Spatiotemporal variation of mammalian protein complex stoichiometries

Synthetic tunable promoters for flexible control of multi-gene expression in mammalian cells

INTRODUCTION

Synthetic biology revolutionizes our ability to decode and recode genetic systems. The capability to reconstruct and flexibly manipulate multi-gene systems is critical for understanding cellular behaviors and has significant applications in therapeutics.

OBJECTIVES

This study aims to construct a diverse library of synthetic tunable promoters (STPs) to enable flexible control of multi-gene expression in mammalian cells.

METHODS

We designed and constructed synthetic tunable promoters (STPs) that incorporate both a universal activation site (UAS) and a specific activation site (SAS), enabling multi-level expression control via the CRISPR activation (CRISPRa) system. To evaluate promoter activity, we utilized Massively Parallel Reporter Assays (MPRA) to assess the basal strengths of the STPs and their activation responses. Next, we constructed a three-gene reporter system to assess the capacity of the synthetic promoters for achieving multilevel control of single-gene expression within multi-gene systems.

RESULTS

The promoter library contains 24,960 unique non-redundant promoters with distinct sequence characteristics. MPRA revealed a wide range of promoter activities, showing different basal strengths and distinct activation levels when activated by the CRISPRa system. When regulated by targeting the SAS, the STPs exhibited orthogonality, allowing multilevel control of single-gene expression within multi-gene systems without cross-interference. Furthermore, the combinatorial activation of STPs in a multi-gene system enlarged the scope of expression levels achievable, providing fine-tuned control over gene expression.

CONCLUSION

We provide a diverse collection of synthetic tunable promoters, offering a valuable toolkit for the construction and manipulation of multi-gene systems in mammalian cells, with applications in gene therapy and biotechnology.

Circadian regulation of macromolecular complex turnover and proteome renewal

Although costly to maintain, protein homeostasis is indispensable for normal cellular function and long-term health. In mammalian cells and tissues, daily variation in global protein synthesis has been observed, but its utility and consequences for proteome integrity are not fully understood. Using several different pulse-labelling strategies, here we gain direct insight into the relationship between protein synthesis and abundance proteome-wide. We show that protein degradation varies in-phase with protein synthesis, facilitating rhythms in turnover rather than abundance. This results in daily consolidation of proteome renewal whilst minimising changes in composition. Coupled rhythms in synthesis and turnover are especially salient to the assembly of macromolecular protein complexes, particularly the ribosome, the most abundant species of complex in the cell. Daily turnover and proteasomal degradation rhythms render cells and mice more sensitive to proteotoxic stress at specific times of day, potentially contributing to daily rhythms in the efficacy of proteasomal inhibitors against cancer. Our findings suggest that circadian rhythms function to minimise the bioenergetic cost of protein homeostasis through temporal consolidation of protein turnover.

Resource allocation in mammalian systems

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

Functional and spatial proteomics profiling reveals intra- and intercellular signaling crosstalk in colorectal cancer

Precision oncology approaches for patients with colorectal cancer (CRC) continue to lag behind other solid cancers. Functional precision oncology-a strategy that is based on perturbing primary tumor cells from cancer patients-could provide a road forward to personalize treatment. We extend this paradigm to measuring proteome activity landscapes by acquiring quantitative phosphoproteomic data from patient-derived organoids (PDOs). We show that kinase inhibitors induce inhibitor- and patient-specific off-target effects and pathway crosstalk. Reconstruction of the kinase networks revealed that the signaling rewiring is modestly affected by mutations. We show non-genetic heterogeneity of the PDOs and upregulation of stemness and differentiation genes by kinase inhibitors. Using imaging mass-cytometry-based profiling of the primary tumors, we characterize the tumor microenvironment (TME) and determine spatial heterocellular crosstalk and tumor-immune cell interactions. Collectively, we provide a framework for inferring tumor cell intrinsic signaling and external signaling from the TME to inform precision (immuno-) oncology in CRC.

Cryo-EM of a heterogeneous biochemical fraction elucidates multiple protein complexes from a multicellular thermophilic eukaryote

Biomolecular complexes and their interactions govern cellular structure and function. Understanding their architecture is a prerequisite for dissecting the cell's inner workings, but their higher-order assembly is often transient and challenging for structural analysis. Here, we performed cryo-EM on a single, highly heterogeneous biochemical fraction derived from Chaetomium thermophilum cell extracts to visualize the biomolecular content of the multicellular eukaryote. After cryo-EM single-particle image processing, results showed that a simultaneous three-dimensional structural characterization of multiple chemically diverse biomacromolecules is feasible. Namely, the thermophilic, eukaryotic complexes of (a) ATP citrate-lyase, (b) Hsp90, (c) 20S proteasome, (d) Hsp60 and (e) UDP-glucose pyrophosphorylase were characterized. In total, all five complexes have been structurally dissected in a thermophilic eukaryote in a total imaged sample area of 190.64 μm2, and two, in particular, 20S proteasome and Hsp60, exhibit side-chain resolution features. The C. thermophilum Hsp60 near-atomic model was resolved at 3.46 Å (FSC = 0.143) and shows a hinge-like conformational change of its equatorial domain, highly similar to the one previously shown for its bacterial orthologue, GroEL. This work demonstrates that cryo-EM of cell extracts will greatly accelerate the structural analysis of cellular complexes and provide unprecedented opportunities to annotate architectures of biomolecules in a holistic approach.

Uncoupled evolution of the Polycomb system and deep origin of non-canonical PRC1

Polycomb group proteins, as part of the Polycomb repressive complexes, are essential in gene repression through chromatin compaction by canonical PRC1, mono-ubiquitylation of histone H2A by non-canonical PRC1 and tri-methylation of histone H3K27 by PRC2. Despite prevalent models emphasizing tight functional coupling between PRC1 and PRC2, it remains unclear whether this paradigm indeed reflects the evolution and functioning of these complexes. Here, we conduct a comprehensive analysis of the presence or absence of cPRC1, nPRC1 and PRC2 across the entire eukaryotic tree of life, and find that both complexes were present in the Last Eukaryotic Common Ancestor (LECA). Strikingly, ~42% of organisms contain only PRC1 or PRC2, showing that their evolution since LECA is largely uncoupled. The identification of ncPRC1-defining subunits in unicellular relatives of animals and fungi suggests ncPRC1 originated before cPRC1, and we propose a scenario for the evolution of cPRC1 from ncPRC1. Together, our results suggest that crosstalk between these complexes is a secondary development in evolution.

