Decoy Approach Research Articles

Assessing Multiple Evidence Streams to Decide on Confidence for Identification of Post-Translational Modifications, within and Across Data Sets.

Phosphorylation is a post-translational modification of great interest to researchers due to its relevance in many biological processes. LC-MS/MS techniques have enabled high-throughput data acquisition, with studies claiming identification and localization of thousands of phosphosites. The identification and localization of phosphosites emerge from different analytical pipelines and scoring algorithms, with uncertainty embedded throughout the pipeline. For many pipelines and algorithms, arbitrary thresholding is used, but little is known about the actual global false localization rate in these studies. Recently, it has been suggested to use decoy amino acids to estimate global false localization rates of phosphosites, among the peptide-spectrum matches reported. Here, we describe a simple pipeline aiming to maximize the information extracted from these studies by objectively collapsing from peptide-spectrum match to the peptidoform-site level, as well as combining findings from multiple studies while maintaining track of false localization rates. We show that the approach is more effective than current processes that use a simpler mechanism for handling phosphosite identification redundancy within and across studies. In our case study using eight rice phosphoproteomics data sets, 6368 unique sites were confidently identified using our decoy approach compared to 4687 using traditional thresholding in which false localization rates are unknown.

Prophylaxis and treatment of SARS-CoV-2 infection by an ACE2 receptor decoy in a preclinical animal model

The emergence of SARS-CoV-2 variants with highly mutated spike proteins has presented an obstacle to the use of monoclonal antibodies for the prevention and treatment of SARS-CoV-2 infection. We show that a high-affinity receptor decoy protein in which a modified ACE2 ectodomain is fused to a single domain of an immunoglobulin heavy chain Fc region dramatically suppressed virus loads in mice upon challenge with a high dose of parental SARS-CoV-2 or Omicron variants. The decoy also potently suppressed virus replication when administered shortly post-infection. The decoy approach offers protection against the current viral variants and, potentially, against SARS-CoV-2 variants that may emerge with the continued evolution of the spike protein or novel viruses that use ACE2 for virus entry.

Quality Control for the Target Decoy Approach for Peptide Identification.

Reliable peptide identification is key in mass spectrometry (MS) based proteomics. To this end, the target decoy approach (TDA) has become the cornerstone for extracting a set of reliable peptide-to-spectrum matches (PSMs) that will be used in downstream analysis. Indeed, TDA is now the default method to estimate the false discovery rate (FDR) for a given set of PSMs, and users typically view it as a universal solution for assessing the FDR in the peptide identification step. However, the TDA also relies on a minimal set of assumptions, which are typically never verified in practice. We argue that a violation of these assumptions can lead to poor FDR control, which can be detrimental to any downstream data analysis. We here therefore first clearly spell out these TDA assumptions, and introduce TargetDecoy, a Bioconductor package with all the necessary functionality to control the TDA quality and its underlying assumptions for a given set of PSMs.

In vitro and in vivo characterization of Recifercept, a soluble fibroblast growth factor receptor 3, as treatment for achondroplasia.

Achondroplasia is a rare genetic disorder caused by mutations in the Fibroblast Growth Factor receptor 3 (FGFR3). These mutations lead to aberrant increase of inhibitory signaling in proliferating chondrocytes at the growth plate. Recifercept is a potential treatment for this disease using a decoy approach to sequester FGFR3 ligands subsequently normalizing activation of the mutated FGFR3 receptor. Recifercept binds to FGF isoforms in vitro and in cellular model systems and reduces FGFR3 signaling. In addition, in a transgenic mouse model of achondroplasia, Recifercept restores reduced body weight and long bone growth in these mice. These data suggest that Recifercept treatment could lead to clinical benefits in children treated with this molecule.

MiR-183/96/182 cluster is an important morphogenetic factor targeting PAX6 expression in differentiating human retinal organoids.

