Shift of the insoluble content of the proteome in the aging mouse brain.

During aging, the cellular response to unfolded proteins is believed to decline, resulting in diminished proteostasis. In model organisms, such as Caenorhabditis elegans, proteostatic decline with age has been linked to proteome solubility shifts and the onset of protein aggregation. However, this correlation has not been extensively characterized in aging mammals. To uncover age-dependent changes in the insoluble portion of a mammalian proteome, we analyzed the detergent-insoluble fraction of mouse brain tissue by mass spectrometry. We identified a group of 171 proteins, including the small heat shock protein α-crystallin, that become enriched in the detergent-insoluble fraction obtained from old mice. To enhance our ability to detect features associated with proteins in that fraction, we complemented our data with a meta-analysis of studies reporting the detergent-insoluble proteins in various mouse models of aging and neurodegeneration. Strikingly, insoluble proteins from young and old mice are distinct in several features in our study and across the collected literature data. In younger mice, proteins are more likely to be disordered, part of membraneless organelles, and involved in RNA binding. These traits become less prominent with age, as an increased number of structured proteins enter the pellet fraction. This analysis suggests that age-related changes to proteome organization lead a group of proteins with specific features to become detergent-insoluble. Importantly, these features are not consistent with those associated with proteins driving membraneless organelle formation. We see no evidence in our system of a general increase of condensate proteins in the detergent-insoluble fraction with age.

Statistical Testing for Protein Equivalence Identifies Core Functional Modules Conserved across 360 Cancer Cell Lines and Presents a General Approach to Investigating Biological Systems.

Quantitative proteomics has enhanced our capability to study protein dynamics and their involvement in disease using various techniques, including statistical testing, to discern the significant differences between conditions. While most focus is on what is different between conditions, exploring similarities can provide valuable insights. However, exploring similarities directly from the analyte level, such as proteins, genes, or metabolites, is not a standard practice and is not widely adopted. In this study, we propose a statistical framework called QuEStVar (Quantitative Exploration of Stability and Variability through statistical hypothesis testing), enabling the exploration of quantitative stability and variability of features with a combined statistical framework. QuEStVar utilizes differential and equivalence testing to expand statistical classifications of analytes when comparing conditions. We applied our method to an extensive data set of cancer cell lines and revealed a quantitatively stable core proteome across diverse tissues and cancer subtypes. The functional analysis of this set of proteins highlighted the molecular mechanism of cancer cells to maintain constant conditions of the tumorigenic environment via biological processes, including transcription, translation, and nucleocytoplasmic transport.

ASAP─Automated Sonication-Free Acid-Assisted Proteomes─from Cells and FFPE Tissues.

Formalin-fixed, paraffin-embedded (FFPE) tissues are an invaluable resource for retrospective studies, but protein extraction and subsequent sample processing steps have been shown to be challenging for mass spectrometry (MS) analysis. Streamlined high-throughput sample preparation workflows are essential for efficient peptide extraction from complex clinical specimens such as fresh frozen tissues or FFPE. Overall, proteome analysis has gained significant improvements in the instrumentation, acquisition methods, sample preparation workflows, and analysis pipelines, yet even the most recent FFPE workflows remain complex and are not readily scalable. Here, we present an optimized workflow for automated sonication-free acid-assisted proteome (ASAP) extraction from FFPE sections. ASAP enables efficient protein extraction from FFPE specimens, achieving similar proteome coverage as established methods using expensive sonicators, resulting in reduced sample processing time. The broad applicability of ASAP on archived pediatric tumor FFPE specimens resulted in high-quality data with increased proteome coverage and quantitative reproducibility. Our study demonstrates the practicality and superiority of the ASAP workflow as a streamlined, time- and cost-effective pipeline for high-throughput FFPE proteomics of clinical specimens.

SQuAPP-simple quantitative analysis of proteins and PTMs.

