Detection of PatIent-Level distances from single cell genomics and pathomics data with Optimal Transport (PILOT).

Although clinical applications represent the next challenge in single-cell genomics and digital pathology, we still lack computational methods to analyze single-cell or pathomics data to find sample-level trajectories or clusters associated with diseases. This remains challenging as single-cell/pathomics data are multi-scale, i.e., a sample is represented by clusters of cells/structures, and samples cannot be easily compared with each other. Here we propose PatIent Level analysis with Optimal Transport (PILOT). PILOT uses optimal transport to compute the Wasserstein distance between two individual single-cell samples. This allows us to perform unsupervised analysis at the sample level and uncover trajectories or cellular clusters associated with disease progression. We evaluate PILOT and competing approaches in single-cell genomics or pathomics studies involving various human diseases with up to 600 samples/patients and millions of cells or tissue structures. Our results demonstrate that PILOT detects disease-associated samples from large and complex single-cell or pathomics data. Moreover, PILOT provides a statistical approach to find changes in cell populations, gene expression, and tissue structures related to the trajectories or clusters supporting interpretation of predictions.

Correction: A stomata classification and detection system in microscope images of maize cultivars.

[This corrects the article DOI: 10.1371/journal.pone.0258679.].

Non-canonical Hedgehog signaling mediates profibrotic hematopoiesis-stroma crosstalk in myeloproliferative neoplasms.

The role of hematopoietic Hedgehog signaling in myeloproliferative neoplasms (MPNs) remains incompletely understood despite data suggesting that Hedgehog (Hh) pathway inhibitors have therapeutic activity in patients. We aim to systematically interrogate the role of canonical vs. non-canonical Hh signaling in MPNs. We show that Gli1 protein levels in patient peripheral blood mononuclear cells (PBMCs) mark fibrotic progression and that, in murine MPN models, absence of hematopoietic Gli1, but not Gli2 or Smo, significantly reduces MPN phenotype and fibrosis, indicating that GLI1 in the MPN clone can be activated in a non-canonical fashion. Additionally, we establish that hematopoietic Gli1 has a significant effect on stromal cells, mediated through a druggable MIF-CD74 axis. These data highlight the complex interplay between alterations in the MPN clone and activation of stromal cells and indicate that Gli1 represents a promising therapeutic target in MPNs, particularly that Hh signaling is dispensable for normal hematopoiesis.

Enhanced fatty acid oxidation through metformin and baicalin as therapy for COVID-19 and associated inflammatory states in lung and kidney.

Progressive respiratory failure is the primary cause of death in the coronavirus disease 2019 (COVID-19) pandemic. It is the final outcome of the acute respiratory distress syndrome (ARDS), characterized by an initial exacerbated inflammatory response, metabolic derangement and ultimate tissue scarring. A positive balance of cellular energy may result crucial for the recovery of clinical COVID-19. Hence, we asked if two key pathways involved in cellular energy generation, AMP-activated protein kinase (AMPK)/acetyl-CoA carboxylase (ACC) signaling and fatty acid oxidation (FAO) could be beneficial. We tested the drugs metformin (AMPK activator) and baicalin (CPT1A activator) in different experimental models mimicking COVID-19 associated inflammation in lung and kidney. We also studied two different cohorts of COVID-19 patients that had been previously treated with metformin. These drugs ameliorated lung damage in an ARDS animal model, while activation of AMPK/ACC signaling increased mitochondrial function and decreased TGF-ß-induced fibrosis, apoptosis and inflammation markers in lung epithelial cells. Similar results were observed with two indole derivatives, IND6 and IND8 with AMPK activating capacity. Consistently, a reduced time of hospitalization and need of intensive care was observed in COVID-19 patients previously exposed to metformin. Baicalin also mitigated the activation of pro-inflammatory bone marrow-derived macrophages (BMDMs) and reduced kidney fibrosis in two animal models of kidney injury, another key target of COVID-19. In human epithelial lung and kidney cells, both drugs improved mitochondrial function and prevented TGF-ß-induced renal epithelial cell dedifferentiation. Our results support that favoring cellular energy production through enhanced FAO may prove useful in the prevention of COVID-19-induced lung and renal damage.

Mapping cardiac remodeling in chronic kidney disease.

