Biology subjects

Best, L.

Publications and source records attributed to Best, L..

5 recordsLinked to original sources

bioRxiv2026

Glucocorticoids reprogram human AML leukemic stem cells to promote elimination through differentiation and apoptosis

Acute myeloid leukemia (AML) is sustained by leukemic stem cells (LSCs) that can evade standard therapies and drive relapse. Targeting LSC-specific vulnerabilities is therefore essential for durable remission. Here we demonstrate that glucocorticoids (GCs) induce potent depletion of AML LSCs by promoting terminal differentiation and apoptosis. This effect is observable within 24 hours and is conserved across multiple LSC-enriched models and primary patient samples. Mechanistically, we establish that GC targeting of LSCs is mediated through the glucocorticoid receptor (NR3C1), with higher receptor binding affinity correlating with greater anti-LSC activity. We performed structure activity relationship (SAR) modeling of 24 corticosteroids and identified key features, including bulky D-ring substituents, associated with enhanced anti-LSC efficacy. Bulk and single-cell transcriptomic data revealed that GC treatment of LSCs suppresses NF-{kappa}B inflammatory signaling and disrupts stemness and quiescence programs while inducing transcriptional signatures associated with transient proliferation, metabolic stress, and terminal differentiation. Notably, GC sensitivity was associated with the expression of pre-existing inflammatory or extracellular matrix (ECM) signatures. Finally, we found that FLT3 ligand (FLT3L) is required for GC-induced proliferation of CD34- blasts but not for LSC depletion, suggesting that FLT3L levels may serve as a biomarker for blast expansion in patients receiving GC therapy. These findings support the clinical development of GC-based therapies in AML and provide mechanistic insights into how GCs target inflammatory and metabolic programs required for LSC survival.

cancer biology↗

bioRxiv2025

Development and evaluation of a low-cost, automated camera trap for surveying bumble bee communities

Widespread declines in insect diversity and abundance underscore an urgent need for standardized, nonlethal monitoring methods for important pollinators such as bumble bees (Bombus spp.). Camera traps are widely used for non-intrusive, continuous surveys of large animals but have not yet been extensively adopted for monitoring insects. An automated camera trap system could improve current insect survey methods, which often rely on lethal traps or in-person observation. We developed an open-source, low-cost camera trap for monitoring wild insects and evaluated its performance relative to established sampling approaches. The system used a low-power microcomputer to collect time-lapse images on colored platforms. We trained whole-image and tiled deep-learning object detection models to detect insects in images captured by the traps. We found that tiled inference models significantly improved detection accuracy and outperformed human review. Bumble bee visitation was highest on platforms featuring a fluorescent bullseye pattern; adding a fluorescent coat to blue platforms increased visitation modestly. With continuous monitoring, the cameras recorded bumble bee visits during all daylight hours. Over 18 days, camera traps recorded six Bombus species, yielding community composition and diversity estimates comparable to those obtained by hand netting and blue vane traps. Using our observed data, we simulated the effect of deploying variable numbers of cameras at sites with distinct levels of diversity. Adding cameras substantially increased sampling completeness, particularly in species-rich communities. Our findings demonstrate that low-cost, automated camera traps paired with deep-learning image analysis can enable scalable, nonlethal studies of bumble bee diversity and behavior. Our work establishes a foundation for monitoring other diurnal insect communities.

ecology↗

bioRxiv2025

Multi-omics analysis highlights the link of aging-related cognitive decline with systemic inflammation and alterations of tissue-maintenance

Aging-related cognitive decline is associated with changes across different tissues and the gut microbiome, including dysfunction of the gut-brain axis. However, only few studies have linked multi-organ alterations to cognitive decline during aging. Here we report a multi-omics analysis integrating metabolomics, transcriptomics, DNA methylation, and metagenomics data from hippocampus, liver, colon, and fecal samples of mice, correlated with cognitive performance in the Barnes Maze spatial learning task across different age groups. We identified 734 molecular features associated with cognitive rank within individual data layers, of which 227 features remain when integrating all data layers with each other. Among the single-layer predictors, several host and microbial features were highlighted, with host-associated markers being predominant. Host features associated with cognitive function mainly belong to innate and adaptive inflammatory activity (inflammaging) and developmental processes. Our findings suggest that cognitive decline in aging is tightly coupled to systemic, age-associated inflammation, potentially initiated by microbiome-driven gastrointestinal inflammatory activity, emphasizing a link between peripheral tissue alterations and brain function.

