Advances in cell-free protein array methods

Development of Lyophilized Eukaryotic Cell-Free Protein Expression System Based on Leishmania tarentolae

Eukaryotic cell-free protein expression systems enable rapid production of recombinant multidomain proteins in their functional form. A cell-free system based on the rapidly growing protozoan Leishmania tarentolae (LTE) has been extensively used for protein engineering and analysis of protein interaction networks. However, like other eukaryotic cell-free systems, LTE deteriorates at ambient temperatures and requires deep freezing for transport and storage. In this study, we report the development of a lyophilized version of LTE. Use of lyoprotectants such as poly(ethylene glycol) and trehalose during the drying process allows retention of 76% of protein expression activity versus nonlyophilized controls. Lyophilized LTE is capable of withstanding storage at room temperature for over 2 weeks. We demonstrated that upon reconstitution the lyophilized LTE could be used for in vitro expression of active enzymes, analysis of protein-protein interactions by AlphaLISA assay, and functional analysis of protein biosensors. Development of lyophilized LTE lowers the barriers to its distribution and opens the door to its application in remote areas.

Development of a protein microarray for profiling circulating autoantibodies in human diseases

PURPOSE

To develop a robust microarray platform to detect thousands of serological autoantibodies (AAbs) simultaneously in different diseases.

EXPERIMENTAL DESIGN

An AAbMap microarray was prepared by printing a total of 4032 purified His-tagged human proteins and peptide probes on a chemically-modified slide. The sensitivity, dynamic range, and the inter- and intra-array reproducibility of the AAb microarray were then systematically tested and optimized. Finally, the large-scale profiling of AAbs in the serum of patients with different human diseases using the AAbMap microarray was demonstrated.

RESULTS

The dynamic range of antibody (Ab) detection was 2 to 3 orders of magnitude with the lowest limit of detection (LOD) of 68 pg/mL. The intra-array (r) correlation of duplicate spots was 1.00, whereas the inter-array correlations between different arrays and batches were 0.99 and 0.97 to 0.98, respectively. Notably, 132, 266, 171, and 84 AAbs were detected in pooled serum from healthy controls (HCs) or patients with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), or lung cancer (LC), respectively. These AAbs included antibodies that target well-known disease biomarkers, such as anti-cyclic citrullinated peptide, anti-ribonucleoprotein, and anti-nucleosome.

CONCLUSIONS AND CLINICAL RELEVANCE

We developed a microarray platform to measure thousands of serological AAbs simultaneously with high sensitivity and reproducibility. The array can help study autoimmunity and complement genomics, proteomics, and metabolomics data for systematic investigations of human diseases.

Protein array-based companion diagnostics in precision medicine

INTRODUCTION

The development of companion diagnostics (CDx) will increase efficacy and cost-benefit markedly, compared to the currently prevailing trial-and-error approach for treatment. Recent improvements in high-throughput protein technology have resulted in large amounts of predictive biomarkers that are potentially useful components of future CDx assays. Current high multiplex protein arrays are suitable for discovery-based approaches, while low-density and more simple arrays are suitable for use in point-of-care facilities.

AREA COVERED

This review discusses the technical platforms available for protein array focused CDx, explains the technical details of the platforms and provide examples of clinical use, ranging from multiplex arrays to low-density clinically applicable arrays. We thereafter highlight recent predictive biomarkers within different disease areas, such as oncology and autoimmune diseases. Lastly, we discuss some of the challenges connected to the implementation of CDx assays as point-of-care tests.

EXPERT OPINION

Recent advances in the field of protein arrays have enabled high-density arrays permitting large biomarker discovery studies, which are beneficial for future CDx assays. The density of protein arrays range from a single protein to proteome-wide arrays, allowing the discovery of protein signatures that may correlate with drug response. Protein arrays will undoubtedly play a key role in future CDx assays.

