International Journal of

Molecular Sciences
ArticleEvaluation of L-Alanine Metabolism in Bacteria andWhole-Body Distribution with Bacterial Infection Model Mice
Yuka Muranaka 1,† , Miki Matsue 2,† , Asuka Mizutani 3 , Masato Kobayashi 3 , Kakeru Sato 1 , Ami Kondo 1 ,Yuri Nishiyama 1 , Shusei Ohata 4 , Kodai Nishi 5 , Kana Yamazaki 6 , Ryuichi Nishii 6 , Naoto Shikano 7 ,Shigefumi Okamoto 3,8 and Keiichi Kawai 3,9, *
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Citation: Muranaka, Y.; Matsue, M.;*†

Division of Health Sciences, Graduate School of Medical Sciences, Kanazawa University, 5-11-80 Kodatsuno,
Kanazawa 920-0942, Japan
Ishikawa Prefectural Institute of Public Health and Environmental Science, 1-11 Taiyogaoka,
Kanazawa 920-1154, Japan
Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University,
5-11-80 Kodatsuno, Kanazawa 920-0942, Japan
Department of Radiation Technology, Toyama Red Cross Hospital, 2-1-58 Ushijimahonmachi,
Toyama 930-8562, Japan
Department of Radioisotope Medicine, Atomic Bomb Disease Institute, Nagasaki University, 1-12-4 Sakamoto,Nagasaki 852-8523, Japan
Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science, Quantum Life
and Medical Science Directorate, National Institutes for Quantum Science and Technology, 4-9-1 Anagawa,Inage, Chiba 263-8555, Japan
Department of Radiological Sciences, Ibaraki Prefectural University of Health Sciences, 4669-2 Ami,
Inashiki 300-0394, Japan
Advanced Health Care Science Research Unit, Innovative Integrated Bio-Research Core Institute for Frontier
Science Initiative, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa 920-0942, Japan
Biomedical Imaging Research Center, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji,
Fukui 910-1193, Japan
Correspondence: kei@mhs.mp.kanazawa-u.ac.jp; Tel.: +81-76-265-2527
These authors contributed equally to this work.

Mizutani, A.; Kobayashi, M.; Sato, K.;
Kondo, A.; Nishiyama, Y.; Ohata, S.;
Nishi, K.; Yamazaki, K.; et al.
Evaluation of L-Alanine Metabolism
in Bacteria and Whole-Body
Distribution with Bacterial Infection
Model Mice. Int. J. Mol. Sci. 2023, 24,4775. https://doi.org/10.3390/
ijms24054775
Academic Editor: Alessandra
Ferramosca
Received: 31 January 2023
Revised: 21 February 2023
Accepted: 27 February 2023
Published: 1 March 2023

Abstract: The World Health Organization has cautioned that antimicrobial resistance (AMR) will be
responsible for an estimated 10 million deaths annually by 2050. To facilitate prompt and accurate
diagnosis and treatment of infectious disease, we investigated the potential of amino acids for use as
indicators of bacterial growth activity by clarifying which amino acids are taken up by bacteria during
the various growth phases. In addition, we examined the amino acid transport mechanisms thatare employed by bacteria based on the accumulation of labeled amino acids, Na+ dependence, andinhibitory effects using a specific inhibitor of system A. We found that 3 H-L-Ala accurately reflects
the proliferative activity of Escherichia coli K-12 and pathogenic EC-14 in vitro. This accumulation in
E. coli could be attributed to the amino acid transport systems being different from those found in
human tumor cells. Moreover, biological distribution assessed in infection model mice with EC-14
using 3 H-L-Ala showed that the ratio of 3 H-L-Ala accumulated in infected muscle to that in control
muscle was 1.20. By detecting the growth activity of bacteria in the body that occurs during the earlystages of infection by nuclear imaging, such detection methods may result in expeditious diagnostic
treatments for infectious diseases.
Keywords: amino acids; alanine; bacterial imaging; nuclear medicine imaging; bacterial infection

Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

1. Introduction
Antimicrobial resistance (AMR) poses significant risks to people around the world,with approximately 33,000 deaths annually attributed to AMR in Europe [1]. The World
Health Organization cautions that if this trend persists, AMR will be responsible for an
estimated 10 million deaths per year by 2050 [2,3].

