Quantitative proteome dynamics across embryogenesis in a model chordate.

The evolution of gene expression programs underlying the development of vertebrates remains poorly characterized. Here, we present a comprehensive proteome atlas of the model chordate Ciona, covering eight developmental stages and ∼7,000 translated genes, accompanied by a multi-omics analysis of co-evolution with the vertebrate Xenopus. Quantitative proteome comparisons argue against the widely held hourglass model, based solely on transcriptomic profiles, whereby peak conservation is observed during mid-developmental stages. Our analysis reveals maximal divergence at these stages, particularly gastrulation and neurulation. Together, our work provides a valuable resource for evaluating conservation and divergence of multi-omics profiles underlying the diversification of vertebrates.

Mitochondrial ATP generation is more proteome efficient than glycolysis.

Metabolic efficiency profoundly influences organismal fitness. Nonphotosynthetic organisms, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. Although respiration is more energy efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (that is, faster). Through quantitative flux analysis and proteomics, we find, however, that mitochondrial respiration is actually more proteome efficient than aerobic glycolysis. This is shown across yeast strains, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which promotes hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth but outgrow respiratory cells during oxygen limitation. We accordingly propose that aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.

Evidence for widespread cytoplasmic structuring into mesoscale condensates.

Compartmentalization is an essential feature of eukaryotic life and is achieved both via membrane-bound organelles, such as mitochondria, and membrane-less biomolecular condensates, such as the nucleolus. Known biomolecular condensates typically exhibit liquid-like properties and are visualized by microscopy on the scale of ~1 µm (refs. 1,2). They have been studied mostly by microscopy, examining select individual proteins. So far, several dozen biomolecular condensates are known, serving a multitude of functions, for example, in the regulation of transcription3, RNA processing4 or signalling5,6, and their malfunction can cause diseases7,8. However, it remains unclear to what extent biomolecular condensates are utilized in cellular organization and at what length scale they typically form. Here we examine native cytoplasm from Xenopus egg extract on a global scale with quantitative proteomics, filtration, size exclusion and dilution experiments. These assays reveal that at least 18% of the proteome is organized into mesoscale biomolecular condensates at the scale of ~100 nm and appear to be stabilized by RNA or gelation. We confirmed mesoscale sizes via imaging below the diffraction limit by investigating protein permeation into porous substrates with defined pore sizes. Our results show that eukaryotic cytoplasm organizes extensively via biomolecular condensates, but at surprisingly short length scales.

Systematic identification and characterization of genes in the regulation and biogenesis of photosynthetic machinery.

Photosynthesis is central to food production and the Earth's biogeochemistry, yet the molecular basis for its regulation remains poorly understood. Here, using high-throughput genetics in the model eukaryotic alga Chlamydomonas reinhardtii, we identify with high confidence (false discovery rate [FDR] < 0.11) 70 poorly characterized genes required for photosynthesis. We then enable the functional characterization of these genes by providing a resource of proteomes of mutant strains, each lacking one of these genes. The data allow assignment of 34 genes to the biogenesis or regulation of one or more specific photosynthetic complexes. Further analysis uncovers biogenesis/regulatory roles for at least seven proteins, including five photosystem I mRNA maturation factors, the chloroplast translation factor MTF1, and the master regulator PMR1, which regulates chloroplast genes via nuclear-expressed factors. Our work provides a rich resource identifying regulatory and functional genes and placing them into pathways, thereby opening the door to a system-level understanding of photosynthesis.

Phase plane dynamics of ERK phosphorylation.

The extracellular signal-regulated kinase (ERK) controls multiple critical processes in the cell and is deregulated in human cancers, congenital abnormalities, immune diseases, and neurodevelopmental syndromes. Catalytic activity of ERK requires dual phosphorylation by an upstream kinase, in a mechanism that can be described by two sequential Michaelis-Menten steps. The estimation of individual reaction rate constants from kinetic data in the full mechanism has proved challenging. Here, we present an analytically tractable approach to parameter estimation that is based on the phase plane representation of ERK activation and yields two combinations of six reaction rate constants in the detailed mechanism. These combinations correspond to the ratio of the specificities of two consecutive phosphorylations and the probability that monophosphorylated substrate does not dissociate from the enzyme before the second phosphorylation. The presented approach offers a language for comparing the effects of mutations that disrupt ERK activation and function in vivo. As an illustration, we use phase plane representation to analyze dual phosphorylation under heterozygous conditions, when two enzyme variants compete for the same substrate.

Slow TCA flux and ATP production in primary solid tumours but not metastases.

