Temporal fluxomics reveals oscillations in TCA cycle flux throughout the mammalian cell cycle

Inferring metabolic objectives and trade-offs in single cells during embryogenesis

While proliferating cells optimize their metabolism to produce biomass, the metabolic objectives of cells that perform non-proliferative tasks are unclear. The opposing requirements for optimizing each objective result in a trade-off that forces single cells to prioritize their metabolic needs and optimally allocate limited resources. Here, we present single-cell optimization objective and trade-off inference (SCOOTI), which infers metabolic objectives and trade-offs in biological systems by integrating bulk and single-cell omics data, using metabolic modeling and machine learning. We validated SCOOTI by identifying essential genes from CRISPR-Cas9 screens in embryonic stem cells, and by inferring the metabolic objectives of quiescent cells, during different cell-cycle phases. Applying this to embryonic cell states, we observed a decrease in metabolic entropy upon development. We further uncovered a trade-off between glutathione and biosynthetic precursors in one-cell zygote, two-cell embryo, and blastocyst cells, potentially representing a trade-off between pluripotency and proliferation. A record of this paper's transparent peer review process is included in the supplemental information.

The main sources of molecular organization in the cell. Atlas of self-organized and self-regulated dynamic biostructures

One of the most important goals of contemporary biology is to understand the principles of the molecular order underlying the complex dynamic architecture of cells. Here, we present an overview of the main driving forces involved in the cellular molecular complexity and in the emergent functional dynamic structures, spanning from the most basic molecular organization levels to the complex emergent integrative systemic behaviors. First, we address the molecular information processing which is essential in many complex fundamental mechanisms such as the epigenetic memory, alternative splicing, regulation of transcriptional system, and the adequate self-regulatory adaptation to the extracellular environment. Next, we approach the biochemical self-organization, which is central to understand the emergency of metabolic rhythms, circadian oscillations, and spatial traveling waves. Such a complex behavior is also fundamental to understand the temporal compartmentalization of the cellular metabolism and the dynamic regulation of many physiological activities. Numerous examples of biochemical self-organization are considered here, which show that practically all the main physiological processes in the cell exhibit this type of dynamic molecular organization. Finally, we focus on the biochemical self-assembly which, at a primary level of organization, is a basic but important mechanism for the order in the cell allowing biomolecules in a disorganized state to form complex aggregates necessary for a plethora of essential structures and physiological functions. In total, more than 500 references have been compiled in this review. Due to these main sources of order, systemic functional structures emerge in the cell, driving the metabolic functionality towards the biological complexity.

Integrative Proteomics-Metabolomics of In Vitro Degeneration of Cardiovascular Cell Lines

Long-term cell culture is an important biological approach but is also characterized by degeneration in cellular morphology, proliferation rate, and function. To explore this phenomenon in a systematic way, we conducted an integrative proteomics-metabolomics measurement of two cardiovascular cell lines of AC16 and HUVECs. The 18th culturing passages, i.e., G18, showed as the turning points by cell metabolism profiles, in which the metabolomic changes demonstrated the dysfunction of energy, amino acid, and ribonucleotide metabolism metabolic pathways. Although active protein networks showed mitochondria abundance AC16 and oxidative/nitrative sensitive HUVECs indicated the different degeneration patterns, the G18 and G30 proteomics evidenced the senescence by processes of signal transduction, signaling by interleukins, programmed cell death, cellular responses to stimuli, cell cycle, mRNA splicing, and translation. Some crucial proteins (RPS8, HNRNPR, SOD2, LMNB1, PSMA1, DECR1, GOT2, OGDH, PNP, CBS, ATIC, and IMPDH2) and metabolites (L-glutamic acid, guanine, citric acid, guanosine, guanosine diphosphate, glucose 6-phosphate, and adenosine) that contributed to the dysregulation of cellular homeostasis are identified by using the integrative proteomic-metabolomic analysis, which highlighted the increased cellular instability. These findings illuminate some vital molecular processes when culturing serial passages, which contribute holistic viewpoints of in vitro biology with emphasis on the replicative senescence of cardiovascular cells.

Re-scoping ultradian rhythms in the context of metabolism

Rapid, ultradian biological rhythms are only partly comparable to circadian (24-h) rhythms. Often, the ensuing expectations from this comparison are that 1) ultradian rhythms should be driven by discrete oscillators, 2) they are biochemically buffered, and 3) they must be functionally linked to extrinsic events and cycles. These three expectations are not always met, but perhaps there is an adaptive benefit to ultradian rhythms not meeting these expectations, which sets them functionally apart from circadian rhythms. In view of the extensive descriptions of the manifold types of ultradian rhythms across all biological levels (e.g., see papers in this research topic), it seems important to ask whether we should actively create a new set of definitions and expectations. To make a start, we here lay out some important questions we need to ask about ultradian rhythms. We then illustrate how these questions highlight one key area of exploration: the linked expression of ultradian rhythms in metabolism and behaviour and the role this plays in addressing a negative energy balance.

A chloroplast sulphate transporter modulates glutathione-mediated redox cycling to regulate cell division

Glutathione redox cycling is important for cell cycle regulation, but its mechanisms are not well understood. We previously identified a small-sized mutant, suppressor of mat3 15-1 (smt15-1) that has elevated cellular glutathione. Here, we demonstrated that SMT15 is a chloroplast sulphate transporter. Reducing expression of γ-GLUTAMYLCYSTEINE SYNTHETASE, encoding the rate-limiting enzyme required for glutathione biosynthesis, corrected the size defect of smt15-1 cells. Overexpressing GLUTATHIONE SYNTHETASE (GSH2) recapitulated the small-size phenotype of smt15-1 mutant, confirming the role of glutathione in cell division. Hence, SMT15 may regulate chloroplast sulphate concentration to modulate cellular glutathione levels. In wild-type cells, glutathione and/or thiol-containing molecules (GSH/thiol) accumulated in the cytosol at the G1 phase and decreased as cells entered the S/M phase. While the cytosolic GSH/thiol levels in the small-sized mutants, smt15-1 and GSH2 overexpressors, mirrored those of wild-type cells (accumulating during G1 and declining at early S/M phase), GSH/thiol was specifically accumulated in the basal bodies at early S/M phase in the small-sized mutants. Therefore, we propose that GSH/thiol-mediated redox signalling in the basal bodies may regulate mitotic division number in Chlamydomonas reinhardtii. Our findings suggest a new mechanism by which glutathione regulates the multiple fission cell cycle in C. reinhardtii.

Identification and validation of protein biomarkers for predicting gastrointestinal stromal tumor recurrence

We conducted a proteomic analysis using mass spectrometry to identify and validate protein biomarkers for accurately predicting recurrence risk in gastrointestinal stromal tumors (GIST) patients, focusing on differentially expressed proteins in metastatic versus primary GIST tissues. We selected five biomarkers-GPX4, RBM4, TPM3, PFKFB2, and PGAM5-and validated their expressions in primary tumors of recurrent and non-recurrent GIST patients via immunohistochemistry. Our analysis of the association between these biomarkers with recurrence-free survival (RFS) and overall survival (OS), along with their interrelationships, revealed that immunohistochemistry confirmed significantly higher expressions of these biomarkers in primary GIST tissues of recurrent patients. Kaplan-Meier survival analysis showed that high expressions of GPX4, RBM4, TPM3, PFKFB2, and PGAM5 correlated with lower RFS, and GPX4 and RBM4 with lower OS. All biomarker pairs showed positive associations, with high expressions correlating with increased recurrence rates, and GPX4 and RBM4 with higher mortality rates. In conclusion, the biomarkers GPX4, RBM4, TPM3, PFKFB2, and PGAM5 are clinically relevant for predicting GIST recurrence, with their high expressions in primary tumors linked to poorer RFS and OS. They serve as potential prognostic indicators, enabling early treatment and improved outcomes. The observed interrelationships among these biomarkers further validate their accuracy in predicting GIST recurrence.

