Review: Cellular Metabolism in Disease (Cancer, Diabetes, Senescence, and NASH)

Science Note

[Nov. 5, 2024]                                                                                                                                                                                                                       Previous Science Note
How Lipid Droplets and Lipid Peroxides Affect Neuronal Toxicity

In recent neurodegenerative disease research has shown that lipid metabolism, such as lipid droplets and lipid peroxides, influences neuronal damage. Here are some of the papers that have identified a relationship between lipid metabolism and the neurotoxic environment.

Neuronal toxicity in neurodegenerative diseases is often associated with the accumulation of lipid droplets and lipid peroxides, which are by-products of lipid metabolism. Lipid droplets in neurons and glia serve as storage for lipids, but excessive accumulation can impair cellular function. Lipid peroxides resulting from oxidative stress are particularly damaging, generating reactive oxygen species that lead to cellular dysfunction and cell death. In tauopathies*, lipid peroxides are transferred to glial cells, exacerbating the inflammation and oxidative stress that contribute to the neurotoxic environment.

*Tauopathy is a neurodegenerative disease characterized by abnormal accumulation of tau protein.

APOE4/4 is linked to damaging lipid droplets in Alzheimer’s disease microglia
Click here for the original article: Michael S. Haney, et. al., Nature, 2024.
Tau is required for glial lipid droplet formation and resistance to neuronal oxidative stress
Click here for the original article: Lindsey D. Goodman, et. al., Nature Neuroscience, 2024.
Microglial lipid droplet accumulation in tauopathy brain is regulated by neuronal AMPK
Click here for the original article: Yajuan Li, et. al., Cell Metabolism, 2024.

Point of Interest
- ACSL1-positive microglia, characterized by the lipid droplet-associated enzyme ACSL1, are abundant in Alzheimer’s patients with the APOE4/4 genotype.

- Fibrillar Aβ induces ACSL1 expression, triglyceride synthesis and lipid droplet accumulation in APOE-dependent microglia.

- Conditioned media from lipid droplet-containing microglia lead to tau phosphorylation and neurotoxicity, linking genetic risk factors for AD to potential therapeutic targets.

 

Point of Interest
- ROS accumulation in tauopathies leads to toxic peroxidized lipids that affect neurons and glia in brain disorders.

- Glial endogenous tau is essential for lipid droplet formation and protection against toxic neuronal lipids in flies, rats and human cells.

- Flies lacking glial endogenous tau show motor defects and reduced lifespan, which can be alleviated by antioxidants such as N-acetylcysteine amide.

Point of Interest
- Tauopathy fly and human iPSC neurons show increased lipogenesis and impaired lipid turnover within lipid droplets.

- Unsaturated lipid transfer from tauopathy neurons to microglia leads to lipid droplet accumulation, oxidative stress, inflammation and impaired phagocytosis.

- AMPK inhibits neuronal lipogenesis and supports lipophagy, reducing lipid transfer to microglia, whereas AMPK depletion exacerbates lipid accumulation and neuropathology.

Related Techniques
Lipid Droplet Staining Lipi-Blue/ Green/ Red/ Deep Red
Lipid Droplet Detection Kit Lipid Droplet Assay Kit - Blue / Deep Red
Intracellular / mitochondrial lipid peroxidation detection Liperfluo, MitoPeDPP
Total ROS detection Highly sensitive DCFH-DA or Photo-oxidation Resistant DCFH-DA
Mitochondrial superoxide detection MitoBright ROS Deep Red - Mitochondrial Superoxide Detection
Glutathione Quantification GSSG/GSH Quantification Kit
First-time autophagy research Autophagic Flux Assay Kit
Lysosomal function Lysosomal Acidic pH Detection Kit -Green/Red and Green/Deep Red
Glycolysis/Oxidative phosphorylation Assay Glycolysis/OXPHOS Assay Kit 
Apoptosis detection in multiple samples Annexin V Apoptosis Plate Assay Kit
Cell proliferation/ cytotoxicity assay Cell Counting Kit-8 and Cytotoxicity LDH Assay Kit-WST
 
Related Applications

Hepatotoxicity test of drug-induced lipidosis using high-content imaging

Propranolol (a sympathetic β-receptor blocker) was added to a human hepatocellular carcinoma cell line (HepG2 cells), and changes in lipid droplets were observed under a fluorescence microscope. The accumulation of lipid droplets was analyzed by measuring the number, area, and fluorescence intensity of lipid droplets from the acquired microscopic images.

