Project description:Environmental DNA (eDNA) techniques are gaining attention as cost-effective, non-invasive strategies for acquiring information on fish and other aquatic organisms from water samples. Currently, eDNA approaches are used to detect specific fish species and determine fish community diversity. Various protocols used with eDNA methods for aquatic organism detection have been reported in different eDNA studies, but there are no general recommendations for fish detection. Herein, we reviewed 168 papers to supplement and highlight the key criteria for each step of eDNA technology in fish detection and provide general suggestions for eliminating detection errors. Although there is no unified recommendation for the application of diverse eDNA in detecting fish species, in most cases, 1 or 2 L surface water collection and eDNA capture on 0.7-?m glass fiber filters followed by extraction with a DNeasy Blood and Tissue Kit or PowerWater DNA Isolation Kit are useful for obtaining high-quality eDNA. Subsequently, species-specific quantitative polymerase chain reaction (qPCR) assays based on mitochondrial cytochrome b gene markers or eDNA metabarcoding based on both 12S and 16S rRNA markers via high-throughput sequencing can effectively detect target DNA or estimate species richness. Furthermore, detection errors can be minimized by mitigating contamination, negative control, PCR replication, and using multiple genetic markers. Our aim is to provide a useful strategy for fish eDNA technology that can be applied by researchers, advisors, and managers.
Project description:Molecular analysis of environmental DNA (eDNA) can be used to assess vertebrate biodiversity in aquatic systems, but limited work has applied eDNA technologies to marine waters. Further, there is limited understanding of the spatial distribution of vertebrate eDNA in marine waters. Here, we use an eDNA metabarcoding approach to target and amplify a hypervariable region of the mitochondrial 12S rRNA gene to characterize vertebrate communities at 10 oceanographic stations spanning 45 km within the Monterey Bay National Marine Sanctuary (MBNMS). In this study, we collected three biological replicates of small volume water samples (1 L) at 2 depths at each of the 10 stations. We amplified fish mitochondrial DNA using a universal primer set. We obtained 5,644,299 high quality Illumina sequence reads from the environmental samples. The sequence reads were annotated to the lowest taxonomic assignment using a bioinformatics pipeline. The eDNA survey identified, to the lowest taxonomic rank, 7 families, 3 subfamilies, 10 genera, and 72 species of vertebrates at the study sites. These 92 distinct taxa come from 33 unique marine vertebrate families. We observed significantly different vertebrate community composition between sampling depths (0 m and 20/40 m deep) across all stations and significantly different communities at stations located on the continental shelf (<200 m bottom depth) versus in the deeper waters of the canyons of Monterey Bay (>200 m bottom depth). All but 1 family identified using eDNA metabarcoding is known to occur in MBNMS. The study informs the implementation of eDNA metabarcoding for vertebrate biomonitoring.
Project description:Analysis of 16S rRNA genes is important for phylogenetic classification of known and novel bacterial genera and species and for detection of uncultivable bacteria. PCR amplification of 16S rRNA genes with universal primers produces a mixture of amplicons from all rRNA operons in the genome, and the sequence data generally yield a consensus sequence. Here we describe valuable data that are missing from consensus sequences, variable effects on sequence data generated from nonidentical 16S rRNA amplicons, and the appearance of data displayed by different software programs. These effects are illustrated by analysis of 16S rRNA genes from 50 strains of the Bacillus cereus group, i.e., Bacillus anthracis, Bacillus cereus, Bacillus mycoides, and Bacillus thuringiensis These species have 11 to 14 rRNA operons, and sequence variability occurs among the multiple 16S rRNA genes. A single nucleotide polymorphism (SNP) previously reported to be specific to B. anthracis was detected in some B. cereus strains. However, a different SNP, at position 1139, was identified as being specific to B. anthracis, which is a biothreat agent with high mortality rates. Compared with visual analysis of the electropherograms, basecaller software frequently missed gene sequence variations or could not identify variant bases due to overlapping basecalls. Accurate detection of 16S rRNA gene sequences that include intragenomic variations can improve discrimination among closely related species, improve the utility of 16S rRNA databases, and facilitate rapid bacterial identification by targeted DNA sequence analysis or by whole-genome sequencing performed by clinical or reference laboratories.
