Epitope-resolved profiling of the SARS-CoV-2 antibody response identifies cross-reactivity with endemic human coronaviruses.

The SARS-CoV-2 proteome shares regions of conservation with endemic human coronaviruses (CoVs), but it remains unknown to what extent these may be cross-recognized by the antibody response. Here, we study cross-reactivity using a highly multiplexed peptide assay (PepSeq) to generate an epitope-resolved view of IgG reactivity across all human CoVs in both COVID-19 convalescent and negative donors. PepSeq resolves epitopes across the SARS-CoV-2 Spike and Nucleocapsid proteins that are commonly targeted in convalescent donors, including several sites also recognized in some uninfected controls. By comparing patterns of homologous reactivity between CoVs and using targeted antibody-depletion experiments, we demonstrate that SARS-CoV-2 elicits antibodies that cross-recognize pandemic and endemic CoV antigens at two Spike S2 subunit epitopes. We further show that these cross-reactive antibodies preferentially bind endemic homologs. Our findings highlight sites at which the SARS-CoV-2 response appears to be shaped by previous CoV exposures and which have the potential to raise broadly neutralizing responses.

Epitope-resolved profiling of the SARS-CoV-2 antibody response identifies cross-reactivity with an endemic human CoV.

A high-resolution understanding of the antibody response to SARS-CoV-2 is important for the design of effective diagnostics, vaccines and therapeutics. However, SARS-CoV-2 antibody epitopes remain largely uncharacterized, and it is unknown whether and how the response may cross-react with related viruses. Here, we use a multiplexed peptide assay ('PepSeq') to generate an epitope-resolved view of reactivity across all human coronaviruses. PepSeq accurately detects SARS-CoV-2 exposure and resolves epitopes across the Spike and Nucleocapsid proteins. Two of these represent recurrent reactivities to conserved, functionally-important sites in the Spike S2 subunit, regions that we show are also targeted for the endemic coronaviruses in pre-pandemic controls. At one of these sites, we demonstrate that the SARS-CoV-2 response strongly and recurrently cross-reacts with the endemic virus hCoV-OC43. Our analyses reveal new diagnostic and therapeutic targets, including a site at which SARS-CoV-2 may recruit common pre-existing antibodies and with the potential for broadly-neutralizing responses.

National Cancer Institute Think-Tank Meeting Report on Proteomic Cartography and Biomarkers at the Single-Cell Level: Interrogation of Premalignant Lesions.

A Think-Tank Meeting was convened by the National Cancer Institute (NCI) to solicit experts' opinion on the development and application of multiomic single-cell analyses, and especially single-cell proteomics, to improve the development of a new generation of biomarkers for cancer risk, early detection, diagnosis, and prognosis as well as to discuss the discovery of new targets for prevention and therapy. It is anticipated that such markers and targets will be based on cellular, subcellular, molecular, and functional aberrations within the lesion and within individual cells. Single-cell proteomic data will be essential for the establishment of new tools with searchable and scalable features that include spatial and temporal cartographies of premalignant and malignant lesions. Challenges and potential solutions that were discussed included (i) The best way/s to analyze single-cells from fresh and preserved tissue; (ii) Detection and analysis of secreted molecules and from single cells, especially from a tissue slice; (iii) Detection of new, previously undocumented cell type/s in the premalignant and early stage cancer tissue microenvironment; (iv) Multiomic integration of data to support and inform proteomic measurements; (v) Subcellular organelles-identifying abnormal structure, function, distribution, and location within individual premalignant and malignant cells; (vi) How to improve the dynamic range of single-cell proteomic measurements for discovery of differentially expressed proteins and their post-translational modifications (PTM); (vii) The depth of coverage measured concurrently using single-cell techniques; (viii) Quantitation - absolute or semiquantitative? (ix) Single methodology or multiplexed combinations? (x) Application of analytical methods for identification of biologically significant subsets; (xi) Data visualization of N-dimensional data sets; (xii) How to construct intercellular signaling networks in individual cells within premalignant tumor microenvironments (TME); (xiii) Associations between intrinsic cellular processes and extrinsic stimuli; (xiv) How to predict cellular responses to stress-inducing stimuli; (xv) Identification of new markers for prediction of progression from precursor, benign, and localized lesions to invasive cancer, based on spatial and temporal changes within individual cells; (xvi) Identification of new targets for immunoprevention or immunotherapy-identification of neoantigens and surfactome of individual cells within a lesion.

High-resolution analysis and functional mapping of cleavage sites and substrate proteins of furin in the human proteome.

