bioRxiv Science⌕ Search

Biology subjects

Kern, F.

Publications and source records attributed to Kern, F..

14 recordsLinked to original sources

Angiopoietin signalling is a central axis of amyloid-driven vascular dysfunction in Alzheimer's disease

The neurovascular unit is critical for brain health, and its dysfunction has been linked to Alzheimers disease (AD). However, a cell-type-resolved understanding of how diverse vascular cells become dysfunctional and contribute to disease has been missing. Here, we applied Vessel Isolation and Nuclei Extraction for Sequencing (VINE-seq) to build a comprehensive transcriptomic atlas from 101 individuals along AD progression. Our analysis of over 842,646 parenchymal and vascular nuclei reveals that vascular dysfunction in AD is driven by transcriptional changes rather than shifts in cell proportions, with brain endothelial cells (BECs) and smooth muscle cells (SMCs) most affected. Strikingly, these molecular signatures emerge early at the mild cognitive impairment (MCI) stage, implicating vascular dysfunction early in AD pathogenesis. Stratifying by pathology reveals distinct vascular responses to {beta}-amyloid and tau: {beta}-amyloid burden primarily perturbs BECs and SMCs, while tau pathology predominantly impacts glial cells. We identify dysregulated angiopoietin signaling across multiple vascular cell types as a key axis, with antagonistic ANGPT2 in vascular cells and ANGPT1 in astrocytes becoming progressively dysregulated with AD. Together, this work provides a foundational resource that reveals early and pathology-specific pathways of vascular dysfunction in AD. Key MessagesO_LIVINE-seq analysis from 101 individuals creates a comprehensive human brain vascular atlas across Alzheimers disease (AD) progression. C_LIO_LIAD vascular dysfunction is driven by transcriptional changes rather than shifts in cell proportions, with BECs and SMCs most affected. C_LIO_LITranscriptional signatures of vascular dysfunction emerge early at the mild cognitive impairment (MCI) stage, preceding severe cognitive symptoms and aligning more closely with AD than cognitively normal individuals. C_LIO_LIA{beta} and tau associate with distinct vascular changes: A{beta} mainly perturbs endothelial and smooth muscle cells, while tau impacts microglia and astrocytes. C_LIO_LIAngiopoietin signaling (antagonistic ANGPT2 in vascular cells vs. ANGPT1 in astrocytes) becomes progressively dysregulated during AD progression. C_LI

neuroscience↗

Spatiotemporal transcriptomic niches of complement pathway and serine protease inhibitor activation in aging and infection

Aging is a multifactorial and complex physiological process, affecting every organ with characteristic manifestations. Understanding the molecular mechanisms that drive aging processes is crucial to targeting age-related disorders. Recent reports suggest that severe post-infection syndromes can partially accelerate aging. However, the underlying gene-encoded regulatory interplay, whether being shared or distinct between aging and infection biology are poorly understood. Here, we employed spatial transcriptomics to establish a multi-organ atlas (brain, heart, kidney, liver, lung, and spleen) across the mouse lifespan (4, 17, and 26 months). Dissecting high-quality fresh-frozen tissue samples at unbiased molecular resolution, we found both organ-specific and cross-organ gene dysregulation upon aging. We identified age-related trajectories in gene expression and cell state, some only detectable within their spatial context, and provide validation at subcellular resolution. The most prominent effect was organ-wide immune system activation with spatially variable severity. We therefore evaluated how aging mimics the expression signatures observed in systemic infection, using spatial transcriptomics slices from young mice infected with Plasmodium berghei ANKA. While on the gene level the effect sizes caused by the infection outweighed those of aging, we reveal a shared activation of the early complement pathway (C4b) and serine protease inhibitors (Serpin gene family) within by phenotype distinct spatial niches. We show that this common RNA signature is driven by tissue-specific cell types and eventually affects protein levels in the aged brain, rendering them a target for future mechanistic and drug discovery studies. Taken together, our study provides a coherent in-depth and cross-organ transcriptomics atlas to systematically study aging and infection in the mouse at spatiotemporal resolution. Key highlightsO_LILarge-scale and high-resolution atlas of spatial transcriptomics from six organs to study aging and systemic infection across two mouse cohorts. C_LIO_LIStrong transcriptional alterations found in distinct organ-specific niches for aging and acute malaria, with organ- and cell type-associated immune responses. C_LIO_LIDysregulation of early complement proteases (C4b) and serine protease inhibitors (Serpina3n) as common theme across central nervous system and peripheral organs. C_LI

molecular biology↗

Aging and viral evolution impair immunity against dominant pan-coronavirus-reactive T cell epitope

