Defining Distinct RNA-Protein Interactomes of SARS-CoV-2 Genomic and Subgenomic RNAs.

Host RNA binding proteins recognize viral RNA and play key roles in virus replication and antiviral mechanisms. SARS-CoV-2 generates a series of tiered subgenomic RNAs (sgRNAs), each encoding distinct viral protein(s) that regulate different aspects of viral replication. Here, for the first time, we demonstrate the successful isolation of SARS-CoV-2 genomic RNA and three distinct sgRNAs (N, S, and ORF8) from a single population of infected cells and characterize their protein interactomes. Over 500 protein interactors (including 260 previously unknown) were identified as associated with one or more target RNA. These included protein interactors unique to a single RNA pool and others present in multiple pools, highlighting our ability to discriminate between distinct viral RNA interactomes despite high sequence similarity. Individual interactomes indicated viral associations with cell response pathways, including regulation of cytoplasmic ribonucleoprotein granules and posttranscriptional gene silencing. We tested the significance of three protein interactors in these pathways (APOBEC3F, PPP1CC, and MSI2) using siRNA knockdowns, with several knockdowns affecting viral gene expression, most consistently PPP1CC. This study describes a new technology for high-resolution studies of SARS-CoV-2 RNA regulation and reveals a wealth of new viral RNA-associated host factors of potential functional significance to infection.

Defining distinct RNA-protein interactomes of SARS-CoV-2 genomic and subgenomic RNAs.

Host RNA binding proteins recognize viral RNA and play key roles in virus replication and antiviral defense mechanisms. SARS-CoV-2 generates a series of tiered subgenomic RNAs (sgRNAs), each encoding distinct viral protein(s) that regulate different aspects of viral replication. Here, for the first time, we demonstrate the successful isolation of SARS-CoV-2 genomic RNA and three distinct sgRNAs (N, S, and ORF8) from a single population of infected cells and characterize their protein interactomes. Over 500 protein interactors (including 260 previously unknown) were identified as associated with one or more target RNA at either of two time points. These included protein interactors unique to a single RNA pool and others present in multiple pools, highlighting our ability to discriminate between distinct viral RNA interactomes despite high sequence similarity. The interactomes indicated viral associations with cell response pathways including regulation of cytoplasmic ribonucleoprotein granules and posttranscriptional gene silencing. We validated the significance of five protein interactors predicted to exhibit antiviral activity (APOBEC3F, TRIM71, PPP1CC, LIN28B, and MSI2) using siRNA knockdowns, with each knockdown yielding increases in viral production. This study describes new technology for studying SARS-CoV-2 and reveals a wealth of new viral RNA-associated host factors of potential functional significance to infection.

Elucidating the RNA-Protein Interactomes of Target RNAs in Tissue.

RNA-protein interactions are key to many aspects of cellular homeostasis and their identification is important to understanding cellular function. Multiple strategies have been developed for the RNA-centric characterization of RNA-protein complexes. However, these studies have all been done in immortalized cell lines that do not capture the complexity of heterogeneous tissue samples. Here, we develop hybridization purification of RNA-protein complexes followed by mass spectrometry (HyPR-MS) for use in tissue samples. We isolated both polyadenylated RNA and the specific long noncoding RNA MALAT1 and characterized their protein interactomes. These results demonstrate the feasibility of HyPR-MS in tissue for the multiplexed characterization of specific RNA-protein complexes.

Axon guidance genes modulate neurotoxicity of ALS-associated UBQLN2.

Mutations in the ubiquitin (Ub) chaperone Ubiquilin 2 (UBQLN2) cause X-linked forms of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) through unknown mechanisms. Here, we show that aggregation-prone, ALS-associated mutants of UBQLN2 (UBQLN2ALS) trigger heat stress-dependent neurodegeneration in Drosophila. A genetic modifier screen implicated endolysosomal and axon guidance genes, including the netrin receptor, Unc-5, as key modulators of UBQLN2 toxicity. Reduced gene dosage of Unc-5 or its coreceptor Dcc/frazzled diminished neurodegenerative phenotypes, including motor dysfunction, neuromuscular junction defects, and shortened lifespan, in flies expressing UBQLN2ALS alleles. Induced pluripotent stem cells (iPSCs) harboring UBQLN2ALS knockin mutations exhibited lysosomal defects while inducible motor neurons (iMNs) expressing UBQLN2ALS alleles exhibited cytosolic UBQLN2 inclusions, reduced neurite complexity, and growth cone defects that were partially reversed by silencing of UNC5B and DCC. The combined findings suggest that altered growth cone dynamics are a conserved pathomechanism in UBQLN2-associated ALS/FTD.

