Download Metabolic adaptation of Mycobacterium avium subsp

Microbiology (2013), 159, 380–391
DOI 10.1099/mic.0.062737-0
Metabolic adaptation of Mycobacterium avium
subsp. paratuberculosis to the gut environment
Mathias Weigoldt,1 Jochen Meens,1 Franz-Christoph Bange,2
Andreas Pich,3 Gerald F. Gerlach134 and Ralph Goethe13
Correspondence
Ralph Goethe
[email protected]
1
Institute for Microbiology, Department of Infectious Diseases, University of Veterinary Medicine
Hannover, Hannover, Germany
2
Department of Medical Microbiology and Hospital Epidemiology, Medical School Hannover,
Hannover, Germany
3
Institute for Toxicology, Medical School Hannover, Hannover, Germany
Received 3 August 2012
Revised
30 November 2012
Accepted 3 December 2012
Knowledge on the proteome level about the adaptation of pathogenic mycobacteria to the
environment in their natural hosts is limited. Mycobacterium avium subsp. paratuberculosis (MAP)
causes Johne’s disease, a chronic and incurable granulomatous enteritis of ruminants, and has
been suggested to be a putative aetiological agent of Crohn’s disease in humans. Using a
comprehensive LC-MS-MS and 2D difference gel electrophoresis (DIGE) approach, we
compared the protein profiles of clinical strains of MAP prepared from the gastrointestinal tract of
diseased cows with the protein profiles of the same strains after they were grown in vitro. LC-MSMS analyses revealed that the principal enzymes for the central carbon metabolic pathways,
including glycolysis, gluconeogenesis, the tricaboxylic acid cycle and the pentose phosphate
pathway, were present under both conditions. Moreover, a broad spectrum of enzymes for boxidation of lipids, nine of which have been shown to be necessary for mycobacterial growth on
cholesterol, were detected in vivo and in vitro. Using 2D-DIGE we found increased levels of
several key enzymes that indicated adaptation of MAP to the host. Among these, FadE5, FadE25
and AdhB indicated that cholesterol is used as a carbon source in the bovine intestinal mucosa;
the respiratory enzymes AtpA, NuoG and SdhA suggested increased respiration during infection.
Furthermore higher levels of the pentose phosphate pathway enzymes Gnd2, Zwf and Tal as well
as of KatG, SodA and GroEL indicated a vigorous stress response of MAP in vivo. In conclusion,
our results provide novel insights into the metabolic adaptation of a pathogenic mycobacterium in
its natural host.
INTRODUCTION
Mycobacterium avium subsp. paratuberculosis (MAP) is
the causative agent of Johne’s disease (paratuberculosis),
a chronic granulomatous enteritis of ruminants (Manning
& Collins, 2001; Harris & Barletta, 2001). Among the
pathogenic mycobacteria, MAP exhibits a strong intestinal
tissue tropism, as it preferentially infects and multiplies in
3These authors contributed equally to this paper.
4Present address: IVD GmbH, Heisterbergallee 12, 30453 Hannover,
Germany.
Abbreviations: BDC, bovine mucosa-derived cytoplasm; CDC, culturederived cytoplasm; COG, Clusters of Orthologous Groups of Proteins;
DIGE, difference gel electrophoresis; MAP, Mycobacterium avium subsp.
paratuberculosis; MTB, Mycobacterium tuberculosis; PPP, pentose
phosphate pathway; TCA cycle, tricarboxylic acid cycle.
Two supplementary figures and two supplementary tables are available
with the online version of this paper.
380
the gut mucosa. This is of particular interest, since MAP
has long been suggested to be associated with Crohn’s
disease in humans (Greenstein, 2003). In cattle, MAP is
transmitted primarily via the faecal–oral route to neonatal
calves. During the subsequent preclinical phase (2–5 years),
bacteria persist and multiply in subepithelial macrophages,
causing a chronic inflammation (Clarke, 1997; Harris &
Barletta, 2001). Pathological alterations are preferentially
found in the distal jejunum, ileum and the ileocaecal
junction (Clarke, 1997). In contrast to other mycobacterial
diseases, granuloma formation at the site of infection is
diffuse, resulting in a granulomatous enteritis with mucosal
thickening. Furthermore, even at late stages of disease no
caseous necrosis or ulceration occurs. Lesions in other
areas are found less commonly, confirming the intestinal
region as the major site of disease (Buergelt et al., 1978).
The molecular mechanisms of MAP pathogenicity are still
incompletely understood. Studies with macrophage cell
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M. avium subsp. paratuberculosis proteome in the host
lines or primary macrophage cells have confirmed that MAP
shares many virulence mechanisms with Mycobacterium
tuberculosis (MTB), particularly the ability to survive in the
hostile environment of macrophages (Coussens, 2001). This
indicates common mechanisms in the pathobiology of
mycobacterial infections.
In recent years, it has become clear that carbon metabolism
is a major determinant of the pathogenicity of MTB.
Analyses of MTB obtained from macrophages in vitro and
from the lungs of mice and humans suggested that MTB
adapts its central metabolism in vivo by utilizing hostderived lipids rather than glucose and glycerol, the primary
carbon sources metabolized in vitro (Russell et al., 2010).
MTB strains lacking the glyoxylate shunt or the gluconeogenic enzyme phosphoenolpyruvate carboxykinase are
attenuated during the chronic phase of infection in a
mouse model of pulmonary tuberculosis (Marrero et al.,
2010; Muñoz-Elı́as & McKinney, 2005; McKinney et al.,
2000). Furthermore, many gene expression analyses
indicate that MTB uses various pathways that mediate
oxidative stress resistance and cell wall synthesis to
evade the host immune responses and adapt to its
intracellular lifestyle in the macrophage (Mukhopadhyay
et al., 2012).
A better understanding of mycobacterial metabolism in the
infected host is of critical importance for developing new
anti-mycobacterial drugs and diagnostic tools. However,
most, if not all pathomechanisms of MAP and other
pathogenic mycobacteria have been deduced to a major
extent from murine and other small-animal models or
from in vitro systems. Little is known about mycobacterial
protein expression in their natural hosts. To identify MAP
factors expressed in the host, RNA- and protein-based
approaches have been employed, although with limited
outcomes, in order to characterize the metabolic situation
of MAP in the host (Janagama et al., 2010; Egan et al.,
2008; Hughes et al., 2007; Wu et al., 2007).
Here we analysed cytosolic proteins of MAP isolated from
the intestinal tissue of diseased cows and compared them
with those of the respective mycobacteria grown in vitro.
Our comprehensive proteome analyses enabled us to deduce
adaptive changes of metabolic pathways of a pathogenic
mycobacterium in its natural host at the proteome level.
Adaptation to the host environment became apparent in
specific metabolic aspects, including nutrient availability,
responses to antimicrobial host reactions and increased need
for energy.
METHODS
Mucosa- and culture-derived MAP. The two genetically different
type II MAP strains (MW080610-2, here named strain 2; MW0808212, here named strain 3) have been described previously (Weigoldt
et al., 2011). They were obtained from cows of different ages (3.6 and
7.9 years) with clinical signs of Johne’s disease. For protein
preparation, the strains were grown in Middlebrook 7H9 broth or
on Middlebrook 7H10 agar containing OADC (oleic acid, albumin
http://mic.sgmjournals.org
fraction V, glucose, catalase) and mycobactin J (2 mg l21) as
described previously (Weigoldt et al., 2011).
