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\begin{document}

\title{Effect of Nutrient Metabolism on Cartilaginous Tissue Formation}



\author[1]{Roberto Tarantino}%
\author[1]{Loraine Chiu}%
\author[2]{Joanna Weber}%
\author[3]{Yat Tse}%
\author[3]{Davide Bardana}%
\author[3]{Stephen Pang}%
\author[1]{Stephen Waldman}%
\affil[1]{Ryerson University}%
\affil[2]{St Michael's Hospital Li Ka Shing Knowledge Institute}%
\affil[3]{Queen's University}%


\vspace{-1em}



  
  \date{June 18, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
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\selectlanguage{english}
\begin{abstract}
Despite the potential of tissue engineering approaches for cartilage
repair, a major shortcoming is the low biosynthetic response of
chondrocytes. While different strategies have been investigated to
upregulate tissue formation, a novel approach may be to control nutrient
metabolism. Although known for their anaerobic metabolism of glucose,
chondrocytes are more synthetically active when cultured under
conditions that elicit mixed aerobic-anaerobic metabolism. Here, we
postulate this metabolic switch induces hypoxia inducible factor 1\selectlanguage{greek}α
\selectlanguage{english}(HIF-1\selectlanguage{greek}α\selectlanguage{english}) signaling leading to improved tissue growth. Transition to
different metabolic states can result in the pooling of intracellular
metabolites, several of which can stabilize HIF-1\selectlanguage{greek}α \selectlanguage{english}by interfering with
proline-hydroxylase-2 (PHD2). Chondrocytes cultured under increased
media availability accelerated tissue deposition (2.2 to 3.5-fold) with
the greatest effect occurring at intermediate volumes (2 mL/106 cells).
Under higher media volumes, metabolism switched from anaerobic to mixed
aerobic-anaerobic. At and beyond this transition, maximal changes in
PHD2 activity (- 45\%), HIF-1\selectlanguage{greek}α \selectlanguage{english}protein expression (8-fold increase), and
HIF-1 gene target expression were observed (2.0 to 2.7-fold increase).
Loss-of-function studies using YC-1 (to degrade HIF-1\selectlanguage{greek}α\selectlanguage{english}) confirmed the
involvement of HIF-1 signaling under these conditions. Lastly, targeted
metabolomic studies of glucose metabolites (14 in total) revealed that
both intracellular lactate and succinate correlated with PHD2 activity.
Although both metabolites can inhibit PHD2, this effect can most likely
be attributed to lactate as succinate was only present in trace amounts.
However, addition work (e.g., 13C flux analyses) are required to confirm
this assertion. Nevertheless, by harnessing this newly identified
metabolic switch, functional engineered cartilage implants may be
developed without the need for sophisticated methods which would allow
for improved translation into the clinical realm.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Articular cartilage has a limited repair capacity (Hunziker, 1999)
leaving it susceptible to damage from trauma or diseases such as
osteoarthritis (OA). Although total joint arthroplasty is currently the
standard-of-care with generally good clinical outcomes, this technique
has limited function and longevity in the younger population. Therefore,
recent efforts have focused on developing biological-based approaches
for cartilage repair. One such promising approach is defect resurfacing
with engineered cartilage (Waldman \emph{et al.} , 2002). While much
progress has been made, it still has proven difficult to produce tissue
suitable for the repair of clinically-sized defects (2 --
6~cm\textsuperscript{2}) (Brittberg \emph{et al.} , 1994). One of the
major shortcomings of most cartilage tissue engineering approaches is
the generally low accumulation of tissue constituents (Buschmann et al.,
1992; Vunjak-Novakovic et al., 1999; Waldman \emph{et al.} , 2002). To
address this challenge, several strategies have been investigated, such
as: growth factor stimulation (Chen \emph{et al.} , 2014; Lam \emph{et
al.} , 2015), gene therapy (Chen \emph{et al.} , 2014), mechanical
stimulation (Waldman \emph{et al.} , 2003), and bioreactor cultivation
(Khan \emph{et al.} , 2009). While each strategy can accelerate tissue
formation, these approaches either rely on use of overly sophisticated
methods and/or suffer from off-target effects, thereby requiring
substantial efforts to implement or optimize.

An alternative and straightforward approach may be to control nutrient
metabolism. Several studies have demonstrated that increased nutrient
availability (primarily by increasing media volume) can improve
cartilaginous tissue growth (Mauck \emph{et al.} , 2003; Heywood
\emph{et al.} , 2006; Khan \emph{et al.} , 2009; Oze \emph{et al.} ,
2012). While these studies did not identify a particular mechanism, this
effect may be due to resultant changes in glucose metabolism (Oze
\emph{et al.} , 2012). Chondrocytes are known for their anaerobic
metabolism of glucose (Khan \emph{et al.} , 2009), even in the presence
of oxygen (Warburg-like effect) (Lane \emph{et al.} , 1977; Suits
\emph{et al.} , 2008). After uptake, glucose is primarily metabolized
through the glycolytic and fermentation pathways resulting in the
release of lactate. The aerobic pathway is typically not well utilized
and little of the pyruvate generated from glycolysis is metabolized
through the tricarboxylic acid (TCA) cycle (Lane \emph{et al.} , 1977).
Interestingly however, chondrocytes tend to synthesize more
extracellular matrix (ECM) when cultured under conditions that elicit a
switch in metabolism from anaerobic to mixed aerobic-anaerobic
metabolism (Lane \emph{et al.} , 1977; Obradovic \emph{et al.} , 1999;
Khan \emph{et al.} , 2009). We postulate that this metabolic switch may
be directed by alterations in hypoxia inducible factor 1\selectlanguage{greek}α \selectlanguage{english}(HIF-1\selectlanguage{greek}α\selectlanguage{english})
signaling. The transition to different metabolic states can result in
the pooling of intracellular metabolites, several of which have been
shown to stabilize HIF-1\selectlanguage{greek}α \selectlanguage{english}by interfering with proline-hydroxylase-2
(PHD2) (Lu \emph{et al.} , 2002; Kim \emph{et al.} , 2010; Ren \emph{et
al.} , 2011; De Saedeleer \emph{et al.} , 2012; Bailey \& Nathan, 2018);
the enzyme responsible for initiating HIF-1\selectlanguage{greek}α \selectlanguage{english}degradation in the presence
of oxygen. For chondrocytes, this pseudo-hypoxic state (hypoxic gene
expression in the absence of hypoxia) is especially important as the
target genes of HIF-1 affect both chondrogenesis and cartilage
homeostasis (Goldring \& Marcu, 2009; Dengler \emph{et al.} , 2014).
Thus, the purpose of this study is to investigate the effect of
increasing nutrient availability on glucose metabolism, HIF-1 signaling,
and resultant tissue formation by primary articular chondrocytes.

