key: cord-0927319-igowtnjg authors: Bramer, L.; Hontz, R.; Eisfeld, A.; Sims, A.; Kim, Y.-M.; Stratton, K.; Nicora, C.; Gritsenko, M.; Schepmoes, A.; Akasaka, O.; Koga, M.; Tsutsumi, T.; Nakamura, M.; Nakachi, I.; Baba, R.; Tateno, H.; Suzuki, S.; Nakajima, H.; Kato, H.; Ishida, K.; Ishii, M.; Uwamino, Y.; Mitamura, K.; Paurus, V.; Nakayasu, E.; Attah, I.; Letizia, A. G.; Waters, K.; Metz, T.; Corson, K.; Kawaoka, Y.; Gerbasi, V. R. title: Multi-omics Characterization of Neutrophil Extracellular Trap Formation in Severe and Mild COVID-19 Infections date: 2022-04-28 journal: nan DOI: 10.1101/2022.04.26.22274196 sha: 17cc5d586de2141fa8bdd152f7bb846f6bce7afe doc_id: 927319 cord_uid: igowtnjg The detailed mechanisms of COVID-19 infection pathology remain poorly understood. To improve our understanding of SARS-CoV-2 pathology, we performed a multi-omics analysis of an immunologically naive SARS-CoV-2 clinical cohort from the plasma of uninfected controls, mild, and severe infections. A comparison of healthy controls and patient samples showed activation of neutrophil degranulation pathways and formation of neutrophil extracellular trap (NET) complexes that were activated in a subset of the mild infections and more prevalent in severe infections (containing multiple NET proteins in individual patient samples). As a potential mechanism to suppress NET formation, multiple redox enzymes were elevated in the mild and severe symptom population. Analysis of metabolites from the same cohort showed a 24- and 60-fold elevation in plasma L-cystine, the oxidized form of cysteine, which is a substrate of the powerful antioxidant glutathione, in mild and severe patients, respectively. Unique to patients with mild infections, the carnosine dipeptidase modifying enzyme (CNDP1) was up-regulated. The strong protein and metabolite oxidation signatures suggest multiple compensatory pathways working to suppress oxidation and NET formation in SARS-CoV-2 infections. To date the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic has reached 500 million cases with 6.2 million deaths. Initial reports of the SARS-CoV-2 novel coronavirus-2019 (nCOV-2019) outbreak indicated the presence of a novel beta-coronavirus from bronchoalveolar lavage fluid causing fever and atypical pneumonia among infected patients (1). Severe acute respiratory syndrome coronavirus-1 (SARS-CoV-1) and Middle Eastern respiratory syndrome coronavirus (MERS-CoV) share similar transmission and symptom characteristics with SARS-CoV-2 but demonstrate considerably higher mortality rates (2) . Despite the potential for SARS-CoV-2 to develop into acute respiratory distress syndrome (ARDS), the rate of asymptomatic infection is estimated to be 30-40% (3, 4) . The penetrance of SARS-CoV-2 in the global population, and disparity in host response between individuals, underscores the need to characterize mechanisms and markers associated with immunopathology. The measurement of biomolecules from blood cells and plasma using mass spectrometry has accelerated our understanding of coronavirus disease -2019 (COVID- 19) infections (5, 6) . While the sensitivity and reliability of mass spectrometry measurements has increased substantially in the past decade, mass analyzers lack an amplification mechanism similar to nucleic acid deep sequencing approaches that employ the logarithmic polymerase chain reaction. The lower sensitivity of "-omics" approaches employing mass spectrometry can still lead to discovery of prevailing differences between experimental and control populations. This is achievable by imposing appropriate quality control measures during sample preparation and analysis (7) . We hypothesized that this might be the case for SARS-CoV-2 infections where infection severity varies greatly but is largely associated with extreme differences in inflammatory processes including neutrophil influx proximal to the alveolar-capillary barrier (8, 9) . All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted https://doi.org/10.1101/2022.04. 