Anthony A. Fodor

Intestinal Inflammation Targets Cancer-Inducing Activity of the Microbiota

Of Microbes and Cancer Inflammation is a well-established driver of tumorigenesis. For example, patients with inflammatory bowel disease have an elevated risk of developing colorectal cancer (CRC). Whether the gut microbiota also contributes to the development of CRC is less well understood. Arthur et al. (p. 120, published online 16 August; see the Perspective by Schwabe and Wang) now show that the microbiota does indeed promote tumorigenesis in an inflammation-driven model of CRC in mice. Although germ-free mice were protected against developing cancer, colonization of mice with Escherichia coli was sufficient to drive tumorigenesis. Microbes resident in the gut can promote colorectal cancer in mice in an inflammation-independent manner. Inflammation alters host physiology to promote cancer, as seen in colitis-associated colorectal cancer (CRC). Here, we identify the intestinal microbiota as a target of inflammation that affects the progression of CRC. High-throughput sequencing revealed that inflammation modifies gut microbial composition in colitis-susceptible interleukin-10–deficient (Il10−/−) mice. Monocolonization with the commensal Escherichia coli NC101 promoted invasive carcinoma in azoxymethane (AOM)–treated Il10−/− mice. Deletion of the polyketide synthase (pks) genotoxic island from E. coli NC101 decreased tumor multiplicity and invasion in AOM/Il10−/− mice, without altering intestinal inflammation. Mucosa-associated pks+ E. coli were found in a significantly high percentage of inflammatory bowel disease and CRC patients. This suggests that in mice, colitis can promote tumorigenesis by altering microbial composition and inducing the expansion of microorganisms with genotoxic capabilities.

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 individuals 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.

A core human microbiome as viewed through 16S rRNA sequence clusters

We explore the microbiota of 18 body sites in over 200 individuals using sequences amplified V1–V3 and the V3–V5 small subunit ribosomal RNA (16S) hypervariable regions as part of the NIH Common Fund Human Microbiome Project. The body sites with the greatest number of core OTUs, defined as OTUs shared amongst 95% or more of the individuals, were the oral sites (saliva, tongue, cheek, gums, and throat) followed by the nose, stool, and skin, while the vaginal sites had the fewest number of OTUs shared across subjects. We found that commonalities between samples based on taxonomy could sometimes belie variability at the sub-genus OTU level. This was particularly apparent in the mouth where a given genus can be present in many different oral sites, but the sub-genus OTUs show very distinct site selection, and in the vaginal sites, which are consistently dominated by the Lactobacillus genus but have distinctly different sub-genus V1–V3 OTU populations across subjects. Different body sites show approximately a ten-fold difference in estimated microbial richness, with stool samples having the highest estimated richness, followed by the mouth, throat and gums, then by the skin, nasal and vaginal sites. Richness as measured by the V1–V3 primers was consistently higher than richness measured by V3–V5. We also show that when such a large cohort is analyzed at the genus level, most subjects fit the stool “enterotype” profile, but other subjects are intermediate, blurring the distinction between the enterotypes. When analyzed at the finer-scale, OTU level, there was little or no segregation into stool enterotypes, but in the vagina distinct biotypes were apparent. Finally, we note that even OTUs present in nearly every subject, or that dominate in some samples, showed orders of magnitude variation in relative abundance emphasizing the highly variable nature across individuals.

Influence of conservation on calculations of amino acid covariance in multiple sequence alignments

It has long been argued that algorithms that find correlated mutations in multiple sequence alignments can be used to find structurally or functionally important residues in proteins. We examined the properties of four different methods for detecting these correlated mutations. On both simple, artificial alignments and real alignments from the Pfam database, we found a surprising lack of agreement between the four correlated mutation methods. We argue that these differences are caused in part by differing sensitivities to background conservation. Correlated mutation algorithms can be envisioned as “filters” of background conservation with each algorithm searching for correlated mutations that occur at a different background conservation frequency. Proteins 2004.

The Adult Cystic Fibrosis Airway Microbiota Is Stable over Time and Infection Type, and Highly Resilient to Antibiotic Treatment of Exacerbations

Cystic fibrosis (CF) is characterized by defective mucociliary clearance and chronic airway infection by a complex microbiota. Infection, persistent inflammation and periodic episodes of acute pulmonary exacerbation contribute to an irreversible decline in CF lung function. While the factors leading to acute exacerbations are poorly understood, antibiotic treatment can temporarily resolve pulmonary symptoms and partially restore lung function. Previous studies indicated that exacerbations may be associated with changes in microbial densities and the acquisition of new microbial species. Given the complexity of the CF microbiota, we applied massively parallel pyrosequencing to identify changes in airway microbial community structure in 23 adult CF patients during acute pulmonary exacerbation, after antibiotic treatment and during periods of stable disease. Over 350,000 sequences were generated, representing nearly 170 distinct microbial taxa. Approximately 60% of sequences obtained were from the recognized CF pathogens Pseudomonas and Burkholderia, which were detected in largely non-overlapping patient subsets. In contrast, other taxa including Prevotella, Streptococcus, Rothia and Veillonella were abundant in nearly all patient samples. Although antibiotic treatment was associated with a small decrease in species richness, there was minimal change in overall microbial community structure. Furthermore, microbial community composition was highly similar in patients during an exacerbation and when clinically stable, suggesting that exacerbations may represent intrapulmonary spread of infection rather than a change in microbial community composition. Mouthwash samples, obtained from a subset of patients, showed a nearly identical distribution of taxa as expectorated sputum, indicating that aspiration may contribute to colonization of the lower airways. Finally, we observed a strong correlation between low species richness and poor lung function. Taken together, these results indicate that the adult CF lung microbiome is largely stable through periods of exacerbation and antibiotic treatment and that short-term compositional changes in the airway microbiota do not account for CF pulmonary exacerbations.

