assay of the multiple energy-producing pathways of mammalian … · 2020. 5. 7. · glucose, animal...

Assay of the Multiple Energy-Producing Pathways ofMammalian CellsBarry R. Bochner1*, Mark Siri1¤a, Richard H. Huang1¤b, Shawn Noble1, Xiang-He Lei1, Paul A. Clemons2,

Bridget K. Wagner2

1 Biolog, Inc., Hayward, California, United States of America, 2 Chemical Biology Program, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of

America

Abstract

Background: To elucidate metabolic changes that occur in diabetes, obesity, and cancer, it is important to understandcellular energy metabolism pathways and their alterations in various cells.

Methodology and Principal Findings: Here we describe a technology for simultaneous assessment of cellular energymetabolism pathways. The technology employs a redox dye chemistry specifically coupled to catabolic energy-producingpathways. Using this colorimetric assay, we show that human cancer cell lines from different organ tissues produce distinctprofiles of metabolic activity. Further, we show that murine white and brown adipocyte cell lines produce profiles that aredistinct from each other as well as from precursor cells undergoing differentiation.

Conclusions: This technology can be employed as a fundamental tool in genotype-phenotype studies to determinechanges in cells from shared lineages due to differentiation or mutation.

Citation: Bochner BR, Siri M, Huang RH, Noble S, Lei X-H, et al. (2011) Assay of the Multiple Energy-Producing Pathways of Mammalian Cells. PLoS ONE 6(3):e18147. doi:10.1371/journal.pone.0018147

Editor: Daniel Tome, Paris Institute of Technology for Life, Food and Environmental Sciences, France

Received August 8, 2010; Accepted February 27, 2011; Published March 24, 2011

Copyright: � 2011 Bochner et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: Principal funding for the research at Biolog was provided by National Institutes of Health (NIH) Grants R43-CA101605 from National Institutes of Health-National Cancer Institute (NIH-NCI) and grant R44-MH074145 (Small Business Innovation Research) from National Institutes of Health-National Institute of MentalHealth (NIH-NIMH). Additional funding and support was from Biolog, Inc., which employed the authors who designed the studies, collected the data, analyzed thedata, and prepared the manuscript. P.A.C. is supported in part by NCI’s Initiative for Chemical Genetics (N01-CO-12400), NIH Genomics-Based Drug Discovery/Target ID Project (RL1-HG004671), and NIH Molecular Libraries Network (U54-HG005032). B.K.W. is supported by the Juvenile Diabetes Research Foundation and aType 1 Diabetes Pathfinder Award (DP2-DK-083048, NIH-NIDDK). Barry Bochner, CEO and CSO at Biolog, made the decision to publish the manuscript.

Competing Interests: Barry Bochner is the CEO, CSO, and Chairman of the Board of Biolog, Inc., and has ownership of stock. Shawn Noble and Xiang-He Lei areemployees of Biolog, Inc., and Mark Siri and Richard Huang were employees of Biolog, Inc. at the time of data collection. Patents 6,696,239 and 6,727,076 havebeen issued to Biolog, Inc., and the Phenotype MicroArrays described in this manuscript are produced and marketed by Biolog, Inc. These relationships do notalter the authors’ adherence to all the PLoS ONE policies on data sharing.

* E-mail: [email protected]

¤a Current address: Denver School of Pharmacy, University of Colorado, Aurora, Colorado, United States of America¤b Current address: Agilent Technologies, Santa Clara, California, United States of America

Introduction

Tetrazolium-based redox assays can be used to measure the

active in vivo energy-producing pathways of a very wide range of

microbial cells [1,2], including eukaryotic microbial cells that

undergo mitochondrial respiration. Tetrazolium reduction is a

ubiquitous property of cells, enabling a simple colorimetric cellular

assay technology to be multiplexed into thousands of different

assays and facilitating detailed cellular analyses in what we term

Phenotype MicroArrays [3–6]. Based on previous success in

profiling metabolic activity of microbial cells (www.biolog.com/

mID_section_13.html), we sought to develop a redox chemistry

that could extend comparable analytical capabilities to mamma-

lian cells.

Redox dyes such as tetrazolium dyes (e.g., MTT, MTS, XTT)

and resazurin-based dyes (e.g., Alamar Blue) measure nonspecific

cellular reductase activities [7–10]. We assayed various mamma-

lian cell lines in RPMI-1640 medium without carbon energy

sources (glucose and glutamine) and found substantial levels of

non-specific background dye reduction, which was exacerbated

by adding serum or electron carriers; however, we were able to

develop two redox chemistries (Dye Mix MA and MB) that give

very little non-specific dye reduction (see Figure S1 and Figure

S2) and are reduced by a wide range of mammalian cells.

Importantly, the reduction of these dyes is dependent on the

presence of a usable carbon-energy source in the medium, such as

glucose. Therefore, just as in microbial cells, our new redox dye

chemistries measure reductase activity due to energy (NADH)

producing catabolic pathways that use diverse biochemical

substrates.

The extent to which animal cells from various organs and

tissues use different carbon substrates for energy has not been

systematically investigated. It is known that, in addition to

glucose, animal cells can metabolize and grow on other substrates

[11–19]. A survey of nutrient metabolism [12] found 32

carbohydrates that could be metabolized by mammalian cells,

of which 15 could support the growth of at least one of five cell

lines tested. However, as in vitro culture media were developed

using glucose, pyruvate, and glutamine as energy sources, which

were shown to support growth of most cells of interest, the

PLoS ONE | www.plosone.org 1 March 2011 | Volume 6 | Issue 3 | e18147

impetus to study further the scope and diversity of nutrients

metabolized by different cell types waned. Information about all

pathways that contribute to energy production not only underlies

our fundamental understanding of animal nutrition, but also is

likely to help us understand and treat undesirable or aberrant

metabolism, such as in obesity and diabetes. It may also help us

develop new approaches in nutritional therapy to improve

treatment of a wide range of conditions, including aging, cancer,

infectious disease, inflammation, and wound repair [20].

