Exploring near-infrared spectroscopy and hyperspectral imaging as novel characterization methods for anaerobic gut fungi.

FEMS microbes Pub Date : 2024-09-10 eCollection Date: 2024-01-01 DOI:10.1093/femsmc/xtae025
Markus Neurauter, Julia M Vinzelj, Sophia F A Strobl, Christoph Kappacher, Tobias Schlappack, Jovan Badzoka, Matthias Rainer, Christian W Huck, Sabine M Podmirseg
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Abstract

Neocallimastigomycota are a phylum of anaerobic gut fungi (AGF) that inhabit the gastrointestinal tract of herbivores and play a pivotal role in plant matter degradation. Their identification and characterization with marker gene regions has long been hampered due to the high inter- and intraspecies length variability in the commonly used fungal marker gene region internal transcribed spacer (ITS). While recent research has improved methodology (i.e. switch to LSU D2 as marker region), molecular methods will always introduce bias through nucleic acid extraction or PCR amplification. Here, near-infrared spectroscopy (NIRS) and hyperspectral imaging (HSI) are introduced as two nucleic acid sequence-independent tools for the characterization and identification of AGF strains. We present a proof-of-concept for both, achieving an independent prediction accuracy of above 95% for models based on discriminant analysis trained with samples of three different genera. We further demonstrated the robustness of the NIRS model by testing it on cultures of different growth times. Overall, NIRS provides a simple, reliable, and nondestructive approach for AGF classification, independent of molecular approaches. The HSI method provides further advantages by requiring less biomass and adding spatial information, a valuable feature if this method is extended to mixed cultures or environmental samples in the future.

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探索近红外光谱和高光谱成像作为厌氧肠道真菌的新型表征方法。
新嗜水气真菌门(Neocallimastigomycota)是厌氧肠道真菌(AGF)的一个门类,栖息在食草动物的胃肠道中,在植物物质降解过程中发挥着关键作用。由于常用的真菌标记基因区域内部转录间隔区(ITS)的种间和种内长度变异很大,长期以来一直无法利用标记基因区域对它们进行鉴定和表征。虽然最近的研究改进了方法(如改用 LSU D2 作为标记区域),但分子方法总会通过核酸提取或 PCR 扩增引入偏差。本文介绍了近红外光谱(NIRS)和高光谱成像(HSI)这两种独立于核酸序列的工具,用于表征和鉴定 AGF 菌株。我们对这两种方法进行了概念验证,基于用三个不同属的样本训练的判别分析模型的独立预测准确率达到 95% 以上。通过对不同生长时间的培养物进行测试,我们进一步证明了 NIRS 模型的稳健性。总之,近红外光谱技术为 AGF 分类提供了一种简单、可靠和无损的方法,与分子方法无关。HSI 方法还具有更多优势,它对生物量的要求更低,并增加了空间信息,如果该方法将来扩展到混合培养物或环境样本,这是一个非常有价值的特点。
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CiteScore
3.30
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0.00%
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审稿时长
15 weeks
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