SUMMARY: The comprehensive analysis of the proteome and its modulation by post-translational modification (PTM) is increasingly used in biological and biomedical studies. As a result, proteomics data analysis is ever more carried out by scientists with limited expertise in this type of data. While excellent software solutions for comprehensive and rigorous analysis of quantitative proteomic data exist, most are complex and not well suited for non-proteomics scientists. Integrative analysis of multi-level proteomics data on protein and diverse PTMs, like phosphorylation or proteolytic processing, remains particularly challenging and inaccessible to most biologists. To fill this void, we developed SQuAPP, an R-Shiny web-based analysis pipeline for the quantitative analysis of proteomic data. SQuAPP uses a streamlined workflow model to guide expert and novice users through quality control, data pre-processing, statistical analysis and visualization steps. Processing the protein, peptide and PTM datasets in parallel and their quantitative integration enable rapid identification of protein-level-independent modulation of protein modifications and intuitive interpretation of dynamic dependencies between different protein modifications. AVAILABILITY AND IMPLEMENTATION: SQuAPP is available at http://squapp.langelab.org/. The source code and local setup instructions can be accessed from https://github.com/LangeLab/SQuAPP.

Positional proteomics: is the technology ready to study clinical cohorts?

INTRODUCTION: Positional proteomics provides proteome-wide information on protein termini and their modifications, uniquely enabling unambiguous identification of site-specific, limited proteolysis. Such proteolytic cleavage irreversibly modifies protein sequences resulting in new proteoforms with distinct protease-generated neo-N and C-termini and altered localization and activity. Misregulated proteolysis is implicated in a wide variety of human diseases. Protein termini, therefore, constitute a huge, largely unexplored source of specific analytes that provides a deep view into the functional proteome and a treasure trove for biomarkers. AREAS COVERED: We briefly review principal approaches to define protein termini and discuss recent advances in method development. We further highlight the potential of positional proteomics to identify and trace specific proteoforms, with a focus on proteolytic processes altered in disease. Lastly, we discuss current challenges and potential for applying positional proteomics in biomarker and pre-clinical research. EXPERT OPINION: Recent developments in positional proteomics have provided significant advances in sensitivity and throughput. In-depth analysis of proteolytic processes in clinical cohorts thus appears feasible in the near future. We argue that this will provide insights into the functional state of the proteome and offer new opportunities to utilize proteolytic processes altered or targeted in disease as specific diagnostic, prognostic and companion biomarkers.

Adaptation of the Th-MYCN Mouse Model of Neuroblastoma for Evaluation of Disseminated Disease.

High-risk neuroblastoma remains a profound clinical challenge that requires eradication of neuroblastoma cells from a variety of organ sites, including bone marrow, liver, and CNS, to achieve a cure. While preclinical modeling is a powerful tool for the development of novel cancer therapies, the lack of widely available models of metastatic neuroblastoma represents a significant barrier to the development of effective treatment strategies. To address this need, we report a novel luciferase-expressing derivative of the widely used Th-MYCN mouse. While our model recapitulates the non-metastatic neuroblastoma development seen in the parental transgenic strain, transplantation of primary tumor cells from disease-bearing mice enables longitudinal monitoring of neuroblastoma growth at distinct sites in immune-deficient or immune-competent recipients. The transplanted tumors retain GD2 expression through many rounds of serial transplantation and are sensitive to GD2-targeted immune therapy. With more diverse tissue localization than is seen with human cell line-derived xenografts, this novel model for high-risk neuroblastoma could contribute to the optimization of immune-based treatments for this deadly disease.

Sensitive Identification of Known and Unknown Protease Activities by Unsupervised Linear Motif Deconvolution.

The cleavage-site specificities for many proteases are not well understood, restricting the utility of supervised classification methods. We present an algorithm and web interface to overcome this limitation through the unsupervised detection of overrepresented patterns in protein sequence data, providing insight into the mixture of protease activities contributing to a complex system. Here, we apply the RObust LInear Motif Deconvolution (RoLiM) algorithm to confidently detect substrate cleavage patterns for SARS-CoV-2 MPro protease in the N-terminome data of an infected human cell line. Using mass spectrometry-based peptide data from a case-control comparison of 341 primary urothelial bladder cancer cases and 110 controls, we identified distinct sequence motifs indicative of increased matrix metallopeptidase activity in urine from cancer patients. The evaluation of N-terminal peptides from patient plasma post-chemotherapy detected novel granzyme B/corin activity. RoLiM will enhance the unbiased investigation of peptide sequences to establish the composition of known and uncharacterized protease activities in biological systems. RoLiM is available at http://langelab.org/rolim/.

