Biology subjects

Alexandrov, T.

Publications and source records attributed to Alexandrov, T..

At least 19 recordsLinked to original sources

bioRxiv2025

How big is enough? Movement-informed zoning for African swine fever mitigation

O_LIAfrican swine fever (ASF) poses a serious threat to domestic pigs and wild boar populations. Wild boar can disperse the virus, making effective containment crucial. One of the main control strategies involves establishing restricted zones around detected cases, i.e., areas with temporary restrictions on access and hunting; however, determining the appropriate size of these zones remains a major challenge. C_LIO_LITo inform the size of restricted zones, we analyzed GPS data from 527 wild boar across 46 European study sites using a two-step approach combining first-passage time analysis and survival modelling to quantify the risk of wild boar leaving areas of different radii (i.e., spatial scales). We investigated how the risk of leaving varied over time and across environmental gradients. To go further, we used our model findings to develop an online application that generates predictive maps of optimal buffer sizes for ASF management at the European scale, based on a given risk threshold (the maximum acceptable probability that a wild boar leaves the area). C_LIO_LIWe found that the relationship between radius and the risk of leaving is negative exponential, and the risk of leaving increased over time, with a more rapid increase for smaller radii. Landscape homogeneity, terrain ruggedness and human impact increased the risk of leaving, with stronger effects at small scales. Contrary to other predictors, agricultural cover exerted a strong effect on risk of leaving over large spatial scales, especially when it was abundant. C_LIO_LIAcross Europe, a buffer radius of [~]8 km is likely sufficient around high-risk infection zones in most areas (considering an infectious period of 14 days and a risk threshold of 5%); however, in certain areas, a radius of up to 20 km may be needed to effectively limit wild boar movement. C_LIO_LISynthesis and applications: Our results highlight the need for adaptive, context-specific restricted zones. Buffers of 8 km around ASF-affected areas can limit the risk of infected wild boar dispersal, but they may be reduced to 5 km in highly heterogeneous landscapes or high-human impacted areas. Larger buffers may be required in agricultural landscapes. We provide spatially explicit outputs (optimal buffer sizes) that can directly inform policy and wildlife disease response strategies. The approach can be adapted to any other infectious disease. C_LI

ecology↗

bioRxiv2025

Regulation of the branched-chain amino acid pathway and its crosstalk to carbon metabolism in yeast

In Saccharomyces cerevisiae, the TORC1 pathway regulates the transition from rapid fermentative growth to respiration during the diauxic shift, by tightly coordinating energy- and biomass-producing pathways. Although leucine and other components of the branched-chain amino acid (BCAA) pathway are known TORC1 regulators, how the BCAA pathway is controlled across this transition and influences the crosstalk between central carbon and amino acid metabolism remains unclear. By integrating high-throughput flow cytometry and untargeted LC-MS metabolomics into a thermodynamically curated genome-scale model, we profiled protein levels, metabolite dynamics, and cellular context during the diauxic shift of a GFP-tagged strain library of the BCAA pathway in wild-type and mutants lacking non-essential genes for BCAA biosynthesis. This analysis revealed that the BCAA pathway operates in two branches, with only the leucine-committed branch exhibiting a fermentative signature aligned with TORC1 activity. We further identified key regulatory elements and showed that dysregulation of the BCAA pathway disrupts distant metabolic circuits, including central carbon metabolism. Our findings highlight the dynamic role of the BCAA pathway in metabolic network integration during the diauxic shift.

systems biology↗

bioRxiv2024

HT SpaceM: A High-Throughput and Reproducible Method for Small-Molecule Single-Cell Metabolomics

Single-cell metabolomics promises to resolve metabolic cellular heterogeneity, yet current methods struggle with detecting small molecules, throughput, and reproducibility. Addressing these gaps, we developed HT SpaceM, a high-throughput single-cell metabolomics method with novel cell preparation, custom glass slides, small-molecule MALDI imaging mass spectrometry protocol, and batch processing. We propose a unified framework covering essential data analysis steps including quality control, characterization, differential analysis, structural validation and functional analysis. Interrogating human HeLa and mouse NIH3T3 cells, we detected 73 diverse small-molecule metabolites validated by bulk LC-MS/MS, achieving high reproducibility across wells and slides. Interrogating nine NCI-60 cancer cells and HeLa, we identified cell-type markers in small subpopulations. Functional analysis revealed overrepresented metabolic pathways, co-abundant metabolites, and metabolic hubs. We demonstrate the ability of SCM to analyze over 120,000 cells from over 112 samples, and provide guidance to interpret single-cell metabolic heterogeneity, revealing metabolic insights beyond population averages.

