Proteomic pattern of breast milk discriminates obese mothers with infants of delayed weight gain from normal-weight mothers with infants of normal weight gain.

We previously reported that exclusively breastfed infants born to mothers with pregestational obesity gain less weight during the first month after birth than those born to mothers of normal pregestational weight. This issue is potentially important since lower weight gain in breastfed infants of obese mothers might increase the risk of developing later obesity. Breast milk quality and quantity, together with breastfeeding practice, possibly influence infants' feeding behavior, appetite control, and regulation of growth later in life. The issue of whether breast milk protein patterns from obese mothers differ in composition from those of non-obese mothers remains largely unexplored. Here, we established a breast milk proteomic pattern that discriminates obese mothers and infants with delayed weight gain at 1 month after birth from normal-weight mothers with infants of the same age and with normal weight gain. Obese mothers were matched to normal-weight mothers (n = 26; body mass index 33.5 ± 3.2 vs 21.5 ± 1.5 kg·m-2). The mean weight gain of infants in the obese group at 1 month after birth was 430.8 g lower than that of the infants in the control group. Analysis of the breast milk delipidized fraction by surface-enhanced laser desorption/ionization on CM10 and Q10 arrays was followed by MS-assisted purification and LC-MS/MS microsequencing of a selected biomarker. We identified 15 candidate protein biomarkers, seven of which were overexpressed in the obese group and eight in the normal-weight group. One of the most significant candidate biomarkers, overexpressed in the obese group, was identified as a fragment of the sixth extracellular domain of the polymeric immunoglobulin receptor. Further structural identification of these candidate biomarkers and their validation in clinical assays may facilitate the development of a predictive immunoassay.

Candidate proteomic biomarkers for three genogroups of the swine pathogen Streptococcus suis serotype 2.

BACKGROUND: Streptococcus suis, more specifically serotype 2, is a major swine pathogen and an emerging zoonotic agent that causes severe infections such as meningitis, endocarditis, and septicemia. In this study, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI) was used to investigate the protein expression profiles of 45 strains of S. suis serotype 2 that had previously been clustered by multilocus sequence typing (MLST) into three sequence types (ST1, ST25, and ST28) (n = 15 for each ST). RESULTS: The SELDI data were analyzed using the univariate Mann-Whitney and Kruskal-Wallis tests and multivariate statistical methods (heatmap/hierarchical clustering). The heatmap identified 136 cell proteins, and hierarchical clustering provided a 100% correct classification of all fifteen ST1 and ST25 strains and thirteen of the fifteen ST28 strains (87% correct). The univariate statistical analyses of the SELDI protein expression profiles identified nine significant proteins that discriminated the strains of the three STs of S. suis. Of these proteins, two were overexpressed in ST1 (5958 Da and 10249 Da), four in ST25 (5989 Da, 6646 Da, 7421 Da, and 9825 Da), and three in ST28 (4516 Da, 7833 Da, and 9342 Da). Two of the proteins associated with the ST28 strains (p4516 and p9342) were purified and were identified as a putative ABC transporter and a nucleoid-DNA-binding protein, respectively. CONCLUSIONS: SELDI analysis of 45 strains of S. suis allowed to identify nine statistically significant proteins that can be specifically correlated with either ST1, ST25 or ST28. The possible involvement of the overexpressed proteins in the pathology of S. suis infections will require further investigation.

Proteomic biomarkers associated with Streptococcus agalactiae invasive genogroups.

Group B streptococcus (GBS, Streptococcus agalactiae) is a leading cause of meningitis and sepsis in newborns and an etiological agent of meningitis, endocarditis, osteoarticular and soft tissue infections in adults. GBS isolates are routinely clustered in serotypes and in genotypes. At present one GBS sequence type (i.e. ST17) is considered to be closely associated with bacterial invasiveness and novel proteomic biomarkers could make a valuable contribution to currently available GBS typing data. For that purpose we analyzed the protein profiles of 170 genotyped GBS isolates by Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI). Univariate statistical analysis of the SELDI profiles identified four protein biomarkers significantly discriminating ST17 isolates from those of the other sequence types. Two of these biomarkers (MW of 7878 Da and 12200 Da) were overexpressed and the other two (MW of 6258 Da and 10463 Da) were underexpressed in ST17. The four proteins were isolated by mass spectrometry-assisted purification and their tryptic peptides analyzed by LC-MS/MS. They were thereby identified as the small subunit of exodeoxyribonuclease VII, the 50S ribosomal protein L7/L12, a CsbD-like protein and thioredoxin, respectively. In conclusion, we identified four candidate biomarkers of ST17 by SELDI for high-throughput screening. These markers may serve as a basis for further studies on the pathophysiology of GBS infection, and for the development of novel vaccines.