Molecular Characterization of Microbiota in Cerebrospinal Fluid From Patients With CSF Shunt Infections Using Whole Genome Amplification Followed by Shotgun Sequencing

Understanding the etiology of cerebrospinal fluid (CSF) shunt infections and reinfections requires detailed characterization of associated microorganisms. Traditionally, identification of bacteria present in the CSF has relied on culture methods, but recent studies have used high throughput sequencing of 16S rRNA genes. Here we evaluated the method of shotgun DNA sequencing for its potential to provide additional genomic information. CSF samples were collected from 3 patients near the beginning and end of each of 2 infection episodes. Extracted total DNA was sequenced by: (1) whole genome amplification followed by shotgun sequencing (WGA) and (2) high-throughput sequencing of the 16S rRNA V4 region (16S). Taxonomic assignments of sequences from WGA and 16S were compared with one another and with conventional microbiological cultures. While classification of bacteria was consistent among the 3 approaches, WGA provided additional insights into sample microbiological composition, such as showing relative abundances of microbial versus human DNA, identifying samples of questionable quality, and detecting significant viral load in some samples. One sample yielded sufficient non-human reads to allow assembly of a high-quality Staphylococcus epidermidis genome, denoted CLIMB1, which we characterized in terms of its MLST profile, gene complement (including putative antimicrobial resistance genes), and similarity to other annotated S. epidermidis genomes. Our results demonstrate that WGA directly applied to CSF is a valuable tool for the identification and genomic characterization of dominant microorganisms in CSF shunt infections, which can facilitate molecular approaches for the development of better diagnostic and treatment methods.

Gut Microbiota and Endothelial Dysfunction Markers in Obese Mexican Children and Adolescents

Obesity is a metabolic disease characterized by low-grade inflammation and accompanied by dyslipidemia and up-regulation of other bioactive molecules, creating a predisposition to endothelial dysfunction and metabolic syndrome. We studied the association between gut microbiota diversity and endothelial dysfunction (EDF) markers in obese Mexican children and adolescents. We examined clinical data including metabolic factors and EDF markers in blood samples. Gut bacterial diversity was characterized by high-throughput sequencing of V3-16S rDNA libraries. Triglycerides, insulin, homeostasis model assessment-insulin resistant (HOMA-IR), leptin, C-reactive protein (CRP), and EDF marker intercellular adhesion molecule 1 (ICAM-1) were significantly higher in obese children and adolescents. Multivariate analysis showed statistically significant positive associations between vascular cell adhesion molecule 1 (VCAM-1) and Veillonellaceae, and between ICAM-1 and Ruminococcus in obese children. In obese adolescents, there was a statistically significant positive association between total cholesterol and Ruminococcus, and between ICAM-1 and Bacteroides. LEfSe analysis showed that the genus Lactobacillus and family Coriobacteriaceae were enriched in children, and genera Collinsella and Prevotella were enriched in obese adolescents. Obese children and adolescents had higher levels of insulin resistance and metabolic syndrome. These results suggest that obese Mexican children and adolescents had increased levels of CRP and a reduction of adiponectin, which causes higher expression of EDF markers, affecting endothelial function and associating with changes in the gut microbiota.

Emerging technologies in paediatric leukaemia

Genetic changes, in particular chromosomal aberrations, are a hallmark of acute lymphoblastic lymphoma (ALL) and accurate detection of them is important in ensuring assignment to the appropriate drug protocol. Our ability to detect these genetic changes has been somewhat limited in the past due to the necessity to analyse mitotically active cells by conventional G-banded metaphase analysis and by mutational analysis of individual genes. Advances in technology include high resolution, microarray-based techniques that permit examination of the whole genome. Here we will review the current available methodology and discuss how the technology is being integrated into the diagnostic setting.