Microscale separation and analysis

There is a recent and growing interest in microscale separation and analysis, a result of advantages of miniaturization such as rapid separation times, high performance and throughput, reduced costs, and the possibility of system integration and multiplexing. Adopting the concepts of conventional capillary electrophoresis, capillary electrochromatography, micellar electrokinetic chromatography and various sample preparation techniques to microchip format, in conjunction with the integration of different analysis steps into a monolithic system, have opened new levels in performance, functionality and throughput. This review summarizes the recent advances in the field of microfabricated separation devices for genomics, proteomics and high-throughput screening applications, also addressing system integration and micropreparative functionalities.     

Simultaneous measurements of auto-immune and infectious disease specific antibodies using a high throughput multiplexing tool

Considering importance of ganglioside antibodies as biomarkers in various immune-mediated neuropathies and neurological disorders, we developed a high throughput multiplexing tool for the assessment of gangliosides-specific antibodies based on Biolpex/Luminex platform. In this report, we demonstrate that the ganglioside high throughput multiplexing tool is robust, highly specific and demonstrating ～100-fold higher concentration sensitivity for IgG detection than ELISA. In addition to the ganglioside-coated array, the high throughput multiplexing tool contains beads coated with influenza hemagglutinins derived from H1N1 A/Brisbane/59/07 and H1N1 A/California/07/09 strains. Influenza beads provided an added advantage of simultaneous detection of ganglioside- and influenza-specific antibodies, a capacity important for the assay of both infectious antigen-specific and autoimmune antibodies following vaccination or disease. Taken together, these results support the potential adoption of the ganglioside high throughput multiplexing tool for measuring ganglioside antibodies in various neuropathic and neurological disorders.     

Discovery of lung cancer biomarkers by profiling the plasma proteome with monoclonal antibody libraries

A challenge in the treatment of lung cancer is the lack of early diagnostics. Here, we describe the application of monoclonal antibody proteomics for discovery of a panel of biomarkers for early detection (stage I) of non-small cell lung cancer (NSCLC). We produced large monoclonal antibody libraries directed against the natural form of protein antigens present in the plasma of NSCLC patients. Plasma biomarkers associated with the presence of lung cancer were detected via high throughput ELISA. Differential profiling of plasma proteomes of four clinical cohorts, totaling 301 patients with lung cancer and 235 healthy controls, identified 13 lung cancer-associated (p < 0.05) monoclonal antibodies. The monoclonal antibodies recognize five different cognate proteins identified using immunoprecipitation followed by mass spectrometry. Four of the five antigens were present in non-small cell lung cancer cells in situ. The approach is capable of generating independent antibodies against different epitopes of the same proteins, allowing fast translation to multiplexed sandwich assays. Based on these results, we have verified in two independent clinical collections a panel of five biomarkers for classifying patient disease status with a diagnostics performance of 77% sensitivity and 87% specificity. Combining CYFRA, an established cancer marker, with the panel resulted in a performance of 83% sensitivity at 95% specificity for stage I NSCLC.     

Scalable High Throughput Selection From Phage-displayed Synthetic Antibody Libraries

The demand for antibodies that fulfill the needs of both basic and clinical research applications is high and will dramatically increase in the future. However, it is apparent that traditional monoclonal technologies are not alone up to this task. This has led to the development of alternate methods to satisfy the demand for high quality and renewable affinity reagents to all accessible elements of the proteome. Toward this end, high throughput methods for conducting selections from phage-displayed synthetic antibody libraries have been devised for applications involving diverse antigens and optimized for rapid throughput and success. Herein, a protocol is described in detail that illustrates with video demonstration the parallel selection of Fab-phage clones from high diversity libraries against hundreds of targets using either a manual 96 channel liquid handler or automated robotics system. Using this protocol, a single user can generate hundreds of antigens, select antibodies to them in parallel and validate antibody binding within 6-8 weeks. Highlighted are: i) a viable antigen format, ii) pre-selection antigen characterization, iii) critical steps that influence the selection of specific and high affinity clones, and iv) ways of monitoring selection effectiveness and early stage antibody clone characterization. With this approach, we have obtained synthetic antibody fragments (Fabs) to many target classes including single-pass membrane receptors, secreted protein hormones, and multi-domain intracellular proteins. These fragments are readily converted to full-length antibodies and have been validated to exhibit high affinity and specificity. Further, they have been demonstrated to be functional in a variety of standard immunoassays including Western blotting, ELISA, cellular immunofluorescence, immunoprecipitation and related assays. This methodology will accelerate antibody discovery and ultimately bring us closer to realizing the goal of generating renewable, high quality antibodies to the proteome.     