Int. J. Mol. Sci. 2023, 24, 4775. https://doi.org/10.3390/ijms24054775

https://www.mdpi.com/journal/ijms

Int. J. Mol. Sci. 2023, 24, 4775

2 of 10The quandary of AMR has become a pressing matter that must be addressed. Consequently, in order to facilitate prompt and accurate diagnosis and treatment of infectious
diseases, a diagnostic methodology capable of detecting pathogenic bacteria at the locus of
infection in the early stages of infection is essential and urgent.
Nuclear medicine imaging has attracted considerable attention as a novel means of
examining bacterial infections. This methodology enables non-invasive examination anddiagnosis through imaging the state of the patient’s body with radiopharmaceutical agentsthat are administered to the patient [4]. In this study, we posited that if the proliferationof bacteria that occurs in the body during the early stages of infection can be captured
by imaging, then such detection methods may result in new and expeditious diagnostic
treatments for infectious diseases.
Bacterial growth can be classified into the lag phase, log phase, stationary phase, anddeath phase [5]. Given that bacteria exhibit varying degrees of proliferative activity during
each phase, we surmised that the prompt detection of changes in proliferative activity may
facilitate the implementation of appropriate treatments. Since the glucose-based diagnostic
imaging agent 2-deoxy-2-[18 F]fluoro-D-glucose (18 F-FDG), which is utilized primarily inclinical practice [6–8], can be taken up by both bacterial pathogens and inflammatory cells
associated with bacterial infection, 18 F-FDG has been investigated as a potential diagnostic
imaging agent for acute infectious diseases [9–11]. However, despite the reported ability of
18 F-FDG to clarify the presence or absence of bacterial infection, limited research has been
conducted on the ability of this agent to detect the growth activity of pathogenic bacteria
in detail. As a method aimed at the specific detection of bacterial infections, 99m Tc-based
imaging agent, such as 99m Tc ciprofloxacin [12] were investigated.
Accordingly, this study focused on the potential of amino acid-based diagnostic
imaging agents for use as novel diagnostic imaging agents that utilize bacterial growth
activity as an indicator of infection. Amino acids are necessary for bacterial growth [13],and it is well-established that the transport function of amino acids is ubiquitous in bacteria,
which can take up many types of amino acids.
Furthermore, our laboratory has developed a method to evaluate the contributionof amino acid transport systems in tumor cells for the development of amino acid tumor
imaging agents targeting human tumor cells in previous study. We have evaluated thecontribution of amino acid transporters, especially system A and system L, which are
known to be highly expressed in tumor cells [14–16]. The application of this method tobacteria is important for the development of imaging agents for identifying amino acidpathogens and for the differential diagnosis of bacterial infections.
In this study, we investigated the utility of amino acids as indicators of bacterial
growth activity by conducting a detailed examination of which amino acids are taken up bybacteria during in the lag phase, log phase, stationary phase, and death phases of bacterial
growth. In addition, we examined the mechanisms involved in amino acid transport inbacteria based on the Na+ dependence and inhibitory effects using a specific inhibitor ofsystem A.
2. Results
2.1. Accumulation of 3 H-L-Ala, 3 H-L-Met, 3 H-L-Glu, and 3 H-L-His in E. coli K-12
The accumulation of 3 H-L-Ala, 3 H-L-Met, 3 H-L-Glu, and 3 H-L-His in E. coli K-12 ineach growth stage is shown in Figure 1. The findings showed that the lag phase of K-12
(2 h) had the highest accumulation of 3 H-L-Glu. In the log phase (6 h and 8 h), higher
levels of 3 H-L-Ala and 3 H-L-Met were accumulated compared to the other amino acids. In
the stationary phase (12 h and 24 h), the accumulation of 3 H-L-Met and 3 H-L-His was thehighest among the amino acids.

Int. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW

Int. J. Mol. Sci. 2023, 24, 4775

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stationary phase (12 h and 24 h), the accumulation of 3H-L-Met and 3H-L-His was the highest among the amino acids.

3 of 10

3 H-L-Met,
3 H-L-Glu,
3 H-L-His
3H-L-Met,
3H-L-Glu,
Figureof 3H-L-Ala,and 3H-L-His
E. coli K-12
Figure1.1.Accumulation
Accumulationof 3 H-L-Ala,and ininatE.eachcoli growthK-12 at each
3H-L-Glu showed
3
3 3
3
the
highestaccumulation.
At
6
h
and
8
stage.
At2h,growth stage. At 2 h, H-L-Glu showed the highest accumulation.h,AtH-L-Ala
6 h andand
8 h,H-L-Met
H-L-Ala andaccumulated
more than the other amino acids. At 12 h and 24 h, the accumulation of 3H-L-Met and3 H-L-Met accumulated
more than the other amino acids. At 12 h and 24 h, the accumulation of
3H-L-His was higher than that of the other amino acids.
33

H-L-Met and H-L-His was higher than that of the other amino acids.

3H2.2.
of of
L-Ala, 3H-3LH-L-Met,-Met, 3H-L3-Glu,
and 3HL-His
in E. coli
3 H-L-Ala,
3 H-L-His
2.2.Accumulation
Accumulation
H-L-Glu,andin EC-14
E. coli EC-14
3H-L-Ala, 3H-L-Met, 3H-L-Glu, and 3H-L-His in E. coli EC-14 at
The
of of
3 H-L-Ala, 3 H-L-Met, 3 H-L-Glu, and 3 H-L-His in E. coli EC-14
Theaccumulation
accumulationeach growth stage is shown in Figure 2. First, in the lag phase of EC-14 (1 h), the accumuat each growth stage is shown in Figure 2. First, in the lag phase of EC-14 (1 h), thelation of most amino acids was low. In the log phase (2 and 4 h), 3H-L-Ala and 3HL-Met
accumulation of most amino acids was low. In the log phase (2 and 4 h), 3 H-L-Ala andInt. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW
4
showedthehighestaccumulation
among
the
amino
acids.
Inthestationary
phase(6,118,
3 H-L-Met showed the highest accumulation among the amino acids. In the ofstationary
and 12 h), 3H-L-His showedthehighestaccumulation.
3phase (6, 8, and 12 h), H-L-His showed the highest accumulation.

3

3

3

3

3H-L-Met,
3H-L-Glu,
Figure2.2.Accumulation
Accumulation
H-L-Ala,
H-L-Met,H-L-Glu,and H-L-His
in EC-14
E. coli at
EC-14
Figureof 3of
H-L-Ala,and 3H-L-His
in E. colieach at each
3H-L-Ala
growthstage.
h, theaccumulationof mostofaminothe amino
wasAt
low.
2 4h h,and
4 h, 3 H-L-Ala
growthstage.
AtAt
1 h,1 theaccumulationof mostof theacidsacids
was low.
2 hAt
and
3 H-L-Met
accumulated
morethanthanthe otheraminoacids.acids.
At 6, At8, andh, 3H-L-His
showedshowedtheandand3H-L-Met
accumulated
more
the otheramino
6, 8,12and
12 h, 3 H-L-His
thehighestaccumulationlevels.
highest accumulation levels.

