1. Volume 25, Issue 9, Pages 2524-2536.e4 (November 2018)
Quantitative Proteomics Evaluation of Human Multipotent Stromal Cell for β Cell Regeneration 
Miljan Kuljanin, Ruth M. Elgamal, Gillian I. Bell, Dimetri Xenocostas, Anargyros Xenocostas, David A. Hess, Gilles A. Lajoie 
Cell Reports 
Volume 25, Issue 9, Pages e4 (November 2018)
DOI: /j.celrep
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2. Cell Reports 2018 25, 2524-2536.e4DOI: (10.1016/j.celrep.2018.10.107)
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3. Figure 1
Quantitative Proteomics Strategies to Evaluate β Cell Regenerative Potency of Donor-Derived hMSC Lines
(A) Donor-derived hMSCs (n = 20) are isolated, expanded ex vivo, and transplanted into a hyperglycemic mouse model. Blood glucose is monitored for 42 days to determine endogenous β cell regenerative potential. Alternatively, donor-derived hMSCs are isolated and expanded ex vivo, and secreted proteins are captured by conditioning media (CM) for 24 hr using serum-free conditions. CM are digested and a protein signature of β cell regenerative hMSCs is determined using mass-spectrometry-based quantitative proteomics.
(B) Principle component analysis displays good separation of regenerative and nonregenerative hMSCs.
(C) Total proteins quantified in each hMSC cell line CM (n = 2). Data are shown as mean.
(D) Quantitative data were filtered using GO cellular component to only include classically secreted proteins (590). Secretome generated from hMSC CM was compared to 3 previously published secretome datasets.
(E) Representative volcano plot of differentially expressed proteins for regenerative versus nonregenerative hMSC CM. Classically secreted proteins are displayed in blue. A change greater than 2-fold is represented outside the boundaries. p < 0.05, false discovery rate (FDR) < 0.05.
Also see Figure S1.
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4. Figure 2
Quantitative Label-free Proteomics Facilitates Efficient Classification of β Cell Regenerative and Nonregenerative Donor-Derived hMSC Lines
(A) Each hMSC CM was analyzed in duplicate by LC-MS/MS. Greater than 80% of the quantified proteins were found in both replicates.
(B) Label-free quantitative reproducibility within and between sample replicates. The intensity of each box represents the Pearson correlation between each sample for all secreted proteins. High correlation scores were obtained between sample replicates (>0.95).
(C and D) Quantitative proteomics data were mined for a β cell regenerative signature using unbiased machine learning. A support vector machine identified 41 proteins that could be used accurately to segregate regenerative and nonregenerative hMSC lines (C). This included 18 classically secreted proteins and 23 intracellular proteins (D).
(E) Classically secreted proteins were mined for a β cell regenerative signature using unbiased machine learning. A support vector machine identified 16 proteins could be used accurately to segregate regenerative and nonregenerative hMSC lines.
(F) Label-free quantitative values for the top 16 proteins obtained from the support vector machine that were highly expressed in regenerative (green) (n = 6) and nonregenerative (gray) (n = 14) hMSC lines.
Data are represented as mean ± SD. ∗∗p < 0.05, ∗∗∗p < See also Figure S2.
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5. Figure 3
Targeted Proteomic Refining of the Predictive Protein Signature for β Cell Regenerative hMSCs
(A) 5-point standard curve spanning 3 orders of magnitude (50 amol to 50 fmol) using light and heavy isotope labeled peptides (glu-1-fibrinopeptide B: EGVNDNEEGFFSAR) as spike in standards.
(B) Intensity of the most abundant fragments ions for CXCL8 quantified in regenerative (left) and nonregenerative (right) CM by PRM-LC-MS/MS.
(C) Total integrated fragment area for each of the peptides selected for PRM evaluation across 20 hMSC CM samples. Total fragment area was normalized the standard peptide spike in (red), and the relative abundance of each peptide or protein was estimated using the standard curve.
(D) Average peptide expression for all 16 peptides comparing regenerative (n = 6) and nonregenerative (n = 14) hMSC samples (shown as Log2 ratios).
Data are represented as mean. See also Figures S2 and S3.
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6. Figure 4
Targeted Proteomics Validation Using ELISA Reveals CXCL8 and IL-6 as Accurate Segregators of β Cell Regenerative and Nonregenerative hMSCs
(A) The area under the receiver operator characteristic (ROC) curve (AUC) was used to evaluate the ability of individual peptides to distinguish between β cell regenerative and nonregenerative hMSC lines. Peptides with high discriminative power are shown to the right of the blue lines (AUC ≥ 0.70).
(B and C) ROC analysis using targeted proteomics data for peptide corresponding to (B) CXCL8 and (C) SFRP1. CXCL8 displays the highest power of segregation between β cell regenerative and nonregenerative hMSCs.
(D and E) Absolute protein concentration was quantified using ELISA for (D) CXCL8 and (E) IL-6. CXCL8 displays 100% specificity and 75% sensitivity below 11.0 pg/mL, while IL-6 displayed 93.75% specificity and 75% sensitivity below 2.2 pg/mL.
See also Figure S4.
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7. Figure 5
Functional Validation of hMSC Lines Characterized by Quantitative Proteomics Using In Vitro and In Vivo Assays
(A) Culturing human islet in CM generated from regenerative hMSC lines (sample 5) (n = 3) increased the proportion of live β cells after 7 days of culture compared to negative controls (black) (n = 3) and islets cultured in CM generated from nonregenerative hMSCs (samples 1–4 and 6–10) (n = 3).
(B) hMSCs from one newly characterized regenerative and one nonregenerative hMSC line were translated into STZ-treated (35 mg/kg/ days 1–5) NOD/SCID mice on day 10, and blood glucose was monitored weekly until day 35. Mice transplanted regenerative hMSCs (green) (n = 4) showed reduced hyperglycemia from days 14 to 35 compared to mice injected with PBS (black) (n = 4) and mice transplanted with nonregenerative hMSCs (gray) (n = 3).
(C) Mice transplanted with regenerative hMSCs showed significantly reduced systemic blood glucose levels over the full time course compared to mice injected with PBS or transplanted with nonregenerative hMSCs.
(D–F) Representative photomicrographs of insulin expressing islets at day 35 in mice injected with PBS (D) or transplanted with nonregenerative hMSCs (E) and regenerative hMSCs (F).
(G–I) Compared to mice injected with PBS or mice transplanted with nonregenerative hMSCs, mice transplanted with regenerative hMSCs showed significantly increased islet number (G) and β cell mass (H), with no difference in islet size (I).
Arrowheads denote islets, and inlets show a 2.5× magnified view of islets outlined with a dotted box. Scale bars, 200 μm. Data are represented as mean ± SEM. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < See also Figure S5.
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8. Figure 6
Donor Characteristics Reveal Body Mass Index as a Potential Pre-screening Tool to Identify More β Cell Regenerative hMSC Lines
(A) Equal number of male (n = 13) and female (n = 16) donors were characterized as regenerative or nonregenerative using in vivo mouse models or quantitative proteomic screens.
(B) No direct correlation between donor age and β cell regenerative potency was observed.
(C) A direct correlation between donor BMI and β cell regenerative potency was observed with samples characterized using in vivo mouse models (hexagon), quantitative proteomics (circle), or both (square).
(D) All hMSC lines derived from patients that had BMIs in the obese category (>29.9) or in the overweight category (>24.9, <29.9) were classified as nonregenerative (gray). In contrast, 80% of samples derived from donors that has healthy BMIs (<24.9) were classified as regenerative (green).
Data are represented as mean ± SD.
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