JEQ
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


Published online 1 May 2009
Published in J Environ Qual 38:1224-1232 (2009)
DOI: 10.2134/jeq2008.0258
© 2009 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA

Open Access Article
This Article
Free via Open Access
Right arrow OA Abstract
Right arrow OA Full Text Free
Right arrow Full Text (PDF) Free
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Bell, A.
Right arrow Articles by Sayler, G. S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Bell, A.
Right arrow Articles by Sayler, G. S.
Agricola
Right arrow Articles by Bell, A.
Right arrow Articles by Sayler, G. S.
Related Collections
Right arrow Surface Water Quality
Right arrow Microbial Processes
Right arrow Other Models
Right arrow Water Pollution

Factors Influencing the Persistence of Fecal Bacteroides in Stream Water

Alyssa Bella, Alice C. Laytonb,*, Larry McKaya, Dan Williamsb, Randy Gentryc and Gary S. Saylerb

a Dep. of Earth and Planetary Sciences, The Univ. of Tennessee Center for Environ. Biotechnology, The Univ. of Tennessee
b Center for Environ. Biotechnology, The Univ. of Tennessee
c Civil and Environ. Eng., The Univ. of Tennessee


Figure 1
View larger version (17K):
[in this window]
[in a new window]

 
Fig. 1. Master standard curve generated from 31 individual standard curves resulting in a linear equation y = –0.31x + 11.49, where y = log (Bacteroides 16S rRNA genes) and x = CT.

 

Figure 2
View larger version (31K):
[in this window]
[in a new window]

 
Fig. 2. Comparison of fecal particle size and the persistence of Bacteroides 16S rRNA genes from three separate slurries: coarse, medium, and fine. (A) visual comparison of the finest and coarsest particle size intervals evaluated in the particle size analysis, (B) size interval distribution for three aggregate size intervals (coarse, medium, and fine) as reflected in percent of total weight for each filtrate.

 

Figure 3
View larger version (17K):
[in this window]
[in a new window]

 
Fig. 3. Comparison of Bacteroides 16S rRNA genes/mL for fine, medium, and coarse fecal slurries in unfiltered water (experimental), in filtered water (filtered control) and stream water without fecal slurry (background control). All microcosms were incubated at 25°C. Error bars in the plots represent the standard deviations between triplicate microcosms for the microcosms containing fecal slurries and the standard deviations in triplicate PCR reactions for the filtered stream water control and the stream water only control. a* = samples from unfiltered stream water microcosms with significantly different Bacteroides 16S rRNA genes/ml concentrations than the corresponding stream water background controls. b* = samples from unfiltered stream water microcosms with significantly different Bacteroides 16S rRNA genes/mL concentrations than the corresponding filtered stream water control.

 

Figure 4
View larger version (17K):
[in this window]
[in a new window]

 
Fig. 4. Comparison of Bacteroides 16S rRNA genes/mL with initial starting fecal concentrations in microcosms of 10, 100, and 1000 mg/L in unfiltered water (experimental), filtered water (filtered control) and in stream water without fecal slurry (background control). All microcosms were incubated at 25°C. Error bars in the plots represent the standard deviations between triplicate microcosms for the unfiltered stream water microcosms containing fecal slurries and the standard deviations in triplicate PCR reactions for the filtered stream water microcosm containing fecal slurries and stream water only microcosm. a* = samples from unfiltered stream water microcosms with significantly different Bacteroides 16S rRNA genes/mL concentrations than the corresponding stream water background controls. b* = samples from unfiltered stream water microcosms with significantly different Bacteroides 16S rRNA genes/mL concentrations than the corresponding filtered stream water controls.

 

Figure 5
View larger version (39K):
[in this window]
[in a new window]

 
Fig. 5. Bacteroides 16S rRNA genes/mL in microcosms incubated with variable temperature ranging from 5 to 35°C. For each temperature three microcosms were used: (1) A fecal slurry of 100 mg/L in unfiltered stream water (experimental) (2) A fecal slurry of 100 mg/L in filtered stream water (filtered control), and (3) the unfiltered stream water without fecal slurry (background control). Error bars in the plots represent the standard deviations between triplicate microcosms for the microcosms containing fecal slurries and the standard deviations in triplicate PCR reactions for the stream water only microcosm. a* = samples from unfiltered stream water microcosms with significantly different Bacteroides 16S rRNA genes/mL concentrations than the corresponding stream water background controls. b* = samples from unfiltered stream water microcosms with significantly different Bacteroides 16S rRNA genes/mL concentrations than the corresponding filtered stream water controls.

 

Figure 6
View larger version (11K):
[in this window]
[in a new window]

 
Fig. 6. Relationship between decay rate (k) of the log concentration Bacteroides 16S rRNA genes/mL with temperature in microcosms in unfiltered stream water using a Peak, Gaussian, 3 Parameter equation (y = a x exp{–0.5 x [(x – x0)/b]2}) and a linear equation (y = y0 + a x x). The error bars represent the standard deviation of k for all experimental microcosms. For the peak Gaussian equation: Parameter a = 0.0304 ± 0.0032 (P = <0.001), parameter b = 15.2113 ± 3.0242 (P = 0.0015) and X0 = 29.8817 ± 3.4623 (P < 0.001). For the linear equation Y0 = 0.0057 ± 0.0032 (P = 0.2132) and a = 0.0009 ± 0.0002 (P = 0.0016).

 





HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
The SCI Journals Agronomy Journal Crop Science
Journal of Natural Resources
and Life Sciences Education
Vadose Zone Journal
Soil Science Society of America Journal Journal of Plant Registrations The Plant Genome
Copyright © 2009 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.