Absolute yeast mitochondrial proteome quantification reveals trade-off between biosynthesis and energy generation during diauxic shift

Metabolic regulation of misfolded protein import into mitochondria

Mitochondria are the cellular energy hub and central target of metabolic regulation. Mitochondria also facilitate proteostasis through pathways such as the 'mitochondria as guardian in cytosol' (MAGIC) whereby cytosolic misfolded proteins (MPs) are imported into and degraded inside mitochondria. In this study, a genome-wide screen in Saccharomyces cerevisiae uncovered that Snf1, the yeast AMP-activated protein kinase (AMPK), inhibits the import of MPs into mitochondria while promoting mitochondrial biogenesis under glucose starvation. We show that this inhibition requires a downstream transcription factor regulating mitochondrial gene expression and is likely to be conferred through substrate competition and mitochondrial import channel selectivity. We further show that Snf1/AMPK activation protects mitochondrial fitness in yeast and human cells under stress induced by MPs such as those associated with neurodegenerative diseases.

Editorial: Mitochondrial Research: Yeast and Human Cells as Models 2.0

Mitochondrial research stands at the forefront of modern biology, unraveling the intricate mechanisms governing cellular metabolism, energy production, and disease pathogenesis [...].

6Pgdh polymorphism in wild bulb mite populations: prevalence, environmental correlates and life history trade-offs

Genetic polymorphism in key metabolic genes plays a pivotal role in shaping phenotypes and adapting to varying environments. Polymorphism in the metabolic gene 6-phosphogluconate dehydrogenase (6Pgdh) in bulb mites, Rhizoglyphus robini is characterized by two alleles, S and F, that differ by a single amino acid substitution and correlate with male reproductive fitness. The S-bearing males demonstrate a reproductive advantage. Although the S allele rapidly fixes in laboratory settings, the persistence of polymorphic populations in the wild is noteworthy. This study examines the prevalence and stability of 6Pgdh polymorphism in natural populations across Poland, investigating potential environmental influences and seasonal variations. We found widespread 6Pgdh polymorphism in natural populations, with allele frequencies varying across locations and sampling dates but without clear geographical or seasonal clines. This widespread polymorphism and spatio-temporal variability may be attributed to population demography and gene flow between local populations. We found some correlation between soil properties, particularly cation content (Na, K, Ca, and Mg) and 6Pgdh allele frequencies, showcasing the connection between mite physiology and soil characteristics and highlighting the presence of environment-dependent balancing selection. We conducted experimental fitness assays to determine whether the allele providing the advantage in male-male competition has antagonistic effects on life-history traits and if these effects are temperature-dependent. We found that temperature does not differentially influence development time or juvenile survival in different 6Pgdh genotypes. This study reveals the relationship between genetic variation, environmental factors, and reproductive fitness in natural bulb mite populations, shedding light on the dynamic mechanisms governing 6Pgdh polymorphism.

Virtually identical does not mean exactly identical: Discrepancy in energy metabolism between glucose and fructose fermentation influences the reproductive potential of yeast cells

The physiological efficiency of cells largely depends on the possibility of metabolic adaptations to changing conditions, especially on the availability of nutrients. Central carbon metabolism has an essential role in cellular function. In most cells is based on glucose, which is the primary energy source, provides the carbon skeleton for the biosynthesis of important cell macromolecules, and acts as a signaling molecule. The metabolic flux between pathways of carbon metabolism such as glycolysis, pentose phosphate pathway, and mitochondrial oxidative phosphorylation is dynamically adjusted by specific cellular economics responding to extracellular conditions and intracellular demands. Using Saccharomyces cerevisiae yeast cells and potentially similar fermentable carbon sources i.e. glucose and fructose we analyzed the parameters concerning the metabolic status of the cells and connected with them alteration in cell reproductive potential. Those parameters were related to the specific metabolic network: the hexose uptake - glycolysis and activity of the cAMP/PKA pathway - pentose phosphate pathway and biosynthetic capacities - the oxidative respiration and energy generation. The results showed that yeast cells growing in a fructose medium slightly increased metabolism redirection toward respiratory activity, which decreased pentose phosphate pathway activity and cellular biosynthetic capabilities. These differences between the fermentative metabolism of glucose and fructose, lead to long-term effects, manifested by changes in the maximum reproductive potential of cells.

A hub for regulation of mitochondrial metabolism: Fatty acid and lipoic acid biosynthesis

Having evolved from a prokaryotic origin, mitochondria retain pathways required for the catabolism of energy-rich molecules and for the biosynthesis of molecules that aid catabolism and/or participate in other cellular processes essential for life of the cell. Reviewed here are details of the mitochondrial fatty acid biosynthetic pathway (FAS II) and its role in building both the octanoic acid precursor for lipoic acid biosynthesis (LAS) and longer-chain fatty acids functioning in chaperoning the assembly of mitochondrial multisubunit complexes. Also covered are the details of mitochondrial lipoic acid biosynthesis, which is distinct from that of prokaryotes, and the attachment of lipoic acid to subunits of pyruvate dehydrogenase, α-ketoglutarate dehydrogenase, and glycine cleavage system complexes. Special emphasis has been placed on presenting what is currently known about the interconnected paths and loops linking the FAS II-LAS pathway and two other mitochondrial realms, the organellar translation machinery and Fe-S cluster biosynthesis and function.

Loss of the yeast transporter Agp2 upregulates the pleiotropic drug-resistant pump Pdr5 and confers resistance to the protein synthesis inhibitor cycloheximide

The transmembrane protein Agp2, initially shown as a transporter of L-carnitine, mediates the high-affinity transport of polyamines and the anticancer drug bleomycin-A5. Cells lacking Agp2 are hyper-resistant to polyamine and bleomycin-A5. In these earlier studies, we showed that the protein synthesis inhibitor cycloheximide blocked the uptake of bleomycin-A5 into the cells suggesting that the drug uptake system may require de novo synthesis. However, our recent findings demonstrated that cycloheximide, instead, induced rapid degradation of Agp2, and in the absence of Agp2 cells are resistant to cycloheximide. These observations raised the possibility that the degradation of Agp2 may allow the cell to alter its drug resistance network to combat the toxic effects of cycloheximide. In this study, we show that membrane extracts from agp2Δ mutants accentuated several proteins that were differentially expressed in comparison to the parent. Mass spectrometry analysis of the membrane extracts uncovered the pleiotropic drug efflux pump, Pdr5, involved in the efflux of cycloheximide, as a key protein upregulated in the agp2Δ mutant. Moreover, a global gene expression analysis revealed that 322 genes were differentially affected in the agp2Δ mutant versus the parent, including the prominent PDR5 gene and genes required for mitochondrial function. We further show that Agp2 is associated with the upstream region of the PDR5 gene, leading to the hypothesis that cycloheximide resistance displayed by the agp2Δ mutant is due to the derepression of the PDR5 gene.

