Biology subjects

Stossi, F.

Publications and source records attributed to Stossi, F..

8 recordsLinked to original sources

bioRxiv2024

SPACe (Swift Phenotypic Analysis of Cells): an open-source, single cell analysis of Cell Painting data

Phenotypic profiling by high throughput microscopy has become one of the leading tools for screening large sets of perturbations in cellular models. Of the numerous methods used over the years, the flexible and economical Cell Painting (CP) assay has been central in the field, allowing for large screening campaigns leading to a vast number of data-rich images. Currently, to analyze data of this scale, available open-source software (i.e., CellProfiler) requires computational resources that are not available to most laboratories worldwide. In addition, the image-embedded cell-to-cell variation of responses within a population, while collected and analyzed, is usually averaged and unused. Here we introduce SPACe (Swift Phenotypic Analysis of Cells), an open source, Python-based platform for the analysis of single cell image-based morphological profiles produced by CP experiments. SPACe can process a typical dataset approximately ten times faster than CellProfiler on common desktop computers without loss in mechanism of action (MOA) recognition accuracy. It also computes directional distribution-based distances (Earth Movers Distance - EMD) of morphological features for quality control and hit calling. We highlight several advantages of SPACe analysis on CP assays, including reproducibility across multiple biological replicates, easy applicability to multiple ([~]20) cell lines, sensitivity to variable cell-to-cell responses, and biological interpretability to explain image-based features. We ultimately illustrate the advantages of SPACe in a screening campaign of cell metabolism small molecule inhibitors which we performed in seven cell lines to highlight the importance of testing perturbations across models.

cell biology↗

bioRxiv2024

Pediatric human nose organoids demonstrate greater susceptibility, epithelial responses, and cytotoxicity than adults during RSV infection.

Respiratory syncytial virus (RSV) is a common cause of respiratory infections, causing significant morbidity and mortality, especially in young children. Why RSV infection in children is more severe as compared to healthy adults is not fully understood. In the present study, we infect both pediatric and adult human nose organoid-air liquid interface (HNO-ALIs) cell lines with two contemporary RSV isolates and demonstrate how they differ in virus replication, induction of the epithelial cytokine response, cell injury, and remodeling. Pediatric HNO-ALIs were more susceptible to early RSV replication, elicited a greater overall cytokine response, demonstrated enhanced mucous production, and manifested greater cellular damage compared to their adult counterparts. Adult HNO-ALIs displayed enhanced mucus production and robust cytokine response that was well controlled by superior regulatory cytokine response and possibly resulted in lower cellular damage than in pediatric lines. Taken together, our data suggest substantial differences in how pediatric and adult upper respiratory tract epithelium responds to RSV infection. These differences in epithelial cellular response can lead to poor mucociliary clearance and predispose infants to a worse respiratory outcome of RSV infection.

microbiology↗

bioRxiv2023

Analysis and Modeling of Early Estradiol-induced GREB1 Single Allele Gene Transcription at the Population Level

Single molecule fluorescence in situ hybridization (smFISH) can be used to visualize transcriptional activation at the single allele level. We and others have applied this approach to better understand the mechanisms of activation by steroid nuclear receptors. However, there is limited understanding of the interconnection between the activation of target gene alleles inside the same nucleus and within large cell populations. Using the GREB1 gene as an early estrogen receptor (ER) response target, we applied smFISH to track E2-activated GREB1 allelic transcription over early time points to evaluate potential dependencies between alleles within the same nucleus. We compared two types of experiments where we altered the initial status of GREB1 basal transcription by treating cells with and without the elongation inhibitor flavopiridol (FV). E2 stimulation changed the frequencies of active GREB1 alleles in the cell population independently of FV pre-treatment. In FV treated cells, the response time to hormone was delayed, albeit still reaching at 90 minutes the same levels as in cells not treated by FV. We show that the joint frequencies of GREB1 activated alleles observed at the cell population level imply significant dependency between pairs of alleles within the same nucleus. We identify probabilistic models of joint alleles activations by applying a principle of maximum entropy. For pairs of alleles, we have then quantified statistical dependency by computing their mutual information. We have then introduced a stochastic model compatible with allelic statistical dependencies, and we have fitted this model to our data by intensive simulations. This provided estimates of the average lifetime for degradation of GREB1 introns and of the mean time between two successive transcription rounds. Our approach informs on how to extract information on single allele regulation by ER from within a large population of cells, and should be applicable to many other genes. AUTHOR SUMMARYAfter application of a gene transcription stimulus, in this case the hormone 17{beta}-estradiol, on large populations of cells over a short time period, we focused on quantifying and modeling the frequencies of GREB1 single allele activations. We have established an experimental and computational pipeline to analyze large numbers of high resolution smFISH images to detect and monitor active GREB1 alleles, that can be translatable to any target gene of interest. A key result is that, at the population level, activation of individual GREB1 alleles within the same nucleus do exhibit statistically significant dependencies which we quantify by the mutual information between activation states of pairs of alleles. After noticing that frequencies of joint alleles activations observed over our large cell populations evolve smoothly in time, we have defined a population level stochastic model which we fit to the observed time course of GREB1 activation frequencies. This provided coherent estimates of the mean time between rounds of GREB1 transcription and the mean lifetime of nascent mRNAs. Our algorithmic approach and experimental methods are applicable to many other genes.

