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An automated method of ribosomal intergenic spacer analysis (ARISA) was developed for the rapid estimation of microbial diversity and community composition in freshwater environments. Following isolation of total community DNA, PCR amplification of the 16S-23S intergenic spacer region in the rRNA operon was performed with a fluorescence-labeled forward primer. ARISA-PCR fragments ranging in size from 400 to 1,200 bp were next discriminated and measured by using an automated electrophoresis system. Database information on the 16S-23S intergenic spacer was also examined, to understand the potential biases in diversity estimates provided by ARISA. In the analysis of three natural freshwater bacterial communities, ARISA was rapid and sensitive and provided highly reproducible community-specific profiles at all levels of replication tested. The ARISA profiles of the freshwater communities were quantitatively compared in terms of both their relative diversity and similarity level. The three communities had distinctly different profiles but were similar in their total number of fragments (range, 34 to 41). In addition, the pattern of major amplification products in representative profiles was not significantly altered when the PCR cycle number was reduced from 30 to 15, but the number of minor products (near the limit of detection) was sensitive to changes in cycling parameters. Overall, the results suggest that ARISA is a rapid and effective community analysis technique that can be used in conjunction with more accurate but labor-intensive methods (e.g., 16S rRNA gene cloning and sequencing) when fine-scale spatial and temporal resolution is needed.

Automated rRNA intergenic spacer analysis (ARISA) was used to characterise bacterial (B-ARISA) and fungal (F-ARISA) communities from different soil types. The 16S-23S intergenic spacer region from the bacterial rRNA operon was amplified from total soil community DNA for B-ARISA. Similarly, the two internal transcribed spacers and the 5.8S rRNA gene (ITS1-5.8S-ITS2) from the fungal rRNA operon were amplified from total soil community DNA for F-ARISA. Universal fluorescence-labeled primers were used for the PCRs, and fragments of between 200 and 1,200 bp were resolved on denaturing polyacrylamide gels by use of an automated sequencer with laser detection. Methodological (DNA extraction and PCR amplification) and biological (inter- and intrasite) variations were evaluated by comparing the number and intensity of peaks (bands) between electrophoregrams (profiles) and by multivariate analysis. Our results showed that ARISA is a high-resolution, highly reproducible technique and is a robust method for discriminating between microbial communities. To evaluate the potential biases in community description provided by ARISA, we also examined databases on length distribution of ribosomal intergenic spacers among bacteria (L. Ranjard, E. Brothier, and S. Nazaret, Appl. Environ. Microbiol. 66:5334–5339, 2000) and fungi.

Two primer sets for automated ribosomal intergenic spacer analysis (ARISA) were used to assess the bacterial community composition (BCC) in Lake Mendota, Wisconsin, over 3 years. Correspondence analysis revealed differences in community profiles generated by different primer sets, but overall ecological patterns were conserved in each case. ARISA is a powerful tool for evaluating BCC change through space and time, regardless of the specific primer set used.

In this study we evaluated the short-term effects of copper, cadmium, and mercury, added singly or in combination at different doses, on soil bacterial community structure using the bacterial automated ribosomal intergenic spacer analysis (B-ARISA) fingerprinting technique. Principal-component analysis of B-ARISA profiles allowed us to deduce the following order of impact: (Cu + Cd + Hg) >> Hg ≥ Cd > Cu. These results demonstrated that there was a cumulative effect of metal toxicity. Furthermore, the trend of modifications was consistent with the “hump-backed” relationships between biological diversity and disturbance described by Giller et al. (K. E. Giller, E. Witler, and S. P. McGrath, Soil Biol. Biochem. 30:1389-1414, 1998).

