Biology subjects

Smallwood, H.

Publications and source records attributed to Smallwood, H..

4 recordsLinked to original sources

bioRxiv2023

Establishing thresholds for cytokine storm and defining their relationship to disease severity in respiratory viral infections

Previous studies have identified cytokines associated with respiratory virus infection illness outcome. However, few studies have included comprehensive cytokine panels, longitudinal analyses, and/or simultaneous assessment across the severity spectrum. This, coupled with subjective definitions of cytokine storm syndrome (CSS), have contributed to inconsistent findings of cytokine signatures, particularly with COVID severity. Here, we measured 38 plasma cytokines and compared profiles in healthy, SARS-CoV-2 infected, and multisystem inflammatory syndrome in children (MIS-C) patients (n = 169). Infected patients spanned the severity spectrum and were classified as Asymptomatic, Mild, Moderate or Severe. Our results showed acute cytokine profiles and longitudinal dynamics of IL1Ra, IL10, MIP1b, and IP10 can differentiate COVID severity groups. Only 4% of acutely infected patients exhibited hypercytokinemia. Of these subjects, 3 were Mild, 3 Moderate, and 1 Severe, highlighting the lack of association between CSS and COVID severity. Additionally, we identified IL1Ra and TNFa as potential biomarkers for patients at high risk for long COVID. Lastly, we compare hypercytokinemia profiles across COVID and influenza patients and show distinct elevated cytokine signatures, wherein influenza induces the most elevated cytokine profile. Together, these results identify key analytes that, if obtained at early time points, can predict COVID illness outcome and/or risk of complications, and provide novel insight for improving the conceptual framework of hypercytokinemia, wherein CSS is a subgroup that requires concomitant severe clinical manifestations, and including a list of cytokines that can distinguish between subtypes of hypercytokinemia.

immunology↗

bioRxiv2021

HIF-dependent expression of creatine kinase brain isoform (CKB) promotes breast cancer metastasis, and blocking creatine kinase activity with cyclocreatine impairs invasion and improves the efficacy of conventional chemotherapies

The oxygen-responsive Hypoxia Inducible Factor (HIF)-1 promotes several steps of the metastatic cascade. A hypoxic gene signature is enriched in triple negative breast cancers (TNBCs) and correlates with poor patient survival. Since inhibiting the HIF transcription factors with small molecules is challenging, we sought to identify genes downstream of HIF-1 that could be targeted to block invasion and metastasis. Creatine kinase brain isoform (CKB) was identified as a highly differentially expressed gene in a screen of HIF-1 wild type and knockout mammary tumor cells derived from a transgenic model of metastatic breast cancer. CKB is a cytosolic enzyme that reversibly catalyzes the phosphorylation of creatine, generating phosphocreatine (PCr) in the forward reaction, and regenerating ATP in the reverse reaction. Creatine kinase activity is inhibited by the creatine analog cyclocreatine (cCr). Loss and gain of function genetic approaches were used in combination with cCr therapy to define the contribution of CKB expression or creatine kinase activity to cell proliferation, migration, invasion, and metastasis in ER-negative breast cancers. CKB was necessary for cell invasion in vitro and strongly promoted tumor growth and metastasis in vivo. Similarly, cyclocreatine therapy repressed cell migration, cell invasion, formation of invadopodia, and lung metastasis. Moreover, in common TNBC cell line models, the addition of cCr to conventional cytotoxic chemotherapy agents was either additive or synergistic to repress tumor cell growth.

cancer biology↗

bioRxiv2020

Discovery and Predictive Modeling of Urine Microbiome, Metabolite and Cytokine Biomarkers in Hospitalized Patients with Community Acquired Pneumonia

