Yuxin Li

C11orf95 – RELA fusions drive oncogenic NF-κB signalling in ependymoma

Members of the nuclear factor-κB (NF-κB) family of transcriptional regulators are central mediators of the cellular inflammatory response. Although constitutive NF-κB signalling is present in most human tumours, mutations in pathway members are rare, complicating efforts to understand and block aberrant NF-κB activity in cancer. Here we show that more than two-thirds of supratentorial ependymomas contain oncogenic fusions between RELA, the principal effector of canonical NF-κB signalling, and an uncharacterized gene, C11orf95. In each case, C11orf95–RELA fusions resulted from chromothripsis involving chromosome 11q13.1. C11orf95–RELA fusion proteins translocated spontaneously to the nucleus to activate NF-κB target genes, and rapidly transformed neural stem cells—the cell of origin of ependymoma—to form these tumours in mice. Our data identify a highly recurrent genetic alteration of RELA in human cancer, and the C11orf95–RELA fusion protein as a potential therapeutic target in supratentorial ependymoma.

U1 small nuclear ribonucleoprotein complex and RNA splicing alterations in Alzheimer’s disease

Deposition of insoluble protein aggregates is a hallmark of neurodegenerative diseases. The universal presence of β-amyloid and tau in Alzheimer’s disease (AD) has facilitated advancement of the amyloid cascade and tau hypotheses that have dominated AD pathogenesis research and therapeutic development. However, the underlying etiology of the disease remains to be fully elucidated. Here we report a comprehensive study of the human brain-insoluble proteome in AD by mass spectrometry. We identify 4,216 proteins, among which 36 proteins accumulate in the disease, including U1-70K and other U1 small nuclear ribonucleoprotein (U1 snRNP) spliceosome components. Similar accumulations in mild cognitive impairment cases indicate that spliceosome changes occur in early stages of AD. Multiple U1 snRNP subunits form cytoplasmic tangle-like structures in AD but not in other examined neurodegenerative disorders, including Parkinson disease and frontotemporal lobar degeneration. Comparison of RNA from AD and control brains reveals dysregulated RNA processing with accumulation of unspliced RNA species in AD, including myc box-dependent-interacting protein 1, clusterin, and presenilin-1. U1-70K knockdown or antisense oligonucleotide inhibition of U1 snRNP increases the protein level of amyloid precursor protein. Thus, our results demonstrate unique U1 snRNP pathology and implicate abnormal RNA splicing in AD pathogenesis.

JUMP: a tag-based database search tool for peptide identification with high sensitivity and accuracy

Database search programs are essential tools for identifying peptides via mass spectrometry (MS) in shotgun proteomics. Simultaneously achieving high sensitivity and high specificity during a database search is crucial for improving proteome coverage. Here we present JUMP, a new hybrid database search program that generates amino acid tags and ranks peptide spectrum matches (PSMs) by an integrated score from the tags and pattern matching. In a typical run of liquid chromatography coupled with high-resolution tandem MS, more than 95% of MS/MS spectra can generate at least one tag, whereas the remaining spectra are usually too poor to derive genuine PSMs. To enhance search sensitivity, the JUMP program enables the use of tags as short as one amino acid. Using a target-decoy strategy, we compared JUMP with other programs (e.g. SEQUEST, Mascot, PEAKS DB, and InsPecT) in the analysis of multiple datasets and found that JUMP outperformed these preexisting programs. JUMP also permitted the analysis of multiple co-fragmented peptides from “mixture spectra” to further increase PSMs. In addition, JUMP-derived tags allowed partial de novo sequencing and facilitated the unambiguous assignment of modified residues. In summary, JUMP is an effective database search algorithm complementary to current search programs.

Systematic optimization of long gradient chromatography mass spectrometry for deep analysis of brain proteome.

The development of high-resolution liquid chromatography (LC) is essential for improving the sensitivity and throughput of mass spectrometry (MS)-based proteomics. Here we present systematic optimization of a long gradient LC–MS/MS platform to enhance protein identification from a complex mixture. The platform employed an in-house fabricated, reverse-phase long column (100 μm × 150 cm, 5 μm C18 beads) coupled to Q Exactive MS. The column was capable of achieving a peak capacity of ∼700 in a 720 min gradient of 10–45% acetonitrile. The optimal loading level was ∼6 μg of peptides, although the column allowed loading as many as 20 μg. Gas-phase fractionation of peptide ions further increased the number of peptide identification by ∼10%. Moreover, the combination of basic pH LC prefractionation with the long gradient LC–MS/MS platform enabled the identification of 96 127 peptides and 10 544 proteins at 1% protein false discovery rate in a post-mortem brain sample of Alzheimer’s disease. Because deep RNA sequencing of the same specimen suggested that ∼16 000 genes were expressed, the current analysis covered more than 60% of the expressed proteome. Further improvement strategies of the LC/LC–MS/MS platform were also discussed.

