Biology subjects

Mendoza-Parra, M. A.

Publications and source records attributed to Mendoza-Parra, M. A..

13 recordsLinked to original sources

bioRxiv2026

SCITRAM: a Single-cell Integrated transcription regulation modeler for predicting master transcription factors

Single-cell omics technologies have provided unprecedented access to molecular cell heterogeneity, revolutionizing our understanding of complex living systems. Although generating such type of data has become a streamlined process, data processing still relies on command-line driven tools, or commercial solutions. Furthermore, single-cell transcriptomics analysis is usually reduced to stratifying cells on the grounds of gene expression signatures, while deconvolving gene regulatory programs (and their associated master transcription factors) responsible for cell heterogeneity are not classically addressed with the available tools, or performed under different data processing platforms. Herein, we present SCITRAM (Single-Cell Integrated TRAnscription regulation Modeler), a user-friendly stand-alone computational solution for predicting master transcription factors from single-cell transcriptomics data. SCITRAM first reconstructs a primary gene regulatory network and subsequently uses this network as template to model transcriptional cascades driven by the in-silico activation of transcription factors identified within the system. We validated SCITRAM performance across a variety of cell fate transition events including T cell exhaustion during solid tumor treatment, lineage stratification during pancreatic endocrinogenesis, as well as nervous tissue formation in cerebral organoid models. Overall, SCITRAM provides an accessible and integrated platform for processing (large amounts of) single-cell transcriptomics data, enabling the investigation of transcriptional regulatory programs and their master transcription factors without requiring a command-line driven environment.

bioinformatics↗

bioRxiv2026

Kruppel-like factors KLF5 & KLF8 emerge as master transcriptional regulators of Alzheimers disease, as revealed on cell fate regulomes in human brain organoids

In addition to the well described beta-amyloid plates accumulation and tau hyper-phosphorylation, Alzheimers disease (AD) is accompanied by major changes in gene expression. Herein, we aimed at revealing master transcription factors (TFs) responsible for gene expression changes during AD progression. For this, we have used human brain organoids (BORGs) harbouring AD-related genetic mutations (APP-Swedish, PSEN1-M146V), which were traced over multiple time-points by bulk and spatially-resolved transcriptomics. By reconstructing gene regulatory networks (GRNs) that recapitulate BORG development, we have identified a subset of 110 AD-specific master TFs, and for 75 of them we retrieved KLF5 and/or KLF8 binding motifs within their promoters. Furthermore, 64 of the AD-specific TFs found in BORGs are significantly over-expressed on AD human patients samples, confirming the relevance of these factors beyond the context of the familial genetic mutations. Finally, we have demonstrated that this AD-specific regulome is at least partially controlled by the aberrant CREB3L2-ATF4 heterodimer previously described as being induced by the beta-amyloid plates deposition. Overall, these findings reconstitute the regulome behind the progression of AD and highlights key TFs as potential druggable targets for the treatment of the disease.

systems biology↗

bioRxiv2025

The Pioneer Transcription Factor Oct4 Differentially Co-opts Bcl11a and Bcl11b to Regulate Reprogramming to Pluripotency

Pioneer transcription factors (TFs) orchestrate development, reprogramming, and cancer. Yet, the molecular mechanisms by which they cooperate with endogenous TFs and chromatin to trigger cell fate conversions remain largely unknown. Here, we identified antagonistic functions in reprogramming to pluripotency for the two paralogous somatic zinc finger TFs Bcl11a and Bcl11b. We reveal that Bcl11a and Bcl11b are initially co-expressed in mouse embryonic fibroblasts and then segregate in cellular intermediates respectively prone or refractory to reprogramming, transdifferentiation, and oncogenic transformation. They exert opposite functions - with Bcl11a promoting and Bcl11b hindering - the efficacy of induced pluripotent stem cells generation. During reprogramming, we uncover that Bcl11b safeguards cellular identity by persistently binding to differentiation genes with Runx1 in refractory intermediates. In contrast, in reprogramming intermediates, Bcl11a interacts with Oct4 and is initially displaced from MEF enhancers. Bcl11a then binds transiently and contributes to activate the E3 ubiquitin ligase Pja1 that regulates Smad3, thus promoting mesenchymal-epithelial transition and constraining senescence. Collectively, our work unveils how the differential repurposing of paralogous TFs by Oct4 orchestrates reprogramming to pluripotency.

