Knowledge synthesis of 100 million biomedical documents augments the deep expression profiling of coronavirus receptors

• Published in: eLife 2020-05, Vol.9
• Main Authors: Venkatakrishnan, A J, Puranik, Arjun, Anand, Akash, Zemmour, David, Yao, Xiang, Wu, Xiaoying, Chilaka, Ramakrishna, Murakowski, Dariusz K, Standish, Kristopher, Raghunathan, Bharathwaj, Wagner, Tyler, Garcia-Rivera, Enrique, Solomon, Hugo, Garg, Abhinav, Barve, Rakesh, Anyanwu-Ofili, Anuli, Khan, Najat, Soundararajan, Venky
• Format: Article
• Language: English
• Subjects: ACE2; Angiotensin-converting enzyme 2; Animals; Artificial intelligence; Artificial neural networks; Betacoronavirus - genetics; Betacoronavirus - metabolism; Coronaviridae; Coronavirus Infections - metabolism; Coronavirus Infections - pathology; Coronavirus Infections - virology; Coronaviruses; COVID-19; Datasets; Disease transmission; Enterocytes; Epidemics; Epithelial cells; Feces; Gene expression; Gene Expression Profiling; Health aspects; Human Biology and Medicine; Humans; Keratinocytes; Knowledge; Knowledge Discovery; Libraries, Medical; Machine learning; Medical research; Mice; Middle East respiratory syndrome; natural language processing; Neural networks; Pandemics; Pneumonia, Viral - metabolism; Pneumonia, Viral - pathology; Pneumonia, Viral - virology; Proteins; Proteomics; Receptors, Coronavirus; Receptors, Virus - chemistry; Receptors, Virus - genetics; Receptors, Virus - metabolism; Respiratory diseases; Ribonucleic acid; RNA; SARS-CoV-2; Severe acute respiratory syndrome coronavirus 2; single cell RNA-seq; Small intestine; Transcription
• ISSN: 2050-084X; 2050-084X
• DOI: 10.7554/eLife.58040

The COVID-19 pandemic demands assimilation of all biomedical knowledge to decode mechanisms of pathogenesis. Despite the recent renaissance in neural networks, a platform for the real-time synthesis of the exponentially growing biomedical literature and deep omics insights is unavailable. Here, we present the nferX platform for dynamic inference from over 45 quadrillion possible conceptual associations from unstructured text, and triangulation with insights from single-cell RNA-sequencing, bulk RNA-seq and proteomics from diverse tissue types. A hypothesis-free profiling of ACE2 suggests tongue keratinocytes, olfactory epithelial cells, airway club cells and respiratory ciliated cells as potential reservoirs of the SARS-CoV-2 receptor. We find the gut as the putative hotspot of COVID-19, where a maturation correlated transcriptional signature is shared in small intestine enterocytes among coronavirus receptors (ACE2, DPP4, ANPEP). A holistic data science platform triangulating insights from structured and unstructured data holds potential for accelerating the generation of impactful biological insights and hypotheses.