Biology subjects

Mestdagh, P.

Publications and source records attributed to Mestdagh, P..

At least 19 recordsLinked to original sources

bioRxiv2025

MYC/MAX balance dictates cell progenitor fate by altering the HOX program in the Drosophila eye

The transcription factor MYC acts canonically as heterodimer with MAX to promote growth, proliferation, and metabolic adaptation. Although MYC and MAX relative levels are normally kept in balance under physiological conditions, those levels are often dysregulated in many human cancers where MYC is overexpressed and MAX can sometimes be reduced. How altered stoichiometry of MYC/MAX can impact on cell biology is not completely understood. Using the Drosophila eye amenable to genetic modifications, we demonstrate that the relative abundance of the fly MYC ortholog dMyc and its partner dMax affect progenitor cell fate. Elevating the dMyc/dMax ratio--through dMyc or human MYCN overexpression, dMax depletion, or combined manipulations--disrupts photoreceptor differentiation and ectopically induces the thoracic HOX gene Antennapedia within the eye disc. When such a ratio is driven to an extreme degree, the change in cell fate results in eye-to-wing transdetermination. Conversely, restoring dMax levels rescues these phenotypes, demonstrating that stoichiometry, not absolute MYC levels, shapes the response. Transcriptomic profiling reveals global repression of eye-specific regulators (e.g., eyegone and prospero) and ectopic activation of wing determinants (e.g., vestigial and nubbin) while genetic interactions identify the cephalic HOX gene Deformed as a key mediator modulating MYC-dependent identity changes. Our findings uncover MYC/MAX imbalance as a developmental switch that can rewire HOX expression and reprogram progenitor identity, suggesting a conserved mechanism underlying MYC-driven cellular plasticity in cancer.

developmental biology↗

bioRxiv2025

Widespread DNA off-targeting confounds studies of RNA chromatin occupancy

The importance of long noncoding RNA (lncRNA) functions is recognized across biological systems, but their modes of action remain poorly understood. One mechanism proposed to be particularly common is gene expression regulation via recruitment to specific genomic regions. Several high-throughput sequencing methods were developed for studying the genome-wide chromatin occupancy of lncRNAs, including ChIRP-seq, CHART-seq, and RAP-seq. These methods utilize biotin-labeled probes targeting the RNA of interest to isolate and recover the chromatin associated with it. Many of the datasets obtained with these methods contain thousands of binding sites, which appears to be in contradiction with the low abundance of the interrogated lncRNAs. We studied the chromatin interactome of NESPR lncRNA in cells with varying levels of endogenous expression and then performed a meta-analysis using dozens of RNA-chromatin interaction datasets in human and mouse cells. We demonstrate that thousands of regions reported to bind lncRNAs most likely arise from the spurious recovery of DNA elements, where the ends of the recovered DNA fragments exhibit partial complementarity with the probes used for the pulldown. In addition, crucial controls were rarely used in studies profiling RNA-chromatin interactions. Therefore, most chromatin regions reported as bound by trans-acting RNAs in recent studies in mammalian cells appear to be technical artifacts. We provide suggestions for assessing the quality of RNA-chromatin datasets and their improvement.

molecular biology↗

bioRxiv2025

Deconvoluting fiber type proportions from human skeletal muscle transcriptomics and proteomics data using FibeRtypeR

