Biology subjects

Hautefort, I.

Publications and source records attributed to Hautefort, I..

7 recordsLinked to original sources

bioRxiv2026

Enriching the Human Stool Microeukaryotes for Shotgun Sequencing

The human gut microbiome harbours a diverse community of microeukaryotes, predominantly fungi, which may potentially play important roles in gut ecology and homeostasis. Despite their potential, the study of gut microeukaryotes has been hampered by the limited sensitivity of standard sequencing approaches, which struggle to capture DNA from low-abundance microorganisms against the overwhelming background of bacterial biomass. To address this, we developed a method to selectively enrich for microeukaryotic cells in human faecal samples by depleting bacterial cells prior to metagenomic sequencing. Through systematic comparison and optimisation at each processing step, we established a robust standard operating procedure (SOP) for microeukaryotic cell enrichment. By benchmarking this SOP across eight human faecal samples with three technical replicates each, we showed that it consistently increased microeukaryote representation in metagenomic libraries, greater microeukaryotic taxonomic diversity, and a reduced proportion of unclassified taxa. Together, these improvements enabled substantially deeper characterisation of the microeukaryotic fraction of the human gut microbiome.

microbiology↗

bioRxiv2024

Decoding Cytokine Networks in Ulcerative Colitis to Identify Pathogenic Mechanisms and Therapeutic Targets

Ulcerative colitis (UC) is a chronic inflammatory disorder of the gastrointestinal tract characterised by dysregulated cytokine signalling. Despite the advent of advanced therapies targeting cytokine signalling, treatment outcomes for UC patients remain suboptimal. Hence, there is a pressing need to better understand the complexity of cytokine regulation in UC by comprehensively mapping the interconnected cytokine signalling networks that are perturbed in UC patients. To address this, we undertook systems immunology modelling of single-cell transcriptomics data from colonic biopsies of treatment-naive and treatment-exposed UC patients to build complex cytokine signalling networks underpinned by putative cytokine-cytokine interactions. The generated cytokine networks effectively captured known physiologically relevant cytokine-cytokine interactions which we recapitulated in vitro in UC patient-derived colonic epithelial organoids. These networks revealed new aspects of UC pathogenesis, including a cytokine subnetwork that is unique to treatment-naive UC patients, the identification of highly rewired cytokines across UC disease states (IL22, TL1A, IL23A, and OSM), JAK paralogue-specific cytokine-cytokine interactions, and the positioning of TL1A as an important upstream regulator of TNF and IL23A as well as an attractive therapeutic target. Overall, these findings open up several avenues for guiding future cytokine-targeting therapeutic approaches in UC, and the presented methodology can be readily applied to gain similar insights into other immune-mediated inflammatory diseases (IMIDs). One Sentence SummaryA systems immunology map of cytokine interaction networks in ulcerative colitis reveals novel insights into disease pathogenesis, with potential to guide future cytokine-targeting therapeutic strategies.

systems biology↗

bioRxiv2021

Multi-layered networks of SalmoNet2 enable strain comparisons of the Salmonella genus on a molecular level

Serovars of the genus Salmonella primarily evolved as gastrointestinal pathogens in a wide range of hosts. Some serotypes later evolved further, adopting a more invasive lifestyle in a narrower host range associated with systemic infections. A system-level knowledge of these pathogens has the potential to identify the complex adaptations associated with the evolution of serovars with distinct pathogenicity, host range and risk to human health. This promises to aid the design of interventions and serve as a knowledge base in the Salmonella research community. Here we present SalmoNet2, a major update to SalmoNet, the first multi-layered interaction resource for Salmonella strains, containing protein-protein, transcriptional regulatory and enzyme enzyme interactions. The new version extends the number of Salmonella genomes from 11 to 20, including strains such as S. Typhimurium D23580, an epidemic multidrug-resistant strain leading to invasive non-typhoidal Salmonella Disease (iNTS), and a strain from Salmonella bongori, another species in the Salmonella genus. The database now uses strain specific metabolic models instead of a generalised model to highlight differences between strains. This has increased the coverage of high-quality protein-protein interactions, and enhances interoperability with other computational resources by adopting standardised formats. The resource website has been updated with tutorials to help researchers analyse their Salmonella data using molecular interaction networks from SalmoNet2. SalmoNet2 is accessible at http://salmonet.org/. ImportanceMulti-layered network databases collate information from multiple sources, and are powerful both as a knowledge base and platform for analysis. Here we present SalmoNet2, an integrated network resource of 20 Salmonella strains, containing protein-protein, transcriptional regulatory, and metabolic interactions. Key improvements to the update include expanding the number of strains, strain-specific metabolic networks, an increase in high quality protein-protein interactions, community standard computational formats to help interoperability, and online tutorials to help users analyse their data using SalmoNet2.

