Marco Y. Hein

Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ

Protein quantification without isotopic labels has been a long-standing interest in the proteomics field. However, accurate and robust proteome-wide quantification with label-free approaches remains a challenge. We developed a new intensity determination and normalization procedure called MaxLFQ that is fully compatible with any peptide or protein separation prior to LC-MS analysis. Protein abundance profiles are assembled using the maximum possible information from MS signals, given that the presence of quantifiable peptides varies from sample to sample. For a benchmark dataset with two proteomes mixed at known ratios, we accurately detected the mixing ratio over the entire protein expression range, with greater precision for abundant proteins. The significance of individual label-free quantifications was obtained via a t test approach. For a second benchmark dataset, we accurately quantify fold changes over several orders of magnitude, a task that is challenging with label-based methods. MaxLFQ is a generic label-free quantification technology that is readily applicable to many biological questions; it is compatible with standard statistical analysis workflows, and it has been validated in many and diverse biological projects. Our algorithms can handle very large experiments of 500+ samples in a manageable computing time. It is implemented in the freely available MaxQuant computational proteomics platform and works completely seamlessly at the click of a button.

The Perseus computational platform for comprehensive analysis of (prote)omics data

A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseuss arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.

Decoding Human Cytomegalovirus

Dissecting HCMV Gene Expression Most of us are infected with human cytomegalovirus (HCMV), but severe disease is almost always limited to immunocompromised individuals or newborn infants. The virus has a relatively large (∼240 kb) DNA genome and shows a complex pattern of gene transcription, hinting at a complex regulatory and coding capacity. Stern-Ginossar et al. (p. 1088) mapped ribosome positions on HCMV transcripts during the course of viral infection of human fibroblast cells. The data suggest the presence of novel open reading frames (ORFs) lying within existing ORFs; very short ORFs upstream of canonical ORFs; ORFs antisense to canonical ORFs; and short, conserved ORFs encoded by long RNAs. Select ORFs were translated, dramatically expanding the coding capacity of the HCMV genome. A closer look at the human cytomegalovirus genome uncovers many new open reading frames. The human cytomegalovirus (HCMV) genome was sequenced 20 years ago. However, like those of other complex viruses, our understanding of its protein coding potential is far from complete. We used ribosome profiling and transcript analysis to experimentally define the HCMV translation products and follow their temporal expression. We identified hundreds of previously unidentified open reading frames and confirmed a fraction by means of mass spectrometry. We found that regulated use of alternative transcript start sites plays a broad role in enabling tight temporal control of HCMV protein expression and allowing multiple distinct polypeptides to be generated from a single genomic locus. Our results reveal an unanticipated complexity to the HCMV coding capacity and illustrate the role of regulated changes in transcript start sites in generating this complexity.

A Human Interactome in Three Quantitative Dimensions Organized by Stoichiometries and Abundances

The organization of a cell emerges from the interactions in protein networks. The interactome is critically dependent on the strengths of interactions and the cellular abundances of the connected proteins, both of which span orders of magnitude. However, these aspects have not yet been analyzed globally. Here, we have generated a library of HeLa cell lines expressing 1,125 GFP-tagged proteins under near-endogenous control, which we used as input for a next-generation interaction survey. Using quantitative proteomics, we detect specific interactions, estimate interaction stoichiometries, and measure cellular abundances of interacting proteins. These three quantitative dimensions reveal that the protein network is dominated by weak, substoichiometric interactions that play a pivotal role in defining network topology. The minority of stable complexes can be identified by their unique stoichiometry signature. This study provides a rich interaction dataset connecting thousands of proteins and introduces a framework for quantitative network analysis.

A Systematic Mammalian Genetic Interaction Map Reveals Pathways Underlying Ricin Susceptibility

Genetic interaction (GI) maps, comprising pairwise measures of how strongly the function of one gene depends on the presence of a second, have enabled the systematic exploration of gene function in microorganisms. Here, we present a two-stage strategy to construct high-density GI maps in mammalian cells. First, we use ultracomplex pooled shRNA libraries (25 shRNAs/gene) to identify high-confidence hit genes for a given phenotype and effective shRNAs. We then construct double-shRNA libraries from these to systematically measure GIs between hits. A GI map focused on ricin susceptibility broadly recapitulates known pathways and provides many unexpected insights. These include a noncanonical role for COPI, a previously uncharacterized protein complex affecting toxin clearance, a specialized role for the ribosomal protein RPS25, and functionally distinct mammalian TRAPP complexes. The ability to rapidly generate mammalian GI maps provides a potentially transformative tool for defining gene function and designing combination therapies based on synergistic pairs.