MicroRNAs (miRNAs), a class of small, noncoding RNA molecules represent important regulators of gene expression. Recent reports have implicated their role in the cell specification process acting as "fine-tuners" to ensure the precise gene expression at the specific stage of cell differentiation. Here, we used retinal organoids differentiated from human pluripotent stem cells (hPSCs) as a model to closely investigate the role of a sensory organ-specific and evolutionary conserved miR-183/96/182 cluster. Using a miRNA tough decoy approach, we inhibited the miR-183/96/182 cluster in hPSCs. Inhibition of the miRNA cluster resulted in an increased expansion of neuroepithelium leading to abnormal "bulged" neural retina in organoids, associated with upregulation of neural-specific and retinal-specific genes. Importantly, we identified PAX6, a well-known essential gene in neuroectoderm specification, as a target of the miR-183/96/182 cluster members. Taken together, the miR-183/96/182 cluster not only represents an important regulator of PAX6 expression, but it also plays a crucial role in retinal tissue morphogenesis.

Nanoparticles presenting clusters of CD4 expose a universal vulnerability of HIV-1 by mimicking target cells

CD4-based decoy approaches against HIV-1 are attractive options for long-term viral control, but initial designs, including soluble CD4 (sCD4) and CD4-Ig, were ineffective. To evaluate a therapeutic that more accurately mimics HIV-1 target cells compared with monomeric sCD4 and dimeric CD4-Ig, we generated virus-like nanoparticles that present clusters of membrane-associated CD4 (CD4-VLPs) to permit high-avidity binding of trimeric HIV-1 envelope spikes. In neutralization assays, CD4-VLPs were >12,000-fold more potent than sCD4 and CD4-Ig and >100-fold more potent than the broadly neutralizing antibody (bNAb) 3BNC117, with >12,000-fold improvements against strains poorly neutralized by 3BNC117. CD4-VLPs also neutralized patient-derived viral isolates that were resistant to 3BNC117 and other bNAbs. Intraperitoneal injections of CD4-CCR5-VLP produced only subneutralizing plasma concentrations in HIV-1-infected humanized mice but elicited CD4-binding site mutations that reduced viral fitness. All mutant viruses showed reduced sensitivity to sCD4 and CD4-Ig but remained sensitive to neutralization by CD4-VLPs in vitro. In vitro evolution studies demonstrated that CD4-VLPs effectively controlled HIV-1 replication at neutralizing concentrations, and viral escape was not observed. Moreover, CD4-VLPs potently neutralized viral swarms that were completely resistant to CD4-Ig, suggesting that escape pathways that confer resistance against conventional CD4-based inhibitors are ineffective against CD4-VLPs. These findings suggest that therapeutics that mimic HIV-1 target cells could prevent viral escape by exposing a universal vulnerability of HIV-1: the requirement to bind CD4 on a target cell. We propose that therapeutic and delivery strategies that ensure durable bioavailability need to be developed to translate this concept into a clinically feasible functional cure therapy.

Optimizing the PBS1 Decoy System to Confer Resistance to Potyvirus Infection in Arabidopsis and Soybean.

The Arabidopsis resistance protein RPS5 is activated by proteolytic cleavage of the protein kinase PBS1 by the Pseudomonas syringae effector protease AvrPphB. We have previously shown that replacing seven amino acids at the cleavage site of PBS1 with a motif cleaved by the NIa protease of turnip mosaic virus (TuMV) enables RPS5 activation upon TuMV infection. However, this engineered resistance conferred a trailing necrosis phenotype indicative of a cell-death response too slow to contain the virus. We theorized this could result from a positional mismatch within the cell between PBS1TuMV, RPS5, and the NIa protease. To test this, we relocalized PBS1TuMV and RPS5 to cellular sites of NIa accumulation. These experiments revealed that relocation of RPS5 away from the plasma membrane compromised RPS5-dependent cell death in Nicotiana benthamiana, even though PBS1 was efficiently cleaved. As an alternative approach, we tested whether overexpression of plasma membrane-localized PBS1TuMV could enhance RPS5 activation by TuMV. Significantly, overexpressing the PBS1TuMV decoy protein conferred complete resistance to TuMV when delivered by either agrobacterium or by aphid transmission, showing that RPS5-mediated defense responses are effective against bacterial and viral pathogens. Lastly, we have now extended this PBS1 decoy approach to soybean by modifying a soybean PBS1 ortholog to be cleaved by the NIa protease of soybean mosaic virus (SMV). Transgenic overexpression of this soybean PBS1 decoy conferred immunity to SMV, demonstrating that we can use endogenous PBS1 proteins in crop plants to engineer economically relevant disease resistant traits.