Emergence of Orchestrated and Dynamic Metabolism of Saccharomyces cerevisiae

Microbial metabolism is a fundamental cellular process that involves many biochemical events and is distinguished by its emergent properties. While the molecular details of individual reactions have been increasingly elucidated, it is not well understood how these reactions are quantitatively orchestrated to produce collective cellular behaviors. Here we developed a coarse-grained, systems, and dynamic mathematical framework, which integrates metabolic reactions with signal transduction and gene regulation to dissect the emergent metabolic traits of Saccharomyces cerevisiae. Our framework mechanistically captures a set of characteristic cellular behaviors, including the Crabtree effect, diauxic shift, diauxic lag time, and differential growth under nutrient-altered environments. It also allows modular expansion for zooming in on specific pathways for detailed metabolic profiles. This study provides a systems mathematical framework for yeast metabolic behaviors, providing insights into yeast physiology and metabolic engineering.

Long-read direct RNA sequencing of the mitochondrial transcriptome of Saccharomyces cerevisiae reveals condition-dependent intron abundance

Mitochondria fulfil many essential roles and have their own genome, which is expressed as polycistronic transcripts that undergo co- or posttranscriptional processing and splicing. Due to the inherent complexity and limited technical accessibility of the mitochondrial transcriptome, fundamental questions regarding mitochondrial gene expression and splicing remain unresolved, even in the model eukaryote Saccharomyces cerevisiae. Long-read sequencing could address these fundamental questions. Therefore, a method for the enrichment of mitochondrial RNA and sequencing using Nanopore technology was developed, enabling the resolution of splicing of polycistronic genes and the quantification of spliced RNA. This method successfully captured the full mitochondrial transcriptome and resolved RNA splicing patterns with single-base resolution and was applied to explore the transcriptome of S. cerevisiae grown with glucose or ethanol as the sole carbon source, revealing the impact of growth conditions on mitochondrial RNA expression and splicing. This study uncovered a remarkable difference in the turnover of Group II introns between yeast grown in either mostly fermentative or fully respiratory conditions. Whether this accumulation of introns in glucose medium has an impact on mitochondrial functions remains to be explored. Combined with the high tractability of the model yeast S. cerevisiae, the developed method enables to monitor mitochondrial transcriptome responses in a broad range of relevant contexts, including oxidative stress, apoptosis and mitochondrial diseases.

Impact of propagation time on yeast physiology during bottle conditioning of beer on an industrial scale

Bottle conditioning occurs when yeast and a fermentable extract are added to beer prior to packaging. Aside from ethanol and carbon dioxide production, this process can minimize the production of off-flavors and increase the shelf-life of beer. The advantages of bottle conditioning rely on the yeast being able to quickly referment the beer and maintain viability during storage. In this study, a commercial ale yeast was propagated in wort on a large scale (30 hL) for 24 h or 72 h and seeded into pale ale beer for bottle conditioning. We found that yeast propagated until the post-diauxic shift (72 h) provided better longevity in the bottle and improved foam stability compared to the 24 h propagated yeast. At the time of seeding, yeast propagated for 72 h showed an upregulation of proteins involved in cellular respiration and general stress pathways that may indicate responses toward mitigating cellular stress levels.

Prediction and biological analysis of yeast VDAC1 phosphorylation

The mitochondrial outer membrane protein porin 1 (Por1), the yeast orthologue of mammalian voltage-dependent anion channel (VDAC), is the major permeability pathway for the flux of metabolites and ions between cytosol and mitochondria. In yeast, several Por1 phosphorylation sites have been identified. Protein phosphorylation is a major modification regulating a variety of biological activities, but the potential biological roles of Por1 phosphorylation remains unaddressed. In this work, we analysed 10 experimentally observed phosphorylation sites in yeast Por1 using bioinformatics tools. Two of the residues, T100 and S133, predicted to reduce and increase pore permeability, respectively, were validated using biological assays. In accordance, Por1T100D reduced mitochondrial respiration, while Por1S133E phosphomimetic mutant increased it. Por1T100A expression also improved respiratory growth, while Por1S133A caused defects in all growth conditions tested, notably in fermenting media. In conclusion, we found phosphorylation has the potential to modulate Por1, causing a marked effect on mitochondrial function. It can also impact on cell morphology and growth both in respiratory and, unpredictably, also in fermenting conditions, expanding our knowledge on the role of Por1 in cell physiology.

A system for inducible mitochondria-specific protein degradation in vivo

Targeted protein degradation systems developed for eukaryotes employ cytoplasmic machineries to perform proteolysis. This has prevented mitochondria-specific analysis of proteins that localize to multiple locations, for example, the mitochondria and the nucleus. Here, we present an inducible mitochondria-specific protein degradation system in Saccharomyces cerevisiae based on the Mesoplasma florum Lon (mf-Lon) protease and its corresponding ssrA tag (called PDT). We show that mitochondrially targeted mf-Lon protease efficiently and selectively degrades a PDT-tagged reporter protein localized to the mitochondrial matrix. The degradation can be induced by depleting adenine from the medium, and tuned by altering the promoter strength of the MF-LON gene. We furthermore demonstrate that mf-Lon specifically degrades endogenous, PDT-tagged mitochondrial proteins. Finally, we show that mf-Lon-dependent PDT degradation can also be achieved in human mitochondria. In summary, this system provides an efficient tool to selectively analyze the mitochondrial function of dually localized proteins.

The energetic costs of cellular complexity in evolution

The evolutionary history of cells has been marked by drastic increases in complexity. Some hypothesize that such cellular complexification requires a massive energy flux as the origin of new features is hypothetically more energetically costly than their evolutionary maintenance. However, it remains unclear how increases in cellular complexity demand more energy. I propose that the early evolution of new genes with weak functions imposes higher energetic costs by overexpression before their functions are evolutionarily refined. In the long term, the accumulation of new genes deviates resources away from growth and reproduction. Accrued cellular complexity further requires additional infrastructure for its maintenance. Altogether, this suggests that larger and more complex cells are defined by increased survival but lower reproductive capacity.

Using MitER for 3D analysis of mitochondrial morphology and ER contacts

We have developed an open-source workflow that allows for quantitative single-cell analysis of organelle morphology, distribution, and inter-organelle contacts with an emphasis on the analysis of mitochondria and mitochondria-endoplasmic reticulum (mito-ER) contact sites. As the importance of inter-organelle contacts becomes more widely recognized, there is a concomitant increase in demand for tools to analyze subcellular architecture. Here, we describe a workflow we call MitER (pronounced "mightier"), which allows for automated calculation of organelle morphology, distribution, and inter-organelle contacts from 3D renderings by employing the animation software Blender. We then use MitER to quantify the variations in the mito-ER networks of Saccharomyces cerevisiae, revealing significantly more mito-ER contacts within respiring cells compared to fermenting cells. We then demonstrate how this workflow can be applied to mammalian systems and used to monitor mitochondrial dynamics and inter-organelle contact in time-lapse studies.

