Biomedical Engineering Reference
In-Depth Information
Teachable moment: the physiome project: the
macroethics of engineering toward health
In
The Bridge,
the Journal of the National Academy of
Engineering, James B. Bassingthwaighte Vol. 32, No. 3 -
(Fall 2002), identified and described some of the most
important
engineering tools and techniques that can be
used to advance health care.
According to Bassingthwaighte, the new tools fall into
four categories:
1. Informatics and information flow
The problem in medicine and biology is that much
relevant information is either irretrievable or undis-
covered. Even a complete human genome cannot
define human function. In fact, it is only a guide to the
possible ingredients. The genetically derived aspects
of the genome (i.e., proteins) are much more numerous
than the genes. To get an idea of the magnitude of the
problem, consider that yeast has about three proteins
per gene, and humans have about 10 proteins per
gene. Pretranslational selection from different parts of
the DNA sequence, the posttranslational slicing out of
parts of the protein, the splicing of two or more
proteins together, and the combining of groups of
proteins into functional, assembly-line-like complexes,
all contribute to the variety of the products of gene
expression. Even a completely identified proteome,
which is still beyond the scientific horizon, will be like
a list of the types of parts of a jumbo jet with no
indication of how many should be used or where they
go. The concentration of proteins, the balance
between synthesis and decay in each cell type, is
governed by environment, by behavior, and by the
dynamic relationships among proteins, substrates,
ionic composition, energy balance, and so on and,
thus, cannot be predicted on the basis of the genome.
the kinetics of others in a signaling sequence), then it
may ''connect'' to any other protein through only a few
links, a kind of ''six degrees of separation'' from any
other protein. Moreover, cells contain not just proteins,
but also substrates and metabolites, and they are
influenced by their environments. Given the possible
permutations and combinations of linkages and the
many multiples further in the dynamics of their
interactions, the combinatorial explosion would
appear to preclude predictions.
3. Managing complexity
The complexity
.
briefly described provides a basis
for functionality that cannot be predicted from
knowledge about each of the components.
''Emergent'' behavior is the result of interactions
among proteins, subcellular systems, and aggregates
of cells, tissues, organs, and systems within an
organism. Physiological systems are highly nonlinear,
higher order systems, and dynamics are often chaotic.
Chaotic systems are only predictable over the short
term; but they have a limited operating range. Even
when Bernard (1927) defined the stability of the ''milieu
interieure,'' he meant a mildly fluctuating state rather
than a stagnant ''homeostasis.'' Biological systems are
''homeodynamic''; they fluctuate, but under control,
and they are neither ''static'' nor ''randomly varying.''
4. Bioinformatics
This vast array of information must be linked into
a consistent whole. The databases must be well
curated and easily accessible, and they must provide
a substrate for behaviorally realistic models of
physiological systems. The arguments for building
large databases to capture biological data are fairly
new. Federal funds support genomic and proteomic
databases, but not databases of higher level
physiological information. Organ and systems data
acquired over the past century have not been
collected in databases and are poorly indexed in the
print literature. Providing searchable texts of articles
online will help but will not be a substitute for organized
databases. The Visible Human Project, the National
Library of Medicine's effort to preserve anatomic
information is a part of the morphome (which we define
as providing anatomic and morphometric information),
analogous to the genome and the proteome.
2. The combinatorial dilemma
Sorting out the genome will leave us with a huge
number of proteins to think about. The estimates of the
number of genes have come down by about half from
earlier estimates of 60 000 to 100 000; because new
ones are also being found, 50 000 is a reasonable
estimate. The level of complexity in mammalian protein
expression far exceeds that of
C. elegans,
which has
19 536 genes and 952 cells. Humans might only have
two or three times as many genes, but probably have
a much higher ratio of proteins per gene. Assuming 10
proteins per gene, we have on the order of a half million
proteins in widely varied abundance, and each protein
has several possible states. If a protein in a given state
interacts with only five other proteins (e.g., exchanging
substrates with neighbors in a pathway or modifying
Bassingthwaighte continues:
All of this information must then be captured in a comprehensive,
consistent, conceptual framework; that is, a model of the system
that conveys understanding, and for this we will need to use
engineering approaches. Understanding complicated systems,
