Supplement bij veertiende jaargang, april 2006 - NVMM

14.01
A genome-scale model of Lactobacillus plantarum WCFS1:
useful for omics data integration and exploring metabolic
capacities
B. Teusink 1,2,3 , A. Wiersma 1,2 , D. Molenaar 1,2 , C. Francke 1,3 ,
W.M. De Vos 1,4 , R.J. Siezen 1,2,3 , E.J. Smid 1,2
1 Wageningen Centre for Food Sciences, Wageningen, 2 NIZO
food research, Ede, 3 Radboud University, Center for Molecular
and Biomolecular Informatics, Nijmegen, 4 Wageningen
University, Microbiology, Wageningen
Systems biology took off because of the omics revolution,
confronting biologists with the need of models for data
integration, analysis, and - ultimately - understanding of
the complexity of biological systems. Hence, if we want to
make optimal use of functional genomics data, we need
models of genome scale. We have built a genome-scale
metabolic model of Lactobacillus plantarum WCFS1, an
important industrial lactic acid bacterium, both for food
and health applications. The complete model currently
consists of 546 unblocked internal reactions and 434
corresponding metabolites, 97 exchange reactions, and 721
genes (23.5% of the genome). The model is based on bioinformatics,
comparison with other genome-scale models,
literature, and in-house generated experimental evidence
for the presence of pathways. Interactive metabolic maps
have been generated, enabling data projection onto these
maps. Chemostat experiments were run to generate physiological
data for model construction and validation. Fluxes
and biomass composition were measured. From this data,
maintenance and growth-associated ATP consumption
rates were estimated. Using Flux Variability Analysis,
we found a remarkable flexibility in ATP-producing and
ATP-consuming pathways, including 28 futile cycles
detected by genome-scale elementary flux mode analysis.
Optimization of an objective function – referred to as flux
balance analysis (FBA) – has been often used to predict flux
distributions in metabolic networks, but it fails miserably
in L. plantarum. Rather than predicting flux distributions,
FBA does appear useful in L. plantarum for exploring
potential contributions to metabolic objectives, such as
ATP generation or biomass yield.
14.02
Culture-independent approaches to elucidate biodiversity
and population dynamics in complex microbial ecosystems
of food fermentations and the intestinal tract
G. Huys
Laboratory of Microbiology, Faculty of Sciences, Ghent
University, Ghent, Belgium
Introduction: In recent years, DNA-based cultureindependent
techniques have opened interesting perspec-
Ned Tijdschr Med Microbiol 2006; 4:Supplement
S47
tives to unravel the composition and population dynamics
of microbial communities in various environments.
Especially in highly complex microbial ecosystems such
as fermented food products and the intestinal tract, there
is ample evidence illustrating that the use of conventional
culture methods alone is inadequate to assess the true
diversity of predominant bacterial groups in food or faecal
samples. Triggered by the universal availability of bacterial
gene and genome sequences and by the development of
new molecular tools, direct microbial analysis of minimally
disturbed samples has become possible.
Methods: Sequence-dependent electrophoresis techniques
such as Denaturing Gradient Gel Electrophoresis (DGGE)
are one of the most commonly used approaches for
microbial population profiling of fermented food and
intestinal ecosystems. Through the use of universal and/
or group-specific PCR primers targetting the 16S rDNA
gene or single-copy housekeeping genes, the PCR-DGGE
concept offers a wide range of possibilities to study the
predominant members or a specific subpopulation in a
given microbial community. On the other hand, it should
be noted that PCR-DGGE – at its best performance – is a
semi-quantitative technique. For the assessment of relative
bacterial concentrations or the quantification of temporal
shifts in complex microbial ecosystems, PCR-DGGE thus
needs to be complemented with quantitative molecular
tools such as Real-time PCR (RT-PCR).
Results: In the course of previous and ongoing research
projects, the biodiversity and population dynamics of
several traditional fermented foods have been studied
with PCR-DGGE. The use of universal V 3 -16S rDNA
primers in PCR-DGGE in combination with digitized
band position analysis and band sequencing allowed to
assign predominant band fragments to specific taxa of the
lactic acid bacteria (LAB) present in Belgian sourdoughs
(mainly Lactobacillus and Weissella species), Flemish
artisanal cheeses (mainly Lactococcus, Lactobacillus and
Pediococcus species) and the South-African fermented
sorghum product Ting (mainly Lactobacillus species). PCR-
DGGE analysis also proved to be highly useful for temporal
monitoring of semi-industrial or lab-scale fermentation
processes and could give a reliable indication of the
minimal fermentation time needed to develop a stable
LAB community in each product. In another set of studies,
the potential of PCR-DGGE to monitor the stability of
predominant microbiota and specific bacterial subgroups
in faecal samples was explored during placebo-controlled
pro-, pre- and synbiotic administration trials in healthy
human volunteers. Although the targetted populations
remained fairly stable based on PCR-DGGE profiling
with V 3 -16S rDNA primers, one striking finding in these
trials concerned the appearance or intensification of one
specific DGGE band after intake of the prebiotic compound
lactulose. Band sequence analysis showed that in 90% of