Supplementary information. Additional methods: Elemental formula assignments

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Impact of instrument and experiment parameters on reproducibility and repeatability of peaks within ultrahigh resolution ESI FT ICR mass spectra of natural organic matter Melissa C. Kido Soule 1, Krista Longnecker 1, Stephen J. Giovannoni 2, and Elizabeth B. Kujawinski 1 (1) Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole MA 02543 (2) Department of Microbiology, Oregon State University, Corvallis OR 97331 Supplementary information Additional methods: Elemental formula assignments Elemental formulas were calculated for the negative ion mode spectra collected to examine the effect of different solvents. The spectra were internally calibrated using a list of calibrants found in all of the spectra. The elemental formulas were then assigned to the aligned m/z values using the Compound Identification Algorithm (CIA), described by Kujawinski and Behn (2006) and modified in Kujawinski et al. (2009). In the CIA, we set the following parameters: (a) formula error was 1 ppm, (b) the relationship error was 20 ppm, and (c) the mass limit above which elemental formulas were assigned by functional group relationships only was 500 Da. Elemental formula assignments were constrained to 12 C, 13 C, 1 H, 16 O, 14 N, 31 P, and 32 S. For this study, elemental formulas were determined for m/z values below 500 Da with an inhouse database of mathematically and chemically legitimate formulae within the 1 ppm error window. These elemental formulas were extended to m/z values above 500 Da through identification of functional group relationships with smaller m/z values. The functional group relationships used by CIA are common to refractory dissolved organic matter (e.g., humic acids); it should be noted that CIA does not presently include many functional group relationships resulting from metabolic (biological) reactions (Kujawinski and Behn 2006).

Supplementary Table 1. Edge effects in wide SIM mode. Spectra were centered at m/z 400 or 600 (column 1) and had widths ranging from 50 m/z up to 600 m/z (column 2). Columns 3 through 4 provide the edge effects on the lower end of the window and columns 5 through 6 provide the edge effects on the upper end of the window. Center (m/z) Width (m/z) Minimum m/z (set) Lower m/z edge Minimum m/z (observed) Maximum m/z (set) Upper m/z edge Maximum m/z (observed ) 400 50 375 375 425 417.2 400 100 350 351 450 443.2 400 200 300 301.1 500 491.2 400 400 200 204.5 600 589.2 400 600 100 103.7 700 645.1 600 50 575 575 625 619.3 600 100 550 551 650 643.3 600 200 500 501 700 691.1 600 400 400 405.2 800 787.2 600 600 300 309.1 900 885.1

Supplementary Figure 1 Untransformed transients in narrow SIM at different AGC values. Data were collected in negative ion mode as narrow SIM data with a window width of 30 m/z. (A,B) have an AGC value of 1X10 4, (C,D) have an AGC value of 5X10 4, (E,F) have an AGC value of 5X10 5. (A,C,E) were spectra collected with m/z centered on 400, (B,D,F) were spectra collected with m/z centered on 600. 3

Supplementary Figure 2 Untransformed transients in wide SIM at different AGC values. Data were collected in negative ion mode as wide SIM data with a window width of 100 m/z. (A,B) have an AGC value of 1X10 5, (C,D) have an AGC value of 2X10 5, (E,F) have an AGC value of 1X10 6. (A,C,E) were spectra collected with m/z centered on 400, (B,D,F) were spectra collected with m/z centered on 600. 4

Supplementary Figure 3 Impact of scan number on spectral parameters in narrow SIM mode. Each plot shows the impact of scan number on the chosen parameter as a function of scans processed. Four parameters are shown here: (A) mean number of peaks found (± one SD), (B) number of peaks shared, (C) percent of peaks shared, (D) noise level. All data were collected in narrow SIM negative ion mode with a window width of 30 m/z; spectra were centered at m/z 400 (circles) or m/z 600 (diamonds). 5

Kide Soule et al. Supplementary Figure 4 Impact of scan number on spectral parameters in wide SIM mode. Each plot shows the impact of scan number on the chosen parameter as a function of scans processed. Four parameters are shown here: (A) mean number of peaks found (± one SD), (B) number of peaks shared, (C) percent of peaks shared, (D) noise level. All data were collected in wide SIM negative ion mode with a window width of 100 m/z; spectra were centered at m/z 400 (circles) or m/z 600 (diamonds). 6

Supplementary Figure 5 Reproducibility of peak detection and peak height in negative ion mode. The first row of the figure depicts run 1 versus run 3 (A C); the second row of the figure depicts run 2 versus run 3 (D F). Symbols depict whether peaks were observed in all three replicates ( ), in two replicates ( ), or in one replicate only ( ). A 1:1 line is provided for reference in all plots. All data were collected in negative ion mode. Full scan mode is depicted in panels (A,C), narrow SIM is depicted in panels (B,D), and wide SIM is depicted in panels (C,F). 7

Supplementary Figure 6 Reproducibility of peak detection and peak height in positive ion mode. The first row of the figure depicts run 1 versus run 2 (A C), the second row of the figure depicts run 1 versus run 3 (D F), the third row of the figure depicts run 2 versus run 3 (G I). Symbols depict whether peaks were observed in all three replicates ( ), in two replicates ( ), or in one replicate only ( ). A 1:1 line is provided for reference in all plots. All data were collected in negative ion mode. Full scan mode is depicted in panels (A,D,G), narrow SIM is depicted in panels (B,E,H), and wide SIM is depicted in panels (C,F,I). 8

Supplementary Figure 7 Van Krevelen diagrams of all formulae assigned to m/z values from SRFA dissolved in (a) 25% methanol in water, (B) 50% methanol in water, and (C) 70% methanol in water. SRFA was run in negative ion mode using the optimized instrument parameters. 9

References cited in supplementary information: Kujawinski, E.B. and M.D. Behn (2006). Automated analysis of electrospray ionization Fourier transform ion cyclotron resonance mass spectra of natural organic matter. Analytical Chemistry 78: 4363 4373. Kujawinski, E.B., K. Longnecker, N.V. Blough, R. Del Vecchio, L. Finlay, J.B. Kitner and S.J. Giovannoni (2009). Identification of possible source markers in marine dissolved organic matter using ultrahigh resolution electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. Geochim. Cosmochim. Acta 73: 4384 4399. 10