Preparation of cytoplasmic fractions. Preparation of cytoplasmic
fractions of MAP from bovine gut mucosa and culture was performed
as described previously (Weigoldt et al., 2011). Cytosolic proteins
were concentrated by precipitation with TCA (15 %, v/v) and
centrifugation at 12 000 g, 15 min, 4 uC. Pellets were washed twice
with 80 % acetone and resuspended in standard cell lysis buffer
[SCLB; 8 M urea, 2 M thiourea, 30 mM Tris/HCl, 4 % CHAPS
(pH 8.5)]. Prior to 2D difference gel electrophoresis (2D-DIGE) and
preparative 2D gel electrophoresis, protein samples were treated with
the PlusOne 2-D Clean-Up kit (GE Healthcare) and resuspended in
SCLB. Final protein concentrations were determined using the 2D
Quant kit (GE Healthcare) and adjusted to protein concentrations of
10 mg ml21.
DIGE minimal labelling and 2D gel electrophoresis. MAP
obtained from three different affected intestinal locations for each
cow and from three independent cultures of each of the two strains
were used for the preparation of bovine mucosa-derived cytoplasm
(BDC) and culture-derived cytoplasm (CDC), respectively. 2DDIGE experiments were performed with the three pairs of BDC–
CDC preparations of each strain, using 50 mg of each preparation
labelled with cyanine dye Cy3 or Cy5 (GE Healthcare). Minimal
labelling was performed according to the manufacturer’s instructions. In parallel, a preparative 2D gel electrophoresis of the
respective BDC was performed, loading 1 mg protein. An additional
2D-DIGE experiment was performed comparing CDC of the two
distinct MAP strains. For 2D gel electrophoresis and 2D-DIGE, all
samples were supplemented with an equal volume of rehydration
buffer [7 M urea (Roth), 2 M thiourea (Sigma) and 4 % w/v CHAPS
(Roth)] supplemented with 2 % of the respective IPG buffer and 2 %
(v/v) DTT (GE Healthcare). Immobiline DryStrips pH 4–7, 24 cm
(GE Healthcare), were rehydrated for 14–16 h using 450 ml
rehydration buffer supplemented with 1 % of the respective IPG
buffer and 2 % (v/v) DTT (GE Healthcare). Samples were loaded
into anodal sample cups and focused as previously described
(Weigoldt et al., 2011). Second-dimension gel electrophoresis was
performed as previously described (Buettner et al., 2009).
Preparative 2D electrophoresis gels were stained with colloidal
Coomassie G-250, and prominent protein spots were excised and
digested with trypsin as described previously (Weigoldt et al., 2011)
before MALDI-TOF MS.
Scanning of 2D gels and protein quantification. Differential 2D
gels were scanned on a Typhoon Trio Scanner (GE Healthcare) at a
resolution of 100 dots cm21 using filters with specific excitation and
emission wavelengths for the Cy3 (580BP30; 532 nm and 580 nm)
and Cy5 (670/BP30; 633 nm and 670 nm). Protein spot abundance
was analysed by DeCyder version 6.0 (Differential Analysis Software,
GE Healthcare) using the differential in-gel analysis module.
Quantification was applied for filter-confirmed spots with slope
.1.4, area ,420 and volume ,130 000. Proteins were considered as
differentially expressed if an at least 1.5-fold expression difference was
determined between BDC and CDC. Not all of the total of six 2DDIGE gels allowed the identification of all spots. Therefore, only those
proteins were considered for Table 1 that could be clearly identified in
at least one gel of the BDC–CDC preparation from each of the two
strains and which showed an at least 1.5-fold expression difference on
all gels where they could be identified.
Protein identification by MALDI-TOF-MS. Dried samples were
solubilized in 3 ml 50 % acetonitrile (ACN) and 0.1 % trifluoroacetic
acid (TFA); 1 ml of the peptide solution was mixed with 1 ml a-cyano-
4-hydroxycinnamic acid (CHCA; 5 mg ml21), 50 % ACN, 0.1 % TFA
and spotted on the target plate. Samples were analysed on a
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381
Annotation
Fatty acid and cholesterol metabolism
MAP3716c
MAP3115c
MAP2101
MAP3399
MAP3694c
MAP3861
MAP2436c
MAP3392c
MAP2698c
MAP1302c
MAP0595c
Central metabolism
MAP2670c
MAP2671c
MAP3478
MAP1177c
MAP1688
MAP0827c
MAP2276c
Microbiology 159
MAP2593c
Antimicrobial stress response
MAP1668c
MAP3525c
MAP4265
MAP2411
MAP0187c
MAP0467c
Energy production
MAP3207
MAP2453c
MAP4227c
MAP3698c
H37Rv locus
Rv0271c
Putative function
RCN*
Molecular mass
(kDa)
pI
COGD
AccD5
FadE5
ScoB
FadA4
FadE25_4
DesA2
BcpB
78.7
76.7
71.9
59.4
66.6
47.9
40.2
42.0
31.6
19.9
5.06
5.21
5.23
5.13
4.98
5.03
4.99
5.18
4.86
5.65
I
I
I
I
I
I
I
I
(2)
O
Putative acyl-CoA dehydrogenase
Putative acyl-CoA dehydrogenase
Putative acyl-CoA oxidase
Propionyl-CoA carboxylase beta chain 2
Putative acyl-CoA dehydrogenase
3-Oxoacid CoA-transferase
Acetyl-CoA acetyltransferase
Putative acyl-CoA dehydrogenase
Acyl-[acyl-carrier protein] desaturase
BcpB (peroxiredoxin family). Bacterioferritin
comigratory protein
S-(Hydroxymethyl) glutathione dehydrogenase
FadE6
FadE22
AdhB
40.2
5.07
C
6-Phosphogluconate dehydrogenase-like protein
Glucose-6-phosphate 1-dehydrogenase
Trehalose phosphatase
Transaldolase
Malyl-CoA lyase
Citrate synthase
2-Oxoglutarate ferredoxin oxidoreductase subunit
beta
1-Pyrroline-5-carboxylate dehydrogenase
Gnd2
Zwf
OtsB2
Tal
CitA
KorA
36.7
53.0
40.5
40.4
23.7
42.3
39.4
5.26
5.23
5.23
4.72
4.75
5.6
5.48
G
G
G
G
G
C
C
RocA
59.1
5.77
C
KatG
FusA2
GroEL1
Rv3846
Rv3592
Catalase/peroxidase
Elongation factor G
Chaperonin GroEL1
Putative pyridoxamine 59-phosphate oxidase
Putative superoxide dismutase
Putative antibiotic biosynthesis monooxygenase
83.4
76.3
81.8
15.5
23.0
11.5
5.06
5.12
4.95
4.81
5.61
5.43
P
J
O
(2)
P
R
Rv3151
Rv1308
Rv3463
Rv0248c
NADH dehydrogenase subunit G
F0F1 ATP synthase subunit alpha
Putative luciferase-like monooxygenase
Succinate dehydrogenase iron–sulfur subunit
83.4
60.2
30.3
70.9
5.06
4.89
6.31
5.76
C
C
C
C
Rv3280
Rv0244c
Rv2503c
Rv1323
Rv3274c
Rv1094
Rv1608c
Rv0761c
Rv1122
Rv1121
Rv3372
Rv1448c
Rv0889c
Rv2454c
Rv1187
Rv1908c
Rv0120c
Rv3417c
SodA
NuoG
AtpA
SdhA
*Reference Common Name.
DFunctional classification of proteins has been adopted from the genome database of MAP K-10 (http://www.ncbi.nlm.nih.gov/sutils/coxik.cgi?gi=380) according to the COG database. Energy
production and conversion (C), carbohydrate transport and metabolism (G), lipid transport and metabolism (I), translation (J), post-translational modification, protein turnover, chaperones (O),
inorganic ion transport and metabolism (P), general function prediction only (R), not in COG (2).