Muscle fibers are the dominant, multinucleated cell type in skeletal muscle. In humans, they can be classified as slow (type 1) and fast (type 2) fibers, traditionally based on distinct properties of their contractile machinery. Slow and fast fibers are characterized by shared and specific cellular complexities that are pivotal for their adaptive capacity to exercise or role in metabolic disease progression. In this era of omics research, there is a critical need to accurately infer muscle fiber type proportions from bulk tissue omics datasets, as single-fiber approaches are not feasible in large-scale or retrospective studies. Here we present FibeRtypeR, an easy-to-use web application to accurately estimate fiber type proportions from bulk transcriptomics and proteomics datasets: https://muscleapps.ugent.be. FibeRtypeR exploits transcriptomics and proteomics profiles of 1000 fiber-typed individual human skeletal muscle fibers as a reference dataset and is validated against paired immunohistochemical fiber type determinations in 160 muscle biopsies. We show that FibeRtypeR can be applied to public datasets, illustrating the application potential across a wide range of biological contexts such as aging, disease and exercise training. This new freely accessible computational tool will prove valuable to the skeletal muscle research community. Key pointsO_LIBulk muscle omics datasets lack fiber type specific information C_LIO_LIOur new tool, FibeRtypeR, leverages in-house collected single-fiber profiles allowing for accurate fiber type inference C_LIO_LIFibeRtypeR is methodologically robust across omics technologies and workflows C_LIO_LIWe host FibeRtypeR as an intuitive open-access Shiny app, applicable to new and publicly available transcriptomics and proteomics datasets C_LI

physiology↗

bioRxiv2025

Non-enzymatic isothermal strand displacement and amplification (NISDA) does not enable sensitive nucleic acid quantification.

Enzyme-free isothermal amplification methods offer a promising alternative to enzymatic assays for nucleic acid detection, particularly in low-resource settings. The nonenzymatic isothermal strand displacement and amplification (NISDA) assay was recently introduced as a highly sensitive, enzyme-free detection strategy. Here, we attempted to replicate its reported performance. Despite extensive testing, we failed to replicate the reported sensitivity and could only produce detectable signals at extremely high target concentrations ([≥]1 x 1011 copies/{micro}L). Our results highlight the critical importance of independent validation in the development of nonenzymatic diagnostic assays.

molecular biology↗

bioRxiv2025

Stress attenuation by the adrenergic-specific lncRNA NESPR prevents cell death in neuroblastoma cells

Neuroblastoma is a pediatric cancer of the sympathetic nervous system characterized by heterogeneous cell states that mirror normal differentiation trajectories. Each state is governed by a core regulatory transcriptional circuitry that reinforces cell identity through an autoregulatory feedforward loop. We identified the long non-coding RNA NESPR as specifically expressed in adrenergic neuroblastoma cells. NESPR expression correlates with high-risk neuroblastoma clinical parameters and poor patient survival. NESPR is located within an insulated gene neighborhood alongside PHOX2B, a master transcription factor of the adrenergic identity. NESPR depletion reduced cell proliferation and increased caspase activity in neuroblastoma cell lines, and NESPR knockout in a neuroblastoma zebrafish model led to reduced tumor penetrance. Subcellular localization revealed NESPR to be a cytosolic long non-coding RNA, suggesting a trans-regulatory function. RNA-sequencing following NESPR depletion revealed a shift from an adrenergic to a mesenchymal cell state, due to proteotoxic stress-induced molecular reprogramming. These findings suggest NESPR as a regulator of neuroblastoma cell identity with potential therapeutic opportunities in high-risk neuroblastoma cases.

genetics↗

bioRxiv2024

Intact messenger RNA exists in human blood plasma and urine, and their purified macromolecular compartments

It is generally assumed that extracellular long RNA molecules in biofluids are fragmented. Few studies have indirectly hinted at the existence of possibly functional, intact long RNA transcripts. In search for such RNA molecules, we developed a long-read full transcript sequencing workflow for low-input and low-quality samples. We applied our method to human blood plasma, urine, and their isolated macromolecular compartments, in parallel with total RNA sequencing. This approach enabled us to find intact messenger RNA molecules in human biofluids and macromolecular compartments. We showed that the full-length transcriptome of human urine and blood plasma differs, but we also reveal intact messenger RNA molecules shared between biofluids. In addition, we show that these intact molecules are differentially distributed over fractionated macromolecular compartments. This study provides a foundation for future extracellular RNA studies to elucidate the human biofluid full-length transcriptome.