A 'proteomic ruler' for protein copy number and concentration estimation without spike-in standards

Absolute protein quantification using mass spectrometry (MS)-based proteomics delivers protein concentrations or copy numbers per cell. Existing methodologies typically require a combination of isotope-labeled spike-in references, cell counting, and protein concentration measurements. Here we present a novel method that delivers similar quantitative results directly from deep eukaryotic proteome datasets without any additional experimental steps. We show that the MS signal of histones can be used as a “proteomic ruler” because it is proportional to the amount of DNA in the sample, which in turn depends on the number of cells. As a result, our proteomic ruler approach adds an absolute scale to the MS readout and allows estimation of the copy numbers of individual proteins per cell. We compare our protein quantifications with values derived via the use of stable isotope labeling by amino acids in cell culture and protein epitope signature tags in a method that combines spike-in protein fragment standards with precise isotope label quantification. The proteomic ruler approach yields quantitative readouts that are in remarkably good agreement with results from the precision method. We attribute this surprising result to the fact that the proteomic ruler approach omits error-prone steps such as cell counting or protein concentration measurements. The proteomic ruler approach is readily applicable to any deep eukaryotic proteome dataset—even in retrospective analysis—and we demonstrate its usefulness with a series of mouse organ proteomes.

Accurate Protein Complex Retrieval by Affinity Enrichment Mass Spectrometry (AE-MS) Rather than Affinity Purification Mass Spectrometry (AP-MS)

Protein–protein interactions are fundamental to the understanding of biological processes. Affinity purification coupled to mass spectrometry (AP-MS) is one of the most promising methods for their investigation. Previously, complexes were purified as much as possible, frequently followed by identification of individual gel bands. However, todays mass spectrometers are highly sensitive, and powerful quantitative proteomics strategies are available to distinguish true interactors from background binders. Here we describe a high performance affinity enrichment-mass spectrometry method for investigating protein–protein interactions, in which no attempt at purifying complexes to homogeneity is made. Instead, we developed analysis methods that take advantage of specific enrichment of interactors in the context of a large amount of unspecific background binders. We perform single-step affinity enrichment of endogenously expressed GFP-tagged proteins and their interactors in budding yeast, followed by single-run, intensity-based label-free quantitative LC-MS/MS analysis. Each pull-down contains around 2000 background binders, which are reinterpreted from troubling contaminants to crucial elements in a novel data analysis strategy. First the background serves for accurate normalization. Second, interacting proteins are not identified by comparison to a single untagged control strain, but instead to the other tagged strains. Third, potential interactors are further validated by their intensity profiles across all samples. We demonstrate the power of our AE-MS method using several well-known and challenging yeast complexes of various abundances. AE-MS is not only highly efficient and robust, but also cost effective, broadly applicable, and can be performed in any laboratory with access to high-resolution mass spectrometers.

A genome-wide resource for the analysis of protein localisation in Drosophila

The Drosophila genome contains >13000 protein-coding genes, the majority of which remain poorly investigated. Important reasons include the lack of antibodies or reporter constructs to visualise these proteins. Here, we present a genome-wide fosmid library of 10000 GFP-tagged clones, comprising tagged genes and most of their regulatory information. For 880 tagged proteins, we created transgenic lines, and for a total of 207 lines, we assessed protein expression and localisation in ovaries, embryos, pupae or adults by stainings and live imaging approaches. Importantly, we visualised many proteins at endogenous expression levels and found a large fraction of them localising to subcellular compartments. By applying genetic complementation tests, we estimate that about two-thirds of the tagged proteins are functional. Moreover, these tagged proteins enable interaction proteomics from developing pupae and adult flies. Taken together, this resource will boost systematic analysis of protein expression and localisation in various cellular and developmental contexts. DOI: http://dx.doi.org/10.7554/eLife.12068.001

Proteomics reveals dynamic assembly of repair complexes during bypass of DNA cross-links

