Encyclopedia of Cell Technology.pdf

ENCYCLOPEDIA OF

CELL TECHNOLOGY

VOLUME 1

Raymond E. Spier

University of Surrey

Guildford, Surrey

United Kingdom

A Wiley-lnterscience Publication

John Wiley & Sons, Inc.

New York / Chichester / Weinheim / Brisbane / Singapore / Toronto

ENCYCLOPEDIA OF

CELL TECHNOLOGY

VOLUME 2

Raymond E. Spier

University of Surrey

Guildford, Surrey

United Kingdom

A Wiley-lnterscience Publication

John Wiley & Sons, Inc.

New York / Chichester / Weinheim / Brisbane / Singapore / Toronto

This book is printed on acid-free paper. @

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Library of Congress Cataloging in Publication Data

Encyclopedia of cell technology / [edited by] Raymond E. Spier.

p. cm.

ISBN 0-471-16123-3 (cloth : set: alk. paper) —ISBN (invalid)

0-471-16643-X(v. 1 : alk. paper). —ISBN 0-471-16623-5 (v. 2 :

alk. paper).

1. Animal cell biotechnology Encyclopedias. 2. Plant cell

biotechnology Encyclopedias. 3. Cell culture Encyclopedias.

4. Cytology Encyclopedias. I. Spier, R. (Raymond)

TP248.27.A53E53 2000

660.6 —dc21

99-25295

Printed in the United States of America.

10 987654321

PREFACE

The Wiley Biotechnology Encyclopedias, composed of

the Encyclopedia of Molecular Biology, the Encyclopedia

ofBioprocess Technology: Fermentation, Biocatalysis, and

Bioseparation; the Encyclopedia of Cell Technology; and

the Encyclopedia of Ethical, Legal, and Policy Issues in

Biotechnology cover very broadly four major contemporary

themes in biotechnology. The series comes at a fascinating

time in that, as we move into the twenty-first century,

the discipline of biotechnology is undergoing striking

paradigm changes.

Biotechnology is now beginning to be viewed as an

informational science. In a simplistic sense there are

three types of biological information. First, there is the

digital or linear information of our chromosomes and genes

with the four-letter alphabet composed of G, C, A, and

T (the bases guanine, cytosine, adenine, and thymine).

Variation in the order of these letters in the digital

strings of our chromosomes or our expressed genes (or

mRNAs) generates information of several distinct types:

genes, regulatory machinery, and information that enables

chromosomes to carry out their tasks as informational

organelles (e.g., centromeric and telomeric sequences).

Second, there is the three-dimensional information of

proteins, the molecular machines of life. Proteins are

strings of amino acids employing a 20-letter alphabet.

Proteins pose four technical challenges: (1) Proteins are

synthesized as linear strings and fold into precise three-

dimensional structures as dictated by the order of amino

acid residues in the string. Can we formulate the rules

for protein folding to predict three-dimensional structure

from primary amino acid sequence? The identification

and comparative analysis of all human and model organ-

ism (bacteria, yeast, nematode, fly, mouse, etc.) genes

and proteins will eventually lead to a lexicon of motifs

that are the building block components of genes and pro-

teins. These motifs will greatly constrain the shape space

that computational algorithms must search to successfully

correlate primary amino acid sequence with the correct

three-dimensional shapes. The protein-folding problem

will probably be solved within the next 10-15 years.

(2) Can we predict protein function from knowledge of

the three-dimensional structure? Once again the lexicon

of motifs with their functional as well as structural cor-

relations will play a critical role in solving this problem.

(3) How do the myriad of chemical modifications of proteins

(e.g., phosphorylation, acetylation, etc.) alter their struc-

tures and modify their functions? The mass spectrometer

will play a key role in identifying secondary modifications.

(4) How do proteins interact with one another and/or with

other macromolecules to form complex molecular machines

(e.g., the ribosomal subunits)? If these functional com-

plexes can be isolated, the mass spectrometer, coupled

with a knowledge of all protein sequences that can be

derived from the complete genomic sequence of the organ-

ism, will serve as a powerful tool for identifying all the

components of complex molecular machines.