Soil microbial community characterization is increasingly being used to determine the responses of soils to stress and disturbances and to assess ecosystem sustainability. However, there is little experimental evidence to indicate that predictable patterns in microbial community structure or composition occur during secondary succession or ecosystem restoration. This study utilized a chronosequence of developing jarrah (Eucalyptus marginata) forest ecosystems, rehabilitated after bauxite mining (up to 18 years old), to examine changes in soil bacterial and fungal community structures (by automated ribosomal intergenic spacer analysis [ARISA]) and changes in specific soil bacterial phyla by 16S rRNA gene microarray analysis. This study demonstrated that mining in these ecosystems significantly altered soil bacterial and fungal community structures. The hypothesis that the soil microbial community structures would become more similar to those of the surrounding nonmined forest with rehabilitation age was broadly supported by shifts in the bacterial but not the fungal community. Microarray analysis enabled the identification of clear successional trends in the bacterial community at the phylum level and supported the finding of an increase in similarity to nonmined forest soil with rehabilitation age. Changes in soil microbial community structure were significantly related to the size of the microbial biomass as well as numerous edaphic variables (including pH and C, N, and P nutrient concentrations). These findings suggest that soil bacterial community dynamics follow a pattern in developing ecosystems that may be predictable and can be conceptualized as providing an integrated assessment of numerous edaphic variables.

In this study, we examined the effect of various pooling strategies on the characterization of soil microbial community composition and phylotype richness estimates. Automated ribosomal intergenic spacer analysis (ARISA) profiles were determined from soil samples that were (i) unpooled (extracted and amplified individually), (ii) pooled prior to PCR amplification, or (iii) pooled prior to DNA extraction. Regression analyses suggest that the less even the soil microbial community (i.e., low Shannon equitability, EH), the greater was the impact of either pooling strategy on microbial detection (R2 = 0.766). For example, at a tropical rainforest site, which had the most uneven fungal (EH of 0.597) and bacterial communities (EH of 0.822), the unpooled procedure detected an additional 67 fungal and 115 bacterial phylotypes relative to either of the pooled procedures. Phylotype rarity, resulting in missed detection upon pooling, differed between the fungal and bacterial communities. Fungi were typified by locally abundant but spatially rare phylotypes, and the bacteria were typified by locally rare but spatially ubiquitous phylotypes. As a result, pooling differentially influenced plot comparisons, leading to an increase in similarity for the bacterial community and a decrease in the fungal community. In conclusion, although pooling reduces sample numbers and variability, it could mask a significant portion of the detectable microbial community, particularly for fungi due to their higher spatial heterogeneity.

This study used a genetic fingerprinting technique (automated ribosomal intergenic spacer analysis [ARISA]) to characterize microbial communities from a culture-independent perspective and to identify those environmental factors that influence the diversity of bacterial assemblages in Wisconsin lakes. The relationships between bacterial community composition and 11 environmental variables for a suite of 30 lakes from northern and southern Wisconsin were explored by canonical correspondence analysis (CCA). In addition, the study assessed the influences of ARISA fragment detection threshold (sensitivity) and the quantitative, semiquantitative, and binary (presence-absence) use of ARISA data. It was determined that the sensitivity of ARISA was influential only when presence-absence-transformed data were used. The outcomes of analyses depended somewhat on the data transformation applied to ARISA data, but there were some features common to all of the CCA models. These commonalities indicated that differences in bacterial communities were best explained by regional (i.e., northern versus southern Wisconsin lakes) and landscape level (i.e., seepage lakes versus drainage lakes) factors. ARISA profiles from May samples were consistently different from those collected in other months. In addition, communities varied along gradients of pH and water clarity (Secchi depth) both within and among regions. The results demonstrate that environmental, temporal, regional, and landscape level features interact to determine the makeup of bacterial assemblages in northern temperate lakes.

We investigated bacterial diversity in different aquatic environments (including marine and lagoon sediments, coastal seawater, and groundwater), and we compared two fingerprinting techniques (terminal restriction fragment length polymorphism [T-RFLP] and automated ribosomal intergenic spacer analysis [ARISA]) which are currently utilized for estimating richness and community composition. Bacterial diversity ranged from 27 to 99 phylotypes (on average, 56) using the T-RFLP approach and from 62 to 101 genotypes (on average, 81) when the same samples were analyzed using ARISA. The total diversity encountered in all matrices analyzed was 144 phylotypes for T-RFLP and 200 genotypes for ARISA. Although the two techniques provided similar results in the analysis of community structure, bacterial richness and diversity estimates were significantly higher using ARISA. These findings suggest that ARISA is more effective than T-RFLP in detecting the presence of bacterial taxa accounting for <5% of total amplified product. ARISA enabled also distinction among aquatic bacterial isolates of Pseudomonas spp. which were indistinguishable using T-RFLP analysis. Overall, the results of this study show that ARISA is more accurate than T-RFLP analysis on the 16S rRNA gene for estimating the biodiversity of aquatic bacterial assemblages.

