Biology subjects

Arnold, C.

Publications and source records attributed to Arnold, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Alternative management strategy reshapes litter microbiome dynamics in a commercial broiler rearing system

Pre-harvest litter management is a key determinant of broiler production conditions, influencing NH generation, pathogen exposure, nutrient retention, and microbial reservoirs that accumulate across production cycles. Conventional chemical and physical management strategies can support flock health, but their effects on pathogen-associated bacterial populations are often transient and may not account for the microbial interactions that govern persistence, exclusion, and community succession. Here, we evaluated an alternative litter management strategy combining IndigoLT(R) pre-/postbiotic with reduced-rate NaHSO across two broiler growouts, with litter sampled at the end of each flock to determine impact on prokaryotic microbiome structure, physicochemistry, and Enterococcus abundance. Alternative management influenced observed richness, phylogenetic diversity, community composition, and co-occurrence network structure while reducing the relative abundance of Enterococcus, including E. cecorum and E. hirae. Digital PCR corroborated sequencing-based Enterococcus abundance patterns, although 16S-based treatment effects were not always reflected as lower absolute copy number at terminal sampling, consistent with reduced proportional dominance rather than sustained absolute suppression. Complementary biofilm- and growth-inhibition assays performed with IndigoLT(R) demonstrated context-dependent antibiofilm and bacteriostatic activity against reference and poultry-derived Enterococcus isolates, with stronger responses for E. cecorum than E. hirae and bactericidal-level reductions in viable recovery at higher exposure levels. These findings demonstrate that biologic-based litter management can alter microbiome structure and pathogen-associated taxa under commercial production conditions, providing a basis for microbiome-informed amendment strategies aimed at reducing pathogen load and supporting broiler health.

microbiology↗

bioRxiv2025

Effect of Large Language Models on P300 Speller Performance with Cross-Subject Training

Amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative disease, severely impairs communication, requiring assistive technologies that restore interaction. The P300 speller brain-computer interface (BCI) enables communication by translating EEG responses into text; however, its practical adoption is limited by slow typing speed and the need for subject-specific calibration. Recent work has demonstrated that large language models (LLMs), such as GPT-2, can significantly improve the performance of the P300 speller by predicting words. However, it remains unclear whether these gains are model-specific or represent a broader trend across language models. Furthermore, the fundamental performance limits of LLM-assisted P300 spellers have not been systematically characterized within a unified decoding framework. In this study, we address these gaps through a systematic multi-model theoretical analysis framework. We evaluate a wide range of language models and introduce an idealized LLM to establish upper bounds on achievable performance. In addition, we incorporate cross-subject classifier training to reduce calibration requirements and assess generalization across subjects. Using extensive simulations on EEG data from 78 subjects, we demonstrate that the evaluated models consistently achieve substantial improvements in typing speed, with gains of up to [~]40% (across-subject training) and [~]75% (within-subject training) over conventional approaches. More importantly, we show that multiple models, despite architectural differences, operate within 5% of the theoretical performance bound, indicating diminishing returns from further model scaling. These improvements generalize across both within-subject and across-subject classifiers. Our results suggest that LLM-assisted P300 spellers are approaching their fundamental performance limits within the considered decoding framework, shifting the primary bottleneck from language modeling to neural signal decoding. This work provides both a practical framework for improving BCI communication and a theoretical perspective on its achievable limits.

neuroscience↗

bioRxiv2025

geneRNIB: a living benchmark for gene regulatory network inference

Gene regulatory networks (GRNs) underpin cellular identity and function, playing a key role in health and disease. GRN inference has received substantial attention, motivating systematic benchmarking. Despite various benchmarking efforts, existing studies remain limited in the number of methods, datasets, and metrics, fail to capture the context-specific nature of regulatory interactions across biological conditions, and are constrained by the absence of a reliable ground truth. Here, we introduce geneRNIB, a comprehensive GRN inference benchmarking framework built on three key principles: continuous integration, context-specific evaluation, and holistic assessment in the absence of a true reference network. geneRNIB enables the seamless incorporation of new algorithms, datasets, and evaluation metrics to reflect ongoing developments. In the current version, we systematically integrated and assessed 12 GRN inference methods, spanning single- and multiomics approaches across 11 datasets including thousands of perturbation scenarios. We introduced complementary metrics specifically designed to assess context-specific inference. Our findings indicate that simple models with fewer assumptions often outperform more complex pipelines across several perturbation-informed and predictive metrics. Notably, gene expression-based algorithms yielded better results than more advanced multimodal approaches. In addition, we identify several potential factors that influence the performance of GRN inference and offer actionable guidelines for the future development of the method. By addressing these critical limitations in existing benchmarks, geneRNIB advances GRN inference research and fosters progress toward personalized medicine.

