Title
Identification
of 2-oxohistidine interacting proteins using E. coli proteome chips.
Date: 20160206
Version: 1
Running Title
Identification
of 2-oxohistidine interacting proteins
Abbreviations
The
abbreviations used are: PTM, post-translational modification, MCO, metal-catalyzed
oxidation, RAGE, receptors for advanced glycation end-products, Aβ, amyloid
beta, AD, Alzheimer’s disease, GO, Gene Ontology, KEGG, Kyoto Encyclopedia of
Genes and Genomes, BSA, bovine serum albumin, TBST, tris-buffered saline with
tween 20, Kd, dissociation
constant, AG peptide, AGAQVAHGNEVAG, SE peptide, SEAGVNHGSAGQA, IA peptide,
IAVENVHAQGLA, Oxo-AG peptide, 2-oxohistidine residue in AG peptide, Oxo-SE
peptide, 2-oxohistidine residue in SE peptide, Oxo-IA peptide, 2-oxohistidine
residue in IA peptide.
Summary
Cellular proteins are constantly
damaged by reactive oxygen species generated by cellular respiration. Due to
its metal-chelating property, histidine residues are easily oxidized in the
presence of Cu/Fe ions and H2O2 via metal-catalyzed
oxidation, usually converted to 2-oxohistidine. We hypothesize that cells may
have evolved antioxidant defenses against the generation of 2-oxohistidine
residues on proteins, and therefore there would be cellular proteins which
specifically interact with this oxidized side chain. Using two chemically
synthesized peptide probes containing 2-oxohistidine, high-throughput
interactome screening was conducted using the E. coli K12 proteome microarray containing >4200 proteins. Ten interacting proteins were successfully validated using
fluorescence polarization assay
through a third peptide probe of different
sequence, as well as binding constant measurements. We discovered 9 out of 10 identified
proteins seem to be involved in redox-related cellular functions. We also built
the functional interaction network to reveal their interacting proteins. The
network showed our interacting proteins were enriched in oxido-reduction process,
ion binding, and carbon metabolism. A
consensus motif was identified among these 10 bacterial interacting proteins
based on bioinformatic analysis, which also appeared to be present on human S100A1 protein.
The preferential binding of S100A1 with 2-oxohistidine over histidine was successfully
validated using all three peptide probes, suggesting that the capacity to
recognize 2-oxohistidine modification may be evolutionarily conserved from
bacteria to humans.
Besides, we found our consensus motif among our identified proteins, including
bacteria and human, were all alpha-helix form and faced the outside of proteins
which mean the motif has a chance to interact with the other proteins. The combination of chemically engineered peptide probes with
proteome microarrays proves to be an efficient discovery platform for protein
interactomes of unusual post-translational modifications, sensitive enough to
detect even the insertion of a single oxygen atom in this case.
Introduction
The
complexity of the proteome arises in a large part due to the hundreds of
post-translational modifications (PTMs) already discover. Many PTMs are enzyme-catalyzed,
such as phosphorylation, glycosylation, or ubiquitination (1,
2), but there are also
numerous non-enzymatic PTMs caused by chemical reactions between reactive
molecules and protein side chains, such as glycation, nitrosylation, and oxidation
by reactive oxygen species (ROS) (3,
4). As protein side
chains are enzymatically modified, there are generally specialized factors in
the cell to recognize such changes. For instance, 14-3-3 family protein can
recognize protein phosphorylation motifs (5) and various lectins can recognize
protein glycosylation (6). However, recognition factors
may also exist for non-enzymatic PTMs, such as receptor for advanced glycation
end-products (RAGE) (7). In this study we seek to
uncover cellular binding factors for 2-oxohistidine, the oxidized product of
histidine, which is an important but less understanding non-enzymatic PTM.
The
generation of ROS is an unavoidable consequence of cellular respiration, which
leads to the oxidation of proteins, lipids, and nucleic acids (4,
8). ROS play regulatory
roles in cellular signaling pathways under low levels (9), but high levels of ROS are
cytotoxic and lead to the accumulation of damaged cellular components (10,
11). The reactions of
proteins with ROS may lead to almost 100 side chain modifications (12,
13). Histidine is highly
susceptible to ROS damage, because it has strong metal chelation affinities and
often constitutes the binding site for metal ions (14,
15). The presence of H2O2
and redox-active metals (Cu and Fe) can lead to metal-catalyzed oxidation (MCO,
also called Fenton-type chemistry), which converts histidine side chains to
2-oxohistidine (16,
17).
The
conversion of histidine to 2-oxohistidine alters its charge state, hydrogen
bonding property, and metal chelation affinity, and hence may have seriously
impact on protein structure and function. The net reaction is oxygen insertion
(+16 Da), which makes it an irreversible PTM. It is unclear if cells simply
tolerate such damages on histidines or employ active mechanisms to recognize
them and use them as redox sensors or as damage markers for promoting protein
degradation. The only known biological function of 2-oxohistidine is to serve
as a redox sensor on bacterial transcription factor PerR (18), while other studies
have used 2-oxohistidine as a stable marker of protein damage during oxidative
stress (12,
19).
Judging
by the potential biological significance of 2-oxohistidine modification, we
hypothesized that there may be cellular factors to recognize it. Previous research
on 2-oxohistidine had been impeded by the difficulty in generating this side
chain with reasonable yields. Recently, we managed to greatly improve the yield
of 2-oxohistidine conversion by optimizing MCO reaction conditions using the
copper/ascorbate system (20), allowing us to synthesize and
purify peptide probes containing 100% 2-oxohistidine for this study.
Here,
we used 2-oxohistidine-containing peptides to mimic the oxidative conversion of
histidine residues on native proteins. Then, we utilized the E. coli K12 proteome chip to identify
2-oxohistidine-interacting proteins via high-throughput screening, and the
interactors turned out to be largely involved redox-related metabolism. From
the bacterial interactors we predicted a consensus binding motif, which could
be validated across different species and correctly predicted S100A1 as a human
binding factor for 2-oxohistidine. Thus, recognition of 2-oxohistidine appears
to be an evolutionarily conserved capacity from bacteria to human.