Plant and soil types are usually considered as the two main drivers of the rhizosphere microbial communities. The aim of this work was to study the effect of both N availability and plant genotype on the plant associated rhizosphere microbial communities, in relation to the nutritional strategies of the plant-microbe interactions, for six contrasted Medicago truncatula genotypes. The plants were provided with two different nutrient solutions varying in their nitrate concentrations (0 mM and 10 mM). First, the influence of both nitrogen availability and Medicago truncatula genotype on the genetic structure of the soil bacterial and fungal communities was determined by DNA fingerprint using Automated Ribosomal Intergenic Spacer Analysis (ARISA). Secondly, the different nutritional strategies of the plant-microbe interactions were evaluated using an ecophysiological framework. We observed that nitrogen availability affected rhizosphere bacterial communities only in presence of the plant. Furthermore, we showed that the influence of nitrogen availability on rhizosphere bacterial communities was dependent on the different genotypes of Medicago truncatula. Finally, the nutritional strategies of the plant varied greatly in response to a modification of nitrogen availability. A new conceptual framework was thus developed to study plant-microbe interactions. This framework led to the identification of three contrasted structural and functional adaptive responses of plant-microbe interactions to nitrogen availability.

We studied the distribution of fungal endophytes of grapevine (Vitis vinifera L.) plants in a subalpine area of northern Italy, where viticulture is of high economic relevance. We adopted both cultivation-based and cultivation-independent approaches to address how various anthropic and nonanthropic factors shape microbial communities. Grapevine stems were harvested from several locations considering organic and integrated pest management (IPM) and from the cultivars Merlot and Chardonnay. Cultivable fungi were isolated and identified by internal-transcribed-spacer sequence analysis, using a novel colony-PCR method, to amplify DNA from fungal specimens. The composition of fungal communities was assessed using a cultivation-independent approach, automated ribosomal intergenic spacer analysis (ARISA). Multivariate statistical analysis of both culture-dependent and culture-independent data sets was convergent and indicated that fungal endophytic communities in grapevines from organically managed farms were different from those from farms utilizing IPM. Fungal communities in plants of cv. Merlot and cv. Chardonnay overlapped when analyzed using culture-dependent approaches but could be partially resolved using ARISA fingerprinting.

“Candidatus Accumulibacter” and total bacterial community dynamics were studied in two lab-scale enhanced biological phosphorus removal (EBPR) reactors by using a community fingerprint technique, automated ribosomal intergenic spacer analysis (ARISA). We first evaluated the quantitative capability of ARISA compared to quantitative real-time PCR (qPCR). ARISA and qPCR provided comparable relative quantification of the two dominant “Ca. Accumulibacter” clades (IA and IIA) detected in our reactors. The quantification of total “Ca. Accumulibacter” 16S rRNA genes relative to that from the total bacterial community was highly correlated, with ARISA systematically underestimating “Ca. Accumulibacter” abundance, probably due to the different normalization techniques applied. During 6 months of normal (undisturbed) operation, the distribution of the two clades within the total “Ca. Accumulibacter” population was quite stable in one reactor while comparatively dynamic in the other reactor. However, the variance in the clade distribution did not appear to affect reactor performance. Instead, good EBPR activity was positively associated with the abundance of total “Ca. Accumulibacter.” Therefore, we concluded that the different clades in the system provided functional redundancy. We disturbed the reactor operation by adding nitrate together with acetate feeding in the anaerobic phase to reach initial reactor concentrations of 10 mg/liter NO3-N for 35 days. The reactor performance deteriorated with a concomitant decrease in the total “Ca. Accumulibacter” population, suggesting that a population shift was the cause of performance upset after a long exposure to nitrate in the anaerobic phase.