\textbf{Methods}

Chondrocyte Isolation and Cell Culture

Full-thickness articular cartilage was aseptically harvested from the
metacarpal-phalangeal joints of skeletally-mature bovine (obtained fresh
from a local slaughterhouse; 20-24 months of age) to isolate primary
chondrocytes by enzymatic digestion (Waldman \emph{et al.} , 2002).
Briefly, cartilage slices were incubated in protease (0.5\% w/v) for 1
hour followed by 18 hours in collagenase A (0.15\% w/v) in Ham's F-12
media. For each isolation, tissue slices from at least two animals were
pooled together to achieve adequate cell numbers. Viable cells
(\textgreater{} 90\%; by trypan blue dye exclusion) were seeded on
collagen II-coated Millicell filters (10 mm dia.; Millipore) in 3D high
density culture (2 x 10\textsuperscript{6} cells/filter or 25,000
cells/mm\textsuperscript{2}) (Kaupp \& Waldman, 2008) and maintained in
Ham's F12 media containing 10 mM glucose and supplemented with 20\% FBS,
100~\selectlanguage{greek}µ\selectlanguage{english}g/mL ascorbate, 20~mM HEPES, and 1\% (v/v) penicillin/streptomycin.
Cultures were grown under varying volumes of media (1 -- 8 mL or
0.5~--~4~mL/10\textsuperscript{6} cells) and maintained under normoxic
conditions (5\% CO\textsubscript{2}:95\% atmospheric air; 95\% relative
humidity; 37\selectlanguage{ngerman}°C) for 4 weeks with media exchanged every 2-3 days. The
same approach was used for both rabbit chondrocytes (Charles River
Laboratories) and human donor chondrocytes; approved by the University
Animal Care Committee (Queen's University) and Research Ethics Board
(Queen's University), respectively.

Biochemical Quantification of Accumulated Tissue

After harvest, constructs were cut out of the culture inserts, blotted
dry, weighed (wet weight), digested by papain (40~\selectlanguage{greek}µ\selectlanguage{english}g/mL in 20 mM
ammonium acetate, 1 mM EDTA, and 2~mM DTT) for 48 hours at 65\selectlanguage{ngerman}°C, and
stored at -20°C until analysis. Aliquots of the digest were assayed
separately for proteoglycan, collagen and DNA contents. The proteoglycan
content was estimated by quantifying the amount of sulphated
glycosaminoglycans using the dimethylmethylene blue dye binding assay
(Goldberg \& Kolibas, 1990). Collagen content was estimated from the
determination of the hydroxyproline content. Aliquots of the papain
digest were hydrolyzed in 6~N HCl at 110ºC for 18 hours and the
hydroxyproline content of the hydrolyzate was then determined using
chloramine-T/Ehrlich's reagent assay (Woessner, 1961). Collagen content
was estimated assuming hydroxyproline accounts for 10\% of the total
collagen mass in cartilage (Heinegard \emph{et al.} , 1998). The DNA
content was also determined from the papain digest using the Hoechst dye
33258 assay (Kim \emph{et al.} , 1988).

\par\null

Histological and Immunohistochemical Assessment

Representative constructs were harvested and fixed overnight in 4\%
paraformaldehyde (0.1 M phosphate buffer, pH 7.2), processed in graded
solvents and embedded in paraffin. Thin (5 \selectlanguage{greek}µ\selectlanguage{english}m) sections were cut and
mounted on Superfrost slides (Fisher Scientific) and dried for 24 hours
at 37\selectlanguage{ngerman}°C. Sections were stained with safranin-O (proteoglycans) and
sirius red (collagen) or assessed for localization of collagen types I
and II by immunohistochemistry, as described previously (Khan \emph{et
al.} , 2009). Briefly, sections were deparaffinized, rehydrated, and
then treated for antigen retrieval. For collagen I, sections were heated
in citrate buffer (10 mM citric acid, 0.05\% Tween 20; pH 6) at
95-100\textsuperscript{o}C for 20 minutes. For collagen II, sections
were treated with 0.25 units/mL chondroitinase ABC (1 hour) and 0.25
units/mL keratinase (30~minutes) in tris-acetate buffer (40 mM tris
acetate, 1 mM EDTA; pH 8.5) at 37°C. Sections were then blocked with 1\%
bovine serum albumin (BSA) in PBS for 30 minutes at room temperature and
incubated with antibodies against collagen I (Abcam ab90395, 1:100
dilution) or collagen II (Developmental Studies Hybridoma Bank II-II6B3,
1:100 dilution) in 1\% BSA in PBS, at 4°C overnight. Sections were then
incubated with Texas Red-labelled goat anti-mouse secondary antibody
(Abcam ab6787, 1:200 dilution in 1\% BSA in PBS) for 2 hours at room
temperature. Sections were counterstained with DAPI mounting medium
(Vector Laboratories), and imaged (ZOE Fluorescent Cell Imager).
Negative controls were performed by replacing primary antibodies with
1\% BSA in PBS, with no staining detected.