Antibody Printing Technologies

Antibody microarrays are routinely employed in the lab and in the clinic for studying protein expression, protein-protein, and protein-drug interactions. The microarray format reduces the size scale at which biological and biochemical interactions occur, leading to large reductions in reagent consumption and handling times while increasing overall experimental throughput. Specifically, antibody microarrays, as a platform, offer a number of different advantages over traditional techniques in the areas of drug discovery and diagnostics. While a number of different techniques and approaches have been developed for creating micro and nanoscale antibody arrays, issues relating to sensitivity, cost, and reproducibility persist. The aim of this review is to highlight current state-of the-art techniques and approaches for creating antibody arrays by providing latest accounts of the field while discussing potential future directions.

PAWER: protein array web exploreR

Background

Protein microarray is a well-established approach for characterizing activity levels of thousands of proteins in a parallel manner. Analysis of protein microarray data is complex and time-consuming, while existing solutions are either outdated or challenging to use without programming skills. The typical data analysis pipeline consists of a data preprocessing step, followed by differential expression analysis, which is then put into context via functional enrichment. Normally, biologists would need to assemble their own workflow by combining a set of unrelated tools to analyze experimental data. Provided that most of these tools are developed independently by various bioinformatics groups, making them work together could be a real challenge.

Results

Here we present PAWER, the online web tool dedicated solely to protein microarray analysis. PAWER enables biologists to carry out all the necessary analysis steps in one go. PAWER provides access to state-of-the-art computational methods through the user-friendly interface, resulting in publication-ready illustrations. We also provide an R package for more advanced use cases, such as bespoke analysis workflows.

Conclusions

PAWER is freely available at https://biit.cs.ut.ee/pawer.

The status of proteomics as we enter the 2020s: Towards personalised/precision medicine

The last decade has seen many major advances in proteomics, with over 70,000 publications in the field since 2010. A comprehensive omics toolbox has been developed facilitating rapid in depth analysis of the human proteome. Such studies are advancing our understanding of the biology of both health and disease. The combination of proteomics with other omics platforms (the omics pipeline), in particular proteogenomics, is giving important insights to the molecular changes leading to disease, covering the spectrum from genotype to phenotype and identifying potential biomarkers for disease detection, surveillance and monitoring, and revealing potential new drug targets. Discovery-based finding are now being translated to clinical application, supporting the rollout of precision/personalised medicine. This perspective has focused on twelve areas of importance that have fuelled the field. Recent exemplars are given to illustrate this and show how, together with some emerging technologies, they are anticipated to lead to further advances in the field. However, hurdles still remain to be overcome, especially in the area of Big Data analysis.

Identification of Novel Native Autoantigens in Rheumatoid Arthritis

The majority of patients diagnosed with rheumatoid arthritis (RA) have developed autoantibodies against neoepitopes in proteins that have undergone post-translational modification, e.g., citrullination or carbamylation. There is growing evidence of their molecular relevance and their potential utility to improve diagnosis, patient stratification, and prognosis for precision medicine. Autoantibodies reacting to native proteins may also have a role in RA pathogenesis, however, their reactivity patterns remain much less studied. We hypothesized that a high-density protein array technology could shed light onto the normal and disease-related autoantibodies produced in healthy and RA patient subgroups. In an exploratory study, we investigated the global reactivity of autoantibodies in plasma pools from 15 anti-cyclic citrullinated peptide (CCP)-positive and 10 anti-CCP-negative RA patients and 10 healthy donors against more than 1600 native and unmodified human proteins using a high-density protein array. A total of 102 proteins recognized by IgG autoantibodies were identified, hereof 86 were recognized by antibodies from CCP-positive RA patients and 76 from anti-CCP-negative RA patients, but not by antibodies from healthy donors. Twenty-four of the identified autoantigens have previously been identified in synovial fluid. Multiple human proteins in their native conformation are recognized by autoantibodies from anti-CCP-positive as well as anti-CCP-negative RA patients.

Autoantibody profiling identifies predictive biomarkers of response to anti-PD1 therapy in cancer patients

Background: Programmed cell death protein 1 (PD1) inhibitors have revolutionized cancer therapy, yet many patients fail to respond. Thus, the identification of accurate predictive biomarkers of therapy response will improve the clinical benefit of anti-PD1 therapy.