26.22274196 doi: medRxiv preprint In the study described herein, we characterized plasma proteins and metabolites from healthy controls (HC), and from both mild, and severe SARS-CoV-2 infections. All samples from this study originated from individuals infected with SARS-CoV-2 during March of 2020 (prior to vaccination and recurrent infections), thus the likelihood of any established adaptive immunity was low. As a result, our study likely demonstrates the natural course of infection with the ancestral strain of SARS-CoV-2 without the influence of poised adaptive immune responses against the virus. Prior efforts towards identification of protective mechanisms have focused on adaptive immunity, and clearly showed that antibodies directed against SARS-CoV-2 Spike protein neutralize virus in natural infection and vaccine recipients (10) (11) (12) . Few studies have worked to identify innate physiological mechanisms that compensate for stress imposed by the infection. Our results indicate that viral infection triggers antioxidant pathways in mild and severe patient cohorts. Patient populations with severe infection show elevation of antioxidant pathway enzymes including up-regulation of cellular superoxide dismutase, glutathione metabolism, and oxidized glutathione metabolite derivatives. Importantly, carnosine dipeptidase 1 (CNDP1), an enzyme required for controlling oxidative stress was elevated in the mild patient population, but not healthy controls or those with severe clinical outcomes. These results raise the possibility that one of the distinguishing features of severe and mild infections is the ability to suppress a threshold of oxidative stress, the ultimate trigger of neutrophil extracellular trap (NET) formation (13) . NETs function as antiviral and antimicrobial DNA-protein complexes released by diverse infection types including bacterial (14) , parasitic (15), and viral infections (5, 16, 17) . Importantly, NET levels were elevated in severe infection when compared to mild infection and healthy control populations. However, substantial NET formation was observed in a All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted https://doi.org/10.1101/2022.04.26.22274196 doi: medRxiv preprint 5 subpopulation of mild infections, suggesting NET formation might be a candidate for postinfection sequelae mechanisms in non-hospitalized patients. Additionally, NET levels were highly correlated with pulmonary surfactant protein leakage from the pulmonary microcapillaries. These results suggest that the extent of NET complex formation might drive the degree of pulmonary capillary permeability. We sought to characterize the host response among patients infected with SARS-CoV-2 through plasma proteomics analysis. A total of 151 patient samples were analyzed, including 40 healthy controls (HCs), 77 mild cases (a PCR-positive COVID 19 test but did not require hospitalization), and 34 severe cases that required oxygen, hospitalization, and/or other support (see methods). Prior to tandem-mass-tag (TMT) labeling (18) and mass spectrometry analysis, abundant plasma proteins were immunodepleted to improve sensitivity. Additionally, TMTlabeled peptides were subjected to high pH, reversed-phase chromatography to enhance the depth of protein identification and quantitation ( Figure 1 ). A total of 2,766 proteins were quantified in our study. A comparison of HC to mild infections revealed a statistically significant difference (adjusted p<0.05) among 209 different proteins with 141 proteins elevated in mild cases and 68 proteins decreased relative to HCs. Comparing severe cases to HCs showed a statistically significant difference in 1,377 different proteins (adjusted p<0.05) with 1,129 proteins elevated and 248 proteins decreased in individuals with severe infection. When comparing mild to severe patients, there were 1,318 proteins statistically different (adjusted p<0.05), with an elevation in 1,097 proteins and a decrease in 221 proteins in severe relative to All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Consistent with reported disruption of the alveolar-capillary barrier observed in ARDS patient samples and other COVID-19 plasma proteomics studies (5), we observed a statistically significant elevation in pulmonary surfactant B (PSPB) when comparing samples from severe infections to HC (adjusted p=3.92E-14) ( Figure 2A&B ). PSPB levels from mild patient samples were not statistically significant relative to HC (adjusted p=0.53). Consistent with previous reports (19) , we also observed an increase in Surfactant Protein D in the severe relative to the mild infections (adjusted p=1.39E-05) and HC samples (adjusted p= 3.07E-05). The presence of pulmonary surfactant in the plasma of severe patient populations is consistent with an ARDS presentation with increased pulmonary capillary permeability (20) . A pathway enrichment analysis of proteins from samples derived from HC, mild, and severe cases strikingly showed the differential expression of proteins that mediate activation of neutrophil degranulation in mild and severe cases relative to HC samples (adjusted p<0.0001) ( Figure 