Biology subjects

Zanini, F.

Publications and source records attributed to Zanini, F..

At least 19 recordsLinked to original sources

bioRxiv2026

SCIMETAR-seq tracks immunophenotype, demethylation, mutations, and transcriptomes in single cells undergoing HMA therapy

5-azacytidine improves haematopoiesis and delays leukaemic progression in myelodysplastic neoplasms, but responses vary and are complicated by clonal mosaicism and heterogenous demethylation. Using a novel single-cell pipeline ("SCIMETAR-seq"), we found 5-azacytidine induced clonally distinct differentiation responses, with nuclear DNA demethylation occurring primarily in cycling progenitors. Despite the absence of significant nuclear DNA demethylation, quiescent stem cells underwent transcriptional remodelling in vivo, accompanied by 5-azacytidine-induced C*G-to-G*C mutations in mitochondria.

cancer biology↗

bioRxiv2026

Social caste switching triggers emergence of novel cellular identities in Zootermopsis termites

A hallmark of eusocial insects is the specialisation of individuals into castes that share the same genome but present distinct phenotypes. Caste switching can affect gene expression1,2, but can it give rise to entirely new cell types? Here, we generated single-cell transcriptomic atlases of a king, a queen, a soldier, and six workers of the termite Zootermopsis nevadensis to understand whether caste differentiation is accompanied by the emergence of novel cellular identities. Out of 24 annotated termite cell types, 18 of which mirrored homologous Drosophila cell types, one was unique for king, one was almost entirely restricted to the queen, and none were exclusive to nonreproductives. Instead, nonreproductive termites possessed more muscle and neuronal cells and less fat cells than reproductives. Caste-linked transcriptional signatures were detected in most cell types, including rare genes expressed with dual specificity for both cell type and caste. Despite the emergence of new cell types in reproductives, expression of hormones, immune genes, carbohydrate-active enzymes3, and rapidly adapting genes4 were only weakly altered by caste. These findings show that cellular differentiation can be induced anew in adult organisms without dysregulating their key physiologic pathways.

evolutionary biology↗

bioRxiv2026

Single cell multiomics reveal clonal and functional dynamics of MDS stem/progenitor cells during hypomethylating therapy

Progressive somatic mutations in hematopoietic stem cells (HSCs) drive the development of myelodysplastic neoplasms (MDS). Hypomethylating agents such as azacitidine (AZA) can improve blood counts and reduce blasts, although responses are rarely durable. Determinants of AZA response are complex and incompletely understood, although accumulating evidence suggests that epigenetic rewiring of mutated HSCs underlies improved hematopoietic output. Using single cell multiomics on longitudinal bone marrow samples, we show that AZA responsiveness involves expansion of cells with transcriptomic profiles shared with hematopoietic stem and progenitor cells (HSPCs) from healthy donors. These regenerating cells are depleted of copy number variations and of TP53 mutations. We also identify patient-restricted cell populations, some of which recede through transcriptional restoration or AZA cytotoxicity, and others which expand, regardless of initial clinical response, and dominate at progression. Individual patients carried multiple patient-restricted populations which had unique surface immunophenotypes and were genetically distinct. Strikingly, sorted cells from in vivo progression clones that were AZA-refractive in patients regained AZA-sensitivity when cultured in vitro, suggesting that lack of AZA response at the cellular level can be modulated by cell-extrinsic factors in vivo. Overall, we find that AZA response involves partial hematopoietic regeneration via functional differentiation of mutated, but not cytogenetically abnormal HSPCs, and that persistence of AZA-refractive sub-populations contributes to eventual disease progression.

cancer biology↗

bioRxiv2025

Single Cell RNA Sequencing Reveals Gene Expression Continuums Along the Spatial Hierarchy of the Pulmonary Circulation

