Abstract
Stable isotope probing (SIP) traces the metabolism of biological cells using isotopically heavy substrates (e.g., (13)C, (15)N, or (2)H). Confident identification of the metabolic products of isotopic labeling remains a challenge due to the difficulties in simulating, visualizing and annotating the isotopic patterns of partially labeled peptides and metabolites found in mass spectrometry (MS) data. Here, we present Aerith, an R package designed to visualize data of simulated and observed isotopic envelopes of peptides and metabolites with user-defined formula and atom % enrichment levels. Aerith models the isotopic distributions of the fragment ion series of a peptide by sequentially convoluting isotopic envelopes of monomeric units using a convolution algorithm. Aerith simulates fine isotopic structures of a compound using Monte Carlo simulation via the multinomial distribution, and calculates the isotopic envelopes of metabolites with known chemical formulas using an FFT-based algorithm. These algorithms provide accurate simulation of the isotopic envelopes of SIP-labeled peptides and metabolites with high computational efficiency. Aerith evaluates peptide-spectrum matches through multiple robust and commonly used scoring functions to compare experimental and theoretical spectra. These algorithms were implemented in C++ and accessed in R via Rcpp to ensure real-time interactivity and significantly improve computational efficiency compared to native R code. We present case studies to demonstrate Aerith's utility in resolving isotopic fine structures and envelopes for glucose, penicillin, and microbial peptides containing natural and enriched isotopes. By providing visualization of isotopically labeled peptides and metabolites, Aerith enables precise annotation of their mass spectra and manual validation of their identifications in proteomic and metabolomic SIP studies.