Unlocking mitochondrial dysfunction-associated senescence (MiDAS) with NAD+ - A Boolean model of mitochondrial dynamics and cell cycle control

The steady accumulation of senescent cells with aging creates tissue environments that aid cancer evolution. Aging cell states are highly heterogeneous. 'Deep senescent' cells rely on healthy mitochondria to fuel a strong proinflammatory secretome, including cytokines, growth and transforming signals. Yet, the physiological triggers of senescence such as reactive oxygen species (ROS) can also trigger mitochondrial dysfunction, and sufficient energy deficit to alter their secretome and cause chronic oxidative stress - a state termed Mitochondrial Dysfunction-Associated Senescence (MiDAS). Here, we offer a mechanistic hypothesis for the molecular processes leading to MiDAS, along with testable predictions. To do this we have built a Boolean regulatory network model that qualitatively captures key aspects of mitochondrial dynamics during cell cycle progression (hyper-fusion at the G1/S boundary, fission in mitosis), apoptosis (fission and dysfunction) and glucose starvation (reversible hyper-fusion), as well as MiDAS in response to SIRT3 knockdown or oxidative stress. Our model reaffirms the protective role of NAD+ and external pyruvate. We offer testable predictions about the growth factor- and glucose-dependence of MiDAS and its reversibility at different stages of reactive oxygen species (ROS)-induced senescence. Our model provides mechanistic insights into the distinct stages of DNA-damage induced senescence, the relationship between senescence and epithelial-to-mesenchymal transition in cancer and offers a foundation for building multiscale models of tissue aging.

Advances in metabolomics profiling of pediatric kidney diseases: A review

Pediatric renal diseases encompass a diverse array of pathological conditions, often engendering enduring ramifications. Metabolomics, an emergent branch of omics sciences, endeavors to holistically delineate alterations in metabolite compositions through the amalgamation of sophisticated analytical chemistry techniques and robust statistical methodologies. Recent advancements in metabolomics research within the realm of pediatric nephrology have been substantial, offering promising avenues for the identification of robust biomarkers, the elaboration of novel therapeutic targets, and the intricate elucidation of molecular mechanisms. The present discourse aims to critically review the progress in metabolomics profiling pertinent to pediatric renal disorders over the previous 12 years.

APC/C-regulated CPT1C promotes tumor progression by upregulating the energy supply and accelerating the G1/S transition

BACKGROUND

In addition to functioning as a precise monitoring mechanism in cell cycle, the anaphase-promoting complex/cyclosome (APC/C) is reported to be involved in regulating multiple metabolic processes by facilitating the ubiquitin-mediated degradation of key enzymes. Fatty acid oxidation is a metabolic pathway utilized by tumor cells that is crucial for malignant progression; however, its association with APC/C remains to be explored.

METHODS

Cell cycle synchronization, immunoblotting, and propidium iodide staining were performed to investigate the carnitine palmitoyltransferase 1 C (CPT1C) expression manner. Proximity ligation assay and co-immunoprecipitation were performed to detect interactions between CPT1C and APC/C. Flow cytometry, 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2 H-tetrazolium, inner salt (MTS) assays, cell-scratch assays, and transwell assays and xenograft transplantation assays were performed to investigate the role of CPT1C in tumor progression in vitro and in vivo. Immunohistochemistry was performed on tumor tissue microarray to evaluate the expression levels of CPT1C and explore its potential clinical value.

RESULTS

We identified CPT1C as a novel APC/C substrate. CPT1C protein levels exhibited cell cycle-dependent fluctuations, peaking at the G1/S boundary. Elevated CPT1C accelerated the G1/S transition, facilitating tumor cell proliferation in vitro and in vivo. Furthermore, CPT1C enhanced fatty acid utilization, upregulated ATP levels, and decreased reactive oxygen species levels, thereby favoring cell survival in a harsh metabolic environment. Clinically, high CPT1C expression correlated with poor survival in patients with esophageal squamous cell carcinoma.

CONCLUSIONS

Overall, our results revealed a novel interplay between fatty acid utilization and cell cycle machinery in tumor cells. Additionally, CPT1C promoted tumor cell proliferation and survival by augmenting cellular ATP levels and preserving redox homeostasis, particularly under metabolic stress. Therefore, CPT1C could be an independent prognostic indicator in esophageal squamous cell carcinoma.

Unlocking Mitochondrial Dysfunction-Associated Senescence (MiDAS) with NAD + - a Boolean Model of Mitochondrial Dynamics and Cell Cycle Control

The steady accumulation of senescent cells with aging creates tissue environments that aid cancer evolution. Aging cell states are highly heterogeneous. 'Deep senescent' cells rely on healthy mitochondria to fuel a strong proinflammatory secretome, including cytokines, growth and transforming signals. Yet, the physiological triggers of senescence such as the reactive oxygen species (ROS) can also trigger mitochondrial dysfunction, and sufficient energy deficit to alter their secretome and cause chronic oxidative stress - a state termed Mitochondrial Dysfunction-Associated Senescence (MiDAS). Here, we offer a mechanistic hypothesis for the molecular processes leading to MiDAS, along with testable predictions. To do this we have built a Boolean regulatory network model that qualitatively captures key aspects of mitochondrial dynamics during cell cycle progression (hyper-fusion at the G1/S boundary, fission in mitosis), apoptosis (fission and dysfunction) and glucose starvation (reversible hyper-fusion), as well as MiDAS in response to SIRT3 knockdown or oxidative stress. Our model reaffirms the protective role of NAD + and external pyruvate. We offer testable predictions about the growth factor- and glucose-dependence of MiDAS and its reversibility at different stages of reactive oxygen species (ROS)-induced senescence. Our model provides mechanistic insights into the distinct stages of DNA-damage induced senescence, the relationship between senescence and epithelial-to-mesenchymal transition in cancer and offers a foundation for building multiscale models of tissue aging.

Highlights

Boolean regulatory network model reproduces mitochondrial dynamics during cell cycle progression, apoptosis, and glucose starvation. Model offers a mechanistic explanation for the positive feedback loop that locks in Mitochondrial Dysfunction-Associated Senescence (MiDAS), involving autophagy-resistant, hyperfused, dysfunctional mitochondria. Model reproduces ROS-mediated mitochondrial dysfunction and suggests that MiDAS is part of the early phase of damage-induced senescence. Model predicts that cancer-driving mutations that bypass the G1/S checkpoint generally increase the incidence of MiDAS, except for p53 loss.

Energy homeostasis in the bone

The bone serves as an energy reservoir and actively engages in whole-body energy metabolism. Numerous studies have determined fuel requirements and bioenergetic properties of bone under physiological conditions as well as the dysregulation of energy metabolism associated with bone metabolic diseases. Here, we review the main sources of energy in bone cells and their regulation, as well as the endocrine role of the bone in systemic energy homeostasis. Moreover, we discuss metabolic changes that occur as a result of osteoporosis. Exploration in this area will contribute to an enhanced comprehension of bone energy metabolism, presenting novel possibilities to address metabolic diseases.