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M. Weigoldt and others
382
Table 1. List and characteristics of proteins with increased expression in BDC
M. avium subsp. paratuberculosis proteome in the host
(a)
(d)
Not in COGs (–)
Energy production and conversion (C)
116
Cell cycle control,
mitosis and meiosis (D)
Amino acid transport
and metabolism (E)
Nucleotide transport
and metabolism (F)
Carbohydrate transport
and metabolism (G)
Coenzyme transport
and metabolism (H)
184
638
BDC
strain 2
BDC
strain 3
(b)
Lipid transport and metabolism (I)
116
194
738
Translation (J)
Transcription (K)
(c)
BDC
strain 2
Replication, recombination and repair (L)
CDC
strain 3
CDC
strain 2
BDC
strain 3
CDC
strain 2
53
57
15
41
Cell wall/membrane biogenesis (M)
CDC
strain 3
Posttranslational modification,
protein turnover, chaperones (O)
lnorganic ion transport
and metabolism (P)
Secondary metabolites biosynthesis,
transport and catabolism (Q)
General function prediction only (R)
99
Function unknown (S)
26
44
79
521
18
50 37
39
92
Signal transduction mechanisms (T)
BDC (638)
CDC (738)
Intracellular trafficking and secretion (U)
0
15
2
4
6
8 10 12
Relative abundance (%)
14
16
Fig. 1. Distribution of proteins and functional classification identified by LC-MS-MS. MAP proteins identified in BDC
preparations (a), CDC preparations (b) and core proteome present in all analysed samples (c). Relative abundance of MAP
proteins identified in BDC preparations (black bars) and CDC preparations (white bars) assigned to COG (d).
VoyagerDE Pro as described previously (Buettner et al., 2009) or an
AB Sciex TOF/TOF 5800 mass spectrometer (both AB Sciex). For
MALDI-TOF/TOF analysis, internal calibration on autolytic porcine
trypsin peptides was applied for precursor MS spectra and external
calibration with Glu-Fib fragments was used for MS-MS spectra. MS
data were searched against the Swiss-Prot Database with carbamidomethylation of cysteines, oxidation of methionine and N-terminal
acetylation as variable modification. A precursor mass deviation of
120 p.p.m. and 0.5 Da for MS-MS fragments was used. At least two
peptides with a Mascot peptide ion score higher than 20 each or one
peptide with a score higher than 55 were used as a threshold for
protein identification.
LC-MS-MS analysis. For this, 30 mg of BDC and CDC was separated
by SDS-PAGE and stained with Coomassie brilliant blue. From each
lane, seven gel slices were excised and trypsin digestion was
performed as previously described (Weigoldt et al., 2011). Peptide
extracts were combined, dried and redissolved in 10 ml 2 % ACN,
0.1 % TFA. LC-MS-MS analysis was performed on an LTQ Orbitrap
Velos mass spectrometer (Thermo-Fisher Scientific) exactly as
described recently (Böer et al., 2011). Data analysis was facilitated
by proteome discoverer software 1.2 (Thermo-Fisher Scientific) and
http://mic.sgmjournals.org
the Mascot search algorithm. Mascot was set up to search a
customized database generated using the UniProt database (release
2012_03). It includes MAP K10 (NCBI reference sequence:
NC_002944.2; 4350 genes, 4323 protein entries in UniProt), and a
total of 6760 reviewed bovine protein entries (searched for Bos
taurus). A false discovery rate of 0.01 and a peptide-score of 30 were
used. Proteins were stated to be identified if at least two peptides
were detected.
Data processing and bioinformatics. Verified datasets were
organized according to their distribution in the database Clusters of
Orthologous Groups of Proteins (COG). Pathway reconstruction was
performed using the cellular overview tool from SRI’s pathway tools
software (http://ecocyc.org/background.shtml) for proteins with a
Reference Common Name (RCN). In order to obtain information
possibly missed using the cellular overview tool, the Kyoto
Encyclopedia of Genes and Genomes (KEGG) database was searched
using MAP annotation numbers, and MTB homologues were
identified by protein homology BLAST using the Multi-Genome
Homology Comparison (Comparative Tools) of Comprehensive
Microbial Resource (CMR) available at http://cmr.jcvi.org and the
TB database (http://genome.tbdb.org).
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383
M. Weigoldt and others
pI 4
pI 7
MW
(KDa)
100
ClpB
NuoG
KatG
FadE6
AtpA
ArgH
ArgG
FadA4
GlnA1 FadE5
66
45
Pgk
Tal
RocA
GlyA
MAP2276c
CitA
FadE25_4
35
MdH
MmaA2
Gap
FadB4
MAP4227c
MAP0494
25
FixA
SodA
15
Fig. 2. Representative 2D-DIGE gel of cytoplasmic proteins of in vivo- and in vitro-grown MAP. The CDC sample was prepared
from strain 3 and labelled with Cy3 (green); the corresponding BDC preparation from strain 3 was labelled with Cy5 (red). A set
of 25 proteins identified by MALDI-TOF are indicated. For abbreviations, see Table S1.
RESULTS
Identification of proteins by LC-MS/MS analysis
Using LC-MS-MS we compared the protein profiles of
BDC of the two MAP strains with their respective CDC. In
the BDC preparations, we identified 938 different MAP
proteins, 638 of which were present in both strains (Fig. 1a,
Table S1a, available with the online version of this paper).
Despite intensive purification, LC-MS-MS revealed the
presence of a considerable number of contaminating
bovine proteins such as fibrillin, collagen, actin, fibrinogen
and fibronectin (67 proteins in both samples; Table S1a). A
total of 1048 different MAP proteins were identified in
CDC preparations with 738 proteins present in both strains
(Fig. 1b, Table S1b). Due to culturing in Middlebrook 7H9
broth containing OADC; BSA and transthyretin were
detected in the CDC preparations in addition to MAP
proteins.
We found a similar distribution of proteins in BDC and
CDC preparations in 18 different functional COG
categories (Fig. 1d). To define the core proteome that is
expressed both in vivo and in vitro, we compared the BDCand CDC-derived proteins and found 521 proteins present
in all preparations (Fig. 1c, Table S1c). These proteins
represented enzymes of the central carbon metabolism
384
[glycolysis, glyconeogenesis, pentose phosphate pathway
(PPP) and tricarboxylic acid (TCA) cycle] (Fig. 3, Table
S1). We found in vivo and in vitro expression of six of the
34 annotated FadD, 11 of the 43 annotated FadE, three of
the four annotated FadB, and four of the 10 annotated
FadA proteins of the fatty acid b-oxidation cycle as well as
the protein components of the methyl-citrate cycle and the
glyoxylate shunt (Table S1c). Moreover, we found that nine
MAP orthologues of proteins which are necessary for MTB
growth on cholesterol (Griffin et al., 2011) were expressed
both in vivo and in vitro.
2D Gel electrophoresis and protein identification
by MALDI-TOF-MS
Proteins of CDC and BDC were further analysed by
quantitative 2D-DIGE, spot isolation from the corresponding preparative Coomassie-stained 2D gels and MALDITOF-MS analysis. Since the two MAP strains used in this
study represented different genotypes (Weigoldt et al., 2011),
we initially compared CDC samples from both strains by 2DDIGE, which resulted in a highly similar protein pattern (Fig.
S1a). Next, 37 identically located protein spots representatively picked from preparative 2D gels of BDC preparations
of the two strains were identified as identical protein matches
(Fig. S1b, c). These results confirmed the high similarity of
both types of protein samples.