BACKGROUND: There is a growing appreciation of the role of proteolytic processes in human health and disease, but tools for analysis of such processes on a proteome-wide scale are limited. Furin is a ubiquitous proprotein convertase that cleaves after basic residues and transforms secretory proproteins into biologically active proteins. Despite this important role, many furin substrates remain unknown in the human proteome. METHODOLOGY/PRINCIPAL FINDINGS: We devised an approach for proteinase target identification that combines an in silico discovery pipeline with highly multiplexed proteinase activity assays. We performed in silico analysis of the human proteome and identified over 1,050 secretory proteins as potential furin substrates. We then used a multiplexed protease assay to validate these tentative targets. The assay was carried out on over 3,260 overlapping peptides designed to represent P7-P1' and P4-P4' positions of furin cleavage sites in the candidate proteins. The obtained results greatly increased our knowledge of the unique cleavage preferences of furin, revealed the importance of both short-range (P4-P1) and long-range (P7-P6) interactions in defining furin cleavage specificity, demonstrated that the R-X-R/K/X-R ↓ motif alone is insufficient for predicting furin proteolysis of the substrate, and identified ≈ 490 potential protein substrates of furin in the human proteome. CONCLUSIONS/SIGNIFICANCE: The assignment of these substrates to cellular pathways suggests an important role of furin in development, including axonal guidance, cardiogenesis, and maintenance of stem cell pluripotency. The novel approach proposed in this study can be readily applied to other proteinases.

A highly scalable peptide-based assay system for proteomics.

We report a scalable and cost-effective technology for generating and screening high-complexity customizable peptide sets. The peptides are made as peptide-cDNA fusions by in vitro transcription/translation from pools of DNA templates generated by microarray-based synthesis. This approach enables large custom sets of peptides to be designed in silico, manufactured cost-effectively in parallel, and assayed efficiently in a multiplexed fashion. The utility of our peptide-cDNA fusion pools was demonstrated in two activity-based assays designed to discover protease and kinase substrates. In the protease assay, cleaved peptide substrates were separated from uncleaved and identified by digital sequencing of their cognate cDNAs. We screened the 3,011 amino acid HCV proteome for susceptibility to cleavage by the HCV NS3/4A protease and identified all 3 known trans cleavage sites with high specificity. In the kinase assay, peptide substrates phosphorylated by tyrosine kinases were captured and identified by sequencing of their cDNAs. We screened a pool of 3,243 peptides against Abl kinase and showed that phosphorylation events detected were specific and consistent with the known substrate preferences of Abl kinase. Our approach is scalable and adaptable to other protein-based assays.

New details of HCV NS3/4A proteinase functionality revealed by a high-throughput cleavage assay.

BACKGROUND: The hepatitis C virus (HCV) genome encodes a long polyprotein, which is processed by host cell and viral proteases to the individual structural and non-structural (NS) proteins. HCV NS3/4A serine proteinase (NS3/4A) is a non-covalent heterodimer of the N-terminal, ∼180-residue portion of the 631-residue NS3 protein with the NS4A co-factor. NS3/4A cleaves the polyprotein sequence at four specific regions. NS3/4A is essential for viral replication and has been considered an attractive drug target. METHODOLOGY/PRINCIPAL FINDINGS: Using a novel multiplex cleavage assay and over 2,660 peptide sequences derived from the polyprotein and from introducing mutations into the known NS3/4A cleavage sites, we obtained the first detailed fingerprint of NS3/4A cleavage preferences. Our data identified structural requirements illuminating the importance of both the short-range (P1-P1') and long-range (P6-P5) interactions in defining the NS3/4A substrate cleavage specificity. A newly observed feature of NS3/4A was a high frequency of either Asp or Glu at both P5 and P6 positions in a subset of the most efficient NS3/4A substrates. In turn, aberrations of this negatively charged sequence such as an insertion of a positively charged or hydrophobic residue between the negatively charged residues resulted in inefficient substrates. Because NS5B misincorporates bases at a high rate, HCV constantly mutates as it replicates. Our analysis revealed that mutations do not interfere with polyprotein processing in over 5,000 HCV isolates indicating a pivotal role of NS3/4A proteolysis in the virus life cycle. CONCLUSIONS/SIGNIFICANCE: Our multiplex assay technology in light of the growing appreciation of the role of proteolytic processes in human health and disease will likely have widespread applications in the proteolysis research field and provide new therapeutic opportunities.

Detection of low prevalence somatic mutations in solid tumors with ultra-deep targeted sequencing.

