Biology subjects

Calfee, C.

Publications and source records attributed to Calfee, C..

3 recordsLinked to original sources

bioRxiv2026

Lipid mobilization establishes metabolic tolerance and prevents autonomic collapse in infection

Survival during infection depends on both pathogen clearance and the ability to tolerate infection-induced physiological changes. Metabolic adaptations are a central component of this tolerance, but the mechanisms underlying these responses remain incompletely defined. Here, we identify white adipose tissue (WAT) lipolysis as a central regulator of metabolic tolerance to infection. In patients with sepsis, higher circulating non-esterified fatty acid (NEFA) levels were associated with reduced mortality. In mouse models of polymicrobial sepsis, infection induced robust adipose lipolysis and increased circulating NEFAs. Genetic ablation of adipose triglyceride lipase (ATGL) in adipose tissue impaired lipolysis, leading to hypothermia, bradycardia, and increased mortality without altering immune cell populations or pathogen burden, consistent with a defect in tolerance rather than resistance. Mechanistically, lipolysis-derived NEFAs, but not glycerol, were required for protection, as restoring circulating NEFAs rescued autonomic stability and survival in adipose tissue ATGL-deficient mice. Infection-induced lipolysis was redundantly regulated and did not depend on any single upstream signaling pathway. Both pharmacologic activation of lipolysis using a {beta}3-adrenergic agonist and exogenous fatty acid supplementation increased circulating NEFAs, improved survival, and promoted tolerance in mice. Consistent with these findings, analysis of real-world electronic health record data demonstrated that septic patients receiving FDA-approved {beta}3-adrenergic agonists had reduced mortality or hospice discharge in a propensity-matched cohort. Together, these results identify WAT lipolysis and circulating fatty acids as key mediators of tolerance to infection and support a therapeutic strategy based on repurposing clinically available {beta}3-adrenergic agonists to improve outcomes in sepsis. One Sentence SummaryWhite adipose tissue lipolysis promotes metabolic tolerance to infection through circulating fatty acids and is associated with improved survival in sepsis

physiology↗

bioRxiv2020

Global Absence and Targeting of Protective Immune States in Severe COVID-19.

While SARS-CoV-2 infection has pleiotropic and systemic effects in some patients, many others experience milder symptoms. We sought a holistic understanding of the severe/mild distinction in COVID-19 pathology, and its origins. We performed a whole-blood preserving single-cell analysis protocol to integrate contributions from all major cell types including neutrophils, monocytes, platelets, lymphocytes and the contents of serum. Patients with mild COVID-19 disease display a coordinated pattern of interferon-stimulated gene (ISG) expression across every cell population and these cells are systemically absent in patients with severe disease. Severe COVID-19 patients also paradoxically produce very high anti-SARS-CoV-2 antibody titers and have lower viral load as compared to mild disease. Examination of the serum from severe patients demonstrates that they uniquely produce antibodies with multiple patterns of specificity against interferon-stimulated cells and that those antibodies functionally block the production of the mild disease-associated ISG-expressing cells. Overzealous and auto-directed antibody responses pit the immune system against itself in many COVID-19 patients and this defines targets for immunotherapies to allow immune systems to provide viral defense. One Sentence SummaryIn severe COVID-19 patients, the immune system fails to generate cells that define mild disease; antibodies in their serum actively prevents the successful production of those cells.

immunology↗

bioRxiv2018

A Metagenomic Comparison of Tracheal Aspirate and Mini-Bronchial Alveolar Lavage for Assessment of Respiratory Microbiota

Lower respiratory tract infections (LRTI) lead to more deaths each year than any other infectious disease category. Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests. In critically ill patients, non-infectious inflammatory syndromes resembling LRTI further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the airway microbiome and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed rules-based and logistic regression models (RBM, LRM) in a derivation cohort of 20 patients with LRTI or non-infectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with non-infectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an AUC of 0.96 (95% CI = 0.86 - 1.00), the diversity metric with an AUC of 0.80 (95% CI = 0.63 - 0.98), and the host transcriptional classifier with an AUC of 0.88 (95% CI = 0.75 - 1.00). Combining these achieved a negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome and host transcriptome may hold promise as a novel tool for LRTI diagnosis.\n\nSIGNIFICANCE STATEMENTLower respiratory tract infections (LRTI) are the leading cause of infectious disease-related death worldwide yet remain challenging to diagnose because of limitations in existing microbiologic tests. In critically ill patients, non-infectious respiratory syndromes that resemble LRTI further complicate diagnosis and confound targeted treatment. To address this, we developed a novel metagenomic sequencing-based approach that simultaneously interrogates three core elements of acute airway infections: the pathogen, airway microbiome and host response. We studied this approach in a prospective cohort of critically ill patients with acute respiratory failure and found that combining pathogen, microbiome and host gene expression metrics achieved accurate LRTI diagnosis and identified etiologic pathogens in patients with clinically identified infections but otherwise negative testing.

microbiology↗