Biology subjects

Aerts, S.

Publications and source records attributed to Aerts, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

The Neural Basis of Attentional Blink as a Selective Control Mechanism in Conscious Perception

Conscious perception of visual stimuli involves large-scale brain networks with multiple activation-deactivation dynamics. Previous works have shown that early detection networks may be switched off about 200ms to 300ms after presentation of a visual stimulus. We hypothesize that these deactivations represent a selective control mechanism of the brain to conserve resources for post-perceptual processing. To this end, we used attentional blink as a behavioral measure for this mechanism. We showed that attentional blink is more likely to occur when a previous visual stimulus was consciously perceived. Using high-resolution eye-tracking, we found prolonged decrease in pupil diameter and transient decrease in blink probability associated with attentional blink. Using scalp EEG data, we further showed that attentional blink is associated with more pronounced event-related potentials related to visual processing and report. One sentence summaryattentional blink may represent a selective control mechanism of neural processing resources underlying conscious perception.

neuroscience↗

bioRxiv2024

Nova-ST: Nano-Patterned Ultra-Dense platform for spatial transcriptomics

Spatial transcriptomics workflows using barcoded capture arrays are commonly used for resolving gene expression in tissues. However, existing techniques are either limited by capture array density or are cost prohibitive for large scale atlasing. We present Nova-ST, a dense nano-patterned spatial transcriptomics technique derived from randomly barcoded Illumina sequencing flow cells. Nova-ST enables customized, low cost, flexible, and high-resolution spatial profiling of large tissue sections. Benchmarking on mouse brain sections demonstrates significantly higher sensitivity compared to existing methods, at reduced cost. MotivationSpatial transcriptomics analysis is becoming exceedingly important in biomedical and clinical research. Several platforms for spatial transcriptomics are currently available, but most of these technologies are commercialized making them inflexible and cost prohibitive. The motivation for this work was to establish an open source, flexible and sensitive sequencing-based spatial transcriptomics platform that can provide a considerable cost advantage for performing large scale spatial profiling. We provide thorough and in-depth guidance and resources both for the experimental and computational components of the workflow, to facilitate easy implementation of Nova-ST.

genomics↗

bioRxiv2023

Spatial transcriptomics in adult Drosophila reveals new cell types in the brain and identifies subcellular mRNA patterns in muscles

Recently, we have achieved a significant milestone with the creation of the Fly Cell Atlas. This single-nuclei atlas encompasses the entire fly, covering the entire head and body, in addition to all major organs. This atlas catalogs many hundreds of cell types, of which we annotated 250. Thus, a large number of clusters remain to be fully characterized, in particular in the brain. Furthermore, by applying single-nuclei sequencing, all information about the spatial location of the cells in the body and of about possible subcellular localization of the mRNAs within these cells is lost. Spatial transcriptomics promises to tackle these issues. In a proof-of-concept study, we have here applied spatial transcriptomics using a selected gene panel to pinpoint the locations of 150 mRNA species in the adult fly. This enabled us to map unknown clusters identified in the Fly Cell Atlas to their spatial locations in the fly brain. Additionally, spatial transcriptomics discovered interesting principles of mRNA localization and transcriptional diversity within the large and crowded muscle cells that may spark future mechanistic investigations. Furthermore, we present a set of computational tools that will allow for easier integration of spatial transcriptomics and single-cell datasets.

developmental biology↗

bioRxiv2023

Developmental transcriptional control of mitochondrial homeostasis is required for activity-dependent synaptic connectivity

During neuronal circuit formation, local control of axonal organelles ensures proper synaptic connectivity. Whether this process is genetically encoded is unclear and if so, its developmental regulatory mechanisms remain to be identified. We hypothesized that developmental transcription factors regulate critical parameters of organelle homeostasis that contribute to circuit wiring. We combined cell type-specific transcriptomics with a genetic screen to discover such factors. We identified Telomeric Zinc finger-Associated Protein (TZAP) as a temporal developmental regulator of neuronal mitochondrial homeostasis genes, including Pink1. In Drosophila, loss of dTzap function during visual circuit development leads to loss of activity-dependent synaptic connectivity, that can be rescued by Pink1 expression. At the cellular level, loss of dTzap/TZAP leads to defects in mitochondrial morphology, attenuated calcium uptake and reduced synaptic vesicle release in fly and mammalian neurons. Our findings highlight developmental transcriptional regulation of mitochondrial homeostasis as a key factor in activity-dependent synaptic connectivity.