Tissues derive ATP from two pathways-glycolysis and the tricarboxylic acid (TCA) cycle coupled to the electron transport chain. Most energy in mammals is produced via TCA metabolism1. In tumours, however, the absolute rates of these pathways remain unclear. Here we optimize tracer infusion approaches to measure the rates of glycolysis and the TCA cycle in healthy mouse tissues, Kras-mutant solid tumours, metastases and leukaemia. Then, given the rates of these two pathways, we calculate total ATP synthesis rates. We find that TCA cycle flux is suppressed in all five primary solid tumour models examined and is increased in lung metastases of breast cancer relative to primary orthotopic tumours. As expected, glycolysis flux is increased in tumours compared with healthy tissues (the Warburg effect2,3), but this increase is insufficient to compensate for low TCA flux in terms of ATP production. Thus, instead of being hypermetabolic, as commonly assumed, solid tumours generally produce ATP at a slower than normal rate. In mouse pancreatic cancer, this is accommodated by the downregulation of protein synthesis, one of this tissue's major energy costs. We propose that, as solid tumours develop, cancer cells shed energetically expensive tissue-specific functions, enabling uncontrolled growth despite a limited ability to produce ATP.

Super-Resolution Mass Spectrometry Enables Rapid, Accurate, and Highly Multiplexed Proteomics at the MS2 Level.

In tandem mass spectrometry (MS2)-based multiplexed quantitative proteomics, the complement reporter ion approaches (TMTc and TMTproC) were developed to eliminate the ratio-compression problem of conventional MS2-level approaches. Resolving all high m/z complement reporter ions (∼6.32 mDa-spaced) requires mass resolution and scan speeds above the performance levels of OrbitrapTM instruments. Therefore, complement reporter ion quantification with TMT/TMTpro reagents is currently limited to 5 out of 11 (TMT) or 9 out of 18 (TMTpro) channels (∼1 Da spaced). We first demonstrate that a FusionTM LumosTM Orbitrap can resolve 6.32 mDa-spaced complement reporter ions with standard acquisition modes extended with 3 s transients. We then implemented a super-resolution mass spectrometry approach using the least-squares fitting (LSF) method for processing Orbitrap transients to achieve shotgun proteomics-compatible scan rates. The LSF performance resolves the 6.32 mDa doublets for all TMTproC channels in the standard mass range with transients as short as ∼108 ms (Orbitrap resolution setting of 50,000 at m/z 200). However, we observe a slight decrease in measurement precision compared to 1 Da spacing with the 108 ms transients. With 256 ms transients (resolution of 120,000 at m/z 200), coefficients of variation are essentially indistinguishable from 1 Da samples. We thus demonstrate the feasibility of highly multiplexed, accurate, and precise shotgun proteomics at the MS2 level.

Differential nuclear import sets the timing of protein access to the embryonic genome.

The development of a fertilized egg to an embryo requires the proper temporal control of gene expression. During cell differentiation, timing is often controlled via cascades of transcription factors (TFs). However, in early development, transcription is often inactive, and many TF levels stay constant, suggesting that alternative mechanisms govern the observed rapid and ordered onset of gene expression. Here, we find that in early embryonic development access of maternally deposited nuclear proteins to the genome is temporally ordered via importin affinities, thereby timing the expression of downstream targets. We quantify changes in the nuclear proteome during early development and find that nuclear proteins, such as TFs and RNA polymerases, enter the nucleus sequentially. Moreover, we find that the timing of nuclear proteins' access to the genome corresponds to the timing of downstream gene activation. We show that the affinity of proteins to importin is a major determinant in the timing of protein entry into embryonic nuclei. Thus, we propose a mechanism by which embryos encode the timing of gene expression in early development via biochemical affinities. This process could be critical for embryos to organize themselves before deploying the regulatory cascades that control cell identities.

Gut bacterial nutrient preferences quantified in vivo.

Great progress has been made in understanding gut microbiomes' products and their effects on health and disease. Less attention, however, has been given to the inputs that gut bacteria consume. Here, we quantitatively examine inputs and outputs of the mouse gut microbiome, using isotope tracing. The main input to microbial carbohydrate fermentation is dietary fiber and to branched-chain fatty acids and aromatic metabolites is dietary protein. In addition, circulating host lactate, 3-hydroxybutyrate, and urea (but not glucose or amino acids) feed the gut microbiome. To determine the nutrient preferences across bacteria, we traced into genus-specific bacterial protein sequences. We found systematic differences in nutrient use: most genera in the phylum Firmicutes prefer dietary protein, Bacteroides dietary fiber, and Akkermansia circulating host lactate. Such preferences correlate with microbiome composition changes in response to dietary modifications. Thus, diet shapes the microbiome by promoting the growth of bacteria that preferentially use the ingested nutrients.