RPS5-Mediated Disease Resistance: Fundamental Insights and Translational Applications.

Focusing on the discovery and characterization of the Arabidopsis disease resistance protein RPS5 and its guardee PBS1, this review discusses work done in the Innes laboratory from the initial identification of the RPS5 gene in 1995 to the recent deployment of the PBS1 decoy system in crops. This is done through discussion of the structure, function, and signaling environment of RPS5 and PBS1, highlighting collaborations and influential ideas along the way. RPS5, a nucleotide-binding leucine-rich repeat (NLR) protein, is activated by the proteolytic cleavage of PBS1. We have shown that the cleavage site within PBS1 can be altered to contain cleavage sites for other proteases, enabling RPS5 activation by these proteases, thereby conferring resistance to different pathogens. This decoy approach has since been translated into crop species using endogenous PBS1 orthologs and holds strong potential for GMO-free development of new genetic resistance against important crop pathogens.

New therapies for systemic lupus erythematosus — past imperfect, future tense

The failure of many new, mostly biologic, drugs to meet their primary end points in double-blind clinical trials in patients with systemic lupus erythematosus (SLE) has caused a profound sense of disappointment among both physicians and patients. Arguably, the success of B cell depletion with rituximab in open-label clinical trials, the approval of belimumab (which blocks B cell-activating factor (BAFF)) for use in patients with lupus nephritis in the USA and in difficult-to-treat patients with SLE in the UK and the recognition that clinical trial design can be improved have given some cause for hope. However, changes to therapies in current use and the development of new approaches are urgently needed. The results of the latest studies investigating the use of several new approaches to treating SLE are discussed in this Review, including: fully humanized anti-CD20 and anti-CD19 monoclonal antibodies; inhibition of tyrosine-protein kinase BTK; CD40 ligand blockade; interfering with the presentation of antigen to autoreactive T cells using a peptide approach; a receptor decoy approach using an analogue of Fcγ receptor IIB; dual blockade of IL-12 and IL-23; and inhibition of Janus kinases.

Engineering a Decoy Substrate in Soybean to Enable Recognition of the Soybean Mosaic Virus NIa Protease.

In Arabidopsis, recognition of the AvrPphB effector protease from Pseudomonas syringae is mediated by the disease resistance (R) protein RPS5, which is activated by AvrPphB-induced cleavage of the Arabidopsis protein kinase PBS1. The recognition specificity of RPS5 can be altered by substituting the AvrPphB cleavage site within PBS1 with cleavage sequences for other proteases, including proteases from viruses. AvrPphB also activates defense responses in soybean (Glycine max), suggesting that soybean may contain an R protein analogous to RPS5. It was unknown, however, whether this response is mediated by cleavage of a soybean PBS1-like protein. Here, we show that soybean contains three PBS1 orthologs and that their products are cleaved by AvrPphB. Further, transient expression of soybean PBS1 derivatives containing a five-alanine insertion at their AvrPphB cleavage sites activated cell death in soybean protoplasts, demonstrating that soybean likely contains an AvrPphB-specific resistance protein that is activated by a conformational change in soybean PBS1 proteins. Significantly, we show that a soybean PBS1 decoy protein modified to contain a cleavage site for the soybean mosaic virus (SMV) NIa protease triggers cell death in soybean protoplasts when cleaved by this protease, indicating that the PBS1 decoy approach will work in soybean, using endogenous PBS1 genes. Lastly, we show that activation of the AvrPphB-dependent cell death response effectively inhibits systemic spread of SMV in soybean. These data also indicate that decoy engineering may be feasible in other crop plant species that recognize AvrPphB protease activity.