systems biology↗

bioRxiv2021

CytokineLink: a cytokine communication map to analyse immune responses in inflammatory and infectious diseases

Intercellular communication mediated by cytokines is critical to the development of immune responses, particularly in the context of infectious and inflammatory diseases. By releasing these small molecular weight peptides, the source cells can influence numerous intracellular processes in the target cells, including the secretion of other cytokines downstream. However, there are no readily available bioinformatic resources that can model cytokine - cytokine interactions. In this effort, we built a communication map between major tissues and blood cells that reveals how cytokine-mediated intercellular networks form during homeostatic conditions. We collated the most prevalent cytokines from literature, and assigned the proteins and their corresponding receptors to source tissue and blood cell types based on enriched consensus RNA-Seq data from the Human Protein Atlas database. To assign more confidence to the interactions, we integrated literature information on cell - cytokine interactions from two systems immunology databases, immuneXpresso and ImmunoGlobe. From the collated information, we defined two metanetworks: a cell-cell communication network connected by cytokines; and a cytokine-cytokine interaction network depicting the potential ways in which cytokines can affect the activity of each other. Using expression data from disease states, we then applied this resource to reveal perturbations in cytokine-mediated intercellular signalling in inflammatory and infectious diseases (ulcerative colitis and COVID-19, respectively). For ulcerative colitis, with CytokineLink we demonstrated a significant rewiring of cytokine-mediated intercellular communication between non-inflamed and inflamed colonic tissues. For COVID-19, we were able to identify inactive cell types and cytokine interactions that may be important following SARS-CoV-2 infection when comparing the cytokine response with other viruses capable of initiating a cytokine storm. Such findings have potential to inform the development of novel, cytokine-targeted therapeutic strategies. CytokineLink is freely available for the scientific community through the NDEx platform and the project github repository (https://github.com/korcsmarosgroup/CytokineLink).

bioinformatics↗

bioRxiv2020

ViralLink: An integrated workflow to investigate the effect of SARS-CoV-2 on intracellular signalling and regulatory pathways

The SARS-CoV-2 pandemic of 2020 has mobilised scientists around the globe to research all aspects of the coronavirus virus and its infection. For fruitful and rapid investigation of viral pathomechanisms, a collaborative and interdisciplinary approach is required. Therefore, we have developed ViralLink: a systems biology workflow which reconstructs and analyses networks representing the effect of viruses on intracellular signalling. These networks trace the flow of signal from intracellular viral proteins through their human binding proteins and downstream signalling pathways, ending with transcription factors regulating genes differentially expressed upon viral exposure. In this way, the workflow provides a mechanistic insight from previously identified knowledge of virally infected cells. By default, the workflow is set up to analyse the intracellular effects of SARS-CoV-2, requiring only transcriptomics counts data as input from the user: thus, encouraging and enabling rapid multidisciplinary research. However, the wide-ranging applicability and modularity of the workflow facilitates customisation of viral context, a priori interactions and analysis methods. Through a case study of SARS-CoV-2 infected bronchial/tracheal epithelial cells, we evidence the functionality of the workflow and its ability to identify key pathways and proteins in the cellular response to infection. The application of ViralLink to different viral infections in a cell-type specific manner using different available transcriptomics datasets will uncover key mechanisms in viral pathogenesis. The workflow is available on GitHub (https://github.com/korcsmarosgroup/ViralLink) in an easily accessible Python wrapper script, or as customisable modular R and Python scripts.Author summary Collaborative and multidisciplinary science provides increased value for experimental datasets and speeds the process of discovery. Such ways of working are especially important at present due to the urgency of the SARS-CoV-2 pandemic. Here, we present a systems biology workflow which models the effect of viral proteins on the infected host cell, to aid collaborative and multidisciplinary research. Through integration of gene expression datasets with context-specific and context-agnostic molecular interaction datasets, the workflow can be easily applied to different datasets as they are made available. Application to diverse SARS-CoV-2 datasets will increase our understanding of the mechanistic details of the infection at a cell type specific level, aid drug target discovery and help explain the variety of clinical manifestations of the infection.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗

bioRxiv2019

Identification of master regulators in goblet cells and Paneth cells using transcriptomics profiling of gut organoids and multi-layered networks