BackgroundThe lung vasculature is comprised of a series of branching vessels extending from the main pulmonary artery to the alveolar capillaries, then back to the pulmonary veins. Lung endothelial cells (EC) exist along this continuum, exposed to gradients of shear stress, oxygen tension and pressure. Single cell RNA sequencing (scRNA-seq) has identified lung EC subsets, but many aspects of the vascular continuum, including vessel size and capillary polarity remain undefined from transcriptomic data. MethodsWe created an endothelial-enriched scRNA-seq dataset from the P3 mouse lung. Using diffusion pseudotime across all lung EC, we developed an analytical framework to delineate transcriptomic gradients and assign vessel-size scores to categorize individual endothelial cells (EC) along the vascular continuum. We confirmed size-related gene expression patterns with fluorescence in situ hybridization. ResultsWe categorized capillary 1, arterial and venous EC along two gradients: arterio-venous zonation and vessel size. This approach distinguished large arteries from arterioles, large veins from venules, and revealed arterio-venous polarity within the capillaries. Our data recapitulated previously established zonally defined cell signaling axes, such as high Cxcl12-Cxcr4 signaling in arterioles. We also identified unique cellular communication occurring in large versus small arteries and veins, and localized injury-induced venous EC proliferation to vessels of specific size. This analytical framework was successfully applied to several published mouse and human datasets across different stages of lung development. ConclusionsThese findings provide a comprehensive transcriptional map of EC across the pulmonary vascular tree, enabling assignment of each individual cell to vessels with defined size and position. This framework offers spatial inferences and novel mechanistic insights from scRNA-seq data sets that may elucidate therapeutic targets to treat pulmonary vascular diseases affecting specific vascular segments. We speculate that similar frameworks could be applied to tissues outside the lung.

cell biology↗

bioRxiv2025

Deep exploration of transcriptomic cellular identities over evolutionary time

Whole-organism cell atlases have painted the cellular landscapes of individual species; however, comparing cells across the tree of life remains challenging. Most cross-species analyses are restricted to orthologous genes, while the complexity of atlas data constitutes an access barrier for many researchers. We developed a computational strategy to accelerate the exploration of cellular identities at scale. We integrated 30 atlases detailing the expression of 861,013 genes by 2,645,508 animal and plant cells and trained a universal model of cellular transcriptomes to track cell type diversification over evolutionary times. Transfer learning achieved cell type annotation of a de novo atlas of the insect Cryptocercus punctulatus within minutes. We devised a generative artificial intelligence approach to construct virtual cell atlases from genome sequences and used it to synthesise an atlas of the Tasmanian tiger, extinct since 1936. We then reduced the footprint of extant atlases by 100 times while retaining crucial information and developed interfaces to answer dozens of query types within seconds, boosting atlas exploration by [~]50,000 times.

evolutionary biology↗

bioRxiv2024

Integrating microscopy and transcriptomics from individual uncultured eukaryotic plankton

Eukaryotic plankton comprises organisms as diverse as diatoms and pelagic larvae, covering a wide spectrum of shapes, molecular compositions, and ecological functions. Plankton research is often approached using either optical methods, especially for taxonomic purposes, or genomics, which excels at describing the biochemistry of microbial communities. This technological dichotomy hampers efforts to link the morpho-optical properties of each species with its genetic and biomolecular makeup, leading to fragmented information and limited reproducibility. Methods to simultaneously acquire multimodal, i.e. optical and genetic, information on planktonic organisms would provide a connection between organismal appearance and function, improve taxonomic prediction, and strengthen ecological analysis. Here we present Ukiyo-e-Seq, an approach to generate paired optical and transcriptomic data from individual eukaryotic plankton. We performed Ukiyo-e-Seq on 66 microscopic organisms from Coogee, NSW, Australia and assembled transcriptomic contigs using a merge-split strategy. While overall phylogenetic heterogeneity spanned hundreds of taxa, diversity in individual wells was low, enabling accurate classification of both microbial plankton and marine larvae. We then combined Ukiyo-e-Seq with AlphaFold 3, a protein language model, and could confidently infer (i) the joint structure and interactions of 34 photosynthesis proteins from a single Chaetoceros diatom, and (ii) the cellular and developmental functions of novel proteins highly expressed in one trout larva. In summary, Ukiyo-e-Seq is a precise tool to connect morphological and genetic information of eukaryotic plankton.

