Proteins In Biological Samples Research Articles

Rapid determination of toxic and essential metal binding proteins in biological samples by size exclusion chromatography-inductively coupled plasma tandem mass spectrometry

Metalloproteins binding with trace elements play a crucial role in biological processes and on the contrary, those binding with exogenous heavy metals have adverse effects. However, the methods for rapid, high sensitivity and simultaneous analysis of these metalloproteins are still lacking. In this study, a fast method for simultaneously determination of both essential and toxic metal-containing proteins was developed by coupling size exclusion chromatography (SEC) with inductively coupled plasma tandem mass spectrometry (ICP-MS/MS). After optimization of the separation and detection conditions, seven metalloproteins with different molecular weight (from 16.0 to 443.0 kDa) were successfully separated within 10 min and the proteins containing iron (Fe), copper (Cu), zinc (Zn), iodine (I) and lead (Pb) elements could be simultaneously detected with the use of oxygen as the collision gas in ICP-MS/MS. Accordingly, the linear relationship between log molecular weight and retention time was established to estimate the molecular weight of unknown proteins. Thus, the trace metal and toxic metal containing proteins could be detected in a single run with high sensitivity (detection limits in the range of 0.0020 – 2.5 μg/mL) and good repeatability (relative standard deviations lower than 4.5 %). This method was then successfully used to analyze metal (e.g., Pb, Zn, Cu and Fe) binding proteins in the blood of Pb-intoxicated patients, and the results showed a negative correlation between the contents of zinc and lead binding proteins, which was identified to contain hemoglobin subunit. In summary, this work provided a rapid and sensitive tool for screening metal containing proteins in large number of biological samples.

Recent Advances in Molecular Imprinting for Proteins on Magnetic Microspheres.

The separation of proteins in biological samples plays an essential role in the development of disease detection, drug discovery, and biological analysis. Protein imprinted polymers (PIPs) serve as a tool to capture target proteins specifically and selectively from complex media for separation purposes. Whereas conventional molecularly imprinted polymer is time-consuming in terms of incubation studies and solvent removal, magnetic particles are introduced using their magnetic properties for sedimentation and separation, resulting in saving extraction and centrifugation steps. Magnetic protein imprinted polymers (MPIPs), which combine molecularly imprinting materials with magnetic properties, have emerged as a new area of research hotspot. This review provides an overview of MPIPs for proteins, including synthesis, preparation strategies, and applications. Moreover, it also looks forward to the future directions for research in this emerging field.

Time-encoded electrical detection of trace RNA biomarker by integrating programmable molecular amplifier on chip

One of the serious challenges facing modern point-of-care (PoC) molecular diagnostic platforms relate to reliable detection of low concentration biomarkers such as nucleic acids or proteins in biological samples. Non-specific analyte-receptor interactions due to competitive binding in the presence of abundant molecules, inefficient mass transport and very low number of analyte molecules in sample volume, in general pose critical hurdles for successful implementation of such PoC platforms for clinical use. Focusing on these specific challenges, this work reports a unique PoC biosensor that combines the advantages of nanoscale biologically-sensitive field-effect transistor arrays (BioFET-arrays) realized in a wafer-scale top-down nanofabrication as high sensitivity electrical transducers with that of sophisticated molecular programs (MPs) customized for selective recognition of analyte miRNAs and amplification resulting in an overall augmentation of signal transduction strategy. The MPs realize a programmable universal molecular amplifier (PUMA) in fluidic matrix on chip and provide a biomarker-triggered exponential release of small nucleic acid sequences easily detected by receptor-modified BioFETs. A common miRNA biomarker LET7a was selected for successful demonstration of this novel biosensor, achieving limit of detection (LoD) down to 10 fM and wide dynamic ranges (10 pM–10 nM) in complex physiological solutions. As the determination of biomarker concentration is implemented by following the electrical signal related to analyte-triggered PUMA in time-domain instead of measuring the threshold shifts of BioFETs, and circumvents direct hybridization of biomarkers at transducer surface, this new strategy also allows for multiple usage (>3 times) of the biosensor platform suggesting exceptional cost-effectiveness for practical use.

