Developing Three-Dimensional
Maps of Metabolism
Core reactions and overlapping signatures among microorganisms could
help in predicting greater metabolic complexities
Diana Downs
nderstanding the full extent of metabolic diversity is a challenge. This diversity among eukaryotes, bacteria,
and archaea reflects the great breadth
of physical and chemical environments that such organisms face. Modern biologists generally accept the idea that the visible diversity we find among the range of living
organisms results from their underlying biochemical diversity.
However, regardless of the structural and
metabolic differences that separate species, each
living cell conducts similar core biochemical reactions. If we could more fully define this common metabolic core by focusing on and thus
discerning its overlapping signature among sev-
U
Summary
• Understanding metabolic networks as threedimensional systems that include flux determinants could provide insights into metabolic potentials under multiple conditions
and circumstances.
• Understanding metabolic processes common
to all organisms in rigorous detail is a valuable
step amid continuing efforts to apprehend the
diversity of life.
• During the next stage of metabolic studies,
investigators will integrate hundreds of biochemical units into a bigger picture, providing
a three-dimensional rather than two-dimensional view.
• This three-dimensional approach could help
toward identifying subtle factors that result in
low level metabolite distribution that may account for the robust qualities of physiology at
the cellular level.
eral relatively simple microorganisms, we would
be better situated to manipulate, model, and
reconstruct metabolism in more complex cells.
Further, insights about core metabolic requirements and capability may lead to improvements
in the environment as well as in human and
animal health.
Understanding metabolic networks as threedimensional systems that include flux determinants will provide us with insights into metabolic potentials under multiple conditions. Deep
knowledge of such dynamic systems and their
adaptive behaviors could lead to models allowing us to predict the behaviors of metabolic
systems in different organisms responding to different environments. Such knowledge thus could
prove more valuable than are our current,
constrained snapshots of metabolism that reflect merely ephemeral responses of cells occupying single environments.
Cellular Physiology Arises from
Integrated Metabolic Networks
At the core of any living cell is its metabolism,
the sum of all biochemical processes contributing to cellular function. Coordinated integration of these processes generates the robust
and responsive physiology that characterizes
life. Common to all living cells is a framework
of biochemical reactions that, when combined, serve at least three key functions: (i)
obtaining energy from organic or inorganic
compounds or by harvesting light energy, (ii)
converting nutrients to cellular building
blocks, and (iii) assembling simple chemical
building blocks into critical cellular components, including proteins, nucleic acids, and
lipids.
Diana Downs is a
professor in the
Department of Bacteriology, University
of Wisconsin, Madison.
Volume 4, Number 1, 2009 / Microbe Y 23
FIGURE 1
Progression toward generating a three-dimensional map of metabolism. Schematically represented are the steps in achieving a three
dimensional understanding of metabolism. In this schematic, generic pathways are shown. Metabolites are represented by dots, and
enzymatic conversions represented with lines in. A) Solid understanding of the individual pathways at the level of genetics and biochemistry
will continue to come from rigorous biochemical genetics and in vitro studies. B) Consolidation of the information obtained in (A) into a
2-dimensional layout of the pathways that are known will continue to be done by increasingly sophisticated computational approaches. C)
Metabolic interactions that are mediated by metabolite distribution and not identified by computational predictions must be identified by
creative in vivo approaches. D) Culmination of efforts depicted in A, B, C will be a complete understanding of the components, metabolites
and flux throughout in bacterial metabolism. The dynamic system described will provide data for modeling various static scenarios that
reflect a snapshot of system function in a given niche.
Coordinating these processes and incorporating system-specific biochemistries enable organisms to propagate, respond to stimuli, perform
diverse functions, and adapt to environments
where constellations of changing forces apply
great pressures on organisms, threatening their
survival. Hence, understanding metabolic processes common to all organisms in rigorous detail is a valuable step amid continuing efforts to
comprehend the diversity of life and, where appropriate, to harness biological systems for our
benefit. Microorganisms provide a useful choice
in these endeavors due to their rapid growth,
technical advantages such as ease of genetic
manipulation, and the conservation of their core
biochemistries according to genomic analyses.
