Protein Detection Techniques

If you work in biologics, you need to read this article. (or at least, save it for later) It provides a comprehensive overview of where analytical methods are heading. Some of the key points to consider: 1. High-Resolution Mass Spectrometry (HRMS) is becoming essential. HRMS lets you identify post-translational modifications, impurities, and sequence details that older methods just can't catch. The paper highlights its value for peptide mapping, biosimilar comparisons, and identifying trace contaminants such as host cell proteins that ELISA reports as an aggregate. 2. Advanced chromatography continues to evolve - UHPLC - HILIC for glycan analysis - Two-dimensional LC - SEC with multi-angle light scattering (MALS). These techniques giving us a clearer view of protein aggregation, charge variants, and structural differences. 3. AI and machine learning are accelerating data interpretation These advanced tools generate massive amounts of data. AI is helping make sense of it through predictive modeling, anomaly detection, and automated analysis. 4. Single-cell and structural characterization methods are maturing Techniques like single-cell RNA sequencing, cryo-EM, and HDX-MS are showing us cellular and protein-level detail we couldn't see before. The through-line across all of this? Orthogonal methods. No single technique gives you the full picture. The paper points out what I see every day: the need to combine complementary analytical approaches to truly understand your product and de-risk your development program. Worth a read when you're thinking about analytical strategy. Anything else you'd point out?

PCR for proteins? Welcome to the world of detecting zepto-moles of protein (10⁻²¹) Many of us use PCR routinely out and probably don’t think too much about how revolutionary it was. It’s become the cornerstone of molecular diagnostics because you can take a single copy of a nucleic acid in 0.1ml of solution (10⁻²⁰ M) and amplify it by 7 orders of magnitude. There is nothing comparable for protein detection. While we can sequence single proteins through nanopores the detection of such tiny quantities of protein for diagnostics hasn’t been possible. ELISA can touch on fM (10⁻¹⁵) sensitivity with some serious development and luck but nothing gets close to PCR. It was with great surprise that while avoiding Deepseek posts this week I stumbled on a paper claiming a novel SPR based approach that can detect protein at 10⁻²⁰ M. Comparable to PCR and many orders of magnitude better than anything else reported. It’s buried in a materials science journal I’ve never heard of or read before! I’m not an SPR expert but here’s my take on it. The SPR sensor surface is densely coated with a thin layer of antibody or other protein. This then undergoes a mild pH conditioning, which partially unfolds some of the material. This puts the bio-material into a metastable state – it’s still functional but right on a cliff edge of changing state. When a target molecule binds it triggers a local conformational change. In standard SPR this change would be undetectable. However, due to the metastable state this local conformational change spreads across the entire layer driven by hydrophobic interactions between partially misfolded proteins in the biolayer. This self-propagating signal cascade amplifies a single binding event into a much larger signal. They show this working in 3 separate assays (anti-HIV, anti-IgG assay and KRAS), in serum with limits of detection at 10⁻²⁰ within an hour. This isn’t my space but it seems pretty mind blowing to me. Would love to hear what specialists in SPR and other assays think. Could this open up a new era for IVD where we can go after ultra-low concentration targets that seemed undetectable previously? Could this be converted into a point-of-care system? Work published in Advanced Materials by Eleonora Macchia and colleagues at the University of Bari in Italy. https://lnkd.in/e-GcyGrC And for those that aren’t so sure on their Greek names for these very small numbers: 10⁻⁹ = nano 10⁻¹² = pico 10⁻¹⁵ = femto 10⁻¹⁸ = atto 10⁻²¹ = zepto 10⁻²⁴ = yokto ----- I'm Ian, I post about antibody engineering, recombinant proteins and my journey to bootstrap Gamma Proteins into a leading supplier of Fc receptors. If you like my content please reshare with your network and follow me to see more.