2.3. Comparing the Accumulation of 3H-L-Ala in E. coli K-12 and EC-14
The accumulation of 3H-L-Ala in E. coli K-12 and EC-14 at each growth stage is shownin Figure 3. 3H-L-Ala accumulation in K-12 showed the highest accumulation during thelog phase, but not much accumulation during the stationary phase. Conversely, the accu-

Int. J. Mol. Sci. 2023, 24, 4775

4 of
10
Figure 2. Accumulation of 3H-L-Ala, 3H-L-Met, 3H-L-Glu, and 3H-L-His in E. coli EC-14 at
eachgrowth stage. At 1 h, the accumulation of most of the amino acids was low. At 2 h and 4 h, 3H-L-Ala
and 3H-L-Met accumulated more than the other amino acids. At 6, 8, and 12 h, 3H-L-His showed thehighest accumulation levels.
2.3. Comparing the Accumulation of 3 H-L-Ala in E. coli K-12 and EC-14

2.3. Comparing the Accumulation of 3H-L-Ala in E. coli K-12 and EC-14

The accumulation of 3 H-L-Ala in E. coli K-12 and EC-14 at each growth stage is shown
The accumulation of 3H-L-Ala in E. coli K-12 and EC-14 at each growth stage is shownin Figure 3. 3 H-L-Ala accumulationin K-12 showed the highest accumulation during
in Figure 3. 3H-L-Ala accumulation in K-12 showed the highest accumulation during thethe log phase,log
but
not
much
accumulation
duringthephase.
Conversely,
thephase, but not much accumulation
duringthestationary
stationary phase.
Conversely,
the accuaccumulation mulationof EC-14ofremained
high
from
the
log
phase
to
the
stationary
phase.
EC-14 remained high from the log phase to the stationary phase.

(a)

(b)

Figure 3. Accumulation of H-L-Ala in (a) E. coli K-12 and (b) EC-14 at each growth stage. H-L-Ala
3

Figure 3. Accumulation of 3 H-L-Ala in (a) E. coli K-12 and (b) EC-14 at each growth stage. H-L-Ala
accumulation in K-12 showed the highest uptake during the log phase, but not much uptake during
accumulation inthe
K-12
showedthe highest
uptakeduring the bylogEC-14
phase,
but nothighmuchduringstationary
phase.
In contrast,
the accumulation
remainedfromuptake
the logarithmic
growth In
stage
to the stationary
phase.
the stationary phase.
contrast,
the accumulation
by EC-14 remained high from the logarithmic
growth stage to the stationary phase.
Int. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW

5 of 112.4. Inhibition of Amino Acid Accumulation in Bacteria and Cancer Cells

To determine some characteristics of the amino acid transport system in bacteria, we
2.4.
Inhibition of
Acidtransport
Accumulationin Bacteria
and Cancer
Cells cells. The accumulation of L-Ala incomparedit Aminowith thesystemin humancancerTo determinesomecharacteristicsof the aminoacid transportsystemin bacteria,
E. coli
K-12 andEC-14
was comparedto thatin humantumor
cells,wei.e., human prostatecompared it with the transport system in human cancer cells. The accumulation of L-Ala
cancer cell line DU145 and human glioblastoma cell line T98G, under control and specificin E. coli K-12 and EC-14 was compared to that in human tumor cells, i.e., human prostate
inhibitor-treated(i.e., treatment
In L-Ala,
13% of K-12 and 24%
cancercell line DU145 conditions
and human glioblastoma
cell linewith
T98G,MeAIB).
under control
and specific+ -dependent, but the percentage was small compared to the more than
of
EC-14
were
Na
inhibitor-treated conditions (i.e., treatment with MeAIB). In L-Ala, 13% of K-12 and 24%+ -dependence
the percentage
was smallto
comparedto the morethanof MeAIB on L-Alaof
EC-14
Na+-dependent,
75%
Nawereof buttumor
cells. Compared
the inhibitory
effect+-dependenceoftumor
cells.
Comparedtotheinhibitory
effect
of
MeAIB
on
L-Ala
75%
Na
accumulation, the K-12 and EC-14 cells showed no significant inhibitory effect on L-Ala
accumulation, the K-12 and EC-14 cells showed no significant inhibitory effect on L-Ala
accumulation by MeAIB, which is observed in tumor cells (DU145 and T98G) (Figure 4).
accumulation by MeAIB, which is observed in tumor cells (DU145 and T98G) (Figure 4).