A Three-Dimensional Perspective Helps
with Understanding Metabolism
The metabolic network is neither static nor merely
two-dimensional. The physiology that arises from
24 Y Microbe / Volume 4, Number 1, 2009
such networks reflects a complex adaptive system
that is characterized by integrated and changing
patterns of metabolites flowing though multiple
points of intersection. In other complex and dynamic systems, the whole is more than the sum of
its parts, a property that is surely also true of
cellular metabolism.
Metabolic networks in living cells might be
the most efficient, complex systems in existence.
They result from billions of years of selective
pressure and perform processes that are essential to life, including the development of robust
and adaptive traits. The numbers of metabolic
interactions within any single microbial cell exceeds our experience with even the most complex human-made machines.
For this discussion, we construe a completed
three-dimensional map of metabolism as having
three key features: (i) information describing all
biochemical processes in a cell, (ii) information
describing connections that result from metabolites flowing among diverse biochemical pro-
Downs: Upbringing Emphasized the Richness of Leading a Good Life
While Diana Downs and her husband, Jorge Escalante-Semerena,
were post-doctoral fellows at the
University of Utah in the late
1980s, they brought their young
son to the lab with them until he
reached ten months of age. “I have
often thought that if this option
hadn’t been available, I wouldn’t
still be in science,” she says. When
their daughter came along in 1990,
the couple had moved to the University of Wisconsin (UW), Madison, where Downs was doing research as a National Institutes of
Health (NIH) fellow. “I called NIH
to see whether I could take a ninemonth break in my funding to stay
home with the kids,” she says.
However, officials indicated there
“was no precedent for this, but encouraged me to write a letter articulating my request. I did, and it
worked just fine, allowing me the
time I wanted with my children.”
Downs tells her students this
story when describing the challenges that professional women
face in balancing work and family,
stressing that ‘‘if something is important to you, ask— because it
might be possible,” she says. Moreover, she adds, ‘‘It also reminds me
just how far things have really
come.”
Today, Downs is a professor in
bacteriology at UW-Madison, and
both her children are in college at
UW. Her son Ryan is a senior, majoring in biology, while her daughter Kelsey is a freshman, majoring
in interior design. She is also her
mother’s running partner. “The
kids were [formerly] the exclusive
focus of our outside work hours for
all their childhood and I wouldn’t
change a day of it,” Downs says.
“Now they are both out of the
house, and Jorge and I are still try-
ing to figure out this new phase in
our lives.”
This perplexity over leisure time
does not extend to her work life,
where Downs is trying to decipher
rules that govern the integration of
metabolism in bacterial cells. “The
significance of understanding biological complexity in the 21st century is epitomized by the realization
that nature is full of diverse systems
that function with an efficiency
man has never matched,” she says.
‘‘Hidden in biological systems are
the solutions to problems that technology will be asked to solve in the
future.” In the long term, results
from such efforts could lead to “the
ability to manipulate metabolism in
a way that will help predict, and
thus eliminate, side reactions of
drugs [and] design cells that can
over-express compounds of interest
more efficiently,” she says.
Downs, 49, was born and lived
in Boulder, Colo., until she moved
to attend the University of Utah,
with support from a gymnastics
scholarship. She majored in biology, received her B.S. in 1981,
and remained there for graduate
school, and to do postdoctoral research. While a graduate student,
she worked with John Roth, completing her Ph.D. in 1987.
Downs is one of three sisters,
and the only one in science. One
sister is a history professor, while
the other works as a computer
software administrator. Her father, who died in 1994, was a
theoretical nuclear physicist at the
University of Colorado. Her
mother, who earned an M.S. in
physics, was a stay-at-home mom
who graded tests, translated
books, and typed papers in that
specialty.
“We grew up on a rural piece of
land,” Downs says. “The most
important thing I remember
from my childhood was the unconditional support for anything we wanted to try—from
wanting a guinea pig in first
grade, to buying a guitar, to
building a balance beam in the
barn—my mother would facilitate any interest we had. My
mother was at every meet and
most practices the many years I
was a gymnast. When I entered
graduate school, she enrolled in
a molecular biology and genetics
course at the University of Colorado, so she would have an idea
of what I was doing.
“My father influenced my career a lot by his interactions with
students,” Downs continues.
“He was an honored teacher,
and I saw him care deeply about
fairness, making himself available to students, flexibility, and
empathy. He told me once the
best thing about being at a university was that it kept you
young. Its true, and I think of his
words often.”
