Biology subjects

Nimo, J.

Publications and source records attributed to Nimo, J..

6 recordsLinked to original sources

bioRxiv2025

OpenDVP: An experimental and computational framework for community-empowered deep visual proteomics

Deep visual proteomics (DVP) is an emerging approach for cell type-specific and spatially resolved proteomics. However, its broad adoption has been constrained by the lack of an open-source end-to-end workflow in a community-driven ecosystem. Here, we introduce openDVP, an experimental and computational framework for simplifying and democratizing DVP. OpenDVP integrates open-source software for image analysis, including MCMICRO, QuPath, and Napari, and uses the scverse data formats AnnData and SpatialData for multi-omics integration. It offers two workflows: a fast-track pipeline requiring no image analysis expertise and an artificial intelligence (AI)-powered pipeline with recent algorithms for image pre-processing, segmentation, and spatial analysis. We demonstrate openDVPs versatility in three archival tissue studies, profiling human placenta, early-stage lung cancer, and locally relapsed breast cancer. In each study, our framework provided insights into health and disease states by integrating spatial single-cell phenotypes with exploratory proteomic data. Finally, we introduce deep proteomic profiling of cellular neighborhoods as a scalable approach to accelerate spatial discovery proteomics across biological systems.

systems biology↗

bioRxiv2025

Maternal smoking in early pregnancy disrupts placental function through syncytiotrophoblast and macrophage dysregulation.

Smoking in pregnancy is the leading avoidable cause of gestational morbidity and mortality, causally linked to fetal growth restriction (FGR). The placenta, functional interface between mother and fetus is essential for healthy fetal development. For the first time, we studied cell type-resolved smoking effects on placental development at high molecular resolution using single-nucleus RNA sequencing and deep visual proteomics of matched tissues. We validated our findings through an independent cohort and in-vitro cigarette smoke exposure to primary human trophoblast cells. Our results show placental macrophages (Hofbauer cells; HBC) and the syncytiotrophoblast (STB) barrier are most affected by smoking, with dysregulation of cell-cell adhesion, extracellular matrix organization, and stress phenotype. STBs show moderate compositional increases in smokers and in-silico trophoblast differentiation modelling indicates a preferential shift towards the STB lineage in this group. The trophoblast displays a large upregulation of pro-angiogenic effectors, increases in xenobiotic detoxification, reduced mitochondrial function, and vastly altered transmembrane transport. These molecular changes affect placental development with important consequences for fetal growth. We provide insight into placental dysfunction contributing to FGR early in pregnancy, before clinical symptoms appear. We anticipate this data to advance diagnostics and therapies to improve FGR outcomes.

systems biology↗

bioRxiv2024

Spatial omics of acute myocardial infarction reveals a novel mode of immune cell infiltration

Myocardial infarction (MI) continues to be a leading cause of death worldwide. Even though it is well-established that the complex interplay between different cell types determines the overall healing response after MI, the precise changes in the tissue architecture are still poorly understood. Here we generated an integrative cellular map of the acute phase after murine MI using a combination of imaging-based transcriptomics (Molecular Cartography) and antibody-based highly multiplexed imaging (Sequential Immunofluorescence), which enabled us to evaluate cell-type compositions and changes at subcellular resolution over time. One striking finding of these analyses was the identification of a novel mode of leukocyte accumulation to the infarcted heart via the endocardium - the inner layer of the heart. To investigate the underlying mechanisms driving this previously unknown infiltration route, we performed unbiased spatial proteomic analysis using Deep Visual Proteomics (DVP). When comparing endocardial cells of homeostatic hearts and infarcted hearts, DVP identified von Willebrand Factor (vWF) as an upregulated mediator of inflammation 24 hours post-MI. To further explore the immune mediating capabilities of vWF and its effect on tissue repair, we performed functional blocking of vWF during acute murine MI. This resulted in a reduced amount of infiltration by CCR2+ monocytes and worse cardiac function post-MI. Our study provides the first spatial map of acute murine MI with subcellular resolution and subsequently discovers a novel route of immune infiltration. Furthermore, we identified vWF as a critical immune mediating agent for endocardial immune cell infiltration.