Figure4. Accumulation
ofinL-Alain E.andcoliEC-14.
K-12Accumulationand EC-14.wasAccumulation
Figure4. Accumulationof L-Ala
E. coli K-12
compared withwasthat compared with that
ininhumantumor
cells (i.e.,cancercells and
T98G humanglioblastoma
cells) glioblastoma cells)
human
tumor
cellsDU145(i.e., human
DU145prostatehumanprostate
cancercells and
T98G humanunder control and specific inhibitor of system A, MeAIB-treated conditions. For L-Ala, comparing
the accumulation of labeled amino acids in Ch-PBS (Na+-free medium) and the accumulation oflabeled amino acids in Na+-PBS, 13% of K-12 and 24% of EC-14 were Na+-dependent. Moreover,comparing the inhibitory effect of MeAIB on L-Ala accumulation, K-12 and EC-14 showed no significant inhibitory effect on L-Ala accumulation by MeAIB, which is observed in tumor cells. * p <0.05, ** p < 0.01 vs. control/Na+.
2.5. Biological Distribution of E. coli EC-14 Infection Model Mice Using 3H-L-Ala

Int. J. Mol. Sci. 2023, 24, 4775

5 of 10under control and specific inhibitor of system A, MeAIB-treated conditions. For L-Ala, comparing
the accumulation of labeled amino acids in Ch-PBS (Na+ -free medium) and the accumulation oflabeled amino acids in Na+ -PBS, 13% of K-12 and 24% of EC-14 were Na+ -dependent. Moreover,comparing the inhibitory effect of MeAIB on L-Ala accumulation, K-12 and EC-14 showed nosignificant inhibitory effect on L-Ala accumulation by MeAIB, which is observed in tumor cells.
* p < 0.05, ** p < 0.01 vs. control/Na+.

2.5. Biological Distribution of E. coli EC-14 Infection Model Mice Using 3 H-L-Ala
Table 1 shows the biological distribution of 3 H-L-Ala in EC-14 infection model mice.
3 H-L-Ala showed a maximum contrast of 1.2 at 2 h after infection, 60 min after 3 H-L-Ala

injection. This contrast is defined as the ratio of accumulation by weight of infected anduninfected muscle. The ratios of infected muscle to blood were 0.79 and 0.75 at 2 and 8 hafter infection, respectively, and 0.89 and 1.31 at 15 and 60 min after 3 H-L-Ala injection,
respectively.
Table 1. Biological distribution of 3 H-L-Ala in EC-14 infection model mice.
Time after
3 H-L-Ala Injection

Organ (%ID/g)
Blood
Heart
Lung
Liver
SpleenKidneyInfected muscle
Control muscle
Infected muscle/bloodInfected muscle/control muscle

15 min60 min2 h after Infection

15 min60 min8 h after Infection

6.54 ± 0.57
4.33 ± 0.44
7.66 ± 1.57
4.26 ± 0.70
17.11 ± 2.39
8.90 ± 0.67
5.14 ± 0.57
4.89 ± 0.81

5.64 ± 0.35
3.87 ± 0.37
5.60 ± 1.31
4.88 ± 1.03
15.64 ± 4.53
7.78 ± 0.54
4.25 ± 1.13
3.55 ± 0.63

5.10 ± 0.55
3.90 ± 0.24
6.17 ± 0.67
3.96 ± 0.65
9.94 ± 0.73
7.06 ± 1.10
4.52 ± 1.13
3.99 ± 0.89

3.05 ± 0.14
3.65 ± 0.26
5.22 ± 0.30
4.23 ± 0.54
7.60 ± 1.22
6.76 ± 0.74
3.99 ± 0.69
3.92 ± 0.36

0.79

0.75

0.89

1.31

1.05

1.20

1.13

1.02

%ID/g indicates percent injected dose per gram of tissue.

3. Discussion
In this study, we investigated the utility of amino acids as indicators of bacterial growth
and activity by conducting a detailed examination of which amino acids are accumulated
by bacteria during the lag phase, log phase, stationary phase, and death phases of growth.
We then clarified the amino acid transport properties in bacteria by investigating theaccumulation of labeled amino acids, Na+ dependence, and inhibitory effects using MeAIB,
specific inhibitor of system A. We previously focused on MeAIB in our research group for
application to positron emission tomography imaging in cancer [17].
First, in the in vitro bacterial accumulation study, the accumulation of neutral aminoacids, 3 H-L-Ala and 3 H-L-Met, increased from the lag phase to the log phase (Figures 1 and 2).
This indicates that neutral amino acids are useful as indicators of proliferative activity in
K-12 and EC-14. The accumulation of the acid amino acid 3 H-L-Glu in EC-14, unlike that in
K-12, did not change during each growth phase and remained constant (Figures 1 and 2).
One of the reasons for this disparity in the accumulation characteristics of K-12 and EC-14
may be due to differences in amino acid transporters. It has been reported that K-12 has
both ATP-binding cassette transporters (ABC transporters) and ion-driven transporters for
L-glutamic acid and L-lysine, while the other natural amino acids used in our experiments
have only one of the two transporters [18]. On the other hand, the details of the amino acidtransporters of EC-14 are unknown because few reports have been published to date, but
it is possible that L-glutamic acid and L-lysine have only one of the two transporters, i.e.,