cell biology↗

bioRxiv2025

Enhancing spatial omics resolution by pseudo-interstitial pixels inference

MotivationSpatially resolved omics technologies are enhancing our understanding of tissues architecture. Despite major technological improvements, gaining in spatial resolution becomes experimentally expensive, while generating spatial landscapes at moderate resolution combined with computational methods for depixelating data represent a cost-effective strategy allowing to enlarge the number of experiments to be performed. ResultsWe have developed a computational strategy able to gain several-folds of resolution by inferring pseudo-interstitial pixels from their closest neighbors. This strategy has been validated in the context of public spatial transcriptomics data issued from melanoma, and human brain cortex tissue sections, by improving the identification of distinct tissue substructures. Furthermore, this methodology has been used for enhancing the resolution of consecutive sections collected from human brain organoids, as a way to demonstrate that a moderate resolution technology, combined with spatial depixelation processing allows to properly discern molecular tissue structures even in small tissues. Contactmmendoza@genoscope.cns.fr

bioinformatics↗

bioRxiv2024

Decoding transcriptional identity during Neuron-Astroglia Cell Fate driven by RAR-specific agonists

How cells respond to different signals leading to defined lineages is an open question to understand physiological differentiation leading to the formation of organs and tissues. Among the various morphogens, retinoic acid signaling, via the RXR/RAR nuclear receptors activation, is a key morphogen of nervous system development and brain homeostasis. Here we analyze gene expression in [~]80,000 cells covering 16 days of monolayer mouse stem cell differentiation driven by the pan-RAR agonist all-trans retinoic acid, the RAR agonist BMS753 or the activation of both RAR{beta} and RAR{gamma} receptors (BMS641+BMS961). Furthermore, we have elucidated the role of these retinoids for driving nervous tissue formation within 90 days of brain organoid cultures, by analyzing > 8,000 distinct spatial regions over 28 brain organoids. Despite a delayed progression in BMS641+BMS961, RAR-specific agonists led to a variety of neuronal subtypes, astrocytes and oligodendrocyte precursors. Spatially-resolved transcriptomics performed in organoids revealed spatially distinct RAR isotype expression leading to specialization signatures associated to matured tissues, including a variety of neuronal subtypes, retina-like tissue structure signatures and even the presence of microglia.

systems biology↗

bioRxiv2024

CREB3 gain of function variants protect against ALS

Amyotrophic lateral sclerosis (ALS) is a fatal and rapidly evolving neurodegenerative disease that arises from the loss of glutamatergic corticospinal neurons (CSN) and cholinergic motoneurons (MN). The disease is mostly sporadic, but genetics is expected to highly contribute to disease onset and progression. Genome wide association studies identified a few genetic disease modifiers, mostly associated with a negative outcome, and demonstrated that ALS is primarily a disease of excitatory glutamatergic neurons. Here, we reasoned that at least a subpart of genetic disease modifiers may directly modulate the molecular pathways selectively activated in vulnerable neurons as the disease progresses, and concentrated on CSN for their selective vulnerability and glutamatergic identity. We implemented comparative cross-species transcriptomics using snRNAseq data from postmortem motor cortex of ALS patients and controls, and longitudinal RNAseq data from anatomically defined CSN purified from the Sod1G86R mouse model of ALS. We report that disease vulnerable neuronal populations undergo ER stress and altered mRNA translation, and identify the transcription factor CREB3 and its regulatory network as a resilience marker of neuronal dysfunction in ALS. Using genetic and epidemiologic analyses we further identify the rare variant CREB3R119G (rs11538707) as a new disease modifier in ALS. Through gain of function, CREB3R119G decreases both the risk of developing ALS and the progression rate of ALS patients. This study reveals novel genetic variants that protect against ALS and highlights the benefice of combining transcriptomics and genetics to identify new disease modifiers and therapeutic targets.

genomics↗

bioRxiv2023

PSEN1-M146V and PSEN1-A246E mutations associated with Alzheimers disease impair proper microglia differentiation