Ultra-deep targeted sequencing (UDT-Seq) can identify subclonal somatic mutations in tumor samples. Early assays' limited breadth and depth restrict their clinical utility. Here, we target 71 kb of mutational hotspots in 42 cancer genes. We present novel methods enhancing both laboratory workflow and mutation detection. We evaluate UDT-Seq true sensitivity and specificity (> 94% and > 99%, respectively) for low prevalence mutations in a mixing experiment and demonstrate its utility using six tumor samples. With an improved performance when run on the Illumina Miseq, the UDT-Seq assay is well suited for clinical applications to guide therapy and study clonal selection in heterogeneous samples.

Discovery of non-ETS gene fusions in human prostate cancer using next-generation RNA sequencing.

Half of prostate cancers harbor gene fusions between TMPRSS2 and members of the ETS transcription factor family. To date, little is known about the presence of non-ETS fusion events in prostate cancer. We used next-generation transcriptome sequencing (RNA-seq) in order to explore the whole transcriptome of 25 human prostate cancer samples for the presence of chimeric fusion transcripts. We generated more than 1 billion sequence reads and used a novel computational approach (FusionSeq) in order to identify novel gene fusion candidates with high confidence. In total, we discovered and characterized seven new cancer-specific gene fusions, two involving the ETS genes ETV1 and ERG, and four involving non-ETS genes such as CDKN1A (p21), CD9, and IKBKB (IKK-beta), genes known to exhibit key biological roles in cellular homeostasis or assumed to be critical in tumorigenesis of other tumor entities, as well as the oncogene PIGU and the tumor suppressor gene RSRC2. The novel gene fusions are found to be of low frequency, but, interestingly, the non-ETS fusions were all present in prostate cancer harboring the TMPRSS2-ERG gene fusion. Future work will focus on determining if the ETS rearrangements in prostate cancer are associated or directly predispose to a rearrangement-prone phenotype.

FusionSeq: a modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data.

We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts, such as misalignment or random pairing of transcript fragments, and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including eight cancers with and without known rearrangements.

N-myc downstream regulated gene 1 (NDRG1) is fused to ERG in prostate cancer.

A step toward the molecular classification of prostate cancer was the discovery of recurrent erythroblast transformation-specific rearrangements, most commonly fusing the androgen-regulated TMPRSS2 promoter to ERG. The TMPRSS2-ERG fusion is observed in around 90% of tumors that overexpress the oncogene ERG. The goal of the current study was to complete the characterization of these ERG-overexpressing prostate cancers. Using fluorescence in situ hybridization and reverse transcription-polymerase chain reaction assays, we screened 101 prostate cancers, identifying 34 cases (34%) with the TMPRSS2-ERG fusion. Seven cases demonstrated ERG rearrangement by fluorescence in situ hybridization without the presence of TMPRSS2-ERG fusion messenger RNA transcripts. Screening for known 5' partners, we determined that three cases harbored the SLC45A3-ERG fusion. To discover novel 5' partners in these ERG-overexpressing and ERG-rearranged cases, we used paired-end RNA sequencing. We first confirmed the utility of this approach by identifying the TMPRSS2-ERG fusion in a known positive prostate cancer case and then discovered a novel fusion involving the androgen-inducible tumor suppressor, NDRG1 (N-myc downstream regulated gene 1), and ERG in two cases. Unlike TMPRSS2-ERG and SCL45A3-ERG fusions, the NDRG1-ERG fusion is predicted to encode a chimeric protein. Like TMPRSS2, SCL45A3 and NDRG1 are inducible not only by androgen but also by estrogen. This study demonstrates that most ERG-overexpressing prostate cancers harbor hormonally regulated TMPRSS2-ERG, SLC45A3-ERG, or NDRG1-ERG fusions. Broader implications of this study support the use of RNA sequencing to discover novel cancer translocations.

Microarray-based multicycle-enrichment of genomic subsets for targeted next-generation sequencing.

