The distribution of log 2 ratio (H/L) for quantified peptides. cleavage sites in each bin of log 2 ratio of quantified. peptides

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1 Journal: Nature Methods Article Title: Corresponding Author: Protein digestion priority is independent of their abundances Mingliang Ye and Hanfa Zou Supplementary Figure 1 Supplementary Figure 2 The distribution of log 2 ratio (H/L) for quantified peptides The percentage of peptides containing at least one missed cleavage sites in each bin of log 2 ratio of quantified peptides Supplementary Table A list of quantified peptides and related information (Given as a separate Excel file). Supplementary Note 1 Some issues for the application of Michaelis-Menten kinetics in DigDeAPr Supplementary Note 2 Definition of fast, slow, very slow cleavage sites, early and later generated peptides Supplementary Note 3 Supplementary Methods Additional discussions Methods for protein digestion, stable isotope dimethyl labeling, RPLC-MS/MS analysis etc.

2 Supplementary Figure Log2Ratio (H/L) Peptides Supplementary Figure 1 The distribution of log 2 ratio (H/L) for quantified peptides

3 Supplementary Figure 2 Percentage (%) Log 2 Ratio Supplementary Figure 2The percentage of peptides containing at least one missed cleavage sites in each bin of log 2 ratio (H/L) of quantified peptides

4 Supplementary Note 1. Some issues for the application of Michaelis-Menten kinetics in DigDeAPr (1) The main reason that Fonslow et al[2] come to a wrong conclusion is because they confused the hydrolysis rate determined by Michaelis-Menten kinetics with the digestion rate typically used in proteomics. The hydrolysis rate determined by Michaelis-Menten kinetics is expressed as d[p]/dt, i.e. the change of product concentration per unit of time. Though this rate is bigger for high abundance proteins, it s hard to say if they can be consumed in shorter time or not because the total amounts of these proteins are also bigger. For example, there are two proteins in a sample. Say that the abundance of protein A has 1000 folds higher than that of protein B. Because they presented in the same sample, the total amount of protein A is 1000 times bigger. Even though protein A could be digested 1000 folds faster, the two proteins could be digested completely in the same time. The digestion rate used in proteomics typically means how fast a protein is consumed in a digestion. It could be defined as the fraction of protein consumed per unit time. The digestion rate of protein A is faster than that of protein B in proteomics typically implies that the consumption of protein A is faster than that of protein B. (2) Considering the protein as the trypsin substrate is inappropriate when applying Michaelis-Menten kinetics. Trypsin catalyzes the hydrolysis of peptide bond after residue of Lys and Arg. A protein may have many Lys and Arg residues, and so have many cleavage sites. When a protein could be digested by trypsin, it can be considered as the substrate of trypsin. However, this expression is not accurate when considering the trypsin catalyzed reaction. Every cleavage site (the peptide bond after the residue) on a protein can form an enzyme-substrate complex and could be cleavged by trypsin. Thus the cleavage site (more accurately the cleavage site with surrounding sequence) which is involved in the trypsin catalyzed reaction should be considered as the substrate. (3) They considered the Km of trypsin for any protein substrates are the same. This is incorrect. The kinetic constants including Km are different for cleavage sites with

5 different nearby residues as have been documented in many publication at peptide level[5, 6]. In fact, this is why some sites on proteins are cut early and some sites are cut later.

6 Supplementary Note 2. Definition of early, later generated peptides and fast, slow, very slow cleavage sites The early and later fractions from the two-step digestion were labeled with light and heavy labels, respectively. Totally 3054 peptides were quantified and the distribution of log 2 ratio (H/L) was given in Supplementary Figure 1. The distribution of peptides containing at least one missed cleavage sites across log 2 ratio (H/L) was given in Supplementary Figure 1, indicating high frequency of missed cleavage occurred at the first digestion step. Later generated Peptides (log 2 ratio > 1): Peptides mainly generated at the second digestion step. If a peptide mainly generated at the second digestion step, its abundance in the later fraction must be much higher than that of early fraction. Change of two fold is typically considered as significant change, thus peptides quantified with log 2 ratio > 1 were considered as Later generated peptides. Early generated peptides (log 2 ratio < 0.2): Peptides mainly generated at the first digestion step. If a peptide is mainly generated at the first digestion step, its abundance in later fraction either decreases or not changes. If the peptides can be further cut, then the abundance of the peptides will decrease in the later fraction (log 2 ratio < 0); If the peptides cannot be cut any more, the abundance of the peptides will not change in the later fraction (log 2 ratio = 0). Considering the accuracy of isotopic labeling based quantification, peptides quantified with log 2 ratio < 0.2 were considered as Early generated peptides. Fast cleavage sites (Both terminal sites, i.e, N- and C-terminal, on Early generated peptides, log 2 ratio < 0.2): The sites cut mainly at the first digestion step. The reason that some peptides could be generated in the first digestion step is because both the two terminal sites could be quickly cut. And so both terminal sites for Early generated peptides are considered as the fast cleavage sites. It should be noted that the fast cleavage sites are derived from the peptides two terminals, while the following slow and very slow cleavage sites are derived from the missed cleavage sites on peptides.