A fast method to distinguish between fermentative and respiratory metabolisms in single yeast cells

Saccharomyces cerevisiae adjusts its metabolism based on nutrient availability, typically transitioning from glucose fermentation to ethanol respiration as glucose becomes limiting. However, our understanding of the regulation of metabolism is largely based on population averages, whereas nutrient transitions may cause heterogeneous responses. Here we introduce iCRAFT, a method that couples the ATP Förster resonance energy transfer (FRET)-based biosensor yAT1.03 with Antimycin A to differentiate fermentative and respiratory metabolisms in individual yeast cells. Upon Antimycin A addition, respiratory cells experienced a sharp decrease of the normalized FRET ratio, while respiro-fermentative cells showed no response. Next, we tracked changes in metabolism during the diauxic shift of a glucose pre-grown culture. Following glucose exhaustion, the entire cell population experienced a progressive rise in cytosolic ATP produced via respiration, suggesting a gradual increase in respiratory capacity. Overall, iCRAFT is a robust tool to distinguish fermentation from respiration, offering a new single-cell opportunity to study yeast metabolism.

Yeast EndoG prevents genome instability by degrading cytoplasmic DNA

In metazoans release of mitochondrial DNA or retrotransposon cDNA to cytoplasm can cause sterile inflammation and disease 1. Cytoplasmic nucleases degrade these DNA species to limit inflammation 2,3. It remains unknown whether degradation these DNA also prevents nuclear genome instability. To address this question, we decided to identify the nuclease regulating transfer of these cytoplasmic DNA species to the nucleus. We used an amplicon sequencing-based method in yeast enabling analysis of millions of DSB repair products. Nuclear mtDNA (NUMTs) and retrotransposon cDNA insertions increase dramatically in nondividing stationary phase cells. Yeast EndoG (Nuc1) nuclease limits insertions of cDNA and transfer of very long mtDNA (>10 kb) that forms unstable circles or rarely insert in the genome, but it promotes formation of short NUMTs (~45-200 bp). Nuc1 also regulates transfer of cytoplasmic DNA to nucleus in aging or during meiosis. We propose that Nuc1 preserves genome stability by degrading retrotransposon cDNA and long mtDNA, while short NUMTs can originate from incompletely degraded mtDNA. This work suggests that nucleases eliminating cytoplasmic DNA play a role in preserving genome stability.

Yeast EndoG prevents genome instability by degrading cytoplasmic DNA

In metazoans release of mitochondrial DNA or retrotransposon cDNA to cytoplasm can cause sterile inflammation and disease. Cytoplasmic nucleases degrade these DNA species to limit inflammation. It remains unknown whether degradation these DNA also prevents nuclear genome instability. To address this question, we decided to identify the nuclease regulating transfer of these cytoplasmic DNA species to the nucleus. We used an amplicon sequencing-based method in yeast enabling analysis of millions of DSB repair products. Nu clear mt DNA (NUMTs) and retrotransposon cDNA insertions increase dramatically in nondividing stationary phase cells. Yeast EndoG (Nuc1) nuclease limits insertions of cDNA and transfer of very long mtDNA (>10 kb) that forms unstable circles or rarely insert in the genome, but it promotes formation of short NUMTs (∼45-200 bp). Nuc1 also regulates transfer of cytoplasmic DNA to nucleus in aging or during meiosis. We propose that Nuc1 preserves genome stability by degrading retrotransposon cDNA and long mtDNA, while short NUMTs can originate from incompletely degraded mtDNA. This work suggests that nucleases eliminating cytoplasmic DNA play a role in preserving genome stability.

Controlling circuitry underlies the growth optimization of Saccharomyces cerevisiae

Microbial growth emerges from coordinated synthesis of various cellular components from limited resources. In Saccharomyces cerevisiae, cyclic AMP (cAMP)-mediated signaling is shown to orchestrate cellular metabolism; however, it remains unclear quantitatively how the controlling circuit drives resource partition and subsequently shapes biomass growth. Here we combined experiment with mathematical modeling to dissect the signaling-mediated growth optimization of S. cerevisiae. We showed that, through cAMP-mediated control, the organism achieves maximal or nearly maximal steady-state growth during the utilization of multiple tested substrates as well as under perturbations impairing glucose uptake. However, the optimal cAMP concentration varies across cases, suggesting that different modes of resource allocation are adopted for varied conditions. Under settings with nutrient alterations, S. cerevisiae tunes its cAMP level to dynamically reprogram itself to realize rapid adaptation. Moreover, to achieve growth maximization, cells employ additional regulatory systems such as the GCN2-mediated amino acid control. This study establishes a systematic understanding of global resource allocation in S. cerevisiae, providing insights into quantitative yeast physiology as well as metabolic strain engineering for biotechnological applications.

Accurate prediction of in vivo protein abundances by coupling constraint-based modelling and machine learning

Quantification of how different environmental cues affect protein allocation can provide important insights for understanding cell physiology. While absolute quantification of proteins can be obtained by resource-intensive mass-spectrometry-based technologies, prediction of protein abundances offers another way to obtain insights into protein allocation. Here we present CAMEL, a framework that couples constraint-based modelling with machine learning to predict protein abundance for any environmental condition. This is achieved by building machine learning models that leverage static features, derived from protein sequences, and condition-dependent features predicted from protein-constrained metabolic models. Our findings demonstrate that CAMEL results in excellent prediction of protein allocation in E. coli (average Pearson correlation of at least 0.9), and moderate performance in S. cerevisiae (average Pearson correlation of at least 0.5). Therefore, CAMEL outperformed contending approaches without using molecular read-outs from unseen conditions and provides a valuable tool for using protein allocation in biotechnological applications.

PARROT: Prediction of enzyme abundances using protein-constrained metabolic models

Protein allocation determines the activity of cellular pathways and affects growth across all organisms. Therefore, different experimental and machine learning approaches have been developed to quantify and predict protein abundance and how they are allocated to different cellular functions, respectively. Yet, despite advances in protein quantification, it remains challenging to predict condition-specific allocation of enzymes in metabolic networks. Here, using protein-constrained metabolic models, we propose a family of constrained-based approaches, termed PARROT, to predict how much of each enzyme is used based on the principle of minimizing the difference between a reference and an alternative growth condition. To this end, PARROT variants model the minimization of enzyme reallocation using four different (combinations of) distance functions. We demonstrate that the PARROT variant that minimizes the Manhattan distance between the enzyme allocation of a reference and an alternative condition outperforms existing approaches based on the parsimonious distribution of fluxes or enzymes for both Escherichia coli and Saccharomyces cerevisiae. Further, we show that the combined minimization of flux and enzyme allocation adjustment leads to inconsistent predictions. Together, our findings indicate that minimization of protein allocation rather than flux redistribution is a governing principle determining steady-state pathway activity for microorganism grown in alternative growth conditions.

The unfolded protein response of the endoplasmic reticulum supports mitochondrial biogenesis by buffering nonimported proteins

Almost all mitochondrial proteins are synthesized in the cytosol and subsequently targeted to mitochondria. The accumulation of nonimported precursor proteins occurring upon mitochondrial dysfunction can challenge cellular protein homeostasis. Here we show that blocking protein translocation into mitochondria results in the accumulation of mitochondrial membrane proteins at the endoplasmic reticulum, thereby triggering the unfolded protein response (UPRER). Moreover, we find that mitochondrial membrane proteins are also routed to the ER under physiological conditions. The level of ER-resident mitochondrial precursors is enhanced by import defects as well as metabolic stimuli that increase the expression of mitochondrial proteins. Under such conditions, the UPRER is crucial to maintain protein homeostasis and cellular fitness. We propose the ER serves as a physiological buffer zone for those mitochondrial precursors that cannot be immediately imported into mitochondria while engaging the UPRER to adjust the ER proteostasis capacity to the extent of precursor accumulation.