Her parents emphasized that
quality of life ‘‘trumped all,” she
says. “I remember a story related
by my husband,” she says. ‘‘When
he first met my father, he was
asked: ‘What do you want to do?’
to which Jorge replied: ‘I’d really
like to be a professor.’ In typical
laid-back fashion, my father
thought for a minute, and then
told him: ‘you’ll never be rich, but
you’ll have a good life.’ That
statement epitomizes my family
upbringing.”
Marlene Cimons
Marlene Cimons is a freelance writer
in Bethesda, Md.
Volume 4, Number 1, 2009 / Microbe Y 25
FIGURE 2
Understanding the complex system of metabolism requires a cyclic process. Schematically shown is the approach to metabolic
understanding that exploits an iterative approach using in vivo and in vitro technologies. Illustrated in the upper right are two biosynthetic
pathways that are distant from each other in the 2-dimensional map to the left, thiamine and tryptophan. By in vivo analysis these pathways
were shown to be connected. The role of detailed molecular analysis in this process is schematically shown by the structure of a single
enzyme, but also meant to represent the broader biochemical analysis that defines the shared metabolites in such a connection. The final
arrow leading back to the map reflects the correlation between the biochemical findings and the in vivo behavior that must exist to
understand the connection and verify that is is significant in the context of the physiology of the cell.
cesses, and (iii) information about metabolite
flow through those connections varying with
time as do the connections themselves. The patterns of flux reflect how cells adapt to specific
niches in time and space.
Developing a full, three-dimensional understanding of metabolism will require a long-term
investment in integrated studies that include genetics, biochemistry, engineering, mathematics,
computer science, and other disciplines (Fig. 1).
Solid biochemical knowledge is essential. Beyond identifying biochemical components, investigators must identify what determines the
flow of metabolites, key kinetic parameters of
enzymes, and how their level and activity is
regulated.
Understanding will be advanced step by step.
For instance, during the first stage, investigators
26 Y Microbe / Volume 4, Number 1, 2009
should try to identify the sets of biochemical
reactions that are common to all modes of life
and environmental niches. This set of reactions
could be considered the metabolic framework
upon which biochemical diversity is built.
During the second, longer-term phase, they
will try to develop a full understanding of diverse metabolisms that provide processes and
properties unique to a representative variety of
organisms. Examples of such subsystems include the abilities to generate energy from sunlight, fix molecular nitrogen, degrade toxic compounds, and produce compounds valuable to
society. These processes must be understood not
only in isolation but also in terms of how they fit
into the general metabolic framework and affect
the behavior of the entire system.
The implications of understanding how me-
tabolism is integrated can be illustrated
by considering the consequences of inborn errors of metabolism or the actions of typical antibiotics. In both
cases, the target—whether it is a mutation to a key metabolic gene or the site
where an antibiotic inhibits a cell—typically is singular. However, the consequences for the organism of that single
event can be physiologically diverse and
potentially catastrophic. In the case of
inborn errors, for instance, metabolic
integration may lead to clinical symptoms that are difficult to associate with
the known effect at the initial biochemical target because some of those symptoms arise from additional disruptions
in distant metabolic pathways.
FIGURE 3
Defining Metabolic Components
Investigators who focus on metabolic
pathways as discreet entities provide
indispensable insights about specific enzymatic reactions, biochemical pathways, and regulatory mechanisms. Despite decades of effort, however, our
understanding of metabolic components is far from complete.
Further, our current approach to
Challenges in flux diversion and metabolite distribution. Several scenarios that emphaconceptualizing metabolism typically
size the need to monitor and direct metabolites in physiology are schematically
relies on one or another two-dimenrepresented. A) Branchpoint metabolites (shown in black circle) must be diverted to two
sional schematics, or “wall charts.”
distinct pathways and might be required under different conditions and in different
quantities. B) Single metabolites can have multiple uses in the cell. As represented by the
These displays consolidate extensive ingrey circles, one metabolite can be a substrate in one or more pathways, an intermediate
formation and are valuable for identifyin another and potentially a regulator of another. Coordination of these function requires
ing metabolic branch points and precontrol of metabolite distribution. C) Enzymes can use two similar metabolites (shown by
different shapes), sometimes in parallel pathways. The need to monitor which substrate,
dicting connections and regulation based
thus which product, is produced is evident if one considers the ratio of the final products.
chemical structures of metabolites.
