Eukaryotic Cell Genetics

265 Pages·1983·6.397 MB·English

by  John Morrow (Auth.)

Eukaryotic Cell
Genetics
J O HN M O R R OW
Department of Biochemistry
Texas Tech University School of Medicine
Lubbock, Texas
1983
ACADEMIC PRESS
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United Kingdom Edition published by
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Library of Congress Cataloging in Publication Data
Morrow, John, Date
Eukaryotic cell genetics.
(Cell biology)
Bibliography: p.
Includes index.
1. Cytogenetics. 2. Eukaryotic cells. I. Title.
II. Series.
QH430.M67 1982 599'.08762 82-11608
ISBN 0-12-507360-7
PRINTED IN THE UNITED STATES OF AMERICA
83 84 85 86 9 8 7 6 5 4 3 2 1
PREFACE
This book represents an effort to accomplish several tasks. Its main purpose is
to describe in a brief and topical fashion the present state of knowledge of
somatic cell genetics. This implies the predominant use of certain techniques,
mainly the use of normal and transformed mammalian cells grown in vitro and
their genetic analysis through the techniques of molecular biology, biochemistry,
cytogenetics, and cell hybridization. Although much of what this volume deals
with is precisely this, it is necessary to go beyond these approaches, especially in
terms of the broad interpretation of these findings. All of the fundamental pro-
cesses which we wish to consider are the result of genetic structures transmitted
through a sexual cycle and expressed in somatic cells in a particular fashion.
Thus descriptions of particular findings at the cellular or molecular level have
frequently been presented in relation to medical, human, and population
genetics.
I have not attempted to cover the various topics in a historical context nor to
review them completely. There are a number of excellent books which have
reviewed the older literature in cell heredity and cell culture, and the reader is
referred to them throughout for the foundation of particular areas. Similarly, I
have included a number of unresolved or controversial topics which, because this
area is moving with such rapidity, may be resolved by the time this book is
published.
I have aimed this book at an audience which includes researchers in the fields
of genetics and molecular biology, nonspecialists interested in what is happening
in a very exciting area of biology, and students at the graduate level in cell
biology. I was forced to make compromises between highly detailed explana-
tions of particular experiments and broader outlines which attempt to integrate
findings in a particular field. In a number of instances, not all of the examples of
a given phenomenon are listed, but representative cases are described.
xi
XÜ Preface
Several friends, colleagues, and students gave me valuable comments and
criticisms. These include David Patterson, Abraham Hsie, Milton Taylor, Olga
Zownir, Stanislaw Cebrat, Daniel Meier, David Hong, Phillip Keller, Susan
Jones, Donald Clive, Court Saunders, and Jean Orme. Their advice has been
extremely helpful in the development of this volume. The original figures were
most competently drawn by Harvey Olney. Finally, I wish to express my thanks
to Shirley Gaddis for her invaluable assistance in assembling references, proof-
ing, and typing the manuscript.
John Morrow
n
Somatic Cell Genetics and the
Legacy of Microbial Systems
I. INTRODUCTION
In the last 20 years our understanding of the genetics of higher organisms has
undergone tremendous growth and metamorphosis. This is not surprising be-
cause during this period all of biological science has expanded tremendously and
our level of comprehension has thereby increased. However, the genetics of
eukaryotic cells is particularly striking in this regard. This progress resulted from
the application of techniques found to be successful in bacterial genetics and
molecular biology to the cells of differentiated, multicellular organisms. Because
of the practical implications of these findings for the biomedical sciences, results
in somatic cell genetics have been greeted with great interest and enthusiasm and
research on the genetics of higher cells has been well supported by the federal
government, as well as by private foundations.
The development of somatic cell genetics has to a large extent concerned itself
with two major needs: a search for variability in cell populations, and an investi-
gation of mechanisms of mating or of exchanging genetic information between
cells. These directions are, of course, readily understandable because isolated
somatic cells do not represent real organisms in a biological sense but rather
derive in an artificial manner from whole individuals that are broken into disag-
gregated collections of cells which are treated as microbial populations. Now
that the problem of satisfying those two basic necessities for genetic analysis is
largely resolved, the study of heredity in somatic cells concerns itself with the
architecture of genetic elements in eukaryotes, including their interaction
through regulative function. In the process of developing our understanding of
these questions, fundamental processes common to higher organisms, including
1
2 Somatic Cell Genetics and the Legacy of Microbial Systems
aging, immunology, differentiation, and neoplasia are gradually becoming
understood.
Because the technical methodology of cell genetics resembles that which has
been so widely utilized in microbial genetics, it is not surprising that the rationale
and approaches would also be derived from similar sources. The idea of applying
the techniques and experimental approaches of bacterial genetics to eukaryotic
somatic cells represented a great asset in that it lent itself effectively to quantita-
tive studies that formed the basis for a later thorough understanding of mam-
malian genetics and molecular biology. At this time, a detailed historical analysis
is probably not warranted. However, one basic approach deserves consideration
because of its widespread use in cell heredity and because it represents a funda-
mental link between microbial and eukaryotic cell genetics.
