Targeting G9a translational mechanism of SARS-CoV-2 pathogenesis for multifaceted therapeutics of COVID-19 and its sequalae

By largely unknown mechanism(s), SARS-CoV-2 hijacks the host translation apparatus to promote COVID-19 pathogenesis. We report that the histone methyltransferase G9a noncanonically regulates viral hijacking of the translation machinery to bring about COVID-19 symptoms of hyperinflammation, lymphopenia, and blood coagulation. Chemoproteomic analysis of COVID-19 patient peripheral mononuclear blood cells (PBMC) identified enhanced interactions between SARS-CoV-2-upregulated G9a and distinct translation regulators, particularly the N 6 -methyladenosine (m 6 A) RNA methylase METTL3. These interactions with translation regulators implicated G9a in translational regulation of COVID-19. Inhibition of G9a activity suppressed SARS-CoV-2 replication in human alveolar epithelial cells. Accordingly, multi-omics analysis of the same alveolar cells identified SARS-CoV-2-induced changes at the transcriptional, m 6 A-epitranscriptional, translational, and post-translational (phosphorylation or secretion) levels that were reversed by inhibitor treatment. As suggested by the aforesaid chemoproteomic analysis, these multi-omics-correlated changes revealed a G9a-regulated translational mechanism of COVID-19 pathogenesis in which G9a directs translation of viral and host proteins associated with SARS-CoV-2 replication and with dysregulation of host response. Comparison of proteomic analyses of G9a inhibitor-treated, SARS-CoV-2 infected cells, or ex vivo culture of patient PBMCs, with COVID-19 patient data revealed that G9a inhibition reversed the patient proteomic landscape that correlated with COVID-19 pathology/symptoms. These data also indicated that the G9a-regulated, inhibitor-reversed, translational mechanism outperformed G9a-transcriptional suppression to ultimately determine COVID-19 pathogenesis and to define the inhibitor action, from which biomarkers of serve symptom vulnerability were mechanistically derived. This cell line-to-patient conservation of G9a-translated, COVID-19 proteome suggests that G9a inhibitors can be used to treat patients with COVID-19, particularly patients with long-lasting COVID-19 sequelae.

Novel brain-penetrant inhibitor of G9a methylase blocks Alzheimer's disease proteopathology for precision medication

Current amyloid beta-targeting approaches for Alzheimer's disease (AD) therapeutics only slow cognitive decline for small numbers of patients. This limited efficacy exists because AD is a multifactorial disease whose pathological mechanism(s) and diagnostic biomarkers are largely unknown. Here we report a new mechanism of AD pathogenesis in which the histone methyltransferase G9a noncanonically regulates translation of a hippocampal proteome that defines the proteopathic nature of AD. Accordingly, we developed a novel brain-penetrant inhibitor of G9a, MS1262, across the blood-brain barrier to block this G9a-regulated, proteopathologic mechanism. Intermittent MS1262 treatment of multiple AD mouse models consistently restored both cognitive and noncognitive functions to healthy levels. Comparison of proteomic/phosphoproteomic analyses of MS1262-treated AD mice with human AD patient data identified multiple pathological brain pathways that elaborate amyloid beta and neurofibrillary tangles as well as blood coagulation, from which biomarkers of early stage of AD including SMOC1 were found to be affected by MS1262 treatment. Notably, these results indicated that MS1262 treatment may reduce or avoid the risk of blood clot burst for brain bleeding or a stroke. This mouse-to-human conservation of G9a-translated AD proteopathology suggests that the global, multifaceted effects of MS1262 in mice could extend to relieve all symptoms of AD patients with minimum side effect. In addition, our mechanistically derived biomarkers can be used for stage-specific AD diagnosis and companion diagnosis of individualized drug effects.

One-Sentence Summary

A brain-penetrant inhibitor of G9a methylase blocks G9a translational mechanism to reverse Alzheimer's disease related proteome for effective therapy.