D) The identification of a metabolite that is generated by more than one pathway may
However, it is important to go beindicate an evolutionary intermediate, either leading to or removing redundancy. This
scenario provides a more complex example of that in (B) since the metabolite can be
yond the confines of the traditional,
made in two ways and may be needed in others. Taken together these scenarios are
two-dimensional framework for delikely to be a minimal representation of the metabolic connections that exist and must be
scribing cellular metabolism. Thus, the
considered in efforts to understand the complexity of the metabolic system.
next stage of metabolic studies will be
distinguished from past efforts, and will
traditional approach to understanding metabodepend on investigators integrating hundreds of
lism and a broader approach that could lead to a
discreet biochemical units into a bigger picture—
one that provides a three-dimensional rather than
fuller three-dimensional understanding of it. For
a conventional two-dimensional view (Fig. 1).
example, an investigator taking the traditional
approach might ask, “how is the vitamin thiaDefining Integrative Paradigms Looms as
mine made in Salmonella?” Meanwhile, an inIntellectually Challenging
vestigator pursing a broader approach might
wonder, “how can a nonlethal mutation in
Let me pose different kinds of questions as a way
to better understand differences between the
phospho-ribosylpyrophosphate synthetase re-
Volume 4, Number 1, 2009 / Microbe Y 27
sult in a cellular requirement for thiamine or
methionine?”
The first of those two questions can be answered
using classical biochemical genetic approaches
culminating in reconstitution of the biochemical
pathway in vitro. In contrast, the best route to
answering the second question is less obvious and
could involve a significant descriptive phase prior
to obtaining useful biochemical data to address the
question in molecular terms. Not only are the
approaches to addressing that first question more
obvious, the results are easier to interpret because
the variables can be minimized and the metabolic
pathway itself studied in isolation.
Contrast this with efforts to address the second
question, in which there are multiple variables,
and efforts must focus on several fronts simultaneously before the analytic process becomes linear. As with solving a maze, the investigator asks
reasonable metabolic questions that might have to
be abandoned if they prove to be dead ends. Thus,
despite being powerful, this approach to defining
global connections requires investigators to work
with multiple variables while frequently revising
their models and accepting intermittent periods of
ignorance as unavoidable. Moreover, they need to
move forward on multiple fronts, often without
resolving each independent question along the
way. Ultimately, of course, in vitro molecular and
biochemical analyses are necessary for validating
the feasibility of an in vivo model. However, in
defining metabolic connections, one major difficulty is reaching the point where a testable unifying biochemical model can be proposed.
Powerful analytic tools from molecular biology,
bioinformatics, biochemistry, and genetics are
available for metabolic studies. Newly emerging
analytical technologies facilitate the discoverybased approaches that identify connections in a
complex system. Together with classical approaches these technologies will allow us to dissect
bacterial physiology more fully, and culminate in
our three-dimensional understanding of the system. One additional challenge is that we must
accept the notion that linear progress is not the
only way forward.
Evaluating Integrating Paradigms
Genetic analysis provides one way for studying
complex interactions between biochemical
pathways. By isolating and analyzing mutants,
28 Y Microbe / Volume 4, Number 1, 2009
investigators can uncover significant metabolic
connections within an organism that might not
be apparent when enzymes, pathways, or regulons are each studied separately. Inferences from
genetic analyses then can be tested using biochemical, molecular, and computational approaches.
Subsequently, details about the biochemistry
need to be considered in the context of the
network within which they supposedly operate
(Fig. 2). Does the biochemistry explain a given
phenotype? For instance, if a mutation causes a
defect in thiamine biosynthesis but lies in the
biochemical pathway to pantothenate, the thiamine and pantothenate pathways might be integrated.
The next challenge is to define how these two
biochemical pathways are integrated. In some
cases, connections between two pathways could
reflect straightforward interactions, such as a
need for Coenzyme A (derived from pantothenate) to synthesize thiamine. In other cases, understanding the connection is less straightforward because it could be based on effects several
pathways away.
In the latter scenario, different mutants and
changing growth conditions are used to help the
investigator better understand the potential and
robustness of the wild-type metabolic system.
Sometimes unanticipated interactions involve
pathways of low metabolic flux, leading some
investigators to question whether this approach
is valid for understanding the cellular network.