Energy depletion by cell proliferation sensitizes the kidney epithelial cells to injury

Acute kidney injury activates both proliferative and antiproliferative pathways, the consequences of which are not fully elucidated. If an initial proliferation of the renal epithelium is necessary for the successful repair, the persistence of proliferation markers is associated with the occurrence of chronic kidney disease. We hypothesized that proliferation in stress conditions impacts cell viability and renal outcomes. We found that proliferation is associated with cell death after various stresses in kidney cells. In vitro, the ATP/ADP ratio oscillates reproducibly throughout the cell cycle, and cell proliferation is associated with a decreased intracellular ATP/ADP ratio. In vivo, transcriptomic data from transplanted kidneys revealed that proliferation was strongly associated with a decrease in the expression of the mitochondria-encoded genes of the oxidative phosphorylation pathway, but not of the nucleus-encoded ones. These observations suggest that mitochondrial function is a limiting factor for energy production in proliferative kidney cells after injury. The association of increased proliferation and decreased mitochondrial function was indeed associated with poor renal outcomes. In summary, proliferation is an energy-demanding process impairing the cellular ability to cope with an injury, highlighting proliferative repair and metabolic recovery as indispensable and interdependent features for successful kidney repair.NEW & NOTEWORTHY ATP depletion is a hallmark of acute kidney injury. Proliferation is instrumental to kidney repair. We show that ATP levels vary during the cell cycle and that proliferation sensitizes renal epithelial cells to superimposed injuries in vitro. More proliferation and less energy production by the mitochondria are associated with adverse outcomes in injured kidney allografts. This suggests that controlling the timing of kidney repair might be beneficial to mitigate the extent of acute kidney injury.

The bidirectional relationship between metabolism and cell cycle control

The relationship between metabolism and cell cycle progression is complex and bidirectional. Cells must rewire metabolism to meet changing biosynthetic demands across cell cycle phases. In turn, metabolism can influence cell cycle progression through direct regulation of cell cycle proteins, through nutrient-sensing signaling pathways, and through its impact on cell growth, which is linked to cell division. Furthermore, metabolism is a key player in mediating quiescence-proliferation transitions in physiologically important cell types, such as stem cells. How metabolism impacts cell cycle progression, exit, and re-entry, as well as how these processes impact metabolism, is not fully understood. Recent advances uncovering mechanistic links between cell cycle regulators and metabolic processes demonstrate a complex relationship between metabolism and cell cycle control, with many questions remaining.

Branched-chain amino acid synthesis is coupled to TOR activation early in the cell cycle in yeast

How cells coordinate their metabolism with division determines the rate of cell proliferation. Dynamic patterns of metabolite synthesis during the cell cycle are unexplored. We report the first isotope tracing analysis in synchronous, growing budding yeast cells. Synthesis of leucine, a branched-chain amino acid (BCAA), increases through the G1 phase of the cell cycle, peaking later during DNA replication. Cells lacking Bat1, a mitochondrial aminotransferase that synthesizes BCAAs, grow slower, are smaller, and are delayed in the G1 phase, phenocopying cells in which the growth-promoting kinase complex TORC1 is moderately inhibited. Loss of Bat1 lowers the levels of BCAAs and reduces TORC1 activity. Exogenous provision of valine and, to a lesser extent, leucine to cells lacking Bat1 promotes cell division. Valine addition also increases TORC1 activity. In wild-type cells, TORC1 activity is dynamic in the cell cycle, starting low in early G1 but increasing later in the cell cycle. These results suggest a link between BCAA synthesis from glucose to TORC1 activation in the G1 phase of the cell cycle.

Integrating glycolysis, citric acid cycle, pentose phosphate pathway, and fatty acid beta-oxidation into a single computational model

The metabolic network of a living cell is highly intricate and involves complex interactions between various pathways. In this study, we propose a computational model that integrates glycolysis, the pentose phosphate pathway (PPP), the fatty acids beta-oxidation, and the tricarboxylic acid cycle (TCA cycle) using queueing theory. The model utilizes literature data on metabolite concentrations and enzyme kinetic constants to calculate the probabilities of individual reactions occurring on a microscopic scale, which can be viewed as the reaction rates on a macroscopic scale. However, it should be noted that the model has some limitations, including not accounting for all the reactions in which the metabolites are involved. Therefore, a genetic algorithm (GA) was used to estimate the impact of these external processes. Despite these limitations, our model achieved high accuracy and stability, providing real-time observation of changes in metabolite concentrations. This type of model can help in better understanding the mechanisms of biochemical reactions in cells, which can ultimately contribute to the prevention and treatment of aging, cancer, metabolic diseases, and neurodegenerative disorders.

MYC disrupts transcriptional and metabolic circadian oscillations in cancer and promotes enhanced biosynthesis

The molecular circadian clock, which controls rhythmic 24-hour oscillation of genes, proteins, and metabolites in healthy tissues, is disrupted across many human cancers. Deregulated expression of the MYC oncoprotein has been shown to alter expression of molecular clock genes, leading to a disruption of molecular clock oscillation across cancer types. It remains unclear what benefit cancer cells gain from suppressing clock oscillation, and how this loss of molecular clock oscillation impacts global gene expression and metabolism in cancer. We hypothesized that MYC or its paralog N-MYC (collectively termed MYC herein) suppress oscillation of gene expression and metabolism to upregulate pathways involved in biosynthesis in a static, non-oscillatory fashion. To test this, cells from distinct cancer types with inducible MYC were examined, using time-series RNA-sequencing and metabolomics, to determine the extent to which MYC activation disrupts global oscillation of genes, gene expression pathways, and metabolites. We focused our analyses on genes, pathways, and metabolites that changed in common across multiple cancer cell line models. We report here that MYC disrupted over 85% of oscillating genes, while instead promoting enhanced ribosomal and mitochondrial biogenesis and suppressed cell attachment pathways. Notably, when MYC is activated, biosynthetic programs that were formerly circadian flipped to being upregulated in an oscillation-free manner. Further, activation of MYC ablates the oscillation of nutrient transporter proteins while greatly upregulating transporter expression, cell surface localization, and intracellular amino acid pools. Finally, we report that MYC disrupts metabolite oscillations and the temporal segregation of amino acid metabolism from nucleotide metabolism. Our results demonstrate that MYC disruption of the molecular circadian clock releases metabolic and biosynthetic processes from circadian control, which may provide a distinct advantage to cancer cells.

The metabolic control of DNA replication: mechanism and function

Metabolism and DNA replication are the two most fundamental biological functions in life. The catabolic branch of metabolism breaks down nutrients to produce energy and precursors used by the anabolic branch of metabolism to synthesize macromolecules. DNA replication consumes energy and precursors for faithfully copying genomes, propagating the genetic material from generation to generation. We have exquisite understanding of the mechanisms that underpin and regulate these two biological functions. However, the molecular mechanism coordinating replication to metabolism and its biological function remains mostly unknown. Understanding how and why living organisms respond to fluctuating nutritional stimuli through cell-cycle dynamic changes and reproducibly and distinctly temporalize DNA synthesis in a wide-range of growth conditions is important, with wider implications across all domains of life. After summarizing the seminal studies that founded the concept of the metabolic control of replication, we review data linking metabolism to replication from bacteria to humans. Molecular insights underpinning these links are then presented to propose that the metabolic control of replication uses signalling systems gearing metabolome homeostasis to orchestrate replication temporalization. The remarkable replication phenotypes found in mutants of this control highlight its importance in replication regulation and potentially genetic stability and tumorigenesis.