systems biology↗

bioRxiv2023

A framework for ultra-low input spatial tissue proteomics

Spatial tissue proteomics combining microscopy-based cell phenotyping with ultra-sensitive mass spectrometry (MS)-based proteomics is an emerging and powerful concept for the study of cell function and heterogeneity in health and disease. However, optimized workflows that preserve morphological information for image-based phenotype discovery and maximize proteome coverage of few or even single cells from laser microdissected archival tissue, are currently lacking. Here, we report a robust and scalable workflow for the proteomic analysis of ultra-low input formalin-fixed, paraffin-embedded (FFPE) material. Benchmarking in the murine liver resulted in up to 2,000 quantified proteins from single hepatocyte contours and nearly 5,000 proteins from 50-cell regions with high quantitative reproducibility. Applied to human tonsil, we profiled 146 microregions including spatially defined T and B lymphocyte niches and quantified cell type specific markers, cytokines, immune cell regulators and transcription factors. These rich data also highlighted proteome dynamics in spatially defined zones of activated germinal centers, illuminating sites undergoing active B-cell proliferation and somatic hypermutation. Our results demonstrate the power of spatially-resolved proteomics for tissue phenotyping by integrating high-content imaging, laser microdissection, and ultra-sensitive mass spectrometry. This approach has broad implications for a wide range of biomedical applications, including early disease profiling, drug target discovery and biomarker research.

systems biology↗

bioRxiv2023

High-resolution molecular atlas of a lung tumor in 3D

Cells live and interact in three-dimensional (3D) cellular neighborhoods. However, histology and spatial omics methods mostly focus on 2D tissue sections. Here we present a 3D spatial atlas of a routine clinical sample, an aggressive human lung carcinoma, by combining in situ quantification of 960 cancer-related genes across [~]340,000 cells with measurements of tissue-mechanical components. 3D cellular neighborhoods subdivided the tumor microenvironment into tumor, stromal, and immune multicellular niches. Interestingly, pseudotime analysis suggested that pro-invasive epithelial-to-mesenchymal transition (EMT), detected in stroma-infiltrating tumor cells, already occurred in one region at the tumor surface. There, myofibroblasts and macrophages specifically co-localized with pre-invasive tumor cells and their multicellular molecular signature identified patients with shorter survival. Moreover, cytotoxic T-cells did not infiltrate this niche but colocalized with inhibitory dendritic and regulatory T cells. Importantly, systematic scoring of cell-cell interactions in 3D neighborhoods highlighted niche-specific signaling networks accompanying tumor invasion and immune escape. Compared to 2D, 3D neighborhoods improved the characterization of immune niches by identifying dendritic niches, capturing the 3D extension of T-cell niches and boosting the quantification of niche-specific cell-cell interactions, including druggable immune checkpoints. We believe that 3D communication analyses can improve the design of clinical studies investigating personalized, combination immuno-oncology therapies.

systems biology↗

bioRxiv2022

Disturbed trophoblast transition links preeclampsia progression from placenta to the maternal syndrome

Pre-eclampsia (PE) is a syndrome that affects multiple organ systems and is the most severe hypertensive disorder in pregnancy. It frequently leads to preterm delivery, maternal and fetal morbidity and mortality and life-long complications1. We currently lack efficient screening tools2, 3 and early therapies4, 5 to address PE. To investigate the early stages of early onset PE, and identify candidate markers and pathways, we performed spatio-temporal multi-omics profiling of human PE placentae and healthy controls and validated targets in early gestation in a longitudinal clinical cohort. We used a single-nuclei RNA-seq approach combined with spatial proteo- and transcriptomics and mechanistic in vitro signalling analyses to bridge the gap from late pregnancy disease to early pregnancy pathomechanisms. We discovered a key disruption in villous trophoblast differentiation, which is driven by the increase of transcriptional coactivator p300, that ultimately ends with a senescence-associated secretory phenotype (SASP) of trophoblasts. We found a significant increase in the senescence marker activin A in preeclamptic maternal serum in early gestation, before the development of clinical symptoms, indicating a translation of the placental syndrome to the maternal side. Our work describes a new disease progression, starting with a disturbed transition in villous trophoblast differentiation. Our study identifies potential pathophysiology-relevant biomarkers for the early diagnosis of the disease as well as possible targets for interventions, which would be crucial steps toward protecting the mother and child from gestational mortality and morbidity and an increased risk of cardiovascular disease later in life.

systems biology↗