Multilayered regulation of autophagy by the Atg1 kinase orchestrates spatial and temporal control of autophagosome formation.

Autophagy is a conserved intracellular degradation pathway exerting various cytoprotective and homeostatic functions by using de novo double-membrane vesicle (autophagosome) formation to target a wide range of cytoplasmic material for vacuolar/lysosomal degradation. The Atg1 kinase is one of its key regulators, coordinating a complex signaling program to orchestrate autophagosome formation. Combining in vitro reconstitution and cell-based approaches, we demonstrate that Atg1 is activated by lipidated Atg8 (Atg8-PE), stimulating substrate phosphorylation along the growing autophagosomal membrane. Atg1-dependent phosphorylation of Atg13 triggers Atg1 complex dissociation, enabling rapid turnover of Atg1 complex subunits at the pre-autophagosomal structure (PAS). Moreover, Atg1 recruitment by Atg8-PE self-regulates Atg8-PE levels in the growing autophagosomal membrane by phosphorylating and thus inhibiting the Atg8-specific E2 and E3. Our work uncovers the molecular basis for positive and negative feedback imposed by Atg1 and how opposing phosphorylation and dephosphorylation events underlie the spatiotemporal regulation of autophagy.

A gas phase fractionation acquisition scheme integrating ion mobility for rapid diaPASEF library generation.

Data independent acquisition (DIA/SWATH) MS is a primary strategy in quantitative proteomics. diaPASEF is a recent adaptation using trapped ion mobility spectrometry (TIMS) to improve selectivity/sensitivity. Complex DIA spectra are typically analyzed with reference to spectral libraries. The best-established method for generating libraries uses offline fractionation to increase depth of coverage. More recently strategies for spectral library generation based on gas phase fractionation (GPF), where a representative sample is injected serially using narrow DIA windows that cover different mass ranges of the complete precursor space, have been introduced that performed comparably to deep offline fractionation-based libraries. We investigated whether an analogous GPF-based approach that accounts for the ion mobility (IM) dimension is useful for the analysis of diaPASEF data. We developed a rapid library generation approach using an IM-GPF acquisition scheme in the m/z versus 1/K0 space requiring seven injections of a representative sample and compared this with libraries generated by direct deconvolution-based analysis of diaPASEF data or by deep offline fractionation. We found that library generation by IM-GPF outperformed direct library generation from diaPASEF and had performance approaching that of the deep library. This establishes the IM-GPF scheme as a pragmatic approach to rapid library generation for analysis of diaPASEF data.

Rapid Profiling of Protein Complex Reorganization in Perturbed Systems.

Protein complexes constitute the primary functional modules of cellular activity. To respond to perturbations, complexes undergo changes in their abundance, subunit composition, or state of modification. Understanding the function of biological systems requires global strategies to capture this contextual state information. Methods based on cofractionation paired with mass spectrometry have demonstrated the capability for deep biological insight, but the scope of studies using this approach has been limited by the large measurement time per biological sample and challenges with data analysis. There has been little uptake of this strategy into the broader life science community despite its rich biological information content. We present a rapid integrated experimental and computational workflow to assess the reorganization of protein complexes across multiple cellular states. The workflow combines short gradient chromatography and DIA/SWATH mass spectrometry with a data analysis toolset to quantify changes in a complex organization. We applied the workflow to study the global protein complex rearrangements of THP-1 cells undergoing monocyte to macrophage differentiation and subsequent stimulation of macrophage cells with lipopolysaccharide. We observed substantial proteome reorganization on differentiation and less pronounced changes in macrophage stimulation. We establish our integrated differential pipeline for rapid and state-specific profiling of protein complex organization.

diaPASEF: parallel accumulation-serial fragmentation combined with data-independent acquisition.

Data-independent acquisition modes isolate and concurrently fragment populations of different precursors by cycling through segments of a predefined precursor m/z range. Although these selection windows collectively cover the entire m/z range, overall, only a few per cent of all incoming ions are isolated for mass analysis. Here, we make use of the correlation of molecular weight and ion mobility in a trapped ion mobility device (timsTOF Pro) to devise a scan mode that samples up to 100% of the peptide precursor ion current in m/z and mobility windows. We extend an established targeted data extraction workflow by inclusion of the ion mobility dimension for both signal extraction and scoring and thereby increase the specificity for precursor identification. Data acquired from whole proteome digests and mixed organism samples demonstrate deep proteome coverage and a high degree of reproducibility as well as quantitative accuracy, even from 10 ng sample amounts.

