Proximity ligation assay: an ultrasensitive method for protein quantification and its applications in pathogen detection

A PLA-mediated transistor biosensor enables specific identification of tumor-derived exosomal PD-L1

The expression of programmed death ligand 1 (PD-L1) on tumor-derived exosomes (tExos) forecasts the efficacy of immunotherapy and tumor diagnosis. Due to the heterogeneity of exosomes, current detection methods face challenges in distinguishing between tumor-derived and non-tumor-derived exosome PD-L1. To address this challenge, we introduce a novel field effect transistor (FET) biosensor based on proximity ligation assay (PLA) technology. This approach uses a single probe to simultaneously recognize two biomarkers on exosomes to identify tumor-derived exosome PD-L1 (tExo-PD-L1). This method, for the first time, integrates the PLA strategy with FET technology, allowing for tracking of exosomes that co-express multiple biomarkers. In clinical diagnostics, this strategy not only significantly improves the sensitivity and specificity, but also enhances the precision and accuracy, compared to conventional approaches that identify total Exo-PD-L1 or Exo-EpCAM using a single biomarker. This technology holds promise for enhancing the reliability of using exosomes as biomarkers in clinical diagnostics and further exploring the biological functions of exosomes more effectively.

An electrochemical proximity assay (ECPA) for antibody detection incorporating flexible spacers for improved performance

A clever approach for biosensing is to leverage the concept of the proximity effect, where analyte binding to probes can be coupled to a second, controlled binding event such as short DNA strands. This analyte-dependent effect has been exploited in various sensors with optical or electrochemical readouts. Electrochemical proximity assays (ECPA) are more amenable to miniaturization and adaptation to the point-of-care, yet ECPA has been generally targeted toward protein sensing with antibody-oligonucleotide probes. Antibodies themselves are also important as biomarkers, since they are produced in bodily fluids in response to various diseases or infections, often in low amounts. In this work, by using antigen-DNA conjugates, we targeted an ECPA method for antibody sensing and showed that the assay performance can be greatly enhanced using flexible spacers in the DNA conjugates. After adding flexible polyethylene glycol (PEG) spacers at two distinct positions, the spacers ultimately increased the antibody-dependent current by a factor of 4.0 without significant background increases, similar to our recent work using thermofluorimetric analysis (TFA). The optimized ECPA was applied to anti-digoxigenin antibody quantification at concentrations ranging over two orders of magnitude, from the limit of detection of 300 pM up to 50 nM. The assay was functional in 90% human serum, where increased ionic strength was used to counteract double-layer repulsion effects at the electrode. This flexible-probe ECPA methodology should be useful for sensing other antibodies in the future with high sensitivity, and the mechanism for signal improvement with probe flexibility may be applicable to other DNA-based electrochemical sensor platforms.

Model fusion for predicting unconventional proteins secreted by exosomes using deep learning

Unconventional secretory proteins (USPs) are vital for cell-to-cell communication and are necessary for proper physiological processes. Unlike classical proteins that follow the conventional secretory pathway via the Golgi apparatus, these proteins are released using unconventional pathways. The primary modes of secretion for USPs are exosomes and ectosomes, which originate from the endoplasmic reticulum. Accurate and rapid identification of exosome-mediated secretory proteins is crucial for gaining valuable insights into the regulation of non-classical protein secretion and intercellular communication, as well as for the advancement of novel therapeutic approaches. Although computational methods based on amino acid sequence prediction exist for predicting unconventional proteins secreted by exosomes (UPSEs), they suffer from significant limitations in terms of algorithmic accuracy. In this study, we propose a novel approach to predict UPSEs by combining multiple deep learning models that incorporate both protein sequences and evolutionary information. Our approach utilizes a convolutional neural network (CNN) to extract protein sequence information, while various densely connected neural networks (DNNs) are employed to capture evolutionary conservation patterns.By combining six distinct deep learning models, we have created a superior framework that surpasses previous approaches, achieving an ACC score of 77.46% and an MCC score of 0.5406 on an independent test dataset.

Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this Review will serve as a handbook for researchers who are new to the field of bottom-up proteomics.

Initiator cell death event induced by SARS-CoV-2 in the human airway epithelium

Virus-induced cell death is a key contributor to COVID-19 pathology. Cell death induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is well studied in myeloid cells but less in its primary host cell type, angiotensin-converting enzyme 2 (ACE2)-expressing human airway epithelia (HAE). SARS-CoV-2 induces apoptosis, necroptosis, and pyroptosis in HAE organotypic cultures. Single-cell and limiting-dilution analysis revealed that necroptosis is the primary cell death event in infected cells, whereas uninfected bystanders undergo apoptosis, and pyroptosis occurs later during infection. Mechanistically, necroptosis is induced by viral Z-RNA binding to Z-DNA-binding protein 1 (ZBP1) in HAE and lung tissues from patients with COVID-19. The Delta (B.1.617.2) variant, which causes more severe disease than Omicron (B1.1.529) in humans, is associated with orders of magnitude-greater Z-RNA/ZBP1 interactions, necroptosis, and disease severity in animal models. Thus, Delta induces robust ZBP1-mediated necroptosis and more disease severity.

