BackgroundThe changes that occur in the microbiome of aging individuals are unclear, especially in light of the imperfect correlation of frailty with age. Studies in older human subjects have reported subtle effects, but these results may be confounded by other variables that often change with age such as diet and place of residence. To test these associations in a more controlled model system, we examined the relationship between age, frailty, and the gut microbiome of female C57BL/6 J mice.ResultsThe frailty index, which is based on the evaluation of 31 clinical signs of deterioration in mice, showed a near-perfect correlation with age. We observed a statistically significant relationship between age and the taxonomic composition of the corresponding microbiome. Consistent with previous human studies, the Rikenellaceae family, which includes the Alistipes genus, was the most significantly overrepresented taxon within middle-aged and older mice.The functional profile of the mouse gut microbiome also varied with host age and frailty. Bacterial-encoded functions that were underrepresented in older mice included cobalamin (B12) and biotin (B7) biosynthesis, and bacterial SOS genes associated with DNA repair. Conversely, creatine degradation, associated with muscle wasting, was overrepresented within the gut microbiomes of the older mice, as were bacterial-encoded β-glucuronidases, which can influence drug-induced epithelial cell toxicity. Older mice also showed an overabundance of monosaccharide utilization genes relative to di-, oligo-, and polysaccharide utilization genes, which may have a substantial impact on gut homeostasis.ConclusionWe have identified taxonomic and functional patterns that correlate with age and frailty in the mouse microbiome. Differences in functions related to host nutrition and drug pharmacology vary in an age-dependent manner, suggesting that the availability and timing of essential functions may differ significantly with age and frailty. Future work with larger cohorts of mice will aim to separate the effects of age and frailty, and other factors.Electronic supplementary materialThe online version of this article (doi:10.1186/s40168-014-0050-9) contains supplementary material, which is available to authorized users.

Identifying differentially abundant microbes is a common goal of microbiome studies. Multiple methods are used interchangeably for this purpose in the literature. Yet, there are few large-scale studies systematically exploring the appropriateness of using these tools interchangeably, and the scale and significance of the differences between them. Here, we compare the performance of 14 differential abundance testing methods on 38 16S rRNA gene datasets with two sample groups. We test for differences in amplicon sequence variants and operational taxonomic units (ASVs) between these groups. Our findings confirm that these tools identified drastically different numbers and sets of significant ASVs, and that results depend on data pre-processing. For many tools the number of features identified correlate with aspects of the data, such as sample size, sequencing depth, and effect size of community differences. ALDEx2 and ANCOM-II produce the most consistent results across studies and agree best with the intersect of results from different approaches. Nevertheless, we recommend that researchers should use a consensus approach based on multiple differential abundance methods to help ensure robust biological interpretations.

BackgroundNon-typhoidal Salmonella enterica serovars, associated with different foods including poultry products, are important causes of bacterial gastroenteritis worldwide. The colonization of the chicken gut by S. enterica could result in the contamination of the environment and food chain. The aim of this study was to compare the genomes of 25 S. enterica serovars isolated from broiler chicken farms to assess their intra- and inter-genetic variability, with a focus on virulence and antibiotic resistance characteristics.Methodology/Principal FindingThe genomes of 25 S. enterica isolates covering five serovars (ten Typhimurium including three monophasic 4,[5],12:i:, four Enteritidis, three Hadar, four Heidelberg and four Kentucky) were sequenced. Most serovars were clustered in strongly supported phylogenetic clades, except for isolates of serovar Enteritidis that were scattered throughout the tree. Plasmids of varying sizes were detected in several isolates independently of serovars. Genes associated with the IncF plasmid and the IncI1 plasmid were identified in twelve and four isolates, respectively, while genes associated with the IncQ plasmid were found in one isolate. The presence of numerous genes associated with Salmonella pathogenicity islands (SPIs) was also confirmed. Components of the type III and IV secretion systems (T3SS and T4SS) varied in different isolates, which could explain in part, differences of their pathogenicity in humans and/or persistence in broilers. Conserved clusters of genes in the T3SS were detected that could be used in designing effective strategies (diagnostic, vaccination or treatments) to combat Salmonella. Antibiotic resistance genes (CMY, aadA, ampC, florR, sul1, sulI, tetAB, and srtA) and class I integrons were detected in resistant isolates while all isolates carried multidrug efflux pump systems regardless of their antibiotic susceptibility profile.Conclusions/SignificanceThis study showed that the predominant Salmonella serovars in broiler chickens harbor genes encoding adhesins, flagellar proteins, T3SS, iron acquisition systems, and antibiotic and metal resistance genes that may explain their pathogenicity, colonization ability and persistence in chicken. The existence of mobile genetic elements indicates that isolates from a given serovar could acquire and transfer genetic material. Conserved genes in the T3SS and T4SS that we have identified are promising candidates for identification of diagnostic, antimicrobial or vaccine targets for the control of Salmonella in broiler chickens.