molecular biology↗

bioRxiv2024

Enrichment analysis for spatial and single-cell metabolomics accounting for molecular ambiguity

SummaryImaging mass spectrometry (imaging MS) has advanced spatial and single-cell metabolomics, but the reliance on MS1 data complicates the accurate identification of molecular structures, not being able to resolve isomeric and isobar molecules. This prevents application of conventional methods for overrepresentation analysis (ORA) and metabolite set enrichment analysis (MSEA). To address this, we introduce S2IsoMEr R package and a web app for METASPACE, which uses bootstrapping to propagate isomeric/isobaric ambiguities into the enrichment analysis. We demonstrate S2IsoMEr for single-cell metabolomics and the METASPACE web app for spatial metabolomics. Availability and ImplementationMETASPACE web app can be used on existing and new datasets submitted to METASPACE (https://metaspace2020.eu). The source code for the S2IsoMEr R package is available on GitHub (https://github.com/alexandrovteam/S2IsoMEr).

bioinformatics↗

bioRxiv2024

Large-Scale Evaluation of Spatial Metabolomics Protocols and Technologies

Spatial metabolomics using imaging mass spectrometry (MS) enables untargeted and label-free metabolite mapping in biological samples. Despite the range of available imaging MS protocols and technologies, our understanding of metabolite detection under specific conditions is limited due to sparse empirical data and predictive theories. Consequently, challenges persist in designing new experiments, and accurately annotating and interpreting data. In this study, we systematically measured the detectability of 172 biologically-relevant metabolites across common imaging MS protocols using custom reference samples. We evaluated 24 MALDI-imaging MS protocols for untargeted metabolomics, and demonstrated the applicability of our findings to complex biological samples through comparison with animal tissue data. We showcased the potential for extending our results to further analytes by predicting metabolite detectability based on molecular properties. Additionally, our interlaboratory comparison of 10 imaging MS technologies, including MALDI, DESI, and IR-MALDESI, showed extensive metabolite coverage and comparable results, underscoring the broad applicability of our findings within the imaging MS community. We share our results and data through a new interactive web application integrated with METASPACE. This resource offers an extensive catalogue of detectable metabolite ions, facilitating protocol selection, supporting data annotation, and benefiting future untargeted spatial metabolomics studies.

systems biology↗

bioRxiv2023

A system-wide analysis of lipid transfer proteins delineates lipid mobility in human cells

Lipid transfer proteins (LTPs) maintain the specialised lipid compositions of biological membranes, and many are associated with disease. In eukaryotes, they support organellar functions by transporting lipids between compartmentalised metabolic pathways. However, for the majority of the hundreds of human LTPs, the cargoes remain unknown. We combined biochemical, lipidomic and computational methods to characterize LTP-lipid complexes assembled in cellulo and in an in vitro biochemical assay. We identified bound lipids for about half of the LTPs analysed, and confirmed known cargoes, while discovering new ones for most LTP families. The data represents a systematic resource that captures the general principles of non-vesicular lipid transport in humans. The specificity of LTPs for lipids involves not only the recognition of specific head groups, but also of specific acyl chains. This selectivity defines lipid species within a lipid class with different metabolic or functional fates. The generalised ability of LTPs to form complexes with more than one class of lipids delineates new relationships between lipids and regulatory mechanisms that may contribute to the coordination of metabolism between different organelles. This work represents a resource and a framework for further analyses in different cell types, in pathological states or following various cellular perturbations.

biochemistry↗

bioRxiv2023

Spatial single-cell isotope tracing reveals heterogeneity of de novo fatty acid synthesis in cancer cells