GCN2 adapts protein synthesis to scavenging-dependent growth.

Pancreatic cancer cells with limited access to free amino acids can grow by scavenging extracellular protein. In a murine model of pancreatic cancer, we performed a genome-wide CRISPR screen for genes required for scavenging-dependent growth. The screen identified key mediators of macropinocytosis, peripheral lysosome positioning, endosome-lysosome fusion, lysosomal protein catabolism, and translational control. The top hit was GCN2, a kinase that suppresses translation initiation upon amino acid depletion. Using isotope tracers, we show that GCN2 is not required for protein scavenging. Instead, GCN2 prevents ribosome stalling but without slowing protein synthesis; cells still use all of the limiting amino acids as they emerge from lysosomes. GCN2 also adapts gene expression to the nutrient-poor environment, reorienting protein synthesis away from ribosomes and toward lysosomal hydrolases, such as cathepsin L. GCN2, cathepsin L, and the other genes identified in the screen are potential therapeutic targets in pancreatic cancer.

The Shuttling Cascade in Lasso Peptide Benenodin-1 is Controlled by Non-Covalent Interactions.

The lasso peptide benenodin-1, a naturally occurring and bacterially produced [1]rotaxane, undergoes a reversible zip tie-like motion under heat activation, in which a peptidic wheel stepwise translates along a molecular thread in a cascade of "tail/loop pulling" equilibria. Conformational and structural analyses of four translational isomers, in solution and in the gas phase, reveal that the equilibrium distribution is controlled by mechanical and non-covalent forces within the lasso peptide. Furthermore, each dynamic pulling step is accompanied by a major restructuring of the intramolecular hydrogen bonding network between wheel and thread, which affects the peptide's physico-chemical properties.

Activity-based RNA-modifying enzyme probing reveals DUS3L-mediated dihydrouridylation.

Epitranscriptomic RNA modifications can regulate RNA activity; however, there remains a major gap in our understanding of the RNA chemistry present in biological systems. Here we develop RNA-mediated activity-based protein profiling (RNABPP), a chemoproteomic strategy that relies on metabolic RNA labeling, mRNA interactome capture and quantitative proteomics, to investigate RNA-modifying enzymes in human cells. RNABPP with 5-fluoropyrimidines allowed us to profile 5-methylcytidine (m5C) and 5-methyluridine (m5U) methyltransferases. Further, we uncover a new mechanism-based crosslink between 5-fluorouridine (5-FUrd)-modified RNA and the dihydrouridine synthase (DUS) homolog DUS3L. We investigate the mechanism of crosslinking and use quantitative nucleoside liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis and 5-FUrd-based crosslinking and immunoprecipitation (CLIP) sequencing to map DUS3L-dependent dihydrouridine (DHU) modifications across the transcriptome. Finally, we show that DUS3L-knockout (KO) cells have compromised protein translation rates and impaired cellular proliferation. Taken together, our work provides a general approach for profiling RNA-modifying enzyme activity in living cells and reveals new pathways for epitranscriptomic RNA regulation.

Evaluating the Arrhenius equation for developmental processes.

The famous Arrhenius equation is well suited to describing the temperature dependence of chemical reactions but has also been used for complicated biological processes. Here, we evaluate how well the simple Arrhenius equation predicts complex multi-step biological processes, using frog and fruit fly embryogenesis as two canonical models. We find that the Arrhenius equation provides a good approximation for the temperature dependence of embryogenesis, even though individual developmental intervals scale differently with temperature. At low and high temperatures, however, we observed significant departures from idealized Arrhenius Law behavior. When we model multi-step reactions of idealized chemical networks, we are unable to generate comparable deviations from linearity. In contrast, we find the two enzymes GAPDH and ß-galactosidase show non-linearity in the Arrhenius plot similar to our observations of embryonic development. Thus, we find that complex embryonic development can be well approximated by the simple Arrhenius equation regardless of non-uniform developmental scaling and propose that the observed departure from this law likely results more from non-idealized individual steps rather than from the complexity of the system.

TMTpro Complementary Ion Quantification Increases Plexing and Sensitivity for Accurate Multiplexed Proteomics at the MS2 Level.