Levels of inflammatory cytokines MCP-1, CCL4, and PD-L1 in CSF differentiate idiopathic normal pressure hydrocephalus from neurodegenerative diseases

BACKGROUND

Neuroinflammatory processes have been suggested to play a role in the pathophysiology of neurodegenerative diseases and post-hemorrhagic hydrocephalus, but have rarely been investigated in patients with idiopathic normal pressure hydrocephalus (iNPH). The aim of this study was to investigate whether levels of inflammatory proteins in CSF are different in iNPH compared to healthy controls and patients with selected neurodegenerative disorders, and whether any of these markers can aid in the differential diagnosis of iNPH.

METHODS

Lumbar CSF was collected from 172 patients from a single center and represented iNPH (n = 74), Alzheimer's disease (AD) (n = 21), mild cognitive impairment (MCI) due to AD (n = 21), stable MCI (n = 22), frontotemporal dementia (n = 13), and healthy controls (HC) (n = 21). Levels of 92 inflammatory proteins were analyzed using a proximity extension assay. As a first step, differences between iNPH and HC were investigated, and proteins that differed between iNPH and HC were then compared with those from the other groups. The linear regressions were adjusted for age, sex, and plate number.

RESULTS

Three proteins showed higher (MCP-1, p = 0.0013; CCL4, p = 0.0008; CCL11, p = 0.0022) and one lower (PD-L1, p = 0.0051) levels in patients with iNPH compared to HC. MCP-1 was then found to be higher in iNPH than in all other groups. CCL4 was higher in iNPH than in all other groups, except in MCI due to AD. PD-L1 was lower in iNPH compared to all other groups, except in stable MCI. Levels of CCL11 did not differ between iNPH and the differential diagnoses. In a model based on the four proteins mentioned above, the mean area under the receiver operating characteristic curve used to discriminate between iNPH and the other disorders was 0.91.

CONCLUSIONS

The inflammatory cytokines MCP-1 and CCL4 are present at higher-and PD-L1 at lower-levels in iNPH than in the other investigated diagnoses. These three selected cytokines may have diagnostic potential in the work-up of patients with iNPH.

Assay methods based on proximity-enhanced reactions for detecting non-nucleic acid molecules

Accurate and reliable detection of biological molecules such as nucleic acids, proteins, and small molecules is essential for the diagnosis and treatment of diseases. While simple homogeneous assays have been developed and are widely used for detecting nucleic acids, non-nucleic acid molecules such as proteins and small molecules are usually analyzed using methods that require time-consuming procedures and highly trained personnel. Recently, methods using proximity-enhanced reactions (PERs) have been developed for detecting non-nucleic acids. These reactions can be conducted in a homogeneous liquid phase via a single-step procedure. Herein, we review three assays based on PERs for the detection of non-nucleic acid molecules: proximity ligation assay, proximity extension assay, and proximity proteolysis assay.

Hybrid Model Teaching in the Postepidemic Period: From Nucleic Acid to Antigen for the Fluorescence Analysis of SARS-CoV-2

Owing to the global spread of the coronavirus disease 2019 (COVID-19), education has shifted to distance online learning, whereas some face-to-face courses have been resumed with the improvement of the outbreak prevention and management situation, including a laboratory course for senior undergraduate students in chemical biology. Here, we present an innovative chemical biology experiment covering COVID-19 topics, which was created for third-year undergraduates. The basic principles of two nucleic-acid- and antigen-based diagnostic techniques for SARS-CoV-2 are demonstrated in detail. These experiments are designed to provide students with comprehensive knowledge of COVID-19 and related diagnoses in daily life. Crucially, the biosafety of this experimental manipulation was ensured by using artificial nucleic acids and recombinant protein. Furthermore, an interactive hybrid online-facing teaching model was designed to cover the key mechanism regarding PCR and serological tests of COVID-19. Finally, a satisfactory evaluation was obtained through a questionnaire, and simultaneously, reasonable improvements to the course design were suggested. The proposed curriculum provides all the necessary information for other instructors to create new courses supported by research.