Automated screening procedure for high-throughput generation of antibody fragments

In the emerging field of proteomics, there is an urgent need for catcher molecules such as antibodies for detecting the proteome or parts of the proteome in a microarray format. A suitable source for providing a large diversity of binders is obtained by combinatorial libraries, such as phage display libraries of single chain antibody fragments (scFv) or Fab fragments. To find novel binders from the n-CoDeR libraries with a high throughput, we have automated the screening process with robotics. The automated system is configured to screen tens of thousands of clones per day to target antigens in various formats, including peptides and soluble proteins, as well as cell-bound targets; thus, it is well designed to meet demands from the proteomics area.     

Detection and quantification of protein biomarkers from fewer than 10 cells

The use of antibody microarrays continues to grow rapidly due to the recent advances in proteomics and automation and the opportunity this combination creates for high throughput multiplexed analysis of protein biomarkers. However, a primary limitation of this technology is the lack of PCR-like amplification methods for proteins. Therefore, to realize the full potential of array-based protein biomarker screening it is necessary to construct assays that can detect and quantify protein biomarkers with very high sensitivity, in the femtomolar range, and from limited sample quantities. We describe here the construction of ultramicroarrays, combining the advantages of microarraying including multiplexing capabilities, higher throughput, and cost savings with the ability to screen very small sample volumes. Antibody ultramicroarrays for the detection of interleukin-6 and prostate-specific antigen (PSA), a widely used biomarker for prostate cancer screening, were constructed. These ultramicroarrays were found to have a high specificity and sensitivity with detection levels using purified proteins in the attomole range. Using these ultramicroarrays, we were able to detect PSA secreted from 100 LNCaP cells in 3 h and from just four LNCaP cells in 24 h. Cellular PSA could also be detected from the lysate of an average of just six cells. This strategy should enable proteomic analysis of materials that are available in very limited quantities such as those collected by laser capture microdissection, neonatal biopsy microspecimens, and forensic samples.     

Quality assessment and interference detection in targeted mass spectrometry data using machine learning

Advances in the field of targeted proteomics and mass spectrometry have significantly improved assay sensitivity and multiplexing capacity. The high-throughput nature of targeted proteomics experiments has increased the rate of data production, which requires development of novel analytical tools to keep up with data processing demand. Currently, development and validation of targeted mass spectrometry assays require manual inspection of chromatographic peaks from large datasets to ensure quality, a process that is time consuming, prone to inter- and intra-operator variability and limits the efficiency of data interpretation from targeted proteomics analyses. To address this challenge, we have developed TargetedMSQC, an R package that facilitates quality control and verification of chromatographic peaks from targeted proteomics datasets. This tool calculates metrics to quantify several quality aspects of a chromatographic peak, e.g. symmetry, jaggedness and modality, co-elution and shape similarity of monitored transitions in a peak group, as well as the consistency of transitions’ ratios between endogenous analytes and isotopically labeled internal standards and consistency of retention time across multiple runs. The algorithm takes advantage of supervised machine learning to identify peaks with interference or poor chromatography based on a set of peaks that have been annotated by an expert analyst. Using TargetedMSQC to analyze targeted proteomics data reduces the time spent on manual inspection of peaks and improves both speed and accuracy of interference detection. Additionally, by allowing the analysts to customize the tool for application on different datasets, TargetedMSQC gives the users the flexibility to define the acceptable quality for specific datasets. Furthermore, automated and quantitative assessment of peak quality offers a more objective and systematic framework for high throughput analysis of targeted mass spectrometry assay datasets and is a step towards more robust and faster assay implementation.     