Experimental Procedures
Fabrication of E. coli K12 proteome chip
The
high throughput protein expression, protein purification, and protein printing
were modified from the previous study (21). Briefly, we expressed and
purified E.coli K12 protein in
96-well plate format and subsequently printed the proteome microarray. All
purified proteins were spotted in duplicate on each aldehyde slide (BaiO,
China) by SmartArrayer 136 (CapitalBio, China) at 4°C. After printing proteins,
the proteome microarray chips were kept at 4°C for protein immobilization on
the slides for 12 h. In the end, the chips were stored at -80°C before probing
with samples.
Peptide oxidation
Solutions
containing 1 mM peptide, 5 mM Cu2+ and 200 mM sodium ascorbate were exposed to
air with gentle shaking at 37 °C for 24 hrs (AG and SE peptide) or 6 hrs (IA
peptide). The oxidation reaction was quenched with 20 mM EDTA and analyzed by
reverse-phase HPLC (10-30% acetonitrile and 0.1% TFA in water, C18 column from
Dr. Maisch, Ammerbuch, Germany) to determine the reaction yield. For LC-MS/MS
analysis of crude reaction mixtures and HPLC fractions, 10 μL samples was
acidified with 2 μL 10% TFA and desalted with ZipTip (Millipore, Billerica, MA)
following manufacturer’s protocols. Oxidized peptides were purified by
semi-preparative HPLC (C18 column, Dr. Maisch). LC-MS/MS experiments were
conducted under previously reported conditions (20).
Peptide labeling
Oxidized and
non-oxidized peptides were dissolved in 50 mM sodium borate buffer at pH 7.5
and analyzed by HPLC to determine peptide concentration by 210 nm absorbance.
DyLight-conjugated NHS esters were dissolved in anhydrous DMF to 10 mg/mL and
added to peptide solutions for 1 hr incubation at room temperature, at the
following fluorophore/peptide ratios: DyLight 650:AG =3:1, DyLight 650:SE =
5:1, DyLight 650:oxo-IA = 1.5:1; DyLight 550:oxo-AG = 5:1, DyLight 550:oxo-SE =
7:1, DyLight 550:IA = 3:1. Labeled peptides were analyzed and purified by HPLC
as described above. Labeled products were verified by LC-MS/MS, and quantified
by absorbance measurements based on fluorophore properties.
E. coli
K12 proteome chip assays with 2-oxohistidine peptides
The
chips were first blocked with 3% bovine serum albumin (BSA) (Sigma-Aldrich, US)
for 5 min. Ten μM of DyLightTM 550-conjugated 2-oxohistidine peptide
and DyLightTM 650-conjugated non-oxohistidine peptide were probed together
onto the chip with LifterSlipsTM (Thermo Scientific, US) at room
temperature for 45 min. Finally, the chips were washed by Tris-buffered
saline-Tween 20 (TBST) in an orbital shaker three times and 5 min each time.
The chip was dried by centrifugation and then scanned with a LuxScanTM
microarray scanner (CapitalBio, China). Signal intensities, foreground median subtract
background median, were acquired and analyzed using GenePix Pro 6.0 software. Then,
we used quantile normalization to normalize the signal intensity from both 2-oxohistidine
containing probes and non-oxohistidine containing probes. To identify positive
2-oxohistidine interacting proteins, four cutoffs were set. 1) The signal from
experimental groups was greater than 1.5 standard deviations away from the mean
for experimental groups. 2) To get the large signal difference between experimental
groups and negative controls, the delta, defined as signal difference between experimental
group and control group, was greater than 1.5 standard deviations away from the
mean for all deltas. 3) To exclude the non-specific binding to 2-oxohistidine
residue, the signal from the negative control was less than 1.5 standard
deviations away from the mean for control group. 4) To remove the
irreproducible hits among triplicate chip assays, the student’s t-test p-values between experimental groups and
negative controls were less 0.05.
Heat Map
The
R programming language (22) was used to display heat map. The
data was presented by signal intensity of foreground subtract background. The gplots
package (23) was used for classifying 2-oxohistidine
containing peptides and non-oxohistidine containing peptides in hierarchy.
Functional interaction analysis
The
identified proteins were used for functional interaction analyses by using EcID
(24) and Cytoscape (25). Briefly, the files of EcID
entities and EcID pairs were downloaded from EcID database. Before mapping identified
proteins to their EcID entities and EcID pairs, we removed the pairs which
based on the prediction mode, such as phylogenetic profiles, gene neighborhood,
mirror tree, insilicon 2 hybrid, or context mirror. After mapping, we used
Cytoscape to generate the functional interaction network, and visualized the identified
proteins and their interacting proteins. Later on, we used AmiGO 2 (26) and KOBAS 2.0 (27) to generated gene ontology (GO) (28) and Kyoto
Encyclopedia of Genes and Genomes (KEGG) (29) results, respectively.
Fluorescence polarization assay
After
blocking the 96-well black plate (Thermo Scientific, US) with 1% BSA at room
temperature for 1 h, the identified proteins was added to the plate. The concentrations
of 10 identified proteins (ThrS, YqjG, YajL, HemE, IlvA, PrpD, Zwf, Eda, Gor,
and PqqL) were 12.0, 25.7, 10.7, 15.6, 3.4, 18.6, 19.5, 11.8, 26.1, and 5.9 μM,
respectively. And the concentrations of BSA, as a negative control, were as
same as the protein they compared to. Ten nM of DyLightTM
550-conjugated 2-oxohistidine peptide was incubated with protein or BSA in a Micromixer
MX4 (FINEPCR, South Korea) at room temperature for 1 h. After incubation, the
degree of polarization of each well was detected by a Synergy 2 (BioTek, US),
using an excitation wavelength of 540 nm and an emission wavelength of 590 nm
with a dichroic mirror of 570 nm.