Metabolism has emerged as a key factor in homeostasis and disease including cancer. Yet, little is known about the heterogeneity of metabolic activity of cancer cells due to the lack of tools to directly probe it. Here, we present a novel method, 13C-SpaceM for spatial single-cell isotope tracing of glucose-dependent de novo lipogenesis. The method combines imaging mass spectrometry for spatially-resolved detection of 13C6-glucose-derived 13C label incorporated into esterified fatty acids with microscopy and computational methods for data integration and analysis. We validated 13C-SpaceM on a spatially-heterogeneous normoxia-hypoxia model of liver cancer cells. Investigating cultured cells, we revealed single-cell heterogeneity of lipogenic acetyl-CoA pool labelling degree upon ACLY knockdown that is hidden in the bulk analysis and its effect on synthesis of individual fatty acids. Next, we adapted 13C-SpaceM to analyze tissue sections of mice harboring isocitrate dehydrogenase (IDH)-mutant gliomas. We found a strong induction of de novo fatty acid synthesis in the tumor tissue compared to the surrounding brain. Comparison of fatty acid isotopologue patterns revealed elevated uptake of mono-unsaturated and essential fatty acids in the tumor. Furthermore, our analysis uncovered substantial spatial heterogeneity in the labelling of the lipogenic acetyl-CoA pool indicative of metabolic reprogramming during microenvironmental adaptation. Overall, 13C-SpaceM enables novel ways for spatial probing of metabolic activity at the single cell level. Additionally, this methodology provides unprecedented insight into fatty acid uptake, synthesis and modification in normal and cancerous tissues.

biochemistry↗

bioRxiv2023

METASPACE-ML: Metabolite annotation for imaging mass spectrometry using machine learning

Imaging mass spectrometry is a powerful technology enabling spatial metabolomics, yet metabolites can be assigned only to a fraction of the data generated. METASPACE-ML is a machine learning-based approach addressing this challenge which incorporates new scores and computationally-efficient False Discovery Rate estimation. For training and evaluation, we use a comprehensive set of 1,710 datasets from 159 researchers from 47 labs encompassing both animal and plant-based datasets representing multiple spatial metabolomics contexts derived from the METASPACE knowledge base. Here we show that, METASPACE-ML outperforms its rule-based predecessor, exhibiting higher precision, increased throughput, and enhanced capability in identifying low-intensity and biologically-relevant metabolites.

bioinformatics↗

bioRxiv2022

Laboratory evolution of flies to morphogen dosage via rapid maternal changes reveals predictable outcomes

Although the effects of genetic and environmental perturbations on multicellular organisms are rarely restricted to single phenotypic layers, our current understanding of how developmental programs react to these challenges at a systems level remains limited. Here, we have examined the phenotypic consequences of disturbing the classic bicoid network in Drosophila, which is essential for anterior-posterior patterning in the early embryo. This network can be synthetically perturbed by increasing the dosage of bicoid, which causes a posterior shift of the networks regulatory outputs and a decrease in fitness. To directly monitor network changes across populations and time with extra copies of bicoid, we performed genome-wide EMS mutagenesis, followed by experimental evolution. After only 8-15 generations, experimental populations have normalized patterns of gene expression and increased survival. Using a phenomics approach, we find that populations were normalized through rapid increases in embryo size driven by maternal changes in metabolism and ovariole development. We extend our results to additional populations of flies, demonstrating predictability. Together, our results necessitate a broader view of regulatory network evolution at the systems level. In the future, such synthetic evolution approaches using animal models could provide a generalizable platform for studying the propagation of genetic perturbations across the many layers of complex multicellular systems.

developmental biology↗

bioRxiv2022

Increasing quantitation in spatial single-cell metabolomics by using fluorescence as ground truth

Imaging mass spectrometry (MS) is becoming increasingly applied for single-cell analyses. Multiple methods for imaging MS-based single-cell metabolomics were proposed, including our recent method SpaceM. An important step in imaging MS-based single-cell metabolomics is the assignment of MS intensities from individual pixels to single cells. In this process, referred to as pixel-cell deconvolution, the MS intensities of regions sampled by the imaging MS laser are assigned to the segmented single cells. The complexity of the contributions from multiple cells and the background, as well as lack of full understanding of how input from molecularly-heterogeneous areas translates into mass spectrometry intensities make the cell-pixel deconvolution a challenging problem. Here, we propose a novel approach to evaluate pixel-cell deconvolution methods by using a molecule detectable both by mass spectrometry and fluorescent microscopy, namely fluorescein diacetate (FDA). FDA is a cell-permeable small molecule that becomes fluorescent after internalisation in the cell and subsequent cleavage of the acetate groups. Intracellular fluorescein can be easily imaged using fluorescence microscopy. Additionally, it is detectable by matrix-assisted laser desorption/ionisation (MALDI) imaging MS. The key idea of our approach is to use the fluorescent levels of fluorescein as the ground truth to evaluate the impact of using various pixel-cell deconvolution methods onto single-cell fluorescein intensities obtained by the SpaceM method. Following this approach, we evaluated multiple pixel-cell deconvolution methods, the weighted average method originally proposed in the SpaceM method as well as the novel linear inverse modelling method. Despite the potential of the latter method in resolving contributions from individual cells, this method was outperformed by the weighted average approach. Using the ground truth approach, we demonstrate the extent of the ion suppression effect which considerably worsens the pixel-cell deconvolution quality. For compensating the ion suppression, we propose a novel data-driven approach. We show that compensating the ion suppression effect in a single-cell metabolomics dataset of co-cultured HeLa and NIH3T3 cells considerably improved the separation between both cell types. Finally, using the same ground truth, we evaluate the impact of drop-outs in the measurements and discuss the optimal filtering parameters of SpaceM processing steps before pixel-cell deconvolution.

