Molecular Omics

Induced pluripotent stem cells (iPSCs) are widely used as patient-specific disease models, yet substantial unexplained variability in molecular and functional readouts limits their reliability. Here, we systematically investigated the sources of variation in iPSC-derived neurons for three rare genetic disorders: Myotonic Dystrophy Type 1, chromodomain-DNA-helicase-binding protein 2-related disorder and N-acetylneuraminic acid synthase deficiency. This was performed by profiling multi-omics layers: genomics, epigenomics, transcriptomics, proteomics, metabolomics and lipidomics. Our study found that clonal variability was comparable to inter-patient differences and that neuronal differentiation state and nutrient-driven metabolic activity emerged as dominant contributors to variability observed across omics layers. Clonal differences could partly be attributed to stochastic differences in DNA methylation established during reprogramming. By modeling and correcting the observed variation, we improved the detection of disease-associated molecular signatures. Our study provides guidelines for improved study design and data analysis to minimize variability, enabling robust biomarker discovery and reliable iPSC-based disease modeling.

Gastroschisis is a congenital abdominal wall defect in which fetal intestines herniate into the amniotic cavity. Despite 97% surgical repair success rate, 40% of affected infants require hospital readmission due to gastrointestinal complications, where underlying mechanisms remain poorly characterized. We hypopthesized that the cord blood metabolome of neonates with gastroschisis differs systematically from controls and may reveal pathway-level alterations relevant to neonatal physiology. Cord blood plasma collected at delivery (23 samples each group) was analyzed using ultra-performance liquid chromatography coupled with tandem mass spectrometry. Unsupervised principal component analysis and hierarchical clustering demonstrated significant separation between groups (PERMANOVA pseudo-F = 4.632, R{superscript 2} = 0.095, p = 0.001). 53 metabolites met criteria for differential abundance, 75% were lipids. Key alterations included reduced free fatty acids, increased fatty acid amides and ceramides, disrupted steroid and bile acid metabolism, and decreased biliverdin and bilirubin isomers. Our findings provide insight into gastroschisis pathophysiology and identify potential biomarkers for future investigation.

Background & AimsGastric epithelial cells maintain homeostasis through dynamic self-renewal mechanisms involving stem and progenitor cells; however, identifying them has been challenging. This study aims to identify stem cells of healthy gastric epithelium and cell type-specific regulators defining gastric epithelial homeostasis via single-nucleus multiome analysis. MethodsTen unique gastric samples were collected from 8-12 week old wildtype mice. Isolated nuclei were subjected to simultaneous profiling of gene expression and chromatin accessibility. After quality control, 31,598 cells were analyzed with Seurat and Signac using weighted-nearest neighbors analysis for joint RNA and ATAC clustering. Furthermore, SCENIC+, MultiVelo, EpiCHAOS and Cell plasticity score were used to uncover gene regulatory networks, cell state dynamics and lineage trajectories. ResultsOur analyses were validated by the identification of known regulators of stem-cell differentiation into mature cell types. More importantly, it revealed previously uncharacterized regulatory networks comprising novel transcription factor combinations that define cell identities, including Ppara, Pparg, Arid5b and Sox5 as candidate regulators of parietal, foveolar, chief and neck cells, respectively. Further, our data support the identity of isthmus cells as stem-like cells of healthy gastric epithelium, as evidenced by epigenetic plasticity that simultaneously contains open chromatin states of all differentiated cell types in the absence of transcriptional reprogramming. ConclusionConsistent with Waddingtons epigenetic landscape hypothesis, gastric epithelial homeostasis is controlled by orchestrated epigenetic and transcriptional programs. Contrary to the prevailing hypothesis, stem cells can be defined not by a separate epigenetic state but by epigenetic superposition of differentiated cell states. Future work is needed to define the universality of these results.

