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Gonorrhea is the second most common sexually transmitted infection in the world and is caused by Gram-negative diplococcus Neisseria gonorrhoeae. Since N. gonorrhoeae is a human-specific pathogen, animal infection models are only of limited use. Therefore, a suitable in vitro cell culture model for studying the complete infection including adhesion, transmigration and transport to deeper tissue layers is required. In the present study, we generated three independent 3D tissue models based on porcine small intestinal submucosa (SIS) scaffold by co-culturing human dermal fibroblasts with human colorectal carcinoma, endometrial epithelial, and male uroepithelial cells. Functional analyses such as transepithelial electrical resistance (TEER) and FITC-dextran assay indicated the high barrier integrity of the created monolayer. The histological, immunohistochemical, and ultra-structural analyses showed that the 3D SIS scaffold-based models closely mimic the main characteristics of the site of gonococcal infection in human host including the epithelial monolayer, the underlying connective tissue, mucus production, tight junction, and microvilli formation. We infected the established 3D tissue models with different N. gonorrhoeae strains and derivatives presenting various phenotypes regarding adhesion and invasion. The results indicated that the disruption of tight junctions and increase in interleukin production in response to the infection is strain and cell type-dependent. In addition, the models supported bacterial survival and proved to be better suitable for studying infection over the course of several days in comparison to commonly used Transwell® models. This was primarily due to increased resilience of the SIS scaffold models to infection in terms of changes in permeability, cell destruction and bacterial transmigration. In summary, the SIS scaffold-based 3D tissue models of human mucosal tissues represent promising tools for investigating N. gonorrhoeae infections under close-to-natural conditions.
Current preclinical models used to evaluate novel therapies for improved healing include both in vitro and in vivo methods. However, ethical concerns related to the use of animals as well as the poor physiological translation between animal and human skin wound healing designate in vitro models as a highly relevant and promising platforms for healing investigation. While current in vitro 3D skin models recapitulate a mature tissue with healing properties, they still represent a simplification of the in vivo conditions, where for example the inflammatory response originating after wound formation involves the contribution of immune cells. Macrophages are among the main contributors to the inflammatory response and regulate its course thanks to their plasticity. Therefore, their implementation into in vitro skin could greatly increase the physiological relevance of the models. As no full-thickness immunocompetent skin model containing macrophages has been reported so far, the parameters necessary for a successful triple co-culture of fibroblasts, keratinocytes and macrophages were here investigated. At first, cell source and culture timed but also an implementation strategy for macrophages were deter-mined. The implementation of macrophages into the skin model focused on the minimization of the culture time to preserve immune cell viability and phenotype, as the environment has a major influence on cell polarization and cytokine production. To this end, incorporation of macrophages in 3D gels prior to the combination with skin models was selected to better mimic the in vivo environment. Em-bedded in collagen hydrogels, macrophages displayed a homogeneous cell distribution within the gel, preserving cell viability, their ability to respond to stimuli and their capability to migrate through the matrix, which are all needed during the involvement of macrophages in the inflammatory response. Once established how to introduce macrophages into skin models, different culture media were evaluated for their effects on primary fibroblasts, keratinocytes and macrophages, to identify a suitable medium composition for the culture of immunocompetent skin. The present work confirmed that each cell type requires a different supplement combination for maintaining functional features and showed for the first time that media that promote and maintain a mature skin structure have negative effects on primary macrophages. Skin differentiation media negatively affected macrophages in terms of viability, morphology, ability to respond to pro- and anti-inflammatory stimuli and to migrate through a collagen gel. The combination of wounded skin equivalents and macrophage-containing gels con-firmed that culture medium inhibits macrophage participation in the inflammatory response that oc-curs after wounding. The described macrophage inclusion method for immunocompetent skin creation is a promising approach for generating more relevant skin models. Further optimization of the co-cul-ture medium will potentially allow mimicking a physiological inflammatory response, enabling to eval-uate the effects novel drugs designed for improved healing on improved in vitro models.
