The Future of Proteomics is Up in the Air: Can Ion Mobility Replace Liquid Chromatography for High Throughput Proteomics?

The coevolution of liquid chromatography (LC) with mass spectrometry (MS) has shaped contemporary proteomics. LC hyphenated to MS now enables quantification of more than 10,000 proteins in a single injection, a number that likely represents most proteins in specific human cells or tissues. Separations by ion mobility spectrometry (IMS) have recently emerged to complement LC and further improve the depth of proteomics. Given the theoretical advantages in speed and robustness of IMS in comparison to LC, we envision that ongoing improvements to IMS paired with MS may eventually make LC obsolete, especially when combined with targeted or simplified analyses, such as rapid clinical proteomics analysis of defined biomarker panels. In this perspective, we describe the need for faster analysis that might drive this transition, the current state of direct infusion proteomics, and discuss some technical challenges that must be overcome to fully complete the transition to entirely gas phase proteomics.

Unraveling the Mechanisms of Efficient Phosphorus Utilization in Popcorn (Zea mays L. var. everta): Insights from Proteomic and Metabolite Analysis.

The expansion of agriculture and the need for sustainable practices drives breeders to develop plant varieties better adapted to abiotic stress such as nutrient deficiency, which negatively impacts yields. Phosphorus (P) is crucial for photosynthesis and plant growth, but its availability in the soil is often limited, hampering crop development. In this study, we examined the response of two popcorn inbred lines, L80 and P7, which have been characterized previously as P-use inefficient and P-use efficient, respectively, under low (stress) and high P (control) availability. Physiological measurements, proteomic analysis, and metabolite assays were performed to unravel the physiological and molecular responses associated with the efficient use of P in popcorn. We observed significant differences in protein abundances in response to the P supply between the two inbred lines. A total of 421 differentially expressed proteins (DEPs) were observed in L80 and 436 DEPs in P7. These proteins were involved in photosynthesis, protein biosynthesis, biosynthesis of secondary metabolites, and energy metabolism. In addition, flavonoids accumulated in higher abundance in P7. Our results help us understand the major components of P utilization in popcorn, providing new insights for popcorn molecular breeding programs.

COL1A2 Barcoding: Bone Species Identification via Shotgun Proteomics.

Species identification of fragmentary bones remains a challenging task in archeology and forensics. A species identification method for such fragmentary bones that has recently attracted interest is the use of bone collagen proteins. Here, we describe a method similar to DNA barcoding that reads collagen protein sequences in bone and automatically determines the species by performing sequence database searches. The method is almost identical to conventional shotgun proteomics analysis of bone samples, except that the database used by the SEQUEST search engine consisted only of entries for collagen type 1 alpha 2 (COL1A2) proteins from various vertebrates. Accordingly, the COL1A2 peptides that differ in sequence among species act as species marker peptides. In SEQUEST-based shotgun proteomics, the protein entries that contain more marker peptide sequences are assigned higher scores; therefore, the highest-scoring protein entry will be the COL1A2 entry for the species from which the analyzed bone was derived. We tested our method using bone samples from 30 vertebrate species and found that all species were correctly identified. In conclusion, COL1A2 can be used as a bone protein barcode and can be read through shotgun proteomics, allowing for automatic bone species identification. Data are available via ProteomeXchange with the identifier PXD045402.

AttnPep: A Self-Attention-Based Deep Learning Method for Peptide Identification in Shotgun Proteomics.

In shotgun proteomics, the proteome search engine analyzes mass spectra obtained by experiments, and then a peptide-spectra match (PSM) is reported for each spectrum. However, most of the PSMs identified are incorrect, and therefore various postprocessing software have been developed for reranking the peptide identifications. Yet these methods suffer from issues such as dependency on distribution, reliance on shallow models, and limited effectiveness. In this work, we propose AttnPep, a deep learning model for rescoring PSM scores that utilizes the Self-Attention module. This module helps the neural network focus on features relevant to the classification of PSMs and ignore irrelevant features. This allows AttnPep to analyze the output of different search engines and improve PSM discrimination accuracy. We considered a PSM to be correct if it achieves a q-value <0.01 and compared AttnPep with existing mainstream software PeptideProphet, Percolator, and proteoTorch. The results indicated that AttnPep found an average increase in correct PSMs of 9.29% relative to the other methods. Additionally, AttnPep was able to better distinguish between correct and incorrect PSMs and found more synthetic peptides in the complex SWATH data set.

