Conventional assessments of ecosystem sample composition are based on morphology-based or DNA barcode identification of individuals. Both approaches are costly and time-consuming, especially when applied to the large number of specimens and taxa commonly included in ecological investigations. Next-generation sequencing approaches can overcome the bottleneck of individual specimen isolation and identification by simultaneously sequencing specimens of all taxa in a bulk mixture. Here we apply multiple parallel amplification primers, multiple DNA barcode markers, 454-pyrosequencing, and Illumina MiSeq sequencing to the same sample to maximize recovery of the arthropod macrobiome and the bacterial and other microbial microbiome of a bulk arthropod sample. We validate this method with a complex sample containing 1,066 morphologically distinguishable arthropods from a tropical terrestrial ecosystem with high taxonomic diversity. Multiamplicon next-generation DNA barcoding was able to recover sequences corresponding to 91% of the distinguishable individuals in a bulk environmental sample, as well as many species present as undistinguishable tissue. 454-pyrosequencing was able to recover 10 more families of arthropods and 30 more species than did conventional Sanger sequencing of each individual specimen. The use of other loci (16S and 18S ribosomal DNA gene regions) also added the detection of species of microbes associated with these terrestrial arthropods. This method greatly decreases the time and money necessary to perform DNA-based comparisons of biodiversity among ecosystem samples. This methodology opens the door to much cheaper and increased capacity for ecological and evolutionary studies applicable to a wide range of socio-economic issues, as well as a basic understanding of how the world works.
Ancient human remains of paleopathological interest typically contain highly degraded DNA in which pathogenic taxa are often minority components, making sequence-based metagenomic characterization costly. Microarrays may hold a potential solution to these challenges, offering a rapid, affordable, and highly informative snapshot of microbial diversity in complex samples without the lengthy analysis and/or high cost associated with high-throughput sequencing. Their versatility is well established for modern clinical specimens, but they have yet to be applied to ancient remains. Here we report bacterial profiles of archaeological and historical human remains using the Lawrence Livermore Microbial Detection Array (LLMDA). The array successfully identified previously-verified bacterial human pathogens, including Vibrio cholerae (cholera) in a 19th century intestinal specimen and Yersinia pestis ("Black Death" plague) in a medieval tooth, which represented only minute fractions (0.03% and 0.08% alignable high-throughput shotgun sequencing reads) of their respective DNA content. This demonstrates that the LLMDA can identify primary and/or co-infecting bacterial pathogens in ancient samples, thereby serving as a rapid and inexpensive paleopathological screening tool to study health across both space and time.
The Deepwater Horizon oil spill led to the severe contamination of coastal environments in the Gulf of Mexico. A previous study detailed coastal saltmarsh erosion and recovery in a number of oil-impacted and nonimpacted reference sites in Barataria Bay, Louisiana over the first 18 months after the spill. Concentrations of alkanes and polyaromatic hydrocarbons (PAHs) at oil-impacted sites significantly decreased over this time period. Here, a combination of DNA, lipid, and isotopic approaches confirm that microbial biodegradation was contributing to the observed petroleum mass loss. Natural abundance (14)C analysis of microbial phospholipid fatty acids (PLFA) reveals that petroleum-derived carbon was a primary carbon source for microbial communities at impacted sites several months following oil intrusion when the highest concentrations of oil were present. Also at this time, microbial community analysis suggests that community structure of all three domains has shifted with the intrusion of oil. These results suggest that Gulf of Mexico marsh sediments have considerable biodegradation potential and that natural attenuation is playing a role in impacted sites.
DNA sequencing of ancient permafrost samples can be used to reconstruct past plant, animal and bacterial communities. In this study, we assess the small-scale reproducibility of taxonomic composition obtained from sequencing four molecular markers (mitochondrial 12S ribosomal DNA (rDNA), prokaryote 16S rDNA, mitochondrial cox1 and chloroplast trnL intron) from two soil cores sampled 10 cm apart. In addition, sequenced control reactions were used to produce a contaminant library that was used to filter similar sequences from sample libraries. Contaminant filtering resulted in the removal of 1% of reads or 0.3% of operational taxonomic units. We found similar richness, overlap, abundance and taxonomic diversity from the 12S, 16S and trnL markers from each soil core. Jaccard dissimilarity across the two soil cores was highest for metazoan taxa detected by the 12S and cox1 markers. Taxonomic community distances were similar for each marker across the two soil cores when the chi-squared metric was used; however, the 12S and cox1 markers did not cluster well when the Goodall similarity metric was used. A comparison of plant macrofossil vs. read abundance corroborates previous work that suggests eastern Beringia was dominated by grasses and forbs during cold stages of the Pleistocene, a habitat that is restricted to isolated sites in the present-day Yukon.