IL-11 induces NLRP3 inflammasome activation in monocytes and inflammatory cell migration to the central nervous system

The objective of this study is to examine IL-11-induced mechanisms of inflammatory cell migration to the central nervous system (CNS). We report that IL-11 is produced at highest frequency by myeloid cells among the peripheral blood mononuclear cell (PBMC) subsets. Patients with relapsing-remitting multiple sclerosis (RRMS) have an increased frequency of IL-11+ monocytes, IL-11+ and IL-11R+ CD4+ lymphocytes, and IL-11R+ neutrophils in comparison to matched healthy controls. IL-11+ and granulocyte-macrophage colony-stimulating factor (GM-CSF)+ monocytes, CD4+ lymphocytes, and neutrophils accumulate in the cerebrospinal fluid (CSF). The effect of IL-11 in-vitro stimulation, examined using single-cell RNA sequencing, revealed the highest number of differentially expressed genes in classical monocytes, including up-regulated NFKB1, NLRP3, and IL1B. All CD4+ cell subsets had increased expression of S100A8/9 alarmin genes involved in NLRP3 inflammasome activation. In IL-11R+-sorted cells from the CSF, classical and intermediate monocytes significantly up-regulated the expression of multiple NLRP3 inflammasome-related genes, including complement, IL18, and migratory genes (VEGFA/B) in comparison to blood-derived cells. Therapeutic targeting of this pathway with αIL-11 mAb in mice with RR experimental autoimmune encephalomyelitis (EAE) decreased clinical scores, CNS inflammatory infiltrates, and demyelination. αIL-11 mAb treatment decreased the numbers of NFκBp65+, NLRP3+, and IL-1β+ monocytes in the CNS of mice with EAE. The results suggest that IL-11/IL-11R signaling in monocytes represents a therapeutic target in RRMS.

STING-induced regulatory B cells compromise NK function in cancer immunity

An immunosuppressive tumour microenvironment is a major obstacle in the control of pancreatic and other solid cancers1-3. Agonists of the stimulator of interferon genes (STING) protein trigger inflammatory innate immune responses to potentially overcome tumour immunosuppression4. Although these agonists hold promise as potential cancer therapies5, tumour resistance to STING monotherapy has emerged in clinical trials and the mechanism(s) is unclear5-7. Here we show that the administration of five distinct STING agonists, including cGAMP, results in an expansion of human and mouse interleukin (IL)-35+ regulatory B cells in pancreatic cancer. Mechanistically, cGAMP drives expression of IL-35 by B cells in an IRF3-dependent but type I interferon-independent manner. In several preclinical cancer models, the loss of STING signalling in B cells increases tumour control. Furthermore, anti-IL-35 blockade or genetic ablation of IL-35 in B cells also reduces tumour growth. Unexpectedly, the STING-IL-35 axis in B cells reduces proliferation of natural killer (NK) cells and attenuates the NK-driven anti-tumour response. These findings reveal an intrinsic barrier to systemic STING agonist monotherapy and provide a combinatorial strategy to overcome immunosuppression in tumours.

Protocol for proteogenomic dissection of intronic splicing enhancer interactome for prediction of individualized cancer prognosis

Inter- or intra-patient tumor heterogeneity hinders the discovery of biomarkers for predicting individualized prognosis. Here, we present a protocol for an alternative splicing activity-based proteogenomic approach for identification of candidate prognostic markers in cancer cell lines and human breast cancer specimens. The pull-down of protein complexes with intronic splicing enhancer (ISE) probes is followed by tandem mass spectrometry (MS/MS) peptide sequencing. The proteogenomic analysis of data from these ISE-MS/MS assays identifies new prognostic markers that can be utilized to stratify patients with poor prognosis.

For complete details on the use and execution of this protocol, please refer to Wang et al. (2018).

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Protocol for LC-MS/MS analysis of ISE interactomes from cancer cell lines or tissues

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Protocol for proteogenomic identification of ISE interactors of prognostic significance

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Protocol for protein extraction, ISE pull-downs, MS/MS, and proteogenomic analysis

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Protocols applicable to cancer cell lines and clinical specimens

Identification of pathogenic TRAIL-expressing innate immune cells during HIV-1 infection in humanized mice by scRNA-Seq