False discovery rate: the Achilles' heel of proteogenomics.

Proteogenomics refers to the integrated analysis of the genome and proteome that leverages mass-spectrometry (MS)-based proteomics data to improve genome annotations, understand gene expression control through proteoforms and find sequence variants to develop novel insights for disease classification and therapeutic strategies. However, proteogenomic studies often suffer from reduced sensitivity and specificity due to inflated database size. To control the error rates, proteogenomics depends on the target-decoy search strategy, the de-facto method for false discovery rate (FDR) estimation in proteomics. The proteogenomic databases constructed from three- or six-frame nucleotide database translation not only increase the search space and compute-time but also violate the equivalence of target and decoy databases. These searches result in poorer separation between target and decoy scores, leading to stringent FDR thresholds. Understanding these factors and applying modified strategies such as two-pass database search or peptide-class-specific FDR can result in a better interpretation of MS data without introducing additional statistical biases. Based on these considerations, a user can interpret the proteogenomics results appropriately and control false positives and negatives in a more informed manner. In this review, first, we briefly discuss the proteogenomic workflows and limitations in database construction, followed by various considerations that can influence potential novel discoveries in a proteogenomic study. We conclude with suggestions to counter these challenges for better proteogenomic data interpretation.

Quantification of snake venom proteomes by mass spectrometry-considerations and perspectives.

The advent of soft ionization mass spectrometry-based proteomics in the 1990s led to the development of a new dimension in biology that conceptually allows for the integral analysis of whole proteomes. This transition from a reductionist to a global-integrative approach is conditioned to the capability of proteomic platforms to generate and analyze complete qualitative and quantitative proteomics data. Paradoxically, the underlying analytical technique, molecular mass spectrometry, is inherently nonquantitative. The turn of the century witnessed the development of analytical strategies to endow proteomics with the ability to quantify proteomes of model organisms in the sense of "an organism for which comprehensive molecular (genomic and/or transcriptomic) resources are available." This essay presents an overview of the strategies and the lights and shadows of the most popular quantification methods highlighting the common misuse of label-free approaches developed for model species' when applied to quantify the individual components of proteomes of nonmodel species (In this essay we use the term "non-model" organisms for species lacking comprehensive molecular (genomic and/or transcriptomic) resources, a circumstance that, as we detail in this review-essay, conditions the quantification of their proteomes.). We also point out the opportunity of combining elemental and molecular mass spectrometry systems into a hybrid instrumental configuration for the parallel identification and absolute quantification of venom proteomes. The successful application of this novel mass spectrometry configuration in snake venomics represents a proof-of-concept for a broader and more routine application of hybrid elemental/molecular mass spectrometry setups in other areas of the proteomics field, such as phosphoproteomics, metallomics, and in general in any biological process where a heteroatom (i.e., any atom other than C, H, O, N) forms integral part of its mechanism.

Research biopsies in kidney transplantation: an evaluation of surgical techniques and optimal tissue mass allowing molecular and histological analyses.

BACKGROUND: Research biopsies have great potential to advance scientific knowledge by helping to establish predictors of favourable or unfavourable outcomes in kidney transplantation. We evaluated punch and core biopsies of different sizes to determine the optimal size for clinical use. METHODS: A total of 54 punch biopsies and 18 core needle biopsies were retrieved by three transplant surgeons. Each surgeon obtained three separate 2 mm, 3 mm and 4 mm punch biopsy samples and three 23 mm (length) core needle biopsies from two pig kidneys. RESULTS: 4 mm punch biopsies yielded the greatest amount of protein (2.11 ± 0.41 mg) with good reproducibility between surgeons and biopsy types (Coefficient of Variation ∼ 22.13%). All surgeons found 2 mm biopsies technically challenging to obtain and sample processing was difficult due to the sample size. Shotgun proteomics identified 3853 gene products with no significant difference in the quantitative proteome of 2 mm and 3 mm punch biopsies. However, the expression of 158 Kidney enriched genes, was higher in bigger and deeper 4 mm punch and core needle biopsies compared to 2 mm biopsy. Only 80% of 2 mm biopsies demonstrated the presence of glomeruli, whereas glomeruli were present in 100% of all other biopsy sizes. CONCLUSIONS: The 2 mm punch biopsy has been shown to be challenging to use and frequently provides inadequate tissue for histology and proteomics while 3 mm research biopsies were the smallest size that were technically obtainable with adequate tissue for molecular studies.

