Biology subjects

Shanahan, F.

Publications and source records attributed to Shanahan, F..

6 recordsLinked to original sources

bioRxiv2025

Identifying the non-Bifidobacterial hallmarks of a Bifidobacterium-receptive gut microbiome

Bifidobacteria are key health-associated members of the human gut and widely used as probiotics, but their colonization success varies across individuals, partly due to baseline microbiome composition. In this analysis encompassing 51,058 gut microbiomes (148 cohorts spanning 46 countries across six continents), we investigated non-Bifidobacterial features associated with the overall detection and abundance of eight major Bifidobacterial species. While non-Bifidobacterial community composition significantly correlated with Bifidobacterial detection in 74% of analyzed cohorts, the associations for the individual species showed distinct age-/lifestyle-/disease-specific patterns (greater similarity within similar cohorts). We quantified these relationships as Association-Scores, further stratified by age group, lifestyle, profiling strategy (16S/WGS) and nine diseases, and reasonably reproduced in an external validation-cohort-set of 8 Bifidobacterium intervention studies (1,063 gut microbiomes). We subsequently utilized these scores to build microbiome-level receptive-scores corresponding to the 8 major Bifidobacterium species and their overall detection. Both robust linear regression and cross-study validation showed that combining baseline abundance of the administered Bifidobacterium with the corresponding baseline receptive-scores significantly predicted post-treatment persistence/increase in 75% trial-probiotic pairs. We identify 129 species-specific-genome-level functional-groups in non-Bifidobacterial taxa correlating with Bifidobacterial Association-Scores. This global analysis highlights non-Bifidobacterial microbiome features influencing Bifidobacterial colonization and provides tools to predict personalized responses to Bifidobacterial-probiotic interventions.

microbiology↗

bioRxiv2025

IL-32 drives inflammatory responses in IFN-γ primed human macrophages via a Myddosome-dependent pathway and is elevated in COVID-19

IFN-{gamma} is secreted by multiple lymphoid subsets in response to antigen stimulation and can reprogram and prime macrophages epigenetically and transcriptionally to increase responses to inflammatory stimuli such as LPS, IL-1{beta} or TNF-. IFN-{gamma}-driven M1-like inflammatory macrophage states are shared across human immune-mediated inflammatory diseases (IMIDs) and while IFN-{gamma} is nonredundant for defense to intracellular pathogens it is unclear if this is also the case in IMIDs. To identify additional secreted ligands which could prime and induce M1-like macrophages we screened >600 human proteins in human primary macrophages. Using complementary functional genomics approaches, we discovered that IL-32{beta} induced an M1-like inflammatory state in non-primed and IFN-{gamma}-primed macrophages. IL-32{beta} induced signaling, transcriptional, tolerance, cross-tolerance, and inflammatory responses in macrophages which were MyD88, IRAK1 and Myddosome-dependent. These responses to host IL-32{beta} were similar to yet distinct from, those induced by microbial LPS. IL-32 protein was elevated in serum from patients with severe COVID-19 and IL-32{beta} together with IFN-{gamma} were expressed by T cells and induced a macrophage transcriptional response which was shared by monocytes and macrophages in mild and severe COVID-19.

immunology↗

bioRxiv2024

Computational modeling of drug response identifies mutant-specific constraints for dosing panRAF and MEK inhibitors in melanoma

Purpose: This study explores the potential of preclinical in vitro cell line response data and computational modeling in identifying optimal dosage requirements of pan-RAF (Belvarafenib) and MEK (Cobimetinib) inhibitors in melanoma treatment. Our research is motivated by the critical role of drug combinations in enhancing anti-cancer responses and the need to close the knowledge gap around selecting effective dosing strategies to maximize their potential. Results: In a drug combination screen of 43 melanoma cell lines, we identified unique dosage landscapes of panRAF and MEK inhibitors for NRAS vs BRAF mutant melanomas. Both experienced benefits, but with a notably more synergistic and narrow dosage range for NRAS mutant melanoma. Computational modeling and molecular experiments attributed the difference to a mechanism of adaptive resistance by negative feedback. We validated in vivo translatability of in vitro dose-response maps by accurately predicting tumor growth in xenografts. Then, we analyzed pharmacokinetic and tumor growth data from Phase 1 clinical trials of Belvarafenib with Cobimetinib to show that the synergy requirement imposes stricter precision dose constraints in NRAS mutant melanoma patients. Conclusion: Leveraging pre-clinical data and computational modeling, our approach proposes dosage strategies that can optimize synergy in drug combinations, while also bringing forth the real-world challenges of staying within a precise dose range. Simple SummaryCombining drugs is crucial for enhancing anti-cancer responses. However, the potential of pre-clinical data in identifying suitable combinations and dosage is often underutilized. In this study, we leverage preclinical in vitro cell line drug response data and computational modeling of signal transduction and of pharmacokinetics to elucidate distinct dose requirements for the combination of pan-RAF and MEK inhibitors in melanoma. Our findings reveal a more synergistic, but narrower dosing landscape in NRAS vs BRAF mutant melanoma, which we linked to a mechanism of adaptive resistance through negative feedback. Further, our analysis suggests the importance of drug dosing strategies to optimize synergy based on mutational context, yet highlights the real-world challenges of maintaining a narrow dose range. This approach establishes a framework for translational investigation of drug responses in the refinement of combination therapy, balancing the potential for synergy and practical feasibility in cancer treatment planning.

