Proteome Profiling of Recombinant DNase Therapy in Reducing NETs and Aiding Recovery in COVID-19 Patients.

Severe coronavirus disease 2019 (COVID-19) can result in pneumonia and acute respiratory failure. Accumulation of mucus in the airways is a hallmark of the disease and can result in hypoxemia. Here, we show that quantitative proteome analysis of the sputum from severe patients with COVID-19 reveal high levels of neutrophil extracellular trap (NET) components, which was confirmed by microscopy. Extracellular DNA from excessive NET formation can increase sputum viscosity and lead to acute respiratory distress syndrome. Recombinant human DNase (Pulmozyme; Roche) has been shown to be beneficial in reducing sputum viscosity and improve lung function. We treated five patients pwith COVID-19 resenting acute symptoms with clinically approved aerosolized Pulmozyme. No adverse reactions to the drug were seen, and improved oxygen saturation and recovery in all severely ill patients with COVID-19 was observed after therapy. Immunofluorescence and proteome analysis of sputum and blood plasma samples after treatment revealed a marked reduction of NETs and a set of statistically significant proteome changes that indicate reduction of hemorrhage, plasma leakage and inflammation in the airways, and reduced systemic inflammatory state in the blood plasma of patients. Taken together, the results indicate that NETs contribute to acute respiratory failure in COVID-19 and that degrading NETs may reduce dependency on external high-flow oxygen therapy in patients. Targeting NETs using recombinant human DNase may have significant therapeutic implications in COVID-19 disease and warrants further studies.

A novel mechanism for NETosis provides antimicrobial defense at the oral mucosa.

Neutrophils are essential for host defense at the oral mucosa and neutropenia or functional neutrophil defects lead to disordered oral homeostasis. We found that neutrophils from the oral mucosa harvested from morning saliva had released neutrophil extracellular traps (undergone NETosis) in vivo. The NETosis was mediated through intracellular signals elicited by binding of sialyl Lewis(X) present on salival mucins to l-selectin on neutrophils. This led to rapid loss of nuclear membrane and intracellular release of granule proteins with subsequent neutrophil extracellular trap (NET) release independent of elastase and reduced NAD phosphate-oxidase activation. The saliva-induced NETs were more DNase-resistant and had higher capacity to bind and kill bacteria than NETs induced by bacteria or by phorbol-myristate acetate. Furthermore, saliva/sialyl Lewis(X) mediated signaling enhanced intracellular killing of bacteria by neutrophils. Saliva from patients with aphthous ulcers and Behçet disease prone to oral ulcers failed to induce NETosis, but for different reasons it demonstrated that disordered homeostasis in the oral cavity may result in deficient saliva-mediated NETosis.

Saliva-Induced Clotting Captures Streptococci: Novel Roles for Coagulation and Fibrinolysis in Host Defense and Immune Evasion.

Streptococcal pharyngitis is among the most common bacterial infections, but the molecular mechanisms involved remain poorly understood. Here we investigate the interactions among three major players in streptococcal pharyngitis: streptococci, plasma, and saliva. We find that saliva activates the plasma coagulation system through both the extrinsic and the intrinsic pathways, entrapping the bacteria in fibrin clots. The bacteria escape the clots by activating host plasminogen. Our results identify a potential function for the intrinsic pathway of coagulation in host defense and a corresponding role for fibrinolysis in streptococcal immune evasion.

The epidermal growth factor receptor is a regulator of epidermal complement component expression and complement activation.

