Data from: Comparison of rapid biodiversity assessment of meiobenthos using MALDI-TOF MS and metabarcoding

Nowadays, most biodiversity assessments involving meiofauna are mainly
carried out using very time-consuming, specimen-wise morphological
identifications, which demands comprehensive taxonomic knowledge. Animals
have to be examined for minor differences of setae compositions, mouthpart
morphology or number of segments for various extremities. DNA-based
methods such as metabarcoding as well as recently emerged rapid analyses
using MALDI-TOF mass spectrometry to identify specimens based on a
proteome fingerprint could vastly accelerate the process of specimen
identification in biodiversity assessments. However, these techniques
depend on reference libraries to connect collected data to morphologically
described species. In this study the success rate of both approaches have
been tested based on reference libraries constructed using part of the
samples from a new study area to identify unknown samples. Using MALDI-TOF
MS we found, that species which do not exist in an incomplete mass spectra
reference library only have minor impact on the results, when employing a
post hoc test for Random Forest classifications. This test reveals
specimens that demand morphological re-examination for the final species
assignment. Metabarcoding however strongly demands a rich reference
library to provide correct MOTU assessments in congruence with
morphological determination. Nevertheless, with a complete library and a
suitable data transformation [herein log(x + 1)], the number of reads per
MOTU reflects relative species abundances in metabarcoding inference. The
results of this study facilitate specimen identification by using MALDI-TOF
MS, which is incomparably cheap for specimen-by specimen identification,
but when it comes to sample-wise analyses, metabarcoding outperforms other
techniques by far.