Project description:<p class='ql-align-justify'>The gut microbiome has been associated with pathological neurophysiological evolvement in extremely premature infants suffering from brain injury. The exact underlying mechanism and its associated metabolic signatures in infants are not fully understood. To decipher metabolite profiles linked to neonatal brain injury, we investigated the longitudinal fecal and plasma metabolome of 51 extremely premature infants using LC-HRMS-based untargeted metabolomics. This was expanded by an investigation of bile acids and amidated bile acid conjugates in feces and plasma by LC-MS/MS-based targeted metabolomics. The resulting data was integrated with 16S rRNA gene amplicon gut microbiome profiles as well as patient cytokine, growth factor and T-cell profiles. We identified an early onset of differentiation in neuroactive metabolites and bile acids between infants with and without brain injury. We detected several bacterially-derived bile acid amino acid conjugates and secondary bile acids in the plasma already 3 days after delivery, indicating the early establishment of a metabolically active gut microbiome. These results give new insights into the early life metabolome of extremely premature infants.</p>
Project description:This study presents a validated, open-source QIIME2- and R-based pipeline for 16S rRNA gene profiling using multi-amplicon sequencing. It aims to overcome the limitations of commercial, closed-source tools by offering a standardized and reproducible workflow. The pipeline was benchmarked against proprietary software using five mock communities and 12 child–caregiver fecal sample pairs, showing nearly identical microbial profiles, greater sequencing depth, and improved taxonomic resolution. High reproducibility (R = 0.99, p < 0.0001) was achieved across all datasets. Application to pediatric cancer samples revealed distinct Bifidobacterium variants in children whose microbiota closely matched their caregivers’. This highlights the pipeline’s utility in studying microbial relationships. Overall, the pipeline supports transparent, adaptable, and accurate microbiome analysis, advancing research in both clinical and experimental settings while promoting open-source solutions for reproducible science.
2025-07-14 | GSE300047 | GEO
Project description:Source-Tracking Klebsiella Outbreaks in Premature Infants using a Novel Amplicon Fingerprinting Method
Project description:Necrotizing enterocolitis (NEC) is an acute and life-threatening gastrointestinal disorder afflicting preterm infants, which is currently unpreventable. Fecal microbiota transplantation (FMT) is a promising preventative therapy, but potential bacterial infection raise concern. Removal of bacteria from donor feces may reduce this risk while maintaining the NEC-preventive effects. We aimed to assess preclinical efficacy and safety of bacteria-free fecal filtrate transfer (FFT). Using fecal material from healthy suckling piglets, we administered FMT rectally, or cognate FFT either rectally or oro-gastrically to formula-fed preterm, cesarean-delivered piglets as a model for preterm infants, We compared gut pathology and related safety parameters with saline controls, and analyzed ileal mucosal transcriptome to gauge the host e response to FMT and FFT treatments relative to control. Results showed that oro-gastric FFT prevented NEC, whereas FMT did not perform better than control. Moreover, FFT but not FMT reduced intestinal permeability, whereas FMT animals had reduced body weight increase and intestinal growth. Global gene expression of host mucosa responded to FMT but not FFT with increased and decreased bacterial and viral defense mechanisms, respectively. In conclusion, as preterm infants are extremely vulnerable to enteric bacterial infections, rational NEC-preventive strategies need incontestable safety profiles. Here we show in a clinically relevant animal model that FFT, as opposed to FMT, efficiently prevents NEC without any recognizable side effects. If translatable to preterm infants, this could lead to a change of practice and in turn a reduction in NEC burden.
Project description:Purpose: This study aims to compare and analyze the differences in bacterial community composition in fecal samples from mice treated with Control(DW), Vancomycin (VAN), Ampicillin (AMP), Neomycin (NEO), Metronidazole (MET), and a combination of all antibiotics (ALL, VANM) using 16S rRNA sequencing. Methods: Each antibiotics treated mice's fecal samples were collected and stored -80'c until analyzation. DNA was extracted using the NucleoSpin DNA Stool Kit (MACHEREY-NAGEL) following the manufacturer’s protocol. Metagenomic sequencing was performed on an Illumina MiSeq platform (Illumina), targeting the V3 and V4 regions of the 16S rRNA gene according to the manufacturer's instructions. PCR products were purified using AMPure XP beads, and sequencing adapters were added using the Nextera XT Index Kit (Illumina). The library was further purified with AMPure XP beads and quantified using automated electrophoresis with the TapeStation System (Agilent). Sequencing was performed using the MiSeq v3 reagent kit (Illumina), following the manufacturer’s protocol. Results: QIIME2 (v2023.02) was used to process and analyze 16S rRNA gene amplicon sequencing data, from sequence preprocessing to taxonomic classification. Paired-end sequences were merged and quality-filtered using Deblur. The resulting amplicon sequence variants (ASVs) were used for downstream analyses. Conclusions: Our study presents a comparative analysis of bacterial community composition in fecal samples from antibiotic-treated mice. We observed that microbiota composition varied distinctly depending on the type of antibiotic administered.
Project description:16S rRNA V3-V4 amplicon sequencing was performed on fecal samples from 12 male C57BL/6J mice across three groups (4 replicates each): Control (distilled water, 3 days), Model (distilled water, 3 days + APAP 300 mg/kg i.p.), and PoH (PO extract 3 g/kg p.o. daily for 3 days + APAP 300 mg/kg i.p.). Sequencing was performed on an Illumina NovaSeq 6000 platform using paired-end 250bp reads.
Project description:Sensitive models of climate change impacts would require a better integration of multi-omics approaches that connect the abundance and activity of microbial populations. Here, we show that climate is a fundamental driver of the protein abundance of microbial populations (metaproteomics), yet not their genomic abundance (16S rRNA gene amplicon sequencing), supporting the hypothesis that metabolic activity may be more closely linked to climate than community composition.