Nuclei of HeLa cells interactomes unravel a network of ghost proteins involved in proteins translation

Microproteins-Discovery, structure, and function

Advances in proteogenomic technologies have revealed hundreds to thousands of translated small open reading frames (sORFs) that encode microproteins in genomes across evolutionary space. While many microproteins have now been shown to play critical roles in biology and human disease, a majority of recently identified microproteins have little or no experimental evidence regarding their functionality. Computational tools have some limitations for analysis of short, poorly conserved microprotein sequences, so additional approaches are needed to determine the role of each member of this recently discovered polypeptide class. A currently underexplored avenue in the study of microproteins is structure prediction and determination, which delivers a depth of functional information. In this review, we provide a brief overview of microprotein discovery methods, then examine examples of microprotein structures (and, conversely, intrinsic disorder) that have been experimentally determined using crystallography, cryo-electron microscopy, and NMR, which provide insight into their molecular functions and mechanisms. Additionally, we discuss examples of predicted microprotein structures that have provided insight or context regarding their function. Analysis of microprotein structure at the angstrom level, and confirmation of predicted structures, therefore, has potential to identify translated microproteins that are of biological importance and to provide molecular mechanism for their in vivo roles.

Biological factors and statistical limitations prevent detection of most noncanonical proteins by mass spectrometry

Ribosome profiling experiments indicate pervasive translation of short open reading frames (ORFs) outside of annotated protein-coding genes. However, shotgun mass spectrometry (MS) experiments typically detect only a small fraction of the predicted protein products of this noncanonical translation. The rarity of detection could indicate that most predicted noncanonical proteins are rapidly degraded and not present in the cell; alternatively, it could reflect technical limitations. Here, we leveraged recent advances in ribosome profiling and MS to investigate the factors limiting detection of noncanonical proteins in yeast. We show that the low detection rate of noncanonical ORF products can largely be explained by small size and low translation levels and does not indicate that they are unstable or biologically insignificant. In particular, proteins encoded by evolutionarily young genes, including those with well-characterized biological roles, are too short and too lowly expressed to be detected by shotgun MS at current detection sensitivities. Additionally, we find that decoy biases can give misleading estimates of noncanonical protein false discovery rates, potentially leading to false detections. After accounting for these issues, we found strong evidence for 4 noncanonical proteins in MS data, which were also supported by evolution and translation data. These results illustrate the power of MS to validate unannotated genes predicted by ribosome profiling, but also its substantial limitations in finding many biologically relevant lowly expressed proteins.

Protocol to identify human subcellular alternative protein interactions using cross-linking mass spectrometry

Since the start of mass-spectrometry-based proteomics, proteins from non-referenced open reading frames or alternative proteins (AltProts) have been overlooked. Here, we present a protocol to identify human subcellular AltProt and decipher some interactions using cross-linking mass spectrometry. We describe steps for cell culture, in cellulo cross-link, subcellular extraction, and sequential digestion. We then detail both liquid chromatography-tandem mass spectrometry and cross-link data analyses. The implementation of a single workflow allows the non-targeted identification of signaling pathways involving AltProts. For complete details on the use and execution of this protocol, please refer to Garcia-del Rio et al.1.

Chemical labeling and proteomics for characterization of unannotated small and alternative open reading frame-encoded polypeptides

Thousands of unannotated small and alternative open reading frames (smORFs and alt-ORFs, respectively) have recently been revealed in mammalian genomes. While hundreds of mammalian smORF- and alt-ORF-encoded proteins (SEPs and alt-proteins, respectively) affect cell proliferation, the overwhelming majority of smORFs and alt-ORFs remain uncharacterized at the molecular level. Complicating the task of identifying the biological roles of smORFs and alt-ORFs, the SEPs and alt-proteins that they encode exhibit limited sequence homology to protein domains of known function. Experimental techniques for the functionalization of these gene classes are therefore required. Approaches combining chemical labeling and quantitative proteomics have greatly advanced our ability to identify and characterize functional SEPs and alt-proteins in high throughput. In this review, we briefly describe the principles of proteomic discovery of SEPs and alt-proteins, then summarize how these technologies interface with chemical labeling for identification of SEPs and alt-proteins with specific properties, as well as in defining the interactome of SEPs and alt-proteins.

