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Nucleic acid and histone modifications critically depend on the tricarboxylic acid (TCA) cycle for substrates and cofactors. Although a few TCA cycle enzymes have been reported in the nucleus, the corresponding pathways are considered to operate in mitochondria. Here, we show that a part of the TCA cycle is operational also in the nucleus. Using13C-tracer analysis, we identified activity of glutamine-to-fumarate, citrate-to-succinate, and glutamine-to-aspartate routes in the nuclei ofHeLacells. Proximity labeling mass spectrometry revealed a spatial vicinity of the involved enzymes with core nuclear proteins. We further show nuclear localization of aconitase 2 and 2-oxoglutarate dehydrogenase in mouse embryonic stem cells. Nuclear localization of the latter enzyme, which produces succinyl-CoA, changed from pluripotency to a differentiated state with accompanying changes in the nuclear protein succinylation. Together, our results demonstrate operation of an extended metabolic pathway in the nucleus, warranting a revision of the canonical view on metabolic compartmentalization.

Cross-feeding is fundamental to the diversity and function of microbial communities. However, identification of cross-fed metabolites is often challenging due to the universality of metabolic and biosynthetic intermediates. Here, we use 13 C isotope tracing in peptides to elucidate cross-fed metabolites in co-cultures of Saccharomyces cerevisiae and Lactococcus lactis. The community was grown on lactose as the main carbon source with either glucose or galactose fraction of the molecule labelled with 13 C. Data analysis allowing for the possible mass-shifts yielded hundreds of peptides for which we could assign both species identity and labelling degree. The labelling pattern showed that the yeast utilized galactose and, to a lesser extent, lactic acid shared by L. lactis as carbon sources. While the yeast provided essential amino acids to the bacterium as expected, the data also uncovered a complex pattern of amino acid exchange. The identity of the cross-fed metabolites was further supported by metabolite labelling in the co-culture supernatant, and by diminished fitness of a galactose-negative yeast mutant in the community. Together, our results demonstrate the utility of 13 C-based proteomics for uncovering microbial interactions.

How cellular metabolic state impacts cellular programs is a fundamental, unresolved question. Here we investigated how glycolytic flux impacts embryonic development, using presomitic mesoderm (PSM) patterning as the experimental model. First, we identified fructose 1,6-bisphosphate (FBP) as an in vivo sentinel metabolite that mirrors glycolytic flux within PSM cells of post-implantation mouse embryos. We found that medium-supplementation with FBP, but not with other glycolytic metabolites, such as fructose 6-phosphate and 3-phosphoglycerate, impaired mesoderm segmentation. To genetically manipulate glycolytic flux and FBP levels, we generated a mouse model enabling the conditional overexpression of dominant active, cytoplasmic Pfkfb3 (cytoPfkfb3). Overexpression of cytoPfkfb3 indeed led to increased glycolytic flux/FBP levels and caused an impairment of mesoderm segmentation, paralleled by the downregulation of Wnt-signaling, reminiscent of the effects seen upon FBP-supplementation. To probe for mechanisms underlying glycolytic flux-signaling, we performed subcellular proteome analysis and revealed that cytoPfkfb3 overexpression altered subcellular localization of certain proteins, including glycolytic enzymes, in PSM cells. Specifically, we revealed that FBP supplementation caused depletion of Pfkl and Aldoa from the nuclear-soluble fraction. Combined, we propose that FBP functions as a flux-signaling metabolite connecting glycolysis and PSM patterning, potentially through modulating subcellular protein localization.

