Proteomics Analysis of Serum from COVID-19 Patients

Valuable Contributions and Lessons Learned from Proteomics and Metabolomics Studies of COVID-19

The COVID-19 pandemic caused by the SARS-CoV-2 virus infected more than 775,686,716 humans and was responsible for the death of more than 7,054,093 individuals. COVID-19 has taught us that the development of vaccines, repurposing of drugs, and understanding the mechanism of a disease can be done within a short time. The COVID-19 proteomics and metabolomics has contributed to its diagnosis, understanding of its progression, host-virus interaction, disease mechanism, and also in the search of suitable anti-COVID therapeutics. Mass spectrometry based proteomics was used to find the potential biomarkers of different stages of COVID-19 including severe and nonsevere cases in the blood serum. Notably, protein-protein interaction techniques to understand host-virus interactions were also significantly useful. The single-cell proteomics studies were carried out to ascertain the changes in immune cell composition and its activation in mild COVID-19 patients versus severe COVID-19 patients using whole-blood and peripheral-blood mononuclear cells. Modern technologies were helpful to deal with the pandemic; however, there is still scope for further development. Further, attempts were made to understand the protein-protein, metabolite-metabolite, and protein-metabolite interactomes, derived from proteins and metabolite fingerprints of COVID-19 patients by reanalysis of COVID-19 public mass spectrometry based proteomics and metabolomics studies. Further, some of these interactions were supported by the literature as validations in the COVID-19 studies.

Unbiased plasma profiling using pre-selected RNA aptamer pools predicts mortality in COVID-19 and identifies protein risk factors

The impact of the COVID-19 pandemic demands effective prognostic tools for precise risk evaluation and timely intervention. This study utilized the APTASHAPE technology to profile plasma proteins in COVID-19 patient samples. Employing a highly diverse 2'-fluoro-protected RNA aptamer pool enriched toward proteins in the plasma samples from COVID-19 patients, we performed a single round of parallel selection on the derivation cohort and identified 93 discriminatory aptamers capable of distinguishing COVID-19 and healthy plasma samples. A subset of these aptamers was then used to predict 30-day mortality with high sensitivity and specificity in a validation cohort of 165 patients. We predicted 30-day mortality with areas under the curve (AUCs) of 0.91 in females and 0.68 in males. Affinity purification coupled with mass spectrometry analysis of the aptamer-targeted proteins identified potential biomarkers associated with disease severity, including complement system components. The study demonstrates the APTASHAPE technology as an unbiased approach that not only aids in predicting disease outcomes but also offers insights into gender-specific differences, shedding light on the nuanced aspects of COVID-19 pathophysiology. In conclusion, the findings highlight the promise of APTASHAPE as a valuable tool for estimating risk factors in COVID-19 patients and enabling stratification for personalized treatment management.

Potential therapeutic applications of circular RNA in acute kidney injury

Acute kidney injury (AKI) is a common clinical syndrome characterized by a rapid deterioration in renal function, manifested by a significant increase in creatinine and a sharp decrease in urine output. The incidence of morbidity and mortality associated with AKI is on the rise, with most patients progressing to chronic kidney disease or end-stage renal disease. Treatment options for patients with AKI remain limited. Circular RNA (circRNA) is a wide and diverse class of non-coding RNAs that are present in a variety of organisms and are involved in gene expression regulation. Studies have shown that circRNA acts as a competing RNA, is involved in disease occurrence and development, and has potential as a disease diagnostic and prognostic marker. CircRNA is involved in the regulation of important biological processes, including apoptosis, oxidative stress, and inflammation. This study reviews the current status and progress of circRNA research in the context of AKI.

