Indian Echis carinatus bite causes sustained tissue destruction at the bite site. Neutrophils, the major leukocytes in the early defence process, accumulate at the bite site. Here we show that E. carinatus venom induces neutrophil extracellular trap (NET) formation. The NETs block the blood vessels and entrap the venom toxins at the injection site, promoting tissue destruction. The stability of NETs is attributed to the lack of NETs-degrading DNase activity in E. carinatus venom. In a mouse tail model, mice co-injected with venom and DNase 1, and neutropenic mice injected with the venom, do not develop NETs, venom accumulation and tissue destruction at the injected site. Strikingly, venom-induced mice tail tissue destruction is also prevented by the subsequent injection of DNase 1. Thus, our study suggests that DNase 1 treatment may have a therapeutic potential for preventing the tissue destruction caused by snake venom.

Modeling human diseases as networks simplify complex multi-cellular processes, helps understand patterns in noisy data that humans cannot find, and thereby improves precision in prediction. Using Inflammatory Bowel Disease (IBD) as an example, here we outline an unbiased AI-assisted approach for target identification and validation. A network was built in which clusters of genes are connected by directed edges that highlight asymmetric Boolean relationships. Using machine-learning, a path of continuum states was pinpointed, which most effectively predicted disease outcome. This path was enriched in gene-clusters that maintain the integrity of the gut epithelial barrier. We exploit this insight to prioritize one target, choose appropriate pre-clinical murine models for target validation and design patient-derived organoid models. Potential for treatment efficacy is confirmed in patient-derived organoids using multivariate analyses. This AI-assisted approach identifies a first-in-class gut barrier-protective agent in IBD and predicted Phase-III success of candidate agents.

Chronic diseases, including inflammatory bowel disease (IBD) urgently need new biomarkers as a significant proportion of patients, do not respond to current medications. Inflammation is a common factor in these diseases, and microbial sensing in the intestinal tract is critical to initiate the inflammation. We have identified ELMO1 (engulfment and cell motility protein 1) as a microbial sensor in epithelial and phagocytic cells that turns on inflammatory signals. Using a stem cell‐based ‘gut‐in‐a‐dish’ coculture model, we studied the interactions between microbes, epithelium, and monocytes in the context of IBD. To mimic the in vivo cell physiology, enteroid‐derived monolayers (EDMs) were generated from the organoids isolated from WT and ELMO1−/− mice and colonic biopsies of IBD patients. The EDMs were infected with the IBD‐associated microbes to monitor the inflammatory responses. ELMO1‐depleted EDMs displayed a significant reduction in bacterial internalization, a decrease in pro‐inflammatory cytokine productions and monocyte recruitment. The expression of ELMO1 is elevated in the colonic epithelium and in the inflammatory infiltrates within the lamina propria of IBD patients where the higher expression is positively correlated with the elevated expression of pro‐inflammatory cytokines, MCP‐1 and TNF‐α. MCP‐1 is released from the epithelium and recruits monocytes to the site of inflammation. Once recruited, monocytes require ELMO1 to engulf the bacteria and propagate a robust TNF‐α storm. These findings highlight that the dysregulated epithelial ELMO1 → MCP‐1 axis can serve as an early biomarker in the diagnostics of IBD and other inflammatory disorders.

Background: SARS-CoV-2, the virus responsible for COVID-19, causes widespread damage in the lungs in the setting of an overzealous immune response whose origin remains unclear.Method: We present a scalable, propagable, personalized, cost-effective adult stem cell-derived human lung organoid model that is complete with both proximal and distal airway epithelia. Monolayers derived from adult lung organoids (ALOs), primary airway cells, or hiPSC-derived alveolar type-II (AT2) pneumocytes were infected with SARS-CoV-2 to create in vitro lung models of COVID-19.Results: Infected ALO-monolayers best recapitulated the transcriptomic signatures in diverse cohorts of COVID-19 patient-derived respiratory samples. The airway (proximal) cells were critical for sustained viral infection, whereas distal alveolar differentiation (AT2→AT1) was critical for mounting the overzealous host immune response in fatal disease; ALO monolayers with well-mixed proximodistal airway components recapitulated both.Conclusions: Findings validate a human lung model of COVID-19, which can be immediately utilized to investigate COVID-19 pathogenesis and vet new therapies and vaccines.Funding: This work was supported by the National Institutes for Health (NIH) grants 1R01DK107585-01A1, 3R01DK107585-05S1 (to SD); R01-AI141630, CA100768 and CA160911 (to PG) and R01-AI 155696 (to PG, DS and SD); R00-CA151673 and R01-GM138385 (to DS), R01- HL32225 (to PT), UCOP-R00RG2642 (to SD and PG), UCOP-R01RG3780 (to P.G. and D.S) and a pilot award from the Sanford Stem Cell Clinical Center at UC San Diego Health (P.G, S.D, D.S). GDK was supported through The American Association of Immunologists Intersect Fellowship Program for Computational Scientists and Immunologists. L.C.A's salary was supported in part by the VA San Diego Healthcare System. This manuscript includes data generated at the UC San Diego Institute of Genomic Medicine (IGC) using an Illumina NovaSeq 6000 that was purchased with funding from a National Institutes of Health SIG grant (#S10 OD026929).

We sought to define the host immune response, a.k.a, the cytokine storm that has been implicated in fatal COVID-19 using an AI-based approach. Over 45,000 transcriptomic datasets of viral pandemics were analyzed to extract a 166-gene signature using ACE2 as a seed gene; ACE2 was rationalized because it encodes the receptor that facilitates the entry of SARS-CoV-2 (the virus that causes COVID-19) into host cells. Surprisingly, this 166-gene signature was conserved in all viral pandemics, including COVID-19, and a subset of 20-genes classified disease severity, inspiring the nomenclatures ViPand severe-ViPsignatures, respectively. The ViPsignatures pinpointed a paradoxical phenomenon wherein lung epithelial and myeloid cells mount an IL15 cytokine storm, and epithelial and NK cell senescence and apoptosis determines severity/fatality. Precise therapeutic goals were formulated and subsequently validated in high-dose SARS-CoV-2-challenged hamsters using neutralizing antibodies that abrogate SARS-CoV-2/ACE2 engagement. IL15/IL15RA were elevated in the lungs of patients with fatal disease, and plasma levels of the cytokine tracked with disease severity. Thus, the ViP signatures provide a quantitative and qualitative framework for titrating the immune response in viral pandemics and may serve as a powerful unbiased tool to rapidly assess disease severity and vet candidate drugs.