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Gut microbiome-derived bacterial extracellular vesicles in patients with solid tumours

细胞外小泡 微生物群 蛋白质组 胞外囊泡 计算生物学 粪便 蛋白质组学 肠道菌群 肠道微生物群 微生物学 基因组 细胞生物学 生物 微泡 生物化学 基因 生物信息学 遗传学 小RNA
作者
Surbhi Mishra,Mysore Vishakantegowda Tejesvi,Jenni Hekkala,Jenni Turunen,Niyati Kandikanti Fatima Unnisa,Anna Kaisanlahti,Marko Suokas,Sirpa Leppä,Pia Vihinen,Hanne Kuitunen,Kaisa Sunela,Jussi Koivunen,Arja Jukkola,Ilja Kalashnikov,Päivi Auvinen,Okko‐Sakari Kääriäinen,Tuula Peñate-Medina,Oula Peñate Medina,Juha Saarnio,Sanna Meriläinen
出处
期刊:Journal of Advanced Research [Elsevier BV]
被引量:7
标识
DOI:10.1016/j.jare.2024.03.003
摘要

Gut microbiome–derived nanoparticles, known as bacterial extracellular vesicles (bEVs), have garnered interest as promising tools for studying the link between the gut microbiome and human health. The diverse composition of bEVs, including their proteins, mRNAs, metabolites, and lipids, makes them useful for investigating diseases such as cancer. However, conventional approaches for studying gut microbiome composition alone may not be accurate in deciphering host–gut microbiome communication. In clinical microbiome research, there is a gap in the knowledge on the role of bEVs in solid tumor patients. Analyzing the functionality of bEVs using (meta)genomics and proteomics could highlight the unique aspects of host–gut microbiome interactions in solid tumor patients. Therefore, we performed a comparative analysis of the proteome and microbiota composition of gut microbiome-derived bEVs isolated from patients with solid tumors and healthy controls. After isolating bEVs from the feces of solid tumor patients and healthy controls, we performed spectrometry analysis of their proteomes and next-generation sequencing (NGS) of the 16S gene. We also investigated the gut microbiomes of feces from patients and controls using 16S sequencing and machine learning to classify the samples into patients and controls based on their bEVs and fecal microbiomes. Solid tumor patients showed decreased microbiota richness and diversity in both the bEVs and feces. However, the bEV proteomes were more diverse in patients than in the controls and were enriched with proteins associated with the metabolism of amino acids and carbohydrates, nucleotide binding, and oxidoreductase activity. Metadata classification of samples was more accurate using fecal bEVs (100%) compared with fecal samples (93%). Our findings suggest that bEVs are unique functional entities. There is a need to explore bEVs together with conventional gut microbiome analysis in functional cancer research to decipher the potential of bEVs as cancer diagnostic or therapeutic biomarkers.
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