molecular biology↗

bioRxiv2024

Coordinated regulation by lncRNAs results in tight lncRNA-target couplings

The determination of long non-coding RNA (lncRNA) function is a major challenge in RNA biology with applications to basic, translational, and medical research [1-7]. Our efforts to improve the accuracy of lncRNA-target inference identified lncRNAs that coordinately regulate both the transcriptional and post-transcriptional processing of their targets. Namely, these lncRNAs may regulate the transcription of their target and chaperone the resulting message until its translation, leading to tightly coupled lncRNA and target abundance. Our analysis suggested that hundreds of cancer genes are coordinately and tightly regulated by lncRNAs and that this unexplored regulatory paradigm may propagate the effects of non-coding alterations to effectively dysregulate gene expression programs. As a proof-of-principle we studied the regulation of DICER1 [8, 9]--a cancer gene that controls microRNA biogenesis--by the lncRNA ZFAS1, showing that ZFAS1 activates DICER1 transcription and blocks its post-transcriptional repression to phenomimic and regulate DICER1 and its target microRNAs.

bioinformatics↗

bioRxiv2023

Beyond Myosin Heavy Chains: Ribosomal Specialization Drives Human Skeletal Muscle Fiber Heterogeneity

Skeletal muscle is an inherently heterogenous tissue comprised primarily of myofibers, which are historically classified into three distinct fiber types in humans: one "slow" (type 1) and two "fast" (type 2A and type 2X), delineated by the expression of myosin heavy chain isoforms (MYHs). However, heterogeneity between and within traditional fiber types remains underexplored. Indeed, whether MYHs are the main classifiers of skeletal muscle fibers has not been examined in an unbiased manner. Through the development and application of novel transcriptomic and proteomic workflows, applied to 1050 and 1038 single muscle fibers from human vastus lateralis, respectively, we show that MYHs are not the only principal drivers of skeletal muscle fiber heterogeneity. Instead, metabolic, ribosomal, and cell junction proteins are a source of multi-dimensional variation between skeletal muscle fibers. Furthermore, whilst slow and fast fiber clusters can be identified, described by their contractile and metabolic profiles, our data suggests that type 2X fibers are not phenotypically distinct to other fast fibers at an omics level. Moreover, MYH-based classifications do not adequately describe the phenotype of skeletal muscle fibers in one of the most common genetic muscle diseases, nemaline myopathy, with fibers shifting towards a non-oxidative phenotype independently of MYH-based fiber type. We also characterize novel transcriptomic and proteomic features of slow and fast skeletal muscle fibers, including identifying several muscle fiber type-specific polypeptides, termed microproteins, encoded by transcripts annotated as non-coding RNA. Overall, our data indicates that skeletal muscle fiber heterogeneity is multi-dimensional with sources of variation beyond myosin heavy chain isoforms.

physiology↗

bioRxiv2023

The MIR-NAT MAPT-AS1 does not regulate Tau expression in human neurons

The MAPT gene encodes Tau protein, a member of the large family of microtubule-associated proteins. Tau forms large insoluble aggregates that are toxic to neurons in several neurological disorders and neurofibrillary Tau tangles represent a key pathological hallmark of Alzheimers disease (AD) and other tauopathies1,2. Several Tau-lowering strategies are being investigated as a potential treatment for AD but the mechanisms that regulate Tau expression at the transcriptional or translational level are not well understood3,4. Recently, Simone et al.5 reported the discovery of a new type of natural antisense transcripts called MIR-NATs (referring to Mammalian-wide Interspersed Repeats - Natural Antisense Transcripts). Simone and colleagues used MAPT-AS1, a MIR-NAT associated to the MAPT gene as an archetype of this new class of long non-coding RNAs. According to Simone et al., MAPT-AS1 represses Tau translation by competing for ribosomal RNA. We investigated the potential functions of MAPT-AS1 in neurons using the same gain- and loss-of-function experiments as described in the original report and expanded our analysis with complementary approaches. Our data do not support a role for MAPT-AS1 in regulating Tau expression in human neurons and urge to cautiously interpret the data provided by Simone et al.5.