II. MUTATION VERSUS ADAPTATION IN
BACTERIAL POPULATIONS
Since the nineteenth century, it has been known that bacterial populations are
not completely homogeneous. Later, variation within a population was shown in
terms of nutritional requirements, drug and virus resistances, cell wall charac-
teristics, and pigment production. The basis of this variation, although genetic,
was not well understood because no experimental means existed whereby the
hypothesis of selection could be distinguished from that of adaptation. Thus,
when a population of bacteria was plated in the presence of bacterial virus, rare
resistant clones arose; whether these clones were preexisting in the population or
induced by the presence of the virus was a question with important philosophical
and experimental implications. If variants were occurring all the time through
spontaneous mutations and were selected out through intervention of the selec-
tion agent, then this would indicate that bacteria possessed genetic systems
comparable to those in higher organisms which were known to be subject to the
rules of classical Darwinian evolution and natural selection. If, on the other
hand, the variants were induced by the presence of the virus, this would suggest
that such populations might be quite different genetically from higher organisms
because this would argue for the existence of a directed mutational process.
Distinguishing between these two possibilities proved to be extremely diffi-
cult, because it is not at all obvious in what way one could test for the existence
of variants without exposing them to the agent in question. The problem was
solved in a most elegant manner through an indirect mathematical approach. The
4 'fluctuation test' ' of Luria and Delbrück ( 1943) consists of two components: first,
a control series in which a larger number of cells are plated on a large number of
plates in an identical fashion in the presence of the selecting agent in order to
calculate a mutation frequency. The distribution of numbers of variants from
culture to culture should be random and should follow the Poisson distribution.
Mutation versus Adaptation in Bacterial Populations 3
Second and parallel to this, there is an experimental series in which secondary
cultures that were initially grown from small samples of cells of the primary
population are harvested independently and plated in the selecting agent. In the
experimental series, the Poisson distribution would also be observed if the mu-
tants originated at the time of the addition of the selecting agent, because the only
source of variability in their numbers would be the statistical fluctuation. On the
other hand, if the variants were preexisting in the primary population, then each
independent experimental culture would reflect a slightly different history: in
some, mutants would have arisen early in the growth period; in some, later; and
so forth. Thus, the variance of the distribution of mutants in the secondary
populations would be much greater than in the control and would not follow the
Poisson equation (Fig. 1.1). It follows from this that a difference in the variation
BOTTLE OF CONFLUENT TISSUE CULTURE CELLS
20 REPLICATE
20 FLASKS INOCULATED CULTURES TESTED
IN DRUG-CONTAINING
WITH 200 CELLS / FLASK
MEDIUM
Fig. 1.1. Protocol of the fluctuation test as adapted to cultured cells. A bottle of confluent
6
cells is harvested, and large numbers (approximately 10 cells) are plated in individual flasks as
shown in the right-hand column. This constitutes the control series. At the same time a series of
flasks are initiated from small starting numbers of cells from the primary bottle and are grown in
normal medium. These are experimental cultures that are then harvested and plated in the
selecting agent. Because each experimental culture has a slightly different history, the frequen-
cy of mutations will vary much more widely from flask to flask in the experimental series than in
the control series.
4 Somatic Cell Genetics and the Legacy of Microbial Systems
("fluctuation") between the control series and the experimental series would
indicate that the variants were preexisting in the primary population and that the
toxic agent merely eliminated the wild-type members from the culture.
The fluctuation test has been widely utilized with a number of systems, includ-
ing bacteria, mammalian cells, yeast, and other microorganisms. In almost every
case the hypothesis of selection rather than adaptation has been proved. This
point is so well established that it is taken for granted and would not merit such
extensive consideration in this volume were it not for the fact that the fluctuation
test also allows one to measure the mutation rate for the particular variant under
selection.
Because the experimental series is started from extremely small numbers of
cells, all preexisting mutants have been eliminated through dilution. Because the
number of cells plated and the number of mutants obtained are measurable
quantities, a rate can be obtained through application of appropriate equations.
The average number of mutants yielded per culture is calculated through methods
derived by Luria and Delbrück (1943) and later expanded upon by Lea and
Coulson (1949) and Capizzi and Jameson (1973). A discussion of these methods
and some examples of their application are given in Lea and Coulson, (1949).
The three methods used for calculating the average number of mutants per
sample and the mutation rates are ( 1 ) P , (2) median, and (3) maximum likelihood.
0
Use of these methods depends upon the distribution of numbers and the degree of
accuracy required by the investigator. Usually close agreement is obtained
among the different methods (Table 1.1).
