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1.
Appl Environ Microbiol ; 85(5)2019 03 01.
Article in English | MEDLINE | ID: mdl-30578268

ABSTRACT

Multiple clades within a microbial taxon often coexist within natural and engineered environments. Because closely related clades have similar metabolic potential, it is unclear how diversity is sustained and what factors drive niche differentiation. In this study, we retrieved three near-complete Competibacter lineage genomes from activated sludge metagenomes at a full-scale pure oxygen activated sludge wastewater treatment plant. The three genomes represent unique taxa within the Competibacteraceae A comparison of the genomes revealed differences in capacity for exopolysaccharide (EPS) biosynthesis, glucose fermentation to lactate, and motility. Using quantitative PCR (qPCR), we monitored these clades over a 2-year period. The clade possessing genes for motility and lacking genes for EPS biosynthesis (CPB_P15) was dominant during periods of suspended solids in the effluent. Further analysis of operational parameters indicate that the dominance of the CPB_P15 clade is associated with low-return activated sludge recycle rates and low wasting rates, conditions that maintain relatively high levels of biomass within the system.IMPORTANCE Members of the Competibacter lineage are relevant in biotechnology as glycogen-accumulating organisms (GAOs). Here, we document the presence of three Competibacteraceae clades in a full-scale activated sludge wastewater treatment plant and their linkage to specific operational conditions. We find evidence for niche differentiation among the three clades with temporal variability in clade dominance that correlates with operational changes at the treatment plant. Specifically, we observe episodic dominance of a likely motile clade during periods of elevated effluent turbidity, as well as episodic dominance of closely related nonmotile clades that likely enhance floc formation during periods of low effluent turbidity.


Subject(s)
Ecosystem , Gammaproteobacteria/isolation & purification , Gammaproteobacteria/metabolism , Sewage/microbiology , Wastewater/microbiology , Water Purification , Biomass , Cloning, Molecular , DNA, Bacterial/genetics , DNA, Bacterial/isolation & purification , Gammaproteobacteria/classification , Gammaproteobacteria/genetics , Genes, Bacterial/genetics , Genome, Bacterial , Metabolic Networks and Pathways , Metagenome , Phylogeny , RNA, Ribosomal, 16S/genetics , Sequence Analysis, DNA , Waste Management
2.
PLoS One ; 10(2): e0117738, 2015.
Article in English | MEDLINE | ID: mdl-25689864

ABSTRACT

Microdroplets are an effective platform for segregating individual cells and amplifying DNA. However, a key challenge is to recover the contents of individual droplets for downstream analysis. This paper offers a method for embedding cells in alginate microspheres and performing multiple serial operations on the isolated cells. Rhodobacter sphaeroides cells were diluted in alginate polymer and sprayed into microdroplets using a fingertip aerosol sprayer. The encapsulated cells were lysed and subjected either to conventional PCR, or whole genome amplification using either multiple displacement amplification (MDA) or a two-step PCR protocol. Microscopic examination after PCR showed that the lumen of the occupied microspheres contained fluorescently stained DNA product, but multiple displacement amplification with phi29 produced only a small number of polymerase colonies. The 2-step WGA protocol was successful in generating fluorescent material, and quantitative PCR from DNA extracted from aliquots of microspheres suggested that the copy number inside the microspheres was amplified up to 3 orders of magnitude. Microspheres containing fluorescent material were sorted by a dilution series and screened with a fluorescent plate reader to identify single microspheres. The DNA was extracted from individual isolates, re-amplified with full-length sequencing adapters, and then a single isolate was sequenced using the Illumina MiSeq platform. After filtering the reads, the only sequences that collectively matched a genome in the NCBI nucleotide database belonged to R. sphaeroides. This demonstrated that sequencing-ready DNA could be generated from the contents of a single microsphere without culturing. However, the 2-step WGA strategy showed limitations in terms of low genome coverage and an uneven frequency distribution of reads across the genome. This paper offers a simple method for embedding cells in alginate microspheres and performing PCR on isolated cells in common bulk reactions, although further work must be done to improve the amplification coverage of single genomes.


Subject(s)
Alginates/chemistry , Cell Separation/methods , Genome, Bacterial/genetics , Microspheres , Polymerase Chain Reaction/methods , Rhodobacter sphaeroides/cytology , Rhodobacter sphaeroides/genetics , Capsules , Feasibility Studies , Glucuronic Acid/chemistry , Hexuronic Acids/chemistry , Sequence Analysis, DNA
3.
Mol Cell Probes ; 21(2): 140-7, 2007 Apr.
Article in English | MEDLINE | ID: mdl-17088045

ABSTRACT

The polymerase chain reaction (PCR) is instrumental in molecular analysis of microorganisms, allowing for the selective amplification of nucleic acids directly from clinical and environmental samples. However, the principles that allow for targeted amplification of DNA become a hindrance when attempting to simultaneously discriminate and quantify complex mixtures of homologous genes. Here we present a simple solution to the quantitative problem by separating the enrichment and amplification aspects of a conventional PCR reaction. In this assay, genes are enriched using a DNA oligonucleotide capture probe and subsequently amplified in a two-step random amplification protocol. In order to evaluate the quantitative aspects of the gene capture assay, we used real-time quantitative-PCR to measure initial and final concentrations of homologous genes from constructed mixtures of genomes. Upon sampling for the universal DNA-dependent RNA polymerase gene, rpoC, we were able to demonstrate quantitative recoveries from a mixed DNA sample despite differences in gene copy number ranging up to 4 orders of magnitude. This suggests that minority populations as low as 0.01% of the total community are represented as accurately as populations at higher abundance. These results offer new possibilities for accurately and quantitatively monitoring diverse mixtures of microorganisms.


Subject(s)
DNA/genetics , Gene Amplification , Base Sequence , DNA/chemistry , DNA Primers , DNA Probes , Polymerase Chain Reaction/methods , Sequence Homology, Nucleic Acid
4.
Biotechniques ; 34(4): 790-4, 796, 798 passim, 2003 Apr.
Article in English | MEDLINE | ID: mdl-12703304

ABSTRACT

Molecular tools based on rRNA (rrn) genes are valuable techniques for the study of microbial communities. However, the presence of operon copy number heterogeneity represents a source of systematic error in community analysis. To understand the types and magnitude of such bias, four commonly used rrn-based techniques were used to perform an in silico analysis of a hypothetical community comprised organisms from the Comprehensive Microbial Resource database. Community profiles were generated, and diversity indices were calculated for length heterogeneity PCR, automated ribosomal integenic spacer analysis, denaturing gradient gel electrophoresis, and terminal RFLP (using RsaI, MspI, and HhaI). The results demonstrate that all techniques present a quantitative bias toward organisms with higher copy numbers. In addition, techniques may underestimate diversity by grouping similar ribotypes or overestimate diversity by allowing multiple signals for one organism. The results of this study suggest that caution should be used when interpreting rrn-based community analysis techniques.


Subject(s)
DNA, Bacterial/genetics , Databases, Genetic , Gene Dosage , Gene Expression Profiling/methods , Sequence Alignment/methods , Sequence Analysis, DNA/methods , rRNA Operon/genetics , DNA, Bacterial/chemistry , Genetic Variation/genetics , Information Storage and Retrieval/methods , Models, Genetic , Models, Statistical , Reproducibility of Results , Sensitivity and Specificity
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