Selective deployment of transcription factor paralogs with submaximal strength facilitates gene regulation in the immune system.

In multicellular organisms, duplicated genes can diverge through tissue-specific gene expression patterns, as exemplified by highly regulated expression of RUNX transcription factor paralogs with apparent functional redundancy. Here we asked what cell-type-specific biologies might be supported by the selective expression of RUNX paralogs during Langerhans cell and inducible regulatory T cell differentiation. We uncovered functional nonequivalence between RUNX paralogs. Selective expression of native paralogs allowed integration of transcription factor activity with extrinsic signals, while non-native paralogs enforced differentiation even in the absence of exogenous inducers. DNA binding affinity was controlled by divergent amino acids within the otherwise highly conserved RUNT domain and evolutionary reconstruction suggested convergence of RUNT domain residues toward submaximal strength. Hence, the selective expression of gene duplicates in specialized cell types can synergize with the acquisition of functional differences to enable appropriate gene expression, lineage choice and differentiation in the mammalian immune system.

NextPBM: a platform to study cell-specific transcription factor binding and cooperativity.

High-throughput (HT) in vitro methods for measuring protein-DNA binding have become invaluable for characterizing transcription factor (TF) complexes and modeling gene regulation. However, current methods do not utilize endogenous proteins and, therefore, do not quantify the impact of cell-specific post-translational modifications (PTMs) and cooperative cofactors. We introduce the HT nextPBM (nuclear extract protein-binding microarray) approach to study DNA binding of native cellular TFs that accounts for PTMs and cell-specific cofactors. We integrate immune-depletion and phosphatase treatment steps into our nextPBM pipeline to characterize the impact of cofactors and phosphorylation on TF binding. We analyze binding of PU.1/SPI1 and IRF8 from human monocytes, delineate DNA-sequence determinants for their cooperativity, and show how PU.1 affinity correlates with enhancer status and the presence of cooperative and collaborative cofactors. We describe how nextPBMs, and our accompanying computational framework, can be used to discover cell-specific cofactors, screen for synthetic cooperative DNA elements, and characterize TF cooperativity.

DNA-binding landscape of IRF3, IRF5 and IRF7 dimers: implications for dimer-specific gene regulation.

Transcription factors IRF3, IRF5 and IRF7 (IRF3/5/7) have overlapping, yet distinct, roles in the mammalian response to pathogens. To examine the role that DNA-binding specificity plays in delineating IRF3/5/7-specific gene regulation we used protein-binding microarrays (PBMs) to characterize the DNA binding of IRF3/5/7 homodimers. We identified both common and dimer-specific DNA binding sites, and show that DNA-binding differences can translate into dimer-specific gene regulation. Central to the antiviral response, IRF3/5/7 regulate type I interferon (IFN) genes. We show that IRF3 and IRF7 bind to many interferon-stimulated response element (ISRE)-type sites in the virus-response elements (VREs) of IFN promoters. However, strikingly, IRF5 does not bind the VREs, suggesting evolutionary selection against IRF5 homodimer binding. Mutational analysis reveals a critical specificity-determining residue that inhibits IRF5 binding to the ISRE-variants present in the IFN gene promoters. Integrating PBM and reporter gene data we find that both DNA-binding affinity and affinity-independent mechanisms determine the function of DNA-bound IRF dimers, suggesting that DNA-based allostery plays a role in IRF binding site function. Our results provide new insights into the role and limitations of DNA-binding affinity in delineating IRF3/5/7-specific gene expression.

Estimating the heritability of SARS-CoV-2 susceptibility and COVID-19 severity.

SARS-CoV-2 has infected over 340 million people, prompting therapeutic research. While genetic studies can highlight potential drug targets, understanding the heritability of SARS-CoV-2 susceptibility and COVID-19 severity can contextualize their results. To date, loci from meta-analyses explain 1.2% and 5.8% of variation in susceptibility and severity respectively. Here we estimate the importance of shared environment and additive genetic variation to SARS-CoV-2 susceptibility and COVID-19 severity using pedigree data, PCR results, and hospitalization information. The relative importance of genetics and shared environment for susceptibility shifted during the study, with heritability ranging from 33% (95% CI: 20%-46%) to 70% (95% CI: 63%-74%). Heritability was greater for days hospitalized with COVID-19 (41%, 95% CI: 33%-57%) compared to shared environment (33%, 95% CI: 24%-38%). While our estimates suggest these genetic architectures are not fully understood, the shift in susceptibility estimates highlights the challenge of estimation during a pandemic, given environmental fluctuations and vaccine introduction.

Using machine learning probabilities to identify effects of COVID-19.