Measurement of dissociation
constant (Kd)
Identified
proteins and S100A1 (Abnova, Taiwan) were printed on aldehyde chips in a
multiple-well format. After printing, the chips were immobilized at 4 °C for 12
h and then stored at -80 °C. The printed chips were blocked at room temperature
for 5 min with 3% BSA. Two folds serial-diluted DyLightTM
550-conjugated 2-oxohistidine peptides, DyLightTM 650-conjugated
non-oxohistidine peptides, and quenched fluorescent dyes were probed onto the wells
of the chip individually with Multi-Well Microarray Hybridization Cassettes
(Arrayit, US), and incubated at room temperature for 45 min. The fluorescent
dyes, DyLightTM 550 and DyLightTM 650, were already quenched
by 5M Tris-HCl (Bionovas, Canada). To check whether calcium affects interaction
between S100A1 and 2-oxohistidine, 1 mM CaCl2 was added in the assay
buffer. After washes with TBST, the chips were dried by centrifugation and then
scanned with a microarray scanner. The Kd
value was calculated by double-reciprocal plot analysis which y is one divided
by fluorescence intensity, and x is one divided by peptide concentration. Set
the regression line formula in the form of y = ax, which “a” is the slope of
regression line. The Kd
value will be “a” times concentration of identified protein.
Motif Search with GLAM2
All
identified proteins were converted to FASTA format and analyzed by Gapped Local
Alignment of Motifs (GLAM2) (30) for surveying consensus motif.
The parameters of GLAM2 were set as default. The resultant motif was then
searched in entire E. coli K12
proteome and human proteome by GLAM2SCAN (30).
Protein 3D structure and
secondary structure prediction
All
protein 3D structures were provided by their provider (31-38) and RCSB PDB (39). The colors in protein 3D
structures were visualized by RasMol software (40). We used the EcoGene 3.0 (41) which contains the QUARK
prediction method (42) to predict the secondary
structure of those proteins which do not have protein 3D structures.
Results
Many
researches revealed that the 2-oxohistidine residue had been discovered in several
peptides or proteins (16,
43-51). We used the E. coli K12 proteome chip to identify
proteins which can bind specifically to 2-oxohistidine residue. To accomplish
our purpose, we fabricated the E. coli
K12 proteome chips, generated the 2-oxohistidine containing peptides, and
probed these peptides with E. coli
K12 proteome chips. After identified the positive hits, we used fluorescence
polarization assays to validate the interactions and measured the binding
affinity by dose-response measurements. Then, we surveyed the consensus motif
among these identified proteins and applied to human proteome to look for the
possible human 2-oxohistidine interacting proteins. Finally, we used the
functional interaction network to find out the possible interacting proteins
and used GO and KEGG to figure out possible process and pathway (Fig. 1).
Oxidation of peptide histidine
residue
Histidine
residues are placed in the middle of 12-mer or 13-mer peptides to eliminate possible
charge effects at N-terminus and C-terminus, creating a context similar to
proteins. Easily oxidized amino acids, such as methionine, cysteine, tyrosine,
tryptophan phenylalanine, lysine, and arginine, are avoided. Three peptides
containing a single histidine residue and random selections of other residues,
namely AGAQVAHGNEVAG (AG), SEAGVNHGSAGQA (SE), and IAVENVHGGLA (IA), were used
for chip assays. We carried out MCO reaction using the copper/ascorbate/air
system shown in Figure 2. The HPLC yield of mono-histidine peptides AG and SE
were around 10%, and for IA peptide around 20% (Fig. 2).
E. coli K12 proteome
chip assays
To
investigate 2-oxohistidine interacting proteins, AGAQVAH*GNEVAG (Oxo-AG
peptide) and SEAGVNH*GSAGQA (Oxo-SE peptide) were conjugated to DyLightTM
550 fluorophore molecular probes. Non-oxidized AG and SE peptides were
conjugated to DyLightTM 650 as negative controls. In the chip assay,
2-oxohistidine containing peptide and its negative control were probed with E. coli K12 proteome chip in triplicate
(Fig. 3). The examples of 2-oxohistidine interacting proteins compared with
non-oxohistidine containing peptide profiling were shown in Figure 4.
To
identify the specific hits to 2-oxohistidine peptides, we set several cutoffs. First,
we chose the hits had strong intensity in experimental groups. Second, we
wanted the hits had high signal in experimental groups and low signal in
negative controls. Thus, we chose the hits had large difference between
experimental groups and negative controls. Third, although we chose the hits
had large difference between two groups, there still were some strong signals
in negative controls. To exclude this kind of non-specific binding to
2-oxohistidine residue, we removed the hits which greater than 1.5 standard
deviationa away from the mean for negative controls. Fourth, in order to have
reproducibility results among triplicate chip assays, we excluded the hits
which had large variances as we described in the section of experimental
procedures. Under such criteria, 38 and 20 protein hits were found to bind
oxo-SE peptide and oxo-AG peptide, respectively (supplementary Table S1-S2). To
avoid the non-specific binding due to the different peptide sequences, we chose
the hits shared by both 2-oxohistidine peptides among those proteins. Only 10
proteins (ThrS, YqjG, YajL, HemE, IlvA, PrpD, Zwf, Eda, Gor, and PqqL) were identified
by both 2-oxohistidine containing peptides (Table 1).
We
used heat map to visualize the intensity of these 10 identified proteins among
2-oxohistidine and non-oxohistidine containing probing results (Fig. 5). The
heat map shows that our 10 identified proteins clearly classified the 2-oxohistidine
peptides from non-oxohistidine peptides.
Functional interaction analysis
We
exploited EcID to find our 2-oxohistidine interacting proteins’ partners that indirectly
interacted to 2-oxohistidine. The EcID database (Escherichia coli Interaction
Database) (24) provided a framework for the
integration of several interactional source, including EcoCyc (metabolic
pathways, protein complexes and regulatory information), KEGG (metabolic
pathways), MINT and IntAct (protein interactions), high-throughput experiment
(protein complexes), and iHOP (text mining).
