Denaturing Gradient Gel Electrophoresis Analysis of 16S Ribosomal DNA Amplicons To Monitor Changes in Fecal Bacterial Populations of Weaning Pigs after Introduction of Lactobacillus reuteri Strain MM53

Abstract

The diversity and stability of the fecal bacterial microbiota in weaning pigs was studied after introduction of an exogenous Lactobacillus reuteri strain, MM53, using a combination of cultivation and techniques based on genes encoding 16S rRNA (16S rDNA). Piglets (n ‫؍‬ 9) were assigned to three treatment groups (control, daily dosed, and 4th-day dosed), and fresh fecal samples were collected daily. Dosed animals received 2.5 ؋ 10 10 CFU of antibiotic-resistant L. reuteri MM53 daily or every 4th day. Mean Lactobacillus counts for the three groups ranged from 1 ؋ 10 9 to 4 ؋ 10 9 CFU/g of feces. Enumeration of strain L. reuteri MM53 on MRS agar (Difco) plates containing streptomycin and rifampin showed that the introduced strain fluctuated between 8 ؋ 10 3 and 5 ؋ 10 6 CFU/g of feces in the two dosed groups. Denaturing gradient gel electrophoresis (DGGE) of PCR-amplified 16S rDNA fragments, with primers specific for variable regions 1 and 3 (V1 and V3), was used to profile complexity of fecal bacterial populations. Analysis of DGGE banding profiles indicated that each individual maintained a unique fecal bacterial population that was stable over time, suggesting a strong host influence. In addition, individual DGGE patterns could be separated into distinct time-dependent clusters. Primers designed specifically to restrict DGGE analysis to a select group of lactobacilli allowed examination of interspecies relationships and abundance. Based on relative band migration distance and sequence determination, L. reuteri was distinguishable within the V1 region 16S rDNA gene patterns. Daily fluctuations in specific bands within these profiles were observed, which revealed an antagonistic relationship between L. reuteri MM53 (band V1-3) and another indigenous Lactobacillus assemblage (band V1-6).

Benchmarking DNA Metabarcoding for Biodiversity-Based Monitoring and Assessment

“…Here, we show that the use of inappropriate PCR conditions can also affect the final taxonomic assignment in metazoan metabarcoding analyses. Our results show that a constant low annealing temperature (46 or 50 • C) provides more accurate taxonomic inferences compared to the touchdown profile, which contrasts with previous studies (Hansen et al, 1998;Simpson et al, 2000;Leray et al, 2013). Moreover, it is well-established that the more PCR cycles, the more spurious sequences and chimera are formed during PCR , which could explain the lower taxa detection rate when using the touchdown profile (which includes five more cycles).…”

Microbial diversity studies of the porcine gastrointestinal ecosystem during weaning transition

“…This changed dramatically after the first introduction of 16S ribosomal RNA (rRNA) as molecular markers in microbial taxonomy by Woese [25], and the first attempts to apply this sequence information in microbial ecology [15]. These new approaches have only recently been introduced in studies on the GI tract and have led to new insights on the pig intestinal microbial ecology, the effect of different dietary strategies and host factors on the bacterial communities composition [4,[7][8][9][10][11]18]. A summary of the uses and drawbacks of various techniques for the analysis of the pig intestinal ecosystem is given in Table I and an example of a denaturing gradient gel electrophoresis (DGGE) analysis of 16S rRNA gene amplicons from ileal and colonic lumen samples of four weaning piglets is shown in Figure 1.…”

Parenteral long-acting amoxicillin reduces intestinal bacterial community diversity in piglets even 5 weeks after the administration

“…This method has been successfully used for several years in the research area of porcine gut ecology (Simpson et al, 1999(Simpson et al, , 2000McCracken et al, 2001;Konstantinov et al, 2004) even though it allows estimation of only dominant bacterial populations of the complex intestinal ecosystem owing to DNA extraction sensitivity and PCR-bias (Muyzer and Smalla, 1998).…”