Biology subjects

Muller, C.

Publications and source records attributed to Muller, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Pangenome Graph Node-Phenotype Association shows GWAS-like quality results with only few individuals

PurposeWe introduce GO_SCPLOWRAC_SCPLOWNPA, standing for Graph Node-Phenotype Association, a method performing a GWAS-like analysis on a pangenome variation graph (PVG) built using a small number of individual genome sequences, without the need for additional population materials or kinship information for qualitative phenotypes. This method reduces the number of individuals required for association studies and prevents reference bias from variant calling in these types of analyses. BackgroundA PVG represents the multiple alignment of a set of complete genomes. It contains all variations, from single nucleotide polymorphisms (SNPs) to large structural variations (SVs), which are represented as nodes in the graph. By integrating phenotype information within nodes, we can assign a Phenotype Score (PS) to each node in the PVG and identify phenotype-related regions directly within it. These regions represent statistically significant shifts in PS distribution, highlighting their implication in the phenotype. Finally, GO_SCPLOWRAC_SCPLOWNPA provides their positions and scores for further analysis. ResultsThis method was tested using simulated data and two publicly available datasets: the Sub1A gene locus for Oryza sativa in a 13 individuals PVG, and the insertion responsible for the white-headed cattle with a PVG of 24 individuals. Source code of GO_SCPLOWRAC_SCPLOWNPA is available here https://forge.ird.fr/diade/graphgwas/granpa under GNU GPLv3. ConclusionGO_SCPLOWRAC_SCPLOWNPA was able to identify the expected area in two simulated datasets and the responsible loci for these two known traits using only a few dozen complete genomes in these PVGs. While currently limited to qualitative phenotypes, this method opens the way to more efficient ones relying on PVGs and few individuals.

bioinformatics↗

bioRxiv2026

SaVanache: indexing and visualizing pangenome variation graphs

With the rapid increase in genome sequencing and the growing availability of genomic resources, genomics is shifting toward pangenome representations that capture intra- and inter-specific diversity by integrating multiple genomes into a single entity. These pangenomes are increasingly modeled as graphs, encoding complex genomic variations in structures such as de Bruijn or variation graphs. However, while genome browsers provide standard and effective solutions for visualizing single or limited numbers of genomes, equivalent interactive tools for graph-based pangenomes remain limited, particularly for variation graph models. We developed SaVanache, a multi-resolution visualization interface designed to explore pangenome variation graphs at various depths. SaVanache enables the exploration of both global diversity and structural variations (SVs) across genomes relative to a user-defined linear pivot genome. Unlike synteny viewers, SaVanache emphasizes variations by representing SV types through a dedicated set of glyphs, facilitating intuitive one-to-many comparisons. To support smooth exploration, SaVanache preprocesses a Graphical Fragment Assembly (GFA) pangenome file into optimized index and data structures, enabling fast, real-time queries on large pangenome graphs. By combining advanced visualization techniques with efficient data handling, SaVanache provides a robust tool for scientists to analyze and visualize genetic variation within genomes and pangenomes, facilitating the identification of genetic determinants associated with phenotypes of interest and fully exploiting current genomic resources. Author summaryWe introduce SaVanache, an innovative tool that transforms the way we explore genomic resources. SaVanache allows visualization and analysis of pangenome variation graphs (PVGs), which capture genomic diversity by integrating structural variants (SV) and single nucleotide polymorphisms (SNPs) across multiple genomes. Unlike traditional genome browsers limited to a few genomes, SaVanache offers a multi-level, user-friendly interface that allows users to explore from whole pangenomes down to individual structural variants, enabling multidimensional research and development. Using a linear pivot genome as a visual reference, SaVanache simplifies complex PVG structures into intuitive comparisons. It efficiently handles large datasets and speeds up data retrieval through internal parsing. The front-end, built with modern JavaScript frameworks, provides interactive and responsive visualization, while the Python/Django backend supports real-time data updates. Users can detect and classify SVs by comparing syntenic segments between genomes, visualized through a novel glyph-based system that uses shapes and colors to represent complex rearrangements. SaVanache supports seamless zooming from chromosome-wide to nucleotide-level views, interactive diversity scatterplots, dynamic pivot genome switching, and grouping genomes by metadata to explore genotype-phenotype links. In addition, export functions bridge visualization with downstream bioinformatics. Developed with user feedback, SaVanache balances biological relevance and computational efficiency, overcoming PVG complexity to empower users with unprecedented insight into genomic diversity and SVs.

