In vitro effects of synbiotic fermentation on the canine faecal microbiota.

Stirred, pH-controlled anaerobic batch cultures were used to investigate the in vitro effects of galacto-oligosaccharides (GOS) alone or combined with the probiotic Bifidobacterium bifidum 02 450B on the canine faecal microbiota of three different donors. GOS supported the growth of B. bifidum 02 450B throughout the fermentation. Quantitative analysis of bacterial populations by FISH revealed significant increases in Bifidobacterium spp. counts (Bif164) and a concomitant decrease in Clostridium histolyticum counts (Chis150) in the synbiotic-containing vessels compared with the controls and GOS vessels. Vessels containing probiotic alone displayed a transient increase in Bifidobacterium spp. and a transient decrease in Bacteroides spp. Denaturing gradient gel electrophoresis analysis showed that GOS elicited similar alterations in the microbial profiles of the three in vitro runs. However, the synbiotic did not alter the microbial diversity of the three runs to the same extent as GOS alone. Nested PCR using universal primers, followed by bifidobacterial-specific primers illustrated low bifidobacterial diversity in dogs, which did not change drastically during the in vitro fermentation. This study illustrates that the canine faecal microbiota can be modulated in vitro by GOS supplementation and that GOS can sustain the growth of B. bifidum 02 450B in a synbiotic combination.

Use of denaturing gradient gel electrophoresis to detect Actinobacteria associated with the human faecal microbiota

With the exceptions of the bifidobacteria, propionibacteria and coriobacteria, the Actinobacteria associated with the human gastrointestinal tract have received little attention. This has been due to the seeming absence of these bacteria from most clone libraries. In addition, many of these bacteria have fastidious growth and atmospheric requirements. A recent cultivation-based study has shown that the Actinobacteria of the human gut may be more diverse than previously thought. The aim of this study was to develop a denaturing gradient gel electrophoresis (DGGE) approach for characterizing Actinobacteria present in faecal samples. Amount of DNA added to the Actinobacteria-specific PCR used to generate strong PCR products of equal intenstity from faecal samples of five infants, nine adults and eight elderly adults was anti-correlated with counts of bacteria obtained using fluorescence in situ hybridization probe HGC69A. A nested PCR using Actinobacteria-specific and universal PCR-DGGE primers was used to generate profiles for the Actinobacteria. Cloning of sequences from the DGGE bands confirmed the specificity of the Actinobacteria-specific primers. In addition to members of the genus Bifidobacterium, species belonging to the genera Propionibacterium, Microbacterium, Brevibacterium, Actinomyces and Corynebacterium were found to be part of the faecal microbiota of healthy humans.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Phylogeographic analysis of the chloroplast DNA variation in wild common bean (Phaseolus vulgaris L.) in the Americas

The wild common bean (Phaseolus vulgaris) is widely but discontinuously distributed from northern Mexico to northern Argentina on both sides of the Isthmus of Panama. Little is known on how the species has reached its current disjunct distribution. In this research, chloroplast DNA polymorphisms in seven non-coding regions were used to study the history of migration of wild P. vulgaris between Mesoamerica and South America. A penalized likelihood analysis was applied to previously published Leguminosae ITS data to estimate divergence times between P. vulgaris and its sister taxa from Mesoamerica, and divergence times of populations within P. vulgaris. Fourteen chloroplast haplotypes were identified by PCR-RFLP and their geographical associations were studied by means of a Nested Clade Analysis and Mantel Tests. The results suggest that the haplotypes are not randomly distributed but occupy discrete parts of the geographic range of the species. The current distribution of haplotypes may be explained by isolation by distance and by at least two migration events between Mesoamerica and South America: one from Mesoamerica to South America and another one from northern South America to Mesoamerica. Age estimates place the divergence of P. vulgaris from its sister taxa from Mesoamerica at or before 1.3 Ma, and divergence of populations from Ecuador-northern Peru at or before 0.6 Ma. As these ages are taken as minimum divergence times, the influence of past events, such as the closure of the Isthmus of Panama and the final uplift of the Andes, on the migration history and population structure of this species cannot be disregarded.

Evaluation of PCR to detect Theileria parva in field-collected tick and bovine samples in Tanzania

The ability of PCR to detect infections of Theileria parva, the cause of East Coast Fever, in field-collected tick and bovine samples from Tanzania was evaluated. PCR-detected infection prevalence was high (15/20, 75%) in unfed adult Rhipicephalus appendiculatus ticks that fed as nymphs on an acutely-infected calf, but low (22/836, 2.6%) in unfed adult R. appendiculatus collected from field sites in Tanzania. Tick infection prevalence was comparable to that in previous studies that used salivary gland staining to detect T parva infection in field-collected host-seeking ticks. Of 282 naturally-exposed zebu calves, seven had PCR-positive buffy coat samples prior to detection of Theileria spp. parasites in stained huffy coat cells or lymph node biopsies. Evidence of Theileria spp. infections was detected in stained smears of lymph node biopsies from 109 calves (38.6%) and huffy coat samples from 81 (28.7%), while huffy coat samples from 66 (23.4%) were PCR-positive for T parva. Implications of these findings for the sensitivity and specificity of the PCR are discussed. (C) 2003 Elsevier Science B.V. All rights reserved.