7 Slow cleavage sites (The missed cleavage sites on peptides with log 2 ratio < -0.53): The sites cut mainly at the second digestion step. The two terminal sites on the Later generated peptides cannot be considered as the slow cleavage sites because it will not be generated in the first digestion step when any of the two sites is slow. The missed cleavage sites on early generated peptides indicate that these sites cannot be cut in the first digestion step. However, if the abundances of these peptides decrease after further digestion, then the missed cleavage sites get cut at the second digestion step. It can be seen from Supplementary Figure 2 that the log 2 ratio < is a good threshold where the abundance of peptides decreased by about two folds after the second digestion. Thus the missed cleavage sites on peptides with log 2 ratio < are considered as the slow cleavage sites. Very slow cleavage sites (The missed cleavage sites on peptides with log 2 ratio > -0.2): The sites cannot be cut even at the second digestion step. If the peptides with missed cleavage sites generated in the first digestion step cannot be cut any more in the second digestion step, the abundance of the peptides will not change (log 2 ratio = 0). And the missed cleavages sites on the peptides generated mainly at the second digestion step are obvious the sites that could not be further cut (log 2 ratio >0). Considering the accuracy of isotopic labeling based quantification, the cleavage sites on peptides with log 2 ratio > -0.2 were considered as Very slow cleavage sites.

8 Supplementary Note 3. Additional discussion With DigDeAPr, the number of identified proteins and peptides increased by 18% and 5.7%, respectively. Since the digestion rate does not depend on protein abundance, why the coverage for proteome analysis was improved? We have mentioned that the cleavage sites surrounded by different residues have different digestion rates. During the first digestion step, the fast cleavage sites, no matter they are on the high abundant proteins or low abundant proteins, are firstly got cut. This will lead to generation of peptide fragments with different size. After ultra filtration, the small peptide fragments are removed and the big fragments are further digested. The Early generated peptides detected in this study are among the removed peptides because of their small size (typically < 3000 Da). We have demonstrated that the Early generated peptides do not bias to high abundant proteins. Then why more low abundant proteins were identified by DigDeAPr? This is because the complexity of the final peptide mixture was reduced because of the removal of early generated small peptides. This is the true reason that coverage for proteome analysis was improved with DigDeAPr. When we look through their dataset, spectra counts for many peptides decreased significantly or even some peptides cannot be identified after treated with DigDeAPr. This is because those peptide fragments were removed by ultra filtration. Then why the overall spectra counts for many abundant proteins decreased while that for low abundance increased? This is probably because the relation of MS response signal and peptide concentration is not linear. In their study, similar protein mass were loaded for LC-MS/MS analysis for DigDeAPr and control. Because the complexity of the peptide mixture in DigDeAPr is reduced, the concentrations of many peptides are higher than that of control. Therefore, the MS response will increase due to the higher peptide concentration. However, because MS signal does not have linear relationship with peptide concentration, the MS signal for high abundant peptides are often saturated and the spectra counts do not increase too much compared with that of low abundant peptides. And because some small peptides were removed by ultra filtration, it was possible that the overall spectra count for the high abundance proteins decreased. Label free quantification by spectra count is a semi-quantification

9 approach and can only be applicable for quantification of samples with similar complexity. Since the complexity of the two samples are significantly different, the reduced spectra count for high abundant proteins does not necessarily means the protein abundance decreased.