bioinformatics↗

bioRxiv2026

A targetable dependency on nonsense-mediated decay for proteostasis and immune control in small cell lung cancer

Small cell lung cancer (SCLC) is among the deadliest cancers with excessive somatic alterations, expectedly resulting in immunogenic epitopes. However, patient benefit from immunotherapy is limited. We found abundant frameshift mutations in SCLC, regarded as highly immunogenic, counterbalanced by a hyperactive nonsense-mediated decay (NMD) pathway, responsible for frameshift-mRNA degradation. NMD activity correlated with tumor mutational burden (TMB) across cancers, suggesting that SCLC depends on NMD for cellular homeostasis and immune evasion. NMD inhibition impaired SCLC proliferation and induced ER stress-dependent apoptosis in a TMB-dependent manner, thereby enabling pharmacological inhibition in vivo which effectively controlled tumor growth. By integrating genome and transcriptome sequencing with MHC-I immunopeptidomics and functional in vitro and in vivo assays, we identified that NMD inhibition boosted neoantigen expression and presentation by tumor cells and increased T cell recognition, thus enhancing overall tumor immunogenicity and further improving immunotherapy efficacy in vivo. Our work shows that SCLC - as a TMBhigh cancer - relies on NMD for survival and immune escape, uncovering a novel TMB-dependent tractable vulnerability for this devastating disease.

cancer biology↗

bioRxiv2026

Integrating metagenome-scale metabolic modelling and metabolomics to identify biochemical interactions in Microcystis phycospheres

Favoured by global changes, freshwater cyanobacterial harmful blooms generate major ecological, economical and public health challenges. Microcystis, one of the most widespread cyanobacterial genera, grows within a phycosphere where specialised interactions with its microbiome occur, and are suspected to influence bloom appearance and its potential toxicity. Using a combination of metagenomic, metabolomic and metabolic modelling, we characterised the phycospheres of twelve Microcystis strains isolated from a French pond. The distribution of metabolic reactions within Microcystis was consistent with their genospecies, whereas the metabolic landscape at the community level diverged from cyanobacterial phylogeny indicating functional decoupling between cyanobacteria and their associated microbiomes. Phycosphere-associated bacteria substantially expand the metabolic repertoire of the system, while maintaining functional redundancy within and across communities. On the other hand, metabolomic profiles were largely driven by cyanobacterial metabolic outputs. Metabolic modelling, together with the identification of toxic specialised metabolites produced by specific biosynthetic gene clusters, further highlighted differences in metabolic potential among phycospheres. Together, these findings deepen the understanding of Microcystis phycosphere functioning, demonstrate the value of multi-omics systems biology approaches, and underscore the ecological relevance of interspecies and inter-phycosphere metabolic interactions as a structuring process in bloom-associated microbiomes.

systems biology↗

bioRxiv2026

Predictive metabolomics reveals leaf systemic metabolic signatures associated with floral traits in Camellia

The genus Camellia comprises more than 200 evergreen species of major economic and ornamental importance, characterised by high morphological and chemical diversity. While several species have been extensively studied for their bioactive compounds, the metabolic basis of floral trait variation across the genus remains poorly understood. In this study, a predictive metabolomics framework was applied to investigate the relationship between leaf metabolic profiles and floral traits, focusing on flower colour and floral form. Leaves from 315 individual trees, including 15 Camellia species and representing 1,160 samples, were analysed by untargeted metabolomics, generating a large-scale metabolic profiling dataset. A dedicated quality control strategy was implemented to ensure analytical stability across multiple injection series and flowering seasons. Penalised generalised linear models were used to uncover robust metabolic predictors associated with floral traits and to evaluate model performance through internal and external validation. Distinct sets of metabolites were associated with flower colour and floral form, with limited overlap between traits. Predictive performance was consistently higher for colour than for floral form, indicating more structured metabolic signatures for chromatic traits. The selected predictors spanned multiple major chemical classes, supporting a systemic organisation of the metabolome rather than reliance on single biosynthetic pathways. Consistently high predictive accuracies were obtained, reaching approximately 87% for both flower colour and floral form, and remaining clearly above the corresponding no-information rates ({approx} 43%). Together, these results demonstrate that leaf metabolomics can be used to robustly predict floral traits in Camellia and highlight the potential of predictive metabolomics as a tool for early phenotype inference, quality control and selection in long-lived ornamental species.