The epithelial lining of the small intestine consists of multiple cell types, including Paneth cells and goblet cells, that work in cohort to maintain gut health. 3D in vitro cultures of human primary epithelial cells, called organoids, have become a key model to study the functions of Paneth cells and goblet cells in normal and diseased conditions. Advances in these models include the ability to skew differentiation to particular lineages, providing a useful tool to study cell type specific function/dysfunction in the context of the epithelium. Here, we use comprehensive profiling of mRNA, microRNA and long non-coding RNA expression to confirm that Paneth cell and goblet cell enrichment of murine small intestinal organoids (enteroids) establishes a physiologically accurate model. We employ network analysis to infer the regulatory landscape altered by skewing differentiation, and using knowledge of cell type specific markers, we predict key regulators of cell type specific functions: Cebpa, Jun, Nr1d1 and Rxra specific to Paneth cells, Gfi1b and Myc specific for goblet cells and Ets1, Nr3c1 and Vdr shared between them. Links identified between these regulators and cellular phenotypes of inflammatory bowel disease (IBD) suggest that global regulatory rewiring during or after differentiation of Paneth cells and goblet cells could contribute to IBD aetiology. Future application of cell type enriched enteroids combined with the presented computational workflow can be used to disentangle multifactorial mechanisms of these cell types and propose regulators whose pharmacological targeting could be advantageous in treating IBD patients with Crohns disease or ulcerative colitis.\n\nTable of contentsWe demonstrate the application of network biology techniques to increase understanding of intestinal dysbiosis through studying transcriptomics data from Paneth and goblet cell enriched enteroids.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC=\"FIGDIR/small/575845v4_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (25K):\norg.highwire.dtl.DTLVardef@16637e5org.highwire.dtl.DTLVardef@1dfaa77org.highwire.dtl.DTLVardef@1307c00org.highwire.dtl.DTLVardef@1d16e0_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2018

Integrative analysis of Paneth cell proteomic data from intestinal organoids reveals functional processes affected in Crohn’s disease due to autophagy impairment

Summary statementUsing an integrative approach encompassing intestinal organoid culture, proteomics, transcriptomics and protein-protein interaction networks, we list Paneth cell functions dependent on autophagy.\n\nAbstractPaneth cells are key epithelial cells providing an antimicrobial barrier and maintaining integrity of the small intestinal stem cell niche. Paneth cell abnormalities are unfortunately detrimental to gut health and often associated with digestive pathologies such as Crohns disease or infections. Similar alterations are observed in individuals with impaired autophagy, a process which recycles cellular components. The direct effect of autophagy-impairment on Paneth cells has not been analysed. To investigate this, we generated a mouse model lacking Atg16l1 specifically in intestinal epithelial cells making these cells impaired in autophagy. Using 3D intestinal organoids enriched for Paneth cells, we compared the proteomic profiles of wild-type (WT) and autophagy-impaired organoids. We used an integrated computational approach combining protein-protein interaction networks, autophagy targeted proteins and functional information to identify the mechanistic link between autophagy-impairment and disrupted pathways. Of the 284 altered proteins, 198 (70%) were more abundant in autophagy-impaired organoids, suggesting reduced protein degradation. Interestingly, these differentially abundant proteins comprised 116 proteins (41%), predicted targets of the selective autophagy proteins p62, LC3 and ATG16L1. Our integrative analysis revealed autophagy-mediated mechanisms degrading proteins key to Paneth cell functions, such as exocytosis, apoptosis and DNA damage repair. Transcriptomic profiling of additional organoids confirmed that 90% of the observed changes upon autophagy alteration affect protein level and not gene expression. We performed further validation experiments showing differential lysozyme secretion, confirming our computationally inferred down-regulation of exocytosis. Our observations could explain how protein level alterations affect Paneth cell homeostatic functions upon autophagy impairment.

systems biology↗