🔬 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐬 𝐢𝐧 𝐈𝐄𝐗/𝐌𝐒 𝐟𝐨𝐫 𝐈𝐧𝐭𝐚𝐜𝐭 𝐏𝐫𝐨𝐭𝐞𝐢𝐧 & 𝐏𝐫𝐨𝐭𝐞𝐨𝐟𝐨𝐫𝐦 𝐂𝐡𝐚𝐫𝐚𝐜𝐭𝐞𝐫𝐢𝐳𝐚𝐭𝐢𝐨𝐧 💡 The characterization of intact proteins and their charge variants remains a critical step in understanding protein heterogeneity—especially in therapeutic contexts such as mAbs, ADCs, and viral vectors. This comprehensive review explores the recent evolution of non-denaturing IEX–MS, with a strong focus on pH-gradient-based methods as an alternative to traditional salt gradients. These developments are particularly valuable for native MS applications, enabling analysis while preserving protein structure and non-covalent interactions. ⚖️ 𝐊𝐞𝐲 𝐭𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐭𝐡𝐞𝐦𝐞𝐬 𝐜𝐨𝐯𝐞𝐫𝐞𝐝 𝐢𝐧𝐜𝐥𝐮𝐝𝐞: 🧪 𝑝𝐻-𝑔𝑟𝑎𝑑𝑖𝑒𝑛𝑡 𝑠𝑡𝑟𝑎𝑡𝑒𝑔𝑖𝑒𝑠 → Chromatofocusing → Linear pH gradients → Salt-mediated pH gradients 💧 𝑉𝑜𝑙𝑎𝑡𝑖𝑙𝑒 𝑏𝑢𝑓𝑓𝑒𝑟 𝑠𝑦𝑠𝑡𝑒𝑚𝑠 → Challenges in achieving linear pH gradients using MS-compatible additives like ammonium acetate and formate → Emerging use of novel volatile buffers (e.g., DFEA, TFEA) to fill critical pH gaps 🧱 𝑆𝑡𝑎𝑡𝑖𝑜𝑛𝑎𝑟𝑦 𝑝ℎ𝑎𝑠𝑒𝑠 𝑎𝑛𝑑 𝑐𝑜𝑙𝑢𝑚𝑛 𝑠𝑒𝑙𝑒𝑐𝑡𝑖𝑜𝑛 → Emphasis on nonporous polymeric materials for enhanced resolution → Role of particle size, hydrophilicity, and charge density in minimizing protein denaturation 🧬 𝐷𝑖𝑟𝑒𝑐𝑡 𝐼𝐸𝑋–𝑀𝑆 𝑐𝑜𝑢𝑝𝑙𝑖𝑛𝑔 𝑡𝑒𝑐ℎ𝑛𝑖𝑞𝑢𝑒𝑠 → Micro/nano-flow LC → Post-column flow splitting → Dopant-enriched nitrogen → Multi-nozzle ESI and nano-IEX–MS for ultra-sensitive detection The review also outlines how IEX–MS supports precise identification of charge variants arising from PTMs, including deamidation, sialylation, phosphorylation, and C-terminal modifications—essential insights for CQA profiling of biopharmaceuticals. 🎯 𝐊𝐞𝐲 𝐓𝐚𝐤𝐞-𝐀𝐰𝐚𝐲𝐬: • ⚛️ pH gradient-based IEC enables MS-compatible, non-denaturing separation of charge variants in intact proteins. • 🧫 Volatile buffer system development is a bottleneck in achieving linear pH control and high-resolution separations. • 💡 Salt-mediated pH gradients offer enhanced selectivity and better MS performance with reduced ion suppression. • 🔍 Column material, flow rate, and ESI strategies critically impact resolution, sensitivity, and native MS compatibility. • 🧬 IEX–MS is becoming increasingly essential for high-resolution profiling of therapeutic protein heterogeneity. #Proteomics #MassSpectrometry #IonExchangeChromatography #Biopharmaceuticals #AnalyticalScience #ProteinCharacterization #TopDownProteomics #NativeMS #ChargeVariants #PTMs #CQA #mAbs #ADC #ViralVectors Ziran Zhai, Thomas Holmark, Lars J. & Andrea Gargano University of Amsterdam

Multiplexed proteomics is getting a big boost 🚀 It's not just speed & scale. 👉 It's also data quality, depth, rich spectra improving de novo sequencing & accurate quantification. Mass spectrometry-based proteomics enables comprehensive characterization of protein abundance, function, and interactions. Label-free approaches are simple to implement but challenging to scale to thousands of samples per day. Multiplexed techniques, such as plexDIA, can address these limitations but remain restricted by the lack of mass tags optimized for data-independent acquisition (DIA) workflows. Here, we present a systematic approach screening a library of 576 compounds that identifies several small molecules that, when conjugated to peptides, improve their detection and sequence identification by mass spectrometry. The lead molecule, PSMtag, substantially increases the detection of fragment b-ions, which increases the confidence of sequence identification and enhances de novo sequencing. PSMtags allow 9-plexDIA, using only stable isotopes of carbon, oxygen and nitrogen. As a result, it allows simultaneously increasing proteome coverage and sample throughput for plexDIA workflows without compromising quantitative accuracy. We demonstrate 240 samples-per-day with 9-plexDIA, while acquiring 28,359 protein data points in the same time label-free methods acquire 4,340. Our approach constitutes an expandable framework for designing mass tags to overcome existing limitations in multiplexed proteomics and provides plexDIA reagents capable of analyzing over 1,000 samples per day when using 10 minute runs. By facilitating higher throughput and improved identification, this innovation holds significant potential for accelerating proteomic studies across diverse biological and clinical applications. https://lnkd.in/enrfCyKV