ImShot: An Open-Source Software for Probabilistic Identification of Proteins In Situ and Visualization of Proteomics Data.

Imaging mass spectrometry (IMS) has developed into a powerful tool allowing label-free detection of numerous biomolecules in situ. In contrast to shotgun proteomics, proteins/peptides can be detected directly from biological tissues and correlated to its morphology leading to a gain of crucial clinical information. However, direct identification of the detected molecules is currently challenging for MALDI-IMS, thereby compelling researchers to use complementary techniques and resource intensive experimental setups. Despite these strategies, sufficient information could not be extracted because of lack of an optimum data combination strategy/software. Here, we introduce a new open-source software ImShot that aims at identifying peptides obtained in MALDI-IMS. This is achieved by combining information from IMS and shotgun proteomics (LC-MS) measurements of serial sections of the same tissue. The software takes advantage of a two-group comparison to determine the search space of IMS masses after deisotoping the corresponding spectra. Ambiguity in annotations of IMS peptides is eliminated by introduction of a novel scoring system that identifies the most likely parent protein of a detected peptide in the corresponding IMS dataset. Thanks to its modular structure, the software can also handle LC-MS data separately and display interactive enrichment plots and enriched Gene Ontology terms or cellular pathways. The software has been built as a desktop application with a conveniently designed graphic user interface to provide users with a seamless experience in data analysis. ImShot can run on all the three major desktop operating systems and is freely available under Massachusetts Institute of Technology license.

Metabolic Adaptation in Epilepsy: From Acute Response to Chronic Impairment.

Epilepsy is characterized by hypersynchronous neuronal discharges, which are associated with an increased cerebral metabolic rate of oxygen and ATP demand. Uncontrolled seizure activity (status epilepticus) results in mitochondrial exhaustion and ATP depletion, which potentially generate energy mismatch and neuronal loss. Many cells can adapt to increased energy demand by increasing metabolic capacities. However, acute metabolic adaptation during epileptic activity and its relationship to chronic epilepsy remains poorly understood. We elicited seizure-like events (SLEs) in an in vitro model of status epilepticus for eight hours. Electrophysiological recording and tissue oxygen partial pressure recordings were performed. After eight hours of ongoing SLEs, we used proteomics-based kinetic modeling to evaluate changes in metabolic capacities. We compared our findings regarding acute metabolic adaptation to published proteomic and transcriptomic data from chronic epilepsy patients. Epileptic tissue acutely responded to uninterrupted SLEs by upregulating ATP production capacity. This was achieved by a coordinated increase in the abundance of proteins from the respiratory chain and oxidative phosphorylation system. In contrast, chronic epileptic tissue shows a 25-40% decrease in ATP production capacity. In summary, our study reveals that epilepsy leads to dynamic metabolic changes. Acute epileptic activity boosts ATP production, while chronic epilepsy reduces it significantly.

Metataxonomic analysis and host proteome response in dairy cows with high and low somatic cell count: a quarter level investigation.

Host response to invasive microbes in the bovine udder has an important role on the animal health and is essential to the dairy industry to ensure production of high-quality milk and reduce the mastitis incidence. To better understand the biology behind these host-microbiome interactions, we investigated the somatic cell proteomes at quarter level for four cows (collected before and after milking) using a shotgun proteomics approach. Simultaneously, we identified the quarter microbiota by amplicon sequencing to detect presence of mastitis pathogens or other commensal taxa. In total, 32 quarter milk samples were analyzed divided in two groups depending on the somatic cell count (SCC). The high SCC group (>100,000 cell/mL) included 10 samples and significant different proteome profiles were detected. Differential abundance analysis uncovers a specific expression pattern in high SCC samples revealing pathways involved in immune responses such as inflammation, activation of the complement system, migration of immune cells, and tight junctions. Interestingly, different proteome profiles were also identified in quarter samples containing one of the two mastitis pathogens, Staphylococcus aureus and Streptococcus uberis, indicating a different response of the host depending on the pathogen. Weighted correlation network analysis identified three modules of co-expressed proteins which were correlated with the SCC in the quarters. These modules contained proteins assigned to different aspects of the immune response, but also amino sugar and nucleotide sugar metabolism, and biosynthesis of amino acids. The results of this study provide deeper insights on how the proteome expression changes at quarter level in naturally infected cows and pinpoint potential interactions and important biological functions during host-microbe interaction.