Results

Metabolic fingerprinting of cancer cellsTo demonstrate the application of this platform to human cells,

we profiled seven diverse human cancer cell lines in four

microplates (termed PM-Ms) containing 367 substrate nutrients

(Figure 1; see Table S1 for a complete map of the nutrients). PM-

M1 contains primarily carbohydrate and carboxylate substrates,

whereas PM-M2, -M3, and -M4 contain individual L-amino acids

and most dipeptide combinations. With the exception of abiotic

color formation in a few wells containing reducing sugars

(palatinose, D-turanose, D-tagatose, and L-sorbose), multiple lines

of evidence presented below suggest that the color formed from

each substrate reflects the energy-producing activity of its catabolic

pathway. This method is simple to perform and reproducible

(Figure S3).

All cell lines tested produced a strong reductive response in wells

containing glucose (Figure 1; green boxes, all panels) and little or

no response in wells lacking any carbon source (Figure 1; red

boxes, all panels). Two leukemic cell lines (CCRF-CEM and HL-

60) show additional metabolism limited to D-mannose, D-maltose,

and maltotriose (Figure 1A,B; blue boxes). Prostate cancer cells

(PC-3) show additional metabolism of fructose, some nucleosides,

and tricarboxylic acid (TCA) cycle intermediates (Figure 1C; blue

boxes), and lung cancer cells (A549) show additional metabolism of

dextrin, glycogen, and galactose (Figure 1D; blue boxes). In

addition, both prostate and lung cells show metabolism of

glutamine and many glutamine-containing dipeptides

(Figure 1C,D; purple wells on PM-Ms 2-4). Both colon

(COLO205) and liver (HepG2) cancer cell lines demonstrate a

more diverse catabolic response, with more wells showing a strong

reductive response (Figure 1E–G). For example, colon cells

additionally metabolize lactic acid, butyric acid, and propionic

acid (Figure 1E; blue boxes), and liver cells metabolize alanine,

arginine, and dipeptides containing them (Figure 1F,G; Ala = blue

boxes, Arg = gold boxes). This last result is consistent with an

NMR-based report that alanine is elevated in response to hypoxia,

and is associated with hepatomas [21].

Importantly, we observe that two genetically related liver cell

lines have similar metabolic profiles. The HepG2/C3A cell line

(Figure 1G) was derived as a spontaneous clonal variant of

HepG2 (Figure 1F), selected for its ability to grow on pyruvate

as the principal energy source [22]. Accordingly, this clone

shows stronger metabolism of pyruvate (Figure 1G; magenta

box) relative to its parent. Interestingly, along with this

metabolic change, HepG2/C3A cells have also been reported

to have additional phenotypes more typical of normal liver cells,

such as producing and secreting higher levels of albumin and

other serum proteins [22]. The colon cell line COLO205 has a

similar metabolic profile to HepG2, with a salient difference

being the observed increased metabolism of butyric acid and

propionic acid, which are plentiful in the colonic environment

due to their production by resident anaerobic bacteria. Thus,

the substrate utilization pattern provides a metabolic charac-

terization as well as a unique profile of the metabolism of an

animal cell.

These results with human cell lines mirror our results with

bacterial and fungal cells [2], in that we observe differential

catabolic activities in different cell types consistent with the

known physiological properties of different cells. Furthermore,

they recapitulate the results of earlier studies [12] that showed

five different cell lines were readily distinguishable by their

profiles of carbohydrate preference. The substrate nutrients in

PM-M1 to –M4 are all present at low millimolar concentrations.

Analyses of blood chemistries from non-fasting normal humans

suggest that the principal circulating carbon energy sources are

glucose (2–10 mM) and fatty acids, both free (0.01–1.0 mM) and

in the form of triglycerides and lipoproteins [23,24]. Glutamine

(0.6 mM), alanine (0.35 mM), and lactic acid (2 mM) also have

significant levels in normal blood [24,25]. A recent metabolomic

study has documented a wider array and higher concentrations of

potentially metabolizeable biochemicals in human plasma after

exercise, including glucose-6-phosphate, inosine, uridine, alanine,

lactate, pyruvate, succinate, malate, fumarate, and glycerol [26].

Furthermore, the cells lining the intestine are exposed to an even

more diverse and variable nutritional environment. Similarly, the

liver is fed directly from the intestine by the portal circulation.

Therefore, it is reasonable to expect that colon and liver cells

would have more diverse capabilities for substrate metabolism

than cells from other tissues.

Mechanism of cellular dye reductionTo study further the mechanistic aspects of this dye-reduction

assay, we tested HepG2/C3A cells in PM-M1 panels with varying

concentrations of the mitochondrial inhibitors carbonyl cyanide-p-

trifluoromethoxyphenylhydrazone (FCCP) and rotenone. Even at

low concentrations, these inhibitors completely block dye reduc-

tion by substrates that would presumably be oxidized mitochon-

drially, such as lactic acid, a-keto-glutaric acid, succinamic acid,

and acetic acid (Figure 2; red boxes). At higher concentrations,

they partially block reduction of fructose, adenosine, and inosine

(Figure 2; blue boxes), but have little effect on color formation in

wells containing glucose or mannose (Figure 2; green boxes).

Adding back 5 mM glucose after an 18-hour exposure is not

sufficient to rescue the cells when the concentration of the

inhibitor was high enough to block substrate catabolism. This

result is consistent with our interpretation that the assay reflects the

production of NADH from various substrates, and that the

fraction of NADH produced mitochondrially is different for

different energy substrates.