<Lipid droplet imaging data>

  Nucleus (blue: Hoechst 33342 ): Ex 385 nm, Em 460 nm  
  Lipid droplet (green: Lipi-Green): Ex 475 nm, Em 535nm

HepG2 cells were treated with propranolol 0, 10, or 30 μmol/l, lipid droplets were stained with Lipi-Green and nuclei with Hoechst 33342 and observed using a fluorescence microscope (Ti2-E inverted microscope). The results showed that lipid droplets increased in a propranolol concentration-dependent manner.

 

Related Products
   - Lipi-BlueGreenRedDeep Red
   - Lipid Droplet Assay Kit - Blue / Deep Red

<Analysis of lipid droplet accumulation relative to drug treatment concentration>

  
 

High Content Analysis (HCA) microscope system
(Nikon Corporation https://www.microscope.healthcare.nikon.com/)

For details of staining and analysis methods, please refer to "APPLICATION NOTE: Hepatotoxicity test of drug-induced lipidosis using high-content imaging" by Nikon Corporation.

From the fluorescence images obtained, the accumulation of lipid droplets per cell was analyzed by measuring cell number from nuclei and area, number, and fluorescence intensity from lipid droplets. The results showed that the number and area of lipid droplets increased in a propranolol concentration-dependent manner, with lipid droplets forming significantly under concentration conditions of 20 μmol/l or higher. The DS-Qi2 camera, which can capture a wide range of cellular areas in a single shot, was used for imaging, and the EDF module of NIS-Elements software, which can acquire focused images of all lipid droplets, was used for analysis, enabling quantitative analysis with highly reliable statistical data. The EDF module of the NIS-Elements software allows for the acquisition of focused images of all lipid droplets.

 


 

Kits and Reagents

Target object Indicator Reagent / Kit
Cellular Metabolism Extracellular OCR Extracellular OCR Plate Assay Kit
Glycolysis/OXPHOS Glycolysis/OXPHOS Assay Kit
Lactate Lactate Assay Kit-WST
Glucose Glucose Assay Kit-WST
ATP ATP Assay Kit-Luminescence
NAD/NADH NAD/NADH Assay Kit-WST
NADP/NADPH NADP/NADPH Assay Kit-WST
Glutamine Glutamine Assay Kit-WST
Glutamate Glutamate Assay Kit-WST
α-Ketoglutarate α-Ketoglutarate Assay Kit-Fluorometric
Nutrient Uptake Glucose Uptake Glucose Uptake Assay Kit–BlueGreenRed
Amino Acid Uptake Amino Acid Uptake Assay Kit
Cystine Uptake Cystine Uptake Assay Kit
Mitochondrial Analysis Mitochondrial Membrane Potential JC-1 MitoMP Detection Kit
Mitochondrial Membrane Potential MT-1 MitoMP Detection Kit

      

 



Analyzing the various intracellular metabolic pathways [e.g., the glycolysis system, the tricarboxylic acid (TCA) cycle, electron transport chain, etc.] is important when trying to understand cellular states. Metabolites and energy sources [e.g., glucose, lactate, and NAD(P)+/NAD(P)H] are the indicators used for analyzing intracellular metabolisms.

Cellular Metabolism and Disease

Intracellular metabolism in disease models such as cancer and diabetes has recently attracted great attention. The changes in metabolic indices associated with each disease are indicated here. Click to jump to academic and related metabolic info for each item

Cancer

Cancer cells rapidly take in large amounts of nutrients in order to maintain active cell growth. They metabolize these nutrients to synthesize and nucleic acids and to produce energy such as ATP. Even under unfavorable conditions, such as hypoxia or low nutrition, cancer cells can survive by altering their metabolic systems. Therefore, the metabolic systems of cancer cells have attracted many researchers’ attention.

  A recurring characteristic of cancer cell metabolism is that cancer cells generally prefer to produce ATP via the glycolytic system despite that system being less efficient than mitochondrial oxidative phosphorylation (Warburg effect). As a result, cancer cells take up large amounts of glucose. They also produce a large amount of lactate due to increased glycolytic activity. This method of ATP production allows cancer cells to proliferate even under hypoxia, because the glycolytic system does not require oxygen. Meanwhile, the mitochondria of cancer cells use amino acids and fats to produce NADH. It is commonly recognized that NADH in cancer cell mitochondria is mainly used for redox regulation in addition to ATP production. The abnormal functions of mitochondria in cancer cells result in increased mitochondrial membrane potential (hyperpolarization) and excessive ROS production. Consequently, they produce large amounts of glutathione to maintain the redox balance. Since glutamine and cysteine are essential nutrients for glutathione production, cancer cells take up large amounts of these amino acids. Additionally, since NADPH is required to maintain the reduction of glutathione, the pentose phosphate pathway (downstream from the glycolytic system) and NADH in mitochondria are used to maintain high NADPH levels.

