Impact of SARS-CoV-2 infection in pregnancy on fetal immune state

SARS-CoV-2 infection during pregnancy is associated with increased risk of adverse maternal and pregnancy outcomes. Maternal COVID- 19 is associated with immune activation and inflammatory response in the pregnant individual and an altered immune repertoire in the placenta. Mother-to-child transmission of infection is reported but uncommon. Still, the potential impact of maternal SARS-CoV-2 infection on the immunologic and inflammatory state of the infant is of interest, both for the acute health of the newborn and longer-term outcomes. In this talk, we will discuss the mixed data from cord blood and infant studies of cytokine profiles, transcriptomics, immunophenotyping, and functional studies. We will address the timing and severity of maternal infection as we explore the potential immunological consequences of in utero exposure to maternal SARS-CoV-2 infection.

IDDF2023-ABS-0045 Spatiotemporal immune landscape of Mas-driven pro-inflammatory microenvironment with hyperactivated glycolysis in acetaminophen-induced liver injury

IDDF2023-ABS-0045 Figure 1 IDDF2023-ABS-0045 Figure 2 IDDF2023-ABS-0045 Figure 3 IDDF2023-ABS-0045 Figure 4

SINGLE CELL MULTIOMIC PROFILING OF DISRUPTED REGULATORY NETWORKS IN COVID19 ASSOCIATED MULTISYSTEM INFLAMMATORY SYNDROME IN CHILDREN

BackgroundChildren infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) usually present minimal symptoms or are asymptomatic. Nevertheless, a subset of children 2-6 weeks after the initial SARS-CoV-2 infection develops a postinfectious SARS-CoV-2-related multisystem inflammatory syndrome in (MIS-C). Recently, transient expansion of TRBV11-2 T cell clonotypes in MIS-C was associated with signatures of inflammation and T cell activation, however, the underlying pathophysiology of MIS-C is not fully understood [1].ObjectivesThe purpose of our project is to characterize the complexity of cell populations and capture cellular heterogeneity to uncover the regulatory networks and interactions that are disrupted during MIS-C flare with simultaneous profiling of gene expression and open chromatin regions from the same nuclei.MethodsSamples of peripheral blood mononuclear cells from patients with MIS-C diagnosed at the University Children's Hospital, University Medical Center Ljubljana, were collected during the initial presentation before any treatment and at 6-12 months in remission. The primary aim is to identify which regulatory networks are driving inflammation in MIS-C flare, for which we are performing single cell Multiome ATAC + Gene Expression Sequencing. To enable simultaneous profiling of epigenomic landscape and gene expression from the same nuclei, we are using Chromium Next GEM Single Cell Multiome ATAC + Gene Expression kit from 10X Genomics.ResultsWe included 32 patients with MIS-C from whom we collected paired blood samples during the initial presentation before treatment and at 6-12 months in remission. In single cell multiomic experiment we included 10 patients with paired samples, with the most viable cell count prior cryopreservation. All samples that are included into multiomic single cell analysis have 75% - 99% viability prior cryopreservation. In the protocol the key is to remove remaining granulocytes causing high mitochondrial RNA burden and extensively optimize the dilution factor of lysis buffer and the length of cell lysis step in order to get intact nuclei with no significant blebbing. Afterward, the single cell ATAC libraries as well as single-cell gene expression libraries are constructed and sequenced. Data are undergoing pairwise analysis to compare the cell population heterogeneity, expression profile and open chromatin landscape in the time of the initial presentation of MIS-C and in the remission, with Cell ranger software as well as with R package scREG [2], and custom scripting. In the second step we will inspect if the resulting altered transcriptomic signature from single-cell experiment is present on larger cohort. In that regard, we will perform bulk transcriptomic profiling on all paired collected samples during the initial presentation of MIS-C before treatment and at 6-12 months in remission.ConclusionThe results of this project are expected to enlighten the underlying pathophysiology of MIS-C flare and thus support clinical decision on more targeted treatment. The identified disrupted networks during MIS-C flare could lead the way to establish an early diagnosis and improve long-term outcome, including prevention of myocardial and neuropsychological impairment. Moreover, a better understanding of the disrupted regulatory networks that are driving inflammation in MIS-C, could lead to new insights into diseases with similar clinical presentations as is Kawasaki Disease.References[1]Sacco, K., Castagnoli, R., Vakkilainen, S. et al. Immunopathological signatures in multisystem inflammatory syndrome in children and pediatric COVID-19. Nat Med 28, 1050–1062 (2022).[2]Duren, Z., Chang, F., Naqing, F. et al. Regulatory analysis of single cell multiome gene expression and chromatin accessibility data with scREG. Genome Biol 23, 114 (2022).AcknowledgementsThis research was supported by Slovenian research agency grant J3-3061 and Interreg ITA-SLO project Cattedra.Disclosure of InterestsNone Declared.