neuroscience↗

bioRxiv2023

Rescuing early Parkinson-induced hyposmia prevents dopaminergic system failure

The classical diagnosis of Parkinsonism is based on motor symptoms that are the consequence of nigrostriatal pathway dysfunction and reduced dopaminergic output. However, a decade prior to the emergence of motor issues, patients frequently experience non-motor symptoms, such as a reduced sense of smell (hyposmia). The cellular and molecular bases for these early defects remain enigmatic. To explore this, we developed a new collection of five fruit fly models of familial Parkinsonism and conducted single-cell RNA sequencing on young brains of these models. Interestingly, cholinergic projection neurons are the most vulnerable cells and genes associated with presynaptic function are the most deregulated. Additional single nucleus sequencing of three specific brain regions of Parkinsons disease patients confirms these findings. Indeed, the disturbances lead to early synaptic dysfunction, notably affecting cholinergic olfactory projection neurons crucial for olfactory function in flies. Correcting these defects specifically in olfactory cholinergic interneurons in flies or inducing cholinergic signaling in Parkinson mutant human induced dopaminergic neurons in vitro using nicotine, both rescue age-dependent dopaminergic neuron decline. Hence, our research uncovers that one of the earliest indicators of disease in 5 different models of familial Parkinsonism is synaptic dysfunction in higher-order cholinergic projection neurons and this contributes to the development of hyposmia. Furthermore, the shared pathways of synaptic failure in these cholinergic neurons ultimately contribute to dopaminergic dysfunction later in life.

neuroscience↗

bioRxiv2022

Enhancer grammar of liver cell types and hepatocyte zonation states

Cell type identity is encoded by gene regulatory networks (GRN), in which transcription factors (TFs) bind to enhancers to regulate target gene expression. In the mammalian liver, lineage TFs have been characterized for the main cell types, including hepatocytes. Hepatocytes cover a relatively broad cellular state space, as they differ significantly in their metabolic state, and function, depending on their position with respect to the central or portal vein in a liver lobule. It is unclear whether this spatially defined cellular state space, called zonation, is also governed by a well-defined gene regulatory code. To address this challenge, we have mapped enhancer-GRNs across liver cell types at high resolution, using a combination of single cell multiomics, spatial omics, GRN inference, and deep learning. We found that cell state changes in transcription and chromatin accessibility in hepatocytes, liver sinusoidal endothelial cells and hepatic stellate cells depend on zonation. Enhancer-GRN mapping suggests that zonation states in hepatocytes are driven by the repressors Tcf7l1 and Tbx3, that modulate the core hepatocyte GRN, controlled by Hnf4a, Cebpa, Hnf1a, Onecut1 and Foxa1, among others. To investigate how these TFs cooperate with cell type TFs, we performed an in vivo massively parallel reporter assay on 12,000 hepatocyte enhancers and used these data to train a hierarchical deep learning model (called DeepLiver) that exploits both enhancer accessibility and activity. DeepLiver confirms Cebpa, Onecut, Foxa1, Hnf1a and Hnf4a as drivers of enhancer specificity in hepatocytes; Tcf7l1/2 and Tbx3 as regulators of the zonation state; and Hnf4a, Hnf1a, AP-1 and Ets as activators. Finally, taking advantage of in silico mutagenesis predictions from DeepLiver and enhancer assays, we confirmed that the destruction of Tcf7l1/2 or Tbx3 motifs in zonated enhancers abrogates their zonation bias. Our study provides a multi-modal understanding of the regulatory code underlying hepatocyte identity and their zonation state, that can be exploited to engineer enhancers with specific activity levels and zonation patterns.