The protein landscape of chronic lymphocytic leukemia.

Many functional consequences of mutations on tumor phenotypes in chronic lymphocytic leukemia (CLL) are unknown. This may be in part due to a scarcity of information on the proteome of CLL. We profiled the proteome of 117 CLL patient samples with data-independent acquisition mass spectrometry and integrated the results with genomic, transcriptomic, ex vivo drug response, and clinical outcome data. We found trisomy 12, IGHV mutational status, mutated SF3B1, trisomy 19, del(17)(p13), del(11)(q22.3), mutated DDX3X and MED12 to influence protein expression (false discovery rate [FDR] = 5%). Trisomy 12 and IGHV status were the major determinants of protein expression variation in CLL as shown by principal-component analysis (1055 and 542 differentially expressed proteins, FDR = 5%). Gene set enrichment analyses of CLL with trisomy 12 implicated B-cell receptor (BCR)/phosphatidylinositol 3-kinase (PI3K)/AKT signaling as a tumor driver. These findings were supported by analyses of protein abundance buffering and protein complex formation, which identified limited protein abundance buffering and an upregulated protein complex involved in BCR, AKT, MAPK, and PI3K signaling in trisomy 12 CLL. A survey of proteins associated with trisomy 12/IGHV-independent drug response linked STAT2 protein expression with response to kinase inhibitors, including Bruton tyrosine kinase and mitogen-activated protein kinase kinase (MEK) inhibitors. STAT2 was upregulated in unmutated IGHV CLL and trisomy 12 CLL and required for chemokine/cytokine signaling (interferon response). This study highlights the importance of protein abundance data as a nonredundant layer of information in tumor biology and provides a protein expression reference map for CLL.

Diagnostics and correction of batch effects in large-scale proteomic studies: a tutorial.

Advancements in mass spectrometry-based proteomics have enabled experiments encompassing hundreds of samples. While these large sample sets deliver much-needed statistical power, handling them introduces technical variability known as batch effects. Here, we present a step-by-step protocol for the assessment, normalization, and batch correction of proteomic data. We review established methodologies from related fields and describe solutions specific to proteomic challenges, such as ion intensity drift and missing values in quantitative feature matrices. Finally, we compile a set of techniques that enable control of batch effect adjustment quality. We provide an R package, "proBatch", containing functions required for each step of the protocol. We demonstrate the utility of this methodology on five proteomic datasets each encompassing hundreds of samples and consisting of multiple experimental designs. In conclusion, we provide guidelines and tools to make the extraction of true biological signal from large proteomic studies more robust and transparent, ultimately facilitating reliable and reproducible research in clinical proteomics and systems biology.

From coarse to fine: the absolute Escherichia coli proteome under diverse growth conditions.

Accurate measurements of cellular protein concentrations are invaluable to quantitative studies of gene expression and physiology in living cells. Here, we developed a versatile mass spectrometric workflow based on data-independent acquisition proteomics (DIA/SWATH) together with a novel protein inference algorithm (xTop). We used this workflow to accurately quantify absolute protein abundances in Escherichia coli for > 2,000 proteins over > 60 growth conditions, including nutrient limitations, non-metabolic stresses, and non-planktonic states. The resulting high-quality dataset of protein mass fractions allowed us to characterize proteome responses from a coarse (groups of related proteins) to a fine (individual) protein level. Hereby, a plethora of novel biological findings could be elucidated, including the generic upregulation of low-abundant proteins under various metabolic limitations, the non-specificity of catabolic enzymes upregulated under carbon limitation, the lack of large-scale proteome reallocation under stress compared to nutrient limitations, as well as surprising strain-dependent effects important for biofilm formation. These results present valuable resources for the systems biology community and can be used for future multi-omics studies of gene regulation and metabolic control in E. coli.

Expression Dysregulation as a Mediator of Fitness Costs in Antibiotic Resistance.

