Cellular Metabolism and Signaling
Our cells engage in protein production, and many of those proteins are enzymes responsible for the chemistry of life.
— Randy Schekman
I. Cell metabolism
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Structure Biology of the Citric Acid Cycle: The citric acid cycle is at the center of cellular metabolism. It plays a starring role in both the process of energy production and biosynthesis. [PDF]
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Regulation of Cholesterol Synthesis:
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Discovery of receptor-mediated endocytosis (RME) of LDL: Michael S. Brown and Joseph L. Goldstein.
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Part 1: Feedback Regulation of HMG CoA Reductase [iBiology Talk video]
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Part 2: Schnyder Corneal Dystrophy: Importance of UBIAD1 in Regulation of Cholesterol [iBiology Talk video]
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Goldstein, Joseph L., and Michael S. Brown. “A Century of Cholesterol and Coronaries: From Plaques to Genes and Statins.” Cell 161, no. 1 (2015): 161–72. [PDF | PMID: 25815993 | DOI Link]
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Question at 1970s:
- Receptors on the plasma membrane communicate with proteins in the nucleus, endoplasmic reticulum, lysosomes, mitochondria, and other structures, how is this cell-wide communication articulated ?
- How does a cell regulate a metabolic pathway whose active components reside in different subcellular compartments ?
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Regulation of Energy metabolism
- Review in 1979: METABOLITE TRANSPORT IN MITOCHONDRIA
- internal energy stress sensing and response program in brain ?
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Lysosome role in metabolic signalling
- Discovery of Lysosome: [Christian de Duve, 1959]
- Review in 2019: The lysosome as a cellular centre for signalling, metabolism and quality control (Rosalie and Roberto, 2019) [PDF | PMID: 30602725 | DOI Link]
- mTORC1 activation of Lysosomal membrane:
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Nutrient sensing machinery
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Cholesterol:
— LYsosomal CHOlesterol Signaling protein (LYCHOS, previously annotated as G-protein coupled receptor 155), Reported at 25-Aug-2022 [PDF | PMID:36007018 | DOI Link]
— PATCHED,
— HMG-CoA reductase,
— Niemann-Pick type C protein 1 (NPC1), Reported at 11-Jul-1997 [PDF | PMID:9211849 | DOI Link]
— SREBP (Sterol regulatory element-binding protein),
— SREBP cleavage-activating protein (SCAP), -
Amino acids:
Review: The Dawn of the Age of Amino Acid Sensors for the mTORC1 Pathway (Wolfson and Sabatini, 2017) [PDF | PMID:28768171 | DOI Link]
— Leucine > Sestrin2
— Arginine(Cytosolic) > CASTOR1 [(David M Sabatini’s lab, 24/03/2016) | PMID: 26972053]
— Arginine(Cytosolic) > RBM39 [(Michael N Hall’s lab, 09/11/2023) | PMID: 37804830]
— Arginine(lysosomal) > SLC38A9
— S-adenosylmethionine > SAMTOR
— S-adenosylmethionine > Unmet(Fly specific)
GATOR2 > Nutrient sensing hub! [CryoEM Structure of human GATOR2 complex | Valenstein et al., 2025] -
Glucose:
— AMPK
— X? – GATOR2-GATOR1-Rags-Ragulator-mTORC1 signaling axis -
Nitrogen sensing in yeast cells:
— X? – SEA complex-EGO-Gtrs-TORC1 signaling axis
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Open questions
- How cells sense, integrate and respond to nutrient availability and how lysosomes are involved in the process ?
- How amino acids were sensed? More amino acid sensors ?
- How different or similar the amino acid and nutrient inputs are that drive mTORC1/TORC1 signaling in diverse organisms ?
- Is GATOR2 the nutrient sensing hub complex ? How does it work to integrate multiple nutrient inputs ?
- How does brain sense the stress of energy supply and initiate its response program ?
- what is the nitrogen sensor in yeast cells ?