Proteomic analysis to unravel the biochemical mechanisms triggered by Bacillus toyonensis SFC 500-1E under chromium(VI) and phenol stress.

Bacillus toyonensis SFC 500-1E is a member of the consortium SFC 500-1 able to remove Cr(VI) and simultaneously tolerate high phenol concentrations. In order to elucidate mechanisms utilized by this strain during the bioremediation process, the differential expression pattern of proteins was analyzed when it grew with or without Cr(VI) (10 mg/L) and Cr(VI) + phenol (10 and 300 mg/L), through two complementary proteomic approaches: gel-based (Gel-LC) and gel-free (shotgun) nanoUHPLC-ESI-MS/MS. A total of 400 differentially expressed proteins were identified, out of which 152 proteins were down-regulated under Cr(VI) and 205 up-regulated in the presence of Cr(VI) + phenol, suggesting the extra effort made by the strain to adapt itself and keep growing when phenol was also added. The major metabolic pathways affected include carbohydrate and energetic metabolism, followed by lipid and amino acid metabolism. Particularly interesting were also ABC transporters and the iron-siderophore transporter as well as transcriptional regulators that can bind metals. Stress-associated global response involving the expression of thioredoxins, SOS response, and chaperones appears to be crucial for the survival of this strain under treatment with both contaminants. This research not only provided a deeper understanding of B. toyonensis SFC 500-1E metabolic role in Cr(VI) and phenol bioremediation process but also allowed us to complete an overview of the consortium SFC 500-1 behavior. This may contribute to an improvement in its use as a bioremediation strategy and also provides a baseline for further research.

Isolation of Acetylated and Unmodified Protein N-Terminal Peptides by Strong Cation Exchange Chromatographic Separation of TrypN-Digested Peptides.

We developed a simple and rapid method to enrich protein N-terminal peptides, in which the protease TrypN is first employed to generate protein N-terminal peptides without Lys or Arg and internal peptides with two positive charges at their N termini, and then, the N-terminal peptides with or without N-acetylation are separated from the internal peptides by strong cation exchange chromatography according to a retention model based on the charge/orientation of peptides. This approach was applied to 20 µg of human HEK293T cell lysate proteins to profile the N-terminal proteome. On average, 1550 acetylated and 200 unmodified protein N-terminal peptides were successfully identified in a single LC/MS/MS run with less than 3% contamination with internal peptides, even when we accepted only canonical protein N termini registered in the Swiss-Prot database. Because this method involves only two steps, protein digestion and chromatographic separation, without the need for tedious chemical reactions, it should be useful for comprehensive profiling of protein N termini, including proteoforms with neo-N termini.

Insights into Common Octopus (Octopus vulgaris) Ink Proteome and Bioactive Peptides Using Proteomic Approaches.

The common octopus (Octopus vulgaris) is nowadays the most demanded cephalopod species for human consumption. This species was also postulated for aquaculture diversification to supply its increasing demand in the market worldwide, which only relies on continuously declining field captures. In addition, they serve as model species for biomedical and behavioral studies. Body parts of marine species are usually removed before reaching the final consumer as by-products in order to improve preservation, reduce shipping weight, and increase product quality. These by-products have recently attracted increasing attention due to the discovery of several relevant bioactive compounds. Particularly, the common octopus ink has been described as having antimicrobial and antioxidant properties, among others. In this study, the advanced proteomics discipline was applied to generate a common octopus reference proteome to screen potential bioactive peptides from fishing discards and by-products such as ink. A shotgun proteomics approach by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) using an Orbitrap Elite instrument was used to create a reference dataset from octopus ink. A total of 1432 different peptides belonging to 361 non-redundant annotated proteins were identified. The final proteome compilation was investigated by integrated in silico studies, including gene ontology (GO) term enrichment, pathways, and network studies. Different immune functioning proteins involved in the innate immune system, such as ferritin, catalase, proteasome, Cu/Zn superoxide dismutase, calreticulin, disulfide isomerase, heat shock protein, etc., were found in ink protein networks. Additionally, the potential of bioactive peptides from octopus ink was addressed. These bioactive peptides can exert beneficial health properties such as antimicrobial, antioxidant, antihypertensive, and antitumoral properties and are therefore considered lead compounds for developing pharmacological, functional foods or nutraceuticals.

Proteomic Analysis Reveals a Critical Role of the Glycosyl Hydrolase 17 Protein in Panax ginseng Leaves under Salt Stress.

