Biology subjects

Jansen, C.

Publications and source records attributed to Jansen, C..

9 recordsLinked to original sources

bioRxiv2026

Mucosal architecture, microbiota resilience and metabolic disruption reveal holobiont dynamics during bovine respiratory disease

The gut-airway axis is increasingly recognised as an important determinant of respiratory health in livestock. However, the interactions among respiratory infections, microbial communities, mucosal barrier function, and microbial metabolism that underpin this axis remain poorly understood. Here, we combined longitudinal immunological, mucosal, microbiological, and metabolic analyses to characterise host-microbiota interactions during antibiotic treatment and experimental bovine respiratory disease (BRD). We found that the bovine respiratory tract is organised as a hierarchically structured mucosal ecosystem, with compartment-specific mucin expression patterns associated with distinct microbial communities. Within this framework, increasing respiratory pathogen loads were associated with greater clinical severity, oxidative stress, acute inflammation, and targeted alterations in mucosal regulation and microbial composition, while serum amyloid A emerged as the host biomarker most closely reflecting infection intensity. Although infection altered host and microbial states, antimicrobial treatment represented the dominant ecological perturbation. Antibiotic exposure reshaped both respiratory and intestinal microbial communities, reducing diversity, increasing community drift, and driving coordinated ecological transitions across the gut-airway axis that exceeded the effects of infection alone. Importantly, these compositional changes were accompanied by profound reductions in acetate, propionate, butyrate, and valerate, identifying short-chain fatty acids as a major functional consequence of gut microbiota disruption. Integrative multi-omics analyses revealed that mucosal organisation, microbial diversity, microbial metabolism, and immune activity were embedded within a highly structured gut-airway network. Together, these findings support a holobiont view of BRD in which disease outcomes emerge not only from pathogen-host interactions but also from ecological disturbances that propagate across interconnected mucosal compartments. Notably, antimicrobial treatment affected ecosystem structure and function more than infection itself, highlighting potential trade-offs between pathogen control and microbiota stability. Preserving microbial resilience and its metabolic functions may therefore represent an important component of future strategies to improve respiratory health and disease resilience in cattle.

systems biology↗

bioRxiv2025

Computational analysis of therapeutic potential for simplified Piper. spp- derived medicinal mixtures in anxiety, sleep, pain and seizure.

Phytomedicines have played a vital role in traditional medical systems globally, particularly in providing culturally relevant and accessible healthcare solutions. Piper methysticum, known as Kava, is a traditional Pacific Island phytomedicine with clinically validated anxiolytic properties, primarily attributed to its Kavalactones. However, the biogeographically restricted distribution of Piper methysticum and the ecological and cultural concerns surrounding its widespread adoption highlight the need to explore alternative sources within the Piper genus. This study investigates whether other species within the Piper genus, used phytomedically in non-Pacific contexts, exhibit similar therapeutic efficacy for anxiety, stress, and related disorders including Post-Traumatic Stress Disorder (PTSD). We employed a computational approach utilizing a novel data platform of non-Western phytomedical pharmacopeias to analyze the secondary metabolomes of various Piper species. Network analysis and multidimensional data projections were used to compare the chemical composition and therapeutic indications of these species with those of Piper methysticum. Our findings suggest that while Kavalactones are predominantly unique to Piper methysticum, other Piper species also contain bioactive compounds associated with anxiolytic and stress-relieving effects. These results provide insight into the potential for culturally and biogeographically contextualized approaches to PTSD treatment, beyond the exclusive use of Kava, and lay the groundwork for future research into alternative phytomedicinal therapies within the Piper genus.

pharmacology and toxicology↗

bioRxiv2025

A pathway to next-generation mast cell stabilizers identified through the novel Phytomedical Analytics for Research Optimization at Scale data platform.

