scholarly journals A DNA Microarray Platform Based on Direct Detection of rRNA for Characterization of Freshwater Sediment-Related Prokaryotic Communities

2006 ◽  
Vol 72 (7) ◽  
pp. 4829-4838 ◽  
Author(s):  
Jörg Peplies ◽  
Christine Lachmund ◽  
Frank Oliver Glöckner ◽  
Werner Manz

ABSTRACT A DNA microarray platform for the characterization of bacterial communities in freshwater sediments based on a heterogeneous set of 70 16S rRNA-targeted oligonucleotide probes and directly labeled environmental RNA was developed and evaluated. Application of a simple protocol for the efficient background blocking of aminosilane-coated slides resulted in an improved signal-to-noise ratio and a detection limit of 10 ng for particular 16S rRNA targets. An initial specificity test of the system using RNA from pure cultures of different phylogenetic lineages showed a fraction of false-positive signals of ∼5% after protocol optimization and a marginal loss of correct positive signals. Subsequent microarray analysis of sediment-related community RNA from four different German river sites suggested low diversity for the groups targeted but indicated distinct differences in community composition. The results were supported by parallel fluorescence in situ hybridization in combination with sensitive catalyzed reporter deposition (CARD-FISH). In comparisons of the data of different sampling sites, specific detection of populations with relative cellular abundances down to 2% as well as a correlation of microarray signal intensities and population size is suggested. Our results demonstrate that DNA microarray technology allows for the fast and efficient precharacterization of complex bacterial communities by the use of standard single-cell hybridization probes and the direct detection of environmental rRNA, also in methodological challenging habitats such as heterogeneous lotic freshwater sediments.

LWT ◽  
2021 ◽  
Vol 147 ◽  
pp. 111579
Author(s):  
Creciana M. Endres ◽  
Ícaro Maia S. Castro ◽  
Laura D. Trevisol ◽  
Juliana M. Severo ◽  
Michele B. Mann ◽  
...  

2008 ◽  
Vol 74 (16) ◽  
pp. 5068-5077 ◽  
Author(s):  
Tatsuhiko Hoshino ◽  
L. Safak Yilmaz ◽  
Daniel R. Noguera ◽  
Holger Daims ◽  
Michael Wagner

ABSTRACT Fluorescence in situ hybridization (FISH) with rRNA-targeted oligonucleotide probes is a method that is widely used to detect and quantify microorganisms in environmental samples and medical specimens by fluorescence microscopy. Difficulties with FISH arise if the rRNA content of the probe target organisms is low, causing dim fluorescence signals that are not detectable against the background fluorescence. This limitation is ameliorated by technical modifications such as catalyzed reporter deposition (CARD)-FISH, but the minimal numbers of rRNA copies needed to obtain a visible signal of a microbial cell after FISH or CARD-FISH have not been determined previously. In this study, a novel competitive FISH approach was developed and used to determine, based on a thermodynamic model of probe competition, the numbers of 16S rRNA copies per cell required to detect bacteria by FISH and CARD-FISH with oligonucleotide probes in mixed pure cultures and in activated sludge. The detection limits of conventional FISH with Cy3-labeled probe EUB338-I were found to be 370 ± 45 16S rRNA molecules per cell for Escherichia coli hybridized on glass microscope slides and 1,400 ± 170 16S rRNA copies per E. coli cell in activated sludge. For CARD-FISH the values ranged from 8.9 ± 1.5 to 14 ± 2 and from 36 ± 6 to 54 ± 7 16S rRNA molecules per cell, respectively, indicating that the sensitivity of CARD-FISH was 26- to 41-fold higher than that of conventional FISH. These results suggest that optimized FISH protocols using oligonucleotide probes could be suitable for more recent applications of FISH (for example, to detect mRNA in situ in microbial cells).


2019 ◽  
Author(s):  
Creciana Maria Endres ◽  
Ícaro Maia Santos de Castro ◽  
Laura Delpino Trevisol ◽  
Michele Bertoni Mann ◽  
Ana Paula Muterle Varela ◽  
...  