Method: We assessed the baseline serological autoantibody (AAb) profile against ~2300 proteins in 10 samples and ~4600 proteins in 35 samples with alveolar soft part sarcoma (ASPS), non-small-cell lung cancer (NSCLC) and lymphoma using Nucleic Acid Programmable Protein Arrays (NAPPA). 23 selected potential AAb biomarkers were verified using simple, affordable and rapid enzyme linked immune sorbent assay (ELISA) technology with baseline plasma samples from 12 ASPS, 16 NSCLC and 46 lymphoma patients. SIX2 and EIF4E2 AAbs were further validated in independent cohorts of 17 NSCLC and 43 lymphoma patients, respectively, using ELISA. The IgG subtypes in response to therapy were also investigated.

Results: Distinct AAb profiles between ASPS, NSCLC and lymphoma were observed. In ASPS, the production of P53 and PD1 AAbs were significantly increased in non-responders (p=0.037). In NSCLC, the SIX2 AAb was predictive of response with area under the curve (AUC) of 0.87, 0.85 and 0.90 at 3 months, 4.5 months, 6 months evaluation time points, respectively. In the validation cohort, the SIX2 AAb was consistently up-regulated in non-responders (p=0.024). For lymphoma, the EIF4E2 AAb correlated with a favorable response with AUCs of 0.68, 0.70, and 0.70 at 3 months, 4.5 months, and 6 months, respectively. In the validation cohort, the AUCs were 0.74, 0.75 and 0.66 at 3 months, 4.5 months, and 6 months, respectively. The PD1 and PD-L1 IgG2 AAbs were highly produced in ~20% of lymphoma responders. Furthermore, bioinformatics analysis revealed antigen functions of these AAb biomarkers.

Conclusion: This study provides the first evidence that AAb biomarkers selected using high-throughput protein microarrays can predict anti-PD1 therapeutic response and guide anti-PD1 therapy.

Identification of tumor-associated antigens with diagnostic ability of colorectal cancer by in-depth immunomic and seroproteomic analysis

Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer related death worldwide. Its diagnosis at early stages would significantly improve the survival of CRC patients. The humoral immune response has been demonstrated useful for cancer diagnosis, predating clinical symptoms up to 3 years. Here, we employed an in-depth seroproteomic approach to identify proteins that elicit a humoral immune response in CRC patients. The seroproteomic approach relied on the immunoprecipitation with patient-derived autoantibodies of proteins from CRC cell lines with different metastatic properties followed by LC-MS/MS. After bioinformatics, we focused on 31 targets of CRC autoantibodies. After WB and IHC validation, ERP44 and TALDO1 showed potential to discriminate disease-free and metastatic CRC patients, and time to recurrence of CRC patients in stage II. Using plasma samples of 30 healthy individuals, 28 premalignant individuals, and 32 CRC patients, nine out of 13 selected targets for seroreactive analysis showed significant diagnostic ability to discriminate either CRC patients or premalignant subjects from controls. Our results suggest that the here defined panel of CRC autoantibodies and their target proteins should be included in CRC blood-based biomarker panels to get a clinically useful blood-based diagnostic signature for CRC detection. SIGNIFICANCE: Colorectal cancer is one of the deadliest cancer types mainly due to its late diagnosis. Its early diagnosis, therefore, is of great importance since it would significantly improve the survival of CRC patients. In our work, the in-depth seroproteomic analysis of colorectal cancer using isolated IgGs from colorectal cancer patients and controls and protein extract of colorectal cancer cells provide the identification of valuable biomarkers with diagnostic and prognostic ability of the disease.