microbiology↗

bioRxiv2024

PIP4K2C inhibition reverses autophagic flux impairment induced by SARS-CoV-2

In search for broad-spectrum antivirals, we discovered a small molecule inhibitor, RMC-113, that potently suppresses the replication of multiple RNA viruses including SARS-CoV-2 in human lung organoids. We demonstrated selective dual inhibition of the lipid kinases PIP4K2C and PIKfyve by RMC-113 and target engagement by its clickable analog. Advanced lipidomics revealed alteration of SARS-CoV-2-induced phosphoinositide signature by RMC-113 and linked its antiviral effect with functional PIP4K2C and PIKfyve inhibition. We discovered PIP4K2Cs roles in SARS-CoV-2 entry, RNA replication, and assembly/egress, validating it as a druggable antiviral target. Integrating proteomics, single-cell transcriptomics, and functional assays revealed that PIP4K2C binds SARS-CoV-2 nonstructural protein 6 and regulates virus-induced impairment of autophagic flux. Reversing this autophagic flux impairment is a mechanism of antiviral action of RMC-113. These findings reveal virus-induced autophagy regulation via PIP4K2C, an understudied kinase, and propose dual inhibition of PIP4K2C and PIKfyve as a candidate strategy to combat emerging viruses.

microbiology↗

bioRxiv2024

Macropinocytosis mediates resistance to loss of glutamine transport in triple-negative breast cancer

Triple-negative breast cancer (TNBC) relies on glutamine uptake by the transporter ASCT2 to sustain their unique glutamine metabolism and growth. Despite previous data showing cell growth inhibition after ASCT2 knockdown, ASCT2 CRISPR knockout was well-tolerated by breast cancer cell lines. Despite the loss of a glutamine transporter and low rate of glutamine uptake, intracellular glutamine steady state levels were higher in ASCT2 knockout compared to control TNBC cells. Proteomics data revealed upregulation of macropinocytosis, reduction in glutamine efflux and glutamine synthesis in ASCT2 knockout cells. Loss of ASCT2 in TNBC cell line HCC1806 induced a 5-10-fold increase in macropinocytosis across 5 separate ASCT2 knockout clones, compared to a modest 2-fold increase in the shRNA ASCT2 knockdown. By comparison, ASCT2 knockout impaired cell proliferation in a non-macropinocytic breast cancer cell line, HCC1569. These data suggest that macropinocytosis provides a novel resistance mechanism to strategies targeting glutamine uptake alone. Despite this adaptation, TNBC cells continue to rely on glutamine metabolism for their growth, which suggests therapeutic targeting may need to focus on downstream glutamine metabolism pathways.

cancer biology↗

bioRxiv2024

Integration of hyperspectral imaging and transcriptomics from individual cells with HyperSeq

Microscopy and omics are complementary approaches to probe the molecular state of cells in health and disease, combining granularity with scalability. While important advances have been achieved over the last decade in each area, integrating both imaging- and sequencing-based assays on the same cell has proven challenging. In this study, a new approach called HyperSeq that combines hyperspectral autofluorescence imaging with transcriptomics on the same cell is demonstrated. HyperSeq was applied to Michigan Cancer Foundation 7 (MCF-7) breast cancer cells and identified a subpopulation of cells exhibiting bright autofluorescence rings at the plasma membrane in optical channel 13 ({lambda}ex = 431 nm,{lambda} em = 594 nm). Correlating the presence of a ring with the gene expression in the same cell indicated that ringed cells are more likely to express hallmark genes of apoptosis and less likely to express genes associated with ATP production. Further, correlation of cell morphology with gene expression suggested that multiple members of the spliceosome were downregulated in larger MCF-7 cells. Multiple genes were evenly expressed across cell sizes but also exhibited higher usage of specific exons in larger or smaller cells. Finally, correlation between gene expression and fluorescence within the spectral range of Nicotinamide adenine dinucleotide hydrogen (NADH) provided insight into the metabolic states of MCF-7 cells. These observations provided a link between the cells optical spectrum and its internal molecular state, demonstrating the utility of HyperSeq to study cell biology at single cell resolution by integrating spectral, morphological and transcriptomic analyses into a single, streamlined workflow.