Puzzling out nuclear pore complex assembly

Nuclear pore complexes (NPCs) are sophisticated multiprotein assemblies embedded within the nuclear envelope and controlling the exchanges of molecules between the cytoplasm and the nucleus. In this review, we summarize the mechanisms by which these elaborate complexes are built from their subunits, the nucleoporins, based on our ever-growing knowledge of NPC structural organization and on the recent identification of additional features of this process. We present the constraints faced during the production of nucleoporins, their gathering into oligomeric complexes, and the formation of NPCs within nuclear envelopes, and review the cellular strategies at play, from co-translational assembly to the enrolment of a panel of cofactors. Remarkably, the study of NPCs can inform our perception of the biogenesis of multiprotein complexes in general - and vice versa.

Proteomic Dynamics of Breast Cancer Cell Lines Identifies Potential Therapeutic Protein Targets

Treatment and relevant targets for breast cancer (BC) remain limited, especially for triple-negative BC (TNBC). We identified 6091 proteins of 76 human BC cell lines using data-independent acquisition (DIA). Integrating our proteomic findings with prior multi-omics datasets, we found that including proteomics data improved drug sensitivity predictions and provided insights into the mechanisms of action. We subsequently profiled the proteomic changes in nine cell lines (five TNBC and four non-TNBC) treated with EGFR/AKT/mTOR inhibitors. In TNBC, metabolism pathways were dysregulated after EGFR/mTOR inhibitor treatment, while RNA modification and cell cycle pathways were affected by AKT inhibitor. This systematic multi-omics and in-depth analysis of the proteome of BC cells can help prioritize potential therapeutic targets and provide insights into adaptive resistance in TNBC.

Global and tissue-specific aging effects on murine proteomes

Maintenance of protein homeostasis degrades with age, contributing to aging-related decline and disease. Previous studies have primarily surveyed transcriptional aging changes. To define the effects of age directly at the protein level, we perform discovery-based proteomics in 10 tissues from 20 C57BL/6J mice, representing both sexes at adult and late midlife ages (8 and 18 months). Consistent with previous studies, age-related changes in protein abundance often have no corresponding transcriptional change. Aging results in increases in immune proteins across all tissues, consistent with a global pattern of immune infiltration with age. Our protein-centric data reveal tissue-specific aging changes with functional consequences, including altered endoplasmic reticulum and protein trafficking in the spleen. We further observe changes in the stoichiometry of protein complexes with important roles in protein homeostasis, including the CCT/TriC complex and large ribosomal subunit. These data provide a foundation for understanding how proteins contribute to systemic aging across tissues.

Genetic dissection of the pluripotent proteome through multi-omics data integration

Genetic background drives phenotypic variability in pluripotent stem cells (PSCs). Most studies to date have used transcript abundance as the primary molecular readout of cell state in PSCs. We performed a comprehensive proteogenomics analysis of 190 genetically diverse mouse embryonic stem cell (mESC) lines. The quantitative proteome is highly variable across lines, and we identified pluripotency-associated pathways that were differentially activated in the proteomics data that were not evident in transcriptome data from the same lines. Integration of protein abundance to transcript levels and chromatin accessibility revealed broad co-variation across molecular layers as well as shared and unique drivers of quantitative variation in pluripotency-associated pathways. Quantitative trait locus (QTL) mapping localized the drivers of these multi-omic signatures to genomic hotspots. This study reveals post-transcriptional mechanisms and genetic interactions that underlie quantitative variability in the pluripotent proteome and provides a regulatory map for mESCs that can provide a basis for future mechanistic studies.

Deep thermal profiling for detection of functional proteoform groups

The complexity of the functional proteome extends considerably beyond the coding genome, resulting in millions of proteoforms. Investigation of proteoforms and their functional roles is important to understand cellular physiology and its deregulation in diseases but challenging to perform systematically. Here we applied thermal proteome profiling with deep peptide coverage to detect functional proteoform groups in acute lymphoblastic leukemia cell lines with different cytogenetic aberrations. We detected 15,846 proteoforms, capturing differently spliced, cleaved and post-translationally modified proteins expressed from 9,290 genes. We identified differential co-aggregation of proteoform pairs and established links to disease biology. Moreover, we systematically made use of measured biophysical proteoform states to find specific biomarkers of drug sensitivity. Our approach, thus, provides a powerful and unique tool for systematic detection and functional annotation of proteoform groups.

Recognition of the CCT5 di-Glu degron by CRL4DCAF12 is dependent on TRiC assembly

Assembly Quality Control (AQC) E3 ubiquitin ligases target incomplete or incorrectly assembled protein complexes for degradation. The CUL4-RBX1-DDB1-DCAF12 (CRL4^DCAF12 ) E3 ligase preferentially ubiquitinates proteins that carry a C-terminal double glutamate (di-Glu) motif. Reported CRL4^DCAF12 di-Glu-containing substrates include CCT5, a subunit of the TRiC chaperonin. How DCAF12 engages its substrates and the functional relationship between CRL4^DCAF12 and CCT5/TRiC is currently unknown. Here, we present the cryo-EM structure of the DDB1-DCAF12-CCT5 complex at 2.8 Å resolution. DCAF12 serves as a canonical WD40 DCAF substrate receptor and uses a positively charged pocket at the center of the β-propeller to bind the C-terminus of CCT5. DCAF12 specifically reads out the CCT5 di-Glu side chains, and contacts other visible degron amino acids through Van der Waals interactions. The CCT5 C-terminus is inaccessible in an assembled TRiC complex, and functional assays demonstrate that DCAF12 binds and ubiquitinates monomeric CCT5, but not CCT5 assembled into TRiC. Our biochemical and structural results suggest a previously unknown role for the CRL4^DCAF12 E3 ligase in overseeing the assembly of a key cellular complex.