Metabolic regulation of misfolded protein import into mitochondria

Mitochondria are the cellular energy hub and central target of metabolic regulation. Mitochondria also facilitate proteostasis through pathways such as the 'mitochondria as guardian in cytosol' (MAGIC) whereby cytosolic misfolded proteins (MPs) are imported into and degraded inside mitochondria. In this study, a genome-wide screen in yeast uncovered that Snf1, the yeast AMP-activated protein kinase (AMPK), inhibits the import of MPs into mitochondria while promoting mitochondrial biogenesis under glucose starvation. We show that this inhibition requires a downstream transcription factor regulating mitochondrial gene expression and is likely to be conferred through substrate competition and mitochondrial import channel selectivity. We further show that Snf1/AMPK activation protects mitochondrial fitness in yeast and human cells under stress induced by MPs such as those associated with neurodegenerative diseases.

y-mtPTM: Yeast mitochondrial posttranslational modification database

One powerful strategy of how to increase the complexity of cellular proteomes is through posttranslational modifications (PTMs) of proteins. Currently, there are ∼400 types of PTMs, the different combinations of which yield a large variety of protein isoforms with distinct biochemical properties. Although mitochondrial proteins undergoing PTMs were identified nearly 6 decades ago, studies on the roles and extent of PTMs on mitochondrial functions lagged behind the other cellular compartments. The application of mass spectrometry for the characterization of the mitochondrial proteome as well as for the detection of various PTMs resulted in the identification of thousands of amino acid positions that can be modified by different chemical groups. However, the data on mitochondrial PTMs are scattered in several data sets, and the available databases do not contain a complete list of modified residues. To integrate information on PTMs of the mitochondrial proteome of the yeast Saccharomyces cerevisiae, we built the yeast mitochondrial posttranslational modification (y-mtPTM) database (http://compbio.fmph.uniba.sk/y-mtptm/). It lists nearly 20,000 positions on mitochondrial proteins affected by ∼20 various PTMs, with phosphorylated, succinylated, acetylated, and ubiquitylated sites being the most abundant. A simple search of a protein of interest reveals the modified amino acid residues, their position within the primary sequence as well as on its 3D structure, and links to the source reference(s). The database will serve yeast mitochondrial researchers as a comprehensive platform to investigate the functional significance of the PTMs of mitochondrial proteins.

Systematic Approaches to Study Eclipsed Targeting of Proteins Uncover a New Family of Mitochondrial Proteins

Dual localization or dual targeting refers to the phenomenon by which identical, or almost identical, proteins are localized to two (or more) separate compartments of the cell. From previous work in the field, we had estimated that a third of the mitochondrial proteome is dual-targeted to extra-mitochondrial locations and suggested that this abundant dual targeting presents an evolutionary advantage. Here, we set out to study how many additional proteins whose main activity is outside mitochondria are also localized, albeit at low levels, to mitochondria (eclipsed). To do this, we employed two complementary approaches utilizing the α-complementation assay in yeast to uncover the extent of such an eclipsed distribution: one systematic and unbiased and the other based on mitochondrial targeting signal (MTS) predictions. Using these approaches, we suggest 280 new eclipsed distributed protein candidates. Interestingly, these proteins are enriched for distinctive properties compared to their exclusively mitochondrial-targeted counterparts. We focus on one unexpected eclipsed protein family of the Triose-phosphate DeHydrogenases (TDH) and prove that, indeed, their eclipsed distribution in mitochondria is important for mitochondrial activity. Our work provides a paradigm of deliberate eclipsed mitochondrial localization, targeting and function, and should expand our understanding of mitochondrial function in health and disease.

Optimization of energy production and central carbon metabolism in a non-respiring eukaryote

Most eukaryotes respire oxygen, using it to generate biomass and energy. However, a few organisms have lost the capacity to respire. Understanding how they manage biomass and energy production may illuminate the critical points at which respiration feeds into central carbon metabolism and explain possible routes to its optimization. Here, we use two related fission yeasts, Schizosaccharomyces pombe and Schizosaccharomyces japonicus, as a comparative model system. We show that although S. japonicus does not respire oxygen, unlike S. pombe, it is capable of efficient NADH oxidation, amino acid synthesis, and ATP generation. We probe possible optimization strategies through the use of stable isotope tracing metabolomics, mass isotopologue distribution analysis, genetics, and physiological experiments. S. japonicus appears to have optimized cytosolic NADH oxidation via glycerol-3-phosphate synthesis. It runs a fully bifurcated TCA pathway, sustaining amino acid production. Finally, we propose that it has optimized glycolysis to maintain high ATP/ADP ratio, in part by using the pentose phosphate pathway as a glycolytic shunt, reducing allosteric inhibition of glycolysis and supporting biomass generation. By comparing two related organisms with vastly different metabolic strategies, our work highlights the versatility and plasticity of central carbon metabolism in eukaryotes, illuminating critical adaptations supporting the preferential use of glycolysis over oxidative phosphorylation.

Evaluating proteome allocation of Saccharomyces cerevisiae phenotypes with resource balance analysis

Saccharomyces cerevisiae is an important model organism and a workhorse in bioproduction. Here, we reconstructed a compact and tractable genome-scale resource balance analysis (RBA) model (i.e., named scRBA) to analyze metabolic fluxes and proteome allocation in a computationally efficient manner. Resource capacity models such as scRBA provide the quantitative means to identify bottlenecks in biosynthetic pathways due to enzyme, compartment size, and/or ribosome availability limitations. ATP maintenance rate and in vivo apparent turnover numbers (k_app) were regressed from metabolic flux and protein concentration data to capture observed physiological growth yield and proteome efficiency and allocation, respectively. Estimated parameter values were found to vary with oxygen and nutrient availability. Overall, this work (i) provides condition-specific model parameters to recapitulate phenotypes corresponding to different extracellular environments, (ii) alludes to the enhancing effect of substrate channeling and post-translational activation on in vivo enzyme efficiency in glycolysis and electron transport chain, and (iii) reveals that the Crabtree effect is underpinned by specific limitations in mitochondrial proteome capacity and secondarily ribosome availability rather than overall proteome capacity.