The complement system is activated in response to tissue injury. During wound healing, complement activation seems beneficial in acute wounds but may be detrimental in chronic wounds. We found that the epidermal expression of many complement components was only increased to a minor extent in skin wounds in vivo and in cultured keratinocytes after exposure to supernatant from stimulated mononuclear cells. In contrast, the epidermal expression of complement components was downregulated in ex vivo injured skin lacking the stimulation from infiltrating inflammatory cells but with intact injury-induced epidermal growth factor receptor (EGFR)-mediated growth factor response. In cultured primary keratinocytes, stimulation with the potent EGFR ligand, TGF-α, yielded a significant downregulation of complement component expression. Indeed, EGFR inhibition significantly enhanced the induction of complement components in keratinocytes and epidermis following stimulation with proinflammatory cytokines. Importantly, EGFR inhibition of cultured keratinocytes either alone or in combination with proinflammatory stimulus promoted activation of the complement system after incubation with serum. In keratinocytes treated solely with the EGFR inhibitor, complement activation was dependent on serum-derived C1q, whereas in keratinocytes stimulated with a combination of proinflammatory cytokines and EGFR inhibition, complement activation was found even with C1q-depleted serum. In contrast to human keratinocytes, EGFR inhibition did not enhance complement component expression or cause complement activation in murine keratinocytes. These data demonstrate an important role for EGFR in regulating the expression of complement components and complement activation in human epidermis and keratinocytes and, to our knowledge, identify for the first time a pathway important for the epidermal regulation of complement activation.

Interpreting biologically informed neural networks for enhanced proteomic biomarker discovery and pathway analysis.

The incorporation of machine learning methods into proteomics workflows improves the identification of disease-relevant biomarkers and biological pathways. However, machine learning models, such as deep neural networks, typically suffer from lack of interpretability. Here, we present a deep learning approach to combine biological pathway analysis and biomarker identification to increase the interpretability of proteomics experiments. Our approach integrates a priori knowledge of the relationships between proteins and biological pathways and biological processes into sparse neural networks to create biologically informed neural networks. We employ these networks to differentiate between clinical subphenotypes of septic acute kidney injury and COVID-19, as well as acute respiratory distress syndrome of different aetiologies. To gain biological insight into the complex syndromes, we utilize feature attribution-methods to introspect the networks for the identification of proteins and pathways important for distinguishing between subtypes. The algorithms are implemented in a freely available open source Python-package ( https://github.com/InfectionMedicineProteomics/BINN ).

Generalized precursor prediction boosts identification rates and accuracy in mass spectrometry based proteomics.

Data independent acquisition mass spectrometry (DIA-MS) has recently emerged as an important method for the identification of blood-based biomarkers. However, the large search space required to identify novel biomarkers from the plasma proteome can introduce a high rate of false positives that compromise the accuracy of false discovery rates (FDR) using existing validation methods. We developed a generalized precursor scoring (GPS) method trained on 2.75 million precursors that can confidently control FDR while increasing the number of identified proteins in DIA-MS independent of the search space. We demonstrate how GPS can generalize to new data, increase protein identification rates, and increase the overall quantitative accuracy. Finally, we apply GPS to the identification of blood-based biomarkers and identify a panel of proteins that are highly accurate in discriminating between subphenotypes of septic acute kidney injury from undepleted plasma to showcase the utility of GPS in discovery DIA-MS proteomics.

A pharmacoproteomic landscape of organotypic intervention responses in Gram-negative sepsis.

Sepsis is the major cause of mortality across intensive care units globally, yet details of accompanying pathological molecular events remain unclear. This knowledge gap has resulted in ineffective biomarker development and suboptimal treatment regimens to prevent and manage organ dysfunction/damage. Here, we used pharmacoproteomics to score time-dependent treatment impact in a murine Escherichia coli sepsis model after administering beta-lactam antibiotic meropenem (Mem) and/or the immunomodulatory glucocorticoid methylprednisolone (Gcc). Three distinct proteome response patterns were identified, which depended on the underlying proteotype for each organ. Gcc enhanced some positive proteome responses of Mem, including superior reduction of the inflammatory response in kidneys and partial restoration of sepsis-induced metabolic dysfunction. Mem introduced sepsis-independent perturbations in the mitochondrial proteome that Gcc counteracted. We provide a strategy for the quantitative and organotypic assessment of treatment effects of candidate therapies in relationship to dosing, timing, and potential synergistic intervention combinations during sepsis.

Cerebrospinal fluid proteome maps detect pathogen-specific host response patterns in meningitis.