Lactobacilli isolated from various sources were identified on the basis of 16S -23S rRNA gene intergenic region amplification and subsequent sequencing of the smaller intergenic region. An in vitro analysis of probiotic properties including binding, ability to tolerate different concentrations of bile, survival in acidic buffer and antimicrobial activity of four different isolates and two standard strains (Lactobacillus plantarum American Type Culture Collection (ATCC) 8014 and L. rhamnosus GG (LGG)) was carried out. The ability of each isolate to stimulate Caco-2 cells, human peripheral blood mononuclear cells (PBMC) and THP-1 cells resulting in immunomodulation of these cells was analysed. Isolates L. rhamnosus CS25 and L. delbrueckii M and standard strain ATCC 8014 showed broad antimicrobial activity, and isolates CS25 (percentage of survival 6·9 % at pH 2·5, 5·1 % at pH 2·0) and L. plantarum CS23 (5·7 % at pH 2·5, 4·9 % at pH 2·0) have shown good tolerance to acidic pH. Isolate CS23 showed a good survival (14 %) after 2 h incubation in de Man, Rogosa and Sharpe (MRS) medium containing 3 % bile salts. Isolates CS23, CS25 and L. fermentum ASt1 could stimulate Caco-2 cells, human PBMC and THP-1 cells for a strong and varied immunomodulatory response in these cells. Though LGG showed poor antimicrobial activity as well as bile and acid tolerance, it was found to be the best binding strain tested. Child faecal isolate CS23 from the present study showed high binding ability (seventeen bacteria/Caco-2), high tolerance to acidic pH and bile salts and significant immunomodulation; therefore it is a good potential probiotic candidate.

Identifying differentially abundant microbes is a common goal of microbiome studies. Multiple methods have been applied for this purpose, which are largely used interchangeably in the literature. Although it has been observed that these tools can produce different results, there have been very few large-scale comparisons to describe the scale and significance of these differences. In addition, it is challenging for microbiome researchers to know which differential abundance tools are appropriate for their study and how these tools compare to one another. Here, we have investigated these questions by analyzing 38 16S rRNA gene datasets with two sample groups for differential abundance testing. We tested for differences in amplicon sequence variants and operational taxonomic units (referred to as ASVs for simplicity) between these groups with 14 commonly used differential abundance tools. Our findings confirmed that these tools identified drastically different numbers and sets of significant ASVs, however, for many tools the number of features identified correlated with aspects of the tested study data, such as sample size, sequencing depth, and effect size of community differences. We also found that the ASVs identified by each method were dependent on whether the abundance tables were prevalence-filtered before testing. ALDEx2 and ANCOM produced the most consistent results across studies and agreed best with the intersect of results from different approaches. In contrast, several methods, such as LEfSe, limma voom, and edgeR, produced inconsistent results and in some cases were unable to control the false discovery rate. In addition to these observations, we were unable to find supporting evidence for a recent recommendation that limma voom, corncob, and DESeq2 are more reliable overall compared with other methods. Although ALDEx2 and ANCOM are two promising conservative methods, we argue that those researchers requiring more sensitive methods should use a consensus approach based on multiple differential abundance methods to help ensure robust biological interpretations.