Glucose Metabolism

Extracellular metabolites (glucose, lactate, O\textsubscript{2},
CO\textsubscript{2}) and pH were determined in the conditioned media
obtained from the last exchange cycle (after 48 hours) of the 4-week
culture period. Glucose and lactate in the media were detected using
enzymatic assays (Lockridge \emph{et al.} , 1972; Blake \& McLean, 1989)
and expressed in terms of consumption or production. Changes in
metabolism were then assessed by determining the yield of
lactate-on-glucose (Y\textsubscript{L/G}; with 2 representing 100\%
anaerobic metabolism) as well as relative changes in
O\textsubscript{2}consumption (qO\textsubscript{2}) and
CO\textsubscript{2} production (qCO\textsubscript{2}), estimated from
pO\textsubscript{2} and pCO\textsubscript{2} levels (Radiometer ABL825).
All results were normalized to DNA content.

HIF-1\selectlanguage{greek}α \selectlanguage{english}Stabilization and Function

The resultant effect on PHD2 activity was determined using a
fluorescence-based assay (McNeill \emph{et al.} , 2005) and the HIF-1\selectlanguage{greek}α
\selectlanguage{english}556--574 peptide substrate (containing the PHD2 hydroxylation site;
19-mer fragment; AnaSpec) in cytoplasmic extracts. Resultant effect on
HIF-1\selectlanguage{greek}α \selectlanguage{english}stabilization was then determined by stain-free,
semi-quantitative Western blotting (WB) (Zhu \emph{et al.} , 2009).
Briefly, protein extracts were separated using stain-free, tris/glycine
12\% polyacrylamide gels and imaged before and after transfer to
nitrocellulose and blotting (ChemiDoc; Bio-Rad) to determine expressed
protein levels relative to the total loaded protein in the gel.

Expression of selected gene targets of HIF-1\selectlanguage{greek}α \selectlanguage{english}and chondrogenesis (Table
S2) were determined by real-time quantitative PCR (qPCR)
(Brenner\emph{et al.} , 2014). Briefly, harvested constructs were snap
frozen (liquid N\textsubscript{2}), and total RNA was extracted (RNeasy
Mini Kit; Qiagen) and reversed transcribed (SuperScript III Reverse
Transcriptase; Invitrogen). qPCR was performed using an ABI ViiA PCR
system (ThermoFisher) with the Power SYBR Green PCR Master Mix (Applied
Biosystems) and 18S (ribosomal RNA) as the endogenous (internal) control
(Brenner \emph{et al.} , 2014). PCR primers were constructed using
Primer-BLAST (NCBI) and published mRNA sequences (NIH GenBank).
Expression levels were calculated using the \selectlanguage{greek}ΔΔ\selectlanguage{english}C\textsubscript{T} method.

Loss-of-function studies were also conducted using YC-1 to degrade
HIF-1\selectlanguage{greek}α \selectlanguage{english}(Chun \emph{et al.} , 2001) with the resultant effect on
extracellular matrix synthesis determined by radioisotope incorporation
(Waldman \emph{et al.} , 2003). After 4 weeks of culture, samples were
incubated in YC-1 (10 \selectlanguage{greek}µ\selectlanguage{english}M) for 48 hours in the presence of
{[}\textsuperscript{3}H{]}-proline (to quantify synthesis of collagen)
and {[}\textsuperscript{35}S{]}-sulfate (to quantify synthesis of
proteoglycans) (2.5~\selectlanguage{greek}µ\selectlanguage{english}Ci each isotope; Perkin Elmer). After incubation,
cultures were washed to remove unincorporated isotope and digested in
papain (refer to \emph{Biochemical Quantification of Accumulated Tissue}
) with aliquots used for \selectlanguage{greek}β-\selectlanguage{english}liquid scintillation counting (Beckman
Coulter). Isotope incorporation was expressed relative to DNA content
(refer to \emph{Biochemical Quantification of Accumulated Tissue} ) and
expressed relative to the controls.

Quantification of Intracellular Metabolites

Constructs were also harvested to determine potential correlations
between intracellular metabolites and PHD2 activity. Briefly, harvested
constructs were cut from the culture inserts, snap frozen (liquid
N\textsubscript{2}) and stored at -80\selectlanguage{ngerman}°C until analysis. Using a targeted
metabolomics approach, intracellular metabolites were extracted by
KOH/ethanol (0.3 M KOH in 25\% ethanol), neutralized with glacial acetic
acid, and then quantified by liquid chromatography tandem quadrupole
mass spectrometry (LC/MS/MS) (Luo \emph{et al.} , 2007) (Agilent 1100
HPLC/Sciex Q4000 Mass Spectrometer). A total of 14 metabolites (Table
S1), representative of glycolysis, fermentation, TCA, and pentose
phosphate pathways, were quantified with results expressed relative to
DNA content.

Statistical Analyses

All quantitative results were expressed as mean ± standard error of the
mean (SEM). Collected data were analyzed statistically using SPSS
(version 17) using a one-way ANOVA and the Tukey's post hoc testing for
subsequent pair-wise comparisons. Data were checked prior to performing
statistical tests for both normality (Shapiro-Wilk) and equal-variance
(Levene's). Spearman rank correlation analysis was used to determine
potential correlations between metabolites and PHD2 activity.
Significance for all tests was associated with \emph{p} -values less
than 0.05.

