A urinary proteomic landscape of COVID-19 progression identifies signaling pathways and therapeutic options

Quercetin induces itaconic acid-mediated M1/M2 alveolar macrophages polarization in respiratory syncytial virus infection

BACKGROUND

Quercetin has received extensive attention for its therapeutic potential treating respiratory syncytial virus (RSV) infection diseases. Recent studies have highlighted quercetin's ability of suppressing alveolar macrophages (AMs)-derived lung inflammation. However, the anti-inflammatory mechanism of quercetin against RSV infection still remains elusive.

PURPOSE

This study aims to elucidate the mechanism about quercetin anti-inflammatory effect on RSV infection.

METHODS

BALB/c mice were intranasally infected with RSV and received quercetin (30, 60, 120 mg/kg/d) orally for 3 days. Additionally, an in vitro infection model utilizing mouse alveolar macrophages (MH-S cells) was employed to validate the proposed mechanism.

RESULTS

Quercetin exhibited a downregulatory effect on glycolysis and tricarboxylic acid (TCA) cycle metabolism in RSV-infected AMs. However, it increased itaconic acid production, a metabolite derived from citrate through activating immune responsive gene 1 (IRG1), and further inhibiting succinate dehydrogenase (SDH) activity. While the suppression of SDH activity orchestrated a cascading downregulation of Hif-1α/NLRP3 signaling, ultimately causing AMs polarization from M1 to M2 phenotypes.

CONCLUSION

Our study demonstrated quercetin stimulated IRG1-mediated itaconic acid anabolism and further inhibited SDH/Hif-1α/NLRP3 signaling pathway, which led to M1 to M2 polarization of AMs so as to ameliorate RSV-induced lung inflammation.

Itaconate alleviates diet-induced obesity via activation of brown adipocyte thermogenesis

Despite medical advances, there remains an unmet need for better treatment of obesity. Itaconate, a product of the decarboxylation of the tricarboxylic acid cycle intermediate cis-aconitate, plays a regulatory role in both metabolism and immunity. Here, we show that itaconate, as an endogenous compound, counteracts high-fat-diet (HFD)-induced obesity through leptin-independent mechanisms in three mouse models. Specifically, itaconate reduces weight gain, reverses hyperlipidemia, and improves glucose tolerance in HFD-fed mice. Additionally, itaconate enhances energy expenditure and the thermogenic capacity of brown adipose tissue (BAT). Unbiased proteomic analysis reveals that itaconate upregulates key proteins involved in fatty acid oxidation and represses the expression of lipogenic genes. Itaconate may provoke a major metabolic reprogramming by inducing fatty acid oxidation and suppression of fatty acid synthesis in BAT. These findings highlight itaconate as a potential activator of BAT-mediated thermogenesis and a promising candidate for anti-obesity therapy.

Anti-Necroptotic Effects of Itaconate and its Derivatives

Itaconate is an unsaturated dicarboxylic acid that is derived from the decarboxylation of the Krebs cycle intermediate cis-aconitate and has been shown to exhibit anti-inflammatory and anti-bacterial/viral properties. But the mechanisms underlying itaconate's anti-inflammatory activities are not fully understood. Necroptosis, a lytic form of regulated cell death (RCD), is mediated by receptor-interacting protein kinase 1 (RIPK1), RIPK3, and mixed lineage kinase domain-like protein (MLKL) signaling. It has been involved in the pathogenesis of organ injury in many inflammatory diseases. In this study, we aimed to explore whether itaconate and its derivatives can inhibit necroptosis in murine macrophages, a mouse MPC-5 cell line and a human HT-29 cell line in response to different necroptotic activators. Our results showed that itaconate and its derivatives dose-dependently inhibited necroptosis, among which dimethyl itaconate (DMI) was the most effective one. Mechanistically, itaconate and its derivatives inhibited necroptosis by suppressing the RIPK1/RIPK3/MLKL signaling and the oligomerization of MLKL. Furthermore, DMI promoted the nuclear translocation of Nrf2 that is a critical regulator of intracellular redox homeostasis, and reduced the levels of intracellular reactive oxygen species (ROS) and mitochondrial superoxide (mtROS) that were induced by necroptotic activators. Consistently, DMI prevented the loss of mitochondrial membrane potential induced by the necroptotic activators. In addition, DMI mitigated caerulein-induced acute pancreatitis in mice accompanied by reduced activation of the necroptotic signaling in vivo. Collectively, our study demonstrates that itaconate and its derivatives can inhibit necroptosis by suppressing the RIPK1/RIPK3/MLKL signaling, highlighting their potential applications for treating necroptosis-associated diseases.