Antimicrobial resistance (AMR) poses a threat to global health and the economy. Rifampicin-resistant Mycobacterium tuberculosis accounts for a third of the global AMR burden. Gaining the upper hand on AMR requires a deeper understanding of the physiology of resistance. AMR often results in a fitness cost in the absence of drug. Identifying the molecular mechanisms underpinning this cost could help strengthen future treatment regimens. Here, we used a collection of M. tuberculosis strains that provide an evolutionary and phylogenetic snapshot of rifampicin resistance and subjected them to genome-wide transcriptomic and proteomic profiling to identify key perturbations of normal physiology. We found that the clinically most common rifampicin resistance-conferring mutation, RpoB Ser450Leu, imparts considerable gene expression changes, many of which are mitigated by the compensatory mutation in RpoC Leu516Pro. However, our data also provide evidence for pervasive epistasis-the same resistance mutation imposed a different fitness cost and functionally distinct changes to gene expression in genetically unrelated clinical strains. Finally, we report a likely posttranscriptional modulation of gene expression that is shared in most of the tested strains carrying RpoB Ser450Leu, resulting in an increased abundance of proteins involved in central carbon metabolism. These changes contribute to a more general trend in which the disruption of the composition of the proteome correlates with the fitness cost of the RpoB Ser450Leu mutation in different strains.

Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses.

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is the main method for high-throughput identification and quantification of peptides and inferred proteins. Within this field, data-independent acquisition (DIA) combined with peptide-centric scoring, as exemplified by the technique SWATH-MS, has emerged as a scalable method to achieve deep and consistent proteome coverage across large-scale data sets. We demonstrate that statistical concepts developed for discovery proteomics based on spectrum-centric scoring can be adapted to large-scale DIA experiments that have been analyzed with peptide-centric scoring strategies, and we provide guidance on their application. We show that optimal tradeoffs between sensitivity and specificity require careful considerations of the relationship between proteins in the samples and proteins represented in the spectral library. We propose the application of a global analyte constraint to prevent the accumulation of false positives across large-scale data sets. Furthermore, to increase the quality and reproducibility of published proteomic results, well-established confidence criteria should be reported for the detected peptide queries, peptides and inferred proteins.

Complex-centric proteome profiling by SEC-SWATH-MS.

Proteins are major effectors and regulators of biological processes that can elicit multiple functions depending on their interaction with other proteins. The organization of proteins into macromolecular complexes and their quantitative distribution across these complexes is, therefore, of great biological and clinical significance. In this paper, we describe an integrated experimental and computational technique to quantify hundreds of protein complexes in a single operation. The method consists of size exclusion chromatography (SEC) to fractionate native protein complexes, SWATH/DIA mass spectrometry to precisely quantify the proteins in each SEC fraction, and the computational framework CCprofiler to detect and quantify protein complexes by error-controlled, complex-centric analysis using prior information from generic protein interaction maps. Our analysis of the HEK293 cell line proteome delineates 462 complexes composed of 2,127 protein subunits. The technique identifies novel sub-complexes and assembly intermediates of central regulatory complexes while assessing the quantitative subunit distribution across them. We make the toolset CCprofiler freely accessible and provide a web platform, SECexplorer, for custom exploration of the HEK293 proteome modularity.

AP-SWATH Reveals Direct Involvement of VCP/p97 in Integrated Stress Response Signaling Through Facilitating CReP/PPP1R15B Degradation.

The ubiquitin-directed AAA-ATPase VCP/p97 facilitates degradation of damaged or misfolded proteins in diverse cellular stress response pathways. Resolving the complexity of its interactions with partner and substrate proteins and understanding its links to stress signaling is therefore a major challenge. Here, we used affinity-purification SWATH mass spectrometry (AP-SWATH) to identify proteins that specifically interact with the substrate-trapping mutant, p97-E578Q. AP-SWATH identified differential interactions over a large detection range from abundant p97 cofactors to pathway-specific partners and individual ligases such as RNF185 and MUL1 that were trapped in p97-E578Q complexes. In addition, we identified various substrate proteins and candidates including the PP1 regulator CReP/PPP1R15B that dephosphorylates eIF2α and thus counteracts attenuation of translation by stress-kinases. We provide evidence that p97 with its Ufd1-Npl4 adapter ensures rapid constitutive turnover and balanced levels of CReP in unperturbed cells. Moreover, we show that p97-mediated degradation, together with a reduction in CReP synthesis, is essential for timely stress-induced reduction of CReP levels and, consequently, for robust eIF2α phosphorylation to enforce the stress response. Thus, our results demonstrate that p97 not only facilitates bulk degradation of misfolded proteins upon stress, but also directly modulates the integrated stress response at the level of signaling.

TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics.

Next-generation mass spectrometric (MS) techniques such as SWATH-MS have substantially increased the throughput and reproducibility of proteomic analysis, but ensuring consistent quantification of thousands of peptide analytes across multiple liquid chromatography-tandem MS (LC-MS/MS) runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we developed TRIC (http://proteomics.ethz.ch/tric/), a software tool that utilizes fragment-ion data to perform cross-run alignment, consistent peak-picking and quantification for high-throughput targeted proteomics. TRIC reduced the identification error compared to a state-of-the-art SWATH-MS analysis without alignment by more than threefold at constant recall while correcting for highly nonlinear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups. Thus, TRIC fills a gap in the pipeline for automated analysis of massively parallel targeted proteomics data sets.