However, while flux through central carbon metabolism is quantitatively different from that
through a vitamin pathway, both are essential
for survival. Meanwhile, a mutation is less likely
to generate a new function than to enhance
some low-level activity that is already present.
This enhancement may be enough to make the
activity visible in the context of a relevant phenotype and thus identify a connection that has
the potential to contribute robustness to the
system under the appropriate conditions.
To take our understanding of metabolism
past the core framework, we need to appreciate
some of the subtle factors that account for the
robust qualities of physiology. Metabolic integration and robustness are likely to depend on
quantitatively small fluxes. Over evolutionary
time, small adjustments exert a significant impact on fitness, suggesting that properties that
increase robustness would have selective advan-
tages. Rerouting or disrupting high-flux pathways seems less likely to occur at the metabolite
level because other regulatory mechanisms
could provide more efficient means for regulating these metabolic units. Perhaps some genes
with unassigned functions are modulators of
robustness. Of course, we cannot recognize
them until they are found experimentally and a
database is built up to permit predictive metabolic modeling.
What Else Might We Expect To Find?
After defining a metabolic network, another feature to understand is how metabolites are diverted
to generate robustness. Several well-established
paradigms help in addressing questions about the
flux of metabolites. For instance, regulation at the
transcriptional level provides one means for modulating metabolic pathways and regulons, producing large changes, and minimizing energy misuse.
Altering metabolite levels and distribution lead to
subtler changes.
Even a relatively crude metabolic map can be
used to highlight issues cells face in regulating
metabolite distributions. In some scenarios, the
balancing of specific metabolites depends on
interpathway communication and thus goes beyond the regulation of metabolic units at the
level of transcription. Allosteric, or posttranslational, regulation of individual enzymes may
come into play, changing availability of single
metabolites in a metabolic unit (Fig. 3).
Branched metabolic pathways split before they
generate two or more different compounds (Fig.
3A). In such cases, the branch-point metabolite is
distributed appropriately to form the correct
amounts of end products. An inability to regulate
such a branch point could lead to inadequate or
overabundant supplies of one or more of those end
compounds, a situation that could damage the
cell. Few paradigms for regulation of metabolic
branch points have been rigorously defined.
Metabolites such as ATP that are consumed
in multiple pathways (Fig. 3B) should be available at the right place and in the right concentrations. How are these metabolites distributed? Meanwhile, promiscuous enzymes can
participate in multiple pathways (Fig. 3C), or
they can generate toxic by-products. Both scenarios illustrate why controlling metabolite
distribution is important. Again, the scope of
paradigms defining how such pathways are
regulated is not known.
In another scenario, a metabolite in one pathway is used as a precursor or intermediate in
other pathways (Fig. 3D). If the relevant metabolite can bypass part of a distinct pathway, it
provides flexibility for regulating or eliminating
enzymatic steps. This or other connections
could be remnants of or intermediates in evolution.
All of these scenarios have implications for
the overall flow of metabolites in cells, no matter
whether kinetic parameters or active regulatory
mechanisms are modulating that flux. Investigators will need to work through many examples
of metabolite diversion before they can begin to
model complex metabolic systems and then expand databases describing new paradigms. As
more of these separate examples are put together, we can become better at describing the
complex metabolic systems of cells and arrive at
a three-dimensional understanding of cell function.
SUGGESTED READING
Downs, D. M. 2006. Understanding microbial metabolism. Annu. Rev. Microbiol. 60:561–558.
Holland, J. H. 1995. Hidden order; how adaptation builds complexity. Perseus Books, Cambridge.
Kitami, T., and J. H. Nadeau. 2002. Biochemical networking contributes more to genetic buffering in human and mouse
metabolic pathways than does gene duplication. Nature Genet. 32:191–194.
Strovas, T. J., and M. E. Lidstrom. 2008. Analyzing bacterial physiology at the single-cell level. Microbe 3:234.
Ramos, I., E. I. Vivas, and D. M. Downs. 2008. Mutations in the tryptophan operon allow PurF-independent thiamine
synthesis by altering flux in vivo. J. Bacteriol. 190:815– 822.
Reed, J. L., and B. O. Palsson. 2003. Thirteen ears of building constraint-based in silico models of Escherichia coli. J. Bacteriol.
185:2692–2699.
Zhu, X., M. Gerstein, and M. Snyder. 2007. Getting connected: analysis and principles of biological networks. Genes Dev.
21:1010 –1024.
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