CoVProt: Toward a Mass Spectrometry Data Portal for COVID-19 Proteomics Research and Development

The coronavirus disease 2019 (COVID-19) pandemic has wreaked havoc globally. Beyond the pandemic, the long-term effects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in multiple organ systems are yet to be deciphered. This calls for continued systems science research. Moreover, the host response to SARS-CoV-2 varies person-to-person and gives rise to different degrees of morbidity and mortality. Mass spectrometry (MS) has been a proven asset in studies of the SARS-CoV-2 from an omics systems science lens. To strengthen the proteomics research dedicated to COVID-19, we introduce here a web-based portal, CoVProt. The portal is work in progress and aims for a comprehensive curation of MS-based proteomics data of COVID-19 clinical samples for deep proteomic investigations, data visualization, and easy data accessibility for life sciences innovations and planetary health research community. Currently, CoVProt contains information on 2725 different proteins and 37,125 different peptides from six data sets covering a total of 202 clinical samples. Moreover, all pertinent data sets extracted from the literature have been reanalyzed using a common analysis pipeline developed by combining multiple tools. Going forward, we anticipate that the CoVProt portal will also provide access to the clinical parameters of the patients. The CoVProt (v1.0) portal addresses an existing significant gap to study COVID-19 host proteomics, which, to the best of our knowledge, is the first effort in this direction. We believe that CoVProt is poised to make contributions as a community resource for proteomic applications and aims to broadly support clinical studies to facilitate the discovery of COVID-19 biomarkers and therapeutics with translational potential.

In-depth urinary and exosome proteome profiling analysis identifies novel biomarkers for diabetic kidney disease

Diabetic kidney disease (DKD) is a major microvascular complication of type 2 diabetes mellitus (T2DM). Monitoring the early diagnostic period and disease progression plays a crucial role in treating DKD. In this study, to comprehensively elucidate the molecular characteristics of urinary proteins and urinary exosome proteins in type 2 DKD, we performed large-scale urinary proteomics (n=144) and urinary exosome proteomics (n=44) analyses on T2DM patients with albuminuria in varying degrees. The dynamics analysis of the urinary and exosome proteomes in our study provides a valuable resource for discovering potential urinary biomarkers in patients with DKD. A series of potential biomarkers, such as SERPINA1 and transferrin (TF), were detected and validated to be used for DKD diagnosis or disease monitoring. The results of our study comprehensively elucidated the changes in the urinary proteome and revealed several potential biomarkers reflecting the progression of DKD, which provide a reference for DKD biomarker screening.

COVIDpro: Database for Mining Protein Dysregulation in Patients with COVID-19

The ongoing pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 still has limited treatment options. Our understanding of the molecular dysregulations that occur in response to infection remains incomplete. We developed a web application COVIDpro (https://www.guomics.com/covidPro/) that includes proteomics data obtained from 41 original studies conducted in 32 hospitals worldwide, involving 3077 patients and covering 19 types of clinical specimens, predominantly plasma and serum. The data set encompasses 53 protein expression matrices, comprising a total of 5434 samples and 14,403 unique proteins. We identified a panel of proteins that exhibit significant dysregulation, enabling the classification of COVID-19 patients into severe and non-severe disease categories. The proteomic signatures achieved promising results in distinguishing severe cases, with a mean area under the curve of 0.87 and accuracy of 0.80 across five independent test sets. COVIDpro serves as a valuable resource for testing hypotheses and exploring potential targets for novel treatments in COVID-19 patients.