Project description:BACKGROUND: Campylobacter is the most commonly reported bacterial cause of enteritis in humans in the EU Member States and other industrialized countries. One significant source of infection is broilers and consumption of undercooked broiler meat. Campylobacter jejuni is the Campylobacter sp. predominantly found in infected humans and colonized broilers. Sequence analysis of the 16S rRNA gene is very useful for identification of bacteria to genus and species level. The objectives in this study were to determine the degree of intraspecific variation in the 16S rRNA genes of C. jejuni and C. coli and to determine whether the 16S rRNA sequence types correlated with genotypes generated by PFGE analysis of SmaI restricted genomic DNA of the strains. METHODS: The 16S rRNA genes of 45 strains of C. jejuni and two C. coli strains isolated from broilers were sequenced and compared with 16S rRNA sequences retrieved from the Ribosomal Database Project or GenBank. The strains were also genotyped by PFGE after digestion with SmaI. RESULTS: Sequence analyses of the 16S rRNA genes revealed nine sequence types of the Campylobacter strains and the similarities between the different sequence types were in the range 99.6-99.9%. The number of nucleotide substitutions varied between one and six among the nine 16S rRNA sequence types. One of the nine 16S rRNA sequence profiles was common to 12 of the strains from our study and two of these were identified as Campylobacter coli by PCR/REA. The other 10 strains were identified as Campylobacter jejuni. Five of the nine sequence types were also found among the Campylobacter sequences deposited in GenBank. The three 16S rRNA genes in the analysed strains were identical within each individual strain for all 47 strains. CONCLUSION: C. jejuni and C. coli seem to lack polymorphisms in their 16S rRNA gene, but phylogenetic analysis based on 16S rRNA sequences was not always sufficient for differentiation between C. jejuni and C. coli. The strains were grouped in two major clusters according to 16S rRNA, one cluster with only C. jejuni and the other with both C. jejuni and C. coli. Genotyping of the 47 strains by PFGE after digestion with SmaI resulted in 22 subtypes. A potential correlation was found between the SmaI profiles and the 16S rRNA sequences, as a certain SmaI type only appeared in one of the two major phylogenetic groups.
Project description:BACKGROUND:There is an increasing demand for rapid biodiversity assessment tools that have a broad taxonomic coverage. Here we evaluate a suite of environmental DNA (eDNA) markers coupled with next generation sequencing (NGS) that span the tree of life, comparing them with traditional biodiversity monitoring tools within ten 20×20 meter plots along a 700 meter elevational gradient. RESULTS:From six eDNA datasets (one from each of 16S, 18S, ITS, trnL and two from COI) we identified sequences from 109 NCBI taxonomy-defined phyla or equivalent, ranging from 31 to 60 for a given eDNA marker. Estimates of alpha and gamma diversity were sensitive to the number of sequence reads, whereas beta diversity estimates were less sensitive. The average within-plot beta diversity was lower than between plots for all markers. The soil beta diversity of COI and 18S markers showed the strongest response to the elevational variation of the eDNA markers (COI: r=0.49, p<0.001; 18S: r=0.48, p<0.001). Furthermore pairwise beta diversities for these two markers were strongly correlated with those calculated from traditional vegetation and invertebrate biodiversity measures. CONCLUSIONS:Using a soil-based eDNA approach, we demonstrate that standard phylogenetic markers are capable of recovering sequences from a broad diversity of eukaryotes, in addition to prokaryotes by 16S. The COI and 18S eDNA markers are the best proxies for aboveground biodiversity based on the high correlation between the pairwise beta diversities of these markers and those obtained using traditional methods.