Meta-analysis of the serum/plasma proteome identifies significant associations between COVID-19 with Alzheimer's/Parkinson's diseases

In recent years, we have seen the widespread devastations and serious health complications manifested by COVID-19 globally. Although we have effectively controlled the pandemic, uncertainties persist regarding its potential long-term effects, including prolonged neurological issues. To gain comprehensive insights, we conducted a meta-analysis of mass spectrometry-based proteomics data retrieved from different studies with a total of 538 COVID-19 patients and 523 healthy controls. The meta-analysis revealed that top-enriched pathways were associated with neurological disorders, including Alzheimer's (AD) and Parkinson's disease (PD). Further analysis confirmed a direct correlation in the expression patterns of 24 proteins involved in Alzheimer's and 23 proteins in Parkinson's disease with COVID-19. Protein-protein interaction network and cluster analysis identified SNCA as a hub protein, a known biomarker for Parkinson's disease, in both AD and PD. To the best of our knowledge, this is the first meta-analysis study providing proteomic profiling evidence linking COVID-19 to neurological complications.

Plasma proteome perturbation for CMV DNAemia in kidney transplantation

BACKGROUND

Cytomegalovirus (CMV) infection, either de novo or as reactivation after allotransplantation and chronic immunosuppression, is recognized to cause detrimental alloimmune effects, inclusive of higher susceptibility to graft rejection and substantive impact on chronic graft injury and reduced transplant survival. To obtain further insights into the evolution and pathogenesis of CMV infection in an immunocompromised host we evaluated changes in the circulating host proteome serially, before and after transplantation, and during and after CMV DNA replication (DNAemia), as measured by quantitative polymerase chain reaction (QPCR).

METHODS

LC-MS-based proteomics was conducted on 168 serially banked plasma samples, from 62 propensity score-matched kidney transplant recipients. Patients were stratified by CMV replication status into 31 with CMV DNAemia and 31 without CMV DNAemia. Patients had blood samples drawn at protocol times of 3- and 12-months post-transplant. Additionally, blood samples were also drawn before and 1 week and 1 month after detection of CMV DNAemia. Plasma proteins were analyzed using an LCMS 8060 triple quadrupole mass spectrometer. Further, public transcriptomic data on time matched PBMCs samples from the same patients was utilized to evaluate integrative pathways. Data analysis was conducted using R and Limma.

RESULTS

Samples were segregated based on their proteomic profiles with respect to their CMV Dnaemia status. A subset of 17 plasma proteins was observed to predict the onset of CMV at 3 months post-transplant enriching platelet degranulation (FDR, 4.83E-06), acute inflammatory response (FDR, 0.0018), blood coagulation (FDR, 0.0018) pathways. An increase in many immune complex proteins were observed at CMV infection. Prior to DNAemia the plasma proteome showed changes in the anti-inflammatory adipokine vaspin (SERPINA12), copper binding protein ceruloplasmin (CP), complement activation (FDR = 0.03), and proteins enriched in the humoral (FDR = 0.01) and innate immune responses (FDR = 0.01).

CONCLUSION

Plasma proteomic and transcriptional perturbations impacting humoral and innate immune pathways are observed during CMV infection and provide biomarkers for CMV disease prediction and resolution. Further studies to understand the clinical impact of these pathways can help in the formulation of different types and duration of anti-viral therapies for the management of CMV infection in the immunocompromised host.

Blood leukocyte transcriptional modules and differentially expressed genes associated with disease severity and age in COVID-19 patients

Since the molecular mechanisms determining COVID-19 severity are not yet well understood, there is a demand for biomarkers derived from comparative transcriptome analyses of mild and severe cases, combined with patients' clinico-demographic and laboratory data. Here the transcriptomic response of human leukocytes to SARS-CoV-2 infection was investigated by focusing on the differences between mild and severe cases and between age subgroups (younger and older adults). Three transcriptional modules correlated with these traits were functionally characterized, as well as 23 differentially expressed genes (DEGs) associated to disease severity. One module, correlated with severe cases and older patients, had an overrepresentation of genes involved in innate immune response and in neutrophil activation, whereas two other modules, correlated with disease severity and younger patients, harbored genes involved in the innate immune response to viral infections, and in the regulation of this response. This transcriptomic mechanism could be related to the better outcome observed in younger COVID-19 patients. The DEGs, all hyper-expressed in the group of severe cases, were mostly involved in neutrophil activation and in the p53 pathway, therefore related to inflammation and lymphopenia. These biomarkers may be useful for getting a better stratification of risk factors in COVID-19.