In any population of microorganisms, mutations are occurring and might be
expected to eventually take over the entire population. The fact that this does not
occur (unless, of course, selective pressures change) demonstrates that new
mutants are at a selective disadvantage and are eliminated from the sample. By
this mechanism, an equilibrium level will be established in which the rate of
addition of new mutants to the population through mutation will be exactly
counterbalanced by their elimination through negative selection. The reason for
this selective disadvantage is not immediately obvious, but no doubt arises from
the fact that most mutations represent a disruption in the normal, finely tuned
system and thus would not be expected to compete effectively with the wild type.
Under these conditions, the mutation frequency and the mutation rate will not be
the same.
Equations have been derived (Morrow, 1964) that give the relationship of the
mutation frequency to the mutation rate. Let μ = forward mutation rate, m =
number of mutants, η = number of wild-type cells, s = generation time of
mutant/generation time of wild type, F = fraction of mutants at generation zero,
0
and F = fraction of mutants at generation t. At any generation, F will be the
t t
result of two factors: the contribution due to the initial frequency F times s to the
0
power t, and the contribution due to mutation, summed for t generations and
Mutation versus Adaptation in Bacterial Populations 5
3
TABLE 1.1 Example of Mutation Rates Obtained Using the Fluctuation Test for the Mutational Step
from Asparagine Requirement to Independence**
Number of cultures
Polyploid experiment Control experiments
Pooled Pooled
data 1 2 3 data
Number of clones
0 11 11 22 4 3 0 7
1 7 4 11 2 3 4 9
2 2 2 2 0 3 5
3 1 1 2 2 1 5
4 1 0 1 2
5 1 1 0 0 2 2
6 2 1 0 3
7 1 0 1 2
8 1 1 0 3 1 4
10 2 1 3
11 1 1 2
13 1 1
16
17 1 1 1 1 2
19 1 1
104 1 1
Number of starting 103 103 103 103 103 103 103
cells/culture
Cells plated in Asn medium 0.96 1.2 1.08 1.7 1.5 2.0 1.7
6
x 10
Mean number of revertant 1.3 1.4 1.4 2.5 2.6 2.0 2.45
clones/flask
Poc 0.550 0.579 0.564 0.222 0.18Î ) 0.000 0.143
Mutation rate
Method 2d 1.4 1.2 1.3 1.5 1.7 1.0 1.4
Method 1 e 0.6 0.47 0.53 0.90 1.1 — 1.1
95% confidence limits on 0.15-0.96 0.71-
pooled data, Method 1
a
From Prickett et al. (1975).
b
Numbers of clones obtained by plating cells in asparagine-free medium and after counting numbers
of macroscopically visible colonies for 2 weeks.
c
P = Number of flasks with 0 clones/total number of flasks.
0
d
Median method.
e
P method.
Q
6 Somatic Cell Genetics and the Legacy of Microbial Systems
adjusted for the growth rate differential. Because the frequency of mutants is
always small, the effect of reverse mutation may be ignored. Therefore
F = μ(1 + s + s2 + s3 + s4 4- . . . + s'-1) + s'F (1.1)
t 0
which may be expressed as
F = μ{[1 + s/(s-\)](sf-1 - 1)} + s'F (1.2)
t 0
At equilibrium the second term will vanish and the equation will reach its
limiting form
ml η = μ/d-s) (1.3)
We have published the results of fluctuation test studies using V79 hamster
cells in which both the frequency and mutation rates were calculated (Morrow et
al., 1978). From these data an s value of 0.94 for the mutant with respect to the
wild type can be calculated indicating the mutant cells are at a slight selective
disadvantage when grown together with wild type. This estimate agrees well
with that obtained a few years ago (Morrow, 1972) on the basis of artificial
mixtures of drug-resistant and drug-sensitive permanent mouse cells. Thus, it
appears that we can account for the population dynamics of mammalian cells on
the basis of a simple mutational model: such cells represent a population in which
new variants are constantly arising through mutation and being eliminated
through natural selection. It does not appear necessary to develop more complex
mathematical models of mutation and selection in cultured mammalian cells to
explain these observations.
III. THE BASIS OF VARIATION IN SOMATIC CELLS
Although their molecular basis is not completely understood, mutation rates
obtained by the fluctuation test have been a frequent topic of investigation, and
this problem is one of both basic and practical interest. As shown in Table 1.2,
the fluctuation test has been widely applied to a variety of cellular systems. The
precise nature of these variants will be considered in detail in subsequent chap-
ters, but there are several generalizations that merit emphasis. In the first place,
there does not appear to be a difference in mutation rates between dominant and
recessive mutations (Table 1.3). Because the cells in question are presumably at
least diploid, this is a difficult observation to understand. This concept is illus-
trated in Fig. 1.2 for a typical diploid locus. In order for a dominant mutation to
be expressed, only one mutational event is required, occurring with a rate x.
However, a recessive mutation requires two simultaneous events with a com-
bined probability of y2. Because χ and y are in the same range (x — y), χ should