The ability of a cell to use a particular nutrient as a source of

energy is necessary but not sufficient to use it as a growth

substrate. To use a chemical as a sole growth substrate, the cell

must also be able to convert the carbon skeleton of that

chemical into all other metabolites that it requires. This assay

format can also be used to determine the survival responses of

cells under different conditions of substrate supply. HepG2/

C3A cells were tested for cell growth or death with PM-M1

substrates over a five-day incubation (Figure 3A). Four

qualitatively distinguishable responses were observed: prolifer-

ation (Figure 3; green boxes), including wells containing D-

glucose, D-mannose, D-fructose, D-galactose, uridine, and

xylitol; stasis (Figure 3A; blue boxes), including wells containing

D-maltose, D-glucose-6-phosphate, and inosine; slow death

(Figure 3A; red boxes), including wells containing dextrin, D-

sorbitol, and pectin; and rapid death, including wells corre-

sponding to no substrate, D-raffinose, and butyrate (Figure 3A;

black boxes). Sodium butyrate, a general inhibitor of histone

Metabolic Profiling Technology for Mammalian Cells


deacetylases, has previously been shown to be quite toxic to

HepG2 cells [27]. The set of substrates assayed as positive for

energy production corresponds with substrates supporting

prolongation of survival, as corroborated by microscopic

observation of the healthy morphology and increased cell

numbers in these wells (Figure 3D, compared to Figures 3B,

Figure 1. Assay of seven human cell lines in 367 metabolic assays. Suspensions of the following cancer cells were inoculated into PhenotypeMicroArrays PM-M1 through PM-M4 (Biolog, Hayward, CA) which contained 367 biochemical substrates that could potentially be metabolized andprovide energy for cells: (A) CCRF-CEM leukemia, (B) HL-60 leukemia, (C) PC-3 prostate cancer, (D) A549 non-small cell lung cancer, (E) COLO205colon cancer, (F) HepG2 hepatocellular cancer, (G) HepG2/C3A, a clonal variant of HepG2. Adherent cells were washed twice in Dulbecco’s PBS (D-PBS) before being detached with trypsin. Detached cells and non-adherent cells were suspended at 400,000 cells/mL in RPMI-1640 that lacked phenolred and glucose and was supplemented with PS and reduced levels of glutamine (0.3 mM) and FBS (5%). The cells were dispensed at 50 mL per well(20,000 cells per well) into the four microplates. Plates were incubated for 40 hr at 37uC under 5% CO2-95% air. This 40-hour incubation allows cells touse up residual carbon-energy sources in the 5% serum (e.g., 5% serum would contribute about 0.35 mM glucose, plus lipids, and amino acids) andminimizes the background color in the negative control wells which have no added biochemical substrate. Furthermore, the 40-hour incubationallows cells to transition their metabolism to use the various substrates provided in the wells. After incubation, we added 10 mL of 6-foldconcentrated Redox Dye Mix MA (Biolog, Hayward, CA) to HepG2/C3A, HepG2, COLO 205, A549, PC-3 cells whereas Redox Dye Mix MB was added toHL-60 and CCRF-CEM cells. Plates were incubated at 37uC under air to assess dye reduction for 5 hr (Redox Dye Mix MA) or 24 hr (Redox Dye Mix MB)and then photographed. Negative controls (red boxes) have no substrate in the well. Wells containing D-glucose (green boxes) serve as a positivecontrol. Additional differentially metabolized substrates (blue boxes) for each cell line are described in the text.doi:10.1371/journal.pone.0018147.g001



C). Further, the quantification of ATP levels in these wells, after

three days in cell culture, shows consistency with our method

(Figure 3E). Thus, the ability to produce energy from a substrate

corresponds with increased survival, even if only temporarily.

One possible exception is pectin which may slow cell death by a

mechanism other than energy production.

Metabolic profiling of adipocytesWe sought to apply this technology to a cellular model system

representing a highly metabolically active state. We reasoned that

adipocyte biology would be well-suited for nutrient-response

profiling, since we could compare white and brown adipocytes,

which have very different physiological roles, as well as analyze the

cell-state changes that must occur during differentiation of

preadipocyte fibroblasts. Therefore, we profiled the mouse cell

line 3T3-L1, which has been used for decades as a model of white

fat [28], and an immortalized brown preadipocyte cell line [29], in

both undifferentiated and differentiated states. This experimental

design enabled us to focus on four major comparisons: brown

preadipocytes with brown adipocytes, white preadipocytes with

white adipocytes, brown with white preadipocytes, and brown

with white adipocytes.

In order to quantitatively compare each state in a rapid and

systematic manner, we developed a scoring system based on the

optical density of each well at 590 nm, normalized to negative-

control wells. As expected, white and brown preadipocytes and

adipocytes have different metabolic profiles as demonstrated with

this dye-reduction assay (Figure 4). In order to quantify these

comparisons, we also calculated a comparison score (CS) as the

absolute value of the ratio between two states being compared at a

particular time point (Figure S4). Quantitatively, the greatest

difference between brown and white preadipocytes was in their

metabolism of glycogen, with brown preadipocytes showing faster

metabolism (Figure S4 and Figure S5). We also observed much

stronger metabolism of the three sugar phosphates (fructose-6-

phosphate, glucose-1-phosphate, and glucose-6-phosphate) by

brown preadipocytes (Figure 4). Interestingly, the metabolism of

these four nutrients decreased during brown adipogenesis.

We also sought to identify differences in substrate metabolism

that might occur during adipocyte differentiation (Figure 4).

Surprisingly, all changes that occurred in brown adipocytes after

differentiation were decreases in metabolism. Like 3T3-L1

differentiation, brown adipocyte differentiation resulted in a

decreased metabolism of dextrin and butyric acid. On the other

hand, after differentiation, there were more substrates for which

dye reduction increased in white and not brown adipocytes.

Acetoacetic acid and succinamic acid resulted in some the greatest

increases in dye reduction. Indeed, for adipocytes, acetoacetic acid

Figure 2. Effect of mitochondrial inhibitors on energy-producing pathways of HepG2/C3A cells. HepG2/C3A cells were washed twicewith serum-free inoculating medium (RPMI-1640 with no phenol red or glucose but containing PS, 0.3 mM glutamine) and resuspended in the samemedium at a density of 400,000 cells/mL with varying concentrations of either FCCP or rotenone. Control cells were incubated with 0.003% DMSO,the solvent for both FCCP and rotenone. These cell suspensions were immediately inoculated into PM-M1 at 50 mL per well. After an 18-hourincubation at 37uC under 5% CO2-95% air, 10 mL of Redox Dye Mix MA was added to each well. After 5 hours with the dye, the plates werephotographed. After the plates were photographed, glucose was added to each well of the plates to a final concentration of 5 mM to assess cellviability. The plates were then incubated overnight and photographed again.doi:10.1371/journal.pone.0018147.g002



consistently produced the strongest dye reduction of any substrate

tested, including D-glucose. Remarkably, all peptides containing

leucine resulted in at least some increase in metabolism after white

adipogenesis, although at a low absolute rate of dye reduction (see

Leu and Leu-Leu, Figure 4). These results indicate that, while

these adipogenic processes may superficially appear to be similar,

each produces a different metabolic response.