MYC disrupts transcriptional and metabolic circadian oscillations in cancer and promotes enhanced biosynthesis

The molecular circadian clock, which controls rhythmic 24-hour oscillation of genes, proteins, and metabolites in healthy tissues, is disrupted across many human cancers. Deregulated expression of the MYC oncoprotein has been shown to alter expression of molecular clock genes, leading to a disruption of molecular clock oscillation across cancer types. It remains unclear what benefit cancer cells gain from suppressing clock oscillation, and how this loss of molecular clock oscillation impacts global gene expression and metabolism in cancer. We hypothesized that MYC or its paralog N-MYC (collectively termed MYC herein) suppress oscillation of gene expression and metabolism to upregulate pathways involved in biosynthesis in a static, non-oscillatory fashion. To test this, cells from distinct cancer types with inducible MYC were examined, using time-series RNA-sequencing and metabolomics, to determine the extent to which MYC activation disrupts global oscillation of genes, gene expression pathways, and metabolites. We focused our analyses on genes, pathways, and metabolites that changed in common across multiple cancer cell line models. We report here that MYC disrupted over 85% of oscillating genes, while instead promoting enhanced ribosomal and mitochondrial biogenesis and suppressed cell attachment pathways. Notably, when MYC is activated, biosynthetic programs that were formerly circadian flipped to being upregulated in an oscillation-free manner. Further, activation of MYC ablates the oscillation of nutrient transporter proteins while greatly upregulating transporter expression, cell surface localization, and intracellular amino acid pools. Finally, we report that MYC disrupts metabolite oscillations and the temporal segregation of amino acid metabolism from nucleotide metabolism. Our results demonstrate that MYC disruption of the molecular circadian clock releases metabolic and biosynthetic processes from circadian control, which may provide a distinct advantage to cancer cells.

Non-canonical and developmental roles of the TCA cycle in plants

Over recent years, our understanding of the tricarboxylic acid cycle (TCAC) in living organisms has expanded beyond its canonical role in cellular energy production. In plants, TCAC metabolites and related enzymes have important roles in physiology, including vacuolar function, chelation of metals and nutrients, photorespiration, and redox regulation. Research in other organisms, including animals, has demonstrated unexpected functions of the TCAC metabolites in a number of biological processes, including signaling, epigenetic regulation, and cell differentiation. Here, we review the recent progress in discovery of non-canonical roles of the TCAC. We then discuss research on these metabolites in the context of plant development, with a focus on research related to tissue-specific functions of the TCAC. Additionally, we review research describing connections between TCAC metabolites and phytohormone signaling pathways. Overall, we discuss the opportunities and challenges in discovering new functions of TCAC metabolites in plants.

Applications of Boolean modeling to study the dynamics of a complex disease and therapeutics responses

Computational modeling has emerged as a critical tool in investigating the complex molecular processes involved in biological systems and diseases. In this study, we apply Boolean modeling to uncover the molecular mechanisms underlying Parkinson's disease (PD), one of the most prevalent neurodegenerative disorders. Our approach is based on the PD-map, a comprehensive molecular interaction diagram that captures the key mechanisms involved in the initiation and progression of PD. Using Boolean modeling, we aim to gain a deeper understanding of the disease dynamics, identify potential drug targets, and simulate the response to treatments. Our analysis demonstrates the effectiveness of this approach in uncovering the intricacies of PD. Our results confirm existing knowledge about the disease and provide valuable insights into the underlying mechanisms, ultimately suggesting potential targets for therapeutic intervention. Moreover, our approach allows us to parametrize the models based on omics data for further disease stratification. Our study highlights the value of computational modeling in advancing our understanding of complex biological systems and diseases, emphasizing the importance of continued research in this field. Furthermore, our findings have potential implications for the development of novel therapies for PD, which is a pressing public health concern. Overall, this study represents a significant step forward in the application of computational modeling to the investigation of neurodegenerative diseases, and underscores the power of interdisciplinary approaches in tackling challenging biomedical problems.

RBM4 dictates ESCC cell fate switch from cellular senescence to glutamine-addiction survival through inhibiting LKB1-AMPK-axis

Cellular senescence provides a protective barrier against tumorigenesis in precancerous or normal tissues upon distinct stressors. However, the detailed mechanisms by which tumor cells evade premature senescence to malignant progression remain largely elusive. Here we reported that RBM4 adversely impacted cellular senescence to favor glutamine-dependent survival of esophageal squamous cell carcinoma (ESCC) cells by dictating the activity of LKB1, a critical governor of cancer metabolism. The level of RBM4 was specifically elevated in ESCC compared to normal tissues, and RBM4 overexpression promoted the malignant phenotype. RBM4 contributed to overcome H-RAS- or doxorubicin-induced senescence, while its depletion caused P27-dependent senescence and proliferation arrest by activating LKB1-AMPK-mTOR cascade. Mechanistically, RBM4 competitively bound LKB1 to disrupt the LKB1/STRAD/MO25 heterotrimeric complex, subsequently recruiting the E3 ligase TRIM26 to LKB1, promoting LKB1 ubiquitination and degradation in nucleus. Therefore, such molecular process leads to bypassing senescence and sustaining cell proliferation through the activation of glutamine metabolism. Clinically, the ESCC patients with high RBM4 and low LKB1 have significantly worse overall survival than those with low RBM4 and high LKB1. The RBM4 high/LKB1 low expression confers increased sensitivity of ESCC cells to glutaminase inhibitor CB-839, providing a novel insight into mechanisms underlying the glutamine-dependency to improve the efficacy of glutamine inhibitors in ESCC therapeutics.

Interference with the HNF4-dependent gene regulatory network diminishes ER stress in hepatocytes

In all eukaryotic cell types, the unfolded protein response (UPR) upregulates factors that promote protein folding and misfolded protein clearance to help alleviate endoplasmic reticulum (ER) stress. Yet ER stress in the liver is uniquely accompanied by the suppression of metabolic genes, the coordination and purpose of which is largely unknown. Here, we used unsupervised machine learning to identify a cluster of correlated genes that were profoundly suppressed by persistent ER stress in the liver. These genes, which encode diverse functions including metabolism, coagulation, drug detoxification, and bile synthesis, are likely targets of the master regulator of hepatocyte differentiation HNF4α. The response of these genes to ER stress was phenocopied by liver-specific deletion of HNF4 α. Strikingly, while deletion of HNF4α exacerbated liver injury in response to an ER stress challenge, it also diminished UPR activation and partially preserved ER ultrastructure, suggesting attenuated ER stress. Conversely, pharmacological maintenance of hepatocyte identity in vitro enhanced sensitivity to stress. Several pathways potentially link HNF4α to ER stress sensitivity, including control of expression of the tunicamycin transporter MFSD2A; modulation of IRE1/XBP1 signaling; and regulation of Pyruvate Dehydrogenase. Together, these findings suggest that HNF4α activity is linked to hepatic ER homeostasis through multiple mechanisms.

Coupling-dependent metabolic ultradian rhythms in confluent cells

Ultradian rhythms in metabolism and physiology have been described previously in mammals. However, the underlying mechanisms for these rhythms are still elusive. Here, we report the discovery of temperature-sensitive ultradian rhythms in mammalian fibroblasts that are independent of both the cell cycle and the circadian clock. The period in each culture is stable over time but varies in different cultures (ranging from 3 to 24 h). We show that transient, single-cell metabolic pulses are synchronized into stable ultradian rhythms across contacting cells in culture by gap junction-mediated coupling. Coordinated rhythms are also apparent for other metabolic and physiological measures, including plasma membrane potential (Δψ_p), intracellular glutamine, α-ketoglutarate, intracellular adenosine triphosphate (ATP), cytosolic pH, and intracellular calcium. Moreover, these ultradian rhythms require extracellular glutamine, several different ion channels, and the suppression of mitochondrial ATP synthase by α-ketoglutarate, which provides a key feedback mechanism. We hypothesize that cellular coupling and metabolic feedback can be used by cells to balance energy demands for survival.