2C ). In addition to differential regulation of neutrophil degranulation pathways, proteins involved in extracellular matrix organization (adjusted p<1.88E-09) were also elevated in COVID-19 patients relative to HCs. As expected, proteins involved in immune response pathways, platelet activation, and degranulation were also increased in COVID-19 patients, especially in severe cases. Other notable activated pathways included biological oxidation pathways that were significant in the severe cases when compared to HCs (adjusted p=0.0008) (Supplemental Table 2 ). All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Neutrophil extracellular traps (NET) are extracellular DNA-protein rich complexes released from neutrophils to capture pathogens during infection (14) . Strong activation of both neutrophil degranulation and oxidation pathways is consistent with the reported physiological environment associated with triggering NET formation in viral infection and during free radical formation in vitro (13) . NETs have been identified in COVID-19 lung tissue, sputum, and sera of infected patients (17, (21) (22) (23) (24) (25) . Importantly, NETs occlude pulmonary vasculature in COVID-19 patients (26) . To characterize the proteome of NETs in our COVID-19 patients, we evaluated the mean relative levels and statistical significance of 18 NET protein components (27) These results are consistent with recent reports of NETs in COVID-19 patient plasma (17, 28) . We then investigated if NET proteins were both present and showed a statistically significant difference among individual patient samples. We addressed this question by evaluating the distribution of NET proteins from individual HC, mild, and severe patient samples by calculating All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 28, 2022. ; https://doi.org/10.1101/2022.04.26.22274196 doi: medRxiv preprint 8 z-scores relative to the HC mean abundance levels. NET proteins with a z-score >2 (see methods) were visualized in a string-plot from each patient to evaluate if: 1) Individual severe patient samples contributed more to the mean NET protein levels than others, 2) Multi-protein NET complexes could be observed from individual severe patent samples, 3) Randomly distributed NET proteins are observed across all severe patient samples. Importantly, an evaluation of NET protein z-score distributions showed: 1) That not all severe patients present detectable NET proteins in plasma ( Figure 3C ) and 2) A subset of the severe patients have detectable and significantly elevated levels of most of the NET proteins we monitored ( Figure 3C ). Importantly, these results suggest that NET formation is isolated to a subset of severe patients and several components of the NET complex are detectable among this subset of the severe patients. Additionally, our results indicate that a subset of mild patients have NET complexes with the number of detectable NET proteins and magnitude of NET protein z-scores considerably lower than that observed in severe cases (Supplemental Figure 2 ). We next evaluated the individual characteristics of the severe patient population mean NET protein z-scores as a function of their respective clinical treatment or outcome (extracorporeal membrane oxygenation (ECMO), intubation, oxygen, and mortality). Patients that were either provided supplemental oxygen or intubated showed a clear trend towards lower mean NET protein z-scores compared to patients that eventually died in the hospital and/or were placed on ECMO treatment, which displayed higher mean NET protein z-scores ( Figure 3C and Figure 3D ). Only three patients died among the 151 patient cohort. Importantly, all three of the patients that died were among the severe group and were among those with the highest mean NET protein z-scores ( Figure 3C ). Consistent with age as a risk factor for severe disease (29, 30) , nine of 33 total severe patients with the highest NET protein z-scores were 7.5 years older (mean All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 28, 2022. ; https://doi.org/10.1101/2022.04.26.22274196 doi: medRxiv preprint 9 value) than that of the 24 severe cases with lower mean NET protein z-scores (p=0.0124). Collectively, these results strongly suggest that formation of NETs is a marker of disease severity, age, and mortality during infection. The precise role of NET complexes in severe COVID-19 infections is currently unknown but NETs have been reported in autopsies and suspected of contributing to increased pulmonary capillary permeability and pulmonary occlusions (26) . Given the consistent observation of pulmonary surfactant B protein in COVID-19 patient plasma, we plotted the mean NET protein z-score in each patient against their relative log2 PSPB protein levels. Mean NET protein zscores and PSPB levels were highly correlated with r= 0.70 (Supplemental Figure 3) . We then performed a pan-correlative analysis of all proteins against each individual patient mean NET zscore. In addition to the previously mentioned correlations with PSPB and NET proteins, we observed strong correlations between mean NET z-scores and S100/calprotectin (S100A11) protein family members (27, 31, 32) and (r= 0.8-0.9) (Supplemental Figure 3 ). Since S100 proteins are established members of the NET complex (27, 32, 33) , these results reinforce the validity of our correlative analysis but identify additional NET proteins beyond the original 18 NETs monitored in our survey. Importantly, our correlation analysis also identified the NET components myeloperoxidase (MPO) (r=0.823) and azurocidin (AZU1) (r=0.769). In addition to identifying other NET complex proteins, our correlative analysis also identified neutrophil cytosolic factor 1b (NCF-1B) (r=0.852), a subunit of NADPH oxidase, the primary source of reactive oxygen species in neutrophils (Supplemental Figure 3 ). All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. We next examined proteins specifically elevated in mild infections. We sought to determine if mild infections displayed signatures of neutrophil degranulation similar to severe infections. ISG-15, a ubiquitin-like protein, is a major component of neutrophil granules and is secreted in response to virus or IFN alpha-beta (34, 35) . Consistent with the neutrophil degranulation pathway activation observed in severe COVID-19 samples ( Figure 2C ), we identified interferon stimulated gene 15 (ISG-15) elevated in mild samples relative to HC (adjusted p=1.86E-06) ( Figure 4A&B ). We then sought to identify candidate proteins among the mild infection samples that might highlight mechanistic differences between mild and severe disease. Analysis of a volcano plot between HCs and mild patient populations clearly showed multiple proteins elevated or decreased during a mild infection ( Figure 4A ). The carnosine dipeptidase 1 (CNDP1) was elevated in mild patients relative to HCs (adjusted p=6.12E-11) but was not statistically significant between HC and severe patient samples ( Figure 4C ) (adjusted p=0.621). This result was particularly interesting, as CNDP1 was among three proteins observed with increased differential expression in mild infection when comparing all three sample populations (HC, mild, and severe) among 2,766 total quantified proteins and might represent a compensatory pathway specific to mild patient populations. CNDP1 processes the antioxidant carnosine and is necessary for survival in animals upon oxidative stress challenge (36) . The other two proteins with similar expression patterns (elevated in mild, but similar in HC and severe) were Trem-like transcript protein (TRML2) and Proto-oncogene tyrosine-protein kinase receptor (RET). Our results suggested that surfactant protein levels might serve as a strong correlate of infection severity ( Figure 2B ). We reasoned that if CNDP1 was protective in the patient population with mild infection, then we might observe a negative correlation between lung surfactant levels All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 28, 2022. ; https://doi.org/10.1101/2022.04.26.22274196 doi: medRxiv preprint (indicator of more severe disease phenotype) and CNDP1 (expression is potentially protective) in plasma. A comparison between CNDP1 and PSPB levels across all patient samples (HC, Mild, and Severe) showed a negative correlation (r= -0.335) (Supplemental Figure 3 ). When CNDP1 and PSPB levels were compared among the severe patient samples (alone) the negative correlation was much stronger with (r= -0.601) (Supplemental Figure 3) . A comparison of CNDP1 and PSPB levels in HC and mild populations showed no significant correlation (HC r=-0.169, mild r= -0.151). Interestingly, a second, more promiscuous dipeptidase, cytosolic nonspecific dipeptidase 2 (CNDP2, also known as carnosine dipeptidase 2), was also detected in our study and was elevated in the severe patient population relative to HC (adjusted p=0.001) but was not elevated in the mild infection relative to HC (adjusted p=0.659). CNDP2 and PSPB levels showed a positive correlation (r= 0.339) (Supplemental Figure 3 ). CNDP1 and CNDP2 share 54% amino acid sequence identity (Supplemental