(447f) Temporal Metabolic Profiling of Plasma in Response to Endotoxemia in Humans

Elective administration of bacterial endotoxin (LPS) to
healthy human subjects has been used as a reproducible experimental procedure
providing mechanistic insights into how cells, tissues and organs respond to
systemic inflammation. Low doses of LPS transiently alter many physiologic and
metabolic processes in a qualitatively similar manner to those observed after
acute injury and systemic inflammation (1,
2); thus allow the analysis of body's
responses to infectious stress at many physiological levels for building better
understanding of the relevant pathology. Analysis of the metabolic response, in
this regard, is of special interest since metabolic composition of a tissue is
uniquely altered in response to stimuli due to collective effects of the regulations
at transcriptional and translational levels. Therefore, concentrations of
metabolites of a sample at a given time, i.e. the ?metabolome? (3), can be thought of as the metabolic
fingerprint representative of the state of the body at that time and give
information about the dominant regulatory mechanisms. Although the changes in
the major metabolites, such as lipids, amino acids and glucose, has been previously
documented for human endotoxemia (4); current study constitutes the first
attempt of a complete metabonomic analysis that describes the coherent temporal
patterns of the metabolic landscape in plasma following exposure to LPS.

Metabonomic
analysis is comprised of global biochemical profiles determined in human plasma
samples from healthy subjects. Nineteen subjects were administered either
placebo (saline, n=4) or LPS (n=15) by a bolus injection and blood samples were
collected at 5 time points within a 24 hour post-treatment period. Global
biochemical profiles obtained by GC/MS and LC/MS/MS platforms represented
information on 366 biochemicals including amino acids, short peptides,
carbohydrates, lipids, nucleotides, cofactors and vitamins, xenobiotics and
intermediate products of major energy production pathways. Within this dataset,
we first identified those metabolites which have differential temporal profiles
between control and LPS groups. The most significant difference between the two
groups was at 6hr time point, which was also an inflection point separating
development and recovery phases of the LPS induced metabolic changes. Then,
through consensus clustering (5), we identified subsets of the metabolites
with common coherent profiles. This analysis yielded two clusters with opposing
directionality as shown in Figure 1. The first cluster (16 metabolites) was
up-regulated within the first 6hr and down-regulated by the 24^th hr and
was mostly composed of metabolites from pathways related to lipid metabolism. The
second cluster (21 metabolites), in contrast, was down-regulated within the
first 6hr post-LPS, and then up-regulated by the 24^th hr. Strikingly
15 out of 21 metabolites in this cluster were amino acids or derivatives and an
additional 2 were dipeptides.

Figure 1: Differential patterns of metabolic response to LPS. Two clusters of plasma
metabolites reflect two distinct patterns with opposing temporal directionality.

Preferential early clearance of amino acids can be
attributed to hepatic uptake for the synthesis of acute phase proteins, while build-up
of fatty acids in the plasma can be due to extensive lipolysis as a result of
cytokine-mediated changes in lipid metabolism. Also, early build-up of some
precursor molecules in sterol/steroid related pathways may indicate the propensity
for hormone biosynthesis to suppress inflammation and promote recovery. These
results highlight the changes in lipid and amino acid metabolism in response to
infectious stress while also reflecting the most-closely associated plasma
metabolites pointing out to co-regulatory schemes governing that response.

References

1.       Lowry SF. Human endotoxemia: a model for
mechanistic insight and therapeutic targeting. Shock. 2005;24 Suppl 1:94-100.

2.       Calvano SE, Coyle SM. Experimental human
endotoxemia: a model of the systemic inflammatory response syndrome? Surg
Infect (Larchmt). 2012;13(5):293-9. PMCID: 3503465.

3.       Nicholson JK, Lindon JC. Systems biology:
Metabonomics. Nature. 2008;455(7216):1054-6.

4.       Fong YM, Marano MA, Moldawer LL, Wei H,
Calvano SE, Kenney JS, et al. The acute splanchnic and peripheral tissue
metabolic response to endotoxin in humans. J Clin Invest. 1990;85(6):1896-904.

5.       Nguyen
TT, Nowakowski RS, Androulakis IP. Unsupervised selection of highly coexpressed
and noncoexpressed genes using a consensus clustering approach. OMICS A Journal
of Integrative Biology. 2009;13(3):219-37.