Biology subjects

Martini, P.

Publications and source records attributed to Martini, P..

13 recordsLinked to original sources

bioRxiv2026

Towards automated gating of clinical flow cytometry data

Flow cytometry analysis is widespread practice in cell biology, immunology and hematology. Cell populations of interest are typically identified by consecutively examining the expression levels of antigen marker pairs. Since this manual gating process lacks standardization and is time-consuming, several machine learning (ML) methods for automated gating of flow cytometry data have been proposed in recent years. However, their translation into routine workflows has been limited. To address this, we developed the Python package FLAG-X ("flow cytometry automated gating toolbox"), which supports two novel workflows that integrate manual with ML-based gating, using labeled and unlabeled training data. We selected state-of-the-art ML methods developed for automated gating for inclusion in FLAG-X, based on their gating performance in comparison to manual expert annotations. FLAG-X provides a unified interface for top-performing methods and enables seamless integration with standard software for manual gating by exporting results as FCS files. To demonstrate its practical utility, we applied FLAG-X to representative cases from clinical practice. FLAG-X is available at https://anaconda.org/channels/bioconda/packages/flagx/overview. Author summaryIn our research, we work with flow cytometry data, a common laboratory technique to measure the expression of specific antigens in individual cells of a patient sample. In everyday clinical diagnostics or research, experts use dedicated software tools to "manually" inspect these data and often select a subset of cells for further analysis, e.g. B cells for Lymphoma subtype classification. However, this manual procedure, known as gating, can be time-consuming and is not standardized such that outcomes may vary based on the clinician carrying out the cell selection. Automated, machine learning-based methods developed to mitigate those problems are rarely used in routine clinical work. In this study, we set out to close this gap by developing novel workflows that allow clinicians to more easily integrate (semi-)automated approaches into their existing workflows. To do this, we we developed a software package that brings together top-performing methods, functionality to handle clinical flow cytometry data and is designed to be compatible with with existing tools for manual analysis. We evaluated our workflows and toolbox using realistic clinical scenarios and considered practical requirements for their use. By integrating automation into familiar workflows, we strive to make flow cytometry gating both faster and more consistent to support wider use of computational methods in clinical diagnostics.

bioinformatics↗

bioRxiv2025

SignifiKANTE: Efficient P-value computation for gene regulatory networks

Gene regulatory networks (GRNs) are graph-based representations of regulatory relationships between transcription factors and target genes. Various tools exist to infer GRNs from gene expression data, but since this task is computationally intensive, statistical significance estimates are often omitted. While permutation-based empirical P-value computation methods are relatively straightforward to implement, they are prohibitively expensive when applied to popular regression-based GRN inference methods and realistically sized datasets. To address this bottleneck, we developed SignifiKANTE. SignifiKANTE is based on the key insight that the background count distributions of groups of target genes may be highly similar, even if their expression vectors show distinct behavior. Relying on this insight, SignifiKANTE employs gene clustering based on the 1-Wasserstein distance to create a small, constant number of background distributions which enables the simultaneous computation of approximate empirical P-values for multiple target genes. This reduces runtime by orders of magnitudes (for some datasets, from several weeks to few hours), without compromising faithfulness of the obtained P-values. SignifiKANTE extends the popular GRN inference package Arboreto and is available as a Python package on GitHub (https://github.com/bionetslab/SignifiKANTE) and PyPI (https://pypi.org/project/signifikante/).

bioinformatics↗

bioRxiv2025

Identifying transcription factors driving cell differentiation

Cellular differentiation is a fundamental biological process at the core of development and growth in multicellular organisms. Understanding it at the level of transcriptomic regulation opens the possibility for novel biological insights, for steering cell development for therapeutic purposes, and for developing targeted therapies for diseases. While many methods exist that infer developmental trajectories from single-cell RNA sequencing data, only few can effectively determine which biological mechanisms drive differentiation along such trajectories. To close this gap, we developed SwitchTFI (switch transcription factor identification), a method to identify differentiation-driving regulatory mechanisms and the transcription factors (TFs) that play a key role in them. SwitchTFI infers a cell state transition-specific gene regulatory network (GRN) from a user-provided baseline GRN via decision stump learning and permutation-based significance tests. Key TFs are then extracted by ranking them according to their centralities in the transition GRN. We show that SwitchTFI can identify TFs known to be involved in pancreatic endocrinogenesis and in erythrocyte differentiation and that it outperforms competitor methods with respect to the functional coherence of the predicted driver TFs. SwitchTFI is available as a Python package at https://github.com/bionetslab/SwitchTFI.