Sorting-free metabolic profiling uncovers the vulnerability of fatty acid β-oxidation in in vitro quiescence models

Quiescent cancer cells are rare nondiving cells with the unique ability to evade chemotherapies and resume cell division after treatment. Despite the associated risk of cancer recurrence, how cells can reversibly switch between rapid proliferation and quiescence remains a long-standing open question. By developing a unique methodology for the cell sorting-free separation of metabolic profiles in cell subpopulations in vitro, we unraveled metabolic characteristics of quiescent cells that are largely invariant to basal differences in cell types and quiescence-inducing stimuli. Consistent with our metabolome-based analysis, we show that impairing mitochondrial fatty acid β-oxidation (FAO) can induce apoptosis in quiescence-induced cells and hamper their return to proliferation. Our findings suggest that in addition to mediating energy and redox balance, FAO can play a role in preventing the buildup of toxic intermediates during transitioning to quiescence. Uncovering metabolic strategies to enter, maintain, and exit quiescence can reveal fundamental principles in cell plasticity and new potential therapeutic targets beyond cancer.

Connecting single-cell ATP dynamics to overflow metabolism, cell growth, and the cell cycle in Escherichia coli

Adenosine triphosphate (ATP) is an abundant and essential metabolite that cells consume and regenerate in large amounts to support growth. Although numerous studies have inferred the intracellular concentration of ATP in bacterial cultures, what happens in individual bacterial cells under stable growth conditions is less clear. Here, we use the QUEEN-2m biosensor to quantify ATP dynamics in single Escherichia coli cells in relation to their growth rate, metabolism, cell cycle, and cell lineage. We find that ATP dynamics are more complex than expected from population studies and are associated with growth-rate variability. Under stable nutrient-rich condition, cells can display large fluctuations in ATP level that are partially coordinated with the cell cycle. Abrogation of aerobic acetate fermentation (overflow metabolism) through genetic deletion considerably reduces both the amplitude of ATP level fluctuations and the cell-cycle trend. Similarly, growth in media in which acetate fermentation is lower or absent results in the reduction of ATP level fluctuation and cell-cycle trend. This suggests that overflow metabolism exhibits temporal dynamics, which contributes to fluctuating ATP levels during growth. Remarkably, at the single-cell level, growth rate negatively correlates with the amplitude of ATP fluctuation for each tested condition, linking ATP dynamics to growth-rate heterogeneity in clonal populations. Our work highlights the importance of single-cell analysis in studying metabolism and its implication to phenotypic diversity and cell growth.

Metabolic modeling-based drug repurposing in Glioblastoma

The manifestation of intra- and inter-tumor heterogeneity hinders the development of ubiquitous cancer treatments, thus requiring a tailored therapy for each cancer type. Specifically, the reprogramming of cellular metabolism has been identified as a source of potential drug targets. Drug discovery is a long and resource-demanding process aiming at identifying and testing compounds early in the drug development pipeline. While drug repurposing efforts (i.e., inspecting readily available approved drugs) can be supported by a mechanistic rationale, strategies to further reduce and prioritize the list of potential candidates are still needed to facilitate feasible studies. Although a variety of ‘omics’ data are widely gathered, a standard integration method with modeling approaches is lacking. For instance, flux balance analysis is a metabolic modeling technique that mainly relies on the stoichiometry of the metabolic network. However, exploring the network’s topology typically neglects biologically relevant information. Here we introduce Transcriptomics-Informed Stoichiometric Modelling And Network analysis (TISMAN) in a recombinant innovation manner, allowing identification and validation of genes as targets for drug repurposing using glioblastoma as an exemplar.

CLUH controls astrin-1 expression to couple mitochondrial metabolism to cell cycle progression

Proliferating cells undergo metabolic changes in synchrony with cell cycle progression and cell division. Mitochondria provide fuel, metabolites, and ATP during different phases of the cell cycle, however it is not completely understood how mitochondrial function and the cell cycle are coordinated. CLUH (clustered mitochondria homolog) is a post-transcriptional regulator of mRNAs encoding mitochondrial proteins involved in oxidative phosphorylation and several metabolic pathways. Here, we show a role of CLUH in regulating the expression of astrin, which is involved in metaphase to anaphase progression, centrosome integrity, and mTORC1 inhibition. We find that CLUH binds both the SPAG5 mRNA and its product astrin, and controls the synthesis and the stability of the full-length astrin-1 isoform. We show that CLUH interacts with astrin-1 specifically during interphase. Astrin-depleted cells show mTORC1 hyperactivation and enhanced anabolism. On the other hand, cells lacking CLUH show decreased astrin levels and increased mTORC1 signaling, but cannot sustain anaplerotic and anabolic pathways. In absence of CLUH, cells fail to grow during G1, and progress faster through the cell cycle, indicating dysregulated matching of growth, metabolism, and cell cycling. Our data reveal a role of CLUH in coupling growth signaling pathways and mitochondrial metabolism with cell cycle progression.

A conformational switch in the SCF-D3/MAX2 ubiquitin ligase facilitates strigolactone signalling

Strigolactones (SLs) are a class of plant hormones that regulate numerous processes of growth and development. SL perception and signal activation involves interaction between F-box E3 ubiquitin ligase D3/MAX2 and DWARF14 (D14) α/β-hydrolase in a SL-dependent manner and targeting of D53/SMXL6/7/8 transcriptional repressors (SMXLs) for proteasome-mediated degradation. D3/MAX2 has been shown to exist in multiple conformational states in which the C-terminal helix (CTH) undergoes a closed-to-open dynamics and regulates D14 binding and SL perception. Despite the multiple modes of D3-D14 interactions found in vitro, the residues that regulate the conformational switch of D3/MAX2 CTH in targeting D53/SMXLs and the subsequent effect on SL signalling remain unclear. Here we elucidate the functional dynamics of ASK1-D3/MAX2 in SL signalling by leveraging conformational switch mutants in vitro and in plants. We report the crystal structure of a dislodged CTH of the ASK1-D3 mutant and demonstrate that disruptions in CTH plasticity via either CRISPR-Cas9 genome editing or expression of point mutation mutants result in impairment of SL signalling. We show that the conformational switch in ASK1-D3/MAX2 CTH directly regulates ubiquitin-mediated protein degradation. A dislodged conformation involved in D53/SMXLs SL-dependent recruitment and ubiquitination and an engaged conformation are required for the release of polyubiquitinated D53/SMXLs and subsequently D14 for proteasomal degradation. Finally, we uncovered an organic acid metabolite that can directly trigger the D3/MAX2 CTH conformational switch. Our findings unravel a new regulatory function of a SKP1-CUL1-F-box ubiquitin ligase in plant signalling.

Hyperglycemia alters N-glycans on colon cancer cells through increased production of activated monosaccharides

Diabetes Mellitus (DM) is both, correlated and a known risk factor for colorectal cancer (CRC). Besides favoring the incidence of CRC, DM also accelerates its progression, worsening its prognosis. Previously, hyperglycemia, the DM hallmark, has been shown to lead to aberrant glycosylation of CRC cells, heightening their malignancy both in vivo and in vitro. Here we use mass spectrometry to elucidate the composition and putative structures of N-glycans expressed by MC38 cultured in normoglycemic (LG) and hyperglycemic-like conditions (HG). N-glycans, 67, were identified in MC38 cells cultured in LG and HG. The cells grown in HG showed a greater abundance of N-glycans when compared to LNG cells, without changes in the proportion of sialylated, fucosylated and mannosylated N-glycans. Among the identified N-glycans, 16 were differentially expressed, mostly mannosylated and fucosylated, with a minority of them being sialylated. Metabolomics analysis indicates that the alterations observed in the N-glycosylation may be mostly due to increase of the activated monosaccharides pool, through an increased glucose entrance into the cells. The alterations found here corroborate data from the literature regarding the progression of CRC, advocating for development or repositioning of effective treatments against CRC in diabetic patients.