A NuRD for all seasons

The nucleosome-remodeling and deacetylase (NuRD) complex is an essential transcriptional regulator in all complex animals. All seven core subunits of the complex exist as multiple paralogs, raising the question of whether the complex might utilize paralog switching to achieve cell type-specific functions. We examine the evidence for this idea, making use of published quantitative proteomic data to dissect NuRD composition in 20 different tissues, as well as a large-scale CRISPR knockout screen carried out in >1000 human cancer cell lines. These data, together with recent reports, provide strong support for the idea that distinct permutations of the NuRD complex with tailored functions might regulate tissue-specific gene expression programs.

Integration of protein context improves protein-based COVID-19 patient stratification

BACKGROUND

Classification of disease severity is crucial for the management of COVID-19. Several studies have shown that individual proteins can be used to classify the severity of COVID-19. Here, we aimed to investigate whether integrating four types of protein context data, namely, protein complexes, stoichiometric ratios, pathways and network degrees will improve the severity classification of COVID-19.

METHODS

We performed machine learning based on three previously published datasets. The first was a SWATH (sequential window acquisition of all theoretical fragment ion spectra) MS (mass spectrometry) based proteomic dataset. The second was a TMTpro 16plex labeled shotgun proteomics dataset. The third was a SWATH dataset of an independent patient cohort.

RESULTS

Besides twelve proteins, machine learning also prioritized two complexes, one stoichiometric ratio, five pathways, and five network degrees, resulting a 25-feature panel. As a result, a model based on the 25 features led to effective classification of severe cases with an AUC of 0.965, outperforming the models with proteins only. Complement component C9, transthyretin (TTR) and TTR-RBP (transthyretin-retinol binding protein) complex, the stoichiometric ratio of SAA2 (serum amyloid A proteins 2)/YLPM1 (YLP Motif Containing 1), and the network degree of SIRT7 (Sirtuin 7) and A2M (alpha-2-macroglobulin) were highlighted as potential markers by this classifier. This classifier was further validated with a TMT-based proteomic data set from the same cohort (test dataset 1) and an independent SWATH-based proteomic data set from Germany (test dataset 2), reaching an AUC of 0.900 and 0.908, respectively. Machine learning models integrating protein context information achieved higher AUCs than models with only one feature type.

CONCLUSION

Our results show that the integration of protein context including protein complexes, stoichiometric ratios, pathways, network degrees, and proteins improves phenotype prediction.

A Nuclear Belt Fastens on Neural Cell Fate

Successful embryonic and adult neurogenesis require proliferating neural stem and progenitor cells that are intrinsically and extrinsically guided into a neuronal fate. In turn, migration of new-born neurons underlies the complex cytoarchitecture of the brain. Proliferation and migration are therefore essential for brain development, homeostasis and function in adulthood. Among several tightly regulated processes involved in brain formation and function, recent evidence points to the nuclear envelope (NE) and NE-associated components as critical new contributors. Classically, the NE was thought to merely represent a barrier mediating selective exchange between the cytoplasm and nucleoplasm. However, research over the past two decades has highlighted more sophisticated and diverse roles for NE components in progenitor fate choice and migration of their progeny by tuning gene expression via interactions with chromatin, transcription factors and epigenetic factors. Defects in NE components lead to neurodevelopmental impairments, whereas age-related changes in NE components are proposed to influence neurodegenerative diseases. Thus, understanding the roles of NE components in brain development, maintenance and aging is likely to reveal new pathophysiological mechanisms for intervention. Here, we review recent findings for the previously underrepresented contribution of the NE in neuronal commitment and migration, and envision future avenues for investigation.

Genome-wide transcript and protein analysis highlights the role of protein homeostasis in the aging mouse heart

Investigation of the molecular mechanisms of aging in the human heart is challenging because of confounding factors, such as diet and medications, as well as limited access to tissues from healthy aging individuals. The laboratory mouse provides an ideal model to study aging in healthy individuals in a controlled environment. However, previous mouse studies have examined only a narrow range of the genetic variation that shapes individual differences during aging. Here, we analyze transcriptome and proteome data from 185 genetically diverse male and female mice at ages 6, 12, and 18 mo to characterize molecular changes that occur in the aging heart. Transcripts and proteins reveal activation of pathways related to exocytosis and cellular transport with age, whereas processes involved in protein folding decrease with age. Additional changes are apparent only in the protein data including reduced fatty acid oxidation and increased autophagy. For proteins that form complexes, we see a decline in correlation between their component subunits with age, suggesting age-related loss of stoichiometry. The most affected complexes are themselves involved in protein homeostasis, which potentially contributes to a cycle of progressive breakdown in protein quality control with age. Our findings highlight the important role of post-transcriptional regulation in aging. In addition, we identify genetic loci that modulate age-related changes in protein homeostasis, suggesting that genetic variation can alter the molecular aging process.

Quality control of protein complex assembly by the ubiquitin-proteasome system

The majority of human proteins operate as multimeric complexes with defined compositions and distinct architectures. How the assembly of these complexes is surveyed and how defective complexes are recognized is just beginning to emerge. In eukaryotes, over 600 E3 ubiquitin ligases form part of the ubiquitin-proteasome system (UPS) which detects structural characteristics in its target proteins and selectively induces their degradation. The UPS has recently been shown to oversee key quality control steps during the assembly of protein complexes. We review recent findings on how E3 ubiquitin ligases regulate protein complex assembly and highlight unanswered questions relating to their mechanism of action.

Conserved exchange of paralog proteins during neuronal differentiation

Paralog proteins promote fine tuning of protein complexes. The author identified a specific paralog signature conserved across vertebrate neuronal differentiation. Altering the ratio of SEC23 paralogs in the COPII complex influences neuronal differentiation in a opposite way.