The majority of single cell-studies use RNA to identify the cell state. However, many RNAs are transient and decrease in response to elevated protein to control homeostasis. Thus, final cell states are largely defined by their unique and dynamic protein composition not RNA. Here a single-cell proteomics approach was used to identify the proteomic profile of human induced pluripotent stem cells (iPSCs) before and during their in vitro differentiation to motor neurons. By measuring up to 1000 proteins in each cell, novel clusters of growing iPSCs could be characterized along with a new proteomic pathway that defines motor neuron development. Interestingly, there was a dynamic and cell type-specific discordance between the protein levels and their corresponding messenger RNAs. This lays the foundation for drawing new single-cell proteomic maps of developing human tissues. IN BRIEFIn this article, we report the first single-cell proteomic maps of induced pluripotent stem cells (iPSCs) and their differentiation into motor neurons (MNs). By identifying proteomes of individual cells, we resolve iPSC and MN states, their proteomic, metabolomic and organellar heterogeneity. We show considerable, stage-specific discordance between the transcriptome and the proteome in differentiated neurons.

BackgroundHepatic stellate cells (HSC) are Vitamin A storing non-parenchymal cells of the liver. During injury and inflammation, HSCs are the major contributors of excessive extracellular matrix (ECM) leading to Liver Fibrosis (LF). Emerging evidence suggests a fibrosis-independent role of these cells as key regulators of liver homeostasis and liver regeneration, emphasising on the dual role of HSCs in liver. HSCs are known to secrete several growth factors through which they largely execute their functions. However, the role of secretome (exosomes) from early activated or undifferentiated HSCs in a fibrotic milieu nor its composition are completely understood. MethodsLX-2 cells were cultured in low to no serum conditions and their isolated exosomes were transplanted into fibrotic severe combined immune deficient (SCID) mice livers, followed by post-transplantation analysis of the liver tissue and compared to the untreated controls. Total proteomic profiling of cell and exosomal cargo was performed using mass spectrometry and the data analysed and compared with the total HSC cell proteome. ResultsSignificant reduction in collagen in the transplanted mice livers compared to untreated fibrotic controls was observed with both the cells and exosomes transplantation. Comparative analysis revealed distinct enrichment of proteins and signaling pathways associated with extracellular matrix regulation, cellular communication, and metabolism in exosomes. Notably, these pathways are prominently represented in the exosomal fraction, suggesting a selective packaging of functional mediators. ConclusionThis study suggests the potential role of HSCs in regulating the complex liver homeostasis via exosomal network of proteins that contribute significantly to liver repair by ECM remodelling and growth factor-mediated signalling to regulate metabolism, fibrosis and liver regeneration. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/721862v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@99bbf4org.highwire.dtl.DTLVardef@1029dd0org.highwire.dtl.DTLVardef@c6f578org.highwire.dtl.DTLVardef@1dba81_HPS_FORMAT_FIGEXP M_FIG C_FIG

Colletotrichum sublineola (Cs), the hemibiotrophic fungus that causes sorghum anthracnose, impacts sorghum grain and biomass crop production worldwide. Although nutrient availability is known to influence development in filamentous fungi, including Colletotrichum species, how in vitro nutrient limitation reprograms the Cs cellular state remains unclear. We cultured Cs on full-strength, half-strength, and one-tenth-strength potato dextrose agar (PDA) to define responses across a nutrient gradient. Nutrient limitation induced a pronounced high-sporulation phenotype, with one-tenth-strength PDA producing the strongest conidiation response, followed by half-strength PDA. To study the underlying molecular programs in each condition, we employed a multiplexed metabolite, protein, and lipid extraction (MPLEx) protocol for global proteomics and metabolomics. Global proteomics resulted in 4,590 protein identifications, including 204 unique to one-tenth-strength PDA. Among them are proteins linked to sporulation, vesicular transport, glycosylphosphatidylinositol (GPI)-anchor biosynthesis, and common in fungal extracellular membrane (CFEM)-domain proteins. Differential abundance and pathway analyses revealed a broad reduction of central carbon and energy metabolism, including glycolysis/gluconeogenesis, pentose phosphate, pyruvate metabolism, and glyoxylate pathways, together with increased ribosome-related processes, cAMP signaling, and cell-surface remodeling in one-tenth-strength PDA conditions. In addition, correlative metabolomics supported selective metabolic depletion and resource reallocation toward stress adaptation, membrane remodeling, and conidiation, supporting proteomics findings. Together, these data support a starvation-adapted Cs developmental state associated with enhanced sporulation, cellular pathway reprogramming, and potential virulence linked preparedness under nutrient-limited growth conditions in vitro. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/724728v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@f6ceb2org.highwire.dtl.DTLVardef@17c4836org.highwire.dtl.DTLVardef@68e995org.highwire.dtl.DTLVardef@1bf3983_HPS_FORMAT_FIGEXP M_FIG C_FIG