Coronavirus disease 2019 (COVID-19), the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, has had extensive economic, social, and public health impacts in the United States and around the world. To date, there have been more than 600 million reported infections worldwide with more than 6 million reported deaths. Retrospective analysis, which identified comorbidities, risk factors, and treatments, has underpinned the response. As the situation transitions to an endemic, retrospective analyses using electronic health records will be important to identify the long-term effects of COVID-19. However, these analyses can be complicated by incomplete records, which makes it difficult to differentiate visits where the patient had COVID-19. To address this issue, we trained a random Forest classifier to assign a probability of a patient having been diagnosed with COVID-19 during each visit. Using these probabilities, we found that higher COVID-19 probabilities were associated with a future diagnosis of myocardial infarction, urinary tract infection, acute renal failure, and type 2 diabetes.

Shotgun transcriptome, spatial omics, and isothermal profiling of SARS-CoV-2 infection reveals unique host responses, viral diversification, and drug interactions.

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin-angiotensin-aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies.

Melatonin is significantly associated with survival of intubated COVID-19 patients.

Background
Respiratory distress requiring intubation is the most serious complication associated with coronavirus disease 2019 (COVID-19).
Methods In this retrospective study, we used survival analysis to determine whether or not mortality following intubation was associated with hormone exposure in patients treated at New York Presbyterian/ Columbia University Irving Medical Center. Here, we report the overall hazards ratio for each hormone for exposure before and after intubation for intubated and mechanically ventilated patients.
Results Among the 189,987 patients, we identified 948 intubation periods across 791 patients who were diagnosed with COVID-19 or infected with SARS-CoV2 and 3,497 intubation periods across 2,981 patients who were not. Melatonin exposure after intubation was statistically associated with a positive outcome in COVID-19 (demographics and comorbidities adjusted HR: 0.131, 95% CI: 7.76E-02 - 0.223, p -value = 8.19E-14) and non-COVID-19 (demographics and comorbidities adjusted HR: 0.278, 95% CI: 0.142 - 0.542, p -value = 1.72E-04) intubated patients. Additionally, melatonin exposure after intubation was statically associated with a positive outcome in COVID-19 patients (demographics and comorbidities adjusted HR: 0.127, 95% CI: 6.01E-02 - 0.269, p -value = 7.15E-08).
Conclusions Melatonin exposure after intubation is significantly associated with a positive outcome in COVID-19 and non-COVID-19 patients. Additionally, melatonin exposure after intubation is significantly associated with a positive outcome in COVID-19 patients requiring mechanical ventilation. While our models account for many covariates, including clinical history and demographics, it is impossible to rule out confounding or collider biases within our population. Further study into the possible mechanism of this observation is warranted.

Identification of Immune complement function as a determinant of adverse SARS-CoV-2 infection outcome.

Understanding the pathophysiology of SARS-CoV-2 infection is critical for therapeutics and public health intervention strategies. Viral-host interactions can guide discovery of regulators of disease outcomes, and protein structure function analysis points to several immune pathways, including complement and coagulation, as targets of the coronavirus proteome. To determine if conditions associated with dysregulation of the complement or coagulation systems impact adverse clinical outcomes, we performed a retrospective observational study of 11,116 patients who presented with suspected SARS-CoV-2 infection. We found that history of macular degeneration (a proxy for complement activation disorders) and history of coagulation disorders (thrombocytopenia, thrombosis, and hemorrhage) are risk factors for morbidity and mortality in SARS-CoV-2 infected patients - effects that could not be explained by age, sex, or history of smoking. Further, transcriptional profiling of nasopharyngeal (NP) swabs from 650 control and SARS-CoV-2 infected patients demonstrated that in addition to innate Type-I interferon and IL-6 dependent inflammatory immune responses, infection results in robust engagement and activation of the complement and coagulation pathways. Finally, we conducted a candidate driven genetic association study of severe SARS-CoV-2 disease. Among the findings, our scan identified putative complement and coagulation associated loci including missense, eQTL and sQTL variants of critical regulators of the complement and coagulation cascades. In addition to providing evidence that complement function modulates SARS-CoV-2 infection outcome, the data point to putative transcriptional genetic markers of susceptibility. The results highlight the value of using a multi-modal analytical approach, combining molecular information from virus protein structure-function analysis with clinical informatics, transcriptomics, and genomics to reveal determinants and predictors of immunity, susceptibility, and clinical outcome associated with infection.

Immune complement and coagulation dysfunction in adverse outcomes of SARS-CoV-2 infection.