\textbf{Results}

Effect of Nutrient Availability on Tissue Formation

To determine the effect of nutrient availability on cartilaginous tissue
formation, isolated articular chondrocytes were seeded in high-density
3D culture and maintained in varying amounts of media (1 -- 8 mL or
0.5~--~4~mL/10\textsuperscript{6} cells) under normoxic conditions for a
period of 4 weeks. Increasing media availability appeared to
significantly accelerate cartilaginous tissue deposition, as
demonstrated by the changes in construct mass and ECM accumulation
compared to 1 mL control (Figure 1a, Table 1). The observed response was
non-monotonic with intermediate media volumes (4 mL or 2
mL/10\textsuperscript{6} cells) eliciting the greatest effect on both
GAG and collagen deposition (3.5-fold and 2.2-fold increase,
respectively) without associated increases in cellularity (Figure 1a,
Table 1). Histological assessment revealed similar trends with maximal
tissue thickness (\textasciitilde{} 0.5 mm) achieved under intermediate
media volumes. Under all media volumes investigated, there were no
observed changes in phenotype (Figure 1b) with tissue constructs
staining positive for sulphated proteoglycans and collagen. Further
analysis of collagen deposition (by immunohistochemical staining)
indicated that the accumulated ECM was primarily collagen II, with only
sporadic intracellular staining observed for collagen I. Finally,
similar studies with rabbit and human chondrocytes (Figure S1) displayed
strikingly similar trends suggesting this effect is conserved across
different species.

Effect of Nutrient Availability on Glucose Metabolism

To investigate the potential relationship with glucose metabolism,
analyses of extracellular metabolites (glucose, lactate,
O\textsubscript{2}, CO\textsubscript{2}) in the conditioned media
obtained from the final exchange cycle of the culture period were
conducted. Glucose consumption and lactate production (Table 1) followed
similar trends to the tissue formation results, with maximal
consumption/production occurring under intermediate media volumes (Table
1). Under low to intermediate media volumes (1 -- 4 mL) metabolism was
primarily anaerobic as indicated by the high lactate-on-glucose yield
(Y\textsubscript{L/G}) and relatively low magnitude of
O\textsubscript{2} consumption and CO\textsubscript{2} production (Table
1). However, larger media volumes (\textgreater{}~4~mL) appeared to
alter metabolism from primarily anaerobic to mixed aerobic-anaerobic
with a steep decline in Y\textsubscript{L/G} as well as observed
increases in
O\textsubscript{2}/CO\textsubscript{2}consumption/production (Table 1).
Lastly, extracellular pH did not follow a similar trend, but rather
experienced monotonic increases (alkaline) with increasing media volume
(Table 1).

Intersection between Glucose Metabolism and the HIF-1\selectlanguage{greek}α \selectlanguage{english}Pathway

The next series of experiments were aimed at confirming the effect on
HIF-1\selectlanguage{greek}α \selectlanguage{english}signaling by determining the changes in PHD2 enzymatic activity,
HIF-1\selectlanguage{greek}α \selectlanguage{english}protein expression, and the expression of selected HIF-1\selectlanguage{greek}α \selectlanguage{english}target
genes. At, and beyond, the transition from anaerobic to mixed
aerobic-anaerobic metabolism ([?]~4 mL), intracellular pyruvate, PHD2
activity, and HIF-1\selectlanguage{greek}α \selectlanguage{english}protein expression were significantly affected
(Figure 2a). Similar to the tissue formation and glucose metabolism
studies, maximal changes were also observed under intermediate volumes
of media (4 mL) (\emph{PHD2 activity} : -45\%, \selectlanguage{greek}\emph{HIF-1α} : \selectlanguage{english}8-fold
increase) (Figure 2a). Corresponding HIF-1\selectlanguage{greek}α \selectlanguage{english}gene targets (GLUT1, PDK1
and SOX9) were also maximally upregulated under these conditions (2.0-
to 2.5-fold increases) (Figure 2b). Loss-of-function experiments
utilizing YC-1 to degrade HIF-1\selectlanguage{greek}α \selectlanguage{english}paralleled these results, with maximal
inhibition of ECM synthesis occurring at 4~mL (\textasciitilde{}70\%
reduction in collagen and proteoglycan synthesis) (Figure 3). Lastly,
HIF-1\selectlanguage{greek}α \selectlanguage{english}expression (by Western blot) after treatment with YC-1 was not
detectable (data not shown).

A targeted metabolomic approach was undertaken to determine whether
intracellular metabolites of glucose metabolic pathways (glycolysis,
fermentation, TCA, and pentose phosphate pathways) were correlated with
PHD2 activity. Of the 14 intracellular metabolites investigated, only
lactate and succinate appeared to be significantly correlated with PHD2
activity (p\textless{}0.02; Table S3). Both intracellular lactate and
succinate had strong negative correlations with PHD2 activity
(\selectlanguage{greek}ρ\selectlanguage{english}~=~--~0.999 and -- 0.986, respectively) with maximal changes also
observed under intermediate media volumes (4 mL) (\emph{lactate} :
2-fold increase, \emph{succinate} : 1.6-fold increase) (Figure 4).
However, the relative concentrations of these metabolites were
different, with lactate present in substantially higher amounts compared
to succinate (order of 100 vs 0.1 nmol/\selectlanguage{greek}µ\selectlanguage{english}g DNA).