Discussion

We have developed a simple colorimetric assay method for

simultaneously measuring multiple energy-producing pathways in cells

and providing a more global perspective of the range and regulation of

multiple energy-producing pathways. This provides a new tool for

researchers wanting to study metabolic pathway activities, with

advantages for measuring in vivo metabolic fluxes. Metabolomic assay

of pool levels are better for detecting the presence of pathways and

detecting the site of pathway blockages, but changes in pathway fluxes

may not result in increases or decreases of pool levels. Another

approach to measuring pathway fluxes using quantitative isotope

tracking, relies on detailed and accurate knowledge of the pathways

present and active. This new colorimetric PM assay is not only

extremely simple to perform, but it does not require any prior

knowledge of the energy pathways present and active in a cell line.

Each well in the PM assay panel provides both qualitative and

quantitative data on the potential of a cell line to metabolize a

biochemical substrate and produce energy, presumably as NADH.

We have provided evidence that glucose is not the only relevant

energy source used by colon cells, liver cells, and adipocytes. This

is likely to be the case for other cells as well. Muscle cells [30] and

brown fat cells [31] are known to actively metabolize fatty acids.

During periods of exercise, blood concentrations of glycerol (20-

120 mM), pyruvic acid (40-180 mM), and lactic acid (0.5–5 mM),

rise to significant levels [26,32]. To prevent the accumulation of

toxic levels of acids in muscles, lactic acid is converted via pyruvic

acid to alanine, which is subsequently metabolized, primarily by

the liver [33,34]. The dominant view has been that alanine is

primarily converted to glucose rather than oxidized to CO2. Our

survey of seven cell lines confirms that liver cells are especially

proficient in metabolism of alanine, but also shows that this amino

acid can be used to produce energy. These results are consistent

with metabolomic profiling methods [21], showing that this simple

method provides an independent, flux-based measurement of

cellular metabolism. Under nutritional stress conditions such as

starvation, acetoacetic acid and D-b-hydroxy-butyric acid can

become principal energy sources for cells [35]. Further, under

long-term calorie-restricted diets, pyruvate may play a key role

both as a fuel for mitochondrial energy production and as a

regulator of the SIRT1 protein in hepatocytes [36]. This evidence

suggests the importance of broadening the study of energy

metabolism beyond glucose.

Liver cells, enteroendocrine cells, and adipocytes seem partic-

ularly important to study in the context of multiple energy-

metabolism assays, obesity, and diabetes. The liver plays an

essential physiological role in helping to maintain a constant

supply of glucose and other substrates to the rest of body. Our

method confirms previous reports showing the toxic effect of

sodium butyrate on HepG2 cells [27]. Enteroendocrine cells of

various types are present in the gut epithelium, sensing certain

substrates in the lumen (e.g., methyl-pyruvate, arginine, peptides)

and releasing incretin hormones such as glucose-dependent

insulinotropic peptide, glucagon-like peptide 1, ghrelin, and

Figure 3. Assay of growth, stasis, or death under different nutritional conditions. (A) HepG2/C3A were suspended at 50,000 cells per mL inserum-free RPMI-1640 medium that lacked phenol red and glucose, but contained PS and 4 mM glutamine. Cells were dispensed into six PM-M1microplates at 50 mL per well (2,500 cells per well) and incubated at 37uC under 5% CO2-95% air. On six consecutive days, starting on day 0 when thecells were plated, 10 mL of Redox Dye Mix MA containing 30 mM glucose (a 6-fold concentrate) was added to one microplate, the plate was sealedwith tape (LMT-SEAL-EX, Phenix Research Products, Hayward, CA) to prevent CO2 loss, and incubated at 37uC in an OmniLog instrument (Biolog,Hayward, CA) for 18 hours to kinetically record formation of purple formazan in the wells on days 0 (red) 1 (yellow) 2 (green) 3, (blue) 4 (purple) and 5(black). Substrates resulting in distinguishable responses are indicated: cell proliferation (green boxes), cell stasis (blue boxes), slow cell death (redboxes), rapid cell death (black boxes). In these kinetic graphs, the X-axis is time and the Y-axis is OmniLog color density units. Additional details on thetesting protocol, OmniLog instrument, and kinetic assay reproducibility are provided in Figure S3. (B) Microscopic image of HepG2 in a negative-control well after three days in culture. (C) Microscopic image of HepG2 in a butyrate-containing well after three days in culture. (D) Microscopicimage of HepG2 in a D-glucose-containing well after three days in culture. (E) Quantification of ATP levels in HepG2 cells after three days in culture,using a luciferase-based method. Scale bars = 100 mm.doi:10.1371/journal.pone.0018147.g003



cholecystokinin, which affect appetite, metabolism, and energy

storage by a variety of mechanisms [37,38]. Adipocytes not only

manage the storage of excess energy in the body, but also produce

and release a number of adipokine-signaling hormones [39].

We observed several significant differences in dye-reduction

profiles between white and brown adipocytes. For example, the

metabolism of glycogen was high in brown versus white preadipo-

cytes, but decreased during cellular differentiation. This observation

is consistent with a report that murine brown preadipocytes show a

myogenic transcriptional profile, suggesting that brown and white

fat arise from separate cell lineages [40]. More recently, the

transcription factor PRDM16 has been shown to control cell fate in

mice; overexpression in myoblasts results in a brown fat state, while

loss of expression induces muscle differentiation [41]. Another

consistent difference between brown and white preadipocytes was

the elevated metabolism of various sugar phosphates. These results

support previous literature reports, in which brown adipose tissue

was shown to have a 15-fold increase in glucose 6-phosphate

dehydrogenase activity [42]. Our results provide additional

evidence for the relationship between brown preadipocytes and

muscle, and show that this assay technology can be used to examine

similarities between distinct cell types, and to dissect subtle

differences between cell types thought to be similar.