Proteoforms expand the world of microproteins and short open reading frame-encoded peptides

Microproteins and short open reading frame-encoded peptides (SEPs) can, like all proteins, carry numerous posttranslational modifications. Together with posttranscriptional processes, this leads to a high number of possible distinct protein molecules, the proteoforms, out of a limited number of genes. The identification, quantification, and molecular characterization of proteoforms possess special challenges to established, mainly bottom-up proteomics (BUP) based analytical approaches. While BUP methods are powerful, proteins have to be inferred rather than directly identified, which hampers the detection of proteoforms. An alternative approach is top-down proteomics (TDP) which allows to identify intact proteoforms. This perspective article provides a brief overview of modified microproteins and SEPs, introduces the proteoform terminology, and compares present BUP and TDP workflows highlighting their major advantages and caveats. Necessary future developments in TDP to fully accentuate its potential for proteoform-centric analytics of microproteins and SEPs will be discussed.

Employing non-targeted interactomics approach and subcellular fractionation to increase our understanding of the ghost proteome

Eukaryotic mRNA has long been considered monocistronic, but nowadays, alternative proteins (AltProts) challenge this tenet. The alternative or ghost proteome has largely been neglected and the involvement of AltProts in biological processes. Here, we used subcellular fractionation to increase the information about AltProts and facilitate the detection of protein-protein interactions by the identification of crosslinked peptides. In total, 112 unique AltProts were identified, and we were able to identify 220 crosslinks without peptide enrichment. Among these, 16 crosslinks between AltProts and Referenced Proteins (RefProts) were identified. We further focused on specific examples such as the interaction between IP_2292176 (AltFAM227B) and HLA-B, in which this protein could be a potential new immunopeptide, and the interactions between HIST1H4F and several AltProts which can play a role in mRNA transcription. Thanks to the study of the interactome and the localization of AltProts, we can reveal more of the importance of the ghost proteome.

Proteomic-driven identification of short open reading frame-encoded peptides

Accumulating evidence has shown that a large number of short open reading frames (sORFs) also have the ability to encode proteins. The discovery of sORFs opens up a new research area, leading to the identification and functional study of sORF encoded peptides (SEPs) at the omics level. Besides bioinformatics prediction and ribosomal profiling, mass spectrometry (MS) has become a significant tool as it directly detects the sequence of SEPs. Though MS-based proteomics methods have proved to be effective for qualitative and quantitative analysis of SEPs, the detection of SEPs is still a great challenge due to their low abundance and short sequence. To illustrate the progress in method development, we described and discussed the main steps of large-scale proteomics identification of SEPs, including SEP extraction and enrichment, MS detection, data processing and quality control, quantification, and function prediction and validation methods. This article is protected by copyright. All rights reserved.

Path to Clonal Theranostics in Luminal Breast Cancers

Integrating tumor heterogeneity in the drug discovery process is a key challenge to tackle breast cancer resistance. Identifying protein targets for functionally distinct tumor clones is particularly important to tailor therapy to the heterogeneous tumor subpopulations and achieve clonal theranostics. For this purpose, we performed an unsupervised, label-free, spatially resolved shotgun proteomics guided by MALDI mass spectrometry imaging (MSI) on 124 selected tumor clonal areas from early luminal breast cancers, tumor stroma, and breast cancer metastases. 2868 proteins were identified. The main protein classes found in the clonal proteome dataset were enzymes, cytoskeletal proteins, membrane-traffic, translational or scaffold proteins, or transporters. As a comparison, gene-specific transcriptional regulators, chromatin related proteins or transmembrane signal receptor were more abundant in the TCGA dataset. Moreover, 26 mutated proteins have been identified. Similarly, expanding the search to alternative proteins databases retrieved 126 alternative proteins in the clonal proteome dataset. Most of these alternative proteins were coded mainly from non-coding RNA. To fully understand the molecular information brought by our approach and its relevance to drug target discovery, the clonal proteomic dataset was further compared to the TCGA breast cancer database and two transcriptomic panels, BC360 (nanoString^®) and CDx (Foundation One^®). We retrieved 139 pathways in the clonal proteome dataset. Only 55% of these pathways were also present in the TCGA dataset, 68% in BC360 and 50% in CDx. Seven of these pathways have been suggested as candidate for drug targeting, 22 have been associated with breast cancer in experimental or clinical reports, the remaining 19 pathways have been understudied in breast cancer. Among the anticancer drugs, 35 drugs matched uniquely with the clonal proteome dataset, with only 7 of them already approved in breast cancer. The number of target and drug interactions with non-anticancer drugs (such as agents targeting the cardiovascular system, metabolism, the musculoskeletal or the nervous systems) was higher in the clonal proteome dataset (540 interactions) compared to TCGA (83 interactions), BC360 (419 interactions), or CDx (172 interactions). Many of the protein targets identified and drugs screened were clinically relevant to breast cancer and are in clinical trials. Thus, we described the non-redundant knowledge brought by this clone-tailored approach compared to TCGA or transcriptomic panels, the targetable proteins identified in the clonal proteome dataset, and the potential of this approach for drug discovery and repurposing through drug interactions with antineoplastic agents and non-anticancer drugs.