\textbf{Discussion}

This study demonstrates that cartilaginous tissue formation can be
significantly upregulated by controlling nutrient metabolism and that
this response appears to be mediated through resultant changes in HIF-1\selectlanguage{greek}α
\selectlanguage{english}signalling. Chondrocytes, although characteristically described as
anaerobic cells (Khan \emph{et al.} , 2009), appear to switch their
metabolism in response to nutrient availability. Under
low-to-intermediate volumes of media (\textless{} 2
mL/10\textsuperscript{6} cells), chondrocytes display an anaerobic
phenotype. At higher media volumes (\textgreater{} 2
mL/10\textsuperscript{6} cells), glucose uptake increases and metabolism
switches to a mixed aerobic-anaerobic phenotype with the aerobic pathway
appearing to be more utilized with further increases in media volume.
This response is similar to the Crabtree effect --- the phenomenon where
aerobic cells also excrete fermentation products (e.g. ethanol or
lactate) in the presence of oxygen and high external glucose (De Deken,
1966). While several potential mechanisms have been postulated to
explain the Crabtree effect (e.g. catabolite repression, catabolite
inactivation, limited respiratory capacity), recently it has been
explained by the overflow of glucose metabolites caused by the
saturation of TCA cycle capacity (Pronk \emph{et al.} , 1996). Here, we
postulate an inverse response (``\emph{inverse Crabtree effect''} )
where under high glucose availability, increased glucose uptake leads to
the saturation of the fermentation pathway causing metabolite overflow
to the TCA cycle (Figure 5). However, it should be noted that additional
studies to quantify metabolic pathway flux (e.g. \textsuperscript{13}C
flux analyses) are required to confirm this notion.

Previous studies have also shown that increased glucose uptake occurs
under elevated media volumes (Heywood \emph{et al.} , 2006;
Suits\emph{et al.} , 2008) and that metabolic switching can occur in
response to glucose availability (Otte, 1991; Lee \& Urban, 1997;
Heywood\emph{et al.} , 2010; Heywood \emph{et al.} , 2014). Under low
glucose, increases in oxidative phosphorylation have been observed,
providing evidence for another Crabtree-like effect under such
conditions (Otte, 1991; Lee \& Urban, 1997; Heywood \emph{et al.} ,
2010; Heywood \emph{et al.} , 2014). Taken together, this suggests that
chondrocytes may have several different metabolic phenotypes depending
on the availability of glucose (in the presence of oxygen):
predominantly anaerobic under intermediate glucose levels (Warburg-like
effect) and increased aerobic activity under either low or high glucose
levels (Crabtree-like effects).

One important consequence of changes in metabolic phenotype was the
increased biosynthetic response (2.2- to 3.5-fold) observed at the
transition between metabolic states (\textasciitilde{}~2
mL/10\textsuperscript{6} cells). Previous studies have demonstrated that
increased nutrient availability (by media volume) can improve
cartilaginous tissue growth (Mauck \emph{et al.} , 2003; Heywood
\emph{et al.} , 2006; Khan \emph{et al.} , 2009; Oze \emph{et al.} ,
2012) as well as that chondrocytes are more synthetically active under
mixed aerobic-anaerobic metabolism (Lane \emph{et al.} , 1977;
Obradovic\emph{et al.} , 1999; Khan \emph{et al.} , 2009). When cultured
at, or near, the point of transition between anaerobic to mixed
aerobic-anaerobic metabolism, a state of pseudo-hypoxia occurs resulting
in the initiation of HIF-1 signaling leading to increased cartilaginous
tissue formation. This response is believed to manifest as a result of
the pooling of intracellular metabolites during the transition to
different metabolic states, which in turn, can stabilize HIF-1\selectlanguage{greek}α \selectlanguage{english}by
interfering with PHD2 (Lu \emph{et al.} , 2002; Kim \emph{et al.} ,
2010; Ren \emph{et al.} , 2011; De Saedeleer \emph{et al.} , 2012;
Bailey \& Nathan, 2018). Of the 14 metabolites investigated, only
intracellular lactate and succinate were correlated with PHD2 activity.
Both lactate (De Saedeleer \emph{et al.} , 2012) and succinate (Bailey
\& Nathan, 2018) can affect PHD2 enzymatic activity; however, by
different means. Lactate inhibits PHD2 by competing with its substrate
\selectlanguage{greek}α-\selectlanguage{english}ketoglutarate (De Saedeleer \emph{et al.} , 2012) whereas succinate
affects PHD2 activity through product inhibition at high concentrations
(Bailey \& Nathan, 2018). While additional work is needed to determine
the relative contributions of intracellular lactate and succinate pools
on PHD2 activity, most likely this affect can be attributed to lactate
due to observation that succinate was only present in trace amounts.

