Explore the vast range of titles available.

IntroductionThe second generation anticycliccitrullinated peptide (anti-CCP2) assay detects the majority but not all anticitrullinated protein/peptide antibodies (ACPA). Anti-CCP2-positive rheumatoid arthritis (RA) is associated with HLA-DRB1* shared epitope (SE) alleles and smoking. Using a multiplex assay to detect multiple specific ACPA, we have investigated the fine specificity of individual ACPA responses and the biological impact of additional ACPA reactivity among anti-CCP2-negative patients.MethodsWe investigated 2825 patients with RA and 551 healthy controls with full data on anti-CCP2, HLA-DRB1* alleles and smoking history concerning reactivity against 16 citrullinated peptides and arginine control peptides with a multiplex array.ResultsThe prevalence of the 16 ACPA specificities ranged from 9% to 58%. When reactivity to arginine peptides was subtracted, the mean diagnostic sensitivity increased by 3.2% with maintained 98% specificity. Of the anti-CCP2-negative patients, 16% were found to be ACPA positive. All ACPA specificities associated with SE, and all but one with smoking. Correction for arginine reactivity also conveyed a stronger association with SE for 13/16 peptides. Importantly, when all ACPA specificities were analysed together, SE and smoking associated with RA in synergy among ACPA positive, but not among ACPA-negative subjects also in the anti-CCP2-negative subset.ConclusionsMultiplexing detects an enlarged group of ACPA-positive but anti-CCP2-negative patients with genetic and environmental attributes previously assigned to anti-CCP2-positive patients. The individual correction for arginine peptide reactivity confers both higher diagnostic sensitivity and stronger association to SE than gross ACPA measurement.

PLAYR (proximity ligation assay for RNA) enables highly multiplexed transcript quantification in combination with protein marker detection in single cells using flow or mass cytometry. To enable the detection of expression signatures specific to individual cells, we developed PLAYR (proximity ligation assay for RNA), a method for highly multiplexed transcript quantification by flow and mass cytometry that is compatible with standard antibody staining. When used with mass cytometry, PLAYR allowed for the simultaneous quantification of more than 40 different mRNAs and proteins. In primary cells, we quantified multiple transcripts, with the identity and functional state of each analyzed cell defined on the basis of the expression of a separate set of transcripts or proteins. By expanding high-throughput deep phenotyping of cells beyond protein epitopes to include RNA expression, PLAYR opens a new avenue for the characterization of cellular metabolism.

We still know very little about how the human immune system responds to SARS-CoV-2. Here we construct a SARS-CoV-2 proteome microarray containing 18 out of the 28 predicted proteins and apply it to the characterization of the IgG and IgM antibodies responses in the sera from 29 convalescent patients. We find that all these patients had IgG and IgM antibodies that specifically bind SARS-CoV-2 proteins, particularly the N protein and S1 protein. Besides these proteins, significant antibody responses to ORF9b and NSP5 are also identified. We show that the S1 specific IgG signal positively correlates with age and the level of lactate dehydrogenase (LDH) and negatively correlates with lymphocyte percentage. Overall, this study presents a systemic view of the SARS-CoV-2 specific IgG and IgM responses and provides insights to aid the development of effective diagnostic, therapeutic and vaccination strategies. Currently very little is known about how our immune system responds to SARS-CoV-2 infection. Here the authors generate a SARS-CoV-2 proteome microarray for profiling of IgG and IgM responses to COVID-19 in patients and find significant responses to ORF9b and NSP5, as well as the S1 and N proteins.

