Recurrent Phases of Strict Protein Limitation Inhibit Tumor Growth and Restore Lifespan in A Drosophila Intestinal Cancer Model.

Diets that restrict caloric or protein intake offer a variety of benefits, including decreasing the incidence of cancer. However, whether such diets pose a substantial therapeutic benefit as auxiliary cancer treatments remains unclear. We determined the effects of severe protein depletion on tumorigenesis in a Drosophila melanogaster intestinal tumor model, using a human RAF gain-of-function allele. Severe and continuous protein restriction significantly reduced tumor growth but resulted in premature death. Therefore, we developed a diet in which short periods of severe protein restriction alternated cyclically with periods of complete feeding. This nutritional regime reduced tumor mass, restored gut functionality, and rescued the lifespan of oncogene-expressing flies to the levels observed in healthy flies on a continuous, fully nutritious diet. Furthermore, this diet reduced the chemotherapy-induced stem cell activity associated with tumor recurrence. Transcriptome analysis revealed long-lasting changes in the expression of key genes involved in multiple major developmental signaling pathways. Overall, the data suggest that recurrent severe protein depletion effectively mimics the health benefits of continuous protein restriction, without undesired nutritional shortcomings. This provides seminal insights into the mechanisms of the memory effect required to maintain the positive effects of protein restriction throughout the phases of a full diet. Finally, the repetitive form of strict protein restriction is an ideal strategy for adjuvant cancer therapy that is useful in many tumor contexts.

The Gene Expression Classifier ALLCatchR Identifies B-cell Precursor ALL Subtypes and Underlying Developmental Trajectories Across Age.

Current classifications (World Health Organization-HAEM5/ICC) define up to 26 molecular B-cell precursor acute lymphoblastic leukemia (BCP-ALL) disease subtypes by genomic driver aberrations and corresponding gene expression signatures. Identification of driver aberrations by transcriptome sequencing (RNA-Seq) is well established, while systematic approaches for gene expression analysis are less advanced. Therefore, we developed ALLCatchR, a machine learning-based classifier using RNA-Seq gene expression data to allocate BCP-ALL samples to all 21 gene expression-defined molecular subtypes. Trained on n = 1869 transcriptome profiles with established subtype definitions (4 cohorts; 55% pediatric / 45% adult), ALLCatchR allowed subtype allocation in 3 independent hold-out cohorts (n = 1018; 75% pediatric / 25% adult) with 95.7% accuracy (averaged sensitivity across subtypes: 91.1% / specificity: 99.8%). High-confidence predictions were achieved in 83.7% of samples with 98.9% accuracy. Only 1.2% of samples remained unclassified. ALLCatchR outperformed existing tools and identified novel driver candidates in previously unassigned samples. Additional modules provided predictions of samples blast counts, patient's sex, and immunophenotype, allowing the imputation in cases where these information are missing. We established a novel RNA-Seq reference of human B-lymphopoiesis using 7 FACS-sorted progenitor stages from healthy bone marrow donors. Implementation in ALLCatchR enabled projection of BCP-ALL samples to this trajectory. This identified shared proximity patterns of BCP-ALL subtypes to normal lymphopoiesis stages, extending immunophenotypic classifications with a novel framework for developmental comparisons of BCP-ALL. ALLCatchR enables RNA-Seq routine application for BCP-ALL diagnostics with systematic gene expression analysis for accurate subtype allocation and novel insights into underlying developmental trajectories.

A dietary carbohydrate - gut Parasutterella - human fatty acid biosynthesis metabolic axis in obesity and type 2 diabetes.