Dynamics of Gene Expression Profiling and Identification of High-Risk Patients for Severe COVID-19.

The clinical manifestations of SARS-CoV-2 infection vary widely, from asymptomatic infection to the development of acute respiratory distress syndrome (ARDS) and death. The host response elicited by SARS-CoV-2 plays a key role in determining the clinical outcome. We hypothesized that determining the dynamic whole blood transcriptomic profile of hospitalized adult COVID-19 patients and characterizing the subgroup that develops severe disease and ARDS would broaden our understanding of the heterogeneity in clinical outcomes. We recruited 60 hospitalized patients with RT-PCR-confirmed SARS-CoV-2 infection, among whom 19 developed ARDS. Peripheral blood was collected using PAXGene RNA tubes within 24 h of admission and on day 7. There were 2572 differently expressed genes in patients with ARDS at baseline and 1149 at day 7. We found a dysregulated inflammatory response in COVID-19 ARDS patients, with an increased expression of genes related to pro-inflammatory molecules and neutrophil and macrophage activation at admission, in addition to an immune regulation loss. This led, in turn, to a higher expression of genes related to reactive oxygen species, protein polyubiquitination, and metalloproteinases in the latter stages. Some of the most significant differences in gene expression found between patients with and without ARDS corresponded to long non-coding RNA involved in epigenetic control.

Comparative spatial transcriptomic profiling of severe acute respiratory syndrome coronavirus 2 Delta and Omicron variants infections in the lungs of cynomolgus macaques.

Recently emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variants are generally less pathogenic than previous strains. However, elucidating the molecular basis for pulmonary immune response alterations is challenging owing to the virus's heterogeneous distribution within complex tissue structure. Here, we revealed the spatial transcriptomic profiles of pulmonary microstructures at the SARS-CoV-2 infection site in the nine cynomolgus macaques upon inoculation with the Delta and Omicron variants. Delta- and Omicron-infected lungs had upregulation of genes involved in inflammation, cytokine response, complement, cell damage, proliferation, and differentiation pathways. Depending on the tissue microstructures (alveoli, bronchioles, and blood vessels), there were differences in the types of significantly upregulated genes in each pathway. Notably, a limited number of genes involved in cytokine and cell damage response were differentially expressed between bronchioles of the Delta- and Omicron-infection groups. These results indicated that despite a significant antigenic shift in SARS-CoV-2, the host immune response mechanisms induced by the variants were relatively consistent, with limited transcriptional alterations observed only in large airways. This study may aid in understanding the pathogenesis of SARS-CoV-2 and developing a clinical strategy for addressing immune dysregulation by identifying potential transcriptional biomarkers within pulmonary microstructures during infection with emerging variants.

The promise and challenge of spatial omics in dissecting tumour microenvironment and the role of AI.