A cross-standardized flow cytometry platform to assess phenotypic stability in precursor B-cell acute lymphoblastic leukemia (B-ALL) xenografts.

With the continued poor outcome of relapsed acute lymphoblastic leukemia (ALL), new patient-specific approaches for disease progression monitoring and therapeutic intervention are urgently needed. Patient-derived xenografts (PDX) of primary ALL in immune-deficient mice have become a powerful tool for studying leukemia biology and therapy response. In PDX mice, the immunophenotype of the patient's leukemia is commonly believed to be stably propagated. In patients, however, the surface marker expression profile of the leukemic population often displays poorly understood immunophenotypic shifts during chemotherapy and ALL progression. We therefore developed a translational flow cytometry platform to study whether the patient-specific immunophenotype is faithfully recapitulated in PDX mice. To enable valid assessment of immunophenotypic stability and subpopulation complexity of the patient's leukemia after xenotransplantation, we comprehensively immunophenotyped diagnostic B-ALL from children and their matched PDX using identical, clinically standardized flow protocols and instrument settings. This cross-standardized approach ensured longitudinal stability and cross-platform comparability of marker expression intensity at high phenotyping depth. This analysis revealed readily detectable changes to the patient leukemia-associated immunophenotype (LAIP) after xenotransplantation. To further investigate the mechanism underlying these complex immunophenotypic shifts, we applied an integrated analytical approach that combined clinical phenotyping depth and high analytical sensitivity with unbiased high-dimensional algorithm-based analysis. This high-resolution analysis revealed that xenotransplantation achieves patient-specific propagation of phenotypically stable B-ALL subpopulations and that the immunophenotypic shifts observed at the level of bulk leukemia were consistent with changes in underlying subpopulation abundance. By incorporating the immunophenotypic complexity of leukemic populations, this novel cross-standardized analytical platform could greatly expand the utility of PDX for investigating ALL progression biology and assessing therapies directed at eliminating relapse-driving leukemic subpopulations.

Detectability of Biotin Tags by LC-MS/MS.

The high affinity of biotin to streptavidin has made it one of the most widely used affinity tags in proteomics. Early methods used biotin for enrichment alone and mostly ignored the biotin-labeled peptide. Recent advances in labeling have led to an increase in biotinylation efficiency and shifted the interest to the detection of the site of biotinylation. This has increased the confidence in identification and provided additional structural information, yet it requires the efficient release of the biotinylated protein/peptide and the sensitive separation and detection of biotinylated peptides by LC-MS/MS. Despite its long use in affinity proteomics, the effect of biotinylation on the chromatographic, ionization, and fragmentation behavior and the ultimate detection of peptides is not well understood. To address this, we compare two commercially available biotin labels, EZ-Link Sulfo-NHS-Biotin and Sulfo-NHS-SS-Biotin, the latter containing a labile linker to efficiently release biotin to determine the effects of peptide modification on peptide detection. We describe an increase in the hydrophobicity and charge reduction with an increasing number of biotin labels attached. On the basis of our data, we recommend gradient optimization to account for more hydrophobic biotinylated peptides and include singly charged precursors to account for charge reduction by biotin.

Sensitive Determination of Proteolytic Proteoforms in Limited Microscale Proteome Samples.

Protein N termini unambiguously identify truncated, alternatively translated or modified proteoforms with distinct functions and reveal perturbations in disease. Selective enrichment of N-terminal peptides is necessary to achieve proteome-wide coverage for unbiased identification of site-specific regulatory proteolytic processing and protease substrates. However, many proteolytic processes are strictly confined in time and space and therefore can only be analyzed in minute samples that provide insufficient starting material for current enrichment protocols. Here we present High-efficiency Undecanal-based N Termini EnRichment (HUNTER), a robust, sensitive and scalable method for the analysis of previously inaccessible microscale samples. HUNTER achieved identification of >1000 N termini from as little as 2 µg raw HeLa cell lysate. Broad applicability is demonstrated by the first N-terminome analysis of sorted human primary immune cells and enriched mitochondrial fractions from pediatric cancer patients, as well as protease substrate identification from individual Arabidopsis thaliana wild type and Vacuolar Processing Enzyme-deficient mutant seedlings. We further implemented the workflow on a liquid handling system and demonstrate the feasibility of clinical degradomics by automated processing of liquid biopsies from pediatric cancer patients.