plant biology↗

bioRxiv2026

MetaNetMap: automatic mapping of metabolomic data onto metabolic networks

MotivationMetabolic networks represent genome-derived information about the biochemical reactions that cells are capable of performing. Mapping omic data onto these networks is important to refine model simulations. However, metabolomic data mapping remains very challenging due to difficulties in identifier reconciliation between annotation profiles and metabolic networks. ResultsMetaNetMap is a Python package designed to automatise the process of mapping metabolomic data onto metabolic networks. It includes several layers of identifier matching, the use of customisable databases, and molecular ontology integration to suggest the most matches between experimentally-identified metabolites and molecules defined in the network. We demonstrate its usability and the quality of automated mapping using two datasets. Availability and ImplementationMetaNetMap is an open source python package and publicly available under the GPLv3 licence. Source code is freely available on GitHub: https://github.com/coraliemuller/metanetmap. Data and code used in the application cases of this paper can be found at: https://doi.org/10.57745/ESFLR8.

systems biology↗

bioRxiv2025

Human bone marrow adipocytes drive prostate cancer bone metastasis progression via lipid-mediated induction of Angiopoietin-like 4

Bone is the main metastatic site in advanced prostate cancer (PCa) and contains bone marrow adipocytes (BMAds), which account for more than 70% of adult bone marrow. However, their role in the progression of PCa metastases remains poorly understood. Herein, we developed a physiologically relevant 3D culture model using primary human BMAds from red hematopoietic rich-areas (rBMAds) and we showed that rBMAds engage in metabolic crosstalk with PCa cells. Specifically, rBMAds release free fatty acids (FFAs) through a non-canonical lipolytic pathway and these FFAs are taken up by PCa cells inducing a transcriptional reprogramming that promotes motility. Among the responsive genes, Angiopoietin like 4 (ANGPTL4) is the most upregulated via a peroxisome proliferator-activated receptor {gamma}-dependent mechanism, and its silencing abolishes the rBMAd-driven migratory and invasive phenotype. Clinically, elevated ANGPTL4 expression is associated with poor overall survival specifically in PCa bone metastases, is maintained during metastatic progression, and is indicative of aggressive disease. Together, our findings uncover a novel adipocyte-tumor interaction and identify ANGPTL4 as a key mediator and potential therapeutic target in bone-metastatic PCa.

cancer biology↗

bioRxiv2025

Red bone marrow hosts metabolically active anucleate adipocytes that support hematopoiesis

Bone marrow adipocytes (BMAds) are a major component of the bone marrow (BM) that regulate bone turnover and hematopoiesis. In rodents, two distinct adipocyte populations exist: constitutive BMAds (cBMAds), located in areas devoid of hematopoietic cells and resistant to metabolic cues, and regulatory BMAds (rBMAds), interspersed within hematopoietic niches and responsive to energy stress. Despite their potential importance, rBMAds have remained poorly characterized due to their scarcity in rodents. Here, we used a high-yield method to isolate human rBMAds, enabling structural, proteomic, lipidomic, and functional analyses. Remarkably, human rBMAds are anucleate yet retain organelles and maintain lipid and glucose metabolism, but unlike their rodent counterparts, they lack lipolytic activity. They actively secrete factors that support hematopoiesis in vitro, implicating them as functional contributors to the BM niche. These findings suggest that human rBMAds may arise from cBMAds through terminal differentiation and define a novel adipocyte subtype critical for BM homeostasis.

cell biology↗

bioRxiv2025

Network Signatures of Disease Progression and Core Symptoms in Dementia with Lewy Bodies Distinct from Alzheimer's Disease