Growing evidence supports the critical role of tumour microenvironment (TME) in tumour progression, metastases, and treatment response. However, the in-situ interplay among various TME components, particularly between immune and tumour cells, are largely unknown, hindering our understanding of how tumour progresses and responds to treatment. While mainstream single-cell omics techniques allow deep, single-cell phenotyping, they lack crucial spatial information for in-situ cell-cell interaction analysis. On the other hand, tissue-based approaches such as hematoxylin and eosin and chromogenic immunohistochemistry staining can preserve the spatial information of TME components but are limited by their low-content staining. High-content spatial profiling technologies, termed spatial omics, have greatly advanced in the past decades to overcome these limitations. These technologies continue to emerge to include more molecular features (RNAs and/or proteins) and to enhance spatial resolution, opening new opportunities for discovering novel biological knowledge, biomarkers, and therapeutic targets. These advancements also spur the need for novel computational methods to mine useful TME insights from the increasing data complexity confounded by high molecular features and spatial resolution. In this review, we present state-of-the-art spatial omics technologies, their applications, major strengths, and limitations as well as the role of artificial intelligence (AI) in TME studies.

Diagnosis of Multisystem Inflammatory Syndrome in Children by a Whole-Blood Transcriptional Signature.

BACKGROUND: To identify a diagnostic blood transcriptomic signature that distinguishes multisystem inflammatory syndrome in children (MIS-C) from Kawasaki disease (KD), bacterial infections, and viral infections. METHODS: Children presenting with MIS-C to participating hospitals in the United Kingdom and the European Union between April 2020 and April 2021 were prospectively recruited. Whole-blood RNA Sequencing was performed, contrasting the transcriptomes of children with MIS-C (n = 38) to those from children with KD (n = 136), definite bacterial (DB; n = 188) and viral infections (DV; n = 138). Genes significantly differentially expressed (SDE) between MIS-C and comparator groups were identified. Feature selection was used to identify genes that optimally distinguish MIS-C from other diseases, which were subsequently translated into RT-qPCR assays and evaluated in an independent validation set comprising MIS-C (n = 37), KD (n = 19), DB (n = 56), DV (n = 43), and COVID-19 (n = 39). RESULTS: In the discovery set, 5696 genes were SDE between MIS-C and combined comparator disease groups. Five genes were identified as potential MIS-C diagnostic biomarkers (HSPBAP1, VPS37C, TGFB1, MX2, and TRBV11-2), achieving an AUC of 96.8% (95% CI: 94.6%-98.9%) in the discovery set, and were translated into RT-qPCR assays. The RT-qPCR 5-gene signature achieved an AUC of 93.2% (95% CI: 88.3%-97.7%) in the independent validation set when distinguishing MIS-C from KD, DB, and DV. CONCLUSIONS: MIS-C can be distinguished from KD, DB, and DV groups using a 5-gene blood RNA expression signature. The small number of genes in the signature and good performance in both discovery and validation sets should enable the development of a diagnostic test for MIS-C.

Systems genetics identifies miRNA-mediated regulation of host response in COVID-19.

BACKGROUND: Individuals infected with SARS-CoV-2 vary greatly in their disease severity, ranging from asymptomatic infection to severe disease. The regulation of gene expression is an important mechanism in the host immune response and can modulate the outcome of the disease. miRNAs play important roles in post-transcriptional regulation with consequences on downstream molecular and cellular host immune response processes. The nature and magnitude of miRNA perturbations associated with blood phenotypes and intensive care unit (ICU) admission in COVID-19 are poorly understood. RESULTS: We combined multi-omics profiling-genotyping, miRNA and RNA expression, measured at the time of hospital admission soon after the onset of COVID-19 symptoms-with phenotypes from electronic health records to understand how miRNA expression contributes to variation in disease severity in a diverse cohort of 259 unvaccinated patients in Abu Dhabi, United Arab Emirates. We analyzed 62 clinical variables and expression levels of 632 miRNAs measured at admission and identified 97 miRNAs associated with 8 blood phenotypes significantly associated with later ICU admission. Integrative miRNA-mRNA cross-correlation analysis identified multiple miRNA-mRNA-blood endophenotype associations and revealed the effect of miR-143-3p on neutrophil count mediated by the expression of its target gene BCL2. We report 168 significant cis-miRNA expression quantitative trait loci, 57 of which implicate miRNAs associated with either ICU admission or a blood endophenotype. CONCLUSIONS: This systems genetics study has given rise to a genomic picture of the architecture of whole blood miRNAs in unvaccinated COVID-19 patients and pinpoints post-transcriptional regulation as a potential mechanism that impacts blood traits underlying COVID-19 severity. The results also highlight the impact of host genetic regulatory control of miRNA expression in early stages of COVID-19 disease.

Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene sets.

Background: Sepsis is a dysfunctional host response to infection. The syndrome leads to millions of deaths annually (19.7% of all deaths in 2017) and is the cause of most deaths from severe Covid infections. High throughput sequencing or 'omics' experiments in molecular and clinical sepsis research have been widely utilized to identify new diagnostics and therapies. Transcriptomics, quantifying gene expression, has dominated these studies, due to the efficiency of measuring gene expression in tissues and the technical accuracy of technologies like RNA-Seq. Objective: Most of these studies seek to uncover novel mechanistic insights into sepsis pathogenesis and diagnostic gene signatures by identifying genes differentially expressed between two or more relevant conditions. However, little effort has been made, to date, to aggregate this knowledge from such studies. In this study we sought to build a compendium of previously described gene sets that combines knowledge gained from sepsis-associated studies. This would enable the identification of genes most associated with sepsis pathogenesis, and the description of the molecular pathways commonly associated with sepsis. Methods: PubMed was searched for studies using transcriptomics to characterize acute infection/sepsis and severe sepsis (i.e., sepsis combined with organ failure). Several studies were identified that used transcriptomics to identify differentially expressed (DE) genes, predictive/prognostic signatures, and underlying molecular responses and pathways. The molecules included in each gene set were collected, in addition to the relevant study metadata (e.g., patient groups used for comparison, sample collection time point, tissue type, etc.). Results: After performing extensive literature curation of 74 sepsis-related publications involving transcriptomics, 103 unique gene sets (comprising 20,899 unique genes) from thousands of patients were collated together with associated metadata. Frequently described genes included in gene sets as well as the molecular mechanisms they were involved in were identified. These mechanisms included neutrophil degranulation, generation of second messenger molecules, IL-4 and -13 signaling, and IL-10 signaling among many others. The database, which we named SeptiSearch, is made available in a web application created using the Shiny framework in R, (available at https://septisearch.ca). Conclusions: SeptiSearch provides members of the sepsis community the bioinformatic tools needed to leverage and explore the gene sets contained in the database. This will allow the gene sets to be further scrutinized and analyzed for their enrichment in user-submitted gene expression data and used for validation of in-house gene sets/signatures.

Antifungal Activity and Potential Action Mechanism of Allicin against Trichosporon asahii.

Trichosporon asahii is an emerging opportunistic pathogen that causes potentially fatal disseminated trichosporonosis. The global prevalence of coronavirus disease 2019 (COVID-19) poses an increasing fungal infection burden caused by T. asahii. Allicin is the main biologically active component with broad-spectrum antimicrobial activity in garlic. In this study, we performed an in-depth analysis of the antifungal characteristics of allicin against T. asahii based on physiological, cytological, and transcriptomic assessments. In vitro, allicin inhibited the growth of T. asahii planktonic cells and biofilm cells significantly. In vivo, allicin improved the mean survival time of mice with systemic trichosporonosis and reduced tissue fungal burden. Electron microscopy observations clearly demonstrated damage to T. asahii cell morphology and ultrastructure caused by allicin. Furthermore, allicin increased intracellular reactive oxygen species (ROS) accumulation, leading to oxidative stress damage in T. asahii cells. Transcriptome analysis showed that allicin treatment disturbed the biosynthesis of cell membrane and cell wall, glucose catabolism, and oxidative stress. The overexpression of multiple antioxidant enzymes and transporters may also place an additional burden on cells, causing them to collapse. Our findings shed new light on the potential of allicin as an alternative treatment strategy for trichosporonosis. IMPORTANCE Systemic infection caused by T. asahii has recently been recognized as an important cause of mortality in hospitalized COVID-19 patients. Invasive trichosporonosis remains a significant challenge for clinicians, due to the limited therapeutic options. The present work suggests that allicin holds great potential as a therapeutic candidate for T. asahii infection. Allicin demonstrated potent in vitro antifungal activity and potential in vivo protective effects. In addition, transcriptome sequencing provided valuable insights into the antifungal effects of allicin.