In
this study, we only selected interactions from experimental mode which was proved
by many databases and the results would be more reliable and confident. We chose
the interacting proteins that had at least interacted 3 out of the 10
identified 2-oxohistidine interacting proteins. As shown in Figure 6, four 2-oxohistidine
interacting proteins (thrS, zwf, eda, and ilvA) were ‘‘hubs’’ that connected
many interacting proteins in the network. From this functional interaction
analysis, 26 interacting proteins were found to have interactions with at least
3 out of the 10 identified proteins. We further analyzed this functional
interaction network, including 10 identified proteins and 26 interacting
proteins, by using AmiGO 2 (26) and KOBAS 2.0 (27) to provide the GO (28) and KEGG (29) results, respectively
(supplementary Table S3-S5). Interestingly, fifteen out of the 36 proteins
(~40%) were in the oxidation-reduction process, which shows significant
enrichment (p < 0.05). Table 2
summarizes the related GO terms and KEGG pathways. Oxidation-reduction process
is a metabolic process that involved in the transfer of electrons between
chemical species (52). This result suggested that our
identified 2-oxohistidine interacting proteins and their interacting proteins
from the network may involve in the oxidation-reduction process. In the
molecular function, ion binding and cofactor binding were enriched in our
network. This result suggested that our proteins may interact with metal ion
which can lead to MCO reaction. Besides, oxoacid metabolic process and carbon
metabolism were also discovered. These kinds of metabolism usually accompany
with energy metabolism that the reducing power and ROS may also carry out in
the process (53). Changes to the oxidation state
of a molecule were frequently carried out as a secondary metabolite were
synthesized or modified (54). Therefore, the biosynthesis of
secondary metabolites was also enriched in our interaction network. These data
showed that identified proteins and their binding proteins may involve in the
redox process or the oxygen sensitive environment to responsible for such kinds
of oxidation change or be a protector or sensor to the oxidative stress.
Fluorescence polarization assays
Although
there were positive results in the chip assays, we still could not exclude the possible
bias of this kind of heterogeneous approach. Fluorescence polarization assay is
a kind of homogeneous binding detection methods to mimic the interaction
between two compounds in the cellular environment (55-59). Fluorescence polarization
assays, investigation of the binding between two molecules were used to
validate the 10 identified proteins in this study. Once the protein bound to
fluorescent 2-oxohistidine containing peptides, a high degree of polarization was
expected. As shown in Figure 7, all the 10 identified proteins had higher
polarization than the negative control, BSA. Besides, the polarization distribution
of two oxidative peptides was similar to each other. It indicated that interaction
between proteins and 2-oxohistidine was not affected by different peptide
sequences. The result confirmed that 10 identified proteins can bind to 2-oxohistidine
in both AG and SE peptides.
Measurement of binding affinity
Dissociation
constant (Kd) described
the propensity of a ligand-protein complex to dissociate reversibly into its
components. We measured the Kd
of these identified proteins to oxidative peptides, normal peptides, and quenched
fluorescent dyes by dose-response measurements. Fluorescent 2-oxohistidine containing
peptides with different concentrations probed onto the slide, where the
identified proteins were immobilized (supplementary Fig. S1A). Using
double-reciprocal plot analysis, we calculated the Kd values for all identified proteins (supplementary Fig.
S1B). The same procedures were done in normal peptides and fluorescent dyes, too.
The result showed our 10 identified proteins had a strong affinity to
2-oxohistidine from 10-8 to 10-10 M, especially the hemE
protein which had the highest Kd
(~10-10 M) in both 2-oxohistidine containing peptides (Table 3). We
also found our proteins slightly preferred oxo-SE peptide than oxo-AG peptide,
but the difference of Kd
was not greater than one order of magnitude. On top of that, the Kd values from oxidative
peptides were significant difference to the normal peptides, and quenched
fluorescent dyes (p < 0.05). To
check the interaction between 2-oxohistidine and identified proteins again in
order to be certain. We used a third peptide, IAVENVH*QGLA (Oxo-IA peptide) and its negative control (IAVENVHQGLA, IA
peptide), which had different peptide sequence and we also swapped their
fluorescent dyes to each other to avoid the influence of fluorescent dyes. The
result also showed the statistically significant difference to its negative
controls (p < 0.05). This
indicated that our 10 identified proteins had a strong binding affinity to
2-oxohistidine, and were not affected by different peptide sequences and
different fluorescent dyes.
Motif Searching in E. coli proteome and human proteome
Based
on fluorescence polarization and binding affinity results, we performed the
GLAM2 (Gapped Local Alignment of Motifs) (30) to survey whether a consensus
motif among these identified proteins. In this study, we found the consensus
motif among these identified proteins is
[SD][QV][AEDT]A[YIL][CE][AK][ARL][MV][AHK]?[KET][LV] [AYLF]E (Fig. 8). In
addition, we used this motif to query entire E. coli K12 proteome by GLAM2SCAN (30). The result showed top ten
ranking proteins containing this motif were identical to our identified
proteins (Table 4). This indicates that motif was significantly unique in the
entire E. coli K12 proteome (p < 0.05). We also applied this motif
to entire human proteome, and found the ranked top one protein is S100 Calcium
Binding Protein A1 (S100A1), which is a member of the S100 family (supplementary
Table S6).
After
motif screening in E. coli and human
proteome, we further investigated the secondary structure of the motif in our
identified proteins and S100A1 by using protein 3D structures (Fig. 9). However,
there were 3 proteins (hemE, zwf, and pqqL) were not available. For these three
proteins, we used the QUARK prediction method to predict their secondary
structures. By proteins 3D structure analysis or QUARK prediction, the result
showed that this motif was usually an alpha-helix in these proteins except for
yajL, which contains 36% beta-sheet and 64% alpha-helix in the motif (Table 5).
Besides, we found these kinds of alpha-helix formed motifs generally faced the
outside of the proteins which mean they had chance to interact with outside molecules.
Our finding suggested that 2-oxohistidine recognized motif was an alpha-helical
structure and conversed between E. coli
and human.
Kd
measurement between human S100A1 protein and the oxidative peptides
To
validate the interaction of human S100A1 protein we found by GLAM2SCAN on
entire human proteome, we calculated the Kd
values according to dose-response measurements for all oxidative peptides,
including oxo-AG peptide, oxo-SE peptide and oxo-IA peptide. The result showed
that S100A1 protein had a strong affinity to all 2-oxohistidine containing
peptides and significant difference to the other unoxidized peptides and
fluorescent dyes (p < 0.05) (Table
6). The binding affinity of S100A1 to 2-oxohistidine were 10-fold to 100-fold
higher than the negative controls, indicating that S100A1 actually had an
ability to bind to the 2-oxohistidine. Since we knew S100A1 is calcium binding
protein, we wondered whether calcium would affect the interaction or not. The
result showed calcium was not involved in the interaction of S100A1 to
2-oxohistidine peptides or the other groups (p > 0.1). This suggested the E.
coli K12 proteome chip was able to be a feasible platform for motif screening
in cross-species studies.
