Biology subjects

Stadler, M.

Publications and source records attributed to Stadler, M..

16 recordsLinked to original sources

bioRxiv2026

Direct 3D isolation in gelatin methacryloyl microbeads versus conventional 2D isolation and culture: a trade-off between mesenchymal stromal cell purity and niche-associated transcriptional profiles

Bone-marrow mesenchymal stromal cell (MSC) isolation typically couples plastic-adherence selection to planar expansion. Therefore, the recovered cells may reflect culture adaptation as much as native stromal biology. Direct isolation within a three-dimensional matrix could reduce planar selection, but its effects on cellular recovery, composition and MSC transcriptional profiles remain insufficiently resolved. We therefore developed a gelatin methacryloyl (GelMA) workflow progressing from bulk hydrogels to medium-surrounded GelMA microbeads (GMBs) and compared 3D-derived cells with conventional 2D cultures. Qualitative live/dead staining with calcein acetoxymethyl ester (CAM) and propidium iodide (PI) and 5-ethynyl-2'-deoxyuridine (EdU) imaging established cellular activity in both GelMA formats. In bulk GelMA cultures from four human donors, CD73-, CD90- and CD105-associated flow-cytometric readouts did not increase from day 7 to day 21. At day 21, the combined marker readout was numerically higher in donor-matched 2D cultures than in bulk 3D cultures, which retained heterogeneous marker-defined populations. GMBs enabled cell recovery and flow-cytometric characterization and motivated an exploratory one-donor single-cell RNA sequencing (scRNA-seq) analysis. The final dataset contained 37,784 cells across four samples and 23 annotated populations. MSC-focused re-embedding resolved 13,175 cells into two 3D and four 2D clusters. A pooled comparison identified 4,840 differentially expressed genes (DEGs, false discovery rate [FDR]<0.01, |log2FC|[≥]1), indicating a broad method-associated expression shift. The 3D C1 cluster combined progenitor-, extracellular-matrix-, adhesion-, cytokine-, hypoxia/glycolysis- and predicted-interaction-associated programmes, whereas 2D clusters showed mitochondrial, cytoskeletal/mechanoadaptive and proliferative programmes. Thus, 2D culture yielded a more strongly represented and compositionally purer MSC compartment, while 3D isolation contained rare MSC clusters with niche-associated transcriptional profiles within a heterogeneous marrow environment. These findings support a testable native-associated tendency for 3D, but donor replication, matched recovery and direct native-reference mapping are required before inferring greater in-vivo similarity or functional superiority.

cell biology↗

bioRxiv2026

Fibroblast-derived thrombospondin-1 shapes macrophage polarization in advanced human co-culture models

BackgroundTumor-associated macrophages (TAMs) are key drivers of the immunosuppressive tumor microenvironment (TME), supporting tumor progression through diverse functions. However, mechanistic studies of TAM polarization remain limited by the lack of physiologically relevant human model systems that capture stromal-immune interactions and macrophage heterogeneity. MethodsWe established advanced human co-culture systems that integrate healthy donor-derived macrophages with patient-derived organoids and tumoroids (PDOs and PDTs), as well as matched normal fibroblasts (NFs) and cancer-associated fibroblasts (CAFs). These multicellular models enabled the investigation of interactions among stromal, epithelial, and immune cells within tumor and adjacent normal tissue environments. ResultsThe co-culture systems recapitulated distinct macrophage states associated with tumor and adjacent normal environments and identified fibroblasts as major regulators of macrophage phenotypes. CAFs promoted macrophage metabolic remodeling characterized by altered lipid handling and enrichment of TAM-like signatures. Mechanistically, we identified thrombospondin 1 (TSP1) as a CAF-secreted factor linked to metabolic priming. Recombinant TSP1 induced transient lipid accumulation followed by mitochondrial remodeling. In tumor co-culture conditions, CD36 inhibition reduced lipid accumulation in macrophages, supporting a role for TSP1-linked lipid crosstalk in stromal-immune interactions. ConclusionOur study establishes advanced patient-derived co-culture models as a platform to investigate human TAM biology and stromal-immune interactions in CRC. Using these systems, we identify a fibroblast-associated TSP1-lipid axis linked to macrophage metabolic remodeling and TAM-like polarization, highlighting stromal metabolic communication as a potential targetable feature of the CRC microenvironment. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=176 HEIGHT=200 SRC="FIGDIR/small/728363v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@11b8c9borg.highwire.dtl.DTLVardef@1ac3aa2org.highwire.dtl.DTLVardef@3da223org.highwire.dtl.DTLVardef@5fc3a7_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2026