Proteome dynamics during transition from exponential to stationary phase under aerobic and anaerobic conditions in yeast

The yeast Saccharomyces cerevisiae is a widely used eukaryotic model organism and a promising cell factory for industry. However, despite decades of research, the regulation of its metabolism is not yet fully understood, and its complexity represents a major challenge for engineering and optimising biosynthetic routes. Recent studies have demonstrated the potential of resource and proteomic allocation data in enhancing models for metabolic processes. However, comprehensive and accurate proteome dynamics data that can be used for such approaches are still very limited. Therefore, we performed a quantitative proteome dynamics study to comprehensively cover the transition from exponential to stationary phase for both aerobically and anaerobically grown yeast cells. The combination of highly controlled reactor experiments, biological replicates and standardised sample preparation procedures ensured reproducibility and accuracy. Additionally, we selected the CEN.PK lineage for our experiments because of its relevance for both fundamental and applied research. Together with the prototrophic, standard haploid strain CEN.PK113-7D, we also investigated an engineered strain with genetic minimisation of the glycolytic pathway, resulting in the quantitative assessment of 54 proteomes. The anaerobic cultures showed remarkably less proteome-level changes compared to the aerobic cultures, during transition from the exponential to the stationary phase as a consequence of the lack of the diauxic shift in the absence of oxygen. These results support the notion that anaerobically growing cells lack resources to adequately adapt to starvation. This proteome dynamics study constitutes an important step towards better understanding of the impact of glucose exhaustion and oxygen on the complex proteome allocation process in yeast. Finally, the established proteome dynamics data provide a valuable resource for the development of resource allocation models as well as for metabolic engineering efforts.

The phosphorylation status of Hsp82 regulates mitochondrial homeostasis during glucose sensing in Saccharomyces cerevisiae

Sensing extracellular glucose, budding yeast switches from aerobic glycolysis to oxidative phosphorylation to adapt to environmental changes. During the conversion of metabolic mode, mitochondrial function and morphology change significantly. Mitochondria are the main supply factories of energy for various life activities in cells. However, the research on the signal pathways from glucose sensing to changes in mitochondrial function and morphology is still scarce and worthy of further exploration. In this study, we found that in addition to the known involvement of molecular chaperone Hsp82 in stress response during the conversion of metabolic mode, the phosphorylation status of Hsp82 at S485 residue regulates mitochondrial function and morphology to maintain mitochondrial homeostasis. The Hsp82^S485A mutant that mimics dephosphorylation at S485 residue showed abnormal growth phenotypes related to mitochondrial defects, such as the petite phenotype, slow growth rates, and inability to use non-fermentable carbon sources. Further exploring the causes of growth defects, we found that the Hsp82^S485A mutant caused mitochondrial dysfunction, including a decrease in cellular oxygen consumption rate, defects in mitochondrial electron transport chain, decreased mitochondrial membrane potential and complete loss of mtDNA. Furthermore, the Hsp82^S485A mutant displayed fragmented or globular mitochondria, which may be responsible for its mitochondrial dysfunction. Our findings suggested that the phosphorylation status of Hsp82 at S485 residue might regulate mitochondrial function and morphology by affecting the stability of mitochondrial fission and fusion-related proteins. Thus, Hsp82 might be a key molecule in the signal pathway from glucose sensing to changes in mitochondrial function and morphology.

High-throughput metabolomics for the design and validation of a diauxic shift model

Saccharomyces cerevisiae is a very well studied organism, yet ∼20% of its proteins remain poorly characterized. Moreover, recent studies seem to indicate that the pace of functional discovery is slow. Previous work has implied that the most probable path forward is via not only automation but fully autonomous systems in which active learning is applied to guide high-throughput experimentation. Development of tools and methods for these types of systems is of paramount importance. In this study we use constrained dynamical flux balance analysis (dFBA) to select ten regulatory deletant strains that are likely to have previously unexplored connections to the diauxic shift. We then analyzed these deletant strains using untargeted metabolomics, generating profiles which were then subsequently investigated to better understand the consequences of the gene deletions in the metabolic reconfiguration of the diauxic shift. We show that metabolic profiles can be utilised to not only gaining insight into cellular transformations such as the diauxic shift, but also on regulatory roles and biological consequences of regulatory gene deletion. We also conclude that untargeted metabolomics is a useful tool for guidance in high-throughput model improvement, and is a fast, sensitive and informative approach appropriate for future large-scale functional analyses of genes. Moreover, it is well-suited for automated approaches due to relative simplicity of processing and the potential to make massively high-throughput.

A quantitative fluorescence-based approach to study mitochondrial protein import

Mitochondria play central roles in cellular energy production and metabolism. Most proteins required to carry out these functions are synthesized in the cytosol and imported into mitochondria. A growing number of metabolic disorders arising from mitochondrial dysfunction can be traced to errors in mitochondrial protein import. The mechanisms underlying the import of precursor proteins are commonly studied using radioactively labeled precursor proteins imported into purified mitochondria. Here, we establish a fluorescence-based import assay to analyze protein import into mitochondria. We show that fluorescently labeled precursors enable import analysis with similar sensitivity to those using radioactive precursors, yet they provide the advantage of quantifying import with picomole resolution. We adapted the import assay to a 96-well plate format allowing for fast analysis in a screening-compatible format. Moreover, we show that fluorescently labeled precursors can be used to monitor the assembly of the F₁ F₀ ATP synthase in purified mitochondria. Thus, we provide a sensitive fluorescence-based import assay that enables quantitative and fast import analysis.

Data integration across conditions improves turnover number estimates and metabolic predictions

Turnover numbers characterize a key property of enzymes, and their usage in constraint-based metabolic modeling is expected to increase the prediction accuracy of diverse cellular phenotypes. In vivo turnover numbers can be obtained by integrating reaction rate and enzyme abundance measurements from individual experiments. Yet, their contribution to improving predictions of condition-specific cellular phenotypes remains elusive. Here, we show that available in vitro and in vivo turnover numbers lead to poor prediction of condition-specific growth rates with protein-constrained models of Escherichia coli and Saccharomyces cerevisiae, particularly when protein abundances are considered. We demonstrate that correction of turnover numbers by simultaneous consideration of proteomics and physiological data leads to improved predictions of condition-specific growth rates. Moreover, the obtained estimates are more precise than corresponding in vitro turnover numbers. Therefore, our approach provides the means to correct turnover numbers and paves the way towards cataloguing kcatomes of other organisms.

The APC/C Activator Cdh1p Plays a Role in Mitochondrial Metabolic Remodelling in Yeast

Cdh1p is one of the two substrate adaptor proteins of the anaphase promoting complex/cyclosome (APC/C), a ubiquitin ligase that regulates proteolysis during cell cycle. In this work, using a proteomic approach, we found 135 mitochondrial proteins whose abundance was significantly altered in the cdh1Δ mutant, with 43 up-regulated proteins and 92 down-regulated proteins. The group of significantly up-regulated proteins included subunits of the mitochondrial respiratory chain, enzymes from the tricarboxylic acid cycle and regulators of mitochondrial organization, suggesting a metabolic remodelling towards an increase in mitochondrial respiration. In accordance, mitochondrial oxygen consumption and Cytochrome c oxidase activity increased in Cdh1p-deficient cells. These effects seem to be mediated by the transcriptional activator Yap1p, a major regulator of the yeast oxidative stress response. YAP1 deletion suppressed the increased Cyc1p levels and mitochondrial respiration in cdh1Δ cells. In agreement, Yap1p is transcriptionally more active in cdh1Δ cells and responsible for the higher oxidative stress tolerance of cdh1Δ mutant cells. Overall, our results unveil a new role for APC/C-Cdh1p in the regulation of the mitochondrial metabolic remodelling through Yap1p activity.