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Microbiology 159
M. avium subsp. paratuberculosis proteome in the host
Furthermore, we performed six 2D-DIGE experiments
comparing BDC versus CDC from the two strains. Spots of
interest were picked and analysed by MALDI-TOF-MS. A
representative 2D-DIGE experiment with 25 identified
proteins is shown in Fig. 2. In total, we analysed 309
protein spots in the BDC and CDC of both strains,
representing 153 different MAP and four different bovine
proteins (Table S2).
compartment (Kuehnel et al., 2001). This so-called
‘recycling endosome’ is segregated from the late endosomal
network, but is still able to communicate with early
endosomes by which mycobacteria may acquire nutrients
from outside the cells (Russell et al., 2010). MAP survives
in macrophages of the distal region of the small intestine,
the major site of host nutrient absorption, and, thus, one
might assume that in the host MAP has access to a complex
array of nutrients.
Quantification of protein expression by 2D-DIGE
Quantitative proteomics studies are limited in that the
enzymic activity, turnover rates and secondary protein
modifications which might be important are missed by
these methods. Nevertheless, currently, together with
transcriptional profiling studies, they are the only means
of measuring metabolic adaptation during infection of the
natural host. Proteomic data from pathogenic mycobacteria in their natural hosts are scarce, because of the
difficulties of obtaining bacterial material in sufficient
amount and quality. Initial work comparing mucosa- and
culture-derived whole-cell lysates of MAP was done by
Hughes et al. (2007) and Egan et al. (2008). Both groups
performed 2D gel electrophoresis and estimated differences
in protein abundance by silver staining. However, both
studies were limited due to the low number of proteins that
could be identified and limitations of silver-stained gels for
protein quantification. In order to avoid these technical
limitations, we used LC-MS-MS and 2D gel electrophoresis/DIGE with subsequent MALDI-TOF-MS. These methods allow quantification of protein levels between different
biological samples (Bell et al., 2012; Tonge et al., 2001).
Furthermore, 2D-DIGE with subsequent MALDI-TOF-MS
possesses high reproducibility between replicates, and small
differences in protein levels are detectable (Friedman et al.,
2007).
Among the proteins identified using densitometric spot
quantification in 2D-DIGE gels, we were able to identify 29
proteins with differential expression between BDC and
CDC (1.5-fold or higher expression in BDC compared with
CDC; Table 1, Fig. S2a–d) and 32 proteins with similar
expression (Table 2).
Among the 32 proteins with similar expression were five
central enzymes necessary for glycolysis and gluconeogenesis
(Pgi/MAP0891c, Gap/MAP1164, Pgk/MAP1165, Tpi/
MAP1166, MAP4308c/putative fructose-bisphosphate aldolase class I) and also five proteins of the canonical mycobacterial TCA cycle (GltA2/MAP0829, Icd1/MAP3455c,
GabD1/MAP3673c, Mdh/MAP2541c and Fum/MAP2693).
Similar expression levels were also found for SucC/MAP0896
and SucD/MAP0897, which can convert succinyl-CoA from
the methylmalonyl pathway to succinate, and also for enzymes
of the glyoxylate shunt (AceAb/MAP1643 and GlcB/
MAP1549c).
The 29 differentially expressed proteins were grouped
according to their putative roles in MAP metabolism in
the gut (Table 1). Thus, 11 proteins (FadE6/MAP3716c,
FadE22/MAP3115c, MAP2101, AccD5/MAP3399, FadE5/
MAP3694c, ScoB/MAP3861, FadA4/MAP2436c, FadE25_4/
MAP3392c, DesA2/MAP2698c, BcpB/MAP1302c and AdhB/
MAP0595c) were assigned to fatty acid and cholesterol
metabolism (Fig. S2a). Eight proteins (Gnd2/MAP2670c,
Zwf/MAP2671c, OtsB2/MAP3478, Tal/MAP1177c, MAP1688,
CitA/MAP0827c, KorA/MAP2276c and RocA/MAP2593c)
were assigned to central metabolism (Fig. S2b). The
antimicrobial stress response was represented by six
differentially expressed proteins (KatG/MAP1668c, FusA2/
MAP3525c, GroEL1/MAP4265, MAP2411, SodA/MAP0187c
and MAP0467c) (Fig. S2c), and another four proteins (NuoG/
MAP3207, AtpA/MAP2453c, MAP4227c and SdhA/
MAP3698c) were required for energy production (Fig. S2d).
DISCUSSION
It is now widely accepted that pathogenic bacteria adapt
their metabolism to the nutrient availability provided by
respective host niches (Eisenreich et al., 2010; Muñoz-Elı́as
& McKinney, 2006). Similar to MTB, in the host, MAP
infects and multiplies in macrophages (Zurbrick &
Czuprynski, 1987). MAP inhibits phagosomal maturation
and, like MTB, it resides in a specialized phagosomal
http://mic.sgmjournals.org
The qualitative LC-MS-MS-identification of 521 proteins
present in both BDC and CDC point to metabolic
pathways that are active in MAP both in vitro and in vivo.
We were able to detect all principal enzymes of the central
carbon metabolism (Fig. 3). MAP also expressed all
components for b-oxidation of lipids in vivo and in vitro.
Accordingly we found expression of enzymes of the
glyoxylate shunt (AceAb/MAP1643 and GlcB/MAP1549c).
The simultaneous expression of isocitrate dehydrogenase
(Icd1) indicates that the canonical TCA cycle is also active.
Of the 29 proteins that showed higher expression levels in
vivo, 11 represented enzymes of the b-oxidation pathway.
MTB lacks a canonical a-ketoglutarate dehydrogenase
(Rhee et al., 2011). Interestingly, the anaerobic type 2oxoglutarate ferredoxin oxidoreductase (MAP2276c) also
showed a higher protein level in vivo. The homologue in
MTB (KOR, Rv2454c) drives a variant of the canonical
TCA cycle by forming succinyl-CoA from a-ketoglutarate.
This atypical TCA cycle is driven by b-oxidation, while in
the absence of b-oxidation, a-ketoglutarate is transformed
via succinic semialdehyde to succinate by the enzymes of
the a-ketoglutarate decarboxylase pathway, Kgd and
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M. Weigoldt and others
MAP 1557c/gnd
MAp 2670c/gnd2
Ribulose 5phosphate
MAP 3884/fgd
MAP 2671c/zwf
MAP 1176c/zwf2
6-Phosphogluconate
MAP 1175c/opcA
MAP 1174c/devB
MAP 2285c/rpi
MAP 1135
rpe
Ribose 5phosphate
Xylose 5phosphate
Glycogen/glucan
Glucose
MAP 2432c
glpG
MAP 2819
MAP 3146c
ppgK
pgmA
Glucose 1-phosphate
Glucose 6-phosphate
MAP 0891c
MAP 0573c/otsA
MAP 0924
pgi
MAP 3478/otsB
galU
Fructose 6-phosphate
MAP 1178c/tkt
MAP 2692
MAP 3044c/pfkA
Sedoheptulose 7phosphate
Trehalose
Fructose 1,6-bisphosphate
MAP 4308c
MAP 1177c/tal
Fructose 6phosphate
Erythrose 4phosphate
Glyceraldehyde 3Dihydroxyacetone
phosphate
phosphate
MAP 1166/tpiA
MAP 1164/gap
MAP 1178c/tkt
1,3-Bisphosphoglycerate
MAP 1165/pgk
3-Phosphoglycerate
MAP 3981/gpmA
2-Phosphoglycerate
β Oxidation of
MAP 0990/eno
MAP 3646/pckG
fatty acids
MAP 1169/ppc
Phosphoenolpyruvate
MAP 1310/pykA
MAP 2540c/mez
PropionylCoA
Pyruvate
MAP 1994/ace; MAP 1956/sucB
MAP 3956/lpdC
Acetyl-CoA
MAP 0294c
pca
MAP 0827c/citA; MAP 0829/gltA2
MAP 3404
accA3
MAP 3399
accD5
Methylcitrate
MAP 1201
acn
Oxaloacetate
MAP 0297c
prpD
Citrate
MAP 2310c
citE
MAP 2541c
mdh
MAP 1201c/acn
Malate
Isocitrate
Methylisocitrate
MAP 2693
fum
MAP 1613
Fumarate
aceAb
S-Methymalonyl-CoA
MAP 1549c/glcB
MAP 1643
MAP 1688
Glyoxylate aceAb
Succinate
R-Methymalonyl-CoA
Succinyl-CoA
MAP 3673c
gabD1
MAP 3861
scoB
Acetoacetate
Glutamate
Succinic
semialdehyde
MAP 2536
kgd
MAP 1041c
gabT
MAP 4257
gadB
GABA
Acetoacetyl-CoA
GabD1/D2 (Baughn et al., 2009). The increased expression
of the oxoacid-CoA transferase ScoB (MAP3861), which
catalyses the reversible conversion of 3-oxoacid-CoA and
succinate to succinyl-CoA, indicates also that lipids are
favoured as carbon source in vivo.