bioinformatics↗

bioRxiv2023

RNA-dependent RNA polymerase of predominant human norovirus forms liquid-liquid phase condensates as platforms for viral replication

Many viral proteins form biomolecular condensates via liquid-liquid phase separation (LLPS) to support viral replication and evade host antiviral responses, and thus, they are potential targets for designing antivirals. In the case of non-enveloped positive-sense RNA viruses, forming such condensates for viral replication is unclear and less understood. Human noroviruses (HuNoV) are positive-sense RNA viruses that cause epidemic and sporadic gastroenteritis worldwide. Here, we show that the RNA-dependent-RNA polymerase (RdRp) of pandemic GII.4 HuNoV forms distinct condensates that exhibit all the signature properties of LLPS with sustained polymerase activity and the capability of recruiting components essential for viral replication. We show that such condensates are formed in HuNoV-infected human intestinal enteroid cultures and are the sites for genome replication. Our studies demonstrate the formation of phase separated condensates as replication factories in a positive-sense RNA virus, which plausibly is an effective mechanism to dynamically isolate RdRp replicating the genomic RNA from interfering with the ribosomal translation of the same RNA. TeaserPolymerase of a positive-sense RNA virus forms LLPS to regulate replication as an elegant solution for an enigmatic question.

biochemistry↗

bioRxiv2021

The human nose organoid respiratory virus model: an ex-vivo human challenge model to study RSV and SARS-CoV-2 pathogenesis and evaluate therapeutics

There is an unmet need for pre-clinical models to understand the pathogenesis of human respiratory viruses; and predict responsiveness to immunotherapies. Airway organoids can serve as an ex-vivo human airway model to study respiratory viral pathogenesis; however, they rely on invasive techniques to obtain patient samples. Here, we report a non-invasive technique to generate human nose organoids (HNOs) as an alternate to biopsy derived organoids. We made air liquid interface (ALI) cultures from HNOs and assessed infection with two major human respiratory viruses, respiratory syncytial virus (RSV) and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Infected HNO-ALI cultures recapitulate aspects of RSV and SARS-CoV-2 infection, including viral shedding, ciliary damage, innate immune responses, and mucus hyper-secretion. Next, we evaluated the feasibility of the HNO-ALI respiratory virus model system to test the efficacy of palivizumab to prevent RSV infection. Palivizumab was administered in the basolateral compartment (circulation) while viral infection occurred in the apical ciliated cells (airways), simulating the events in infants. In our model, palivizumab effectively prevented RSV infection in a concentration dependent manner. Thus, the HNO-ALI model can serve as an alternate to lung organoids to study respiratory viruses and testing therapeutics.

microbiology↗

bioRxiv2021

Multiple RSV strains infecting HEp-2 and A549 cells reveal cell line-dependent differences in resistance to RSV infection.