bioinformatics↗

bioRxiv2024

Biomimetic Virus-Like Particles to control cell functions

Biomimetic cues from the extracellular matrix (ECM) are essential for optimizing cell microenvironments and biomaterials. While native ECM proteins or synthetic peptides offer potential solutions, challenges such as production cost, solubility, and conformational stability limit their use. Here, we present the development of virus-like particles (VLPs) derived from the AP205 RNA phage displaying peptides from key ECM proteins and evaluate their biological activity in a variety of assays. We show that our engineered VLPs can effectively stimulate cell adhesion, migration, proliferation and differentiation. By comparing focal adhesions formed by RGD VLPs with their parent protein, fibronectin, we elucidate both similarities and differences in cell interactions. In addition, we construct heterodimeric particles co-expressing RGD with differentiation peptides and demonstrate retention of bioactivity in a multi-peptide context. This study establishes AP205 VLPs as versatile nanoscale platforms capable of tuning cell functions, with promising applications in nanomedicine and biomaterials. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/612851v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@191b2c2org.highwire.dtl.DTLVardef@6edf5corg.highwire.dtl.DTLVardef@10a134aorg.highwire.dtl.DTLVardef@7864ef_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG

bioengineering↗

bioRxiv2024

Mechanistic basis of gene-specific transcription regulation by the Integrator complex

The Integrator complex (INT) regulates gene expression via premature transcription termination of RNA polymerase II (RNAP2) at promoter-proximal pausing sites. This attenuation of transcription is required for cellular response to external stimuli, cell differentiation and neurodevelopment. How gene-specific regulation is achieved by INT in an inducible manner remains unclear. Here, we identify two sites on INT subunits 13/14 that serve as direct binding hubs for diverse sets of sequence-specific transcription factors (TFs) and other transcription effector complexes. The TFs co-localize with INT genome-wide, increase INT abundance on target genes and co-regulate inducible transcriptional programs. Consistently, disruption of INT-TF contacts impairs sensory cilia formation in response to glucose starvation. Structural analysis places INTs TF binding hubs upstream of the transcription bubble when attached to paused RNAP2, consistent with simultaneous TF-promoter association. Our data establish TF-mediated recruitment of INT to promoters as a widespread mechanism for targeted and inducible transcription attenuation.

molecular biology↗

bioRxiv2024

Integration of genetic and epigenetic data pinpoints autoimmune specific remodelling of enhancer landscape in CD4+ T cells

CD4+ T cells play a crucial role in adaptive immune responses and have been implicated in the pathogenesis of autoimmune diseases (ADs). Despite numerous studies, the molecular mechanisms underlying T cell dysregulation in ADs remain incompletely understood. Here, we used transcriptomic and epigenomic data from CD4+ T cells of healthy donors and patients with systemic lupus erythematosus (SLE), psoriasis, juvenile idiopathic arthritis (JIA), and Graves disease to investigate the role of enhancers in AD pathogenesis. By generating enhancer-based gene regulatory networks (eGRNs), we identified disease-specific dysregulated pathways and potential downstream target genes of enhancers harbouring AD-associated single-nucleotide polymorphisms, which we also validated using CRISPRi in primary CD4+ T cells. Our results suggest that alterations in the regulatory landscapes of CD4+ T cells, including enhancers, contribute to the development of ADs and provide a basis for developing new therapeutic approaches.

genomics↗

bioRxiv2023

Scalable ultra-high-throughput single-cell chromatin and RNA sequencing reveals gene regulatory dynamics linking macrophage polarization to autoimmune disease