386
MAP 2593c
rocA
MAP 2276c
korA
MAP 0896/sucC
MAP 0897/sucD
Succinyl-CoA
MAP 1225/mutA
MAP 1226/mutB
MAP 3455c/icd1
MAP 3455c/icd2
α-Ketoglutarate
MAP 3443/sdhA
MAP 3444/sdhB
Proline
MAP 3991
proC
1-Pyrroline-5carboxylate
Host cholesterol has been proposed as another mycobacterial carbon source in vivo. It has been shown that MTB
relies on cholesterol degradation for full virulence (Chang
et al., 2009; Griffin et al., 2011; Nesbitt et al., 2010; Pandey
& Sassetti, 2008; Sassetti & Rubin, 2003; Van der Geize
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Microbiology 159
M. avium subsp. paratuberculosis proteome in the host
Fig. 3. Scheme of the metabolic pathway network of M. avium subsp. paratuberculosis (adopted from Rhee et al., 2011;
Baughn et al., 2009). Overview of proteins belonging to the major metabolic pathways identified in this study. MAP locus tags
and gene abbreviations of proteins detected by LC-MS/MS in BDC and CDC samples of both strains are indicated. Red type
indicates proteins with higher expression in vivo as determined by 2D-DIGE and MALDI-TOF-MS experiments. aceAb,
isocitrate/methylisocitrate lyase; accA3, accD5, propionyl CoA carboxylase; aceE, dlaT and lpdC, pyruvate dehydrogenase E1
and E2 components; acn, aconitase/methylaconitase; citA, citrate synthase 2; citE, citrate lyase; CoA, coenzyme A; devB, 6phosphogluconolactonase; eno, enolase; fgd, F420-dependent glucose-6-phosphate dehydrogenase; fructose 1,6bisphosphatase; fum, fumarate hydratase; gabD1, succinic semialdehyde dehydrogenase, gabT, GABA transaminase; gadB,
glutamate decarboxylase; galU, glucose-1-phosphate uridylyltransferase; gap, glyceraldehyde-3-phosphate dehydrogenase;
glcB, malate synthase, glgP, glycogen phosphorylase; glpX, fructose 1,6-bisphosphatase; gltA2, type II citrate synthase; gnd
and gnd2, 6-phosphogluconate dehydrogenase; icd1 and icd2, isocitrate dehydrogenase; kgd, a-ketoglutarate decarboxylase;
kor, a-ketoglutarate ferredoxin oxidoreductase; methylmalonyl CoA epimerase; mdh, malate dehydrogenase, mutAB,
methylmalonyl-CoA mutase, small and large subunit, mez, malic enzyme; opcA, glucose-6-phosphate dehydrogenase
assembly protein; otsA, trehalose-phosphate synthase; otsB, trehalose-phosphate phosphatase; ppgK, glucokinase; pca,
pyruvate carboxylase; pckA, phosphoenolpyruvate carboxykinase; pfkA, phosphofructose kinase; pgi, phosphoglucose
isomerase; pgk, phosphoglycerate kinase; pgmA and gpmA, phosphoglycerate mutase; ppc, phosphoenolpyruvate
carboxylase; proC, pyrroline 5-carboxylate reductase; prpD, methylcitrate dehydratase; pykA, pyruvate kinase; rocA, 1pyrroline-5-carboxylate dehydrogenase; rpe, ribulose-phosphate 3-epimerase; rpi, ribose-5-phosphate isomerase; scoB, 3oxoacid CoA transferase, sdhAB, succinate dehydrogenase flavoprotein subunits; sucCD, succinyl-CoA synthetase beta and
alpha subunits; tal, transaldolase; tkt, transketolase; tpiA, triosephosphate isomerase; zwf and zwf2, glucose-6-phosphate 1dehydrogenase; GABA, gamma-aminobutyrate.
et al., 2007). Among the nine MAP orthologues of proteins
that have been described to be necessary for mycobacterial
growth on cholesterol and which were expressed in vivo
and in vitro, HsaA/MAP0497 and HsaD/MAP0498 are
involved in cholesterol ring degradation, and FadD36/
MAP2580c and FadE25/MAP3392c are involved in sidechain degradation. The constitutive expression of these
proteins even in the absence of cholesterol (in vitro)
suggests metabolic ‘preparedness’ of MAP for different
carbon sources.
Several enzymes of cholesterol metabolism displayed
increased protein levels in MAP in vivo, such as AccD5,
the propionyl-CoA carboxylase beta chain. Propionyl-CoA
carboxylase converts propionyl-CoA, derived from the
degradation of odd-numbered fatty acids or the cholesterol
side chains, into methylmalonyl-CoA. Methylmalonyl-CoA
is further converted to succinyl-CoA, which can enter the
TCA cycle. The likewise-upregulated enzymes acyl-CoA
dehydrogenase FadE5 and acetyl-CoA acetyltransferase
FadE25 have been reported recently to be required for
MTB growth on cholesterol in vitro (Griffin et al., 2011). In
addition, we observed an increased abundance of AdhB and
BcpB, whose orthologues in MTB were identified to be also
essential for growth on cholesterol (Griffin et al., 2011).
Support for the hypothesis of MAP feeding on cholesterol
inside the host was also provided by increased expression of
an orthologue of the MTB MCE-family protein Mce4D
(MAP0567/Rv3496c), a cholesterol transport protein identified in the membrane fraction of mucosa-derived MAP in
our previous study (Weigoldt et al., 2011).
In the host, MAP carbon metabolism seems to rely on the TCA
cycle. This is further supported by the enhanced expression of
RocA and of CitA. RocA is encoded on a predicted operon
together with a proline dehydrogenase (MAP2592c). Both
enzymes are found in MTB (Rv1187–Rv1188) and are
http://mic.sgmjournals.org
responsible for the two-step degradation of proline to
glutamate. Glutamate, after conversion to 2-oxoglutarate or
via the GABA shunt, can enter the TCA cycle. Since the genes
for the generation of proline from arginine are not present in
MAP, the increased expression of RocA in MAP in the host
might indicate that MAP increasingly metabolizes proline
provided from the host. One source might be host collagen.
This could reflect a special adaptation of MAP grown in the
ruminant host, since proline can accumulate in plants
(Verbruggen & Hermans, 2008) and might be provided in
high amounts through the diet of ruminants.
