We performed gut content analysis of three alpine grasshopper species—Sigaus nitidus, Sigaus nivalis, and Sigaus australis—collected from three alpine regions in New Zealand, using chloroplast DNA markers. First, we assessed the taxonomic resolution of the trnL and rbcL markers using 12 gut samples from Mount Hutt. We then analysed diet composition across species, sexes, and locations using 28 samples from three sites (Mount Hutt, Craigieburn Range, and Foggy Peak) with the trnL marker. The dataset includes raw sequence files (FastQ) and amplicon sequence variants (ASVs) classified as plant taxa (Viridiplantae: Streptophyta), comprising 112 rbcL and 328 trnL ASVs. ASVs were generated using the DADA2 pipeline in QIIME2 and identified via a custom reference database using the QIIME2 BLAST+ algorithm. The trnL marker revealed higher taxonomic diversity (23 genera, 2 species), compared to 17 genera and 2 species identified using rbcL. To further refine species-level identifications, trnL sequences with 100% pairwise identity were additionally compared against the NCBI nucleotide database, with matches retained only when the species are known to occur in New Zealand.

Methods

Sampling

Adult grasshoppers of Sigaus nitidus, Sigaus nivalis, and Sigaus australis used for gut content analysis were collected from Mount Hutt (−43.5118, 171.5492; authorization number: 49878-RES), Foggy Peak (−43.294107, 171.744770), and Craigieburn Range (−43.125750, 171.686239; authorization number: 97397-FLO) in New Zealand during the summer months (February–March) between 2020 and 2023. Collections were carried out with permission from the New Zealand Department of Conservation, the New Zealand Forest Service, and local ski area operators. Grasshoppers were sampled from alpine habitats at elevations between 1340 m and 1700 m above sea level, within areas of  >100 m², to ensure access to the same range of food plants. Specimens were preserved in 99% ethanol, with an incision made in the abdomen to maximize DNA preservation in the crop and gut.

DNA extraction and amplification

DNA was extracted from crop contents of 28 adult grasshoppers using the GeneJET Plant DNA extraction Kit (Thermo Fisher Scientific) according to the manufacturer’s instructions. Polymerase chain reaction amplified two segments of the chloroplast genome, trnL intron and rbcL (Erickson et al. 2017; Kress and Erickson 2007). DNA sequencing with customised primers and sample barcodes were sequenced on a NovaSeq platform providing 250bp paired end (PE) reads for > 50,000 tags per sample.

Bioinformatic analysis

Resulting 250 PE sequences were filtered and denoised using DADA2 in the QIIME2 (version 2024.5) platform using the following command:

1.Converting data

#fastq -> qza format (QIIME2 format)

Ref: How to import data for use with QIIME 2 - Microbiome marker gene analysis with QIIME 2

qiime tools import \

--type 'SampleData[SequencesWithQuality]' \

--input-path manifest.txt \

--output-path single-end-demux.qza  \ *paired-end-demux.qza if paired-end sequences

--input-format SingleEndFastqManifestPhred33V2

 

2.DADA2 denoising

#Denoising

Ref: dada2 - Microbiome marker gene analysis with QIIME 2

qiime dada2 denoise-single \ *qiime dada2 denoise-paired if paired-end sequences

--i-demultiplexed-seqs single-end-demux.qza \

--p-trunc-len-f 0 \

--p-trunc-len-r 0 \

--o-table table.qza \

--o-representative-sequences rep-seqs.qza \

--o-denoising-stats denoising-stats.qza

 

3.Data visualization (qzv files can be visualized in https://view.qiime2.org/)

#Denoising summary: percentage and number of sequences after filtered, denoised, chimera removal (and merged if paired-end)

qiime metadata tabulate \

--m-input-file denoising-stats.qza \

--o-visualization denoising_stats

 

#ASV summary table: list of consensus sequences and sequence length statistics

qiime feature-table tabulate-seqs \

--i-data rep-seqs.qza \

--o-visualization rep-seqs

 

#ASV table: visualize the number of sequence per sample per ASV

qiime tools export

--input-path table.qza

--output-path table

 

4.Blasting ASVs against NCBI custom reference database

qiime feature-classifier classify-consensus-blast \

--i-query rep-seqs.qza \

--i-reference-reads NCBI_fasta_file.qza \ *created using Dubois et al. 2022

--i-reference-taxonomy NCBI_taxonomic_lineages.qza \ *created using Dubois et al. 2022

--o-classification classified_sequence.qza \

--o-search-results searchresults.qza

 

BLAST and custom reference database

Identification of plant taxa was performed by comparing ASVs against a global custom QIIME2 trnL reference database, created using the DB4Q2 workflow (Dubois et al. 2022). This reference was built from FASTA-format nucleotide data retrieved from the NCBI database (https://www.ncbi.nlm.nih.gov/) in September 2024, using the following Entrez text queries:

trnL:

 (viridiplantae[Organism] AND (trnL[Gene Name] OR tRNA-Leu[Title] OR (trnL-trnF[Title] AND intergenic spacer[Title]) OR trnL[Title] AND 100:500000[Sequence Length]) AND (chloroplast[Gene Name]) OR chloroplast[Title])

rbcL:

(viridiplantae[Organism] AND (rbcL[Gene Name] OR ribulose-1,5-bisphosphate carboxylase/oxygenase[Title] OR ribulose-1,5-bisphosphate carboxylase oxygenase[Title] OR rbcL[Title]) AND 100:500000[Sequence Length]) AND (chloroplast[Gene Name]) OR chloroplast[Title])

trnL ASV sequences that were not identified through the QIIME2 BLAST+ algorithm were further examined using the megablast function on the NCBI website to find the closest matches. Species-level identification was assigned only when a 100% pairwise identity match was found with plant species known to occur in New Zealand. The presence or absence of identified plant taxa in the Southern Alps was verified using the New Zealand Plant Conservation Network (https://www.nzpcn.org.nz/) and iNaturalist (https://www.inaturalist.org/).

References

Dubois B, Debode F, Hautier L, et al (2022) A detailed workflow to develop QIIME2-formatted reference databases for taxonomic analysis of DNA metabarcoding data. BMC Genomic Data 23:1–14. https://doi.org/10.1186/s12863-022-01067-5

Erickson DL, Reed E, Ramachandran P, et al (2017) Reconstructing a herbivore’s diet using a novel rbcL DNA mini-barcode for plants. AoB Plants 9:. https://doi.org/10.1093/aobpla/plx015

Kress WJ, Erickson DL (2007) A two-locus global DNA barcode for land plants: the coding rbcL gene complements the non-coding trnH-psbA spacer region. PLoS One 2:. https://doi.org/10.1371/journal.pone.0000508