Meningitis is a potentially life-threatening infection characterized by the inflammation of the leptomeningeal membranes. Many different viral and bacterial pathogens can cause meningitis, with differences in mortality rates, risk of developing neurological sequelae, and treatment options. Here, we constructed a compendium of digital cerebrospinal fluid (CSF) proteome maps to define pathogen-specific host response patterns in meningitis. The results revealed a drastic and pathogen-type specific influx of tissue-, cell-, and plasma proteins in the CSF, where, in particular, a large increase of neutrophil-derived proteins in the CSF correlated with acute bacterial meningitis. Additionally, both acute bacterial and viral meningitis result in marked reduction of brain-enriched proteins. Generation of a multiprotein LASSO regression model resulted in an 18-protein panel of cell- and tissue-associated proteins capable of classifying acute bacterial meningitis and viral meningitis. The same protein panel also enabled classification of tick-borne encephalitis, a subgroup of viral meningitis, with high sensitivity and specificity. The work provides insights into pathogen-specific host response patterns in CSF from different disease etiologies to support future classification of pathogen type based on host response patterns in meningitis.

Evaluation of the Forsvall biopsy needle in an ex vivo model of transrectal prostate biopsy - a novel needle design with the objective to reduce the risk of post-biopsy infection.

BACKGROUND: Transrectal prostate biopsy (TRbx) transfers colonic bacteria into prostatic tissue, potentially causing infectious complications, including sepsis. Our objective was to determine whether biopsy needle shape, surface properties and sampling mechanism affect the number of bacteria transferred through the colon wall, and evaluate a novel needle with improved properties. METHODS: The standard Tru-Cut biopsy needle used today was evaluated for mechanisms of bacterial transfer in a pilot study. A novel Tru-Cut needle (Forsvall needle prototype) was developed. TRbx was simulated using human colons ex-vivo. Four subtypes of the prototype needle were compared with a standard Tru-Cut needle (BARD 18 G). Prototype and standard needles were used to puncture 4 different colon specimens in 10 randomized sites per colon. Needles were submerged into culture media to capture translocated bacteria. The media was cultured on blood agar and then the total amount of transferred bacteria was calculated for each needle. The primary outcome measure was the percent reduction of bacteria translocated by the prototype needles relative to the standard needle. Secondary outcome measures were the effects of tip design and coating on the percent reduction of translocated bacteria. RESULTS: Prototype needles reduced the number of translocated bacteria by, on average, 96.0% (95% confidence interval 93.0-97.7%; p < 0.001) relative to the standard needle. This percent reduction was not significantly affected by prototype needle tip style or surface coating. CONCLUSIONS: The Forsvall needle significantly reduces colonic bacterial translocation, suggesting that it could reduce infectious complications in prostate biopsy. A clinical trial has been initiated.

Fever of Unknown Origin in a Renal Transplant Recipient: Lactate Dehydrogenase as an Important Clue to Diagnosis.

Histoplasmosis is a rare disease in nonendemic areas. We report a case of a 23-year-old male patient who presented with fever of unknown origin, cytopenias, organomegaly, and allograft dysfunction 4 months after renal transplant with father as donor. Bone marrow examination showed intracellular budding yeast cells, which was confirmed as histoplasmosis by culture of bone marrow biopsy sample. The patient was treated with intravenous liposomal amphotericin and responded well.

Automated Image-Based Quantification of Neutrophil Extracellular Traps Using NETQUANT.

Neutrophil extracellular traps (NETs) are web-like antimicrobial structures consisting of DNA and granule derived antimicrobial proteins. Immunofluorescence microscopy and image-based quantification methods remain important tools to quantitate neutrophil extracellular trap formation. However, there are key limitations to the immunofluorescence-based methods that are currently available for quantifying NETs. Manual methods of image-based NET quantification are often subjective, prone to error and tedious for users, especially non-experienced users. Also, presently available software options for quantification are either semi-automatic or require training prior to operation. Here, we demonstrate the implementation of an automated immunofluorescence-based image quantification method to evaluate NET formation called NETQUANT. The software is easy to use and has a user-friendly graphical user interface (GUI). It considers biologically relevant parameters such as an increase in the surface area and DNA:NET marker protein ratio, and nuclear deformation to define NET formation. Furthermore, this tool is built as a freely available app, and allows for single-cell resolution quantification and analysis.

Neutrophil extracellular traps in the central nervous system hinder bacterial clearance during pneumococcal meningitis.