A multi-omic approach utilizing a single biospecimen is important to avoid intra-sample heterogeneity associated with testing multiple omic single-samples, and for more efficient use of small volumes of precious biopsies (<30 mg). This is especially true for the microanatomy of post-mortem human brain samples. Using post-mortem human brain biospecimens from the NIH NeuroBioBank, a penta-omic sequential extraction method is described, Simultaneous Metabolomic, Proteomic, Lipidomic - DNA, RNA Extraction (SiMPL-DREx). Each sequential omic extract was compared to those obtained by the gold standard single omic method. Preserving RIN is critical for brain and tissue banks, as it is a primary measure of tissue quality. For all five omic extracts, the tissue integrity numbers and omic profiles did not significantly differ from those obtained by the respective omic gold standard method. Unlike past multi-omic studies, this study quantified the relative solvent percentages and upstream losses for both the organic and aqueous phases, confirming an omics loss of under 5%.

Human milk contains structurally diverse glycans with key roles in shaping infant development, yet analytical constraints limit characterisation from low-volume samples. Glycosaminoglycans (GAGs), including chondroitin sulphate (CS), are understudied due to existing protocols requiring sample volumes of at least 5 mL and lengthy extraction steps prior to instrumental analysis. This study establishes a workflow for quantifying CS disaccharides from 25 {micro}L of human milk, enabling analysis of samples previously inaccessible to GAG profiling, such as those collected as salvage samples from neonatal intensive care units. For CS quantification, the CS is first enzymatically depolymerised using chondroitinase ABC to release repeating disaccharide units. Matrix complexity is reduced via two rounds of acetonitrile-based protein and lipid precipitation. Disaccharides are separated by hydrophilic interaction liquid chromatography and detected using a Triple Quadrupole Mass Spectrometer, providing robust sensitivity for all CS disaccharides. Method development and validation were performed using pooled mature human milk from term infants. This workflow facilitates detection of all CS disaccharides, with low but reproducible recoveries for total CS. Low- and high-level spike recoveries were 41.3% (RSDr 7.5%, RSDiR 15.9%) and 43.7% (RSDr 24.4%, RSDiR 27.9%), respectively. Despite modest absolute accuracy, precision remained sufficient to make relative comparison of CS concentrations between samples. This method expands the analytical toolkit for human milk glycomics, enabling same day preparation and CS profiling from sample volumes that are 200 times smaller than prior work, supporting future investigations into GAG-mediated functions in early life. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/723732v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@176dffborg.highwire.dtl.DTLVardef@16ae4ccorg.highwire.dtl.DTLVardef@d333c2org.highwire.dtl.DTLVardef@1eb3216_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO Schematic of sample preparation protocol 25 L of human milk is combined with lyase enzymes and TRIS buffer containing the internal standard prior to incubation. Samples then undergo multiple rounds of centrifugation and refrigeration before analysis via LC-MS/MS. Made using BioRender.com. Glycan nomenclature following Varki et al., 2015. C_FIG