Figure 4) . A manual investigation of peptide fragments quantified and identified from this study showed that the two proteins (CNDP1 and CNDP2) were unambiguously identified (Supplemental Figure 4) . While we observed a mean elevation in CDNP1 levels among mild infection samples, we found that some individual severe patients had CNDP1 levels matching or exceeding that of the mean CNDP1 levels in the mild infection group ( Figure 4C ). Given this result, we sought to evaluate a potential relationship between NET protein complex formation and CNDP1 levels among the patient sample groups. Therefore, we plotted mean NET protein z-scores observed in individual HC, Mild, and severe patients against their CNDP1 levels (assuming a linear model). In HC samples, the slope of CNDP1 levels vs. mean NET z-scores was positive (slope=0.463, p=0.036). In contrast, in mild and severe patient samples, the slope of CNDP1 levels vs. mean NET z-scores was negative (mild disease slope= -0.137, p=0.016, severe disease slope= -0.188, All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Figure 3) . We also observed a positive correlation between mean NET protein z-scores and CNDP2 levels (r=0.59). There was no significant correlation between CNDP1 and CNDP2 levels (r=-0.06). Both CNDP1 and CNDP2 play essential roles in modifying potent antioxidants. These results highlight the intriguing possibility that each of the CNDP dipeptidases might have a different mechanistic role in suppression of NET protein complexes. In addition to analyzing protein levels between the previously mentioned patient populations, we quantified metabolite levels using gas chromatography-mass spectrometry (GC-MS)-based metabolomics analysis. In total, we quantified 205 metabolites across all patient samples (Supplemental Table 3 ). Comparing mild infection to HC showed a statistically significant (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 28, 2022. ; https://doi.org/10.1101/2022.04.26.22274196 doi: medRxiv preprint 13 cystine) levels were elevated in both mild (p=0.003) and severe (p=0.0004) relative to HC (Supplemental Table 3 ). NET formation is suppressed by antioxidants in vitro and in vivo (37, 38) . Glutathione is the cell's most potent antioxidant. L-cystine forms in the extracellular space from reduced glutathione. Upon transport into cells, L-cystine is an eventual substrate for glutathione synthesis. As increased levels of NET proteins were detected in a sub-population of our severe infection patient samples, we worked to evaluate relationships between mean NET protein zscores observed in the severe samples and L-cystine log2-fold abundance relative to HCs. Interestingly, we observed that mean NET protein z-scores were correlated to L-cystine levels (r All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Severe COVID-19 patients can develop acute respiratory distress syndrome (ARDS) which is characterized by hypoxemia and lung stiffness often related to increased permeability of the alveolar-capillary barrier, and an influx of neutrophils into the pulmonary space (1). Mouse models of ARDS recapitulate similar aspects of severe Coronavirus disease (38, 39) . Multiple studies using bacterial-induced ARDS display evidence of increased microcapillary permeability (38, 39) . Disruption of the alveolar-capillary barrier likely leads to both infiltration of leukocytes from the capillaries to the pulmonary space and exchange of alveolar contents to the blood. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. NETs are found in pulmonary capillary occlusions in mouse models of ARDS (39) and autopsies of coronavirus-induced ARDS (42) . Occlusions and endothelial cell disruption within the pulmonary capillaries are hypothesized as a possible mechanism to explain the increased permeability observed in ARDS (43) . In our study, comparison of mean NET protein z-scores to pulmonary surfactant B levels showed a strong correlation consistent with a direct relationship, suggesting that as NET formation increases, pulmonary capillary permeability increases. These results support the model of NETs driving permeability, potentially through the formation of capillary occlusions. In addition to significant correlations between the NET proteins and PSPB, we identified significant correlations between mean NET z-scores and 389 other proteins (r>0.6) (Supplemental Table 4 ). Among the other significant correlations were multiple established NET proteins characterized from other studies. We anticipate that within our correlative analysis to NETs there are other