BK calcium-activated potassium channels regulate circadian behavioral rhythms and pacemaker output

Spontaneous action potentials in the suprachiasmatic nucleus (SCN) are necessary for normal circadian timing of behavior in mammals. The SCN exhibits a daily oscillation in spontaneous firing rate (SFR), but the ionic conductances controlling SFR and the relationship of SFR to subsequent circadian behavioral rhythms are not understood. We show that daily expression of the large conductance Ca2+-activated K+ channel (BK) in the SCN is controlled by the intrinsic circadian clock. BK channel–null mice (Kcnma1−/−) have increased SFRs in SCN neurons selectively at night and weak circadian amplitudes in multiple behaviors timed by the SCN. Kcnma1−/− mice show normal expression of clock genes such as Arntl (Bmal1), indicating a role for BK channels in SCN pacemaker output, rather than in intrinsic time-keeping. Our findings implicate BK channels as important regulators of the SFR and suggest that the SCN pacemaker governs the expression of circadian behavioral rhythms through SFR modulation.

Use of culture and molecular analysis to determine the effect of antibiotic treatment on microbial community diversity and abundance during exacerbation in patients with cystic fibrosis

Background Anaerobic bacteria are increasingly regarded as important in cystic fibrosis (CF) pulmonary infection. The aim of this study was to determine the effect of antibiotic treatment on aerobic and anaerobic microbial community diversity and abundance during exacerbations in patients with CF. Methods Sputum was collected at the start and completion of antibiotic treatment of exacerbations and when clinically stable. Bacteria were quantified and identified following culture, and community composition was also examined using culture-independent methods. Results Pseudomonas aeruginosa or Burkholderia cepacia complex were detected by culture in 24/26 samples at the start of treatment, 22/26 samples at completion of treatment and 11/13 stable samples. Anaerobic bacteria were detected in all start of treatment and stable samples and in 23/26 completion of treatment samples. Molecular analysis showed greater bacterial diversity within sputum samples than was detected by culture; there was reasonably good agreement between the methods for the presence or absence of aerobic bacteria such as P aeruginosa (κ=0.74) and B cepacia complex (κ=0.92), but agreement was poorer for anaerobes. Both methods showed that the composition of the bacterial community varied between patients but remained relatively stable in most individuals despite treatment. Bacterial abundance decreased transiently following treatment, with this effect more evident for aerobes (median decrease in total viable count 2.3×107 cfu/g, p=0.005) than for anaerobes (median decrease in total viable count 3×106 cfu/g, p=0.046). Conclusion Antibiotic treatment targeted against aerobes had a minimal effect on abundance of anaerobes and community composition, with both culture and molecular detection methods required for comprehensive characterisation of the microbial community in the CF lung. Further studies are required to determine the clinical significance of and optimal treatment for these newly identified bacteria.

Molecular Diversity of a North Carolina Wastewater Treatment Plant as Revealed by Pyrosequencing

ABSTRACT 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.

A perturbation-based method for calculating explicit likelihood of evolutionary co-variance in multiple sequence alignments

MOTIVATION The constituent amino acids of a protein work together to define its structure and to facilitate its function. Their interdependence should be apparent in the evolutionary record of each protein family: positions in the sequence of a protein family that are intimately associated in space or in function should co-vary in evolution. A recent approach by Ranganathan and colleagues proposes to look at subsets of a protein family, selected for their sequence at one position, to see how this affects variation at other positions. RESULTS We present a quantitative algorithm for assessing covariation with this approach, based on explicit likelihood calculations. By applying our algorithm to 138 Pfam families with at least one member of known structure, we demonstrate that our method has improved power in finding physically close residues in crystal structures, compared to that of Ranganathan and colleagues. SUPPLEMENTARY INFORMATION www.afodor.net/bioinfosup.html

Microbial genomic analysis reveals the essential role of inflammation in bacteria-induced colorectal cancer

Enterobacteria, especially Escherichia coli, are abundant in patients with inflammatory bowel disease or colorectal cancer (CRC). However, it is unclear whether cancer is promoted by inflammation-induced expansion of E. coli and/or changes in expression of specific microbial genes. Here we use longitudinal (2, 12 and 20 weeks) 16S rRNA sequencing of luminal microbiota from ex-germ free mice to show that inflamed Il10−/− mice maintain a higher abundance of Enterobacteriaceae than healthy wild-type mice. Experiments with mono-colonized Il10−/− mice reveal that host inflammation is necessary for E. coli cancer-promoting activity. RNA-sequence analysis indicates significant changes in E. coli gene catalogue in Il10−/− mice, with changes mostly driven by adaptation to the intestinal environment. Expression of specific genes present in the tumor-promoting E. coli pks island are modulated by inflammation/CRC development. Thus, progression of inflammation in Il10−/− mice supports Enterobacteriaceae and alters a small subset of microbial genes important for tumor development.