Metabolic adaptation to the host cell is important for obligate intracellular pathogens such as Chlamydia trachomatis (Ct). Here we infer the flux differences for Ct from proteome and qRT-PCR data by comprehensive pathway modeling. We compare the comparatively inert infectious elementary body (EB) and the active replicative reticulate body (RB) systematically using a genome-scale metabolic model with 321 metabolites and 277 reactions. This did yield 84 extreme pathways based on a published proteomics dataset at three different time points of infection. Validation of predictions was done by quantitative RT-PCR of enzyme mRNA expression at three time points. Ct’s major active pathways are glycolysis, gluconeogenesis, glycerol-phospholipid (GPL) biosynthesis (support from host acetyl-CoA) and pentose phosphate pathway (PPP), while its incomplete TCA and fatty acid biosynthesis are less active. The modeled metabolic pathways are much more active in RB than in EB. Our in silico model suggests that EB and RB utilize folate to generate NAD(P)H using independent pathways. The only low metabolic flux inferred for EB involves mainly carbohydrate metabolism. RB utilizes energy -rich compounds to generate ATP in nucleic acid metabolism. Validation data for the modeling include proteomics experiments (model basis) as well as qRT-PCR confirmation of selected metabolic enzyme mRNA expression differences. The metabolic modeling is made fully available here. Its detailed insights and models on Ct metabolic adaptations during infection are a useful modeling basis for future studies.
This thesis elucidates patterns and drivers of invertebrate herbivory, herbivore diversity, and community-level biomass along elevational and land use gradients at Mt. Kilimanjaro, Tanzania.
Chapter I provides background information on the response and predictor variables, study system, and the study design. First, I give an overview of the elevational patterns of species diversity/richness and herbivory published in the literature. The overview illuminates existing debates on elevational patterns of species diversity/richness and herbivory. In connection to these patterns, I also introduce several hypotheses and mechanisms put forward to explain macroecological patterns of species richness. Furthermore, I explain the main variables used to test hypotheses. Finally, I describe the study system and the study design used.
Chapter II explores the patterns of invertebrate herbivory and their underlying drivers along extensive elevational and land use gradients on the southern slopes of Mt. Kilimanjaro. I recorded standing leaf herbivory from leaf chewers, leaf miners and gall-inducing insects on 55 study sites located in natural and anthropogenic habitats distributed from 866 to 3060 meters above sea level (m asl) on Mt. Kilimanjaro. Standing leaf herbivory was related to climatic variables [mean annual temperature - (MAT) and mean annual precipitation - (MAP)], net primary productivity (NPP) and plant functional traits (leaf traits) [specific leaf area (SLA), carbon to nitrogen ratio (CN), and nitrogen to phosphorous ratio (NP)]. Results revealed an unimodal pattern of total leaf herbivory along the elevation gradient in natural habitats. Findings also revealed differences in the levels and patterns of herbivory among feeding guilds and between anthropogenic and natural habitats. Changes in NP and CN ratios which were closely linked to NPP were the strongest predictors of leaf herbivory. Our study uncovers the role of leaf nutrient stoichiometry and its linkages to climate in explaining the variation in leaf herbivory along climatic gradients.
Chapter III presents patterns and unravels direct and indirect effects of resource (food) abundance (NPP), resource (food) diversity [Functional Dispersion (FDis)], resource quality (SLA, NP, and CN rations), and climate variables (MAT and MAP) on species diversity of phytophagous beetles. Data were collected from 65 study sites located in natural and anthropogenic habitats distributed from 866 to 4550 m asl on the southern slopes of Mt. Kilimanjaro. Sweep net and beating methods were used to collect a total of 3,186 phytophagous beetles representing 21 families and 304 morphospecies. Two groups, weevils (Curculionidae) and leaf beetles (Chrysomelidae) were the largest and most diverse families represented with 898 and 1566 individuals, respectively. Results revealed complex (bimodal) and dissimilar patterns of Chao1-estimated species richness (hereafter referred to as species diversity) along elevation and land use gradients. Results from path analysis showed that temperature and climate-mediated changes in NPP had a significant positive direct and indirect effect on species diversity of phytophagous beetles, respectively. The results also revealed that the effect of NPP (via beetles abundance and diversity of food resources) on species diversity is stronger than that of temperature. Since we found that factors affecting species diversity were intimately linked to climate, I concluded that predicted climatic changes over the coming decades will likely alter the species diversity patterns which we observe today.