 (Note) The above information represents the general metabolic characteristics of cancer cells and may vary depending on the type of cancer cell and its environment.

References:

Below articles are general review on cancer cell metabolism.

1) Glycolytic system:
M. G. Vander Heiden, L. C. Cantley, and C. B. Thompson, “Understanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation”, Science2009, 324, 1029.

2) Amino Acids metabolism, ROS:
P. Koppula, Y. Zhang, and B. Gan, “Amino Acid Transporter SLC7A11/xCT at the Crossroads of Regulating Redox Homeostasis and Nutrient Dependency of Cancer”, Cancer Commun.2018, 38, 12.

3) Amino Acids:
E. L. Lieu, T. Nguyen, S. Rhyne, and J. Kim, “Amino Acids in Cancer”, Exp. Mol. Med.2020, 52, 15.

4) Mitochondrial, ROS, NADPH:
F. Ciccarese and V. Ciminale, “Escaping Death: Mitochondrial Redox Homeostasis in Cancer Cells”,  Front. Oncol.2017,  7, 117.

5) NADH:
A. Chiarugi, C. Dolle, R. Felici, and M. Ziegler, “The NAD Metabolome-A Key Determinant of Cancer Cell Biology”, Nat. Rev. Cancer2012, 12, 741.

 


Cellular Metabolism Related Disease

  • Glucose Metabolism Inhibition and Anticancer Effects
  • Amino Acid Metabolism Inhibition and Anticancer Effects
  • Fatty Acid Metabolism Inhibition and Anticancer Effects
  • Cancer Immunity and Metabolism

Glucose Metabolism Inhibition and Anticancer Effects

  Cancer cells mainly use the glycolytic system to produce ATP. Thus, the glycolytic system is the most important pathway to understand in the metabolism of cancer cells. Consequently, the glycolytic system has long been a target of anticancer drug development. Although effective anticancer drugs have not yet been developed, the glycolytic system remains a major drug target.

 One of the drug discovery target proteins of the glycolytic system is the glucose transporter (GLUT). Since cancer cells take up large amounts of sugar via glucose transporters, it is possible to suppress the glycolytic system by directly inhibiting glucose transporters. Inhibition of the enzymes responsible for glucose starvation and glycolysis [hexokinase (HK), lactate dehydrogenase (LDH), etc] as well as inhibition of the efflux of lactate (the end product of glycolysis) are also effective.

Changes in Intracellular Metabolism by Each Inhibitor / References

Cell Line Inhibitor / Inducer Changes to Cellular Metabolism Publication

SKOV3, OVCAR3, HEY, A2780

GLUT1 inhibitor: BAY-876

ATP  ↓, Lactate  ↓

Cancer, 2019, 11, 33

H1299, H460, H2030

GLUT1 express inhibitor: Apigenin

Glucose consumption  ↓

Lactate  ↓, ATP  ↓

NADPH  ↓, GSH/GSSG  ↓

ROS  ↓

Int. J. Oncol., 2016, 48, 399

HCT116

HK inhibitor: 2-DG

Glucose uptake   ↓

Lactate  ↓, Acetyl-CoA  ↓

H3K27Ac  ↓

Cancer Metab., 2015, 3, 10

SKOV3, HEY

HK inhibitor: 2-DG + Metformin

ATP  ↓, Lactate  ↓

Am. J. Transl. Res., 2016, 8, 4821

CT26

Complex I inhibitor: Phenformin,

LDH inhibitor: Oxamate

Glucose uptake  ↓

Lactate  ↓, ATP  ↓

ROS  ↑

PLoS One., 2014, 9, e85576

P493

LDH inhibitor: FX11

ATP  ↓, Lactate  ↓

NADH/NAD  ↑, ROS  ↑

Mitochondrial MP  ↓

Proc. Natl. Acad. Sci. USA, 2010, 107(5), 2037

Raji

MCT inhibitor: AZD3965

Glucose uptake  ↓

Intracellular Lactate  ↑

(Extracellular Lactate  ↓)