Proteomic Investigation of COVID-19 Severity During the Tsunamic Second Wave in Mumbai

Maharashtra was severely affected during the noxious second wave of COVID-19, with the highest number of cases recorded across India. The emergence of new symptoms and dysregulation of multiple organs resulted in high disease severity during the second wave which led to increased difficulties in understanding the molecular mechanisms behind the disease pathology. Exploring the underlying factors can help to relieve the burden on the medical communities to some extent by prioritizing the patients and, at the same time, opening avenues for improved treatments. In the current study, we have performed a mass-spectrometry-based proteomic analysis to investigate the disease pathology using nasopharyngeal swab samples collected from the COVID-19 patients in the Mumbai region of Maharashtra over the period of March-June 2021, the peak of the second wave. A total of 59 patients, including 32 non-severe and 27 severe cases, were considered for this proteomic study. We identified 23 differentially regulated proteins in severe patients as a host response to infection. In addition to the previously identified innate mechanisms of neutrophil and platelet degranulation, this study revealed significant alterations of anti-microbial peptide pathways in severe conditions, illustrating its role in the severity of the infectious strain of COVID-19 during the second wave. Furthermore, myeloperoxidase, cathepsin G, and profilin-1 were identified as potential therapeutic targets of the FDA-approved drugs dabrafenib, ZINC4097343, and ritonavir. This study has enlightened the role of the anti-microbial peptide pathway associated with the second wave in India and proposed its importance in potential therapeutics for COVID-19.

Glutamine-Driven Metabolic Adaptation to COVID-19 Infection

Background

COVID-19 is known to be transmitted by direct contact, droplets or feces/orally. There are many factors which determines the clinical progression of the disease. Aminoacid disturbance in viral disease is shown in many studies. İn this study we aimed to evaluate the change of aminoacid metabolism especially the aspartate, glutamine and glycine levels which have been associated with an immune defence effect in viral disease.

Methods

Blood samples from 35 volunteer patients with COVID-19, concretized diagnosis was made by oropharyngeal from nazofaringeal swab specimens and reverse transcriptase-polymerase chain reaction, and 35 control group were analyzed. The amino acid levels were measured with liquid chromatography-mass spectrometry technology. Two groups were compared by Kolmogorov-Smirnov analysis, Kruskal-Wallis and the Mann-Whitney U. The square test was used to evaluate the tests obtained by counting, and the error level was taken as 0.05.

Results

The average age of the patient and control group were 48.5 ± 14.9 and 48.8 ± 14.6 years respectively. The decrease in aspartate (p = 5.5 × 10^-9) and glutamine levels (p = 9.0 × 10^-17) were significiantly in COVID group, whereas Glycine (p = 0.243) increase was not significiant.

Conclusions

Metabolic pathways, are affected in rapidly dividing cells in viral diseases which are important for immun defence. We determined that aspartate, glutamine and glycine levels in Covid 19 patients were affected by the warburg effect, malate aspartate shuttle, glutaminolysis and pentose phosphate pathway. Enteral or parenteral administration of these plasma amino acid levels will correct the duration and pathophysiology of the patients' stay in hospital and intensive care.

Expression profiling of inflammation-related genes including IFI-16, NOTCH2, CXCL8, THBS1 in COVID-19 patients

The present study aimed to scrutinize the expression profile of inflammatory-related genes (IFI-16, NOTCH2, CXCL8, and THBS1) from acute to post-acute stage of this infectious epidemic. The current cross-sectional study consisted of 53 acute-phase COVID-19 patients and 53 healthy individuals between February and March 2021. The extraction of total RNA was performed from PBMC specimens and also expression level of selected genes (IFI-16, NOTCH2, CXCL8, and THBS1) was evaluated by real-time PCR. Subsequently, levels of these factors were re-measured six weeks after the acute phase to determine if the levels of chosen genes returned to normal after the acute phase of COVID-19. Receiver operating characteristic (ROC) curve was plotted to test potential of genes as a diagnostic biomarker. The expression levels of inflammatory-related genes were significantly different between healthy and COVID-19 subjects. Besides, a significant higher CXCL8 level was found in the acute-phase COVID-19 compared to post-acute-phase infection which may be able to be considered as a potential biomarker for distinguishing between the acute phases from the post-acute-phase status. Deregulation of the inflammatory-related genes in COVID-19 patients, especially CXCL-8, can be serving as potent biomarkers to manage the COVID-19 infection.

