TYPE
Original Research
PUBLISHED
05 April 2024
DOI
10.3389/fmicb.2024.1338486
OPEN ACCESS
EDITED BY
Shuhei Ono,
Massachusetts Institute of Technology,
United States
REVIEWED BY
Naohiko Ohkouchi,
Japan Agency for Marine-Earth Science and
Technology (JAMSTEC), Japan
Jeemin H. Rhim,
University of California, Santa Barbara,
United States
*CORRESPONDENCE
Shaelyn N. Silverman
ssilverman@caltech.edu
†
PRESENT ADDRESS
Reto S. Wijker,
Geological Institute, Department of Earth
Sciences, ETH Zürich, Zürich, Switzerland
RECEIVED
14 November 2023
ACCEPTED
20 February 2024
PUBLISHED
05 April 2024
CITATION
Silverman SN, Wijker RS and Sessions AL
(2024) Biosynthetic and catabolic pathways
control amino acid
δ
2
H values in aerobic
heterotrophs.
Front. Microbiol.
15:1338486.
doi: 10.3389/fmicb.2024.1338486
COPYRIGHT
©
2024 Silverman, Wijker and Sessions. This is
an open-access article distributed under the
terms of the
Creative Commons Attribution
License (CC BY)
. The use, distribution or
reproduction in other forums is permitted,
provided the original author(s) and the
copyright owner(s) are credited and that the
original publication in this journal is cited, in
accordance with accepted academic practice.
No use, distribution or reproduction is
permitted which does not comply with these
terms.
Biosynthetic and catabolic
pathways control amino acid
δ
2
H
values in aerobic heterotrophs
Shaelyn N. Silverman
*
, Reto S. Wijker
†
and Alex L. Sessions
Division of Geological and Planetary Sciences, California Insti
tute of Technology, Pasadena, CA,
United States
The hydrogen isotope ratios (
δ
2
H
AA
values) of amino acids in all organisms are
substantially fractionated relative to growth water. In additio
n, they exhibit large
variations within microbial biomass, animals, and human tissue
s, hinting at rich
biochemical information encoded in such signals. In lipids, such
δ
2
H variations
are thought to primarily reflect NADPH metabolism. Analogous
biochemical
controls for amino acids remain largely unknown, but must be elu
cidated to
inform the interpretation of these measurements. Here, we me
asured the
δ
2
H
values of amino acids from five aerobic, heterotrophic microbes
grown on
di erent carbon substrates, as well as five
Escherichia coli
mutant organisms
with perturbed NADPH metabolisms. We observed similar
δ
2
H
AA
patterns
across all organisms and growth conditions, which–consistent with
previous
hypotheses–suggests a first-order control by biosynthetic p
athways. Moreover,
δ
2
H
AA
values varied systematically with the catabolic pathways activated
for
substrate degradation, with variations explainable by the is
otopic compositions
of important cellular metabolites, including pyruvate and NAD
PH, during growth
on each substrate. As such, amino acid
δ
2
H values may be useful for interrogating
organismal physiology and metabolism in the environment, p
rovided we can
further elucidate the mechanisms underpinning these signals
.
KEYWORDS
amino acids, hydrogen isotopes, isotope fractionation, aerob
ic metabolism,
heterotrophic bacteria, pyruvate, NADPH
1 Introduction
Stable hydrogen isotope analysis of amino acids (
δ
2
H
AA
) is receiving growing attention
due to its potential utility as a tracer of ecological and/or physiological processes, as well
as the extreme fractionations recorded in laboratory-grown and natural organisms. In
the first published study on terrestrial
δ
2
H
AA
values,
Fogel et al.
(
2016
) discovered large
(>100‰) variations in
δ
2
H
AA
values in
Escherichia coli
cultured on glucose or tryptone
(a complex protein source) in different growth waters, with two key insights emerging
from their study: (1) patterns of
δ
2
H
AA
values may be driven by ubiquitous biochemical
mechanisms associated with amino acid synthesis in organisms, and (2) hydrogen can be
directly routed from organic substrates, or incorporated from water via de novo amino acid
synthesis, to variable extents depending on the protein content of the medium. Expanding
this work to an animal model,
Newsome et al.
(
2020
) observed that hydrogen sources
of amino acids in mouse muscle tissue are driven by similar metabolic factors as
E. coli
,
but that carbohydrates and amino acids from both the diet and gut microbiome are
particularly important hydrogen sources. Recently,
Gharibi et al.
(
2022a
) reported extreme
2
H-enrichments in proline and hydroxyproline (
δ
2
H values >1,000‰) from seal bone
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10.3389/fmicb.2024.1338486
collagen, although the cause of these extreme
δ
2
H values was
not identified.
Smith et al.
(
2022
) ruled out growth rate as a
primary control on
δ
2
H
AA
values in
E. coli
and revealed that
carbon and hydrogen isotope compositions of amino acids are
governed by different biochemical factors. Drawing on the well-
known spatial variations in precipitation isotope ratios (
Craig,
1961
;
Dansgaard, 1964
;
Rozanski et al., 1993
;
Kendall and
Coplen, 2001
;
Poage and Chamberlain, 2001
),
Mancuso et al.
(
2023
) revealed the first systematic link between
δ
2
H
AA
values
in human tissue (scalp hair) and local water
δ
2
H, supporting
the utility of this compound-specific tool as a potential tracer
of geographical origin (
Rubenstein and Hobson, 2004
;
Bowen
et al., 2005
). Together, these results encourage a variety of
potential exciting applications of
δ
2
H
AA
analysis across diverse
fields such as ecology, archaeology, microbiology, biogeochemistry,
and forensics. However, these applications are limited by our lack
of fundamental understanding of which biochemical controls set
δ
2
H
AA
values in terrestrial organisms.
Here we seek to elucidate some of the mechanistic controls on
biological
δ
2
H
AA
values. We focus on microbes, which are simpler
systems than animals because most microbes are unicellular, can
synthesize all 20 amino acids (
Price et al., 2018
), and can be grown
in defined media. Furthermore, microbes are the major drivers
of biogeochemical processes such as energy and nutrient cycling
in the environment (
Falkowski et al., 2008
), so understanding
how their
δ
2
H
AA
values relate to their metabolic activities may
render
δ
2
H
AA
analysis a useful tool for interrogating the critical
microbial-driven changes to our planet’s surface geochemistry.
