Adaptive changes in the neuronal proteome: mitochondrial energy production, endoplasmic reticulum stress, and ribosomal dysfunction in the cellular response to metabolic stress

Impaired energy metabolism in neurons is integral to a range of neurodegenerative diseases, from Alzheimer’s disease to stroke. To investigate the complex molecular changes underpinning cellular adaptation to metabolic stress, we have defined the proteomic response of the SH-SY5Y human neuroblastoma cell line after exposure to a metabolic challenge of oxygen glucose deprivation (OGD) in vitro. A total of 958 proteins across multiple subcellular compartments were detected and quantified by label-free liquid chromatography mass spectrometry. The levels of 130 proteins were significantly increased (P<0.01) after OGD and the levels of 63 proteins were significantly decreased (P<0.01) while expression of the majority of proteins (765) was not altered. Network analysis identified novel protein–protein interactomes involved with mitochondrial energy production, protein folding, and protein degradation, indicative of coherent and integrated proteomic responses to the metabolic challenge. Approximately one third (61) of the differentially expressed proteins was associated with the endoplasmic reticulum and mitochondria. Electron microscopic analysis of these subcellular structures showed morphologic changes consistent with the identified proteomic alterations. Our investigation of the global cellular response to a metabolic challenge clearly shows the considerable adaptive capacity of the proteome to a slowly evolving metabolic challenge

Studies of molecular mechanisms integrating carbon metabolism and growth in plants

Plants use light energy, carbon dioxide and water to produce sugars and other carbohydrates, which serve as stored energy reserves and as building blocks for biosynthetic reactions. Supply of light is variable and plants have evolved means to adjust their growth and development accordingly. An increasing body of evidence suggests that the basic mechanisms for sensing and signaling energy availability in eukaryotes are evolutionary conserved and thus shared between plants, animals and fungi. I have used different experimental approaches that take advantage of findings from other eukaryotes in studying carbon and energy metabolism in plants. In the first part, I developed a novel screening procedure in yeast aimed at isolating cDNAs from other organisms encoding proteins with a possible function in sugar sensing or signaling. The feasibility of the method was confirmed by the cloning of a cDNA from Arabidopsis thaliana encoding a new F-box protein named AtGrh1, which is related to the yeast Grr1 protein that is involved in glucose repression. In the second part of the study, plant homologues of key components in the yeast glucose repression pathway were cloned and characterized in the moss Physcomitrella patens, in which gene function can be studied by gene targeting. We first cloned PpHXK1 which was shown to encode a chloroplast localized hexokinase representing a previously overlooked class of plant hexokinases with an N-terminal chloroplast transit peptide. Significantly, PpHxk1 is the major hexokinase in Physcomitrella, accounting for 80% of the glucose phosphorylating activity. A knockout mutant deleted for PpHXK1 exhibits a complex phenotype affecting growth, development and sensitivities to plant hormones. I also cloned and characterized two closely related Physcomitrella genes, PpSNF1a and PpSNF1b, encoding type 1 Snf1-related kinases. A double knockout mutant for these genes was viable even though it lacks detectable Snf1-like kinase activity. The mutant suffers from pleiotropic phenotypes which may reflect a constitutive high energy growth mode. Significantly, the double mutant requires constant high light and is therefore unable to grow in a normal day/night light cycle. These findings are consistent with the proposed role of the Snf1-related kinases as energy gauges which are needed to recognize and respond to low energy conditions

Metabolic regulation of regulatory T cell development and function

It is now well established that the effector T cell (Teff) response is regulated by a series of metabolic switches. Quiescent T cells predominantly require ATP-generating processes, whereas proliferating Teff require high metabolic flux through growth-promoting pathways, such as glycolysis. Pathways that control metabolism and immune cell function are intimately linked, and changes in cell metabolism at both the cell and system levels have been shown to enhance or suppress specific T cell effector functions. Furthermore, functionally distinct T cell subsets have been shown to require distinct energetic and biosynthetic pathways to support their specific functional needs. In particular, naturally occurring regulatory T cells (Treg) are characterized by a unique metabolic signature distinct to that of conventional Teff cells. We here briefly review the signaling pathways that control Treg metabolism and how this metabolic phenotype integrates their differentiation and function. Ultimately, these metabolic features may provide new opportunities for the therapeutic modulation of unwanted immune responses

In Silico Genome-Scale Reconstruction and Validation of the Staphylococcus aureus Metabolic Network