Recent rodent microbiome experiments suggest that besides Akkermansia, Parasutterella sp. are important in type 2 diabetes and obesity development. In the present translational human study, we aimed to characterize Parasutterella in our European cross-sectional FoCus cohort (n = 1,544) followed by validation of the major results in an independent Canadian cohort (n = 438). In addition, we examined Parasutterella abundance in response to a weight loss intervention (n = 55). Parasutterella was positively associated with BMI and type 2 diabetes independently of the reduced microbiome α/ß diversity and low-grade inflammation commonly found in obesity. Nutritional analysis revealed a positive association with the dietary intake of carbohydrates but not with fat or protein consumption. Out of 126 serum metabolites differentially detectable by untargeted HPLC-based MS-metabolomics, L-cysteine showed the strongest reduction in subjects with high Parasutterella abundance. This is of interest, since Parasutterella is a known high L-cysteine consumer and L-cysteine is known to improve blood glucose levels in rodents. Furthermore, metabolic network enrichment analysis identified an association of high Parasutterella abundance with the activation of the human fatty acid biosynthesis pathway suggesting a mechanism for body weight gain. This is supported by a significant reduction of the Parasutterella abundance during our weight loss intervention. Together, these data indicate a role for Parasutterella in human type 2 diabetes and obesity, whereby the link to L-cysteine might be relevant in type 2 diabetes development and the link to the fatty acid biosynthesis pathway for body weight gain in response to a carbohydrate-rich diet in obesity development.

Microbial regulation of hexokinase 2 links mitochondrial metabolism and cell death in colitis.

Hexokinases (HK) catalyze the first step of glycolysis limiting its pace. HK2 is highly expressed in gut epithelium, contributes to immune responses, and is upregulated during inflammation. We examined the microbial regulation of HK2 and its impact on inflammation using mice lacking HK2 in intestinal epithelial cells (Hk2ΔIEC). Hk2ΔIEC mice were less susceptible to acute colitis. Analyzing the epithelial transcriptome from Hk2ΔIEC mice during colitis and using HK2-deficient intestinal organoids and Caco-2 cells revealed reduced mitochondrial respiration and epithelial cell death in the absence of HK2. The microbiota strongly regulated HK2 expression and activity. The microbially derived short-chain fatty acid (SCFA) butyrate repressed HK2 expression via histone deacetylase 8 (HDAC8) and reduced mitochondrial respiration in wild-type but not in HK2-deficient Caco-2 cells. Butyrate supplementation protected wild-type but not Hk2ΔIEC mice from colitis. Our findings define a mechanism how butyrate promotes intestinal homeostasis and suggest targeted HK2-inhibition as therapeutic avenue for inflammation.

Modeling the energy metabolism in immune cells.

In this review, we summarize and briefly discuss various approaches to modeling the metabolism in human immune cells, with a focus on energy metabolism. These approaches include metabolic reconstruction, elementary modes, and flux balance analysis, which are often subsumed under constraint-based modeling. Further approaches are evolutionary game theory and kinetic modeling. Many immune cells such as macrophages show the Warburg effect, meaning that glycolysis is upregulated upon activation. We outline a minimal model for explaining that effect using optimization. The effect of a confrontation with pathogen cells on immunometabolism is highlighted. Models describing the differences between M1 and M2 macrophages, ROS production in neutrophils, and tryptophan metabolism are discussed. Obstacles and future prospects are outlined.

Metabolic Functions of Gut Microbes Associate With Efficacy of Tumor Necrosis Factor Antagonists in Patients With Inflammatory Bowel Diseases.