Refined phosphopeptide enrichment by phosphate additive and the analysis of human brain phosphoproteome.

Alzheimers disease (AD) is the most common form of dementia, characterized by progressive loss of cognitive function. One of the pathological hallmarks of AD is the formation of neurofibrillary tangles composed of abnormally hyperphosphorylated tau protein, but global deregulation of protein phosphorylation in AD is not well analyzed. Here, we report a pilot investigation of AD phosphoproteome by titanium dioxide enrichment coupled with high resolution LC‐MS/MS. During the optimization of the enrichment method, we found that phosphate ion at a low concentration (e.g. 1 mM) worked efficiently as a nonphosphopeptide competitor to reduce background. The procedure was further tuned with respect to peptide‐to‐bead ratio, phosphopeptide recovery, and purity. Using this refined method and 9 h LC‐MS/MS, we analyzed phosphoproteome in one milligram of digested AD brain lysate, identifying 5243 phosphopeptides containing 3715 nonredundant phosphosites on 1455 proteins, including 31 phosphosites on the tau protein. This modified enrichment method is simple and highly efficient. The AD case study demonstrates its feasibility of dissecting phosphoproteome in a limited amount of postmortem human brain. All MS data have been deposited in the ProteomeXchange with identifier PXD001180 (http://proteomecentral.proteomexchange.org/dataset/PXD001180).

Sequential Elution Interactome Analysis of the Mind Bomb 1 Ubiquitin Ligase Reveals a Novel Role in Dendritic Spine Outgrowth

The mind bomb 1 (Mib1) ubiquitin ligase is essential for controlling metazoan development by Notch signaling and possibly the Wnt pathway. It is also expressed in postmitotic neurons and regulates neuronal morphogenesis and synaptic activity by mechanisms that are largely unknown. We sought to comprehensively characterize the Mib1 interactome and study its potential function in neuron development utilizing a novel sequential elution strategy for affinity purification, in which Mib1 binding proteins were eluted under different stringency and then quantified by the isobaric labeling method. The strategy identified the Mib1 interactome with both deep coverage and the ability to distinguish high-affinity partners from low-affinity partners. A total of 817 proteins were identified during the Mib1 affinity purification, including 56 high-affinity partners and 335 low-affinity partners, whereas the remaining 426 proteins are likely copurified contaminants or extremely weak binding proteins. The analysis detected all previously known Mib1-interacting proteins and revealed a large number of novel components involved in Notch and Wnt pathways, endocytosis and vesicle transport, the ubiquitin-proteasome system, cellular morphogenesis, and synaptic activities. Immunofluorescence studies further showed colocalization of Mib1 with five selected proteins: the Usp9x (FAM) deubiquitinating enzyme, alpha-, beta-, and delta-catenins, and CDKL5. Mutations of CDKL5 are associated with early infantile epileptic encephalopathy-2 (EIEE2), a severe form of mental retardation. We found that the expression of Mib1 down-regulated the protein level of CDKL5 by ubiquitination, and antagonized CDKL5 function during the formation of dendritic spines. Thus, the sequential elution strategy enables biochemical characterization of protein interactomes; and Mib1 analysis provides a comprehensive interactome for investigating its role in signaling networks and neuronal development.

Extensive Peptide Fractionation and y1 Ion-Based Interference Detection Method for Enabling Accurate Quantification by Isobaric Labeling and Mass Spectrometry

Isobaric labeling quantification by mass spectrometry (MS) has emerged as a powerful technology for multiplexed large-scale protein profiling, but measurement accuracy in complex mixtures is confounded by the interference from coisolated ions, resulting in ratio compression. Here we report that the ratio compression can be essentially resolved by the combination of pre-MS peptide fractionation, MS2-based interference detection, and post-MS computational interference correction. To recapitulate the complexity of biological samples, we pooled tandem mass tag (TMT)-labeled Escherichia coli peptides at 1:3:10 ratios and added in ∼20-fold more rat peptides as background, followed by the analysis of two-dimensional liquid chromatography (LC)-MS/MS. Systematic investigation shows that quantitative interference was impacted by LC fractionation depth, MS isolation window, and peptide loading amount. Exhaustive fractionation (320 × 4 h) can nearly eliminate the interference and achieve results comparable to the MS3-based method. Importantly, the interference in MS2 scans can be estimated by the intensity of contaminated y1 product ions, and we thus developed an algorithm to correct reporter ion ratios of tryptic peptides. Our data indicate that intermediate fractionation (40 × 2 h) and y1 ion-based correction allow accurate and deep TMT profiling of more than 10 000 proteins, which represents a straightforward and affordable strategy in isobaric labeling proteomics.