The serum of COVID-19 asymptomatic patients up-regulates proteins related to endothelial dysfunction and viral response in circulating angiogenic cells ex-vivo

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already caused 6 million deaths worldwide. While asymptomatic individuals are responsible of many potential transmissions, the difficulty to identify and isolate them at the high peak of infection constitutes still a real challenge. Moreover, SARS-CoV-2 provokes severe vascular damage and thromboembolic events in critical COVID-19 patients, deriving in many related deaths and long-hauler symptoms. Understanding how these processes are triggered as well as the potential long-term sequelae, even in asymptomatic individuals, becomes essential.

Methods

We have evaluated, by application of a proteomics-based quantitative approach, the effect of serum from COVID-19 asymptomatic individuals over circulating angiogenic cells (CACs). Healthy CACs were incubated ex-vivo with the serum of either COVID-19 negative (PCR −/IgG −, n:8) or COVID-19 positive asymptomatic donors, at different infective stages: PCR +/IgG − (n:8) and PCR −/IgG + (n:8). Also, a label free quantitative approach was applied to identify and quantify protein differences between these serums. Finally, machine learning algorithms were applied to validate the differential protein patterns in CACs.

Results

Our results confirmed that SARS-CoV-2 promotes changes at the protein level in the serum of infected asymptomatic individuals, mainly correlated with altered coagulation and inflammatory processes (Fibrinogen, Von Willebrand Factor, Thrombospondin-1). At the cellular level, proteins like ICAM-1, TLR2 or Ezrin/Radixin were only up-regulated in CACs treated with the serum of asymptomatic patients at the highest peak of infection (PCR + /IgG −), but not with the serum of PCR −/IgG + individuals. Several proteins stood out as significantly discriminating markers in CACs in response to PCR or IgG + serums. Many of these proteins particiArticle title: Kindly check and confirm the edit made in the article title.pate in the initial endothelial response against the virus.

Conclusions

The ex vivo incubation of CACs with the serum of asymptomatic COVID-19 donors at different stages of infection promoted protein changes representative of the endothelial dysfunction and inflammatory response after viral infection, together with activation of the coagulation process. The current approach constitutes an optimal model to study the response of vascular cells to SARS-CoV-2 infection, and an alternative platform to test potential inhibitors targeting either the virus entry pathway or the immune responses following SARS-CoV-2 infection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-022-00465-w.

Antibody-Based Affinity Capture Combined with LC-MS Analysis for Identification of COVID-19 Disease Serum Biomarkers

Blood serum or plasma proteins are potentially useful in COVID-19 research as biomarkers for risk prediction, diagnosis, stratification, and treatment monitoring. However, serum protein-based biomarker identification and validation is complicated due to the wide concentration range of these proteins, which spans more than ten orders of magnitude. Here we present a combined affinity purification-liquid chromatography mass spectrometry approach which allows identification and quantitation of the most abundant serum proteins along with the nonspecifically bound and interaction proteins. This led to the reproducible identification of more than 100 proteins that were not specifically targeted by the affinity column. Many of these have already been implicated in COVID-19 disease.

Characterization by Quantitative Serum Proteomics of Immune-Related Prognostic Biomarkers for COVID-19 Symptomatology