Aroma perception during food consumption results from the combined effects of food composition, oral processing (such as chewing and saliva action), the release and transport of volatile compounds toward the olfactory epithelium, followed by cognitive integration in the brain. Recent advances in real-time analytical techniques, particularly Proton Transfer Reaction-Time-of-Flight Mass Spectrometry (PTR-ToF-MS), enable in vivo monitoring of aroma release with high temporal resolution and have become widely used for analyzing the composition of exhaled air. However, the interpretation of aroma release kinetics remains challenging due to substantial intra- and inter-individual variability caused by differences in physiology, anatomy, oral behavior, and respiratory patterns. In this context, the present study was designed to quantify aroma release associated with different food oral processing (FOP) mechanisms, such as chewing and swallowing, using simple model matrices containing a single aroma compound, and to document inter- and intra-individual variability among subjects. Real-time PTR-MS measurements were combined with self-reported oral events and simultaneous respiratory monitoring to analyze aroma release from aqueous solutions and gummy discs flavored with isoamyl acetate. The results showed that inter-individual variability was higher than intra-individual variability and allowed its quantification in aroma release. Significant differences in aroma release kinetics were observed depending on FOP protocols. The importance of considering swallowing events when analyzing aroma release data was also highlighted.

Inflammation and oxidative stress (OS) are key to Parkinsons disease (PD). We performed a cross-dataset integrative transcriptomic analysis to identify OS- and inflammation-related hub genes persistently dysregulated in PD and to evaluate their response to nutrigenomic interventions using publicly available datasets. Four GEO datasets (GSE7621, GSE20141, GSE20146, GSE49036) were analysed to identify differentially expressed genes (DEGs), which were intersected with GeneCards OS-inflammation gene sets. Functional enrichment analyses, including gene ontology (GO), pathway over-representation analysis (ORA), and protein-protein interaction (PPI) analysis, were used to identify key pathways and hub genes. Gene-food bioactive compound (FBC) association was explored by integrating PD signatures with nutrigenomic profiles from NutriGenomeDB. We identified 183 DEGs in PD, enriched in synaptic, dopaminergic, OS, and inflammatory pathways. Intersection analysis yielded 26 OS-inflammation-related genes and 10 central regulators, including TH, DDC, SNCA, LRRK2, HSPB1, and HSPA1B. revealed opposing transcriptional patterns, with several FBCs suppressing stress-related genes and upregulating dopaminergic markers such as TH, GCH1, and DDC. Overall, this integrative analysis highlights OS-inflammation gene networks in PD and identifies candidate diet-gene interactions that warrant further experimental validation

Oxidized phospholipids (OxPLs) play critical roles in inflammation, ferroptosis, and other oxidative stress-associated processes, yet their systematic characterization in biological systems remains a major analytical challenge owing to their low abundance and vast structural diversity. Here we report RISOP (Reference-Assisted Identification of Sample-specific Oxidized Phospholipids), an untargeted LC-MS/MS workflow that leverages chemically enriched OxPL reference pools to substantially improve OxPL annotation. Reference pools encompassing diverse oxidative modifications and a wide abundance range were experimentally generated using Fenton reaction and H2O2 treatment, providing broad coverage of OxPLs. Reference-assisted integrative analysis yielded a more than twofold increase in identified OxPL species in biological samples under elevated oxidative stress, as demonstrated in ML210-treated cells, a model of ferroptotic stress. We further show that the widely used BODIPY C11 lipid peroxidation probe captures cellular oxidative burden in only a subset of OxPLs identified by RISOP, highlighting the importance of untargeted, comprehensive OxPL profiling. Overall, RISOP provides a versatile platform readily applicable to other classes of oxidized complex lipids for comprehensive characterization in physiological and pathological contexts. Abstract Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/728773v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@c38797org.highwire.dtl.DTLVardef@faf0d9org.highwire.dtl.DTLVardef@da6d6eorg.highwire.dtl.DTLVardef@465132_HPS_FORMAT_FIGEXP M_FIG C_FIG