Exploring the potential mechanisms of impairment on genitourinary system associated with coronavirus disease 2019 infection: Bioinformatics and molecular simulation analyses

Objective

The novel coronavirus (severe acute respiratory syndrome coronavirus 2) has been spreading worldwide since December 2019, posing a serious danger to human health and socioeconomic development. A large number of clinical trials have revealed that coronavirus disease 2019 (COVID-19) results in multi-organ damage including the urogenital system. This study aimed to explore the potential mechanisms of genitourinary damage associated with COVID-19 infection through bioinformatics and molecular simulation analysis.

Methods

We used multiple publicly available databases to explore the expression patterns of ACE2, TMPRSS2, and CD147 (Basigin [BSG]) in major organs in the healthy and disease-specific populations, particularly the genitourinary organs. Single-cell RNA sequencing was used to analyze the cell-specific expression patterns of ACE2, TMPRSS2, CD147, cytokine receptors, and cytokine interacting proteins in genitourinary organs, such as the bladder, kidney, prostate, and testis. Additionally, gene set enrichment analysis was used to investigate the relationship between testosterone levels and COVID-19 vulnerability in patients with prostate cancer.

Results

The results revealed that ACE2, TMPRSS2, and CD147 were highly expressed in normal urogenital organs. Then, they were also highly expressed in multiple tumors and chronic kidney diseases. Additionally, ACE2, TMPRSS2, and CD147 were significantly expressed in a range of cells in urogenital organs according to single-cell RNA sequencing. Cytokine receptors and cytokine interacting proteins, especially CCL2, JUN, and TIMP1, were commonly highly expressed in urogenital organs. Finally, gene set enrichment analysis results showed that high testosterone levels in prostate cancer patients were significantly related to the JAK/STAT signaling pathway and the Toll-like receptor signaling pathway which were associated with COVID-19.

Conclusion

Our study provides new insights into the potential mechanisms of severe acute respiratory syndrome coronavirus 2 damage to urogenital organs from multiple perspectives, which may draw the attention of urologists to COVID-19 and contribute to the development of targeted drugs.

Effectiveness of massage therapy on anxiety and depression of COVID-19 convalescent: A protocol for systematic review and meta-analysis

BACKGROUND

Novel coronavirus pneumonia was first detected in Wuhan, China, in late December 2019. Its widespread infectivity and strong pathogenicity has posed a great threat to public health, seriously affecting social production and life. The disease caused by this virus has been officially named COVID-19 (coronavirus disease 2019) by the World Health Organization (WHO). Tuina (massage) therapy is 1 of the widely employed complementary and alternative medicine interventions in the world. As a useful therapy implemented on human's skin, muscles and joints, tuina (massage) has unique advantages in the field of medicine. This systematic review and meta-analysis will summarize the current evidence of tuina (massage) used as an intervention for COVID-19.

METHODS

We will search the following electronic databases for randomized controlled trials to evaluate the effectiveness and safety of massage therapy in treating all patients recovering from COVID-19: Wanfang and Pubmed Database, china national knowledge infrastructure database, cochrane central register of controlled trials, cumulative index of nursing and allied health literature and excerpta medica database. Each database will be searched from inception to October 2022. The entire process will include study selection, data extraction, risk of bias assessment and meta-analyses.

RESULTS

This proposed study will evaluate the effectiveness and safety of massage therapy for patients recovering from COVID-19.

CONCLUSIONS

This proposed systematic review will evaluate the existing evidence on the effectiveness and safety of massage therapy for patients recovering from COVID-19.