Switzerland: EPFL scientists build first self-illuminating biosensor. Engineers harnessed quantum physics to detect the presence of biomolecules without the need for an external light source, overcoming a significant obstacle to the use of optical biosensors in healthcare and environmental monitoring settings. Participating institutions: ETH Zurich, ICFO (Spain), and Yonsei University (Korea). 26 June 2025. Excerpt: Optical biosensors use light waves as a probe to detect molecules, and are essential for precise medical diagnostics, personalized medicine, and environmental monitoring. Their performance is dramatically enhanced if the sensors can focus light waves down to the nanometer scale – small enough to detect proteins or amino acids, for example – using nanophotonic structures that ‘squeeze’ light at the surface of a tiny chip. The generation and detection of light for nanophotonic biosensors requires bulky, expensive equipment that greatly limits their use in rapid diagnostics or point-of-care settings. The design of the team’s nanostructure creates just the right conditions for an electron passing upward through it to cross a barrier of aluminum oxide and arrive at an ultrathin layer of gold. In the process, the electron transfers some of its energy to a plasmon, which then emits a photon. Their design ensures the intensity and spectrum of light changes in response to contact with biomolecules, resulting in a powerful method for extremely sensitive, real-time, label-free detection. Key: “Tests showed our self-illuminating biosensor can detect amino acids and polymers at picogram concentrations – that’s one-trillionth of a gram – rivaling the most advanced sensors available today,” says Bionanophotonic Systems Laboratory head Hatice Altug. Refer to the enclosed press release further information. The work has been published in Nature Photonics (26 June) in collaboration with researchers at ETH Zurich, ICFO (Spain), and Yonsei University (Korea). https://lnkd.in/eC8SqVh8

How to Use Immunohistochemistry (IHC) for Disease Diagnosis and Pathology Research Immunohistochemistry (IHC) is an important tool in disease diagnosis and pathology research that allows visualization of specific proteins in tissue samples. This technique provides insight into disease mechanisms, helps improve diagnostic accuracy, and guides treatment plans. The following is a step-by-step guide to using IHC in these situations: 1. Tissue preparation Tissue samples are obtained from biopsies or surgical specimens and fixed in formalin to preserve cellular structure and proteins. Tissues are embedded in paraffin and cut into thin sections (3-5 µm) for mounting on microscope slides. 2. Dewaxing and antigen retrieval Paraffin is removed with xylene and sections are rehydrated through a graded series of ethanol. Antigen retrieval is performed using heat-induced epitope retrieval (HIER) or enzymatic digestion to restore antibody binding sites. 3. Blocking If an enzyme-based assay is used, endogenous peroxidase activity is blocked using hydrogen peroxide. Blocking buffers (e.g., serum or BSA) are used to reduce nonspecific binding and background staining. 4. Primary Antibody Incubation Incubate tissue with primary antibodies against disease-associated proteins (e.g., HER2 for breast cancer, amyloid-β for Alzheimer's disease). Optimize incubation time and temperature to achieve strong, specific staining. 5. Secondary Antibodies and Detection Add secondary antibodies conjugated to enzymes (e.g., HRP) or fluorophores. Develop with DAB (brown) or visualize using fluorescence microscopy. 6. Counterstaining and Imaging Counterstained with hematoxylin to distinguish nuclei and tissue architecture. Visualize protein expression under light or fluorescence microscopy to identify disease-specific markers. 7. Applications in Diagnosis and Pathology (1) Cancer Diagnosis: Cancer classification and prognosis can be determined by detecting biomarkers such as HER2, Ki-67, or p53. (2) Infectious Disease Diagnosis: Pathogens can be identified using antibodies against microbial antigens. (3) Neurodegenerative Disease Diagnosis: Neurodegenerative diseases can be diagnosed by visualizing proteins such as tau or amyloid-β. In conclusion, IHC can effectively improve the accuracy of disease diagnosis, thereby providing valuable insights into disease characteristics and progression. References [1] So-Woon Kim et al., Journal of Pathology and Translational Medicine 2014 (doi: 10.4132/jptm.2016.08.08) [2] Di Ai et al., Modern Pathology 2020 (DOI: 10.1038/s41379-020-00692-8) #IHC #DiseaseDiagnosis #Pathology #BiomedicalResearch #CancerBiomarkers #Immunohistochemistry #MolecularBiology #PrecisionMedicine