genomics↗

bioRxiv2022

SCENIC+: single-cell multiomic inference of enhancers and gene regulatory networks

Joint profiling of chromatin accessibility and gene expression of individual cells provides an opportunity to decipher enhancer-driven gene regulatory networks (eGRN). Here we present a new method for the inference of eGRNs, called SCENIC+. SCENIC+ predicts genomic enhancers along with candidate upstream transcription factors (TF) and links these enhancers to candidate target genes. Specific TFs for each cell type or cell state are predicted based on the concordance of TF binding site accessibility, TF expression, and target gene expression. To improve both recall and precision of TF identification, we curated and clustered more than 40,000 position weight matrices that we could associate with 1,553 human TFs. We validated and benchmarked each of the SCENIC+ components on diverse data sets from different species, including human peripheral blood mononuclear cell types, ENCODE cell lines, human melanoma cell states, and Drosophila retinal development. Next, we exploit SCENIC+ predictions to study conserved TFs, enhancers, and GRNs between human and mouse cell types in the cerebral cortex. Finally, we provide new capabilities that exploit the inferred eGRNs to study the dynamics of gene regulation along differentiation trajectories; to map regulatory activities onto tissues using spatial omics data; and to predict the effect of TF perturbations on cell state. SCENIC+ provides critical insight into gene regulation, starting from multiome atlases of scATAC-seq and scRNA-seq. The SCENIC+ suite is available as a set of Python modules at https://scenicplus.readthedocs.io.

bioinformatics↗

bioRxiv2022

Cell type directed design of synthetic enhancers

Transcriptional enhancers act as docking stations for combinations of transcription factors and thereby regulate spatiotemporal activation of their target genes. A single enhancer, of a few hundred base pairs in length, can autonomously and independently of its location and orientation drive cell-type specific expression of a gene or transgene. It has been a long-standing goal in the field to decode the regulatory logic of an enhancer and to understand the details of how spatiotemporal gene expression is encoded in an enhancer sequence. Recently, deep learning models have yielded unprecedented insight into the enhancer code, and well-trained models are reaching a level of understanding that may be close to complete. As a consequence, we hypothesized that deep learning models can be used to guide the directed design of synthetic, cell type specific enhancers, and that this process would allow for a detailed tracing of all enhancer features at nucleotide-level resolution. Here we implemented and compared three different design strategies, each built on a deep learning model: (1) directed sequence evolution; (2) directed iterative motif implanting; and (3) generative design. We evaluated the function of fully synthetic enhancers to specifically target Kenyon cells in the fruit fly brain using transgenic animals. We then exploited this concept further by creating "dual-code" enhancers that target two cell types, and minimal enhancers smaller than 50 base pairs that are fully functional. By examining the trajectories followed during state space searches towards functional enhancers, we could accurately define the enhancer code as the optimal strength, combination, and relative distance of TF activator motifs, and the absence of TF repressor motifs. Finally, we applied the same three strategies to successfully design human enhancers. In conclusion, enhancer design guided by deep learning leads to better understanding of how enhancers work and shows that their code can be exploited to manipulate cell states.

genomics↗

bioRxiv2022

Neuronal identity defines a-synuclein and tau toxicity

Pathogenic -synuclein and tau are critical drivers of neurodegeneration and their mutations cause neuronal loss in patients. Whether the underlying preferential neuronal vulnerability is a cell-type intrinsic property or a consequence of increased expression levels is an open question. Here, we explore cell-type specific -synuclein and tau expression in human brain datasets and use deep phenotyping as well as brain-wide single-cell RNA sequencing of >200 live neuron types in fruit flies to ask which cellular environments react most to -synuclein or tau toxicity. We detect phenotypic and transcriptomic evidence of differential neuronal vulnerability independent of -synuclein or tau expression levels. Comparing vulnerable with resilient neurons enabled us to identify molecular signatures associated with these differential responses. We used these to verify, and then predict resilient and vulnerable neuron subtypes in human brains. This confirms substantia nigra dopaminergic neurons to be sensitive to -synuclein, and we predict pathogenic tau vulnerable and protected cortical neuron subtypes. Our work indicates that cellular determinants confer selective vulnerability to specific types of amyloid toxicity, thus paving the way to leverage neuronal identity to uncover modifiers of neurodegeneration-associated toxic proteins.