Virus detection in high-throughput sequencing data without a reference genome of the host

Discovery of novel viruses in host samples is a multidisciplinary process which relies increasingly on next-generation sequencing (NGS) followed by computational analysis. A crucial step in this analysis is to separate host sequence reads from the sequence reads of the virus to be discovered. This becomes especially difficult if no reference genome of the host is available. Furthermore, if the total number of viral reads in a sample is low, de novo assembly of a virus which is a requirement for most existing pipelines is hard to realize.We present a new modular, computational pipeline for discovery of novel viruses in host samples. While existing pipelines rely on the availability of the hosts reference genome for filtering sequence reads, our new pipeline can also cope with cases for which no reference genome is available. As a further novelty of our method a decoy module is used to assess false classification rates in the discovery process. Additionally, viruses with a low read coverage can be identified and visually reviewed. We validate our pipeline on simulated data as well as two experimental samples with known virus content. For the experimental samples, we were able to reproduce the laboratory findings.Our newly developed pipeline is applicable for virus detection in a wide range of host species. The three modules we present can either be incorporated individually in other pipelines or be used as a stand-alone pipeline. We are the first to present a decoy approach within a virus detection pipeline that can be used to assess error rates so that the quality of the final result can be judged. We provide an implementation of our modules via Github. However, the principle of the modules can easily be re-implemented by other researchers.

STAT3 Cyclic Decoy Demonstrates Robust Antitumor Effects in Non-Small Cell Lung Cancer.

Constitutively activated STAT3 plays a critical role in non-small cell lung carcinoma (NSCLC) progression by mediating proliferation and survival. STAT3 activation in normal cells is transient, making it an attractive target for NSCLC therapy. The therapeutic potential of blocking STAT3 in NSCLC was assessed utilizing a decoy approach by ligating a double-stranded 15-mer oligonucleotide that corresponds to the STAT3 response element of STAT3-target genes, to produce a cyclic STAT3 decoy (CS3D). The decoy was evaluated using NSCLC cells containing either wild-type EGFR (201T) or mutant EGFR with an additional EGFRi resistance mutation (H1975). These cells are resistant to EGFR inhibitors and require an alternate therapeutic approach. CS3D activity was compared with an inactive cyclic control oligonucleotide (CS3M) that differs by a single base pair, rendering it unable to bind to STAT3 protein. Transfection of 0.3 μmol/L of CS3D caused a 50% inhibition in proliferation in 201T and H1975 cells, relative to CS3M, and a 2-fold increase in apoptotic cells. Toxicity was minimal in normal cells. CS3D treatment caused a significant reduction of mRNA and protein expression of the STAT3 target gene c-Myc and inhibited colony formation by 70%. The active decoy decreased the nuclear pool of STAT3 compared with the mutant. In a xenograft model, treatments with CS3D (5 mg/kg) caused a potent 96.5% and 81.7% reduction in tumor growth in 201T (P < 0.007) and H1975 models (P < 0.0001), respectively, and reduced c-Myc and p-STAT3 proteins. Targeting STAT3 with the cyclic decoy could be an effective therapeutic strategy for NSCLC. Mol Cancer Ther; 17(9); 1917-26. ©2018 AACR.

Modeling the therapeutic efficacy of NF\u03baB synthetic decoy oligodeoxynucleotides (ODNs)