Beyond its fundamental role in fulfilling the nutritional and energetic needs of the cell, metabolism has emerged as an important component of cellular regulatory processes which are central to diverse biological phenomena, ranging from cell differentiation to cancer and longevity. These metabolic pleiotropic roles often converge on the crosstalk with gene expression regulation which is sensitive to the availability of specific metabolites utilized for chromatin and RNA chemical modifications. These required metabolites are often assumed to freely diffuse into the nuclear space, with their key biosynthetic pathways mainly assigned to function elsewhere. However, considering that the intracellular environment is a rather viscous space where the free diffusion between the different compartments could be restricted, a significant question arises of how the nucleus ensures a reliable supply of these essential metabolites, especially as it is often a reaction-diffusion scenario and not only diffusion. Along these lines, the aim of the current PhD thesis was to explore the hypothesis that the nucleus could harbor extended metabolic networks, and not only individual enzymatic steps, for local production of nuclear-relevant metabolites. To examine this, firstly, nuclear proteomics data and nuclear localization signal motif analysis were utilized to assess the potentiality of a nuclear presence of the corresponding metabolic enzymes. Next, by employing stable isotope [U-13C]-based metabolomics analysis in isolated nuclei, we tracked an operational activity. Proximity ligation mass spectrometry for selected enzymatic players allowed us to examine their proximity interactome further corroborating a nuclear subcellular topology. Cumulatively, our data provided multi-level evidence for a functional metabolic pathway operating in a mammalian nucleus. The identified pathway is made of parts of the TCA cycle with intermediates having key roles in chromatin and RNA modifications, reflecting thus the presence of a metabolic nuclear niche ensuring a stable supply of essential metabolites with nucleus-relevant functionalities. The aforementioned crosstalk between metabolism and gene expression regulation highlights the importance of considering metabolic deregulations in pathophysiological conditions. Cancer metabolic alterations are a well-studied phenomenon. Yet, little is known for the metabolic physiology of residual cancer cells that survive treatment and contribute to cancer relapse. The current PhD thesis contributed to the characterization of the metabolic particularities of residual cancer cells derived from a mouse model of breast cancer. The analysis indicated that the residual cells, although phenotypically similar to their normal counterparts and despite the absence of oncogenes expression, preserved a tumorous metabolic memory with main characteristics of an enhanced glycolysis, deregulated TCA and urea cycle. Considering glycolysis’ central role, we next aimed at investigating the network-wide metabolic responses upon inhibition of two important facilitators of the pathway, namely lactate dehydrogenase A and the monocarboxylate transporters 1 and 2, involved in lactate generation and transportation, respectively, in cancer cell lines. The results revealed opposite changes in metabolite concentration pools in glycolysis and TCA cycle intermediates between the two inhibitors treatment, and an overall lower biosynthetic flux. Interesting metabolic nodes were identified that could potentially be therapeutically exploited. Uncovering and understanding metabolic network activities in previously overlooked places, like the existence of a nuclear multistep metabolic network, or the perseverance in cancer regressed cells of a metabolic phenotype mnemonic to the tumorous state, can shed light on the hitherto unknown mechanisms of gene regulation and its interplay with the metabolic state of a cell.

info:eu-repo/semantics/publishedVersion

Funder: European Molecular Biology Laboratory (EMBL); Id: http://dx.doi.org/10.13039/100013060, Adaptive laboratory evolution has proven highly effective for obtaining microorganisms with enhanced capabilities. Yet, this method is inherently restricted to the traits that are positively linked to cell fitness, such as nutrient utilization. Here, we introduce coevolution of obligatory mutualistic communities for improving secretion of fitness‐costly metabolites through natural selection. In this strategy, metabolic cross‐feeding connects secretion of the target metabolite, despite its cost to the secretor, to the survival and proliferation of the entire community. We thus co‐evolved wild‐type lactic acid bacteria and engineered auxotrophic Saccharomyces cerevisiae in a synthetic growth medium leading to bacterial isolates with enhanced secretion of two B‐group vitamins, viz., riboflavin and folate. The increased production was specific to the targeted vitamin, and evident also in milk, a more complex nutrient environment that naturally contains vitamins. Genomic, proteomic and metabolomic analyses of the evolved lactic acid bacteria, in combination with flux balance analysis, showed altered metabolic regulation towards increased supply of the vitamin precursors. Together, our findings demonstrate how microbial metabolism adapts to mutualistic lifestyle through enhanced metabolite exchange.