Uncrossing covalently linked DNA strands DNA interstrand cross-links (ICLs) covalently link the two strands of the double helix. ICL mutations are difficult to repair, because the two DNA strands cannot be separated and so one strand cannot be used as a template to repair the other. Räschle et al. developed a mass spectrometry–based method to systematically analyze a time series of all the proteins recruited to repair ICLs in Xenopus egg extracts. They found many of the known factors required for ICL repair. They also found a number of new factors, two of which define a new repair pathway for ICL mutations. Science, this issue 10.1126/science.1253671 Surveying the battery of proteins required to repair covalently linked DNA strands reveals a new repair pathway. INTRODUCTION DNA damage encountered during DNA replication represents a major challenge to the integrity of the genome. Because replicative polymerases are unable to synthesize across DNA lesions, prolonged stalling of replisomes can lead to replication fork collapse, giving rise to gross genomic alterations. Cells have evolved intricate responses that orchestrate the reorganization of the replication fork necessary for overcoming such roadblocks, but the full set of factors involved in these processes has not been defined. Here, we performed unbiased proteomic analyses of the dynamically changing protein landscape at damaged chromatin undergoing DNA replication. This yielded mechanistic insights into the pathways that ensure genomic stability during perturbed DNA replication. RATIONALE We combined the powerful and well-established Xenopus egg extract system for cell-free DNA replication with quantitative mass spectrometry to develop CHROMASS (chromatin mass spectrometry), a simple yet robust method for the unbiased analysis of chromatin composition. Using bifunctional cross-linkers, compounds commonly applied in chemotherapy, we systematically monitored the assembly and disassembly of protein complexes on replicating chromatin containing DNA interstrand cross-links (ICLs). RESULTS We show that replication of ICL-containing chromatin templates triggers recruitment of more than 90 DNA repair and genome maintenance factors. Addition of replication inhibitors revealed the subset of proteins that accumulate in a strictly replication-dependent fashion. The quantitative readout by CHROMASS is highly lesion-specific, as the known repair factors enriched on psoralen–cross-linked templates had previously been linked to ICL repair or specific branches of DNA damage signaling. In contrast, virtually none of the proteins involved in unrelated DNA repair pathways (e.g., base excision repair or nonhomologous end joining) showed damage-specific enrichment. The temporal profiles of hundreds of proteins across an extensive time course and a variety of perturbations provided a data-rich resource that could be mined to identify previously unknown genome maintenance factors. Among such hits, we identified SLF1 and SLF2 and showed that they physically link RAD18 with the SMC5/6 complex. This defines a linear RAD18-SLF1-SLF2 recruitment pathway for the SMC5/6 complex to RNF8/RNF168-generated ubiquitylations at damaged DNA in vertebrate cells. We found that SLF2 is a distant ortholog of yeast NSE6, an SMC5/6-associated factor that is essential for targeting this complex to damaged DNA to promote faithful repair of the lesions. Consistent with pivotal functions of SMC5/6 in the suppression of replication stress-induced, illegitimate recombination intermediates, depletion of SLF1 or SLF2 led to mitotic errors and compromised cell survival in response to genotoxic agents. CONCLUSIONS CHROMASS enables rapid and unbiased time-resolved insights into the chromatin interaction dynamics of entire DNA repair pathways. Combined with specific perturbations, CHROMASS allows systems-level interrogation of the consequences of inactivating particular aspects of the repair process. We compiled comprehensive proteome-wide profiles of dynamic protein interactions with damaged chromatin. These can be mined to pinpoint genome stability maintenance factors, exemplified here by the identification of SLF1 and SLF2, which define a recruitment pathway for the SMC5/6 complex. CHROMASS can be applied to other chromatin-associated pathways and may also shed light on the dynamics of posttranslational modifications governing the regulation of these processes. CHROMASS analysis of proteins recruited to stalled replication forks reveals a specific set of DNA repair factors involved in the replication stress response. Among these, SLF1 and SLF2 are found to bridge the SMC5/6 complex to RAD18, thereby linking SMC5/6 recruitment to ubiquitylation products formed at various DNA lesions. DNA interstrand cross-links (ICLs) block replication fork progression by inhibiting DNA strand separation. Repair of ICLs requires sequential incisions, translesion DNA synthesis, and homologous recombination, but the full set of factors involved in these transactions remains unknown. We devised a technique called chromatin mass spectrometry (CHROMASS) to study protein recruitment dynamics during perturbed DNA replication in Xenopus egg extracts. Using CHROMASS, we systematically monitored protein assembly and disassembly on ICL-containing chromatin. Among numerous prospective DNA repair factors, we identified SLF1 and SLF2, which form a complex with RAD18 and together define a pathway that suppresses genome instability by recruiting the SMC5/6 cohesion complex to DNA lesions. Our study provides a global analysis of an entire DNA repair pathway and reveals the mechanism of SMC5/6 relocalization to damaged DNA in vertebrate cells.

COMMD1 is linked to the WASH complex and regulates endosomal trafficking of the copper transporter ATP7A

The COMMD1 protein, implicated in copper homeostasis, is found to regulate endosomal sorting of the copper transporter ATP7A through a novel protein complex containing CCDC22, CCDC93, and C16orf62, which link COMMD1 to the WASH complex.