Little but Loud. The Diversity of Functions of Small Proteins and Peptides - Translational Products of Short Reading Frames

Cell functioning is tightly regulated process. For many years, research in the fields of proteomics and functional genomics has been focused on the role of proteins in cell functioning. The advances in science have led to the uncovering that short open reading frames, previously considered non-functional, serve a variety of functions. Short reading frames in polycistronic mRNAs often regulate their stability and translational efficiency of the main reading frame. The improvement of proteomic analysis methods has made it possible to identify the products of translation of short open reading frames in quantities that suggest the existence of functional role of those peptides and short proteins. Studies demonstrating their role unravel a new level of the regulation of cell functioning and its adaptation to changing conditions. This review is devoted to the analysis of functions of recently discovered peptides and short proteins.

Bottom-up and top-down proteomic approaches for the identification, characterization, and quantification of the low molecular weight proteome with focus on short open reading frame-encoded peptides

The recent discovery of alternative open reading frames creates a need for suitable analytical approaches to verify their translation and to characterize the corresponding gene products at the molecular level. As the analysis of small proteins within a background proteome by means of classical bottom-up proteomics is challenging, method development for the analysis of small open reading frame encoded peptides (SEPs) have become a focal point for research. Here, we highlight bottom-up and top-down proteomics approaches established for the analysis of SEPs in both pro- and eukaryotes. Major steps of analysis, including sample preparation and (small) proteome isolation, separation and mass spectrometry, data interpretation and quality control, quantification, the analysis of post-translational modifications, and exploration of functional aspects of the SEPs by means of proteomics technologies are described. These methods do not exclusively cover the analytics of SEPs but simultaneously include the low molecular weight proteome, and moreover, can also be used for the proteome-wide analysis of proteolytic processing events.

In-depth proteomics analysis of sentinel lymph nodes from individuals with endometrial cancer

Endometrial cancer (EC) is one of the most common gynecological cancers worldwide. Sentinel lymph node (SLN) status could be a major prognostic factor in evaluation of EC, but several prospective studies need to be performed. Here we report an in-depth proteomics analysis showing significant variations in the SLN protein landscape in EC. We show that SLNs are correlated to each tumor grade, which strengthens evidence of SLN involvement in EC. A few proteins are overexpressed specifically at each EC tumor grade and in the corresponding SLN. These proteins, which are significantly variable in both locations, should be considered potential markers of overall survival. Five major proteins for EC and SLN (PRSS3, PTX3, ASS1, ALDH2, and ANXA1) were identified in large-scale proteomics and validated by immunohistochemistry. This study improves stratification and diagnosis of individuals with EC as a result of proteomics profiling of SLNs.

OpenProt 2021: deeper functional annotation of the coding potential of eukaryotic genomes

OpenProt (www.openprot.org) is the first proteogenomic resource supporting a polycistronic annotation model for eukaryotic genomes. It provides a deeper annotation of open reading frames (ORFs) while mining experimental data for supporting evidence using cutting-edge algorithms. This update presents the major improvements since the initial release of OpenProt. All species support recent NCBI RefSeq and Ensembl annotations, with changes in annotations being reported in OpenProt. Using the 131 ribosome profiling datasets re-analysed by OpenProt to date, non-AUG initiation starts are reported alongside a confidence score of the initiating codon. From the 177 mass spectrometry datasets re-analysed by OpenProt to date, the unicity of the detected peptides is controlled at each implementation. Furthermore, to guide the users, detectability statistics and protein relationships (isoforms) are now reported for each protein. Finally, to foster access to deeper ORF annotation independently of one's bioinformatics skills or computational resources, OpenProt now offers a data analysis platform. Users can submit their dataset for analysis and receive the results from the analysis by OpenProt. All data on OpenProt are freely available and downloadable for each species, the release-based format ensuring a continuous access to the data. Thus, OpenProt enables a more comprehensive annotation of eukaryotic genomes and fosters functional proteomic discoveries.

