Entometabolomics: applications of modern analytical techniques to insect studies - PubMed

A sample data processing workflow. This investigation assessed differences in the larval metabolome across two pyralid moth species: rice moth (Corcyra cephalonica

S

tainton) and Indian mealmoth (Plodia interpunctella

H

übner) (C Snart, unpubl.). Lipid extracts were generated using a modified methanol‐chloroform‐water extraction protocol and analysed using

LC

‐

MS

(A and B).

LC

‐

MS

chromatograms were aligned to a common reference sample and framed using the Thermo

SIEVE

(Thermo Fisher Scientific, Waltham, MA, USA) processing software. Aligned and framed data were then exported to the statistical software

SIMCA

13.0.3 (Umetrics, Umeå, Sweden) and analysed using principle component analysis (

PCA

) (C and D). Group clustering of samples based on the two experimental groups was confirmed in the negative electrospray ionisation (

ESI

) mode

PCA

analysis (C). The two treatment groups were defined and an

PLS

‐

DA

analysis was utilised to directly compare between the two groups (R2X = 0.706, R2Y = 0.988, Q2 = 0.98). A loadings plot was utilised to aid in identifying major differences between the two groups (D). Group‐to‐group comparisons were used to highlight loadings (highlighted in grey) associated with the two groups. These differential loadings were examined for their associated mass‐to‐charge ratios (m/z) and elution times (E). Using these values, variable

ID

9 was identified as a cholesterol derivative based on consultation with online metabolite databases [

LIPID MAPS

and the Human Metabolome Database (

HMDB

)]. Further qualitative data for this metabolite were generated using the Thermo

XCALIBUR

software (Thermo Fisher Scientific). Mean relative abundances (± 1

SD

) are shown on a bar chart (F) and

ANOVA

found a significant difference in metabolite level between the two groups (F).