Machine Learning Method for Optimizing Coding Sequences in Mammalian Cells

Mammalian cell lines are the preferred hosts for producing commercially relevant therapeutic proteins such as antibodies, multispecifics, and cytokine fusion proteins. Even though significant investment is made to optimize upstream and downstream processes, the optimal gene design parameters for heterologous recombinant protein expression remain poorly understood. We describe here a generic approach to gene optimization in which design features are systematically sampled and modulated iteratively using machine learning (ML). Synthetic genes encoding the Dasher fluorescent protein, differing only in synonymous codons, were used to interrogate the gene-sequence preferences of transient antibody-expressing HEK293 cells. Synonymous codon variations influenced expression by more than two orders of magnitude. This variation in protein yield was used to build ML models relating gene design features, which were then employed to design further-improved genes. The ML models were shown to be expression system-specific. Messenger RNA levels and ribosome occupancy were highly correlated with protein levels, suggesting that mRNA lifetime has a causal relationship with coding bias. Our results illustrate a novel, generally applicable method to improve gene expression via synonymous re-coding for any protein target or host cell.

bioengineering↗

bioRxiv2026

Structure Elucidation, Biosynthesis and Biological Evaluation of Neosorangicin A, a Member of the Sorangicin Family

Antimicrobial resistance represents an escalating global health crisis, with drug-resistant infections predicted to cause up to 10 million deaths annually by 2050, underscoring the urgent need for novel antibiotics. Natural products play a crucial role in the discovery and development of antibiotics, with myxobacteria emerging as a particularly promising source due to their ability to produce structurally diverse and bioactive compounds. One prominent example of antibiotics from myxobacteria are the sorangicins, potent inhibitors of the bacterial RNA polymerase (RNAP). Here, we report the isolation of two unprecedented compounds, neosorangicin A (1) and neosorangioside A (2), from Sorangium cellulosum strain Soce439, elucidated their molecular structures, thereby revealing significant structural variation in comparison to sorangicin, and describe their biosynthetic pathway. Neosorangicin A (1) exhibited strong activity against various Gram-positive bacteria, with enhanced potency on intracellular Staphylococcus aureus. In a murine wound infection model, a head-to-head comparison of neosorangicin A (1) and sorangicin A (3) provided useful insights into how the altered physicochemical properties, arising from the shortened side chain and the lack of the free carboxylic acid of neosorangicin A, influence the in vivo efficacy of sorangicin derivatives.

microbiology↗

bioRxiv2025

Chemical clues to infection: Metabolome differentiation underlies host colonization of potential biocontrol agents from the entomopathogenic genus Cordyceps

Cordyceps species are widely recognized as entomopathogens, with some developed as biocontrol agents. These fungi produce bioactive metabolites contributing to their ecology and pathogenicity, yet their specific role during host infection remains poorly understood. To gain insights into how these fungi control their insect hosts, we investigated the metabolome and virulence traits of two potential biocontrol agents from the genus Cordyceps. Virulence assays on beet armyworms (Spodoptera exigua, Lepidoptera) revealed varying levels of pathogenicity, with C. javanica BCC 82944 exhibiting a higher virulence than C. blackwelliae BCC 37653, which revealed intermediate pathogenicity. Using state-of-the-art metabolomics, combined with 3D electron diffraction (3D ED) crystallography and comprehensive 1D/2D NMR spectroscopy, we identified diverse metabolites, including the cyclodepsipeptides beauverolides. Cordyceps javanica exhibited remarkable beauverolide diversity, featuring various amino acid rearrangements and fatty acid chain lengths, including three previously undescribed derivatives (1-3). While the main products of C. blackwelliae were diketopiperazines, feature-based molecular networking (FBMN) analysis uncovered the production of unprecedented beauverolides. To explore the functional relevance of these unique natural products, we analyzed the original insect cadavers from which each fungus was isolated. Our results revealed the presence of beauverolides and beauvericins in the host tissue, providing for the first time direct evidence of their involvement in fungal colonization during infection. Notably, not all beauverolides induced insect mortality in vitro, suggesting differentiated biological functions dependent on their amino acid organization. These findings indicate that distinct secondary metabolites may contribute to specific steps of the infection process. Moreover, the detection of species-specific metabolite profiles in the insect corpses suggests that Cordyceps species have developed chemically divergent infection strategies, possibly shaped by host specificity and ecological niche adaptation.