Amino acids are formed via biosynthetic pathways that are
ubiquitous across most forms of life. Their carbon skeleton
precursors are the intermediates of central metabolic pathways
(
Figure 1
), and the hydrogen on each amino acid is derived
from different combinations of sources, including the organic
precursors, water, and NAD(P)H. As such,
δ
2
H
AA
values are
complicated to interpret, but may contain multiple layers of useful
biochemical information.
In this study, we investigated the
δ
2
H values of amino
acids from the biomass of five aerobic, heterotrophic
bacteria that was previously generated for lipid
δ
2
H analysis
(
Wijker et al., 2019
). The organisms included
E. coli
,
Bacillus subtilis
,
Ensifer meliloti
,
Pseudomonas fluorescens
,
and
Rhizobium radiobacter
, as well as five mutant
E. coli
organisms lacking specific dehydrogenase or transhydrogenase
enzymes. These organisms were grown on different carbon
substrates, including on glucose for which their metabolic
fluxes were characterized (
Wijker et al., 2019
), enabling
investigation of the mechanistic link between
δ
2
H
AA
values
and microbial metabolism. This experimental system provides
the opportunity to test a number of hypotheses about the
mechanisms that govern amino acid
δ
2
H values, including
whether NADPH metabolism is a primary control (the case
for lipids;
Zhang et al., 2009
;
Wijker et al., 2019
), and how
varied fluxes through specific enzymes in central metabolism
affect
δ
2
H
AA
values. We targeted five amino acids–proline,
phenylalanine, leucine, valine, and isoleucine–which were selected
because (1) they span different parts of central metabolism
(
Figure 1
), and (2) their hydrogen isotope compositions
are among the most reliable to interpret, as these amino
acids exhibit consistent baseline chromatographic separation
(
Supplementary Figure S1
), have relatively high ionization
efficiencies, and maintain stable hydrogen isotope compositions
through hydrolysis and derivatization (
Supplementary Figures S9
,
S10
;
Supplementary Table S4
;
Silverman et al., 2022
; for further
details, see
Supplementary Section 1
). We provide hypotheses
for the observed
δ
2
H
AA
patterns within and across organisms
cultured under different conditions. As such, we aim to elucidate
the underlying mechanisms that control
2
H/
1
H fractionation in
these five amino acids.
Additionally,
δ
2
H
AA
analyses to-date have been hampered
by the presence of “labile” organic hydrogen in the amine (–
NH
2
) and carboxyl (–COOH) groups, which readily exchange with
hydrogen in both water and ambient water vapor. Derivatization
of amino acids removes the carboxyl- and one amine-bound
hydrogen, but the remaining amine hydrogen cannot be excluded
from the measured isotopic composition, and may dilute or
obscure biological signals (i.e., those of non-exchangeable, C-
bound hydrogen in the amino acids) and furthermore lead to
incomparable results across laboratories. Previous studies (
Fogel
et al., 2016
;
Newsome et al., 2020
;
Smith et al., 2022
;
Mancuso
et al., 2023
) have attempted to correct for the contribution of
derivative and exchangeable hydrogen to measured
δ
2
H
AA
values
through the use of amino acid standards, whereby the
δ
2
H
values of underivatized amino acid powders pre-equilibrated with
ambient water vapor (following the comparative equilibration
method;
Wassenaar and Hobson, 2003
) are measured via a
high-temperature conversion elemental analyzer coupled to an
isotope ratio mass spectrometer, then subtracted via mass balance
from the
δ
2
H values of corresponding derivatized amino acids.
The central issue with this approach is that hydrogen in the
derivative reagents, derivatized amino acids, and underivatized
amino acids cannot be mass balanced, as (1) the isotopic
fractionations between the exchangeable hydrogen and water
(or ambient moisture) are unknown, thus the
δ
2
H values
of the carboxyl and amine hydrogen atoms removed during
derivatization cannot be properly accounted for, and (2) the
isotopic fractionation between the amine-bound hydrogen and
water likely differs when amino acids are in derivatized (possessing
a secondary amine) vs. underivatized (primary amine) form, so
knowledge of the amine hydrogen
δ
2
H value in the latter case
may not help correct for exchangeable hydrogen in the former
case. Independent measurements of the derivative reagent
δ
2
H
values are possible in some cases, but without accompanying
correction for the amine-bound hydrogen in derivatized amino
acids, errors in the reported
δ
2
H values of amino acid carbon-
bound hydrogen may be significant (on the order of 10 to
100‰;
Supplementary Figure S7
;
Supplementary Section 4
). Here
we have developed a new, simple procedure for controlling this
exchangeable amine-bound hydrogen based on separate oxidation
and derivatization of a diamine compound to obtain the combined
δ
2
H value of our amine group derivative and the exchangeable
hydrogen. By subtracting the isotopic contribution of both the
derivative hydrogen and exchangeable amine-bound hydrogen, we
are able to accurately calculate the
δ
2
H value of pure carbon-bound
hydrogen in amino acids.
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FIGURE 1
Simplified schematic of biosynthetic pathways (showing end-m
ember compounds), central metabolic pathway precursors, and hy
drogen sources
for the five amino acids investigated in this study (proline, phe
nylalanine, leucine, valine, isoleucine). Hydrogen atoms are v
isually tracked from
source to amino acid through colors: green indicates hydrogen from NAD(
P)H, light blue from water, and the remaining colors correspond to
hydrogen from organic precursors. Solid arrows denote single metabolic r
eactions; dashed arrows encompass multiple steps. Although NAD(
P)H is
used to reduce substrates in all amino acid biosynthetic path
ways, some NAD(P)H-derived hydrogen is subsequently lost due to
elimination or
equilibration with water (see detailed biosynthetic pathway
s in
Supplementary Figures S16
–
S19
). EMP, Embden-Meyerhof-Parnas; ED,
Entner-Doudoro ; PP, pentose phosphate; TCA, tricarboxylic ac
id.
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FIGURE 2
Derivatization scheme for amino acids and methods used to measu
re
δ
2
H values of derivative reagents.