Genetic variants associated with the late onset of Alzheimers disease (AD), were correlated with genes known to be expressed in microglia, suggesting for an AD-genetic component directly influencing microglia behavior. Instead, the role of the familial AD (fAD) genetic mutations was systematically studied from the angle of the Amyloid-Beta pathway; leaving their participation in microglia homeostasis unexplored. Here we demonstrate that two previously described fAD-related PSEN1 mutations directly impair proper microglia differentiation. While human induced pluripotent stem cells harboring the PSEN1-M146V mutation did not give rise to hematopoietic precursor (HPC) intermediate during microglia differentiation, a PSEN1-A246E mutant line managed to produce HPCs, but died within the first days of microglia differentiation. Detailed transcriptomics/epigenomics and functional assays revealed the setup of a pro-apoptotic program in the PSEN1-A246E mutant, which was circumvented when HPCs were grafted in brain organoids (BORGs). Microglia obtained in BORGs presented preferentially pro-inflammatory signatures, further supported by their correlation with recent data providing a detailed stratification of the various microglia populations within AD-patient samples. Overall, this study contributes to reconsider the influence of the previously identified familial mutations in the homeostasis of this immune component of the central nervous system.

neuroscience↗

bioRxiv2023

A 3-dimensional molecular cartography of human cerebral organoids revealed by double-barcoded spatial transcriptomics

Spatially-resolved transcriptomics is revolutionizing our understanding of complex tissues, but their current use for the exploration of a few sections is not representative of their 3-dimensional architecture. In this work we present a low-cost strategy for manufacturing molecularly double-barcoded DNA arrays, enabling large-scale spatially-resolved transcriptomics studies. We applied this technique to spatially resolve gene expression in several human brain organoids, including the reconstruction of a 3-dimensional view from multiple consecutive sections, revealing gene expression divergencies throughout the tissue.

systems biology↗

bioRxiv2022

A synergistic activation of RARb and RARg nuclear receptors restores cell-types specialization during stem cells differentiation by hijacking RARa-controlled program

How cells respond to different external cues to develop along defined cell lineages to form complex tissues is a major question in systems biology. Here, we investigated the potential of retinoic acid receptor (RARs)-selective synthetic agonists to activate the gene-regulatory programs driving cell specialization during nervous tissue formation from P19 stem cells. Specifically, we found that the synergistic activation of the RAR{beta} and RAR{gamma} by selective ligands (BMS641 or BMS961) induces cell maturation to specialized neuronal subtypes, as well as to astrocytes and oligodendrocyte precursors. Using RAR istoype knockout lines exposed to RAR-specific agonists, interrogated by global transcriptome landscaping and in silico modeling of transcription regulatory signal propagation, revealed major RAR-driven gene programs essential for optimal neuronal cell specialization, and hijacked by the synergistic activation of the RAR{beta} and RAR{gamma} receptors. Overall, this study provides a systems biology view of the gene programs accounting for the previously observed redundancy between RAR receptors, paving the way towards their potential use for directing cell specialization during nervous tissue formation.

molecular biology↗

bioRxiv2020

The comprehensive roadmaps of reprogramming and transformation unveiled antagonistic roles for bHLH transcription factors in the control of cellular plasticity

Coordinated changes of cellular identity and plasticity are critical for pluripotent reprogramming (PR) and malignant transformation (MT). However, the molecular circuitries orchestrating these modifications, as well as their degree of analogy during reprogramming and transformation, remain unknown. To address this question, we generated "repro-transformable" mice models and dissected comparatively the early events underpinning PR - mediated by Oct4, Sox2, Klf4, c-Myc - and MT - triggered by oncogenic Ras and c-Myc. Transcriptomic analyses allowed the identification of a unique set of markers - the cell surface glycoprotein Thy1 and the transcription factor (TF) Bcl11b - that are commonly downregulated during PR and MT and delineate cellular intermediates (CI) highly amenable to generate pluripotent or malignant derivatives. Comprehensive transcriptomic, epigenomic and functional analyses of different CI, prone or refractory to PR/MT, unveiled that cellular plasticity acquisition precedes the broad extinction of cellular identity. It also demonstrated the existence of specific and shared molecular features of PR and MT while ensuring the identification of broad-range regulators of cellular plasticity. As a proof-of-concept, we revealed that the basic helix-loop-helix (bHLH) class A TF Atoh8 constrains rodent and human iPS cells generation as well as MT and direct neuron conversion. Mechanistically, this TF hampers the reactivation of the pluripotent network during PR and limits the acquisition of phenotypic plasticity during MT. Furthermore, an integrated analysis of Atoh8 genome-wide binding, alongside the other bHLH TFs c-Myc, Ascl1 and MyoD promoting reprogramming/transdifferentiation, unveiled how Atoh8 constrains cellular plasticity by occupying a specific subset of MEF enhancers and by finetuning WNT signalling activity. Collectively, by deconvoluting the early steps of the reprogramming and transformation roadmaps, this integrated study uncoupled changes of cellular plasticity and identity to shed light on novel insights into reprogramming and cancer biology. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=161 SRC="FIGDIR/small/424606v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1718383org.highwire.dtl.DTLVardef@1714ab8org.highwire.dtl.DTLVardef@e0958borg.highwire.dtl.DTLVardef@7a0643_HPS_FORMAT_FIGEXP M_FIG C_FIG One-sentence summaryComparative roadmaps of cellular plasticity acquisition during pluripotent reprogramming and malignant transformation.