Enhancers and transcription factors (TFs) are crucial in regulating cellular processes, including disease-associated cell states. Current multiomic technologies to study these elements in gene regulatory mechanisms lack multiplexing capability and scalability. Here, we present SUM-seq, a cost-effective, scalable Single-cell Ultra-high-throughput Multiomic sequencing method for co-assaying chromatin accessibility and gene expression in single nuclei. SUM-seq enables profiling hundreds of samples at the million cell scale and outperforms current high-throughput single-cell methods. We applied SUM-seq to dissect the gene regulatory mechanisms governing macrophage polarization and explored their link to traits from genome-wide association studies (GWAS). Our analyses confirmed known TFs orchestrating M1 and M2 macrophage programs, unveiled key regulators, and demonstrated extensive enhancer rewiring. Integration with GWAS data further pinpointed the impact of specific TFs on a set of immune traits. Notably, inferred enhancers regulated by the STAT1/STAT2/IRF9 (ISGF3) complex were enriched for genetic variants associated with Crohns disease, ulcerative colitis and multiple sclerosis, and their target genes included known drug targets. This highlights the potential of SUM-seq for dissecting molecular disease mechanisms. SUM-seq offers a cost-effective, scalable solution for ultra-high-throughput single-cell multiomic sequencing, excelling in unraveling complex gene regulatory networks in cell differentiation, responses to perturbations, and disease studies.

genomics↗

bioRxiv2023

Multi-variate statistical and machine learning reveals the interplay between sex and age in antibody responses to de novo SARS-CoV-2 infection and vaccination

Prevention of negative COVID19 infection outcomes and infection/vaccine-acquired immunity is associated with the quality of antibody responses, whose variance by age and sex are poorly understood. Integrated, network approaches, identified sex and age effects in antibody responses and neutralization potential of de novo infection and vaccination throughout the Covid-19 pandemic. Cluster analysis found neutralization values followed SARS-CoV-2 specific receptor binding RIgG, spike SIgG and S and RIgA levels based on COVID19 status. Stochastic behavior tests and other analytical methods revealed sex differences only in persons <40y.o. Serum IgA antibody titers correlated with neutralization only in females 40-60y.o. Network analysis found males could improve IgA responses after vaccination dose 2, unlike >60y.o. females. Complex correlation analyses found vaccination induced less antibody isotype switching and neutralization in older persons, especially in females. Sex dependent antibody & neutralization behavior decayed fastest in older males and with vaccination. Such sex and age characterization by machine learning can direct studies integrating cell mediated responses to define yet elusive correlates of protection and inform age and sex precision-focused vaccine design.

immunology↗

bioRxiv2022

Body-plan reorganization in a sponge correlates with microbiome change

Mounting evidence suggests that animals and their associated bacteria interact via intricate molecular mechanisms, and it is hypothesized that disturbances to the microbiome can influence animal development. Sponges diverged from other animals more than 750 MYA and represent one of the earliest branching animal phyla that exhibit symbiotic relationships with diverse bacteria. Over 41 microbial phyla have been found in association with sponges, forming a holobiont that is integral to aquatic ecosystems worldwide. Sponge-associated microbes contain an enriched set of proteins bearing eukaryotic-like domains, and their metabolism supports the host with nutrients. This indicates strong physiological interconnections in the holobiont, which are thought to be modulated by sponge immunity and pattern-recognition proteins. Despite the hypothesized tight physiological integration and ancient origin of the sponge holobiont, the effect of changes in the symbiotic community on the sponge metabolism and morphogenesis remains poorly understood. Here, we show that the loss of a key microbial sponge symbiont correlates with a stark body plan reorganization of the sponge host. This reorganization is coupled with broad transcriptomic changes and includes the modulation of signaling pathways known to be involved in morphogenesis and innate immune response in sponges and other animals. This study provides a combined genetic, physiological, and morphological assessment of the effect of changes in the microbiome on sponge post-embryonic development and homeostasis. The drastic microbiome reorganization and the correlated response observed in the sponge host provide evidence for a coupling between sponge transcriptomic state and the state of its microbiome. Our results suggest that sponges use molecular mechanisms to respond to changes in their microbiome and that the ability to sense and respond to microbiome perturbations has deep evolutionary origins among animals.