systems biology↗

bioRxiv2024

Towards a Health-Associated Core Keystone (HACK) index for the human gut microbiome

Variations in the normal gut microbiome and the existence of context-dependent disease associations have confounded the identification of microbiome markers of health. A reliable indexing of taxa based on their association with host health and microbiome resilience could accelerate development of microbiome-based therapeutics including selection of live biotherapeutics and facilitate microbiome comparisons in diverse study populations. Here we first investigated 196 taxa for their association with three hallmark properties of health and microbiome-resilience, namely prevalence/community-influence in non-diseased subjects, longitudinal stability and host health, using a discovery cohort of 39,926 publicly available adult (> 18 years) gut microbiomes from 127 studies spanning 42 countries and 28 disease conditions (including 9,434 longitudinal samples). We identified 18 species-level-taxa, referred to as Health-Associated Core Keystones (HACKs), with association-strengths in the top 30 percentile for all three properties. We integrated these association-strengths into a single value, the HACK-index, that ranks taxa based on their estimated contribution to both microbiome stability and host health. We then demonstrate the reproducibility of these indices for the taxon associations with the three properties, using a validation cohort of 4,500 gut microbiomes (from 11 studies with various demographics and diseases). Specific consortia of high HACK-index taxa are also associated with positive response to Mediterranean Diet interventions and Immuno-Checkpoint-Inhibitor therapies. We finally identify the distinguishing microbial genomic functions associated with high HACK-indices/HACK-taxa that can be investigated using targeted mechanistic studies to identify microbiome effectors of improved health. The availability of HACK-indices provides a rational basis for microbiome comparisons and will facilitate the selection and design of microbiome-based therapeutics.

microbiology↗

bioRxiv2022

An IBD-associated pathobiont synergises with NSAID to promote colitis which is blocked by NLRP3 inflammasome and Caspase-8 inhibitors

Conflicting evidence exists on the association between consumption of non-steroidal anti-inflammatory drugs (NSAIDs) and symptomatic worsening of inflammatory bowel disease (IBD). We hypothesise that the heterogeneous prevalence of pathobionts [e.g., adherent-invasive Escherichia coli (AIEC)], might explain this inconsistent NSAIDs/IBD correlation. Using IL10 -/- mice, we show aggravation of colitis in AIEC-colonised animals fed NSAID. This is accompanied by activation of the NLRP3 inflammasome, Caspase-8, apoptosis and pyroptosis; features not seen in mice exposed to AIEC or NSAID alone, revealing an AIEC/NSAID synergistic effect. Inhibition of NLRP3 or Caspase-8 activity ameliorated colitis, with reduction in NLRP3 inflammasome activation, cell death markers and activated T-cells and macrophages, improved histology and increased abundance of Clostridium cluster XIVa species. Our findings provide mechanistic insights into how NSAID and an opportunistic gut-pathobiont can synergise to worsen IBD symptoms. Thus, targeting the NLRP3 inflammasome and Caspase-8 could be a potential therapeutic strategy in patients with NSAID-worsened inflammation.

immunology↗

bioRxiv2021

Fiber-associated Lachnospiraceae reduce colon tumorigenesis by modulation of the tumor-immune microenvironment

Patients with colorectal cancer (CRC) harbor gut microbiomes that differ in structure and function from those of healthy individuals, suggesting this altered microbiome could contribute to tumorigenesis. Despite increasing evidence implicating the gut microbiome in CRC, the collective role of different microbial consortia in CRC carcinogenesis is unclear. We have previously described these consortia as co-abundance groups that co-exist at different abundance levels in the same patient. Here, we report that tumor biopsy tissue from patients with a "high-risk" Pathogen-type microbiome had a different immune transcriptome and immune cell infiltrate from those with a "low-risk" Lachnospiraceae-type microbiome. Transplantation from patients of the two fecal microbiome types into mice with an orthotopic tumor differentially affected tumor growth and the systemic anti-tumor immune response. The differences in tumor volume and immunophenotype between mice receiving the high-risk and the low-risk microbiome correlated with differences in the engrafted human microbial species and predicted microbiome-encoded metabolites in the two groups. Of twelve taxa whose abundance in recipient mice led to increased tumor onset, seven corresponded with differentially abundant taxa in a global dataset of 325 CRC patients versus 310 healthy controls. These data suggest that the enrichment for a Lachnospiraceae-type configuration of the gut microbiome may influence colon cancer progression and disease outcome by modulating the local and systemic anti-tumor immune response. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/432654v2_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@1de9ff5org.highwire.dtl.DTLVardef@d790d5org.highwire.dtl.DTLVardef@65be8aorg.highwire.dtl.DTLVardef@1c096da_HPS_FORMAT_FIGEXP M_FIG C_FIG Proposed model of how the high-risk Pathogen and low-risk Lachnospiraceae CAGs differentially modulate the tumor immune response.

microbiology↗