Project description:Phormium yellow leaf (PYL) phytoplasma causes a lethal disease of the monocotyledon, New Zealand flax (Phormium tenax). The 16S rRNA genes of PYL phytoplasma were amplified from infected flax by PCR and cloned, and the nucleotide sequences were determined. DNA sequencing and Southern hybridization analysis of genomic DNA indicated the presence of two copies of the 16S rRNA gene. The two 16S rRNA genes exhibited sequence heterogeneity in 4 nucleotide positions and could be distinguished by the restriction enzymes BpmI and BsrI. This is the first record in which sequence heterogeneity in the 16S rRNA genes of a phytoplasma has been determined by sequence analysis. A phylogenetic tree based on 16S rRNA gene sequences showed that PYL phytoplasma is most closely related to the stolbur and German grapevine yellows phytoplasmas, which form the stolbur subgroup of the aster yellows group. This phylogenetic position of PYL phytoplasma was supported by 16S/23S spacer region sequence data.
Project description:The traditional identification of bacteria on the basis of phenotypic characteristics is generally not as accurate as identification based on genotypic methods. Comparison of the bacterial 16S rRNA gene sequence has emerged as a preferred genetic technique. 16S rRNA gene sequence analysis can better identify poorly described, rarely isolated, or phenotypically aberrant strains, can be routinely used for identification of mycobacteria, and can lead to the recognition of novel pathogens and noncultured bacteria. Problems remain in that the sequences in some databases are not accurate, there is no consensus quantitative definition of genus or species based on 16S rRNA gene sequence data, the proliferation of species names based on minimal genetic and phenotypic differences raises communication difficulties, and microheterogeneity in 16S rRNA gene sequence within a species is common. Despite its accuracy, 16S rRNA gene sequence analysis lacks widespread use beyond the large and reference laboratories because of technical and cost considerations. Thus, a future challenge is to translate information from 16S rRNA gene sequencing into convenient biochemical testing schemes, making the accuracy of the genotypic identification available to the smaller and routine clinical microbiology laboratories.
Project description:A bacterial strain Bz02 was isolated from a water sample collected from river Gomti at the Indian city of Lucknow. We characterized the strain using 16S rRNA sequence. Phylogenetic analysis showed that the strain formed a monophyletic clade with members of the genus Comamonas. The closest phylogenetic relative was Comamonas testosteroni with 95% 16S rRNA gene sequence similarity. It is proposed that the identified strain Bz02 be assigned as the type strain of a species of the genus Comamonas (Comamonas sp Bz02) based on 16S rRNA gene sequence search in Ribosomal Database Project, small subunit rRNA and large subunit rRNA databases together with the phylogenetic tree analysis. The sequence is deposted in GenBank with the accession number FJ211417.
Project description:Terrestrial arthropods comprise the most species-rich communities on Earth, and grassland flowers provide resources for hundreds of thousands of arthropod species. Diverse grassland ecosystems worldwide are threatened by various types of environmental change, which has led to decline in arthropod diversity. At the same time, monitoring grassland arthropod diversity is time-consuming and strictly dependent on declining taxonomic expertise. Environmental DNA (eDNA) metabarcoding of complex samples has demonstrated that information on species compositions can be efficiently and non-invasively obtained. Here, we test the potential of wild flowers as a novel source of arthropod eDNA. We performed eDNA metabarcoding of flowers from several different plant species using two sets of generic primers, targeting the mitochondrial genes 16S rRNA and COI. Our results show that terrestrial arthropod species leave traces of DNA on the flowers that they interact with. We obtained eDNA from at least 135 arthropod species in 67 families and 14 orders, together representing diverse ecological groups including pollinators, parasitoids, gall inducers, predators, and phytophagous species. Arthropod communities clustered together according to plant species. Our data also indicate that this experiment was not exhaustive, and that an even higher arthropod richness could be obtained using this eDNA approach. Overall, our results demonstrate that it is possible to obtain information on diverse communities of insects and other terrestrial arthropods from eDNA metabarcoding of wild flowers. This novel source of eDNA represents a vast potential for addressing fundamental research questions in ecology, obtaining data on cryptic and unknown species of plant-associated arthropods, as well as applied research on pest management or conservation of endangered species such as wild pollinators.