(A)
Amino acids were derivatized with
anhydrous methanol, pyridine, and methyl chloroformate in 0.1N
HCl; see Section 2.2 for details. The exchangeable amine hydrogen
atom (blue in
derivatized product) was equilibrated in the solvent (0.1N HC
l), which was prepared using the same water supply as that use
d to equilibrate the
N-bound hydrogen in the dimethyl 1,4-phenylenedicarbamate pr
oduct [DCP; depicted in
(C)
].
(B)
The
δ
2
H value of anhydrous methanol was
measured by derivatizing disodium phthalate with known isotopic
composition (
Sessions et al., 2002
) with anhydrous methanol in acetyl chloride
(AcCl); see Section 2.5 for details.
(C)
The
δ
2
H value of methyl chloroformate was measured by first oxidizing
p
-phenylenediamine (PPD) to
dinitrobenzene (DNB) to obtain the aromatic hydrogen
δ
2
H value (top reaction), then separately derivatizing PPD with
methyl chloroformate to
produce the DCP (bottom reaction). DCP was purified, then dissolve
d in a 1:1 (v/v) mixture of anhydrous methanol:water to equilibra
te the N-bound
hydrogen atoms before extraction and measurement via GC/P/IRMS.
See Section 2.5 for details.
2 Materials and methods
2.1 Strain and culture conditions
The microbial biomass measured here was generated in a prior
study targeting lipid
δ
2
H analysis (
Wijker et al., 2019
); all relevant
culturing details are recapitulated here. Five wildtype aerobic
heterotrophic microbes (
Escherichia coli
MG1655,
Bacillus subtilis
PY79,
Ensifer meliloti
Young 2003,
Pseudomonas fluorescens
2-79,
and
Rhizobium radiobacter
C58) and five mutant
E. coli
organisms
carrying specific deletions of dehydrogenase or transhydrogenase
genes (glucose 6-phosphate dehydrogenase deleted in JW1841,
phosphoglucose isomerase deleted in JW3985, membrane-bound
transhydrogenase deleted in PntAB, soluble transhydrogenase
deleted in UdhA, and both transhydrogenases deleted in UdhA-
PntAB) were cultured on unlabeled glucose for hydrogen isotope
analysis, and on
13
C-labeled glucose (100% 1-
13
C-glucose and a
mixture of 20% (wt/wt) U-
13
C
6
-glucose + 80% (wt/wt) unlabeled
glucose) for metabolic flux analysis. The relative metabolic fluxes
were calculated based on the
13
C-labeling pattern of proteinogenic
amino acids—see
Wijker et al.
(
2019
) for more details. Wildtype
organisms were additionally cultured on acetate, citrate, fructose,
pyruvate, and/or succinate in an isotopically constant growth water;
as well as on glucose in growth waters with different isotopic
compositions, which were manipulated by adding specific volumes
of 99.9% purity D
2
O to distilled, deionized water. Each organism
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was grown with 4 g/L of carbon source in M9 minimal medium
(prepared as described in
Fuhrer et al., 2005
) in batch culture on
a rotary shaker at 200 rpm, thereby ensuring aerobic conditions
were maintained and fermentation was avoided throughout the
course of the experiments. The carbon source served as the limiting
nutrient in each culture, causing cells to transition to stationary
growth phase upon depletion.
B. subtilis
and
R. radiobacter
cultures
were supplemented with a vitamin mixture, while strains JW1841
and JW3985 were given 50
g/mL of kanamycin.
B. subtilis
and
E. coli
cultures were incubated at 37
◦
C; all other organisms were
incubated at 30
◦
C. All wildtype cultures were prepared in duplicate
except for organisms grown in D
2
O-spiked media (for growth
water experiments) and for
E. coli
, which was grown on pyruvate
and acetate in single cultures, and on glucose in two non-replicate
cultures: culture #1 was grown along with the rest of the wildtype
organisms,
E. coli
mutants, and growth water experiments for non-
E. coli
organisms; culture #2 was grown at a later date as one of four
cultures in
E. coli
growth water experiments. Although culturing
conditions were identical between
E. coli
cultures #1 and #2 grown
on glucose, the different timing of culturing, and different methods
used to process the biomass (see Section 2.2), renders culture #2 a
repeat experiment, but not true biological replicate, to culture #1.
Culture growth was monitored by measuring optical density at 600
nm (OD
600
), and cells were harvested in late-exponential phase,
lyophilized, and stored at -80
◦
C until further processing for lipid
and amino acid
δ
2
H analysis (
Wijker et al., 2019
and this study,
respectively).
2.2 Amino acid hydrolysis, derivatization,
extraction, and quantification
A 10–20 mg of dry biomass from each sample was hydrolyzed
anoxically in 6N HCl at 110
◦
C for 24 h in tightly capped VOA
vials. Following hydrolysis, samples were uncapped and left on
the hot plates until the 6N HCl was completely evaporated, then
samples were resuspended in 0.5 ml of 0.1N HCl. Amino acids
in all samples except
E. coli
culture #2 were derivatized with
7:6:3 (v/v/v) anhydrous methanol (MeOH), pyridine, and methyl
chloroformate (MCF); reagents were added at room temperature,
then samples were immediately capped and sonicated for
∼
5 min
(procedure adapted from
Hu
̆
sek, 1991a
,
b
and
Zampolli et al.,
2007
).
E. coli
culture #2 was derivatized with the same reagent
bottles and reaction procedure as the other samples, but was
placed on dry ice while derivative reagents were added to slow
the derivatization reaction. Note that in contrast to most published
δ
2
H
AA
studies (
Fogel et al., 2016
;
Newsome et al., 2020
;
Smith et al.,
2022
;
Mancuso et al., 2023
), we avoid using fluorinated derivative
reagents, as hydrofluoric acid can form during pyrolysis in the
gas chromatograph/isotope ratio mass spectrometer (GC/IRMS),
leading to potential hydrogen isotope fractionation (
Sauer et al.,
2001
;
Renpenning et al., 2017
;
Silverman et al., 2022
).
The resulting methoxycarbonyl (MOC) esters (
Figure 2A
)
were extracted twice with methyl tert-butyl ether (MTBE) and
filtered through a sodium sulfate column to adsorb any water
present. Samples were concentrated to
∼
0.25–0.5 ml under N
2
.