BACKGROUND & AIMS: Altered interactions between the mucosal immune system and intestinal microbiota contribute to pathogenesis of inflammatory bowel diseases (IBD). It is not clear how inhibitors of cytokines, such as antagonists of tumor necrosis factor (anti-TNF), affect the intestinal microbiome. We investigated the effects of anti-TNF agents on gut microbe community structure and function in a longitudinal 2-step study of patients with IBD. We correlated our findings with outcomes of treatment and investigated patterns of metabolites in fecal samples before and after anti-TNF therapy. METHODS: We performed a prospective study of 2 cohorts of patients in Germany; the discovery cohort comprised 12 patients with IBD, 17 patients with rheumatic disease, and 19 healthy individuals (controls); fecal samples were collected at baseline and 2, 6, and 30 weeks after induction of anti-TNF therapy. The validation cohort comprised 23 patients with IBD treated with anti-TNF or vedolizumab (anti-α4ß7 integrin) and 99 healthy controls; fecal samples were collected at baseline and at weeks 2, 6, and 14. Fecal microbiota were analyzed by V3-V4 16S ribosomal RNA gene amplicon sequencing. Clinical response and remission were determined by clinical disease activity scores. Metabolic network reconstruction and associated fecal metabolite level inference was performed in silico using the AGORA (Assembly of Gut Organisms through Reconstruction and Analysis) resource. Metabolomic analyses of fecal samples from a subset of patients were performed to validate metabolites associated with treatment outcomes. RESULTS: Anti-TNF therapy shifted the diversity of fecal microbiota in patients with IBD, but not with rheumatic disease, toward that of controls. Across timepoints, diversity indices did not vary significantly between patients with IBD who did or did not achieve clinical remission after therapy. In contrast, in silico modeling of metabolic interactions between gut microbes found metabolite exchange to be significantly reduced at baseline in fecal samples from patients with IBD and to be associated with later clinical remission. Predicted levels of butyrate and substrates involved in butyrate synthesis (ethanol or acetaldehyde) were significantly associated with clinical remission following anti-TNF therapy, verified by fecal metabolomic analyses. CONCLUSIONS: Metabolic network reconstruction and assessment of metabolic profiles of fecal samples might be used to identify patients with IBD likely to achieve clinical remission following anti-TNF therapy and increase our understanding of the heterogeneity of IBD.

Publisher Correction: Transcriptomic alterations during ageing reflect the shift from cancer to degenerative diseases in the elderly.

The original version of this Article contained an error in the spelling of the author Jule Müller, which was incorrectly given as Julia Müller. Additionally, in Fig. 4a, the blue-red colour scale for fold change in ageing/disease regulation included a blue stripe in place of a red stripe at the right-hand end of the scale. These errors have been corrected in both the PDF and HTML versions of the Article.

Metastasis of pancreatic cancer: An uninflamed liver micromilieu controls cell growth and cancer stem cell properties by oxidative phosphorylation in pancreatic ductal epithelial cells.

Pancreatic ductal adenocarcinoma (PDAC) is commonly diagnosed when liver metastases already emerged. We recently demonstrated that hepatic stromal cells determine the dormancy status along with cancer stem cell (CSC) properties of pancreatic ductal epithelial cells (PDECs) during metastasis. This study investigated the influence of the hepatic microenvironment - and its inflammatory status - on metabolic alterations and how these impact cell growth and CSC-characteristics of PDECs. Coculture with hepatic stellate cells (HSCs), simulating a physiological liver stroma, but not with hepatic myofibroblasts (HMFs) representing liver inflammation promoted expression of Succinate Dehydrogenase subunit B (SDHB) and an oxidative metabolism along with a quiescent phenotype in PDECs. SiRNA-mediated SDHB knockdown increased cell growth and CSC-properties. Moreover, liver micrometastases of tumor bearing KPC mice strongly expressed SDHB while expression of the CSC-marker Nestin was exclusively found in macrometastases. Consistently, RNA-sequencing and in silico modeling revealed significantly altered metabolic fluxes and enhanced SDH activity predominantly in premalignant PDECs in the presence of HSC compared to HMF. Overall, these data emphasize that the hepatic microenvironment determines the metabolism of disseminated PDECs thereby controlling cell growth and CSC-properties during liver metastasis.

Epithelial RNase H2 Maintains Genome Integrity and Prevents Intestinal Tumorigenesis in Mice.