Recent Advances in Lateral Flow Assays for Viral Protein Detection with Nanomaterial-Based Optical Sensors.

Controlling the progression of contagious diseases is crucial for public health management, emphasizing the importance of early viral infection diagnosis. In response, lateral flow assays (LFAs) have been successfully utilized in point-of-care (POC) testing, emerging as a viable alternative to more traditional diagnostic methods. Recent advancements in virus detection have primarily leveraged methods such as reverse transcription-polymerase chain reaction (RT-PCR), reverse transcription-loop-mediated isothermal amplification (RT-LAMP), and the enzyme-linked immunosorbent assay (ELISA). Despite their proven effectiveness, these conventional techniques are often expensive, require specialized expertise, and consume a significant amount of time. In contrast, LFAs utilize nanomaterial-based optical sensing technologies, including colorimetric, fluorescence, and surface-enhanced Raman scattering (SERS), offering quick, straightforward analyses with minimal training and infrastructure requirements for detecting viral proteins in biological samples. This review describes the composition and mechanism of and recent advancements in LFAs for viral protein detection, categorizing them into colorimetric, fluorescent, and SERS-based techniques. Despite significant progress, developing a simple, stable, highly sensitive, and selective LFA system remains a formidable challenge. Nevertheless, an advanced LFA system promises not only to enhance clinical diagnostics but also to extend its utility to environmental monitoring and beyond, demonstrating its potential to revolutionize both healthcare and environmental safety.

Abstract 1847: Human protein atlas: A resource for target expression across 19 tissues

Abstract Proteins are the primary targets and off-targets of therapeutics such as small molecule and biologics. Thus, a thorough understanding of their expression profiles across various human tissues in health and disease is essential through all stages of drug development. However, generating such a comprehensive proteome profile for each tissue poses a major analytical challenge due to the large dynamic range of protein abundance within a tissue and the enormous complexity introduced by distinct proteoforms. These proteoforms may arise from genetic variations (e.g. mutations), posttranscriptional events (e.g. isoforms from alternative splicing) or posttranslational modifications, resulting in more than a million protein species from 20,000 protein-coding genes. Thanks to advancements in sensitivity and speed in the recent years, mass spectrometry (MS)-based proteomics can now be routinely applied to quantify ten thousand of proteins in biological samples. Taking advantage of MS being an unbiased and matrix-agnostic method, we pivoted the generation of a high quality and uniform protein expression atlas of 19 healthy human tissues and 3 cancerous tissues. We constructed the atlas in two parts aiming to address the following two aspects respectively: 1) a deep library providing evidence for protein/proteoform presence in each of the 22 tissues; 2) quantitative profiles for cross-comparison in all tissues. For the first part, each tissue sample was subjected to an extensive fractionation process followed by MS analysis of each of the fractions. In total, we identified 20’025 protein groups mapped to 17’715 protein-coding genes, providing protein-level evidence for > 90% of all protein-coding genes annotated in the neXtProt repository. Among all identified proteins, 10’755 were detectable across all tissues. Notably, we identified 37 proteins mapping to putative genes. In part two of the atlas, quantitative expression profiles were generated for 15’772 protein groups using TrueDiscovery DIA-MS across the 22 tissues. These data allow us to investigate ubiquitous vs. tissue-restricted protein expression of various protein classes such as surface receptors or kinases. Moreover, we performed correlation analysis between protein expression and mRNA abundance across 19 tissues, demonstrating that for a significant portion of the proteome, mRNA level-information is not an adequate proxy for protein expression. Collectively, this MS-based resource alleviates dependency on antibody-based reagents. We envision that the tissue atlas can be expanded to cover various disease indications, providing valuable insights for target discovery and assessment of target/off-target tissue distribution. Citation Format: Sandra Schaer, Marco Tognetti, Roland Bruderer, Polina Shichkova, Yuehan Feng, Lukas Reiter. Human protein atlas: A resource for target expression across 19 tissues [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1847.