Depletion of CD4+ T cells during HIV-1 infection is mostly mediated by inflammatory cells via indirect but not clearly defined mechanisms. In this report, we used single-cell RNA-Seq (scRNA-Seq) technology to study HIV-induced transcriptomic change in innate immune cells in lymphoid organs. We performed scRNA-Seq on hCD45+hCD3-hCD19- human leukocytes isolated from spleens of humanized NOD/Rag2-/-γc-/- (NRG) mice transplanted with human CD34+ hematopoietic stem progenitor cells (NRG-hu HSC mice). We identified major populations of innate immune cells, including plasmacytoid dendritic cells (pDCs), myeloid dendritic cells (mDCs), macrophages, NK cells, and innate lymphoid cells (ILCs). HIV-1 infection significantly upregulated genes involved in type I IFN inflammatory pathways in each of the innate immune subsets. Interestingly, we found that TRAIL was upregulated in the innate immune populations, including pDCs, mDCs, macrophages, NK cells, and ILCs. We further demonstrated that blockade of the TRAIL signaling pathway in NRG-hu HSC mice prevented HIV-1-induced CD4+ T cell depletion in vivo. In summary, we characterized HIV-induced transcriptomic changes of innate immune cells in the spleen at single-cell levels, identified the TRAIL+ innate immune cells, and defined an important role of the TRAIL signaling pathway in HIV-1-induced CD4+ T cell depletion in vivo.

Multi-omic Dissection of Oncogenically Active Epiproteomes Identifies Drivers of Proliferative and Invasive Breast Tumors

Proliferative and invasive breast tumors evolve heterogeneously in individual patients, posing significant challenges in identifying new druggable targets for precision, effective therapy. Here we present a functional multi-omics method, interaction-Correlated Multi-omic Aberration Patterning (iC-MAP), which dissects intra-tumor heterogeneity and identifies in situ the oncogenic consequences of multi-omics aberrations that drive proliferative and invasive tumors. First, we perform chromatin activity-based chemoproteomics (ChaC) experiments on breast cancer (BC) patient tissues to identify genetic/transcriptomic alterations that manifest as oncogenically active proteins. ChaC employs a biotinylated small molecule probe that specifically binds to the oncogenically active histone methyltransferase G9a, enabling sorting/enrichment of a G9a-interacting protein complex that represents the predominant BC subtype in a tissue. Second, using patient transcriptomic/genomic data, we retrospectively identified some G9a interactor-encoding genes that showed individualized iC-MAP. Our iC-MAP findings represent both new diagnostic/prognostic markers to identify patient subsets with incurable metastatic disease and targets to create individualized therapeutic strategies.

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ChaC dissects tumor heterogeneity for identifying oncogenic-active proteins

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An oncogenic-active G9a-interactome represents the invasive tumor in a tissue

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iC-MAP identifies multi-omics aberrations that drive invasive tumors

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Patient-specific iC-MAP of select interactor genes are of prognostic value

Novel secretome-to-transcriptome integrated or secreto-transcriptomic approach to reveal liquid biopsy biomarkers for predicting individualized prognosis of breast cancer patients

Background

Presently, a 50-gene expression model (PAM50) serves as a breast cancer (BC) subtype classifier that is insufficient to distinguish, within each single PAM50-classified subtype, patient subpopulations having different prognosis. There is a pressing need for inexpensive and minimally invasive biomarker tests to easily and accurately predict individuals’ clinical outcomes and response to treatments. Although quantitative proteomic approaches have been developed to identify/profile proteins secreted (secretome) from various cancer cell lines in vitro, missing are the clinicopathological relevance and the associated prognostic value of these secretomic identifications.

Methods

To discover biomarkers to predict individualized prognosis we introduce a new multi-omics (secreto-transcriptomics) method that identifies, in their oncogenically secreted states, candidate markers of BC subtypes whose genes bear patient-specific mRNA expression alterations of prognostic significance. First, we used label-free quantitative (LFQ) proteomics to identify the proteins showing BC-subtypic secretion from a series of BC cell lines representing major BC-subtypes. To determine and externally validate the prognostic value of these secreted proteins, we developed a secreto-transcriptomic approach that discovered a PAM50-subtypic Secretion-Correlated mRNA Expression Pattern (SeCEP) wherein the PAM50-subtypic secretion of select proteins statistically correlated with cis-mRNA expression of their encoding genes in patients of the corresponding PAM50-subtypes. Kaplan-Meier analysis of SeCEP genes was used to identify new liquid biopsy biomarkers for predicting individualized prognosis.