In addition to using this assay technology to examine and

compare metabolic differences in cells from various tissues, it is

also productive to compare isogenic cell lines with specifically-

engineered mutations. One of the most significant aspects of this

work is the metabolic comparison of the nearly isogenic cell lines

HepG2 and HepG2/C3A. The C3A line was selected by its ability

to grow on pyruvate, and our assay showed that increased

pyruvate metabolism was the salient detectable metabolic

phenotype. With this tool, it would be illuminating to examine

changes in global energy-producing metabolism in mammalian

cells with knockouts or activations of key genes, for example those

encoding p53, Foxo3a, SIRT1 [43], ChREBP [44], BAD [45],

LXR [46], PPARd [47], GCN 5, or PGC-1a [48]. The assay

technology could also be used in conjunction with RNAi gene

silencing studies in cell lines or primary cells.

Other areas where metabolic profiling analysis of multiple

energy-producing pathways may lead to advancement are cancer,

nutrition, and aging. For example, there are potential applications

in studying the energy metabolism of non-glucose compounds in

PET imaging in neurology and cancer diagnostics. There is

renewed interest in the Warburg effect [49] and in using it in novel

approaches to killing cancer cells with energy antagonists such as

2-deoxyglucose [50] or Akt inhibitors [51]. Energy metabolism is

also relevant in calorie-restricted longevity and cachexia. This

method provides biologists with a simple tool for precise and

detailed phenotypic analysis of animal cells and, as we have

previously shown with microbial cells [6], enables a wide range of

studies relating genotype to phenotype.

Materials and Methods

Cell cultureAll cell lines were obtained from ATCC (Manassas, VA). Cells

were cultured in an RPMI-1640-based media (without phenol red,

with penicillin/streptomycin and 10% FCS) and incubated at 37uCwith 6.5% CO2. Cells were washed in Dulbecco’s PBS and

resuspended at a density of 400,000 cells/mL in matched medium

Figure 4. Comparison of substrate metabolism in brown and white preadipocytes and adipocytes. Normalized optical-density scoresrepresenting nutrient metabolism, showing the greatest differences between white fat (top) and brown fat (bottom) cells in either anundifferentiated (gray bars) or differentiated (black bars) state. Included are a) wells that cause no change (1, negative control), b) nutrients that arehigh in brown preadipocytes and decrease upon differentiation (2, a-D-glucose-1-phosphate; 3, D-glucose-6-phosphate; 4, D-fructose-6-phosphate; 5,glycogen), c) a similarly behaved nutrient that is high in white fat (6, hexanoic acid), d) nutrients that decrease during differentiation of both cell types(7, dextrin; 8, butyric acid), and e) nutrients that increase upon white fat differentiation (9, L-leucine; 10, Leu-Leu; 11, succinamic acid, 12. acetoaceticacid). The normalized scores shown are reprentative of two independent biological experiments. The error bars represent the error for the six alpha-D-glucose wells in each experiment, which was taken as the largest and most conservative estimate of the error for other nutrients.doi:10.1371/journal.pone.0018147.g004



depleted of carbon-energy sources (no glucose, low glutamine

(0.3 mM), and low FCS (5%)). 50 mL per well of this suspension

(20,000 cells per well) is dispensed into four microplates containing

367 biochemicals that could potentially be metabolized and provide

energy for cells. We found that a 40-hour incubation is optimal for

decreasing the background color in the negative control wells and

increasing the color in various wells with metabolized substrates, to

allow cells to use any remaining carbon-energy sources (e.g., from the

glucose (5% serum would contribute about 0.35 mM glucose), lipids,

glutamine, and other amino acids in the serum), and to adapt the cells

to using the substrate provided in the well. After this incubation,

10 mL of Redox Dye Mix MA (HepG2/C3A, HepG2, COLO 205,

A549, PC-3) or MB (HL-60 and CCRF-CEM) was added, and cells

were incubated to assess dye reduction for 5 hours (Redox Dye Mix

MA) or 24 hours (Redox Dye Mix MB) and photographed.

Effect of mitochondrial inhibitors in HepG2/C3A cellsHepG2/C3A cells were washed twice with serum-free inocu-

lating medium (modified RPMI 1640, with 1X vitamins, 1X salts,

1X amino acids, 0.3 mM glutamine, and no glucose) and

resuspended in the same medium at a density of 400,000 cells/

mL with varying concentrations of either FCCP or rotenone.

Control cells were incubated with 0.003% DMSO, the solvent for

both FCCP and rotenone. These cell suspensions were immedi-

ately inoculated into PM-M1. After an 18-hour incubation, 10 mL

of Redox Dye Mix MA was added to each well. After 5 hours with

the dye, the plates were photographed. After the plates were

photographed, glucose was added to each well of the plates to a

final concentration of 5 mM to assess cell viability. The plates were

then incubated overnight and photographed again.

Assessment of cell proliferation, stasis, or death underdifferent nutritional conditions

HepG2/C3A cells were suspended in inoculating medium with

4 mM glutamine and 1X penicillin/streptomycin, seeded at 2500

cells per well into six PM-M1 microplates, and incubated at 37 C

with CO2. Each day, one microplate was removed and Biolog

Redox Dye MA plus 5 mM glucose was added. The microplate

was then incubated in an OmniLog for 18 hours with purple color

formation data recorded. Cellular ATP levels were measured using

the luciferase-based CellTiterGlo kit (Promega).

Adipocyte cell culture3T3-L1 preadipocytes were grown in Dulbecco’s Modified

Eagle’s Medium (DMEM) supplemented with 10% donor calf

serum and 100 mg/mL penicillin/streptomycin mix in a humidified

atmosphere at 37C with 5% CO2. Immortalized brown preadipo-

cytes were cultured similarly, in media containing 10% fetal bovine

serum (FBS). Adipocytes were differentiated prior to incubation in

PM-M microplates, such that .90% of cells contained lipid

droplets. 3T3-L1 cells were differentiated by culturing 48 hours in

DMEM with 10% FBS, 170 nM insulin, 2 mg/mL dexamethasone,

and 250 mM isobutylmethylxanthine (IBMX), followed by changing

the media every 48 hours to DMEM containing FBS and insulin.

Brown preadipocytes were differentiated by culturing 48 hours in

DMEM with 10% FBS, 20 nM insulin, 250 mM indomethacin,

1 nM triiodothyronine (T3), 2 mg/mL dexamethasone, and

250 mM IBMX, followed by changing the media every 48 hours

to DMEM containing FBS, insulin, and T3.