MOC ester peaks were identified via gas chromatography/mass
spectrometry (GC/MS) on a Thermo-Scientific Trace ISQ equipped
with a Zebron ZB-5 ms column (30-m
×
0.25-mm i.d., 0.25
m
film thickness) and programmable temperature vaporizing (PTV)
injector operated in splitless mode, using He as a carrier gas
(flow rate = 1.4 ml/min). The GC oven was held at 80
◦
C for 1
min, ramped at 5
◦
C/min to 280
◦
C with no hold, then ramped at
20
◦
C/min to 310
◦
C with a final 5 min temperature hold. Peaks
were identified by comparing the relative retention times and mass
spectra to those of known MOC ester standards, as well as to mass
spectra in the NIST MS Library database.
2.3 Isotope analysis
The
δ
2
H values of MOC esters were measured by a gas
chromatograph coupled to an isotope ratio mass spectrometer
(Thermo Finnigan Delta
+
XP) using a pyrolysis interface (i.e.,
GC/P/IRMS). Chromatographic separation was achieved on a
thick-film Zebron ZB-5ms column (30-m
×
0.25-mm i.d., 1.00
m
film thickness) with a nearly identical chromatographic method as
used in GC/MS analysis [exceptions included a higher carrier gas
flow rate (1.7 ml/min) and slight modifications to the temperature
program to optimize MOC ester separation] so peaks could
be identified by retention order and relative height. Measured
isotope ratios were calibrated using hydrogen gas of known
isotopic composition and are reported in
δ
notation (in units of
‰, or parts per thousand;
Urey, 1948
;
McKinney et al., 1950
)
relative to the Vienna Standard Mean Ocean Water (VSMOW)
international standard (
δ
2
H =
R
AA
/
R
VSMOW
−
1), where
R
=
2
H/
1
H. Additionally, an eight-compound fatty acid methyl ester
standard mixture was analyzed between every 5–6 samples to
verify instrument accuracy and precision. Samples were analyzed
in triplicate, and the MOC ester
δ
2
H values were corrected for the
addition of methyl hydrogen from the derivative reagents, as well
as for the remaining exchangeable amine hydrogen (see Section
2.5). The standard deviation of triplicate analyses for individual
amino acids was typically
≤
6‰. The average root-mean-square
error of the external FAME standard was 3.2‰ across all analyses.
δ
2
H values of the culture media (
δ
2
H
w
) were measured previously
using a Los Gatos Research DLT-100 liquid water isotope analyzer
and calibrated against up to four working standards with
δ
2
H
values ranging from –73 to +458‰ (
Wijker et al., 2019
). Data
are reported as apparent fractionations between amino acids (AA)
and culture medium water (w) according to the equation
2
ε
AA/w
= (
δ
2
H
AA
+
1)/(
δ
2
H
w
+
1)
−
1, with uncertainty propagated as
Equation 1
σ
ε
=
(
δ
2
H
AA
+
1
δ
2
H
w
+
1
)
√
(
σ
AA
δ
2
H
AA
+
1
)
2
+
(
σ
w
δ
2
H
w
+
1
)
2
(1)
2.4 Hydrolysis and derivatization tests for
isotopic alteration
Potential changes in amino acid isotopic compositions during
acid hydrolysis were investigated by varying the hydrolysis
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conditions used (temperature, duration, and O
2
presence). For
a control treatment, standard bovine serum albumin (BSA) was
hydrolyzed in 6N HCl for 24 h at 110
◦
C under anoxic conditions
(achieved by sparging samples with N
2
for 2 min with vigorous
shaking). Variations on these conditions were achieved by either
hydrolyzing BSA (1) without sparging with N
2
(oxic hydrolysis),
(2) at 105
◦
C, or (3) for 20 or 48 h. All conditions were prepared in
duplicate. Amino acids were derivatized to MOC esters, extracted,
and analyzed via GC/P/IRMS using methods described in Sections
2.2, 2.3.
Additionally, to test for hydrogen isotope exchange with
aqueous medium during hydrolysis and derivatization (
Hill and
Leach, 1964
;
Fogel et al., 2016
;
Silverman et al., 2022
), BSA and a
mixture of pure amino acid standards were separately hydrolyzed
(6N HCl, 24 h, 110
◦
C, oxic) and derivatized (0.1N HCl, 7:2:3
v/v/v anhydrous MeOH, pyridine, MCF) in aqueous solvent with
different hydrogen isotope compositions.
2.5 Correction for derivative and
exchangeable amine hydrogen
To determine the
δ
2
H value of MeOH, 100
g of disodium
phthalate with known isotopic composition (
Sessions et al., 2002
)
was derivatized in 2 ml of 20:1 (v/v) anhydrous MeOH:acetyl
chloride (70
◦
C, 30 min;
Figure 2B
). The derivatized product was
extracted with 4 ml of 1:1 water:hexane, then measured by
GC/P/IRMS, and contribution of disodium phthalate hydrogen was
subtracted by mass balance.
The combined
δ
2
H value of MCF and the remaining
exchangeable amine hydrogen was characterized via derivatization
of
p
-phenylenediamine (PPD)—a compound with two primary
amine groups—with MCF and separate oxidation of PPD to
dinitrobenzene (DNB), which has no nitrogen-bound hydrogen.
One hundred mM of PPD was dissolved in 5 ml of anoxic
dichloromethane with 3 eq. triethylamine (pre-distilled with CaH
2
to remove any HCl generated in the reaction) and 0.1 eq. 4-
dimethylamino pyridine, and was subsequently derivatized via
an overnight reaction with 2.5 eq. MCF to yield dimethyl 1,4-
phenylenedicarbamate (hereafter, “dicarbamate product”, or DCP
in
Equation 2
;
Figure 2C
). The DCP was purified via flash column
chromatography with silica gel. Five mg of DCP was dissolved in 2
ml of anhydrous MeOH, then 2 ml of distilled, deionized water was
slowly added. The solution was mixed on a shaker for 2 h to ensure
complete equilibration of the two amine hydrogen atoms with
water, then the DCP was extracted once with 4 ml MTBE, filtered
through a sodium sulfate column, and analyzed by GC/P/IRMS. In
a separate reaction, PPD was oxidized to DNB using 8 eq. of
m
-
chloroperbenzoic acid added under refluxing 1,2-dichloroethane in
a procedure adapted from
Liu et al.
