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Lipids tailor membrane identities and function as molecular hubs in all cellular processes. The development of pioneering technologies, including affinity-purification lipidomics and the liposome microarray-based assay (LiMA), will enable researchers to decipher protein–lipid interactions and enhance our understanding of how lipids modulate protein function and structure. Lipids tailor membrane identities and function as molecular hubs in all cellular processes. However, the ways in which lipids modulate protein function and structure are poorly understood and still require systematic investigation. In this Innovation article, we summarize pioneering technologies, including lipid-overlay assays, lipid pull-down assays, affinity-purification lipidomics and the liposome microarray-based assay (LiMA), that will enable protein–lipid interactions to be deciphered on a systems level. We discuss how these technologies can be applied to the charting of system-wide networks and to the development of new pharmaceutical strategies.

Various post‐translational modifications (PTMs) fine‐tune the functions of almost all eukaryotic proteins, and co‐regulation of different types of PTMs has been shown within and between a number of proteins. Aiming at a more global view of the interplay between PTM types, we collected modifications for 13 frequent PTM types in 8 eukaryotes, compared their speed of evolution and developed a method for measuring PTM co‐evolution within proteins based on the co‐occurrence of sites across eukaryotes. As many sites are still to be discovered, this is a considerable underestimate, yet, assuming that most co‐evolving PTMs are functionally associated, we found that PTM types are vastly interconnected, forming a global network that comprise in human alone >50 000 residues in about 6000 proteins. We predict substantial PTM type interplay in secreted and membrane‐associated proteins and in the context of particular protein domains and short‐linear motifs. The global network of co‐evolving PTM types implies a complex and intertwined post‐translational regulation landscape that is likely to regulate multiple functional states of many if not all eukaryotic proteins. This study is the first large‐scale comparative analysis of multiple types of post‐translational modifications in different eukaryotic species. The resulting network of co‐evolving and functionally associated modifications reveals the global landscape of post‐translational regulation. Synopsis This study is the first large‐scale comparative analysis of multiple types of post‐translational modifications in different eukaryotic species. The resulting network of co‐evolving and functionally associated modifications reveals the global landscape of post‐translational regulation. In all, 115 149 non‐redundant post‐translational modifications (PTMs) of 13 different types were collected from 8 eukaryotes. Comparison of evolution speed reveals that carboxylation is the most conserved while SUMOylation is the fastest evolving PTM type. Co‐evolution of PTM pairs that co‐occur within proteins reveals a vastly interconnected global network of functionally associated PTM types in eukaryotes. Central to the network of functionally associated PTM types appear phosphorylation, acetylation, ubiquitination and O‐linked glycosylation that control both temporal events and processes that govern protein localization.

Targets for drugs have so far been predicted on the basis of molecular or cellular features, for example, by exploiting similarity in chemical structure or in activity across cell lines. We used phenotypic side-effect similarities to infer whether two drugs share a target. Applied to 746 marketed drugs, a network of 1018 side effect-driven drug-drug relations became apparent, 261 of which are formed by chemically dissimilar drugs from different therapeutic indications. We experimentally tested 20 of these unexpected drug-drug relations and validated 13 implied drug-target relations by in vitro binding assays, of which 11 reveal inhibition constants equal to less than 10 micromolar. Nine of these were tested and confirmed in cell assays, documenting the feasibility of using phenotypic information to infer molecular interactions and hinting at new uses of marketed drugs.