Chapter IV presents patterns and unravels the direct and indirect effects of climate, NPP and anthropogenic disturbances on species richness and community-level biomass of wild large mammals which represent endothermic organisms and the most important group of vertebrate herbivores. Data were collected from 66 study sites located in natural and anthropogenic habitats distributed from 870 to 4550 m asl on the southern slopes of Mt. Kilimanjaro. Mammals were collected using camera traps and used path analysis to disentangle the direct and indirect effects of climatic variables, NPP, land use, land area, levels of habitat protection and occurrence of domesticated mammals on the patterns of richness and community-level biomass of wild mammals, respectively. Results showed unimodal patterns for species richness and community-level biomass of wild mammals along elevation gradients and that the patterns differed depending on the type of feeding guild. Findings from path analysis showed that net primary productivity and levels of habitat protection had a strong direct effect on species richness and community-level biomass of wild mammals whereas temperature had an insignificant direct effect. Findings show the importance of climate-mediated food resources in determining patterns of species richness of large mammals. While temperature is among key predictors of species richness in several ectotherms, its direct influence in determining species richness of wild mammals was insignificant. Findings show the sensitivity of wild mammals to anthropogenic influences and underscore the importance of protected areas in conserving biodiversity.
In conclusion, despite a multitude of data sets on species diversity and ecosystem functions along broad climatic gradients, there is little mechanistic understanding of the underlying causes. Findings obtained in the three studies illustrate their contribution to the scientific debates on the mechanisms underlying patterns of herbivory and diversity along elevation gradients. Results present strong evidence that plant functional traits play a key role in determining invertebrate herbivory and species diversity along elevation gradients and that, their strong interdependence with climate and anthropogenic activities will shape these patterns in future. Additionally, findings from path analysis demonstrated that herbivore diversity, community-level biomass, and herbivory are strongly influenced by climate (either directly or indirectly). Therefore, the predicted climatic changes are expected to dictate ecological patterns, biotic interactions, and energy and nutrient fluxes in terrestrial ecosystems in the coming decades with stronger impacts probably occurring in natural ecosystems. Furthermore, findings demonstrated the significance of land use effects in shaping ecological patterns. As anthropogenic pressure is advancing towards more pristine higher elevations, I advocate conservation measures which are responsive to and incorporate human dimensions to curb the situation. Although our findings emanate from observational studies which have to take several confounding factors into account, we have managed to demonstrate global change responses in real ecosystems and fully established organisms with a wide range of interactions which are unlikely to be captured in artificial experiments. Nonetheless, I recommend additional experimental studies addressing the effect of top-down control by natural enemies on herbivore diversity and invertebrate herbivory in order to deepen our understanding of the mechanisms driving macroecological patterns along elevation gradients.
Since its first experimental implementation in 2005, single-molecule localization microscopy (SMLM) emerged as a versatile and powerful imaging tool for biological structures with nanometer resolution. By now, SMLM has compiled an extensive track-record of novel insights in sub- and inter- cellular organization.\\
Moreover, since all SMLM techniques rely on the analysis of emission patterns from isolated fluorophores, they inherently allocate molecular information $per$ $definitionem$.\\
Consequently, SMLM transitioned from its origin as pure high-resolution imaging instrument towards quantitative microscopy, where the key information medium is no longer the highly resolved image itself, but the raw localization data set.\\
The work presented in this thesis is part of the ongoing effort to translate those $per$ $se$ molecular information gained by SMLM imaging to insights into the structural organization of the targeted protein or even beyond. Although largely consistent in their objectives, the general distinction between global or segmentation clustering approaches on one side and particle averaging or meta-analyses techniques on the other is usually made.\\
During the course of my thesis, I designed, implemented and employed numerous quantitative approaches with varying degrees of complexity and fields of application.\\ \\
In my first major project, I analyzed the localization distribution of the integral protein gp210 of the nuclear pore complex (NPC) with an iterative \textit{k}-means algorithm. Relating the distinct localization statistics of separated gp210 domains to isolated fluorescent signals led, among others, to the conclusion that the anchoring ring of the NPC consists of 8 homo-dimers of gp210.\\
This is of particular significance, both because it answered a decades long standing question about the nature of the gp210 ring and it showcased the possibility to gain structural information well beyond the resolution capabilities of SMLM by crafty quantification approaches.\\ \\
The second major project reported comprises an extensive study of the synaptonemal complex (SNC) and linked cohesin complexes. Here, I employed a multi-level meta-analysis of the localization sets of various SNC proteins to facilitate the compilation of a novel model of the molecular organization of the major SNC components with so far unmatched extend and detail with isotropic three-dimensional resolution.\\