BackgroundResting-state fMRI studies in dementia with Lewy bodies (DLB) and Alzheimers disease (AD) have described connectivity alterations in large-scale brain networks. However, little is known about functional changes across disease stages, particularly in DLB. ObjectiveTo investigate functional connectivity of key brain networks in DLB patients at different stages, compare them to AD and healthy controls (HC) and examine associations with core clinical symptoms. MethodsNinety DLB patients, comprising 63 with mild cognitive impairment (MCI-DLB) and 27 with dementia (d-DLB), along with 25 AD patients (11 MCI-AD and 14 d-AD) and 34 HC underwent clinical, neuropsychological and resting-state fMRI assessment. ROI-to-ROI analyses were performed using the CONN toolbox, (pFDR<0.05). ResultsThe DLB group showed reduced functional connectivity within the salience network (SN) compared with HC, but did not differ from AD. While MCI-DLB patients showed no significant differences, d-DLB patients showed reduced SN and frontoparietal network (FPN) connectivity compared to HC and AD. SN connectivity was associated with severity of fluctuations and FPN connectivity with REM sleep behavior disorder and cognitive decline in DLB. In contrast, in the AD group, decreased default mode network (DMN) connectivity was associated with lower MMSE scores. ConclusionSN and FPN connectivity impairments relate to disease progression and core clinical features in DLB, whereas DMN connectivity is linked to cognitive decline in AD. These distinct patterns highlight divergent paths of network dysfunction in the two diseases, offering insight into their underlying mechanisms and clinical expression.

neuroscience↗

bioRxiv2025

Behavioral variation affects persistence of an experimental food-chain

Intraspecific behavioral variation in prey could alter predator-prey interactions, yet its effects on temporal dynamics and food-web persistence remain underexplored. Pea aphids (Acyrthosiphon pisum) exhibit dropping behavior in response to predators like the seven-spot ladybird (Coccinella septempunctata). This response could be an effective anti-predator defense but could be costly in terms of energy expenditure and time not available for feeding. To investigate the impact of behavioral variation on food-chain persistence and dynamics, we used a tri-trophic experimental system with Vicia faba (plant), pea aphids (prey), and seven-spot ladybirds (predator), implementing three aphid behavioral treatments: droppers, non-droppers, and a mix of both droppers and non-droppers. To minimize genetic differences, we used clonal aphid populations across all treatments. We then tracked predator-prey population dynamics and species persistence over 25 days. Our results showed that aphid dropping behavior reduced food-chain persistence, with extinction risk significantly higher in dropper treatments than in the mix or non-dropper treatments. Ladybirds persisted across treatments, although they showed a steeper decline in abundance in the dropper treatment. In the mixed behavioral treatment, they had an intermediate persistence, suggesting a buffering effect of behavioral variation. Trophic food-chain state transitions also differed by treatment, with tri-trophic states most stable in the non-dropper, and least frequent in the dropper treatment. Furthermore, our results showed a trend of dropper treatments becoming more stable and robust towards the end of the experiment. These results demonstrate that prey behavior influences the persistence and dynamics of food-chains, with important implications for behavior-driven community dynamics.

ecology↗

bioRxiv2025

Enhanced C/EBPα function extends healthspan and lifespan in the African turquoise killifish

The transcription factor CCAAT/enhancer binding protein alpha (C/EBP) regulates cell differentiation, proliferation, and function in various tissues, including the liver, adipose tissue, skin, lung, and hematopoietic system. Studies in rats, mice, humans, and chickens have shown that CEBPA mRNA undergoes alternative translation initiation, producing three C/EBP protein isoforms. Two of these isoforms act as full-length transcription factors with N-terminal transactivation domains and a C-terminal dimerization and DNA-binding domains. The third isoform is an N-terminally truncated variant, translated from a downstream AUG codon. It competes with full-length isoforms for DNA binding, thereby antagonizing their activity. Expression of the truncated C/EBP isoform depends on the initial translation of a short upstream open reading frame (uORF) in CEBPA mRNA and subsequent re-initiation at a downstream AUG codon, a process stimulated by mTORC1 signaling. We investigated whether the ortholog of the CEBPA gene in the evolutionarily distant, short-lived African turquoise killifish (Nothobranchius furzeri) is regulated by similar mechanisms. Our findings reveal that the uORF- mediated regulation of C/EBP isoform expression is conserved in killifish. Disruption of the uORF selectively eliminates the truncated isoform, leading to unrestrained activity of the full-length C/EBP isoforms. This genetic modification significantly extended both the median and maximal lifespan and improved the healthspan of male N. furzeri. These results highlight a conserved mechanism of CEBPA gene regulation across species and its potential role in modulating the lifespan and aging phenotypes.