bioinformatics↗

bioRxiv2022

Metabolic enhancement of mammalian developmental pausing

The quest to model and modulate embryonic development became a recent cornerstone of stem cell and developmental biology. Mammalian developmental timing is adjustable in vivo by preserving preimplantation embryos in a dormant state called diapause. Inhibition of the growth regulator mTOR (mTORi) pauses mouse development in vitro, yet constraints to pause duration are unrecognized. By comparing the response of embryonic and extraembryonic stem cells to mTORi-induced pausing, we identified lipid usage as a bottleneck to developmental pausing. Enhancing fatty acid oxidation (FAO) boosts embryo longevity, while blocking it reduces the pausing capacity. Genomic and metabolic analyses of single embryos point toward a deeper dormant state in FAO-enhanced pausing and reveal a link between lipid metabolism and embryo morphology. Our results lift a constraint on in vitro embryo survival and suggest that lipid metabolism may be a critical metabolic transition relevant for longevity and stem cell function across tissues. One-Sentence SummaryFacilitating fatty acid oxidation by carnitine supplementation enhances mTOR inhibition-mediated developmental pausing.

developmental biology↗

bioRxiv2022

Developmental phenomics suggests that H3K4 monomethylation catalyzed by Trr functions as a phenotypic capacitor

How epigenetic modulators of gene regulation affect the development and evolution of animals has been difficult to ascertain. Despite the widespread presence of histone 3 lysine 4 monomethylation (H3K4me1) on enhancers, hypomethylation appears to have minor effects on animal development and viability. In this study, we performed quantitative, unbiased and multi-dimensional explorations of key phenotypes on Drosophila melanogaster with genetically induced hypomethylation. Hypomethylation reduced transcription factor enrichment in nuclear microenvironments, leading to reduced gene expression, and phenotypes outside of standard laboratory conditions. Our developmental phenomics survey further showed that H3K4me1 hypomethylation led to context-dependent changes in morphology, metabolism, and behavior. Therefore, H3K4me1 may contribute to phenotypic evolution as a phenotypic capacitor by buffering the effects of chance, genotypes and environmental conditions on transcriptional enhancers. Quote"Developmental biologists are often not so much opposed to a role for ecology as they simply ignore it" -Doug Erwin1

developmental biology↗

bioRxiv2021

Reprogramming of the intestinal epithelial-immune cell interactome during SARS-CoV-2 infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents an unprecedented worldwide health problem. Although the primary site of infection is the lung, growing evidence points towards a crucial role of the intestinal epithelium. Yet, the exact effects of viral infection and the role of intestinal epithelial-immune cell interactions in mediating the inflammatory response are not known. In this work, we apply network biology approaches to single-cell RNA-seq data from SARS-CoV-2 infected human ileal and colonic organoids to investigate how altered intracellular pathways upon infection in intestinal enterocytes leads to modified epithelial-immune crosstalk. We point out specific epithelial-immune interactions which could help SARS-CoV-2 evade the immune response. By integrating our data with existing experimental data, we provide a set of epithelial ligands likely to drive the inflammatory response upon infection. Our integrated analysis of intra- and inter-cellular molecular networks contribute to finding potential drug targets, and suggest using existing anti-inflammatory therapies in the gut as promising drug repurposing strategies against COVID-19.

bioinformatics↗

bioRxiv2021

Network-based identification and pharmacological targeting of host cell master regulators induced by SARS-CoV-2 infection