BACKGROUND & AIMS: RNase H2 is a holoenzyme, composed of 3 subunits (ribonuclease H2 subunits A, B, and C), that cleaves RNA:DNA hybrids and removes mis-incorporated ribonucleotides from genomic DNA through ribonucleotide excision repair. Ribonucleotide incorporation by eukaryotic DNA polymerases occurs during every round of genome duplication and produces the most frequent type of naturally occurring DNA lesion. We investigated whether intestinal epithelial proliferation requires RNase H2 function and whether RNase H2 activity is disrupted during intestinal carcinogenesis. METHODS: We generated mice with epithelial-specific deletion of ribonuclease H2 subunit B (H2bΔIEC) and mice that also had deletion of tumor-suppressor protein p53 (H2b/p53ΔIEC); we compared phenotypes with those of littermate H2bfl/fl or H2b/p53fl/fl (control) mice at young and old ages. Intestinal tissues were collected and analyzed by histology. We isolated epithelial cells, generated intestinal organoids, and performed RNA sequence analyses. Mutation signatures of spontaneous tumors from H2b/p53ΔIEC mice were characterized by exome sequencing. We collected colorectal tumor specimens from 467 patients, measured levels of ribonuclease H2 subunit B, and associated these with patient survival times and transcriptome data. RESULTS: The H2bΔIEC mice had DNA damage to intestinal epithelial cells and proliferative exhaustion of the intestinal stem cell compartment compared with controls and H2b/p53ΔIEC mice. However, H2b/p53ΔIEC mice spontaneously developed small intestine and colon carcinomas. DNA from these tumors contained T>G base substitutions at GTG trinucleotides. Analyses of transcriptomes of human colorectal tumors associated lower levels of RNase H2 with shorter survival times. CONCLUSIONS: In analyses of mice with disruption of the ribonuclease H2 subunit B gene and colorectal tumors from patients, we provide evidence that RNase H2 functions as a colorectal tumor suppressor. H2b/p53ΔIEC mice can be used to study the roles of RNase H2 in tissue-specific carcinogenesis.

Transcriptomic alterations during ageing reflect the shift from cancer to degenerative diseases in the elderly.

Disease epidemiology during ageing shows a transition from cancer to degenerative chronic disorders as dominant contributors to mortality in the old. Nevertheless, it has remained unclear to what extent molecular signatures of ageing reflect this phenomenon. Here we report on the identification of a conserved transcriptomic signature of ageing based on gene expression data from four vertebrate species across four tissues. We find that ageing-associated transcriptomic changes follow trajectories similar to the transcriptional alterations observed in degenerative ageing diseases but are in opposite direction to the transcriptomic alterations observed in cancer. We confirm the existence of a similar antagonism on the genomic level, where a majority of shared risk alleles which increase the risk of cancer decrease the risk of chronic degenerative disorders and vice versa. These results reveal a fundamental trade-off between cancer and degenerative ageing diseases that sheds light on the pronounced shift in their epidemiology during ageing.

Modelling the host-pathogen interactions of macrophages and Candida albicans using Game Theory and dynamic optimization.

The release of fungal cells following macrophage phagocytosis, called non-lytic expulsion, is reported for several fungal pathogens. On one hand, non-lytic expulsion may benefit the fungus in escaping the microbicidal environment of the phagosome. On the other hand, the macrophage could profit in terms of avoiding its own lysis and being able to undergo proliferation. To analyse the causes of non-lytic expulsion and the relevance of macrophage proliferation in the macrophage-Candida albicans interaction, we employ Evolutionary Game Theory and dynamic optimization in a sequential manner. We establish a game-theoretical model describing the different strategies of the two players after phagocytosis. Depending on the parameter values, we find four different Nash equilibria and determine the influence of the systems state of the host upon the game. As our Nash equilibria are a direct consequence of the model parameterization, we can depict several biological scenarios. A parameter region, where the host response is robust against the fungal infection, is determined. We further apply dynamic optimization to analyse whether macrophage mitosis is relevant in the host-pathogen interaction of macrophages and C. albicans For this, we study the population dynamics of the macrophage-C. albicans interactions and the corresponding optimal controls for the macrophages, indicating the best macrophage strategy of switching from proliferation to attacking fungal cells.

Uncoupling of mucosal gene regulation, mRNA splicing and adherent microbiota signatures in inflammatory bowel disease.