(
2014
) (
Figure 2C
). DNB was
purified via flash column chromatography with silica gel, then 3 mg
of DNB was dissolved in MTBE and analyzed via GC/P/IRMS. The
δ
2
H value of MCF and the exchangeable nitrogen-bound hydrogen
(MCF+NH) was obtained by solving for
F
MCF+NH
in the mass
balance equation
12
F
DCP
=
8
F
MCF
+
NH
+
4
F
DNB
(2)
where
F
is the fractional abundance (i.e., mole fraction) of
2
H
in each compound. PPD was chosen for these reactions (1) because
of the favorable 8/4 ratio of (MCF + amine)/aromatic hydrogen
in the dicarbamate product, and (2) because the exchangeable
amine hydrogen atoms on the dicarbamate product and on MOC
esters should have similar hydrogen isotope compositions when
equilibrated in the same water supply, as the amine hydrogen
in the dicarbamate product and in MOC esters share similar
intramolecular bonding environments so should be controlled
by similar equilibrium
2
H/
1
H fractionation factors at a constant
temperature (
Wang et al., 2009
).
3 Results
3.1 Derivative correction
Hydrogen atoms on amine and carboxyl groups rapidly
exchange with water so do not contribute information about native
δ
2
H
AA
values. Derivatization of the carboxyl group removes the
exchangeable hydrogen, but derivatization of the amine group
removes only one of the two exchangeable hydrogen atoms
(
Figure 2A
). In order to determine the isotope compositions of
the native, non-exchangeable (i.e., carbon-bound) hydrogen on
the amino acids, it is necessary to correct
δ
2
H
AA
values not
only for the added derivative (MeOH and MCF) hydrogen, but
also for the exchangeable amine hydrogen atom remaining after
derivatization. A suitable method for this latter correction has
eluded prior studies of
δ
2
H
AA
thus far, yet is imperative, as
errors in reported
δ
2
H
AA
values can be on the order of 10 to
100‰ when the amine-bound hydrogen is improperly accounted
for (
Supplementary Figure S7
;
Supplementary Section 4
). Here we
developed a method to characterize the combined
δ
2
H values of
MCF and the exchangeable amine hydrogen by derivatizing PPD
with MCF, separately oxidizing PPD to DNB (which removes all
four of the nitrogen-bound hydrogens;
Figure 2C
), and analyzing
both resulting products using GC/P/IRMS. Importantly, this
approach requires derivatizing samples with the same reagents and
water as those used to measure PPD.
The
δ
2
H value of the MCF + amine hydrogen was –111.43
±
1.96‰ when equilibrated with water of
δ
2
H = –86.50
±
0.36‰. The
δ
2
H value of MeOH was –67.27
±
1.78‰. Correction
for these non-biological contributions generally shifted
δ
2
H
AA
values lower (
Figure 3
). For the relatively
2
H-depleted amino
acids (leucine, valine, and isoleucine), changes in
δ
2
H values were
substantial, reaching up to 123‰ for wildtype organisms grown
on glucose. For the relatively
2
H-enriched amino acids (proline
and phenylalanine), this correction resulted in small or negligible
changes, but in some cases resulted in higher
δ
2
H values. However,
note that correction of proline
δ
2
H values using this approach may
introduce small (<20‰) errors, as proline does not contain amine-
bound hydrogen after derivatization, but the isotopic composition
of MCF cannot be isolated from our measured
δ
2
H value for
MCF + amine hydrogen (see
Supplementary Section 4
). For other
researchers to adopt our correction method, they will need to re-
analyze PPD of known
δ
2
H (available by request) with their own
reagents and water.
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FIGURE 3
Size of derivative
δ
2
H corrections vs. native amino acid isotopic
compositions. Measured
δ
2
H
AA
values were corrected for derivative
and exchangeable amine hydrogen contributions (
δ
2
H
MeOH
=
–67.27
±
1.78
‰
,
δ
2
H
MCF+NH
= –111.43
±
1.96
‰
). Data displayed
are from one replicate of wildtype organisms grown on glucose
(shapes denote organisms as defined in the
lower right legend
).
Amino acids are denoted by colors
(upper left legend)
and
corresponding symbols are connected to highlight
compound-specific magnitudes of correction e ects. Horizontal
error bars (indicating the propagated uncertainties (
±
1
σ
) from the
amino acid and derivative measurements) are smaller than sy
mbols.
3.2 Tests for isotopic alteration during
sample preparation
Certain preparatory steps can alter the isotopic compositions
of amino acids (reviewed in
Silverman et al., 2022
). In particular,
degradation or non-quantitative recovery of amino acids during
acid hydrolysis can lead to isotopic fractionation (e.g.,
Bada et al.,
1989
;
Phillips et al., 2021
). To assess the isotopic consequences
of different hydrolysis conditions on
δ
2
H
AA
values, standard BSA
protein was hydrolyzed at different temperatures (105 or 110
◦
C),
for different durations (20, 24, or 48 h), anoxically or with O
2
present. Compared to conventional hydrolysis conditions (6N HCl,
110
◦
C, 20-24 h, anoxic;
Silverman et al., 2022
), no treatment
significantly altered the hydrogen isotope composition of amino
acids (
Supplementary Table S4
).
To investigate whether carbon-bound hydrogen in amino
acids exchanges with aqueous medium during hydrolysis or
derivatization, BSA and a mixture of amino acid standards were
separately hydrolyzed (6N HCl, 110
◦
C, 24 h) and derivatized
to MOC esters in solvents with different isotopic compositions.
Slopes of regressions of amino acid vs. water
δ
2
H values
(
Supplementary Figures S9
,
S10
) represent the equilibrium
fractionation factor (
α
eq
) between organic hydrogen and water,
multiplied by the fraction of hydrogen exchanged in the amino
acid. To estimate the maximum percent of carbon-bound hydrogen
exchanged, each slope was divided by
α
eq
= 0.9, an estimate based
on fractionation factors for a variety of hydrogen positions in
linear and cyclic organic molecules (
Wang et al., 2009
,
2013
).