ecology↗

bioRxiv2024

Systematic Characterization of Transport Regulation in Escherichia coli across defined environmental cues

Transport of small molecules across the bacterial cell envelope is essential to ensure nutrient uptake and protect bacteria from toxic compounds. Due to its decisive role, transport is controlled by complex regulatory networks, knowledge of which - in particular across external cues - remains poorly understood. Here we investigate transcriptional regulation of seven prominent transport genes in Escherichia coli across 94 defined chemical cues, and simultaneously map the contributions of the key regulators MarA, SoxS and Rob to promoter activity. One third of all tested compounds triggered transcriptional changes, the vast majority of which previously unknown. Importantly, we exposed main drivers of transport control in E. coli, e.g. bacteriostatic, but not bactericidal, antibiotics trigger expression of efflux pumps, and that Rob contributes to [~]1/3 of all measured transcriptional changes, thereby emerging as a more prominent transport regulator than previously thought. We showcase the potential of our resource by elucidating the molecular mechanism of antibiotic antagonisms with widely consumed caffeine in E. coli. Altogether, our resource capitalizes on providing a quantitative overview of transport determinants across environments, and brings perspective to long-term prevailing concepts in the field.

microbiology↗

bioRxiv2024

Elucidation of the life cycle of a saprotrophic inoperculate discomycete that is associated with pinesap, using a polyphasic taxonomic approach

This study deals with the elucidation of the life cycle of an inoperculate discomycete that was eventually collected from conifer wood in South Germany and has become famous for the extraordinary diversity of its secondary metabolites when it was studied extensively during the 1990s. It had then been identified as Lachnum papyraceum (Lachnaceae, Helotiales) based on morphological traits, and extracts from its mycelial cultures were found to possess extraordinary nematicidal and antibiotic activities. Over 60 different secondary metabolites were finally identified from this fungus after extensive variation of culture media and scale up of production up to 100 litre scale. Among the main active principles were mycorrhizin A and chloromycorrhizin A, which had first been reported in 1987 from an unnamed "mycorrhizal" fungus of the hemiparasitic plant, Monotropa hypopitys (pinesap) that was isolated in Sweden. We noted that both the Lachnum strain and the original mycorrhizin producer were still available in the public domain, and decided to study them for comparison, using a multilocus phylogeny and also generated secondary metabolite profiles of both strains using analytical high performance liquid chromatography coupled to diode array and mass spectrometric detection (HPLC-DAD/MS). Surprisingly, the sequence data as well as the secondary metabolite profiles of both strains were highly similar, and it was also confirmed by phylogenetic methods that the strains are indeed nested within the genus Lachnum by comparison of their ITS, LSU and RBP2 sequences. The specimen called L. papyraceum in the old publications was tentatively re-identified by Hans-Otto Baral as L. cf. subvirgineum, but substantial further work on the taxonomy of the genus remains to be done, anyway. We conclude that some Lachnum species have a highly complex but all the more interesting life cycle, and the mycorrhizal symbiont partner may invade the host plant, where it may persist as an endophyte and finally turn saprotrophic on the wood of the senescent pine tree. The taxonomy of these fungi should also be further resolved in the future, using a polythetic concept that includes chemotaxonomic data and a multi-locus genealogy.

ecology↗

bioRxiv2024

Predictive modeling of microbial data with interaction effects

Microbial interactions are of fundamental importance for the functioning and the maintenance of microbial communities. Deciphering these interactions from (time-series) observational data or controlled lab experiments remains a formidable challenge due to their context-dependent nature, such as, e.g., (a)biotic factors, host characteristics, and overall community composition. Complementary to the classical ecological view, recent research advocates an empirical "community-function landscape" framework where an outcome of interest, e.g., a community function, is learned via statistical regression models that include pairwise or higher-order statistical species interaction effects. Here, we adopt the latter viewpoint and present penalized quadratic interaction models that can accommodate all common microbial data types, including microbial presence-absence data, relative (or compositional) abundance data from microbiome surveys, and quantitative (absolute abundance) microbiome data. We propose novel interaction models for compositional data and bring modern statistical techniques such as hierarchical interaction constraints and stability-based model selection to the microbial realm. To illustrate our frameworks versatility, we consider prediction tasks across a wide range of microbial datasets and ecosystems, including butyrate production in model communities in designed experiments and environmental covariate prediction from marine microbiome data. We show improved predictive performance of these interaction models and assess their limits in the presence of extreme data sparsity. On a large-scale gut microbiome cohort data, we identify interaction models that can accurately predict the abundance of antimicrobial resistance genes, enabling novel biological hypotheses about microbial community composition and antimicrobial resistance. Author SummaryMicrobes live in complex communities where interactions between species shape their function and stability. Understanding these interactions is crucial for predicting how microbial communities respond to environmental changes, medical treatments, or shifts in their host organisms. However, identifying these relationships is challenging because they depend on many factors, including the surrounding environment and community composition. In this study, we introduce a new statistical modeling approach to uncover microbial interactions from different types of data, including presence-absence patterns, relative abundance from microbiome surveys, and absolute abundance measurements. Our method builds on modern statistical techniques to improve accuracy and reliability, even when data are sparse or noisy. We demonstrate the power of our approach by applying it to diverse microbial datasets, from marine ecosystems to gut microbiomes. In one case, we successfully predicted antimicrobial resistance gene abundance based on microbial interactions, opening new avenues for understanding how resistance spreads in microbial communities. By advancing statistical tools for microbiome research, our work provides a new way to explore the hidden relationships between microbes, with potential applications in medicine, environmental science, and biotechnology.