Enhancing affinity purification of monoclonal antibodies from human serum for subsequent CZE-MS analysis

Due to the separation technique employed, capillary electrophoresis coupled to mass spectrometry (CE-MS) analysis performances are significantly influenced by the chemical composition and the complexity of the sample. In various applications, that impact has prevented the use of CE-MS for the characterization and quantification of proteins in biological samples. Here we present the development and evaluation and a sample preparation procedure, based on affinity purification, for the specific extraction of the monoclonal antibody (mAbs) infliximab from human serum in order to perform subsequent proteolytic digestion and CE-MS/MS analysis. Three distinctive sample preparation strategies were envisaged. In each case, the different steps composing the protocol were thoroughly optimized and evaluated in order to provide a sample preparation addressing the important complexity of serums samples while providing an optimal compatibility with CE-MS/MS analysis. The different sample preparation strategies were assessed concerning the possibility to achieve an appropriate absolute quantification of the mAbs using CE-MS/MS for samples mimicking patient serum samples. Also, the possibility to perform the characterization of several types of post-translational modifications (PTMs) was evaluated. The sample preparation protocols allowed the quantification of the mAbs in serums samples for concentration as low as 0.2 µg·mL−1 (2.03 nM) using CE-MS/MS analysis, also the possibility to characterize and estimate the modification level of PTMs hotspots in a consistent manner. Results allowed to attribute the effect on the electrophoretic separation of the different steps composing sample preparation. Finally, they demonstrated that sample preparation for CE-MS/MS analysis could benefit greatly for the extended applicability of this type of analysis for complex biological matrices.

Peptide-Based Mass Spectrometry for the Investigation of Protein Complexes.

In the last two decades, biological mass spectrometry has become the gold standard for the identification of proteins in biological samples. The technological advancement of mass spectrometers and the development of methods for ionization, gas phase transfer, peptide fragmentation as well as for acquisition of high-resolution mass spectrometric data marked the success of the technique. This chapter introduces peptide-based mass spectrometry as a tool for the investigation of protein complexes. It provides an overview of the main steps for sample preparation starting from protein fractionation, reduction, alkylation and focus on the final step of protein digestion. The basic concepts of biological mass spectrometry as well as details about instrumental analysis and data acquisition are described. Finally, the most common methods for data analysis and sequence determination are summarized with an emphasis on its application to protein-protein complexes.

A Comparative Study of Deep Learning Approaches for Amyotrophic Lateral Sclerosis Super-Resolution Image Classification

Amyotrophic lateral sclerosis is a fatal degenerative neurological disease known as motor neuron disease. According to research, amyotrophic lateral sclerosis affects nerve cells related to movement in the brain and spinal cord, leading to the death of motor neurons, making the brain unable to control muscle movement, and resulting in a significant loss of motor nerve cells, leading to muscle atrophy. In the early stages of ALS, symptoms are mild, often go unnoticed, and can easily be confused with other diseases. Patients may only feel symptoms such as weakness, convulsions, and fatigue, gradually develop muscle atrophy all over the body, difficulty swallowing, and finally die of respiratory failure. TDP-43 is a DNA/RNA binding protein typically located in the nucleus regulating various steps of RNA metabolism. Meanwhile, TDP-43 is the most prominent pathological protein in the characteristics of ALS patients.[1] TDP-43 is depleted in the nucleus in nearly all ALS cases but accumulates in the cytoplasm.Deep learning is learning the internal laws and representation levels of sample data. The information obtained from these learning processes can significantly help interpret data such as text, images, and sounds. Its goal is to enable machines to analyze and learn like humans and recognize data. Additionally, super-resolution microscopy can be used to observe the conformation of proteins in biological samples, thereby gaining insight into the structure and assembly mechanism of TDP-43 aggregates.This project aims to use super-resolution images for machine learning to build a model for classifying ALS patients from non-ALS patients. At the same time, multiple neural network models are used for training and then compared to select the model with the highest accuracy.

Anti-SpCas9 IgY Polyclonal Antibodies Production for CRISPR Research Use.