In a second venture, the two murine cohesin components SMC3 and STAG3 connected to the SNC were analyzed. Applying an adapted algorithm, considering the disperse nature of cohesins, led to the realization that there is an apparent polarization of those cohesin complexes in the SNC, as well as a possible sub-structure of STAG3 beyond the resolution capabilities of SMLM.\\ \\
Other minor projects connected to localization quantification included the study of plasma membrane glycans regarding their overall localization distribution and particular homogeneity as well as the investigation of two flotillin proteins in the membrane of bacteria, forming clusters of distinct shapes and sizes.\\ \\
Finally, a novel approach to three-dimensional SMLM is presented, employing the precise quantification of single molecule emitter intensities. This method, named TRABI, relies on the principles of aperture photometry which were improved for SMLM.\\
With TRABI it was shown, that widely used Gaussian fitting based localization software underestimates photon counts significantly. This mismatch was utilized as a $z$-dependent parameter, enabling the conversion of 2D SMLM data to a virtual 3D space. Furthermore it was demonstrated, that TRABI can be combined beneficially with a multi-plane detection scheme, resulting in superior performance regarding axial localization precision and resolution.\\
Additionally, TRABI has been subsequently employed to photometrically characterize a novel dye for SMLM, revealing superior photo-physical properties at the single-molecule level.\\
Following the conclusion of this thesis, the TRABI method and its applications remains subject of diverse ongoing research.
Viral infections induce a significant impact on various functional categories of biological processes in the host. The understanding of this complex modification of the infected host immune system requires a global and detailed overview on the infection process. Therefore it is essential to apply a powerful approach which identifies the involved components conferring the capacity to recognize and respond to specific pathogens, which in general are defeated in so-called compatible virus-plant infections. Comparative and integrated systems biology of plant-virus interaction progression may open a novel framework for a systemic picture on the modulation of plant immunity during different infections and understanding pathogenesis mechanisms. In this thesis these approaches were applied to study plant-virus infections during two main viral pathogens of cassava: Cassava brown streak virus and African cassava mosaic virus.
Here, the infection process was reconstructed by a combination of omics data-based analyses and metabolic network modelling, to understand the major metabolic pathways and elements underlying viral infection responses in different time series, as well as the flux activity distribution to gain more insights into the metabolic flow and mechanism of regulation; this resulted in simultaneous investigations on a broad spectrum of changes in several levels including the gene expression, primary metabolites, and enzymatic flux associated with the characteristic disease development process induced in Nicotiana benthamiana plants due to infection with CBSV or ACMV.
Firstly, the transcriptome dynamics of the infected plant was analysed by using mRNA-sequencing, in order to investigate the differential expression profile according the symptom developmental stage. The spreading pattern and different levels of biological functions of these genes were analysed associated with the infection stage and virus entity. A next step was the Real-Time expression modification of selected key pathway genes followed by their linear regression model. Subsequently, the functional loss of regulatory genes which trigger R-mediated resistance was observed. Substantial differences were observed between infected mutants/transgenic lines and wild-types and characterized in detail. In addition, we detected a massive localized accumulation of ROS and quantified the scavenging genes expression in the infected wild-type plants relative to mock infected controls.
Moreover, we found coordinated regulated metabolites in response to viral infection measured by using LC-MS/MS and HPLC-UV-MS. This includes the profile of the phytohormones, carbohydrates, amino acids, and phenolics at different time points of infection with the RNA and DNA viruses. This was influenced by differentially regulated enzymatic activities along the salicylate, jasmonate, and chorismate biosynthesis, glycolysis, tricarboxylic acid cycle, and pentose phosphate pathways, as well as photosynthesis, photorespiration, transporting, amino acid and fatty acid biosynthesis. We calculated the flux redistribution considering a gradient of modulation for enzymes along different infection stages, ranging from pre-symptoms towards infection stability.
Collectively, our reverse-engineering study consisting of the generation of experimental data and modelling supports the general insight with comparative and integrated systems biology into a model plant-virus interaction system. We refine the cross talk between transcriptome modification, metabolites modulation and enzymatic flux redistribution during compatible infection progression. The results highlight the global alteration in a susceptible host, correlation between symptoms severity and the alteration level. In addition we identify the detailed corresponding general and specific responses to RNA and DNA viruses at different stages of infection. To sum up, all the findings in this study strengthen the necessity of considering the timing of treatment, which greatly affects plant defence against viral infection, and might result in more efficient or combined targeting of a wider range of plant pathogens.