Fold-Change Compression: An Unexplored But Correctable Quantitative Bias Caused by Nonlinear Electrospray Ionization Responses in Untargeted Metabolomics.

The nonlinear signal response of electrospray ionization (ESI) presents a critical limitation for mass spectrometry (MS)-based quantitative analysis. In the field of metabolomics research, this issue has largely remained unaddressed; MS signal intensities are usually directly used to calculate fold changes for quantitative comparison. In this work, we demonstrate that, due to the nonlinear ESI response, signal intensity ratios of a metabolic feature calculated between two samples may not reflect their real metabolic concentration ratios (i.e., fold-change compression), implying that conventional fold-change calculations directly using MS signal intensities can be misleading. In this regard, we developed a quality control (QC) sample-based signal calibration workflow to overcome the quantitative bias caused by the nonlinear ESI response. In this workflow, calibration curves for every metabolic feature are first established using a QC sample injected in serial injection volumes. The MS signals of each metabolic feature are then calibrated to their equivalent QC injection volumes for comparative analysis. We demonstrated this novel workflow in a targeted metabolite analysis, showing that the accuracy of fold-change calculations can be significantly improved. Furthermore, in a metabolomic comparison of the bone marrow interstitial fluid samples from leukemia patients before and after chemotherapy, an additional 59 significant metabolic features were found with fold changes larger than 1.5, and an additional 97 significant metabolic features had fold changes corrected by more than 0.1. This work enables high-quality quantitative analysis in untargeted metabolomics, thus providing more confident biological hypotheses generation.

Origins and clinical relevance of proteoforms in pediatric malignancies.

INTRODUCTION: Cancer changes the proteome in complex ways that reach well beyond simple changes in protein abundance. Genomic and transcriptional variations and post-translational protein modification create functional variants of a protein, known as proteoforms. Childhood cancers have fewer genomic alterations but show equally dramatic phenotypic changes as malignant cells in adults. Therefore, unraveling the complexities of the proteome is even more important in pediatric malignancies. Areas covered: In this review, the biological origins of proteoforms and technological advancements in the study of proteoforms are discussed. Particular emphasis is given to their implication in childhood malignancies and the critical role of cancer-specific proteoforms for the next generation of cancer therapies and diagnostics. Expert opinion: Recent advancements in technology have led to a better understanding of the underlying mechanisms of tumorigenesis. This has been critical for the development of more effective and less harmful treatments that are based on direct targeting of altered proteins and deregulated pathways. As proteome coverage and the ability to detect complex proteoforms increase, the most need for change is in data compilation and database availability to mediate high-level data analysis and allow for better functional annotation of proteoforms.

LysargiNase mirrors trypsin for protein C-terminal and methylation-site identification.

To improve proteome coverage and protein C-terminal identification, we characterized the Methanosarcina acetivorans thermophilic proteinase LysargiNase, which cleaves before lysine and arginine up to 55 °C. Unlike trypsin, LysargiNase-generated peptides had N-terminal lysine or arginine residues and fragmented with b ion-dominated spectra. This improved protein C terminal-peptide identification and several arginine-rich phosphosite assignments. Notably, cleavage also occurred at methylated or dimethylated lysine and arginine, facilitating detection of these epigenetic modifications.

Network analyses reveal pervasive functional regulation between proteases in the human protease web.

Proteolytic processing is an irreversible posttranslational modification affecting a large portion of the proteome. Protease-cleaved mediators frequently exhibit altered activity, and biological pathways are often regulated by proteolytic processing. Many of these mechanisms have not been appreciated as being protease-dependent, and the potential in unraveling a complex new dimension of biological control is increasingly recognized. Proteases are currently believed to act individually or in isolated cascades. However, conclusive but scattered biochemical evidence indicates broader regulation of proteases by protease and inhibitor interactions. Therefore, to systematically study such interactions, we assembled curated protease cleavage and inhibition data into a global, computational representation, termed the protease web. This revealed that proteases pervasively influence the activity of other proteases directly or by cleaving intermediate proteases or protease inhibitors. The protease web spans four classes of proteases and inhibitors and so links both recently and classically described protease groups and cascades, which can no longer be viewed as operating in isolation in vivo. We demonstrated that this observation, termed reachability, is robust to alterations in the data and will only increase in the future as additional data are added. We further show how subnetworks of the web are operational in 23 different tissues reflecting different phenotypes. We applied our network to develop novel insights into biologically relevant protease interactions using cell-specific proteases of the polymorphonuclear leukocyte as a system. Predictions from the protease web on the activity of matrix metalloproteinase 8 (MMP8) and neutrophil elastase being linked by an inactivating cleavage of serpinA1 by MMP8 were validated and explain perplexing Mmp8-/- versus wild-type polymorphonuclear chemokine cleavages in vivo. Our findings supply systematically derived and validated evidence for the existence of the protease web, a network that affects the activity of most proteases and thereby influences the functional state of the proteome and cell activity.