Cancer Res., 2017, 77(21), 5913

Related Products

Objective Product Name Code
Glucose Metabolism Assay Glucose Assay Kit-WST G264
Glucose Uptake Assay Glucose Uptake Assay Kit-Green UP02
Lactic Acid Measurement Lactate Assay Kit-WST L256
NAD+/NADH Assay NAD/NADH Assay Kit-WST N509
NADP+/NADPH Assay NADP/NADPH Assay Kit-WST N510

JC-1 Mitochondrial Membrane Potential Detection

JC-1 MitoMP Detection Kit MT09
MT-1 Mitochondrial Membrane Potential Detection MT-1 MitoMP Detection Kit MT13
 

Amino Acid Metabolism Inhibition and Anticancer Effects

 In cancer cells, which are actively proliferating, amino acids are essential for the synthesis of proteins and nucleic acids. Furthermore, many cancer cells downregulate acetyl CoA production from pyruvate, requiring cancer cells to also use amino acids as nutrient sources for the TCA cycle. This explains why cancer cells have been shown to increase expression of amino acid transporters to take up large amounts of amino acids.

 Glutamine in particular is a raw material for glutathione and a source of α-ketoglutarate, which is essential for the TCA cycle. For these reasons, glutamine uptake and glutaminolysis (glutamine metabolism) have attracted attention as drug targets. As well, the amino acid transporter LAT (L-type amino acid transporter), which is involved in the uptake of many essential amino acids, was found to be overexpressed in many cancer cells. LAT is expected to a be future drug target.

 Because cancer cells produce a large amount of reactive oxygen species, they maintain redox balance by increasing the production of glutathione, an antioxidant. Thus, inhibition of the pathways involved in glutathione production can change the intracellular redox balance and induce methods of cell death such as ferroptosis. In addition to the reason just stated, glutathione also contributes to drug resistance, which is why the pathway involved in glutathione production has become a major target for drug development.

 Cysteine is an amino acid also required for redox regulation and is mainly taken up into cells by the cystine transporter (xCT). Sulfasalazine, long used as an anti-inflammatory drug, and sorafenib, a molecular targeted therapy for cancer, have recently been shown to inhibit xCT. For the same cell death-mediated anticancer effect as glutathione inhibition, xCT has also attracted attention as a target for drug development.

Changes in Intracellular Metabolism by Each Inhibitor / References

Cell Line Inhibitor / Inducer Changes to Cellular Metablism Publication

KO99L

LAT1 inhibitor: JPH203

Mitochondrial MP  ↓

Autophagy  ↑

Leukemia, 2015, 29, 1253

LS174T

A549

LAT1 inhibitor: JPH203

Glutamine uptake  ↓

Leucine uptake  ↓

J. Biol. Chem., 2018, 293(8), 2877

HeLa

LAT1 inhibitor: BCH

Tryptophan uptake  ↓

J. Immunol., 2011, 187(4), 1617

A549

ASCT2 inhibitor: GPNA

Glutamine uptake  ↓

ROS  ↑

Clin. Cancer Res., 2013, 19(3), 560

MG63.3

GLS inhibitor: CB839

Glutamine  ↑

Glutamate  ↓, GSH  ↓

Cancer&Metab., 2020, 8:4

OCI-AML3

GLS inhibitor: CB839

ATP  ↓, NADH/NAD  ↓

GSH/GSSG  ↓, Alanine  ↓

Glutamate  ↓

Mol. Cancer Ther., 2019, 18(11), 1937

H1299

MDA-MB231

GDH inhibitor: R162

ROS  ↑

GPx activity  ↓

Cancer Cell, 2015, 27, 257

A2780

xCT inhibitor: Erastin

Cystine uptake  ↓

GSH  ↓

Sci. Rep., 2018, 8(1), 968

B16-F10

xCT inhibitor: Sulfasalazine

GSH  ↓

ROS  ↑

PLoS One., 2018, 13(4), e0195151.