Data-independent acquisition-based SWATH-MS for quantitative proteomics: a tutorial.

Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH-MS is a specific variant of data-independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH-MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH-MS data, a strategy based on peptide-centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH-MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH-MS data using peptide-centric scoring. Furthermore, concepts on how to improve SWATH-MS data acquisition, potential trade-offs of parameter settings and alternative data analysis strategies are discussed.

In Vivo and in Vitro Proteome Analysis of Human Immunodeficiency Virus (HIV)-1-infected, Human CD4+ T Cells.

Host-directed therapies against HIV-1 are thought to be critical for long term containment of the HIV-1 pandemic but remain elusive. Because HIV-1 infects and manipulates important effectors of both the innate and adaptive immune system, identifying modulations of the host cell systems in humans during HIV-1 infection may be crucial for the development of immune based therapies. Here, we quantified the changes of the proteome in human CD4+ T cells upon HIV-1 infection, both in vitro and in vivo A SWATH-MS approach was used to measure the proteome of human primary CD4+ T cells infected with HIV-1 in vitro as well as CD4+ T cells from HIV-1-infected patients with paired samples on and off antiretroviral treatment. In the in vitro experiment, the proteome of CD4+ T cells was quantified over a time course following HIV-1 infection. 1,725 host cell proteins and 4 HIV-1 proteins were quantified, with 145 proteins changing significantly during the time course. Changes in the proteome peaked 24 h after infection, concomitantly with significant HIV-1 protein production. In the in vivo branch of the study, CD4+ T cells from viremic patients and those with no detectable viral load after treatment were sorted, and the proteomes were quantified. We consistently detected 895 proteins, 172 of which were considered to be significantly different between the viremic patients and patients undergoing successful treatment. The proteome of the in vitro-infected CD4+ T cells was modulated on multiple functional levels, including TLR-4 signaling and the type 1 interferon signaling pathway. Perturbations in the type 1 interferon signaling pathway were recapitulated in CD4+ T cells from patients. The study shows that proteome maps generated by SWATH-MS indicate a range of functionally significant changes in the proteome of HIV-infected human CD4+ T cells. Exploring these perturbations in more detail may help identify new targets for immune based interventions.

Assessment of a method to characterize antibody selectivity and specificity for use in immunoprecipitation.

Antibodies are used in multiple cell biology applications, but there are no standardized methods to assess antibody quality-an absence that risks data integrity and reproducibility. We describe a mass spectrometry-based standard operating procedure for scoring immunoprecipitation antibody quality. We quantified the abundance of all the proteins in immunoprecipitates of 1,124 new recombinant antibodies for 152 chromatin-related human proteins by comparing normalized spectral abundance factors from the target antigen with those of all other proteins. We validated the performance of the standard operating procedure in blinded studies in five independent laboratories. Antibodies for which the target antigen or a member of its known protein complex was the most abundant protein were classified as 'IP gold standard'. This method generates quantitative outputs that can be stored and archived in public databases, and it represents a step toward a platform for community benchmarking of antibody quality.

Identification of a Set of Conserved Eukaryotic Internal Retention Time Standards for Data-independent Acquisition Mass Spectrometry.

Accurate knowledge of retention time (RT) in liquid chromatography-based mass spectrometry data facilitates peptide identification, quantification, and multiplexing in targeted and discovery-based workflows. Retention time prediction is particularly important for peptide analysis in emerging data-independent acquisition (DIA) experiments such as SWATH-MS. The indexed RT approach, iRT, uses synthetic spiked-in peptide standards (SiRT) to set RT to a unit-less scale, allowing for normalization of peptide RT between different samples and chromatographic set-ups. The obligatory use of SiRTs can be costly and complicates comparisons and data integration if standards are not included in every sample. Reliance on SiRTs also prevents the inclusion of archived mass spectrometry data for generation of the peptide assay libraries central to targeted DIA-MS data analysis. We have identified a set of peptide sequences that are conserved across most eukaryotic species, termed Common internal Retention Time standards (CiRT). In a series of tests to support the appropriateness of the CiRT-based method, we show: (1) the CiRT peptides normalized RT in human, yeast, and mouse cell lysate derived peptide assay libraries and enabled merging of archived libraries for expanded DIA-MS quantitative applications; (2) CiRTs predicted RT in SWATH-MS data within a 2-min margin of error for the majority of peptides; and (3) normalization of RT using the CiRT peptides enabled the accurate SWATH-MS-based quantification of 340 synthetic isotopically labeled peptides that were spiked into either human or yeast cell lysate. To automate and facilitate the use of these CiRT peptide lists or other custom user-defined internal RT reference peptides in DIA workflows, an algorithm was designed to automatically select a high-quality subset of datapoints for robust linear alignment of RT for use. Implementations of this algorithm are available for the OpenSWATH and Skyline platforms. Thus, CiRT peptides can be used alone or as a complement to SiRTs for RT normalization across peptide spectral libraries and in quantitative DIA-MS studies.