neuroscience↗

bioRxiv2022

Effective methods for bulk RNA-Seq deconvolution using scnRNA-Seq transcriptomes

RNA profiling technologies at single-cell resolutions, including single-cell and single-nuclei RNA sequencing (scRNA-Seq and snRNA-Seq, scnRNA-Seq for short), can help characterize the composition of tissues and reveal cells that influence key functions in both healthy and disease tissues. However, the use of these technologies is operationally challenging because of high costs and stringent sample-collection requirements. Computational deconvolution methods that infer the composition of bulk-profiled samples using scnRNA-Seq-characterized cell types can broaden scnRNA-Seq applications, but their effectiveness remains controversial. We produced the first systematic evaluation of deconvolution methods on datasets with either known or scnRNA-Seq-estimated compositions. Our analyses revealed biases that are common to scnRNA-Seq 10X Genomics assays and illustrated the importance of accurate and properly controlled data preprocessing and method selection and optimization. Moreover, our results suggested that concurrent RNA-Seq and scnRNA-Seq profiles can help improve the accuracy of both scnRNA-Seq preprocessing and the deconvolution methods that employ them. Indeed, our proposed method, Single-cell RNA Quantity Informed Deconvolution (SQUID), combined RNA-Seq transformation and dampened weighted least-squares deconvolution approaches to consistently outperform other methods in predicting the composition of cell mixtures and tissue samples. Furthermore, our analysis suggested that only SQUID could identify outcomes-predictive cancer cell subclones in pediatric acute myeloid leukemia and neuroblastoma datasets, suggesting that deconvolution accuracy improvements are vital to enabling its applications in the life sciences.

systems biology↗

bioRxiv2022

Blocking unwanted sequences by target specific high-affinity binding oligonucleotides during transcriptome library preparation

RNA sequencing has become the gold standard for transcriptome analysis but has an inherent limitation of challenging quantification of low-abundant transcripts. In contrast to microarray technology, RNA sequencing reads are proportionally divided in function of transcript abundance. Therefore, low-abundant RNAs compete against highly abundant - and sometimes non-informative - RNA species. We developed an easy-to-use strategy based on high-affinity RNA-binding oligonucleotides to block reverse transcription and PCR amplification of specific RNA transcripts, thereby substantially reducing their abundance in the final sequencing library. To demonstrate the broad application potential of our method, we applied it to different transcripts and library preparation strategies, including YRNAs in small RNA sequencing of human blood plasma, mitochondrial rRNAs in both 3 end sequencing and long-read sequencing, and MALAT1 in single-cell 3 end sequencing. We demonstrate that the blocking strategy is highly efficient, reproducible, specific, and generally results in better transcriptome coverage and complexity. Furthermore, our method does not require modifications of the library preparation procedure apart from simply adding blocking oligonucleotides to the RT reaction and can thus be easily integrated into virtually any RNA sequencing library preparation protocol.

molecular biology↗

bioRxiv2021

A 3'-end capture sequencing method for high-throughput targeted gene expression profiling

Molecular phenotyping through shallow 3-end RNA-sequencing workflows is increasingly applied in the context of large-scale chemical or genetic perturbation screens to study disease biology or support drug discovery. While these workflows enable accurate quantification of the most abundant genes, they are less effective for applications that require expression profiling of low abundant transcripts, like long non-coding RNAs (lncRNAs), or selected gene panels. To tackle these issues, we describe a workflow combining 3-end library preparation with 3-end hybrid capture probes and shallow RNA-sequencing for cost-effective, targeted quantification of subsets of (low abundant) genes across hundreds to thousands of samples. To assess the performance of the method, we designed a capture probe set for more than 100 mRNA and lncRNA target genes and applied the workflow to a cohort of 360 samples. When compared to standard 3-end RNA-sequencing, 3-end capture sequencing resulted in a more than 100-fold enrichment of target gene abundance while conserving relative inter-gene and inter-sample abundances. 3-end RNA capture sequencing enables accurate targeted gene expression profiling at extremely shallow sequencing depth.