Results

The mRNA expression-to-secretion correlation (SeCEP) pinpointed multiple genes that are fully translated into the oncogenically active secretome in a PAM50-subtypic manner. Further, multiple SeCEP genes in distinct combinations or panels of multiple SeCEP genes were identified as ‘systems prognostic markers’ that showed mRNA co-overexpression patterns in the distinct subpopulations of PAM50-subtypic patients with poor prognosis or high-risk of relapse. Thus, our secreto-transcriptomic approach statistically linked BC subtypic secretome genes with patient-specific information about their mRNA expression alterations and significantly improved the sensitivity and specificity in patient stratification in the context of clinical outcomes or prognosis.

Conclusions

By combining LFQ secretome screening with proteo-transcriptomic retrospective analysis of patient data our integrated multi-omics approach bypasses costly, tedious, genome-wide fishing and predictive modeling that are commonly required to distinguish a few prognostically altered genes from thousands of other non-BC related genes in a genome.

Electronic supplementary material

The online version of this article (10.1186/s12920-019-0530-7) contains supplementary material, which is available to authorized users.

Novel RNA-Affinity Proteogenomics Dissects Tumor Heterogeneity for Revealing Personalized Markers in Precision Prognosis of Cancer

To discriminate the patient subpopulations with different clinical outcomes within each breast cancer (BC) subtype, we introduce a robust, clinical-practical, activity-based proteogenomic method that identifies, in their oncogenically active states, candidate biomarker genes bearing patient-specific transcriptomic/genomic alterations of prognostic value. First, we used the intronic splicing enhancer (ISE) probes to sort ISE-interacting trans-acting protein factors (trans-interactome) directly from a tumor tissue for subsequent mass spectrometry characterization. In the retrospective, proteogenomic analysis of patient datasets, we identified those ISE trans-factor-encoding genes showing interaction-correlated expression patterns (iCEPs) as new BC-subtypic genes. Further, patient-specific co-alterations in mRNA expression of select iCEP genes distinguished high-risk patient subsets/subpopulations from other patients within a single BC subtype. Function analysis further validated a tumor-phenotypic trans-interactome contained the drivers of oncogenic splicing switches, representing the predominant tumor cells in a tissue, from which novel personalized biomarkers were clinically characterized/validated for precise prognostic prediction and subsequent individualized alignment of optimal therapy.

Recommendations for the Generation, Quantification, Storage, and Handling of Peptides Used for Mass Spectrometry-Based Assays

BACKGROUND

For many years, basic and clinical researchers have taken advantage of the analytical sensitivity and specificity afforded by mass spectrometry in the measurement of proteins. Clinical laboratories are now beginning to deploy these work flows as well. For assays that use proteolysis to generate peptides for protein quantification and characterization, synthetic stable isotope-labeled internal standard peptides are of central importance. No general recommendations are currently available surrounding the use of peptides in protein mass spectrometric assays.

CONTENT

The Clinical Proteomic Tumor Analysis Consortium of the National Cancer Institute has collaborated with clinical laboratorians, peptide manufacturers, metrologists, representatives of the pharmaceutical industry, and other professionals to develop a consensus set of recommendations for peptide procurement, characterization, storage, and handling, as well as approaches to the interpretation of the data generated by mass spectrometric protein assays. Additionally, the importance of carefully characterized reference materials-in particular, peptide standards for the improved concordance of amino acid analysis methods across the industry-is highlighted. The alignment of practices around the use of peptides and the transparency of sample preparation protocols should allow for the harmonization of peptide and protein quantification in research and clinical care.

Using the CPTAC Assay Portal to Identify and Implement Highly Characterized Targeted Proteomics Assays

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as an open-source repository of well-characterized targeted proteomic assays. The portal is designed to curate and disseminate highly characterized, targeted mass spectrometry (MS)-based assays by providing detailed assay performance characterization data, standard operating procedures, and access to reagents. Assay content is accessed via the portal through queries to find assays targeting proteins associated with specific cellular pathways, protein complexes, or specific chromosomal regions. The position of the peptide analytes for which there are available assays are mapped relative to other features of interest in the protein, such as sequence domains, isoforms, single nucleotide polymorphisms, and posttranslational modifications. The overarching goals are to enable robust quantification of all human proteins and to standardize the quantification of targeted MS-based assays to ultimately enable harmonization of results over time and across laboratories.

QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to "rescue" the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes.

Abstract 1999: Proteogenomic characterization of breast cancer sub-types in patient derived xenografts

The goal of this talk is to introduce an integrated quantitative proteogenomic approach to comprehensively map proteomic information back to their encoding genes. We seek evidence from mass spectrometry-based large-scale proteomic data of patient populations in conjunction with patient-centric next-generation sequencing data and unbiased sequencing strategies to study breast cancer (BC) subtypes from a genomic context.

We have obtained global and phosphoproteomic data with matching next generation sequencing data for 18 patient-derived xenografts (PDXs) representing the major clinical subtypes of BC. Our workflow starts with the creation of several protein sequence databases that serve as a template for mass spectrometry database identifications. These databases include 1) completely annotated reference protein sequences, 2) patient-specific databases that were created using next generation sequencing data, 3) isoform databases that contain all possible splicing combinations, and 4) amino acid sequence database resulting from a six-frame translation of the entire human reference and customized genomes. All mass spectrometry raw data are searched against the databases for obtaining identifications at the peptide level, and assembly of peptides for quantification using taxonomy-based label-free quantitation (LFQ) that can specifically quantify unique human peptide sequences found in PDXs. The peptides are then mapped to the human genome and visualized using a genome browser. Quantitative changes across PDXs are presented at the protein level or at the isoform level via peptide role-up to specific exons and visualized as a quantitative data track.

By combining search results from these databases we obtain a comprehensive view of our PDXs. The complementary nature of the databases enable greater proteomic depth, i.e. databases with complete splicing combinations capture proteomic evidence when patient-specific databases fail due to possible erroneous RNA-seq reads. Similarly, 6-frame translated amino acid databases can capture potentially novel coding regions but are unable to detect splicing. Peptide maps are obtained for individual genes or specific protein isoforms covering both knowledge-driven and novel genomic annotation types. We compile peptides carrying variants, splice junctions, fusions, and new coding regions specific to each PDX or in common with a specific BC subtype. Majority of data is mapped back to the genome loci using unmodified peptides via global proteomics while phosphopeptides that contain variants and splicing are also mapped in a similar manner using phosphoproteomic data.

We have currently annotated 455 novel proteogenomic hits covering many examples outlined above for genes related to breast cancer and show how these can be specifically identified and in some instances differentially quantified in the PDX models.

Citation Format: Harsha P. Gunawardena, John A. Wrobel, Jonathon O'Brien, Ling Xie, Petra Erdmann-Gilmore, Sherri R. Davies, Shunqiang Li, Song Cao, Michael McLellan, Kelly V. Ruggles, David Fenyo, R. Reid Townsend, Li Ding, Bahjat F. Qaqish, Matthew J. Ellis, Xian Chen. Proteogenomic characterization of breast cancer sub-types in patient derived xenografts. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1999. doi:10.1158/1538-7445.AM2015-1999

A chromatin activity-based chemoproteomic approach reveals a transcriptional repressome for gene-specific silencing

Immune cells develop endotoxin tolerance (ET) after prolonged stimulation. ET increases the level of a repression mark H3K9me2 in the transcriptional-silent chromatin specifically associated with pro-inflammatory genes. However, it is not clear what proteins are functionally involved in this process. Here we show that a novel chromatin activity based chemoproteomic (ChaC) approach can dissect the functional chromatin protein complexes that regulate ET-associated inflammation. Using UNC0638 that binds the enzymatically active H3K9-specific methyltransferase G9a/GLP, ChaC reveals that G9a is constitutively active at a G9a-dependent mega-dalton repressome in primary endotoxin-tolerant macrophages. G9a/GLP broadly impacts the ET-specific reprogramming of the histone code landscape, chromatin remodeling, and the activities of select transcription factors. We discover that the G9a-dependent epigenetic environment promotes the transcriptional repression activity of c-Myc for gene-specific co-regulation of chronic inflammation. ChaC may be also applicable to dissect other functional protein complexes in the context of phenotypic chromatin architectures.