Quantifying protein interaction dynamics by SWATH mass spectrometry: application to the 14-3-3 system.

Protein complexes and protein interaction networks are essential mediators of most biological functions. Complexes supporting transient functions such as signal transduction processes are frequently subject to dynamic remodeling. Currently, the majority of studies on the composition of protein complexes are carried out by affinity purification and mass spectrometry (AP-MS) and present a static view of the system. For a better understanding of inherently dynamic biological processes, methods to reliably quantify temporal changes of protein interaction networks are essential. Here we used affinity purification combined with sequential window acquisition of all theoretical spectra (AP-SWATH) mass spectrometry to study the dynamics of the 14-3-3ß scaffold protein interactome after stimulation of the insulin-PI3K-AKT pathway. The consistent and reproducible quantification of 1,967 proteins across all stimulation time points provided insights into the 14-3-3ß interactome and its dynamic changes following IGF1 stimulation. We therefore establish AP-SWATH as a tool to quantify dynamic changes in protein-complex interaction networks.

Quantitative variability of 342 plasma proteins in a human twin population.

The degree and the origins of quantitative variability of most human plasma proteins are largely unknown. Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2-7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors. The data indicate that different proteins show vastly different patterns of abundance variability among humans and that genetic control and longitudinal variation affect protein levels and biological processes to different degrees. The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors. Moreover, we identified 13 cis-SNPs significantly influencing the level of specific plasma proteins. These results therefore have immediate implications for the effective design of blood-based biomarker studies.

Development of a pharmaceutical hepatotoxicity biomarker panel using a discovery to targeted proteomics approach.

There is a pressing and continued need for improved predictive power in preclinical pharmaceutical toxicology assessment as substantial numbers of drugs are still removed from the market, or from late-stage development, because of unanticipated issues of toxicity. In recent years a number of consortia have been formed with a view to integrating -omics molecular profiling strategies to increase the sensitivity and predictive power of preclinical toxicology evaluation. In this study we report on the LC-MS based proteomic analysis of the effects of the hepatotoxic compound EMD 335823 on liver from rats using an integrated discovery to targeted proteomics approach. This compound was one of a larger panel studied by a variety of molecular profiling techniques as part of the InnoMed PredTox Consortium. Label-free LC-MS analysis of hepatotoxicant EMD 335823 treated animals revealed only moderate correlation of individual protein expression with changes in mRNA expression observed by transcriptomic analysis of the same liver samples. Significantly however, analysis of the protein and transcript changes at the pathway level revealed they were in good agreement. This higher level analysis was also consistent with the previously suspected PPARα activity of the compound. Subsequently, a panel of potential biomarkers of liver toxicity was assembled from the label-free LC-MS proteomics discovery data, the previously acquired transcriptomics data and selected candidates identified from the literature. We developed and then deployed optimized selected reaction monitoring assays to undertake multiplexed measurement of 48 putative toxicity biomarkers in liver tissue. The development of the selected reaction monitoring assays was facilitated by the construction of a peptide MS/MS spectral library from pooled control and treated rat liver lysate using peptide fractionation by strong cation exchange and off-gel electrophoresis coupled to LC-MS/MS. After iterative optimization and quality control of the selected reaction monitoring assay panel, quantitative measurements of 48 putative biomarkers in the liver of EMD 335823 treated rats were carried out and this revealed that the panel is highly enriched for proteins modulated significantly on drug treatment/hepatotoxic insult. This proof-of-principle study provides a roadmap for future large scale pre-clinical toxicology biomarker verification studies whereby putative toxicity biomarkers assembled from multiple disparate sources can be evaluated at medium-high throughput by targeted MS.