Adipogenesis is the process of adipose-derived stem cells (ADSCs) responding to extracellular signals from the stem cell niche to differentiate into adipocytes (fat cells) and may be studied in vitro using a cocktail of chemicals that promote adipogenic differentiation to produce differentiated ADSCs (dADSCs). The global membrane N- and O-glycosylation changes of this process have been previously analysed and compared to native adipocytes as a benchmark for a true adipocyte profile, and revealed that bisecting GlcNAc type N-glycans are characteristic of adipogenesis. As stem cell differentiation has been widely reported to result in cellular protein changes, the same cells (ADSCs, dADSCs and mature adipocytes) were characterised for their membrane proteome here using label-free quantitative shotgun proteomics analysis. The membrane proteome displayed more differences in protein numbers between the cell types compared to the previously reported N-glycome which had shown high identical glycomes between stem cells and in vitro dADSCs, suggesting that the proteome is more dynamic during in vitro adipogenesis. Following the global shotgun proteomics analysis, a more targeted approach of carrying out proteomic analysis of de-N-glycosylated peptides of gel-separated proteins unearthed new glycoproteins not detected in the shotgun proteomic analysis. This approach identified the adipogenic marker, CD36, to be under-represented in the shotgun proteome analysis, but as the dominant (glyco)protein in the adipocyte membrane proteome that was also up-regulated at the mRNA transcript level in both the in vitro differentiated ADSCs (7.1-fold increase) and mature adipocytes (102.9-fold increase). A comparison of CD36 sequence coverage in the global shotgun analysis with the de-N-glycosylated CD36 revealed a 41% increase when N-glycans were removed prior to trypsin digestion, explaining its observed increased abundance and highlights the crucial need for de-N-glycosylation of proteins in proteomics experiments for increased identification of glycoproteins. The systems glycobiology approach by the integration of previously reported glycomics data and the proteomics and transcriptomics analyses in this work extended the investigation of membrane protein glycosylation changes in adipose-derived stem cell differentiation. The work provides a framework for future glycoproteomics-based investigations into the differentiation of stem cells into adipocytes, and will allow their related pathologies and potential therapeutic applications to be discovered. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=121 SRC="FIGDIR/small/722121v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@189a786org.highwire.dtl.DTLVardef@5563b8org.highwire.dtl.DTLVardef@5cb5borg.highwire.dtl.DTLVardef@69e11f_HPS_FORMAT_FIGEXP M_FIG C_FIG

Glycosaminoglycans (GAGs) are linear polysaccharides with essential roles in a myriad of biological processes. Despite their biological importance, methods to determine both spatial and compositional information is limited. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) provides spatially resolved compositional information of biological molecules without enzymatic digestion or label incorporation, enabling unbiased analysis independent of enzyme or label selectivity, overcoming many current limitations in GAG analysis. Here, we present the identification and validation of GAG discriminatory ions from biological samples by comparison of spectra from purified GAGs and cells with genetically modified GAG biosynthetic pathways. Ions discriminatory of specific GAG sub-families are identified and related to GAG structural components. The analysis is applied to human induced pluripotent stem cells engineered to lack heparan sulphate (HS), where compensatory changes in GAG display that link to function were observed. Furthermore, the broad applicability and spatial resolution of the technique is highlighted through detection of a disease-induced reduction in HS within the individual glomeruli of diabetic mice.