Multi-scale Mechanisms of Maxing Shigantang in Treating Pneumonia Based on Transcriptomic Data.

Objective: Pneumonia is an infectious inflammation of the alveoli,distal airway,and interstitium caused by bacterial,viral,and other pathogens. Maxing Shigantang,originated from Treatise On Cold Damage Diseases,is a classic prescription for treating pneumonia,with significant clinical efficacy. However,its treatment mechanism is still elusive. Method(s): In that paper,the transcriptome-based multi-scale network pharmacology was used to reveal the overall pharmacological mechanism of Maxing Shigantang in treating pneumonia from six scales of tissue,cell,pathological process,biological process,signaling pathway, and target. Result(s):At the tissue level,Maxing Shigantang mainly acted on the focal tissue of pneumonia-lung and the main inflammatory immune tissues-blood and spleen. Analysis of cell,pathological process and biological process suggested that Maxing Shigantang could treat pneumonia by reversing inflammatory and immune functions and improving cardiopulmonary and vascular injury caused by pneumonia. Analysis of signaling pathway and target showed that Maxing Shigantang regulated inflammatory immune response pathways such as "coronavirus disease-COVID-19" and "Toll-like receptor signaling pathway",and related targets such as "MAPKAPK3" and "NRG1". Conclusion(s):This paper,from molecular to tissue levels,indicated Maxing Shigantang treated pneumonia mainly by regulating inflammatory immune response and improving cardiopulmonary and vascular injury.Copyright © 2023, China Academy of Chinese Medical Sciences Institute of Chinese Materia Medica. All rights reserved.

A Counterintuitive Neutrophil-Mediated Pattern in COVID-19 Patients Revealed through Transcriptomics Analysis.

The COVID-19 pandemic has persisted for almost three years. However, the mechanisms linked to the SARS-CoV-2 effect on tissues and disease severity have not been fully elucidated. Since the onset of the pandemic, a plethora of high-throughput data related to the host transcriptional response to SARS-CoV-2 infections has been generated. To this end, the aim of this study was to assess the effect of SARS-CoV-2 infections on circulating and organ tissue immune responses. We profited from the publicly accessible gene expression data of the blood and soft tissues by employing an integrated computational methodology, including bioinformatics, machine learning, and natural language processing in the relevant transcriptomics data. COVID-19 pathophysiology and severity have mainly been associated with macrophage-elicited responses and a characteristic "cytokine storm". Our counterintuitive findings suggested that the COVID-19 pathogenesis could also be mediated through neutrophil abundance and an exacerbated suppression of the immune system, leading eventually to uncontrolled viral dissemination and host cytotoxicity. The findings of this study elucidated new physiological functions of neutrophils, as well as tentative pathways to be explored in asymptomatic-, ethnicity- and locality-, or staging-associated studies.

Metatranscriptomics analysis reveals a novel transcriptional and translational landscape during Middle East respiratory syndrome coronavirus infection.

Among all RNA viruses, coronavirus RNA transcription is the most complex and involves a process termed "discontinuous transcription" that results in the production of a set of 3'-nested, co-terminal genomic and subgenomic RNAs during infection. While the expression of the classic canonical set of subgenomic RNAs depends on the recognition of a 6- to 7-nt transcription regulatory core sequence (TRS), here, we use deep sequence and metagenomics analysis strategies and show that the coronavirus transcriptome is even more vast and more complex than previously appreciated and involves the production of leader-containing transcripts that have canonical and noncanonical leader-body junctions. Moreover, by ribosome protection and proteomics analyses, we show that both positive- and negative-sense transcripts are translationally active. The data support the hypothesis that the coronavirus proteome is much vaster than previously noted in the literature.

Multi-Omics Profiling for Health.