Mast cell stabilizers (MCS) have the potential to address unmet therapeutic need in allergy and inflammation management. MCS chronically suppress all arms of the pro-inflammatory mast cell response to stimulation (e.g., histamine, protease, lipid mediators, cytokines, chemokines). They may therefore outperform approaches such as H1, H2 and H4 inhibitors (antihistamines) which block only the acute histamine release by mast cells and leave the rest of the functional response untouched. Despite their potential, current MCS (e.g., cromolyn sodium, Tranilast, nedocromil) in clinical use are hindered by poor bioavailability, frequent dosing, long lags to onset of relief, and enigmatic mechanisms of action. MCS have their origins in phytomedicine: cromolyn sodium is the longest standing drug in the class and is a derivatized form of Khellin from Ammi visnaga, used as an anti-inflammatory. Other phytopharmacopeias may offer candidate next generation MCS (ngMCS) and in this study we hypothesized that a coupled pharmacoanalytic and in vitro pharmacology approach could be used to identify, prioritize and derisk additional candidate MCS from phytomedical sources for later pre-clinical and clinical evaluation. Here, we report a novel data analytics workflow starting with a newly developed phytopharmacopeia data platform with >3.5B linkage pathways (country [->] medical system [->] formulation [->] indication [->] ingredient organism [->] chemical component [->] other parameters), covering 22 M sq. miles of biogeography and historical and contemporary timeframes. Additional data layers include druggability indices, target and pathway analyses. The current study validates a subset of candidate phytomedical ngMCS using in silico workflow and in vitro pharmacology, and develops a new harmonic mean-based MCS score for further streamlining of the candidate prioritization process. This proof-of-concept study may have particular relevance for complex presentations such as Mast Cell Activation Syndrome (MCAS) where ngMCS may outperform current management approaches.

immunology↗

bioRxiv2025

Design and development of lysyl tRNA synthetase inhibitors, for the treatment of tuberculosis

There is currently a public health crisis due to the rise of multi-drug-resistant tuberculosis cases, as well as the rise in number of deaths from tuberculosis. To achieve the United Nations Sustainable Development Goal of ending the tuberculosis epidemic by 2030, new treatments are urgently required. We previously reported the discovery of 49, a pre-clinical candidate that acted through inhibition of the Mycobacterium tuberculosis lysyl-tRNA synthetase (LysRS). In this report, the full medicinal chemistry program is reviewed from the original hit through to the optimised lead. The work was guided by the first crystal structure of M. tuberculosis LysRS. The physicochemical and pharmacokinetic properties were optimised to afford compounds suitable for evaluation in mouse efficacy models of tuberculosis and with the potential for clinical development.

microbiology↗

bioRxiv2023

Cross-species regulatory landscapes and elements revealed by novel joint systematic integration of human and mouse blood cell epigenomes

Knowledge of locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using epigenetic features in one species, making comparisons difficult between species. In contrast, we conducted an interspecies study defining epigenetic states and identifying cCREs in blood cell types to generate regulatory maps that are comparable between species, using integrative modeling of eight epigenetic features jointly in human and mouse in our Validated Systematic Integration (VISION) Project. The resulting catalogs of cCREs are useful resources for further studies of gene regulation in blood cells, indicated by high overlap with known functional elements and strong enrichment for human genetic variants associated with blood cell phenotypes. The contribution of each epigenetic state in cCREs to gene regulation, inferred from a multivariate regression, was used to estimate epigenetic state Regulatory Potential (esRP) scores for each cCRE in each cell type, which were used to categorize dynamic changes in cCREs. Groups of cCREs displaying similar patterns of regulatory activity in human and mouse cell types, obtained by joint clustering on esRP scores, harbored distinctive transcription factor binding motifs that were similar between species. An interspecies comparison of cCREs revealed both conserved and species-specific patterns of epigenetic evolution. Finally, we showed that comparisons of the epigenetic landscape between species can reveal elements with similar roles in regulation, even in the absence of genomic sequence alignment.

genomics↗

bioRxiv2021

Systematic Phenotyping and Characterization of the 5xFAD mouse model of Alzheimer's Disease

Mouse models of human diseases are invaluable tools for studying pathogenic mechanisms and testing interventions and therapeutics. For disorders such as Alzheimers disease in which numerous models are being generated, a challenging first step is to identify the most appropriate model and age to effectively evaluate new therapeutic approaches. Here we conducted a detailed phenotypic characterization of the 5xFAD model on a congenic C57BL/6J strain background, across its lifespan - including a seldomly analyzed 18-month old time point to provide temporally correlated phenotyping of this model and a template for characterization of new models of LOAD as they are generated. This comprehensive analysis included quantification of plaque burden, A{beta} biochemical levels, and neuropathology, neurophysiological measurements and behavioral and cognitive assessments, and evaluation of microglia, astrocytes, and neurons. Analysis of transcriptional changes was conducted using bulk-tissue generated RNA-seq data from microdissected cortices and hippocampi as a function of aging, which can be explored at the UCI Mouse Explorer and AD Knowledge Portal. This deep-phenotyping pipeline identified novel aspects of age-related pathology in the 5xFAD model.