Immune evasion by escape mutations subverts immunity against SARS-CoV-2. A role of pan-coronavirus immunity for more durable protection is being discussed but has remained understudied. We here investigated the effects of age, mutations, and homo-/heterologous vaccination regimens on the dominant pan-coronavirus-specific cellular and humoral epitope iCope after SARS-CoV-2 infection and vaccination in detail. In the older, quantitatively, and qualitatively reduced iCope-reactive CD4+ T cell responses with narrow TCR repertoires could not be enhanced by vaccination and were further compromised by emerging spike mutations. In contrast pan-coronavirus-reactive humoral immunity was affected only by mutations and not by age. Our results reveal a distinct deficiency of the dichotomous layer of pan-coronavirus immunity in the older, critical for long-term protection against SARS-CoV-2 variants. One-Sentence SummaryAging and viral evolution impair dominant pan-coronavirus immunity, a hallmark of efficient and broad immune competence against SARS-CoV-2

immunology↗

SRF transcriptionally regulates the oligodendrocyte cytoskeleton during CNS myelination

Myelination of neuronal axons is essential for nervous system development. Myelination requires dramatic cytoskeletal dynamics in oligodendrocytes, but how actin is regulated during myelination is poorly understood. We recently identified serum response factor (SRF)--a transcription factor known to regulate expression of actin and actin regulators in other cell types--as a critical driver of myelination in the aged brain. Yet, a major gap remains in understanding the fundamental role of SRF in oligodendrocyte lineage cells. Here we show that SRF is required cell autonomously in oligodendrocytes for myelination during development. Combining ChIP-seq with RNA-seq identifies SRF-target genes in OPCs and oligodendrocytes that include actin and other key cytoskeletal genes. Accordingly, SRF knockout oligodendrocytes exhibit dramatically reduced actin filament levels early in differentiation, consistent with its role in actin-dependent myelin sheath initiation. Together, our findings identify SRF as a transcriptional regulator that controls the expression of cytoskeletal genes required in oligodendrocytes for myelination. This study identifies a novel pathway regulating oligodendrocyte biology with high relevance to brain development, aging, and disease. HighlightsO_LIDevelopmental CNS myelination requires the transcription factor SRF in oligodendrocytes. C_LIO_LISRF targets actin and actin-regulatory but not myelin related genes. C_LIO_LISRF drives oligodendrocyte actin cytoskeleton dynamics during early stages of myelination. C_LI

neuroscience↗

A spatiotemporal map of the aging mouse brain reveals white matter tracts as vulnerable foci

Aging is the key risk factor for cognitive decline, yet the molecular changes underlying brain aging remain poorly understood. Here, we conducted spatiotemporal RNA-seq of the mouse brain, profiling 1,076 samples from 15 regions across 7 ages and 2 rejuvenation interventions. Our analysis identified a brain-wide gene signature of aging in glial cells, which exhibited spatially defined changes in magnitude. By integrating spatial and single-nucleus transcriptomics, we found that glia aging was particularly accelerated in white matter compared to cortical regions, while specialized neuronal populations showed region-specific expression changes. Rejuvenation interventions, including young plasma injection and dietary restriction, exhibited distinct effects on gene expression in specific brain regions. Furthermore, we discovered differential gene expression patterns associated with three human neurodegenerative diseases, highlighting the importance of regional aging as a potential modulator of disease. Our findings identify molecular foci of brain aging, providing a foundation to target age-related cognitive decline.