Bacterioplankton community diversity was investigated in the subtropical Brisbane River-Moreton Bay estuary, Australia (27°25′S, 153°5′E). Bacterial communities were studied using automated rRNA intergenic spacer analysis (ARISA), which amplifies 16S-23S ribosomal DNA internally transcribed spacer regions from mixed-community DNA and detects the separated products on a fragment analyzer. Samples were collected from eight sites throughout the estuary and east to the East Australian Current (Coral Sea). Bacterioplankton communities had the highest operational taxonomic unit (OTU) richness, as measured by ARISA at eastern bay stations (S [total richness] = 84 to 85 OTU) and the lowest richness in the Coral Sea (S = 39 to 59 OTU). Richness correlated positively with bacterial abundance; however, there were no strong correlations between diversity and salinity, NO3− and PO43− concentrations, or chlorophyll a concentration. Bacterioplankton communities at the riverine stations were different from communities in the bay or Coral Sea. The main differences in OTU richness between stations were in taxa that each represented 0.1% (the detection limit) to 0.5% of the total amplified DNA, i.e., the “tail” of the distribution. We found that some bacterioplankton taxa are specific to distinct environments while others have a ubiquitous distribution from river to sea. Bacterioplankton richness and diversity patterns in the estuary are potentially a consequence of greater niche availability, mixing of local and adjacent environment communities, or intermediate disturbance. Furthermore, these results contrast with previous reports of spatially homogeneous bacterioplankton communities in other coastal waters.

Microorganisms associated with the stems and roots of nonnodulated (Nod−), wild-type nodulated (Nod+), and hypernodulated (Nod++) soybeans [Glycine max (L.) Merril] were analyzed by ribosomal intergenic transcribed spacer analysis (RISA) and automated RISA (ARISA). RISA of stem samples detected no bands specific to the nodulation phenotype, whereas RISA of root samples revealed differential bands for the nodulation phenotypes. Pseudomonas fluorescens was exclusively associated with Nod+ soybean roots. Fusarium solani was stably associated with nodulated (Nod+ and Nod++) roots and less abundant in Nod− soybeans, whereas the abundance of basidiomycetes was just the opposite. The phylogenetic analyses suggested that these basidiomycetous fungi might represent a root-associated group in the Auriculariales. Principal-component analysis of the ARISA results showed that there was no clear relationship between nodulation phenotype and bacterial community structure in the stem. In contrast, both the bacterial and fungal community structures in the roots were related to nodulation phenotype. The principal-component analysis further suggested that bacterial community structure in roots could be classified into three groups according to the nodulation phenotype (Nod−, Nod+, or Nod++). The analysis of root samples indicated that the microbial community in Nod− soybeans was more similar to that in Nod++ soybeans than to that in Nod+ soybeans.

Microbialites are organosedimentary structures that result from the trapping, binding, and lithification of sediments by microbial mat communities. In this study we developed a model artificial microbialite system derived from natural stromatolites, a type of microbialite, collected from Exuma Sound, Bahamas. We demonstrated that the morphology of the artificial microbialite was consistent with that of the natural system in that there was a multilayer community with a pronounced biofilm on the surface, a concentrated layer of filamentous cyanobacteria in the top 5 mm, and a lithified layer of fused oolitic sand grains in the subsurface. The fused grain layer was comprised predominantly of the calcium carbonate polymorph aragonite, which corresponded to the composition of the Bahamian stromatolites. The microbial diversity of the artificial microbialites and that of natural stromatolites were also compared using automated ribosomal intergenic spacer analysis (ARISA) and 16S rRNA gene sequencing. The ARISA profiling indicated that the Shannon indices of the two communities were comparable and that the overall diversity was not significantly lower in the artificial microbialite model. Bacterial clone libraries generated from each of the three artificial microbialite layers and natural stromatolites indicated that the cyanobacterial and crust layers most closely resembled the ecotypes detected in the natural stromatolites and were dominated by Proteobacteria and Cyanobacteria. We propose that such model artificial microbialites can serve as experimental analogues for natural stromatolites.