II. Cell signaling for cell growth control
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mTORC1 pathway
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AMPK pathway
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PI3K-AKT pathway
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Autophagy signaling ()
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Cell size checkpoint
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Hippo-YAP/TAZ pathway (Kun-Liang Guan)
III. Cell signaling in innate immune response
Between 1998 and 2000, innate immunity transitioned from a phenomenological description of inflammatory responses to a receptor- and adaptor-defined signaling architecture, setting the stage for the discovery that immune identity is encoded not by receptors alone, but by adaptor-mediated kinase licensing.
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Pattern recognition receptors (PRRs): These receptors are crucial for sensing danger signals.
- Toll-like receptors (TLRs): TLR4 [Poltorak et al., Science 1998]; TLR3 []; TLR9 []
- C-type lectin receptors (CLRs)
- NOD-like receptors (NLRs)
- RIG-I-like receptors (RLRs)
- AIM2-like receptors (ALRs)
- Key question at that time (before 2014): What is the intracellular receptor of LPS ?
- Cytosolic DNA sensor: cGAS [James Chen Lab, 2012]
- Non-canonical LPS sensor: Caspase 11 [Feng Shao Lab, 2014]
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Pathogen-associated molecular patterns (PAMPs)
- LPS
- dsRNA or its analog poly(I:C)
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Damage-associated molecular patterns (DAMPs)
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Signaling adaptors:
- TRIF (cell membrane):
- MAVS (in Mitochondria): [James Chen Lab, 2005]
- STING (in ER/Golgi) [Barber Lab, 2008]
- SLC15A4-TASL (in endolysosome) [Superti-Furga Lab, 2020]
1. TLR4-TRIF-TBK1-IRF3 signaling axis
TLR4–TRIF–TBK1–IRF3 axis links pathogen recognition at the plasma membrane to type I interferon production in the nucleus.
(1) TLR4: Sensing Danger at the Cell Surface
- Toll-like receptor 4 (TLR4) is a pattern recognition receptor that detects lipopolysaccharide (LPS) from Gram-negative bacteria. Unlike many receptors that signal through a single pathway, TLR4 is unique in that it activates two distinct downstream signaling programs:
- MyD88-dependent signaling, leading to NF-κB activation and inflammatory cytokines
- TRIF-dependent signaling, leading to TBK1 activation and type I interferon production [Shizuo Akira Lab, Dec 2002 | Tsukasa Seya Lab, Jan 2003 | Shizuo Akira Lab, Aug 2003]
(2) Spatial Control as a Signaling Logic
(3) TRIF: A Central Adaptor with Kinase-Licensing Function
- innate immune signaling is not determined by receptors alone, but by adaptor-defined kinase licensing, a principle that later emerged as a unifying logic across diverse membrane-associated signaling pathways.
(4) TBK1: Context-Dependent Kinase Activation
2. cGAS-STING-TBK1-IRF3 signaling axis
Understanding Innate Immunity: Cells constantly face threats from pathogens and damaged DNA. A central question in immunology has been: how do cells detect cytosolic DNA and convert this information into an antiviral response?
(1) Discovery of cytosolic DNA sensor: cGAS (2006-2013)
- Key question at that time: What is the cytosolic DNA sensor that trigger antiviral response ?
- pioneering works:
- Stetson, Daniel B., and Ruslan Medzhitov. “Recognition of cytosolic DNA activates an IRF3-dependent innate immune response.” Immunity 24.1 (2006): 93-103. [PMID: 16413926]
- Ishii, Ken J., et al. “A Toll-like receptor–independent antiviral response induced by double-stranded B-form DNA.” Nature immunology 7.1 (2006): 40-48. [PMID: 16286919]
- Key discovery works:
- The first step in this signaling cascade is the detection of cytosolic DNA by the enzyme cGAS (cyclic GMP-AMP synthase). cGAS binds double-stranded DNA, irrespective of sequence, and synthesizes the second messenger cGAMP.
(2) STING: The Adaptor on Membranes
- cGAMP binds to STING (Stimulator of Interferon Genes), a transmembrane protein localized primarily at the endoplasmic reticulum (ER). Upon binding, STING relocalizes to perinuclear puncta, often associated with the Golgi.