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6 of 10

the ABC transporter or an ion-driven transporter, and this difference may be related to thedifference in uptake between the two strains.
Furthermore, 3 H-L-Ala showed the largest accumulation among the neutral aminoacids in both K-12 and EC-14 (Figures 1 and 2). Therefore, it is possible that 3 H-L-Ala may
best reflect the proliferative activity of E. coli. One of the reasons for the high accumulation of 3 H-L-Ala during the log phase may be due to cell wall synthesis. Peptidoglycan,
one of the components of the cell wall, is composed of a sugar chain consisting of Nacetylglucosamine (GlcNAc) and N-acetylmuramic acid (MurNAc) linked alternately by
β-1.4 bonds, as well as L-Ala, D-Glu, L-diaminopimelic acid (L-DAP), and D-Ala [19].
The highest accumulation of 3 H-L-Ala during the log phase is considered to be due to its
incorporation into the cell wall as a component of peptidoglycan, as the synthesis of thecell wall is promoted by the activation of proliferation [20].
3 H-L-Ala is taken up by the bacteria as they grow. In pathogenic EC-14, 3 H-L-Ala
accumulation is maintained even during the stationary phase, suggesting that the takeup of 3 H-L-Ala may be maintained as the pathogenic bacteria proliferate. Based on theassumption of the existence of a specific transport system for the accumulation of alanine,
we performed the accumulation inhibition experiments. In this study, the amino acidtransport system and inhibitors were determined based on studies performed in humancancer cells [16]. Previously, we developed a method to evaluate the contribution ofamino acid transport systems in tumor cells for the development of amino acid tumor
imaging agents targeting human tumor cells [14–16]. By using this evaluate method, weinvestigated the accumulation inhibition experiments. Moreover, amino acid transportsystems in humans can be divided into two major types: Na+ -dependent transport systems,
which show transport activity in the presence of Na+ , and Na+ -independent transportsystems, which show transport activity regardless of the presence or absence of Na+ . We
aimed to elucidate these transport properties in bacteria as well. The results showed thatfor 3 H-L-Ala, 13% of K-12 and 24% of EC-14 were Na+ -dependent, but the percentage wassmall compared to the Na+ -dependence levels of more than 75% observed in tumor cells(Figure 4). Comparing the inhibitory effect of MeAIB on 3 H-L-Ala accumulation, the K-12
and EC-14 showed no significant inhibitory effect on 14 C-L-Ala accumulation by MeAIB,
which is observed in tumor cells. The findings revealed that the amino acid transportsystem employed by E. coli differs from that found in human tumor cells. The applicationof this method which evaluate the contribution of amino acid transporters for bacteria is
important for the development of imaging agents for identifying pathogens.
Table 1 shows the biological distribution of 3 H-L-Ala in EC-14 infection model mice.
In vivo, 3 H-L-Ala had a maximum contrast of 1.20 at 2 h after infection. This contrast
is defined as the ratio of amino acid accumulation by weight of infected and uninfectedmuscle. The low accumulation of radiotracer in the heart may be better suited than 18 F-FDG,
which showed high levels of physiological accumulation [21], for detecting infections in theupper body and other parts of the body. Also in the biological distribution, the detection
window of infection was narrow because the maximum contrast of 1.2 at 2 h after infection
was close to 1.0 (showing no contrast). We have to pay attention to it raised a concern that
there could be false negative results in practice. A limitation of this study was that we
could not perform imaging as our facility is not equipped with a cyclotron or an automaticsynthesizer for 11 C labeling. However, the results of the whole-body biodistribution are
considered to be equivalent to those of whole-body imaging [22].
4. Materials and Methods[2,3-3 H]-L-Ala (3 H-L-Ala), [S-methyl-3 H]-L-Met (3 H-L-Met), [2,3,4-3 H]-L-glutamic
acid (3 H-L-Glu), and [ring 2,5-3 H]-L-histidine (3 H-L-His) (American Radiolabeled Chemicals; St. Louis, MO, USA) were used in this study. Only in the cancer cell accumulation inhibition experiment study, was [14 C(U)]-L-alanine (14 C-L-Ala) used (PerkinElmer, Waltham,
MA, USA).