Proteome TopFIND 3.0 with TopFINDer and PathFINDer: database and analysis tools for the association of protein termini to pre- and post-translational events.

The knowledgebase TopFIND is an analysis platform focussed on protein termini, their origin, modification and hence their role on protein structure and function. Here, we present a major update to TopFIND, version 3, which includes a 70% increase in the underlying data to now cover a 90,696 proteins, 165,044 N-termini, 130,182 C-termini, 14,382 cleavage sites and 33,209 substrate cleavages in H. sapiens, M. musculus, A. thaliana, S. cerevisiae and E. coli. New features include the mapping of protein termini and cleavage entries across protein isoforms and significantly, the mapping of protein termini originating from alternative transcription and alternative translation start sites. Furthermore, two analysis tools for complex data analysis based on the TopFIND resource are now available online: TopFINDer, the TopFIND ExploRer, characterizes and annotates proteomics-derived N- or C-termini sets for their origin, sequence context and implications for protein structure and function. Neo-termini are also linked to associated proteases. PathFINDer identifies indirect connections between a protease and list of substrates or termini thus supporting the evaluation of complex proteolytic processes in vivo. To demonstrate the utility of the tools, a recent N-terminomics data set of inflamed murine skin has been re-analyzed. In re-capitulating the major findings originally performed manually, this validates the utility of these new resources. The point of entry for the resource is http://clipserve.clip.ubc.ca/topfind from where the graphical interface, all application programming interfaces (API) and the analysis tools are freely accessible.

Annotating N termini for the human proteome project: N termini and Nα-acetylation status differentiate stable cleaved protein species from degradation remnants in the human erythrocyte proteome.

A goal of the Chromosome-centric Human Proteome Project is to identify all human protein species. With 3844 proteins annotated as "missing", this is challenging. Moreover, proteolytic processing generates new protein species with characteristic neo-N termini that are frequently accompanied by altered half-lives, function, interactions, and location. Enucleated and largely void of internal membranes and organelles, erythrocytes are simple yet proteomically challenging cells due to the high hemoglobin content and wide dynamic range of protein concentrations that impedes protein identification. Using the N-terminomics procedure TAILS, we identified 1369 human erythrocyte natural and neo-N-termini and 1234 proteins. Multiple semitryptic N-terminal peptides exhibited improved mass spectrometric identification properties versus the intact tryptic peptide enabling identification of 281 novel erythrocyte proteins and six missing proteins identified for the first time in the human proteome. With an improved bioinformatics workflow, we developed a new classification system and the Terminus Cluster Score. Thereby we described a new stabilizing N-end rule for processed protein termini, which discriminates novel protein species from degradation remnants, and identified protein domain hot spots susceptible to cleavage. Strikingly, 68% of the N-termini were within genome-encoded protein sequences, revealing alternative translation initiation sites, pervasive endoproteolytic processing, and stabilization of protein fragments in vivo. The mass spectrometry proteomics data have been deposited to ProteomeXchange with the data set identifier .

TopFIND 2.0--linking protein termini with proteolytic processing and modifications altering protein function.