Selection of recombinant anti‐SH3 domain antibodies by high‐throughput phage display

Antibodies are indispensable tools in biochemical research and play an expanding role as therapeutics. While hybridoma technology is the dominant method for antibody production, phage display is an emerging technology. Here, we developed and employed a high‐throughput pipeline that enables selection of antibodies against hundreds of antigens in parallel. Binding selections using a phage‐displayed synthetic antigen‐binding fragment (Fab) library against 110 human SH3 domains yielded hundreds of Fabs targeting 58 antigens. Affinity assays demonstrated that representative Fabs bind tightly and specifically to their targets. Furthermore, we developed an efficient affinity maturation strategy adaptable to high‐throughput, which increased affinity dramatically but did not compromise specificity. Finally, we tested Fabs in common cell biology applications and confirmed recognition of the full‐length antigen in immunoprecipitation, immunoblotting and immunofluorescence assays. In summary, we have established a rapid and robust high‐throughput methodology that can be applied to generate highly functional and renewable antibodies targeting protein domains on a proteome‐wide scale.     

PRINCESS, a protein interaction confidence evaluation system with multiple data sources

Advances in proteomics technologies have enabled novel protein interactions to be detected at high speed, but they come at the expense of relatively low quality. Therefore, a crucial step in utilizing the high throughput protein interaction data is evaluating their confidence and then separating the subsets of reliable interactions from the background noise for further analyses. Using Bayesian network approaches, we combine multiple heterogeneous biological evidences, including model organism protein-protein interaction, interaction domain, functional annotation, gene expression, genome context, and network topology structure, to assign reliability to the human protein-protein interactions identified by high throughput experiments. This method shows high sensitivity and specificity to predict true interactions from the human high throughput protein-protein interaction data sets. This method has been developed into an on-line confidence scoring system specifically for the human high throughput protein-protein interactions. Users may submit their protein-protein interaction data on line, and the detailed information about the supporting evidence for query interactions together with the confidence scores will be returned. The Web interface of PRINCESS (protein interaction confidence evaluation system with multiple data sources) is available at the website of China Human Proteome Organisation.     

A proteomics-based approach for monoclonal antibody characterization

The determination of monoclonal antibody specificity is dependent upon the availability of purified antigen. Such material is not always available and this has proven to be one of the rate-limiting steps in monoclonal antibody production. The aim of the present study was to develop a generic approach to defining antibody specificity that bypassed the need for pure antigens through the use of proteomics. The scheme and its application to several biological mixtures are described. The results demonstrate the ability of the approach to identify antibodies against both the major components and the minor contaminants of a protein mixture. This approach should markedly enhance the characterization of antibodies to complex antigen mixtures.     

High-level generation of polyclonal antibodies by genetic immunization

Antibodies are important tools for investigating the proteome, but current methods for producing them have become a rate-limiting step. A primary obstacle in most methods for generating antibodies or antibody-like molecules is the requirement for at least microgram quantities of purified protein. We have developed a technology for producing antibodies using genetic immunization. Genetic immunization-based antibody production offers several advantages, including high throughput and high specificity. Moreover, antibodies produced from genetically immunized animals are more likely to recognize the native protein. Here we show that a genetic immunization-based system can be used to efficiently raise useful antibodies to a wide range of antigens. We accomplished this by linking the antigen gene to various elements that enhance antigenicity and by codelivering plasmids encoding genetic adjuvants. Our system, which was tested by immunizing mice with >130 antigens, has shown a final success rate of 84%.     