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7 of 104.1. Bacterial Strain and Culture Conditions
The bacterial strains used in this study were Escherichia coli K-12 (DH5α strain) andE. coli EC-14 (Shionogi, Osaka, Japan), which was used as the clinical isolate strain [23]. In
the pre-cultivation process, 1:100 mixtures of EC-14 stock solutions containing 50% glycerol
and THY medium made up of Todd–Hewitt Broth (Becton, Dickinson and Company,
Franklin Lakes, NJ, USA) and 0.2% yeast extract (Becton, Dickinson and Company) wereused. The mixtures were shaken at 37 ◦ C for 12–14 h before EC-14 was seeded in aminoacid-free Dulbecco’s Modified Eagle’s Medium (DMEM; FUJIFILM Wako Pure Chemical
Corporation, Osaka, Japan) and incubated with shaking at 37 ◦ C. A Pierce™ BCA Protein
Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA) was used to measure bacterial
protein concentrations.
4.2. Human Tumor Cell Line and Culture Conditions
For brain tumor cells, human glioblastoma cell line T98G was used. For prostatecancer cells, the DU145 cell line was used. These cell lines were purchased from American
Type Culture Collection (Manassas, VA, USA) and have been used in previous studies by
our research group [14,15].
First, human tumor cells were cultured in a cell culture dish. The cells were washedtwice with phosphate buffered saline (PBS; pH 7.3) (Medical & Biological Laboratories Co.,
Ltd., Aichi, Japan) and then collected with 0.25% trypsin-EDTA solution. The reaction wasthen stopped in culture medium, and the cells were seeded in 24-well multi-well plates at
1 × 105 cells/well. The cells were incubated for approximately 24 h after seeding. DMEM
containing 10% fatal bovine serum (FBS) and 1% sodium pyruvate was used for culturing
T98G cells. RPMI 1640 medium containing 10% FBS and 1% sodium pyruvate was used for
culturing DU145 cells.
4.3. Accumulation of 3 H-L-Ala, 3 H-L-Met, 3 H-L-Glu, and 3 H-L-His in E. coli K-12 and EC-14
E. coli K-12 at 1.3 × 106 CFU/200 µL and EC-14 at 1.2 × 108 CFU/100 µL were seededin 5 mL of amino acid-free DMEM and incubated for 1, 2, 4, 6, 8, 12, and 24 h. Afterincubation, 37 kBq/10 µL of 3 H-L-Ala, 3 H-L-Met, 3 H-L-Glu, and 3 H-L-His were added tothe bacterial solution and incubated for 5 min at 37 ◦ C with gentle shaking. K-12 and EC-14
were collected by centrifugation at 7000× g for 10 min at 4 ◦ C, washed three times with
5 mL of PBS.
K-12 and EC-14 were lysed by the addition of 1 mL of 0.1 M NaOH. The radioactivityof the mixture made up of 500 µL of bacterial lysate and 5 mL of liquid scintillation
cocktail (ULTIMA GOLD, Perkin Elmer, Waltham, MA, USA) was measured using a liquid
scintillation counter (LSC-5100; Hitachi Aloka Medical, Tokyo, Japan).
4.4. Inhibition of Amino Acid Accumulation in Bacteria
In this study, we applied the experimental methods used to study human cancer cells
to bacteria. E. coli K-12 and EC-14 were cultured under the same conditions as describedin Section 4.3. The pre-cultured bacteria solution was incubated at 37 ◦ C in 20 mL ofamino acid-free DMEM at 160 rpm. The relationship between the number of bacteria andincubation time was expressed as a growth curve for E. coli to show the lag phase (K-12:
2 h, EC-14: 1 h), the log phase (K-12: 6 h, EC-14: 3 h), the stationary phase (K-12: 12 h,
EC-14: 6 h), and the death phase. The lag phase of bacteria is the early phase of the growth
period, and the log phase means the period when the bacteria proliferate actively due toactive enzyme activity in the bacteria. And the death phase means the period when theratio of cell growth to cell death is equal due to nutrient deprivation and accumulation of
toxic metabolites.
In this experiment, after incubation of K-12 for 6 h and EC-14 for 3 h, which is thelog phase, the DMEM culture medium was replaced with medium containing 137 mM
NaCl, 2.7 mM KCl, 8 mM Na2 HPO4 , 1.5 mM KH2 PO4 , 5.6 mM D-glucose, 0.9 mM CaCl2 ,and 0.5 mM MgCl2 Na+ -PBS (pH 7.3), or choline-PBS (Ch-PBS; pH 7.3), with NaCl andInt. J. Mol. Sci. 2023, 24, 4775

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Na2 HPO4 in Na+ -PBS replaced with the same concentrations of chlorine-Cl and K2 HPO4 ,respectively. Ch-PBS is the Na+ -free medium used for contrast with Na+ contain medium.
Following solvent exchange, 7.4 kBq of labeled amino acids and α-(methylamino)isobutyricacid (MeAIB; Sigma-Aldrich, St. Louis, MO, USA), which is a specific inhibitor of systemA, were added to a final concentration of 1.0 mM and uptake of the mixture was promoted
by incubating in a water bath at 37 ◦ C for 5 min with gentle shaking. After centrifugation
at 7000× g for 6 min at 4 ◦ C, the supernatant was removed, and the pellet was loosened,
1.0 mL of Na+ -PBS and Ch-PBS were added, and centrifugation was performed twice towash the pellet.
After washing, the supernatant was removed, the pellet was loosened, and 1.0 mL of
0.1 M NaOH was added to lyse the E. coli to prepare the sample lysate. A 500 µL aliquot
was then removed from the sample lysate and the radioactivity was measured using aliquid scintillation counter. A Pierce™ BCA Protein Assay Kit was used to measure thebacterial protein.
To calculate the contribution of amino acid transporter systems, we used the methods
reported by Kobayashi et al. [16]. The accumulation of the labeled amino acids under eachcondition was thus expressed as a relative value (percentage of control/Na+ [%]) basedon the assumption that the accumulation in Na+ -PBS without inhibitor (Na+ -control) was
100%. Moreover, to calculate the Na+ dependency, the accumulation of labeled amino acids
in Ch-PBS (Na+ -free medium) was expressed as a relative value based on the accumulationof the control, in which the accumulation of labeled amino acids in Na+ -PBS was 100%. In
this study, Ch-PBS is the Na+ -free medium used for contrast with Na+ -containing medium.
4.5. Inhibition of Amino Acid Accumulation in Cancer Cells
For competitive inhibition experiments, the culture medium in the wells was removed
and the cells were incubated in 300 µL of Na+ -PBS (pH 7.3) buffer containing 137 mM NaCl,
2.7 mM KCl, 8 mM Na2 HPO4 , 1.5 mM KH2 PO4 , 5.6 mM D-glucose, 0.9 mM CaCl2 , and
0.5 mM MgCl2 or Na+ -choline-PBS (pH 7.3), in which NaCl and Na2 HPO4 in PBS were
replaced with the same concentrations of choline-Cl and K2 HPO4 , and the plates werepreincubated at 37 ◦ C for 10 min.
After 10 min, 9.25 kBq/well of 14 C-L-Ala and 1 mM of MeAIB were added and theplates were incubated at 37 ◦ C. After incubation, the solution in the wells was removed,
and the cell surface and wells were briefly washed twice with ice-cold Na+ -PBS or Ch-PBS.
Then, 500 µL of 0.1 M NaOH was added to each well to lyse the cells, 350 µL of the celllysate was mixed with liquid scintillation cocktail, and radioactivity was measured with aliquid scintillation counter. The remaining cell lysate was used to measure the cell protein
mass in each well and to correct for the accumulation count of labeled amino acids in eachwell. These results were used to evaluate the contribution of the inhibitor.
4.6. Biological Distribution of E. coli EC-14 Infection Model Mice Using 3 H-L-Ala
All procedures of animal study were approved by the Animal Care Committee ofKanazawa University (AP-183983) and were conducted in accordance with the international
standards for animal welfare and institutional guidelines.
EC-14 (approximately 5 × 106 CFU/100 µL) were injected into the muscle of the hindleg of mice (n = 4), described in Muranaka et al. [21]. At 2 and 8 h after infection, mice
were administered 50 kBq/50 µL of 3 H-L-Ala intravenously. Prior to administration, themice were fasted for 4 h. Mice were then euthanized at 15 min (n = 4) and at 60 min (n = 4)
after administration, and approximately 100 mg of blood, heart, lung, liver, kidney, spleen,
infected perineal muscle, and non-infected perineal muscle (control muscle) tissues werecollected.
The collected organs were divided into approximately 100 mg portions and dissolved
by adding 1.0 mL of solubilizer (Solvable, PerkinElmer, Waltham, MA, USA) and crushed
using a disposable homogenizer (BioMasher® , Nippi Inc., Tokyo, Japan). The radioactivity