Discussion
Enzymatic and non-enzymatic PTMs are comparable in their diversity and
chemical complexity, but past research efforts have mostly focused
on the former,
leaving a huge gap in our understanding of biological phenomena associated with
non-enzymatic PTMs. Even though non-enzymatic PTMs are
not generated by enzyme actions, there may still be specific enzymes to
chemically reverse such modifications, or specific receptors to detect
such modification. For example, the chemical oxidation of methionine to
methionine sulfoxide can be reduced back to methionine by specific reductases MsrA and MsrB (60);
RAGE can recognize protein glycation and lead to inflammatory responses (7).
However, there are still many non-enzymatic PTMs for which the biological
functions are little known.
Among non-enzymatic PTMs,
2-oxohistidine is particularly interesting because of its
minimal size, involving the insertion of just one oxygen atom. It probably represents the smallest atom-scale
alteration associated with a known PTM, and we
investigated if cells have evolved the ability to monitor such a small
change on the surface of proteins. Because histidine often plays critical roles
in protein function, both structurally and catalytically, we hypothesized there
would be cellular factors that specifically recognize 2-oxohistidine side
chains, and this hypothesis was tested with specially synthesized peptide
probes, and E.coli proteome chips.
Using three peptide probes with homogeneous 2-oxohistidine modification,
we were able to identify 10 proteins that show preferential binding for
2-oxohistidine-containing peptides over non-oxidized control peptides (Table 1). Since these three probes have very different
flanking sequences, it is very likely that we have identified proteins which
specifically recognize side-chain differences between 2-oxohistidine and
histidine, and we will refer to them as 2-oxohistidine recognition factors.
Before this study, the
recognition factors of 2-oxohistidine had never been proposed or identified.
In
theory, the recognition of 2-oxohistidine
could play several different biological roles. First, it may act as a redox
sensor, similar
to S-nitrosylation (61).
Secondly, it may identify oxidatively damaged proteins and mark it for
degradation. Third, it may trigger cellular stress responses and antioxidant
pathways. Although there is
no known involvement of 2-oxohistidine in different E. coli physiological pathways, several
of the recognition factors in E. coli
appear to be related to redox pathways and antioxidant pathways.
Among the
10 putative recognition factors
identified via proteome array, 9
seem to be involved in redox-related cellular functions.
Gor is a glutathione reductase, involved in the generation of glutathione,
which maintains the reducing environment of the cell (62). YqjG is glutathionyl hydroquinone reductase, which utilizes
glutathione to reduce
a wide range of organic molecules (38).
HemE is an uroporphyrinogen decarboxylase involved in the biothesis of
the heme group, which is an important cofactor for antioxidant enzymes like
catalase and peroxidase
(63).
Zwf is a glucose-6-phosphate dehydrogenase, which helps supply NADPH
through the pentose phosphate pathway (64), and NADPH is a cofactor used as a reducing agent by
many metabolic enzymes
(65,
66). PqqL in
E. coli is a putative zinc
metalloprotease, but functionally it may be similar to pqqF in Klebsiella pneumoniae, which has a
supportive role in pyrroloquinoline quinone
biosynthesis
(67).
Pyroloquinoline quinone is
a redox cofactor that provides reducing power for the cell, and also a ROS
scavenger (68).
YajL
is an anti-oxidative-stress chaperone, which promotes disulfide formation to
help maintain order in the thiol proteome (69). Interestingly, the
human homolog of yajL, DJ-1, is also an anti-oxidative stress protein, and its
mutations are known to cause familial Parkinsonism (70). On the other hand,
ilvA and thrS are both involved in threonine metabolism, and known to be
regulated by oxygen levels in the cell. IlvA, a threonine dehydratase, converts
threonine to 2-oxobutanoate, and its promoter is activated by oxygen (71). ThrS is a threonyl-tRNA
synthetase, and potentially also an oxygen sensor in the cell through Cys182
oxidation (72). Eda,
Entner-Doudoroff aldolase (also
called KDPG aldolase),
is involved in the Entner-Doudoroff pathway that generates pyruvate and NADPH
by consuming glucose. Eda is a multi-functional aldolase which also catalyze the addition of pyruvate to electrophilic aldehydes to detoxify harmful byproducts generated by oxidative
stress (73).
PrpD,
a 2-methylcitrate dehydratase, does not appear to be directly involved in redox functions, but it
converts
propionyl-CoA
into pyruvate through the methylcitrate cycle (74),
and pyruvate can be utilized by the aforementioned eda
to detoxify oxidized organic molecules with aldehydes. Therefore, all 10
putative recognition factors for 2-oxohistidine identified here appear to be
involved in supplying reducing power to the cell or in oxygen-sensitive regulation of carbon metabolism. This strongly implies
that recognition of 2-oxohistidine in E.
coli may play certain roles in redox sensing and metabolic regulation, but
further experiments are required to elucidate its actual function.
Using
motif analysis by GLAM2 and GLAM2SCAN, we identified
putative 2-oxohistidine binding motif from these
10 recognition factors, which turned out to be: [SD][QV][AEDT]A[YIL][CE][AK][ARL][MV][AHK]?[KET][LV][AYLF]E. We further validated
this binding motif by searching for the highest-scoring
match in the human proteome, which turned out to be DVDAVDKVMKELDE
on S100A1 protein, and we verified
that S100A1 indeed exhibited 2-oxohistidine binding affinity. S100A1
is a calcium binding protein highly expressed in the brain and heart, and its
calcium binding affinity is greatly enhanced by the oxidative nitrosylation of
Cys86 (75). It is believed to regulate
calcium and nitric oxide signaling in neuronal cells, affecting neurotransmitter
release as well as inflammation (76). Interestingly, since S100A1 is
also secreted extracellularly (77), it may bind to
oxidized amyloid beta (Aβ) with 2-oxohisitidine side chains, which are released
from extracellular senile plaques which trap metals and generate ROS (45,
78, 79). Since Aβ is known to
cause calcium misregulation (80), oxidative stress (81), and inflammatory response (82) in the brain, the
interaction between S100A1 and oxidized Aβ through 2-oxohistidine recognition
may play a role in Alzheimer’s disease (AD) pathogenesis, which warrants future
investigation.