These calculations indicate that ten amino acids experienced
negligible (<2%) hydrogen exchange with aqueous medium during
hydrolysis, while tryptophan experienced significant exchange
(
∼
27%;
Supplementary Figure S9
). Asparagine + aspartic acid
(Asx), glutamine + glutamic acid (Glx), and tyrosine experienced
moderate exchange (4%–10%); this effect has been previously
demonstrated through deuterated and tritiated hydrolysis
experiments (
Hill and Leach, 1964
;
Fogel et al., 2016
) and is
likely due to the increased lability of hydrogen adjacent to the
polar—R groups. Hydrogen exchange in tryptophan may have
occurred through a reversible reaction with sulfur-containing
amino acids in the presence of oxygen (common tryptophan
degradation mechanisms summarized in
Silverman et al., 2022
).
All amino acids experienced low (<2%) hydrogen exchange during
derivatization (
Supplementary Figure S10
).
3.3
2
H/
1
H fractionations and carbon fluxes
across wildtype organisms grown on
glucose
The substantial variations in
2
ε
AA/w
values within wildtype
organisms grown on glucose are summarized in
Figure 4A
and
Supplementary Table S2
for the five amino acids analyzed, and
in
Supplementary Figure S6
and
Supplementary Table S3
for the
other amino acids measured in this study. All organisms produced
similar
2
ε
AA/w
patterns, where phenylalanine and proline were
the most
2
H-enriched, while isoleucine and valine were the most
2
H-depleted. This pattern mirrors that previously observed for
E. coli
(
Fogel et al., 2016
), with the exception of phenylalanine,
which in our study was significantly more
2
H-enriched relative
to the average. Within a single organism, the five
2
ε
AA/w
values
spanned large ranges (220‰–352‰). Valine exhibited the largest
variation across organisms (190‰) while proline and leucine
2
ε
AA/w
values varied the least (86‰–93‰).
2
ε
AA/w
values from
biological replicates of wildtype organisms grown on glucose were
generally reproducible (within 30‰) except for phenylalanine and
isoleucine from
P. fluorescens
cultures (
Supplementary Figure S5
;
Supplementary Table S2
), which differed between replicates for
unknown reasons.
2
ε
AA/w
values in
E. coli
cultures grown on
glucose also differed by >30‰ for four of the amino acids, but these
cultures are not considered biological replicates due to differences
in sample preparation (see Sections 2.1, 2.2).
Metabolic flux analysis carried out in a previous study (
Wijker
et al., 2019
) revealed substantial differences in pathways used for
glucose breakdown and in carbon fluxes through central metabolic
enzymes (
Supplementary Figure S3
;
Supplementary Table S1
;
Wijker et al., 2019
).
E. coli
and
B. subtilis
primarily used the
EMP pathway for glucose catabolism and excreted high fluxes of
acetate. In contrast,
E. meliloti
and
R. radiobacter
mainly relied
on the ED pathway to metabolize glucose and exhibited moderate
fluxes through the TCA cycle.
P. fluorescens
exhibited high fluxes
through the ED pathway and TCA cycle, as well as periplasmic
conversion of glucose to gluconate and 2-ketogluconate, and cyclic
flux through the EDEMP pathway (
Nikel et al., 2015
;
Wijker et al.,
2019
).
2
ε
AA/w
values for leucine and valine correlated with carbon
fluxes through enzymes related to pyruvate synthesis: KDPG
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aldolase (ED pathway), PEP carboxykinase (anaplerotic pathway),
phosphoglucose isomerase (EMP pathway), pyruvate kinase
(EMP + ED pathways), and transketolase (PP pathway;
Figure 5
).
Directions of correlations between
2
ε
AA/w
values and carbon
flux through EMP and ED pathways opposed those observed for
lipid/water fractionations (
2
ε
L/w
, presented in
Wijker et al., 2019
),
although these relationships may not be directly comparable, as
2
ε
L/w
values are primarily controlled by NADPH metabolism
(
Zhang et al., 2009
;
Wijker et al., 2019
) while leucine and valine
do not inherit hydrogen from NADPH.
2
ε
AA/w
values for other
amino acids did not correlate with carbon flux through any central
metabolic enzyme in wildtype organisms.
3.4
2
H/
1
H fractionations and carbon fluxes
in
E. coli
knockout mutants grown on
glucose
Specific dehydrogenase and transhydrogenase genes were
deleted in
E. coli
organisms in a previous study (
Wijker et al.,
2019
) to interrogate the influence of NADPH on lipid
δ
2
H values.
Deletion of these genes forced carbon flux through alternative
central metabolic enzymes to accomplish glucose catabolism
and NADPH balance (
Supplementary Figure S4
;
Table S1
). Despite
drastic differences in the magnitudes of carbon fluxes,
E. coli
mutant organisms produced similar
2
ε
AA/w
values compared
to wildtype
E. coli
culture #1, differing by <40‰ for any
given amino acid (
Figure 4B
;
Supplementary Table S2
; see note
about
E. coli
culture #2 in Section 3.3). Lipid
δ
2
H values
showed a similar response in these organisms (
Wijker et al.,
2019
), as did
δ
2
H
AA
values in
E. coli
mutants with inhibited
glycolysis or oxidative pentose phosphate pathways in a previous
study (
Smith et al., 2022
). Nevertheless, variations in isotopic
compositions hint at some control by NADPH, as
δ
2
H
AA
values
correlated with carbon fluxes through all NADPH-related enzymes
(
Supplementary Figure S15
), with proline exhibiting the strongest
correlations (R
2
= 0.70–0.86), followed by phenylalanine (R
2
=
0.58–0.71), then isoleucine (R
2
= 0.36–0.49). The PGI knockout
mutant, JW3985, had a severely perturbed metabolism and fell
off the regressions in most cases so was excluded from the
regression analyses.
3.5
2
H/
1
H fractionations across wildtype
organisms grown on di erent substrates
In addition to glucose, wildtype organisms were cultured
on acetate, citrate, fructose, pyruvate, and/or succinate, which
enter central metabolism at different nodes and activate different
catabolic pathways for substrate breakdown.
