCLCs). TLS lacking Tbx6 form ectopic neural tubes, mirroring the embryonic mutant phenotype. ESC-derived trunk-like structures thus constitute a novel powerful in vitro platform for investigating lineage decisions and morphogenetic processes shaping the post-implantation embryo. One sentence summaryA platform for generating trunk-like-structures with precursors of spinal cord, bone and muscle from stem cells in a dish

developmental biology↗