Queueing theory model of pentose phosphate pathway

Due to its role in maintaining the proper functioning of the cell, the pentose phosphate pathway (PPP) is one of the most important metabolic pathways. It is responsible for regulating the concentration of simple sugars and provides precursors for the synthesis of amino acids and nucleotides. In addition, it plays a critical role in maintaining an adequate level of NADPH, which is necessary for the cell to fight oxidative stress. These reasons prompted the authors to develop a computational model, based on queueing theory, capable of simulating changes in PPP metabolites’ concentrations. The model has been validated with empirical data from tumor cells. The obtained results prove the stability and accuracy of the model. By applying queueing theory, this model can be further expanded to include successive metabolic pathways. The use of the model may accelerate research on new drugs, reduce drug costs, and reduce the reliance on laboratory animals necessary for this type of research on which new methods are tested.

Queueing theory model of Krebs cycle

MOTIVATION

Queueing theory can be effective in simulating biochemical reactions taking place in living cells, and the article paves a step toward development of a comprehensive model of cell metabolism. Such a model could help to accelerate and reduce costs for developing and testing investigational drugs reducing number of laboratory animals needed to evaluate drugs.

RESULTS

The article presents a Krebs cycle model based on queueing theory. The model allows for tracking of metabolites concentration changes in real time. To validate the model, a drug-induced inhibition affecting activity of enzymes involved in Krebs cycle was simulated and compared with available experimental data.

AVAILABILITYAND IMPLEMENTATION

The source code is freely available for download at https://github.com/UTP-WTIiE/KrebsCycleUsingQueueingTheory, implemented in C# supported in Linux or MS Windows.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Transient phases of OXPHOS inhibitor resistance reveal underlying metabolic heterogeneity in single cells

Cell-to-cell heterogeneity in metabolism plays an unknown role in physiology and pharmacology. To functionally characterize cellular variability in metabolism, we treated cells with inhibitors of oxidative phosphorylation (OXPHOS) and monitored their responses with live-cell reporters for ATP, ADP/ATP, or activity of the energy-sensing kinase AMPK. Across multiple OXPHOS inhibitors and cell types, we identified a subpopulation of cells resistant to activation of AMPK and reduction of ADP/ATP ratio. This resistant state persists transiently for at least several hours and can be inherited during cell divisions. OXPHOS inhibition suppresses the mTORC1 and ERK growth signaling pathways in sensitive cells, but not in resistant cells. Resistance is linked to a multi-factorial combination of increased glucose uptake, reduced protein biosynthesis, and G0/G1 cell-cycle status. Our results reveal dynamic fluctuations in cellular energetic balance and provide a basis for measuring and predicting the distribution of cellular responses to OXPHOS inhibition.

Origin of exponential growth in nonlinear reaction networks

Exponentially growing systems are prevalent in nature, spanning all scales from biochemical reaction networks in single cells to food webs of ecosystems. How exponential growth emerges in nonlinear systems is mathematically unclear. Here, we describe a general theoretical framework that reveals underlying principles of long-term growth: scalability of flux functions and ergodicity of the rescaled systems. Our theory shows that nonlinear fluxes can generate not only balanced growth but also oscillatory or chaotic growth modalities, explaining nonequilibrium dynamics observed in cell cycles and ecosystems. Our mathematical framework is broadly useful in predicting long-term growth rates from natural and synthetic networks, analyzing the effects of system noise and perturbations, validating empirical and phenomenological laws on growth rate, and studying autocatalysis and network evolution.

Computationally enhanced quantitative phase microscopy reveals autonomous oscillations in mammalian cell growth

The fine balance of growth and division is a fundamental property of the physiology of cells, and one of the least understood. Its study has been thwarted by difficulties in the accurate measurement of cell size and the even greater challenges of measuring growth of a single cell over time. We address these limitations by demonstrating a computationally enhanced methodology for quantitative phase microscopy for adherent cells, using improved image processing algorithms and automated cell-tracking software. Accuracy has been improved more than twofold and this improvement is sufficient to establish the dynamics of cell growth and adherence to simple growth laws. It is also sufficient to reveal unknown features of cell growth, previously unmeasurable. With these methodological and analytical improvements, in several cell lines we document a remarkable oscillation in growth rate, occurring throughout the cell cycle, coupled to cell division or birth yet independent of cell cycle progression. We expect that further exploration with this advanced tool will provide a better understanding of growth rate regulation in mammalian cells.

Mapping metabolic oscillations during cell cycle progression

Proliferating cells must synthesize a wide variety of macromolecules while progressing through the cell cycle, but the coordination between cell cycle progression and cellular metabolism is still poorly understood. To identify metabolic processes that oscillate over the cell cycle, we performed comprehensive, non-targeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) based metabolomics of HeLa cells isolated in the G₁ and SG₂M cell cycle phases, capturing thousands of diverse metabolite ions. When accounting for increased total metabolite abundance due to cell growth throughout the cell cycle, 18% of the observed LC-HRMS peaks were at least twofold different between the stages, consistent with broad metabolic remodeling throughout the cell cycle. While most amino acids, phospholipids, and total ribonucleotides were constant across cell cycle phases, consistent with the view that total macromolecule synthesis does not vary across the cell cycle, certain metabolites were oscillating. For example, ribonucleotides were highly phosphorylated in SG₂M, indicating an increase in energy charge, and several phosphatidylinositols were more abundant in G₁, possibly indicating altered membrane lipid signaling. Within carbohydrate metabolism, pentose phosphates and methylglyoxal metabolites were associated with the cycle. Interestingly, hundreds of yet uncharacterized metabolites similarly oscillated between cell cycle phases, suggesting previously unknown metabolic activities that may be synchronized with cell cycle progression, providing an important resource for future studies.

Metabolic Reprogramming is a Hallmark of Metabolism Itself

The reprogramming of metabolism has been identified as one of the hallmarks of cancer. It is becoming more and more frequent to connect other diseases with metabolic reprogramming. This article aims to argue that metabolic reprogramming is not driven by disease but instead is the main hallmark of metabolism, based on its dynamic behavior that allows it to continuously adapt to changes in the internal and external conditions.

Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing sample-specific ion distributions

Mass spectrometry based metabolomics is a widely used approach in biomedical research. However, current methods coupling mass spectrometry with chromatography are time-consuming and not suitable for high-throughput analysis of thousands of samples. An alternative approach is flow-injection mass spectrometry (FI-MS) in which samples are directly injected to the ionization source. Here, we show that the sensitivity of Orbitrap FI-MS metabolomics methods is limited by ion competition effect. We describe an approach for overcoming this effect by analyzing the distribution of ion m/z values and computationally determining a series of optimal scan ranges. This enables reproducible detection of ~9,000 and ~10,000 m/z features in metabolomics and lipidomics analysis of serum samples, respectively, with a sample scan time of ~15 s and duty time of ~30 s; a ~50% increase versus current spectral-stitching FI-MS. This approach facilitates high-throughput metabolomics for a variety of applications, including biomarker discovery and functional genomics screens.

Metabolomics markers in Neurology: current knowledge and future perspectives for therapeutic targeting

INTRODUCTION

Metabolomics is an emerging approach providing new insights into the metabolic changes and underlying mechanisms involved in the pathogenesis of neurological disorders.

AREAS COVERED

Here, the authors present an overview of the current knowledge of metabolic profiling (metabolomics) to provide critical insight on the role of biochemical markers and metabolic alterations in neurological diseases.

EXPERT OPINION

Elucidation of characteristic metabolic alterations in neurological disorders is crucial for a better understanding of their pathogenesis, and for identifying potential biomarkers and drug targets. Nevertheless, discrepancies in diagnostic criteria, sample handling protocols, and analytical methods still affect the generalizability of current study results.

