Creative proteomics

10/21/2026

🧬 Same antibody sequence, different N-glycans — different behavior in the clinic.

N-glycans at Asn-X-Ser/Thr sites shape binding affinity, Fc effector function, PK, and immunogenicity. That is why regulators ask for the N-glycan profile, and why process changes demand re-profiling.

The analytical reality: released glycans form isobaric, isomeric mixtures. One technique is rarely enough.

Creative Proteomics' N-Glycan Profiling Service combines:

✔ MALDI-TOF-MS for rapid screening ✔ HILIC-UHPLC-MS with optional 2-AB labeling ✔ CE-MS for orthogonal confirmation ✔ Full annotation: sites, quantification, heterogeneity, linkage

Antibodies, Fc-fusions, vaccines, plasma, cell supernatants — we profile them all. Entering CMC characterization or comparing production clones? A well-annotated N-glycan profile is where the answer starts, and our team can help you pick the right combination of platforms for your question.

📄 Details: https://www.creative-proteomics.com/services/n-glycan-profiling-service.htm

10/21/2026

🔬 Glycans decide how proteins behave — half-life, receptor binding, immune signaling — yet they remain the hardest chain to read.

Unlike DNA or proteins, glycans are not template-encoded. They appear as isomer mixtures with weak MS ionization, so a standard LC-MS workflow can miss or misassign them entirely.

At Creative Proteomics, glycomics is a dedicated platform, not an add-on:

✔ Enzymatic release and 2-AB labeling ✔ HILIC-UHPLC, CE, and MALDI-TOF-MS ✔ N-/O-glycan profiling with site-specific information ✔ Linkage analysis, quantification, and glycan sequencing ✔ Glycopeptide analysis and glycan microarrays for binding screens

Biotherapeutic characterization, expression-system comparison, or disease biomarker discovery — the analytical strategy should match your question. Not sure which branch of the workflow fits your samples? Our team helps you decide before preparation starts, so budget and samples are spent on the right experiments.

📄 Learn more: https://www.creative-proteomics.com/services/glycomics-service.htm

10/21/2026

🔬 Case study: when you alter glycosylation, does the ER itself change shape?

A team at the University of Liège and NYU Abu Dhabi published in Science Advances (Kerselidou et al., 2021) a multi-omics + imaging study identifying a glycosyltransferase that controls the size and tubular extension of the endoplasmic reticulum in mammalian cells.

For the glycan analysis component, the authors used N-glycans and O-glycans profiling provided by Creative Proteomics — MALDI-TOF-based glycan profiling that connected the genetic perturbation to its biochemical consequence, with glycan structural changes mapped to altered glycosyltransferase function.

The bigger lesson: glycosylation is not just cargo processing. The glycosylation machinery feeds back on ER dynamics — with real implications for protein folding capacity and secretory stress. If your model system touches glycosylation, it is worth asking what the ER is doing in response.

📄 Read the full paper: https://doi.org/10.1126/sciadv.abe8349

Integration of multiomics and imaging identifies a glycosyltransferase enzyme regulating endoplasmic reticulum sizes.

10/21/2026

📄 100 pg of protein, a complete N-glycome, ~1.5 hours of sample prep.

A new Nature Communications paper (Tursumamat et al., 2026) introduces seGRAP — a method that packs glycan reduction, desalting, permethylation, and enrichment into a single porous graphitized carbon tip, ending the multi-step extraction/drying cycle where low-input samples get lost.

The numbers: ✔ Intact high-mannose N-glycans detected from 100 pg RNase B (MALDI-TOF MS) ✔ N-glycome coverage from 2 pL of human plasma (nanoRPLC-MS) ✔ 27 single human oocytes analyzed → 46 N-glycan compositions, and a strikingly conserved oocyte N-glycome across individuals and maturation stages

Single-cell and low-input glycomics on routine MS platforms is now practical — rare cell populations and limited clinical specimens just became accessible to glycan-level questions. For labs without specialized instrumentation, that is the quiet revolution here.

Full paper: https://doi.org/10.1038/s41467-026-73050-y

Glycomic analysis of scarce material remains a major challenge, limiting insight into glycosylation in human biology and disease. Here, the authors develop seGRAP-MS, an ultrasensitive and accessible workflow enabling single-oocyte glycome profiling that reveals a conserved human oocyte N-glycome.

10/13/2026

🫀 New research: gut microbes may shape heart and kidney health years before symptoms appear.

A Nature Communications study (Chechi et al., 2026) mapped what the authors call the gut microbiome–kidney–heart axis:

✔ Plasma metabolomics + quantitative microbiome data from the MetaCardis cohort (n=1,877) ✔ Longitudinal validation in 8,669 people (CLSA) and ~20-year follow-up in EPIC-Norfolk (n=11,966)

The key players are microbial phenylalanine/tyrosine metabolites — phenylacetylglutamine, p-cresol sulfate, vanillactate, cinnamoylglycine. They mediate the link between microbiome composition and kidney function, and Mendelian randomization supports causality in both directions.

In the CLSA cohort, baseline levels of these metabolites predicted future myocardial infarction and all-cause mortality — and adding 6 of them to a clinical risk model improved prediction accuracy.

Interestingly, the "healthy" microbiome–metabolite associations largely vanished in cardiometabolic disease patients. The axis degrades as disease develops.

📄 Open access: https://doi.org/10.1038/s41467-026-69405-0

The gut microbiome-kidney crosstalk has been previously linked with metabolic and kidney diseases. Here, the authors show that microbial amino acid metabolism interacts with host kidney function to influence cardiorenal physiology in the early stages, with potential implications for long-term r...

10/13/2026

📚 Customer publication spotlight:

A 4-week pomegranate extract intervention raised plasma propionate by 162% — and the SCFA measurements behind that number came from our GC-MS platform.