Gene duplication enables the emergence of new functions by lowering the evolutionary pressure that is posed on the ancestral genes. Previous studies have highlighted the role of specific paralog genes during cell differentiation, for example, in chromatin remodeling complexes. It remains unexplored whether similar mechanisms extend to other biological functions and whether the regulation of paralog genes is conserved across species. Here, we analyze the expression of paralogs across human tissues, during development and neuronal differentiation in fish, rodents and humans. Whereas ∼80% of paralog genes are co-regulated, a subset of paralogs shows divergent expression profiles, contributing to variability of protein complexes. We identify 78 substitutions of paralog pairs that occur during neuronal differentiation and are conserved across species. Among these, we highlight a substitution between the paralogs SEC23A and SEC23B members of the COPII complex. Altering the ratio between these two genes via RNAi-mediated knockdown is sufficient to influence neuron differentiation. We propose that remodeling of the vesicular transport system via paralog substitutions is an evolutionary conserved mechanism enabling neuronal differentiation.

Structure, Maintenance, and Regulation of Nuclear Pore Complexes: The Gatekeepers of the Eukaryotic Genome

In eukaryotic cells, the genetic material is segregated inside the nucleus. This compartmentalization of the genome requires a transport system that allows cells to move molecules across the nuclear envelope, the membrane-based barrier that surrounds the chromosomes. Nuclear pore complexes (NPCs) are the central component of the nuclear transport machinery. These large protein channels penetrate the nuclear envelope, creating a passage between the nucleus and the cytoplasm through which nucleocytoplasmic molecule exchange occurs. NPCs are one of the largest protein assemblies of eukaryotic cells and, in addition to their critical function in nuclear transport, these structures also play key roles in many cellular processes in a transport-independent manner. Here we will review the current knowledge of the NPC structure, the cellular mechanisms that regulate their formation and maintenance, and we will provide a brief description of a variety of processes that NPCs regulate.

RoDiCE: robust differential protein co-expression analysis for cancer complexome

MOTIVATION

The full spectrum of abnormalities in cancer-associated protein complexes remains largely unknown. Comparing the co-expression structure of each protein complex between tumor and healthy cells may provide insights regarding cancer-specific protein dysfunction. However, the technical limitations of mass spectrometry-based proteomics, including contamination with biological protein variants, causes noise that leads to non-negligible over- (or under-) estimating co-expression.

RESULTS

We propose a robust algorithm for identifying protein complex aberrations in cancer based on differential protein co-expression testing. Our method based on a copula is sufficient for improving identification accuracy with noisy data compared to conventional linear correlation-based approaches. As an application, we use large-scale proteomic data from renal cancer to show that important protein complexes, regulatory signaling pathways and drug targets can be identified. The proposed approach surpasses traditional linear correlations to provide insights into higher-order differential co-expression structures.

AVAILABILITY AND IMPLEMENTATION

https://github.com/ymatts/RoDiCE.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

One Hundred Years of Gene Balance: How Stoichiometric Issues Affect Gene Expression, Genome Evolution, and Quantitative Traits

A century ago experiments with the flowering plant Datura stramonium and the fruit fly Drosophila melanogaster revealed that adding an extra chromosome to a karyotype was much more detrimental than adding a whole set of chromosomes. This phenomenon was referred to as gene balance and has been recapitulated across eukaryotic species. Here, we retrace some developments in this field. Molecular studies suggest that the basis of balance involves stoichiometric relationships of multi-component interactions. This concept has implication for the mechanisms controlling gene expression, genome evolution, sex chromosome evolution/dosage compensation, speciation mechanisms, and the underlying genetics of quantitative traits.

Regulation of protein abundance in genetically diverse mouse populations

Genetically diverse mouse populations are powerful tools for characterizing the regulation of the proteome and its relationship to whole-organism phenotypes. We used mass spectrometry to profile and quantify the abundance of 6,798 proteins in liver tissue from mice of both sexes across 58 Collaborative Cross (CC) inbred strains. We previously collected liver proteomics data from the related Diversity Outbred (DO) mice and their founder strains. We show concordance across the proteomics datasets despite being generated from separate experiments, allowing comparative analysis. We map protein abundance quantitative trait loci (pQTLs), identifying 1,087 local and 285 distal in the CC mice and 1,706 local and 414 distal in the DO mice. We find that regulatory effects on individual proteins are conserved across the mouse populations, in particular for local genetic variation and sex differences. In comparison, proteins that form complexes are often co-regulated, displaying varying genetic architectures, and overall show lower heritability and map fewer pQTLs. We have made this resource publicly available to enable quantitative analyses of the regulation of the proteome.

Protein Complex Organization Imposes Constraints on Proteome Dysregulation in Cancer

Protein assembly is a highly dynamic process and proteins can interact in different ways and stoichiometries within a complex. The importance of maintaining protein stoichiometry for complex function and avoiding aggregation of orphan subunits has been demonstrated. However, how exactly the organization of proteins into complexes constrains differential protein abundance in extreme cellular conditions like cancer, where a lot of protein abundance changes occur, has not been systematically investigated. To study this, we collected proteomic data made available by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) to quantify proteomic changes during carcinogenesis and systematically tested five interaction types in complexes to investigate which of these features impact on protein abundance correlation patterns in cancer. We found that higher than expected fraction of protein complex subunits does not show changes in their abundances compared to those in the normal samples. Furthermore, we found that the way proteins interact in complexes indeed constrains their co-abundance patterns. Our results highlight the role of the interactions between the proteins and the need of cancer cells to deal with aberrant changes in protein abundance.

An atlas of protein-protein interactions across mouse tissues

Cellular processes arise from the dynamic organization of proteins in networks of physical interactions. Mapping the interactome has therefore been a central objective of high-throughput biology. However, the dynamics of protein interactions across physiological contexts remain poorly understood. Here, we develop a quantitative proteomic approach combining protein correlation profiling with stable isotope labeling of mammals (PCP-SILAM) to map the interactomes of seven mouse tissues. The resulting maps provide a proteome-scale survey of interactome rewiring across mammalian tissues, revealing more than 125,000 unique interactions at a quality comparable to the highest-quality human screens. We identify systematic suppression of cross-talk between the evolutionarily ancient housekeeping interactome and younger, tissue-specific modules. Rewired proteins are tightly regulated by multiple cellular mechanisms and are implicated in disease. Our study opens up new avenues to uncover regulatory mechanisms that shape in vivo interactome responses to physiological and pathophysiological stimuli in mammalian systems.