2
ε
AA/w
values from
biological replicates of wildtype organisms grown on each substrate
were generally reproducible (within 30‰) except for proline and
phenylalanine in
B. subtilis
grown on succinate, and proline
in
R. radiobacter
grown on succinate, which differed between
replicates for unclear reasons (
Figure 6
,
Supplementary Figure S5
,
Supplementary Table S2
). Fructose led to similar
2
ε
AA/w
values as
glucose-based growth, while pyruvate and TCA cycle substrates
(acetate, citrate, and succinate) led to
2
H-enrichment of all amino
acids (
Figure 6
), mirroring phenomena observed for lipids (
Zhang
et al., 2009
;
Osburn et al., 2016
;
Wijker et al., 2019
). The amount
of
2
H-enrichment varied widely for each amino acid. Proline in
B. subtilis
grown on succinate, and isoleucine and phenylalanine
in
P. fluorescens
grown on acetate, exhibited the largest singular
2
H-enrichments (286‰–360‰ higher
2
ε
AA/w
values relative to
those during glucose-based growth). However, phenylalanine was
generally
2
H-enriched by the least amount (<100‰ difference
between
2
ε
Phe/w
values upon growth on TCA cycle substrates
relative to on glucose for all organisms except
P. fluorescens
), while
valine was generally
2
H-enriched by the greatest amount (142–
245‰). These differences were significantly greater than those
between growth water (<15‰) or substrate
δ
2
H values (<85‰;
Supplementary Table S2
).
4 Discussion
Consistencies in
2
ε
AA/w
patterns (i.e., the relative ordering
of
2
ε
AA/w
values) within each growth condition, coupled with
the substantial shifts in
2
ε
AA/w
values across growth conditions,
underscore the existence of systematic controls on
δ
2
H
AA
values.
Initial investigations (
Fogel et al., 2016
;
Newsome et al., 2020
;
Gharibi et al., 2022a
;
Smith et al., 2022
;
Mancuso et al., 2023
) have
begun to explore the complicated factors driving
δ
2
H
AA
signals in
heterotrophic microbes, mammals, and humans, but we are still far
from mechanistic understanding of these controls. In the following
sections we interrogate several biochemical controls on the patterns
and variations in microbial
δ
2
H
AA
values in an attempt to elucidate
how these signals can be used as tracers for microbial or ecological
studies in the environment (summarized in
Table 1
). Our data allow
us to provide a mechanistic explanation for some, though not all,
of the observed
2
ε
AA/w
patterns. As numerous enzymes in central
metabolism are referenced throughout the discussion, a schematic
of the central metabolic pathways with all enzymes annotated is
provided for reference (
Supplementary Figure S2
).
4.1 Controls on the
2
ε
AA/w
pattern during
glucose metabolism
2
ε
AA/w
patterns were strikingly similar across wildtype
organisms and
E. coli
mutants grown on all carbon substrates
(
Figures 4
,
6
), indicating that biosynthetic pathways (as opposed to
catabolic pathways) serve as first-order controls on
δ
2
H
AA
values.
Our interpretation is consistent with
Fogel et al.
(
2016
), who
observed similar
δ
2
H
AA
patterns in
E. coli
cultured on glucose or
tryptone in different growth waters. In this section, we investigate
the biochemical factors that set the general
2
ε
AA/w
pattern in
glucose-grown cultures, focusing our interpretation on hydrogen
sources and mechanisms of hydrogen exchange, as well as relevant
isotope effects associated with enzymes in central metabolic and
biosynthetic pathways. Based on these interpretations, we speculate
on the most prominent types of biological information that can be
obtained from
δ
2
H
AA
measurements. Amino acids are discussed
in order from most to least
2
H-enriched. As these microbes
share the same biosynthetic pathways, variations in
2
ε
values of
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FIGURE 4
Summary of
2
H/
1
H fractionations between amino acids and water in wildtype organi
sms
(A)
and in
E. coli
wildtype (WT) and mutant organisms
(B)
grown on glucose. Wildtype cultures were grown in biological duplicate
, except for
E. coli
, which was grown in two non-replicate cultures (see
Sections 2.1, 2.2) distinguished by blue and gray symbols for cult
ures #1 and #2, respectively. Error bars indicate the propagated u
ncertainties (
±
1
σ
)
from the amino acid, derivative, and water measurements and ar
e smaller than symbols. Amino acids are proline (Pro), phenylal
anine (Phe), leucine
(Leu), valine (Val), and isoleucine (Ile).
FIGURE 5
2
ε
AA/w
values for leucine (black) and valine (white) in wildtype organi
sms grown on glucose vs. relative carbon flux (i.e., normalized to gluc
ose uptake
rates) through pyruvate synthesis-related enzymes in centra
l metabolism: KDPG aldolase (ED pathway), PEP carboxykinase (a
naplerotic pathway),
phosphoglucose isomerase (EMP pathway), pyruvate kinase (EMP + ED
pathways), and fructose 6-phosphate-forming transketolase (PP
pathway).
Error bars represent
±
1
σ
. Regression analyses were performed using
2
ε
AA/w
values from the first of each biological replicate condition (see
Supplementary Table S2
).
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FIGURE 6
Summary of
2
H/
1
H fractionations between amino acids and water in wildtype organi
sms grown on di erent substrates (denoted by colors) spanning
metabolically distinct classes (denoted by shapes). Error bar
s indicate the propagated uncertainties (
±
1
σ
) from the amino acid, derivative, and water
measurements, and are smaller than symbols. Duplicate cultu
res were set up for all organisms and conditions except
E. coli
, which was grown on
acetate and pyruvate in a single replicate, and on glucose in two d
i erent (non-replicate) experiments (with cultures #1 and #2 d
istinguished by dark
blue circles with black and gray borders, respectively; see Se
ctions 2.1, 2.2).
a given amino acid across organisms (e.g.,
Figure 4A
) hint at
the importance of additional, second-order controls, which are
examined in Section 4.2.
4.1.1 Proline
The high
δ
2
H values of proline are likely due in large part to
the
2
H-enriching kinetic isotope effect (KIE) of citrate synthase in
the TCA cycle. Proline is mainly synthesized from the TCA cycle
intermediate
α
-ketoglutarate and inherits four hydrogen atoms
from
α
-ketoglutarate, two from NAD(P)H, and one from water
(
Figure 1
,
Supplementary Figure S16
). In the first step of the TCA
cycle, citrate synthase combines acetyl-CoA with oxaloacetate to
form citrate, abstracting a proton from acetyl-CoA’s methyl group
with a large KIE (1.94 measured
in vitro
;
Lenz et al., 1971
).