Adaptive laboratory evolution has proven highly effective for obtaining microorganisms with enhanced capabilities. Yet, this method is inherently restricted to the traits that are positively linked to cell fitness, such as nutrient utilization. Here, we introduce coevolution of obligatory mutualistic communities for improving secretion of fitness-costly metabolites through natural selection. In this strategy, metabolic cross-feeding connects secretion of the target metabolite, despite its cost to the secretor, to the survival and proliferation of the entire community. We thus co-evolved wild-type lactic acid bacteria and engineered auxotrophic Saccharomyces cerevisiae in a synthetic growth medium leading to bacterial isolates with enhanced secretion of two B-group vitamins, viz., riboflavin and folate. The increased production was specific to the targeted vitamin, and evident also in milk, a more complex nutrient environment that naturally contains vitamins. Genomic, proteomic and metabolomic analyses of the evolved lactic acid bacteria, in combination with flux balance analysis, showed altered metabolic regulation towards increased supply of the vitamin precursors. Together, our findings demonstrate how microbial metabolism adapts to mutualistic lifestyle through enhanced metabolite exchange.

Many microorganisms live in communities and depend on metabolites secreted by fellow community members for survival. Yet our knowledge of interspecies metabolic dependencies is limited to few communities with small number of exchanged metabolites, and even less is known about cellular regulation facilitating metabolic exchange. Here we show how yeast enables growth of lactic acid bacteria through endogenous, multi-component, crossfeeding in a readily established community. In nitrogen- rich environments, Saccharomyces cerevisiae adjusts its metabolism by secreting a pool of metabolites, especially amino acids, and thereby enables survival of Lactobacillus plantarum and Lactococcus lactis. Quantity of the available nitrogen sources and the status of nitrogen catabolite repression pathways jointly modulate this niche creation. We demonstrate how nitrogen overflow by yeast benefits L. plantarum in grape juice, and contributes to emergence of mutualism with L. lactis in a medium with lactose. Our results illustrate how metabolic decisions of an individual species can benefit others., Cell Systems, 5 (4), ISSN:2405-4720

Bacteria in the gut can modulate the availability and efficacy of therapeutic drugs. However, the systematic mapping of the interactions between drugs and bacteria has only started recently1 and the main underlying mechanism proposed is the chemical transformation of drugs by microorganisms (biotransformation). Here we investigated the depletion of 15 structurally diverse drugs by 25 representative strains of gut bacteria. This revealed 70 bacteria-drug interactions, 29 of which had not to our knowledge been reported before. Over half of the new interactions can be ascribed to bioaccumulation; that is, bacteria storing the drug intracellularly without chemically modifying it, and in most cases without the growth of the bacteria being affected. As a case in point, we studied the molecular basis of bioaccumulation of the widely used antidepressant duloxetine by using click chemistry, thermal proteome profiling and metabolomics. We find that duloxetine binds to several metabolic enzymes and changes the metabolite secretion of the respective bacteria. When tested in a defined microbial community of accumulators and non-accumulators, duloxetine markedly altered the composition of the community through metabolic cross-feeding. We further validated our findings in an animal model, showing that bioaccumulating bacteria attenuate the behavioural response of Caenorhabditis elegans to duloxetine. Together, our results show that bioaccumulation by gut bacteria may be a common mechanism that alters drug availability and bacterial metabolism, with implications for microbiota composition, pharmacokinetics, side effects and drug responses, probably in an individual manner.

First-principle metabolic modelling holds potential for designing microbial chassis that are resilient against phenotype reversal due to adaptive mutations. Yet, the theory of model-based chassis design has rarely been put to rigorous experimental test. Here, we report the development of Saccharomyces cerevisiae chassis strains for dicarboxylic acid production using genome-scale metabolic modelling. The chassis strains, albeit geared for higher flux towards succinate, fumarate and malate, do not appreciably secrete these metabolites. As predicted by the model, introducing product-specific TCA cycle disruptions resulted in the secretion of the corresponding acid. Adaptive laboratory evolution further improved production of succinate and fumarate, demonstrating the evolutionary robustness of the engineered cells. In the case of malate, multi-omics analysis revealed a flux bypass at peroxisomal malate dehydrogenase that was missing in the yeast metabolic model. In all three cases, flux balance analysis integrating transcriptomics, proteomics and metabolomics data confirmed the flux re-routing predicted by the model. Taken together, our modelling and experimental results have implications for the computer-aided design of microbial cell factories., We would like to acknowledge the support of R. Mattel and F. Stein from the Proteomics Core Facility and the Genomics Core Facility at the European Molecular Biology Laboratory (EMBL Heidelberg, Germany). This study was supported by national funds through FCT/MCTES (Portugal, Ref. ERA-IB-2/0003/2013) and BMBF (Germany, Grant number: 031A343A, Ref. ERA-IB-2/0003/2013). The Portuguese Foundation for Science and Technology (FCT) supported HL through grant ref. PD/BD/52336/2013. FCT also supported this study under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684) and through the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462). Open Access funding enabled and organized by Projekt DEAL., info:eu-repo/semantics/publishedVersion