genomics↗

bioRxiv2021

mTOR inhibition enhances delivery and activity of antisense oligonucleotides in uveal melanoma cells

Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Due to a lack of effective treatments, patients with metastatic disease have a median survival time of 6-12 months. We recently demonstrated that the SAMMSON long non-coding RNA (lncRNA) is essential for uveal melanoma cell survival and that antisense oligonucleotide (ASO)-mediated silencing of SAMMSON impaired cell viability and tumor growth in vitro and in vivo. By screening a library of 2911 clinical stage compounds, we identified the mTOR inhibitor GDC-0349 to synergize with SAMMSON inhibition in UM. Mechanistic studies revealed that mTOR inhibition enhanced uptake and reduced lysosomal accumulation of lipid complexed SAMMSON ASOs, improving SAMMSON knockdown and further decreasing UM cell viability. We found mTOR inhibition to also enhance target knockdown in other cancer cell lines as well as normal cells when combined with lipid nanoparticle complexed or encapsulated ASOs or small interfering RNAs (siRNAs). Our results are relevant to nucleic acid treatment in general and highlight the potential of mTOR inhibition to enhance ASO and siRNA mediated target knockdown.

cancer biology↗

bioRxiv2021

Performance of RNA purification kits and blood collection tubes in the Extracellular RNA Quality Control (exRNAQC) study

The use of blood-based extracellular RNA (cell-free RNA; exRNA) as clinical biomarker requires the implementation of a validated procedure for sample collection, processing, and profiling. So far, no study has systematically addressed the pre-analytical variables affecting transcriptome analysis of exRNAs. In the exRNAQC study, we evaluated ten blood collection tubes, three time intervals between blood draw and downstream processing, and eight RNA purification methods using the supplier-specified minimum and maximum biofluid input volumes. The impact of these pre-analytics on deep transcriptome profiling of both small and messenger RNA from healthy donors plasma or serum was assessed for each pre-analytical variable separately and for interactions between a selected set of pre-analytics, resulting in 456 extracellular transcriptomes. Making use of 189 synthetic spike-in RNAs, the processing and analysis workflow was controlled. When comparing blood collection tubes, so-called preservation tubes do not stabilize exRNA well, and result in variable RNA concentration and sensitivity (i.e., the number of detected RNAs) over time, as well as compromised reproducibility. We also document large differences in RNA purification kit performance in terms of sensitivity, reproducibility, and observed transcriptome complexity, and demonstrate interactions between specific blood collection tubes, purification kits and time intervals. Our results are summarized in 11 performance metrics that enable an informed selection of the most optimal sample processing workflow for a given experiment. In conclusion, we put forward robust quality control metrics for exRNA quantification methods with validated standard operating procedures (SOPs), representing paramount groundwork for future exRNA-based precision medicine applications.

genomics↗

bioRxiv2021

Custom long non-coding RNA capture enhances detection sensitivity in different human sample types

Long non-coding RNAs (lncRNAs) are a heterogeneous group of transcripts that lack protein coding potential and display regulatory functions in various cellular processes. As a result of their cell- and cancer-specific expression patterns, lncRNAs have emerged as potential diagnostic and therapeutic targets. The accurate characterization of lncRNAs in bulk transcriptome data remains challenging due to their low abundance compared to protein coding genes. To tackle this issue, we describe a unique short-read custom lncRNA capture sequencing approach that relies on a comprehensive set of 565,878 capture probes for 49,372 human lncRNA genes. This custom lncRNA capture approach was evaluated on various sample types ranging from artificial high-quality RNA mixtures to more challenging formalin-fixed paraffin-embedded tissue and biofluid material. The custom enrichment approach allows the detection of a more diverse repertoire of lncRNAs, with better reproducibility and higher coverage compared to classic total RNA-sequencing.