Molecular fingerprinting techniques offer great promise for analyzing changes in microbial community structure, especially when dealing with large number of samples. However, a serious limitation has been the lack of quantification offered by such techniques since the relative abundances of the identified operational taxonomic units (OTUs) in the original samples are not measured. A quantitative fingerprinting approach designated “qfingerprinting” is proposed here. This method involves serial dilutions of the sample of interest and further systematic fingerprinting of all dilution series. Using the ultimate dilutions for which OTU are still PCR amplifiable and taking into account peak size inaccuracy and peak reproducibility, the relative abundance of each OTU is then simultaneously determined over a scale spanning several orders of magnitude. The approach was illustrated by using a quantitative version of automated ribosomal intergenic spacer analysis (ARISA), here called qARISA. After validating the concept with a synthetic mixture of known DNA targets, qfingerprinting was applied to well-studied marine sediment samples to examine specific changes in OTU abundance associated with sediment depth. The new strategy represents a major advance for the detailed quantitative description of specific OTUs within complex communities. Further ecological applications of the new strategy are also proposed.

Permeable sediments and associated microbial communities play a fundamental role in nutrient recycling within coral reef ecosystems by ensuring high levels of primary production in oligotrophic environments. A previous study on organic matter degradation within biogenic carbonate and terrigenous silicate reef sands in the Red Sea suggested that observed sand-specific differences in microbial activity could be caused by variations in microbial biomass and diversity. Here, we tested this hypothesis by comparing bacterial abundance and community structure in both sand types, and by further exploring the structuring effects of time (season) and space (sediment depth, in/out-reef). Changes in bacterial community structure, as determined via automated ribosomal intergenic spacer analysis (ARISA), were primarily driven by sand mineralogy at specific seasons, sediment depths and reef locations. By coupling ARISA with 16S-ITS rRNA sequencing, we detected significant community shifts already at the bacterial class level, with Proteobacteria (Gamma-, Delta-, Alpha-) and Actinobacteria being prominent members of the highly diverse communities. Overall, our findings suggest that reef sand-associated bacterial communities vary substantially with sand type. Especially in synergy with environmental variation over time and space, mineralogical differences seem to play a central role in maintaining high levels of bacterial community heterogeneity. The local co-occurrence of carbonate and silicate sands may thus significantly increase the availability of microbial niches within a single coral reef ecosystem.

Fluorescent Pseudomonas strains were isolated from 38 undisturbed pristine soil samples from 10 sites on four continents. A total of 248 isolates were confirmed as Pseudomonas sensu stricto by fluorescent pigment production and group-specific 16S ribosomal DNA (rDNA) primers. These isolates were analyzed by three molecular typing methods with different levels of resolution: 16S rDNA restriction analysis (ARDRA), 16S-23S rDNA intergenic spacer-restriction fragment length polymorphism (ITS-RFLP) analysis, and repetitive extragenic palindromic PCR genomic fingerprinting with a BOX primer set (BOX-PCR). All isolates showed very similar ARDRA patterns, as expected. Some ITS-RFLP types were also found at every geographic scale, although some ITS-RFLP types were unique to the site of origin, indicating weak endemicity at this level of resolution. Using a similarity value of 0.8 or more after cluster analysis of BOX-PCR fingerprinting patterns to define the same genotypes, we identified 85 unique fluorescent Pseudomonas genotypes in our collection. There were no overlapping genotypes between sites as well as continental regions, indicating strict site endemism. The genetic distance between isolates as determined by degree of dissimilarity in BOX-PCR patterns was meaningfully correlated to the geographic distance between the isolates' sites of origin. Also, a significant positive spatial autocorrelation of the distribution of the genotypes was observed among distances of <197 km, and significant negative autocorrelation was observed between regions. Hence, strong endemicity of fluorescent Pseudomonas genotypes was observed, suggesting that these heterotrophic soil bacteria are not globally mixed.