bioinformatics↗

bioRxiv2024

Structure, motion, and multiscale search of traveling networks

Network models are widely applied to describe connectivity and flow in diverse systems. In contrast, the fact that many connected systems move through space as the result of dynamic restructuring has received little attention. Therefore, we introduce the concept of traveling networks, and we analyze a tree-based model where the leaves are stochastically manipulated to grow, branch, and retract. We derive how these restructuring rates determine key attributes of network structure and motion, enabling a compact understanding of higher-level network behaviors such as multiscale search. These networks self-organize to the critical point between exponential growth and decay, allowing them to detect and respond to environmental signals with high sensitivity. Finally, we demonstrate how the traveling network concept applies to real-world systems, such as slime molds, the actin cytoskeleton, and human organizations, exemplifying how restructuring rules and rates in general can select for versatile search strategies in real or abstract spaces.

biophysics↗

bioRxiv2024

Fast and lightweight cell atlas approximations across organs and organisms

Omic technologies at single-cell resolution are reshaping our understanding of cellular diversity. The generation of cell atlases that capture the cellular composition of an entire individual is progressing rapidly. However, the science of organising and extracting information from these atlases is still in its infancy and for many biomedical researchers atlas exploration remains challenging. Here, we leveraged extensive experience in single-cell data analytics to pinpoint three major accessibility barriers to cell atlases, related to (i) programming skill or language, (ii) scalability, and (iii) dissemination standards. To help researchers overcome these barriers, we developed cell atlas approximations, a computational approach enabling the analysis of cell atlases across organs and organisms without programming skills, rapidly, and at scale. The web interface at https://atlasapprox.org facilitates the exploration of cell atlases in 19 species across the tree of life through a chatbot driven by frontend natural language processing. In parallel, application programming interfaces streamline data access for computational researchers and include specialised packages for Python, R, JavaScript, and Bash. Supported queries include marker gene identification, cross-organ comparisons, cell embeddings, gene sequences, searches for similar features, and bidirectional zoom between cell types and cell states. Most queries are answered in less than 1.5 seconds thanks to lossy data compression algorithms based on cell annotations and similarity graphs. Compared to traditional cell atlas analysis, this approach can reduce data size by more than 100 times and accelerate workflows by up to 100,000 times. Atlas approximations aim to make the exploration of cell atlases accessible to anyone in the world.

cell biology↗

bioRxiv2022

Global and cell type-specific immunological hallmarks of severe dengue progression

Severe dengue (SD) is a major cause of morbidity and mortality impacting approximately 5 million of the 400 million people infected with dengue virus (DENV) annually. To define DENV target cells and immunological hallmarks of SD progression in childrens blood, we integrated virus-inclusive single cell RNA-Seq 2 (viscRNA-Seq 2) with functional assays. Beyond myeloid cells, in natural infection, B cells harbor replicating DENV capable of infecting permissive cells. Alterations in cell type abundance, gene and protein expression and secretion, and cell-cell communications point towards increased migration and inflammation in SD progressors (SDp). Concurrently, antigen presenting cells from SDp demonstrate intact uptake, yet impaired interferon responses and antigen presentation, in part DENV-modulated. Increased activation, regulation, and exhaustion of effector responses and expansion of HLA-DR-expressing, possibly compensatory, adaptive-like NK cells also characterize SDp. These findings reveal DENV target cells in the human blood and provide insight into SD pathogenesis beyond antibody-mediated enhancement.