HT-1080

xCT inhibitor: Sorafenib

Cystine uptake  ↓, GSH  ↓

Lipid peroxidation  ↑

Elife, 2014, 3, e02523

PANC-1

GCL inhibitor: BSO

GSH  ↓

Lipid peroxidation  ↑

Oncol. Lett., 2018, 15(6), 8735

A549

GCL inhibitor: BSO

Cystine uptake  ↓, GSH  ↓

Toxicol. Appl. Pharmacol., 1985, 381

Related Products

Objective Product Name Code
NAD+/NADH Assay NAD/NADH Assay Kit-WST N509
JC-1 Mitochondrial Membrane Potential Detection       JC-1 MitoMP Detection Kit MT09
MT-1 Mitochondrial Membrane Potential Detection MT-1 MitoMP Detection Kit MT13
Total ROS Detection ROS Assay Kit-Highly Sensitive DCFH-DA- R252
Glutamine Assay Glutamine Assay Kit-WST G268
Glutamate Assay Glutamate Assay Kit-WST G269
Glutathione Quantification GSSG/GSH Quantification Kit G257
Lipid Peroxide Detection Liperfluo L248
Mitochondrial Lipid Peroxide Detection MitoPeDPP M466
Autophagosome Detection DAPGreen – Autophagy Detection D676
DAPRed – Autophagy Detection D677
 


Fatty Acid Metabolism Inhibition and Anticancer Effects

Cancer cells, which are actively proliferating, naturally require a large amount of lipids. Thus, intracellular fatty acid synthesis and extracellular fatty acid uptake are both very active. Therefore, many cancer cells have enhanced lipid droplet accumulation. Consequently, the pathway involved in fatty acid production is a very popular therapeutic target for cancer, and many inhibitors have been developed. Additionally, cancer cells perform β-oxidation of fatty acids for efficient energy production in order to compensate for inefficient energy production by the glycolytic system. Thus, drugs targeting the  β-oxidation of fatty acids are also being developed.

Changes in Intracellular Metabolism by Each Inhibitor / References

Cell Line Inhibitor / Inducer Changes to Cellular Metabolism Publication

CD36 Highly expressed MCF7, SUM159

CD36 inhibitor: SSO

Fatty acid uptake  ↓

Lipid droplet  ↓

Cancers, 2019, 11, 2012

A375, SKMel28

FATP inhibitor: Lipofermata

Fatty acid uptake  ↓

Lipid droplet  ↓

Cancer Discov., 2018, 8(8), 1006

BT474, MCF7, T47D

ACACA inhibitor: TOFA

Lipid droplet  ↓

FA oxidation  ↓

J. Clin. Med., 2020, 9, 87

ccRCC

SREBP inhibitor: Betulin

ACACA inhibitor: TOFA

FASN inhibitor: C75

Lipid droplet  ↓

Mol. Cell Biol., 2017, 37(22), e00265-17

NCI-H1703

ACSL inhibitor: Triacsin C

Lipid droplet  ↓

Int. J. Cancer, 2020, 147, 1680

UM-UC-3

FAO inhibitor: Etomoxir

Lipid droplet  ↑

ATP  ↓,  NADPH  ↓

Clin. Sci., 2019, 133 (15), 1745

SF188

FAO inhibitor: Etomoxir

ATP  ↓,  NADPH  ↓

GSH  ↓

ROS  ↑

Biochim. Biophys. Acta, 2011, 1807(6), 726

Related Products

Objective Product Name Code
Lipid Droplet Assay Lipid Droplet Assay Kit – Blue LD05
Lipid Droplet Assay Kit – Deep Red LD06
Lipid Droplet Staining Lipi-Blue LD01
Lipi-Green LD02
Lipi-Red LD03
Lipi-Deep Red LD04
NADP+/NADPH  Assay NADP/NADPH Assay Kit-WST N510
Glutathione Quantification GSSG/GSH Quantification Kit G257
Total ROS Detection ROS Assay Kit -Highly Sensitive DCFH-DA- R252

 

 

Cancer Immunity and Cellular Metabolism

  T cells play a central role in the immune system by eliminating cancer cells. In recent years, it has become clear that metabolism is also involved in the regulation of T cell functions such as differentiation and activation, inspiring more active research on metabolism in cancer immunity.

Cancer cells take in large amounts of nutrients to maintain their proliferative activity. Activated T cells also require large amounts of nutrients to eliminate cancer cells. Cancer cells and activated T cells thus compete for nutrients – particularly glucose.

  Activated T cells express the PD-1 immune checkpoint receptor on their surface. Cancer cells, in turn, express PD-L1, as the interaction will suppress T cell glucose uptake. It is in this way that cancer cells will regulate the metabolism of immune cells in order to evade the immune system. Therefore, it is important to understand the metabolism of not only cancer cells but also immune cells for the sake of cancer immunology.