genomics↗

bioRxiv2021

GRaNIE and GRaNPA: Inference and evaluation of enhancer-mediated gene regulatory networks applied to study macrophages

Among the biggest challenges in the post-GWAS (genome-wide association studies) era is the interpretation of disease-associated genetic variants in non-coding genomic regions. Enhancers have emerged as key players in mediating the effect of genetic variants on complex traits and diseases. Their activity is regulated by a combination of transcription factors (TFs), epigenetic changes and genetic variants. Several approaches exist to link enhancers to their target genes, and others that infer TF-gene connections. However, we currently lack a framework that systematically integrates enhancers into TF-gene regulatory networks. Furthermore, we lack an unbiased way of assessing whether inferred regulatory interactions are biologically meaningful. Here we present two methods, implemented as user-friendly R packages: GRaNIE (Gene Regulatory Network Inference including Enhancers) for building enhancer-based gene regulatory networks (eGRNs) and GRaNPA (Gene Regulatory Network Performance Analysis) for evaluating GRNs. GRaNIE jointly infers TF-enhancer, enhancer-gene and TF-gene interactions by integrating open chromatin data such as ATAC-Seq or H3K27ac with RNA-seq across a set of samples (e.g. individuals), and optionally also Hi-C data. GRaNPA is a general framework for evaluating the biological relevance of TF-gene GRNs by assessing their performance for predicting cell-type specific differential expression. We demonstrate the power of our tool-suite by investigating gene regulatory mechanisms in macrophages that underlie their response to infection and cancer, their involvement in common genetic diseases including autoimmune diseases, and identify the TF PURA as putative regulator of pro-inflammatory macrophage polarisation. Availability- GRaNIE: https://bioconductor.org/packages/release/bioc/html/GRaNIE.html - GRaNPA: https://git.embl.de/grp-zaugg/GRaNPA Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

genomics↗

bioRxiv2021

Identifying a novel role for the master regulator Tal1 in the Endothelial to Hematopoietic Transition

Recent progress in the generation of bona-fide Hematopoietic Stem and Progenitor Cells (HSPCs) in vitro and ex vivo has been built on the knowledge of developmental hematopoiesis, underscoring the importance of understanding in detail this developmental process. Here, we sought to elucidate the function of the hematopoietic regulators Tal1, Lmo2 and Lyl1 in the Endothelial to Hematopoietic Transition (EHT), the process through which HSPCs are generated from endothelial precursors during embryogenesis. We used a mouse embryonic-stem cell (mESC)-based differentiation system to model hematopoietic development, and combined gain-of-function experiments in sorted vascular smooth muscle cells (VSM) with multi-omics to obtain mechanistic insights into the mode of action of Tal1, Lmo2 and Lyl1. We found that these factors promote the silencing of the VSM transcriptional program and the activation of the hematopoietic one. Through this approach and the use of a Tet-on system to control the expression of Tal1 during hematopoietic specification from mESCs, we discovered that its expression in endothelial cells is crucial for the EHT to occur.

developmental biology↗

bioRxiv2021

Enhancer-priming in ageing human bone marrow mesenchymal stromal cells contributes to immune traits

Bone marrow mesenchymal stromal cells (BMSCs) can differentiate into adipocytes and osteoblasts, and are important regulators of the haematopoietic system. Ageing associates with an increased ratio of bone marrow adipocytes to osteoblasts and immune dysregulation. Here, we carried out an integrative multiomics analysis of ATAC-Seq, RNA-Seq and proteomics data from primary human BMSCs in a healthy cohort age between 20 - 60. We identified age-sensitive elements uniquely affecting each molecular level where transcription is mostly spared, and characterised the underlying biological pathways, revealing the interplay of age-related gene expression mechanism changes spanning multiple gene regulatory layers. Through data integration with enhancer-mediated gene regulatory network analysis, we discovered that enhancers and transcription factors influence cell differentiation potential in the ageing BMSCs. By combining our results with genome-wide association study data, we found that age-specific changes could contribute to common traits related to BMSC-derived tissues such as bone and adipose tissue, and to immune-related traits on a systemic level such as asthma. We demonstrate here that a multiomics approach is crucial for unravelling complex information, providing new insights on how ageing contributes to bone marrow- and immune-related disorders.