Ginseng, an important crop in East Asia, exhibits multiple medicinal and nutritional benefits because of the presence of ginsenosides. On the other hand, the ginseng yield is severely affected by abiotic stressors, particularly salinity, which reduces yield and quality. Therefore, efforts are needed to improve the ginseng yield during salinity stress, but salinity stress-induced changes in ginseng are poorly understood, particularly at the proteome-wide level. In this study, we report the comparative proteome profiles of ginseng leaves at four different time points (mock, 24, 72, and 96 h) using a label-free quantitative proteome approach. Of the 2484 proteins identified, 468 were salt-responsive. In particular, glycosyl hydrolase 17 (PgGH17), catalase-peroxidase 2, voltage-gated potassium channel subunit beta-2, fructose-1,6-bisphosphatase class 1, and chlorophyll a-b binding protein accumulated in ginseng leaves in response to salt stress. The heterologous expression of PgGH17 in Arabidopsis thaliana improved the salt tolerance of transgenic lines without compromising plant growth. Overall, this study uncovers the salt-induced changes in ginseng leaves at the proteome level and highlights the critical role of PgGH17 in salt stress tolerance in ginseng.

GroEL-Proteotyping of Bacterial Communities Using Tandem Mass Spectrometry.

Profiling bacterial populations in mixed communities is a common task in microbiology. Sequencing of 16S small subunit ribosomal-RNA (16S rRNA) gene amplicons is a widely accepted and functional approach but relies on amplification primers and cannot quantify isotope incorporation. Tandem mass spectrometry proteotyping is an effective alternative for taxonomically profiling microorganisms. We suggest that targeted proteotyping approaches can complement traditional population analyses. Therefore, we describe an approach to assess bacterial community compositions at the family level using the taxonomic marker protein GroEL, which is ubiquitously found in bacteria, except a few obligate intracellular species. We refer to our method as GroEL-proteotyping. GroEL-proteotyping is based on high-resolution tandem mass spectrometry of GroEL peptides and identification of GroEL-derived taxa via a Galaxy workflow and a subsequent Python-based analysis script. Its advantage is that it can be performed with a curated and extendable sample-independent database and that GroEL can be pre-separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to reduce sample complexity, improving GroEL identification while simultaneously decreasing the instrument time. GroEL-proteotyping was validated by employing it on a comprehensive raw dataset obtained through a metaproteome approach from synthetic microbial communities as well as real human gut samples. Our data show that GroEL-proteotyping enables fast and straightforward profiling of highly abundant taxa in bacterial communities at reasonable taxonomic resolution.

Shotgun Proteomics Analysis, Functional Networks, and Peptide Biomarkers for Seafood-Originating Biogenic-Amine-Producing Bacteria.

Biogenic amine-producing bacteria are responsible for the production of basic nitrogenous compounds (histamine, cadaverine, tyramine, and putrescine) following the spoilage of food due to microorganisms. In this study, we adopted a shotgun proteomics strategy to characterize 15 foodborne strains of biogenic-amine-producing bacteria. A total of 10,673 peptide spectrum matches belonging to 4081 peptides and corresponding to 1811 proteins were identified. Relevant functional pathways were determined, and strains were differentiated into hierarchical clusters. An expected protein-protein interaction network was created (260 nodes/1973 interactions). Most of the determined proteins were associated with networks/pathways of energy, putrescine metabolism, and host-virus interaction. Additionally, 556 peptides were identified as virulence factors. Moreover, 77 species-specific peptide biomarkers corresponding to 64 different proteins were proposed to identify 10 bacterial species. This represents a major proteomic dataset of biogenic-amine-producing strains. These results may also be suitable for new treatments for food intoxication and for tracking microbial sources in foodstuffs.

A Practical Guide to Small Protein Discovery and Characterization Using Mass Spectrometry.

Small proteins of up to ∼50 amino acids are an abundant class of biomolecules across all domains of life. Yet due to the challenges inherent in their size, they are often missed in genome annotations, and are difficult to identify and characterize using standard experimental approaches. Consequently, we still know few small proteins even in well-studied prokaryotic model organisms. Mass spectrometry (MS) has great potential for the discovery, validation, and functional characterization of small proteins. However, standard MS approaches are poorly suited to the identification of both known and novel small proteins due to limitations at each step of a typical proteomics workflow, i.e., sample preparation, protease digestion, liquid chromatography, MS data acquisition, and data analysis. Here, we outline the major MS-based workflows and bioinformatic pipelines used for small protein discovery and validation. Special emphasis is placed on highlighting the adjustments required to improve detection and data quality for small proteins. We discuss both the unbiased detection of small proteins and the targeted analysis of small proteins of interest. Finally, we provide guidelines to prioritize novel small proteins, and an outlook on methods with particular potential to further improve comprehensive discovery and characterization of small proteins.