Fast, Free, and Flexible Peptide and Protein Quantification with FlashLFQ.

The rapid and accurate quantification of peptides is a critical element of modern proteomics that has become increasingly challenging as proteomic data sets grow in size and complexity. We present here FlashLFQ, a computer program for high-speed label-free quantification of peptides and proteins following a search of bottom-up mass spectrometry data. FlashLFQ is approximately an order of magnitude faster than established label-free quantification methods and can quantify data-dependent analysis (DDA) search results from any proteomics search program. It is available as a graphical user interface program, a command line tool, a Docker image, and integrated into the MetaMorpheus search software.

Multi-step recognition of potential 5' splice sites by the Saccharomyces cerevisiae U1 snRNP.

In eukaryotes, splice sites define the introns of pre-mRNAs and must be recognized and excised with nucleotide precision by the spliceosome to make the correct mRNA product. In one of the earliest steps of spliceosome assembly, the U1 small nuclear ribonucleoprotein (snRNP) recognizes the 5' splice site (5' SS) through a combination of base pairing, protein-RNA contacts, and interactions with other splicing factors. Previous studies investigating the mechanisms of 5' SS recognition have largely been done in vivo or in cellular extracts where the U1/5' SS interaction is difficult to deconvolute from the effects of trans-acting factors or RNA structure. In this work we used colocalization single-molecule spectroscopy (CoSMoS) to elucidate the pathway of 5' SS selection by purified yeast U1 snRNP. We determined that U1 reversibly selects 5' SS in a sequence-dependent, two-step mechanism. A kinetic selection scheme enforces pairing at particular positions rather than overall duplex stability to achieve long-lived U1 binding. Our results provide a kinetic basis for how U1 may rapidly surveil nascent transcripts for 5' SS and preferentially accumulate at these sequences rather than on close cognates.

Discovery of Dehydroamino Acid Residues in the Capsid and Matrix Structural Proteins of HIV-1.

Human immunodeficiency virus type 1 (HIV-1) remains a deadly infectious disease despite existing antiretroviral therapies. A comprehensive understanding of the specific mechanisms of viral infectivity remains elusive and currently limits the development of new and effective therapies. Through in-depth proteomic analysis of HIV-1 virions, we discovered the novel post-translational modification of highly conserved residues within the viral matrix and capsid proteins to the dehydroamino acids, dehydroalanine and dehydrobutyrine. We further confirmed their presence by labeling the reactive alkene, characteristic of dehydroamino acids, with glutathione via Michael addition. Dehydroamino acids are rare, understudied, and have been observed mainly in select bacterial and fungal species. Until now, they have not been observed in HIV proteins. We hypothesize that these residues are important in viral particle maturation and could provide valuable insight into HIV infectivity mechanisms.

MetaNetwork Enhances Biological Insights from Quantitative Proteomics Differences by Combining Clustering and Enrichment Analyses.

Interpreting proteomics data remains challenging due to the large number of proteins that are quantified by modern mass spectrometry methods. Weighted gene correlation network analysis (WGCNA) can identify groups of biologically related proteins using only protein intensity values by constructing protein correlation networks. However, WGCNA is not widespread in proteomic analyses due to challenges in implementing workflows. To facilitate the adoption of WGCNA by the proteomics field, we created MetaNetwork, an open-source, R-based application to perform sophisticated WGCNA workflows with no coding skill requirements for the end user. We demonstrate MetaNetwork's utility by employing it to identify groups of proteins associated with prostate cancer from a proteomic analysis of tumor and adjacent normal tissue samples. We found a decrease in cytoskeleton-related protein expression, a known hallmark of prostate tumors. We further identified changes in module eigenproteins indicative of dysregulation in protein translation and trafficking pathways. These results demonstrate the value of using MetaNetwork to improve the biological interpretation of quantitative proteomics experiments with 15 or more samples.

Towards an Ideal In Cell Hybridization-Based Strategy to Discover Protein Interactomes of Selected RNA Molecules.

RNA-binding proteins are crucial to the function of coding and non-coding RNAs. The disruption of RNA-protein interactions is involved in many different pathological states. Several computational and experimental strategies have been developed to identify protein binders of selected RNA molecules. Amongst these, 'in cell' hybridization methods represent the gold standard in the field because they are designed to reveal the proteins bound to specific RNAs in a cellular context. Here, we compare the technical features of different 'in cell' hybridization approaches with a focus on their advantages, limitations, and current and potential future applications.