The signaling pathways and therapeutic potential of itaconate to alleviate inflammation and oxidative stress in inflammatory diseases

Endogenous small molecules are metabolic regulators of cell function. Itaconate is a key molecule that accumulates in cells when the Krebs cycle is disrupted. Itaconate is derived from cis-aconitate decarboxylation by cis-aconitate decarboxylase (ACOD1) in the mitochondrial matrix and is also known as immune-responsive gene 1 (IRG1). Studies have demonstrated that itaconate plays an important role in regulating signal transduction and posttranslational modification through its immunoregulatory activities. Itaconate is also an important bridge among metabolism, inflammation, oxidative stress, and the immune response. This review summarizes the structural characteristics and classical pathways of itaconate, its derivatives, and the compounds that release itaconate. Here, the mechanisms of itaconate action, including its transcriptional regulation of ATF3/IκBζ axis and type I IFN, its protein modification regulation of KEAP1, inflammasome, JAK1/STAT6 pathway, TET2, and TFEB, and succinate dehydrogenase and glycolytic enzyme metabolic action, are presented. Moreover, the roles of itaconate in diseases related to inflammation and oxidative stress induced by autoimmune responses, viruses, sepsis and IRI are discussed in this review. We hope that the information provided in this review will help increase the understanding of cellular immune metabolism and improve the clinical treatment of diseases related to inflammation and oxidative stress.

COVIDpro: Database for mining protein dysregulation in patients with COVID-19

Background

The ongoing pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still has limited treatment options partially due to our incomplete understanding of the molecular dysregulations of the COVID-19 patients. We aimed to generate a repository and data analysis tools to examine the modulated proteins underlying COVID-19 patients for the discovery of potential therapeutic targets and diagnostic biomarkers.

Methods

We built a web server containing proteomic expression data from COVID-19 patients with a toolset for user-friendly data analysis and visualization. The web resource covers expert-curated proteomic data from COVID-19 patients published before May 2022. The data were collected from ProteomeXchange and from select publications via PubMed searches and aggregated into a comprehensive dataset. Protein expression by disease subgroups across projects was compared by examining differentially expressed proteins. We also visualize differentially expressed pathways and proteins. Moreover, circulating proteins that differentiated severe cases were nominated as predictive biomarkers.

Findings

We built and maintain a web server COVIDpro ( https://www.guomics.com/covidPro/ ) containing proteomics data generated by 41 original studies from 32 hospitals worldwide, with data from 3077 patients covering 19 types of clinical specimens, the majority from plasma and sera. 53 protein expression matrices were collected, for a total of 5434 samples and 14,403 unique proteins. Our analyses showed that the lipopolysaccharide-binding protein, as identified in the majority of the studies, was highly expressed in the blood samples of patients with severe disease. A panel of significantly dysregulated proteins was identified to separate patients with severe disease from non-severe disease. Classification of severe disease based on these proteomic signatures on five test sets reached a mean AUC of 0.87 and ACC of 0.80.

Interpretation

COVIDpro is an online database with an integrated analysis toolkit. It is a unique and valuable resource for testing hypotheses and identifying proteins or pathways that could be targeted by new treatments of COVID-19 patients.

Funding

National Key R&D Program of China: Key PDPM technologies (2021YFA1301602, 2021YFA1301601, 2021YFA1301603), Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars (LR19C050001), Hangzhou Agriculture and Society Advancement Program (20190101A04), National Natural Science Foundation of China (81972492) and National Science Fund for Young Scholars (21904107), National Resource for Network Biology (NRNB) from the National Institute of General Medical Sciences (NIGMS-P41 GM103504).

