Biology subjects

Salmen, F.

Publications and source records attributed to Salmen, F..

7 recordsLinked to original sources

bioRxiv2025

WNT inhibition primes the transcriptional landscape of mesoderm to initiate a phased ventricular cardiomyocyte specification programme

Background and AimsCardiac reprogramming holds promise for treating ischemic heart diseases and advancing personalised medicine, but current approaches do not yet reliably generate human functional, homogeneous cardiomyocyte cultures. This limited success likely reflects our incomplete understanding of hierarchical transcriptional programmes guiding cardiomyocyte specification. Here, we modelled cardiomyocyte differentiation aiming to uncover gene regulatory networks (GRNs) guiding early human ventricular cardiomyocyte development. Our study focused on defining how inhibition of WNT signalling remodels the transcriptional landscape underlying human cardiomyocyte differentiation, since both in vivo cardiac development and in vitro cardiomyocyte differentiation protocols require WNT inhibition. MethodsWe modelled left ventricular cardiomyocyte differentiation from human pluripotent stem cells and experimentally manipulated WNT signalling to uncover transcriptional responses using single-cell RNA sequencing. Bioinformatics analysis defined cell identities, reconstructed differentiation trajectories, and inferred WNT inhibition-dependent gene expression and regulatory networks driving cardiomyocyte specification. ResultsWe found that WNT inhibition (WNTi) decisively redirects mesoderm cells towards a cardiomyocyte progenitor fate, expanding their numbers while limiting alternative trajectories. GRN inference revealed both WNTi-dependent and -independent programmes and a hierarchical cascade of transcription factors driving the mesoderm-to-cardiomyocyte progenitor transition. Notably, MEIS2 emerged as a central WNTi-independent regulator, while WNTi-responsive networks featured early (ISL1, PBX3, TBX5 and KLF1) and late (MEF2-related genes, GATA-related genes, PBX1, CREM, FOXP1 and NKX3-1) factors. Mesodermal GRNs were primed for cardiomyocyte specification in WNTi-treated cultures but, in the absence of WNTi, mesodermal GRNs remained ambiguous, activating ISL1 and PBX3 but failing to establish cardiomyocyte commitment and subsequent differentiation into contractile cells. ConclusionThis work provides the first comprehensive dissection of WNTi-dependent and -independent regulatory hierarchies guiding human ventricular cardiomyocyte specification and highlights new transcriptional players which could improve cardiac reprogramming efficiency and fidelity. Translational PerspectiveDeciphering the transcriptional programmes that drive early cardiomyocyte specification has clear translational potential for regenerative therapies and cardiac reprogramming. By modelling left ventricular cardiomyocyte differentiation from hPSCs, our study highlights how inhibition of WNT signalling promotes ventricular cardiomyocyte progenitor commitment while restricting alternative fates. The discovery of both WNTi-dependent and -independent transcriptional activators, including some not previously linked to cardiomyocyte development, provides new insights for improving the efficiency and fidelity of direct cardiac reprogramming. Importantly, these TF candidates may also guide the development of targeted therapies for ischemic heart disease and inform personalised approaches for repairing and regenerating damaged myocardium.

developmental biology↗

bioRxiv2024

T-ChIC: multi-omic detection of histone modifications and full-length transcriptomes in the same single cell

Epigenetic mechanisms, including histone modifications, are key regulators of transcription and influence cellular differentiation. To uncover the interplay between histone modifications and transcription, we developed T-ChIC (Transcriptome + Chromatin ImmunoCleavage), which detects full-length transcripts and histone modifications in the same single cell. We applied T-ChIC to gastruloids, an in vitro model containing cell types derived from all three germ layers. During gastruloid development we observed a switch in transcription start site usage from multiple regions marked by H3K4me3 to one marked start site per gene. H3K27me3 coverage transitions from global marking of non-transcribed regions towards localised marking of repressive regions. Upon lineage commitment, bivalent regions are sequentially resolved towards a germ layer-specific state, where endoderm retains a high abundance of H3K27me3 while ectoderm displays a widespread loss. Together, we propose a model for a cell-intrinsic epigenetic timer, which ensures sequential perceptiveness of pluripotent cells to transcriptional activation of germ layer-specific genes.

genomics↗

bioRxiv2021

Droplet-based Single-cell Total RNA-seq Reveals Differential Non-Coding Expression and Splicing Patterns during Mouse Development