proteins that might stimulate NET formation. In addition, our correlative All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Recent studies from SARS-CoV-2 patient neutrophils show elevated release of reactive oxygen species (44) . Free radicals and oxidative stress pathways trigger NET formation. One of the primary sources of ROS in neutrophils is the NADPH oxidase enzyme (45) (46) (47) (48) (49) . We observed a clear correlation between mean NET z-protein scores and NAPDH protein levels in our study. In addition to activation of oxidation pathways driving NET formation, we observed a substantial elevation in antioxidant factors that might dampen NET formation. Specifically, we found that the glutathione substrate L-cystine was elevated in both the mild and severe infection patient samples. Activated neutrophils import L-cystine to produce glutathione (50) . Importantly, our proteomics experiments showed a complementary elevation of enzymes critical for glutathione metabolism including GSHR (glutathione reductase), GSH1 (Glutamate-cysteine ligase), and CNDP2 (promiscuous dipeptidase) in the severe infection patients, with an elevation of GSHR and GSH1 in the mild infection patients. Taken together, the most logical interpretation of these results is that glutathione synthesis is elevated in the blood plasma of all SARS-COV-2 patient populations and this likely represents a mechanism to suppress over-activation of neutrophils (and NET formation), and other harmful processes triggered by oxidation ( Figure 6 ). In addition to observing multiple, elevated signatures of glutathione synthesis in our studies, we observed an elevation of the carnosinase CNDP1 in mild infection samples. Unlike CNDP2, CNDP1 lacks a reported activity against Cys-Gly dipeptides in glutathione metabolism and instead, specifically digests the antioxidant dipeptide carnosine (alanine-histidine) (51) . Hence, CNDP1 activity is unlikely to accelerate glutathione synthesis. Instead, CNDP1's narrow metabolic activity targeting carnosine in mild infection patients is likely to drive an independent All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 28, 2022. ; https://doi.org/10.1101/2022.04.26.22274196 doi: medRxiv preprint antioxidant pathway working separately from the multiple enzymes observed driving glutathione synthesis. The substrate of CNDP1 (carnosine) has strong antioxidant activities (52) (53) (54) . Reactivity of carnosine with harmful, chemical species typically occurs within Carnosine's amine groups (distant from the peptide bond). Hence, it is possible that plasma CNDP1 carnosinase cleaves both modified carnosine derivative metabolites and non-oxidized forms. It is currently unclear how carnosinase activity would have a direct role in reducing oxidation and NET formation. One possibility is that cleavage of carnosine metabolites at the peptidyl bond facilitates excretion of adducted carnosine metabolites into the urine. Additionally, cleavage of carnosine into histidine and alanine metabolites could result in re-formation of carnosine through carnosine synthetase for subsequent rounds of antioxidant activity. The unique upregulation of CNDP1 in mild, but not severe infection patients raises the possibility that CNDP1 has a protective role in patients with mild infections. In support of this possibility, our results clearly show that CNDP1 levels are negatively correlated with PSPB levels and, in both mild and severe infection populations, as CNDP1 levels increase, mean NET protein z-scores decrease. To our knowledge, CNDP1 would be one of the first candidate enzymes to regulate NET formation in the context of infection. Animals with targeted deletions in CNDP1 display a shortened lifespan and have increased sensitivity to oxidative stress (36) . Importantly, administration of carnosine suppresses NET formation and capillary permeability in a mouse model of ARDS induced by bacteria (38) and suppresses capillary permeability, lung pathology, and neutrophil myeloperoxidase activity in mice infected with H9N2 influenza (55) . Taken together, these studies and ours highlight the possibility of CNDP1 up-regulation as part of a protective mechanism distinct to individuals with mild infections to suppress oxidative stress and NET formation. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Plasma samples were isolated in EDTA-coated tubes and were subjected to both proteomic analysis preparation including immunodepletion, trypsinization, TMT-labeling, and basic-RPfractionation and metabolomic analysis preparation using the Metabolite, Protein, Lipid All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Extraction method, essentially described previously (56, 57) . Briefly, plasma samples were (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The extracted metabolites from MPLEx were chemically derivatized based on the method reported previously (62) . To protect carbonyl groups and reduce the number of tautomeric isomers, methoxyamine (20 µL of a 30 mg/mL stock in anhydrous pyridine) was added to each sample, followed by incubation at 37°C with shaking for 90 min. To derivatize hydroxyl and amine groups to trimethylsilylated (TMS) forms, N-methyl-N-(trimethylsilyl)trifluoroacetamide with 1% trimethylchlorosilane (80 µL) was added to each vial, followed by incubation at 37°C with shaking for 30 min. The derivatized samples were analyzed by gas chromatography-mass spectrometry (GC-MS; Agilent 7890A GC with 5975 MSD single quadrupole; Agilent Technologies, Santa Clara, CA). Separation of metabolites were done by HP-5MS GC column (30 m × 0.25 mm × 0.25 µm; Agilent Technologies) and 1 µL of samples was injected in splitless mode. The helium flowrate was adjusted by retention time locking function, and the injection port temperature was held at 250°C throughout the analysis. The GC oven was held at 60°C for 1 min after injection, and the temperature was then increased to 325°C by 10°C/min, followed by a 10 min hold at 325°C. Data were collected over the mass range 50-600 m/z. A mixture of FAMEs (C8-C28) was analyzed together with the samples for retention index alignment purposes during subsequent data analysis. GC-MS data files were converted to CDF format and they are deconvoluted and aligned by Metabolite Detector (63) . Identification of metabolites was done by matching with PNNL metabolomics databases -augmented version of Agilent Fiehn metabolomics database (64) . The database contains mass spectra and retention index information of over 1,000 authentic chemical standards and they were cross-checked with commercial GC-MS databases such as NIST20 spectral library and Wiley 11th version GC-MS All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 28, 2022. ; https://doi.org/10.1101/2022.04.26.22274196 doi: medRxiv preprint databases (65, 66) . Three unique fragmented ions were selected and used to integrate peak area values, and a few metabolites were curated manually, when necessary. Major plasma proteins were immunodepleted using a Multiple Affinity Removal System (MARS) column (Hu-14 4.6 x 100 mm, Agilent Technologies, Santa Clara, CA) column in-line with an Agilent 1200 HPLC system and analyzed as described previously (67) . Flow-through fractions were collected and concentrated from the depletion column as described previously (57) . Depleted proteins were quantified using the BCA Protein Assay and denatured in 8M Immunodepleted, TMT-labeled peptide sample fractions were randomized and analyzed on a NanoAcuity UPLC system interfaced with a Thermofisher Q-Exactive HFX Orbital trap mass spectrometer (Thermofisher). Separation was carried out in a C18 revered-phase column (70 cm × 75 μm i.d., Phenomenex Jupiter, 3 μm particle size, 300 Å pore size) for 152 minutes. For detailed in gradient information and mass spectrometer settings please refer to previous work (57) . Briefly, precursor ions were analyzed between 300-1800 Thomson, at 60K resolution, an automatic gain control (AGC) of 3E6, and an injection time of 20ms. The top-12 most abundant precursor ions were fragmented by HCD (NCE setting=30) with a quadrupole isolation width of 0.7 Thomson, employing 30K resolution, an AGC target of 1E5 ions. Dynamic exclusion was All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 28, 2022. Quantitative information of the TMT reporter ion intensities was extracted using MASIC (70) . The median intensity of each peptide abundance for each sample was scaled to the combined internal standard TMT channel consisting of an equal concentration of plasma peptides from all patient samples as described previously (7) . Quantitation and statistical analysis of TMT results to generate graphs and plots utilized an in-house R-studio package (described below). Quantification and Statistical Analysis: All data preprocessing was done in R version 4.1.0 with the pmartR package (71) . Proteomics data was normalized to the reference sample by computing the ratio of each sample's peptide abundances to the respective combined internal standard TMT channel calculated within each plex. Peptide-level data and metabolomics data were log2 transformed and filtered to