immunology↗

bioRxiv2022

Single cell genotyping of matched bone marrow and peripheral blood cells in treatment naive and AZA-treated MDS and CMML

Progressively acquired somatic mutations in hematopoietic stem cells are central to pathogenesis in myelodysplastic syndromes (MDS) and chronic myelomonocytic leukemia (CMML). They can lead to proliferative advantages, impaired differentiation and progressive cytopenias. MDS or CMML patients with high-risk disease are treated with hypomethylating agents including 5-azacytidine (AZA). Clinical improvement does not require eradication of mutated cells and may be related to improved differentiation capacity of mutated hematopoietic stem and progenitor cells (HSPCs). However, the contribution of mutated HSPCs to steadystate hematopoiesis in MDS and CMML is unclear. To address this, we characterised the somatic mutations of individual stem, progenitor (common myeloid progenitor, granulocyte monocyte progenitor, megakaryocyte erythroid progenitor), and matched circulating (monocyte, neutrophil, naive B cell) haematopoietic cells in treatment naive and AZA-treated MDS and CMML via high-throughput single cell genotyping. The mutational burden was similar across multiple hematopoietic cell types, and even the most mutated stem and progenitor clones maintained their capacity to differentiate to mature myeloid and, in some cases, lymphoid cell types in vivo. Our data show that even highly mutated HSPCs contribute significantly to circulating blood cells in MDS and CMML, prior to and following AZA treatment. Key points* Highly mutated HSPCs contribute significantly to circulating blood cells in MDS and CMML, prior to and following AZA treatment. * The mutational burden in matched bone marrow and peripheral blood cells in MDS and CMML was similar throughout myelopoiesis.

cancer biology↗

bioRxiv2021

Disentangling single-cell omics representation with a power spectral density-based feature extraction

Emerging single-cell technologies provide high-resolution measurements of distinct cellular modalities opening new avenues for generating detailed cellular atlases of many and diverse tissues. The high dimensionality, sparsity, and inaccuracy of single cell sequencing measurements, however, can obscure discriminatory information, mask cellular subtype variations and complicate downstream analyses which can limit our understanding of cell function and tissue heterogeneity. Here, we present a novel pre-processing method (scPSD) inspired by power spectral density analysis that enhances the accuracy for cell subtype separation from large-scale single-cell omics data. We comprehensively benchmarked our method on a wide range of single-cell RNA-sequencing datasets and showed that scPSD pre-processing, while being fast and scalable, significantly reduces data complexity, enhances cell-type separation, and enables rare cell identification. Additionally, we applied scPSD to transcriptomics and chromatin accessibility cell atlases and demonstrated its capacity to discriminate over 100 cell types across the whole organism and across different modalities of single-cell omics data.

bioinformatics↗

bioRxiv2021

Hepatitis C Virus Infects and Perturbs Liver Stem Cells

Hepatitis C virus (HCV) is the leading cause of death from liver disease. How HCV infection causes lasting liver damage and increases cancer risk beyond viral clearance remains unclear. We identify bipotent liver stem cells as novel targets for HCV infection, and their erroneous differentiation as the potential cause of impaired liver regeneration and cancer development. We show 3D organoids generated from liver stem cells from actively HCV-infected individuals carry replicating virus and maintain low-grade infection over months. Organoids can be infected with a primary HCV isolate. Virus-inclusive single-cell RNA-sequencing uncovered extensive transcriptional reprogramming in HCV+ cells supporting hepatocytic differentiation, cancer stem cell development and viral replication while stem cell proliferation and interferon signaling are disrupted. Our data adds a pathogenesis factor - infection of liver stem cells - to the biology of HCV infection that explains persistent liver damage and enhanced cancer risk through an altered stem cell state.

microbiology↗

bioRxiv2021

Mesoderm-Derived PDGFRA+ Cells Regulate the Emergence of Hematopoietic Stem Cells in the Dorsal Aorta