Multiplexed proteomics is a powerful tool to assay cell states in health and disease, but accurate quantification of relative protein changes is impaired by interference from co-isolated peptides. Interference can be reduced by using MS3-based quantification, but this reduces sensitivity and requires specialized instrumentation. An alternative approach is quantification by complementary ions, the balancer group-peptide conjugates, which allows accurate and precise multiplexed quantification at the MS2 level and is compatible with most proteomics instruments. However, complementary ions of the popular TMT-tag form inefficiently and multiplexing is limited to five channels. Here, we evaluate and optimize complementary ion quantification for the recently released TMTpro-tag, which increases complementary ion plexing capacity to eight channels (TMTproC). Furthermore, the beneficial fragmentation properties of TMTpro increase sensitivity for TMTproC, resulting in ∼65% more proteins quantified compared to TMTpro-MS3 and ∼18% more when compared to real-time-search TMTpro-MS3 (RTS-SPS-MS3). TMTproC quantification is more accurate than TMTpro-MS2 and even superior to RTS-SPS-MS3. We provide the software for quantifying TMTproC data as an executable that is compatible with the MaxQuant analysis pipeline. Thus, TMTproC advances multiplexed proteomics data quality and widens access to accurate multiplexed proteomics beyond laboratories with MS3-capable instrumentation.

The gain-of-function allele bamAE470K bypasses the essential requirement for BamD in ß-barrel outer membrane protein assembly.

The outer membrane (OM) of gram-negative bacteria confers innate resistance to toxins and antibiotics. Integral ß-barrel outer membrane proteins (OMPs) function to establish and maintain the selective permeability of the OM. OMPs are assembled into the OM by the ß-barrel assembly machine (BAM), which is composed of one OMP-BamA-and four lipoproteins-BamB, C, D, and E. BamB, C, and E can be removed individually with only minor effects on barrier function; however, depletion of either BamA or BamD causes a global defect in OMP assembly and results in cell death. We have identified a gain-of-function mutation, bamAE470K , that bypasses the requirement for BamD. Although bamD::kan bamAE470K cells exhibit growth and OM barrier defects, they assemble OMPs with surprising robustness. Our results demonstrate that BamD does not play a catalytic role in OMP assembly, but rather functions to regulate the activity of BamA.

Precise Temporal Regulation of Post-transcriptional Repressors Is Required for an Orderly Drosophila Maternal-to-Zygotic Transition.

In animal embryos, the maternal-to-zygotic transition (MZT) hands developmental control from maternal to zygotic gene products. We show that the maternal proteome represents more than half of the protein-coding capacity of Drosophila melanogaster's genome, and that 2% of this proteome is rapidly degraded during the MZT. Cleared proteins include the post-transcriptional repressors Cup, Trailer hitch (TRAL), Maternal expression at 31B (ME31B), and Smaug (SMG). Although the ubiquitin-proteasome system is necessary for clearance of these repressors, distinct E3 ligase complexes target them: the C-terminal to Lis1 Homology (CTLH) complex targets Cup, TRAL, and ME31B for degradation early in the MZT and the Skp/Cullin/F-box-containing (SCF) complex targets SMG at the end of the MZT. Deleting the C-terminal 233 amino acids of SMG abrogates F-box protein interaction and confers immunity to degradation. Persistent SMG downregulates zygotic re-expression of mRNAs whose maternal contribution is degraded by SMG. Thus, clearance of SMG permits an orderly MZT.

Inference of Multisite Phosphorylation Rate Constants and Their Modulation by Pathogenic Mutations.

Multisite protein phosphorylation plays a critical role in cell regulation [1-3]. It is widely appreciated that the functional capabilities of multisite phosphorylation depend on the order and kinetics of phosphorylation steps, but kinetic aspects of multisite phosphorylation remain poorly understood [4-6]. Here, we focus on what appears to be the simplest scenario, when a protein is phosphorylated on only two sites in a strict, well-defined order. This scenario describes the activation of ERK, a highly conserved cell-signaling enzyme. We use Bayesian parameter inference in a structurally identifiable kinetic model to dissect dual phosphorylation of ERK by MEK, a kinase that is mutated in a large number of human diseases [7-12]. Our results reveal how enzyme processivity and efficiencies of individual phosphorylation steps are altered by pathogenic mutations. The presented approach, which connects specific mutations to kinetic parameters of multisite phosphorylation mechanisms, provides a systematic framework for closing the gap between studies with purified enzymes and their effects in the living organism.

Multi-Omic Analyses Provide Links between Low-Dose Antibiotic Treatment and Induction of Secondary Metabolism in Burkholderia thailandensis.