The intracellular antibody capture technology (IACT): towards a consensus sequence for intracellular antibodies

We describe the application of an intracellular antibody capture technology (IACT) as a generic in vivo selection procedure for isolating intracellular antibodies or ICAbs. IACT was applied to the de novo selection of functional ICAbs against the microtubule-associated protein TAU, found in neurofibrillary lesions of Alzheimer's disease brains. A panel of 17 different ICAbs was created which bind TAU inside cells and the epitopes recognized by the selected ICAbs have been determined by an in vivo epitope mapping procedure. Finally, sequence analysis showed that the IACT-derived ICAbs are characterized by a common signature of conserved amino acid residues, suggesting that the IACT naturally selects a sort of "captured consensus sequence" for intracellular antibodies. The development of IACT, together with the possibility of scaling up in a high throughput and automated format, makes IACT a new enabling tool for target validation in functional genomics and global proteomics.     

Index hopping on the Illumina HiseqX platform and its consequences for ancient DNA studies

The high‐throughput capacities of the Illumina sequencing platforms and the possibility to label samples individually have encouraged wide use of sample multiplexing. However, this practice results in read misassignment (usually <1%) across samples sequenced on the same lane. Alarmingly high rates of read misassignment of up to 10% were reported for lllumina sequencing machines with exclusion amplification chemistry. This may make use of these platforms prohibitive, particularly in studies that rely on low‐quantity and low‐quality samples, such as historical and archaeological specimens. Here, we use barcodes, short sequences that are ligated to both ends of the DNA insert, to directly quantify the rate of index hopping in 100‐year old museum‐preserved gorilla (Gorilla beringei) samples. Correcting for multiple sources of noise, we identify on average 0.470% of reads containing a hopped index. We show that sample‐specific quantity of misassigned reads depends on the number of reads that any given sample contributes to the total sequencing pool, so that samples with few sequenced reads receive the greatest proportion of misassigned reads. This particularly affects ancient DNA samples, as these frequently differ in their DNA quantity and endogenous content. Through simulations we show that even low rates of index hopping, as reported here, can lead to biases in ancient DNA studies when multiplexing samples with vastly different quantities of endogenous material.     

A cancer protein microarray platform using antibody fragments and its clinical applications

Antibody microarrays have shown great potential for measurement of either a spectrum of target proteins in proteomics or disease-associated antigens in molecular diagnostics. Despite its importance, the applications of antibody microarrays are still limited by a variety of fundamental problems. Among them, cross-reactivity significantly limits the multiplexing ability in parallel sandwich immunoassays. As a result, it is very important to design new capture probes in order to incorporate a universal label into the assay configuration. In this report, an antibody fragments (F(ab')2) microarray platform for serum tumor markers was developed. Each antigen was detected at different concentrations to assemble its calibration curve, and combinations of different markers were tested to examine the specificity of simultaneous detection based on the F(ab')2 microarrays. Diagnostics of serum samples with this cancer antibody microarray platform and immunoradiometric assays (IRMA) were also performed. Wide range calibration curves (0-1280 U mL(-1)) were obtained for each tumor marker. Comparative studies demonstrated that such F(ab')2 microarrays exhibited both moderately improved sensitivity and better specificity than full-sized monoclonal antibody microarrays. It is also demonstrated that this microarray platform is quantitative, highly specific and reasonably sensitive. More importantly, clinical applications of our F(ab')2 microarray platform for upwards of 100 patient serum samples clearly show its potential in cancer diagnostics.     

Single plasmonic nanoparticles for biosensing

Along with remarkable progress of nanoplasmonics over the past 10 years, single plasmonic nanoparticle sensors have introduced a completely new dimension to the sensing scale, considering that nanoparticles are comparable in size to biomolecules such as nucleic acids or antibodies. Single particle sensing methods have recently shown the possibility of detecting the adsorption of single biomolecules, and have already provided information about conformational changes of single molecules. For practical application, arrays of such compact sensor units are expected to realize massive multiplexing and high throughput in diagnostics and drug discovery in the near future. In this review, recent achievements and perspectives of this emerging biosensing technique are discussed.     

