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. 

https://doi.org/10.1016/j.redox.2022.102553

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

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. 

https://www.nature.com/articles/s41598-022-20040-x.pdf

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

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.

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

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

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. 

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

Signaling pathway alterations in COVID-19 of living humans as well as therapeutic targets of the host proteins are not clear. We analyzed 317 urine proteomes, including 86 COVID-19, 55 pneumonia and 176 healthy controls, and identified specific RNA virus detector protein DDX58/RIG-I only in COVID-19 samples. Comparison of the COVID-19 urinary proteomes with controls revealed major pathway alterations in immunity, metabolism and protein localization. Biomarkers that may stratify severe symptoms from moderate ones suggested that macrophage induced inflammation and thrombolysis may play a critical role in worsening the disease. Hyper activation of the TCA cycle is evident and a macrophage enriched enzyme CLYBL is up regulated in COVID-19 patients. As CLYBL converts the immune modulatory TCA cycle metabolite itaconate through the citramalyl-CoA intermediate to acetyl-CoA, an increase in CLYBL may lead to the depletion of itaconate, limiting its anti-inflammatory function. These observations suggest that supplementation of itaconate and inhibition of CLYBL are possible therapeutic options for treating COVID-19, opening an avenue of modulating host defense as a means of combating SARS-CoV-2 viruses. 

/pdf/a-urinary-proteomic-landscape-of-covid-19-progression-5w4evz5i.pdf

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

Background: The evolutionary and epidemiological history and the regional differences of various hepatitis C virus (HCV) genotypes are complex. Our aim was to better understand the molecular epidemiology and evolutionary dynamics of HCV among HIV/HCV co-infected individuals in Guizhou Province. This information could contribute to improve HCV prevention and control strategies in Guizhou and surrounding provinces. Methods: The HCV RNA was extracted from the serum of HIV/HCV co-infected patients, and reverse transcription/nested PCR was performed to amplify nucleotide sequences of the C-E1 region. Then, the successfully amplified sequences were selected for phylogenetic analysis. The available C-E1 region reference sequences from the surrounding provinces of Guizhou (Guangxi, Yunnan, Hunan, and Sichuan) were retrieved in GenBank, and the evolutionary analysis by Bayesian Markov chain Monte Carlo (MCMC) algorithm was performed using BEAST software to reconstruct a phylogeographic tree in order to explore their migration patterns. Finally, the epidemiological history of HCV in the Guizhou region was retraced by reconstructing Bayesian skyline plots (BSPs) after excluding sequences from surrounding provinces. Results: Among 186 HIV/HCV co-infected patients, the C-E1 region sequence was successfully amplified in 177 cases. Phylogenetic analysis classified these sequences into six subtypes: 1a, 1b, 3a, 3b, 6a, and 6n. Among them, subtype 6a was the most dominant strain (n = 70), followed by 3b (n = 55), 1b (n = 31), 3a (n = 11), 1a (n = 8), and 6n (n = 2). By reconstructing the phylogeographic tree, we estimated that the 6a strain in Guizhou mainly originated from Yunnan and Guangxi, while the 3b strain emerged due to transmission from the IDU network in Yunnan. Subtypes 1b, 3a, 3b, and 6a, as the major subtypes of HCV in HIV/HCV co-infected individuals in Guizhou, emerged and later grew more rapidly than the national average. Notably, BSPs of the currently prevalent HCV predominant strain subtype 6a in Guizhou have shown a rapid population growth since 2004. Although the growth rate slowed down around 2010, this growth has continued to date. Conclusion: Overall, despite the improvement and implementation of a series of HCV prevention and control policies and measures, a delayed growth pattern may indicate a unique history of the spread of 6a in Guizhou. Its trend as the dominant strain in Guizhou in recent years may continue to increase slowly over subsequent years.

Growth history of hepatitis C virus among HIV/HCV co-infected patients in Guizhou Province

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

Growth history of hepatitis C virus among HIV/HCV co-infected patients in Guizhou Province