scholarly journals 16S Ribosomal DNA-Based Analysis of Bacterial Diversity in Purified Water Used in Pharmaceutical Manufacturing Processes by PCR and Denaturing Gradient Gel Electrophoresis

2002 ◽  
Vol 68 (2) ◽  
pp. 699-704 ◽  
Author(s):  
Mako Kawai ◽  
Eiichi Matsutera ◽  
Hisashi Kanda ◽  
Nobuyasu Yamaguchi ◽  
Katsuji Tani ◽  
...  
Keyword(s):  
Bacterial Diversity ◽  
Ribosomal Dna ◽  
Gel Electrophoresis ◽  
Esterase Activity ◽  
Denaturing Gradient Gel Electrophoresis ◽  
Pharmaceutical Manufacturing ◽  
Manufacturing Processes ◽  
Culturable Bacteria ◽  
16S Ribosomal Dna ◽  
Gradient Gel Electrophoresis

ABSTRACT The bacterial community in partially purified water, which is prepared by ion exchange from tap water and is used in pharmaceutical manufacturing processes, was analyzed by denaturing gradient gel electrophoresis (DGGE). 16S ribosomal DNA fragments, including V6, -7, and -8 regions, were amplified with universal primers and analyzed by DGGE. The bacterial diversity in purified water determined by PCR-DGGE banding patterns was significantly lower than that of other aquatic environments. The bacterial populations with esterase activity sorted by flow cytometry and isolated on soybean casein digest (SCD) and R2A media were also analyzed by DGGE. The dominant bacterium in purified water possessed esterase activity but could not be detected on SCD or R2A media. DNA sequence analysis of the main bands on the DGGE gel revealed that culturable bacteria on these media were Bradyrhizobium sp., Xanthomonas sp., and Stenotrophomonas sp., while the dominant bacterium was not closely related to previously characterized bacteria. These data suggest the importance of culture-independent methods of quality control for pharmaceutical water.

scholarly journals Numerical Analysis of Grassland Bacterial Community Structure under Different Land Management Regimens by Using 16S Ribosomal DNA Sequence Data and Denaturing Gradient Gel Electrophoresis Banding Patterns

2001 ◽  
Vol 67 (10) ◽  
pp. 4554-4559 ◽  
Author(s):  
Allison E. McCaig ◽  
L. Anne Glover ◽  
James I. Prosser
Keyword(s):  
Ribosomal Dna ◽  
Gel Electrophoresis ◽  
Denaturing Gradient Gel Electrophoresis ◽  
Sequence Data ◽  
Canonical Variate ◽  
Similarity Coefficients ◽  
Grassland Soils ◽  
Soil Dna ◽  
16S Ribosomal Dna ◽  
Gradient Gel Electrophoresis

ABSTRACT Bacterial diversity in unimproved and improved grassland soils was assessed by PCR amplification of bacterial 16S ribosomal DNA (rDNA) from directly extracted soil DNA, followed by sequencing of ∼45 16S rDNA clones from each of three unimproved and three improved grassland samples (A. E. McCaig, L. A. Glover, and J. I. Prosser, Appl. Environ. Microbiol. 65:1721–1730, 1999) or by denaturing gradient gel electrophoresis (DGGE) of total amplification products. Semi-improved grassland soils were analyzed only by DGGE. No differences between communities were detected by calculation of diversity indices and similarity coefficients for clone data (possibly due to poor coverage). Differences were not observed between the diversities of individual unimproved and improved grassland DGGE profiles, although considerable spatial variation was observed among triplicate samples. Semi-improved grassland samples, however, were less diverse than the other grassland samples and had much lower within-group variation. DGGE banding profiles obtained from triplicate samples pooled prior to analysis indicated that there was less evenness in improved soils, suggesting that selection for specific bacterial groups occurred. Analysis of DGGE profiles by canonical variate analysis but not by principal-coordinate analysis, using unweighted data (considering only the presence and absence of bands) and weighted data (considering the relative intensity of each band), demonstrated that there were clear differences between grasslands, and the results were not affected by weighting of data. This study demonstrated that quantitative analysis of data obtained by community profiling methods, such as DGGE, can reveal differences between complex microbial communities.

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