Biological function and cellular responses to environmental perturbations are regulated by a complex interplay of DNA, RNA, proteins and metabolites inside cells. To understand these central processes in living systems at the molecular level, we integrated experimentally determined abundance data for mRNA, proteins, as well as individual protein half‐lives from the genome‐reduced bacterium Mycoplasma pneumoniae . We provide a fine‐grained, quantitative analysis of basic intracellular processes under various external conditions. Proteome composition changes in response to cellular perturbations reveal specific stress response strategies. The regulation of gene expression is largely decoupled from protein dynamics and translation efficiency has a higher regulatory impact on protein abundance than protein turnover. Stochastic simulations using in vivo data show how low translation efficiency and long protein half‐lives effectively reduce biological noise in gene expression. Protein abundances are regulated in functional units, such as complexes or pathways, and reflect cellular lifestyles. Our study provides a detailed integrative analysis of average cellular protein abundances and the dynamic interplay of mRNA and proteins, the central biomolecules of a cell. Synopsis A hallmark of Systems Biology is the integration of diverse, large quantitative data sets with the aim to gain novel insights into how biological processes work. We measured individual mRNA and protein abundances as well as protein turnover in the bacterium Mycoplasma pneumoniae . This human pathogen is an ideal model organism for organism‐wide studies. It can be readily cultured under laboratory conditions and it has a very small genome with only 690 protein‐coding genes. This comparably low complexity allows for the exhaustive analysis of major cellular biomolecules avoiding constrains introduced by limitations of available analysis techniques. Using a recently developed mass spectrometry‐based approach, we determined the average cellular copy number for over 400 individual proteins under different growth and stress conditions. The 20 most abundant proteins, including Elongation factor Tu, cellular chaperones, and proteins involved in metabolizing glucose, the major energy source of M. pneumoniae account for nearly 44% of the total cellular protein mass. We observed abundance changes of many expected and several unexpected proteins in response to cellular stress, such as heat shock, DNA damage and osmotic stress, as well as along batch culture growth over 4 days. Integration of the protein abundance data with quantitative mRNA measurements revealed a modest correlation between these two classes of biomolecules. However, for several classical stress‐induced proteins, we observed a correlated induction of mRNA and protein in response to heat shock. A focused analysis of mRNA–protein abundance dynamics during batch culture growth suggested that the regulation of gene expression is largely decoupled from protein dynamics in M. pneumoniae , indicating extensive post‐transcriptional and post‐translational regulation influencing the cellular mRNA–protein ratios. To investigate the factors influencing the cellular protein abundance, we measured individual protein turnover rates by mass spectrometry using a label‐chase approach involving stable isotope‐labelled amino acids. The average half‐life of a protein in M. pneumoniae is 23 h. Based on the measured quantitative mRNA data, the protein abundances and their half‐lives, we established an ordinary differential equations model for the estimation of individual in vivo protein degradation and translation efficiency rates. We found out that translation efficiency rather than protein turnover is the dominating factor influencing protein abundance. Using our abundance and turnover data, we additionally performed stochastic simulations of gene expression. We observed that long protein half‐life and low translational efficiency buffers gene expression noise propagating from low cellular mRNA levels in vivo. We compared the abundance ratios of proteins associating into complexes in vivo with their expected functional stoichiometries. We observed that for stable protein complexes, such as the GroEL/ES chaperonin or DNA gyrase, our measured abundance ratios reflected the expected subunit stoichiometries. More dynamic protein complexes, such as the DnaK/J/GrpE chaperone system or RNA polymerase, showed several unusual subunit ratios, pointing towards transient interaction of sub‐stoichiometric subunits for function. A detailed, quantitative analysis of the ribosome, the largest cellular protein complex, revealed large abundance differences of the 51 subunits. This observation indicates a multi‐functionality for several, abundant ribosomal proteins. Finally, a comparison of the determined average cellular protein abundances with a different pathogenic bacterium, Leptospira interrogans , revealed that cellular protein abundances closely reflect their respective lifestyles. Our study represents an organism‐wide, quantitative analysis of cellular protein abundances. Integrating our proteomics data with determined mRNA levels and protein turnover rates reveals insights into the dynamic interplay and regulation of mRNA and proteins, the central biomolecules of a cell. Our study provides a fine‐grained, quantitative picture to unprecedented detail in an established model organism for systems‐wide studies. Our integrative approach reveals a novel, dynamic view on the processes, interactions and regulations underlying the central dogma pathway and the composition of protein complexes. Simulations using our quantitative data on mRNA, protein and turnover show how an organism copes with stochastic noise in gene expression in vivo . Our data serve as an important resource for colleagues both within our field of research and in related disciplines.