Int. J. Mol. Sci. 2023, 24, 4775

9 of 10of 3 H-L-Ala was measured using a liquid scintillation counter (LSC-5100, Hitachi Aloka
Medical).
4.7. Statistical Analysis
Data are reported as means and standard deviation of percent injected dose per gramof tissue (%ID/g) and analyzed using the F-test and Student’s t-test. A p value of less than
0.01 or 0.05 was considered indicative of a statistically significant difference.
5. Conclusions
3 H-L-Ala reflects accurately the proliferative activity of E. coli K-12 and EC-14. Thisutility of amino acids as indicators of bacterial growth activity may result in expeditious
diagnostic treatments for infectious diseases. In addition, this accumulation in E. coli could
be attributed to the amino acid transport systems being different from those found in
human tumor cells.
Author Contributions: Conceptualization, Y.M., M.K. and K.K.; methodology, Y.N., K.N., N.S. and
S.O. (Shigefumi Okamoto); investigation, Y.M., M.M., A.M., K.S., A.K. and S.O. (Shusei Ohata);
writing—original draft preparation, Y.M.; writing—review and editing, K.Y., R.N., M.K. and K.K. All
authors have read and agreed to the published version of the manuscript.
Funding: This study was funded, in part, by Grants-in-Aid for Scientific Research from the Japan
Society for the Promotion of Science (Nos. 18K19508, 21H02865, 21K15774, 22H03016 and 22K195042)
and the Network-type Joint Usage/Research Center for Radiation Disaster Medical Science. Also
this work was supported by JST, the establishment of university fellowships towards the creation ofscience technology innovation (Grant No. JPMJFS2116).
Institutional Review Board Statement: The animal study protocol was approved by the Institutional
Review Board of Kanazawa University (protocol code AP-183983 and date of approval 26 March 2021).
Informed Consent Statement: Not applicable.
Data Availability Statement: The authors confirm that the data supporting the findings of this study
are available within the article.
Acknowledgments: The authors would like to thank Mikie Ohtaki, Akane Yonezawa, and the staffof the Faculty of Health Sciences, Kanazawa University, for their valued contributions to the study.
Conflicts of Interest: Yuri Nishiyama is an employee of Shionogi & Co., Ltd.

References
1.

2.
3.
4.
5.
6.
7.
8.

9.

Cassini, A.; Högberg, L.D.; Plachouras, D.; Quattrocchi, A.; Hoxha, A.; Struelens, M.J.; Suetens, C.C.; Monnet, D.L. Attributable
deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European
Economic Area in 2015: A population-level modelling analysis. Lancet Infect. Dis. 2018, 19, 56–66. [CrossRef] [PubMed]
Kraker, M.E.A.; Stewardson, A.J.; Harbarth, S. Will 10 Million People Die a Year due to Antimicrobial Resistance by 2050? PLoS
Med. 2016, 13, e1002184. [CrossRef] [PubMed]
O’Neill, J. The Review on Antimicrobial Resistance. In Tackling Drug Resistant Infections Globally: Final Report and Recommendations;
Wellcome Trust and the Department of Health of United Kingdom Government: London, UK, 2016.
Bunschoten, A.; Welling, M.M.; Termaat, M.F.; Sathekge, M.; van Leeuwen, F.W.B. Development and Prospects of DedicatedTracers for the Molecular Imaging of Bacterial Infections. Bioconjug. Chem. 2013, 24, 1971–1989. [CrossRef]
Vogel, S.J.; Tank, M.; Goodyear, N. Variation in detection limits between bacterial growth phases and precision of an ATP
bioluminescence system. Lett. Appl. Microbiol. 2014, 58, 370–375. [CrossRef] [PubMed]
Schöder, H.; Larson, S.M. Positron emission tomography for prostate, bladder, and renal cancer. Semin. Nucl. Med. 2004, 34,
274–292. [CrossRef] [PubMed]
Hess, S.; Blomberg, B.A. The pivotal role of FDG-PET/CT in modern medicine. Acad. Radiol. 2014, 21, 232–249. [CrossRef]
Duclos, V.; Iep, A.; Gomez, L.; Goldfarb, L.; Besson, F.L. PET Molecular Imaging: A Holistic Review of Current Practice andEmerging Perspectives for Diagnosis, Therapeutic Evaluation and Prognosis in Clinical Oncology. Int. J. Mol. Sci. 2021, 16, 4159.
[CrossRef]
Kumar, R.; Basu, S.; Torigian, D.; Anand, V.; Zhuang, H.; Alavi, A. Role of modern imaging techniques for diagnosis of infectionin the era of 18 F-fluorodeoxyglucose positron emission tomography. Clin. Microbiol. Rev. 2008, 21, 209–224. [CrossRef]

Int. J. Mol. Sci. 2023, 24, 4775

10.
11.