neuroscience↗

bioRxiv2022

Shared enhancer gene regulatory networks between wound and oncogenic programs

Wound response programs are often activated during neoplastic growth in tumors. In both wound repair and tumor growth, cells respond to acute stress and balance the activation of multiple programs including apoptosis, proliferation, and cell migration. Central to those responses are the activation of the JNK/MAPK and JAK/STAT signaling pathways. Yet, to what extent these signaling cascades interact at the cis-regulatory level, and how they orchestrate different regulatory and phenotypic responses is still unclear. Here, we aim to characterize the regulatory states that emerge and cooperate in the wound response, using the Drosophila melanogaster wing disc as a model system, and compare these with cancer cell states induced by rasV12scrib-/- in the eye disc. We used single-cell multiome profiling to derive enhancer Gene Regulatory Networks (eGRNs) by integrating chromatin accessibility and gene expression signals. We identify a "proliferative" eGRN, active in the majority of wounded cells and controlled by AP-1 and STAT. In a smaller, but distinct population of wound cells, a "senescent" eGRN is activated and driven by C/EBP-like transcription factors (Irbp18, Xrp1, Slow border, and Vrille) and Scalloped. In tumor cells on the other hand, both eGRN signatures are simultaneously active within the same cell. Our single-cell multiome and eGRNs resource offers an in-depth characterisation of the senescence markers, together with a new perspective on the shared gene regulatory programs acting during wound response and oncogenesis.

cell biology↗

bioRxiv2022

Heparins enhance C1 esterase inhibitor activity: a promising remedy for acute hereditary angioedema

RationaleHereditary angioedema (HAE) is a potentially life-threatening illness most commonly due to deficiency or dysfunction of C1-esterase inhibitor (C1-INH). While specific treatments are available to thwart acute exacerbations, they are extremely costly and some can be associated with rare but serious side effects. The heparins are long known to augment C1-INH activity and case reports / series have documented their efficacy in treating HAE. Objectiveto determine if unfractionated heparin and two low-molecular weight heparins (enoxaparin and nadroparin) can augment C1-INH activity ex vivo in the sera of patients with HAE and in an in vitro biochemical assay. MethodsC1-INH activity in the absence or presence of the heparin formulations were analyzed by two different methods. To measure C1-INH activity ex vivo, a commercially available assay was utilized with patient sera, excess amounts of C1s, and a substrate of C1s which, upon cleavage by C1s, produces a chromogenic product. To determine biochemically the C1-INH activity in vitro, a pharmacologic grade C1-INH, recombinant C1s (C1s-CCP12SP), and a peptide substrate of C1s were employed. Microscale thermophoresis was used to determine whether C1-INH binds to heparin. Main resultsin patient sera, nadroparin was superior to enoxaparin and unfractionated heparin in augmenting C1-INH activity, followed by enoxaparin and then unfractionated heparin. In the in vitro biochemical assay, all three heparins augmented C1-INH-C1s binding linearly in a dose-dependent fashion. Microscale thermophoresis assay demonstrated that nadroparin binds to C1-INH, providing a mechanism by which heparin facilitates the interaction between C1-INH and the proteases known to produce bradykinin, the mediator of HAE. Conclusionlow-molecular weight heparin augments C1-INH activity and should be studied as a potential treatment for acute HAE.