Low doses of antibiotics can trigger secondary metabolite biosynthesis in bacteria, but the underlying mechanisms are generally unknown. We sought to better understand this phenomenon by studying how the antibiotic trimethoprim activates the synthesis of the virulence factor malleilactone in Burkholderia thailandensis Using transcriptomics, quantitative multiplexed proteomics, and primary metabolomics, we systematically mapped the changes induced by trimethoprim. Surprisingly, even subinhibitory doses of the antibiotic resulted in broad transcriptional and translational alterations, with ∼8.5% of the transcriptome and ∼5% of the proteome up- or downregulated >4-fold. Follow-up studies with genetic-biochemical experiments showed that the induction of malleilactone synthesis can be sufficiently explained by the accumulation of methionine biosynthetic precursors, notably homoserine, as a result of inhibition of the folate pathway. Homoserine activated the malleilactone gene cluster via the transcriptional regulator MalR and gave rise to a secondary metabolome which was very similar to that generated by trimethoprim. Our work highlights the expansive changes that low-dose trimethoprim induces on bacterial physiology and provides insights into its stimulatory effect on secondary metabolism.IMPORTANCE The discovery of antibiotics ranks among the most significant accomplishments of the last century. Although the targets of nearly all clinical antibiotics are known, our understanding regarding their natural functions and the effects of subinhibitory concentrations is in its infancy. Stimulatory rather than inhibitory functions have been attributed to low-dose antibiotics. Among these, we previously found that antibiotics activate silent biosynthetic genes and thereby enhance the metabolic output of bacteria. The regulatory circuits underlying this phenomenon are unknown. We take a first step toward elucidating these circuits and show that low doses of trimethoprim (Tmp) have cell-wide effects on the saprophyte Burkholderia thailandensis Most importantly, inhibition of one-carbon metabolic processes by Tmp leads to an accumulation of homoserine, which induces the production of an otherwise silent cytotoxin via a LuxR-type transcriptional regulator. These results provide a starting point for uncovering the molecular basis of the hormetic effects of antibiotics.

A Click-Chemistry-Based Enrichable Crosslinker for Structural and Protein Interaction Analysis by Mass Spectrometry.

Mass spectrometry is the method of choice for the characterisation of proteomes. Most proteins operate in protein complexes, in which their close association modulates their function. However, with standard MS analysis, information on protein-protein interactions is lost and no structural information is retained. To gain structural and interactome data, new crosslinking reagents are needed that freeze inter- and intramolecular interactions. Herein, the development of a new reagent, which has several features that enable highly sensitive crosslinking MS, is reported. The reagent enables enrichment of crosslinked peptides from the majority of background peptides to facilitate efficient detection of low-abundant crosslinked peptides. Due to the special cleavable properties, the reagent can be used for MS2 and potentially for MS3 experiments. Thus, the new crosslinking reagent, in combination with high-end MS, should enable sensitive analysis of interactomes, which will help researchers to obtain important insights into cellular states in health and diseases.

Bayesian Confidence Intervals for Multiplexed Proteomics Integrate Ion-statistics with Peptide Quantification Concordance.

Multiplexed proteomics has emerged as a powerful tool to measure relative protein expression levels across multiple conditions. The relative protein abundances are inferred by comparing the signals generated by isobaric tags, which encode the samples' origins. Intuitively, the trust associated with a protein measurement depends on the similarity of ratios from the protein's peptides and the signal-strength of these measurements. However, typically the average peptide ratio is reported as the estimate of relative protein abundance, which is only the most likely ratio with a very naive model. Moreover, there is no sense on the confidence in these measurements. Here, we present a mathematically rigorous approach that integrates peptide signal strengths and peptide-measurement agreement into an estimation of the true protein ratio and the associated confidence (BACIQ). The main advantages of BACIQ are: (1) It removes the need to threshold reported peptide signal based on an arbitrary cut-off, thereby reporting more measurements from a given experiment; (2) Confidence can be assigned without replicates; (3) For repeated experiments BACIQ provides confidence intervals for the union, not the intersection, of quantified proteins; (4) For repeated experiments, BACIQ confidence intervals are more predictive than confidence intervals based on protein measurement agreement. To demonstrate the power of BACIQ we reanalyzed previously published data on subcellular protein movement on treatment with an Exportin-1 inhibiting drug. We detect ∼2× more highly significant movers, down to subcellular localization changes of ∼1%. Thus, our method drastically increases the value obtainable from quantitative proteomics experiments, helping researchers to interpret their data and prioritize resources. To make our approach easily accessible we distribute it via a Python/Stan package.