Secretomic Insight into Glucose Metabolism of <i>Aspergillus brasiliensis</i> in Solid-State Fermentation

The genus <i>Aspergillus</i> is ubiquitous in nature and includes various species extensively exploited industrially due to their ability to produce and secrete a variety of enzymes and metabolites. Most processes are performed in submerged fermentation (SmF); however, solid-state fermentation (SSF) offers several advantages, including lower catabolite repression and substrate inhibition and higher productivity and stability of the enzymes produced. This study aimed to explain the improved metabolic behavior of <i>A. brasiliensis</i> ATCC9642 in SSF at high glucose concentrations through a proteomic approach. Online respirometric analysis provided reproducible samples for secretomic studies when the maximum CO₂ production rate occurred, ensuring consistent physiological states. Extracellular extracts from SSF cultures were treated by SDS-PAGE, digested with trypsin, and analyzed by LC–MS/MS. Of 531 sequences identified, 207 proteins were analyzed. Twenty-five were identified as the most abundant unregulated proteins; 87 were found to be up-regulated and 95 were down-regulated with increasing glucose concentration. Of the regulated proteins, 120 were enzymes, most involved in the metabolism of carbohydrates (51), amino acids (23), and nucleotides (9). This study shows the high protein secretory activity of <i>A. brasiliensis</i> under SSF conditions. High glucose concentration favors catabolic activities, while some stress-related proteins and those involved in proteolysis are down-regulated

One-Step Selective Exoenzymatic Labeling (SEEL) Strategy for the Biotinylation and Identification of Glycoproteins of Living Cells

Technologies that can visualize, capture, and identify subsets of biomolecules that are not encoded by the genome in the context of healthy and diseased cells will offer unique opportunities to uncover the molecular mechanism of a multitude of physiological and disease processes. We describe here a chemical reporter strategy for labeling of cell surface glycoconjugates that takes advantage of recombinant glycosyltransferases and a corresponding sugar nucleotide functionalized by biotin. The exceptional efficiency of this method, termed one-step selective exoenzymatic labeling, or SEEL, greatly improved the ability to enrich and identify large numbers of tagged glycoproteins by LC–MS/MS. We further demonstrated that this labeling method resulted in far superior enrichment and detection of glycoproteins at the plasma membrane compared to a sulfo-NHS-activated biotinylation or two-step SEEL. This new methodology will make it possible to profile cell surface glycoproteomes with unprecedented sensitivity in the context of physiological and disease states

Site-Specific Glycan Microheterogeneity of Inter-Alpha-Trypsin Inhibitor Heavy Chain H4

Inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) is a 120 kDa acute-phase glycoprotein produced primarily in the liver, secreted into the blood, and identified in serum. ITIH4 is involved in liver development and stabilization of the extracellular matrix (ECM), and its expression is altered in liver disease. In this study, we aimed to characterize glycosylation of recombinant and serum-derived ITIH4 using analytical mass spectrometry. Recombinant ITIH4 was analyzed to optimize glycopeptide analyses, followed by serum-derived ITIH4. First, we confirmed that the four ITIH4 N-X-S/T sequons (N81, N207, N517, and N577) were glycosylated by treating ITIH4 tryptic/GluC glycopeptides with PNGaseF in the presence of ¹⁸O water. Next, we performed glycosidase-assisted LC–MS/MS analysis of ITIH4 trypsin-GluC glycopeptides enriched via hydrophilic interaction liquid chromatography to characterize ITIH4 N-glycoforms. While microheterogeneity of N-glycoforms differed between ITIH4 protein expressed in HEK293 cells and protein isolated from serum, occupancy of N-glycosylation sites did not differ. A fifth N-glycosylation site was discovered at N274 with the rare nonconsensus NVV motif. Site N274 contained high-mannose N-linked glycans in both serum and recombinant ITIH4. We also identified isoform-specific ITIH4 O-glycoforms and documented that utilization of O-glycosylation sites on ITIH4 differed between the cell line and serum

Discrimination between Adenocarcinoma and Normal Pancreatic Ductal Fluid by Proteomic and Glycomic Analysis