The resulting
2
H-enriched hydrogen in citrate is retained through
formation of
α
-ketoglutarate (and ultimately, synthesis of proline),
as aconitase and isocitrate dehydrogenase stereospecifically remove
the oxaloacetate-derived hydrogen from citrate and isocitrate,
respectively (
Supplementary Figure S16
;
Lowenstein, 1967
;
Smith
and York, 1970
;
Csonka and Fraenkel, 1977
;
Ochs and Talele,
2020
). As proline inherits
∼
30% of its hydrogen from NAD(P)H
through this synthesis pathway, and its
δ
2
H value appears
to be controlled to some extent by NADPH metabolism (see
Section 4.2.1.2), proline may be a sensitive indicator of redox
balance in cells. Some microbial species within the families
Rhizobiaceae and Pseudomonadaceae can additionally synthesize
proline from ornithine, which in turn is synthesized from arginine
(
Stalon et al., 1987
;
Schindler et al., 1989
). The prevalence of
this pathway in the
P. fluorescens
and
R. radiobacter
strains
examined in this study is unclear, but its operation would
presumably reduce the fraction of NAD(P)H-derived hydrogen
in proline.
4.1.2 Phenylalanine
The source of phenylalanine’s high
δ
2
H values is unclear, but
may be due to relatively large fractions of water-derived hydrogen
in phenylalanine’s organic precursors (phosphoenolpyruvate and
erythrose-4-phosphate;
Figure 1
,
Supplementary Figure S17
).
During glucose metabolism, phosphoenolpyruvate (PEP) is
primarily synthesized through the EMP or ED pathway, and
its hydrogen can be directly routed from glucose or partially
exchanged with water (e.g., at the triose phosphate level;
Rose
and O’Connell, 1961
;
Saur et al., 1968
;
Reynolds et al., 1971
;
Russell and Young, 1990
). Erythrose-4-phosphate is synthesized
through the PP pathway, which includes numerous isomerizations
and reversible reactions that exchange organic hydrogen with
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TABLE 1
Summary of potential biochemical controls on
δ
2
H
AA
values.
AA(s)
Biochemical
control hypothesized
E ect on
δ
2
H
AA
values
Data where e ect
is observed/explored
Potential
application of
δ
2
H
AA
analysis
Pro
Citrate synthase: KIE leads to
2
H-enrichment of
α
-ketoglutarate
(proline precursor in TCA cycle).
Stimulates high proline
δ
2
H values,
i.e., small proline/water
fractionations.
High proline
δ
2
H values across all
carbon substrate conditions (
Figure 6
).
Large slopes in regressions of proline vs.
water
δ
2
H (growth water experiments;
Supplementary Figure S11
), implying
small proline/water fractionations
(
Supplementary Section 6.1
).
Phe
High fraction of water-derived
hydrogen in precursors PEP and
erythrose-4-phosphate, with
water-derived hydrogen having
equilibrated with water.
Leads to small but positive
phenylalanine/water
fractionations, with phenylalanine
δ
2
H values relatively insensitive to
diet.
Supported by small phenylalanine/water
fractionations across all substrate
conditions (except in
P. fluorescens
grown on TCA cycle substrates;
Figure 6
).
Proxy for environmental
water
δ
2
H.
Bio-thermometer if organic
hydrogen/water
equilibration is
temperature-dependent.
Pro, Phe, Ile
NADPH metabolism: KIEs of
dehydrogenases and
transhydrogenases control the
δ
2
H
value of the NADPH pool.
Contributes to some variations in
δ
2
H values of amino acids with
NADPH-derived hydrogen.
Correlations between
δ
2
H
AA
values and
carbon flux through NADPH-related
enzymes, and between
δ
2
H
AA
values
and NADPH imbalance fluxes in
E. coli
organisms (
Supplementary Figure S15
;
Section 4.2.1.2).
Correlations between
δ
2
H
AA
shifts in
organisms grown on glucose
→
TCA
cycle substrates and fraction of
NADPH-derived amino acid hydrogen
(
Figure 7B
,
Supplementary Figure S13
).
Substrate ordering of estimated
NADPH-related
2
H- enrichment of
proline with measured and published
NADPH imbalance fluxes in
E. coli
and
B. subtilis
(
Figure 7C
; Section 4.2.1.2).
Elucidate NADPH balance
and redox metabolism in
cells.
All AAs
Catabolic pathways activated:
control
δ
2
H values of central
metabolites (e.g., pyruvate)
through differential activation of
catabolic pathways and
associated enzymes.
Contributes to systematic
variations in
δ
2
H
AA
values, with
lowest
δ
2
H values upon growth on
sugars, moderate upon growth on
pyruvate, and highest upon growth
on TCA cycle substrates.
Correlations between leucine and valine
δ
2
H values and carbon flux through
pyruvate synthesis-related enzymes in
organisms grown on glucose (
Figure 5
).
Correlations between
δ
2
H
AA
shifts in
organisms grown on glucose
→
TCA
cycle substrates and fraction of
pyruvate-derived amino acid hydrogen
(
Figure 7B
,
Supplementary Figure S12
).
Systematic variations in
δ
2
H
AA
values
(
Figure 7A
) explainable by considering
relative
2
H-enrichment of cellular
pyruvate in different carbon substrate
conditions (
Figure 8
; Section 4.2.1.1).
Interrogate an organism’s
diet and/or metabolic
lifestyle.
Enzymes in biosynthetic pathways.
Set the overall pattern of
δ
2
H
AA
values, but variations in enzymes
and isotope effects across
organisms may contribute to
variations in
δ
2
H
AA
values.
Similar
δ
2
H
AA
patterns across
organisms and substrate conditions
(
Figure 6
).
Similar
δ
2
H
AA
values across
E. coli
organisms grown on glucose, despite
different fluxes through catabolic
pathways (
Figure 4B
).
Diversity in isozymes employed in each
amino acid biosynthetic step across
organisms (
Supplementary Figure S20
).
Fingerprinting method to
trace origins of amino acids
in organic matter, if
δ
2
H
AA
patterns within different
taxonomic groups are
unique.
water (
Russell and Young, 1990
). As these equilibrations are
presumably controlled by equilibrium rather than kinetic isotope
effects, the resulting fractionations are unlikely to be strongly
negative (in contrast to the potentially large normal KIEs
expressed during water incorporation into pyruvate; Section
4.1.3). Indeed, theoretical calculations predict slightly negative to
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