Στην μετα-γονιδιωματική εποχή, την εποχή της συστημικής βιολογίας, η κατανόηση της πολυπλοκότητας της κυτταρικής φυσιολογίας απαιτεί την ανάλυση της δυναμικής των δικτύων βιομοριακών αλληλεπιδράσεων σε όλα τα μοριακά επίπεδα κυτταρικής λειτουργίας. Με τη σειρά της, η λειτουργική γονιδιωματική, ένας θεμελιώδης λίθος της συστημικής βιολογίας, στοχεύει στον πολυδιάστατο χαρακτηρισμό ενός γονιδίου, συνδυάζοντας δεδομένα από τις τεχνολογίες υψηλής απόδοσης. Είναι αυτή ακριβώς η ενοποίηση όλων των μοριακών προτύπων για ένα διαταραγμένο βιολογικό σύστημα που μπορεί να δώσει πληροφορίες αναφορικά με την λειτουργία ενός αγνώστου γονιδίου. Στο πλαίσιο αυτό, η παρούσα Διπλωματική Εργασία αποτελεί μέρος της ολιστικής λειτουργικής ανάλυσης δύο αλληλεπιδρώντων, αγνώστου βιολογικού ρόλου, πρωτεϊνών, της DGCR14 και της FRA10AC1, οι οποίες έχουν απομονωθεί ως συστατικά του σωματιδίου συναρμογής και έχουν συσχετιστεί με νευρολογικές ασθένειες. Η παρούσα εργασία επικεντρώνεται στην μεταβολομική μελέτη των μοριακών επιπτώσεων της υπερέκφρασης της DGCR14 σε ένα ανθρώπινο κυτταρικό μοντέλο, τα κύτταρα HeLa, με την χρήση της αέριας χρωματογραφίας - φασματομετρία μάζας. Ωστόσο, για να επιτευχθεί αυτό, θέματα σχετικά με τις δυνατότητες ποσοτικοποίησης των πολυβηματικών ομικών αναλύσεων έπρεπε να επιλυθούν. Μια σημαντική παράμετρος αφορά στην γρήγορη αδρανοποίηση των ενζυματικών διεργασιών έτσι ώστε οι αποκτηθέντες μετρήσεις να αντικατοπτρίζουν την πραγματική κυτταρική φυσιολογία. Για τον σκοπό αυτό, ο πειραματικός σχεδιασμός πρέπει να τροποποιείται κατάλληλα έτσι ώστε οποιεσδήποτε απαιτούμενες προ-αναλυτικές διαδικασίες χειρισμού των κυττάρων να έχουν ελάχιστη επίδραση στην φυσιολογία τους. Μελετήσαμε συνεπώς την επίδραση τεσσάρων πρωτοκόλλων συλλογής προσκολλημένων κυττάρων και δύο διαφορετικών διαλυμάτων έκπλυσης στο μεταβολικό πρότυπο κυττάρων HeLa. Τα μεταβολομικά δεδομένα αξιολογήθηκαν στο πλαίσιο της καρκινικής μεταβολικής φυσιολογίας και το πρωτόκολλο με την ελάχιστη δυνατή επίδραση στην κυτταρική φυσιολογία καθορίστηκε. Μεταξύ των αποτελεσμάτων αυτής της μελέτης, πολύτιμες πληροφορίες σχετικά με την μεταβολική φυσιολογία των αθανατοποιημένων κυτταρικών σειρών προέκυψαν, οι οποίες ενίσχυσαν σημαντικά την υπάρχουσα γνώση γύρω από τον καρκινικό μεταβολισμό, σε σταθερές ή μεταβαλλόμενες περιβαλλοντικές συνθήκες. Επακόλουθα, η βελτιστοποίηση της διαδικασίας συλλογής είχε ως αποτέλεσμα την δημιουργία ενός αντιπροσωπευτικού μεταβολικού προτύπου κυττάρων HeLa πάνω στο οποίο πραγματοποιήθηκε η αξιολόγηση της υπερέκφρασης της πρωτεΐνης DGCR14 χωρίς να επισκιάζεται από πειραματικές αποκλίσεις εισαγόμενες από την διαδικασία χειρισμού των κυττάρων. Αναφορικά με τα κύτταρα που υπερεκφράζουν την DGCR14, η μεταβολομική ανάλυση εντόπισε μια αλλαγή φυσιολογίας συνδεόμενη με συγκεκριμένα μεταβολικά μονοπάτια τα οποία υποδηλώνουν έντονο μεταβολικό στρες. Για να διερευνήσουμε την συσχέτιση της υπερέκφρασης της DGCR14 με τον παραπάνω μεταβολικό φαινότυπο, χρησιμοποιήσαμε το ανακατασκευασμένο δίκτυο πρωτεϊνικών αλληλεπιδράσεων του σωματιδίου συναρμογής στον άνθρωπο και το δίκτυο πρωτεϊνικών αλληλεπιδράσεων στον άνθρωπο από την μετα-βάση δεδομένων PICKLE, προκειμένου να αντλήσουμε επιπλέον πληροφορίες για τον ρόλο της DGCR14 βάσει της θέσης της σε σχέση με άλλους κόμβους και υπερ-κόμβους. Μια πιθανή λειτουργική συσχέτιση της DGCR14 με αυτοφαγικούς