Influence of Fecal Sample Storage on Bacterial Community Diversity

Previous studies have identified a correlation, either positive or negative, between specific stool bacteria strains and certain autoimmune diseases. These conflicting data may relate to sample collection. The aim of this work was to evaluate the influence of the collection parameters of time and temperature on bacterial community composition. Samples were taken from healthy children and immediately divided in 5 sub-samples. One sample was frozen immediately at -80°C, while the other aliquots were frozen 12, 24, 48, and 72h later DNA extracted from each sample was used to amplify the 16S rRNA with barcoded primers. The amplified products were pooled and partial 16S rRNA sequences were obtained by pyrosequencing. Person-to-person variability in community diversity was high. A list of those taxa that comprise at least 1% of the community was made for each individual. None of these were present in high numbers in all individuals. The Bacteroides were present in the highest abundance in three of four subjects. A total of 23,701 16S rRNA sequences were obtained with an average of 1,185 reads per sample with an average length of 200 bases. Although pyrosequencing of amplified 16S rRNA identified changes in community composition over time (~10%), little diversity change was observed at 12 hours (3.06%) with gradual changes occurring after 24 (8.61%), 48 (9.72%), and 72 h (10.14%), post collection

Complete Genome Sequence of the N2-Fixing Broad Host Range Endophyte Klebsiella pneumoniae 342 and Virulence Predictions Verified in Mice

We report here the sequencing and analysis of the genome of the nitrogen-fixing endophyte, Klebsiella pneumoniae 342. Although K. pneumoniae 342 is a member of the enteric bacteria, it serves as a model for studies of endophytic, plant-bacterial associations due to its efficient colonization of plant tissues (including maize and wheat, two of the most important crops in the world), while maintaining a mutualistic relationship that encompasses supplying organic nitrogen to the host plant. Genomic analysis examined K. pneumoniae 342 for the presence of previously identified genes from other bacteria involved in colonization of, or growth in, plants. From this set, approximately one-third were identified in K. pneumoniae 342, suggesting additional factors most likely contribute to its endophytic lifestyle. Comparative genome analyses were used to provide new insights into this question. Results included the identification of metabolic pathways and other features devoted to processing plant-derived cellulosic and aromatic compounds, and a robust complement of transport genes (15.4%), one of the highest percentages in bacterial genomes sequenced. Although virulence and antibiotic resistance genes were predicted, experiments conducted using mouse models showed pathogenicity to be attenuated in this strain. Comparative genomic analyses with the presumed human pathogen K. pneumoniae MGH78578 revealed that MGH78578 apparently cannot fix nitrogen, and the distribution of genes essential to surface attachment, secretion, transport, and regulation and signaling varied between each genome, which may indicate critical divergences between the strains that influence their preferred host ranges and lifestyles (endophytic plant associations for K. pneumoniae 342 and presumably human pathogenesis for MGH78578). Little genome information is available concerning endophytic bacteria. The K. pneumoniae 342 genome will drive new research into this less-understood, but important category of bacterial-plant host relationships, which could ultimately enhance growth and nutrition of important agricultural crops and development of plant-derived products and biofuels

Genetic risk for autoimmunity is associated with distinct changes in the human gut microbiome

Susceptibility to many human autoimmune diseases is under strong genetic control by class II human leukocyte antigen (HLA) allele combinations. These genes remain by far the greatest risk factors in the development of type 1 diabetes and celiac disease. Despite this, little is known about HLA influences on the composition of the human gut microbiome, a potential source of environmental influence on disease. Here, using a general population cohort from the All Babies in Southeast Sweden study, we report that genetic risk for developing type 1 diabetes autoimmunity is associated with distinct changes in the gut microbiome. Both the core microbiome and beta diversity differ with HLA risk group and genotype. In addition, protective HLA haplotypes are associated with bacterial genera Intestinibacter and Romboutsia. Thus, general population cohorts are valuable in identifying potential environmental triggers or protective factors for autoimmune diseases that may otherwise be masked by strong genetic control.Funding Agencies|Barndiabetesfonden (Swedish Child Diabetes Foundation); Swedish Council for Working Life and Social Research [FAS2004-1775]; Swedish Research Council [K2005-72 x - 11242-11A, K2008-69 x - 20826-01-4]; Medical Research Council of Southeast Sweden (FORSS); JDRF Wallenberg Foundation [K 98-99D-12813-01A]; ALF grant from Region Ostergotland, Sweden; ALF grant from Linkoping University, Sweden; LfoU grant from Region Ostergotland, Sweden; LfoU grant from Linkoping University, Sweden; Ostgota Brandstodsbolag</p

Influence of own mother's milk and different proportions of formula on intestinal microbiota of very preterm newborns.