Circadian and Sleep Metabolomics Across Species

Under normal circadian function, metabolic control is temporally coordinated across tissues and behaviors with a 24-h period. However, circadian disruption results in negative consequences for metabolic homeostasis including energy or redox imbalances. Yet, circadian disruption has become increasingly prevalent within today's society due to many factors including sleep loss. Metabolic consequences of both have been revealed by metabolomics analyses of circadian biology and sleep. Specifically, two primary analytical platforms, mass spectrometry and nuclear magnetic resonance spectroscopy, have been used to study molecular clock and sleep influences on overall metabolic rhythmicity. For example, human studies have demonstrated the prevalence of metabolic rhythms in human biology, as well as pan-metabolome consequences of sleep disruption. However, human studies are limited to peripheral metabolic readouts primarily through minimally invasive procedures. For further tissue- and organism-specific investigations, a number of model systems have been studied, based upon the conserved nature of both the molecular clock and sleep across species. Here we summarize human studies as well as key findings from metabolomics studies using mice, Drosophila, and zebrafish. While informative, a limitation in existing literature is a lack of interpretation regarding dynamic synthesis or catabolism within metabolite pools. To this extent, future work incorporating isotope tracers, specific metabolite reporters, and single-cell metabolomics may provide a means of exploring dynamic activity in pathways of interest.

Evidence for rate-dependent filtering of global extrinsic noise by biochemical reactions in mammalian cells

Recent studies have revealed that global extrinsic noise arising from stochasticity in the intracellular biochemical environment plays a critical role in heterogeneous cell physiologies. However, it remains largely unclear how such extrinsic noise dynamically influences downstream reactions and whether it could be neutralized by cellular reactions. Here, using fluorescent protein (FP) maturation as a model biochemical reaction, we explored how cellular reactions might combat global extrinsic noise in mammalian cells. We developed a novel single-cell assay to systematically quantify the maturation rate and the associated noise for over a dozen FPs. By exploiting the variation in the maturation rate for different FPs, we inferred that global extrinsic noise could be temporally filtered by maturation reactions, and as a result, the noise levels for slow-maturing FPs are lower compared to fast-maturing FPs. This mechanism is validated by directly perturbing the maturation rates of specific FPs and measuring the resulting noise levels. Together, our results revealed a potentially general principle governing extrinsic noise propagation, where timescale separation allows cellular reactions to cope with dynamic global extrinsic noise.

Current Status and Future Prospects of Genome-Scale Metabolic Modeling to Optimize the Use of Mesenchymal Stem Cells in Regenerative Medicine

Mesenchymal stem cells are a promising source for externally grown tissue replacements and patient-specific immunomodulatory treatments. This promise has not yet been fulfilled in part due to production scaling issues and the need to maintain the correct phenotype after re-implantation. One aspect of extracorporeal growth that may be manipulated to optimize cell growth and differentiation is metabolism. The metabolism of MSCs changes during and in response to differentiation and immunomodulatory changes. MSC metabolism may be linked to functional differences but how this occurs and influences MSC function remains unclear. Understanding how MSC metabolism relates to cell function is however important as metabolite availability and environmental circumstances in the body may affect the success of implantation. Genome-scale constraint based metabolic modeling can be used as a tool to fill gaps in knowledge of MSC metabolism, acting as a framework to integrate and understand various data types (e.g., genomic, transcriptomic and metabolomic). These approaches have long been used to optimize the growth and productivity of bacterial production systems and are being increasingly used to provide insights into human health research. Production of tissue for implantation using MSCs requires both optimized production of cell mass and the understanding of the patient and phenotype specific metabolic situation. This review considers the current knowledge of MSC metabolism and how it may be optimized along with the current and future uses of genome scale constraint based metabolic modeling to further this aim.

An appreciation of the prescience of Don Gilbert (1930-2011): master of the theory and experimental unravelling of biochemical and cellular oscillatory dynamics

We review Don Gilbert's pioneering seminal contributions that both detailed the mathematical principles and the experimental demonstration of several of the key dynamic characteristics of life. Long before it became evident to the wider biochemical community, Gilbert proposed that cellular growth and replication necessitate autodynamic occurrence of cycles of oscillations that initiate, coordinate and terminate the processes of growth, during which all components are duplicated and become spatially re-organised in the progeny. Initiation and suppression of replication exhibit switch-like characteristics, that is, bifurcations in the values of parameters that separate static and autodynamic behaviour. His limit cycle solutions present models developed in a series of papers reported between 1974 and 1984, and these showed that most or even all of the major facets of the cell division cycle could be accommodated. That the cell division cycle may be timed by a multiple of shorter period (ultradian) rhythms, gave further credence to the central importance of oscillatory phenomena and homeodynamics as evident on multiple time scales (seconds to hours). Further application of the concepts inherent in limit cycle operation as hypothesised by Gilbert more than 50 years ago are now validated as being applicable to oscillatory transcript, metabolite and enzyme levels, cellular differentiation, senescence, cancerous states and cell death. Now, we reiterate especially for students and young colleagues, that these early achievements were even more exceptional, as his own lifetime's work on modelling was continued with experimental work in parallel with his predictions of the major current enterprises of biological research.

Abundances of transcripts, proteins, and metabolites in the cell cycle of budding yeast reveal coordinate control of lipid metabolism

Establishing the pattern of abundance of molecules of interest during cell division has been a long-standing goal of cell cycle studies. Here, for the first time in any system, we present experiment-matched datasets of the levels of RNAs, proteins, metabolites, and lipids from unarrested, growing, and synchronously dividing yeast cells. Overall, transcript and protein levels were correlated, but specific processes that appeared to change at the RNA level (e.g., ribosome biogenesis) did not do so at the protein level, and vice versa. We also found no significant changes in codon usage or the ribosome content during the cell cycle. We describe an unexpected mitotic peak in the abundance of ergosterol and thiamine biosynthesis enzymes. Although the levels of several metabolites changed in the cell cycle, by far the most significant changes were in the lipid repertoire, with phospholipids and triglycerides peaking strongly late in the cell cycle. Our findings provide an integrated view of the abundance of biomolecules in the eukaryotic cell cycle and point to a coordinate mitotic control of lipid metabolism.

Untargeted metabolomics links glutathione to bacterial cell cycle progression

Cell cycle progression requires the coordination of cell growth, chromosome replication, and division. Consequently, a functional cell cycle must be coupled with metabolism. However, direct measurements of metabolome dynamics remained scarce, in particular in bacteria. Here, we describe an untargeted metabolomics approach with synchronized Caulobacter crescentus cells to monitor the relative abundance changes of ~400 putative metabolites as a function of the cell cycle. While the majority of metabolite pools remains homeostatic, ~14% respond to cell cycle progression. In particular, sulfur metabolism is redirected during the G1-S transition, and glutathione levels periodically change over the cell cycle with a peak in late S phase. A lack of glutathione perturbs cell size by uncoupling cell growth and division through dysregulation of KefB, a K+/H+ antiporter. Overall, we here describe the impact of the C. crescentus cell cycle progression on metabolism, and in turn relate glutathione and potassium homeostasis to timely cell division.