BackgroundTransfection of NF κB synthetic decoy Oligodeoxynucleotides (ODNs) has been proposed as a promising therapeutic strategy for a variety of diseases arising from constitutive activation of the eukaryotic transcription factor NF κB. The decoy approach faces some limitations under physiological conditions notably nuclease-induced degradation.ResultsIn this work, we show how a systems pharmacology model of NF κB regulatory networks displaying oscillatory temporal dynamics, can be used to predict quantitatively the dependence of therapeutic efficacy of NF κB synthetic decoy ODNs on dose, unbinding kinetic rates and nuclease-induced degradation rates. Both deterministic mass action simulations and stochastic simulations of the systems biology model show that the therapeutic efficacy of synthetic decoy ODNs is inversely correlated with unbinding kinetic rates, nuclease-induced degradation rates and molecular stripping rates, but is positively correlated with dose. We show that the temporal coherence of the stochastic dynamics of NF κB regulatory networks is most sensitive to adding NF κB synthetic decoy ODNs having unbinding time-scales that are in-resonance with the time-scale of the limit cycle of the network.ConclusionsThe pharmacokinetics/pharmacodynamics (PK/PD) predicted by the systems-level model should provide quantitative guidance for in-depth translational research of optimizing the thermodynamics/kinetic properties of synthetic decoy ODNs.

DecoyPyrat: Fast Non-redundant Hybrid Decoy Sequence Generation for Large Scale Proteomics.

Accurate statistical evaluation of sequence database peptide identifications from tandem mass spectra is essential in mass spectrometry based proteomics experiments. These statistics are dependent on accurately modelling random identifications. The target-decoy approach has risen to become the de facto approach to calculating FDR in proteomic datasets. The main principle of this approach is to search a set of decoy protein sequences that emulate the size and composition of the target protein sequences searched whilst not matching real proteins in the sample. To do this, it is commonplace to reverse or shuffle the proteins and peptides in the target database. However, these approaches have their drawbacks and limitations. A key confounding issue is the peptide redundancy between target and decoy databases leading to inaccurate FDR estimation. This inaccuracy is further amplified at the protein level and when searching large sequence databases such as those used for proteogenomics. Here, we present a unifying hybrid method to quickly and efficiently generate decoy sequences with minimal overlap between target and decoy peptides. We show that applying a reversed decoy approach can produce up to 5% peptide redundancy and many more additional peptides will have the exact same precursor mass as a target peptide. Our hybrid method addresses both these issues by first switching proteolytic cleavage sites with preceding amino acid, reversing the database and then shuffling any redundant sequences. This flexible hybrid method reduces the peptide overlap between target and decoy peptides to about 1% of peptides, making a more robust decoy model suitable for large search spaces. We also demonstrate the anti-conservative effect of redundant peptides on the calculation of q-values in mouse brain tissue data.

General guidelines for validation of decoy models for HRM/DIA/SWATH as exemplified using spectronaut

Protein extracts of the human HEK-293 cell line were spiked with the HRM Kit and measured in six replicates on a Thermo Scientific Q Exactive mass spectrometer with a 2h gradient in HRM mode and analyzed in Spectronaut. To perform a fair analysis the human HEK-293 library was combined with the E. coli library such that the analysis software did not know about the positive and negative control. This combined library was then tested with three common decoy approaches.

HIF-1α decoy oligodeoxynucleotides inhibit HIF-1α signaling and breast cancer proliferation.

Although HIF-1α is considered an attractive target for the development of cancer therapies, like other transcriptional factors, it has been regarded as 'undruggable'. The decoy approach is a new class of antigene strategy that can be used to modulate the function of endogenous transcriptional factors. Here, we designed a decoy oligodeoxynucleotide (ODN) and tested its effect on the function of HIF-1α. We found the HIF-1α decoy ODN could efficiently enter into cells. Furthermore, these decoy ODNs can significantly block the expression of VEGFA, a known targeted gene of HIF-1α suggesting that the HIF-1α decoy ODNs can inhibit the function of HIF-1α. More importantly, the HIF-1α decoy ODN induced apoptosis and cell cycle arrest in MDA-MB-231 breast cancer cells. In summary, HIF-1α decoy ODNs can inhibit the function of HIF-1α and induce cancer cell apoptosis. Therefore, HIF-1α decoy ODNs should be further modified to improve their biological activity invivo.