Dual proteome-scale networks reveal cell-specific remodeling of the human interactome

Thousands of interactions assemble proteins into modules that impart spatial and functional organization to the cellular proteome. Through affinity-purification mass spectrometry, we have created two proteome-scale, cell-line-specific interaction networks. The first, BioPlex 3.0, results from affinity purification of 10,128 human proteins-half the proteome-in 293T cells and includes 118,162 interactions among 14,586 proteins. The second results from 5,522 immunoprecipitations in HCT116 cells. These networks model the interactome whose structure encodes protein function, localization, and complex membership. Comparison across cell lines validates thousands of interactions and reveals extensive customization. Whereas shared interactions reside in core complexes and involve essential proteins, cell-specific interactions link these complexes, "rewiring" subnetworks within each cell's interactome. Interactions covary among proteins of shared function as the proteome remodels to produce each cell's phenotype. Viewable interactively online through BioPlexExplorer, these networks define principles of proteome organization and enable unknown protein characterization.

Rtpca: an R package for differential thermal proximity coaggregation analysis

Summary

Rtpca is an R package implementing methods for inferring protein–protein interactions (PPIs) based on thermal proteome profiling experiments of a single condition or in a differential setting via an approach called thermal proximity coaggregation. It offers user-friendly tools to explore datasets for their PPI predictive performance and easily integrates with available R packages.

Availability and implementation

Rtpca is available from Bioconductor (https://bioconductor.org/packages/Rtpca).

Supplementary information

Supplementary data are available at Bioinformatics online.

Discovery-Versus Hypothesis-Driven Detection of Protein-Protein Interactions and Complexes

Protein complexes are the main functional modules in the cell that coordinate and perform the vast majority of molecular functions. The main approaches to identify and quantify the interactome to date are based on mass spectrometry (MS). Here I summarize the benefits and limitations of different MS-based interactome screens, with a focus on untargeted interactome acquisition, such as co-fractionation MS. Specific emphasis is given to the discussion of discovery- versus hypothesis-driven data analysis concepts and their applicability to large, proteome-wide interactome screens. Hypothesis-driven analysis approaches, i.e., complex- or network-centric, are highlighted as promising strategies for comparative studies. While these approaches require prior information from public databases, also reviewed herein, the available wealth of interactomic data continuously increases, thereby providing more exhaustive information for future studies. Finally, guidance on the selection of interactome acquisition and analysis methods is provided to aid the reader in the design of protein-protein interaction studies.

Microtubule-assisted mechanism for toxisome assembly in Fusarium graminearum

In Fusarium graminearum, a trichothecene biosynthetic complex known as the toxisome forms ovoid and spherical structures in the remodelled endoplasmic reticulum (ER) under mycotoxin-inducing conditions. Previous studies also demonstrated that disruption of actin and tubulin results in a significant decrease in deoxynivalenol (DON) biosynthesis in F. graminearum. However, the functional association between the toxisome and microtubule components has not been clearly defined. In this study we tested the hypothesis that the microtubule network provides key support for toxisome assembly and thus facilitates DON biosynthesis. Through fluorescent live cell imaging, knockout mutant generation, and protein-protein interaction assays, we determined that two of the four F. graminearum tubulins, α₁ and β₂ tubulins, are indispensable for DON production. We also showed that these two tubulins are directly associated. When the α₁ -β₂ tubulin heterodimer is disrupted, the metabolic activity of the toxisome is significantly suppressed, which leads to significant DON biosynthesis impairment. Similar phenotypic outcomes were shown when F. graminearum wild type was treated with carbendazim, a fungicide that binds to microtubules and disrupts spindle formation. Based on our results, we propose a model where α₁ -β₂ tubulin heterodimer serves as the scaffold for functional toxisome assembly in F. graminearum.

Aggregation and disaggregation features of the human proteome

Protein aggregates have negative implications in disease. While reductionist experiments have increased our understanding of aggregation processes, the systemic view in biological context is still limited. To extend this understanding, we used mass spectrometry-based proteomics to characterize aggregation and disaggregation in human cells after non-lethal heat shock. Aggregation-prone proteins were enriched in nuclear proteins, high proportion of intrinsically disordered regions, high molecular mass, high isoelectric point, and hydrophilic amino acids. During recovery, most aggregating proteins disaggregated with a rate proportional to the aggregation propensity: larger loss in solubility was counteracted by faster disaggregation. High amount of intrinsically disordered regions were associated with faster disaggregation. However, other characteristics enriched in aggregating proteins did not correlate with the disaggregation rates. In addition, we analyzed changes in protein thermal stability after heat shock. Soluble remnants of aggregated proteins were more thermally stable compared with control condition. Therefore, our results provide a rich resource of heat stress-related protein solubility data and can foster further studies related to protein aggregation diseases.

Nuclear Periphery Takes Center Stage: The Role of Nuclear Pore Complexes in Cell Identity and Aging

In recent years, the nuclear pore complex (NPC) has emerged as a key player in genome regulation and cellular homeostasis. New discoveries have revealed that the NPC has multiple cellular functions besides mediating the molecular exchange between the nucleus and the cytoplasm. In this review, we discuss non-transport aspects of the NPC focusing on the NPC-genome interaction, the extreme longevity of the NPC proteins, and NPC dysfunction in age-related diseases. The examples summarized herein demonstrate that the NPC, which first evolved to enable the biochemical communication between the nucleus and the cytoplasm, now doubles as the gatekeeper of cellular identity and aging.

mRNAs, proteins and the emerging principles of gene expression control

Gene expression involves transcription, translation and the turnover of mRNAs and proteins. The degree to which protein abundances scale with mRNA levels and the implications in cases where this dependency breaks down remain an intensely debated topic. Here we review recent mRNA-protein correlation studies in the light of the quantitative parameters of the gene expression pathway, contextual confounders and buffering mechanisms. Although protein and mRNA levels typically show reasonable correlation, we describe how transcriptomics and proteomics provide useful non-redundant readouts. Integrating both types of data can reveal exciting biology and is an essential step in refining our understanding of the principles of gene expression control.