OBJECTIVE: An inadequate host response to the intestinal microbiota likely contributes to the manifestation and progression of human inflammatory bowel disease (IBD). However, molecular approaches to unravelling the nature of the defective crosstalk and its consequences for intestinal metabolic and immunological networks are lacking. We assessed the mucosal transcript levels, splicing architecture and mucosa-attached microbial communities of patients with IBD to obtain a comprehensive view of the underlying, hitherto poorly characterised interactions, and how these are altered in IBD. DESIGN: Mucosal biopsies from Crohn's disease and patients with UC, disease controls and healthy individuals (n=63) were subjected to microbiome, transcriptome and splicing analysis, employing next-generation sequencing. The three data levels were integrated by different bioinformatic approaches, including systems biology-inspired network and pathway analysis. RESULTS: Microbiota, host transcript levels and host splicing patterns were influenced most strongly by tissue differences, followed by the effect of inflammation. Both factors point towards a substantial disease-related alteration of metabolic processes. We also observed a strong enrichment of splicing events in inflamed tissues, accompanied by an alteration of the mucosa-attached bacterial taxa. Finally, we noted a striking uncoupling of the three molecular entities when moving from healthy individuals via disease controls to patients with IBD. CONCLUSIONS: Our results provide strong evidence that the interplay between microbiome and host transcriptome, which normally characterises a state of intestinal homeostasis, is drastically perturbed in Crohn's disease and UC. Consequently, integrating multiple OMICs levels appears to be a promising approach to further disentangle the complexity of IBD.

Differential transcriptional responses to Ebola and Marburg virus infection in bat and human cells.

The unprecedented outbreak of Ebola in West Africa resulted in over 28,000 cases and 11,000 deaths, underlining the need for a better understanding of the biology of this highly pathogenic virus to develop specific counter strategies. Two filoviruses, the Ebola and Marburg viruses, result in a severe and often fatal infection in humans. However, bats are natural hosts and survive filovirus infections without obvious symptoms. The molecular basis of this striking difference in the response to filovirus infections is not well understood. We report a systematic overview of differentially expressed genes, activity motifs and pathways in human and bat cells infected with the Ebola and Marburg viruses, and we demonstrate that the replication of filoviruses is more rapid in human cells than in bat cells. We also found that the most strongly regulated genes upon filovirus infection are chemokine ligands and transcription factors. We observed a strong induction of the JAK/STAT pathway, of several genes encoding inhibitors of MAP kinases (DUSP genes) and of PPP1R15A, which is involved in ER stress-induced cell death. We used comparative transcriptomics to provide a data resource that can be used to identify cellular responses that might allow bats to survive filovirus infections.

Mathematical models for explaining the Warburg effect: a review focussed on ATP and biomass production.

For producing ATP, tumour cells rely on glycolysis leading to lactate to about the same extent as on respiration. Thus, the ATP synthesis flux from glycolysis is considerably higher than in the corresponding healthy cells. This is known as the Warburg effect (named after German biochemist Otto H. Warburg) and also applies to striated muscle cells, activated lymphocytes, microglia, endothelial cells and several other cell types. For similar phenomena in several yeasts and many bacteria, the terms Crabtree effect and overflow metabolism respectively, are used. The Warburg effect is paradoxical at first sight because the molar ATP yield of glycolysis is much lower than that of respiration. Although a straightforward explanation is that glycolysis allows a higher ATP production rate, the question arises why cells do not re-allocate protein to the high-yield pathway of respiration. Mathematical modelling can help explain this phenomenon. Here, we review several models at various scales proposed in the literature for explaining the Warburg effect. These models support the hypothesis that glycolysis allows for a higher proliferation rate due to increased ATP production and precursor supply rates.

Metabolic costs of amino acid and protein production in Escherichia coli.

Escherichia coli is the most popular microorganism for the production of recombinant proteins and is gaining increasing importance for the production of low-molecular weight compounds such as amino acids. The metabolic cost associated with the production of amino acids and (recombinant) proteins from glucose, glycerol and acetate was determined using three different computational techniques to identify those amino acids that put the highest burden on the biosynthetic machinery of E. coli. Comparing the costs of individual amino acids, we find that methionine is the most expensive amino acid in terms of consumed mol of ATP per molecule produced, while leucine is the most expensive amino acid when taking into account the cellular abundances of amino acids. Moreover, we show that the biosynthesis of a large number of amino acids from glucose and particularly from glycerol provides a surplus of energy, which can be used to balance the high energetic cost of amino acid polymerization.