Precise characterization and targeting of host cell transcriptional machinery hijacked by SARS-CoV-2 remains challenging. To identify therapeutically targetable mechanisms that are critical for SARS-CoV-2 infection, here we elucidated the Master Regulator (MR) proteins representing mechanistic determinants of the gene expression signature induced by SARS-CoV-2. The analysis revealed coordinated inactivation of MR-proteins linked to regulatory programs potentiating efficiency of viral replication (detrimental host MR-signature) and activation of MR-proteins governing innate immune response programs (beneficial MR-signature). To identify MR-inverting compounds capable of rescuing activity of inactivated host MR-proteins, with-out adversely affecting the beneficial MR-signature, we developed the ViroTreat algorithm. Overall, >80% of drugs predicted to be effective by this methodology induced significant reduction of SARS-CoV-2 infection, without affecting cell viability. ViroTreat is fully generalizable and can be extended to identify drugs targeting the host cell-based MR signatures induced by virtually any pathogen.

microbiology↗

bioRxiv2021

Single-cell proteo-genomic reference maps of the hematopoietic system enable the purification and massive profiling of precisely defined cell states

Single-cell genomics has transformed our understanding of complex cellular systems. However, excessive costs and a lack of strategies for the purification of newly identified cell types impede their functional characterization and large-scale profiling. Here, we have generated high content single-cell proteo-genomic reference maps of human blood and bone marrow that quantitatively link the expression of up to 197 surface markers to cellular identities and biological processes across all major hematopoietic cell types in healthy aging and leukemia. These reference maps enable the automatic design of cost-effective high-throughput cytometry schemes that outperform state-of-the-art approaches, accurately reflect complex topologies of cellular systems, and permit the purification of precisely defined cell states. The systematic integration of cytometry and proteo-genomic data enables measuring the functional capacities of precisely mapped cell states at the single-cell level. Our study serves as an accessible resource and paves the way for a data-driven era in cytometry.

immunology↗

bioRxiv2020

Quantification reveals early dynamics in Drosophila maternal gradients

The Bicoid (Bcd) protein is a primary determinant of early anterior-posterior (AP) axis specification in Drosophila embryogenesis. This morphogen is spatially distributed in an anterior-high gradient, and affects particular AP cell fates in a concentration-dependent manner. The early distribution and dynamics of the bicoid (bcd) mRNA, the source for the Bcd protein gradient, is not well understood, leaving a number of open questions for how Bcd positional information develops and is regulated. Confocal microscope images of whole early embryos, stained for bcd mRNA or the Staufen (Stau) protein involved in its transport, were processed to extract quantitative AP intensity profiles at two depths (apical - under the embryo surface but above the nuclear layer; and basal - below the nuclei). Each profile was quantified by a two- (or three-) exponential equation. The parameters of these equations were used to analyze the early developmental dynamics of bcd. Analysis of 1D profiles was compared with 2D intensity surfaces from the same images. This approach reveals strong early changes in bcd and Stau, which appear to be coordinated. We can unambiguously discriminate three stages in early development using the exponential parameters: pre-blastoderm, syncytial blastoderm and cellularization. Key features which differ in this period are how fast the first exponential (anterior component) of the apical profile drops with distance and whether it is higher or lower than the basal first exponential. We can further discriminate early and late embryos within the pre-blastoderm stage, depending on how quickly the anterior exponential drops. This relates to the posterior-wards spread of bcd in the first hour of development. Both bcd and Stau show several redistributions in the head cytoplasm, quite probably related to nuclear activity: first shifting inwards towards the core plasm, forming either protrusions (early pre-blastoderm) or round aggregations (early nuclear cleavage cycles, cc, 13 and 14), then moving to the embryo surface and spreading posteriorly. These movements are seen both with the 2D surface study and the 1D profile analysis. The continued spreading of bcd can be tracked from the time of nuclear layer formation (later pre-blastoderm) to the later syncytial blastoderm stages by the progressive loss of steepness of the apical anterior exponential (for both bcd and Stau). Finally, at the beginning of cc14 (cellularization stage) we see a distinctive flip from the basal anterior gradient being higher to the apical gradient being higher (for both bcd and Stau). Quantitative analysis reveals substantial (and correlated) bcd and Stau redistributions during early development, supporting that the distribution and dynamics of bcd mRNA are key factors in the formation and maintenance of the Bcd protein morphogenetic gradient. This analysis reveals the complex and dynamic nature of bcd redistribution, particularly in the head cytoplasm. These resemble observations in oogenesis; their role and significance have yet to be clarified. The observed co-localization during redistribution of bcd and Stau may indicate the involvement of active transport.