In Situ Identification of Both IL-4 and IL-10 Cytokine-Receptor Interactions during Tissue Regeneration

Cytokines secreted by individual immune cells regulate tissue regeneration and allow communication between various cell types. Cytokines bind to cognate receptors and trigger the healing process. Determining the orchestration of cytokine interactions with their receptors on their cellular targets is essential to fully understanding the process of inflammation and tissue regeneration. To this end, we have investigated the interactions of Interleukin-4 cytokine (IL-4)/Interleukin-4 cytokine receptor (IL-4R) and Interleukin-10 cytokine (IL-10)/Interleukin-10 cytokine receptor (IL-10R) using in situ Proximity Ligation Assays in a regenerative model of skin, muscle and lung tissues in the mini-pig. The pattern of protein-protein interactions was distinct for the two cytokines. IL-4 bound predominantly to receptors on macrophages and endothelial cells around the blood vessels while the target cells of IL-10 were mainly receptors on muscle cells. Our results show that in situ studies of cytokine-receptor interactions can unravel the fine details of the mechanism of action of cytokines.

The Dawn of a New Era: Targeting the "Undruggables" with Antibody-Based Therapeutics

The high selectivity and affinity of antibodies toward their antigens have made them a highly valuable tool in disease therapy, diagnosis, and basic research. A plethora of chemical and genetic approaches have been devised to make antibodies accessible to more "undruggable" targets and equipped with new functions of illustrating or regulating biological processes more precisely. In this Review, in addition to introducing how naked antibodies and various antibody conjugates (such as antibody-drug conjugates, antibody-oligonucleotide conjugates, antibody-enzyme conjugates, etc.) work in therapeutic applications, special attention has been paid to how chemistry tools have helped to optimize the therapeutic outcome (i.e., with enhanced efficacy and reduced side effects) or facilitate the multifunctionalization of antibodies, with a focus on emerging fields such as targeted protein degradation, real-time live-cell imaging, catalytic labeling or decaging with spatiotemporal control as well as the engagement of antibodies inside cells. With advances in modern chemistry and biotechnology, well-designed antibodies and their derivatives via size miniaturization or multifunctionalization together with efficient delivery systems have emerged, which have gradually improved our understanding of important biological processes and paved the way to pursue novel targets for potential treatments of various diseases.

Oligomerization of the heteromeric γ-aminobutyric acid receptor GABAB in a eukaryotic cell-free system

Understanding the assembly mechanism and function of membrane proteins is a fundamental problem in biochemical research. Among the membrane proteins, G protein-coupled receptors (GPCRs) represent the largest class in the human body and have long been considered to function as monomers. Nowadays, the oligomeric assembly of GPCRs is widely accepted, although the functional importance and therapeutic intervention remain largely unexplored. This is partly due to difficulties in the heterologous production of membrane proteins. Cell-free protein synthesis (CFPS) with its endogenous endoplasmic reticulum-derived structures has proven as a technique to address this issue. In this study, we investigate for the first time the conceptual CFPS of a heteromeric GPCR, the γ-aminobutyric acid receptor type B (GABAB), from its protomers BR1 and BR2 using a eukaryotic cell-free lysate. Using a fluorescence-based proximity ligation assay, we provide evidence for colocalization and thus suggesting heterodimerization. We prove the heterodimeric assembly by a bioluminescence resonance energy transfer saturation assay providing the manufacturability of a heterodimeric GPCR by CFPS. Additionally, we show the binding of a fluorescent orthosteric antagonist, demonstrating the feasibility of combining the CFPS of GPCRs with pharmacological applications. These results provide a simple and powerful experimental platform for the synthesis of heteromeric GPCRs and open new perspectives for the modelling of protein-protein interactions. Accordingly, the presented technology enables the targeting of protein assemblies as a new interface for pharmacological intervention in disease-relevant dimers.

On the Applicability of Electrophoresis for Protein Quantification

Polyacrylamide gel electrophoresis is widely used for studying proteins and protein-containing objects. However, it is employed most frequently as a qualitative method rather than a quantitative one. This paper shows the feasibility of routine digital image acquisition and mathematical processing of electropherograms for protein quantification when using vertical gel electrophoresis and Chrom & Spec software. Both the well-studied model protein molecules (bovine serum albumin) and more complex real-world protein-based products (casein-containing isolate for sports nutrition), which were subjected to mechanical activation in a planetary ball mill to obtain samples characterized by different protein denaturation degrees, were used as study objects. Protein quantification in the mechanically activated samples was carried out. The degree of destruction of individual protein was shown to be higher compared to that of the protein-containing mixture after mechanical treatment for an identical amount of time. The methodological approach used in this study can serve as guidance for other researchers who would like to use electrophoresis for protein quantification both in individual form and in protein mixtures. The findings prove that photographic imaging of gels followed by mathematical data processing can be applied for analyzing the electrophoretic data as an affordable, convenient and quick tool.