systems biology↗

bioRxiv2021

Pathological LSD1 mutations cause HDAC-mediated aberrant gene repression during early cell differentiation

Lysine-specific demethylase 1 (LSD1/KDM1A) demethylates both histone and non-histone substrates, recruits repressive chromatin complexes, and is increased in cancers. De novo LSD1 mutations impairing protein function lead to a rare developmental disorder, but the molecular details of the pathology remains unclear. Using patient-derived fibroblasts, reprogrammed pluripotent stem cells, and differentiated cells, we found over 4000 differentially expressed genes and 68 transcription factors (TFs) whose motif accessibilities changed upon LSD1 mutation. An enhancer-mediated gene regulatory network approach identified transcriptional repressors with impaired activity in fibroblast and stem cells, leading to erroneous activation of their target genes. We also revealed overall decreases in TF target gene expression during early lineage differentiation of LSD1 mutant stem cells, likely caused by increased activity of repressive histone deacetylases (HDACs), co-factors of LSD1. Indeed, an HDACs inhibitor restored changes in gene expression including downregulation phenotype. Our findings characterize the molecular pathogenesis of LSD1 mutations and suggest potential therapeutic strategies for the developmental disorder and cancers caused by LSD1 dysregulations.

genomics↗

bioRxiv2021

Hox genes regulate asexual reproductive behavior and tissue segmentation in adult animals

Hox genes are highly conserved transcription factors renowned for their roles in the segmental patterning of the embryonic anterior-posterior (A/P) axis1. Emerging evidence for Hox gene expression and function in postnatally derived structures has fueled interest in their additional roles beyond embryogenesis2,3. We report novel functions for Hox genes in A/P adult tissue segmentation and transverse fission behavior underlying asexual reproduction in the planarian flatworm, Schmidtea mediterranea. Silencing of each of the planarian Hox family members identified 5 Hox genes required for asexual reproduction. Among these, silencing of hox3 genes resulted in supernumerary segments, while silencing of post2b eliminated segmentation altogether. The opposing roles of hox3 and post2b in segmentation are paralleled in their respective regulation of fission behavior. Silencing of hox3 increased the frequency of fission behavior initiation, while silencing of post2b eliminated fission behavior entirely. Furthermore, we identified a network of downstream effector genes mediating Hox gene regulation of asexual reproduction, thereby providing insight into their respective mechanisms of action. Our study establishes postembryonic roles for Hox genes in regulating the emergence of tissue segmentation and specific behaviors associated with asexual reproduction in adult animals.

developmental biology↗

bioRxiv2020

Image-based patch selection for deep learning to improve automated Gleason grading in histopathological slides

Automated Gleason grading can be a valuable tool for physicians when assessing risk and planning treatment for prostate cancer patients. Semantic segmentation provides pixel-wise Gleason predictions across an entire slide, which can be more informative than classification of pre-selected homogeneous regions. Deep learning methods can automatically learn visual semantics to accomplish this task, but training models on whole slides is impractical due to large image sizes and scarcity of fully annotated data. Patch-based methods can alleviate these problems, and have been shown to produce significant results in histopathology segmentation. However, the irregular contours of biopsies on slides makes performance highly dependent on patch selection. In the traditional grid-based strategy, many patches lie on biopsy boundaries, reducing segmentation accuracy due to a reduction in contextual information. In this paper, we propose an automatic patch selection process based on image features. This algorithm segments the biopsy and aligns patches based on the tissue contour to maximize the amount of contextual information in each patch. This method was used to generate patches for a fully convolutional network to segment high grade, low grade, and benign tissue from a set of 59 histopathological slides, and results were compared against manual physician labels. We show that using our image-based patch selection algorithm results in a significant improvement in segmentation accuracy over the traditional grid-based approach. Our results suggest that informed patch selection can be a valuable addition to an automated histopathological analysis pipeline.

bioengineering↗

bioRxiv2020

Refactoring the formicamycin biosynthetic gene cluster to make high-level producing strains and new molecules