References:

1) Z. Yin, L. Bai, W. Li, T. Zheng, H. Tian, and J. Cui, “Targeting T cell metabolism in the tumor microenvironment: an anti-cancer therapeutic stratety”, J. Exp. Clin. Cancer Res201938, 403.

2) L. Almeida, M. Lochner, L. Berod, and T. Sparwasser, “Metabolic pathways in T cell activation and linear differentiation”, Semin. Immunol201628(5), 514.

3) A. Kumar and K. Chamoto, “Immune metabolism in PD-1 blockage-based cancer immunotherapy”, Int. Immunol., 2020 Jul 5;dxaa046.

4) D. G. Franchina, F. He, and D. Brenner, “Survival of the fittest: Cancer challenges T cell metabolism”, Cancer Lett., 2018412, 216.

5) N. Patsoukis, K. Bardhan, P. Chatterjee, D. Sari, B. Liu, L. N. Bell, E. D. Karoly, G. J. Freeman, V. Petkova, P. Seth, L. Li, and V. A. Boussiotis, “PD-1 alters T-cell metabolic reprogramming by inhibiting glycolysis and promoting lipolysis and fatty acid oxidation”, Nat. Commun., 20156, 6692.

Changes in Intracellular Metabolism by Each Inhibitor / References

Cell Line

Antigen Activation

Changes to Cellular Metabolism

Publication

T cell

Activation

Glucose uptake   ↑

J. Immunol., 2008, 180, 4476

CD8(+) T cell

Activation

Glucose uptake   ↑
FAO   ↓

J. Clin. Invest., 2013, 123, 4479

CD4(+) T cell

Activation

Glucose uptake   ↑

Lactate   ↑, ATP   ↑

eLife, 2018, 7, e30938

CD4(+) T cell

Activation

Glucose uptake   ↑, Lactate   ↑

Glutamine uptake   ↑

FAO   ↓

Nat. Commun., 2015, 6, 6692
CD4(+) T cell

Activation

(Interactions between PD-1 & PDL1)

Glucose uptake   ↓, Lactate   ↓

Glutamine uptake   ↓

FAO   ↑

Related Products

Objective Product Name Code
Glucose Metabolism Assay Glucose Assay Kit-WST G264
Glucose Uptake Assay Glucose Uptake Assay Kit-Green UP02
Lactate Detection Lactate Assay Kit-WST L256
Glutamine Detection Glutamine Assay Kit-WST G268
Glutamate Detection Glutamate Assay Kit-WST G269
ATP Measurement ATP Assay Kit-Luminescence A550

 

Diabetes

Hyperglycemic State and Increased Polyol Metabolism

 In hyperglycemic conditions, intracellular glucose concentration increases and polyol pathway metabolism is enhanced. This leads to excessive consumption of NADPH and a decrease in reduced glutathione (GSH).

 Overall, this results in increased oxidative stress and accelerated cellular damage.

Reference:

M. Brownlee, “The pathobiology of diabetic complications: a unifying mechanism”, DIABETES, 2005, 54, 1615.

Related Products

Objective Product Name Code
NAD+/NADH Assay NAD/NADH Assay Kit-WST N509
NADP+/NADPH Assay NADP/NADPH Assay Kit-WST N510
Glutathione Quantification GSSG/GSH Quantification Kit G257
Glucose Metabolism Assay Glucose Assay Kit-WST G264
Glucose Uptake Assay Glucose Uptake Assay Kit-Green UP02

 

Senescence

  • Relationship between Senescence-Related Diseases and Lactate/NAD+
  • Senescence due to DNA Damage
  • Glutamine Metabolism and Cellular Senescence

Relationship Between Senescence-Related Diseases and Lactate/NAD+

Recently, the relationship between NAD+ and senescence has been attracting attention. In the mouse aging model, a decreased amount of NAD+ was observed in the liver and other organs,1 whereas inhibition of NAD+ synthase has been reported to induce senescence-like decline in various cellular functions.2 Additionally, it has been suggested that a decrease in in NAD+ levels leads to decreased mitochondrial function,3 whereas a decrease in mitochondrial function has similarly been suggested to lead to a decrease in NAD+ levels and a senescence-like decline in cellular function.4

DNA Damage-Triggered Senescence

When mitochondrial function declines, ATP becomes more predominantly produced via anaerobic glycolysis, resulting in increased lactate production. DNA damage is one way cellular senescence can cause mitochondrial dysfunction.