The third type of biological information arises from

complex biological systems and networks. Systems

information is four dimensional because it varies with

time. For example, the human brain has 1,012 neu-

rons making approximately 1,015 connections. From this

network arise systems properties such as memory, con-

sciousness, and the ability to learn. The important point is

that systems properties cannot be understood from study-

ing the network elements (e.g., neurons) one at a time;

rather the collective behavior of the elements needs to be

studied. To study most biological systems, three issues

need to be stressed. First, most biological systems, three

issues need to be stressed. First, most biological systems

are too complex to study directly, therefore they must

be divided into tractable subsystems whose properties in

part reflect those of the system. These subsystems must

be sufficiently small to analyze all their elements and con-

nections. Second, high-throughput analytic or global tools

are required for studying many systems elements at one

time (see later). Finally the systems information needs

to be modeled mathematically before systems properties

can be predicted and ultimately understood. This will

require recruiting computer scientists and applied math-

ematicians into biology—just as the attempts to decipher

the information of complete genomes and the protein fold-

ing and structure/function problems have required the

recruitment of computational scientists.

I would be remiss not to point out that there are many

other molecules that generate biological information:

amino acids, carbohydrates, lipids, and so forth. These too

must be studied in the context of their specific structures

and specific functions.

The deciphering and manipulation of these various

types of biological information represent an enormous

technical challenge for biotechnology. Yet major new and

powerful tools for doing so are emerging.

One class of tools for deciphering biological information

is termed high-throughput analytic or global tools. These

tools can be used to study many genes or chromosome

features (genomics), many proteins (proteomics), or many

cells rapidly: large-scale DNA sequencing, genomewide

genetic mapping, cDNA or oligonucleotide arrays, two-

dimensional gel electrophoresis and other global protein

separation technologies, mass spectrometric analysis of

proteins and protein fragments, multiparameter, high-

throughput cell and chromosome sorting, and high-

throughput phenotypic assays.

A second approach to the deciphering and manipula-

tion of biological information centers around combinatorial

strategies. The basic idea is to synthesize an informa-

tional string (DNA fragments, RNA fragments, protein

fragments, antibody combining sites, etc.) using all combi-

nations of the basic letters of the corresponding alphabet,

thus creating many different shapes that can be used to

activate, inhibit, or complement the biological functions of

designated three-dimensional shapes (e.g., a molecule in a

signal transduction pathway). The power of combinational

chemistry is just beginning to be appreciated.

A critical approach to deciphering biological infor-

mation will ultimately be the ability to visualize the

functioning of genes, proteins, cells, and other informa-

tional elements within living organisms (in vivo informa-

tional imaging).

Finally, there are the computational tools required to

collect, store, analyze, model, and ultimately distribute

the various types of biological information. The creation

presents a challenge comparable to that of developing

new instrumentation and new chemistries. Once again

this means recruiting computer scientists and applied

mathematicians to biology. The biggest challenge in this

regard is the language barriers that separate different

scientific disciplines. Teaching biology as an informational

science has been a very effective means for breeching these

barriers.

The challenge is, of course, to decipher various

types of biological information and then be able to

use this information to manipulate genes, proteins,

cells, and informational pathways in living organisms to

eliminate or prevent disease, produce higher-yield crops,

or increase the productivity of animals for meat and other

foods.

Biotechnology and its application raise a host of

social, ethical, and legal questions, for example, genetic

privacy, germline genetic engineering, cloning of animals,

genes that influence behavior, cost of therapeutic drugs

generated by biotechnology, animal rights, and the nature

and control of intellectual property.

Clearly, the challenge is to educate society so that

each citizen can thoughtfully and rationally deal with

these issues, for ultimately society dictates the resources

and regulations that circumscribe the development and

practice of biotechnology. Ultimately, I feel enormous

responsibility rests with scientists to inform and educate

society about the challenges as well as the opportunities

arising from biotechnology. These are critical issues

for biotechnology that are developed in detail in the

Encyclopedia of Ethical, Legal, and Policy Issues in

Biotechnology.

The view that biotechnology is an informational

science pervades virtually every aspect of this science,

including discovery, reduction of practice, and societal

concerns. These Encyclopedias of Biotechnology reinforce

the emerging informational paradigm change that is

powerfully positioning science as we move into the twenty-

first century to more effectively decipher and manipulate

for humankind's benefit the biological information of

relevant living organisms.

Leroy Hood

University of Washington

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