This image compares three types of blotting techniques used to detect specific molecules: Southern Blot, Northern Blot, and Western Blot. These methods help analyze DNA, RNA, and protein, respectively. Key Points: 1. Southern Blot (DNA) Detects specific DNA fragments. Steps: DNA is cut using restriction enzymes. Gel electrophoresis separates fragments on agarose gel. Transferred to a membrane and probed with complementary single-stranded DNA or RNA. Results: Allows detection of specific DNA sequences and measurement of fragment size and quantity. 2. Northern Blot (RNA) Detects specific RNA transcripts (e.g., mRNA). Steps: RNA is separated using gel electrophoresis on agarose gel. Transferred to a membrane and probed with single-stranded DNA or RNA complementary to the transcript. Results: Identifies RNA fragments, their size, and the level of expression. 3. Western Blot (Protein) Detects specific proteins. Steps: Proteins are denatured and separated using electrophoresis on acrylamide gel. Transferred to a membrane. Primary antibodies bind to the target protein, and secondary antibodies amplify detection. Results: Measures protein size and expression levels. Summary of Differences: Target Molecule: DNA (Southern), RNA (Northern), Protein (Western). Gel Type: Agarose for DNA/RNA; Acrylamide for protein. Probes: Southern/Northern: Single-stranded complementary sequences. Western: Antibodies. Each blotting method provides unique insights into gene expression, genetic sequences, and protein analysis, making them essential tools in molecular biology.

SDS-PAGE (Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis) is a laboratory technique used to separate proteins based on their molecular weight. The process involves several key steps: 1. Denaturation: Proteins are treated with SDS, a detergent, which denatures them by disrupting non-covalent interactions, causing the proteins to unfold into linear chains. SDS also coats the proteins with a negative charge, ensuring they migrate toward the positive electrode during electrophoresis. 2. Polyacrylamide Gel: The proteins are then loaded into a gel matrix made of polyacrylamide. This gel acts as a molecular sieve, allowing smaller proteins to move faster through the matrix than larger ones during the electrophoresis process. 3. Electrophoresis: An electric field is applied to the gel, causing the negatively charged protein-SDS complexes to migrate toward the positive electrode. The proteins move through the gel at different rates depending on their size, with smaller proteins traveling faster than larger ones. 4. Staining: After electrophoresis, the gel is stained with a dye (e.g., Coomassie Brilliant Blue or silver stain) to visualize the protein bands, allowing researchers to estimate the size of the proteins based on their migration relative to known molecular weight markers. SDS-PAGE is commonly used for protein analysis, including determining the molecular weight of proteins, checking protein purity, and assessing the presence of specific proteins in a sample.

🔬 **Revolutionizing Protein Analysis with Charge Detection Mass Spectrometry (CDMS)! 🚀** 🔍Charge detection mass spectrometry (CDMS) provides direct mass measurements of varied samples by identifying the charge state and mass-to-charge ratio of individual ions. This method differs from standard mass spectrometry, which measures large groups of ions. Juetten et al study showcases the integration of Fourier transform multiplexing and drift tube ion mobility with Orbitrap-based CDMS for analyzing protein complexes. 🎯 Summary: Direct Mass Measurement Enabled precise measurements of heterogeneous samples at the single-ion level. Juetten et al observed that by utilizing stepped frequency modulation, we improved the accuracy and signal-to-noise ratio of ion mobility spectra. Juetten et al method provides crucial insights into each ion's size and mass, allowing for unambiguous frequency assignments during mobility sweeps. This innovative approach addresses the duty cycle mismatch of online separation techniques, paving the way for more efficient protein characterization. 🔗 Check out the full paper here 📌 https://lnkd.in/eZqEmiyP #massspectrometry ##massspec #science #scienceandtechnology #chemistry #pharma #qualitycontrol #mabs #proteins