 The accumulation of DNA damage activates DNA repair mechanisms and increases NAD+ consumption. The decrease in available NAD+ decreases the activity of SIRT1, an important factor in maintaining mitochondrial function. Mitochondrial dysfunction results as decreased SIRT1 activity leads to inhibition of electron transfer, resulting in reduced ATP production and NAD+.3,8

Glutamine Metabolism and Cellular Senescence

Tumor suppressor menin prevents effector CD8 T cell dysfunction by targeting mTORC1-dependent metabolic activation9

Menin is a tumor suppressor that plays an important role preventing T cell dysfunction from aging and fatigue. When menin is deficient, mTORC1 is activated, and oxidative phosphorylation via glycolysis and glutaminolysis is enhanced, leading to CD8 T cell dysfunction. Additionally, α-ketoglutarate, an intermediate product of glutamine metabolism, maintains the activation of mTORC1 and contributes to the promotion of cellular senescence (increased SA-β-gal activity). It has been suggested that the glutamine-α ketoglutarate pathway plays an important role in the induction of CD8 T cell dysfunction and that menin may inhibit T cell senescence.

References:

1) J. Yoshino, K. F. Mills, M. J. Yoon and S. Imai, “Nicotinamide mononucleotide, a key NAD+ intermediate, treats the pathophysiology of diet- and age-induced diabetes in mice”, Cell Metab., 2011, 14(4), 528.

2) L. R. Stein and S. Imai, “Specific ablation of Nampt in adult neural stem cells recapitulates their functional defects during aging”, EMBO J., 2014, 33(12), 1321.

3) J. Wu, Z. Jin, H. Zheng and L. Yan, “Sources and implications of NADH/NAD+ redox imbalance in diabetes and its complications”, Diabetes Metab. Syndr. Obes., 2016, 9, 145.

4) A. Bratic and N. Larsson, “The role of mitochondria in aging”, J Clin Invest. 2013, 123(3), 951.

5) I. San-Millancorresponding and G. A. Brooks, “Reexamining cancer metabolism: lactate production for carcinogenesis could be the purpose and explanation of the Warburg Effect”, Carcinogenesis, 2017, 38(2), 119.

6) Y. Wu, Y. Dong, M. Atefi, Y. Liu, Y. Elshimali, and J. V. Vadgama, “Lactate, a Neglected Factor for Diabetes and Cancer Interaction”, Mediators Inflamm., 2016. DOI: 10.1155/2016/6456018

7) Z. Feng, R. W. Hanson, N. A. Berger and A. Trubitsyn, “Reprogramming of energy metabolism as a driver of aging”, Oncotarget., 2016, 7(13), 15410.

8) S. Imai and L. Guarente, “NAD+ and sirtuins in aging and disease”, Trends in Cell Biology, 2014, 24(8), 464.

9) J. Suzuki, et al, “The tumor suppressor menin prevents effector CD8 T-cell dysfunction by targeting mTORC1-dependent metabolic activation.”, Commun  Nat Commun, 2018, 9(1), 3296.

Related Products

Objective Product Name Code
Cellular Senescence Detection(Microscopy/ FCM) Cellular Senescence Detection Kit – SPiDER-βGal SG04
Cellular Senescence Detection(Plate Reader) Cellular Senescence Plate Assay Kit – SPiDER-βGal SG05
JC-1 Mitochondrial Membrane Potential Detection JC-1 MitoMP Detection Kit MT09
MT-1 MitoMP Detection Kit MT13
α-Ketoglutaric Acid Measurement α-Ketoglutarate Assay Kit-Fluorometric K261
Glucose Metabolism Assay Glucose Assay Kit-WST G264

 

NASH

Nonalcoholic steatohepatitis (NASH)

 Nonalcoholic fatty liver disease (NAFLD) is a pathological change in the liver that occurs predominantly in the elderly, regardless of drinking history. NAFLD is a comprehensive disease concept that progresses from fatty liver (steatosis) through nonalcoholic steatohepatitis (NASH) to fibrosis/cirrhosis and finally hepatocellular carcinoma (HCC). 1

Recently, it has been reported that cellular senescence and associated mitochondrial dysfunctions contribute significantly to the development of NAFLD/NASH, and these reports have attracted much attention. 2,3,4,5
Obesity, a risk factor for NAFLD/NASH, increases lipid deposition, which then promotes the production of reactive oxygen species (ROS) and inflammatory cytokines, leading to cellular senescence. 2 The decrease in NAD+ levels associated with cellular senescence results in a decrease in mitochondrial function. 3 The decrease in mitochondrial function then leads to a further decrease in NAD+ levels, which exacerbates senescence-like changes in cellular function. 4

On the other hand, liver-specific induction of cellular senescence has been shown to increase lipid deposition and promote fibrosis.5 This indicates that cellular senescence, abnormal mitochondrial function, and associated metabolic changes produce a synergy in the development of NAFLD/NASH, forming inflammatory and fibrotic pathologies.