The CRISPR/Cas adaptative immune system has been harnessed as an RNA-guided, programmable genome editing tool, allowing for diverse biotechnological applications. The implementation of the system relies on the ability to detect the Cas9 protein in biological samples. This task is facilitated by employing antibodies, which exhibit several advantageous features and applications in the context of tropical neglected diseases. This study reports a one-month immunization scheme with the Cas9 protein fromStreptococcus pyogenes to produce IgY polyclonal antibodies (anti-SpCas9), which can be rapidly isolated by combining yolk de-lipidation with protein salting out using pectin and ammonium sulfate, respectively. Immunodetection assays indicate that the antibodies are highly sensitive, specific, and useful for detecting the SpCas9 protein in promastigotes ofLeishmania braziliensisexpressing exogenous SpCas9. Thus, the simple method for producing anti-SpCas9 IgY antibodies will accelerate CRISPR/Cas-based studies in Leishmania spp. This approach serves as a valuable research tool in this parasite model and holds the potential for wide application in various other biological samples, promoting the implementation of the system. In fact, a bioinformatics approach based on the identification of antigenic determinants in the SpCas9 protein suggests the possibility of using the anti-SpCas9 IgY antibodies in applications such as Prime and Base editing.

Tailoring the Amphiphilicity of Fluorescent Protein Chromophores to Detect Intracellular Proteome Aggregation in Diverse Biological Samples.

The formation of amorphous misfolded and aggregated proteins is a hallmark of proteome stress in diseased cells. Given its lack of defined targeting sites, the rational design of intracellular proteome aggregation sensors has been challenging. Herein, we modulate the amphiphilicity of fluorescent protein chromophores to enable selective detection of aggregated proteins in different biological samples, including recombinant proteins, stressed live cells, intoxicated mouse liver tissue, and human hepatocellular carcinoma tissue. By tuning the number of hydroxyl groups, we optimize the selectivity of fluorescent protein chromophores toward aggregated proteins in these biological samples. In recombinant protein applications, the most hydrophobic P0 (cLogP = 5.28) offers the highest fold change (FC = 31.6), sensitivity (LLOD = 0.1 μM), and brightness (Φ = 0.20) upon binding to aggregated proteins. In contrast, P4 of balanced amphiphilicity (cLogP = 2.32) is required for selective detection of proteome stresses in live cells. In mouse and human liver histology tissues, hydrophobic P1 exhibits the best performance in staining the aggregated proteome. Overall, the amphiphilicity of fluorescent chromophores governs the sensor's performance by matching the diverse nature of different biological samples. Together with common extracellular amyloid sensors (e.g., Thioflavin T), these sensors developed herein for intracellular amorphous aggregation complement the toolbox to study protein aggregation.

Western Blotting with Fast SDS-PAGE and Semi-Dry Protein Transfer.

Western blotting is a method widely used in cell and molecular biology for the specific detection of proteins in biological samples. It is time-consuming and normally takes up to 2 days to complete. This protocol introduces a more time-efficient method to complete western blots, covering the preparation of protein extracts (including strategies for solubilization), electrophoretic separation of proteins, transfer of proteins to the membrane, and probing with antibodies. We describe an SDS-PAGE protocol that achieves a gradient-like separation of proteins (10-400 kDa) on a single-percentage polyacrylamide gel in only 45 min. Additionally, we present a rapid (10-14 min) semi-dry transfer of proteins from standard Tris/glycine polyacrylamide gels onto a membrane using homemade Tris/HEPES- or Tris/EPPS-based buffers. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) Support Protocol 1: Cell lysis and protein extraction Support Protocol 2: Protein quantification with BCA assay and sample preparation for loading on gel Basic Protocol 2: Protein transfer with a fast semi-dry transfer (FSDT) buffer Basic Protocol 3: Immunoprobing, chemiluminescent visualization, stripping, and reuse of membranes.