Background: Fragile X-associated Tremor/Ataxia Syndrome (FXTAS) is a late-onset neurodegenerative disorder caused by FMR1 premutation CGG repeat expansions (55-200 repeats). The epigenetic landscape of the FXTAS brain remains uncharacterized. We performed genome-wide DNA methylation profiling of postmortem prefrontal cortex tissue to identify differentially methylated positions (DMPs) and candidate genes, and sought protein-level support for a neuroinflammatory signal. Methods: DNA methylation was profiled in postmortem prefrontal cortex (Brodmann area 9) from 27 male FXTAS cases and 29 male controls using the Illumina MethylationEPIC array (EPICv1 and EPICv2 platforms), merging 721,802 common probes. Surrogate variable analysis (SVA) controlled for confounders. DMPs were defined by p-value and FDR < 0.05; exploratory Reactome 2024 pathway analysis was performed on the DMP-associated gene list. Targeted proteomic profiling was performed in the same brain region using the Olink (proximity extension assay) Inflammation panel in 9 FXTAS cases and 12 controls, with SVA-adjusted differential abundance analysis, and concordance assessment against a prior mass spectrometry dataset. Results: We identified 108 significant cg-type DMPs mapping to 80 genes (50 hypermethylated, 58 hypomethylated in FXTAS). The strongest signal was CYP2E1 (7 concordant hypomethylated DMPs), an oxidative stress gene also implicated in Parkinsons disease. FTCD, a one-carbon cycle enzyme, carried 5 hypermethylated DMPs. A cluster of DMP-associated genes with established roles in innate immune and NF-kB signaling, TRAF3 (the single most significant DMP among the inflammation genes, hypermethylated), BATF, RCOR1, and MSI2; they pointed toward neuroinflammatory dysregulation. Additional genes included LINGO1 (myelination inhibitor), SYT3 (synaptic vesicle), and SLC39A4 (zinc transporter). Exploratory Reactome enrichment using the DMP-associated gene set nominated themes including neuroinflammation resolution, axonal growth inhibition, zinc homeostasis, and CYP2E1 metabolism at nominal significance (p<0.05); however, the gene-to-pathway mapping rate was low and no pathway survived correction for multiple testing. Olink proteomic analysis independently identified 60 significantly altered inflammation proteins (59 downregulated), including CXCL8, CXCL10, IL6, IL15, IL18, TLR3, IRAK1/4, and complement C1QA, which were directionally concordant with prior mass spectrometry data. Conclusions: This integrated study reveals a genome-wide epigenetic signature in the FXTAS prefrontal cortex implicating oxidative stress, myelination failure, zinc dysregulation, one-carbon cycle disruption, and most notably a coordinated set of epigenetically altered genes governing innate immune and NF-kB signaling. Convergence of TRAF3 hypermethylation with independent downregulation of TLR3 and NF-kB-pathway proteins at the protein level supports a coherent, cross-platform model of dysregulated neuroinflammatory signaling in FXTAS, identified here through individual gene- and protein-level convergence rather than formal pathway enrichment. FTCD hypermethylation proposes a self-reinforcing epigenetic loop via SAM depletion. These multi-omic findings establish FXTAS as a disorder of pervasive epigenetic reprogramming and nominate candidate genes for future mechanistic and therapeutic investigation.

BACKGROUND: Erythrophagocytosis constitutes a major pathogenic mechanism of metabolic dysfunction associated fatty liver disease (MAFLD). Our previous research established a quantitative thin-layer chromatography (TLC) technique for sphingomyelin, revealing reduced levels in the red blood cells (erythrocytes) of patients with metabolic dysfunction associated fatty liver disease (MAFLD). This reduction was accompanied by erythrocyte sphingosine accumulation, a driver of pro-inflammatory erythrophagocytosis, though sphingosine 1-phosphate release remained stable. To better understand erythrocyte sphingosine metabolism, we adapted our quantitative TLC method to analyze sphingosine within the erythrocyte-conditioned media (ECM) of MAFLD patients. Methodology Separation was performed on 10X10cm Silica gel 60 F254 plates using a mobile phase of chloroform, methanol, acetic acid, and water (60:50:1:4 v/v/v/v). The dynamic range, linearity, and range of linearity were assessed by analysing sphingosine levels from 0.1 to 10microg/spot. We validated the system precision and sensitivity by performing triplicate analyses of sphingosine standards (1.25, 2.5, and microg). The limits of detection and quantification were derived from the calibration curve slope and standard deviation (3.3 XSD/slope for LOD; 10 XSD/slope for LOQ). Accuracy was assessed via recovery tests at 100%, 200%, and 300% of a 2.5microg load. We confirmed specificity by evaluating the retention factors against other lipid species. This protocol was applied to Folch-extracted lipids from the ECM (5 X 107 cells/ml) of four MAFLD patients and four healthy controls, spiked with 5microg of sphingosine. Findings The calibration model, based on combined Green and Blue color intensities, followed the linear equation y = -11.171x + 353.25(R2 = 0.94). Interday precision values were 0.21%, 1.65%, and 0.44%, while recovery rates (accuracy) ranged from 94.5% to 98.7%. The measured LOD and LOQ were 0.75microg and 1.21microg, respectively. The sensitivity was calculated at 90ng. Statistical analysis showed no significant variance in sphingosine concentrations in erythrocyte-conditioned media between the MAFLD group and the control group. Summary The described thin layer chromatography is accurate, precise, sensitive, with good limits of detection and quantification, and most importantly is low-cost and time-efficient. Using this method, we show that while erythrocytes of MAFLD patients exhibit sphingosine accumulation, the utilisation of exogenous sphingosine from their erythrocytes is not affected. This suggests that the metabolic shift may be driven by increased sphingosine supply from the plasma.