Detecting and investigating substrate cycles in a genome-scale human metabolic network.

Substrate cycles, also known as futile cycles, are cyclic metabolic routes that dissipate energy by hydrolysing cofactors such as ATP. They were first described to occur in the muscles of bumblebees and brown adipose tissue in the 1970s. A popular example is the conversion of fructose 6-phosphate to fructose 1,6-bisphosphate and back. In the present study, we analyze a large number of substrate cycles in human metabolism that consume ATP and discuss their statistics. For this purpose, we use two recently published methods (i.e. EFMEvolver and the K-shortest EFM method) to calculate samples of 100,000 and 15,000 substrate cycles, respectively. We find an unexpectedly high number of substrate cycles in human metabolism, with up to 100 reactions per cycle, utilizing reactions from up to six different compartments. An analysis of tissue-specific models of liver and brain metabolism shows that there is selective pressure that acts against the uncontrolled dissipation of energy by avoiding the coexpression of enzymes belonging to the same substrate cycle. This selective force is particularly strong against futile cycles that have a high flux as a result of thermodynamic principles.

Combining metabolic pathway analysis with Evolutionary Game Theory: explaining the occurrence of low-yield pathways by an analytic optimization approach.

Elementary-mode analysis is a powerful method for detecting all potential pathways in a metabolic network and computing the associated molar yields. Metabolic pathways can be interpreted as different strategies of organisms. Thus, methods from Evolutionary Game Theory can be employed. In Flux Balance Analysis (FBA), it is usually assumed that molar yields of relevant products (such as biomass or ATP) have been maximized during evolution. This has been questioned on game-theoretical grounds. In particular, in situations that can be characterized as a Prisoner's Dilemma, maximization of flux is not in line with maximization of yield. Under other conditions (that is, for other parameter values of maximal velocities), a Harmony game can result, where the above two maximization criteria give the same result. Here, we analyse the optimal situations under varying conditions. In particular, we consider the case where the cell can allocate a certain amount of protein on several enzymes in a varying distribution and model this by a linear programming problem in which not only the rates but also the maximal velocities are variable. It turns out that in the case of low or moderate synthesis costs for the enzymes of the high-yield pathway, maximizing pathway flux is in line with maximizing molar yield while in the case of high costs, it is not. This may explain the observation that many cells such as striated muscle cells, tumour cells, activated lymphocytes and several yeasts do not reallocate protein away from glycolytic enzymes towards TCA cycle and respiratory chain enzymes, in spite of the higher efficiency of respiration. This provides a straightforward explanation of the Warburg effect in tumour cells.

Inhibition of alanine aminotransferase in silico and in vivo promotes mitochondrial metabolism to impair malignant growth.

Cancer cells commonly exhibit increased nonoxidative D-glucose metabolism whereas induction of mitochondrial metabolism may impair malignant growth. We have first used an in silico method called elementary mode analysis to identify inhibition of ALAT (L-alanine aminotransferase) as a putative target to promote mitochondrial metabolism. We then experimentally show that two competitive inhibitors of ALAT, L-cycloserine and ß-chloro-L-alanine, inhibit L-alanine production and impair D-glucose uptake of LLC1 Lewis lung carcinoma cells. The latter inhibition is linked to an initial energy deficit, as quantified by decreased ATP content, which is then followed by an activation of AMP-activated protein kinase and subsequently increased respiration rates and mitochondrial production of reactive oxygen species, culminating in ATP replenishment in ALAT-inhibited LLC1 cells. Moreover, we observe altered phosphorylation of p38 MAPK (mitogen-activated protein kinase 14), ERK (extracellular signal-regulated kinase 1/2), and Rb1 (retinoblastoma 1) proteins, as well as decreased expression of Cdc25a (cell decision cycle 25 homolog A) and Cdk4 (cyclin-dependent kinase 4). Importantly, these sequelae of ALAT inhibition culminate in similarly reduced anchorage-dependent and anchorage-independent growth rates of LLC1 cells, together suggesting that inhibition of ALAT efficiently impairs cancer growth by counteracting the Warburg effect due to compensatory activation of mitochondrial metabolism.