The world has witnessed a steady rise in both non-infectious and infectious chronic diseases, prompting a cross-disciplinary approach to understand and treating disease. Current medical care focuses on treating people after they become patients rather than preventing illness, leading to high costs in treating chronic and late-stage diseases. Additionally, a "one-size-fits all" approach to health care does not take into account individual differences in genetics, environment, or lifestyle factors, decreasing the number of people benefiting from interventions. Rapid advances in omics technologies and progress in computational capabilities have led to the development of multi-omics deep phenotyping, which profiles the interaction of multiple levels of biology over time and empowers precision health approaches. This review highlights current and emerging multi-omics modalities for precision health and discusses applications in the following areas: genetic variation, cardio-metabolic diseases, cancer, infectious diseases, organ transplantation, pregnancy, and longevity/aging. We will briefly discuss the potential of multi-omics approaches in disentangling host-microbe and host-environmental interactions. We will touch on emerging areas of electronic health record and clinical imaging integration with muti-omics for precision health. Finally, we will briefly discuss the challenges in the clinical implementation of multi-omics and its future prospects.

Dynamic and spatial transcriptional responses in COVID-19-related chilblains

"COVID-toes" are chilblains that occurred in patients who may have been exposed to SARS-CoV-2, but without COVID-19 symptoms and/or with negative PCR or serology. The literature suggests that chilblains are an unexpected consequence of a strong interferon-mediated antiviral response, but the underlying molecular mechanisms remain poorly understood. We thus sought to explore the physiopathology of COVID-related chilblains by using spatially and temporally resolved transcriptomics. We included 19 patients with COVID-toes, and performed a complete virological assessment to exclude SARS-CoV-2 infection including skin viral metagenomics. Some patients had clinical symptoms evoking viral infection, but none had COVID-19. Apart from low levels of non-conventional antiphospholipid antibodies, biological tests were unremarkable. We performed spatially resolved transcriptomics (Visium, 10X Genomics) in 3 patients at different timepoints and compared them with 1 vaccination-related chilblain. We observed a different transcriptional profile in COVID-toes compared with COVID-19 vaccine-related chilblains. IRF1, CXCL10, ISG15 and STAT1 were highly expressed in COVID-toes and their expression decreased over time, confirming an activation of interferon and JAK/STAT pathways that was absent in vaccine-related chilblains. The proportion of inflammatory cell types obtained by spatial deconvolution varied over time in COVID-toes. Migratory dendritic cells were present at early stages, while T lymphocytes populations increased later. Overall, this work explores the mechanisms of COVID-19-related chilblains using spatially and temporally resolved transcriptomics.Copyright © 2023

Constructing custom-made radiotranscriptomic signatures from CT angiograms: An application in COVID-19 vascular inflammation

Background: Advances in computational methodologies have enabled processing of large datasets originating from imaging studies. However, most imaging biomarkers suffer from a lack of direct links with underlying biology, as they are only observationally correlated with pathophysiology. Purpose(s): To develop and validate a novel AI-assisted image analysis platform, by applying quantitative radiotranscriptomics that quantifies cytokinedriven vascular inflammation from routine CT angiograms (CTA) performed as part of clinical care in COVID-19. Method(s): We used this platform to train the radiotranscriptomic signature C19-RS, derived from the perivascular space around the aorta and the internal mammary artery in routine chest CTAs, to best describe cytokinedriven vascular inflammation, defined using transcriptomic profiles from RNA sequencing data from human arterial biopsies (A). This signature was validated externally in 358 clinically indicated CT pulmonary angiograms from patients with or without COVID-19 from 3 different geographical regions. Result(s): First, 22 patients who had a CTA before the pandemic underwent repeat CTA <6 months post COVID-19 infection (B). Compared with 22 controls (matched for age, gender, and BMI) C19-RS was increased only in the COVID-19 group (C). Next, C19-RS was calculated in a cohort of 331 patients hospitalised during the pandemic, and was higher in COVID-19 positives (adjusted OR=2.97 [95% CI: 1.43-6.27], p=0.004, D). C19-RS had prognostic value for in-hospital mortality in COVID-19, with HR=3.31 ([95% CI: 1.49-7.33], p=0.003) and 2.58 ([95% CI: 1.10-6.05], p=0.028) in two testing cohorts respectively (E, F), adjusted for clinical factors and biochemical biomarkers of inflammation and myocardial injury. The corrected HR for in-hospital mortality was 8.24 [95% CI: 2.16-31.36], p=0.002 for those who received no treatment with dexamethasone, but only 2.27 [95% CI: 0.69-7.55], p=0.18 in those who received dexamethasone subsequently to the C19-RS based image analysis, suggesting that vascular inflammation may have been a therapeutic target of dexamethasone in COVID-19. Finally, C19-RS was strongly associated (r=0.61, p=0.0003) with a whole blood transcriptional module representing dysregulation of coagulation and platelet aggregation pathways. Conclusion(s): We present the first proof of concept study that combines transcriptomics with radiomics to provide a platform for the development of machine learning derived radiotranscriptomics analysis of routine clinical CT scans for the development of non-invasive imaging biomarkers. Application in COVID-19 produced C19-RS, a marker of cytokine-driven inflammation driving systemic activation of coagulation, that predicts inhospital mortality and identifies people who will have better response to anti-inflammatory treatments, allowing targeted therapy. This AI-assisted image analysis platform may have applications across a wide range of vascular diseases, from infections to autoimmune diseases.