The assessment of programmed death 1 ligand 1 (PD-L1) expression by Immunohistochemistry (IHC) is the US Food and Drug Administration (FDA)-approved predictive marker to select responders to checkpoint blockade anti-PD-1/PD-L1 axis immunotherapies. Different PD-L1 immunohistochemistry (IHC) assays use different antibodies and different scoring methods in tumor cells and immune cells. Multiple studies have compared the performance of these assays with variable results. Here, we investigate an alternative method for assessment of PD-L1 using a new technology known as digital spatial profiling. We use a previously described standardization tissue microarray (TMA) to assess the accuracy of the method and compare digital spatial profiler (DSP) to each FDA-approved PD-L1 assays, one LDT assay and three quantitative fluorescence assays. The standardized cell line Index tissue microarray contains 10 isogenic cells lines in triplicates expressing various ranges of PD-L1. The dynamic range of PD-L1 digital counts was measured in the ten cell lines on the Index TMA using the GeoMx DSP assay and read on the nCounter platform. The digital method shows very high correlation with immunohistochemistry scored with quantitative software and with quantitative fluorescence. High correlation of PD-L1 digital DSP counts were seen between rows on the same Index TMA. Finally, experiments from two Index TMAs showed reproducibility of DSP counts were independent of variable slide storage time over a three-week period after antibody labeling but before collection of cleaved tags. In summary, DSP appears to have quantitative potential comparable to quantitative immunohistochemistry. It is possible that this technology could be used as a PD-L1 protein measurement system for companion diagnostic testing for immune therapy. Digital spatial profiling is a new high-plex technology with potential to multiplex hundreds of proteins on a single slide. Here the authors validate the digital aspect of the technology on a control tissue microarray with known amounts of PD-L1 expression to show it has quantitative capacity comparable to quantitative immunofluorescence.

Infrared absorption spectroscopy is a powerful biochemical analysis tool as it extracts detailed molecular structural information in a label-free fashion. Its molecular specificity renders the technique sensitive to the subtle conformational changes exhibited by proteins in response to a variety of stimuli. Yet, sensitivity limitations and the extremely strong absorption bands of liquid water severely limit infrared spectroscopy in performing kinetic measurements in biomolecules’ native, aqueous environments. Here we demonstrate a plasmonic chip-based technology that overcomes these challenges, enabling the in-situ monitoring of protein and nanoparticle interactions at high sensitivity in real time, even allowing the observation of minute volumes of water displacement during binding events. Our approach leverages the plasmonic enhancement of absorption bands in conjunction with a non-classical form of internal reflection. These features not only expand the reach of infrared spectroscopy to a new class of biological interactions but also additionally enable a unique chip-based technology. Infrared absorption spectroscopy provides important information about molecules, but is hampered by the absorption of water. Adato and Altug exploit the plasmonic enhancement from nanoantennas to overcome this, enabling chip-based monitoring of biological samples in aqueous environments.

Genome-wide location analysis, also known as ChIP-Chip, combines chromatin immunoprecipitation and DNA microarray analysis to identify protein-DNA interactions that occur in living cells. Protein-DNA interactions are captured in vivo by chemical crosslinking. Cell lysis, DNA fragmentation and immunoaffinity purification of the desired protein will co-purify DNA fragments that are associated with that protein. The enriched DNA population is then labeled, combined with a differentially labeled reference sample and applied to DNA microarrays to detect enriched signals. Various computational and bioinformatic approaches are then applied to normalize the enriched and reference channels, to connect signals to the portions of the genome that are represented on the DNA microarrays, to provide confidence metrics and to generate maps of protein-genome occupancy. Here, we describe the experimental protocols that we use from crosslinking of cells to hybridization of labeled material, together with insights into the aspects of these protocols that influence the results. These protocols require approximately 1 week to complete once sufficient numbers of cells have been obtained, and have been used to produce robust, high-quality ChIP-chip results in many different cell and tissue types.

Glycan microarrays provide a high-throughput means of profiling the interactions of glycan-binding proteins with their ligands. However, the construction of current glycan microarray platforms is time consuming and expensive. Here, we report a fast and cost-effective method for the assembly of cell-based glycan arrays to probe glycan–glycan-binding protein interactions directly on the cell surface. Chinese hamster ovary cell mutants with a narrow and relatively homogeneous repertoire of glycoforms serve as the foundation platforms to develop these arrays. Using recombinant glycosyltransferases, sialic acid, fucose, and analogs thereof are installed on cell-surface glycans to form cell-based arrays displaying diverse glycan epitopes that can be probed with glycan-binding proteins by flow cytometry. Using this platform, high-affinity glycan ligands are discovered for Siglec-15—a sialic acid-binding lectin involved in osteoclast differentiation. Incubating human osteoprogenitor cells with cells displaying a high-affinity Siglec-15 ligand impairs osteoclast differentiation, demonstrating the utility of this cell-based glycan array technology. Glycans, interaction platforms protruding from the surface of cells, are hard to study due to their diverse architecture. Here, the authors present a method to obtain cells carrying defined glycans, which can then be used to find proteins specifically recognizing these tags.