physiology↗

bioRxiv2025

Three species, three labs, three experiments: testing the reproducibility of ecological studies on insect behaviour in a multi-laboratory setting

The reproducibility of studies involving insect species is an underexplored area in the broader discussion about poor reproducibility in science. Our study addresses this gap by conducting a systematic multi-laboratory investigation into the reproducibility of ecological studies on insect behaviour. We implemented a 3x3 experimental design, incorporating three study sites, and three independent experiments on three insect species from different orders: the turnip sawfly (Athalia rosae, Hymenoptera), the meadow grasshopper (Pseudochorthippus parallelus, Orthoptera) and the red flour beetle (Tribolium castaneum, Coleoptera). Using random-effect meta-analysis, we compared the consistency and accuracy of treatment effects on insect behavioural traits across replicate experiments. We successfully reproduced the overall statistical treatment effect in 83% of the replicate experiments, but overall effect size replication was achieved in only 66% of the replicates. Thus, though demonstrating sufficient reproducibility in some measures, this study also provides first experimental evidence for cases of poor reproducibility in insect experiments. Our findings further show that reasons causing poor reproducibility established in rodent research also hold for other study organisms and research questions. We believe that a rethinking of current best practices is required to face reproducibility issues in insect studies, but also across disciplines. Specifically, we advocate for adopting open research practices and the implementation of methodological strategies that reduce bias and problems arising from over-standardization. With respect to the latter, the introduction of systematic variation through multi-laboratory or heterogenized designs may contribute to improved reproducibility in studies involving any living organisms.

animal behavior and cognition↗

bioRxiv2024

Modeling the emergent metabolic potential of soil microbiomes in Atacama landscapes

Soil microbiomes harbor complex communities and exhibit important ecological roles resulting from biochemical transformations and microbial interactions. Difficulties in characterizing the mechanisms and consequences of such interactions together with the multidimensionality of niches hinder our understanding of these ecosystems. The Atacama Desert is an extreme environment that includes unique combinations of stressful abiotic factors affecting microbial life. In particular, the Talabre Lejia transect has been proposed as a unique natural laboratory for understanding adaptation mechanisms. We propose a systems biology-based computational framework for the reconstruction and simulation of community-wide and genome-resolved metabolic models, in order to provide an overview of the metabolic potential as a proxy of how microbial communities are prepared to respond to the environment. Through a multifaceted approach that includes taxonomic and functional profiling of microbiomes, simulation of the metabolic potential, and multivariate analyses, we were able to identify key species and functions from six contrasting soil samples across the Talabre Lejia transect. We highlight the functional redundancy of whole metagenomes, which act as a gene reservoir from which site-specific functions emerge at the species level. We also link the physicochemistry from the puna and the lagoon samples to specific metabolic machineries that could be associated with their adaptation to the unique environmental conditions found there. We further provide an abstraction of community composition and structure for each site that allows to describe them as sensitive or resilient to environmental shifts through putative cooperation events. Our results show that the study of community-wide and genome-resolved metabolic potential, together with targeted modeling, may help to elucidate the role of producible metabolites in the adaptation of microbial communities. Our framework was designed to handle non-model microorganisms, making it suitable for any (meta)genomic dataset that includes nucleotide sequence data and high-quality environmental metadata for different samples.