Establishing an immunological profile of 96 cytokines, chemokines, and growth factors in human biofluids via MILLIPLEX® multiplex immunoassay

Abstract Multiplex immunoassays are well-established research tools enabling the simultaneous measurement of several proteins in biological samples. In the field of immunology, these immunoassay kits have been critically important for profiling the expression of a wide array of immunomodulatory proteins, including cytokines, chemokines, and growth factors. To this end, we recently developed two MILLIPLEX® multiplex immunoassay kits, each capable of the simultaneous measurement of 48 unique proteins in human samples. In this study, our objective was to profile the relative abundance of 96 cytokines, chemokines, and growth factors in a diverse collection of human biofluids, including serum, plasma, cerebrospinal fluid, saliva, sputum, urine, tears, milk, synovial fluid, and bronchoalveolar lavage (BAL). For each analyte, the fold increase in the average sample measurement relative to the limit of detection was determined. Some biofluids were generally rich in these immunological factors, such as BAL samples, whereas others were sparse, as noted in milk samples. Additionally, the reagent compatibility of the two immunoassay kits used to interrogate the sample cohort was examined to define opportunities for developing novel custom multiplex immunoassays containing analytes from each of the parent kits. The result of this effort was the generation of a set of rules guiding the acceptable combinations amongst the 96 proteins as well as the identification of mutually exclusive protein targets.

Discrimination of cationic peptides using malaria translocon, EXP2, nanopores.

Protein identification provides crucial information on the extensive biochemical reaction in our life. Although mass spectrometry has generally been used for protein/peptide identification, the scarcity of proteins in biological samples and post-translational modifications have remained a challenge. Nanopores, which provide rapid and sensitive single-molecule analysis have attracted attention as an alternative to these techniques. The sensing accuracy of nanopores mainly depends on the congeniality of electrostatic affinity and size between the nanopores and molecules. In this study, we evaluated the capability of peptide detection on EXP2 nanopore, which intrinsically transports a polypeptide chain in vivo as a malaria translocon, using peptides with different sizes and numbers of charges. Our previous studies found that wild-typed EXP2 (Wt-EXP2) nanopore could detect and identify two types of poly-L-lysine (short poly-L-lysine: 10,000 Da, long poly-L-lysine: 30,000-70,000 Da) with different molecular weights. Although the Wt-EXP2 nanopore could discriminate the poly-cationic peptides, the inherent current noise of the Wt-EXP2 nanopore in the analyte-free state interfered with more accurate single-molecule detection. This current noise probably owing to the fluctuation of its C-terminus region, so we designed ΔD231-EXP2, a variant with the deletion of the C-terminus region. The result shows that the current noise frequency of ΔD231-EXP2 nanopore decreased by half compared with Wt-EXP2, and we succeeded in discriminating the two types of oligo-arginine (R7X, X=W, G). Furthermore, the capture frequencies of these cationic peptides of the EXP2 nanopore were higher than the α-hemolysin nanopore. ΔD231-EXP2 nanopore also could identify the five types of trypsinized fragments (893.4-1,429 Da) from lysozyme. These results suggest that the EXP2 nanopore may be suitable for cationic peptides detection and identification. We are going to apply another variant EXP2NC (K42D+S46F) whose amino acid in the constriction region is exchanged for more accurate peptide identification.

Proteomics Evaluation of Semen of Clinically Healthy Beagle-Breed Dogs.

The objectives of the present work were to evaluate the semen of dogs by means of proteomics methods and to compare with proteomics results of the blood of the animals, in order to increase available knowledge on the topic and present relevant reference values for semen samples. Semen samples were collected from five Beagle-breed dogs. Reproductive assessment of the animals by means of clinical, ultrasonographic and seminological examinations confirmed their reproductive health. The sperm-rich fraction and the prostatic fraction of semen were processed for proteomics evaluation. LC-MS/MS analysis was performed by means of a LTQ Orbitrap Elite system. The technology combines high separation capacity and strong qualitative ability of proteins in biological samples that require deep proteome coverage. Protein classification was performed based on their functional annotations using Gene Ontology (GO). In blood plasma, semen sperm-rich fraction, and semen prostatic fraction, 59, 42 and 43 proteins, respectively, were detected. Two proteins were identified simultaneously in plasma and the semen sperm-rich fraction, 11 proteins in plasma and the semen prostatic fraction, and three proteins in the semen sperm-rich and prostatic fractions. In semen samples, most proteins were related to cell organization and biogenesis, metabolic processes or transport of ions and molecules. Most proteins were located in the cell membrane, the cytosol or the nucleus. Finally, most proteins performed functions related to binding or enzyme regulation. There were no differences between the semen sperm-rich fraction and prostatic fractions in terms of the clustering of proteins. In conclusion, a baseline reference for proteins in the semen of Beagle-breed dogs is provided. These proteins are involved mostly in supporting spermatozoan maturation, survival and motility, enhancing the reproductive performance of male animals. There appears potential for the proteomics examination of semen to become a tool in semen evaluation. This analysis may potentially identify biomarkers for reproductive disorders. This can be particularly useful in stud animals, also given its advantage as a non-invasive method.