Bacteria associated with the onset of type 1 diabetes in a rat model system were identified. In two experiments, stool samples were collected at three time points after birth from bio-breeding diabetes-prone (BB-DP) and bio-breeding diabetes-resistant (BB-DR) rats. DNA was isolated from these samples and the 16S rRNA gene was amplified using universal primer sets. In the first experiment, bands specific to BB-DP and BB-DR genotypes were identified by automated ribosomal intergenic spacer analysis at the time of diabetes onset in BB-DP. Lactobacillus and Bacteroides strains were identified in the BB-DR- and BB-DP-specific bands, respectively. Sanger sequencing showed that the BB-DP and BB-DR bacterial communities differed significantly but too few reads were available to identify significant differences at the genus or species levels. A second experiment confirmed these results using higher throughput pyrosequencing and quantitative PCR of 16S rRNA with more rats per genotype. An average of 4541 and 3381 16S rRNA bacterial reads were obtained from each of the 10 BB-DR and 10 BB-DP samples collected at time of diabetes onset. Nine genera were more abundant in BB-DP whereas another nine genera were more abundant in BB-DR. Thirteen and eleven species were more abundant in BB-DP and BB-DR, respectively. An average of 23% and 10% of all reads could be classified at the genus and species levels, respectively. Quantitative PCR verified the higher abundance of Lactobacillus and Bifidobacterium in the BB-DR samples. Whether these changes are caused by diabetes or are involved in the development of the disease is unknown.

Disturbances act as powerful structuring forces on ecosystems. To ask whether environmental microbial communities have capacity to recover after a large disturbance event, we conducted a whole-ecosystem manipulation, during which we imposed an intense disturbance on freshwater microbial communities by artificially mixing a temperate lake during peak summer thermal stratification. We employed environmental sensors and water chemistry analyses to evaluate the physical and chemical responses of the lake, and bar-coded 16S ribosomal RNA gene pyrosequencing and automated ribosomal intergenic spacer analysis (ARISA) to assess the bacterial community responses. The artificial mixing increased mean lake temperature from 14 to 20 °C for seven weeks after mixing ended, and exposed the microorganisms to very different environmental conditions, including increased hypolimnion oxygen and increased epilimnion carbon dioxide concentrations. Though overall ecosystem conditions remained altered (with hypolimnion temperatures elevated from 6 to 20 °C), bacterial communities returned to their pre-manipulation state as some environmental conditions, such as oxygen concentration, recovered. Recovery to pre-disturbance community composition and diversity was observed within 7 (epilimnion) and 11 (hypolimnion) days after mixing. Our results suggest that some microbial communities have capacity to recover after a major disturbance.

This study examined the similarity of epilimnetic bacterial community composition (BCC) across several within- and among-lake spatial scales, and the environmental factors giving rise to similar bacterial communities in different lakes were also explored. Samples were collected from 13 northern and southern Wisconsin lakes representing gradients in lake size, productivity, dissolved organic carbon and humic acid contents, and pH. Hypotheses regarding patchy distribution of bacterial communities in lakes were tested by comparing samples collected from nearby (tens of meters) and distant (hundreds of meters) sampling sites in the same lake. BCC was characterized by using a molecular fingerprinting technique, automated ribosomal intergenic spacer analysis (ARISA). Overall, samples collected at the 10-m, 100-m, and between-lake scales differed by 13, 17, and 75%, respectively. Variation at these last two scales was significant. The development of within-lake variation in BCC appeared to depend on the isolation of water by lake shoreline features such as bays or narrow constrictions. ARISA profiles from northern lakes had fewer peaks and were less similar to each other than were those of the southern lakes, suggesting that regional features do not necessarily lead to the development of similar bacterial communities. Lakes at similar positions on productivity and dissolved organic carbon concentration gradients had similar bacterial communities, and bacterial diversity was positively correlated with lake productivity and water temperature. Factorial studies taking into account these gradients, as well as regional spatial scales, should provide much insight into the nature of aquatic bacterial biogeography.

Patterns of microbial community dynamics in the turkey intestine were examined. Every week of the 18-week production cycle, cecal bacterial communities and Campylobacter loads were examined from five birds for each of two flocks. Molecular fingerprinting via the automated ribosomal intergenic spacer analysis (ARISA) and terminal restriction fragment length polymorphism (T-RFLP) of the cecal samples revealed that microbial communities changed in a time-dependent manner, and during both trials they developed via transition through three phases during the production cycle. A core component of the microbiota consisting of 11 Bacteroidetes types was present throughout both trials. In contrast, constant succession was detected in the Clostridiales populations until week 10 or 11, with few shared sequences between the flocks. Changes in Campylobacter jejuni and Campylobacter coli loads were correlated to, but not dependent on, the two acute transitions delimiting the three developmental phases.