The lack of efficient high-throughput methods for enrichment of specific sequences from genomic DNA represents a key bottleneck in exploiting the enormous potential of next-generation sequencers. Such methods would allow for a systematic and targeted analysis of relevant genomic regions. Recent studies reported sequence enrichment using a hybridization step to specific DNA capture probes as a possible solution to the problem. However, so far no method has provided sufficient depths of coverage for reliable base calling over the entire target regions. We report a strategy to multiply the enrichment performance and consequently improve depth and breadth of coverage for desired target sequences by applying two iterative cycles of hybridization with microfluidic Geniom biochips. Using this strategy, we enriched and then sequenced the cancer-related genes BRCA1 and TP53 and a set of 1000 individual dbSNP regions of 500 bp using Illumina technology. We achieved overall enrichment factors of up to 1062-fold and average coverage depths of 470-fold. Combined with high coverage uniformity, this resulted in nearly complete consensus coverages with >86% of target region covered at 20-fold or higher. Analysis of SNP calling accuracies after enrichment revealed excellent concordance, with the reference sequence closely mirroring the previously reported performance of Illumina sequencing conducted without sequence enrichment.

Highly parallel genomic assays.

Recent developments in highly parallel genome-wide assays are transforming the study of human health and disease. High-resolution whole-genome association studies of complex diseases are finally being undertaken after much hypothesizing about their merit for finding disease loci. The availability of inexpensive high-density SNP-genotyping arrays has made this feasible. Cancer biology will also be transformed by high-resolution genomic and epigenomic analysis. In the future, most cancers might be staged by high-resolution molecular profiling rather than by gross cytological analysis. Here, we describe the key developments that enable highly parallel genomic assays.

High-throughput DNA methylation profiling using universal bead arrays.

We have developed a high-throughput method for analyzing the methylation status of hundreds of preselected genes simultaneously and have applied it to the discovery of methylation signatures that distinguish normal from cancer tissue samples. Through an adaptation of the GoldenGate genotyping assay implemented on a BeadArray platform, the methylation state of 1536 specific CpG sites in 371 genes (one to nine CpG sites per gene) was measured in a single reaction by multiplexed genotyping of 200 ng of bisulfite-treated genomic DNA. The assay was used to obtain a quantitative measure of the methylation level at each CpG site. After validating the assay in cell lines and normal tissues, we analyzed a panel of lung cancer biopsy samples (N = 22) and identified a panel of methylation markers that distinguished lung adenocarcinomas from normal lung tissues with high specificity. These markers were validated in a second sample set (N = 24). These results demonstrate the effectiveness of the method for reliably profiling many CpG sites in parallel for the discovery of informative methylation markers. The technology should prove useful for DNA methylation analyses in large populations, with potential application to the classification and diagnosis of a broad range of cancers and other diseases.

A genome-wide scalable SNP genotyping assay using microarray technology.

Oligonucleotide probe arrays have enabled massively parallel analysis of gene expression levels from a single cDNA sample. Application of microarray technology to analyzing genomic DNA has been stymied by the sequence complexity of the entire human genome. A robust, single base-resolution direct genomic assay would extend the reach of microarray technology. We developed an array-based whole-genome genotyping assay that does not require PCR and enables effectively unlimited multiplexing. The assay achieves a high signal-to-noise ratio by combining specific hybridization of picomolar concentrations of whole genome-amplified DNA to arrayed probes with allele-specific primer extension and signal amplification. As proof of principle, we genotyped several hundred previously characterized SNPs. The conversion rate, call rate and accuracy were comparable to those of high-performance PCR-based genotyping assays.

A novel, high-performance random array platform for quantitative gene expression profiling.

We have developed a new microarray technology for quantitative gene-expression profiling on the basis of randomly assembled arrays of beads. Each bead carries a gene-specific probe sequence. There are multiple copies of each sequence-specific bead in an array, which contributes to measurement precision and reliability. We optimized the system for specific and sensitive analysis of mammalian RNA, and using RNA controls of defined concentration, obtained the following estimates of system performance: specificity of 1:250,000 in mammalian poly(A(+)) mRNA; limit of detection 0.13 pM; dynamic range 3.2 logs; and sufficient precision to detect 1.3-fold differences with 95% confidence within the dynamic range. Measurements of expression differences between human brain and liver were validated by concordance with quantitative real-time PCR (R(2) = 0.98 for log-transformed ratios, and slope of the best-fit line = 1.04, for 20 genes). Quantitative performance was further verified using a mouse B- and T-cell model system. We found published reports of B- or T-cell-specific expression for 42 of 59 genes that showed the greatest differential expression between B- and T-cells in our system. All of the literature observations were concordant with our results. Our experiments were carried out on a 96-array matrix system that requires only 100 ng of input RNA and uses standard microtiter plates to process samples in parallel. Our technology has advantages for analyzing multiple samples, is scalable to all known genes in a genome, and is flexible, allowing the use of standard or custom probes in an array.

A versatile assay for high-throughput gene expression profiling on universal array matrices.