Understanding the pathophysiology of SARS-CoV-2 infection is critical for therapeutic and public health strategies. Viral-host interactions can guide discovery of disease regulators, and protein structure function analysis points to several immune pathways, including complement and coagulation, as targets of coronaviruses. To determine whether conditions associated with dysregulated complement or coagulation systems impact disease, we performed a retrospective observational study and found that history of macular degeneration (a proxy for complement-activation disorders) and history of coagulation disorders (thrombocytopenia, thrombosis and hemorrhage) are risk factors for SARS-CoV-2-associated morbidity and mortality-effects that are independent of age, sex or history of smoking. Transcriptional profiling of nasopharyngeal swabs demonstrated that in addition to type-I interferon and interleukin-6-dependent inflammatory responses, infection results in robust engagement of the complement and coagulation pathways. Finally, in a candidate-driven genetic association study of severe SARS-CoV-2 disease, we identified putative complement and coagulation-associated loci including missense, eQTL and sQTL variants of critical complement and coagulation regulators. In addition to providing evidence that complement function modulates SARS-CoV-2 infection outcome, the data point to putative transcriptional genetic markers of susceptibility. The results highlight the value of using a multimodal analytical approach to reveal determinants and predictors of immunity, susceptibility and clinical outcome associated with infection.

Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused thousands of deaths worldwide, including >18,000 in New York City (NYC) alone. The sudden emergence of this pandemic has highlighted a pressing clinical need for rapid, scalable diagnostics that can detect infection, interrogate strain evolution, and identify novel patient biomarkers. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs, plus a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, bacterial, and viral profiling. We applied both technologies across 857 SARS-CoV-2 clinical specimens and 86 NYC subway samples, providing a broad molecular portrait of the COVID-19 NYC outbreak. Our results define new features of SARS-CoV-2 evolution, nominate a novel, NYC-enriched viral subclade, reveal specific host responses in interferon, ACE, hematological, and olfaction pathways, and examine risks associated with use of ACE inhibitors and angiotensin receptor blockers. Together, these findings have immediate applications to SARS-CoV-2 diagnostics, public health, and new therapeutic targets.

Comprehensive study of nuclear receptor DNA binding provides a revised framework for understanding receptor specificity.

The type II nuclear receptors (NRs) function as heterodimeric transcription factors with the retinoid X receptor (RXR) to regulate diverse biological processes in response to endogenous ligands and therapeutic drugs. DNA-binding specificity has been proposed as a primary mechanism for NR gene regulatory specificity. Here we use protein-binding microarrays (PBMs) to comprehensively analyze the DNA binding of 12 NR:RXRα dimers. We find more promiscuous NR-DNA binding than has been reported, challenging the view that NR binding specificity is defined by half-site spacing. We show that NRs bind DNA using two distinct modes, explaining widespread NR binding to half-sites in vivo. Finally, we show that the current models of NR specificity better reflect binding-site activity rather than binding-site affinity. Our rich dataset and revised NR binding models provide a framework for understanding NR regulatory specificity and will facilitate more accurate analyses of genomic datasets.

Robust adaptive immune response against Babesia microti infection marked by low parasitemia in a murine model of sickle cell disease.

The intraerythrocytic parasite Babesia microti is the number 1 cause of transfusion-transmitted infection and can induce serious, often life-threatening complications in immunocompromised individuals including transfusion-dependent patients with sickle cell disease (SCD). Despite the existence of strong long-lasting immunological protection against a second infection in mouse models, little is known about the cell types or the kinetics of protective adaptive immunity mounted following Babesia infection, especially in infection-prone SCD that are thought to have an impaired immune system. Here, we show, using a mouse B microti infection model, that infected wild-type (WT) mice mount a very strong adaptive immune response, characterized by (1) coordinated induction of a robust germinal center (GC) reaction; (2) development of follicular helper T (TFH) cells that comprise ∼30% of splenic CD4+ T cells at peak expansion by 10 days postinfection; and (3) high levels of effector T-cell cytokines, including interleukin 21 and interferon γ, with an increase in the secretion of antigen (Ag)-specific antibodies (Abs). Strikingly, the Townes SCD mouse model had significantly lower levels of parasitemia. Despite a highly disorganized splenic architecture before infection, these mice elicited a surprisingly robust adaptive immune response (including comparable levels of GC B cells, TFH cells, and effector cytokines as control and sickle trait mice), but higher immunoglobulin G responses against 2 Babesia-specific proteins, which may contain potential immunogenic epitopes. Together, these studies establish the robust emergence of adaptive immunity to Babesia even in immunologically compromised SCD mice. Identification of potentially immunogenic epitopes has implications to identify long-term carriers, and aid Ag-specific vaccine development.