Biology subjects

Pietropaoli, A.

Publications and source records attributed to Pietropaoli, A..

3 recordsLinked to original sources

bioRxiv2023

The effect of clinically relevant beta-lactam, aminoglycoside, and quinolone antibiotics on bacterial extracellular vesicle release from E. coli

Sepsis, a leading cause of death in hospitals, can be defined as a dysregulated host inflammatory response to infection, which can lead to tissue damage, organ failure, and cardiovascular complications. Although there is no cure for sepsis, the condition is typically managed with broad spectrum antibiotics to eliminate any potential bacterial source of infection. However, a potential side-effect of antibiotic treatment is the enhanced release of bacterial extracellular vesicles (BEVs). BEVs are membrane-bound nanoparticles produced by a variety of mechanisms, one of which includes the pinching-off of the outer membrane (in Gram-negative bacteria) to enclose proteins and other biological molecules for transport and intercellular communication. Some of the Gram-negative EV cargo, including Peptidoglycan associated lipoprotein (Pal) and Outer membrane protein A (OmpA), have been shown to induce both acute and chronic inflammation in host tissue. We hypothesize that antibiotic concentration and its mechanism of action can have an effect on the amount of released BEVs, which could potentially exacerbate the host inflammatory response. In this study, we evaluated nine clinically relevant antibiotics for their effect on EV release from Escherichia coli. EVs were characterized using immunoblotting, nanoparticle tracking analysis, and transmission electron microscopy. Several beta-lactam antibiotics caused significantly more EV release, while quinolone and aminoglycosides caused relatively less vesiculation. Further study is warranted to corroborate the correlation between an antibiotics mechanism of action and its effect on EV release, but these results underline the importance of antibiotic choice when treating sepsis patients.

microbiology↗

bioRxiv2023

Thrombocytopenia Independently Leads to Monocyte Immune Dysfunction

In addition to their well-studied hemostatic functions, platelets are immune cells. Platelets circulate at the interface between the vascular wall and leukocytes, and transient platelet-leukocyte complexes are found in both healthy and disease states, positioning platelets to provide physiologic cues of vascular health and injury. Roles for activated platelets in inducing and amplifying immune responses have received an increasing amount of research attention, but our past studies also showed that normal platelet counts are needed in healthy conditions to maintain immune homeostasis. We have now found that thrombocytopenia (a low platelet count) leads to monocyte dysfunction, independent of the cause of thrombocytopenia, in a manner that is dependent on direct platelet-monocyte CD47 interactions that regulate monocyte immunometabolism and gene expression. Compared to monocytes from mice with normal platelet counts, monocytes from thrombocytopenic mice had increased toll-like receptor (TLR) responses, including increased IL-6 production. Furthermore, ex vivo co-incubation of resting platelets with platelet naive bone marrow monocytes, induced monocyte metabolic programming and durable changes in TLR agonist responses. Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-Seq) on monocytes from thrombocytopenic mice showed persistently open chromatin at LPS response genes and resting platelet interactions with monocytes induced histone methylation in a CD47 dependent manner. Using mouse models of thrombocytopenia and sepsis, normal platelet numbers were needed to limit monocyte immune dysregulation and IL6 expression in monocytes from human patients with sepsis also inversely correlated with patient platelet counts. Our studies demonstrate that in healthy conditions, resting platelets maintain monocyte immune tolerance by regulating monocyte immunometabolic processes that lead to epigenetic changes in TLR-related genes. This is also the first demonstration of sterile cell interactions that regulate of innate immune-metabolism and monocyte pathogen responses.

immunology↗

bioRxiv2019

Categorical Assignment of Pulmonary Embolism is a Simple and More Accurate Indicator of Right Ventricular Dysfunction and Short Team Mortality

Several risk stratification tools are available to predict short-term mortality in patients with acute pulmonary embolism (PE). Right ventricular (RV) dysfunction, which is common to intermediate and high risk PE, is an independent predictor of mortality and may be a faster and simpler way to assess patient risk in acute care settings. We evaluated 571 patients presenting with acute PE as the primary diagnosis, stratifying them by the Pulmonary Embolism Severity Index (PESI), by the BOVA score, or categorically as low risk (no RV dysfunction by imaging), intermediate risk (RV dysfunction by imaging), or high risk PE (RV dysfunction by imaging with sustained hypotension). Using imaging data to firstly define the presence of RV dysfunction, and plasma cardiac troponin T (cTnT) and NT-proBNP as additional evidence for myocardial strain, we evaluated the PESI and BOVA scoring systems compared to categorical assignment of PE as low risk, submassive, and massive PE. Cardiac biomarkers poorly distinguished between PESI classes and BOVA stages in patients with acute PE. Cardiac TnT and NT-proBNP easily distinguished low risk from submassive PE with an area under the curve (AUC) of 0.84 (95% C.I. 0.73 - 0.95, p< 0.0001), and 0.88 (95% C.I. 0.79-0.97, p< 0.0001), respectively, and low risk from massive PE with an area under the curve (AUC) of 0.89 (95% C.I. 0.78 - 1.00, p< 0.0001), and 0.89 (95% C.I. 0.82-0.95, p< 0.0001), respectively. Predicted short-term mortality by PESI score or BOVA stage was lower than the observed mortality for submassive PE by a two-fold order of magnitude. These data suggest the presence of RV dysfunction in the context of acute PE is sufficient for the purposes of risk stratification, while more complicated risk stratification algorithms may under-estimate short-term mortality risk.

biochemistry↗