Reduced proteasome activity in the aging brain results in ribosome stoichiometry loss and aggregation

A progressive loss of protein homeostasis is characteristic of aging and a driver of neurodegeneration. To investigate this process quantitatively, we characterized proteome dynamics during brain aging in the short-lived vertebrate Nothobranchius furzeri combining transcriptomics and proteomics. We detected a progressive reduction in the correlation between protein and mRNA, mainly due to post-transcriptional mechanisms that account for over 40% of the age-regulated proteins. These changes cause a progressive loss of stoichiometry in several protein complexes, including ribosomes, which show impaired assembly/disassembly and are enriched in protein aggregates in old brains. Mechanistically, we show that reduction of proteasome activity is an early event during brain aging and is sufficient to induce proteomic signatures of aging and loss of stoichiometry in vivo. Using longitudinal transcriptomic data, we show that the magnitude of early life decline in proteasome levels is a major risk factor for mortality. Our work defines causative events in the aging process that can be targeted to prevent loss of protein homeostasis and delay the onset of age-related neurodegeneration.

Meltome atlas-thermal proteome stability across the tree of life

We have used a mass spectrometry-based proteomic approach to compile an atlas of the thermal stability of 48,000 proteins across 13 species ranging from archaea to humans and covering melting temperatures of 30-90 °C. Protein sequence, composition and size affect thermal stability in prokaryotes and eukaryotic proteins show a nonlinear relationship between the degree of disordered protein structure and thermal stability. The data indicate that evolutionary conservation of protein complexes is reflected by similar thermal stability of their proteins, and we show examples in which genomic alterations can affect thermal stability. Proteins of the respiratory chain were found to be very stable in many organisms, and human mitochondria showed close to normal respiration at 46 °C. We also noted cell-type-specific effects that can affect protein stability or the efficacy of drugs. This meltome atlas broadly defines the proteome amenable to thermal profiling in biology and drug discovery and can be explored online at http://meltomeatlas.proteomics.wzw.tum.de:5003/ and http://www.proteomicsdb.org.

The translational landscape of ground state pluripotency

Translational control plays a central role in regulation of gene expression and can lead to significant divergence between mRNA- and protein-abundance. Here, we used genome-wide approaches combined with time-course analysis to measure the mRNA-abundance, mRNA-translation rate and protein expression during the transition of naïve-to-primed mouse embryonic stem cells (ESCs). We find that the ground state ESCs cultured with GSK3-, MEK-inhibitors and LIF (2iL) display higher ribosome density on a selective set of mRNAs. This set of mRNAs undergo strong translational buffering to maintain stable protein expression levels in 2iL-ESCs. Importantly, we show that the global alteration of cellular proteome during the transition of naïve-to-primed pluripotency is largely accompanied by transcriptional rewiring. Thus, we provide a comprehensive and detailed overview of the global changes in gene expression in different states of ESCs and dissect the relative contributions of mRNA-transcription, translation and regulation of protein stability in controlling protein abundance.

Translational control of gene expression can lead to significant divergence between mRNA and protein abundance. Here, the authors describe transcriptional rewiring and translational buffering during transition from naïve to primed pluripotency through quantitation of mRNA-abundance, translation rate and protein expression.

The design and development of covalent protein-protein interaction inhibitors for cancer treatment

Protein-protein interactions (PPIs) are central to a variety of biological processes, and their dysfunction is implicated in the pathogenesis of a range of human diseases, including cancer. Hence, the inhibition of PPIs has attracted significant attention in drug discovery. Covalent inhibitors have been reported to achieve high efficiency through forming covalent bonds with cysteine or other nucleophilic residues in the target protein. Evidence suggests that there is a reduced risk for the development of drug resistance against covalent drugs, which is a major challenge in areas such as oncology and infectious diseases. Recent improvements in structural biology and chemical reactivity have enabled the design and development of potent and selective covalent PPI inhibitors. In this review, we will highlight the design and development of therapeutic agents targeting PPIs for cancer therapy.

Gene family information facilitates variant interpretation and identification of disease-associated genes in neurodevelopmental disorders

BACKGROUND

Classifying pathogenicity of missense variants represents a major challenge in clinical practice during the diagnoses of rare and genetic heterogeneous neurodevelopmental disorders (NDDs). While orthologous gene conservation is commonly employed in variant annotation, approximately 80% of known disease-associated genes belong to gene families. The use of gene family information for disease gene discovery and variant interpretation has not yet been investigated on a genome-wide scale. We empirically evaluate whether paralog-conserved or non-conserved sites in human gene families are important in NDDs.

METHODS

Gene family information was collected from Ensembl. Paralog-conserved sites were defined based on paralog sequence alignments; 10,068 NDD patients and 2078 controls were statistically evaluated for de novo variant burden in gene families.

RESULTS

We demonstrate that disease-associated missense variants are enriched at paralog-conserved sites across all disease groups and inheritance models tested. We developed a gene family de novo enrichment framework that identified 43 exome-wide enriched gene families including 98 de novo variant carrying genes in NDD patients of which 28 represent novel candidate genes for NDD which are brain expressed and under evolutionary constraint.

CONCLUSION

This study represents the first method to incorporate gene family information into a statistical framework to interpret variant data for NDDs and to discover new NDD-associated genes.

Nuclear Pore Complexes: Global Conservation and Local Variation

Nuclear pore complexes are the transport gates to the nucleus. Most proteins forming these huge complexes are evolutionarily conserved, as is the eightfold symmetry of these complexes. A new study reporting the structure of the yeast nuclear pore complex now shows striking differences from its human counterpart.