Patients with advanced chronic kidney disease (CKD) mostly die from sudden cardiac death and recurrent heart failure. The mechanisms of cardiac remodeling are largely unclear. To dissect molecular and cellular mechanisms of cardiac remodeling in CKD in an unbiased fashion, we performed left ventricular single-nuclear RNA sequencing in two mouse models of CKD. Our data showed a hypertrophic response trajectory of cardiomyocytes with stress signaling and metabolic changes driven by soluble uremia-related factors. We mapped fibroblast to myofibroblast differentiation in this process and identified notable changes in the cardiac vasculature, suggesting inflammation and dysfunction. An integrated analysis of cardiac cellular responses to uremic toxins pointed toward endothelin-1 and methylglyoxal being involved in capillary dysfunction and TNFα driving cardiomyocyte hypertrophy in CKD, which was validated in vitro and in vivo. TNFα inhibition in vivo ameliorated the cardiac phenotype in CKD. Thus, interventional approaches directed against uremic toxins, such as TNFα, hold promise to ameliorate cardiac remodeling in CKD.

Platelet-instructed SPP1+ macrophages drive myofibroblast activation in fibrosis in a CXCL4-dependent manner.

Fibrosis represents the common end stage of chronic organ injury independent of the initial insult, destroying tissue architecture and driving organ failure. Here we discover a population of profibrotic macrophages marked by expression of Spp1, Fn1, and Arg1 (termed Spp1 macrophages), which expands after organ injury. Using an unbiased approach, we identify the chemokine (C-X-C motif) ligand 4 (CXCL4) to be among the top upregulated genes during profibrotic Spp1 macrophage differentiation. In vitro and in vivo studies show that loss of Cxcl4 abrogates profibrotic Spp1 macrophage differentiation and ameliorates fibrosis after both heart and kidney injury. Moreover, we find that platelets, the most abundant source of CXCL4 in vivo, drive profibrotic Spp1 macrophage differentiation. Single nuclear RNA sequencing with ligand-receptor interaction analysis reveals that macrophages orchestrate fibroblast activation via Spp1, Fn1, and Sema3 crosstalk. Finally, we confirm that Spp1 macrophages expand in both human chronic kidney disease and heart failure.

scMEGA: single-cell multi-omic enhancer-based gene regulatory network inference.

Summary: The increasing availability of single-cell multi-omics data allows to quantitatively characterize gene regulation. We here describe scMEGA (Single-cell Multiomic Enhancer-based Gene Regulatory Network Inference) that enables an end-to-end analysis of multi-omics data for gene regulatory network inference including modalities integration, trajectory analysis, enhancer-to-promoter association, network analysis and visualization. This enables to study the complex gene regulation mechanisms for dynamic biological processes, such as cellular differentiation and disease-driven cellular remodeling. We provide a case study on gene regulatory networks controlling myofibroblast activation in human myocardial infarction. Availability and implementation: scMEGA is implemented in R, released under the MIT license and available from https://github.com/CostaLab/scMEGA. Tutorials are available from https://costalab.github.io/scMEGA. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Adult human kidney organoids originate from CD24+ cells and represent an advanced model for adult polycystic kidney disease.

Adult kidney organoids have been described as strictly tubular epithelia and termed tubuloids. While the cellular origin of tubuloids has remained elusive, here we report that they originate from a distinct CD24+ epithelial subpopulation. Long-term-cultured CD24+ cell-derived tubuloids represent a functional human kidney tubule. We show that kidney tubuloids can be used to model the most common inherited kidney disease, namely autosomal dominant polycystic kidney disease (ADPKD), reconstituting the phenotypic hallmark of this disease with cyst formation. Single-cell RNA sequencing of CRISPR-Cas9 gene-edited PKD1- and PKD2-knockout tubuloids and human ADPKD and control tissue shows similarities in upregulation of disease-driving genes. Furthermore, in a proof of concept, we demonstrate that tolvaptan, the only approved drug for ADPKD, has a significant effect on cyst size in tubuloids but no effect on a pluripotent stem cell-derived model. Thus, tubuloids are derived from a tubular epithelial subpopulation and represent an advanced system for ADPKD disease modeling.

Spatial multi-omic map of human myocardial infarction.