In the future, more detailed analysis of the relationship between this complex synergy and NAFLD/NASH is expected to contribute to the establishment of new treatments.

Reported cases in each NAFLD/NASH model

* Click on the links in the table to visit the store pages of these measurement kits/reagents

NAFLD/NASH model Cellular functions, metabolic changes, etc. References

Mouse model of aging, obesity, and diabetes

Hepatocyte senescence(SA-ß-Gal  ↑, p21  ↑)
⇒ Removal of senescent cells improves healthspan

Nat. Commun., 2016, 8, 15691.

Mice treated with high-fat + high-cholesterol diet

Abnormal mitochondrial function in the liver
(ATP  ↓,membrane potential  ↓,hydrogen peroxide production  ↑)

Redox Biol., 2018, 15, 86-96

Mice treated with high-fat diet

Abnormal mitochondrial function in liver(ATP  ↓,NAD  ↓),PARP  ↑
⇒ inhibition of PARP expression improves mitochondrial function and medical condition

J. Hepatol., 2017, 66, 132–141

Hepatic astrocyte fibrosis model

a-ketoglutarate  ↑,type I collagen  ↑ 
→ addition of a-ketoglutarate improves fibrosis

Biosci. Rep., 2020, 40, BSR20193385

High-fat diet treated mice

Lipid deposition in liver  ↑,liver function  ↓
→ addition of a-ketoglutarate improves the condition

Liver Res., 2020, 4, 94e10095

Reference:

1) T. Hardy, F. Oakley, Q. M. Anstee and C. P. Day, “Nonalcoholic fatty liver disease: pathogenesis and disease spectrum”, Annu. Rev. Pathol., 2016, 11, 451-496.

2) M. J. Schafer, et al, “Exercise Prevents Diet-Induced Cellular Senescence in Adipose Tissue”, Diabetes, 2016, 65, 1606-1615.

3) J. Wu, Z. Jin, H. Zheng and L. Yan, “Sources and implications of NADH/NAD+ redox imbalance in diabetes and its complications”, Diabetes Metab. Syndr. Obes., 2016, 9, 145.

4) A. Bratic and N. Larsson, “The role of mitochondria in aging”, J Clin Invest. 2013, 123(3), 951.

5) M. Ogrodnik, et al, “Cellular senescence drives age-dependent hepatic steatosis”, Nat. Commun., 2016, 8, 15691.

Others

Glutamine Metabolism and Autophagy

Promotion of autophagy and glutaminolysis via stabilization of glutaminase by BAG3
BAG3 is a protein involved in the regulation of various cellular functions, such as apoptosis, cell differentiation, and macroautophagy, etc. In cells overexpressing BAG3, glutaminase (GLS) succinylation is promoted, which prevents ubiquitination and subsequent proteosomal degradation, stabilizing the GLS protein. Stabilization of GLS promotes glutaminolysis, which in turn increases glutamine consumption. This results in increased intracellular glutamate and increased intracellular α-ketoglutarate, an intermediate product of glutamine metabolism. Accelerated glutaminolysis produces ammonia in the culture medium, which contributes to the activation of autophagy. For cancer cells with enhanced glutaminolysis, BAG3 has been suggested as a potential target for cancer therapy.

* BAG3 is a protein that is ubiquitously distributed in human tissues and is induced by various stresses. BAG3 is a protein involved in the regulation of various cellular functions and is also associated with cancer and age-related neurodegenerative diseases.

Reference:

S. Zhao, et al, “BAG3 promotes autophagy and glutaminolysis via stabilizing glutaminase”, Cell Death & Disease2019, 284(10).

Related Products

Objective Product Name Code
α-Ketoglutaric Acid Measurement α-Ketoglutarate Assay Kit-Fluorometric K261
Glutamine Assay Glutamine Assay Kit-WST G268
Glutamate Assay Glutamate Assay Kit-WST G269
Autolysosome Detection DALGreen – Autophagy Detection D675
Autophagosome Detection DAPGreen – Autophagy Detection D676
DAPRed – Autophagy Detection D677

 

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