Protein termini provide critical insights into the functional state of individual proteins. With recent advances in specific proteomics approaches to enrich for N- and C-terminomes, the global analysis of whole terminomes at a proteome-wide scale is now possible. Information on the actual N- and C-termini of proteins in vivo and any post-translational modifications, including their generation by proteolytic processing, is rapidly accumulating. To access this information we present version 2.0 of TopFIND (http://clipserve.clip.ubc.ca/topfind), a knowledgebase for protein termini, terminus modifications and underlying proteolytic processing. Built on a protein-centric framework TopFIND covers five species: Homo sapiens, Mus musculus, Arabidopsis thaliana, Saccharomyces cerevisiae and Escherichia coli and incorporates information from curated community submissions, publications, UniProtKB and MEROPS. Emphasis is placed on the detailed description and classification of evidence supporting the reported identification of each cleavage site, terminus and modification. A suite of filters can be applied to select supporting evidence. A dynamic network representation of the relationship between proteases, their substrates and inhibitors as well as visualization of protease cleavage site specificities complements the information displayed. Hence, TopFIND supports in depth investigation of protein termini information to spark new hypotheses on protein function by correlating cleavage events and termini with protein domains and mutations.

The Eµ-Ret mouse is a novel model of hyperdiploid B-cell acute lymphoblastic leukemia.

The presence of supernumerary chromosomes is the only abnormality shared by all patients diagnosed with high-hyperdiploid B cell acute lymphoblastic leukemia (HD-ALL). Despite being the most frequently diagnosed pediatric leukemia, the lack of clonal molecular lesions and complete absence of appropriate experimental models have impeded the elucidation of HD-ALL leukemogenesis. Here, we report that for 23 leukemia samples isolated from moribund Eµ-Ret mice, all were characterized by non-random chromosomal gains, involving combinations of trisomy 9, 12, 14, 15, and 17. With a median gain of three chromosomes, leukemia emerged after a prolonged latency from a preleukemic B cell precursor cell population displaying more diverse aneuploidy. Transition from preleukemia to overt disease in Eµ-Ret mice is associated with acquisition of heterogeneous genomic abnormalities affecting the expression of genes implicated in pediatric B-ALL. The development of abnormal centrosomes in parallel with aneuploidy renders both preleukemic and leukemic cells sensitive to inhibitors of centrosome clustering, enabling targeted in vivo depletion of leukemia-propagating cells. This study reveals the Eµ-Ret mouse to be a novel tool for investigating HD-ALL leukemogenesis, including supervision and selection of preleukemic aneuploid clones by the immune system and identification of vulnerabilities that could be targeted to prevent relapse.

RNA Polymerase II transcription independent of TBP in murine embryonic stem cells.

Transcription by RNA Polymerase II (Pol II) is initiated by the hierarchical assembly of the pre-initiation complex onto promoter DNA. Decades of research have shown that the TATA-box binding protein (TBP) is essential for Pol II loading and initiation. Here, we report instead that acute depletion of TBP in mouse embryonic stem cells has no global effect on ongoing Pol II transcription. In contrast, acute TBP depletion severely impairs RNA Polymerase III initiation. Furthermore, Pol II transcriptional induction occurs normally upon TBP depletion. This TBP-independent transcription mechanism is not due to a functional redundancy with the TBP paralog TRF2, though TRF2 also binds to promoters of transcribed genes. Rather, we show that the TFIID complex can form and, despite having reduced TAF4 and TFIIA binding when TBP is depleted, the Pol II machinery is sufficiently robust in sustaining TBP-independent transcription.

Targetable lesions and proteomes predict therapy sensitivity through disease evolution in pediatric acute lymphoblastic leukemia.

Childhood acute lymphoblastic leukemia (ALL) genomes show that relapses often arise from subclonal outgrowths. However, the impact of clonal evolution on the actionable proteome and response to targeted therapy is not known. Here, we present a comprehensive retrospective analysis of paired ALL diagnosis and relapsed specimen. Targeted next generation sequencing and proteome analysis indicate persistence of actionable genome variants and stable proteomes through disease progression. Paired viably-frozen biopsies show high correlation of drug response to variant-targeted therapies but in vitro selectivity is low. Proteome analysis prioritizes PARP1 as a pan-ALL target candidate needed for survival following cellular stress; diagnostic and relapsed ALL samples demonstrate robust sensitivity to treatment with two PARP1/2 inhibitors. Together, these findings support initiating prospective precision oncology approaches at ALL diagnosis and emphasize the need to incorporate proteome analysis to prospectively determine tumor sensitivities, which are likely to be retained at disease relapse.