Protecting our environment, a motivating outdoor game for proteomics!

The global Earth ecosystem faces many intertwined threats, primarily anthropogenic pollution, drastic reduction of wild spaces, faster spread of pathogens, and global climate warming. Ecotoxicology, the integration of toxicology and ecology, aims to describe the effects of toxicants on organisms, whether at the level of the population, the community, the ecosystem, or the biosphere. Sentinel species are employed to assess threats to life, giving advance warning of danger. In this issue of Proteomics, Wilde and collaborators (Proteomics 2022, 22, https://doi.org/10.1002/pmic.202100289) present a comprehensive coverage of the proteome of the crustacean Daphnia magna, a species used to evaluate aquatic pollution. This study illustrates how current shotgun proteomics technology allows straightforward quantitation of any protein for whole animals or dissected organs, making global molecular phenotyping a reality for animals. Tandem mass spectrometry operated in data-independent acquisition can be used to compare the response of sentinels to various environmental conditions. The current low number of well-annotated animal or plant genomes, the high diversity of genetic backgrounds of each species, and the paucity of knowledge about protein functions for most of the relevant sentinels pose huge challenges for data interpretation. As a result, ecology and ecotoxicology today constitute an exceptional field for proteomics.

Dual roles of drug or its metabolite-protein conjugate: Cutting-edge strategy of drug discovery using shotgun proteomics.

Many drugs can bind directly to proteins or be bioactivated by metabolizing enzymes to form reactive metabolites (RMs) that rapidly bind to proteins to form drug-protein conjugates or metabolite-protein conjugates (DMPCs). The close relationship between DMPCs and idiosyncratic adverse drug reactions (IADRs) has been recognized; drug discovery teams tend to avoid covalent interactions in drug discovery projects. Covalent interactions in DMPCs can provide high potency and long action duration and conquer the intractable targets, inspiring drug design, and development. This forms the dual role feature of DMPCs. Understanding the functional implications of DMPCs in IADR control and therapeutic applications requires precise identification of these conjugates from complex biological samples. While classical biochemical methods have contributed significantly to DMPC detection in the past decades, the low abundance and low coverage of DMPCs have become a bottleneck in this field. An emerging transformation toward shotgun proteomics is on the rise. The evolving shotgun proteomics techniques offer improved reproducibility, throughput, specificity, operability, and standardization. Here, we review recent progress in the systematic discovery of DMPCs using shotgun proteomics. Furthermore, the applications of shotgun proteomics supporting drug development, toxicity mechanism investigation, and drug repurposing processes are also reviewed and prospected.

Challenging Targets or Describing Mismatches? A Comment on Common Decoy Distribution by Madej et al.

In their recent article, Madej et al. (Madej, D.; Wu, L.; Lam, H.Common Decoy Distributions Simplify False Discovery Rate Estimation in Shotgun Proteomics. J. Proteome Res.2022, 21 (2), 339-348) proposed an original way to solve the recurrent issue of controlling for the false discovery rate (FDR) in peptide-spectrum-match (PSM) validation. Briefly, they proposed to derive a single precise distribution of decoy matches termed the Common Decoy Distribution (CDD) and to use it to control for FDR during a target-only search. Conceptually, this approach is appealing as it takes the best of two worlds, i.e., decoy-based approaches (which leverage a large-scale collection of empirical mismatches) and decoy-free approaches (which are not subject to the randomness of decoy generation while sparing an additional database search). Interestingly, CDD also corresponds to a middle-of-the-road approach in statistics with respect to the two main families of FDR control procedures: Although historically based on estimating the false-positive distribution, FDR control has recently been demonstrated to be possible thanks to competition between the original variables (in proteomics, target sequences) and their fictional counterparts (in proteomics, decoys). Discriminating between these two theoretical trends is of prime importance for computational proteomics. In addition to highlighting why proteomics was a source of inspiration for theoretical biostatistics, it provides practical insights into the improvements that can be made to FDR control methods used in proteomics, including CDD.