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INTRODUCTION: 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. OBJECTIVES: 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. METHODS: 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 used machine learning to classify the samples into patients and controls based on their bEVs and fecal microbiomes. RESULTS: 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%). CONCLUSION: 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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Both exposure to antibiotics at birth and delivery via Caesarean section influence the gut bacteriome's development in infants. Using 16S rRNA and internal transcribed spacer sequencing on the Ion Torrent platform, we employed network analysis to investigate the bacterial and fungal interkingdom relationships in the gut microbiome from birth to age 18 months in a prospective cohort study of 140 infants. The gut microbiome at ages six and 18 months revealed distinctive microbial interactions, including both positive and negative associations between bacterial and fungal genera in the gut ecosystem. Perinatal factors, delivery mode and intrapartum antibiotic exposure affected the associations between bacterial and fungal species. In infants exposed and unexposed to perinatal antibiotics, the gut microbiome formed distinct networks for the bacteriome and mycobiome. The fungi Saccharomyces, Trichosporon, Pezoloma, Cystofilobasidium, Rigidoporus and Fomitopsis were strongly associated with exposure to antibiotics at birth. Hyaloscypha, Trichosporon, Fomitopsis and Vishniacozyma were strongly associated with the control group that was not exposed to antibiotics. Five distinct networks were formed according to delivery mode. The present study confirms that bacteria and fungi clearly interact in the infant gut ecosystem. Furthermore, perinatal factors appear to influence the relationships between bacteria and fungi in the developing gut microbiome.
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BACKGROUND: The composition of the gut fungal microbiome, mycobiome, is likely associated with human health. Yet, the development of gut mycobiome is poorly understood in infants and children. Here we investigate how perinatal events influence the development of gut mycobiome. METHODS: In this prospective cohort study of 140 infants, we used ITS gene sequencing of fecal samples from birth to the age of 18 months. We compared gut mycobiome composition according to delivery mode and exposure to intrapartum antibiotics during vaginal delivery. RESULTS: At birth, gut mycobiome were dominated by the genus Candida, at 6-month stool samples by Malassezia and Cystofilobasidium, and the 18-month stool samples by Trichosporon and unidentified fungi. Perinatal factors altered mycobiome. At 18 months, gut mycobiome of infants born vaginally consisted mostly of Trichosporon (32%) and unidentified fungi (31%), while those born via Cesarean section delivery samples had mycobiome dominated by Saccharomyces (50%). At the age of 18 months, those exposed to intrapartum antibiotics had mycobiome dominated by Trichosporon (66%) not seen in those unexposed to antibiotics. CONCLUSIONS: Delivery mode and exposure to intrapartum antibiotic prophylaxis were markedly associated with gut mycobiome composition from birth to 18 months of age. IMPACT: The composition of the gut mycobiome is likely associated with human health. Yet, the development of gut mycobiome is poorly understood in infants and children. In this prospective cohort study, delivery mode and exposure to intrapartum antibiotic prophylaxis were markedly associated with gut mycobiome composition from birth to 18 months of age. The impact of intrapartum antibiotic prophylaxis on fungal microbiome in vaginally born infants, previously shown to influence gut bacteriome composition, may be explained by the interaction between bacteria and fungi. Gut mycobiome composition likely deserves further investigation in relation to gut microbiome and health in children.