Sensitive and specific biomarkers for pancreatic cancer are currently unavailable. The high mortality associated with adenocarcinoma of the pancreatic epithelium justifies the broadest possible search for new biomarkers that can facilitate early detection or monitor treatment efficacy. Protein glycosylation is altered in many cancers, leading many to propose that glycoproteomic changes may provide suitable biomarkers. In order to assess this possibility for pancreatic cancer, we have performed an in-depth LC–MS/MS analysis of the proteome and MSⁿ-based characterization of the N-linked glycome of a small set of pancreatic ductal fluid obtained from normal, pancreatitis, intraductal papillary mucinous neoplasm (IPMN), and pancreatic adenocarcinoma patients. Our results identify a set of seven proteins that were consistently increased in cancer ductal fluid compared to normal (AMYP, PRSS1, GP2-1, CCDC132, REG1A, REG1B, and REG3A) and one protein that was consistently decreased (LIPR2). These proteins are all directly or indirectly associated with the secretory pathway in normal pancreatic cells. Validation of these changes in abundance by Western blotting revealed increased REG protein glycoform diversity in cancer. Characterization of the total N-linked glycome of normal, IPMN, and adenocarcinoma ductal fluid clustered samples into three discrete groups based on the prevalence of six dominant glycans. Within each group, the profiles of less prevalent glycans were able to distinguish normal from cancer on this small set of samples. Our results emphasize that individual variation in protein glycosylation must be considered when assessing the value of a glycoproteomic marker, but also indicate that glycosylation diversity across human subjects can be reduced to simpler clusters of individuals whose N-linked glycans share structural features

Use of cancer-specific yeast-secreted biotinylated recombinant antibodies for serum biomarker discovery-4

bound to case-pool serum. The enriched yeast-display scFv were labeled with anti-c-myc mAb and 25 μg/ml (A,B,E,F) or 100 μg/ml (C,D,G,H) of biotinylated case (A,C,E,G) or control (B,D,F,H) serum pools, before (A-D) or after depletion by magnetic sorting (E-H). Binding signals were detected as shown with the secondary antibody 488-alexa anti-mouse Ig (488 anti-mIg) and PE-labeled streptavidin (SA-PE).<p><b>Copyright information:</b></p><p>Taken from "Use of cancer-specific yeast-secreted biotinylated recombinant antibodies for serum biomarker discovery"</p><p>http://www.translational-medicine.com/content/6/1/41</p><p>Journal of Translational Medicine 2008;6():41-41.</p><p>Published online 24 Jul 2008</p><p>PMCID:PMC2503970.</p><p></p

Use of cancer-specific yeast-secreted biotinylated recombinant antibodies for serum biomarker discovery-2

endometrioid origin (as shown) were diluted in binding buffer, coated on plastic wells, and detected with polyclonal antibodies made to the center (pAb, white bars) or N-terminal (pAb, gray bars) region of PEBP1 or with a pAb made to the whole recombinant protein (black bars). Samples were tested in triplicates. Averages are shown. Wells coated with binding buffer were used as negative controls.<p><b>Copyright information:</b></p><p>Taken from "Use of cancer-specific yeast-secreted biotinylated recombinant antibodies for serum biomarker discovery"</p><p>http://www.translational-medicine.com/content/6/1/41</p><p>Journal of Translational Medicine 2008;6():41-41.</p><p>Published online 24 Jul 2008</p><p>PMCID:PMC2503970.</p><p></p

Use of cancer-specific yeast-secreted biotinylated recombinant antibodies for serum biomarker discovery-1

Trophoresis before (lanes 1,3) or after (lanes 2,4) depletion for abundant proteins by cibacron blue and detected by coomassie blue straining. B-C: Control- and ovarian cancer-pool serum depleted for abundant sequences were immunoprecipitated with biobodies selected for specific binding to case-pool serum. The products of elution from control sera (B lane 2, and C) and ovarian cancer (B lane 1, and D) were separated by 1-D (B) or 2-D (C,D) protein electrophoresis and detected by silver staining. In the 2-D gels, the immunoprecipitates were focused over a pH3 to pH10 range and run on a 10% acrylamide gel. The circle indicates the region where PEBP1 was found in patient serum (D) but not in control serum (C).<p><b>Copyright information:</b></p><p>Taken from "Use of cancer-specific yeast-secreted biotinylated recombinant antibodies for serum biomarker discovery"</p><p>http://www.translational-medicine.com/content/6/1/41</p><p>Journal of Translational Medicine 2008;6():41-41.</p><p>Published online 24 Jul 2008</p><p>PMCID:PMC2503970.</p><p></p

Global glycan occupancy site utilization across 94 HIV gp120s.