Comparison of the membrane proteome of virulent Mycobacterium tuberculosis and the attenuated Mycobacterium bovis BCG vaccine strain by label-free quantitative proteomics

The Mycobacterium tuberculosis membrane is rich in antigens that are potential targets for diagnostics and the development of new vaccines. To better understand the mechanisms underlying MTB virulence and identify new targets for therapeutic intervention, we investigated the differential composition of membrane proteomes between virulent M. tuberculosis H37Rv (MTB) and the Mycobacterium bovis BCG vaccine strain. To compare the membrane proteomes, we used LC-MS/MS analysis in combination with label-free quantitative proteomics, utilizing the area under the curve of the extracted ion chromatograms of peptides obtained from m/z and retention time alignment of MS1 features. With this approach, we obtained relative abundance ratios for 2203 identified membrane-associated proteins in high confidence. Of these proteins, 294 showed statistically significant differences of at least two fold in relative abundance between MTB and BCG membrane fractions. Our comparative analysis detected several proteins associated with known genomic regions of difference between MTB and BCG as being absent, which validated the accuracy of our approach. In further support of our label-free quantitative data, we verified select protein differences by immunoblotting. To our knowledge, we have generated the first comprehensive and high-coverage profile of comparative membrane proteome changes between virulent MTB and its attenuated relative BCG, which helps elucidate the proteomic basis of the intrinsic virulence of the MTB pathogen.

Whole human genome proteogenomic mapping for ENCODE cell line data: identifying protein-coding regions

BACKGROUND

Proteogenomic mapping is an approach that uses mass spectrometry data from proteins to directly map protein-coding genes and could aid in locating translational regions in the human genome. In concert with the ENcyclopedia of DNA Elements (ENCODE) project, we applied proteogenomic mapping to produce proteogenomic tracks for the UCSC Genome Browser, to explore which putative translational regions may be missing from the human genome.

RESULTS

We generated ~1 million high-resolution tandem mass (MS/MS) spectra for Tier 1 ENCODE cell lines K562 and GM12878 and mapped them against the UCSC hg19 human genome, and the GENCODE V7 annotated protein and transcript sets. We then compared the results from the three searches to identify the best-matching peptide for each MS/MS spectrum, thereby increasing the confidence of the putative new protein-coding regions found via the whole genome search. At a 1% false discovery rate, we identified 26,472, 24,406, and 13,128 peptides from the protein, transcript, and whole genome searches, respectively; of these, 481 were found solely via the whole genome search. The proteogenomic mapping data are available on the UCSC Genome Browser at http://genome.ucsc.edu/cgi-bin/hgTrackUi?db=hg19&g=wgEncodeUncBsuProt.

CONCLUSIONS

The whole genome search revealed that ~4% of the uniquely mapping identified peptides were located outside GENCODE V7 annotated exons. The comparison of the results from the disparate searches also identified 15% more spectra than would have been found solely from a protein database search. Therefore, whole genome proteogenomic mapping is a complementary method for genome annotation when performed in conjunction with other searches.

Analysis of HIV type 1 reverse transcriptase: comparing sequences of viral isolates with mutational data

A result of the high level of mutagenesis during HIV-1 viral replication is that many, if not most, HIV-1 virions and proviruses are defective and are not infectious. There is a vast amount of HIV-1 sequence data available. Unless any particular sequence is shown to be from a stable DNA clone (e.g., lambda) that can transfect cells and produce virions, then it is not known if that sequence was from an infectious HIV-1. Most sequences have not been shown to be from infectious clones. We have reported a saturation mutagenesis of a 109-amino acid region of the HIV-1 reverse transcriptase, in which we assayed the effects of 366 single-amino acid substitutions. We examined a set of sequences in the Los Alamos HIV-1 sequence database. We found that none of the sequences derived from stable infectious clones had substitutions that produce an inactive reverse transcriptase. However, we found that other sequences in this database had substitutions that inactivate the reverse transcriptase. We predict that these sequences are not from infectious clones. This method may also be useful for evaluating the sequences of other viruses.