In this randomized, double-blind, placebo-controlled trial (Sivamani et al., Foods, 2024), healthy adults took a standardized pomegranate extract (75 mg punicalagins/day). Metagenomics showed enrichment of SCFA-producing bacteria — Faecalibacterium prausnitzii, Roseburia, Ruminococcus — without changes in overall diversity.

🔬 For this study, the authors used short-chain fatty acid quantification (GC-MS) provided by Creative Proteomics to measure plasma SCFA concentrations, with 8-point calibration curves and selected-ion monitoring.

The payoff: propionate +162% (p = 0.02), acetate +38% (trend) — direct evidence that the microbial shift translated into functional output.

A solid template for diet–microbiome studies: sequence for who, quantify for what.

📄 Open access: https://doi.org/10.3390/foods13010015

Punica granatum L., commonly known as the pomegranate, is an abundant source of polyphenols, including hydrolyzable ellagitannins, ellagic acid, anthocyanins, and other bioactive phytochemicals shown to be effective in defending against oxidative stress, and has immunomodulatory activities. Ellagita...

10/13/2026

🦠 Sequencing tells you who lives in the gut. Metabolomics tells you what they're actually doing.

Most microbiome studies end at taxonomy — shifted abundances, diversity scores. But the mechanisms behind immune modulation, metabolic health, and drug response play out at the metabolite level: short-chain fatty acids, bile acids, tryptophan indoles, TMAO-pathway intermediates, bioamines.

Creative Proteomics' gut microbiota metabolomics service covers the whole loop:

✔ Untargeted discovery profiling (Orbitrap HRMS) for hypothesis generation ✔ Targeted absolute quantification (QTRAP 6500+ MRM) across 12+ metabolite classes ✔ SCFA quantification by GC-MS with absolute concentrations ✔ Pathway mapping + multi-omics integration packages

📄 F***s (from 50 mg), plasma, tissue, and culture supernatant all supported — with QC at every stage.

Whether it's a probiotic trial, dietary intervention, or drug–microbiome study, the metabolite layer is where the mechanism lives.

Learn more: https://metabolomics.creative-proteomics.com/gut-microbiota-metabolomics-services.htm

10/13/2026

🔬 Your neurotransmitter data may be missing half the story.

A single concentration measurement tells you how much dopamine or serotonin is in the sample. It cannot tell you whether that system is turning over fast or stalled — and that is often the real question in psychiatric drug studies and neurodegeneration models.

Creative Proteomics quantifies 30+ neurotransmitters and metabolites across 5 pathways in one LC-MS/MS workflow:

✔ Catecholamines: DA, NE, E + DOPAC, HVA, 3-MT, MHPG ✔ Serotonin/tryptophan: 5-HT, 5-HIAA, Trp, Kyn, melatonin ✔ GABA/glutamate, acetylcholine, histamine

Turnover ratios like HVA/DA and 5-HIAA/5-HT come standard — the dynamic readout reviewers ask for.

📄 Works with brain tissue, CSF, plasma, urine, and microdialysate — absolute quantification by stable isotope dilution, detection limits down to 0.01 ng/mL.

Full panel details: https://metabolomics.creative-proteomics.com/neurotransmitters-analysis-service.htm

Targeted LC-MS/MS quantification of 30+ neurotransmitters and metabolites across catecholamine, serotonin, GABA/glutamate, acetylcholine, and histamine pathways. Absolute quantification with stable isotope internal standards, turnover ratios, and full QC reporting for brain tissue, CSF, plasma, and....

10/08/2026

Paper Highlight: Microfluidic EV Analysis for Breast Cancer Subtyping

Extracellular vesicles carry membrane and cargo information directly from tumors, making them a promising target for blood-based diagnostics. The main obstacle is specificity — separating cancer-derived EVs from the normal circulating background.

A 2026 Nature Communications study by Zou, Jin, and colleagues presents a homotypic membrane electrochemical sensor. The device uses breast cancer cell membranes to capture matching cancer-derived EVs, then detects them with a silver nanoparticle–CD47 probe. In a blinded validation cohort of 90 breast cancer patients, 20 healthy controls, and 31 individuals with other diseases, the platform accurately identified ER-positive, HER2-positive, and triple-negative breast cancer subtypes.

The study shows that EV-based diagnostics can advance when capture chemistry is matched to the tumor biology.

Read the paper: https://doi.org/10.1038/s41467-026-68770-0

The cancer cell membrane replicates the characteristic molecular profile of its parental cells. Here, authors construct a homotypic membrane-powered biomimetic interface for subtype-specific analysis of breast cancer extracellular vesicles.

10/08/2026

Case Study: NK-Cell Extracellular Vesicles and Anti-Tumor Activity

Natural killer cells release extracellular vesicles that carry protein cargo able to induce cancer-cell death. Mapping that cargo is key to understanding how NK-cell EVs exert their effects.

In this Frontiers in Cell and Developmental Biology study, Cochran and Kornbluth isolated EVs from the NK3.3 human NK-cell line and tested their anti-tumor activity against K562 leukemia cells. For proteomic characterization of the K562 tumor cells after EV exposure, the authors used proteomic analysis provided by Creative Proteomics.

The research shows how mass spectrometry can connect the NK-cell EV proteome to downstream tumor-cell responses, moving the field from descriptive observations to mechanistic insight. For teams studying cell-based immunotherapies, EV cargo profiling opens a window into effector function that surface markers alone cannot provide.

Read the full paper: https://doi.org/10.3389/fcell.2021.698639

Natural killer (NK) cells are critical mediators of immune function, responsible for rapid destruction of tumor cells. They kill primarily through the relea...