neuroscience↗

Vesicle-bound regulatory RNAs are associated with tissue aging

Previous work on murine models and human demonstrated global as well as tissue-specific molecular aging trajectories in solid tissues and body fluids1-8. Extracellular vesicles like exosomes play a crucial role in communication and information exchange in between such systemic factors and solid tissues9,10. We sequenced freely circulating and vesicle-bound small regulatory RNAs in mice at five time points across the average life span from 2 to 18 months. Intriguingly, each small RNA class exhibits unique aging patterns, which showed differential signatures between vesicle-bound and freely circulating molecules. In particular, tRNA fragments showed overall highest correlation with aging which also matched well between sample types, facilitating age prediction with non-negative matrix factorization (86% accuracy). Interestingly, rRNAs exhibited inverse correlation trajectories between vesicles and plasma while vesicle-bound microRNAs (miRNAs) were exceptionally strong associated with aging. Affected miRNAs regulate the inflammatory response and transcriptional processes, and adipose tissues show considerable effects in associated gene regulatory modules. Finally, nanoparticle tracking and electron microscopy suggest a shift from overall many small to fewer but larger vesicles in aged plasma, potentially contributing to systemic aging trajectories and affecting the molecular aging of organs.

molecular biology↗

A human brain vascular atlas reveals diverse cell mediators of Alzheimer's disease risk

The human brain vasculature is of vast medical importance: its dysfunction causes disability and death, and the specialized structure it forms--the blood-brain barrier--impedes treatment of nearly all brain disorders. Yet, no molecular atlas of the human brain vasculature exists. Here, we develop Vessel Isolation and Nuclei Extraction for Sequencing (VINE-seq) to profile the major human brain vascular and perivascular cell types through 143,793 single-nucleus transcriptomes from 25 hippocampus and cortex samples of 17 control and Alzheimers disease (AD) patients. We identify brain region-enriched pathways and genes divergent between humans and mice, including those involved in disease. We describe the principles of human arteriovenous organization, recapitulating a gradual endothelial and punctuated mural cell continuum; but discover that many zonation and cell-type markers differ between species. We discover two subtypes of human pericytes, marked by solute transport and extracellular matrix (ECM) organization; and define perivascular versus meningeal fibroblast specialization. In AD, we observe a selective vulnerability of ECM-maintaining pericytes and gene expression patterns implicating dysregulated blood flow. With an expanded survey of brain cell types, we find that 30 of the top 45 AD GWAS genes are expressed in the human brain vasculature, confirmed in situ. Vascular GWAS genes map to endothelial protein transport, adaptive immune, and ECM pathways. Many are microglia-specific in mice, suggesting an evolutionary transfer of AD risk to human vascular cells. Our work unravels the molecular basis of the human brain vasculature, informing our understanding of overall brain health, disease, and therapy.

neuroscience↗

Broad transcriptional dysregulation of brain and choroid plexus cell types with COVID-19

Though SARS-CoV-2 primarily targets the respiratory system, it is increasingly appreciated that patients may suffer neurological symptoms of varied severity1-3. However, an unbiased understanding of the molecular processes across brain cell types that could contribute to these symptoms in COVID-19 patients is still missing. Here, we profile 47,678 droplet-based single-nucleus transcriptomes from the frontal cortex and choroid plexus across 10 non-viral, 4 COVID-19, and 1 influenza patient. We complement transcriptomic data with immunohistochemical staining for the presence of SARS-CoV-2. We find that all major cortex parenchymal and choroid plexus cell types are affected transcriptionally with COVID-19. This arises, in part, from SARS-CoV-2 infection of the cortical brain vasculature, meninges, and choroid plexus, stimulating increased inflammatory signaling into the brain. In parallel, peripheral immune cells infiltrate the brain, microglia activate programs mediating the phagocytosis of live neurons, and astrocytes dysregulate genes involved in neurotransmitter homeostasis. Among neurons, layer 2/3 excitatory neurons--evolutionarily expanded in humans4--show a specific downregulation of genes encoding major SNARE and synaptic vesicle components, predicting compromised synaptic transmission. These perturbations are not observed in terminal influenza. Many COVID-19 gene expression changes are shared with those in chronic brain disorders and reside in genetic variants associated with cognitive function, schizophrenia, and depression. Our findings and public dataset provide a molecular framework and new opportunities to understand COVID-19 related neurological disease.