Our
preliminary evidence suggests that both bacteria and humans have cellular
factors which can recognize 2-oxohistidine side chains, and a conserved binding
motif has been putatively identified. Through the course of evolution, the
recognition of 2-oxohistidine may carry important cellular functions related to
redox signaling. We have also shown that E.
coli K12 proteome microarray is capable of being exploited as a motif
library for screening small molecule binding, and that even a single-atom
modification on the molecule may be recognized. We expect a wide application of
this approach for studying the interaction of other post-translational
modifications, such as phosphorylation, methylation, acetylation, amidation,
thiolation, sulfation, nitrosylation, as well as many non-enzymatic PTMs. With
regard to 2-oxohistidine, future work is required to elucidate how
single-oxygen insertion can be recognized on the protein surface, and how
recognizing this modification regulates biological functions.
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Figure Legends
Figure
1. Overall strategy for the identification of 2-oxohistidine interacting
proteins using E. coli K12 proteome chip. We expressed and purified ~4,300
E. coli proteins in high-throughput to fabricate the E. coli K12 proteome chip. We used an
improved condition to obtain 2-oxohistidine peptides in high purity.
2-Oxohistidine peptides were then probed to E. coli K12 proteome chip and identified the preferential
binding proteins. We also built their functional interaction network to investigate
their biology. Fluorescence polarization assays were used to validate the
identified proteins. We conducted dose-response fluorescence assays to measure
the Kd of these proteins. Furthermore,
we used GLAM2 to search consensus motif among these identified proteins and
also applied this motif to entire E. coli K12 proteome and human proteome by GLAM2SCAN.
Figure 2. Summary scheme for the synthesis of 2-oxohistidine-containing peptides.
The process was synthesized by using metal-catalyzed oxidation, and the
histidine side chain on peptides was converted to 2-oxohistidine.
Figure
3. Schematic of E. coli K12 proteome
chip assays with 2-oxohistidine peptide probes. To
detect the 2-oxohistidine interacting proteins, E. coli K12 proteome chips were probed with
2-oxohistidine-containing peptides and un-oxidized control peptides labeled
with different fluorophores.
Each protein was printed in duplicate on the chips.
Figure 4. Representative images
of the E. coli K12 proteome chips
probed with 2-oxohistidine containing peptide (Oxo-SE peptide) and
non-oxohistidine containing peptide (SE peptide). The representative positive hits
(yqjG and thrS) and non-specific binding protein (yeiG) on the chip were
enlarged from sample images of oxo-SE peptide and SE peptide, respectively. The
contrast and brightness of images had been equally adjusted using the same
parameters.
Figure 5. The heat map of 10
identified proteins.
The heat map showed the classification of 10 identified proteins in oxo-AG,
oxo-SE, AG and SE chip assay probing result. Each peptide probes had triplicate
results. The R programming language and gplots package were used to display
heat map.
Figure 6. The functional interaction network of the 10 identified proteins and 26
interacting proteins. The interaction pairs for 10 identified proteins
were downloaded from EcID database, and functional interaction network was
visualized by Cytoscape. We only showed the interacting proteins that interact
with at least 3 out of 10 identified proteins, and 26 interacting proteins were
identified. Four out of 10 identified proteins, eda, ilvA, zwf, and thrS, had
many interactions and considered to be hubs. Square shapes represented the 10
identified proteins, and round shapes represented the 26 interacting proteins.
The node color showed the number of interactions, the red is greater than 10
interactions, the green is greater than 5 interactions, and the others are
yellow which smaller than 5 interactions. The thicker edge lines symbolized
that more databases showed the interaction between 2 proteins.
Figure
7. Validation of the interactions between 2-oxohistidine peptides and
identified proteins using fluorescence polarization assays. In fluorescence
polarization assays, the polarizations of the tested proteins were compared
with same concentration of BSA, as a negative control. A. The fluorescence polarization assays for oxo-AG peptide and
identified proteins. B. The
fluorescence polarization assays for oxo-SE peptide and identified proteins.
The black bar is identified proteins and the gray bar is BSA. The asterisks
mean the polarizations of the identified proteins were significant difference
to the BSA control (p < 0.05).
Figure
8. Consensus motif among the 10 validated proteins. A motif [SD][QV][AEDT]A
[YIL][CE][AK][ARL][MV][AHK]?[KET][LV][AYLF]E was identified by GLAM2. The table
showed the protein sequences of 10 validated proteins aligned with consensus
motif.
Figure 9. Protein 3D structure of
E. coli identified proteins and human
S100A1.
Only 7 E. coli identified proteins
(thrS, yqjG, yajL, ilvA, prpD, eda, gor) and human S100A1 had protein 3D
structures. The protein 3D structures were provided by their provider and RCSB
PDB, and visualized by RasMol software. Beta-sheets are shown in yellow bands;
alpha-helices are shown as pink bands and random coil as white lines. The blue bands
are the consensus motif we found by GLAM2. Only yqjG, yajL, prpD, gor and
S100A1 were provided by homodimer structure. The other is the monomer
structure.
Tables
Table 1. 2-Oxohistidine interacting
proteins identified by E. coli K12 proteome chips. There were 38 and 20
proteins are identified by oxo-AG peptide and oxo-SE peptide chip assays,
respectively. To avoid the non-specific binding due to the different peptide
sequences, we only chose the hits were shared by both 2-oxohistidine containing
peptides (oxo-AG peptide and oxo-SE peptide).