(3) Activation of TBK1
- After translocating to the Golgi, STING recruits TBK1 kinase, initiating phosphorylation cascades.
- The activation triggers IRF3 phosphorylation, leading to type I interferon production.
- Key works:
- A critical advancement was the identification of the PLPLRT/SD motif in STING’s C-terminal tail (CTT). [Pingwei Li Lab, 2019]
- Structural Insights: Full-Length STING–TBK1 Complex. [James Chen Lab, UTSW structure team (Xuewu Zhang, Xiao-chen Bai), 2019]
IV. Immune surveillance against cancer
- Firstly proposed by Sir Frank Macfarlane Burnet (1970)
- Discovery of PD1: [Tasuku Honjo, 1992]
- Discovery of PD-L1 (B7-H1): [Lieping Chen, 1999]
V. Cell death pathways
1. Programmed cell death - Apoptosis (1995-2002)
- Discovery of the genes:
- Identification of Apaf1
2. Programmed cell death - Necrosis
- Discovery of the genes:
- Identification of RIP3
- Identification of MLKL
3. Inflammation induced pyroptosis
- Discovery of GSDMD
Rather than viewing signaling pathways as linear cascades, here we trying to focus on adaptor-mediated control nodes that license kinase activation in specific membrane and tissue contexts. By integrating genetics, biochemistry, and structural biology, we aim to uncover unannotated signaling grammars that govern cell growth, immunity, and vascular development.
Textbooks
- Fundamentals of Biochemistry, Life at the Molecular Level, 5th edition [View PDF]

- Lehninger Principles of Biochemistry, 4th edition [View PDF]

- Molecular Biology of The Cell, 6th edition [View PDF]

Online Courses
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BIOLOGICAL CHEMISTRY I, MIT OpenCourseWare [Source]
- Instructors: JoAnne Stubbe, John Essigmann | Bogdan Fedeles]
- Lexicon of biochemical reactions [PDF]
- Metabolic Pathways Chart [PDF]
- Inborn Errors of Metabolism [PDF]
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BIOLOGICAL CHEMISTRY II, MIT OpenCourseWare [Source]
- Instructors: JoAnne Stubbe, Elizabeth Marie Nolan
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BIOCHEMISTRY LABORATORY, MIT OpenCourseWare [Source]
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Principles of Biochemistry, HarvardX, EdX:
This introduction to biochemistry explores the molecules of life, starting at simple building blocks and culminating in complex metabolism. [Source]- Instructors: Alain Viel, Rachelle Gaudet
- Edward A. Dennis (2010) “LIPID MAPS Lipid Metabolomics Tutorial”:
These tutorial videos were prepared for students in the UCSD School of Medicine and School of Pharmacy and Pharmaceutical Sciences by Professor Edward A. Dennis, Department of Chemistry and Biochemistry and Department of Pharmacology, School of Medicine, University of California, San Diego. [Tutorial outline PDF]- Part 1: Fatty Acid Biosynthesis [Lecture Slide | Video]
- Part 2: Lipoprotein Structure and Receptor Function [Lecture Slide | Video A | Video B]
- Part 3: Cholesterol Regulation and Homeostasis [Lecture Slide | Video]
- Part 4: Bioenergetics and Mitochondrial Functioning [Video A | Video B]
- Part 5: Specialized Lipids and Disease [Video A | Video B]
- LIPID MAPS Spring School, April 2021
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Day 1:
- Introduction to lipids, by Valerie O’Donnell
- Sterols, bile acids, oxysterols, by William Griffiths
- shorthand nomenclature and classification, by Matthew Conroy
- Sphingolipids, by Al Merrill
- Fatty acids and eicosanoids: Structure and Function, by Edward Dennis
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Day 2:
- Phospholipid structures and functions, by Junken Aoki
- Introduction to (LC)MS based lipidomics, by Maria Fedorova
- Vendors presentations, by Christian Klose (Lipotype) Rebecca Sayers, (SCIEX), Sven Mayer (BRUKER)