A genetic approach for identifying critical residues in the fingers and palm subdomains of HIV-1 reverse transcriptase

By using oligonucleotide-directed saturation mutagenesis, we collected 366 different single amino acid substitutions in a 109-aa segment (residues 95-203) in the fingers and palm subdomains of the HIV-1 reverse transcriptase (RT), the enzyme that replicates the viral genome. After expression in Escherichia coli, two phenotypic assays were performed. The first assay tested for RNA-dependent DNA polymerase activity. The other assay used Western blot analysis to estimate the stability of each mutant protein by measuring the processing of the RT into its mature heterodimeric form, consisting of a 66-kDa subunit and a 51-kDa subunit. The resulting phenotypic data provided a "genetic" means to identify amino acid side chains that are important for protein function or stability, as well as side chains located on the protein surface. Several HIV-1 RT crystal structures were used to evaluate the mutational analysis. Our genetic map correlates well with the crystal structures. Combining our phenotype data with crystallographic data allowed us to study the genetically defined critical residues. The important functional residues are found near the enzyme active site. Many residues important for the stability of the RT participate in potential hydrogen bonding or hydrophobic interactions in the protein interior. In addition to providing a better understanding of the HIV-1 RT, this work demonstrates the utility of saturation mutagenesis to study the function, structure, and stability of proteins in general. This strategy should be useful for studying proteins for which no crystallographic data are available.

The effects of anions, substrates, metal ions and sulfhydryl reagents on the proteolytic susceptibility of yeast phosphoglycerate kinase

With the aim of confirming our previous spectrophotometric binding studies ((1978) Eur. J. Biochem. 85, 345-350 and (1980) Eur. J. Biochem. 104, 249-254) and of ascertaining the full physiological significance of ion binding, we investigated the effects of ions and thiol reagents on the proteolysis of yeast phosphoglycerate kinase (ATP: 3-phospho-D-glycerate 1-phosphotransferase, EC 2.7.2.3). The single non-essential thiol of the enzyme was modified with 5,5'-dithiobis(2-nitrobenzoic acid) or 2-chloromercuri-4-nitrophenol. Both modifications greatly increased the susceptibility of the kinase to inactivation by trypsin or yeast proteinase A, when compared with that of the native kinase. Electrophoresis in sodium dodecyl sulfate (SDS) revealed that limited proteolysis had occurred. The time courses for the proteolysis and loss of catalytic activity were followed and the active and inactive fragments identified. The molecular masses of the major proteolytic fragments differed with the two endopeptidases. Substrate and non-substrate anions in a concentration-dependent fashion, protected the native and mercurial-labelled kinase from inactivation by trypsin or yeast proteinase A. However, Zn2+, in a concentration-dependent fashion, increased the susceptibility of the native kinase to inactivation by each endopeptidase. The time courses for the inactivation and for the proteolysis allowed the active and inactive fragments to be identified. Zn2+ decreased the rate of inactivation of the mercurial-labelled kinase by proteinase A. The effects of these ions were detected at concentrations compatible with occupancy of an anion binding site and a low affinity Zn2+ binding site, both of which have been indicated from our previous binding studies.

Anion binding to yeast phosphoglycerate kinase

The single thiol of yeast phosphoglycerate kinase was labelled with the chromophoric sulfhydryl reagent, 2-chloromercuri-4-nitrophenol. Sequential additions of individual anions to this modified enzyme brought about a decrease in absorbance at 410 nm that reflected the degree of saturation of the enzyme with anion. The binding curves were analyzed to determine the dissociation constants of a number of anions with charges varying from--1 to--4.1. A linear relationship was found between the charge of the anion and the negative logarithm of the dissociation constant for the labelled enzyme-anion complex. The highly charged anions, such as ATP, bound more tightly than did anions with less charge, such as Cl-. The average number of binding sites for those anions for which accurate results could be obtained was 1.06 mol per 47000 g of enzyme. Several lines of evidence suggested that titration of the active center was not being monitored. Anions bound to phosphoglycerate kinase decreased the rate of reaction between the enzyme thiol and 5,5'-dithiobis(2-nitrobenzoic acid). The relationship between the degree of saturation of the anion binding site and the reaction rate constant was used to calculate the dissociation constant between anion and enzyme. Dissociation constants determined in this manner were in good agreement with those determined by titration of the enzyme-mercurial complex.