Supporting Information

Figure S1 A549 lung cells were cultured as described inMaterials and Methods, suspended in RPMI-1640 me-

dium without phenol red, and 50 mL of cell suspensionwas added to each column of wells at 2-fold dilutions(right to left) in the same medium. After 4 hours, 10 mL of 4

different redox dye chemistries were added to a final tetrazolium

concentration of 500 mM.

(TIF)

Figure S2 HepG2/C3A liver cells were cultured inPhenotype MicroArray PM-M1 for 40 hours and assayedfor dye reduction, as described in Materials andMethods. Four different redox dye chemistries were used but

in all cases, the concentration of the tetrazolium dye was 500 mM.

(TIF)

Figure S3 PM Assay with kinetics of dye reductionrecorded by the OmniLog instrument. This figure shows the

steps in running a PMM assay. Assays are initiated by adding a cell

suspension to the wells, followed by addition of a redox dye. The

PMM microplates are placed inside of the OmniLog instrument,

which incubates the microplates and reads the color formation in

wells with an internal color video camera every 15 minutes. The

OmniLog software then generates kinetic graphs of color versus time

for all wells. These assays have very high reproducibility. In the

example shown, HME human breast cells (a generous gift of Dr.

Chris Torrance, Horizon Discovery Ltd., Cambridge, UK) were

tested using the standard protocol, but without serum and with the

glutamine concentration increased to 2 mM. The graph shows a

triplicate repeat of the assay with runs shown in green, red, and black.

(TIF)

Figure S4 Comparison of substrate metabolism in brownand white preadipocytes and adipocytes. All adipoctye cell

lines were assayed with Redox Dye Mix MB. (A) Substrates resulting

in the greatest difference in comparison score (CS) at 24 hours

between immortalized brown preadipocytes (blue lines) and 3T3-L1

white preadipocytes (green lines). To simplify the analysis, we only

considered the CS at the 24-hour time point measurement,

reasoning that since the accumulation of signal only increases over

time, we would detect the most stable differences at this time, rather

than only detecting kinetic changes in absorbance. (B) Substrates

resulting in the greatest difference in CS at 24 hours between fully

differentiated brown (blue lines) and 3T3-L1 white adipocytes (green

lines). Graphs are depicted as the normalized change in absorbance

(DDAbs), using the zero-hour time point as baseline.

(TIF)

Figure S5 Analysis of effects of adipocyte differentiationon substrate metabolism. (A) Substrates resulting in the

greatest difference in comparison score (CS) at 24 hours between

undifferentiated 3T3-L1 preadipocytes (blue lines) and 3T3-L1

white adipocytes (green lines). (B) Substrates resulting in the

greatest difference in CS at 24 hours between undifferentiated

brown preadipocytes (blue lines) and brown adipocytes (green

lines). Graphs are depicted as the normalized change in

absorbance.

(TIF)

Table S1 Plate maps of Phenotype MicroArray Micro-Plates PM-M1 through -M4.

(DOC)

Author Contributions

Conceived and designed the experiments: BB XHL PAC BKW. Performed

the experiments: MS RHH SN XHL BKW. Analyzed the data: MS RHH

SN XHL PAC BKW. Wrote the paper: BB PAC BKW.



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Bochner et al.

Supporting Information

Assay of the multiple energy-producing pathways of

mammalian cells

Barry R. Bochner1, Mark Siri1†, Richard H. Huang1‡, Shawn Noble1, Xiang-He Lei1, Paul A.

Clemons2, Bridget K. Wagner2

1 Biolog, Inc., 21124 Cabot Boulevard, Hayward, CA 94545

2 Chemical Biology Program, Broad Institute of Harvard and MIT, 7 Cambridge Center,

Cambridge, MA 02142

† Current address: University of Colorado, Denver School of Pharmacy, 12631 E. 17th Avenue,

Aurora, CO 80045

‡ Current address: Agilent Technologies, 5301 Stevens Creek Blvd, Santa Clara, CA 95051

* Corresponding author email: [email protected].

25

mailto:[email protected]

Bochner et al.

Figure S1. A549 lung cells were cultured as described in Materials and Methods, suspended in

RPMI-1640 medium without phenol red, and 50 μL of cell suspension was added to each

column of wells at 2-fold dilutions (right to left) in the same medium. After 4 hours, 10 μL of 4

different redox dye chemistries were added to a final tetrazolium concentration of 500 μM.

26

Bochner et al.

Figure S2. HepG2/C3A liver cells were cultured in Phenotype MicroArray PM-M1 for 40 hours

and assayed for dye reduction, as described in Materials and Methods. Four different redox dye

chemistries were used but in all cases, the concentration of the tetrazolium dye was 500 μM.

27

Bochner et al.

Figure S3. PM Assay with kinetics of dye reduction recorded by the OmniLog instrument.

This figure shows the steps in running a PMM assay. Assays are initiated by adding a cell

suspension to the wells, followed by addition of a redox dye. The PMM microplates are placed

inside of the OmniLog instrument, which incubates the microplates and reads the color

formation in wells with an internal color video camera every 15 minutes. The OmniLog software

then generates kinetic graphs of color versus time for all wells. These assays have very high

reproducibility. In the example shown, HME human breast cells (a generous gift of Dr. Chris

Torrance, Horizon Discovery Ltd., Cambridge, UK) were tested using the standard protocol, but

without serum and with the glutamine concentration increased to 2 mM. The graph shows a

triplicate repeat of the assay with runs shown in green, red, and black.

OmniLog PM System

Holds 50 microplates at a set temperature

and measures color formation at 15-minute intervals

Kinetic assay readout for up to 4,800 wells in a

single experiment

Highly reproducible kineticsCVs typically < 10%

PM assays initiated by adding cells to wells

Add 50 μl of cells

Add 10 μl of redox dye

28

Bochner et al.

