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1.
Microb Ecol ; 70(2): 311-21, 2015 Aug.
Article in English | MEDLINE | ID: mdl-25721726

ABSTRACT

Denitrification is a critically important biogeochemical pathway that removes fixed nitrogen from ecosystems and thus ultimately controls the rate of primary production in nitrogen-limited systems. We examined the community structure of bacteria containing the nirS gene, a signature gene in the denitrification pathway, from estuarine and salt marsh sediments and from the water column of two of the world's largest marine oxygen-deficient zones (ODZs). We generated over 125,000 nirS gene sequences, revealing a large degree of genetic diversity including 1,815 unique taxa, the vast majority of which formed clades that contain no cultured representatives. These results underscore how little we know about the genetic diversity of metabolisms underlying this critical biogeochemical pathway. Marine sediments yielded 1,776 unique taxa when clustered at 95 % sequence identity, and there was no single nirS denitrifier that was a competitive dominant; different samples had different highly abundant taxa. By contrast, there were only 39 unique taxa identified in samples from the two ODZs, and 99 % of the sequences belonged to 5 or fewer taxa. The ODZ samples were often dominated by nirS sequences that shared a 92 % sequence identity to a nirS found in the anaerobic ammonium-oxidizing (anammox) genus Scalindua. This sequence was abundant in both ODZs, accounting for 38 and 59 % of all sequences, but it was virtually absent in marine sediments. Our data indicate that ODZs are remarkably depauperate in nirS genes compared to the remarkable genetic richness found in coastal sediments.


Subject(s)
Geologic Sediments/microbiology , Oxygen , Bacteria/metabolism , Denitrification , Ecosystem , Genetic Variation , Seawater/microbiology
2.
Bioinformatics ; 29(9): 1212-4, 2013 May 01.
Article in English | MEDLINE | ID: mdl-23511542

ABSTRACT

SUMMARY: Pyrosequencing of 16S rDNA is widely used to study microbial communities, and a rich set of software tools support this analysis. Pyrosequencing of protein-coding genes, which can help elucidate functional differences among microbial communities, significantly lags behind 16S rDNA in availability of sequence analysis software. In both settings, frequent homopolymer read errors inflate the estimation of microbial diversity, and de-noising is required to reduce that bias. Here we describe FunFrame, an R-based data-analysis pipeline that uses recently described algorithms to de-noise functional gene pyrosequences and performs ecological analysis on de-noised sequence data. The novelty of this pipeline is that it provides users a unified set of tools, adapted from disparate sources and designed for different applications, that can be used to examine a particular protein coding gene of interest. We evaluated FunFrame on functional genes from four PCR-amplified clones with sequence depths ranging from 9084 to 14 494 sequences. FunFrame produced from one to nine Operational Taxanomic Units for each clone, resulting in an error rate ranging from 0 to 0.18%. Importantly, FunFrame reduced spurious diversity while retaining more sequences than a commonly used de-noising method that discards sequences with frameshift errors. AVAILABILITY: Software, documentation and a complete set of sample data files are available at http://faculty.www.umb.edu/jennifer.bowen/software/FunFrame.zip.


Subject(s)
Metagenomics/methods , Sequence Analysis, DNA/methods , Software , Algorithms , Proteins/genetics
3.
J Microbiol Methods ; 93(1): 68-71, 2013 Apr.
Article in English | MEDLINE | ID: mdl-23337813

ABSTRACT

The study of environmental biofilms is complicated by the difficulty of working with them under lab conditions. Nonetheless, knowledge of cellular activity and interactions within environmental biofilms could lead to novel biomedical applications. As a first step in this direction we propose a novel technique for inducing resistance to Staphylococcus aureus (S. aureus) in an intact environmental biofilm. Agar plates were prepared with or without the addition of 20% S. aureus spent culture media and immersed in coastal seawater (Boston Harbor, Massachusetts, USA) for four days to grow up an environmental biofilm. Nucleopore filters inoculated with an overnight culture of S. aureus were then applied to the surface of the agar plates with the environmental biofilms, incubated 4h at 37°C, removed and subsequently stained and analyzed. Marine environmental biofilms grown on agar containing S. aureus spent culture media were significantly more inhibitory of S. aureus growth than were marine environmental biofilms grown on plain agar.


Subject(s)
Antibiosis , Biofilms/growth & development , Environmental Microbiology , Microbiological Techniques/methods , Staphylococcus aureus/growth & development , Culture Media/chemistry
4.
FEMS Microbiol Lett ; 243(1): 235-42, 2005 Feb 01.
Article in English | MEDLINE | ID: mdl-15668024

ABSTRACT

The method for DNA fingerprinting of the 16S-23S rDNA intergenic spacer region was modified to increase resolution of bacterial strains by thermal gradient gel electrophoresis (TGGE) analysis. By utilizing the high melting temperature region of the tRNA gene located in the middle of the 16S-23S rDNA intergenic spacer region as an internal clamp for TGGE, multiple melting domain problems were solved. PCR primers lacking a stretch of GC-rich sequences (GC-clamp) amplified the intergenic spacer region more efficiently than GC-clamped primers. Therefore, PCR artifacts were avoided by using low, 17-cycle, PCR. The method was successfully applied to diverse bacterial species for strain differentiation by TGGE without requiring a special PCR primer set.


Subject(s)
DNA Primers , DNA, Ribosomal Spacer/analysis , Electrophoresis, Polyacrylamide Gel/methods , GC Rich Sequence/genetics , Gram-Negative Bacteria/classification , Polymerase Chain Reaction/methods , Bacterial Typing Techniques , DNA Fingerprinting/methods , DNA, Bacterial/analysis , Gram-Negative Bacteria/genetics , Hot Temperature , RNA, Ribosomal, 16S/genetics , RNA, Ribosomal, 23S/genetics , Sequence Analysis, DNA
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