ObjectiveTo determine the differences in preterm infants' stool microbiota considering the use of exclusive own mother's milk and formula in different proportions in the first 28 days of life.MethodsThe study included newborns with GA ≤ 32 weeks divided in 5 group according the feeding regimen: 7 exclusive own mother's milk, 8 exclusive preterm formula, 16 mixed feeding with >70% own mother's milk, 16 mixed feeding with >70% preterm formula, and 15 mixed 50% own mother's milk and preterm formula. Exclusion criteria: congenital infections, congenital malformations and newborns of drug addicted mothers. Stools were collected weekly during the first 28 days. Microbial DNA extraction, 16S rRNA amplification and sequencing were performed.ResultsAll groups were similar in perinatal and neonatal data. There were significant differences in microbial community among treatments. Approximately 37% of the variation in distance between microbial communities was explained by use of exclusive own mother´s milk only compared to other diets. The diet composed by exclusive own mother´s milk allowed for greater microbial richness (average of 85 OTUs) while diets based on preferably formula, exclusive formula, preferably maternal milk, and mixed of formula and maternal milk presented an average of 9, 29, 23, and 25 OTUs respectively. The mean proportion of the genus Escherichia and Clostridium was always greater in those containing formula than in the those with maternal milk only.ConclusionsFecal microbiota in the neonatal period of preterm infants fed with exclusive own mother's milk presented increased richness and differences in microbial composition from those fed with different proportions of formula

Low Microbial Diversity and Abnormal Microbial Succession Is Associated with Necrotizing Enterocolitis in Preterm Infants

Despite increased efforts, the diverse etiologies of Necrotizing Enterocolitis (NEC) have remained largely elusive. Clinical predictors of NEC remain ill-defined and currently lack sufficient specificity. The development of a thorough understanding of initial gut microbiota colonization pattern in preterm infants might help to improve early detection or prediction of NEC and its associated morbidities. Here we compared the fecal microbiota successions, microbial diversity, abundance and structure of newborns that developed NEC with preterm controls. A 16S rRNA based microbiota analysis was conducted in a total of 132 fecal samples that included the first stool (meconium) up until the 5th week of life or NEC diagnosis from 40 preterm babies (29 controls and 11 NEC cases). A single phylotype matching closest to the Enterobacteriaceae family correlated strongly with NEC. In DNA from the sample with the greatest abundance of this phylotype additional shotgun metagenomic sequencing revealed Citrobacter koseri and Klebsiella pneumoniae as the dominating taxa. These two taxa might represent suitable microbial biomarker targets for early diagnosis of NEC. In NEC cases, we further detected lower microbial diversity and an abnormal succession of the microbial community before NEC diagnosis. Finally, we also detected a disruption in anaerobic microorganisms in the co-occurrence network of meconium samples from NEC cases. Our data suggest that a strong dominance of Citrobacter koseri and/or Klebsiella pneumoniae, low diversity, low abundance of Lactobacillus, as well as an altered microbial-network structure during the first days of life, correlate with NEC risk in preterm infants. Confirmation of these findings in other hospitals might facilitate the development of a microbiota based screening approach for early detection of NEC

PANGEA: pipeline for analysis of next generation amplicons

High-throughput DNA sequencing can identify organisms and describe population structures in many environmental and clinical samples. Current technologies generate millions of reads in a single run, requiring extensive computational strategies to organize, analyze and interpret those sequences. A series of bioinformatics tools for high-throughput sequencing analysis, including preprocessing, clustering, database matching and classification, have been compiled into a pipeline called PANGEA. The PANGEA pipeline was written in Perl and can be run on Mac OSX, Windows or Linux. With PANGEA, sequences obtained directly from the sequencer can be processed quickly to provide the files needed for sequence identification by BLAST and for comparison of microbial communities. Two different sets of bacterial 16S rRNA sequences were used to show the efficiency of this workflow. The first set of 16S rRNA sequences is derived from various soils from Hawaii Volcanoes National Park. The second set is derived from stool samples collected from diabetes-resistant and diabetes-prone rats. The workflow described here allows the investigator to quickly assess libraries of sequences on personal computers with customized databases. PANGEA is provided for users as individual scripts for each step in the process or as a single script where all processes, except the χ(2) step, are joined into one program called the ‘backbone’