HIF-1\selectlanguage{greek}α \selectlanguage{english}stabilization occurred primarily at intermediate volumes, leading
to the regulation of hypoxia-induced gene expression (Lu \emph{et al.} ,
2002; Kim \emph{et al.} , 2010; Ren \emph{et al.} , 2011; De
Saedeleer\emph{et al.} , 2012; Bailey \& Nathan, 2018). Although HIF-1
has many target genes, several support chondrogenesis and regulate
cartilage homeostasis (Kim \emph{et al.} , 2010), including glucose
uptake (GLUT1), TCA cycle suppression (PDK1), and chondrogenic
differentiation (SOX9); each of which was upregulated (by 2.0- to
2.7-fold) under these conditions. Lastly, loss of function experiments
using YC-1 (to degrade HIF-1\selectlanguage{greek}α\selectlanguage{english}) confirmed the involvement of the HIF-1\selectlanguage{greek}α
\selectlanguage{english}pathway in these studies. While HIF mediated gene transcription can be
induced by other factors, they most likely do not play as prominent a
role in the current study. HIF-1\selectlanguage{greek}α \selectlanguage{english}can also be regulated by FIH-1 (factor
inhibiting HIF) (Masoud \& Li, 2015). Similarly, in the presence of
oxygen, FIH-1 hydroxylates HIF-1\selectlanguage{greek}α \selectlanguage{english}to prevent interaction with p300 and
blocks transcriptional activation (Masoud \& Li, 2015); however,
intracellular pyruvate does not affect FIH-1 expression (Dalgard
\emph{et al.} , 2004) or its activity (Hewitson \emph{et al.} , 2007).
Additionally, the other known HIF transcription factors (HIF-2\selectlanguage{greek}α, \selectlanguage{english}HIF-3\selectlanguage{greek}α\selectlanguage{english})
are also probably not involved as intracellular pyruvate does not affect
HIF-2\selectlanguage{greek}α \selectlanguage{english}(Ren \emph{et al.} , 2011) and HIF-3\selectlanguage{greek}α \selectlanguage{english}has multiple variants with
different and opposing functions (Duan, 2016). Lastly, while direct
hypoxia has been investigated as an anabolic stimulus for chondrocytes
(Coyle \emph{et al.} , 2009; Yodmuang \emph{et al.} , 2013), conflicting
results have been observed, most likely due to the fact that
chondrocytes require oxygen to a certain degree and prolonged hypoxia
has been definitively shown to inhibit ECM synthesis (Gibson \emph{et
al.} , 2008).

It is also recognized that other factors could potentially contribute to
the observed response. To account for changes in hydrostatic pressure
between cultures of different media volumes, these studies were
conducted using different sized culture plates (i.e. 24-, 12- and 6-well
plates). Estimates of the maximum hydrostatic pressure difference
between conditions were relatively small ([?] 50 Pa) due to the minimal
changes in media height above the cultures ([?] 5~mm). Previous studies
have shown that hydrostatic pressures of several orders of magnitude
higher (kPa to MPa range) are required to elicit changes in ECM
synthesis (anabolic or catabolic) (Elder \& Athanasiou, 2009) indicating
that the potential influences were negligible. Limitations in oxygen
delivery to the cultures can also be a concern with varying culture
volumes (Place \emph{et al.} , 2017). However, the distance from the
cells to the media surface was also accounted for by using different
sized culture plates and held relatively constant across groups (within
5~mm). In addition, as media buffering capacity changes proportionally
with volume, there may have been an influence of extracellular pH.
Chondrocytes are sensitive to pH with relatively small changes
influencing ECM synthesis (Wilkins \& Hall, 1995). However, observed
differences in extracellular pH did not correlate with the changes in
ECM deposition, which was maximal at intermediate media volumes. Lastly,
as the cultures were only evaluated after a 4-week culture period (or
the last 48-hour media exchange cycle), additional studies are required
to determine whether these effects manifest throughout the culture
period.

\textbf{Conclusions}

The results of this study demonstrate that cartilaginous tissue
formation can be upregulated through the control of nutrient metabolism
and that the observed response is mediated through resultant changes in
HIF-1\selectlanguage{greek}α \selectlanguage{english}signalling. By culturing in elevated volumes of media, glucose
uptake by chondrocytes is increased, leading to a change in metabolism
from primarily anaerobic to mixed aerobic-anaerobic (\emph{inverse
Crabtree effect} ). When cultured at the transition between metabolic
states, a pseudo-hypoxic state is induced resulting in HIF-1\selectlanguage{greek}α \selectlanguage{english}mediated
gene transcription and an associated increase in chondrogenesis. These
findings represent a novel, paradigm-shifting approach to develop
functional engineered cartilage implants that can be produced without
sophisticated stimulation methods. The developed methodology is highly
transferable and can be applied to any cartilage tissue engineering
approach. Such methods are attractive as they have fewer regulatory
barriers to aid commercialization efforts, thereby allowing for improved
clinical translation. Additionally, these newly identified metabolic
pathways could potentially provide insights into the mechanisms of
cartilage growth and development. Future avenues of research will
include metabolic modelling (e.g. \textsuperscript{13}C flux analyses)
to provide a framework to control chondrogenesis.

\textbf{Acknowledgements}

Funding for this work was provided by the Canadian Institutes of Health
Research (CIHR).

\textbf{Author Contributions}

Conception and design: RT SDW. Acquisition of data: RT LLYC JFW MYT DDB
SCP.~ Analysis and interpretation of the data: RT LLYC SDW. Obtaining of
funding: SDW. Drafting of the article: RT LLYC SDW. Critical revision of
the article for important intellectual content: JFW MYT DDB SCP. Final
approval of the article: RT LLYC JFW MYT DDB SCP SDW.

\textbf{Conflict of Interest}

None.

\par\null

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\textbf{Figure Captions}

\textbf{Figure 1}

Effect of media volume on tissue formation. (A) Biochemical accumulation
of cartilaginous constituents (GAG, collagen and DNA). (B) Histological
(sulphated proteoglycan stain: \emph{safranin-O} ; collagen
stain:\emph{sirius red} ) and immunohistochemical (collagen I and
collagen II) appearance of the developed tissue constructs. Data
presented as mean \selectlanguage{ngerman}± SEM, normalized to 1~mL control
(n=6/group);\textsuperscript{a}~significantly different
(p\textless{}0.05); all scale bars: 150 \selectlanguage{greek}µ\selectlanguage{english}m.