Pneumonia is the leading cause of infectious related death costing 12 billion dollars annually in the United States alone. Despite improvements in clinical care, total mortality remains around 4%, with inpatient mortality reaching 5-10%. For unknown reasons, mortality risk remains high even after hospital discharge and there is a need to identify those patients most at risk. Also of importance, clinical symptoms alone do not distinguish viral from bacterial infection which may delay appropriate treatment and may contribute to short-term and long-term mortality. Biomarkers have the potential to provide point of care diagnosis, identify high-risk patients, and increase our understanding of the biology of disease. However, there have been mixed results on the diagnostic performance of many of the analytes tested to date. Urine represents a largely untapped source for biomarker discovery and is highly accessible. To test this hypothesis, we collected urine from hospitalized patients with community-acquired pneumonia (CAP) and performed a comprehensive screen for urinary tract microbiota signatures, metabolite, and cytokine profiles. CAP patients were diagnosed with influenza or bacterial (S. aureus and S. pneumoniae) etiologies and compared with healthy volunteers. Microbiome signatures showed marked shifts in taxonomic levels in patients with bacterial etiology versus influenza and CAP versus normal. Predictive modeling of 291 microbial and metabolite values achieved a +90% accuracy with LASSO in predicting specific pneumonia etiology. This study demonstrates that urine from patients hospitalized with pneumonia may serve as a reliable and accessible sample to evaluate biomarkers that may diagnose etiology and predict clinical outcomes. Author SummaryUrine has been classically considered sterile since most microorganisms are not readily culturable under healthy circumstances. Further, many pneumonia patients are immediately placed on antibiotics rendering culture-based techniques useless. However, the advent of next generation sequencing has enabled unprecedented analysis of the microbial communities - living or detected as free DNA - found in many niches of the human body. Here, we describe a urine microbiome as well as metabolites and cytokines measured in patients newly admitted to the hospital diagnosed with influenza or bacterial (S. aureus and S. pneumoniae) infection pneumonia, compared with healthy controls. Using these parameters alone, we were able to achieve high success in predicting patient pneumonia. This study provides a proof of concept that urine samples, which are easily accessible in outpatient and inpatient settings, could provide additional diagnostic insights to patient infectious status and future risk factor for complication.

systems biology↗

bioRxiv2020

Dynamic metabolic reprogramming in dendritic cells: an early response to influenza infection that is essential for effector function

Infection with the influenza virus triggers an innate immune response aimed at initiating the adaptive response to halt viral replication and spread. However, the metabolic response fueling the molecular mechanisms underlying changes in innate immune cell homeostasis remain undefined. Thus, we compared the metabolic response of dendritic cells to that of those infected with active and inactive influenza A virus or treated with toll like receptor agonists. While influenza infects dendritic cells, it does not productively replicate in these cells, and therefore metabolic changes upon infection may represent an adaptive response on the part of the host cells. Using quantitative mass spectrometry along with pulse chase substrate utilization assays and metabolic flux measurements, we found global metabolic changes 17 hours post infection, including significant changes in carbon commitment via glycolysis and glutaminolysis, as well as ATP production via TCA cycle and oxidative phosphorylation. Influenza infection of dendritic cells led to a metabolic phenotype, distinct from that induced by TLR agonists, with significant resilience in terms of metabolic plasticity. We identified Myc as one transcription factor modulating this response. Restriction of either Myc activity or mitochondrial substrates resulted in significant changes in the innate immune functions of dendritic cells, including reduced motility and T cell activation. Transcriptome analysis of inflammatory dendritic cells isolated following influenza infection showed similar metabolic reprogramming occurs in vivo. Thus, early in the infection process dendritic cells respond with global metabolic restructuring that is present in lung DC 9 days following infection and impacts their effector function, suggesting that metabolic switching in dendritic cells plays a vital role in initiating the immune response to influenza infection. Author SummaryIn response to influenza infection we found that dendritic cells, cells that are critical in mounting an effective immune response, undergo a profound metabolic shift. They alter the concentration and location of hundreds of proteins, including c-MYC, mediating a shift to a highly glycolytic phenotype that is also flexible in terms of fueling respiration. Dendritic cells initiate the immune response to influenza and activate the adaptive response allowing viral clearance and manifesting immune memory for protection against subsequent infections. We found that limiting access to specific metabolic pathways or substrates diminished key immune functions. Previously we described an immediate, fixed, hypermetabolic state in infected respiratory epithelial cells. We now show the metabolic responses of epithelial and dendritic cells are distinct. Here, we also demonstrate that dendritic cells tailor their metabolic response to the pathogen or TLR stimulus. This metabolic reprogramming occurs rapidly in vitro and it is sustained in inflammatory dendritic cells in vivo for at least 9 days following influenza infection. Thus, drugs targeting metabolism are likely to have cell- and pathogen-specific activities in the context of infection. These studies open the possibility of modulating the immune response to viral infection via customizing metabolic therapy to enhance or diminish the function of specific cells.

immunology↗