Yu ChenShenzhen Institute of Advanced Technology, Chinese Academy of Sciences
Yu Chen
PhD
About
37
Publications
9,014
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877
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Introduction
My research interest is in systems biology of metabolism. Currently, I am working on proteome-constrained models.
Skills and Expertise
Additional affiliations
September 2015 - August 2017
September 2012 - June 2018
Education
September 2012 - June 2018
September 2008 - June 2012
Publications
Publications (37)
Significance
Organisms use the central carbon metabolism for both breakdown of substrate into biomass precursors and extraction of energy, making the pathways overlapping. We present a modeling concept that can decompose the overlapping pathways and hence account for protein cost for each of them. This enables comparisons between pathways within an...
Significance
Metal ions are essential to all living cells, as they can serve as cofactors of enzymes to drive catalysis of biochemical reactions. We present a constraint-based model of yeast that relates metabolism with metal ions via enzymes. The model is able to capture responses of metabolism and gene expression upon iron depletion, suggesting t...
Cells adapt to different conditions via gene expression that tunes metabolism for maximal fitness. Constraints on cellular proteome may limit such expression strategies and introduce trade-offs. Resource allocation under proteome constraints has explained regulatory strategies in bacteria. It is unclear, however, to what extent these constraints ca...
Turnover numbers (k cat values) quantitatively represent the activity of enzymes, which are mostly measured in vitro. While a few studies have reported in vivo catalytic rates (k app values) in bacteria, a large-scale estimation of k app in eukaryotes is lacking. Here, we estimated k app of the yeast Saccharomyces cerevisiae under diverse condition...
Proteins, as essential biomolecules, account for a large fraction of cell mass, and thus the synthesis of the complete set of proteins (i.e., the proteome) represents a substantial part of the cellular resource budget. Therefore, cells might be under selective pressures to optimize the resource costs for protein synthesis, particularly the biosynth...
Over the last 15 years, genome‐scale metabolic models (GEMs) have been reconstructed for human and model animals, such as mouse and rat, to systematically understand metabolism, simulate multicellular or multi‐tissue interplay, understand human diseases, and guide cell factory design for biopharmaceutical protein production. Here, we describe how m...
Background: Glycolysis is one of the oldest and most fundamental metabolic pathways responsible for glucose breakdown and energy production in cells. The key regulatory enzyme in glycolysis is phosphofructokinase (Pfks), which catalyzes the phosphorylation of fructose 6-phosphate (F6P) to fructose 1,6-bisphosphate. The regulation of Pfks plays a cr...
CO 2 fixation plays a key role to make biobased production cost competitive. Here, we used 3-hydroxypropionic acid (3-HP) to showcase how CO 2 fixation enabled approaching theoretical-yield production. Using genome-scale metabolic models to calculate the production envelope, we demonstrated that the provision of bicarbonate, formed from CO 2 , seal...
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Background
With unique physiochemical environments in subcellular organelles, there has been growing interest in harnessing yeast organelles for bioproduct synthesis. Among these organelles, the yeast mitochondrion has been found to be an attractive compartment for production of terpenoids and branched-chain alcohols, which could be credited to the...
Although many prokaryotes have glycolysis alternatives, it's considered as the only energy-generating glucose catabolic pathway in eukaryotes. Here, we managed to create a hybrid-glycolysis yeast. Subsequently, we identified an inositol pyrophosphatase encoded by OCA5 that could regulate glycolysis and respiration by adjusting 5-diphosphoinositol 1...
The diterpenoid sclareol is an industrially important precursor for alternative sustainable supply of ambergris. However, its current production from plant extraction is neither economical nor environmental-friendly, since it requires laborious and cost-intensive purification procedures and plants cultivation is susceptible to environmental factors...
Enzyme parameters are essential for quantitatively understanding, modelling, and engineering cells. However, experimental measurements cover only a small fraction of known enzyme-compound pairs in model organisms, much less in other organisms. Artificial intelligence (AI) techniques have accelerated the pace of exploring enzyme properties by predic...
Enzyme turnover numbers (kcat) are key to understanding cellular metabolism, proteome allocation and physiological diversity, but experimentally measured kcat data are sparse and noisy. Here we provide a deep learning approach (DLKcat) for high-throughput kcat prediction for metabolic enzymes from any organism merely from substrate structures and p...
Eukaryotic cells are used as cell factories to produce and secrete multitudes of recombinant pharmaceutical proteins, including several of the current top-selling drugs. Due to the essential role and complexity of the secretory pathway, improvement for recombinant protein production through metabolic engineering has traditionally been relatively ad...
Saccharomyces cerevisiae is a widely used cell factory; therefore, it is important to understand how it organizes key functional parts when cultured under different conditions. Here, we perform a multiomics analysis of S. cerevisiae by culturing the strain with a wide range of specific growth rates using glucose as the sole limiting nutrient. Under...
Advances in synthetic biology enable microbial hosts to synthesize valuable natural products in an efficient, cost-competitive and safe manner. However, current engineering endeavors focus mainly on enzyme engineering and pathway optimization, leaving the role of cofactors in microbial production of natural products and cofactor engineering largely...
Yeasts have been widely used for production of bread, beer and wine as well as for production of bioethanol, but they have also been designed as cell factories to produce various chemicals, advanced biofuels and recombinant proteins. To systematically understand and rationally engineer yeast metabolism, genome-scale metabolic models (GEMs) have bee...
Eukaryal cells are used for the production of many recombinant pharmaceutical proteins, including several of the current top-selling products. The protein secretory pathway in eukaryal cells is complex and involves many different processes such as post-translational modifications, translocation, and folding. Furthermore, recombinant protein product...