genomics↗

bioRxiv2024

asteRIa enables robust interaction modeling between chromatin modifications and epigenetic readers

Chromatin, the nucleoprotein complex consisting of DNA and histone proteins, plays a crucial role in regulating gene expression by controlling access to DNA. Chromatin modifications are key players in this regulation, as they help to orchestrate DNA transcription, replication, and repair. These modifications recruit epigenetic "reader" proteins, which mediate downstream events. Most modifications occur in distinctive combinations within a nucleosome, suggesting that epigenetic information can be encoded in combinatorial chromatin modifications. A detailed understanding of how multiple modifications cooperate in recruiting such proteins has, however, remained largely elusive. Here, we integrate nucleosome affinity purification data with high-throughput quantitative proteomics and hierarchical interaction modeling to estimate combinatorial effects of chromatin modifications on protein recruitment. This is facilitated by the computational workflow asteRIa which combines hierarchical interaction modeling, stability-based model selection, and replicate-consistency checks for a stable estimation of Robust Interactions among chromatin modifications. asteRIa identifies several epigenetic reader candidates responding to specific interactions between chromatin modifications. For the polycomb protein CBX8, we independently validate our results using genome-wide ChIP-Seq and bisulphite datasets. We provide the first quantitative framework for identifying cooperative effects of chromatin modifications on protein binding.

molecular biology↗

bioRxiv2024

RNF43 is a gatekeeper for colitis-associated cancer

Somatic mutations in the tumor suppressor Ring finger protein 43 (RNF43) were frequently found in colitis-associated cancer (CAC) and related to the duration of chronic inflammation, but their significance in inflammation and inflammation-associated carcinogenesis remained elusive. We assessed the onset of RNF43 mutations at different stages of human CAC development by exome sequencing, and comprehensively characterized RNF43 loss-of-function-driven malignant transformation in mice by RNA sequencing, flow cytometry, immunohistochemistry, computational transcriptome-microbiome associations, and determined the underlying mechanisms by performing functional stem-cell derived organoid studies and fecal microbiota transfers. Mutations in RNF43 were frequent (12.9 %) in precancerous lesions of ulcerative colitis (UC) patients and eventually detectable in 24.4 % of CAC patients. In a bacterial-induced colitis mouse model, Rnf43 mutations caused invasive colorectal carcinomas by aggravating and perpetuating inflammation due to impaired epithelial barrier integrity and pathogen control. We could demonstrate that Rnf43 loss-of-function-mutations were even sufficient to cause spontaneous intestinal inflammation, resulting in UC-typical pathological features and subsequent invasive carcinoma development. In detail, mutant Rnf43 impaired intestinal epithelial and particularly goblet cell homeostasis in a cell-intrinsic manner, and caused dysbiosis. The altered microbiota composition induced epithelial DNA damage and spontaneous mucosal inflammation characterized by TGF-{beta}-activating dendritic cells and pro-inflammatory (IL-17+, IL-22+, TNF+) T cells. Over time, the continuous epithelial and goblet cell dysfunction, combined with pro-tumorigenic and pro-inflammatory microbiota, resulted in accumulated epithelial damage with transformation into inflammation-associated cancer in the presence of constitutive WNT signaling activation. We identified mutant RNF43 as susceptibility gene for UC and bona fide driver of CAC.

cancer biology↗

bioRxiv2023

The Novel Silver-Containing Antimicrobial Potentiates Aminoglycoside Activity Against Pseudomonas aeruginosa.