και λυσοσωμικούς μηχανισμούς βρέθηκε, η οποία θα αξιολογηθεί και μελλοντικά μέσω της ανάλυσης, ξεχωριστά και συνδυαστικά, των μοριακών συνεπειών της υπερ- και υπο-έκφρασης σε όλα τα μοριακά επίπεδα κυτταρικής λειτουργίας. In the post-genomic, systems biology era, developing a systems level understanding of a physiological process requires the analysis of biomolecular network dynamics at all molecular levels of cellular function. Likewise, functional genomics, an essential foundation of systems biology research, aims to define and analyze gene function at a global level by integrating data obtained from multiple high-throughput technologies. It is the integration of all the molecular profiles for a systematically perturbed system that can provide insight about the function of unknown genes. Along these lines, the present study is part of the systematic functional analysis of two interacting, but yet of unknown biological role, spliceosomal proteins, DGCR14 and FRA10AC1, that have both been implicated in neurological diseases. The present work focuses on studying the molecular consequences of DGCR14 overexpression in a human cell model, HeLa cells, at the metabolic level using Gas Chromatography-(ion trap) Mass Spectrometry. However, to succeed in this, issues regarding the quantification capabilities of the multistep omic analysis procedures needed to be resolved. A major concern refers to the fast quenching of any enzymatic processes, so that the acquired measurements indeed reflect the cellular physiology in vivo. To this end, the experimental design should be appropriately adjusted so that any required sample handling actions before quenching have a minimal effect on cellular physiology. Thus, we investigated the effect of four cell collection protocols and two different washing solutions on the intracellular metabolic profile measurements of a HeLa cell culture. The measurements were interpreted in the context of the known cancer cell metabolic physiology and the protocol with the minimum possible effect on cellular physiology was specified. Among the results of this study, valuable information about the metabolic physiology of the immortal cell line arise, which improved our knowledge about cancer metabolism under steady or varying environmental conditions. Subsequently, the optimization of the collection procedure enabled us to establish a representative metabolic profile of HeLa cells against which the overexpression of DGCR14 was evaluated without being obscured by the effect of the sample handling. Regarding the overexpressing cells, the metabolomic analysis detected a trend of physiological change connected to specific metabolic pathways indicating strong metabolic stress. To understand how DGCR14 overexpression generates this particular metabolic phenotype, we used the human spliceosomal complex protein-protein interaction (PPI) network and the integrated human PPI meta-database PICKLE to extract additional information about DGCR14 role based on its location with respect to other nodes and hubs. A possible functional correlation of DGCR14 to autophagic and lysosomal mechanisms was established, that will be further evaluated in the future through the analysis, separately and in combination, of the consequences of DGCR14 over- and under-expression at all molecular levels of cellular function.