pharmacology and toxicology↗

bioRxiv2022

Cell type diversity in a developing octopus brain

Octopuses are mollusks that have evolved intricate neural systems comparable with vertebrates in terms of cell number, complexity and size. The cell types within the octopus brain that control their amazingly rich behavioral repertoire are still unknown. Here we profile cell diversity of the paralarval Octopus vulgaris brain to build a comprehensive cell type atlas that comprises mostly neural cells, as well as multiple glial subtypes, endothelial cells and fibroblasts. Moreover, we spatially map cell types within the octopus brain, including vertical and optic lobe cell types. Investigation of cell type conservation reveals a shared gene signature between glial cells of mice, fly and octopus. Genes related to learning and memory are enriched in vertical lobe cells, which show molecular similarities with Kenyon cells in Drosophila. Taken together, our data sheds light on cell type diversity and evolution of the complex octopus brain. Highlights & Key findingsO_LICharacterization of different cell types present in the early paralarval brain C_LIO_LICross-species comparisons reveal a conserved glial gene expression signature C_LIO_LIVertical lobe amacrine cells in octopus have molecular similarities to fly Kenyon cells C_LIO_LIHomeobox genes are defining transcription factors for cell type identity C_LIO_LIRecently expanded gene families may underlie cellular diversification C_LI

developmental biology↗

bioRxiv2021

Species-specific mitochondria dynamics and metabolism regulate the timing of neuronal development

The evolution of species involves changes in the timeline of key developmental programs. Among these, neuronal development is considerably prolonged in the human cerebral cortex compared with other mammals, leading to brain neoteny. Here we explore whether mitochondria influence the species-specific properties of cortical neuron maturation. By comparing human and mouse cortical neuronal maturation at high temporal and cell resolution, we found a slower pattern of mitochondria development in human cortical neurons compared with the mouse, together with lower mitochondria metabolic activity, particularly oxidative phosphorylation. Stimulation of mitochondria metabolism in human neurons resulted in accelerated maturation, leading to excitable and complex cells weeks ahead of time. Our data identify mitochondria as important regulators of the pace of neuronal development underlying human-specific features of brain evolution.

neuroscience↗

bioRxiv2021

Decoding gene regulation in the fly brain

The Drosophila brain is a work horse in neuroscience. Single-cell transcriptome analysis 1-5, 3D morphological classification 6, and detailed EM mapping of the connectome 7-10 have revealed an immense diversity of neuronal and glial cell types that underlie the wide array of functional and behavioral traits in the fruit fly. The identities of these cell types are controlled by - still unknown - gene regulatory networks (GRNs), involving combinations of transcription factors that bind to genomic enhancers to regulate their target genes. To characterize the GRN for each cell type in the Drosophila brain, we profiled chromatin accessibility of 240,919 single cells spanning nine developmental timepoints, and integrated this data with single-cell transcriptomes. We identify more than 95,000 regulatory regions that are used in different neuronal cell types, of which around 70,000 are linked to specific developmental trajectories, involving neurogenesis, reprogramming and maturation. For 40 cell types, their uniquely accessible regions could be associated with their expressed transcription factors and downstream target genes, through a combination of motif discovery, network inference techniques, and deep learning. We illustrate how these "enhancer-GRNs" can be used to reveal enhancer architectures leading to a better understanding of neuronal regulatory diversity. Finally, our atlas of regulatory elements can be used to design genetic driver lines for specific cell types at specific timepoints, facilitating the characterization of brain cell types and the manipulation of brain function.

genomics↗

bioRxiv2021

Analysis of long and short enhancers in melanoma cell states

Understanding how enhancers drive cell type specificity and efficiently identifying them is essential for the development of innovative therapeutic strategies. In melanoma, the melanocytic (MEL) and the mesenchymal-like (MES) states present themselves with different responses to therapy, making the identification of specific enhancers highly relevant. Using massively parallel reporter assay (MPRA) in a panel of patient-derived melanoma lines (MM lines), we set to identify and decipher melanoma enhancers by first focusing on regions with state specific H3K27 acetylation close to differentially expressed genes. A more in-depth evaluation of those regions was then pursued by investigating the activity of ATAC-seq peaks found therein along with a full tiling of the acetylated regions with 190 bp sequences. Activity was observed in more than 60% of the selected regions and we were able to precisely locate the active regions within ATAC-seq peaks. Comparison of sequence content with activity, using the deep learning model DeepMEL2, revealed that AP-1 alone is responsible for the MES enhancer activity, while SOX and MITF both influence MEL enhancer activity with SOX being required to achieve high levels of activity. Overall, our MPRA assays shed light on the relationship between long and short sequences in terms of their sequence content, enhancer activity, and specificity as reporters across melanoma cell states.