SARS-Cov-2 Interactome with Human Ghost Proteome: A Neglected World Encompassing a Wealth of Biological Data

Conventionally, eukaryotic mRNAs were thought to be monocistronic, leading to the translation of a single protein. However, large-scale proteomics have led to a massive identification of proteins translated from mRNAs of alternative ORF (AltORFs), in addition to the predicted proteins issued from the reference ORF or from ncRNAs. These alternative proteins (AltProts) are not represented in the conventional protein databases and this "ghost proteome" was not considered until recently. Some of these proteins are functional and there is growing evidence that they are involved in central functions in physiological and physiopathological context. Based on our experience with AltProts, we were interested in finding out their interaction with the viral protein coming from the SARS-CoV-2 virus, responsible for the 2020 COVID-19 outbreak. Thus, we have scrutinized the recently published data by Krogan and coworkers (2020) on the SARS-CoV-2 interactome with host cells by affinity purification in co-immunoprecipitation (co-IP) in the perspective of drug repurposing. The initial work revealed the interaction between 332 human cellular reference proteins (RefProts) with the 27 viral proteins. Re-interrogation of this data using 23 viral targets and including AltProts, followed by enrichment of the interaction networks, leads to identify 218 RefProts (in common to initial study), plus 56 AltProts involved in 93 interactions. This demonstrates the necessity to take into account the ghost proteome for discovering new therapeutic targets, and establish new therapeutic strategies. Missing the ghost proteome in the drug metabolism and pharmacokinetic (DMPK) drug development pipeline will certainly be a major limitation to the establishment of efficient therapies.

Shedding Light on the Ghost Proteome

Conventionally, eukaryotic mRNAs were thought to be monocistronic, leading to the translation of a single protein. However, large-scale proteomics has led to the identification of proteins translated from alternative open reading frames (AltORFs) in mRNAs. AltORFs are found in addition to predicted reference ORFs and noncoding RNA. Alternative proteins are not represented in the conventional protein databases, and this 'Ghost proteome' was not considered until recently. Some of these proteins are functional, and there is growing evidence that they are involved in central functions in physiological and physiopathological contexts. Here, we review how this Ghost proteome fills the gap in our understanding of signaling pathways, establishes new markers of pathologies, and highlights therapeutic targets.

Epigenetic Studies Revealed a Ghost Proteome in PC1/3 KD Macrophages under Antitumoral Resistance Induced by IL-10

Our previous investigation on macrophages has allowed us to show that the inhibition of the enzyme proprotein convertase (PC1/3) controls the activation of macrophages. We demonstrated that PC1/3 knockdown (KD) in macrophages exhibits an increased secretion of proinflammatory and antitumoral factors. In this biological context, we assessed the presence of histone modifications and the presence and contribution of a "ghost proteome" in these macrophages. We identified a set of alternative proteins (AltProts) that have a key role in the regulation of various signaling pathways. In this study, to further investigate the underlying mechanisms involved in the resistance of PC1/3-KD macrophages to anti-inflammatory stimuli, we have conducted a proteomic system biology study to assess the epigenome variation, focusing on histone modifications. Results from our study have indicated the presence of significant variations in histone modifications along with the identification of 28 AltProts, which can be correlated with antitumoral resistance under IL-10 stimulation. These findings highlight a key role of altered epigenome histone modifications in driving resistance and indicate that like the reference proteins, AltProts can have a major impact in the field of epigenetics and regulation of gene expression, as shown in our results.

Modelling of pathogen-host systems using deeper ORF annotations and transcriptomics to inform proteomics analyses

The Zika virus is a flavivirus that can cause fulminant outbreaks and lead to Guillain-Barré syndrome, microcephaly and fetal demise. Like other flaviviruses, the Zika virus is transmitted by mosquitoes and provokes neurological disorders. Despite its risk to public health, no antiviral nor vaccine are currently available. In the recent years, several studies have set to identify human host proteins interacting with Zika viral proteins to better understand its pathogenicity. Yet these studies used standard human protein sequence databases. Such databases rely on genome annotations, which enforce a minimal open reading frame (ORF) length criterion. An ever-increasing number of studies have demonstrated the shortcomings of such annotation, which overlooks thousands of functional ORFs. Here we show that the use of a customized database including currently non-annotated proteins led to the identification of 4 alternative proteins as interactors of the viral capsid and NS4A proteins. Furthermore, 12 alternative proteins were identified in the proteome profiling of Zika infected monocytes, one of which was significantly up-regulated. This study presents a computational framework for the re-analysis of proteomics datasets to better investigate the viral-host protein interplays upon infection with the Zika virus.