In recent years, single-cell transcriptome sequencing has revolutionized biology, allowing for the unbiased characterization of cellular subpopulations. However, most methods amplify the termini of polyadenylated transcripts capturing only a small fraction of the total cellular transcriptome. This precludes the detection of many long non-coding, short non-coding and non-polyadenylated protein-coding transcripts. Additionally, most workflows do not sequence the full transcript hindering the analysis of alternative splicing. We therefore developed VASA-seq to detect the total transcriptome in single cells. VASA-seq is compatible with both plate-based formats and droplet microfluidics. We applied VASA-seq to over 30,000 single cells in the developing mouse embryo during gastrulation and early organogenesis. The dynamics of the total single-cell transcriptome result in the discovery of novel cell type markers many based on non-coding RNA, an in vivo cell cycle analysis and an improved RNA velocity characterization. Moreover, it provides the first comprehensive analysis of alternative splicing during mammalian development.

molecular biology↗

bioRxiv2021

Identification of the stress granule transcriptome via RNA-editing in single cells and in vivo

Stress granules are phase separated assemblies formed around mRNAs whose identities remain elusive. The techniques available to identify the RNA content of stress granules rely on their physical purification, and are therefore not suitable for single cells and tissues displaying cell heterogeneity. Here, we adapted TRIBE (Target of RNA-binding proteins Identified by Editing) to detect stress granule RNAs by fusing a stress granule RNA-binding protein (FMR1) to the catalytic domain of an RNA-editing enzyme (ADAR). RNAs colocalized with this fusion are edited, producing mutations that are detectable by sequencing. We first optimized the expression of this fusion protein so that RNA editing preferentially occurs in stress granules. We then show that this purification-free method can reliably identify stress granule RNAs in bulk and single S2 cells, and in Drosophila tissues, such as 398 neuronal stress granule mRNAs encoding ATP binding, cell cycle and transcription factors. This new method opens the possibility to identify the RNA content of stress granules as well other RNA based assemblies in single cells derived from tissues.

cell biology↗

bioRxiv2020

Spatial Deconvolution of HER2-positive Breast Tumors Reveals Novel Intercellular Relationships

In the past decades, transcriptomic studies have revolutionized cancer treatment and diagnosis. However, tumor sequencing strategies typically result in loss of spatial information, critical to understand cell interactions and their functional relevance. To address this, we investigate spatial gene expression in HER2-positive breast tumors using Spatial Transcriptomics technology. We show that expression-based clustering enables data-driven tumor annotation and assessment of intra-and interpatient heterogeneity; from which we discover shared gene signatures for immune and tumor processes. We integrate and spatially map tumor-associated types from single cell data to find: segregated epithelial cells, interactions between B and T-cells and myeloid cells, co-localization of macrophage and T-cell subsets. A model is constructed to infer presence of tertiary lymphoid structures, applicable across tissue types and technical platforms. Taken together, we combine different data modalities to define novel interactions between tumor-infiltrating cells in breast cancer and provide tools generalizing across tissues and diseases.

cancer biology↗

bioRxiv2019

High-density spatial transcriptomics arrays for in situ tissue profiling

Tissue function relies on the precise spatial organization of cells characterized by distinct molecular profiles. Single-cell RNA-Seq captures molecular profiles but not spatial organization. Conversely, spatial profiling assays either lack global transcriptome information or are not at the single-cell level. Here, we develop High-Density Spatial Transcriptomics (HDST), a method for RNA-seq at high spatial resolution. Spatially barcoded reverse transcription oligonucleotides are coupled to beads that are then randomly deposited in individual wells on a slide. The barcoded beads are decoded and coupled to a specific spatial address. We then capture and spatially in situ label RNA from the same histological tissue sections placed on the bead array slide. HDST recovers hundreds of thousands of transcript-coupled barcodes per experiment at 2 m resolution. We demonstrate HDST in the mouse brain, use it to resolve spatial expression patterns and cell types, and show how to combine it with histological stains to relate expression patterns to tissue architecture and anatomy. HDST opens the way to 2D spatial analysis of tissues at high resolution.

genomics↗

bioRxiv2018

Multidimensional transcriptomics provides detailed information about immune cell distribution and identity in HER2+ breast tumors

The comprehensive analysis of tumor tissue heterogeneity is crucial for determining specific disease states and establishing suitable treatment regimes. Here, we analyze tumor tissue sections from ten patients diagnosed with HER2+ breast cancer. We obtain and analyze multidimensional, genome-wide transcriptomics data to resolve spatial immune cell distribution and identity within the tissue sections. Furthermore, we determine the extent of immune cell infiltration in different regions of the tumor tissue, including invasive cancer regions. We combine cross-sectioning and computational alignment to build three-dimensional images of the transcriptional landscape of the tumor and its microenvironment. The three-dimensional data clearly demonstrates the heterogeneous nature of tumor-immune interactions and reveal interpatient differences in immune cell infiltration patterns. Our study shows the potential for an improved stratification and description of the tumor-immune interplay, which is likely to be essential in treatment decisions.

cancer biology↗