Suppr超能文献

在微生物组研究中实施高通量昆虫条形码技术:非破坏性DNA提取对微生物组重建的影响。

Implementing high-throughput insect barcoding in microbiome studies: impact of non-destructive DNA extraction on microbiome reconstruction.

作者信息

Andriienko Veronika, Buczek Mateusz, Meier Rudolf, Srivathsan Amrita, Łukasik Piotr, Kolasa Michał R

机构信息

Institute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland.

Institute of Zoology and Biomedical Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland.

出版信息

bioRxiv. 2024 Apr 30:2024.04.30.591865. doi: 10.1101/2024.04.30.591865.

Abstract

BACKGROUND

Symbiotic relationships with diverse microorganisms are crucial for many aspects of insect biology. However, while our understanding of insect taxonomic diversity and the distribution of insect species in natural communities is limited, we know much less about their microbiota. In the era of rapid biodiversity declines, as researchers increasingly turn towards DNA-based monitoring, developing and broadly implementing approaches for high-throughput and cost-effective characterization of both insect and insect-associated microbial diversity is essential. We need to verify whether approaches such as high-throughput barcoding, a powerful tool for identifying wild insects, would permit subsequent microbiota reconstruction in these specimens.

METHODS

High-throughput barcoding ("megabarcoding") methods often rely on non-destructive approaches for obtaining template DNA for PCR amplification by leaching DNA out of insect specimens using alkaline buffers such as HotSHOT. This study investigated the impact of HotSHOT on microbial abundance estimates and the reconstructed bacterial community profiles. We addressed this question by comparing quantitative 16S rRNA amplicon sequencing data for HotSHOT-treated or untreated specimens of 16 insect species representing six orders and selected based on the expectation of limited variation among individuals.

RESULTS

We find that in 13 species, the treatment significantly reduced microbial abundance estimates, corresponding to an estimated 15-fold decrease in amplifiable 16S rRNA template on average. On the other hand, HotSHOT pre-treatment had a limited effect on microbial community composition. The reconstructed presence of abundant bacteria with known significant effects was not affected. On the other hand, we observed changes in the presence of low-abundance microbes, those close to the reliable detection threshold. Alpha and beta diversity analyses showed compositional differences in only a few species.

CONCLUSION

Our results indicate that HotSHOT pre-treated specimens remain suitable for microbial community composition reconstruction, even if abundance may be hard to estimate. These results indicate that we can cost-effectively combine barcoding with the study of microbiota across wild insect communities. Thus, the voucher specimens obtained using megabarcoding studies targeted at characterizing insect communities can be used for microbiome characterizations. This can substantially aid in speeding up the accumulation of knowledge on the microbiomes of abundant and hyperdiverse insect species.

摘要

背景

与多种微生物的共生关系对昆虫生物学的许多方面都至关重要。然而,尽管我们对昆虫分类多样性以及自然群落中昆虫物种分布的了解有限,但我们对它们的微生物群了解得更少。在生物多样性迅速下降的时代,随着研究人员越来越多地转向基于DNA的监测,开发并广泛应用高通量且经济高效的方法来表征昆虫及其相关微生物的多样性至关重要。我们需要验证诸如高通量条形码技术(一种识别野生昆虫的强大工具)等方法是否能在这些标本中进行后续的微生物群重建。

方法

高通量条形码技术(“宏条形码技术”)方法通常依赖于非破坏性方法,通过使用碱性缓冲液(如HotSHOT)从昆虫标本中浸出DNA来获取用于PCR扩增的模板DNA。本研究调查了HotSHOT对微生物丰度估计和重建细菌群落图谱的影响。我们通过比较16种昆虫(代表六个目,基于个体间变异有限的预期进行选择)经HotSHOT处理或未处理标本的定量16S rRNA扩增子测序数据来解决这个问题。

结果

我们发现,在13个物种中,该处理显著降低了微生物丰度估计值,平均而言,可扩增的16S rRNA模板估计减少了15倍。另一方面,HotSHOT预处理对微生物群落组成的影响有限。已知具有显著影响的丰富细菌的重建存在情况未受影响。另一方面,我们观察到低丰度微生物(那些接近可靠检测阈值的微生物)的存在情况发生了变化。α和β多样性分析表明,只有少数物种存在组成差异。

结论

我们的结果表明,即使丰度可能难以估计,经HotSHOT预处理的标本仍适用于微生物群落组成重建。这些结果表明,我们可以经济高效地将条形码技术与野生昆虫群落微生物群的研究结合起来。因此,使用旨在表征昆虫群落的宏条形码技术研究获得的凭证标本可用于微生物组表征。这可极大地有助于加快对丰富且高度多样的昆虫物种微生物组知识的积累。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/360b/11092579/ff4f0c0099cc/nihpp-2024.04.30.591865v1-f0001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验