The rapid dissemination of antibiotic resistance combined with the decline in the discovery of novel antibiotics represents a major challenge for infectious disease control that can only be mitigated by investments into novel treatment strategies. Alternative antimicrobials, including silver, have regained interest due to their diverse mechanisms of inhibiting microbial growth. One such example is AGXX(R), a broad-spectrum silver containing antimicrobial that produces highly cytotoxic reactive oxygen species (ROS) to inflict extensive macromolecular damage. Due to connections identified between ROS production and antibiotic lethality, we hypothesized that AGXX(R) could potentially increase the activity of conventional antibiotics. Using the gram-negative pathogen Pseudomonas aeruginosa, we screened possible synergistic effects of AGXX(R) on several antibiotic classes. We found that the combination of AGXX(R) and aminoglycosides tested at sublethal concentrations led to a rapid exponential decrease in bacterial survival and restored sensitivity of a kanamycin-resistant strain. ROS production contributes significantly to the bactericidal effects of AGXX(R)/aminoglycoside treatments, which is dependent on oxygen availability and can be reduced by the addition of ROS scavengers. Additionally, P. aeruginosa strains deficient in ROS detoxifying/repair genes were more susceptible to AGXX(R)/aminoglycoside treatment. We further demonstrate that this synergistic interaction was associated with significant increase in outer and inner membrane permeability, resulting in increased antibiotic influx. Our study also revealed that AGXX(R)/aminoglycoside-mediated killing requires an active proton motive force across the bacterial membrane. Overall, our findings provide an understanding of cellular targets that could be inhibited to increase the activity of conventional antimicrobials. IMPORTANCEThe emergence of drug-resistant bacteria coupled with the decline in antibiotic development highlights the need for novel alternatives. Thus, new strategies aimed at repurposing conventional antibiotics have gained significant interest. The necessity of these interventions is evident especially in gram-negative pathogens as they are particularly difficult to treat due to their outer membrane. This study highlights the effectiveness of the silver containing antimicrobial AGXX(R) in potentiating aminoglycoside activities against P. aeruginosa. The combination of AGXX(R) and aminoglycosides not only reduces bacterial survival rapidly but also significantly re-sensitizes aminoglycoside-resistant P. aeruginosa strains. In combination with gentamicin, AGXX(R) induces increased endogenous oxidative stress, membrane damage and iron sulfur cluster disruption. These findings emphasize AGXX(R)s potential as a route of antibiotic adjuvant development and shed light into potential targets to enhance aminoglycoside activity.

microbiology↗

bioRxiv2023

Building a genome-based understanding of bacterial pH preferences

The environmental preferences of many microbes remain undetermined. This is the case for bacterial pH preferences, which can be difficult to predict a priori despite the importance of pH as a factor structuring bacterial communities in many systems. We compiled data on bacterial distributions from five datasets spanning pH gradients in soil and freshwater systems (1470 samples in total), quantified the pH preferences of bacterial taxa across these datasets, and compiled genomic data from representative bacterial taxa. While taxonomic and phylogenetic information were generally poor predictors of bacterial pH preferences, we identified genes consistently associated with pH preference across environments. We then developed and validated a machine learning model to estimate bacterial pH preferences from genomic information alone, a model which could aid in the selection of microbial inoculants, improve species distribution models, or help design effective cultivation strategies. More generally, we demonstrate the value of combining biogeographic and genomic data to infer and predict the environmental preferences of diverse bacterial taxa.

ecology↗

bioRxiv2022

Neurotrophic and immunomodulatory lanostane triterpenoids from wood-inhabiting Basidiomycota

Neurotrophins such as nerve growth factor (ngf) and brain derived neurotrophic factor (bdnf) play important roles in the central nervous system. They are potential therapeutic drugs for treatment of neurodegerative diseases including Alzheimers disease and Parkinsons disease. In this study, we investigated the neurotrophic properties of triterpenes isolated from fruiting bodies of Laetiporus sulphureus and a mycelial culture of Antrodia sp. MUCL 56049. The structures of the isolated compounds were elucidated based on nuclear magnetic resonance (NMR) spectroscopy in combination with high-resolution Electrospray mass spectrometry (HR-ESIMS). The secondary metabolites were tested for neurotrophin (ngf and bdnf) expression levels on human astrocytoma 1321N1 cells. Neurite outgrowth activity using rat pheochromocytoma (PC-12) cells was also determined. Twelve triterpenoids were isolated, of which several potently stimulated the expression of neurotrophic factors namely, ngf (sulphurenic acid, 15-dehydroxytrametenolic acid, fomefficinic acid D and 16-hydroxyeburicoic acid) and bdnf (sulphurenic acid and 15- dehydroxytrametenolic acid), respectively. The triterpenes also potentiated ngf-induced neurite outgrowth in PC-12 cells. This is, to the best of our knowledge, the first report on the compound class of lanostanes in direct relation to bdnf and ngf enhancement. These compounds are widespread in medicinal mushrooms; hence, they appear promising as starting point for development of drugs and mycopharmaceuticals to combat neurodegenerative diseases. Interestingly, they do not show any pronounced cytotoxicity and may therefore be better suited for therapy than many other neurotrophic compounds that were previously reported.