A fundamental question in current biology concerns the translational mechanisms leading from genetic variability to phenotypes. Technologies have evolved to the extent that they can efficiently and economically determine an individual’s genomic composition, while at the same time big data on clinical profiles and diagnostics have substantially accumulated. Genome-wide association studies linking genomic loci to certain traits, however, remain limited in their capacity to explain the cellular mechanisms that underlie the given association. For most associations, gene expression has been blamed; yet given that transcript and protein abundance oftentimes do not correlate, that finding does not necessarily decrypt the underlying mechanism. Thus, the integration of further information is crucial to establish a model that could prove more accurate in predicting genotypic effects on the human organism.
In this work we describe the so-called proteotype as a feature of the cell that could provide a substantial link between genotype and phenotype. Rather than looking at the proteome as a set of independent molecules, we demonstrate a consistent modular architecture of the proteome that is driven by molecular cooperativity. Functional modules, especially protein complexes, can be further interrogated for differences between individuals and tackled as imprints of genetic and environmental variability. We also show that subtle stoichiometric changes of protein modules could have broader effects on the cellular system, such as the transport of specific molecular cargos.
The presented work also delineates to what extent temporal events and processes influence the stoichiometry of protein complexes and functional modules. The re-wiring of the glycolytic pathway for example is illustrated as a potential cause for an increased Warburg effect during the ageing of the human bone marrow. On top of analyzing protein abundances we also interrogate proteome dynamics in terms of stability and solubility transitions during the short temporal progression of the cell cycle. One of our main observations in the thesis encompass the delineation of protein complexes into respective sub-complexes according to distinct stability patterns during the cell cycle. This has never been demonstrated before, and is functionally relevant for our understanding of the dis- and assembly of large protein modules.
The insights presented in this work imply that the proteome is more than the sum of its parts, and primarily driven by variability in entire protein ensembles and their cooperative nature. Analyzing protein complexes and functional modules as molecular reflections of genetic and environmental variations could indeed prove to be a stepping stone in closing the gap between genotype and phenotype and customizing clinical treatments in the future.
Cosmology often uses intricate formulas and mathematics to derive new theories and concepts. We do something different in this paper: We look at biological processes and derive from these heuristics so that the revised cosmology agrees with astronomical observations but does also agree with standard biological observations. We show that we then have to replace any type of singularity at the start of the universe by a condensation nucleus and that the very early period of the universe usually assumed to be inflation has to be replaced by a period of rapid crystal growth as in Weiss magnetization domains.
Impressively, these minor modifications agree well with astronomical observations including removing the strong inflation perturbations which were never observed in the recent BICEP2 experiments. Furthermore, looking at biological principles suggests that such a new theory with a condensation nucleus at start and a first rapid phase of magnetization-like growth of the ordered, physical laws obeying lattice we live in is in fact the only convincing theory of the early phases of our universe that also is compatible with current observations.
We show in detail in the following that such a process of crystal creation, breaking of new crystal seeds and ultimate evaporation of the present crystal readily leads over several generations to an evolution and selection of better, more stable and more self-organizing crystals. Moreover, this explains the “fine-tuning” question why our universe is fine-tuned to favor life: Our Universe is so self-organizing to have enough offspring and the detailed physics involved is at the same time highly favorable for all self-organizing processes including life.
This biological theory contrasts with current standard inflation cosmologies. The latter do not perform well in explaining any phenomena of sophisticated structure creation or self-organization. As proteins can only thermodynamically fold by increasing the entropy in the solution around them we suggest for cosmology a condensation nucleus for a universe can form only in a “chaotic ocean” of string-soup or quantum foam if the entropy outside of the nucleus rapidly increases. We derive an interaction potential for 1 to n-dimensional strings or quantum-foams and show that they allow only 1D, 2D, 4D or octonion interactions. The latter is the richest structure and agrees to the E8 symmetry fundamental to particle physics and also compatible with the ten dimensional string theory E8 which is part of the M-theory. Interestingly, any other interactions of other dimensionality can be ruled out using Hurwitz compositional theorem. Crystallization explains also extremely well why we have only one macroscopic reality and where the worldlines of alternative trajectories exist: They are in other planes of the crystal and for energy reasons they crystallize mostly at the same time, yielding a beautiful and stable crystal. This explains decoherence and allows to determine the size of Planck´s quantum h (very small as separation of crystal layers by energy is extremely strong).