Myocardial infarction is a leading cause of death worldwide1. Although advances have been made in acute treatment, an incomplete understanding of remodelling processes has limited the effectiveness of therapies to reduce late-stage mortality2. Here we generate an integrative high-resolution map of human cardiac remodelling after myocardial infarction using single-cell gene expression, chromatin accessibility and spatial transcriptomic profiling of multiple physiological zones at distinct time points in myocardium from patients with myocardial infarction and controls. Multi-modal data integration enabled us to evaluate cardiac cell-type compositions at increased resolution, yielding insights into changes of the cardiac transcriptome and epigenome through the identification of distinct tissue structures of injury, repair and remodelling. We identified and validated disease-specific cardiac cell states of major cell types and analysed them in their spatial context, evaluating their dependency on other cell types. Our data elucidate the molecular principles of human myocardial tissue organization, recapitulating a gradual cardiomyocyte and myeloid continuum following ischaemic injury. In sum, our study provides an integrative molecular map of human myocardial infarction, represents an essential reference for the field and paves the way for advanced mechanistic and therapeutic studies of cardiac disease.

Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data.

The growing availability of single-cell data, especially transcriptomics, has sparked an increased interest in the inference of cell-cell communication. Many computational tools were developed for this purpose. Each of them consists of a resource of intercellular interactions prior knowledge and a method to predict potential cell-cell communication events. Yet the impact of the choice of resource and method on the resulting predictions is largely unknown. To shed light on this, we systematically compare 16 cell-cell communication inference resources and 7 methods, plus the consensus between the methods' predictions. Among the resources, we find few unique interactions, a varying degree of overlap, and an uneven coverage of specific pathways and tissue-enriched proteins. We then examine all possible combinations of methods and resources and show that both strongly influence the predicted intercellular interactions. Finally, we assess the agreement of cell-cell communication methods with spatial colocalisation, cytokine activities, and receptor protein abundance and find that predictions are generally coherent with those data modalities. To facilitate the use of the methods and resources described in this work, we provide LIANA, a LIgand-receptor ANalysis frAmework as an open-source interface to all the resources and methods.

Mapping the cardiac vascular niche in heart failure.

The cardiac vascular and perivascular niche are of major importance in homeostasis and during disease, but we lack a complete understanding of its cellular heterogeneity and alteration in response to injury as a major driver of heart failure. Using combined genetic fate tracing with confocal imaging and single-cell RNA sequencing of this niche in homeostasis and during heart failure, we unravel cell type specific transcriptomic changes in fibroblast, endothelial, pericyte and vascular smooth muscle cell subtypes. We characterize a specific fibroblast subpopulation that exists during homeostasis, acquires Thbs4 expression and expands after injury driving cardiac fibrosis, and identify the transcription factor TEAD1 as a regulator of fibroblast activation. Endothelial cells display a proliferative response after injury, which is not sustained in later remodeling, together with transcriptional changes related to hypoxia, angiogenesis, and migration. Collectively, our data provides an extensive resource of transcriptomic changes in the vascular niche in hypertrophic cardiac remodeling.

Human pluripotent stem cell-derived kidney organoids for personalized congenital and idiopathic nephrotic syndrome modeling.

Nephrotic syndrome (NS) is characterized by severe proteinuria as a consequence of kidney glomerular injury due to podocyte damage. In vitro models mimicking in vivo podocyte characteristics are a prerequisite to resolve NS pathogenesis. The detailed characterization of organoid podocytes resulting from a hybrid culture protocol showed a podocyte population that resembles adult podocytes and was superior compared with 2D counterparts, based on single-cell RNA sequencing, super-resolution imaging and electron microscopy. In this study, these next-generation podocytes in kidney organoids enabled personalized idiopathic nephrotic syndrome modeling, as shown by activated slit diaphragm signaling and podocyte injury following protamine sulfate, puromycin aminonucleoside treatment and exposure to NS plasma containing pathogenic permeability factors. Organoids cultured from cells of a patient with heterozygous NPHS2 mutations showed poor NPHS2 expression and aberrant NPHS1 localization, which was reversible after genetic correction. Repaired organoids displayed increased VEGFA pathway activity and transcription factor activity known to be essential for podocyte physiology, as shown by RNA sequencing. This study shows that organoids are the preferred model of choice to study idiopathic and congenital podocytopathies.

Single-cell analysis of cultured bone marrow stromal cells reveals high similarity to fibroblasts in situ.