Microfluidic analysis of antibody specificity in a compact disk format

A new and flexible technology for high throughput analysis of antibody specificity and affinity is presented. The method is based on microfluidics and takes advantage of compact disks (CDs) in which the centrifugal force moves fluids through microstructures containing immobilized metal affinity chromatography columns. Analyses are performed as a sandwich assay, where antigen is captured to the column via a genetically attached His6-tag. The antibodies to be analyzed are applied onto the columns. Thereafter, fluorescently labeled secondary antibodies recognize the bound primary antibodies, and detection is carried out by laser-induced fluorescence. The CDs contain 104 microstructures enabling analysis of antibodies against more than 100 different proteins using a single CD. Importantly, through the three-dimensional visualization of the binding patterns in a column it is possible to separate high affinity from low affinity binding. The method presented here is shown to be very sensitive, flexible and reproducible.     

Multispecific monoclonal antibodies]

Immunization of BALB/c mice with Rickettsia prowazekii antigens, Bordetella pertussis toxin and Legionella pneumophila cytolysin induces the synthesis of IgM autoantibodies of different specificity. Among monoclonal antibodies, multispecific antibodies with a wide reactivity spectrum have been found to make up high percentage (30-80%). Monoclonal antibodies interact with different bacterial antigens and tissue substances. A hypothesis has been put forward that normally the injection of the antigen is followed by the appearance of antigen-nonspecific "immunological noise", including the synthesis of both tissue-specific and multispecific autoantibodies. Such antigen nonspecific "immunological noise" must have a certain threshold level which can be determined with the use of hybridoma techniques. This problem is particularly topical for bacterial antigens, as many of them are used in the development of vaccinal preparations, which may lead to an increase in the synthesis of autoantibodies and induce different autoimmune disturbances in the body.     

Investigation of post-translational modifications in type 2 diabetes

The investigation of post-translational modifications (PTMs) plays an important role for the study of type 2 diabetes. The importance of PTMs has been realized with the advancement of analytical techniques. The challenging detection and analysis of post-translational modifications is eased by different enrichment methods and by high throughput mass spectrometry based proteomics studies. This technology along with different quantitation methods provide accurate knowledge about the changes happening in disease conditions as well as in normal conditions. In this review, we have discussed PTMs such as phosphorylation, N-glycosylation, O-GlcNAcylation, acetylation and advanced glycation end products in type 2 diabetes which have been characterized by high throughput mass spectrometry based proteomics analysis.     

Urinary proteomics: a tool to discover biomarkers of kidney diseases

There is intense interest in applying proteomics to urine analysis in order to promote a better understanding of kidney disease processes, develop new biomarkers for diagnosis and detect early factors that contribute to end-stage renal diseases. This interest creates numerous opportunities as well as challenges. To fulfill this task, proteomics requires, in its different stages of realization, various technological platforms with high sensitivity, high throughput and large automation ability. In this review, we will give an overview of promising proteomic methods that can be used for analyzing urinary proteome and detecting biomarkers for different kidney diseases. Furthermore, we will focus on the current status and future directions in investigating kidney diseases using urinary proteomics.     

Deep Profiling of Cellular Heterogeneity by Emerging Single‐Cell Proteomic Technologies

The ability to comprehensively profile cellular heterogeneity in functional proteome is crucial in advancing the understanding of cell behavior, organism development, and disease mechanisms. Conventional bulk measurement by averaging the biological responses across a population often loses the information of cellular variations. Single‐cell proteomic technologies are becoming increasingly important to understand and discern cellular heterogeneity. The well‐established methods for single‐cell protein analysis based on flow cytometry and fluorescence microscopy are limited by the low multiplexing ability owing to the spectra overlap of fluorophores for labeling antibodies. Recent advances in mass spectrometry (MS), microchip, and reiterative staining‐based techniques for single‐cell proteomics have enabled the evaluation of cellular heterogeneity with high throughput, increased multiplexity, and improved sensitivity. In this review, the principles, developments, advantages, and limitations of these advanced technologies in analysis of single‐cell proteins, along with their biological applications to study cellular heterogeneity, are described. At last, the remaining challenges, possible strategies, and future opportunities that will facilitate the improvement and broad applications of single‐cell proteomic technologies in cell biology and medical research are discussed.