Comparative proteome analysis of different Saccharomyces cerevisiae strains during growth on sucrose and glucose

Both the identity and the amount of a carbon source present in laboratory or industrial cultivation media have major impacts on the growth and physiology of a microbial species. In the case of the yeast Saccharomyces cerevisiae, sucrose is arguably the most important sugar used in industrial biotechnology, whereas glucose is the most common carbon and energy source used in research, with many well-known and described regulatory effects, e.g. glucose repression. Here we compared the label-free proteomes of exponentially growing S. cerevisiae cells in a defined medium containing either sucrose or glucose as the sole carbon source. For this purpose, bioreactor cultivations were employed, and three different strains were investigated, namely: CEN.PK113-7D (a common laboratory strain), UFMG-CM-Y259 (a wild isolate), and JP1 (an industrial bioethanol strain). These strains present different physiologies during growth on sucrose; some of them reach higher specific growth rates on this carbon source, when compared to growth on glucose, whereas others display the opposite behavior. It was not possible to identify proteins that commonly presented either higher or lower levels during growth on sucrose, when compared to growth on glucose, considering the three strains investigated here, except for one protein, named Mnp1-a mitochondrial ribosomal protein of the large subunit, which had higher levels on sucrose than on glucose, for all three strains. Interestingly, following a Gene Ontology overrepresentation and KEGG pathway enrichment analyses, an inverse pattern of enriched biological functions and pathways was observed for the strains CEN.PK113-7D and UFMG-CM-Y259, which is in line with the fact that whereas the CEN.PK113-7D strain grows faster on glucose than on sucrose, the opposite is observed for the UFMG-CM-Y259 strain.

MitoStores: chaperone-controlled protein granules store mitochondrial precursors in the cytosol

Hundreds of nucleus-encoded mitochondrial precursor proteins are synthesized in the cytosol and imported into mitochondria in a post-translational manner. However, the early processes associated with mitochondrial protein targeting remain poorly understood. Here, we show that in Saccharomyces cerevisiae, the cytosol has the capacity to transiently store mitochondrial matrix-destined precursors in dedicated deposits that we termed MitoStores. Competitive inhibition of mitochondrial protein import via clogging of import sites greatly enhances the formation of MitoStores, but they also form during physiological cell growth on nonfermentable carbon sources. MitoStores are enriched for a specific subset of nucleus-encoded mitochondrial proteins, in particular those containing N-terminal mitochondrial targeting sequences. Our results suggest that MitoStore formation suppresses the toxic potential of aberrantly accumulating mitochondrial precursor proteins and is controlled by the heat shock proteins Hsp42 and Hsp104. Thus, the cytosolic protein quality control system plays an active role during the early stages of mitochondrial protein targeting through the coordinated and localized sequestration of mitochondrial precursor proteins.

Estimating Total Quantitative Protein Content in Escherichia coli, Saccharomyces cerevisiae, and HeLa Cells

The continuous improvement of proteomic techniques, most notably mass spectrometry, has generated quantified proteomes of many organisms with unprecedented depth and accuracy. However, there is still a significant discrepancy in the reported numbers of total protein molecules per specific cell type. In this article, we explore the results of proteomic studies of Escherichia coli, Saccharomyces cerevisiae, and HeLa cells in terms of total protein copy numbers per cell. We observe up to a ten-fold difference between reported values. Investigating possible reasons for this discrepancy, we conclude that neither an unmeasured fraction of the proteome nor biases in the quantification of individual proteins can explain the observed discrepancy. We normalize protein copy numbers in each study using a total protein amount per cell as reported in the literature and create integrated proteome maps of the selected model organisms. Our results indicate that cells contain from one to three million protein molecules per µm³ and that protein copy density decreases with increasing organism complexity.

Do mitochondria use efflux pumps to protect their ribosomes from antibiotics?

Fungal environments are rich in natural and engineered antimicrobials, and this, combined with the fact that fungal genomes are rich in coding sequences for transporters, suggests that fungi are an intriguing group in which to search for evidence of antimicrobial efflux pumps in mitochondria. Herein, the range of protective mechanisms used by fungi against antimicrobials is introduced, and it is hypothesized, based on the susceptibility of mitochondrial and bacterial ribosomes to the same antibiotics, that mitochondria might also contain pumps that efflux antibiotics from these organelles. Preliminary evidence of ethidium bromide efflux is presented and several candidate efflux pumps are identified in fungal mitochondrial proteomes.

A Transcriptomic Analysis of Higher-Order Ecological Interactions in a Eukaryotic Model Microbial Ecosystem

Nonlinear ecological interactions within microbial ecosystems and their contribution to ecosystem functioning remain largely unexplored. Higher-order interactions, or interactions in systems comprised of more than two members that cannot be explained by cumulative pairwise interactions, are particularly understudied, especially in eukaryotic microorganisms. The wine fermentation ecosystem presents an ideal model to study yeast ecosystem establishment and functioning. Some pairwise ecological interactions between wine yeast species have been characterized, but very little is known about how more complex, multispecies systems function. Here, we evaluated nonlinear ecosystem properties by determining the transcriptomic response of Saccharomyces cerevisiae to pairwise versus tri-species culture. The transcriptome revealed that genes expressed during pairwise coculture were enriched in the tri-species data set but also that just under half of the data set comprised unique genes attributed to a higher-order response. Through interactive protein-association network visualizations, a holistic cell-wide view of the gene expression data was generated, which highlighted known stress response and metabolic adaptation mechanisms which were specifically activated during tri-species growth. Further, extracellular metabolite data corroborated that the observed differences were a result of a biotic stress response. This provides exciting new evidence showing the presence of higher-order interactions within a model microbial ecosystem. IMPORTANCE Higher-order interactions are one of the major blind spots in our understanding of microbial ecosystems. These systems remain largely unpredictable and are characterized by nonlinear dynamics, in particular when the system is comprised of more than two entities. By evaluating the transcriptomic response of S. cerevisiae to an increase in culture complexity from a single species to two- and three-species systems, we were able to confirm the presence of a unique response in the more complex setting that could not be explained by the responses observed at the pairwise level. This is the first data set that provides molecular targets for further analysis to explain unpredictable ecosystem dynamics in yeast.

An excess of glycolytic enzymes under glucose-limited conditions may enable Saccharomyces cerevisiae to adapt to nutrient availability

Microorganisms, including the budding yeast Saccharomyces cerevisiae, express glycolytic proteins to a maximal capacity that (largely) exceeds the actual flux through the enzymes, especially at low growth rates. An open question is if this apparent expression level is really an overcapacity, or maintains the (optimal) enzyme capacity needed to carry flux at (very) low substrate availability. Here, we use computational modelling to suggest that yeast maintains a genuine excess of glycolytic enzymes at low specific growth rates. During fast fermentative growth at high glucose levels, the observed expression of the glycolytic enzymes matched the predicted optimal levels. We suggest that the excess glycolytic capacity at low glucose levels is a preparatory strategy in the adaptation to sugar fluctuations in the environment.