<p>(a) The heat map represents the N-linked glycosylation site occupancy profiles of 94 distinct recombinant gp120 proteins. Site utilization was determined by mass spectrometry, and the frequency of utilized sites at each potential glycosylation site (columns) is presented using a yellow-to-black gradient. The gray boxes depict the absence of a sequon (N-X-S/T, X≠P) at that specific site within that sequence. The right panel shows the average glycosylation site occupancy per protein. N-glycan sites were aligned based on the HXB2 sequence. Canonical N-glycan sites were designated based on the aligned sequence. Non-canonical N-glycan sites, which are not present in the HXB2 sequence, are shown in decimal numbers, based on the previously aligned N-glycan site. (b)-(e) The bar graphs show (b) the frequency of sequons present at each potential N-glycan site across all strains; (c) the mean (± standard deviation) glycan occupancy; (d) the variance of the glycosylation site occupancy (dotted line represents the top 15th percentile). (e) The N-glycan sites with the top 15% highest variance were mapped onto the BG505.SOSIP crystal structure (PDB #: 4NCO) highlighted as red. The approximate binding epitopes of various bNAbs on the Env structure are labeled in hatched circles.</p

Defining the glycosylation site determinants that shape bNAb binding profiles.

<p>(a)-(d) Four different Bayesian MCMC-SVR models were evaluated for their respective abilities to predict PGT121 binding to the 94 proteins. The models include a Bayesian MCMC-SVR model based on: (a) sequon presence (Figure A in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006093#pcbi.1006093.s001" target="_blank">S1 File</a>); (b) protein sequence; (c) glycosylation site occupancy; or (d) glycosylation site occupancy and sequence combined. Cross validation (100-iterative 10-fold) was used to evaluate model performance. Goodness-of-fit was assessed and is reported as the mean squared error (MSE) between predicted and ELISA-measured binding. (e) Heat map shows the binding signatures of individual Abs (rows), where the selected glycan sites (determinants) that mediate effects on Ab binding are highlighted. NAbs that share similar glycan determinants are grouped by hierarchical clustering. (f) The significant glycan site determinants for PGT121, PGT128, and VRC01 are plotted onto a 3-dimensional gp120 monomer structure using the same directional color coding as the heat-map. Additionally, the critical protein residues predicted by our model are shaded in yellow on the same 3D structure. Finally, broad Ab-binding sites were highlighted for each bNAb in hatched circles. (g) Agonistic and antagonistic glycan site determinants and critical protein residues for PGT122 are projected on the BG505 SOSIP.664-PGT122 co-crystal structure (PDB #: 4NCO) with the same color coding. The V3 loop is highlighted in light green shading.</p

Proof-of-concept glycoengineering of gp120 antigens to selectively enhance antigenicity.

<p>(a) Cartoon depicts the overall <i>de novo</i> antigen optimization design approach. (b) The heat maps, as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006093#pcbi.1006093.g003" target="_blank">Fig 3E</a>, depict the glycosylation site determinant profiles preferred by PGT121 and PGT128 including directional glycan coloring across all N-glycan sites (columns). (c) The top heat map represents the original wild-type MG535.W0M.ENV.D11 gp120 sequon site profile (yellow = sequon site absent and black = sequon site present); middle and bottom heat maps indicated the introduced point mutations (brown = sequon site knock-in, light blue = sequon site knock-out) for the gp120s engineered to have increased binding to PGT121 (+PGT121), PGT128 (+PGT128), and both PGT121 and PGT128 (+PGT121+PGT128); also, the gp120s engineered to selectively bind PGT121 but not PGT128 (+PGT121-PGT128), or PGT128 but not PGT121 (-PGT121+PGT128 and -PGT121+PGT128 2nd). (d) The bar graph depicts comparison of the predicted binding (beige = PGT121 and brown = PGT128) and ELISA-determined binding (light blue = PGT121, dark blue = PGT128, and grey = VRC01 binding) to the wildtype and engineered gp120s. ELISA binding activity was determined as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006093#pcbi.1006093.g002" target="_blank">Fig 2A</a>. In order to compare the model predictions to the experimental results, both the model and actual ELISA values were normalized to wild-type binding values, which were set to 1. Error bars indicate the standard deviation from six replicates. (e) The bar graph shows the degree of steric hindrance found on each antigen by summing all steric glycan site pairs (Figure J in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006093#pcbi.1006093.s001" target="_blank">S1 File</a>), if any site in the pair was considered essential for predicting Ab binding. Pink highlighted region denotes the average and range of the degree of steric hindrance across all the 94 recombinant gp120 proteins.</p