bioinformatics↗

bioRxiv2025

Feeder-free culture of naive human pluripotent stem cells retaining embryonic, extraembryonic and blastoid generation potential

Conventional human pluripotent stem cells (hPSCs) are widely used to study early embryonic development, generate somatic cells, and model diseases, with differentiation potential aligned to a post-implantation epiblast identity. In the past decade, naive hPSCs, representing a pre-implantation stage, have been derived. Naive hPSCs efficiently differentiate towards embryonic and extraembryonic lineages such as trophectoderm, primitive endoderm, and extraembryonic mesoderm, and also self-organize into blastocyst-like structures called blastoids. However, their culture typically relies on mouse embryonic fibroblasts (MEFs), which are variable, resource-intensive, and can confound analyses. We report the long-term maintenance of naive hPSCs in a feeder-free, serum-coated system. We successfully expanded for up to 25 passages 8 different naive hPSCs lines across 5 laboratories. Growth rate, clonogenicity, and gene expression profiles on serum coating were comparable to MEF-based cultures, but serum coating eliminated fibroblast contamination. Naive hPSCs cultured on serum exhibited more efficient germ layer specification, retained trophectoderm potential and high blastoid formation efficiency. Exome sequencing revealed fewer mutations in serum-cultured cells, and mass spectrometry identified extracellular matrix proteins such as vitronectin, fibronectin, and collagens in the serum coating. Overall, serum coating offers a scalable, cost-effective and therefore widely applicable alternative for naive hPSC culture, maintaining developmental potential, reducing DNA mutations, and eliminating MEF-related confounding factors. We believe serum coating will expand the use of naive hPSCs to large-scale studies and facilitate the investigation of mechanistic insights into developmental and disease modelling.

cell biology↗

bioRxiv2023

The incidence of movement disorders increases with age and contrasts with subtle and limited neuroimaging abnormalities in argininosuccinic aciduria.

Argininosuccinate lyase is integral to the urea cycle detoxifying neurotoxic ammonia and the nitric oxide biosynthesis cycle. Inherited argininosuccinate lyase deficiency causes argininosuccinic aciduria (ASA), a rare disease with hyperammonaemia and nitric oxide deficiency. Patients present with developmental delay, epilepsy and movement disorders, associated with nitric oxide-mediated downregulation of central catecholamine biosynthesis. A neurodegenerative phenotype has been proposed in ASA. To better characterise this neurodegenerative phenotype in ASA, we conducted a retrospective study in six paediatric and adult metabolic centres in the UK in 2022. We identified 60 patients and specifically looked for movement disorders-related symptoms: movement disorders such as ataxia, tremor and dystonia, hypotonia and abnormal behaviour. We analysed neuroimaging with diffusion tensor imaging (DTI) magnetic resonance imaging (MRI) in an ASA patient with movement disorders. We assessed conventional and DTI MRI alongside single photon emission computer tomography (SPECT) with dopamine analogue radionuclide 123I-ioflupane, in Asl-deficient mice treated by hASL mRNA with normalised ureagenesis. Movement disorders in ASA appears in the 2nd and 3rd decades of life, becoming more prevalent with ageing and independent from the age of onset of hyperammonaemia. Neuroimaging can show abnormal DTI features affecting both grey and white matter, preferentially basal ganglia. ASA mouse model with normalised ureagenesis did not recapitulate these DTI findings and showed normal 123I-ioflupane SPECT and cerebral dopamine metabolomics. Altogether these findings support the pathophysiology of a late-onset movement disorders with functional central catecholamine dysregulation but without or limited neurodegeneration of dopaminergic neurons, making these symptoms amenable to targeted therapy. SynopsisMovement disorders-related symptoms in ASA appear in the 2nd and 3rd decades of life, becoming more prevalent with age and shows abnormal neuroimaging features of basal ganglia in ASA patients, not recapitulated in ASA mice.