Identifying Protein Interactomes of Target RNAs Using HyPR-MS.

RNA-protein interactions are integral to maintaining proper cellular function and homeostasis, and the disruption of key RNA-protein interactions is central to many disease states. HyPR-MS (hybridization purification of RNA-protein complexes followed by mass spectrometry) is a highly versatile and efficient technology which enables multiplexed discovery of specific RNA-protein interactomes. This chapter provides extensive guidance for successful application of HyPR-MS to the system and target RNA(s) of interest, as well as a detailed description of the fundamental HyPR-MS procedure, including: (1) experimental design of controls, capture oligonucleotides, and qPCR assays; (2) formaldehyde cross-linking of cell culture; (3) cell lysis and RNA solubilization; (4) isolation of target RNA(s); (5) RNA purification and RT-qPCR analysis; (6) protein preparation and mass spectrometric analysis; and (7) mass spectrometric data analysis.

Fused in sarcoma regulates DNA replication timing and kinetics.

Fused in sarcoma (FUS) encodes an RNA-binding protein with diverse roles in transcriptional activation and RNA splicing. While oncogenic fusions of FUS and transcription factor DNA-binding domains are associated with soft tissue sarcomas, dominant mutations in FUS can cause amyotrophic lateral sclerosis. FUS has also been implicated in genome maintenance. However, the underlying mechanisms of its actions in genome stability are unknown. Here, we applied gene editing, functional reconstitution, and integrated proteomics and transcriptomics to illuminate roles for FUS in DNA replication and repair. Consistent with a supportive role in DNA double-strand break repair, FUS-deficient cells exhibited subtle alterations in the recruitment and retention of double-strand break-associated factors, including 53BP1 and BRCA1. FUS-/- cells also exhibited reduced proliferative potential that correlated with reduced speed of replication fork progression, diminished loading of prereplication complexes, enhanced micronucleus formation, and attenuated expression and splicing of S-phase-associated genes. Finally, FUS-deficient cells exhibited genome-wide alterations in DNA replication timing that were reversed upon re-expression of FUS complementary DNA. We also showed that FUS-dependent replication domains were enriched in transcriptionally active chromatin and that FUS was required for the timely replication of transcriptionally active DNA. These findings suggest that alterations in DNA replication kinetics and programming contribute to genome instability and functional defects in FUS-deficient cells.

Mesh Fragmentation Improves Dissociation Efficiency in Top-down Proteomics.

Top-down proteomics is a key mass spectrometry-based technology for comprehensive analysis of proteoforms. Proteoforms exhibit multiple high charge states and isotopic forms in full MS scans. The dissociation behavior of proteoforms in different charge states and subjected to different collision energies is highly variable. The current widely employed data-dependent acquisition (DDA) method selects a narrow m/z range (corresponding to a single proteoform charge state) for dissociation from the most abundant precursors. We describe here Mesh, a novel dissociation strategy, to dissociate multiple charge states of one proteoform with multiple collision energies. We show that the Mesh strategy has the potential to generate fragment ions with improved sequence coverage and improve identification ratios in top-down proteomic analyses of complex samples. The strategy is implemented within an open-source instrument control software program named MetaDrive to perform real time deconvolution and precursor selection.

Identification of host proteins differentially associated with HIV-1 RNA splice variants.

HIV-1 generates unspliced (US), partially spliced (PS), and completely spliced (CS) classes of RNAs, each playing distinct roles in viral replication. Elucidating their host protein 'interactomes' is crucial to understanding virus-host interplay. Here, we present HyPR-MSSV for isolation of US, PS, and CS transcripts from a single population of infected CD4+ T-cells and mass spectrometric identification of their in vivo protein interactomes. Analysis revealed 212 proteins differentially associated with the unique RNA classes, including preferential association of regulators of RNA stability with US and PS transcripts and, unexpectedly, mitochondria-linked proteins with US transcripts. Remarkably, >80 of these factors screened by siRNA knockdown impacted HIV-1 gene expression. Fluorescence microscopy confirmed several to co-localize with HIV-1 US RNA and exhibit changes in abundance and/or localization over the course of infection. This study validates HyPR-MSSV for discovery of viral splice variant protein interactomes and provides an unprecedented resource of factors and pathways likely important to HIV-1 replication.

Improving Proteoform Identifications in Complex Systems Through Integration of Bottom-Up and Top-Down Data.