Alternative proteins are functional regulators in cell reprogramming by PKA activation

It has been recently shown that many proteins are lacking from reference databases used in mass spectrometry analysis, due to their translation templated on alternative open reading frames. This questions our current understanding of gene annotation and drastically expands the theoretical proteome complexity. The functions of these alternative proteins (AltProts) still remain largely unknown. We have developed a large-scale and unsupervised approach based on cross-linking mass spectrometry (XL-MS) followed by shotgun proteomics to gather information on the functional role of AltProts by mapping them back into known signalling pathways through the identification of their reference protein (RefProt) interactors. We have identified and profiled AltProts in a cancer cell reprogramming system: NCH82 human glioma cells after 0, 16, 24 and 48 h Forskolin stimulation. Forskolin is a protein kinase A activator inducing cell differentiation and epithelial–mesenchymal transition. Our data show that AltMAP2, AltTRNAU1AP and AltEPHA5 interactions with tropomyosin 4 are downregulated under Forskolin treatment. In a wider perspective, Gene Ontology and pathway enrichment analysis (STRING) revealed that RefProts associated with AltProts are enriched in cellular mobility and transfer RNA regulation. This study strongly suggests novel roles of AltProts in multiple essential cellular functions and supports the importance of considering them in future biological studies.

Reference and Ghost Proteins Identification in Rat C6 Glioma Extracellular Vesicles

Extracellular vesicles (EVs) mediate intercellular communication and regulate a broad range of biological processes. Novel therapeutic strategies have emerged based on the use of EVs as biological nanoparticles. To separate isolated EVs from protein aggregates and the external part of EVs membrane proteins, we performed a Trypsin/Lys C digestion treatment of EVs pellets, followed by Amicon filtration. After these steps, all the fractions have been subjected to proteomic analyses. Comparison between 6 h Trypsin/Lys C treatment or non-treated EVs revealed a quantitative variation of the surface proteins. Some surface proteins have been demasked after 6 h enzymatic digestion like CD81, CD82, Ust, Vcan, Lamp 1, Rab43, Annexin A2, Synthenin, and VSP37b. Moreover, six ghost proteins have also been identified and one corresponds to a long noncoding RNA. We thus demonstrate the presence of ghost proteins in EVs produced by glioma cells that can contribute to tumorigenesis.

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Glioma C6 extracellular vesicle protein mapping

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Quick steps protocols to map outer/inner membrane EV membrane proteins

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C6 glioma cell line EVs contain ghost proteins

To Cleave or Not To Cleave in XL-MS?

Cross-linking mass spectrometry (XL-MS) is an efficient technique for uncovering structural features and interactions of the in-solution state of the proteins under investigation. Distance constraints obtained by this technique are highly complementary to classical structural biology approaches like X-ray crystallography and cryo-EM and have successfully been leveraged to shed light on protein structures of increasing size and complexity. To accomplish this, small reagents are used that typically incorporate two amine reactive moieties connected by a spacer arm and that can be applied in solution to protein structures of any size. Over the years, many reagents initially developed for different applications were adopted, and others were specifically developed for XL-MS. This has resulted in a vast array of options, making it difficult to make the right choice for specific experiments. Here, we delve into the previous decade of published XL-MS literature to uncover which workflows have been predominantly applied. We focus on application papers as these represent proof that biologically valid results can be extracted. This ignores some more recent approaches that did not have sufficient time to become more widely applied, for which we supply a separate discussion. From our selection, we extract information on the types of samples, cross-linking reagent, prefractionation, instruments, and data analysis, to highlight widely used workflows. All of the results are summarized in an easy-to-use flow chart defined by selection points resulting from our analysis. Although potentially biased by our own experiences, we expect this overview to be useful for novices stepping into this rapidly expanding field.

Optimized Sample Preparation Workflow for Improved Identification of Ghost Proteins

Large scale proteomic strategies rely on database interrogation. Thus, only referenced proteins can be identified. Recently, Alternative Proteins (AltProts) translated from nonannotated Alternative Open reading frame (AltORFs) were discovered using customized databases. Because of their small size which confers them peptide-like physicochemical properties, they are more difficult to detect using standard proteomics strategies. In this study, we tested different preparation workflows for improving the identification of AltProts in NCH82 human glioma cell line. The highest number of identified AltProts was achieved with RIPA buffer or boiling water extraction followed by acetic acid precipitation.