remove peptides and metabolites without enough observations to conduct at least one statistical comparison of interest (72) . One sample from the mild and one sample from the severe infection group was removed from the proteomics dataset and five samples from the metabolomics dataset (three from mild, one HC, one severe) as All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 28, 2022. protein, the z-score was calculated as z-score = (log2 abundance -mean of log2 HC abundances)/(pooled standard deviation) for each sample. The interpretation of the z-score value is the number of standard deviations away from the mean of the HC group. Statistically, any protein or metabolite with a z-score > 1 is in the top 16% of values, and a z-score > 2 corresponds with approximately the top 2.5% of observations. Pathway enrichment analysis was conducted using the ReactomePA R package (77) and statistically significant proteins for each pairwise comparison (adjusted p<0.05). Significant pathways were identified and prioritized based on adjusted p-values and associated gene counts. Statistical significance of age differences between the 9-highest severe patient NET protein z-scores and those 24 severe patients with lower NET protein z-scores were evaluated using a non-parametric kruskal-wallis test. All visualizations were generated using the ggplot2 (78) and trelliscopejs R packages. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Proteins in green have a mean difference between mild and severe with (P>0.05) (C) Analysis of NET protein z-score distributions among severe patient plasma samples. Numbers in red to the right indicate the number of NET proteins from the severe plasma sample with a z-score>2. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 28, 2022. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 28, 2022. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 28, 2022. ; https://doi.org/10.1101/2022.04.26.22274196 doi: medRxiv preprint 34 analysis of protein abundance between HC, mild, and severe samples of antioxidation response proteins CNDP2, GSHR, SODE, SODC, SODM, and GSH1 levels. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 28, 2022. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 28, 2022. A Novel Coronavirus from Patients with Pneumonia in China A decade after SARS: strategies for controlling emerging coronaviruses Global Percentage of Asymptomatic SARS-CoV-2 Infections Among the Tested Population and Individuals With Confirmed COVID-19 Diagnosis: A Systematic Review and Meta-analysis CoV-2 infection: A systematic review and meta-analysis Multi-omic Analysis of COVID-19 Severity Multi-Omics Resolves a Sharp Disease-State Shift between Mild and Moderate COVID-19 Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation Neutrophils and COVID-19: Nots, NETs, and knots Heightened Innate Immune Responses in the Respiratory Tract of COVID-19 Patients Neutralizing antibody levels are highly predictive of immune protection from symptomatic SARS-CoV-2 infection Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine Naturally enhanced neutralizing breadth against SARS-CoV-2 one year after infection The Role of Reactive Oxygen Species (ROS) in the Formation of Extracellular Traps (ETs) in Humans Leishmania amazonensis promastigotes induce and are killed by neutrophil extracellular traps Omics Analysis of Human Ebola Virus Disease Pathogenesis Neutrophil extracellular traps in COVID-19 Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS The Potential of Lung Epithelium Specific Proteins as Biomarkers for COVID-19-Associated Lung Injury. 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No reuse allowed without permission.(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted April 28, 2022. ; https://doi.org/10.1101/2022.04.26.22274196 doi: medRxiv preprint All rights reserved. No reuse allowed without permission.(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted April 28, 2022. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted April 28, 2022. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted April 28, 2022. ; https://doi.org/10.1101/2022.04.26.22274196 doi: medRxiv preprint 44 All rights reserved. No reuse allowed without permission.(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted April 28, 2022. ; https://doi.org/10.1101/2022.04.26.22274196 doi: medRxiv preprint 45 All rights reserved. No reuse allowed without permission.(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted April 28, 2022. ; https://doi.org/10.1101/2022.04.26.22274196 doi: medRxiv preprint