The lipid-binding profiles of all lipid-transfer proteins in Saccharomyces cerevisiae are determined and a new subfamily of oxysterol-binding proteins that function in phosphatidylserine homeostasis and transport is identified. A novel family of phosphatidylserine transport proteins Eukaryotic cells are compartmentalized internally by a series of functionally specialized membrane-bound organelles with unique lipid composition. In this study, Anne-Claude Gavin and colleagues determine the lipid-binding profiles of all lipid-transfer proteins in the budding yeast Saccharomyces cerevisiae , and identify a previously unrecognized subfamily of oxysterol-binding proteins (OSBPs) that function in phosphatidylserine homeostasis and transport rather than in the transfer of sterols. Phylogenetic analysis shows that similar OSPBs are broadly conserved — including in humans where they are associated with pathologies including cancer and metabolic syndrome. The internal organization of eukaryotic cells into functionally specialized, membrane-delimited organelles of unique composition implies a need for active, regulated lipid transport. Phosphatidylserine (PS), for example, is synthesized in the endoplasmic reticulum and then preferentially associates—through mechanisms not fully elucidated—with the inner leaflet of the plasma membrane 1 , 2 , 3 . Lipids can travel via transport vesicles. Alternatively, several protein families known as lipid-transfer proteins (LTPs) can extract a variety of specific lipids from biological membranes and transport them, within a hydrophobic pocket, through aqueous phases 4 , 5 , 6 , 7 . Here we report the development of an integrated approach that combines protein fractionation and lipidomics to characterize the LTP–lipid complexes formed in vivo . We applied the procedure to 13 LTPs in the yeast Saccharomyces cerevisiae : the six Sec14 homology (Sfh) proteins and the seven oxysterol-binding homology (Osh) proteins. We found that Osh6 and Osh7 have an unexpected specificity for PS. In vivo , they participate in PS homeostasis and the transport of this lipid to the plasma membrane. The structure of Osh6 bound to PS reveals unique features that are conserved among other metazoan oxysterol-binding proteins (OSBPs) and are required for PS recognition. Our findings represent the first direct evidence, to our knowledge, for the non-vesicular transfer of PS from its site of biosynthesis (the endoplasmic reticulum) to its site of biological activity (the plasma membrane). We describe a new subfamily of OSBPs, including human ORP5 and ORP10, that transfer PS and propose new mechanisms of action for a protein family that is involved in several human pathologies such as cancer, dyslipidaemia and metabolic syndrome.

Identifying all essential genomic components is critical for the assembly of minimal artificial life. In the genome‐reduced bacterium Mycoplasma pneumoniae , we found that small ORFs (smORFs; < 100 residues), accounting for 10% of all ORFs, are the most frequently essential genomic components (53%), followed by conventional ORFs (49%). Essentiality of smORFs may be explained by their function as members of protein and/or DNA/RNA complexes. In larger proteins, essentiality applied to individual domains and not entire proteins, a notion we could confirm by expression of truncated domains. The fraction of essential non‐coding RNAs (ncRNAs) non‐overlapping with essential genes is 5% higher than of non‐transcribed regions (0.9%), pointing to the important functions of the former. We found that the minimal essential genome is comprised of 33% (269,410 bp) of the M. pneumoniae genome. Our data highlight an unexpected hidden layer of smORFs with essential functions, as well as non‐coding regions, thus changing the focus when aiming to define the minimal essential genome. Synopsis A genome essentiality analysis in the genome‐reduced bacterium Mycoplasma pneumoniae , reveals that protein essentiality should be considered at the domain level and that small proteins (< 100 aa) and ncRNAs are frequently essential genomic elements. A genome essentiality analysis is performed using two mini‐transposon mutant libraries of M. pneumoniae . The results indicate that ORF essentiality should be considered at the protein domain level. Small ORFs are as essential as conventional ORFs and they can interact with DNA. Some essential antisense ncRNAs are involved in the regulation of essential ORF expression. Graphical Abstract A genome essentiality analysis in the genome‐reduced bacterium Mycoplasma pneumoniae , reveals that protein essentiality should be considered at the domain level and that small proteins (< 100 aa) and ncRNAs are frequently essential genomic elements.