Metabolomics for Investigating Physiological and Pathophysiological Processes

Metabolomics uses advanced analytical chemistry techniques to enable the high-throughput characterization of metabolites from cells, organs, tissues, or biofluids. The rapid growth in metabolomics is leading to a renewed interest in metabolism and the role that small molecule metabolites play in many biological processes. As a result, traditional views of metabolites as being simply the "bricks and mortar" of cells or just the fuel for cellular energetics are being upended. Indeed, metabolites appear to have much more varied and far more important roles as signaling molecules, immune modulators, endogenous toxins, and environmental sensors. This review explores how metabolomics is yielding important new insights into a number of important biological and physiological processes. In particular, a major focus is on illustrating how metabolomics and discoveries made through metabolomics are improving our understanding of both normal physiology and the pathophysiology of many diseases. These discoveries are yielding new insights into how metabolites influence organ function, immune function, nutrient sensing, and gut physiology. Collectively, this work is leading to a much more unified and system-wide perspective of biology wherein metabolites, proteins, and genes are understood to interact synergistically to modify the actions and functions of organelles, organs, and organisms.

Glutamine Metabolism Is Essential for Stemness of Bone Marrow Mesenchymal Stem Cells and Bone Homeostasis

Skeleton has emerged as an endocrine organ which is both capable of regulating energy metabolism and being a target for it. Glutamine is the most bountiful and flexible amino acid in the body which provides adenosine 5′-triphosphate (ATP) demands for cells. Emerging evidences support that glutamine which acts as the second metabolic regulator after glucose exerts crucial roles in bone homeostasis at cellular level, including the lineage allocation and proliferation of bone mesenchymal stem cells (BMSCs), the matrix mineralization of osteoblasts, and the biosynthesis in chondrocytes. The integrated mechanism consisting of WNT, mammalian target of rapamycin (mTOR), and reactive oxygen species (ROS) signaling pathway in a glutamine-dependent pattern is responsible to regulate the complex intrinsic biological process, despite more extensive molecules are deserved to be elucidated in glutamine metabolism further. Indeed, dysfunctional glutamine metabolism enhances the development of degenerative bone diseases, such as osteoporosis and osteoarthritis, and glutamine or glutamine progenitor supplementation can partially restore bone defects which may promote treatment of bone diseases, although the mechanisms are not quite clear. In this review, we will summarize and update the latest research findings and clinical trials on the crucial regulatory roles of glutamine metabolism in BMSCs and BMSC-derived bone cells, also followed with the osteoclasts which are important in bone resorption.

Metabolite Exchange between Mammalian Organs Quantified in Pigs

Mammalian organs continually exchange metabolites via circulation, but systems-level analysis of this shuttling process is lacking. Here, we compared, in fasted pigs, metabolite concentrations in arterial blood versus draining venous blood from 11 organs. Greater than 90% of metabolites showed arterial-venous differences across at least one organ. Surprisingly, the liver and kidneys released not only glucose but also amino acids, both of which were consumed primarily by the intestine and pancreas. The liver and kidneys exhibited additional unexpected activities: liver preferentially burned unsaturated over more atherogenic saturated fatty acids, whereas the kidneys were unique in burning circulating citrate and net oxidizing lactate to pyruvate, thereby contributing to circulating redox homeostasis. Furthermore, we observed more than 700 other cases of tissue-specific metabolite production or consumption, such as release of nucleotides by the spleen and TCA intermediates by pancreas. These data constitute a high-value resource, providing a quantitative atlas of inter-organ metabolite exchange.

Metabolic switches from quiescence to growth in synchronized Saccharomyces cerevisiae

INTRODUCTION

The switch from quiescence (G0) into G1 and cell cycle progression critically depends on specific nutrients and metabolic capabilities. Conversely, metabolic networks are regulated by enzyme-metabolite interaction and transcriptional regulation that lead to flux modifications to support cell growth. How cells process and integrate environmental information into coordinated responses is challenging to analyse and not yet described quantitatively.

OBJECTIVES

To quantitatively monitor the central carbon metabolism during G0 exit and the first 2 h after reentering the cell cycle from synchronized Saccharomyces cerevisiae.

METHODS

Dynamic tailored ¹³C metabolic flux analysis was used to observe the intracellular metabolite flux changes, and the metabolome and proteome were observed to identify regulatory mechanisms.

RESULTS

G0 cells responded immediately to an extracellular increase of glucose. The intracellular metabolic flux changed in time and specific events were observed. High fluxes into trehalose and glycogen synthesis were observed during the G0 exit. Both fluxes then decreased, reaching a minimum at t = 65 min. Here, storage degradation contributed significantly (i.e. 21%) to the glycolytic flux. In contrast to these changes, the glucose uptake rate remained constant after the G0 exit. The flux into the oxidative pentose phosphate pathway was highest (29-fold increase, 36.4% of the glucose uptake) at t = 65 min, while it was very low at other time points. The maximum flux seems to correlate with a late G1 state preparing for the S phase transition. In the G1/S phase (t = 87 min), anaplerotic reactions such as glyoxylate shunt increased. Protein results show that during this transition, proteins belonging to clusters related with ribosome biogenesis and assembly, and initiation transcription factors clusters were continuously synthetised.

CONCLUSION

The intracellular flux distribution changes dynamically and these major rearrangements highlight the coordinate reorganization of metabolic flux to meet requirements for growth during different cell state.

Ultrasensitive Single Cell Metabolomics by Capillary Electrophoresis-Mass Spectrometry with a Thin-Walled Tapered Emitter and Large-Volume Dual Sample Preconcentration

Single cell metabolome analysis is essential for studying microscale life phenomena such as neuronal networks and tumor microenvironments. Capillary electrophoresis-mass spectrometry (CE-MS) is one of the most sensitive technologies; however, its sensitivity is still not enough for single cell analysis on general human cells such as HeLa. To address these issues, we first developed an efficient ionization emitter, named as a "nanoCESI" emitter, that had a thin-walled (∼10 μm) and tapered (5-10 μm) end. The thin conductive wall enabled sheathless ionization and minimized the flow rate of ionizing sample, and the tapered end efficiently ionized analytes via an electrospray ionization mechanism, providing up to 3.5-fold increase in sensitivity compared with a conventional sheathless emitter. Fifty repetitive analyses on 20 amino acids were successfully achieved with a nanoCESI emitter. Relative standard deviations of 50 analyses were 1.5%, 4.4%, and 6.8% for migration time, peak height, and peak area, respectively, where a limit of detection (LOD) of 170 pM (850 zmol) was achieved. Second, a sample enrichment method, large-volume dual preconcentration by isotachophoresis and stacking (LDIS), was applied to a newly designed protocol of nanoCESI-MS. This approach achieved up to 380-fold enhanced sensitivity and LOD of 450 fM. Compared with normal sheathless CE-MS, coupling of nanoCESI and LDIS provided up to 800-fold increase of sensitivity in total. Finally, metabolome analyses of single HeLa cells were performed, where 20 amino acids were successfully quantified with triple-quadrupole MS and 40 metabolites were identified with quadrupole-time-of-flight MS, as a promising analytical platform for microscale bioanalysis for the next generation.

Regulatory mechanisms underlying coordination of amino acid and glucose catabolism in Escherichia coli

How microbes dynamically coordinate uptake and simultaneous utilization of nutrients in complex nutritional ecosystems is still an open question. Here, we develop a constraint-based modeling approach that exploits non-targeted exo-metabolomics data to unravel adaptive decision-making processes in dynamic nutritional environments. We thereby investigate metabolic adaptation of Escherichia coli to continuously changing conditions during batch growth in complex medium. Unexpectedly, model-based analysis of time resolved exo-metabolome data revealed that fastest growth coincides with preferred catabolism of amino acids, which, in turn, reduces glucose uptake and increases acetate overflow. We show that high intracellular levels of the amino acid degradation metabolites pyruvate and oxaloacetate can directly inhibit the phosphotransferase system (PTS), and reveal their functional role in mediating regulatory decisions for uptake and catabolism of alternative carbon sources. Overall, the proposed methodology expands the spectrum of possible applications of flux balance analysis to decipher metabolic adaptation mechanisms in naturally occurring habitats and diverse organisms.