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A comparative analysis of spider prey spectra analyzed through the next‐generation sequencing of individual and mixed DNA samples

ABSTRACT: Abstract As one of the most abundant predators of insects in terrestrial ecosystems, spiders have long received much attention from agricultural scientists and ecologists. Do spiders have a certain controlling effect on the main insect pests of concern in farmland ecosystems? Answering this question requires us to fully understand the prey spectrum of spiders. Next‐generation sequencing (NGS) has been successfully employed to analyze spider prey spectra. However, the high sequencing costs make it difficult to analyze the prey spectrum of various spider species with large samples in a given farmland ecosystem. We performed a comparative analysis of the prey spectra of Ovia alboannulata (Araneae, Lycosidae) using NGS with individual and mixed DNA samples to demonstrate which treatment was better for determining the spider prey spectra in the field. We collected spider individuals from tea plantations, and two treatments were then carried out: (1) The DNA was extracted from the spiders individually and then sequenced separately (DESISS) and (2) the DNA was extracted from the spiders individually and then mixed and sequenced (DESIMS). The results showed that the number of prey families obtained by the DESISS treatment was approximately twice that obtained by the DESIMS treatment. Therefore, the DESIMS treatment greatly underestimated the prey composition of the spiders, although its sequencing costs were obviously lower. However, the relative abundance of prey sequences detected in the two treatments was slightly different only at the family level. Therefore, we concluded that if our purpose were to obtain the most accurate prey spectrum of the spiders, the DESISS treatment would be the best choice. However, if our purpose were to obtain only the relative abundance of prey sequences of the spiders, the DESIMS treatment would also be an option. The present study provides an important reference for choosing applicable methods to analyze the prey spectra and food web compositions of animal in ecosystems. Individual DNA sample sequencing obtains the accurate prey spectrum of spiders. Mixed DNA sample sequencing underestimates the prey spectrum of spiders. Individual and mixed DNA sample sequencing obtains almost the same relative abundance of prey sequences of spiders.

SUBMITTER: Yang T

PROVIDER: S-EPMC8571630 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundMetagenomic next-generation sequencing (mNGS) is emerging as a promising technique for pathogens detection. However, reports on the application of mNGS in mixed pulmonary infection remain scarce.MethodsFrom July 2018 to March 2019, 55 cases were enrolled in this retrospective analysis. Cases were classified into mixed pulmonary infection (36 [65.5%]) and non-mixed pulmonary infection (19 [34.5%]) according to primary diagnoses. The performances of mNGS and conventional test on mixed pulmonary infection diagnosis and pathogen identification were compared.ResultsThe sensitivity of mNGS in mixed pulmonary infection diagnosis was much higher than that of conventional test (97.2% vs 13.9%; P < 0.01), but the specificity was the opposite (63.2% vs 94.7%; P = 0.07). The positive predictive value of mNGS was 83.3% (95% CI, 68.0-92.5%), and the negative predictive value was 92.3% (95% CI, 62.1-99.6%). A total of 5 (9.1%) cases were identified as mixed pulmonary infection by both conventional tests and mNGS, however, the pathogens identification results were consistent between these two methods in only 1 (1.8%) case. In summary, the pathogens detected by mNGS in 3 (5.5%) cases were consistent with those by conventional test, and only 1 (1.8%) case was mixed pulmonary infection. According to our data, mNGS had a broader spectrum for pathogen detection than conventional tests. In particular, application of mNGS improved the diagnosis of pulmonary fungal infections. Within the 55 cases, mNGS detected and identified fungi in 31 (56.4%) cases, of which only 10 (18.2%) cases were positive for the same fungi by conventional test. The most common pathogen detected by mNGS was Human cytomegalovirus in our study, which was identified in 19 (34.5%) cases of mixed pulmonary infection. Human cytomegalovirus and Pneumocystis jirovecii, which were detected in 7 (12.7%) cases, were the most common co-pathogens in the group of mixed pulmonary infection.ConclusionsmNGS is a promising technique to detect co-pathogens in mixed pulmonary infection, with potential benefits in speed and sensitivity.Trial registration(retrospectively registered): ChiCTR1900023727. Registrated 9 JUNE 2019.

Project description:Histopathological samples are a treasure-trove of DNA for clinical research. However, the quality of DNA can vary depending on the source or extraction method applied. Thus a standardized and cost-effective workflow for the qualification of DNA preparations is essential to guarantee interlaboratory reproducible results. The qualification process consists of the quantification of double strand DNA (dsDNA) and the assessment of its suitability for downstream applications, such as high-throughput next-generation sequencing. We tested the two most frequently used instrumentations to define their role in this process: NanoDrop, based on UV spectroscopy, and Qubit 2.0, which uses fluorochromes specifically binding dsDNA. Quantitative PCR (qPCR) was used as the reference technique as it simultaneously assesses DNA concentration and suitability for PCR amplification. We used 17 genomic DNAs from 6 fresh-frozen (FF) tissues, 6 formalin-fixed paraffin-embedded (FFPE) tissues, 3 cell lines, and 2 commercial preparations. Intra- and inter-operator variability was negligible, and intra-methodology variability was minimal, while consistent inter-methodology divergences were observed. In fact, NanoDrop measured DNA concentrations higher than Qubit and its consistency with dsDNA quantification by qPCR was limited to high molecular weight DNA from FF samples and cell lines, where total DNA and dsDNA quantity virtually coincide. In partially degraded DNA from FFPE samples, only Qubit proved highly reproducible and consistent with qPCR measurements. Multiplex PCR amplifying 191 regions of 46 cancer-related genes was designated the downstream application, using 40 ng dsDNA from FFPE samples calculated by Qubit. All but one sample produced amplicon libraries suitable for next-generation sequencing. NanoDrop UV-spectrum verified contamination of the unsuccessful sample. In conclusion, as qPCR has high costs and is labor intensive, an alternative effective standard workflow for qualification of DNA preparations should include the sequential combination of NanoDrop and Qubit to assess the purity and quantity of dsDNA, respectively.

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A comparative analysis of spider prey spectra analyzed through the next‐generation sequencing of individual and mixed DNA samples

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