We identified four enzymes of the PPP with higher expression
in BDC. Zwf (MAP2671c) and Gnd2 (MAP2670c) encode a
glucose-6-phosphate 1-dehydrogenase and a 6-phosphogluconate dehydrogenase, respectively, which catalyse the
conversion of glucose 6-phosphate to ribulose 5-phosphate.
Tal (MAP1177c) is a transaldolase required for the production of fructose 6-phosphate and erythrose 4-phosphate in the
non-oxidative branch of the PPP. The mycobacterial PPP is
necessary for the generation of NADPH, which serves as
reducing agent in many biosynthetic pathways as well as in
the oxidative stress response, and as a pentose source for
nucleotide biosynthesis and for arabinose, which is an
essential part of the mycobacterial cell envelope (Alderwick
et al., 2011). Thus, increased expression of PPP in vivo might
serve various purposes in adaptation of MAP during
infection.
After crossing the intestinal barrier, MAP infects and
survives inside macrophages, where it has to resist reactive
oxygen species (ROS) and reactive nitrogen species (RNS)
(Ehrt & Schnappinger, 2009). Among the more highly
expressed MAP proteins necessary for combating stress,
SodA converts superoxide radicals to hydrogen peroxide,
which is converted into water and oxygen by KatG. An
upregulation of katG in host-derived MAP at the mRNA
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387
Annotation
Glycolysis/gluconeogenesis
MAP0891c
MAP1164
MAP1165
MAP1166
MAP3044c
MAP3146c
MAP3981
MAP4308c
PPP
MAP1557c
TCA cycle
MAP0829
MAP0896
MAP0897
MAP1549c
MAP1643
MAP2541c
MAP2693
MAP3455c
MAP3673c
Amino acid transport and metabolism
MAP1024
MAP1361
MAP1365
MAP1367
MAP1368
MAP1962
MAP2661
MAP2699c
H37Rv locus
Putative function
RCN*
Molecular mass
(kDa)
pI
COGD
Rv0946c
Rv1436
Rv1437
Rv1438
Rv3010c
Rv3068c
Rv0489
Glucose-6-phosphate isomerase
Glyceraldehyde-3-phosphate dehydrogenase
Phosphoglycerate kinase
Triosephosphate isomerase
6-Phosphofructokinase
Phosphoglucomutase
Phosphoglyceromutase
Fructose-1,6-bisphosphate aldolase
Pgi
Gap
Pgk
Tpi
PfkA
PgmA
Gpm
60.7
36.1
42.4
27.5
37.0
58.0
27.2
33.6
5.32
5.22
4.84
5.23
6.06
5.48
5.42
5.31
G
G
G
G
G
G
G
G
Rv1844c
6-Phosphogluconate dehydrogenase
Gnd
52.8
5.23
G
Rv0896
Rv0951
Rv0952
Rv1837c
Rv1916
Rv1240
Rv1098c
Rv3339c
Rv0234c
Type II citrate synthase
Succinyl-CoA synthetase subunit beta
Succinyl-CoA synthetase subunit alpha
Malate synthase G
Isocitrate lyase
Malate dehydrogenase
Fumarate hydratase
Isocitrate dehydrogenase 1
Succinic semialdehyde dehydrogenase
GltA2
SucC
SucD
GlcB
AceAb
Mdh
Fum
Icd1
GabD1
48.3
43.2
30.8
80.3
85.2
34.6
49.7
46.4
50.0
5.09
4.95
5.23
4.83
5.35
4.87
5.36
5.63
4.77
C
C
C
C
C
C
C
C
C
Rv1077
Rv1652
Rv1656
Rv1658
Rv1659
Rv2220
Rv1133c
Putative cystathionine beta-synthase
N-Acetyl-gamma-glutamyl-phosphate reductase
Ornithine carbamoyltransferase
Argininosuccinate synthase
Argininosuccinate lyase
Glutamine synthetase
5-Methyltetrahydropteroyltriglutamate—homocysteine
methyltransferase
Serine hydroxymethyltransferase
CysM2
ArgC
ArgF
ArgG
ArgH
GlnA1
MetE
49.2
35.3
33.6
43.8
49.7
53.7
81.6
5.1
5.86
4.9
5.21
5.06
4.96
5.02
E
E
E
E
E
E
E
GlyA
45.0
5.75
E
Rv1093
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M. Weigoldt and others
388
Table 2. List and characteristics of proteins of the major metabolic pathways with similar expression in BDC and CDC
Rv0859
Rv0215c
Rv0644c
MAP0789
MAP3651c
MAP4095c
http://mic.sgmjournals.org
*Reference Common Name.
DFunctional classification of proteins has been adopted from the genome database of MAP K-10 (http://www.ncbi.nlm.nih.gov/sutils/coxik.cgi?gi=380) according to the COG database. Energy
production and conversion (C), amino acid transport and metabolism (E), carbohydrate transport and metabolism (G), lipid transport and metabolism (I), cell wall/membrane biogenesis (M).
I
I
M
42.6
44.1
33.1
FadA_1
FadE3_2
MmaA2
5.03
6.15
5.12
I
I
I
5.18
12.0
5.15
30.8
46.1
40.8
FadB2
EchA3
GcpE
3-Hydroxybutyryl-CoA dehydrogenase
Putative enoyl-CoA hydratase/isomerase (MAPs_39340)
4-Hydroxy-3-methylbut-2-en-1-yl diphosphate synthase
(IspG)
Acetyl-CoA acetyltransferase
Putative acyl-CoA dehydrogenase
Cyclopropane-fatty-acyl-phospholipid synthase
Rv0468
Rv0632c
Rv2868c
Fatty acid transport and metabolism
MAP3962
MAP4102c
MAP2938c
Annotation
Table 2. cont.
H37Rv locus
Putative function
RCN*
Molecular mass
(kDa)
pI
COGD
M. avium subsp. paratuberculosis proteome in the host
level has been shown using real-time PCR (Granger et al.,
2004). The induction of both sodA and katG has been shown
in culture at the transcriptional level in MTB after applying
oxidative and nitrosative stress (Voskuil et al., 2011).
Furthermore, expression of these proteins sustained the
viability of MTB in mouse infection models (Edwards et al.,
2001; Li et al., 1998). GroEL1 (MAP4265) protein levels were
increased up to 21-fold in vivo. GroEL1 has high similarity to
its counterpart in MTB (Rv3417c). In MTB, both GroEL1
and GroEL2 proteins are upregulated during heat shock
(Stewart et al., 2002), the oxidative stress response (Dosanjh
et al., 2005), and oxidative damage upon macrophage
infection (Monahan et al., 2001). Moreover, some studies
suggest their involvement in the immune response to MTB
infection (Lewthwaite et al., 2001; Orme et al., 1993).
Recently it has been reported that GroEL1 binds strongly to
DNA and effectively functions as a DNA-protecting agent
against DNase I or hydroxyl radicals (Basu et al., 2009). In
addition, the orthologues of FusA2 and BcpB as well as the
monooxygenase MAP0467c have been suggested to be
involved in counteracting stress responses of MTB and
MAP (Seshadri et al., 2009; Berney & Cook, 2010; Janagama
et al., 2010; Jaeger, 2007).
It seems that in the host, MAP exhibits enhanced metabolic
activity. In agreement with this, expression of three enzymes
involved in oxidative phosphorylation was strongly
increased. NuoG belongs to the NADH : ubiquinone oxidoreductase complex I, the first component of the respiratory
chain (Friedrich & Böttcher, 2004). MAP3698c is highly
homologous to MTB Rv0248c a putative subunit of the
succinate dehydrogenase (SdhA) of the respiratory chain.