12.

13.
14.

15.

16.

17.

18.
19.
20.
21.

22.

23.

10 of 10

Love, C.; Tomas, M.B.; Tronco, G.G.; Palestro, C.J. FDG PET of infection and inflammation. Radiographics 2005, 25, 1368–1375.
[CrossRef]
Heuker, M.; Sijbesma, J.W.A.; Aguilar, S.R.; de Jong, J.R.; Boersma, H.H.; Luurtsema, G.; Elsinga, P.H.; Glaudemans, A.W.J.M.; Van
Dam, G.M.; Van Dijl, J.M.; et al. In vitro imaging of bacteria using 18 F-fluorodeoxyglucose micro positron emission tomography.
Sci. Rep. 2017, 7, 4973. [CrossRef]
Britton, K.E.; Wareham, D.W.; Das, S.S.; Solanki, K.K.; Amaral, H.; Bhatnagar, A.; Katamihardja, A.H.; Malamitsi, J.; Moustafa,
H.M.; Soroa, V.E.; et al. Imaging bacterial infection with 99m Tc-ciprofloxacin (Infecton). J. Clin. Pathol. 2002, 55, 817–823. [CrossRef][PubMed]Bonnet, M.; Lagier, J.C.; Raoult, D.; Khelaifia, S. Bacterial culture through selective and non-selective conditions: The evolution ofculture media in clinical microbiology. New Microbes New Infect. 2020, 30, 100622. [CrossRef] [PubMed]
Okudaira, H.; Shikano, N.; Nishii, R.; Miyagi, T.; Yoshimoto, M.; Kobayashi, M.; Ohe, K.; Nakanishi, T.; Tamai, I.; Namiki, M.;
et al. Putative transport mechanism and intracellular fate of trans-1-amino-3-18 F-fluorocyclobutanecarboxylic acid in humanprostate cancer. J. Nucl. Med. 2011, 52, 822–829. [CrossRef] [PubMed]
Kobayashi, M.; Mizutani, A.; Nishi, K.; Nakajima, S.; Shikano, N.; Nishii, R.; Fukuchi, K.; Kawai, K. Differences in accumulationand the transport mechanism of L- and D-methionine in high- and low-grade human glioma cells. Nucl. Med. Biol. 2017, 44,
78–82. [CrossRef] [PubMed]
Kobayashi, M.; Hashimoto, F.; Ohe, K.; Nadamura, T.; Nishi, K.; Shikano, N.; Nishii, R.; Higashi, T.; Okazawa, H.; Kawai, K.
Transport mechanism of 11 C-labeled L-and D-methionine in human-derived tumor cells. Nucl. Med. Biol. 2012, 39, 1213–1218.
[CrossRef]
Nishii, R.; Higashi, T.; Kagawa, S.; Arimoto, M.; Kishibe, Y.; Takahashi, M.; Yamada, S.; Saiki, M.; Arakawa, Y.; Yamauchi, H.; et al.
Differential Diagnosis between Low-Grade and High-Grade Astrocytoma Using System A Amino Acid Transport PET Imaging
with C-11-MeAIB: A Comparison Study with C-11-Methionine PET Imaging. Contrast Media Mol. Imaging 2018, 2018, 1292746.
[CrossRef]
Zhou, Y.; Imlay, J.A. Escherichia coli K-12 Lacks a High-Affinity Assimilatory Cysteine Importer. mBio 2020, 11, e01073-20.
[CrossRef]
Auer, G.K.; Weibel, D.B. Bacterial Cell Mechanics. Biochemistry 2017, 56, 3710–3724. [CrossRef]
Vollmer, W.; Blanot, D.; de Pedro, M.A. Peptidoglycan structure and architecture. FEMS Microbiol. Rev. 2008, 32, 149–167.
[CrossRef]
Muranaka, Y.; Mizutani, A.; Kobayashi, M.; Nakamoto, K.; Matsue, M.; Takagi, F.; Okazaki, K.; Nishi, K.; Yamazaki, K.; Nishii, R.;
et al. 123 I-BMIPP, a Radiopharmaceutical for Myocardial Fatty Acid Metabolism Scintigraphy, Could Be Utilized in Bacterial
Infection Imaging. Pharmaceutics 2022, 14, 1008. [CrossRef]
Schneider, D.W.; Heitner, T.; Alicke, B.; Light, D.R.; McLean, K.; Satozawa, N.; Parry, G.; Yoo, J.; Lewis, J.S.; Parry, R. In vivo
biodistribution, PET imaging, and tumor accumulation of 86 Y- and 111 In-antimindin/RG-1, engineered antibody fragments in
LNCaP tumor-bearing nude mice. J. Nucl. Med. 2009, 50, 435–443. [CrossRef] [PubMed]
Wick, W.E.; Preston, D.A.; White, W.A.; Gordee, R.S. Compound 64716, a new synthetic antibacterial agent. Antimicrob. Agents
Chemother. 1973, 4, 415–420. [CrossRef] [PubMed]

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