Examining changes in bacterial abundance in complex communities using next-generation sequencing is enhanced with quantitative PCR.

Changes in the composition of microbial communities are often examined using high-throughput sequencing (HTS). Here we analyzed bar-coded Illumina sequencing data from a previous work describing the microbial community found in the sputum of a cystic fibrosis patient by itself or in combination with qPCR to measure the absolute abundance of Pseudomonas aeruginosa and Burkholderia multivorans. Through this comparison we were able to determine the computational analysis accuracy of sequencing data to measure the relative abundance of specific taxa. While no correlation was found between relative abundance and absolute abundance of P. aeruginosa or B. multivorans, we did find conclusions derived from HTS data alone differed from those derived from a combination of HTS and qPCR. Our results highlight the importance of using qPCR with HTS when characterizing organisms in microbial communities having a dominant taxon.

Identification of epithelial ovarian tumor-specific aptamers.

Ovarian cancer is often diagnosed in late stages with few treatment options and poor long-term prognosis. New clinical tools for early detection of ovarian malignancies will significantly help reduce mortality and improve current long-term survival rates. The objective of this work was to identify ovarian tumor-specific single-stranded DNA aptamers that bind to malignant ovarian tumor cells and internalize with high affinity and specificity. Aptamers can identify unique tumor biomarkers, can aid in early detection and diagnosis of neoplastic disorders, and can be functionalized by conjugation to small molecules. To identify aptamers from random single-stranded DNA pools (60 bases long), we used whole Cell-SELEX (systematic evolution of ligands by exponential enrichment) to enrich and isolate tumor-specific aptamers that bind to tumor-specific receptors in their native state on the cell surface. Next-Generation sequencing identified seven novel aptamers and detailed analyses of three are described. Aptamers bound to, and were internalized by, target Caov-3 cell populations, but not nontarget nonmalignant ovarian epithelial HOSE 6-3 cells or multiple other epithelial tumor cell lines. Furthermore, aptamers showed unique binding affinities with apparent dissociation constants (Kd) measuring in the submicromolar range supporting their physiological relevance and potential use in clinical applications.

Analysis of changes in diversity and abundance of the microbial community in a cystic fibrosis patient over a multiyear period.

The evolution of pulmonary disease in cystic fibrosis (CF) usually begins when bacteria get trapped in mucus in the lungs and become established as a chronic infection. While most CF patients experience periods of stability, pulmonary exacerbations (PEs) can occur multiple times per year and result in permanent damage to the lungs. Little is known of the shift from a period of stability to a PE, but this shift is likely to be attributed to changes in the bacterial community. Here, we identified changes in the lung microbiota to determine if they reflect patient health, indicate the onset of exacerbations, or are related to antibiotic treatment. In contrast to most bacterial studies on CF, we collected weekly samples from an adult CF patient over a period of 3 years and performed quantitative PCR (qPCR) and Illumina sequencing on those samples. While many DNA-based studies have shown the CF microbiota to be relatively stable, we observed an increase in the total bacterial abundance over time (P < 0.001), while the number of different taxa (bacterial richness) and the number of different taxa and their abundances (diversity) significantly decreased over time (P < 0.03), which was likely due to repeated antibiotic exposure. Using genus-specific primers with qPCR, we observed an increase in the abundance of Burkholderia multivorans, a CF-associated pathogen, prior to the occurrence of a PE (P = 0.006). Combining these DNA-based techniques with frequent sampling identified a potential initiator for exacerbations and described a response of the CF microbiota to time and antibiotic treatment not observed in previous CF microbiota studies.

Comparison of culture and molecular techniques for microbial community characterization in infected necrotizing pancreatitis.

BACKGROUND: Infected necrotizing pancreatitis is associated with significant morbidity and mortality. Peripancreatic fluid cultures may fail to identify all the infecting organisms. The aim of this study was to compare the bacterial biome of peripancreatic fluid from infected necrotizing pancreatitis patients using 16S ribosomal RNA (rRNA) DNA deep sequencing and quantitative polymerase chain reaction (qPCR) targeting the 16S rRNA gene versus standard laboratory culture. MATERIALS AND METHODS: Peripancreatic fluid was collected during operative or radiologic intervention and samples sent for culture. In parallel, microbial DNA was extracted, qPCR targeting the 16S rRNA gene and 16S rRNA PCR amplification followed by Illumina deep sequencing were performed. RESULTS: Using culture techniques, the bacterial strains most frequently identified were gram-negative rods (Escherichia coli, Klebsiella pneumoniae) and Enterococcus. Samples in which culture results were negative had copy numbers of the 16S rRNA gene close to background in qPCR analysis. For samples with high bacterial load, sequencing results were in some cases in good agreement with culture data, whereas in others there were disagreements, likely due to differences in taxonomic classification, cultivability, and differing susceptibility to background contamination. Sequencing results appeared generally unreliable in cases of negative culture where little microbial DNA was input into qPCR sequencing reactions. CONCLUSIONS: Both sequencing and culture data display their own sources of bias and potential error. Consideration of data from multiple techniques will yield a more accurate view of bacterial infections than can be achieved by any single technique.

Dietary fructose induces endotoxemia and hepatic injury in calorically controlled primates.

