Biology subjects

Salvador-Martinez, I.

Publications and source records attributed to Salvador-Martinez, I..

6 recordsLinked to original sources

bioRxiv2024

STAMP: Single-Cell Transcriptomics Analysis and Multimodal Profiling through Imaging

We introduce Single-Cell Transcriptomics Analysis and Multimodal Profiling (STAMP), a scalable profiling approach of individual cells. Leveraging transcriptomics and proteomics imaging platforms, STAMP eliminates sequencing costs, to enable single-cell genomics from hundreds to millions of cells at an unprecedented low cost. Stamping cells in suspension onto imaging slides, STAMP supports single-modal (RNA or protein) and multimodal (RNA and protein) profiling and flexible, ultra-high-throughput formats. STAMP allows the analysis of a single or multiple samples within the same experiment, enhancing experimental flexibility, throughput and scale. We tested STAMP with diverse sample types, including peripheral blood mononuclear cells (PBMCs), dissociated cancer cells and differentiated embryonic stem cell cultures, as well as whole cells and nuclei. Combining RNA and protein profiling, we applied immuno-phenotyping of millions of blood cells simultaneously. We also used STAMP to identify ultra-rare cell populations, simulating clinical applications to identify circulating tumor cells (CTCs). Performing in vitro differentiation studies, we further showed its potential for large-scale perturbation studies. Together, STAMP establishes a new standard for cost-effective, scalable single-cell analysis. Without the need for sequencing, STAMP makes high-resolution profiling more affordable and accessible. Designed to meet the needs of research labs, diagnostic cores and pharmaceutical companies, STAMP holds the promise to transform our capacity to map human biology, diagnose diseases and drug discovery.

genomics↗

bioRxiv2023

Quantifying Adaptive Evolution of the Human Immune Cell Landscape

The human immune system is under constant evolutionary pressure, primarily through its role as first line of defence against pathogens. Accordingly, population genomics studies have shown that immune-related genes have a high rate of adaptive evolution. These studies, however, are mainly based on protein-coding genes without cellular context, leaving the adaptive role of cell types and states uncharted. Inferring the rate of protein-coding genes adaptation in developing and adult immune cells at cellular resolution, we found cell types from both the lymphoid and myeloid compartments to harbour significantly increased adaptation rates. Specific cell states, such as foetal Pre-Pro B cells and adult T resident memory CD8+ cells show highly elevated rates of adaptation. We further analysed activated cell states, specifically, iPSC-derived macrophages responding to various challenges, including pro- and anti-inflammatory cytokines or bacterial and viral infections, the latter simulating the evolutionary arms race between humans and pathogens. Here, we found positive selection to be concentrated in early immune responses, suggesting benefits for the host to adapt to early stages of infection to control pathogen numbers and spread. Together, our study reveals spatio-temporal and functional biases in human immune populations with evidence of rapid adaptive evolution and provides a retrospect of forces that shaped the complexity, architecture, and function of the human body.

immunology↗

bioRxiv2023

The cellular landscape of the endochondral bone highlights its multipotent and immunomodulatory features during the transition to extrauterine life

The cellular complexity of the endochondral bone underlies its essential and pleiotropic roles during organismal life. While the adult bone has received significant attention, we still lack a deep understanding of the perinatal bone cellulome. Here, we have profiled the full composition of the murine endochondral bone at the single-cell level during the transition from fetal to newborn life and in comparison to the adult tissue, with particular emphasis on the mesenchymal compartment. The perinatal bone contains different fibroblastic clusters with blastema-like characteristics in organizing and supporting skeletogenesis, angiogenesis, and hematopoiesis. Our data also suggests dynamic inter- and intra-compartment interactions as well as a bone marrow milieu that seems prone to anti-inflammation, which we hypothesize is necessary to ensure the proper program of lymphopoiesis and the establishment of central and peripheral tolerance in early life. Our study provides an integrative roadmap for the future design of genetic and cellular functional assays to validate cellular interactions and lineage relationships within the perinatal bone.

cell biology↗

bioRxiv2020

CeLaVi: An Interactive Cell Lineage Visualisation Tool

Recent innovations in genetics and imaging are providing the means to reconstruct cell lineages, either by tracking cell divisions using live microscopy, or by deducing the history of cells using molecular recorders. A cell lineage on its own, however, is simply a description of cell divisions as branching events. A major goal of current research is to integrate this description of cell relationships with information about the spatial distribution and identities of the cells those divisions produce. Visualising, interpreting and exploring these complex data in an intuitive manner requires the development of new tools. Here we present CeLaVi, a web-based visualisation tool that allows users to navigate and interact with a representation of cell lineages, whilst simultaneously visualising the spatial distribution, identities and properties of cells. CeLaVis principal functions include the ability to explore and manipulate the cell lineage tree; to visualise the spatial distribution of cell clones at different depths of the tree; to colour cells in the 3D viewer based on lineage relationships; to visualise various cell qualities on the 3D viewer (e.g. gene expression, cell type, tissue layer) and to annotate selected cells/clones. All these capabilities are demonstrated with four different example data sets. CeLaVi is available at http://www.celavi.pro.

developmental biology↗

bioRxiv2019

Computational discovery of hidden breaks in 28S rRNA across eukaryotes and consequences for RNA Integrity Numbers

In some eukaryotes, a hidden break has been described in which the 28S ribosomal RNA molecule is cleaved into two subparts. The break is common in protostome animals (arthropods, molluscs, annelids etc.) but a break has also been reported in some vertebrates and non-metazoan eukaryotes. We present a new computational approach to determine the presence of the hidden break in 28S rRNAs using mapping of RNA-Seq data. We find a homologous break is present across protostomes although has been lost in a small number of taxa. We show that rare breaks in vertebrate 28S rRNAs are not homologous to the protostome break. A break is found in just 4 out of 331 species of non-animal eukaryotes studied and three of these are located in the same position as the protostome break suggesting a striking instance of convergent evolution. RNA Integrity Numbers (RIN) rely on intact 28s rRNA and will be consistently underestimated in the great majority of animal species with a break.

bioinformatics↗

bioRxiv2018

Is it possible to reconstruct an accurate cell lineage using CRISPR recorders?

Cell lineages provide the framework for understanding how multicellular organisms are built and how cell fates are decided during development. Describing cell lineages in most organisms is challenging, given the number of cells involved; even a fruit fly larva has ~50,000 cells and a small mammal has more than 1 billion cells. Recently, the idea of using CRISPR to induce mutations during development as heritable markers for lineage reconstruction has been proposed and trialled by several groups. While an attractive idea, its practical value depends on the accuracy of the cell lineages that can be generated by this method. Here, we use computer simulations to estimate the performance of this approach under different conditions. Our simulations incorporate empirical data on CRISPR-induced mutation frequencies in Drosophila. We show significant impacts from multiple biological and technical parameters - variable cell division rates, skewed mutational outcomes, target dropouts and different mutation sequencing strategies. Our approach reveals the limitations of recently published CRISPR recorders, and indicates how future implementations can be optimised to produce accurate cell lineages.

developmental biology↗