Association of Vegetable and Fruit Consumption with Urinary Oxidative Biomarkers in Teenaged Girls: A School-Based Pilot Study in Japan.

Hexanoyl-lysine (HEL), 8-hydroxy-2′deoxyguanosine (8-OHdG), and dityrosine (DT) have served as potential biomarkers for detecting oxidative modified lipids, DNA, and proteins in biological samples, respectively. Whether regular higher levels of consumption of vegetables/fruit (V/F) would decrease oxidative modification of these biomolecules in the body remain unelucidated. To examine the association of regular V/F consumption with the generation of these reactive oxygen species-induced biomarkers, this study evaluated V/F consumption in a school-based sample of teenaged girls (mean age 15.6 ± 1.7 years, n = 103), and quantified the formation of oxidative stress biomarkers in their urine. Only 19.4% and 23.3% of participants reported that they consumed the recommended daily amount of vegetables and fruits, respectively. Individuals who consumed lower levels of fruit (<100g/day) or vegetables (<250g/day) had significantly higher HEL excretion in their urine than those who consumed higher levels of fruit (≥100g/day) (p < 0.05) or vegetables (≥250g/day) (p = 0.057). The results of a multiple regression analysis showed that vegetable consumption was an important inhibiting factor of early lipid peroxidation measured as HEL in urine, independent of various confounders (β = − 0.332, p < 0.05). The findings suggest that relatively higher consumption of vegetables would help in the prevention of early lipid peroxidation in adolescents.

Laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS)-based strategies applied for the analysis of metal-binding protein in biological samples: an update on recent advances.

New analytical strategies for metal-binding protein facilitate researchers learning about how metals play a significant role in life. Laser ablation-inductively coupled plasmamass spectrometry (LA-ICP-MS) offers many advantages for the metal analysis of biological samples and shows a promising future in protein analysis, but recent advances in LA-ICP-MS-based strategies for identifying metal-binding proteins via endogenous metals remain less updated yet. To present the current status in this field, the main analytical strategies for metal-binding proteins with LA-ICP-MS are reviewed here, including in situ analysis of biospecimens and ex situ analysis with gel electrophoresis. A critical discussion of challenges and future perspectives is also given. Multifarious laser ablation-inductively coupled plasmamass spectrometry (LA-ICP-MS)-based strategies have been developed and applied to investigate the metal-binding proteins in biospecimens in situ or through gel electrophoresis ex situ over the past decades, facilitating researchers disclosing how essential metals are implicated in life or what proteins toxic metals will target.

A DISTRIBUTED ALGORITHM FOR PROTEIN IDENTIFICATION FROM TANDEM MASS SPECTROMETRY DATA

Tandem mass spectrometry is an analytical technique widely used in proteomics for the high-throughput characterization of proteins in biological samples. Modern in-depth proteomic studies require the collection of even millions of mass spectra representing short protein fragments (peptides). In order to identify the peptides, the measured spectra are most often scored against a database of amino acid sequences of known proteins. Due to the volume of input data and the sizes of proteomic databases, this is a resource-intensive task, which requires an efficient and scalable computational strategy. Here, we present SparkMS, an algorithm for peptide and protein identification from mass spectrometry data explicitly designed to work in a distributed computational environment. To achieve the required performance and scalability, we use Apache Spark, a modern framework that is becoming increasingly popular not only in the field of “big data” analysis but also in bioinformatics. This paper describes the algorithm in detail and demonstrates its performance on a large proteomic dataset. Experimental results indicate that SparkMS scales with the number of worker nodes and the increasing complexity of the search task. Furthermore, it exhibits a protein identification efficiency comparable to X!Tandem, a widely-used proteomic search engine.