Accession ID
|
Protein Symbol
|
Protein
Name
|
Protein
Function
|
EG11001
|
thrS
|
Threonyl-tRNA
synthetase
|
An enzyme involved in
protein synthesis which is regulated
by aerobic and anaerobic metabolisms
|
EG12746
|
yqjG
|
Glutathionyl-hydroquinone
reductase
|
Reduction of
organic small molecules
|
EG13272
|
yajL
|
Anti-oxidative
stress chaperone
|
A covalent chaperone
for thiol-containing proteome, also promoting disulfide formation
|
EG11543
|
hemE
|
Uroporphyrinogen
decarboxylase
|
Involved in the synthesis of heme group, which is a critical cofactor for antioxidant enzymes
|
EG10493
|
ilvA
|
Threonine
dehydratase
|
A metabolic enzyme
that converts threonine to 2-oxobutanoate,
regulated by an
oxygen-responsive promoter
|
EG13603
|
prpD
|
2-Methylcitrate
dehydratase
|
A
metabolic enzyme in the methylcitrate cycle that converts propionyl-CoA to
pyruvate
|
EG11221
|
zwf
|
Glucose-6-phosphate
dehydrogenase
|
A metabolic enzyme
in the pentose-phosphate pathway that supplies reducing power to
cells generating NADPH
|
EG10256
|
eda
|
KDPG
aldolase
|
An enzyme in the Entner-Doudoroff
pathway, also a multi-function aldolase to detoxify aldehydes generated by
oxidative stress
|
EG10412
|
gor
|
Glutathione
reductase
|
An enzyme that generates glutathione to maintain a reducing environment in the cell
|
EG11744
|
pqqL
|
Putative
periplasmic M16 family zinc metalloendopeptidase
|
An enzyme involed in
pyrroloquinoline quinone biosynthesis, which is a redox cofactor that supplies reducing
power
|
Table 2. Summary for functional analysis of 36 proteins from
functional interaction network. The 36 proteins, including 10
identified proteins and 26 interacting proteins, were used to do the functional
analysis. The GO and KEGG results were generated by AmiGO 2 and KOBAS 2.0,
respectively. We summarizedthe related GO terms and KEGG pathways in this
table. The entirely detailed information of GO and KEGG results were shown on
supplementary Table S3-S5.
GO Term (Biological
process)
|
ID
|
Protein involved numbers
|
p-value
|
Oxoacid metabolic
process
|
GO:0043436
|
21
|
5.29E-08
|
Oxidation-reduction
process
|
GO:0043436
|
15
|
5.03E-03
|
GO Term (Molecular
function)
|
ID
|
Protein involved numbers
|
p-value
|
Ion binding
|
GO:0043167
|
27
|
3.43E-05
|
Cofactor binding
|
GO:0048037
|
15
|
2.38E-06
|
KEGG
|
ID
|
Protein involved numbers
|
p-value
|
Carbon metabolism
|
eco01200
|
11
|
2.89E-03
|
Biosynthesis of
secondary metabolites
|
eco01110
|
19
|
1.25E-02
|
Table 3. Kd values for 2-oxohistidine peptides binding to
identified proteins. All
Kd values were determined by
dose-response measurements. Different concentration of fluorescent oxidative
peptides, normal peptides, and fluorescent dye were probed onto the chip which
10 identified proteins immobilized. Based on the dose-response, we could use
double-reciprocal plot to calculate the Kd
values. We also used
the oxo-IA peptide, which was different peptide sequence and
labeled different fluorescent dye, and its negative control (IA peptide) to confirm
the binding between identified proteins and 2-oxohistidine.
|
Oxidative
Peptides
|
Normal
Peptides
|
Fluorescent
Dyes
|
Name
|
DyLight 550 oxo-AG
|
DyLight 550 oxo-SE
|
DyLight
650
oxo-IA
|
DyLight 650 AG
|
DyLight 650 SE
|
DyLight 550 IA
|
DyLightTM
550
|
DyLightTM
650
|
thrS
|
1.2E-8 ±
9.6E-10a
|
6.7E-9 ±
1.9E-9a
|
3.9E-8 ± 4.7E-9a
|
1.4E-7 ±
3.5E-8
|
2.5E-7 ±
8.3E-8
|
1.0E-7 ± 6.8E-8
|
8.5E-8 ±
1.1E-8
|
1.1E-7 ± 1.6E-8
|
yqjG
|
1.1E-8 ±
9.2E-10a
|
3.4E-9 ±
2.4E-10a
|
1.4E-8 ± 1.7E-9a
|
4.9E-7 ±
2.1E-7
|
1.0E-7 ±
4.5E-9
|
1.2E-7 ± 7.0E-8
|
2.9E-7 ±
9.7E-8
|
1.4E-7 ± 2.7E-8
|
yajL
|
5.6E-8 ±
2.8E-8a
|
1.4E-8 ±
7.5E-9a
|
1.0E-7 ± 3.1E-8a
|
3.7E-7 ±
1.9E-7
|
8.6E-7 ± 2.8E-7
|
2.2E-7 ± 1.2E-7
|
2.5E-7 ±
1.3E-7
|
4.4E-7 ± 2.9E-7
|
hemE
|
8.7E-10 ±
6.1E-11a
|
6.9E-10 ±
2.3E-11a
|
5.6E-9 ± 5.3E-10a
|
1.9E-7 ±
3.4E-8
|
1.2E-8 ±
7.7E-10
|
1.2E-7 ± 3.5E-8
|
1.4E-7 ±
5.4E-8
|
4.8E-8 ± 5.7E-9
|
ilvA
|
1.6E-8 ±
4.1E-9a
|
2.8E-8 ±
3.6E-8a
|
5.9E-7 ± 1.7E-7a
|
2.9E-7 ±
4.1E-8
|
2.9E-7 ±
5.9E-8
|
1.5E-6 ± 6.8E-7
|
8.5E-8 ±
5.4E-8
|
1.3E-6 ± 5.3E-7
|
prpD
|
1.6E-7 ±
1.7E-7a
|
9.0E-8 ±
1.8E-7a
|
1.3E-7 ± 2.1E-8a
|
7.3E-7 ±
1.0E-7
|
6.2E-7 ±
4.2E-7
|
7.9E-7 ± 1.7E-7
|
1.3E-6 ±
8.7E-7
|
2.4E-6 ± 5.7E-7
|
zwf
|
1.4E-8 ±
1.5E-9a
|
2.3E-8 ±
2.7E-8a
|
7.2E-8 ± 1.7E-8a
|
1.2E-6 ±
5.3E-7
|
5.8E-7 ±
2.2E-7
|
3.7E-7 ± 2.7E-7
|
5.6E-7 ±
3.6E-7
|
6.4E-7 ± 2.7E-7
|
eda
|
3.9E-9 ±
2.7E-10a
|
2.0E-9 ±
2.6E-10a
|
9.2E-8 ± 1.6E-8a
|
3.3E-7 ±
1.1E-7
|
2.6E-7 ±
9.4E-8
|
2.6E-7 ± 1.1E-7
|
2.2E-7 ±
2.4E-7
|
4.6E-7 ± 2.1E-7
|
gor
|
2.4E-8 ±
3.5E-9a
|
1.2E-8 ±
1.8E-9a
|
8.3E-8 ± 3.4E-8a
|
1.1E-6 ±
5.5E-7
|
8.6E-7 ±
5.0E-7
|
2.2E-7 ± 8.2E-8
|
9.0E-7 ±
5.0E-7
|
6.1E-7 ± 3.7E-7
|
pqqL
|
5.4E-9 ±
4.7E-10a
|
1.8E-9 ±
2.3E-10a
|
6.7E-8 ± 1.1E8a
|
3.0E-7 ±
2.0E-7
|
3.0E-7 ±
1.1E-7
|
3.7E-7 ± 2.7E-7
|
1.5E-7 ±
9.2E-8
|
6.3E-7 ± 3.8E-8
|
a
Significant difference to its normal peptide control and fluorescent dye
control ( p < 0.05).
