RSI Research Seminar

Join us every other Monday at noon for lunch and a 30-minute research talk, presented by Resnick Sustainability Institute Graduate Fellows and Caltech researchers funded by the Resnick Sustainability Institute. To see the full schedule of speakers, visit the RSI Research Seminar web page. Seminars currently take place in a hybrid format, both in-person (Jorgensen building first-floor conference room) and via Zoom. For more information and to get the Zoom login info, please reach out to ramonae@caltech.edu

Development and Evaluation of a Quantitative Sequencing Method for Absolute Quantification of Fungal Communities

Fungi are instrumental players in many ecosystems, mediating significant environmental processes such as nutrient cycling, plant productivity and carbon fixation. Next-Generation DNA Sequencing (NGS) is a prominent genetic tool used to interrogate fungal communities ("mycobiome"). However, a major drawback to using NGS is that it only produces compositional data, that is, mycobiomes are described in terms of percentages of a whole (relative abundances). NGS alone cannot measure the absolute numbers (absolute abundance) of fungal taxa, which limits the field's ability to accurately profile the composition of fungal communities and measure shifts in community composition in response to external factors such as disease. Yet, when using relative abundances, the reasons for shifts in relative abundances of a fungal community are ambiguous. For example, an increase in the relative abundance of a single taxon can be both caused by growth of that taxon or reduction of all other taxa. This ambiguity can be resolved if absolute abundances are measured.

To address the ambiguity in community shifts introduced from using relative abundances, our lab has previously developed "Quantitative Sequencing", a method that combines highly-sensitive digital droplet PCR (ddPCR) with NGS to measure absolute abundances of bacterial taxa. However, no analogous approach currently exists for fungi due to multiple reasons, including a lack of consensus on a universal fungal barcode and the large variation in barcode copy numbers.

Here, we describe the development of a dual-barcode fungal quantitative sequencing "Fungal Quant-Seq" pipeline. Using in silico PCR, digital PCR, and NGS, we evaluate and modify two barcodes, ITS and TEF, used in conjunction, to broaden fungal taxonomic identification and improve specificity. We find that although ITS is selective towards fungi, published primers for TEF amplify human DNA, limiting their utility in samples with large amounts of human DNA, such as agricultural samples with human DNA contamination. We modify the published primers for TEF to improve their selectivity and show that the modified primers nearly eliminate amplification of human DNA. Next, using NGS and the genus Candida as an example, we show that both barcodes can taxonomically distinguish closely related fungi in addition to detecting 90% of taxa in a commercial mycobiome standard. Finally, using in silico PCR, we propose additional modifications of the TEF primers that further improve the coverage of fungal organisms by over a factor of 2.

"Fungal Quant-Seq" improves on previous fungal barcoding tools and enables the absolute quantification of a broad range of fungal taxa to monitor shifts in the environmental mycobiome.