10 Supplementary Methods Reagents and chemicals. All the water used in this experiment was prepared using a Mill-Q system (Millipore, Bedford, MA). Formic acid (FA) was provided by Fluka (Buchs, Germany). Acetonitrile (ACN, HPLC grade) was purchased from Merck (Darmstadt, Germany). All the other chemicals and reagents were purchased from Sigma (St. Louis, MO). Fused silica capillaries with 75 μm i.d. were obtained from Polymicro Technologies (Phoenix, AZ). Cell growth and lysis. The HeLa cells were grown according to Bian et al[1]. The cell pellets were softly homogenized in a cold lysis buffer containing 8M urea, 50 mm TEAB (triethyl ammonium bicarbonate, ph = 8.0), 2% protease cocktail (vol/vol), 1% Triton X-100 (vol/vol), 65 mm DTT, 1 mm EDTA, 1 mm EDGA, 1 mm PMSF, 1 mm NaF, and 1 mm Na 3 VO 4, sonicated for 400 W 120 s, and centrifuged at 23000g for 1 h. The supernatant containing the total cell proteins was precipitated with 5 volumes of cold acetone/ethanol/acetic acid (vol/vol/vol = 50/50/0.1) at 20 C. Protein precipitant was centrifuged at 15000g for 30 min. The pellet was washed separately with acetone and 75% ethanol, then lyophilized to dryness and stored at 80 C. Protein digestion and stable isotope dimethyl labeling. Similar to the DigDeAPr [2], proteins (1 mg, the protein concentration was determined by Bradford assay) were denatured and reduced in 250 µl of 8 M urea, 100 mm TEAB, ph 8.0, and 10 mm DTT at 56 C for 40 min and then alkylated by 20 mm IAA in the darkness at room temperature for 30 min. The sample was diluted to 1 ml (2 M urea) with 100 mm TEAB, ph 8.0. Trypsin (Sigma) was added at a 25,000:1 protein/protease mass ratio along with CaCl 2 to 1 mm for a 12 h-digestion at 37 C. Then the sample were divided into two parts, one aliquot was without any further processing, another was digest completely by adding 10 µg of trypsin and CaCl 2 to 1 mm for an overnight digestion at 37 C. Then the two aliquot above were labeled with light and heavy dimethyl, respectively. For the stable isotope dimethyl labeling[3], 250 μl of CH 2 O (4%, vol/vol) and CD 2 O (4%, vol/vol) were added into the sample solution, respectively, and then, 250 μl of

11 freshly prepared NaBH 3 CN (0.6 M) were added subsequently. The resultant mixture was incubated for 1 h at room temperature. Then, 10 μl of ammonia (25%) and 25 μl of FA were added to consume the excess labeling reagents and to acidify the sample, respectively. After mixed in a ratio of 1:1 on the basis of the total protein amount, the labeled peptide mixture was desalted by the SPE column. The samples were dried down by vacuum centrifugation and stored at 80 C until used. Nano LC-MS/MS analysis. RPLC-MS/MS system consisted of a LTQ-Orbitrap mass spectrometer (Thermo Fisher Scientific) with a nanospray source. A capillary column was first manually pulled to a fine point as spray tip, and then packed with C18 AQ beads (3 μm, 120 Å, Michrom Bio Resources). 0.1% (vol/vol) formic acid in water and 0.1 % (vol/vol) formic acid in acetonitrile were applied as the mobile phase. Gradient elution from 5% to 35% (vol/vol) of the 0.1% (vol/vol) formic acid in acetonitrile in 180 min was performed to elute each sample. All MS and MS/MS spectra were acquired in the data dependent mode with the twenty most intense ions were fragmented by CID. Data analysis. Protein quantification was performed using MaxQuant[4] ( ). The raw files were searched against International Protein Index human database (v3.80), carbamidomethylation on cysteine was set as a fixed modification, and oxidation on methionine was set as variable modifications. Peptides were searched using fully tryptic cleavage constraints and up to two missed cleavages sites were allowed. For quantification, stable isotope dimethyl labeling, different quantification modes integrated into Maxquant were selected, respectively. The other settings were the same to the conventional search. Sequence logos were automatically generated by the WebLogo program ( The sequences were centered at the cleavage site and extended 13 residues ( ± 6 residues). The N- or C- terminal sequences that could not be extended were excluded.

12 Supplementary References 1. Bian, Y., et al., Improve the Coverage for the Analysis of Phosphoproteome of HeLa Cells by a Tandem Digestion Approach. Journal of Proteome Research, (5): p Fonslow, B.R., et al., Digestion and depletion of abundant proteins improves proteomic coverage. Nature methods, (1): p Song, C., et al., Improvement of the quantification accuracy and throughput for phosphoproteome analysis by a pseudo triplex stable isotope dimethyl labeling approach. Analytical Chemistry, (20): p Cox, J. and M. Mann, MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotech, (12): p Caprioli, R.M. and L. Smith, Determination of Km and Vmax for Tryptic Peptide Hydrolysis Using Fast-Atom-Bombardment Mass-Spectrometry. Analytical Chemistry, (6): p Pozsgay, M., et al., Investigation of the Substrate-Binding Site of Trypsin by the Aid of Tripeptidyl-Para-Nitroanilide Substrates. European Journal of Biochemistry, (3): p

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