The COVID-19 pandemic caused by SARS-CoV-2 challenges the understanding of factors affecting disease progression and severity. The identification of prognostic biomarkers and physiological processes associated with disease symptoms is relevant for the development of new diagnostic and therapeutic interventions to contribute to the control of this pandemic. To address this challenge, in this study, we used a quantitative proteomics together with multiple data analysis algorithms to characterize serum protein profiles in five cohorts from healthy to SARS-CoV-2-infected recovered (hospital discharge), nonsevere (hospitalized), and severe [at the intensive care unit (ICU)] cases with increasing systemic inflammation in comparison with healthy individuals sampled prior to the COVID-19 pandemic. The results showed significantly dysregulated proteins and associated biological processes and disorders associated to COVID-19. These results corroborated previous findings in COVID-19 studies and highlighted how the representation of dysregulated serum proteins and associated BPs increases with COVID-19 disease symptomatology from asymptomatic to severe cases. The analysis was then focused on novel disease processes and biomarkers that were correlated with disease symptomatology. To contribute to translational medicine, results corroborated the predictive value of selected immune-related biomarkers for disease recovery [Selenoprotein P (SELENOP) and Serum paraoxonase/arylesterase 1 (PON1)], severity [Carboxypeptidase B2 (CBP2)], and symptomatology [Pregnancy zone protein (PZP)] using protein-specific ELISA tests. Our results contributed to the characterization of SARS-CoV-2–host molecular interactions with potential contributions to the monitoring and control of this pandemic by using immune-related biomarkers associated with disease symptomatology.

Mass Spectrometry-based Proteomics and Glycoproteomics in COVID-19 Biomarkers Identification: A Mini-review

The first corona-pandemic, coronavirus disease 2019 (COVID-19) caused a huge health crisis and incalculable damage worldwide. Knowledge of how to cure the disease is urgently needed. Emerging immune escaping mutants of the virus suggested that it may be potentially persistent in human society as a regular health threat as the flu virus. Therefore, it is imperative to identify appropriate biomarkers to indicate pathological and physiological states, and more importantly, clinic outcomes. Proteins are the performers of life functions, and their abundance and modification status can directly reflect the immune status. Protein glycosylation serves a great impact in modulating protein function. The use of both unmodified and glycosylated proteins as biomarkers has also been proved feasible in the studies of SARS, Zika virus, influenza, etc. In recent years, mass spectrometry-based glycoproteomics, as well as proteomics approaches, advanced significantly due to the evolution of mass spectrometry. We focus on the current development of the mass spectrometry-based strategy for COVID-19 biomarkers' investigation. Potential application of glycoproteomics approaches and challenges in biomarkers identification are also discussed.

Multi-omic profiling of plasma reveals molecular alterations in children with COVID-19

Rationale: Children usually develop less severe symptoms responding to Coronavirus Disease 2019 (COVID-19) than adults. However, little is known about the molecular alterations and pathogenesis of COVID-19 in children. Methods: We conducted plasma proteomic and metabolomic profilings of the blood samples of a cohort containing 18 COVID-19-children with mild symptoms and 12 healthy children, which were enrolled from hospital admissions and outpatients, respectively. Statistical analyses were performed to identify molecules specifically altered in COVID-19-children. We also developed a machine learning-based pipeline named inference of biomolecular combinations with minimal bias (iBM) to prioritize proteins and metabolites strongly altered in COVID-19-children, and experimentally validated the predictions. Results: By comparing to the multi-omic data in adults, we identified 44 proteins and 249 metabolites differentially altered in COVID-19-children against healthy children or COVID-19-adults. Further analyses demonstrated that both deteriorative immune response/inflammation processes and protective antioxidant or anti-inflammatory processes were markedly induced in COVID-19-children. Using iBM, we prioritized two combinations that contained 5 proteins and 5 metabolites, respectively, each exhibiting a total area under curve (AUC) value of 100% to accurately distinguish COVID-19-children from healthy children or COVID-19-adults. Further experiments validated that all the 5 proteins were up-regulated upon coronavirus infection. Interestingly, we found that the prioritized metabolites inhibited the expression of pro-inflammatory factors, and two of them, methylmalonic acid (MMA) and mannitol, also suppressed coronaviral replication, implying a protective role of these metabolites in COVID-19-children. Conclusion: The finding of a strong antagonism of deteriorative and protective effects provided new insights on the mechanism and pathogenesis of COVID-19 in children that mostly underwent mild symptoms. The identified metabolites strongly altered in COVID-19-children could serve as potential therapeutic agents of COVID-19.