genetics↗

bioRxiv2023

KLF7 is a general inducer of human pluripotency

Pluripotency is the capacity to give rise to all differentiated cells of the body and the germ line and is governed by a self-reinforcing network of transcription factors. The forced expression of only some of these factors enables the reprogramming of somatic cells to pluripotency. In murine cells, several kruppel-like factors (KLFs) have been identified as stabilisers and inducers of pluripotency. Human somatic cells are routinely reprogrammed by expression of KLF4 in combination with OCT4, SOX2 and cMYC (OSKM). An extensive transcriptome analysis revealed, however, that KLF4 is barely expressed in conventional human pluripotent stem cells (PSCs). Here we show that KLF7 is robustly expressed in conventional human PSCs and it allows transcription factor-mediated somatic reprogramming. Moreover, we find that KLF7 is highly expressed in naive PSCs and its forced expression in conventional hPSCs induces upregulation of naive markers and boosts efficiency of chemical resetting to naive PSCs, overall suggesting that KLF7 is a general human pluripotency factor and an inducer of pluripotency.

developmental biology↗

bioRxiv2023

Lipid nanoparticle-mediated delivery of mRNA into the mouse and human retina and other ocular tissues.

Structured Abstract PurposeLipid nanoparticles (LNPs) show promise in their ability to introduce mRNA to drive protein expression in specific cell types of the mammalian eye. Here, we examined the ability of mRNA encapsulated in lipid nanoparticles (LNPs) with two distinct formulations to drive gene expression in mouse and human retina and other ocular tissues. MethodsWe introduced mRNA carrying LNPs into two biological systems. Intravitreal injections were tested to deliver LNPs into the mouse eye. Human retinal pigment epithelium (RPE) and retinal explants were used to assess mRNA expression in human tissue. We analyzed specificity of expression using histology, immunofluorescence, and imaging. ResultsIn mice, mRNAs encoding GFP and ciliary neurotrophic factor (CNTF) were specifically expressed by Muller glia and retinal pigment epithelium (RPE). Acute inflammatory changes measured by microglia distribution (Iba-1) or interleukin-6 (IL-6) expression were not observed 6 hours post-injection. Human RPE also expressed high levels of GFP. Human retinal explants expressed GFP in cells with apical and basal processes consistent with Muller glia and in perivascular cells consistent with macrophages. ConclusionsWe demonstrated the ability to reliably transfect subpopulations of retinal cells in mice eye tissues in vivo and in human ocular tissues. Of significance, intravitreal injections were sufficient to transfect the RPE in mice. To our knowledge we demonstrate delivery of mRNA using LNPs in human ocular tissues for the first time. Translational RelevanceOcular gene-replacement therapies using non-viral vector methods are of interest as alternatives to adeno-associated virus (AAV) vectors. Our studies show that mRNA LNP delivery can be used to transfect retinal cells in both mouse and human tissues without inducing significant inflammation. This promising methodology could be used to transfect retinal cell lines, tissue explants, mice, or potentially as gene-replacement therapy in a clinical setting in the future.

molecular biology↗

bioRxiv2023

Ex vivo primary liver sections recapitulate disease phenotype and therapeutic rescue for liver monogenic diseases