Abstract Yeasts are known to have versatile metabolic traits, while how these metabolic traits have evolved has not been elucidated systematically. We performed integrative evolution analysis to investigate how genomic evolution determines trait generation by reconstructing genome‐scale metabolic models (GEMs) for 332 yeasts. These GEMs could compr...
Enzyme turnover numbers ( k cat values) are key parameters to understand cell metabolism, proteome allocation and physiological diversity, but experimentally measured k cat data are sparse and noisy. Here we provide a deep learning approach to predict k cat values for metabolic enzymes in a high-throughput manner with the input of substrate structu...
This chapter introduces the kinetic models of metabolism followed by examples on the construction of kinetic models as well as applications. With the Michaelis–Menten formulation, the influence of enzyme properties, enzyme abundance, and metabolite concentration on the dynamic behavior of a reaction can be explained mechanistically. Kinetic models...
Genome‐scale metabolic models (GEMs) describe the stoichiometry of all reactions in the cellular metabolic network, and at the same time associate the reactions to the enzymes that catalyze them. This chapter discusses proteome constraints followed by examples on how one particular type of cellular constraint, namely a proteome constraint, is a pow...
Structurally complex and diverse polyamines and polyamine analogues are potential therapeutics and agrochemicals that can address grand societal challenges, for example, healthy ageing and sustainable food production. However, their structural complexity and low abundance in nature hampers either bulk chemical synthesis or extraction from natural r...
Saccharomyces cerevisiae is widely used as a cell factory and it is therefore important to understand how it organizes key functional parts when cultured under different conditions. Here we performed a multi-omics analysis of S. cerevisiae by culturing the strain under a wide range of specific growth rates using glucose as the sole limited nutrient...
Genome-scale metabolic models (GEMs) are widely used to predict phenotypes with the aid of constraint-based modelling. In order to improve the predictive power of these models there have been many efforts on imposing biological constraints, among which proteome constraints are of particular interest. Here we describe the concept of proteome constra...
Cells adapt to different conditions via gene expression that tunes metabolism and stress resistance for maximal fitness. Constraints on cellular proteome may limit such expression strategies and introduce trade-offs; Resource allocation under proteome constraints has emerged as a powerful paradigm to explain regulatory strategies in bacteria. It is...
Through advanced mechanistic modeling and the generation of large high-quality datasets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can be combined to enable accurate genotype-to-phenotype predictions. We use a genome-scale model to pinpoin...
Lactic acid is widely used in many industries especially the production of poly‐lactic acid. Bacillus coagulans is a promising lactic acid producer in industrial fermentation due to its thermophilic property. In this study, we developed the first genome‐scale metabolic model (GEM) of B. coagulans iBag597, together with an enzyme‐constrained model e...
In combination with advanced mechanistic modeling and the generation of high-quality multi-dimensional data sets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can complement each other and be used in a combined approach to enable accurate gen...
The production of bioactive plant compounds using microbial hosts is considered a safe, cost-competitive and scalable approach to their production. However, microbial production of some compounds like aromatic amino acid (AAA)-derived chemicals, remains an outstanding metabolic engineering challenge. Here we present the construction of a Saccharomy...
Genome-scale metabolic models (GEMs) are mathematical models that enable systematic analysis of metabolism. This modeling concept has been applied to study the metabolism of many organisms including the eukaryal model organism, the yeast Saccharomyces cerevisiae, that also serves as an important cell factory for production of fuels and chemicals. W...
MOTIVATION:
Protein phosphorylation is a post-translational modification that affects proteins by changing their structure and conformation in a rapid and reversible way, and it is an important mechanism for metabolic regulation in cells. Phosphoproteomics enables high-throughput identification of phosphorylation events on metabolic enzymes, but id...
Protein phosphorylation is one of the most important mechanisms regulating metabolism as it can directly modify metabolic enzymes by the addition of phosphate groups. Attributed to such a rapid and reversible mechanism, cells can adjust metabolism rapidly in response to temporal changes. The yeast Saccharomyces cerevisiae, a widely used cell factor...
With determined components and experimental reducibility, the chemically defined medium (CDM) and the minimal chemically defined medium (MCDM) are used in many metabolism and regulation studies. This research aimed to develop the chemically defined medium supporting high cell density growth of Bacillus coagulans, which is a promising producer of la...
For commercial lactic acid production, a considerable amount of time (phase II) is required for the depletion of residual sugar to an acceptable range after glucose exhaustion. In this study, the effects of pH, glucoamylase, pullulanase and invertase addition on the degradation of residual sugar were investigated. When pH value in phase II was cont...
Questions
Questions (3)
I am now making a central carbon metabolic (CCM) model for a bacterium, but I don't know how to formulate the biomass equation. I have a genome-scale metabolic model (GEM) for the bacterium but its biomass equation is beyond the scope of the CCM model. Some of the metabolites in the GEM biomass equation are not involved in the CCM model. Could you please tell me how to simplify the GEM biomass equation?
Hello, I would like to collect all the Transcription Units (TUs) for Lactic Acid Bacterial (LAB), but I cannot find any publications or databases involving genome-scale TUs. I only have genome sequence available online, so I just wonder if it is possible to determine TUs based on genome information alone, and how to do it? Thank you!
For a specific phosphosite, maybe we can find several phosphopeptides containing such a phosphosite in phosphoproteomics data, but these phosphopeptides are different and thereby have different detected values (See the picture below).
How do you usually quantify the fold change of the phosphosite if such a site from different peptides (e.g. S27 in the picture)?