Figure S4. Comparison of substrate metabolism in brown and white preadipocytes and

adipocytes. All adipoctye cell lines were assayed with Redox Dye Mix MB. (A) Substrates

resulting in the greatest difference in comparison score (CS) at 24 hours between immortalized

brown preadipocytes (blue lines) and 3T3-L1 white preadipocytes (green lines). To simplify the

analysis, we only considered the CS at the 24-hour time point measurement, reasoning that

since the accumulation of signal only increases over time, we would detect the most stable

differences at this time, rather than only detecting kinetic changes in absorbance. (B)

Substrates resulting in the greatest difference in CS at 24 hours between fully differentiated

brown (blue lines) and 3T3-L1 white adipocytes (green lines). Graphs are depicted as the

normalized change in absorbance (ΔΔAbs), using the zero-hour time point as baseline.

29

Bochner et al.

Figure S5. Analysis of effects of adipocyte differentiation on substrate metabolism. (A)

Substrates resulting in the greatest difference in comparison score (CS) at 24 hours between

undifferentiated 3T3-L1 preadipocytes (blue lines) and 3T3-L1 white adipocytes (green lines).

(B) Substrates resulting in the greatest difference in CS at 24 hours between undifferentiated

brown preadipocytes (blue lines) and brown adipocytes (green lines). Graphs are depicted as

the normalized change in absorbance.

30

Bochner et al.

Table S1. Plate maps of Phenotype MicroArray MicroPlates PM-M1 through -M4 PM-M1 MicroPlate™ - carbon-energy source assays A1 Negative Control

A2 Negative Control

A3 Negative Control

A4 -Cyclodextrin

A5 Dextrin

A6 Glycogen

A7 Maltitol

A8 Maltotriose

A9 D-Maltose

A10 D-Trehalose

A11 D-Cellobiose

A12 -Gentiobiose

B1 D-Glucose-6-Phosphate

B2 -D-Glucose-1-Phosphate

B3 L-Glucose

B4 -D-Glucose

B5 -D-Glucose

B6 -D-Glucose

B7 3-O-Methyl-D-Glucose

B8 -Methyl-D-Glucoside

B9 -Methyl-D-Glucoside

B10 D-Salicin

B11 D-Sorbitol

B12 N-Acetyl-D-Glucosamine

C1 D-Glucosaminic Acid

C2 D-Glucuronic Acid

C3 Chondroitin-6-Sulfate

C4 Mannan

C5 D-Mannose

C6 -Methyl-D-Mannoside

C7 D-Mannitol

C8 N-Acetyl--D-Mannosamine

C9 D-Melezitose

C10 Sucrose

C11 Palatinose

C12 D-Turanose

D1 D-Tagatose

D2 L-Sorbose

D3 L-Rhamnose

D4 L-Fucose

D5 D-Fucose

D6 D-Fructose-6-Phosphate

D7 D-Fructose

D8 Stachyose

D9 D-Raffinose

D10 D-Lactitol

D11 Lactulose

D12 -D-Lactose

E1 Melibionic Acid

E2 D-Melibiose

E3 D-Galactose

E4 -Methyl-D-Galactoside

E5 -Methyl-D-Galactoside

E6N-Acetyl-Neuraminic Acid

E7 Pectin

E8 Sedoheptulosan

E9 Thymidine

E10 Uridine

E11 Adenosine

E12 Inosine

F1 Adonitol

F2 L- Arabinose

F3 D-Arabinose

F4 -Methyl-D-Xylopyranoside

F5 Xylitol

F6 Myo-Inositol

F7 Meso-Erythritol

F8Propylene glycol

F9 Ethanolamine

F10 D,L- -Glycerol-Phosphate

F11 Glycerol

F12 Citric Acid

G1 Tricarballylic Acid

G2 D,L-Lactic Acid

G3 Methyl D-lactate

G4 Methyl pyruvate

G5 Pyruvic Acid

G6 -Keto-Glutaric Acid

G7Succinamic Acid

G8 Succinic Acid

G9 Mono-Methyl Succinate

G10 L-Malic Acid

G11 D-Malic Acid

G12 Meso-Tartaric Acid

H1 Acetoacetic Acid (a)

H2 -Amino-N-Butyric Acid

H3 -Keto- Butyric Acid

H4 -Hydroxy-Butyric Acid

H5 D,L--Hydroxy-Butyric Acid

H6 -Hydroxy-Butyric Acid

H7 Butyric Acid

H8 2,3-Butanediol

H9 3-Hydroxy-2-Butanone

H10 Propionic Acid

H11 Acetic Acid

H12 Hexanoic Acid

PM-M2 MicroPlate™ - carbon-energy and nitrogen source assays A1 Negative Control

A2 Negative Control

A3 Negative Control

A4 Tween 20

A5 Tween 40

A6 Tween 80

A7 Gelatin

A8 L-Alaninamide

A9 L-Alanine

A10 D-Alanine

A11 L-Arginine

A12 L-Asparagine

B1 L-Aspartic Acid

B2 D-Aspartic Acid

B3 L-Glutamic Acid

B4 D-Glutamic Acid

B5 L-Glutamine

B6 Glycine

B7 L-Histidine

B8 L-Homoserine

B9 Hydroxy-L-Proline

B10 L-Isoleucine

B11 L-Leucine

B12 L-Lysine

C1 L-Methionine

C2 L-Ornithine

C3 L-Phenylalanine

C4 L-Proline

C5 L-Serine

C6 D-Serine

C7 L-Threonine

C8 D-Threonine

C9 L-Tryptophan

C10 L-Tyrosine

C11 L-Valine

C12 Ala-Ala

D1 Ala-Arg

D2 Ala-Asn

D3 Ala-Asp

D4 Ala-Glu

D5 Ala-Gln

D6 Ala-Gly

D7 Ala-His

D8 Ala-Ile

D9 Ala-Leu

D10 Ala-Lys

D11 Ala-Met

D12 Ala-Phe

E1 Ala-Pro

E2 Ala-Ser

E3 Ala-Thr

E4 Ala-Trp

E5 Ala-Tyr

E6 Ala-Val

E7 Arg-Ala (b)

E8 Arg-Arg (b)

E9 Arg-Asp

E10 Arg-Gln

E11 Arg-Glu

E12 Arg-Ile (b)

F1 Arg-Leu (b)

F2 Arg-Lys (b)

F3 Arg-Met (b)

F4 Arg-Phe (b)

F5 Arg-Ser (b)

F6 Arg-Trp

F7 Arg-Tyr (b)

F8 Arg-Val (b)

F9 Asn-Glu

F10 Asn-Val

F11 Asp-Ala

F12 Asp-Asp

G1 Asp-Glu

G2 Asp-Gln

G3 Asp-Gly

G4 Asp-Leu

G5 Asp-Lys

G6 Asp-Phe

G7 Asp-Trp

G8 Asp-Val

G9 Glu-Ala

G10 Glu-Asp

G11 Glu-Glu

G12 Glu-Gly

H1 Glu-Ser

H2 Glu-Trp

H3 Glu-Tyr

H4 Glu-Val

H5 Gln-Glu

H6 Gln-Gln

H7 Gln-Gly

H8 Gly-Ala

H9 Gly-Arg

H10 Gly-Asn

H11 Gly-Asp

H12 -D-Glucose

31

Bochner et al.