Identifying drug targets in tissues and whole blood with thermal-shift profiling

Monitoring drug-target interactions with methods such as the cellular thermal-shift assay (CETSA) is well established for simple cell systems but remains challenging in vivo. Here we introduce tissue thermal proteome profiling (tissue-TPP), which measures binding of small-molecule drugs to proteins in tissue samples from drug-treated animals by detecting changes in protein thermal stability using quantitative mass spectrometry. We report organ-specific, proteome-wide thermal stability maps and derive target profiles of the non-covalent histone deacetylase inhibitor panobinostat in rat liver, lung, kidney and spleen and of the B-Raf inhibitor vemurafenib in mouse testis. In addition, we devised blood-CETSA and blood-TPP and applied it to measure target and off-target engagement of panobinostat and the BET family inhibitor JQ1 directly in whole blood. Blood-TPP analysis of panobinostat confirmed its binding to known targets and also revealed thermal stabilization of the zinc-finger transcription factor ZNF512. These methods will help to elucidate the mechanisms of drug action in vivo.

ComplexBrowser: A Tool for Identification and Quantification of Protein Complexes in Large-scale Proteomics Datasets

We have developed ComplexBrowser, an open source, online platform for supervised analysis of quantitative proteomic data (label free and isobaric mass tag based) that focuses on protein complexes. The software uses manually curated information from CORUM and Complex Portal databases to identify protein complex components. For the first time, we provide a Complex Fold Change (CFC) factor that identifies up- and downregulated complexes based on the level of complex subunits coregulation. The software provides interactive visualization of protein complexes' composition and expression for exploratory analysis and incorporates a quality control step that includes normalization and statistical analysis based on the limma package. ComplexBrowser was tested on two published studies identifying changes in protein expression within either human adenocarcinoma tissue or activated mouse T-cells. The analysis revealed 1519 and 332 protein complexes, of which 233 and 41 were found coordinately regulated in the respective studies. The adopted approach provided evidence for a shift to glucose-based metabolism and high proliferation in adenocarcinoma tissues, and the identification of chromatin remodeling complexes involved in mouse T-cell activation. The results correlate with the original interpretation of the experiments and provide novel biological details about the protein complexes affected. ComplexBrowser is, to our knowledge, the first tool to automate quantitative protein complex analysis for high-throughput studies, providing insights into protein complex regulation within minutes of analysis.

Quantitative Proteome Landscape of the NCI-60 Cancer Cell Lines

Here we describe a proteomic data resource for the NCI-60 cell lines generated by pressure cycling technology and SWATH mass spectrometry. We developed the DIA-expert software to curate and visualize the SWATH data, leading to reproducible detection of over 3,100 SwissProt proteotypic proteins and systematic quantification of pathway activities. Stoichiometric relationships of interacting proteins for DNA replication, repair, the chromatin remodeling NuRD complex, β-catenin, RNA metabolism, and prefoldins are more evident than that at the mRNA level. The data are available in CellMiner (discover.nci.nih.gov/cellminercdb and discover.nci.nih.gov/cellminer), allowing casual users to test hypotheses and perform integrative, cross-database analyses of multi-omic drug response correlations for over 20,000 drugs. We demonstrate the value of proteome data in predicting drug response for over 240 clinically relevant chemotherapeutic and targeted therapies. In summary, we present a novel proteome resource for the NCI-60, together with relevant software tools, and demonstrate the benefit of proteome analyses.

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High-quality NCI-60 proteotypes created using pressure cycling technology and SWATH-MS

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Proteotypes improve drug response prediction in multi-omics regression analysis

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∼3000 measured proteins allow investigation into protein complex stoichiometry

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CellMinerCDB (discover.nci.nih.gov/cellminercdb) portal allows dataset exploration

Multidimensional Proteomics Identifies Declines in Protein Homeostasis and Mitochondria as Early Signals for Normal Aging and Age-associated Disease in Drosophila

Aging is characterized by a gradual deterioration in proteome. However, how protein dynamics that changes with normal aging and in disease is less well understood. Here, we profiled the snapshots of aging proteome in Drosophila, from head and muscle tissues of post-mitotic somatic cells, and the testis of mitotically-active cells. Our data demonstrated that dysregulation of proteome homeostasis, or proteostasis, might be a common feature associated with age. We further used pulsed metabolic stable isotope labeling analysis to characterize protein synthesis. Interestingly, this study determined an age-modulated decline in protein synthesis with age, particularly in the pathways related to mitochondria, neurotransmission, and proteostasis. Importantly, this decline became dramatically accelerated in Pink1 mutants, a Drosophila model of human age-related Parkinson's disease. Taken together, our multidimensional proteomic study revealed tissue-specific protein dynamics with age, highlighting mitochondrial and proteostasis-related proteins. We suggest that declines in proteostasis and mitochondria early in life are critical signals prior to the onset of aging and aging-associated diseases.

An integrated genome-wide multi-omics analysis of gene expression dynamics in the preimplantation mouse embryo

Early mouse embryos have an atypical translational machinery that consists of cytoplasmic lattices and is poorly competent for translation. Hence, the impact of transcriptomic changes on the operational level of proteins is predicted to be relatively modest. To investigate this, we performed liquid chromatography–tandem mass spectrometry and mRNA sequencing at seven developmental stages, from the mature oocyte to the blastocyst, and independently validated our data by immunofluorescence and qPCR. We detected and quantified 6,550 proteins and 20,535 protein-coding transcripts. In contrast to the transcriptome – where changes occur early, mostly at the 2-cell stage – our data indicate that the most substantial changes in the proteome take place towards later stages, between the morula and blastocyst. We also found little to no concordance between the changes in protein and transcript levels, especially for early stages, but observed that the concordance increased towards the morula and blastocyst, as did the number of free ribosomes. These results are consistent with the cytoplasmic lattice-to-free ribosome transition being a key mediator of developmental regulation. Finally, we show how these data can be used to appraise the strengths and limitations of mRNA-based studies of pre-implantation development and expand on the list of known developmental markers.