|
Table 4. Top 10 protein list of [SD][QV][AEDT]A[YIL][CE][AK][ARL][MV][AHK]? [KET][LV][AYLF]E
enriched in entire E. coli K12. The motif was searched in entire E.
coli K12 proteome by GLAM2SCAN.
Rank
|
Name
|
EcoGene Accession
|
START
|
SITE
|
END
|
SCORE
|
1
|
ilvA
|
EG10493
|
266
|
DSDAICAAMKDLFE
|
279
|
29.2
|
2
|
thrS
|
EG11001
|
116
|
DVEALEKRMHELAE
|
129
|
28.1
|
3
|
yqjG
|
EG12746
|
202
|
SQEAYDEAVAKVFE
|
215
|
26
|
4
|
pqqL
|
EG11744
|
357
|
MQDAANALMAELAT
|
370
|
24.3
|
5
|
prpD
|
EG13603
|
293
|
SQTAVEAAM.TLYE
|
305
|
23
|
6
|
eda
|
EG10256
|
53
|
AVDAIRAIAKEVPE
|
66
|
22.6
|
7
|
gor
|
EG10412
|
87
|
SRTAYIDRIHTSYE
|
100
|
22.5
|
8
|
zwf
|
EG11221
|
54
|
DKAAYTKVVREALE
|
67
|
21.8
|
9
|
yajL
|
EG13272
|
101
|
IVAAICAAPATVLV
|
114
|
21.1
|
10
|
hemE
|
EG11543
|
174
|
DPQALHALLDKLAK
|
187
|
20
|
Table 5. Secondary structure of
Motifs from 10 E. coli K12 identified
proteins and human S100A1 proteins. The secondary structure of
motifs for each protein was provided by their provider and RCSB PDB with protein
3D structures. However, the hemE, zwf and pqqL do not have the protein 3D
structure in RCSB PDB. We used the EcoGene 3.0 which contains the QUARK prediction
method to predict the secondary structure of motifs.
Name
|
Secondary structure of Motif
|
Source
|
PDB ID
|
QUARK ID
|
Reference
|
thrS
|
Alpha-helix
|
RCSB PDB
|
1TJE
|
|
(34, 39)
|
yqjG
|
Alpha-helix
|
RCSB PDB
|
4G0L
|
|
(38, 39)
|
yajL
|
Beta-sheet+Alpha-helix
|
RCSB PDB
|
2AB0
|
|
(36, 39)
|
hemE
|
Alpha-helix
|
EcoGene 3.0
|
|
E11780
|
(41, 42)
|
ilvA
|
Alpha-helix
|
RCSB PDB
|
1TDJ
|
|
(33, 39)
|
prpD
|
Alpha-helix
|
RCSB PDB
|
1SZQ
|
|
(31, 39)
|
zwf
|
Alpha-helix
|
EcoGene 3.0
|
|
E14278
|
(41, 42)
|
eda
|
Alpha-helix
|
RCSB PDB
|
1WAU
|
|
(37, 39)
|
gor
|
Alpha-helix
|
RCSB PDB
|
1GEU
|
|
(32, 39)
|
pqqL
|
Alpha-helix
|
EcoGene 3.0
|
|
E12551
|
(41, 42)
|
S100A1
|
Alpha-helix
|
RCSB PDB
|
1ZFS
|
|
(35, 39)
|
Table 6. Kd values for 2-oxohistidine peptides binding to S100A1.
|
Oxidative
Peptides
|
Normal
Peptides
|
Fluorescent
Dyes
|
S100A1
|
DyLight 550 oxo-AG
|
DyLight 550 oxo-SE
|
DyLight
650
oxo-IA
|
DyLight 650 AG
|
DyLight 650 SE
|
DyLight 550 IA
|
DyLightTM
550
|
DyLightTM
650
|
w/o
calciumb
|
5.3E-9
± 4.9E-9a
|
5.2E-9
± 2.1E-9a
|
1.2E-8
± 4.2E-9a
|
3.9E-8
± 4.0E-8
|
8.2E-8
± 5.7E-8
|
3.1E-8
± 2.0E-8
|
3.4E-7
± 2.4E-7
|
3.6E-7
± 3.6E-7
|
w/
calcium
|
7.3E-9
± 4.8E-9a
|
2.9E-9
± 6.4E-10a
|
2.8E-8
± 9.8E-9a
|
1.3E-7
± 9.1E-8
|
8.5E-8
± 5.5E-8
|
6.6E-8
± 3.7E-8
|
5.6E-8
± 3.8E-8
|
1.2E-7
± 8.4E-8
|
a
Significant difference to its normal peptide control and fluorescent dye
control ( p < 0.05).
b No
significant difference to with calcium group (p > 0.1).
|
Figures
Figure 1.
Figure 2.
Figure 3.
Figure
4.
Figure 5.
Figure 6.
Figure 7A.