We report a flexible, sensitive, and quantitative gene-expression profiling system for assaying more than 400 genes, with three probes per gene, for 96 samples in parallel. The cDNA-mediated annealing, selection, extension and ligation (DASL) assay targets specific transcripts, using oligonucleotides containing unique address sequences that can hybridize to universal arrays. Cell-specific gene expression profiles were obtained using this assay for hormone-treated cell lines and laser-capture microdissected cancer tissues. Gene expression profiles derived from this assay were consistent with those determined by qRT-PCR. The DASL assay has been automated for use with a bead-based 96-array matrix system. The combined high-throughput assay and readout system is accurate and efficient, and can cost-effectively profile the expression of hundreds of genes in thousands of samples.

Decoding randomly ordered DNA arrays.

We have developed a simple and efficient algorithm to identify each member of a large collection of DNA-linked objects through the use of hybridization, and have applied it to the manufacture of randomly assembled arrays of beads in wells. Once the algorithm has been used to determine the identity of each bead, the microarray can be used in a wide variety of applications, including single nucleotide polymorphism genotyping and gene expression profiling. The algorithm requires only a few labels and several sequential hybridizations to identify thousands of different DNA sequences with great accuracy. We have decoded tens of thousands of arrays, each with 1520 sequences represented at approximately 30-fold redundancy by up to approximately 50,000 beads, with a median error rate of <1 x 10(-4) per bead. The approach makes use of error checking codes and provides, for the first time, a direct functional quality control of every element of each array that is manufactured. The algorithm can be applied to any spatially fixed collection of objects or molecules that are associated with specific DNA sequences.

Efficient strategies for the conjugation of oligonucleotides to antibodies enabling highly sensitive protein detection.

Three methods for the conjugation of oligonucleotides to antibodies and the subsequent application of these conjugates to protein detection at attomole levels in immunoassays are described. The methods are based on chemical modification of both antibody and oligonucleotide. Aldehydes were introduced onto antibodies by modification of primary amines or oxidation of carbohydrate residues. Aldehyde- or hydrazine-modified oligonucleotides were prepared either during phosphoramidite synthesis or by post-synthesis derivatization. Conjugation between the modified oligonucleotide and antibody resulted in the formation of a hydrazone bond that proved to be stable over long periods of time under physiological conditions. The binding activity of each antibody-oligonucleotide conjugate was determined to be comparable to the corresponding unmodified antibody using a standard sandwich ELISA. Each oligonucleotide contained a unique DNA sequence flanked by universal primers at both ends and was assigned to a specific antibody. Highly sensitive immunoassays were performed by immobilizing analyte for each conjugate onto a solid support with cognate capture antibodies. Binding of the antibody-oligonucleotide conjugate to the immobilized analyte allowed for amplification of the attached DNA. Products of amplification were visualized using gel electrophoresis, thus denoting the presence of bound analyte. The preferred conjugation method was used to generate a set of antibody-oligonucleotide conjugates suitable for high-sensitivity protein detection.

A highly informative SNP linkage panel for human genetic studies.

We have developed a highly informative set of single-nucleotide polymorphism (SNP) assays designed for linkage mapping of the human genome. These assays were developed on a robust multiplexed assay system to provide a combination of very high accuracy and data completeness with high throughput for linkage studies. The linkage panel is comprised of approximately 4,700 SNPs with 0.39 average minor allele frequency and 624-kb average spacing. Based on almost 2 million genotypes, data quality was shown to be extremely high, with a 99.94% call rate, >99.99% reproducibility and 99.995% genotypes consistent with mendelian inheritance. We constructed a genetic map with an average 1.5-cM resolution using series of 28 CEPH pedigrees. The relative information content of this panel was higher than those of commonly used STR marker panels. The potent combination of this SNP linkage panel with the multiplexed assay system provides a previously unattainable level of performance for linkage studies.

BeadArray technology: enabling an accurate, cost-effective approach to high-throughput genotyping.

The Human Genome Project has opened the door to personalized medicine, provided that human genetic diversity can be analyzed in a high-throughput and cost-effective way Illumina has developed a genotyping system that combines very high throughput and accuracy with low cost per SNP analysis. The system uses our BeadArray platform, a high level of multiplexing, and modular, scalable automation to meet the requirements for cost-effective, genome-wide linkage disequilibrium studies. As implemented in a high-throughput genotyping service facility at Illumina, the system has a current capacity of one million SNP assays per day and is easily expandable. Each SNP call is associated with a quality score that correlates with accuracy