\textbf{Figure 2}

Effect of media volume on metabolic pathway activity and stabilization
of HIF-1\selectlanguage{greek}α. \selectlanguage{english}(A)~Intracellular pyruvate (n=4/group), PHD2 activity
(n=3/group), and HIF-1\selectlanguage{greek}α \selectlanguage{english}expression (n=3/group). Biochemical data
normalized to 1 mL. (B) Selected gene targets of HIF-1\selectlanguage{greek}α \selectlanguage{english}(SOX9, PDK1,
GLUT1) (n=3/group). qPCR expression calculated using the
\selectlanguage{greek}ΔΔ\selectlanguage{english}C\textsubscript{T} method. Data presented as mean \selectlanguage{ngerman}±
SEM;\textsuperscript{a}~significantly different from 1 mL
(p\textless{}0.05); \textsuperscript{b} significantly different from 1
mL and 2 mL (p\textless{}0.05); \textsuperscript{*}~significantly
different from all other groups (p\textless{}0.05).

\textbf{Figure 3}

Effect of YC-1 on ECM synthesis. 2 mL group was not investigated due to
the general lack of differences from 1 mL. Data presented as mean ± SEM,
normalized to 1 mL control (n=4/group); \textsuperscript{a}significantly
different from no YC-1 control (p\textless{}0.05).

\textbf{Figure 4}

Effect of media volume on intracellular lactate and succinate. Data
presented as mean ± SEM, normalized to 1 mL control
(n=4/group).\textsuperscript{a}~significantly different from 1 mL
(p\textless{}0.05).

\textbf{Figure 5}

Proposed mechanism illustrating the intersection between glucose
metabolism and the HIF-1\selectlanguage{greek}α \selectlanguage{english}pathway. At the transition from anaerobic to
mixed anaerobic-aerobic metabolism, intracellular lactate concentration
is maximal. In the presence of oxygen, the accumulation of lactate
stabilizes the transcription factor HIF-1\selectlanguage{greek}α \selectlanguage{english}(hypoxia inducible factor 1\selectlanguage{greek}α\selectlanguage{english})
by interfering with proline-hydroxylase-2 (PHD2), resulting in the
regulation of hypoxia-induced gene expression independent of hypoxia
(pseudo-hypoxia).



\textbf{Figure 1}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 2}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 3}

\textbf{Hosted file}

\verb`image4.emf`  available at \url{https://authorea.com/users/391261/articles/505429-effect-of-nutrient-metabolism-on-cartilaginous-tissue-formation}



\textbf{Figure 4}

\textbf{Hosted file}

\verb`image5.emf`  available at \url{https://authorea.com/users/391261/articles/505429-effect-of-nutrient-metabolism-on-cartilaginous-tissue-formation}



\textbf{Figure 5}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image6/image6}

\end{center}
\end{figure}



\textbf{Tables}

\textbf{Table 1} : Effect of media volume on ECM accumulation and
glucose metabolism.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
& \textbf{Media Volume} & \textbf{Media Volume} & \textbf{Media Volume}
& \textbf{Media Volume}\tabularnewline
\midrule
\endhead
& \textbf{1 mL} & \textbf{2 mL} & \textbf{4 mL} & \textbf{8
mL}\tabularnewline
Wet Weight {[}normalized to control (1 mL){]} & 1.00 \selectlanguage{ngerman}± 0.09 * & 1.42 \selectlanguage{ngerman}±
0.08 \textsuperscript{a} & 2.4 \selectlanguage{ngerman}± 0.3 * & 2.0 \selectlanguage{ngerman}± 0.2\tabularnewline
GAG/DNA {[}normalized to control (1 mL){]} & 1.00 \selectlanguage{ngerman}± 0.11 * & 1.61 \selectlanguage{ngerman}± 0.22
\textsuperscript{a} & 3.30 \selectlanguage{ngerman}± 0.41 & 2.78 \selectlanguage{ngerman}± 0.23\tabularnewline
Collagen/DNA {[}normalized to control (1 mL){]} & 1.00 \selectlanguage{ngerman}± 0.09 * & 1.35 \selectlanguage{ngerman}±
0.40 \selectlanguage{english}\textsuperscript{+} & 2.26 \selectlanguage{ngerman}± 0.63 \selectlanguage{english}\textsuperscript{+} & 2.03 \selectlanguage{ngerman}±
0.69\tabularnewline
Glucose Consumption {[}nmol/h/\selectlanguage{greek}µ\selectlanguage{english}g DNA{]} & 15 \selectlanguage{ngerman}± 2 \textsuperscript{a} &
25 \selectlanguage{ngerman}± 3 \textsuperscript{a} & 63 \selectlanguage{ngerman}± 25 \textsuperscript{b} & 53 \selectlanguage{ngerman}± 13
\textsuperscript{b}\tabularnewline
Lactate Production {[}nmol/h/\selectlanguage{greek}µ\selectlanguage{english}g DNA{]} & 28 \selectlanguage{ngerman}± 3 \textsuperscript{a} & 45
\selectlanguage{ngerman}± 7 \textsuperscript{a} & 105 \selectlanguage{ngerman}± 39 \textsuperscript{b} & 83 \selectlanguage{ngerman}± 21
\textsuperscript{b}\tabularnewline
Y\textsubscript{L/G} (yield of lactate-on-glucose)\selectlanguage{english}+ & 1.88 \selectlanguage{ngerman}± 0.03
\selectlanguage{english}\textsuperscript{+} & 1.75 \selectlanguage{ngerman}± 0.09 & 1.74 \selectlanguage{ngerman}± 0.06 & 1.55 \selectlanguage{ngerman}± 0.06
\selectlanguage{english}\textsuperscript{+}\tabularnewline
Extracellular pH & 6.62 \selectlanguage{ngerman}± 0.04 & 6.70 \selectlanguage{ngerman}± 0.04 & 6.86 \selectlanguage{ngerman}± 0.04 * & 7.05 \selectlanguage{ngerman}±
0.05 *\tabularnewline
O\textsubscript{2} Consumption (qO\textsubscript{2}) {[}nmol/h/\selectlanguage{greek}µ\selectlanguage{english}g DNA{]}
& 0.23 \selectlanguage{ngerman}± 0.04 \textsuperscript{a} & 0.43 \selectlanguage{ngerman}± 0.05 \textsuperscript{a} &
0.84 \selectlanguage{ngerman}± 0.08 \textsuperscript{b} & 1.2 \selectlanguage{ngerman}± 0.1
\textsuperscript{b}\tabularnewline
CO\textsubscript{2} Production (qCO\textsubscript{2}) {[}nmol/h/\selectlanguage{greek}µ\selectlanguage{english}g
DNA{]} & 4.0 \selectlanguage{ngerman}± 0.8 & 6.7 \selectlanguage{ngerman}± 0.5 & 11.5 \selectlanguage{ngerman}± 0.9 & 27 \selectlanguage{ngerman}± 3 *\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{ngerman}