Cellular functions are performed by a vast and diverse set of proteoforms. Proteoforms are the specific forms of proteins produced as a result of genetic variations, RNA splicing, and post-translational modifications (PTMs). Top-down mass spectrometric analysis of intact proteins enables proteoform identification, including proteoforms derived from sequence cleavage events or harboring multiple PTMs. In contrast, bottom-up proteomics identifies peptides, which necessitates protein inference and does not yield proteoform identifications. We seek here to exploit the synergies between these two data types to improve the quality and depth of the overall proteomic analysis. To this end, we automated the large-scale integration of results from multiprotease bottom-up and top-down analyses in the software program Proteoform Suite and applied it to the analysis of proteoforms from the human Jurkat T lymphocyte cell line. We implemented the recently developed proteoform-level classification scheme for top-down tandem mass spectrometry (MS/MS) identifications in Proteoform Suite, which enables users to observe the level and type of ambiguity for each proteoform identification, including which of the ambiguous proteoform identifications are supported by bottom-up-level evidence. We used Proteoform Suite to find instances where top-down identifications aid in protein inference from bottom-up analysis and conversely where bottom-up peptide identifications aid in proteoform PTM localization. We also show the use of bottom-up data to infer proteoform candidates potentially present in the sample, allowing confirmation of such proteoform candidates by intact-mass analysis of MS1 spectra. The implementation of these capabilities in the freely available software program Proteoform Suite enables users to integrate large-scale top-down and bottom-up data sets and to utilize the synergies between them to improve and extend the proteomic analysis.

A Bayesian Null Interval Hypothesis Test Controls False Discovery Rates and Improves Sensitivity in Label-Free Quantitative Proteomics.

Statistical significance tests are a common feature in quantitative proteomics workflows. The Student's t-test is widely used to compute the statistical significance of a protein's change between two groups of samples. However, the t-test's null hypothesis asserts that the difference in means between two groups is exactly zero, often marking small but uninteresting fold-changes as statistically significant. Compensations to address this issue are widely used in quantitative proteomics, but we suggest that a replacement of the t-test with a Bayesian approach offers a better path forward. In this article, we describe a Bayesian hypothesis test in which the null hypothesis is an interval rather than a single point at zero; the width of the interval is estimated from population statistics. The improved sensitivity of the method substantially increases the number of truly changing proteins detected in two benchmark data sets (ProteomeXchange identifiers PXD005590 and PXD016470). The method has been implemented within FlashLFQ, an open-source software program that quantifies bottom-up proteomics search results obtained from any search tool. FlashLFQ is rapid, sensitive, and accurate and is available both as an easy-to-use graphical user interface (Windows) and as a command-line tool (Windows/Linux/OSX).

Proteomic analysis of affinity-purified 26S proteasomes identifies a suite of assembly chaperones in Arabidopsis.

The 26S proteasome is an essential protease that selectively eliminates dysfunctional and short-lived regulatory proteins in eukaryotes. To define the composition of this proteolytic machine in plants, we tagged either the core protease (CP) or the regulatory particle (RP) sub-complexes in Arabidopsis to enable rapid affinity purification followed by mass spectrometric analysis. Studies on proteasomes enriched from whole seedlings, with or without ATP needed to maintain the holo-proteasome complex, identified all known proteasome subunits but failed to detect isoform preferences, suggesting that Arabidopsis does not construct distinct proteasome sub-types. We also detected a suite of proteasome-interacting proteins, including likely orthologs of the yeast and mammalian chaperones Pba1, Pba2, Pba3, and Pba4 that assist in CP assembly; Ump1 that helps connect CP half-barrels; Nas2, Nas6, and Hsm3 that assist in RP assembly; and Ecm29 that promotes CP-RP association. Proteasomes from seedlings exposed to the proteasome inhibitor MG132 accumulated assembly intermediates, reflecting partially built proteasome sub-complexes associated with assembly chaperones, and the CP capped with the PA200/Blm10 regulator. Genetic analyses of Arabidopsis UMP1 revealed that, unlike in yeast, this chaperone is essential, with mutants lacking the major UMP1a and UMP1b isoforms displaying a strong gametophytic defect. Single ump1 mutants were hypersensitive to conditions that induce proteotoxic, salt and osmotic stress, and also accumulated several proteasome assembly intermediates, consistent with its importance for CP construction. Insights into the chaperones reported here should enable study of the assembly events that generate the 26S holo-proteasome in Arabidopsis from the collection of 64 or more subunits.