The neoepitope landscape in pediatric cancers

BackgroundNeoepitopes derived from tumor-specific somatic mutations are promising targets for immunotherapy in childhood cancers. However, the potential for such therapies in targeting these epitopes remains uncertain due to a lack of knowledge of the neoepitope landscape in childhood cancer. Studies to date have focused primarily on missense mutations without exploring gene fusions, which are a major class of oncogenic drivers in pediatric cancer.MethodsWe developed an analytical workflow for identification of putative neoepitopes based on somatic missense mutations and gene fusions using whole-genome sequencing data. Transcriptome sequencing data were incorporated to interrogate the expression status of the neoepitopes.ResultsWe present the neoepitope landscape of somatic alterations including missense mutations and oncogenic gene fusions identified in 540 childhood cancer genomes and transcriptomes representing 23 cancer subtypes. We found that 88% of leukemias, 78% of central nervous system tumors, and 90% of solid tumors had at least one predicted neoepitope. Mutation hotspots in KRAS and histone H3 genes encode potential epitopes in multiple patients. Additionally, the ETV6-RUNX1 fusion was found to encode putative neoepitopes in a high proportion (69.6%) of the pediatric leukemia harboring this fusion.ConclusionsOur study presents a comprehensive repertoire of potential neoepitopes in childhood cancers, and will facilitate the development of immunotherapeutic approaches designed to exploit them. The source code of the workflow is available at GitHub (https://github.com/zhanglabstjude/neoepitope).

Discrete roles and bifurcation of PTEN signaling and mTORC1-mediated anabolic metabolism underlie IL-7–driven B lymphopoiesis

PTEN-PI3K and IL-7R–mTORC1–Myc are two discrete signaling axes driving B cell development. Interleukin-7 (IL-7) drives early B lymphopoiesis, but the underlying molecular circuits remain poorly understood, especially how Stat5 (signal transducer and activator of transcription 5)–dependent and Stat5-independent pathways contribute to this process. Combining transcriptome and proteome analyses and mouse genetic models, we show that IL-7 promotes anabolic metabolism and biosynthetic programs in pro-B cells. IL-7–mediated activation of mTORC1 (mechanistic target of rapamycin complex 1) supported cell proliferation and metabolism in a Stat5-independent, Myc-dependent manner but was largely dispensable for cell survival or Rag1 and Rag2 gene expression. mTORC1 was also required for Myc-driven lymphomagenesis. PI3K (phosphatidylinositol 3-kinase) and mTORC1 had discrete effects on Stat5 signaling and independently controlled B cell development. PI3K was actively suppressed by PTEN (phosphatase and tensin homolog) in pro-B cells to ensure proper IL-7R expression, Stat5 activation, heavy chain rearrangement, and cell survival, suggesting the unexpected bifurcation of the classical PI3K-mTOR signaling. Together, our integrative analyses establish IL-7R–mTORC1–Myc and PTEN-mediated PI3K suppression as discrete signaling axes driving B cell development, with differential effects on IL-7R–Stat5 signaling.

Target-Decoy-Based False Discovery Rate Estimation for Large-Scale Metabolite Identification

Metabolite identification is a crucial step in mass spectrometry (MS)-based metabolomics. However, it is still challenging to assess the confidence of assigned metabolites. We report a novel method for estimating the false discovery rate (FDR) of metabolite assignment with a target-decoy strategy, in which the decoys are generated through violating the octet rule of chemistry by adding small odd numbers of hydrogen atoms. The target-decoy strategy was integrated into JUMPm, an automated metabolite identification pipeline for large-scale MS analysis and was also evaluated with two other metabolomics tools, mzMatch and MZmine 2. The reliability of FDR calculation was examined by false data sets, which were simulated by altering MS1 or MS2 spectra. Finally, we used the JUMPm pipeline coupled to the target-decoy strategy to process unlabeled and stable-isotope-labeled metabolomic data sets. The results demonstrate that the target-decoy strategy is a simple and effective method for evaluating the confidence of high-throughput metabolite identification.