genomics↗

bioRxiv2021

Fly Cell Atlas: a single-cell transcriptomic atlas of the adult fruit fly

The ability to obtain single cell transcriptomes for stable cell types and dynamic cell states is ushering in a new era for biology. We created the Tabula Drosophilae, a single cell atlas of the adult fruit fly which includes 580k cells from 15 individually dissected sexed tissues as well as the entire head and body. Over 100 researchers from the fly community contributed annotations to >250 distinct cell types across all tissues. We provide an in-depth analysis of cell type-related gene signatures and transcription factor markers, as well as sexual dimorphism, across the whole animal. Analysis of common cell types that are shared between tissues, such as blood and muscle cells, allowed the discovery of rare cell types and tissue-specific subtypes. This atlas provides a valuable resource for the entire Drosophila community and serves as a comprehensive reference to study genetic perturbations and disease models at single cell resolution.

genomics↗

bioRxiv2021

HyDrop: droplet-based scATAC-seq and scRNA-seq using dissolvable hydrogel beads

Single-cell RNA-seq and single-cell ATAC-seq technologies are being used extensively to create cell type atlases for a wide range of organisms, tissues, and disease processes. To increase the scale of these atlases, lower the cost, and allow for more specialized multi-ome assays, custom droplet microfluidics may provide complementary solutions to commercial setups. We developed HyDrop, a flexible and generic droplet microfluidic platform encompassing three protocols. The first protocol involves creating dissolvable hydrogel beads with custom oligos that can be released in the droplets. In the second protocol, we demonstrate the use of these beads for HyDrop-ATAC, a low-cost non-commercial scATAC-seq protocol in droplets. After validating HyDrop-ATAC, we applied it to flash-frozen mouse cortex and generated 8,502 high-quality single-cell chromatin accessibility profiles in a single run. In the third protocol, we adapt both the reaction chemistry and the capture sequence of the barcoded hydrogel bead to capture mRNA, and demonstrate a significant improvement in throughput and sensitivity compared to previous open-source droplet-based scRNA-seq assays (Drop-seq and inDrop). Similarly, we applied HyDrop-RNA to flash-frozen mouse cortex and generated 9,508 single-cell transcriptomes closely matching reference single-cell gene expression data. Finally, we leveraged HyDrop-RNAs high capture rate to analyse a small population of FAC-sorted neurons from the Drosophila brain, confirming the protocols applicability to low-input samples and small cells. HyDrop is currently capable of generating single-cell data in high throughput and at a reduced cost compared to commercial methods, and we envision that HyDrop can be further developed to be compatible with novel (multi-) omics protocols.

genomics↗

bioRxiv2020

Comparative analysis of antibody- and lipid-based multiplexing methods for single-cell RNA-seq

Multiplexing of samples in single-cell RNA-seq studies allows significant reduction of experimental costs, straightforward identification of doublets, increased cell throughput, and reduction of sample-specific batch effects. Recently published multiplexing techniques using oligo-conjugated antibodies or - lipids allow barcoding sample-specific cells, a process called hashing. Here, we compare the hashing performance of TotalSeq-A and -C antibodies, custom synthesized lipids and MULTI-seq lipid hashes in four cell lines, both for single-cell RNA-seq and single-nucleus RNA-seq. Hashing efficiency was evaluated using the intrinsic genetic variation of the cell lines. Benchmarking of different hashing strategies and computational pipelines indicates that correct demultiplexing can be achieved with both lipid- and antibody-hashed human cells and nuclei, with MULTISeqDemux as the preferred demultiplexing function and antibody-based hashing as the most efficient protocol on cells. Antibody hashing was further evaluated on clinical samples using PBMCs from healthy and SARS-CoV-2 infected patients, where we demonstrate a more affordable approach for large single-cell sequencing clinical studies, while simultaneously reducing batch effects.

genomics↗