Research in context

Evidence before this study: Although an increasing number of therapies against COVID-19 are being developed, they are still insufficient, especially with the rise of new variants of concern. This is partially due to our incomplete understanding of the disease’s mechanisms. As data have been collected worldwide, several questions are now worth addressing via meta-analyses. Most COVID-19 drugs function by targeting or affecting proteins. Effectiveness and resistance to therapeutics can be effectively assessed via protein measurements. Empowered by mass spectrometry-based proteomics, protein expression has been characterized in a variety of patient specimens, including body fluids (e.g., serum, plasma, urea) and tissue (i.e., formalin-fixed and paraffin-embedded (FFPE)). We expert-curated proteomic expression data from COVID-19 patients published before May 2022, from the largest proteomic data repository ProteomeXhange as well as from literature search engines. Using this resource, a COVID-19 proteome meta-analysis could provide useful insights into the mechanisms of the disease and identify new potential drug targets.Added value of this study: We integrated many published datasets from patients with COVID-19 from 11 nations, with over 3000 patients and more than 5434 proteome measurements. We collected these datasets in an online database, and generated a toolbox to easily explore, analyze, and visualize the data. Next, we used the database and its associated toolbox to identify new proteins of diagnostic and therapeutic value for COVID-19 treatment. In particular, we identified a set of significantly dysregulated proteins for distinguishing severe from non-severe patients using serum samples.Implications of all the available evidence: COVIDpro will support the navigation and analysis of patterns of dysregulated proteins in various COVID-19 clinical specimens for identification and verification of protein biomarkers and potential therapeutic targets.

Identification of the effects of COVID-19 on patients with pulmonary fibrosis and lung cancer: a bioinformatics analysis and literature review

Coronavirus disease 2019 (COVID-19) poses a serious threat to human health and life. The effective prevention and treatment of COVID-19 complications have become crucial to saving patients’ lives. During the phase of mass spread of the epidemic, a large number of patients with pulmonary fibrosis and lung cancers were inevitably infected with the SARS-CoV-2 virus. Lung cancers have the highest tumor morbidity and mortality rates worldwide, and pulmonary fibrosis itself is one of the complications of COVID-19. Idiopathic lung fibrosis (IPF) and various lung cancers (primary and metastatic) become risk factors for complications of COVID-19 and significantly increase mortality in patients. Therefore, we applied bioinformatics and systems biology approaches to identify molecular biomarkers and common pathways in COVID-19, IPF, colorectal cancer (CRC) lung metastasis, SCLC and NSCLC. We identified 79 DEGs between COVID-19, IPF, CRC lung metastasis, SCLC and NSCLC. Meanwhile, based on the transcriptome features of DSigDB and common DEGs, we identified 10 drug candidates. In this study, 79 DEGs are the common core genes of the 5 diseases. The 10 drugs were found to have positive effects in treating COVID-19 and lung cancer, potentially reducing the risk of pulmonary fibrosis.

Spike S1 domain interactome in non-pulmonary systems: A role beyond the receptor recognition

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes Coronavirus Disease 2019 (COVID-19), which, since 2019 in China, has rapidly become a worldwide pandemic. The aggressiveness and global spread were enhanced by the many SARS-CoV-2 variants that have been isolated up to now. These mutations affect mostly the viral glycoprotein Spike (S), the capsid protein mainly involved in the early stages of viral entry processes, through the recognition of specific receptors on the host cell surface. In particular, the subunit S1 of the Spike glycoprotein contains the Receptor Binding Domain (RBD) and it is responsible for the interaction with the angiotensin-converting enzyme 2 (ACE2). Although ACE2 is the primary Spike host receptor currently studied, it has been demonstrated that SARS-CoV-2 is also able to infect cells expressing low levels of ACE2, indicating that the virus may have alternative receptors on the host cells. The identification of the alternative receptors can better elucidate the pathogenicity and the tropism of SARS-CoV-2. Therefore, we investigated the Spike S1 interactomes, starting from host membrane proteins of non-pulmonary cell lines, such as human kidney (HK-2), normal colon (NCM460D), and colorectal adenocarcinoma (Caco-2). We employed an affinity purification-mass spectrometry (AP-MS) to pull down, from the membrane protein extracts of all cell lines, the protein partners of the recombinant form of the Spike S1 domain. The purified interactors were identified by a shotgun proteomics approach. The lists of S1 potential interacting proteins were then clusterized according to cellular localization, biological processes, and pathways, highlighting new possible S1 intracellular functions, crucial not only for the entrance mechanisms but also for viral replication and propagation processes.