Constructing Human Proteoform Families Using Intact-Mass and Top-Down Proteomics with a Multi-Protease Global Post-Translational Modification Discovery Database.

Complex human biomolecular processes are made possible by the diversity of human proteoforms. Constructing proteoform families, groups of proteoforms derived from the same gene, is one way to represent this diversity. Comprehensive, high-confidence identification of human proteoforms remains a central challenge in mass spectrometry-based proteomics. We have previously reported a strategy for proteoform identification using intact-mass measurements, and we have since improved that strategy by mass calibration based on search results, the use of a global post-translational modification discovery database, and the integration of top-down proteomics results with intact-mass analysis. In the present study, we combine these strategies for enhanced proteoform identification in total cell lysate from the Jurkat human T lymphocyte cell line. We collected, processed, and integrated three types of proteomics data (NeuCode-labeled intact-mass, label-free top-down, and multi-protease bottom-up) to maximize the number of confident proteoform identifications. The integrated analysis revealed 5950 unique experimentally observed proteoforms, which were assembled into 848 proteoform families. Twenty percent of the observed proteoforms were confidently identified at a 3.9% false discovery rate, representing 1207 unique proteoforms derived from 484 genes.

Comprehensive in vivo identification of the c-Myc mRNA protein interactome using HyPR-MS.

Proteins bind mRNA through their entire life cycle from transcription to degradation. We analyzed c-Myc mRNA protein interactors in vivo using the HyPR-MS method to capture the crosslinked mRNA by hybridization and then analyzed the bound proteins using mass spectrometry proteomics. Using HyPR-MS, 229 c-Myc mRNA-binding proteins were identified, confirming previously proposed interactors, suggesting new interactors, and providing information related to the roles and pathways known to involve c-Myc. We performed structural and functional analysis of these proteins and validated our findings with a combination of RIP-qPCR experiments, in vitro results released in past studies, publicly available RIP- and eCLIP-seq data, and results from software tools for predicting RNA-protein interactions.

HDA9-PWR-HOS15 Is a Core Histone Deacetylase Complex Regulating Transcription and Development.

Histone deacetylases remove acetyl groups from histone proteins and play important roles in many genomic processes. How histone deacetylases perform specialized molecular and biological functions in plants is poorly understood. Here, we identify HIGH EXPRESSION OF OSMOTICALLY RESPONSIVE GENES 15 (HOS15) as a core member of the Arabidopsis (Arabidopsis thaliana) HISTONE DEACETYLASE9-POWERDRESS (HDA9-PWR) complex. HOS15 immunoprecipitates with both HDA9 and PWR. Mutation of HOS15 induces histone hyperacetylation and methylation changes similar to hda9 and pwr mutants. HOS15, HDA9, and PWR are coexpressed in all organs, and mutant combinations display remarkable phenotypic resemblance and nonadditivity for organogenesis and developmental phase transitions. Ninety percent of HOS15-regulated genes are also controlled by HDA9 and PWR HDA9 binds to and directly represses 92 genes, many of which are responsive to biotic and abiotic stimuli, including a family of ethylene response factor genes. Additionally, HOS15 regulates HDA9 nuclear accumulation and chromatin association. Collectively, this study establishes that HOS15 forms a core complex with HDA9 and PWR to control gene expression and plant development.

Identification and Quantification of Murine Mitochondrial Proteoforms Using an Integrated Top-Down and Intact-Mass Strategy.

The development of effective strategies for the comprehensive identification and quantification of proteoforms in complex systems is a critical challenge in proteomics. Proteoforms, the specific molecular forms in which proteins are present in biological systems, are the key effectors of biological function. Thus, knowledge of proteoform identities and abundances is essential to unraveling the mechanisms that underlie protein function. We recently reported a strategy that integrates conventional top-down mass spectrometry with intact-mass determinations for enhanced proteoform identifications and the elucidation of proteoform families and applied it to the analysis of yeast cell lysate. In the present work, we extend this strategy to enable quantification of proteoforms, and we examine changes in the abundance of murine mitochondrial proteoforms upon differentiation of mouse myoblasts to myotubes. The integrated top-down and intact-mass strategy provided an increase of ∼37% in the number of identified proteoforms compared to top-down alone, which is in agreement with our previous work in yeast; 1779 unique proteoforms were identified using the integrated strategy compared to 1301 using top-down analysis alone. Quantitative comparison of proteoform differences between the myoblast and myotube cell types showed 129 observed proteoforms exhibiting statistically significant abundance changes (fold change >2 and false discovery rate <5%).