In academic research and the pharmaceutical industry, in vitro single cell line cultures and in vivo animal models are considered as gold standards in modelling diseases and assessing therapeutic efficacy. However, both models have limitations, with incomplete reproduction of pathophysiological characteristics and absence of 3-dimensional architecture with cell lines or the use of live animals brings ethical considerations, limiting the experimental scale and design. The use of precision-cut tissue slices can bridge the gap between these mainstream models as this technique combines the advantages of studying all cell sub-types whilst preserving the tissue-matrix architecture, thereby closely mimicking a mini-organ. Here, we describe an optimised and easy-to-implement protocol for the culture of sections from mouse livers. We show that precision-cut liver sections can be a reliable model for recapitulating the biological phenotype of inherited metabolic diseases, exemplified by common urea cycle defects citrullinemia type 1 and argininosuccinic aciduria, caused by argininosuccinic synthase (ASS1) and argininosuccinic lyase (ASL) deficiencies respectively. Therapeutic response to gene therapy such as messenger RNA replacement delivered via lipid nanoparticles can be monitored, demonstrating that precision-cut liver sections can be used as a preclinical screening tool to assess therapeutic response and toxicity in monogenic liver diseases.

cell biology↗

bioRxiv2023

signifinder enables the identification of tumor cell states and cancer expression signatures in bulk, single-cell and spatial transcriptomic data

Over the last decade, many studies and some clinical trials have proposed gene expression signatures as a valuable tool for understanding cancer mechanisms, defining subtypes, monitoring patient prognosis, and therapy efficacy. However, technical and biological concerns about reproducibility have been raised. Technical reproducibility is a major concern: we currently lack a computational implementation of the proposed signatures, which would provide detailed signature definition and assure reproducibility, dissemination, and usability of the classifier. Another concern regards intratumor heterogeneity, which has never been addressed when studying these types of biomarkers using bulk transcriptomics. With the aim of providing a tool able to improve the reproducibility and usability of gene expression signatures, we propose signifinder, an R package that provides the infrastructure to collect, implement, and compare expression-based signatures from cancer literature. The included signatures cover a wide range of biological processes from metabolism and programmed cell death, to morphological changes, such as quantification of epithelial or mesenchymal-like status. Collected signatures can score tumor cell characteristics, such as the predicted response to therapy or the survival association, and can quantify microenvironmental information, including hypoxia and immune response activity. signifinder has been used to characterize tumor samples and to investigate intra-tumor heterogeneity, extending its application to single-cell and spatial transcriptomic data. Through these higher-resolution technologies, it has become increasingly apparent that the single-sample score assessment obtained by transcriptional signatures is conditioned by the phenotypic and genetic intratumor heterogeneity of tumor masses. Since the characteristics of the most abundant cell type or clone might not necessarily predict the properties of mixed populations, signature prediction efficacy is lowered, thus impeding effective clinical diagnostics. Through signifinder, we offer general principles for interpreting and comparing transcriptional signatures, as well as suggestions for additional signatures that would allow for more complete and robust data inferences. We consider signifinder a useful tool to pave the way for reproducibility and comparison of transcriptional signatures in oncology.

bioinformatics↗

bioRxiv2022

Spatial compartmentalization of signalling imparts source-specific functions on secreted factors

Efficient regeneration requires multiple cell types acting in a coordination. To better understand the intercellular networks involved and how they change when regeneration fails, we profiled the transcriptome of hematopoietic, stromal, myogenic, and endothelial cells over 14 days following acute muscle damage. A time-resolved computational model of interactions was generated, and VEGFA-driven endothelial engagement was identified as a key differentiating feature in models of successful and failed regeneration. In addition, it revealed that the majority of secreted signals, including VEGFA, are simultaneously produced by multiple cell types. To test whether the cellular source of a factor determines its function, we deleted VEGFA from two cell types residing in close proximity, stromal and myogenic progenitors. By comparing responses to different types of damage, we found that myogenic and stromal VEGFA have distinct functions in regeneration. This suggests that spatial compartmentalization of signaling plays a key role in intercellular communication networks. HighlightsO_LILigand-receptor signaling redundancy during skeletal muscle regeneration C_LIO_LIInflammatory cells, and muscle and fibro/adipogenic progenitors produce VEGFA C_LIO_LIVEGFA from muscle progenitors control their proliferation after muscle damage C_LIO_LIVEGFA from FAP controls angiogenesis only after ischemic damage C_LI eTOC blurbGroppa et al. performed a novel time-resolved bioinformatics analysis that revealed extensive ligand-receptor redundancy among the cell types contributing to skeletal muscle regeneration. They focused on one of these pathways, and showed that VEGFA from different cell types has distinct roles in regeneration.