biochemistry↗

bioRxiv2022

Single-cell analysis reveals inter- and intratumour heterogeneity in metastatic breast cancer

Metastasis is the leading cause of cancer-related deaths of breast cancer patients. Some cancer cells in a tumour go through successive steps, referred to as the metastatic cascade, and give rise to metastases at a distant site. We know that the plasticity and heterogeneity of cancer cells play critical roles in metastasis but the precise underlying molecular mechanisms remain elusive. Here we aimed to identify molecular mechanisms of metastasis during colonization, one of the most important yet poorly understood steps of the cascade. We performed single-cell RNA-Seq (scRNA-Seq) on tumours and matched lung macrometastases of patient-derived xenografts of breast cancer. After correcting for confounding factors such as the cell cycle and the percentage of detected genes (PDG), we identified cells in three states in both tumours and metastases. Gene-set Enrichment Analysis revealed biological processes specific to proliferation and invasion in two states. Our findings suggest that these states are a balance between epithelial-to-mesenchymal (EMT) and mesenchymal-to-epithelial transitions (MET) traits that results in so-called partial EMT phenotypes. Analysis of the top Differentially Expressed Genes (DEGs) between these cell states revealed a common set of partial EMT Transcriptions Factors (TFs) controlling gene expression, including ZNF750, OVOL2, TP63, TFAP2C and HEY2. Our data suggest that the TFs related to EMT delineate different cell states in tumours and metastases. The results highlight the marked interpatient heterogeneity of breast cancer but identify common features of single cells from five models of metastatic breast cancer.

cancer biology↗

bioRxiv2019

Spatial single-cell profiling of intracellular metabolomes in situ

The recently unveiled extent of cellular heterogeneity demands for single-cell investigations of intracellular metabolomes to reveal their roles in intracellular processes, molecular microenvironment and cell-cell interactions. To address this, we developed SpaceM, a method for in situ spatial single-cell metabolomics of cell monolayers which detects >100 metabolites in >10000 individual cells together with fluorescence and morpho-spatial cellular features. We discovered that the intracellular metabolomes of co-cultured human HeLa cells and mouse NIH3T3 fibroblasts predict the cell type with 90.4% accuracy and revealed a short-distance metabolic intermixing between HeLa and NIH3T3. We characterized lipid classes composing lipid droplets in steatotic differentiated human hepatocytes, and discovered a preferential accumulation of long-chain phospholipids, a co-regulation of oleic and linoleic acids, and an association of phosphatidylinositol monophosphate with high cell-cell contact. SpaceM provides single-cell metabolic, phenotypic, and spatial information and enables spatio-molecular investigations of intracellular metabolomes in a variety of cellular models.

molecular biology↗

bioRxiv2017

Dense Bicoid Hubs Accentuate Binding along the Morphogen Gradient

Morphogen gradients direct the spatial patterning of developing embryos, however, the mechanisms by which these gradients are interpreted remain elusive. Here we perform in vivo single molecule imaging in early Drosophila melanogaster embryos of the transcription factor Bicoid that forms a gradient and initiates patterning along the anteroposterior axis. We observe that Bicoid binds to DNA with a rapid off-rate, such that its average occupancy at target loci is on-rate dependent, a property required for concentration-sensitive regulation. Surprisingly, we also observe abundant specific DNA binding in posterior nuclei, where Bicoid levels are vanishingly low. Live embryo imaging reveals spatiotemporal \"hubs\" of local high Bicoid concentration that are dependent on the ubiquitous maternal factor Zelda. We propose that localized modulation of transcription factor on-rates via clustering, provides a general mechanism to facilitate binding to low-affinity targets, and that this may be a prevalent feature directing other developmental transcription networks.

developmental biology↗