Side effect similarities of drugs have recently been employed to predict new drug targets, and networks of side effects and targets have been used to better understand the mechanism of action of drugs. Here, we report a large‐scale analysis to systematically predict and characterize proteins that cause drug side effects. We integrated phenotypic data obtained during clinical trials with known drug–target relations to identify overrepresented protein–side effect combinations. Using independent data, we confirm that most of these overrepresentations point to proteins which, when perturbed, cause side effects. Of 1428 side effects studied, 732 were predicted to be predominantly caused by individual proteins, at least 137 of them backed by existing pharmacological or phenotypic data. We prove this concept in vivo by confirming our prediction that activation of the serotonin 7 receptor (HTR7) is responsible for hyperesthesia in mice, which, in turn, can be prevented by a drug that selectively inhibits HTR7. Taken together, we show that a large fraction of complex drug side effects are mediated by individual proteins and create a reference for such relations. Protein–side effects associations are identified by integrating drug–target data with side effects information from drug labels. Benchmarking against the literature and validation with an in vivo mouse model shows that these pairs correspond to causal relations. Synopsis Protein–side effects associations are identified by integrating drug–target data with side effects information from drug labels. Benchmarking against the literature and validation with an in vivo mouse model shows that these pairs correspond to causal relations. For more than half of the investigated side effects, we can predict causal proteins. Off‐targets contribute slightly more to the explained side effects than main targets. With the current data, we are most successful in explaining the side effects of drugs that target G protein‐coupled receptors. Activation of HTR7 causes hyperesthesia in mice, explaining a side effect of triptan drugs.

In pharmacology, it is crucial to understand the complex biological responses that drugs elicit in the human organism and how well they can be inferred from model organisms. We therefore identified a large set of drug‐induced transcriptional modules from genome‐wide microarray data of drug‐treated human cell lines and rat liver, and first characterized their conservation. Over 70% of these modules were common for multiple cell lines and 15% were conserved between the human in vitro and the rat in vivo system. We then illustrate the utility of conserved and cell‐type‐specific drug‐induced modules by predicting and experimentally validating (i) gene functions, e.g., 10 novel regulators of cellular cholesterol homeostasis and (ii) new mechanisms of action for existing drugs, thereby providing a starting point for drug repositioning, e.g., novel cell cycle inhibitors and new modulators of α ‐adrenergic receptor, peroxisome proliferator‐activated receptor and estrogen receptor. Taken together, the identified modules reveal the conservation of transcriptional responses towards drugs across cell types and organisms, and improve our understanding of both the molecular basis of drug action and human biology. Drug‐induced transcriptional modules (biclusters) were identified and annotated in three human cell lines and rat liver. These were used to assess conservation across systems and to infer and experimentally validate novel drug effects and gene functions. Synopsis Drug‐induced transcriptional modules (biclusters) were identified and annotated in three human cell lines and rat liver. These were used to assess conservation across systems and to infer and experimentally validate novel drug effects and gene functions. Biclustering of drug‐induced gene expression profiles resulted in modules of drugs and genes, which were enriched in both drug and gene annotations. Identifying drug‐induced transcriptional modules separately in three human cell lines and rat liver allows assessment of their conservation across model systems. About 70% of modules are conserved across cell lines, a lower bound of 15% was estimated for their conservation across organisms, and between the in vitro and in vivo systems. Drug‐induced transcriptional modules can predict novel gene functions. A conserved module associated with (chole)sterol metabolism revealed novel regulators of cellular cholesterol homeostasis; 10 of them were validated in functional imaging assays. Analysis of drugs clustered into modules can give new insights into their mechanisms of action and provide leads for drug repositioning. We predicted and experimentally validated novel cell cycle inhibitors and modulators of PPARγ, estrogen and adrenergic receptors, with potential for developing new therapies against diabetes and cancer.