• The internal transcribed spacer (ITS) of the nuclear ribosomal DNA region is a widely used species marker for plants and fungi. Recent metagenomic studies using next-generation sequencing, however, generate only partial ITS sequences. Here we compare the performance of partial and full-length ITS sequences with several classification methods. • We compiled a full-length ITS data set and created short fragments to simulate the read lengths commonly recovered from current next-generation sequencing platforms. We compared recovery, erroneous recovery, and coverage for the following methods: best BLAST hit classification, MEGAN classification, and automated phylogenetic assignment using the Statistical Assignment Program (SAP). • We found that summarizing results with more inclusive taxonomic ranks increased recovery and reduced erroneous recovery. The similarity-based methods BLAST and MEGAN performed consistently across most fragment lengths. Using a phylogeny-based method, SAP runs with queries 400 bp or longer worked best. Overall, BLAST had the highest recovery rates and MEGAN had the lowest erroneous recovery rates. • A high-throughput ITS classification method should be selected, taking into consideration read length, an acceptable tradeoff between maximizing the total number of classifications and minimizing the number of erroneous classifications, and the computational speed of the assignment method.
The Blastocladiomycota is a recently described phylum of ecologically diverse zoosporic fungi whose species have not been thoroughly sampled and placed within a molecular phylogeny. In this study, we investigated the phylogeny of the Blastocladiomycota based on ribosomal DNA sequences from strains identified by traditional morphological and ultrastructural characters. Our results support the monophyly of the Coelomomycetaceae and Physodermataceae but the Blastocladiaceae and Catenariaceae are paraphyletic or polyphyletic. The data support two clades within Allomyces with strains identified as Allomyces arbusculus in both clades, suggesting that species concepts in Allomyces are in need of revision. A clade of Catenaria species isolated from midge larvae group separately from other Catenaria species, suggesting that this genus may need revision. In the Physodermataceae, Urophlyctis species cluster with a clade of Physoderma species. The algal parasite Paraphysoderma sedebokerensis nom. prov. clusters sister to other taxa in the Physodermataceae. Catenomyces persicinus, which has been classified in the Catenariaceae, groups with the Chytridiomycota rather than Blastocladiomycota. The rDNA operon seems to be suitable for classification within the Blastocladiomycota and distinguishes among genera; however, this region alone is not suitable to determine the position of the Blastocladiomycota among other basal fungal phyla with statistical support. A focused effort to find and isolate, or directly amplify DNA from additional taxa will be necessary to evaluate diversity in this phylum. We provide this rDNA phylogeny as a preliminary framework to guide further taxon and gene sampling and to facilitate future ecological, morphological, and systematic studies.
The Rhizopus oryzae species complex is a group of zygomycete fungi that are common, cosmopolitan saprotrophs. Some strains are used beneficially for production of Asian fermented foods but they can also act as opportunistic human pathogens. Although R. oryzae reportedly has a heterothallic (+/-) mating system, most strains have not been observed to undergo sexual reproduction and the genetic structure of its mating locus has not been characterized. Here we report on the mating behavior and genetic structure of the mating locus for 54 isolates of the R. oryzae complex. All 54 strains have a mating locus similar in overall organization to Phycomyces blakesleeanus and Mucor circinelloides (Mucoromycotina, Zygomycota). In all of these fungi, the minus (-) allele features the SexM high mobility group (HMG) gene flanked by an RNA helicase gene and a TP transporter gene (TPT). Within the R. oryzae complex, the plus (+) mating allele includes an inserted region that codes for a BTB/POZ domain gene and the SexP HMG gene. Phylogenetic analyses of multiple genes, including the mating loci (HMG, TPT, RNA helicase), ITS1-5.8S-ITS2 rDNA, RPB2, and LDH genes, identified two distinct groups of strains. These correspond to previously described sibling species R. oryzae sensu stricto and R. delemar. Within each species, discordant gene phylogenies among multiple loci suggest an outcrossing population structure. The hypothesis of random-mating is also supported by a 50:50 ratio of plus and minus mating types in both cryptic species. When crossed with tester strains of the opposite mating type, most isolates of R. delemar failed to produce zygospores, while isolates of R. oryzae produced sterile zygospores. In spite of the reluctance of most strains to mate in vitro, the conserved sex locus structure and evidence for outcrossing suggest that a normal sexual cycle occurs in both species.
Nuclear large subunit ribosomal DNA is widely used in fungal phylogenetics and to an increasing extent also amplicon-based environmental sequencing. The relatively short reads produced by next-generation sequencing, however, makes primer choice and sequence error important variables for obtaining accurate taxonomic classifications. In this simulation study we tested the performance of three classification methods: 1) a similarity-based method (BLAST + Metagenomic Analyzer, MEGAN); 2) a composition-based method (Ribosomal Database Project naïve bayesian classifier, NBC); and, 3) a phylogeny-based method (Statistical Assignment Package, SAP). We also tested the effects of sequence length, primer choice, and sequence error on classification accuracy and perceived community composition. Using a leave-one-out cross validation approach, results for classifications to the genus rank were as follows: BLAST + MEGAN had the lowest error rate and was particularly robust to sequence error; SAP accuracy was highest when long LSU query sequences were classified; and, NBC runs significantly faster than the other tested methods. All methods performed poorly with the shortest 50-100 bp sequences. Increasing simulated sequence error reduced classification accuracy. Community shifts were detected due to sequence error and primer selection even though there was no change in the underlying community composition. Short read datasets from individual primers, as well as pooled datasets, appear to only approximate the true community composition. We hope this work informs investigators of some of the factors that affect the quality and interpretation of their environmental gene surveys.
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