April, 2011
NMR Metabolite Profiling of Bacterial Biofilms in Chronic Wounds
K.L. Morrissey, L.K. Jennings, P.R. Secor, B. Tripet, G.A. James, P.S. Stewart, V. Copié
Department of Chemistry and Biochemistry, MSU’s NMR and MS Metabolomics Research Facilities
METHODS
PRELIMINARY RESULTS
We hypothesize that anaerobic bacterial metabolism
occurs deep within the wound bed where oxygen
concentrations are low, and that the presence of
fermenting microorganisms can be detected through
NMR metabolite profiling. However, if adequate blood
circulation is present near the bottom of the wound
bed, anaerobic metabolism may be more active in the
middle of the biofilm.
PRELIMINARY RESULTS
Intensity
lactate
acetate
BCM - biofilm
PCM - planktonic
EPI – media control
Sum line
glucose
Intensity
histamine
hydroxyphenylacetate
histamine
Chemical Shift (ppm, upfield)
formate
Chronic-wound
biofilms
are
host-pathogen
environments that harbor a large diversity of bacterial
species including anaerobic, aerobic, and facultative
organisms. Metabolomic profiling of chronic wounds
may provide a more accurate indication of the
average oxidative state of cells within the biofilm
allowing treatment to be tailored to individual patients.
Metabolomics is an emerging field that involves the
quantification of small-molecule metabolites (<1000
Da) in bodily fluids, tissues, or cells to gain insight into
the operation of biological systems.
glutamine
Chronic wounds including diabetic foot ulcers, venous
leg ulcers, and pressure ulcers are healing-resistant
wounds that are characterized by prolonged
inflammation and failure to re-epithelialize.
The
presence of a biofilm is increasingly accepted as the
major impediment to wound healing. Disruption of the
biofilm community and removal of necrotic tissue via
debridement has proven successful in the treatment
of chronic wounds. Unfortunately, it is difficult to
completely remove the biofilm, and incomplete
removal can result in inability to clear the infection
and, ultimately, limb amputations.
glutamine
INTRODUCTION
Figure 2. Bruker 600 equipped with sample jet
Cell
metabolites
were
extracted
using
a
methanol/chloroform/water extraction method. 1-D
NOESY 1H NMR spectrum were acquired using a
Bruker 600 MHz NMR equipped with an autosampler.
The NMR spectra were processed and the
metabolites quantified using Chenomx software suite.
Quantification of the metabolites were determined by
comparison to the internal standard 4,4-dimethyl-4silapentane-1-sulfonic acid (DSS).
Hierarchical
clustering conducted in Genesis was used to visualize
results.
Peg Dirckx CBE
Figure 1. Illustration of chronic wound micro-community
where biofilms are a major barrier to wound healing.
OBJECTIVE
The goal of this study is to use NMR metabolite
profiling to analyze the extracellular metabolome of
Staphylococcus aureus biofilms compared to
planktonically grown cells.
S. aureus is an important human pathogen and a
predominant organism found in chronic-wound microcommunities. Metabolite profiling of S. aureus
excretions may provide insight into the mechanism of
pathogenesis and the persistence of infection in
chronic wounds.
7
7
Wound tissue metabolites were extracted also using a
methanol/chloroform/water extraction method. Similar
to the method with the cells, 1-D NOESY 1H NMR
spectrum were acquired and the NMR spectra were
processed and the metabolites quantified using
Chenomx software suite.
Tissue Sample
Conc. ( mM )
Metabolite
Serum Sample
Conc. ( mM )
Lactate
0.3866
Glucose
6.4612
Glucose
0.3553
Lactate
2.5069
Taurine
0.2008
Glutamine
0.9771
Fructose
0.1195
Alanine
0.7244
Homoserine
0.1058
Glycerol
0.4299
Alanine
O-Phosphoethanolamine
Glycerol
0.0755
Valine
0.3507
0.0703
Threonate
0.2725
0.066
Propylene glycol
0.2392
Glutamate
0.0617
Lysine
0.2247
Glutamine
0.0614
Citrate
0.2218
Table 1. Most abundant metabolite concentrations found in
the right foot medial tissue and corresponding serum
sample in the NMR tube. This data must be normalized in
the future for further analysis and comparison.
Note: Further validation of metabolites'
presence and
concentration using 2D NMR and mass spectrometry is in
progress.
CONCLUSIONS
Chemical Shift (ppm, downfield)
Figure 3. NMR spectra of excreted metabolites from S.
aureus biofilms (blue), planktonic cells (green), and EpiLife
growth medium (EPI, black).
PCM BCM EPI
Preliminary results indicate that glucose and amino
acids were selectively consumed by S. aureus biofilms,
while mixed-acid fermentation products (lactate,
acetate, and formate) were produced.
The results
agree with previously published findings from
proteomics, transcriptomics, and identification of
individual metabolite studies that suggest that
anaerobic or microaerobic metabolism is important to
the S. aureus biofilm phenotype.
NMR-metabolite profiling was effective at quantifying
metabolites in S. aureus biofilm and planktonic cells.
Metabolite profiling of S. aureus excretions revealed
metabolites unique to biofilms and may provide insight
into the mechanism of pathogenesis and the
persistence of infection in chronic wounds.
Pressure ulcer Samples:
Pressure ulcer biopsies
Serum samples
Metabolite
Low Conc.
High Conc.
Mixed-acid
fermentation products
formed by biofilm
Preliminary results of the chronic wound and serum
profiling demonstrate abundant metabolites found in
the corresponding samples in the NMR tube. The
serum control can help delineate host metabolites from
biofilm metabolites once the data can be accurately
compared.
ACKNOWLEDGMENTS
Amino acids in media
selectively consumed
by biofilm and
planktonic cells
Serum metabolites were extracted using a 3 kDa
Amicon Ultra 0.5 ml filter. The filter was washed 5
times with 0.5 ml of sterile water and centrifuged for
12 minutes at 14,000 g. The Filter is coated with a
small molecule membrane preservative, such as
glycerol, which can interfere with metabolite analysis.
Adding these rinsing steps can improve the recovery
of metabolites from the protein component. Following
the washing, 1 ml of serum, split between two filters
(0.5 ml in each filter), was filtered through the washed
filter by centrifuging for 30 minutes at 14,000 g.
Figure 4. Hierarchical clustering (covariance distance) of
S. aureus metabolites from triplicate PCM, BCM, and EPI.
Light colors indicate high metabolite concentrations, while
black indicates metabolite concentrations below detection.
The serum filtrate was combined with 10% D2O NMR
buffer and 1-D NOESY 1H NMR spectrum were
acquired. Metabolites were again quantified using
Chenomx software suite.
Note: Further validation of metabolites'
presence and
concentration using 2D NMR and mass spectrometry is in
progress.
C-source
Funding was provided by the Undergraduate Hughes
Scholars Program through the Howard Hughes Medical
Institute (Grant #52006931) and NCRR Administrative
Supplement Award to “Advance T1 & T2 Translational
Research” to NIH P20 RR024237 COBRE Award.
The NMR Metabolomics Facility at MSU is supported
by an Administrative Supplement Award to Dr. Dratz
“Center for the Analysis of Cellular Mechanisms and
Systems Biology”. We thank MSU COBRE director, Dr.
Ed Dratz, as well as Dr. Brian Bothner, and Dr.
Jonathan Hilmer, Director and Manager, respectively, of
MSU’s Mass Spectrometry and Proteomics Facility. We
also thank the Medical Biofilms Laboratory at the
Center for Biofilm Engineering, Al Parker, Scott Busse,
and Kate McInnerney for technical assistance.