Quantification of ruminal Clostridium proteoclasticum by real-time PCR using a molecular beacon approach

Aims: All members of the ruminal Butyrivibrio group convert linoleic acid (cis-9,cis-12-18 : 2) via conjugated 18 : 2 metabolites (mainly cis-9,trans-11-18 : 2, conjugated linoleic acid) to vaccenic acid (trans-11-18 : 1), but only members of a small branch, which includes Clostridium proteoclasticum, of this heterogeneous group further reduce vaccenic acid to stearic acid (18 : 0, SA). The aims of this study were to develop a real-time polymerase chain reaction (PCR) assay that would detect and quantify these key SA producers and to use this method to detect diet-associated changes in their populations in ruminal digesta of lactating cows. Materials and Results: The use of primers targeting the 16S rRNA gene of Cl. proteoclasticum was not sufficiently specific when only binding dyes were used for detection in real-time PCR. Their sequences were too similar to some nonproducing strains. A molecular beacon probe was designed specifically to detect and quantify the 16S rRNA genes of the Cl. proteoclasticum subgroup. The probe was characterized by its melting curve and validated using five SA-producing and ten nonproducing Butyrivibrio-like strains and 13 other common ruminal bacteria. Analysis of ruminal digesta collected from dairy cows fed different proportions of starch and fibre indicated a Cl. proteoclasticum population of 2-9% of the eubacterial community. The influence of diet on numbers of these bacteria was less than variations between individual cows. Conclusion: A molecular beacon approach in qPCR enables the detection of Cl. proteoclasticum in ruminal digesta. Their numbers are highly variable between individual animals. Signifance and Impact of the Study: SA producers are fundamental to the flow of polyunsaturated fatty acid and vaccenic acid from the rumen. The method described here enabled preliminary information to be obtained about the size of this population. Further application of the method to digesta samples from cows fed diets of more variable composition should enable us to understand how to control these bacteria in order to enhance the nutritional characteristics of ruminant-derived foods, including milk and beef.

Application of real-time and multiplex PCR assays to study leaf blotch epidemics in barley

Leaf blotch, caused by Rhynchosporium secalis, was studied in a range of winter barley cultivars using a combination of traditional plant pathological techniques and newly developed multiplex and real-time polymerase chain reaction (PCR) assays. Using PCR, symptomless leaf blotch colonization was shown to occur throughout the growing season in the resistant winter barley cv. Leonie. The dynamics of colonization throughout the growing season were similar in both Leonie and Vertige, a susceptible cultivar. However, pathogen DNA levels were approximately 10-fold higher in the susceptible cultivar, which expressed symptoms throughout the growing season. Visual assessments and PCR also were used to determine levels of R. secalis colonization and infection in samples from a field experiment used to test a range of winter barley cultivars with different levels of leaf blotch resistance. The correlation between the PCR and visual assessment data was better at higher infection levels (R(2) = 0.81 for leaf samples with >0.3% disease). Although resistance ratings did not correlate well with levels of disease for all cultivars tested, low levels of infection were observed in the cultivar with the highest resistance rating and high levels of infection in the cultivar with the lowest resistance rating.

The automation and evaluation of nested clade phylogeographic analysis

Nested clade phylogeographic analysis (NCPA) is a popular method for reconstructing the demographic history of spatially distributed populations from genetic data. Although some parts of the analysis are automated, there is no unique and widely followed algorithm for doing this in its entirety, beginning with the data, and ending with the inferences drawn from the data. This article describes a method that automates NCPA, thereby providing a framework for replicating analyses in an objective way. To do so, a number of decisions need to be made so that the automated implementation is representative of previous analyses. We review how the NCPA procedure has evolved since its inception and conclude that there is scope for some variability in the manual application of NCPA. We apply the automated software to three published datasets previously analyzed manually and replicate many details of the manual analyses, suggesting that the current algorithm is representative of how a typical user will perform NCPA. We simulate a large number of replicate datasets for geographically distributed, but entirely random-mating, populations. These are then analyzed using the automated NCPA algorithm. Results indicate that NCPA tends to give a high frequency of false positives. In our simulations we observe that 14% of the clades give a conclusive inference that a demographic event has occurred, and that 75% of the datasets have at least one clade that gives such an inference. This is mainly due to the generation of multiple statistics per clade, of which only one is required to be significant to apply the inference key. We survey the inferences that have been made in recent publications and show that the most commonly inferred processes (restricted gene flow with isolation by distance and contiguous range expansion) are those that are commonly inferred in our simulations. However, published datasets typically yield a richer set of inferences with NCPA than obtained in our random-mating simulations, and further testing of NCPA with models of structured populations is necessary to examine its accuracy.

The automation of nested clade phylogeographic analysis

ANeCA is a fully automated implementation of Nested Clade Phylogeographic Analysis. This was originally developed by Templeton and colleagues, and has been used to infer, from the pattern of gene sequence polymorphisms in a geographically structured population, the historical demographic processes that have shaped its evolution. Until now it has been necessary to perform large parts of the procedure manually. We provide a program that will take data in Nexus sequential format, and directly output a set of inferences. The software also includes TCS v1.18 and GeoDis v2.2 as part of automation.

Characterization and PCR multiplexing of polymorphic microsatellite loci in cashew (Anacardium occidentale L.) and their cross-species utilization

Cashew (Anacardium occidentale L.) is the most economically important tropical nut crop in the world, and yet there are no sequence tagged site (STS) markers available for its study. Here we use an automated, high-throughput system to isolate cashew microsatellites from a non-enriched genomic library blotted onto membranes at high density for screening. Sixty-five sequences contained a microsatellite array, of which 21 proved polymorphic among a closely related seed garden population of 49 genotypes. Twelve markers were suitable for multiplex analysis. Of these, 10 amplified in all three related tropical tree species tested: Anacardium microcarpum, Anacardium pumilum and Anacardium nanum.