In silico identification of potential miRNAs -mRNA inflammatory networks implicated in the pathogenesis of COVID-19

COVID-19 has been found to affect the expression profile of several mRNAs and miRNAs, leading to dysregulation of a number of signaling pathways, particularly those related to inflammatory responses. In the current study, a systematic biology procedure was used for the analysis of high-throughput expression data from blood specimens of COVID-19 and healthy individuals. Differentially expressed miRNAs in blood specimens of COVID-19 vs. healthy specimens were then identified to construct and analyze miRNA-mRNA networks and predict key miRNAs and genes in inflammatory pathways. Our results showed that 171 miRNAs were expressed as outliers in box plot and located in the critical areas according to our statistical analysis. Among them, 8 miRNAs, namely miR-1275, miR-4429, miR-4489, miR-6721-5p, miR-5010-5p, miR-7110-5p, miR-6804-5p and miR-6881-3p were found to affect expression of key genes in NF-KB, JAK/STAT and MAPK signaling pathways implicated in COVID-19 pathogenesis. In addition, our results predicted that 25 genes involved in above-mentioned inflammatory pathways were targeted not only by these 8 miRNAs but also by other obtained miRNAs (163 miRNAs). The results of the current in silico study represent candidate targets for further studies in COVID-19.Copyright © 2023 Elsevier B.V.

Transcriptomic approaches in COVID-19: From infection to vaccines

Transcriptomics technologies have enabled the rapid response to the coronavirus disease 2019 (COVID-19) pandemic. A variety of platforms including oligonucleotide microarrays, RNA sequencing (RNA-seq), and single-cell RNA-seq (scRNA-seq) have been applied to the most diverse set of samples acquired from cell cultures, organoids, and animal models experimentally infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as well as from cells, tissues, and biofluids from COVID-19 patients. In this chapter, we will discuss transcriptomic approaches used to determine the aspects of SARS-CoV-2 structure, entry and replication, understand host responses to infection, identify diagnostic signatures, discovery, and repurpose drugs, and to elucidate the protective correlates of vaccination. © 2023 Elsevier Inc. All rights reserved.

Gene expression in organoids: an expanding horizon.

Recent development of human three-dimensional organoid cultures has opened new doors and opportunities ranging from modelling human development in vitro to personalised cancer therapies. These new in vitro systems are opening new horizons to the classic understanding of human development and disease. However, the complexity and heterogeneity of these models requires cutting-edge techniques to capture and trace global changes in gene expression to enable identification of key players and uncover the underlying molecular mechanisms. Rapid development of sequencing approaches made possible global transcriptome analyses and epigenetic profiling. Despite challenges in organoid culture and handling, these techniques are now being adapted to embrace organoids derived from a wide range of human tissues. Here, we review current state-of-the-art multi-omics technologies, such as single-cell transcriptomics and chromatin accessibility assays, employed to study organoids as a model for development and a platform for precision medicine.