neuroscience↗

Deep sncRNA-seq of the PPMI cohort to study Parkinson's disease progression

Coding and non-coding RNAs have diagnostic and prognostic importance in Parkinsons diseases (PD). We studied circulating small non-coding RNAs (sncRNAs) in 7, 003 samples from two longitudinal PD cohorts (Parkinsons Progression Marker Initiative (PPMI) and Luxembourg Parkinsons Study (NCER-PD)) and modelled their influence on the transcriptome. First, we sequenced sncRNAs in 5, 450 blood samples of 1, 614 individuals in PPMI. The majority of 323 billion reads (59 million reads per sample) mapped to miRNAs. Other covered RNA classes include piRNAs, rRNAs, snoRNAs, tRNAs, scaRNAs, and snRNAs. De-regulated miRNAs were associated with the disease and disease progression and occur in two distinct waves in the third and seventh decade of live. Originating mostly from a characteristic set of immune cells they resemble a systemic inflammation response and mitochondrial dysfunction, two hallmarks of PD. By profiling 1, 553 samples from 1, 024 individuals in the NCER-PD cohort using an independent technology, we validate relevant findings from the sequencing study. Finally, network analysis of sncRNAs and transcriptome sequencing of the original cohort identified regulatory modules emerging in progressing PD patients.

neuroscience↗

Competitive learning suggests circulating miRNA profiles for cancers decades prior to diagnosis

Small non-coding RNAs such as microRNAs are master regulators of gene expression. One of the most promising applications of miRNAs is the use as liquid biopsy. Especially early diagnosis is an effective means to increase patients overall survival. E.g. in oncology a tumor is detected at best prior to its clinical manifestation. We generated genome-wide miRNA profiles from serum of patients and controls from the population-based Janus Serum Bank (JSB) and analyzed them by bioinformatics and artificial intelligence approaches. JSB contains sera from 318,628 originally healthy persons, more than 96,000 of whom later developed cancer. We selected 210 serum samples of patients with lung, colon or breast cancer at three time points prior to diagnosis, after cancer diagnosis and controls. The controls were matched with regard to age of the blood donor and to the time points of blood drawing, which were 27, 32, or 38 years prior to diagnosis. Using ANOVA we report 70 significantly deregulated markers (adjusted p-value<0.05). The driver for the significance was the diagnostic time point (miR-575, miR-6821-5p, miR-630 had adjusted p-values<10-10). Further, 91miRNAs were differently expressed in pre-diagnostic samples as compared to controls (nominal p<0.05). Unsupervised competitive learning by self-organized maps indicated larges effects in lung cancer samples while breast cancer samples showed the least pronounced changes. Self-organized maps also highlighted cancer and time point specific miRNA dys-regulation. Intriguingly, a detailed breakdown of the results highlighted that 51% of all miRNAs were highly specific, either for a time-point or a cancer entity. Our results indicate that tumors may be indicated by serum miRNAs decades prior the clinical manifestation.

cancer biology↗

miEAA 2.0: Integrating multi-species microRNA enrichment analysis and workflow management systems

Gene set enrichment analysis has become one of the most frequently used applications in molecular biology research. Originally developed for gene sets, the same statistical principles are now available for all omics types. In 2016, we published the miRNA enrichment analysis and annotation tool (miEAA) for human precursor and mature miRNAs. Here, we present miEAA 2.0, supporting miRNA input from Homo sapiens, Mus musculus, and Rattus norvegicus. To facilitate inclusion of miEAA in workflow systems, we implemented an Application Programming Interface (API). Users can perform miRNA set enrichment analysis using either the web-interface, a dedicated Python package, or custom remote clients. Moreover, the number of category sets was raised by an order of magnitude. We implemented novel categories like annotation confidence level or localisation in biological compartments. In combination with the miR-Base miRNA-version and miRNA-to-precursor converters, miEAA supports research settings where older releases of miRBase are in use. The web server also offers novel comprehensive visualisations such as heatmaps and running sum curves with background distributions. Lastly, additional methods to correct for multiple hypothesis testing were implemented. We demonstrate the new features using case studies for human kidney cancer and mouse samples. The tool is freely accessible at: https://www.ccb.uni-saarland.de/mieaa2.

bioinformatics↗

Systematic assessment of blood-borne microRNAs highlights molecular profiles of endurance sport and carbohydrate uptake