genomics↗

bioRxiv2021

The long non-coding RNA SAMMSON is essential for uveal melanoma cell survival

PurposeLong non-coding RNAs (lncRNAs) can exhibit cell-type and cancer-type specific expression profiles, making them highly attractive as therapeutic targets. Pan-cancer RNA sequencing data revealed broad expression of the SAMMSON lncRNA in uveal melanoma (UM), the most common primary intraocular malignancy in adults. Currently, there are no effective treatments for UM patients with metastatic disease, resulting in a median survival time of 6-12 months. We aimed to investigate the therapeutic potential of SAMMSON inhibition in UM. Experimental DesignThe impact of antisense oligonucleotide (ASO)-mediated SAMMSON inhibition was evaluated in a panel of UM cell lines and patient derived xenograft (PDX) models. Cell proliferation and apoptosis were quantified in vitro and in vivo and complemented with molecular profiles established through RNA-sequencing. SAMMSON interaction partners were identified using ChIRP-MS. ResultsSAMMSON inhibition impaired the growth and viability of a genetically diverse panel of uveal melanoma cell lines. These effects were accompanied by an induction of apoptosis and were recapitulated in two uveal melanoma PDX models through subcutaneous ASO delivery. SAMMSON pulldown revealed several candidate interaction partners, including various proteins involved in mitochondrial translation. Consequently, inhibition of SAMMSON impaired global protein translation levels and mitochondrial function in uveal melanoma cells. ConclusionSAMMSON expression is essential for uveal melanoma cell survival. ASO-mediated silencing of SAMMSON may provide an effective treatment strategy to treat primary and metastatic uveal melanoma patients.

cancer biology↗

bioRxiv2020

Recurrent chromosomal imbalances provide selective advantage to human embryonic stem cells under enhanced replicative stress conditions

Human embryonic stem cells (hESCs) and embryonal tumors share a number of common features including a compromised G1/S checkpoint. Consequently, these rapidly dividing hESCs and cancer cells undergo elevated levels of replicative stress which is known to induce genomic instability causing chromosomal imbalances. In this context, it is of interest that long-term in vitro cultured hESCs exhibit a remarkable high incidence of segmental DNA copy number gains, some of which are also highly recurrent in certain malignancies such as 17q gain (17q+). The selective advantage of DNA copy number changes in these cells has been attributed to several underlying processes including enhanced proliferation. We hypothesized that these recurrent chromosomal imbalances become rapidly embedded in the cultured hESCs through a replicative stress driven Darwinian selection process. To this end, we compared the effect of hydroxyurea induced replicative stress versus normal growth conditions in an equally-mixed cell population of isogenic euploid and 17q+ hESCs. We could show that 17q+ hESCs rapidly overtook normal hESCs. Our data suggest that recurrent chromosomal segmental gains provide a proliferative advantage to hESCs under increased replicative stress, a process that may also explain the highly recurrent nature of certain imbalances in cancer.

cancer biology↗

bioRxiv2020

When DNA gets in the way in RNA-seq experiments, a sequel

Using a newly developed method dubbed SILVER-Seq--enabling extracellular RNA sequencing (exRNA-seq) directly from a small volume of human serum or plasma-- Yan et al. recently reported in Current Biology a potential exRNA biomarker for the early diagnosis of Alzheimers disease [1]. After the publication of the initial paper describing the SILVER-Seq method [2], we reported our concern regarding potential DNA contamination in their datasets [3]. Although the authors replied they were able to successfully treat RNA samples with DNase to avoid such contamination, they did not address our observations of the majority of reads without evidence of being derived from RNA, nor documented verified absence of DNA after DNase treatment [4]. To assess whether the newly data generated may suffer from DNA contamination, we downloaded the publicly available sequencing data and evaluated two quality control metrics (i.e., fraction of exonic and splice reads), which were not reported in the paper. We found that both quality metrics were much lower than expected for RNA-seq data (6.28% exonic and 0.478% splice reads), in line with our previous findings on the first SILVER-Seq paper. These observations suggest the data and results presented by Yan et al. are affected by DNA contamination, an issue that may be inherent to the SILVER-Seq technology.

molecular biology↗