Tiron Has Negative Effects on Osteogenic Differentiation via Mitochondrial Dysfunction in Human Periosteum-Derived Cells

Tiron is a potent antioxidant that counters the pathological effects of reactive oxygen species (ROS) production due to oxidative stress in various cell types. We examined the effects of tiron on mitochondrial function and osteoblastic differentiation in human periosteum-derived cells (hPDCs). Tiron increased mitochondrial activity and decreased senescence-associated β-galactosidase activity in hPDCs; however, it had a detrimental effect on osteoblastic differentiation by reducing alkaline phosphatase (ALP) activity and alizarin red-positive mineralization, regardless of H₂O₂ treatment. Osteoblast-differentiating hPDCs displayed increased ROS production compared with non-differentiating hPDCs, and treatment with tiron reduced ROS production in the differentiating cells. Antioxidants decreased the rates of oxygen consumption and ATP production, which are increased in hPDCs during osteoblastic differentiation. In addition, treatment with tiron reduced the levels of most mitochondrial proteins, which are increased in hPDCs during culture in osteogenic induction medium. These results suggest that tiron exerts negative effects on the osteoblastic differentiation of hPDCs by causing mitochondrial dysfunction.

Dissociation of ERMES clusters plays a key role in attenuating the endoplasmic reticulum stress

In yeast, ERMES, which mediates phospholipid transport between the ER and mitochondria, forms a limited number of oligomeric clusters at ER-mitochondria contact sites in a cell. Although the number of the ERMES clusters appears to be regulated to maintain proper inter-organelle phospholipid trafficking, its underlying mechanism and physiological relevance remain poorly understood. Here, we show that mitochondrial dynamics control the number of ERMES clusters. Moreover, we find that ER stress causes dissociation of the ERMES clusters independently of Ire1 and Hac1, canonical ER-stress response pathway components, leading to a delay in the phospholipid transport from the ER to mitochondria. Our biochemical and genetic analyses strongly suggest that the impaired phospholipid transport contributes to phospholipid accumulation in the ER, expanding the ER for ER stress attenuation. We thus propose that the ERMES dissociation constitutes an overlooked pathway of the ER stress response that operates in addition to the canonical Ire1/Hac1-dependent pathway.

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Mitochondrial fusion and division regulate the clustering of the ERMES complex

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ER stress leads to dissociation of the ERMES clusters independently of Ire1 and Hac1

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The dissociated ERMES complexes have less activity in transporting phospholipids

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The defective phospholipid transport may cause the ER expansion to relieve ER stress

The metabolite-controlled ubiquitin conjugase Ubc8 promotes mitochondrial protein import

Mitochondria play a key role in cellular energy metabolism. Transitions between glycolytic and respiratory conditions induce considerable adaptations of the cellular proteome. These metabolism-dependent changes are particularly pronounced for the protein composition of mitochondria. Here, we show that the yeast cytosolic ubiquitin conjugase Ubc8 plays a crucial role in the remodeling process when cells transition from respiratory to fermentative conditions. Ubc8 is a conserved and well-studied component of the catabolite control system that is known to regulate the stability of gluconeogenic enzymes. Unexpectedly, we found that Ubc8 also promotes the assembly of the translocase of the outer membrane of mitochondria (TOM) and increases the levels of its cytosol-exposed receptor subunit Tom22. Ubc8 deficiency results in compromised protein import into mitochondria and reduced steady-state levels of mitochondrial proteins. Our observations show that Ubc8, which is controlled by the prevailing metabolic conditions, promotes the switch from glucose synthesis to glucose usage in the cytosol and induces the biogenesis of the mitochondrial TOM machinery to improve mitochondrial protein import during phases of metabolic transition.

Phenotypic response of yeast metabolic network to availability of proteinogenic amino acids

Genome-scale metabolism can best be described as a highly interconnected network of biochemical reactions and metabolites. The flow of metabolites, i.e., flux, throughout these networks can be predicted and analyzed using approaches such as flux balance analysis (FBA). By knowing the network topology and employing only a few simple assumptions, FBA can efficiently predict metabolic functions at the genome scale as well as microbial phenotypes. The network topology is represented in the form of genome-scale metabolic models (GEMs), which provide a direct mapping between network structure and function via the enzyme-coding genes and corresponding metabolic capacity. Recently, the role of protein limitations in shaping metabolic phenotypes have been extensively studied following the reconstruction of enzyme-constrained GEMs. This framework has been shown to significantly improve the accuracy of predicting microbial phenotypes, and it has demonstrated that a global limitation in protein availability can prompt the ubiquitous metabolic strategy of overflow metabolism. Being one of the most abundant and differentially expressed proteome sectors, metabolic proteins constitute a major cellular demand on proteinogenic amino acids. However, little is known about the impact and sensitivity of amino acid availability with regards to genome-scale metabolism. Here, we explore these aspects by extending on the enzyme-constrained GEM framework by also accounting for the usage of amino acids in expressing the metabolic proteome. Including amino acids in an enzyme-constrained GEM of Saccharomyces cerevisiae, we demonstrate that the expanded model is capable of accurately reproducing experimental amino acid levels. We further show that the metabolic proteome exerts variable demands on amino acid supplies in a condition-dependent manner, suggesting that S. cerevisiae must have evolved to efficiently fine-tune the synthesis of amino acids for expressing its metabolic proteins in response to changes in the external environment. Finally, our results demonstrate how the metabolic network of S. cerevisiae is robust towards perturbations of individual amino acids, while simultaneously being highly sensitive when the relative amino acid availability is set to mimic a priori distributions of both yeast and non-yeast origins.

Mitochondrial mRNA localization is governed by translation kinetics and spatial transport

For many nuclear-encoded mitochondrial genes, mRNA localizes to the mitochondrial surface co-translationally, aided by the association of a mitochondrial targeting sequence (MTS) on the nascent peptide with the mitochondrial import complex. For a subset of these co-translationally localized mRNAs, their localization is dependent on the metabolic state of the cell, while others are constitutively localized. To explore the differences between these two mRNA types we developed a stochastic, quantitative model for MTS-mediated mRNA localization to mitochondria in yeast cells. This model includes translation, applying gene-specific kinetics derived from experimental data; and diffusion in the cytosol. Even though both mRNA types are co-translationally localized we found that the steady state number, or density, of ribosomes along an mRNA was insufficient to differentiate the two mRNA types. Instead, conditionally-localized mRNAs have faster translation kinetics which modulate localization in combination with changes to diffusive search kinetics across metabolic states. Our model also suggests that the MTS requires a maturation time to become competent to bind mitochondria. Our work indicates that yeast cells can regulate mRNA localization to mitochondria by controlling mitochondrial volume fraction (influencing diffusive search times) and gene translation kinetics (adjusting mRNA binding competence) without the need for mRNA-specific binding proteins. These results shed light on both global and gene-specific mechanisms that enable cells to alter mRNA localization in response to changing metabolic conditions.