cell biology↗

bioRxiv2020

Inferring functionally relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes

Developments on spatial transcriptomics (ST) are providing means to interrogate organ/tissue architecture from the angle of the gene programs defining their molecular complexity. However, computational methods to analyze ST data under-exploits the spatial signature retrieved within the maps. Inspired by contextual pixel classification strategies applied to image analysis, we have developed MULTILAYER, allowing to stratify ST maps into functionally-relevant molecular substructures. For it, MULTILAYER applies agglomerative clustering strategies within contiguous locally-defined transcriptomes (herein defined as gene expression elements or Gexels), combined with community detection methods for graph partitioning. MULTILAYER has been evaluated over multiple public ST data, including developmental tissues but also tumor biopsies. Its performance has been challenged for the processing of high-resolution ST maps and it has been used for an enhanced comparison of multiple public tissue biopsies issued from a cancerous prostate. MULTILAYER provides a digital perspective for the analysis of spatially-resolved transcriptomes and anticipates the application of contextual gexel classification strategies for developing self-supervised molecular diagnostics solutions. Overall, the development of MULTILAYER anticipates the application of contextual gexel classification strategies for developing self-supervised molecular diagnostics solutions.

bioinformatics↗

bioRxiv2019

Patient-matched analysis identifies deregulated networks in prostate cancer to guide personalized therapeutic intervention

Prostate cancer (PrCa) is the second most common malignancy in men1. More than 50% of advanced prostate cancers display the TMPRSS2-ERG fusion2. Despite extensive cancer genome/transcriptome2-4 and phosphoproteome5 data, little is known about the impact of mutations and altered transcription on regulatory networks in the PrCa of individual patients. Using patient-matched normal and tumor samples, we established somatic variations and differential transcriptome profiles of primary ERG-positive prostate cancers. Integration of protein-protein interaction and gene-regulatory network databases6, 7 defined highly diverse patient-specific network alterations. We found that different components of a given regulatory pathway were altered by novel and known mutations and/or aberrant gene expression, including deregulated ERG targets, such that different sets of pathways were altered in each individual PrCa. In a given PrCa, several deregulated pathways share common factors, predicting synergistic effects on cancer progression. Our integrated analysis provides a paradigm to identify key deregulated factors within regulatory networks to guide personalized therapies.

genomics↗

bioRxiv2018

Highly dynamic chromatin interactions drive neurogenesis through gene regulatory networks

Lineage commitment is a fundamental process that enables the morphogenesis of multicellular organisms from a single pluripotent cell. While many genes involved in the commitment to specific lineages are known, the logic of their joint action is incompletely understood, and predicting the effects of genetic perturbations on lineage commitment is still challenging. Here, we devised a gene regulatory network analysis approach, GRN-loop, to identify key cis-regulatory DNA elements and transcription factors that drive lineage commitment. GRN-loop is based on signal propagation and combines transcription factor binding data with the temporal profiles of gene expression, chromatin state and 3D chromosomal architecture. Applying GRN-loop to a model of morphogen-induced early neural lineage commitment, we discovered a set of driver transcription factors and enhancers, some of them validated in recent data and others hitherto unknown. Our work provides the basis for an integrated understanding of neural lineage commitment, and demonstrates the potential of gene regulatory network analyses informed by 3D chromatin architecture to uncover the key genes and regulatory elements driving developmental processes.

molecular biology↗