High throughput immunoassay is increasingly crucial for both scientific and clinical applications. Here we propose a “Lab-in-a-Tip” (LIT) concept to fabricate a pipette tip containing a high-density protein array and other essential reagents. The protein array is made by self-assembling digitally encoded microparticles inside the modified tip. Mounted on a robotic workstation, it automates liquid-handling steps. Notably, compared with Luminex, the current gold standard in multiplex immunoassays, such a design enables LIT to demonstrate multiple advantages in terms of analytical sensitivity, speed, and throughput. It detects analyte concentrations as low as fg/ml, representing a sensitivity improvement of two orders of magnitude over Luminex. Incubation time is reduced to 15 minutes from Luminex’s 210 minutes. Furthermore, LIT requires only 10 µl of sample, one-fifth of what Luminex needs. This makes LIT ideal for rapid diagnostics and studies with limited biological samples, greatly expanding its application scope. High-throughput immunoassay is crucial for scientific and clinical applications. Here, the authors introduce a multiplex immunoassay platform engineered by modifying a pipette tip with a self-assembled barcoded protein array. It outperforms the gold standard in sensitivity, speed, and sample volume.

Bacterial proteome microarrays enable simultaneous investigation of thousands of proteins, facilitating exploration of pathogenicity, host interactions, and clinical diseases.Recent studies have identified novel antigens and diagnostic markers for infectious diseases (e.g., those caused by Chlamydia trachomatis, Campylobacter jejuni, Helicobacter pylori), autoimmune disorders (e.g., pre-eclampsia, Kawasaki disease), and mental health conditions (e.g., schizophrenia, autism).Proteome microarrays accelerate vaccine development by identifying immunogenic antigens that elicit protective responses, as demonstrated for C. jejuni and H. pylori.Future applications include investigating bacterial protein cross-reactivity in autoimmune diseases, employing artificial intelligence for data analysis, and adopting the technology in clinical settings for improved diagnostics and treatments. Bacterial proteome microarrays are high-throughput, adaptable tools that allow the simultaneous investigation of thousands of proteins from various bacterial species. These arrays are used to explore bacterial pathogenicity, pathogen–host interactions, and clinical diseases. Recent advancements have expanded their application to profiling human antibodies, identifying biomarkers for infectious and autoimmune diseases, and studying antimicrobial peptides (AMPs). This review highlights significant outcomes from recent studies, focusing on their diverse applications in biomedical research. Notable findings include the identification of novel antigens and diagnostic markers for gastrointestinal infections, autoimmune diseases, and mental health disorders. This technology promises to further elucidate the complex relationship between bacteria and their hosts, ultimately informing the development of new diagnostic, therapeutic, and preventive strategies. Bacterial proteome microarrays are high-throughput, adaptable tools that allow the simultaneous investigation of thousands of proteins from various bacterial species. These arrays are used to explore bacterial pathogenicity, pathogen–host interactions, and clinical diseases. Recent advancements have expanded their application to profiling human antibodies, identifying biomarkers for infectious and autoimmune diseases, and studying antimicrobial peptides (AMPs). This review highlights significant outcomes from recent studies, focusing on their diverse applications in biomedical research. Notable findings include the identification of novel antigens and diagnostic markers for gastrointestinal infections, autoimmune diseases, and mental health disorders. This technology promises to further elucidate the complex relationship between bacteria and their hosts, ultimately informing the development of new diagnostic, therapeutic, and preventive strategies.

Using a diverse collection of small molecules generated from a variety of sources, we measured protein-binding activities of each individual compound against each of 100 diverse (sequence-unrelated) proteins using small-molecule microarrays. We also analyzed structural features, including complexity, of the small molecules. We found that compounds from different sources (commercial, academic, natural) have different protein-binding behaviors and that these behaviors correlate with general trends in stereochemical and shape descriptors for these compound collections. Increasing the content of sp³-hybridized and stereogenic atoms relative to compounds from commercial sources, which comprise the majority of current screening collections, improved binding selectivity and frequency. The results suggest structural features that synthetic chemists can target when synthesizing screening collections for biological discovery. Because binding proteins selectively can be a key feature of high-value probes and drugs, synthesizing compounds having features identified in this study may result in improved performance of screening collections.