systems biology↗

bioRxiv2024

Carbon Dioxide Controls Fungal Fitness and Skin Tropism of Candida auris

The pronounced skin tropism and pan-antifungal resistance traits of the fungal pathogen Candida auris stand out as a serious health threat. Here, we show that a carbonic sensing pathway (CSP) promotes development of resistance to amphotericin B through a reactive oxygen species (ROS) response, as well as ectopic cell wall and membrane lipid homeostasis. Mechanistically, the transcription factor Rca1 acts in cooperation with Efg1 to control the expression and activity of the carbonic anhydrase Nce103 as a key effector component. The conversion of carbon dioxide to bicarbonate provides a direct link to energy metabolism, facilitating colonization and growth on skin tissues. Native mouse and human skin models unequivocally show that the CSP is essential for maintaining skin tropism as well as fungal fitness. Curiously, upon ablation of Rca1 and Efg1, C. auris debilitates efficient growth on native skin. Collectively, our findings highlight critical roles of the CSP in C. auris skin tropism and antifungal drug resistance. The work suggests therapeutic options for disrupting skin colonization and thus preventing infections. Highlights{checkmark} Proteo-transcriptomics links a carbonic sensing pathway (CSP) to C. auris multidrug resistance {checkmark}The Nce103 carbonic anhydrase controls drug resistance as a key component of the CSP {checkmark}The transcription factors Rca1 and Efg1 control Nce103 and link CSP with C. auris skin tropism {checkmark}CSP acts through ectopic ROS response, cell wall architecture and membrane lipid function {checkmark}CSP is required for C. auris fitness and efficient growth and colonization of skin tissues Result contents{checkmark} Integrated omics reveals multidrug-resistant mechanisms in C. auris {checkmark}CO2-sensing controls amphotericin B resistance (AMBR) traits through Rca1 and Efg1 {checkmark}The carbonic anhydrase Nce103 governs susceptibility to amphotericin B {checkmark}The CSP influences AMBR by maintaining reactive oxygen species homeostasis {checkmark}The CSP controls AMBR via cell membrane and cell wall remodelling {checkmark}The CSP regulates fungal fitness through controlling energy metabolism {checkmark}C. auris requires the CSP for skin colonization

microbiology↗

bioRxiv2024

Metabolic fingerprinting reveals roles of Arabidopsis thaliana BGLU1, BGLU3 and BGLU4 in glycosylation of various flavonoids

Flavonoids are specialized metabolites that play important roles in plants, including interactions with the environment. The high structural diversity of this metabolite group is largely due to enzyme-mediated modifications of flavonoid core skeletons. In particular, glycosylation with different sugars is very common. In this study, the functions of the Arabidopsis thaliana glycoside hydrolase family 1-type glycosyltransferase proteins BGLU1, BGLU3 and BGLU4 were investigated, using a reverse genetics approach and untargeted metabolic fingerprinting. We screened for metabolic differences between A. thaliana wild type, loss-of-function mutants and overexpression lines and partially identified differentially accumulating metabolites, which are putative products and/or substrates of the BGLU enzymes. Our study revealed that the investigated BGLU proteins are glycosyltransferases involved in the glycosylation of already glycosylated flavonoids using different substrates. While BGLU1 appears to be involved in the rhamnosylation of a kaempferol diglycoside in leaves, BGLU3 and BGLU4 are likely involved in the glycosylation of quercetin glycosides in A. thaliana seeds. In addition, we present evidence that BGLU3 is a multifunctional enzyme that catalyzes other metabolic reactions with more complex substrates. This study deepens our understanding of the metabolic pathways and enzymes that contribute to the high structural diversity of flavonoids. HighlightThe proteins BGLU1, BGLU3 and BGLU4 are involved in glycosylations of different, already glycosylated flavonoids in Arabidopsis thaliana. BGLU3 appears to be multifunctional, acting on several complex substrates.

plant biology↗

bioRxiv2023

Chemodiversity affects preference for Tanacetum vulgare chemotypes in two aphid species