32


A2 Negative Control

A3 Negative Control

A4 Gly-Gly

A5 Gly-His

A6 Gly-Ile

A7 Gly-Leu

A8 Gly-Lys

A9 Gly-Met

A10 Gly-Phe

A11 Gly-Pro

A12 Gly-Ser

B1 Gly-Thr

B2 Gly-Trp

B3 Gly-Tyr

B4 Gly-Val

B5 His-Ala

B6 His-Asp

B7 His-Glu

B8 His-Gly

B9 His-His (c)

B10 His-Leu

B11 His-Lys (d)

B12 His-Met

C1 His-Pro

C2 His-Ser

C3 His-Trp

C4 His-Tyr

C5 His-Val

C6 Ile-Ala

C7 Ile-Arg (b)

C8 Ile-Asn

C9 Ile-Gln

C10 Ile-Gly

C11 Ile-His

C12 Ile-Ile

D1 Ile-Leu

D2 Ile-Met

D3 Ile-Phe

D4 Ile-Pro

D5 Ile-Ser

D6 Ile-Trp

D7 Ile-Tyr

D8 Ile-Val

D9 Leu-Ala

D10 Leu-Arg (b)

D11 Leu-Asn

D12 Leu-Asp

E1 Leu-Glu

E2 Leu-Gly

E3 Leu-His

E4 Leu-Ile

E5 Leu-Leu

E6 Leu-Met

E7 Leu-Phe

E8 Leu-Pro

E9 Leu-Ser

E10 Leu-Trp

E11 Leu-Tyr

E12 Leu-Val

F1 Lys-Ala (d)

F2 Lys-Arg (b)

F3 Lys-Asp

F4 Lys-Glu

F5 Lys-Gly

F6 Lys-Ile (b)

F7 Lys-Leu (b)

F8 Lys-Lys

F9 Lys-Met (e)

F10 Lys-Phe

F11 Lys-Pro

F12 Lys-Ser

G1 Lys-Thr

G2 Lys-Trp (b)

G3 Lys-Tyr (b)

G4 Lys-Val (d)

G5 Met-Arg (b)

G6 Met-Asp

G7 Met-Gln

G8 Met-Glu

G9 Met-Gly

G10 Met-His

G11 Met-Ile

G12 Met-Leu

H1 Met-Lys (e)

H2 Met-Met

H3 Met-Phe

H4 Met-Pro

H5 Met-Thr

H6 Met-Trp

H7 Met-Tyr

H8 Met-Val

H9 Phe-Ala

H10 Phe-Asp

H11 Phe-Glu

H12 -D-Glucose


A2 Negative Control

A3 Negative Control

A4 Phe-Gly

A5 Phe-Ile

A6 Phe-Met

A7 Phe-Phe

A8 Phe-Pro

A9 Phe-Ser

A10 Phe-Trp

A11 Phe-Tyr

A12 Phe-Val

B1 Pro-Ala

B2 Pro-Arg (b)

B3 Pro-Asn

B4 Pro-Asp

B5 Pro-Glu

B6 Pro-Gln

B7 Pro-Gly

B8 Pro-Hyp

B9 Pro-Ile

B10 Pro-Leu

B11 Pro-Lys (b)

B12 Pro-Phe

C1 Pro-Pro

C2 Pro-Ser

C3 Pro-Trp

C4 Pro-Tyr

C5 Pro-Val

C6 Ser-Ala

C7 Ser-Asn

C8 Ser-Asp

C9 Ser-Glu

C10 Ser-Gln

C11 Ser-Gly

C12 Ser-His (b)

D1 Ser-Leu

D2 Ser-Met

D3 Ser-Phe

D4 Ser-Pro

D5 Ser-Ser

D6 Ser-Tyr

D7 Ser-Val

D8 Thr-Ala

D9 Thr-Arg (f)

D10 Thr-Asp

D11 Thr-Glu

D12 Thr-Gln

E1 Thr-Gly

E2 Thr-Leu

E3 Thr-Met

E4 Thr-Phe

E5 Thr-Pro

E6 Thr-Ser

E7 Trp-Ala

E8 Trp-Arg

E9 Trp-Asp

E10 Trp-Glu

E11 Trp-Gly

E12 Trp-Leu

F1 Trp-Lys (e)

F2 Trp-Phe

F3 Trp-Ser

F4 Trp-Trp

F5 Trp-Tyr

F6 Trp-Val

F7 Tyr-Ala

F8 Tyr-Gln

F9 Tyr-Glu

F10 Tyr-Gly

F11 Tyr-His

F12 Tyr-Ile

G1 Tyr-Leu

G2 Tyr-Lys

G3 Tyr-Phe

G4 Tyr-Trp

G5 Tyr-Tyr

G6 Tyr-Val

G7 Val-Ala

G8 Val-Arg

G9 Val-Asn

G10 Val-Asp

G11 Val-Glu

G12 Val-Gln

H1 Val-Gly

H2 Val-His

H3 Val-Ile

H4 Val-Leu

H5 Val-Lys

H6 Val-Met

H7 Val-Phe

H8 Val-Pro

H9 Val-Ser

H10 Val-Tyr

H11 Val-Val

H12 -D-Glucose

assay of the multiple energy-producing pathways of mammalian … · 2020. 5. 7. · glucose, animal...

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