Neutrophils are crucial mediators of host defense that are recruited to the central nervous system (CNS) in large numbers during acute bacterial meningitis caused by Streptococcus pneumoniae. Neutrophils release neutrophil extracellular traps (NETs) during infections to trap and kill bacteria. Intact NETs are fibrous structures composed of decondensed DNA and neutrophil-derived antimicrobial proteins. Here we show NETs in the cerebrospinal fluid (CSF) of patients with pneumococcal meningitis, and their absence in other forms of meningitis with neutrophil influx into the CSF caused by viruses, Borrelia and subarachnoid hemorrhage. In a rat model of meningitis, a clinical strain of pneumococci induced NET formation in the CSF. Disrupting NETs using DNase I significantly reduces bacterial load, demonstrating that NETs contribute to pneumococcal meningitis pathogenesis in vivo. We conclude that NETs in the CNS reduce bacterial clearance and degrading NETs using DNase I may have significant therapeutic implications.

NETQUANT: Automated Quantification of Neutrophil Extracellular Traps.

Neutrophil extracellular traps (NETs) that are extensive webs of DNA covered with antimicrobial proteins into the extracellular environment during infection or inflammation as a part of their defense arsenal. Image acquisition of fluorescently labeled NETs and subsequent image-based quantification is frequently used to analyze NET formation (NETosis) in response to various stimuli. However, there are important limitations in the present methods for quantification. Manual methods tend to be error-prone, tedious, and often quite subjective, whereas the software-rooted options are either semi-automatic or difficult to operate. Here, we present an automated and uncomplicated approach for quantifying NETs from fluorescence images, built as a freely available app for MATLAB®. It is based on detection of a set of clearly defined parameters, all related to the biological manifestation of NETs and allowing for single-cell resolution quantification and analysis.

FAF and SufA: proteins of Finegoldia magna that modulate the antibacterial activity of histones.

Many bacterial pathogens have developed methods to overcome the defences of the host innate immune system. One such defence is the release of antimicrobial peptides (AMPs). Histones have been found to function as AMPs, in addition to their main biological function of packaging and organising DNA into nucleosomes. In this study, the Gram-positive anaerobic coccus Finegoldia magna was found to bind histones by Western blot and immunoprecipitation analysis. F. magna, which is normally a commensal of the skin and mucous membranes, is also known to act as an opportunistic pathogen and has been isolated from various clinical infection sites. It was found to bind to histones extracted from human skin epidermis through its surface and extracellular adhesion protein FAF. Through FAF binding, F. magna was protected from histone bactericidal activity. Furthermore, the histones were found to be degraded by SufA, a subtilisin-like extracellular serine protease of F. magna. Hence, the results of the present study will give more insight into how F. magna persists both as a commensal organism at the basement membrane of the skin and as an opportunistic pathogen during infection.

Azurophil granule proteins constitute the major mycobactericidal proteins in human neutrophils and enhance the killing of mycobacteria in macrophages.

Pathogenic mycobacteria reside in, and are in turn controlled by, macrophages. However, emerging data suggest that neutrophils also play a critical role in innate immunity to tuberculosis, presumably by their different antibacterial granule proteins. In this study, we purified neutrophil azurophil and specific granules and systematically analyzed the antimycobacterial activity of some purified azurophil and specific granule proteins against M. smegmatis, M. bovis-BCG and M. tuberculosis H37Rv. Using gel overlay and colony forming unit assays we showed that the defensin-depleted azurophil granule proteins (AZP) were more active against mycobacteria compared to other granule proteins and cytosolic proteins. The proteins showing antimycobacterial activity were identified by MALDI-TOF mass spectrometry. Electron microscopic studies demonstrate that the AZP disintegrate bacterial cell membrane resulting in killing of mycobacteria. Exogenous addition of AZP to murine macrophage RAW 264.7, THP-1 and peripheral blood monocyte-derived macrophages significantly reduced the intracellular survival of mycobacteria without exhibiting cytotoxic activity on macrophages. Immunofluorescence studies showed that macrophages actively endocytose neutrophil granular proteins. Treatment with AZP resulted in increase in co-localization of BCG containing phagosomes with lysosomes but not in increase of autophagy. These data demonstrate that neutrophil azurophil proteins may play an important role in controlling intracellular survival of mycobacteria in macrophages.