Anti‐nonspecific adsorption segments‐assisted self‐driven surface imprinted fibers for efficient protein separation

AbstractAt present, the development of high‐performance protein imprinted materials is still a research hotspot in the field of protein imprinting. Herein, anti‐protein adsorption segment (CBMA)‐assisted self‐driven bovine serum albumin (BSA) surface imprinted fibers MTCFs@SIP@CBMA with high recognition selectivity are pioneered using the strategies of combining magnetic nanomaterial surface imprinting technique with amino‐Michael addition. The special structure of the carrier MTCFs endows MTCFs@SIP@CBMA with magnetic performance and self‐driven adsorption performance, which simplifies the separation process while improving the adsorption capacity and accelerating the adsorption rate. The adsorption capacity for BSA reached 390 ± 20 mg/g within 30 min. The introduction of CBMA segments on the surface after imprinting by amino‐Michael addition makes its polymer chain length and position controllable. Under the strongest anti‐nonspecific adsorption effect, MTCFs@SIP@CBMA exhibit excellent specific identification to BSA from mixed proteins. Additionally, MTCFs@SIP@CBMA show considerable reusability. Therefore, MTCFs@SIP@CBMA are expected to be applied in efficient separation of proteins in biological samples.

DIA-MS proteome analysis of formalin-fixed paraffin-embedded glioblastoma tissues

Developments in quantitative proteomics and data-independent acquisition (DIA) methodology is enabling quantification of proteins in biological samples. Currently, there are a few reports on DIA mass spectrometry (MS) approaches for proteome analysis of formalin-fixed paraffin-embedded (FFPE) tissues. Therefore, to facilitate detection and quantification of immune- and glioblastoma (GBM)-relevant proteins from FFPE patient materials, we established a simple and precise DIA-MS workflow. We first evaluated different lysis buffers for their efficiency in protein extractions from FFPE GBM tissues. Our results showed that more than 1700 proteins were detected and over 1400 proteins were quantified from GBM FFPE tissue microdissections. GBM-relevant proteins (e.g., GFAP, FN1, VIM, and MBP) were quantified with high precision (median coefficient of variation <12%). In addition, immune-related proteins (e.g., ILF2, MIF, and CD38) were consistently detected and quantified. The strategy holds great potential for routinizing protein quantification in FFPE tissue samples.

Microfluidic Size Exclusion Chromatography (μSEC) for Extracellular Vesicles and Plasma Protein Separation.

Extracellular vesicles (EVs) are recognized as next generation diagnostic biomarkers due to their disease-specific biomolecular cargoes and importance in cell-cell communications. A major bottleneck in EV sample preparation is the inefficient and laborious isolation of nanoscale EVs (≈50-200nm) from endogenous proteins in biological samples. Herein, a unique microfluidic platform is reported for EV-protein fractionation based on the principle of size exclusion chromatography (SEC). Using a novel rapid (≈20min) replica molding technique, a fritless microfluidic SEC device (μSEC) is fabricated using thiol-ene polymer (UV glue NOA81, Young's modulus ≈1GPa) for high pressure (up to 6bar) sample processing. Controlled on-chip nanoliter sample plug injection (600 nL) using a modified T-junction injector is first demonstrated with rapid flow switching response time (<1.5 s). Device performance is validated using fluorescent nanoparticles (50nm), albumin, and breast cancer cells (MCF-7)-derived EVs. As a proof-of-concept for clinical applications, EVs are directly isolated from undiluted human platelet-poor plasma using μSEC and show distinct elution profiles between EVs and proteins based on nanoparticle particle analysis (NTA), Western blot and flow cytometry analysis. Overall, the optically transparent μSEC can be readily automated and integrated with EV detection assays for EVs manufacturing and clinical diagnostics.