- Shotgun lipidomics, by Gerhard Liebisch
- Chromatography of lipids-potential for separation of various types of lipid isomers, by Michal Holčapek
- Neutral lipids (TG, DG, CE), by Robert Murphy
- Parameters for confirming lipid identification by LC-MS, by Stacy Wendell
- Sample preparation and storage considerations, by Robert Murphy
- Quantitation of free and esterified fatty acids and eicosanoids, by Edward Dennis
- Identification of oxidized complex lipids from LC-MS/MS datasets, by Maria Fedorova
- Targeted quantification of sphingolipids, by Al Merrill
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Day 3:
- Targeted Phospholipid analysis in mass spectrometry, by Junken Aoki
- Quantification of lipid species, by Gerhard Liebisch
- Standards for broad lipid categories and for cohort work, by Cameron Sullards
- Optimizing the use of standards for eicosanoidanalysis, by Paul Kennedy/Miguel Gijon
- Lipid Imaging using MS and MS/MS, by Zoltan Takats
- Ion mobility application to lipidomics, by Jules Griffin
- Novel technologies: REIMS, iKnife, LDI, DESI imaging of lipids, by Zoltan Takats
- Introduction to tutorials, by Maria Fedorova
- Use of XCMS for processing large MS or MS/MS datasets, by Gary Siuzdak
- LipidFinder, by Jorge Alvarezz Jarreta
- LDA, by Juergen Hartler
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Day 4:
- Targeted analysis of sterols and related mediators, by William Griffiths
- UHPSFC/MS in high-throughput lipidomic quantitation, by Michal Holčapek
- Cohort lipidomics: Overview of current state of the art, standardization, & pitfalls, Federico Torta
- MS-DIAL, by Hiroshi Tsugawa
- High-throughput identification of oxidized lipids by LPPtiger, by Zhixu Ni
- MZmine Demonstration, by Ansgar Korf
- METASPACE tutorial, by Theodor Alexandrov
- Biostatistical tools for MS lipidomics, by Shankar Subramaniam
- Systems biology data integration–lipidomics perspectives, by Shankar Subramaniam
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Day 5:
- An introduction to biostatistical approaches in lipidomics, by Laura Goracci
- LipidCreator: A workbench to probe the lipidomic landscape, by Robert Ahrends
- LION/web:a web-suite for lipidomics data analysis, by Martin Molenaar
- LipidLynxX Links lipid identification to data integration at systems level, by Zhixu Ni
- LIPID MAPS databases, tools and other resources, by Matthew Conroy
- BioPAN: A web-based tool to explore mammalian metabolic pathways on LIPID MAPS, by Caroline Gaud
- WikiPathway, by Egon Willighagen
Ref. Database
Nobel laureates
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Bruce A. Beutler, University of Texas Southwestern Medical Center at Dallas, Dallas, TX, USA; The Scripps Research Institute, La Jolla, CA, USA Nobel Prize in Physiology or Medicine 2011
How Mammals Sense Infection: From Endotoxin to the Toll-like Receptors [Lecture slides | Source] -
George E. Palade, Yale University, School of Medicine, New Haven, CT, USA Nobel Prize in Physiology or Medicine 1974
Intracellular Aspects of the Process of Protein Secretion [Read the Lecture | Source] -
Christian de Duve, Rockefeller University, New York, NY, USA; Université Catholique de Louvain, Louvain, Belgium Nobel Prize in Physiology or Medicine 1974
Exploring Cells with a Centrifuge [Read the Lecture | Source] -
Hans Krebs, Sheffield University, Sheffield, United Kingdom Nobel Prize in Physiology or Medicine 1953
The Citric Acid Cycle [Read the Lecture | Source] -
Fritz Lipmann, Harvard Medical School, Boston, MA, USA; Massachusetts General Hospital, Boston, MA, USA Nobel Prize in Physiology or Medicine 1953
Development of the Acetylation Problem: A Personal Account [Read the Lecture | Source]