AbstractThe production of sheep’s milk cheese has grown in recent years since it is a high value-added product with excellent properties. As such, it is necessary to provide data on the microbiota and organoleptic characteristics of this product, as well as the influence of these microorganisms on public health. Thus, the aim of the present study was to characterize the microbial community of different types of sheep cheeses using high-throughput sequencing of the 16S rRNA gene. The study was conducted with four groups of cheese: colonial, fresh, feta, and pecorino (n = 5 samples per group). The high-throughput 16S rRNA amplicon sequencing revealed 55 operational taxonomic units in the 20 samples, representing 9 genera of the two bacterial phyla Firmicutes and Proteobacteria. The predominant genera in the samples were Streptococcus and Lactobacillus. When evaluating alpha diversity by the indexes of Simpson, Chao1, Shannon, and Skew no significant differences were observed between the groups. Evaluating of the beta diversity using Bray-Curtis dissimilarity, the group of colonial cheeses presented a significant difference when compared to the feta (q = 0.030) and pecorino groups (q = 0.030). Additionally, the fresh group differed from the pecorino group (q = 0.030). The unweighted Unifrac distance suggests that the colonial cheese group differed from the others. Moreover, the feta cheese group differed from the fresh group. The distance-weighted Unifrac suggests that no significance exists between the groups. According to this information, the microbiota characterization of these cheese groups was useful in demonstrating the bacterial communities belonging to each group, its effects on processing, elaboration, maturation, and public health.


2012 ◽  
Vol 155 (1) ◽  
pp. 72-80 ◽  
Author(s):  
Meiju Li ◽  
Mi Zhou ◽  
Elizabeth Adamowicz ◽  
John A. Basarab ◽  
Le Luo Guan

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Daniela Numberger ◽  
Lars Ganzert ◽  
Luca Zoccarato ◽  
Kristin Mühldorfer ◽  
Sascha Sauer ◽  
...  

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250401
Author(s):  
Pedro E. Romero ◽  
Erika Calla-Quispe ◽  
Camila Castillo-Vilcahuaman ◽  
Mateo Yokoo ◽  
Hammerly Lino Fuentes-Rivera ◽  
...  

The Rimac river is the main source of water for Lima, Peru’s capital megacity. The river is constantly affected by different types of contamination including mine tailings in the Andes and urban sewage in the metropolitan area. In this work, we aim to produce the first characterization of aquatic bacterial communities in the Rimac river using a 16S rRNA metabarcoding approach which would be useful to identify bacterial diversity and potential understudied pathogens. We report a lower diversity in bacterial communities from the Lower Rimac (Metropolitan zone) in comparison to other sub-basins. Samples were generally grouped according to their geographical location. Bacterial classes Alphaproteobacteria, Bacteroidia, Campylobacteria, Fusobacteriia, and Gammaproteobacteria were the most frequent along the river. Arcobacter cryaerophilus (Campylobacteria) was the most frequent species in the Lower Rimac while Flavobacterium succinicans (Bacteroidia) and Hypnocyclicus (Fusobacteriia) were the most predominant in the Upper Rimac. Predicted metabolic functions in the microbiota include bacterial motility and quorum sensing. Additional metabolomic analyses showed the presence of some insecticides and herbicides in the Parac-Upper Rimac and Santa Eulalia-Parac sub-basins. The dominance in the Metropolitan area of Arcobacter cryaerophilus, an emergent pathogen associated with fecal contamination and antibiotic multiresistance, that is not usually reported in traditional microbiological quality assessments, highlights the necessity to apply next-generation sequencing tools to improve pathogen surveillance. We believe that our study will encourage the integration of omics sciences in Peru and its application on current environmental and public health issues.


2020 ◽  
Vol 143 ◽  
pp. 104115 ◽  
Author(s):  
Abbas Maleki ◽  
Maryam Zamirnasta ◽  
Morovat Taherikalani ◽  
Iraj Pakzad ◽  
Jasem Mohammadi ◽  
...  

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