Lastly, MAP2453c/AtpA is a subunit alpha of the F0F1 ATPsynthase, which generates ATP within aerobic respiration.
Overall, these data indicate that MAP, in the host, displays
enhanced respiration, which is a further indication of MAP
adaptation to the host environment.
Conclusion
Within the host, changes in MAP metabolism seem to be
dominated by an adaptation to antimicrobial host
reactions, which is indicated by the enhanced expression
of protective enzymes such as SodA and KatG. Energy
losses due to these processes might be compensated by
an enhanced activity of the PPP and enhanced ATP
generation through respiratory phosphorylation. The
central metabolism appears to be driven by b-oxidation
of alternative lipid sources, most probably cholesterol,
which is abundant in host cell membranes. The acetyl-CoA
generated enters an alternative TCA pathway in which a
type 2 oxoglutarate ferredoxin oxidoreductase contributes
to the conversion of a-ketoglutarate to succinyl-CoA.
Upon growth on the TCA cycle, MAP uses the glyoxylate
shunt. Carbon efflux for gluconeogenesis via phosphoenolypyruvate and for amino acid synthesis might be
compensated by the generation of a-ketoglutarate from
glutamate via degradation of proline.
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389
M. Weigoldt and others
Overall, our results provide novel insights into the
metabolic adaptation of a pathogenic mycobacterium in
its natural host.
Edwards, K. M., Cynamon, M. H., Voladri, R. K., Hager, C. C.,
DeStefano, M. S., Tham, K. T., Lakey, D. L., Bochan, M. R. &
Kernodle, D. S. (2001). Iron-cofactored superoxide dismutase inhibits
host responses to Mycobacterium tuberculosis. Am J Respir Crit Care
Med 164, 2213–2219.
ACKNOWLEDGEMENTS
Egan, S., Lanigan, M., Shiell, B., Beddome, G., Stewart, D., Vaughan,
J. & Michalski, W. P. (2008). The recovery of Mycobacterium avium
We are grateful to Klaus Doll (Clinic for Ruminants and Swine,
Justus-Liebig-University, Giessen, Germany) for supporting the
organization of infected cattle, and to Peter Valentin-Weigand for
critical reading of the manuscript. This work was supported by the
German Ministry for Science and Education (BMBF; ZooMAP,
01KI0750 and ZooMAPII 01KI1003A, 01KI1003B). R. G. was
additionally supported by a grant from the German Research
Foundation (DFG; Ge522/6-1).
subspecies paratuberculosis from the intestine of infected ruminants
for proteomic evaluation. J Microbiol Methods 75, 29–39.
Ehrt, S. & Schnappinger, D. (2009). Mycobacterial survival strategies
in the phagosome: defence against host stresses. Cell Microbiol 11,
1170–1178.
Eisenreich, W., Dandekar, T., Heesemann, J. & Goebel, W. (2010).
Carbon metabolism of intracellular bacterial pathogens and possible
links to virulence. Nat Rev Microbiol 8, 401–412.
Friedman, D. B., Wang, S. E., Whitwell, C. W., Caprioli, R. M. &
Arteaga, C. L. (2007). Multivariable difference gel electrophoresis and
mass spectrometry: a case study on transforming growth factor-b and
REFERENCES
Alderwick, L. J., Lloyd, G. S., Lloyd, A. J., Lovering, A. L., Eggeling,
L. & Besra, G. S. (2011). Biochemical characterization of the
Mycobacterium tuberculosis phosphoribosyl-1-pyrophosphate synthetase. Glycobiology 21, 410–425.
Basu, D., Khare, G., Singh, S., Tyagi, A., Khosla, S. & Mande, S. C.
(2009). A novel nucleoid-associated protein of Mycobacterium
tuberculosis is a sequence homolog of GroEL. Nucleic Acids Res 37,
4944–4954.
Baughn, A. D., Garforth, S. J., Vilchèze, C. & Jacobs, W. R., Jr (2009).
An anaerobic-type a-ketoglutarate ferredoxin oxidoreductase com-
pletes the oxidative tricarboxylic acid cycle of Mycobacterium
tuberculosis. PLoS Pathog 5, e1000662.
Bell, C., Smith, G. T., Sweredoski, M. J. & Hess, S. (2012).
ERBB2 signaling. Mol Cell Proteomics 6, 150–169.
Friedrich, T. & Böttcher, B. (2004). The gross structure of the
respiratory complex I: a Lego System. Biochim Biophys Acta 1608, 1–9.
Granger, K., Moore, R. J., Davies, J. K., Vaughan, J. A., Stiles, P. L.,
Stewart, D. J. & Tizard, M. L. (2004). Recovery of Mycobacterium
avium subspecies paratuberculosis from the natural host for the
extraction and analysis in vivo-derived RNA. J Microbiol Methods 57,
241–249.
Greenstein, R. J. (2003). Is Crohn’s disease caused by a mycobacter-
ium? Comparisons with leprosy, tuberculosis, and Johne’s disease.
Lancet Infect Dis 3, 507–514.
Griffin, J. E., Gawronski, J. D., Dejesus, M. A., Ioerger, T. R., Akerley,
B. J. & Sassetti, C. M. (2011). High-resolution phenotypic profiling
defines genes essential for mycobacterial growth and cholesterol
catabolism. PLoS Pathog 7, e1002251.
Characterization of the Mycobacterium tuberculosis proteome by
liquid chromatography mass spectrometry-based proteomics techniques: a comprehensive resource for tuberculosis research. J Proteome
Res 11, 119–130.
Harris, N. B. & Barletta, R. G. (2001). Mycobacterium avium subsp.
Berney, M. & Cook, G. M. (2010). Unique flexibility in energy
Hughes, V., Smith, S., Garcia-Sanchez, A., Sales, J. & Stevenson, K.
(2007). Proteomic comparison of Mycobacterium avium subspecies
metabolism allows mycobacteria to combat starvation and hypoxia.
PLoS ONE 5, e8614.
Böer, U., Lohrenz, A., Klingenberg, M., Pich, A., Haverich, A. &
Wilhelmi, M. (2011). The effect of detergent-based decellularization
procedures on cellular proteins and immunogenicity in equine
carotid artery grafts. Biomaterials 32, 9730–9737.
Buergelt, C. D., Hall, C., McEntee, K. & Duncan, J. R. (1978).
Pathological evaluation of paratuberculosis in naturally infected cattle.
Vet Pathol 15, 196–207.
Buettner, F. F., Bendalla, I. M., Bossé, J. T., Meens, J., Nash, J. H.,
Härtig, E., Langford, P. R. & Gerlach, G. F. (2009). Analysis of the
Actinobacillus pleuropneumoniae HlyX (FNR) regulon and identification of iron-regulated protein B as an essential virulence factor.
Proteomics 9, 2383–2398.
Chang, J. C., Miner, M. D., Pandey, A. K., Gill, W. P., Harik, N. S.,
Sassetti, C. M. & Sherman, D. R. (2009). igr Genes and
Mycobacterium tuberculosis cholesterol metabolism. J Bacteriol 191,
5232–5239.
Clarke, C. J. (1997). The pathology and pathogenesis of paratubercu-
losis in ruminants and other species. J Comp Pathol 116, 217–261.
Coussens, P. M. (2001). Mycobacterium paratuberculosis and the
paratuberculosis in veterinary medicine. Clin Microbiol Rev 14, 489–512.
paratuberculosis grown in vitro and isolated from clinical cases of
ovine paratuberculosis. Microbiology 153, 196–206.
Jaeger, T. (2007). Peroxiredoxin systems in mycobacteria. Subcell
Biochem 44, 207–217.