Proteome microarray technology and application: higher, wider, and deeper

Introduction: Protein microarray is a powerful tool for both biological study and clinical research. The most useful features of protein microarrays are their miniaturized size (low reagent and sample consumption), high sensitivity and their capability for parallel/high-throughput analysis. The major focus of this review is functional proteome microarray. Areas covered: For proteome microarray, this review will discuss some recently constructed proteome microarrays and new concepts that have been used for constructing proteome microarrays and data interpretation in past few years, such as PAGES, M-NAPPA strategy, VirD technology, and the first protein microarray database. this review will summarize recent proteomic scale applications and address the limitations and future directions of proteome microarray technology. Expert opinion: Proteome microarray is a powerful tool for basic biological and clinical research. It is expected to see improvements in the currently used proteome microarrays and the construction of more proteome microarrays for other species by using traditional strategies or novel concepts. It is anticipated that the maximum number of features on a single microarray and the number of possible applications will be increased, and the information that can be obtained from proteome microarray experiments will more in-depth in the future.

In-depth serum proteomics reveals biomarkers of psoriasis severity and response to traditional Chinese medicine

Serum and plasma contain abundant biological information that reflect the body's physiological and pathological conditions and are therefore a valuable sample type for disease biomarkers. However, comprehensive profiling of the serological proteome is challenging due to the wide range of protein concentrations in serum. Methods: To address this challenge, we developed a novel in-depth serum proteomics platform capable of analyzing the serum proteome across ~10 orders or magnitude by combining data obtained from Data Independent Acquisition Mass Spectrometry (DIA-MS) and customizable antibody microarrays. Results: Using psoriasis as a proof-of-concept disease model, we screened 50 serum proteomes from healthy controls and psoriasis patients before and after treatment with traditional Chinese medicine (YinXieLing) on our in-depth serum proteomics platform. We identified 106 differentially-expressed proteins in psoriasis patients involved in psoriasis-relevant biological processes, such as blood coagulation, inflammation, apoptosis and angiogenesis signaling pathways. In addition, unbiased clustering and principle component analysis revealed 58 proteins discriminating healthy volunteers from psoriasis patients and 12 proteins distinguishing responders from non-responders to YinXieLing. To further demonstrate the clinical utility of our platform, we performed correlation analyses between serum proteomes and psoriasis activity and found a positive association between the psoriasis area and severity index (PASI) score with three serum proteins (PI3, CCL22, IL-12B). Conclusion: Taken together, these results demonstrate the clinical utility of our in-depth serum proteomics platform to identify specific diagnostic and predictive biomarkers of psoriasis and other immune-mediated diseases.

Toward multiomics-based next-generation diagnostics for precision medicine

Our healthcare system is experiencing a paradigm shift to precision medicine, aiming at an early prediction of individual disease risks and targeted interventions. Whole-genome sequencing is currently gaining momentum, as it has the potential to capture all classes of genetic variation, thus providing a more complete picture of the individual's genetic makeup, which could be utilized in genetic testing; however, this will also lead to difficulties in interpreting the test results, necessitating careful integration of genomic data with other layers of information, both molecular multiomics measurements of epigenome, transcriptome, proteome, metabolome and even microbiome, as well as comprehensive information on diet, lifestyle and environment. Overall, the translation of patient-specific data into actionable diagnostic tools will be a challenging task, requiring expertise from multiple disciplines, secure data sharing in large reference databases and a strong computational infrastructure.

Glycosylation Profiling of Tumor Marker in Plasma Using Bead-Based Immunoassay

As one of the most important posttranslational modifications, glycosylation plays critical roles in protein folding, trafficking, cell differentiation, immune recognition, etc. The alteration of glycosylation is closely associated with the pathological processes during and after caner development, and thus holds great value in cancer detection. In this chapter, we describe a protocol on the glycosylation profiling of tumor marker in plasma using bead-based immunoassay with CA125 as a model, including bead coupling, coupling control, glycosylation assay, as well as the plasma screening for breast cancer patients. This protocol can be used to profile the glycosylation of protein markers in clinical plasma or serum samples for different human cancers.

Tissue and plasma proteomics for early stage cancer detection

The pursuit of novel and effective biomarkers is essential in the struggle against cancer, which is a leading cause of mortality worldwide. Here we discuss the relative advantages and disadvantages of the most frequently used proteomics techniques, concentrating on the latest advances and application of tissue and plasma proteomics for novel cancer biomarker discovery.