cell biology↗

bioRxiv2022

Chemical conversion of human conventional Pluripotent Stem Cells to Trophoblast Stem Cells

In human embryos, naive pluripotent cells of the inner cell mass generate epiblast, primitive endoderm and Trophectoderm (TE) lineage, whence trophoblast cells derive. In vitro, naive pluripotent stem cells (PSCs) retain this potential and can generate trophoblast stem cells (TSCs), while conventional PSCs form amnion-like cells and lack the competence to generate TSCs. Transient histone deacetylase and MEK inhibitions with LIF stimulation can be used to chemically reset conventional to naive PSCs. Here we report that chemical resetting induced expression of both naive and TSC markers and of placental imprinted genes. A modified chemical resetting protocol allowed for the fast and efficient conversion of conventional PSCs into TSCs, entailing shutdown of pluripotency genes and full activation of the trophoblast master regulators, without induction of amnion markers. Chemical resetting generates a responsive intermediate state, in which conventional PSCs rapidly acquire competence to form TSCs without the need of stabilisation and expansion in a naive state. The efficiency and rapidity of our system will be useful for the study of cell fate transitions, and to generate models of placental disorders.

developmental biology↗

bioRxiv2020

Allelic expression analysis of Imprinted and X-linked genes from bulk and single-cell transcriptomes

Genomic imprinting and X chromosome inactivation (XCI) are two prototypical epigenetic mechanisms whereby a set of genes is expressed mono-allelically in order to fine-tune their expression levels. Defects in genomic imprinting have been observed in several neurodevelopmental disorders, in a wide range of tumours and in induced pluripotent stem cells (iPSCs). Single Nucleotide Variants (SNVs) are readily detectable by RNA-sequencing allowing determination of whether imprinted or X-linked genes are aberrantly expressed from both alleles, although standardised analysis methods are still missing. We have developed a tool, named BrewerIX, that provides comprehensive information about the allelic expression of a large, manually-curated set of imprinted and X-linked genes. BrewerIX does not require programming skills, runs on a standard personal computer, and can analyze both bulk and single-cell transcriptomes of human and mouse cells directly from raw sequencing data. BrewerIX confirmed previous observations regarding the bi-allelic expression of some imprinted genes in naive pluripotent cells and extended them to preimplantation embryos. BrewerIX identified also misregulated imprinted genes in breast cancer cells and in human organoids and identified new genes escaping XCI in human somatic cells. We believe BrewerIX will be useful for the study of genomic imprinting and XCI during development and reprogramming, and for detecting aberrations in cancer, iPSCs and organoids. Due to its ease of use to non-computational biologists, its implementation could become standard practice during sample assessment, thus raising robustness and reproducibility of future studies.

bioinformatics↗

bioRxiv2018

Lipid utilization in skeletal muscle cells is modulated in vitro and in vivo by specific miRNAs

Skeletal muscle is composed by different myofiber types that can preferentially use glycolysis or lipids for ATP production. How fuel preference is specified in these post-mitotic cells is unknown. Here we show that miRNAs are important players in defining the myofiber metabolic profile. mRNA and miRNA signatures of all myofiber types obtained at single cell level unveiled fiber-specific regulatory networks and identified two master miRNAs that coordinately control myofiber fuel preference and mitochondrial morphology. Our work provides a complete and integrated myofiber type-specific catalogue of genes and miRNAs expressed and establishes miR-27a-3p and miR-142-3p as key regulators of lipid utilization in skeletal muscle.\n\nHIGHLIGHTSO_LITranscriptional networking in single cells distinguished myofibers based on glycolytic or oxidative metabolism, regulated by specific miRNAs\nC_LIO_LImiR-27a-3p and -142-3p influence mitochondrial morphology\nC_LIO_LImiR-27a-3p improves lipid utilization and increases glycogen storage both in vitro and in vivo\nC_LIO_LImiR-142-3p reduces lipid utilization both in vitro and in vivo\nC_LI

genomics↗