Mouse hematopoietic stem cells (HSCs) first emerge at embryonic day 10.5 (E10.5) on the ventral surface of the dorsal aorta, by endothelial-to-hematopoietic transition (EHT). We investigated whether cells with mesenchymal stem cell-like activity, which provide an essential niche for long-term HSCs (LT-HSCs) in the bone marrow, reside in the aorta- gonad-mesonephros (AGM) and contribute to the structural development of the dorsal aorta and EHT. Using transgenic mice, we demonstrate a lineage hierarchy for AGM stromal cells and traced the E10.5/E11.5 aortic endothelium and HSCs to mesoderm derived (Mesp1) PDGFRA+ stromal cells (Mesp1der PSCs). Mesp1der PSCs dominate the sub-endothelial and ventral stroma in the E10.5-E11.5 AGM but by E13.5 were replaced by neural crest (Wnt1) derived PDGFRA+ stromal cells (Wnt1der PSCs). Co-aggregating non-hemogenic embryonic and adult endothelial cells with Mesp1der PSCs but not with Wnt1der PSCs resulted in activation of a hematopoietic transcriptional program in endothelial cells accompanied by EHT and generation of LT-HSCs. Dose-dependent inhibition of PDGFRA signalling or BMP, WNT, NOTCH signalling interrupted this reprogramming event. This partnership between endothelial cells and AGM Mesp1der PSCs could potentially be harnessed to manufacture LT-HSCs from endothelium.

developmental biology↗

bioRxiv2021

Progressive Increases in Mesenchymal Cell Diversity Modulate Lung Development and are Attenuated by Hyperoxia

Lung mesenchymal cells play an essential role in development and at birth, as the lung moves from a fluid-filled to an oxygen-rich environment with a stable gas-liquid interface. The molecular details and cellular changes accompanying this highly coordinated process remain incompletely understood. Therefore, we performed single cell transcriptomics and in-situ imaging of the developing lung in both health and disease to characterize the spectrum of mesenchymal cell states prior to the onset of air-breathing life through late alveolarization to gain insight into their role in orchestrating tissue maturation. We found that cell type diversity in the mesenchymal compartment increases rapidly during normal development but is delayed during neonatal exposure to 80% O2 hyperoxia, a model for bronchopulmonary dysplasia. This study identifies the molecular transitions between populations of mesenchymal cells at discrete developmental time points across fibroblast, smooth muscle, and mural compartments and elucidates the global and cell type-specific effects of neonatal hyperoxia, including the emergence of Acta1+ cells which are absent in normoxic neonatal lungs. These granular insights hold the promise of targeted treatment for neonatal lung disease, which remains a major cause of infant morbidity and mortality across the world.

developmental biology↗

bioRxiv2021

Phenotypic diversity and sensitivity to injury of the pulmonary endothelium during a period of rapid postnatal growth

At birth, the lung is still immature, heightening susceptibility to injury but enhancing regenerative capacity. Angiogenesis drives postnatal lung development. Therefore, we profiled the transcriptional ontogeny and sensitivity to injury of pulmonary endothelial cells (EC) during early postnatal life. Although subtype speciation was evident at birth, immature lung EC exhibited transcriptomes distinct from mature counterparts, which progressed dynamically over time. Gradual, temporal changes in aerocyte capillary EC (CAP2), contrasted with more marked alterations in general capillary EC (CAP1) phenotype, including distinct CAP1 present only in the early alveolar lung expressing Peg3, a paternally imprinted transcription factor. Hyperoxia, an injury which impairs angiogenesis, induced both common and unique endothelial gene signatures, dysregulated capillary EC cross-talk, and suppressed CAP1 proliferation while stimulating venous EC proliferation. These data highlight the diversity, transcriptomic evolution, and pleiotropic responses to injury of immature lung EC, possessing broad implications for lung development and injury across the lifespan.

developmental biology↗