Janagama, H. K., Lamont, E. A., George, S., Bannantine, J. P., Xu,
W. W., Tu, Z. J., Wells, S. J., Schefers, J. & Sreevatsan, S. (2010).
Primary transcriptomes of Mycobacterium avium subsp. paratuberculosis reveal proprietary pathways in tissue and macrophages. BMC
Genomics 11, 561.
Kuehnel, M. P., Goethe, R., Habermann, A., Mueller, E., Rohde, M.,
Griffiths, G. & Valentin-Weigand, P. (2001). Characterization of the
intracellular survival of Mycobacterium avium ssp. paratuberculosis:
phagosomal pH and fusogenicity in J774 macrophages compared with
other mycobacteria. Cell Microbiol 3, 551–566.
Lewthwaite, J. C., Coates, A. R., Tormay, P., Singh, M., Mascagni, P.,
Poole, S., Roberts, M., Sharp, L. & Henderson, B. (2001).
Mycobacterium tuberculosis chaperonin 60.1 is a more potent cytokine
stimulator than chaperonin 60.2 (Hsp 65) and contains a CD14binding domain. Infect Immun 69, 7349–7355.
Li, Z., Kelley, C., Collins, F., Rouse, D. & Morris, S. (1998). Expression
bovine immune system. Anim Health Res Rev 2, 141–161.
of katG in Mycobacterium tuberculosis is associated with its growth
and persistence in mice and guinea pigs. J Infect Dis 177, 1030–1035.
Dosanjh, N. S., Rawat, M., Chung, J. H. & Av-Gay, Y. (2005). Thiol
Manning, E. J. & Collins, M. T. (2001). Mycobacterium avium subsp.
specific oxidative stress response in Mycobacteria. FEMS Microbiol
Lett 249, 87–94.
paratuberculosis: pathogen, pathogenesis and diagnosis. Rev Sci Tech
20, 133–150.
390
Downloaded from www.microbiologyresearch.org by
IP: 88.99.165.207
On: Sat, 29 Apr 2017 20:20:55
Microbiology 159
M. avium subsp. paratuberculosis proteome in the host
Marrero, J., Rhee, K. Y., Schnappinger, D., Pethe, K. & Ehrt, S.
(2010). Gluconeogenic carbon flow of tricarboxylic acid cycle
intermediates is critical for Mycobacterium tuberculosis to establish
and maintain infection. Proc Natl Acad Sci U S A 107, 9819–9824.
McKinney, J. D., Höner zu Bentrup, K., Muñoz-Elı́as, E. J., Miczak, A.,
Chen, B., Chan, W. T., Swenson, D., Sacchettini, J. C., Jacobs, W. R.,
Jr & Russell, D. G. (2000). Persistence of Mycobacterium tuberculosis
in macrophages and mice requires the glyoxylate shunt enzyme
isocitrate lyase. Nature 406, 735–738.
Monahan, I. M., Betts, J., Banerjee, D. K. & Butcher, P. D. (2001).
Differential expression of mycobacterial proteins following phagocytosis by macrophages. Microbiology 147, 459–471.
Mukhopadhyay, S., Nair, S. & Ghosh, S. (2012). Pathogenesis in
tuberculosis: transcriptomic approaches to unraveling virulence mechanisms and finding new drug targets. FEMS Microbiol Rev 36, 463–485.
Muñoz-Elı́as, E. J. & McKinney, J. D. (2005). Mycobacterium
tuberculosis isocitrate lyases 1 and 2 are jointly required for in vivo
growth and virulence. Nat Med 11, 638–644.
Muñoz-Elı́as, E. J. & McKinney, J. D. (2006). Carbon metabolism of
Sassetti, C. M. & Rubin, E. J. (2003). Genetic requirements for
mycobacterial survival during infection. Proc Natl Acad Sci U S A 100,
12989–12994.
Seshadri, A., Samhita, L., Gaur, R., Malshetty, V. & Varshney, U.
(2009). Analysis of the fusA2 locus encoding EFG2 in Mycobacterium
smegmatis. Tuberculosis (Edinb) 89, 453–464.
Stewart, G. R., Wernisch, L., Stabler, R., Mangan, J. A., Hinds, J.,
Laing, K. G., Young, D. B. & Butcher, P. D. (2002). Dissection of the
heat-shock response in Mycobacterium tuberculosis using mutants and
microarrays. Microbiology 148, 3129–3138.
Tonge, R., Shaw, J., Middleton, B., Rowlinson, R., Rayner, S., Young,
J., Pognan, F., Hawkins, E., Currie, I. & Davison, M. (2001). Validation
and development of fluorescence two-dimensional differential gel
electrophoresis proteomics technology. Proteomics 1, 377–396.
Van der Geize, R., Yam, K., Heuser, T., Wilbrink, M. H., Hara, H.,
Anderton, M. C., Sim, E., Dijkhuizen, L., Davies, J. E. & other authors
(2007). A gene cluster encoding cholesterol catabolism in a soil
actinomycete provides insight into Mycobacterium tuberculosis
survival in macrophages. Proc Natl Acad Sci U S A 104, 1947–1952.
intracellular bacteria. Cell Microbiol 8, 10–22.
Verbruggen, N. & Hermans, C. (2008). Proline accumulation in
Nesbitt, N. M., Yang, X., Fontán, P., Kolesnikova, I., Smith, I., Sampson,
N. S. & Dubnau, E. (2010). A thiolase of Mycobacterium tuberculosis is
plants: a review. Amino Acids 35, 753–759.
required for virulence and production of androstenedione and
androstadienedione from cholesterol. Infect Immun 78, 275–282.
response of Mycobacterium tuberculosis to reactive oxygen and
nitrogen species. Front Microbiol 2, 105.
Orme, I. M., Roberts, A. D., Griffin, J. P. & Abrams, J. S. (1993).
Cytokine secretion by CD4 T lymphocytes acquired in response to
Mycobacterium tuberculosis infection. J Immunol 151, 518–525.
Pandey, A. K. & Sassetti, C. M. (2008). Mycobacterial persistence
requires the utilization of host cholesterol. Proc Natl Acad Sci U S A
105, 4376–4380.
Rhee, K. Y., de Carvalho, L. P., Bryk, R., Ehrt, S., Marrero, J., Park,
S. W., Schnappinger, D., Venugopal, A. & Nathan, C. (2011). Central
carbon metabolism in Mycobacterium tuberculosis: an unexpected
frontier. Trends Microbiol 19, 307–314.
Russell, D. G., VanderVen, B. C., Lee, W., Abramovitch, R. B., Kim,
M. J., Homolka, S., Niemann, S. & Rohde, K. H. (2010). Mycobacterium
tuberculosis wears what it eats. Cell Host Microbe 8, 68–76.
http://mic.sgmjournals.org
Voskuil, M. I., Bartek, I. L., Visconti, K. & Schoolnik, G. K. (2011). The
Weigoldt, M., Meens, J., Doll, K., Fritsch, I., Möbius, P., Goethe, R. &
Gerlach, G. F. (2011). Differential proteome analysis of Mycobacterium
avium subsp. paratuberculosis grown in vitro and isolated from cases of
clinical Johne’s disease. Microbiology 157, 557–565.
Wu, C. W., Schmoller, S. K., Shin, S. J. & Talaat, A. M. (2007). Defining
the stressome of Mycobacterium avium subsp. paratuberculosis in vitro
and in naturally infected cows. J Bacteriol 189, 7877–7886.
Zurbrick, B. G. & Czuprynski, C. J. (1987). Ingestion and intracellular
growth of Mycobacterium paratuberculosis within bovine blood
monocytes and monocyte-derived macrophages. Infect Immun 55,
1588–1593.
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