Within the heterogenous pool of bone marrow stromal cells, mesenchymal stromal cells (MSCs) are of particular interest because of their hematopoiesis-supporting capacities, contribution to disease progression, therapy resistance, and leukemic initiation. Cultured bone marrow-derived stromal cells (cBMSCs) are used for in vitro modeling of hematopoiesis-stroma interactions, validation of disease mechanisms, and screening for therapeutic targets. Here, we place cBMSCs (mouse and human) in a bone marrow tissue context by systematically comparing the transcriptome of plastic-adherent cells on a single-cell level with in vivo counterparts. Cultured BMSCs encompass a rather homogenous cell population, independent of the isolation method used and, although still possessing hematopoiesis-supporting capacity, are distinct from freshly isolated MSCs and more akin to in vivo fibroblast populations. Informed by combined cell trajectories and pathway analyses, we illustrate that TGFb inhibition in vitro can preserve a more "MSC"-like phenotype.

SARS-CoV-2 infects the human kidney and drives fibrosis in kidney organoids.

Kidney failure is frequently observed during and after COVID-19, but it remains elusive whether this is a direct effect of the virus. Here, we report that SARS-CoV-2 directly infects kidney cells and is associated with increased tubule-interstitial kidney fibrosis in patient autopsy samples. To study direct effects of the virus on the kidney independent of systemic effects of COVID-19, we infected human-induced pluripotent stem-cell-derived kidney organoids with SARS-CoV-2. Single-cell RNA sequencing indicated injury and dedifferentiation of infected cells with activation of profibrotic signaling pathways. Importantly, SARS-CoV-2 infection also led to increased collagen 1 protein expression in organoids. A SARS-CoV-2 protease inhibitor was able to ameliorate the infection of kidney cells by SARS-CoV-2. Our results suggest that SARS-CoV-2 can directly infect kidney cells and induce cell injury with subsequent fibrosis. These data could explain both acute kidney injury in COVID-19 patients and the development of chronic kidney disease in long COVID.

Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell immunoprofiling.

Introduction: SARS-CoV-2 infection results in varying disease severity, ranging from asymptomatic infection to severe illness. A detailed understanding of the immune response to SARS-CoV-2 is critical to unravel the causative factors underlying differences in disease severity and to develop optimal vaccines against new SARS-CoV-2 variants. Methods: We combined single-cell RNA and T cell receptor sequencing with CITE-seq antibodies to characterize the CD8+ T cell response to SARS-CoV-2 infection at high resolution and compared responses between mild and severe COVID-19. Results: We observed increased CD8+ T cell exhaustion in severe SARS-CoV-2 infection and identified a population of NK-like, terminally differentiated CD8+ effector T cells characterized by expression of FCGR3A (encoding CD16). Further characterization of NK-like CD8+ T cells revealed heterogeneity among CD16+ NK-like CD8+ T cells and profound differences in cytotoxicity, exhaustion, and NK-like differentiation between mild and severe disease conditions. Discussion: We propose a model in which differences in the surrounding inflammatory milieu lead to crucial differences in NK-like differentiation of CD8+ effector T cells, ultimately resulting in the appearance of NK-like CD8+ T cell populations of different functionality and pathogenicity. Our in-depth characterization of the CD8+ T cell-mediated response to SARS-CoV-2 infection provides a basis for further investigation of the importance of NK-like CD8+ T cells in COVID-19 severity.

A stomata classification and detection system in microscope images of maize cultivars.

Plant stomata are essential structures (pores) that control the exchange of gases between plant leaves and the atmosphere, and also they influence plant adaptation to climate through photosynthesis and transpiration stream. Many works in literature aim for a better understanding of these structures and their role in the evolution process and the behavior of plants. Although stomata studies in dicots species have advanced considerably in the past years, even there is not much knowledge about the stomata of cereal grasses. Due to the high morphological variation of stomata traits intra- and inter-species, detecting and classifying stomata automatically becomes challenging. For this reason, in this work, we propose a new system for automatic stomata classification and detection in microscope images for maize cultivars based on transfer learning strategy of different deep convolution neural netwoks (DCNN). Our performed experiments show that our system achieves an approximated accuracy of 97.1% in identifying stomata regions using classifiers based on deep learning features, which figures out as a nearly perfect classification system. As the stomata are responsible for several plant functionalities, this work represents an important advance for maize research, providing an accurate system in replacing the current manual task of categorizing these pores on microscope images. Furthermore, this system can also be a reference for studies using images from different cereal grasses.

The Wild Sugarcane and Sorghum Kinomes: Insights Into Expansion, Diversification, and Expression Patterns.