Respiratory syncytial virus (RSV) is a leading cause of pediatric acute respiratory infection worldwide. There are currently no approved vaccines or antivirals to combat RSV disease. A few transformed cell lines and two historic strains have been extensively used to study RSV. Here we report a thorough molecular and cell biological characterization of HEp-2 and A549 cells infected with four strains of RSV representing both major subgroups as well as historic and more contemporaneous genotypes -- [RSV/A/Tracy (GA1), RSV/A/Ontario (ON), RSV/B/18537 (GB1), RSV/B/Buenos Aires (BA)] -- via measurements of viral replication kinetics and viral gene expression, immunofluorescence-based imaging of gross cellular morphology and cell-associated RSV, and measurements of host response including transcriptional changes and levels of secreted cytokines and growth factors. Our findings strongly suggest 1) the existence of a conserved difference in gene expression between RSV subgroups A and B; 2) the A549 cell line is a more stringent and natural host of replicating RSV than the HEp-2 cell line; and 3) consistent with previous studies, determining the full effects of viral genetic variation in RSV pathogenesis requires model systems as tractable as transformed cell lines but better representative of the human host. IMPORTANCEInfection with respiratory syncytial virus (RSV) early in life is essentially guaranteed and can lead to severe disease. In vitro data from two historic RSV/A strains and two cell lines, HEp-2 and A549, constitute most of our knowledge; but RSV contains ample variation from two evolving subgroups (A and B) showing recent convergent evolution. Here we measure viral action and host response in HEp-2 and A549 cells infected with four RSV strains from both subgroups and representing both historic and more contemporaneous strains. We discover a subgroup-dependent difference in viral gene expression and find A549 cells are more potently antiviral and more sensitive, albeit subtly, to viral variation. Our findings reveal important differences between RSV subgroups and two widely used cell lines and provide baseline data for experiments with model systems better representative of natural RSV infection.

microbiology↗

bioRxiv2020

Identification of Celastrol as a novel HIV-1 Latency Reversal Agent by an Image-Based Screen

Although current antiretroviral therapies (ART) are successful in controlling HIV-1 infection, a stable viral reservoir reactivates when ART is discontinued. Consequently, there is a major research effort to develop approaches to disrupt the latent viral reservoir and enhance the immune systems ability to clear HIV-1. A number of small molecules, termed latency reversal agents (LRAs), have been identified which can reactivate latent HIV-1 in cell lines and patients cells ex vivo. However, clinical trials have suggested that combinations of LRAs will be required to efficiently reactivate HIV-1 in vivo, especially LRAs that act synergistically by functioning through distinct pathways. To identify novel LRAs, we used an image-based assay to screen a natural compound library for the ability to induce a low level of aggregation of resting primary CD4+ T cells from healthy donors. We identified celastrol as a novel LRA. Celastrol functions synergistically with other classes of LRA to reactivate latent HIV-1 in a Jurkat cell line, suggesting a novel mechanism in its LRA activity. Additionally, celastrol does not appear to activate resting CD4+ T cells at levels at which it can reactivate latent HIV-1. Celastrol appears to represent a novel class of LRAs and it therefore can serve as a lead compound for LRA development.

microbiology↗

bioRxiv2018

The Signaling Pathways Project: an integrated ‘omics knowledgebase for mammalian cellular signaling pathways

Integrated mining of public transcriptomic and ChIP-Seq datasets has the potential to illuminate facets of mammalian cellular signaling pathways not yet explored in the research literature. Here, we designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates stable community classifications of the four major categories of signaling pathway node (receptors, enzymes, transcription factors and co-nodes) and their cognate bioactive small molecules (BSMs). We then mapped over 10,000 public transcriptomic or cistromic experiments to their relevant signaling pathway node, BSM or biosample of study. To provide for prediction of pathway node-target transcriptional regulatory relationships, we generated consensus omics signatures, or consensomes, based on measures of significant differential expression of genomic targets across all underlying transcriptomic experiments. To expose the SPP knowledgebase to researchers, a web browser interface accommodates a variety of routine data mining strategies. Consensomes were validated using alignment with literature-based knowledge, gene target-level integration of transcriptomic and ChIP-Seq data points, and in bench experiments that confirmed previously uncharacterized node-gene target regulatory relationships. SPP is freely accessible at https://beta.signalingpathways.org.

bioinformatics↗