neuroscience↗

bioRxiv2021

Uncovering the Gene Regulatory Networks Underlying Macrophage Polarization Through Comparative Analysis of Bulk and Single-Cell Data

Gene regulatory networks (GRNs) provide a powerful framework for studying cellular differentiation. However, it is less clear how GRNs encode cellular responses to everyday microenvironmental cues. Macrophages can be polarized and potentially repolarized based on environmental signaling. In order to identify the GRNs that drive macrophage polarization and the heterogeneous single-cell subpopulations that are present in the process, we used a high-resolution time course of bulk and single-cell RNA-seq and ATAC-seq assays of HL-60-derived macrophages polarized towards M1 or M2 over 24 hours. We identified transient M1 and M2 markers, including the main transcription factors that underlie polarization, and subpopulations of naive, transitional, and terminally polarized macrophages. We built bulk and single-cell polarization GRNs to compare the recovered interactions and found that each technology recovered only a subset of known interactions. Our data provide a resource to study the GRN of cellular maturation in response to microenvironmental stimuli in a variety of contexts in homeostasis and disease.

genomics↗

bioRxiv2020

Uncovering the mesendoderm gene regulatory network through multi-omic data integration

Mesendodermal specification is one of the earliest events in embryogenesis, where cells first acquire distinct identities. Cell differentiation is a highly regulated process that involves the function of numerous transcription factors (TFs) and signaling molecules, which can be described with gene regulatory networks (GRNs). Cell differentiation GRNs are difficult to build because existing mechanistic methods are low-throughput, and high-throughput methods tend to be non-mechanistic. Additionally, integrating highly dimensional data comprised of more than two data types is challenging. Here, we use linked self-organizing maps to combine ChIP-seq/ATAC-seq with temporal, spatial and perturbation RNA-seq data from Xenopus tropicalis mesendoderm development to build a high resolution genome scale mechanistic GRN. We recovered both known and previously unsuspected TF-DNA/TF-TF interactions and validated through reporter assays. Our analysis provides new insights into transcriptional regulation of early cell fate decisions and provides a general approach to building GRNs using highly-dimensional multi-omic data sets. HighlightsO_LIBuilt a generally applicable pipeline to creating GRNs using highly-dimensional multi-omic data sets C_LIO_LIPredicted new TF-DNA/TF-TF interactions during mesendoderm development C_LIO_LIGenerate the first genome scale GRN for vertebrate mesendoderm and expanded the core mesendodermal developmental network with high fidelity C_LIO_LIDeveloped a resource to visualize hundreds of RNA-seq and ChIP-seq data using 2D SOM metaclusters. C_LI

genomics↗

bioRxiv2018

Building gene regulatory networks from single-cell ATAC-seq and RNA-seq using Linked Self-Organizing Maps

Rapid advances in single-cell assays have outpaced methods for analysis of those data types. Different single-cell assays show extensive variation in sensitivity and signal to noise levels. In particular, scATAC-seq generates extremely sparse and noisy datasets. Existing methods developed to analyze this data require cells amenable to pseudo-time analysis or require datasets with drastically different cell-types. We describe a novel approach using self-organizing maps (SOM) to link scATAC-seq and scRNA-seq data that overcomes these challenges and can generate draft regulatory networks. Our SOMatic package generates chromatin and gene expression SOMs separately and combines them using a linking function. We applied SOMatic on a mouse pre-B cell differentiation time-course using controlled Ikaros over-expression to recover gene ontology enrichments, identify motifs in genomic regions showing similar single-cell profiles, and generate a gene regulatory network that both recovers known interactions and predicts new Ikaros targets during the differentiation process. The ability of linked SOMs to detect emergent properties from multiple types of highly-dimensional genomic data with very different signal properties opens new avenues for integrative analysis of single-cells.

genomics↗