The protein kinase (PK) superfamily is one of the largest superfamilies in plants and the core regulator of cellular signaling. Despite this substantial importance, the kinomes of sugarcane and sorghum have not been profiled. Here, we identified and profiled the complete kinomes of the polyploid Saccharum spontaneum (Ssp) and Sorghum bicolor (Sbi), a close diploid relative. The Sbi kinome was composed of 1,210 PKs; for Ssp, we identified 2,919 PKs when disregarding duplications and allelic copies, and these were related to 1,345 representative gene models. The Ssp and Sbi PKs were grouped into 20 groups and 120 subfamilies and exhibited high compositional similarities and evolutionary divergences. By utilizing the collinearity between the species, this study offers insights into Sbi and Ssp speciation, PK differentiation and selection. We assessed the PK subfamily expression profiles via RNA-Seq and identified significant similarities between Sbi and Ssp. Moreover, coexpression networks allowed inference of a core structure of kinase interactions with specific key elements. This study provides the first categorization of the allelic specificity of a kinome and offers a wide reservoir of molecular and genetic information, thereby enhancing the understanding of Sbi and Ssp PK evolutionary history.

Microbial co-occurrence network and its key microorganisms in soil with permanent application of composted tannery sludge.

Soil microbial communities act on important environmental processes, being sensitive to the application of wastes, mainly those potential contaminants, such as tannery sludge. Due to the microbiome complexity, graph-theoretical approaches have been applied to represent model microbial communities interactions and identify important taxa, mainly in contaminated soils. Herein, we performed network and statistical analyses into microbial 16S rRNA gene sequencing data from soil samples with the application of different levels of composted tannery sludge (CTS) to assess the most connected nodes and the nodes that act as bridges to identify key microbes within each community. The network analysis revealed hubs belonging to Proteobacteria in soil with lower CTS rates, while active degraders of recalcitrant and pollutant chemical hubs belonging to Proteobacteria and Actinobacteria were found in soils under the highest CTS rates. The majority of classified connectors belonged to Actinobacteria, but similarly to hubs taxa, they shifted from metabolic functional profile to taxa with abilities to degrade toxic compounds, revealing a soil perturbation with the CTS application on community organization, which also impacted the community modularity. Members of Actinobacteria and Acidobacteria were identified as both hub and connector suggesting their role as keystone groups. Thus, these results offered us interesting insights about crucial taxa, their response to environmental alterations, and possible implications for the ecosystem.

CrossTalkeR: analysis and visualization of ligand-receptorne tworks.

MOTIVATION: Ligand-receptor (LR) network analysis allows the characterization of cellular crosstalk based on single cell RNA-seq data. However, current methods typically provide a list of inferred LR interactions and do not allow the researcher to focus on specific cell types, ligands or receptors. In addition, most of these methods cannot quantify changes in crosstalk between two biological phenotypes. RESULTS: CrossTalkeR is a framework for network analysis and visualization of LR interactions. CrossTalkeR identifies relevant ligands, receptors and cell types contributing to changes in cell communication when contrasting two biological phenotypes, i.e. disease versus homeostasis. A case study on scRNA-seq of human myeloproliferative neoplasms reinforces the strengths of CrossTalkeR for characterization of changes in cellular crosstalk in disease. AVAILABILITY AND IMPLEMENTATION: CrosstalkeR is an R package available at: Github: https://github.com/CostaLab/CrossTalkeR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Heterogeneous bone-marrow stromal progenitors drive myelofibrosis via a druggable alarmin axis.

Functional contributions of individual cellular components of the bone-marrow microenvironment to myelofibrosis (MF) in patients with myeloproliferative neoplasms (MPNs) are incompletely understood. We aimed to generate a comprehensive map of the stroma in MPNs/MFs on a single-cell level in murine models and patient samples. Our analysis revealed two distinct mesenchymal stromal cell (MSC) subsets as pro-fibrotic cells. MSCs were functionally reprogrammed in a stage-dependent manner with loss of their progenitor status and initiation of differentiation in the pre-fibrotic and acquisition of a pro-fibrotic and inflammatory phenotype in the fibrotic stage. The expression of the alarmin complex S100A8/S100A9 in MSC marked disease progression toward the fibrotic phase in murine models and in patient stroma and plasma. Tasquinimod, a small-molecule inhibiting S100A8/S100A9 signaling, significantly ameliorated the MPN phenotype and fibrosis in JAK2V617F-mutated murine models, highlighting that S100A8/S100A9 is an attractive therapeutic target in MPNs.