Ultimate dissolution of real crystals suggests an explanation for dark energy agreeing with estimates for the “big rip”. The halo distribution of dark matter favoring galaxy formation is readily explained by a crystal seed starting with unit cells made of normal and dark matter.
That we have only matter and not antimatter can be explained as there may be right handed mattercrystals and left-handed antimatter crystals. Similarly, real crystals are never perfect and we argue that exactly such irregularities allow formation of galaxies, clusters and superclusters. Finally, heuristics from genetics suggest to look for a systems perspective to derive correct vacuum and Higgs Boson energies.
In this work models for molecular networks consisting of ordinary differential equations are extended by terms that include the interaction of the corresponding molecular network with the environment that the molecular network is embedded in. These terms model the effects of the external stimuli on the molecular network. The usability of this extension is demonstrated with a model of a circadian clock that is extended with certain terms and reproduces data from several experiments at the same time.
Once the model including external stimuli is set up, a framework is developed in order to calculate external stimuli that have a predefined desired effect on the molecular network. For this purpose the task of finding appropriate external stimuli is formulated as a mathematical optimal control problem for which in order to solve it a lot of mathematical methods are available. Several methods are discussed and worked out in order to calculate a solution for the corresponding optimal control problem. The application of the framework to find pharmacological intervention points or effective drug combinations is pointed out and discussed. Furthermore the framework is related to existing network analysis tools and their combination for network analysis in order to find dedicated external stimuli is discussed.
The total framework is verified with biological examples by comparing the calculated results with data from literature. For this purpose platelet aggregation is investigated based on a corresponding gene regulatory network and associated receptors are detected. Furthermore a transition from one to another type of T-helper cell is analyzed in a tumor setting where missing agents are calculated to induce the corresponding switch in vitro. Next a gene regulatory network of a myocardiocyte is investigated where it is shown how the presented framework can be used to compare different treatment strategies with respect to their beneficial effects and side effects quantitatively. Moreover a constitutively activated signaling pathway, which thus causes maleficent effects, is modeled and intervention points with corresponding treatment strategies are determined that steer the gene regulatory network from a pathological expression pattern to physiological one again.
Inefficient vascularisation of solid tumours leads to the formation of oxygen and nutrient gradients. In order to mimic this specific feature of the tumour microenvironment, a multicellular tumour spheroid (SPH) culture system was used. These experiments were implemented in p53 isogenic colon cancer cell lines (HCT116 p53 +/+ and HCT116 p53-/-) since Tp53 has important regulatory functions in tumour metabolism. First, the characteristics of the cells cultured as monolayers and as spheroids were investigated by using RNA sequencing and metabolomics to compare gene expression and metabolic features of cells grown in different conditions. This analysis showed that certain features of gene expression found in tumours are also present in spheroids but not in monolayer cultures, including reduced proliferation and induction of hypoxia related genes. Moreover, comparison between the different genotypes revealed that the expression of genes involved in cholesterol homeostasis is induced in p53 deficient cells compared to p53 wild type cells and this difference was only detected in spheroids and tumour samples but not in monolayer cultures. In addition, it was established that loss of p53 leads to the induction of enzymes of the mevalonate pathway via activation of the transcription factor SREBP2, resulting in a metabolic rewiring that supports the generation of ubiquinone (coenzyme Q10). An adequate supply of ubiquinone was essential to support mitochondrial electron transport and pyrimidine biosynthesis in p53 deficient cancer cells under conditions of metabolic stress. Moreover, inhibition of the mevalonate pathway using statins selectively induced oxidative stress and apoptosis in p53 deficient colon cancer cells exposed to oxygen and nutrient deprivation. This was caused by ubiquinone being required for electron transfer by dihydroorotate dehydrogenase, an essential enzyme of the pyrimidine nucleotide biosynthesis pathway. Supplementation with exogenous nucleosides relieved the demand for electron transfer and restored viability of p53 deficient cancer cells under metabolic stress. Moreover, the mevalonate pathway was also essential for the synthesis of ubiquinone for nucleotide biosynthesis to support growth of intestinal tumour organoids. Together, these findings highlight the importance of the mevalonate pathway in cancer cells and provide molecular evidence for an enhanced sensitivity towards the inhibition of mitochondrial electron transfer in tumour-like metabolic environments.