Sexual Dimorphism in the Age of Genomics: How, When, Where

In mammals, sex chromosomes start to program autosomal gene expression and epigenetic patterns very soon after fertilization. Yet whether the resulting sex differences are perpetuated throughout development and how they connect to the sex-specific expression patterns in adult tissues is not known. There is a dearth of information on the timing and continuity of sex biases during development. It is also unclear whether sex-specific selection operates during embryogenesis. On the other hand, there is mounting evidence that all adult tissues exhibit sex-specific expression patterns, some of which are independent of hormonal influence and due to intrinsic regulatory effects of the sex chromosome constitution. There are many diseases with origins during embryogenesis that also exhibit sex biases. Epigenetics has provided us with viable mechanisms to explain how the genome stores the memory of developmental events. We propose that some of these marks can be traced back to the sex chromosomes, which interact with the autosomes and establish sex-specific epigenetic features soon after fertilization. Sex-biased epigenetic marks that linger after reprograming may reveal themselves at the transcriptional level at later developmental stages and possibly, throughout the lifespan. Detailed molecular information on the ontogeny of sex biases would also elucidate the sex-specific selective pressures operating on embryos and how compensatory mechanisms evolved to resolve sexual conflict.

Paralog dependency indirectly affects the robustness of human cells

The protective redundancy of paralogous genes partly relies on the fact that they carry their functions independently. However, a significant fraction of paralogous proteins may form functionally dependent pairs, for instance, through heteromerization. As a consequence, one could expect these heteromeric paralogs to be less protective against deleterious mutations. To test this hypothesis, we examined the robustness landscape of gene loss-of-function by CRISPR-Cas9 in more than 450 human cell lines. This landscape shows regions of greater deleteriousness to gene inactivation as a function of key paralog properties. Heteromeric paralogs are more likely to occupy such regions owing to their high expression and large number of protein-protein interaction partners. Further investigation revealed that heteromers may also be under stricter dosage balance, which may also contribute to the higher deleteriousness upon gene inactivation. Finally, we suggest that physical dependency may contribute to the deleteriousness upon loss-of-function as revealed by the correlation between the strength of interactions between paralogs and their higher deleteriousness upon loss of function.

Chromosome-wide co-fluctuation of stochastic gene expression in mammalian cells

Gene expression is subject to stochastic noise, but to what extent and by which means such stochastic variations are coordinated among different genes are unclear. We hypothesize that neighboring genes on the same chromosome co-fluctuate in expression because of their common chromatin dynamics, and verify it at the genomic scale using allele-specific single-cell RNA-sequencing data of mouse cells. Unexpectedly, the co-fluctuation extends to genes that are over 60 million bases apart. We provide evidence that this long-range effect arises in part from chromatin co-accessibilities of linked loci attributable to three-dimensional proximity, which is much closer intra-chromosomally than inter-chromosomally. We further show that genes encoding components of the same protein complex tend to be chromosomally linked, likely resulting from natural selection for intracellular among-component dosage balance. These findings have implications for both the evolution of genome organization and optimal design of synthetic genomes in the face of gene expression noise.

Protein aggregation mediates stoichiometry of protein complexes in aneuploid cells

In this study, Brennan et al. identify protein complex stoichiometry imbalances as a major cause of protein aggregation in aneuploid cells. They propose that proteotoxic stress is a universal feature of aneuploid cells and show that degradation and aggregation of excess polypeptides function as a form of dosage compensation.

Aneuploidy, a condition characterized by chromosome gains and losses, causes reduced fitness and numerous cellular stresses, including increased protein aggregation. Here, we identify protein complex stoichiometry imbalances as a major cause of protein aggregation in aneuploid cells. Subunits of protein complexes encoded on excess chromosomes aggregate in aneuploid cells, which is suppressed when expression of other subunits is coordinately altered. We further show that excess subunits are either degraded or aggregate and that protein aggregation is nearly as effective as protein degradation at lowering levels of excess proteins. Our study explains why proteotoxic stress is a universal feature of the aneuploid state and reveals protein aggregation as a form of dosage compensation to cope with disproportionate expression of protein complex subunits.

Differential analysis of combinatorial protein complexes with CompleXChange

BACKGROUND

Although a considerable number of proteins operate as multiprotein complexes and not on their own, organism-wide studies so far are only able to quantify individual proteins or protein-coding genes in a condition-specific manner for a sizeable number of samples, but not their assemblies. Consequently, there exist large amounts of transcriptomic data and an increasing amount of data on proteome abundance, but quantitative knowledge on complexomes is missing. This deficiency impedes the applicability of the powerful tool of differential analysis in the realm of macromolecular complexes. Here, we present a pipeline for differential analysis of protein complexes based on predicted or manually assigned complexes and inferred complex abundances, which can be easily applied on a whole-genome scale.

RESULTS

We observed for simulated data that results obtained by our complex abundance estimation algorithm were in better agreement with the ground truth and physicochemically more reasonable compared to previous efforts that used linear programming while running in a fraction of the time. The practical usability of the method was assessed in the context of transcription factor complexes in human monocyte and lymphoblastoid samples. We demonstrated that our new method is robust against false-positive detection and reports deregulated complexomes that can only be partially explained by differential analysis of individual protein-coding genes. Furthermore we showed that deregulated complexes identified by the tool potentially harbor significant yet unused information content.

CONCLUSIONS

CompleXChange allows to analyze deregulation of the protein complexome on a whole-genome scale by integrating a plethora of input data that is already available. A platform-independent Java binary, a user guide with example data and the source code are freely available at https://sourceforge.net/projects/complexchange/ .

Disentangling Genetic and Environmental Effects on the Proteotypes of Individuals

Proteotypes, like genotypes, have been found to vary between individuals in several studies, but consistent molecular functional traits across studies remain to be quantified. In a meta-analysis of 11 proteomics datasets from humans and mice, we use co-variation of proteins in known functional modules across datasets and individuals to obtain a consensus landscape of proteotype variation. We find that individuals differ considerably in both protein complex abundances and stoichiometry. We disentangle genetic and environmental factors impacting these metrics, with genetic sex and specific diets together explaining 13.5% and 11.6% of the observed variation of complex abundance and stoichiometry, respectively. Sex-specific differences, for example, include various proteins and complexes, where the respective genes are not located on sex-specific chromosomes. Diet-specific differences, added to the individual genetic backgrounds, might become a starting point for personalized proteotype modulation toward desired features.

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Benchmarking of datasets on human and mouse proteotypes

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Consistent co-variation landscape of functional modules across individuals

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Protein complexes vary in their stoichiometry across individuals

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Quantifying effects of genetic sex and specific diets on complexes