systems biology↗

bioRxiv2020

Public LC-Orbitrap-MS/MS Spectral Library for Metabolite Identification

Liquid chromatography-mass spectrometry(LC-MS)-based untargeted metabolomics studies require high-quality spectral libraries for reliable metabolite identification. We have constructed EMBL-MCF, an open LC-MS/MS spectral library that currently contains over 1600 fragmentation spectra from 435 authentic standards of endogenous metabolites and lipids. The unique features of the library are presence of chromatographic profiles acquired with different LC-MS methods and coverage of different adduct ions. The library covers many biologically important metabolites with some unique metabolites and lipids as compared to other public libraries. The EMBL-MCF spectral library is created and shared using an in-house developed web-application at https://curatr.mcf.embl.de/. The library is freely available online and also integrated with other mass spectral repositories.

biochemistry↗

bioRxiv2020

Single-cell analyses reveal SARS-CoV-2 interference with intrinsic immune response in the human gut

ObjectiveExacerbated pro-inflammatory immune response contributes to COVID-19 pathology. Despite the evidence about SARS-CoV-2 infecting the human gut, little is known about the importance of the enteric phase of SARS-CoV-2 for the viral lifecycle and for the development of COVID-19-associated pathologies. Similarly, it remains unknown whether the innate immune response triggered in this organ to combat viral infection is similar or distinct compared to the one triggered in other organs. DesignWe exploited human ileum- and colon-derived organoids as a non-transformed culture model supporting SARS-CoV-2 infection. We characterized the replication kinetics of SARS-CoV-2 in intestinal epithelial cells and correlated the expression of the viral receptor ACE2 with infection. We performed conventional and targeted single-cell transcriptomics and multiplex single-molecule RNA fluorescence in situ hybridization and used IFN-reporter bioassays to characterize the response of primary human intestinal epithelial cells to SARS-CoV-2 infection. ResultsWe identified a subpopulation of enterocytes as the prime target of SARS-CoV-2. We found the lack of positive correlation between susceptibility to infection and the expression of ACE2 and revealed that SARS-CoV-2 downregulates ACE2 expression upon infection. Infected cells activated strong proinflammatory programs and produced interferon, while expression of interferon-stimulated genes was limited to bystander cells due to SARS-CoV-2 suppressing the autocrine action of interferon in infected cells. ConclusionOur findings reveal that SARS-CoV-2 curtails the immune response in primary human intestinal epithelial cells to promote its replication and spread and this highlights the gut as a proinflammatory reservoir that should be considered to fully understand SARS-CoV-2 pathogenesis. Significance of the studyWhat is already known about this subject? O_LICOVID-19 patients have gastrointestinal symptoms which likely correlates with SARS-CoV-2 infection of the intestinal epithelium C_LIO_LISARS-CoV-2 replicates in human intestinal epithelial cells. C_LIO_LIIntestinal organoids are a good model to study SARS-CoV-2 infection of the gastrointestinal tract C_LIO_LIThere is a limited interferon response in human lung epithelial cells upon SARS-CoV-2 infection. C_LI What are the new findings? O_LIA specific subpopulation of enterocytes are the prime targets of SARS-CoV-2 infection of the human gut. C_LIO_LIThere is a lack of correlation between ACE2 expression and susceptibility to SARS-CoV-2 infection. SARS-CoV-2 downregulates ACE2 expression upon infection. C_LIO_LIHuman intestinal epithelium cells produce interferon upon SARS-CoV-2 infection. C_LIO_LIInterferon acts in a paracrine manner to induce interferon stimulated genes that control viral infection only in bystander cells. C_LIO_LISARS-CoV-2 actively blocks interferon signaling in infected cells. C_LI How might it impact on clinical practice in the foreseeable future? O_LIThe absence of correlation between ACE2 levels and susceptibility suggest that medications influencing ACE2 levels (e.g. high blood pressure drugs) will not make patients more susceptible to SARS-CoV-2 infection. C_LIO_LIThe restricted cell tropism and the distinct immune response mounted by the GI tract, suggests that specific cellular restriction/replication factors and organ specific intrinsic innate immune pathways can represent unique therapeutic targets to treat COVD-19 patients by considering which organ is most infected/impacted by SARS-CoV-2. C_LIO_LIThe strong pro-inflammatory signal mounted by the intestinal epithelium can fuel the systemic inflammation observed in COVID-19 patients and is likely participating in the lung specific pathology. C_LI

immunology↗