iment in sextuplicates representative of two performed. Acknowledgments We thank Drs. Grzegorz Bereta and Dominik Czaplicki for critically reading the manuscript. Supporting Information Text S1 Generation of mouse recombinant His-NRG- Diabetes mellitus is one of the most common metabolic disorders in the world, in which more than 
90% are grouped to type 2 diabetes mellitus . Given the predicted explosion in the number of T2DM cases worldwide, the biomedical researchers face much stronger challenges, particularly on understanding the pathogenesis of disease and 12604092 discovering biomarkers for tracking the disease process. T2DM is characterized by abnormal glucose homeostasis leading to hyperglycemia, and the serum glucose has been used as a golden standard for diabetes diagnosis. However, T2DM is a kind of disease involving defects of multiple organs, which cannot be distinguished through the measurement of the serum-glucose level. In addition, T2DM is a multiple-stage disease, which usually covers several decades from impaired plasma glucose to various complications. The serum-glucose level only reflects the consequence of multiple physiological disorders in the given stage. Therefore, many efforts have been made to identify genetic and protein markers to reveal the molecular/cellular details or Diabetes Serum Proteome density lipoproteins apoA-I and apoA-II and their glycosylated products in patients with diabetes and cardiovascular disease. Zhang et al. found that the protease inhibitors including clade A and C, alpha 2-macroglobulin, fibrinogen, and the proteins involved in the classical complement pathway such as complement C3, and C4 exhibited the higher expression-levels in insulin resistance/type-2 diabetes. Bergsten et al. analyzed the serum proteins in T2DM by SELDI-TOF-MS and peptide-mass fingerprinting, and found the expression levels of Daclatasvir price apolipoprotein, complement C3 and transthyretin were overrepresented, whereas albumin and transferrin were underrepresented in T2DM. However, none of these above works provided the real globe view for the protein profile of the diabetic serum, since the proteomic analysis of serum is a formidable challenge for its huge complexity and 11335724 dynamic range. Recent advances in serum sample preparation such as a depletion of high abundance proteins can be coupled to 1D or 2D-LC-MS/MS analysis, which have provided the new ways for large-scale serum proteomic analysis. However, the step of the depletion of the high abundance proteins might cause some artifacts. In the present study, we used a label-free proteomic method with LC-MS/MS to investigate the protein profiling between the non-diabetic and diabetic serum without removing the high abundant proteins. After analyzing the proteomics data according to the stringent criteria, a total of 3,010 proteins and 3,224 proteins were identified from the non-diabetic and diabetic serum, respectively. In-depth bioinformatic analysis was employed for these differential proteins between the nondiabetic and diabetic serum. spectra to 189,792 peptide counts, resulting in 5,960 unique peptides corresponding to 3,224 protein groups in diabetic serum. Supplementary Results Selection of non-diabetic subjects and diabetic patients Previous studies observed that T2DM might occurred at a greater frequency in adults who are younger than 65 years, suggesting that people who are old than 65 without diabetes mellitus usually do not anticipate the genetic susceptibility. Therefore, w