Plants of the same species often strongly differ in morphological traits, as well as in the abundance and composition of specialized metabolite profiles. Specialized metabolites can act as mediators of interactions on plants, and affect insect presence and abundance in the field. However, how specialized chemistry shapes plant attractiveness to herbivorous insects is not fully understood. Here we used common tansy (Tanacetum vulgare L., Asteraceae) - a perennial plant that is highly diverse in terpenoid composition and is known to have variable chemotypes - to test whether 1) plants with different chemotype profiles differ in attractiveness to two specialized aphids, Macrosiphoniella tanacetaria and Uroleucon tanaceti, in pairwise choice assays. Furthermore, we tested whether 2) the diversity of the terpenoid blend affects aphid attractiveness. Lastly, we tested how 3) plant chemical traits relate to plant morphological traits, and which best explain aphid preference. We found that M. tanacetaria preferred two out of five chemotypes, dominated by -thujone/{beta}-thujone and {beta}-trans-chrysanthenyl acetate, respectively, while avoiding a chemotype dominated by -pinene/sabinene. U. tanaceti showed no clear preference towards chemotypes, but when given the choice between chemotypes dominated by -thujone/{beta}-thujone and by -pinene/sabinene, they preferred the former. Importantly, plant attractiveness to aphids tended to be negatively correlated with chemodiversity, i.e., the number of terpenoid compounds, in M. tanacetaria, but not in U. tanaceti. Interestingly, the approximate concentration and number of terpenoid compounds was generally higher in larger and bushier plants. Hence, we did not observe a trade-off between plant growth and defence. We conclude that plant chemical composition affects plant attractiveness to aphids and hence may contribute to variation in natural aphid colonization patterns on plants of the same species.

ecology↗

bioRxiv2023

Collagen remodeling leads to inflammation-free expansion of periprostatic adipose tissue and promotes prostate cancer progression

One of the most striking features of the adipose depot surrounding the prostate (periprostatic adipose tissue, PPAT) is that its accumulation is independent of body mass index. Its volume varies considerably between individual with some patients exhibiting abundant PPATs that have been correlated to occurrence of aggressive prostate cancer (PCa). However, abundant PPAT are not defined at biological levels. We used a new statistical approach to define abundant PPAT by normalizing PPAT volume to prostate volume in a cohort of 351 patients with a linear regression model. Applying this definition, we confirmed the link between abundant PPAT and PCa aggressiveness, therefore validating our approach. At biological levels, we showed that abundant PPAT exhibited extensive extracellular matrix remodeling, notably of the collagen network, decreasing the mechanical constraints in hypertrophic adipocytes leading to an inflammation free-expansion. Degradation of the most abundant collagen in AT, collagen VI was associated with increased production of endotrophin, a signaling peptide derived from AT, that was also elevated in the urine of patients with abundant PPAT confirming the clinical relevance of our results. These results highlight a unique mechanism of expansion of an adipose depot and open new mechanistic avenues to explain its role in prostate-related disorders.

cancer biology↗

bioRxiv2022

Hepatic mTORC2 compensates for loss of adipose mTORC2 in mediating energy storage and glucose homeostasis

Mammalian target of rapamycin complex 2 (mTORC2) is a protein kinase complex that plays an important role in energy homeostasis. Loss of adipose mTORC2 reduces lipogenic enzyme expression and de novo lipogenesis in adipose tissue. Adipose-specific mTORC2 knockout mice also displays triglyceride accumulation in the liver. However, the mechanism and physiological role of hepatic triglyceride accumulation upon loss of adipose mTORC2 are unknown. Here, we show that loss of adipose mTORC2 increases expression of de novo lipogenic enzymes in the liver, thereby causing accumulation of hepatic triglyceride and hypertriglyceridemia. Simultaneous inhibition of lipogenic enzymes in adipose tissue and liver by ablating mTORC2 in both tissues prevented accumulation of hepatic triglycerides and hypertriglyceridemia. However, loss of adipose and hepatic mTORC2 caused severe insulin resistance and glucose intolerance. Thus, our findings suggest that increased hepatic lipogenesis is a compensatory mechanism to cope with loss of lipogenesis in adipose tissue, and further suggest that mTORC2 in adipose tissue and liver plays a crucial role in maintaining whole-body energy homeostasis. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/521172v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@904812org.highwire.dtl.DTLVardef@6b9f43org.highwire.dtl.DTLVardef@1a507b9org.highwire.dtl.DTLVardef@19e08a7_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