Multiple studies endorsed the positive effect of regular exercising on mental and physical health. However, the molecular mechanisms underlying training-induced fitness in combination with personal life-style remain largely unexplored. Circulating biomarkers such as microRNAs (miRNAs) offer themselves for studying systemic and cellular changes since they can be collected from the bloodstream in a low-invasive manner. In Homo sapiens miRNAs are known to regulate a substantial number of protein-coding genes in a post-transcriptional manner and hence are of great interest to understand differential gene expression profiles, offering a cost-effective mechanism to study molecular training adaption, and connecting the dots from genomics to observed phenotypes.\n\nHere, we investigated molecular expression patterns of 2, 549 miRNAs in whole-blood samples from 23 healthy and untrained adult participants of a cross-over study, consisting of 8 weeks of endurance training, with several sessions per week, followed by 8 weeks of washout and another 8 weeks of running, using microarrays. Participants were randomly assigned to one of the two study groups, one of which administered carbohydrates before each session in the first training period, switching the treatment group for the second training period. During running sessions clinical parameters as heartbeat frequency were recorded. This information was extended with four measurements of maximum oxygen uptake (VO2 max) for each participant.\n\nWe observed that multiple circulating miRNAs show expression changes after endurance training, leveraging the capability to separate the blood samples by training status. To this end, we demon-strate that most of the variance in miRNA expression can be explained by both common and known biological and technical factors. Our findings highlight six distinct clusters of miRNAs, each exhibiting an oscillating expression profile across the four study timepoints, that can effectively be utilized to predict phenotypic VO2 max levels. In addition, we identified miR-532-5p as a candidate marker to determine personal alterations in physical training performance on a case-by-case analysis taking the influence of a carbohydrate-rich nutrition into account. In literature, miR-532-5p is known as a common down-regulated miRNA in diabetes and obesity, possibly providing a molecular link between cellular homeostasis, personal fitness levels, and health in aging.\n\nWe conclude that circulating miRNAs expression can be altered due to regular endurance training, independent of the carbohydrate availability in the timeframe around training. Further validation studies are required to confirm the role of exercise-affected miRNAs and the extraordinary function of miR-532-5p in modulating the metabolic response to a high availability of glucose.

systems biology↗

Integrative prediction of gene expression with chromatin accessibility and conformation data

BackgroundEnhancers play a fundamental role in orchestrating cell state and development. Although several methods have been developed to identify enhancers, linking them to their target genes is still an open problem. Several theories have been proposed on the functional mechanisms of enhancers, which triggered the development of various methods to infer promoter enhancer interactions (PEIs). The advancement of high-throughput techniques describing the three-dimensional organisation of the chromatin, paved the way to pinpoint long-range PEIs. Here we investigated whether including PEIs in computational models for the prediction of gene expression improves performance and interpretability.\n\nResultsWe have extended our Tepic framework to include DNA contacts deduced from chromatin conformation capture experiments and compared various methods to determine PEIs using predictive modelling of gene expression from chromatin accessibility data and predicted transcription factor (TF) motif data. We found that including long-range PEIs deduced from both HiC and HiChIP data indeed improves model performance. We designed a novel machine learning approach that allows to prioritize TFs in distal loop and promoter regions with respect to their importance for gene expression regulation. Our analysis revealed a set of core TFs that are part of enhancer-promoter loops involving YY1 in different cell lines.\n\nConclusionWe show that the integration of chromatin conformation data improves gene expression prediction, underlining the importance of enhancer looping for gene expression regulation. Our general approach can be used to prioritize TFs that are involved in distal and promoter-proximal regulation using accessibility, conformation and expression data.

bioinformatics↗

Identification of reduced host transcriptomic signatures for tuberculosis and digital PCR-based validation and quantification

Recently, host whole blood gene expression signatures have been identified for diagnosis of tuberculosis (TB). Absolute quantification of the concentrations of signature transcripts in blood have not been reported, but would facilitate the development of diagnostic tests.\n\nTo identify minimal transcript signatures, we applied a novel transcript selection procedure to microarray data from African adults comprising 536 patients with TB, other diseases (OD) and latent TB (LTBI), divided into training and test sets. Signatures were validated using reverse transcriptase (RT) - digital PCR (dPCR).\n\nA four-transcript signature (GBP6, TMCC1, PRDM1, ARG1) measured using RT-dPCR distinguished TB patients from those with OD (area under the curve (AUC) 93.8% (CI95% 82.2 - 100%). A three-transcript signature (FCGR1A, ZNF296, C1QB) differentiated TB from LTBI (AUC 97.3%, CI95%: 93.3 - 100%), regardless of HIV.\n\nThese signatures have been validated across platforms and across samples offering strong, quantitative support for their use as diagnostic biomarkers for TB.

molecular biology↗