Integrated microbiome, metabolome, and proteome analysis identifies a novel interplay among commensal bacteria, metabolites and candidate targets in non‐small cell lung cancer

ObjectiveThe gut micro-biome plays a pivotal role in the progression of lung cancer. However, the specific mechanisms by which the intestinal microbiota and its metabolites are involved in the lung cancer process remain unclear.MethodStool samples from 52 patients with lung cancer and 29 healthy control individuals were collected and subjected to 16S rRNA gene amplification sequencing and non-targeted gas/liquid chromatography-mass spectrometry metabolomics analysis. Then microbiota, metabolites and potential signaling pathways that may play an important role in the disease were filtered.ResultsFirmicutes, Clostridia, Bacteroidacea, Bacteroides, and Lachnospira showed a greater abundance in healthy controls. In contrast, the Ruminococcus gnavus(R.gnavus) was significantly upregulated in lung cancer patients. In this respect, the micro-biome of the squamous cell carcinoma(SCC)group demonstrated a relatively higher abundance of Proteobacteria, Gammaproteobacteria, Bacteroides,and Enterobacteriaceae, as well as higher abundances of Fusicatenibacter and Roseburia in adenocarcinoma(ADC) group. Metabolomic analysis showed significant alterations in fecal metabolites including including quinic acid, 3-hydroxybenzoic acid,1-methylhydantoin,3,4-dihydroxydrocinnamic acid and 3,4-dihydroxybenzeneacetic acid were significantly altered in lung cancer patients. Additionally, the R.gnavus and Fusicatenibacter of lung cancer were associated with multiple metabolite levels.ConclusionOur study provides essential guidance for a fundamental systematic and multilevel assessment of the contribution of gut micro-biome and their metabolites in lung cancer,which has great potential for understanding the pathogenesis of lung cancer and for better early prevention and targeted interventions.

Section: Discussioncontrasting

confidence: 97%

Structure of gut microbiota and characteristics of fecal metabolites in patients with lung cancer

Lu¹,

Xiong²,

Zheng³

et al. 2023

“…Prevotella copri is the most well-known of the Prevotella genus and is positively correlated with many inflammatory diseases, such as rheumatoid arthritis and ankylosing spondylitis ( Tett et al., 2021 ). Transplantation of Prevotella copri induces dysbiosis of inflammatory and immune functions and can induce arthritis in mice ( Maeda et al., 2016 ; Qian et al., 2022 ). Although less well studied, Clostridium ramosum has been proven to be positively correlated with Covid-19 disease severity, as well as infection and bacteremia ( Zuo et al., 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Altered gut microbiota in the early stage of acute pancreatitis were related to the occurrence of acute respiratory distress syndrome

Han

Zhou

et al. 2023

BackgroundAcute respiratory distress syndrome (ARDS) is the most common cause of organ failure in acute pancreatitis (AP) patients, which associated with high mortality. Specific changes in the gut microbiota have been shown to influence progression of acute pancreatitis. We aimed to determine whether early alterations in the gut microbiota is related to and could predict ARDS occurrence in AP patients.MethodsIn this study, we performed 16S rRNA sequencing analysis in 65 AP patients and 20 healthy volunteers. The AP patients were further divided into two groups: 26 AP-ARDS patients and 39 AP-nonARDS patients based on ARDS occurrence during hospitalization.ResultsOur results showed that the AP-ARDS patients exhibited specific changes in gut microbiota composition and function as compared to subjects of AP-nonARDS group. Higher abundances of Proteobacteria phylum, Enterobacteriaceae family, Escherichia-Shigella genus, and Klebsiella pneumoniae, but lower abundances of Bifidobacterium genus were found in AP-ARDS group compared with AP-nonARDS groups. Random forest modelling analysis revealed that the Escherichia-shigella genus was effective to distinguish AP-ARDS from AP-nonARDS, which could predict ARDS occurrence in AP patients.ConclusionsOur study revealed that alterations of gut microbiota in AP patients on admission were associated with ARDS occurrence after hospitalization, indicating a potential predictive and pathogenic role of gut microbiota in the development of ARDS in AP patients.

“…Disorders of gut microbiota-host co-metabolites are associated with diseases ( Yang et al., 2019 ; Yan et al., 2022 ; Qian et al., 2022 ). Correlation analysis has shown a positive correlation between the pyruvic acid and the severity of ICH.…”

Section: Discussionmentioning

confidence: 99%

Multi-omics reveals specific host metabolism-microbiome associations in intracerebral hemorrhage

Chen

Wang

Zhang

et al. 2022

Intracerebral hemorrhage (ICH) is the most devastating subtype of stroke, but effective prevention and treatment strategies are lacking. Recently, gut microbiome and its metabolitesis are considered to be an influencing factor of stroke. However, little is known about the effects of the gut microbiome on ICH and host metabolic activity. Therefore, we used 16S sequencing, macrogenomics sequencing and untargeted metabolomics to explore the differences in gut microbial-metabolome interactions between patients with intracerebral hemorrhage and healthy control populations. We found a significant decrease in the phylum of Firmicutes and a significant increase of Bacteroidetes in ICH patients. At the genus level, Streptococcus, Bifidobacterium, Akkermansia, and Lactobacillus were more abundant in ICH patients. Macrogenomic analysis revealed active glycosaminoglycan degradation, heme synthesis, galactose degradation, lipopolysaccharide core region synthesis, and beta-Lactam resistance in ICH patients. Serum untargeted metabolomic analysis combined with ROC curves showed that octanoylcarnitine, decanoylcarnitine, dodecanoylcarnitine, glyceric acid, pyruvic acid, aspartic acid, methylcysteine, pyroglutamic acid, 9E-tetradecenoic acid, N-Acetylneuraminic acid, and aconitic acid were the best markers for the diagnosis of ICH. Correlation analysis showed that microbiome enriched in the gut of ICH patients were significantly correlated with serum metabolites, revealing a close correlation between the gut microbiome of ICH patients and the host metabolome, and significant differences from the healthy population. microbiota-host co-metabolites including pyruvic acid and 9E-tetradecenoic acid is associated with the the National Institutes of Health Stroke Scale (NIHSS) scores. In conclusion, microbiome-related metabolites in ICH patients was associated with the severity of ICH, the microbiota-host co-metabolites may be a potential may be potential therapeutic targets.