BACKGROUND: Controversy exists regarding the causative role of dietary fructose in obesity and fatty liver diseases. Clinical trials have indicated that negative health consequences may occur only when fructose is consumed within excess calories. Animal studies have suggested that fructose impairs intestinal integrity and leads to hepatic steatosis (HS). OBJECTIVES: We assessed nonhuman primates after chronic ad libitum and short-term calorically controlled consumption of a high-fructose (HFr), low-fat diet (24% of calories). Microbial translocation (MT), microbiome, and metabolic health indexes were evaluated. DESIGN: Seventeen monkeys fed 0.3­7 y of an HFr ad libitum diet were compared with 10 monkeys fed a low-fructose, low-fat diet (control). Ten middle-aged, weight-stable, fructose-naive monkeys were stratified into HFr and control groups fed for 6 wk at caloric amounts required to maintain weight stability. Metabolic endpoints, feces, liver, small and large intestinal biopsies, and portal blood samples were collected. RESULTS: Monkeys allowed ad libitum HFr developed HS in contrast to the control diet, and the extent of ectopic fat was related to the duration of feeding. Diabetes incidence also increased. Monkeys that consumed calorically controlled HFr showed significant increases in biomarkers of liver damage, endotoxemia, and MT indexes and a trend for greater hepatitis that was related to MT; however, HS did not develop. CONCLUSIONS: Even in the absence of weight gain, fructose rapidly causes liver damage that we suggest is secondary to endotoxemia and MT. HS relates to the duration of fructose consumption and total calories consumed. These data support fructose inducing both MT and ectopic fat deposition in primates.

Association between composition of the human gastrointestinal microbiome and development of fatty liver with choline deficiency.

BACKGROUND & AIMS: Nonalcoholic fatty liver disease affects up to 30% of the US population, but the mechanisms underlying this condition are incompletely understood. We investigated how diet standardization and choline deficiency influence the composition of the microbial community in the human gastrointestinal tract and the development of fatty liver under conditions of choline deficiency. METHODS: We performed a 2-month inpatient study of 15 female subjects who were placed on well-controlled diets in which choline levels were manipulated. We used 454-FLX pyrosequencing of 16S ribosomal RNA bacterial genes to characterize microbiota in stool samples collected over the course of the study. RESULTS: The compositions of the gastrointestinal microbial communities changed with choline levels of diets; each individual's microbiome remained distinct for the duration of the experiment, even though all subjects were fed identical diets. Variations between subjects in levels of Gammaproteobacteria and Erysipelotrichi were directly associated with changes in liver fat in each subject during choline depletion. Levels of these bacteria, change in amount of liver fat, and a single nucleotide polymorphism that affects choline were combined into a model that accurately predicted the degree to which subjects developed fatty liver on a choline-deficient diet. CONCLUSIONS: Host factors and gastrointestinal bacteria each respond to dietary choline deficiency, although the gut microbiota remains distinct in each individual. We identified bacterial biomarkers of fatty liver that result from choline deficiency, adding to the accumulating evidence that gastrointestinal microbes have a role in metabolic disorders.

Effects of experimental choices and analysis noise on surveys of the "rare biosphere".

When planning a survey of 16S rRNA genes from a complex environment, investigators face many choices including which primers to use and how to taxonomically classify sequences. In this study, we explored how these choices affected a survey of microbial diversity in a sample taken from the aerobic basin of the activated sludge of a North Carolina wastewater treatment plant. We performed pyrosequencing reactions on PCR products generated from primers targeting the V1-V2, V6, and V6-V7 variable regions of the 16S rRNA gene. We compared these sequences to 16S rRNA gene sequences found in a whole-genome shotgun pyrosequencing run performed on the same sample. We found that sequences generated from primers targeting the V1-V2 variable region had the best match to the whole-genome shotgun reaction across a range of taxonomic classifications from phylum to family. Pronounced differences between primer sets, however, occurred in the "rare biosphere" involving taxa that we observed in fewer than 11 sequences. We also examined the results of analysis strategies comparing a classification scheme using a nearest-neighbor approach to directly classifying sequences with a naïve Bayesian algorithm. Again, we observed pronounced differences between these analysis schemes in infrequently observed taxa. We conclude that if a study is meant to probe the rare biosphere, both the experimental conditions and analysis choices will have a profound impact on the observed results.

Molecular diversity of a North Carolina wastewater treatment plant as revealed by pyrosequencing.

We report the results of pyrosequencing of DNA collected from the activated sludge basin of a wastewater treatment plant in Charlotte, NC. Using the 454-FLX technology, we generated 378,601 sequences with an average read length of 250.4 bp. Running the 454 assembly algorithm over our sequences yielded very poor assembly, with only 0.3% of our sequences participating in assembly of significant contigs. Of the 117 contigs greater than 500 bp long that were assembled, the most common annotations were to transposases and hypothetical proteins. Comparing our sequences to known microbial genomes showed nonspecific recruitment, indicating that previously described taxa are only distantly related to the most abundant microbes in this treatment plant. A comparison of proteins generated by translating our sequence set to translations of other sequenced microbiomes shows a distinct metabolic profile for activated sludge with high counts for genes involved in metabolism of aromatic compounds and low counts for genes involved in photosynthesis. Taken together, these data document the substantial levels of microbial diversity within activated sludge and further establish the great utility of pyrosequencing for investigating diversity in complex ecosystems.