A genome-scale metabolic model of the Gram-positive, facultative anaerobic opportunistic pathogen Staphylococcus aureus N315 was constructed based on current genomic data, literature, and physiological information. The model comprises 774 metabolic processes representing approximately 23% of all protein-coding regions. The model was extensively validated against experimental observations and it correctly predicted main physiological properties of the wild-type strain, such as aerobic and anaerobic respiration and fermentation. Due to the frequent involvement of S. aureus in hospital-acquired bacterial infections combined with its increasing antibiotic resistance, we also investigated the clinically relevant phenotype of small colony variants and found that the model predictions agreed with recent findings of proteome analyses. This indicates that the model is useful in assisting future experiments to elucidate the interrelationship of bacterial metabolism and resistance. To help directing future studies for novel chemotherapeutic targets, we conducted a large-scale in silico gene deletion study that identified 158 essential intracellular reactions. A more detailed analysis showed that the biosynthesis of glycans and lipids is rather rigid with respect to circumventing gene deletions, which should make these areas particularly interesting for antibiotic development. The combination of this stoichiometric model with transcriptomic and proteomic data should allow a new quality in the analysis of clinically relevant organisms and a more rationalized system-level search for novel drug targets.

Deep Proteomics of Mouse Skeletal Muscle Enables Quantitation of Protein Isoforms, Metabolic Pathways, and Transcription Factors

Skeletal muscle constitutes 40% of individual body mass and plays vital roles in locomotion and whole-body metabolism. Proteomics of skeletal muscle is challenging because of highly abundant contractile proteins that interfere with detection of regulatory proteins. Using a state-of-the art MS workflow and a strategy to map identifications from the C2C12 cell line model to tissues, we identified a total of 10,218 proteins, including skeletal muscle specific transcription factors like myod1 and myogenin and circadian clock proteins. We obtain absolute abundances for proteins expressed in a muscle cell line and skeletal muscle, which should serve as a valuable resource. Quantitation of protein isoforms of glucose uptake signaling pathways and in glucose and lipid metabolic pathways provides a detailed metabolic map of the cell line compared with tissue. This revealed unexpectedly complex regulation of AMP-activated protein kinase and insulin signaling in muscle tissue at the level of enzyme isoforms

Modeling cancer metabolism on a genome scale

Cancer cells have fundamentally altered cellular metabolism that is associated with their tumorigenicity and malignancy. In addition to the widely studied Warburg effect, several new key metabolic alterations in cancer have been established over the last decade, leading to the recognition that altered tumor metabolism is one of the hallmarks of cancer. Deciphering the full scope and functional implications of the dysregulated metabolism in cancer requires both the advancement of a variety of omics measurements and the advancement of computational approaches for the analysis and contextualization of the accumulated data. Encouragingly, while the metabolic network is highly interconnected and complex, it is at the same time probably the best characterized cellular network. Following, this review discusses the challenges that genome‐scale modeling of cancer metabolism has been facing. We survey several recent studies demonstrating the first strides that have been done, testifying to the value of this approach in portraying a network‐level view of the cancer metabolism and in identifying novel drug targets and biomarkers. Finally, we outline a few new steps that may further advance this field

The thermodynamics of metabolism, cardiovascular performance and exercise, in health and diabetes: The objective of clinical markers

Extensive experience in UK National Health Service metabolic syndrome/type 2 diabetes clinics highlights the need for convenient clinical marker(s) which can be readily used to indicate the success or otherwise of alternative therapies. In this paper we study the metabolic context of the healthy and diseased states, which points to the haemodynamics being a possible key in identifying candidate markers. Human metabolism relates to two elemental thermodynamic systems, the individual cell and the human body in its entirety. The fundamental laws of thermodynamics apply to humans, animals, and their individual cells for both healthy and diseased conditions. as they are to classic heat engines. In compliance with the second law enhanced levels of heat are generated under exercise, heat itself being another factor modulating the cardiovascular response to physical exercise. Nutrients and oxygen uptake occurs via the digestive system and lungs, respectively, leading to ATP production by the established metabolic pathways: this is controlled by insulin. These are then delivered to the cells via the haemodynamic system to satisfy local metabolic need. The supply and demand of oxygen are finely regulated, in part, via oxygen-dependent release of ATP from the circulating erythrocytes. Energy supply and demand are regulated to sustain muscle activity resulting in the body’s output of measurable thermodynamic work—i.e. exercise. Recently a dynamic pathway model allowing quantification of ATP release from the erythrocytes and its contribution to oxygen supply regulation has been published. However, metabolic uptake is well known to be greatly affected by disease such as the highly prevalent diabetes type 2 with insulin resistance and beta cell dysfunction having mechanistic roles. In 2010, over 25% of residents above 65 in the USA had diabetes 2. The complexity of the metabolic pathways means that monitoring of patient-specific treatment would be beneficial from a diabetic marker which may be haemodynamic-related and traceable via the local fluid dynamics