The formicamycins are promising antibiotics with potent activity against Gram-positive pathogens including VRE and MRSA and display a high barrier to selection of resistant isolates. They were first identified in Streptomyces formicae KY5, which produces the formicamycins at low levels on solid agar but not in liquid culture, thus hindering further investigation of these promising antibacterial compounds. We hypothesised that by understanding the organisation and regulation of the for biosynthetic gene cluster, we could rationally refactor the cluster to increase production levels. Here we report that the for biosynthetic gene cluster consists of 24 genes expressed on nine transcripts. Seven of these transcripts, including those containing all the major biosynthetic genes, are repressed by the MarR-regulator ForJ which also controls the expression of the ForGF two-component system that initiates biosynthesis. A third cluster-situated regulator, ForZ, autoregulates and controls production of the putative MFS transporter ForAA. Consistent with these findings, deletion of forJ increased formicamycin biosynthesis 5-fold, while over-expression of forGF in the {Delta}forJ background increased production 10-fold compared to the wild-type. De-repression by deleting forJ also switched on biosynthesis in liquid-culture and induced the production of two novel formicamycin congeners. By combining mutations in regulatory and biosynthetic genes, six new biosynthetic precursors with antibacterial activity were also isolated. This work demonstrates the power of synthetic biology for the rational redesign of antibiotic biosynthetic gene clusters both to engineer strains suitable for fermentation in large scale bioreactors and to generate new molecules. ImportanceAntimicrobial resistance is a growing threat as existing antibiotics become increasingly ineffective against drug resistant pathogens. Here we determine the transcriptional organisation and regulation of the gene cluster encoding biosynthesis of the formicamycins, promising new antibiotics with activity against drug resistant bacteria. By exploiting this knowledge, we construct stable mutant strains which over-produce these molecules in both liquid and solid culture whilst also making some new compound variants. This will facilitate large scale purification of these molecules for further study including in vivo experiments and the elucidation of their mechanism of action. Our work demonstrates that understanding the regulation of natural product biosynthetic pathways can enable rational improvement of the producing strains.

microbiology↗

bioRxiv2020

Multiplex single-molecule kinetics of nanopore-coupled polymerases

DNA polymerases have revolutionized the biotechnology field due to their ability to precisely replicate stored genetic information. Screening variants of these enzymes for unique properties gives the opportunity to identify polymerases with novel features. We have previously developed a single-molecule DNA sequencing platform by coupling a DNA polymerase to a -hemolysin pore on a nanopore array. Here, we use this approach to demonstrate a single-molecule method that enables rapid screening of polymerase variants in a multiplex manner. In this approach, barcoded DNA strands are complexed with polymerase variants and serve as templates for nanopore sequencing. Nanopore sequencing of the barcoded DNA reveals both the barcode identity and kinetic properties of the polymerase variant associated with the cognate barcode, allowing for multiplexed investigation of many polymerase variants in parallel on a single nanopore array. Further, we develop a robust classification algorithm that discriminates kinetic characteristics of the different polymerase mutants. As a proof of concept, we demonstrate the utility of our approach by screening a library of ~100 polymerases to identify variants for potential applications of biotechnological interest. We anticipate our screening method to be broadly useful for applications that require polymerases with unique or altered physical properties.

synthetic biology↗

bioRxiv2019

Can individual and integrated water, sanitation, and handwashing interventions reduce fecal contamination in the household environment? Evidence from the WASH Benefits cluster-randomized trial in rural Kenya

Combined water, sanitation, and handwashing (WSH) interventions have the potential to reduce fecal pathogens along more transmission pathways than single interventions alone. We measured Escherichia coli levels in 3909 drinking water samples, 2691 child hand rinses, and 2422 toy ball rinses collected from households enrolled in a two-year cluster-randomized controlled trial evaluating single and combined WSH interventions. Water treatment alone reduced E. coli in drinking water, while a combined WSH intervention improved water quality by the same magnitude but did not affect levels of fecal indicator bacteria on child hands or toy balls. The failure of the WSH interventions to reduce E. coli along important child exposure pathways is consistent with the lack of a protective effect from the interventions on child diarrhea or child growth during the trial. Our results have important implications for WSH program design; the sanitation and handwashing interventions implemented in this trial should not be expected to reduce child exposure to fecal contamination in other similar settings.

microbiology↗