* significantly different from all groups
(p\textless{}0.01);\selectlanguage{english}\textsuperscript{+} significantly different from each
other (p\textless{}0.05); \textsuperscript{a} significantly different
from 4 and 8 mL (p\textless{}0.05); \textsuperscript{b} significantly
different from 1 and 2 mL (p\textless{}0.05); Data presented as mean +-
SEM with n=6/group, except qO\textsubscript{2} and qCO\textsubscript{2}
with n=3/group; \selectlanguage{english}+~ratio of 2 (Y\textsubscript{L/G}) indicates 100\%
anaerobic metabolism.



\textbf{Supplemental Figure Captions}

\textbf{Figure S1}

Effect of media volume on tissue formation from rabbit (A) and human (B)
chondrocytes. Tissue engineered constructs were developed from
chondrocytes of either skeletally mature New Zealand White rabbits (two
female donors, \textasciitilde{} 11 months old, \textasciitilde{} 4 kg;
P0 cells) or human donors (two female donors aged 45 and 47; P2 cells).
Data presented as mean +- SEM, n=4/group.



\textbf{Supplemental Figure 1}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image7/image7}

\end{center}
\end{figure}

\textbf{Supplemental Tables}

\textbf{Table S1} : Measured metabolites.\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\begin{minipage}[b]{0.22\columnwidth}\raggedright\strut
\textbf{Glycolysis}\strut
\end{minipage} & \begin{minipage}[b]{0.22\columnwidth}\raggedright\strut
\textbf{Fermentation}\strut
\end{minipage} & \begin{minipage}[b]{0.22\columnwidth}\raggedright\strut
\textbf{TCA Cycle}\strut
\end{minipage} & \begin{minipage}[b]{0.22\columnwidth}\raggedright\strut
\textbf{Pentose Phosphate Pathway}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
G6P F6P FBP DHAP 3PG PEP PYR\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
PYR LAC\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
PYR AKG SUC FUM MAL\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
G6P 6GP R5P\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table S2} : PCR primers.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\textbf{Gene} & \textbf{Sense} & \textbf{Anti-Sense} & \textbf{Length} &
\textbf{T\textsubscript{m}}\tabularnewline
\midrule
\endhead
SOX9 & GCCGTGATTGGCCCTTGTATTTA & CCACTGAAGTTCCAGGTCAGTTTC & 93 bp &
65\selectlanguage{ngerman}°C\tabularnewline
PDK1 & TGCTAGGCGTCTGTGTGATTTG & CTTGTATTGGCTGTCCTGGTGATT & 92 bp &
65\selectlanguage{ngerman}°C\tabularnewline
GLUT1 & GAGGTGTCGGCGTTTGATTCTT & CACTGGCAAGCTCCACCATAAC & 104 bp &
65\selectlanguage{ngerman}°C\tabularnewline
18S & GTGGAGCGATTTGTCTGGGTTAAT & TGAACGCCACTTGTCCCTCTAA & 120 bp &
65\selectlanguage{ngerman}°C\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{ngerman}

\textbf{Table S3} : Correlation between intracellular metabolites and
PHD2 activity.\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\textbf{Metabolite} & \textbf{Metabolic Pathway} & \selectlanguage{greek}\textbf{Correlation
Coefficient (ρ)}\selectlanguage{english} & p-value\tabularnewline
\midrule
\endhead
G6P & Glycolysis, PPP & 0.693 & 0.407\tabularnewline
F6P & Glycolysis & 0.636 & 0.465\tabularnewline
3PG & Glycolysis & -0.180 & 0.860\tabularnewline
FBP & Glycolysis & -0.079 & 0.939\tabularnewline
DHAP & Glycolysis & -0.438 & 0.648\tabularnewline
PEP & Glycolysis & -0.384 & 0.694\tabularnewline
LAC & Fermentation & -0.999 & 0.000\tabularnewline
6PG & PPP & 0.361 & 0.714\tabularnewline
R5P & PPP & -0.627 & 0.475\tabularnewline
PYR & Glycolysis, Fermentation, TCA & -0.794 & 0.294\tabularnewline
AKG & TCA & -0.078 & 0.940\tabularnewline
SUC & TCA & -0.986 & 0.017\tabularnewline
FUM & TCA & -0.865 & 0.202\tabularnewline
MAL & TCA & -0.767 & 0.326\tabularnewline
\bottomrule
\end{longtable}

\emph{TCA} : Tricarboxylic Acid Cycle; \emph{PPP} : Pentose Phosphate
Pathway

\selectlanguage{english}
\FloatBarrier
\end{document}