Summary/AbstractFamilial Parkinsons disease (PD) is caused by mutations in more than twenty genes that affect diverse cellular pathways, including mitochondrial quality control, lysosomal function, and vesicular trafficking. A central question is how mutations impacting these distinct pathways converge to cause the selective degeneration of dopamine neurons. Human pluripotent stem cell (hPSC)-based disease models provide a valuable system to study this; however, systematic comparison of the pathogenic effects of different mutations has been limited by genetic background variability. To address this, we generated an isogenic single-cell transcriptomic atlas of fourteen familial PD mutations comprising more than 200,000 hPSC-derived midbrain specified cells. Integrated analysis revealed mutation-specific transcriptional signatures alongside shared dysregulated genes and modules that converge on mitochondrial homeostasis, endolysosomal degradation, and iron/ferroptosis pathways. Differentially expressed genes were significantly enriched for PD GWAS-implicated genes in dopamine neurons, bridging monogenic and sporadic PD genetic risk and highlighting a shared downstream state across multiple mutations. Finally, cells with a DNAJC6 mutation, which is associated with juvenile-onset parkinsonism, exhibited alteration of neurodevelopmental and psychiatric disorder risk genes, providing a transcriptional correlate for neurodevelopmental features observed in early-onset PD. Together, this resource enables molecular stratification of familial PD mutations and provides a foundational benchmarking data set.

Astrocytic homeostatic programs, many of which are regulated by the circadian clock, are disrupted early in neurodegenerative disease. The core clock transcription factor (TF) BMAL1 is required for normal astrocyte function, but its role during disease remains unclear. This is partly because methods for identifying cell type-specific TF binding sites are limited. Here, we developed MACS-Calling Cards (MACS-CC), a strategy for mapping astrocyte-specific TF occupancy in vivo. We used MACS-CC to define BMAL1 binding in the Cln3{Delta}ex7/8 mouse model of CLN3 disease, a fatal neurodegenerative disorder marked by early astrocyte dysfunction and circadian disruption. BMAL1 binding was extensively redistributed in Cln3{Delta}ex7/8 astrocytes: wild-type-specific binding sites enriched near glial differentiation genes, whereas Cln3{Delta}ex7/8-specific sites lacked functional enrichment. Consistent with these changes, Cln3{Delta}ex7/8 astrocytes decreased expression of mature astrocyte markers. To define mechanisms underlying BMAL1 retargeting, we tested whether altered chromatin accessibility explained the changes in BMAL1 binding. Although chromatin accessibility was broadly remodeled, differential accessibility did not predict BMAL1 redistribution. Instead, motif analysis suggested that loss of cooperative TF interactions drives BMAL1 retargeting. These findings demonstrate that MACS-CC enables astrocyte-specific TF occupancy mapping and reveals mechanisms behind early rewiring of circadian regulatory programs within a model of a neurodegenerative disease. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/721783v2_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@1ada239org.highwire.dtl.DTLVardef@7564a3org.highwire.dtl.DTLVardef@122222forg.highwire.dtl.DTLVardef@1f2729c_HPS_FORMAT_FIGEXP M_FIG C_FIG