systems biology↗

bioRxiv2024

Deletion of epithelial HKDC1 decelerates cellular proliferation and impairs mitochondrial function of tumorous epithelial cells thereby protecting from intestinal carcinogenesis in mice

BackgroundA metabolic switch favoring glycolysis over aerobic oxidative phosphorylation, namely the "Warburg effect", represents a hallmark of cancer cells. Hexokinases (HK) catalyze the first step of glycolysis, thereby regulating its rate. Dysregulated HKDC1 (HK domain containing 1) expression has been associated with various cancer types and blocking HKDC1 prevents disease progression for hepatic carcinoma T cell lymphoma and lung adenocarcinoma, but its implication for colorectal cancer (CRC) remained unknown. Here, we functionally investigated the role of HKDC1 for intestinal carcinogenesis. MethodsFirst, we analyzed HKDC1 expression in the intestinal mucosa of healthy controls (HC) and CRC patients and in different tumor tissues using transcriptomic data from publicly available databases. We then generated HKDC1-deficient human and murine colonic epithelial cell lines as well as intestinal organoids and profiled their phenotypic functions. Next, we screened for proteins interacting with HKDC1 by immunoprecipitation. Finally, we generated tumor-bearing ApcMin/+ mice with a conditional deletion of HKDC1 in intestinal epithelial cells and also performed a xenograft mouse model to test the role of HKDC1 for intestinal carcinogenesis in vivo. ResultsHKDC1 was found to be overexpressed in tumor compared to normal tissue of CRC patients. In vitro, HKDC1-deficient human Caco-2 and murine CMT-93 cells displayed reduced proliferation, altered susceptibility to cell death induction, and disrupted mitochondrial functions, particularly mitochondrial respiration. These altered cancer hallmarks were then corroborated in HKDC1-deficient normal and tumor-derived ApcMin/+ intestinal organoids. Immunoprecipitation and mass spectometry proteomic analyses revealed interactions of HKDC1 with several mitochondria-related proteins. In vivo, two distinct mouse models demonstrated that epithelial deletion of HKDC1 protected from carcinogenesis. First, ApcMin/+-Hkdc1{Delta}IEC mice showed mildly improved disease phenotypes in the colon accompanied with reduced numbers of Ki67-positive proliferating epithelial cells. Finally, HKDC1-deficient Caco-2 cells completely failed to form any tumor mass in a xenograft model when implanted into immunodeficient mice. ConclusionsWe demonstrate that HKDC1 influences cancer cell proliferation and susceptibility to cell death, potentially through interactions with mitochondrial proteins that regulate membrane permeability, ultimately impacting intestinal carcinogenesis. Collectively, these findings highlight the significance of HKDC1 for CRC pathobiology, presenting it as a promising target for further investigation and potential therapeutic interventions.

cancer biology↗

bioRxiv2024

Metabolic modeling reveals the aging-associated decline of host-microbiome metabolic interactions in mice

Aging is the predominant cause of morbidity and mortality in industrialized countries. The specific molecular mechanisms that drive aging are poorly understood, especially the contribution of the microbiota in these processes. Here, we combined multi-omics with metabolic modeling in mice to comprehensively characterize host-microbiome interactions and how they are affected by aging. Our findings reveal a complex dependency of host metabolism on microbial functions, including previously known as well as novel interactions. We observed a pronounced reduction in metabolic activity within the aging microbiome, which we attribute to reduced beneficial interactions in the microbial community and a reduction in its metabolic output. These microbial changes coincided with a corresponding downregulation of key host pathways predicted by our model to be dependent on the microbiome that are crucial for maintaining intestinal barrier function, cellular replication, and homeostasis. Our results elucidate microbiome-host interactions that potentially influence host aging processes, focusing on microbial nucleotide metabolism as a pivotal factor in aging dynamics. These pathways could serve as future targets for the development of microbiome-based therapies against aging. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/587009v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@a8e7faorg.highwire.dtl.DTLVardef@115f35aorg.highwire.dtl.DTLVardef@1bbf32org.highwire.dtl.DTLVardef@1a58c7f_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