The arrangement of proteins into complexes is a key organizational principle for many cellular functions. Although the topology of many complexes has been systematically analyzed in isolation, their molecular sociology in situ remains elusive. Here, we show that crude cellular extracts of a eukaryotic thermophile, Chaetomium thermophilum , retain basic principles of cellular organization. Using a structural proteomics approach, we simultaneously characterized the abundance, interactions, and structure of a third of the C. thermophilum proteome within these extracts. We identified 27 distinct protein communities that include 108 interconnected complexes, which dynamically associate with each other and functionally benefit from being in close proximity in the cell. Furthermore, we investigated the structure of fatty acid synthase within these extracts by cryoEM and this revealed multiple, flexible states of the enzyme in adaptation to its association with other complexes, thus exemplifying the need for in situ studies. As the components of the captured protein communities are known—at both the protein and complex levels—this study constitutes another step forward toward a molecular understanding of subcellular organization. Synopsis An integrative structural systems biology approach is presented to systematically characterize native protein communities of dynamically associated protein complexes. Cryo‐electron microscopy detects a metabolon involved in fatty acid synthesis at unprecedented molecular details. In addition to the grouping of proteins into complexes, intracellular function requires a further layer of organization that involves multiple spatially and temporally interacting macromolecular complexes or protein communities. However, experimental approaches to capture this higher‐order proteome organization are still missing. Here, we show that crude cellular fractions from a thermophilic eukaryote retain basic principles of proteome organization, and can be exploited to capture protein communities through integrative structural biology approaches. We report a compendium of 27 protein communities and have experimentally characterized and structurally analyzed one of these comprising enzymes involved in fatty acid metabolism. From the crude extracts, we obtained a cryo‐EM structure of fungal fatty acid synthase that reveals a thus far uncharacterized catalytic intermediate. We demonstrate the feasibility of high‐resolution cryoEM without the need to obtain biochemically highly homogenous samples. Graphical Abstract An integrative structural systems biology approach is presented to systematically characterize native protein communities of dynamically associated protein complexes. Cryo‐electron microscopy detects a metabolon involved in fatty acid synthesis at unprecedented molecular details.

Protein post‐translational modifications (PTMs) represent important regulatory states that when combined have been hypothesized to act as molecular codes and to generate a functional diversity beyond genome and transcriptome. We systematically investigate the interplay of protein phosphorylation with other post‐transcriptional regulatory mechanisms in the genome‐reduced bacterium Mycoplasma pneumoniae . Systematic perturbations by deletion of its only two protein kinases and its unique protein phosphatase identified not only the protein‐specific effect on the phosphorylation network, but also a modulation of proteome abundance and lysine acetylation patterns, mostly in the absence of transcriptional changes. Reciprocally, deletion of the two putative N ‐acetyltransferases affects protein phosphorylation, confirming cross‐talk between the two PTMs. The measured M. pneumoniae phosphoproteome and lysine acetylome revealed that both PTMs are very common, that (as in Eukaryotes) they often co‐occur within the same protein and that they are frequently observed at interaction interfaces and in multifunctional proteins. The results imply previously unreported hidden layers of post‐transcriptional regulation intertwining phosphorylation with lysine acetylation and other mechanisms that define the functional state of a cell. The effect of kinase, phosphatase and N ‐acetyltransferase deletions on proteome phosphorylation and acetylation was investigated in Mycoplasma pneumoniae . Bi‐directional cross‐talk between post‐transcriptional modifications suggests an underlying regulatory molecular code in prokaryotes. Synopsis The effect of kinase, phosphatase and N ‐acetyltransferase deletions on proteome phosphorylation and acetylation was investigated in Mycoplasma pneumoniae . Bi‐directional cross‐talk between post‐transcriptional modifications suggests an underlying regulatory molecular code in prokaryotes. Post‐translational modifications (PTMs) change the chemical properties of proteins, conferring diversity beyond the amino‐acid sequence. Proteins are often modified on multiple sites. A PTM code has been proposed, whereby modifications at specific positions influence further modifications. These regulatory circuits though have rarely been studied on a large‐scale; conservation in prokaryotes remains elusive. Here, we studied two important PTMs– phosphorylation and lysine acetylation in the small bacterium Mycoplasma pneumoniae . We combined genetics and quantitative mass spectrometry to measure the effect of systematic kinase, phosphatase and N ‐acetyltransferase deletions on proteome abundance, phosphorylation and lysine acetylation. The data set represents a comprehensive analysis of both phosphorylation and lysine acetylation in a single prokaryote. It reveals (1) proteins often carry multiple modifications and multiple types of PTMs, reminiscent of the PTM code proposed in eukaryotes, (2) phosphorylation exerts pleiotropic effect on proteins abundances, phosphorylation, but also lysine acetylation, (3) the cross‐talk between the two PTMs is bi‐directional and (4) PTMs are frequently located at interaction interfaces and in multifunctional proteins, illustrating how PTMs could modulate protein functions affecting the way they interact. The study provides an unbiased and quantitative view on cross‐talk between phosphorylation and lysine acetylation. It suggests that these regulatory circuits are a fundamental principle of regulation that might have evolved before the divergence of prokaryotes and eukaryotes.