Changes to the mtDNA copy number during yeast culture growth

We show that the mitochondrial DNA (mtDNA) copy number in growing cultures of the yeast Saccharomyces cerevisiae increases by a factor of up to 4, being lowest (approx. 10 per haploid genome) and stable during rapid fermentative growth, and highest at the end of the respiratory phase. When yeast are grown on glucose, the onset of the mtDNA copy number increase coincides with the early stages of the diauxic shift, and the increase continues through respiration. A lesser yet still substantial copy number increase occurs when yeast are grown on a nonfermentable carbon source, i.e. when there is no diauxic shift. The mtDNA copy number increase during and for some time after the diauxic shift is not driven by an increase in cell size. The copy number increase occurs in both haploid and diploid strains but is markedly attenuated in a diploid wild isolate that is a ready sporulator. Strain-to-strain differences in mtDNA copy number are least apparent in fermentation and most apparent in late respiration or stationary phase. While changes in mitochondrial morphology and function were previously known to accompany changes in physiological state, it had not been previously shown that the mtDNA copy number changes substantially over time in a clonal growing culture. The mtDNA copy number in yeast is therefore a highly dynamic phenotype.

Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0

Genome-scale metabolic models (GEMs) have been widely used for quantitative exploration of the relation between genotype and phenotype. Streamlined integration of enzyme constraints and proteomics data into such models was first enabled by the GECKO toolbox, allowing the study of phenotypes constrained by protein limitations. Here, we upgrade the toolbox in order to enhance models with enzyme and proteomics constraints for any organism with a compatible GEM reconstruction. With this, enzyme-constrained models for the budding yeasts Saccharomyces cerevisiae, Yarrowia lipolytica and Kluyveromyces marxianus are generated to study their long-term adaptation to several stress factors by incorporation of proteomics data. Predictions reveal that upregulation and high saturation of enzymes in amino acid metabolism are common across organisms and conditions, suggesting the relevance of metabolic robustness in contrast to optimal protein utilization as a cellular objective for microbial growth under stress and nutrient-limited conditions. The functionality of GECKO is expanded with an automated framework for continuous and version-controlled update of enzyme-constrained GEMs, also producing such models for Escherichia coli and Homo sapiens. In this work, we facilitate the utilization of enzyme-constrained GEMs in basic science, metabolic engineering and synthetic biology purposes.

Differential Proteome and Interactome Analysis Reveal the Basis of Pleiotropy Associated With the Histidine Methyltransferase Hpm1p

The methylation of histidine is a post-translational modification whose function is poorly understood. Methyltransferase histidine protein methyltransferase 1 (Hpm1p) monomethylates H243 in the ribosomal protein Rpl3p and represents the only known histidine methyltransferase in Saccharomyces cerevisiae. Interestingly, the hpm1 deletion strain is highly pleiotropic, with many extraribosomal phenotypes including improved growth rates in alternative carbon sources. Here, we investigate how the loss of histidine methyltransferase Hpm1p results in diverse phenotypes, through use of targeted mass spectrometry (MS), growth assays, quantitative proteomics, and differential crosslinking MS. We confirmed the localization and stoichiometry of the H243 methylation site, found unreported sensitivities of Δhpm1 yeast to nonribosomal stressors, and identified differentially abundant proteins upon hpm1 knockout with clear links to the coordination of sugar metabolism. We adapted the emerging technique of quantitative large-scale stable isotope labeling of amino acids in cell culture crosslinking MS for yeast, which resulted in the identification of 1267 unique in vivo lysine-lysine crosslinks. By reproducibly monitoring over 350 of these in WT and Δhpm1, we detected changes to protein structure or protein-protein interactions in the ribosome, membrane proteins, chromatin, and mitochondria. Importantly, these occurred independently of changes in protein abundance and could explain a number of phenotypes of Δhpm1, not addressed by expression analysis. Further to this, some phenotypes were predicted solely from changes in protein structure or interactions and could be validated by orthogonal techniques. Taken together, these studies reveal a broad role for Hpm1p in yeast and illustrate how crosslinking MS will be an essential tool for understanding complex phenotypes.

Innovation trends in industrial biotechnology

Microbial fermentations are used for the sustainable production of a range of products. Due to increasing trends in the food sector toward plant-based foods and meat and dairy product substitutes, microbial fermentation will have an increasing role in this sector, as it will enable a sustainable and scalable production of valuable foods and food ingredients. Microbial fermentation will also be used to advance and expand the production of sustainable chemicals and natural products. Much of this market expansion will come from new start-ups that translate academic research into novel processes and products using state-of-the art technologies. Here, we discuss the trends in innovation and technology and provide recommendations for how to successfully start and grow companies in industrial biotechnology.

Genome-scale modeling of yeast metabolism: retrospectives and perspectives

Yeasts have been widely used for production of bread, beer and wine, as well as for production of bioethanol, but they have also been designed as cell factories to produce various chemicals, advanced biofuels and recombinant proteins. To systematically understand and rationally engineer yeast metabolism, genome-scale metabolic models (GEMs) have been reconstructed for the model yeast Saccharomyces cerevisiae and nonconventional yeasts. Here, we review the historical development of yeast GEMs together with their recent applications, including metabolic flux prediction, cell factory design, culture condition optimization and multi-yeast comparative analysis. Furthermore, we present an emerging effort, namely the integration of proteome constraints into yeast GEMs, resulting in models with improved performance. At last, we discuss challenges and perspectives on the development of yeast GEMs and the integration of proteome constraints.

Dual role of Mic10 in mitochondrial cristae organization and ATP synthase-linked metabolic adaptation and respiratory growth

Invaginations of the mitochondrial inner membrane, termed cristae, are hubs for oxidative phosphorylation. The mitochondrial contact site and cristae organizing system (MICOS) and the dimeric F₁F_o-ATP synthase play important roles in controlling cristae architecture. A fraction of the MICOS core subunit Mic10 is found in association with the ATP synthase, yet it is unknown whether this interaction is of relevance for mitochondrial or cellular functions. Here, we established conditions to selectively study the role of Mic10 at the ATP synthase. Mic10 variants impaired in MICOS functions stimulate ATP synthase oligomerization like wild-type Mic10 and promote efficient inner membrane energization, adaptation to non-fermentable carbon sources, and respiratory growth. Mic10's functions in respiratory growth largely depend on Mic10^ATPsynthase, not on Mic10^MICOS. We conclude that Mic10 plays a dual role as core subunit of MICOS and as partner of the F₁F_o-ATP synthase, serving distinct functions in cristae shaping and respiratory adaptation and growth.

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Dual role of Mic10 of mitochondrial contact site and cristae organizing system (MICOS)

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Mic10 binds to mitochondrial ATP synthase and stabilizes higher order assemblies

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Oligomerization of Mic10 is required for its function in MICOS, not at ATP synthase

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Mic10 binding to ATP synthase supports metabolic adaptation and respiratory growth

Pathways shaping the mitochondrial inner membrane

Mitochondria are complex organelles with two membranes. Their architecture is determined by characteristic folds of the inner membrane, termed cristae. Recent studies in yeast and other organisms led to the identification of four major pathways that cooperate to shape cristae membranes. These include dimer formation of the mitochondrial ATP synthase, assembly of the mitochondrial contact site and cristae organizing system (MICOS), inner membrane remodelling by a dynamin-related GTPase (Mgm1/OPA1), and modulation of the mitochondrial lipid composition. In this review, we describe the function of the evolutionarily conserved machineries involved in mitochondrial cristae biogenesis with a focus on yeast and present current models to explain how their coordinated activities establish mitochondrial membrane architecture.