Physicochemical characterization, automated ribosomal intergenic spacer analysis (ARISA) community profiling, and 16S rRNA gene sequencing approaches were used to study bacterial communities inhabiting submerged Lake Huron sinkholes inundated with hypoxic, sulfate-rich groundwater. Photosynthetic cyanobacterial mats on the sediment surface were dominated by Phormidium autumnale, while deeper, organically rich sediments contained diverse and active bacterial communities.

Genetic background affects susceptibility to ileocolitis in mice deficient in two intracellular glutathione peroxidases, GPx1 and GPx2. The C57BL/6 (B6) GPx1/2 double-knockout (DKO) mice have mild ileocolitis, and 129S1/Sv (129) DKO mice have severe inflammation. We used diet to modulate ileocolitis; a casein-based defined diet with AIN76A micronutrients (AIN) attenuates inflammation compared to conventional LabDiets. Because luminal microbiota induce DKO ileocolitis, we assessed bacterial composition with automated ribosomal intergenic-spacer analysis (ARISA) on cecal DNA. We found that mouse strain had the strongest impact on the composition of microbiota than diet and GPx genotypes. In comparing AIN and LabDiet, DKO mice were more resistant to change than the non-DKO or WT mice. However, supplementing yeast and inulin to AIN diet greatly altered microflora profiles in the DKO mice. From 129 DKO strictly, we found overgrowth of Escherichia coli. We conclude that genetic background predisposes mice to colonization of potentially pathogenic E. coli.

Genetic background affects susceptibility to ileocolitis in mice deficient in two intracellular glutathione peroxidases, GPx1 and GPx2. The C57BL/6 (B6) GPx1/2 double-knockout (DKO) mice have mild ileocolitis, and 129S1/Sv (129) DKO mice have severe inflammation. We used diet to modulate ileocolitis; a casein-based defined diet with AIN76A micronutrients (AIN) attenuates inflammation compared to conventional LabDiets. Because luminal microbiota induce DKO ileocolitis, we assessed bacterial composition with automated ribosomal intergenic-spacer analysis (ARISA) on cecal DNA. We found that mouse strain had the strongest impact on the composition of microbiota than diet and GPx genotypes. In comparing AIN and LabDiet, DKO mice were more resistant to change than the non-DKO or WT mice. However, supplementing yeast and inulin to AIN diet greatly altered microflora profiles in the DKO mice. From 129 DKO strictly, we found overgrowth of Escherichia coli. We conclude that genetic background predisposes mice to colonization of potentially pathogenic E. coli.

This study investigated the effects of dietary supplementation with a prebiotic mannan oligosaccharide (MOS) on broiler performance, bacterial community structure, and phylogenetic populations of cecal contents. Bird performance data were collected, and cecal samples were extracted from randomly caught poults from each treatment group every 7 days from hatching to the age of 42 days. Weight gain, feed consumption, and feed efficiency ratios did not differ significantly between groups. Automated ribosomal intergenic spacer analysis (ARISA) of the bacterial communities in birds receiving MOS-supplemented diets indicated that dietary supplementation with MOS at either of 2 levels significantly altered the bacterial community structure from that of the control group on all sample days. The phylogenetic identities of bacteria contained within the cecum were determined by constructing a 16S rRNA gene clone library. A total of 594 partial 16S rRNA gene sequences from the cecal contents were analyzed and compared for the three dietary treatments. The dominant bacteria of the cecum belonged to three phyla, Firmicutes, Bacteroidetes, and Proteobacteria; of these, Firmicutes were the most dominant in all treatment groups. Statistical analysis of the bacterial 16S rRNA gene clone libraries showed that the compositions of the clone libraries from broilers receiving MOS-supplemented diets were, in most cases, significantly different from that of the control group. It can be concluded that in this trial MOS supplementation significantly altered the cecal bacterial community structure.