Embodiments described herein generally relate to technologies for analyzing peptide structures for diagnosing and/or treating a disease state advancing through a disease progression. A non-limiting example of a method relating to the technologies described in the subject application may include receiving peptide structure data corresponding to the biological sample obtained from the subject, identifying a peptide structure profile, and diagnosing a disease state within a disease progression. The example may further include generating a diagnosis output relating to the disease state. In at least some cases, the peptide structure profile may include glycosylated peptides, aglycosylated peptides, or both.

A proteomic expression platform to identify age-related sepsis risk is disclosed using patients with an intra-abdominal infection. A semi-quantitative plasma proteomics workflow was applied which incorporated tandem immuno affinity depletion, iTRAQ labeling, strong cation exchange fractionation, and nanoflow-liquid chromatography coupled to high resolution mass spectrometry. A protein profile was determined that exhibit statistically significant differences in expression levels amongst patients with severe sepsis as a function of age. Representative pathways that are differentially-expressed include, but are not limited to, acute phase response, coagulation signaling, atherosclerosis signaling, lipid metabolism, and production of nitric oxide/reactive oxygen species.

Methods for peptide and/or protein quantification by mass spectrometry using labeled peptides, wherein multiple labels lead to distinct fragments for the labeled peptides and their unlabeled variant, thus facilitating data analysis and enhancing the potential for quantification. Methods for selecting the label and label position are further given, as well as sets of labeled peptides resulting from or for use in the above-mentioned methods. The methods and substances are especially useful for data-independent or multiplexed parallel reaction monitoring proteomics applications involving peptide quantification.

The invention relates to a method to evaluate mass spectrometry data for the analysis of peptides from biological samples, particularly MALDI-TOF mass spectrometry data, comprising the steps of: providing expected mass defects; determining measured mass defects, i.e. the mass defects resulting from the mass spectrometry data; and comparing the measured mass defects with the expected mass defects.

Compositions and methods for analyzing disulfide bonds are provided. An exemplary method includes preparing peptide standards having no disulfide bonds, scrambled disulfide bond peptide standards, and native disulfide bond peptide standards according to the sequence of the region of the protein drug product that includes the disulfide bond, digesting a sample of protein drug product into peptides, separating the protein drug product peptides, analyzing the protein drug product peptides and the peptide standards, identifying scrambled and native disulfide bond peptides by retention time, and quantifying the level of scrambled disulfide bond peptides.

It is provided a reversible streptavidin based analyte enrichment system for use in crosslinking mass spectrometry analysis, in particular for enriching at least parts of crosslinked peptides pairs in mass spectrometry analysis, and a method of enriching at least parts of crosslinked peptides pairs, in particular for use in crosslinking mass spectroscopy analysis.

Method and devices are provided for assessing tissue samples from a plurality of tissue sites in a subject using molecular analysis. In certain aspects, devices of the embodiments allow for the collection of liquid tissue samples and delivery of the samples for mass spectrometry analysis.

Systems and methods for determining amino acid sequences of peptides that bind to MHC-I or HLA-I complex or MHC-II or HLA-II complex are provided. One embodiment includes isolating peptides from MHC or HLA class I or class II-peptide complexes and adding one or more known labeled peptides of interest to form a sample containing labeled peptides and unlabeled isolated peptides. The method also includes analyzing the sample with an LC-MS/MS system to obtain sequence data of the peptides, and increasing the sensitivity of the LC-MS/MS system when the labeled peptide is detected by the LC-MS/MS system. The method then concludes with determining the amino acid sequence of the unlabeled peptides in an m/z range that includes the m/z of the labeled peptide. The system can be triggered to increase the sensitivity in or near the m/z of the labeled peptide using an algorithm or computer program.

Provided are methods for quantitating an amount of a polypeptide that comprises a portion of an antibody present in a sample (e.g., a plasma or serum sample) wherein the antibody comprises a constant region (e.g., a heavy chain or light chain constant region) that comprises an engineered mutation.

An integrated biomarker system for evaluating a risk of impaired fasting glucose (IFG) and type 2 diabetes mellitus (T2DM) for the first time is disclosed. The integrated biomarker system includes quantitative determination results of L-glutamine, L-valine, L-leucine, L-lysine, L-proline, L-phenylalanine, L-arginine, L-glutamic acid, L-isoleucine, L-methionine, L-carnitine, acetyl-L-carnitine, lysophosphatidyl choline (LPC (P-16:0)), LPC (17:0), LPC (14:0) and propionyl-L-carnitine in a sample. The integrated biomarker system for IFG and T2DM of subject serum sample contains a correlative biomarker group on a biological network path to reflect the overall metabolic characteristics information of IFG and T2DM and to avoid that characteristic information of a disease cannot be reflected integrally and completely due to single or separate analysis of a biomarker.