When Target–Decoy False Discovery Rate Estimations Are Inaccurate and How to Spot Instances

To address problems with estimating the reliability of proteomic search engine results from mass spectrometry fragmentation data, the use of target-decoy database searching has become the de facto approach for estimating a false discovery rate. Several articles have been written about the effects of different ways of creating the decoy database, effects of the search engine scoring, or effects of search parameters on whether this approach provides an accurate estimate, not all agreeing with each other's conclusions. Hence, there may be some confusion about how effective this approach is and how broadly it can be applied. Although it is generally very effective, in this article I will try to emphasize some of the pitfalls and dangers of using the target-decoy approach and will indicate tell-tale signs that something may be amiss. This information will hopefully help researchers become more astute in their assessment of search results.

PatternLab: from mass spectra to label-free differential shotgun proteomics.

PatternLab for proteomics is a self-contained computational environment for analyzing shotgun proteomic data. Recent improvements incorporate modules to facilitate the computational analysis, such as FastaDBXtractor for sequence database preparation and ProLuCID runner for simplifying and managing the protein identification search engine; modules for pushing the limits on proteomics standards, such as SEPro, which relies on a semi-labeled decoy approach for increasing confidence in filtering and organizing peptide spectrum matches; and modules with novel features, such as SEProQ for enabling label-free quantitation by extracted ion chromatograms according to a distributed normalized ion abundance factor approach (dNIAF). Existing modules were also improved, such as the TFold module for pinpointing differentially expressed proteins. These new modules are integrated into the previously described arsenal of tools for further data analysis. Here we provide detailed instructions for operating and understanding them.

Addressing Statistical Biases in Nucleotide-Derived Protein Databases for Proteogenomic Search Strategies

Proteogenomics has the potential to advance genome annotation through high quality peptide identifications derived from mass spectrometry experiments, which demonstrate a given gene or isoform is expressed and translated at the protein level. This can advance our understanding of genome function, discovering novel genes and gene structure that have not yet been identified or validated. Because of the high-throughput shotgun nature of most proteomics experiments, it is essential to carefully control for false positives and prevent any potential misannotation. A number of statistical procedures to deal with this are in wide use in proteomics, calculating false discovery rate (FDR) and posterior error probability (PEP) values for groups and individual peptide spectrum matches (PSMs). These methods control for multiple testing and exploit decoy databases to estimate statistical significance. Here, we show that database choice has a major effect on these confidence estimates leading to significant differences in the number of PSMs reported. We note that standard target:decoy approaches using six-frame translations of nucleotide sequences, such as assembled transcriptome data, apparently underestimate the confidence assigned to the PSMs. The source of this error stems from the inflated and unusual nature of the six-frame database, where for every target sequence there exists five “incorrect” targets that are unlikely to code for protein. The attendant FDR and PEP estimates lead to fewer accepted PSMs at fixed thresholds, and we show that this effect is a product of the database and statistical modeling and not the search engine. A variety of approaches to limit database size and remove noncoding target sequences are examined and discussed in terms of the altered statistical estimates generated and PSMs reported. These results are of importance to groups carrying out proteogenomics, aiming to maximize the validation and discovery of gene structure in sequenced genomes, while still controlling for false positives.

A Complex Standard for Protein Identification, Designed by Evolution

Shotgun proteomic investigations rely on the algorithmic assignment of mass spectra to peptides. The quality of these matches is therefore a cornerstone in the analysis and has been the subject of numerous recent developments. In order to establish the benefits of novel algorithms, they are applied to reference samples of known content. However, these were recently shown to be either too simple to resemble typical real-life samples or as leading to results of lower accuracy as the method itself. Here, we describe how to use the proteome of Pyrococcus furiosus , a hyperthermophile, as a standard to evaluate proteomics identification workflows. Indeed, we prove that the Pyrococcus furiosus proteome provides a valid method for detecting random hits, comparable to the decoy databases currently in popular use, but we also prove that the Pyrococcus furiosus proteome goes squarely beyond the decoy approach by also providing many hundreds of highly reliable true positive hits. Searching the Pyrococcus furiosus proteome can thus be used as a unique test that provides the ability to reliably detect both false positives as well as proteome-scale true positives, allowing the rigorous testing of identification algorithms at the peptide and protein level.