Biological metal chelators are of great interest for investigation due to their capacity to retain or mobilize metals from the environment. While some biological and bioinspired chelators find use in medical applications, others are promising platforms for the mining or recycling of technologically important metal ions. In particular, the siderophores, which are primarily iron chelators, have been studied. Four siderophores of relevance are schizokinen and its derivatives, which have been isolated from bacterial and algae cultures, in addition to soil. These siderophores have shown metal chelating activity with different metals such as iron, copper, and aluminum. In the time of metabolomics, it is required to unambiguously determine the identity of the produced siderophores as quickly as possible. Thus, Liquid Chromatography coupled to High Resolution Mass Spectrometry and mass-tandem fragmentation (LC-HRMS-MS) provides a quick and applicable alternative for identification of schizokinen and its derivatives. Here, we report an analytical method for the identification and potential quantification of the schizokinen siderophore series. We developed a working method through LC-HRMS-MS, which provides the unequivocal identification of the four schizokinen derivatives, which has not been reported to date. Additionally, we constructed the molecular network for the four molecules to enable their identification using the Global Natural Products Social Molecular Networking (GNPS) platform. Most importantly, this contribution can help speed up the characterization of schizokinen producers and facilitate the dereplication process of siderophores.

Comprehensive detection of steroids, beyond the limited panels typically analyzed in clinical chemistry laboratories, has become increasingly important given their pivotal roles in diverse biological processes. However, steroid quantification poses several analytical challenges, including differences in ionization efficiency and structural similarities across the entire steroid metabolic network. To address these challenges, we developed a targeted ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) assay to analyze 21 steroids using reverse-phase chromatography combined with rapid polarity switching. Mass spectrometry (MS) analysis was performed in scheduled multiple reaction monitoring (sMRM) mode. Depending on the steroid and matrix, the validated lower limits of quantitation (LLOQ) ranged from 12.0 pM to 1216 pM in plasma and 41.1 pM to 384 pM in fecal sample homogenates. In adipose tissue, it was from 0.01 pmol/g to 9 pmol/g. Measured steroid concentrations obtained from the commercial control samples (MassTrak Steroid Serum QC Set 1 and the MassCheck Steroid Panel 1 Serum Control) showed close agreement with the reference values. As a proof of concept, the method was successfully applied to 469 plasma samples in several projects, 15 adipose tissue samples, and 332 fecal samples, demonstrating its applicability to large-scale studies. In conclusion, the method enables sensitive, derivatization-free quantification of an expanded steroid panel in plasma and complex biological matrices, including adipose tissue and fecal samples, representing a significant advancement in comprehensive steroid profiling.

Aims/hypothesisSingle-cell RNA sequencing (scRNA-seq) of pancreatic islet tissue is a powerful tool for investigating Type 1 Diabetes (T1D). However, individual datasets are limited in size and fragmented across donors, laboratories, and experimental conditions, highlighting the need for a unified single-cell atlas. This study aimed to construct a comprehensive, integrated scRNA-seq map of human isolated pancreatic islets by collating data from diverse sources. MethodsPublicly available scRNA-seq datasets derived from isolated pancreatic islets, generated and/or provided by the Human Pancreas Analysis Program (HPAP), Prodo Labs, and the Integrated Islet Distribution Program (IIDP), were collected. Systematic quality controls were implemented to select high-quality samples, reads and cells. Data integration was conducted, accounting for important variables such as age, sex, body mass index (BMI), origin study, treatments, islet data/distribution resources, and sequencing chemistry. ResultsWe generated a comprehensive single-cell atlas of human pancreatic islets comprising 191 high-quality assays from 140 donors (59 female, 81 male) across five phenotypic groups: controls without diabetes (69 donors), autoantibody-positive donors without diabetes (12), pre-diabetic donors (11), donors with type 1 diabetes (12), and donors with type 2 diabetes (36). The atlas also includes experimentally perturbed samples, including those exposed to SARS-CoV-2 infection and pro-inflammatory cytokines. In total, the atlas contains 448,935 cells, capturing major endocrine islet populations, such as alpha cells (43.3%) and beta cells (26.8%), as well as non-endocrine populations such as endothelial cells (0.75%) and immune cells (0.6%). Conclusions/interpretationBy uniformly harmonizing and integrating data from multiple sources, we have developed a comprehensive single-cell atlas of isolated human pancreatic islets, which is publicly available at www.pankbase.org. The atlas provides a platform for hypothesis-driven investigation of diabetes pathophysiology and, given rigorous quality control at the read, barcode, and sample levels alongside careful metadata curation, is well suited for downstream machine-learning applications.