Simulation of polyribosome disaggregation

BIOCHIMICA ET BIOPHYSICA ACTA

I55

BBA 96621

SIMULATION OF POLYRIBOSOME DISAGGREGATION G. M. V A S S A R T , J. E. D U M O N T AND F. R. L. C A N T R A I N E

Laboratory o/ Nuclear Medicine, School o/ Medicine, Free University o[ Brussels, and Biology Department, Euratom, Brussels, Belgium (Received April 3rd, 197 o)

SUMMARY

Deterministic and stochastic models for polyribosome breakdown into monosomes are developed simulating two situations. (i) Polyribosome degradation by ribonuclease (ii) Polyribosome degradation by mechanical forces. Another model is developed simulating the modification of polyribosome distribution in acellular protein synthesis systems in the absence of significant initiation. The hypothetical mechanisms of these three phenomena are discussed in light of the comparison between the results of the simulations and experimental data available in the literature.

INTRODUCTION

The central role of polyribosomes in cellular protein synthesis has been well established 1-4. In this process, individual ribosomes move sequentially along mRNA while synthesizing proteins corresponding to the information coded in this mRNA; both the attachment of ribosomes or ribosomal subunits at the beginning of mRNA (initiation) and release of ribosomes at the 3' end of mRNA after completion of protein synthesis (termination) are active processes. Much information about the function of polyribosomes can therefore be obtained from polyribosome profiles, i.e. polysome distribution expressed as ultraviolet absorbance vs. sedimentation rate in ultracentrifugation. Such profiles are the most common means used to follow polysome distribution in tissues under various experimental conditions. It is therefore of great interest to define how various processes may affect polysome distribution in tissues. In this work, we have simulated the effect of three types of disaggregations (i) random hydrolysis of the bonds between the ribosomes, (ii) preferential degradation of heavy polysomes, (iii) sequential release of ribosomes at the end of the polysomes in the absence of initiation. These models have been proposed to account for polysome disaggregation, respectively: (i) in ribonuclease hydrolysis, (ii) in mechanical degradation, and (iii) during amino acid incorporation in acellular systems~-,5,6. Two different types of models have been used: a deterministic model using probability calculus and a stochastic model using the Monte Carlo method. A b b r e v i a t i o n : / - s o m e = p o l y r i b o s o m e c o n t a i n i n g i ribosomes.

Biochim. Biophys. Acta. 224 (197 o) 155-164

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156 METHODS

Model I. Random interribosome bond rupture (degradation by ribonuclease) Given a polysome population, we intend to simulate a situation in which each bond between contiguous ribosomes of any polysomes would be just as likely to be ruptured b y ribonuclease and to generate the new polysome distribution, after a given number of ruptures. The assumptions used in this model are: I. All bonds between ribosomes are equally susceptible to ribonuclease disruption. This assumption could be explained for instance by the three following subassumptions. (a) The sensitivity to ribonuclease of all interribonucleotide bonds between ribosomes is similar. ( b ) T h e distance between two contiguous ribosomes is the same in a n y polysome. (c) The bonds tying ribosomes into polysomes are all susceptible to ribonuclease disruption. 2. There are no recombinations between polysomes or ribosomes. 3. The ribonuclease concentration is chosen so that ribosomes are not degraded. These assumptions are consistent with available data in the literature. However it must be recognized that the distance between ribosomes on polysomes does not appear equal in electron micrographs but is statistically distributed£ The model does not apply to ribonuclease-resistant polysome preparations as for instance in polysomes synthesizing v-globulins and collagen in which ribosomes appear to be partially bound together b y proteins s,9. This model does not take into account the nonspecifie aggregation of some monomers into dimers observed in liver homogenates 1°. However, in this case, apart from the fact that the dimer peak will follow the monomer peak, the pattern of polysome disaggregation is similar to the simulated pattern.

A. Deterministic model Let Ci,i be the number of i-somes in a polysome population at time/" × / I t ; we can represent the polysome distribution at time o by a column vector: {Cz,o, C2,o . . . .

Ci,o . . . .

Cn,o}

We c a l l , the probability for one bond to be ruptured during one time interval ~It, and Pk,i the probability for a / - s o m e to give rise to a k-some during /It. If we represent the polysome distribution at time I x / I t by another column vector, {c~,r, c2,z. . . . ci,~. . . . Cn,r} it is evident that one contribution to C2,,, for instance, (the number of 2-somes present at time o + / I t ) is given b y multiplying C3,o (the number of 3-somes at time o) with P2,3 (the probability for a 3-some to give rise to a 2-some during /It). Another contribution to C~,~ will be given b y C,,oXP2,,... and so on for each Ci,o. One particular contribution to C2,, is given by C~,o× P .... where P~,~ is the probability for a 2-some not to be degraded during At. Thus: C2,r = C2,0 " P 2 , 2 ~ - C 3 , 0 • P 2 , 3 + C 4 , o "

P2,4 ...

a generalization of this equation gives: Cz,r = k Ci,o × P z , i i=z

Biochim.

Biophys.

Acta,

224 (197 o) I55-I64

2vCn,o " P 2 , n

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SIMULATION OF POLYRIBOSOME DISAGGREGATION

n C2,r ~ ~, Ci,o )< P2,i i=2

Ch,, = ~ Ci,o )< Ph,i i=h Cn,x = Cn,o × Pn,n

or, in m a t r i x form

]

Cz,z]

FPI,r

PI,2

c~,~l

I °

P2,~

L n,z-I

o

d.

1

o

P~',3 ' ' ' Pl:.nP 2 , 3 . . . P2,n P 3 , 3 " . " P3,n

o

. .

Ci,o C2,o C3,o

I

L ~,o

•

o~

2

3

4

Fig. I. 1Ribonuclease action, deterministic model: example of a 4-some r u p t u r e . PI,4 = probability for 1-2 b o n d r u p t u r e plus p r o b a b i l t y for 3-4 bond r u p t u r e : 2~. P4,4 ~ probability 1-2 n o t to be r u p t u r e d and probability 2 - 3 n o t to be r u p t u r e d and . . . . (i--3c~).

The Pk,i values m u s t now be c o m p u t e d as shown in Fig. I : if i > k, we h a v e Pk,~ = 2~ (two different r u p t u r e s in a / - s o m e are able to give rise to a k-some) if i = k, we h a v e P~,i = ( I - - ( i - - I ) ~ ) (i.e. t h e p r o b a b i l i t y for ( i - - I ) b o n d s n o t to be r u p t u r e d ) if i < k, we h a v e Pk,i = 0 (i.e. t h e r e is no r e c o m b i n a t i o n ) . W e assume t h a t c~ is so s m a l l t h a t t h e p r o b a b i l i t y for several c o n c o m i t a n t b o n d d i s r u p t i o n s could be d i s r e g a r d e d . If this was not so, Ph,~ would e q u a l the p r o b a b i l i t y for two p a r t i c u l a r b o n d s to be r u p t u r e d m u l t i p l i e d b y the p r o b a b i l i t y for t h e others to r e m a i n i n t a c t ; s a y 2 ~ ( I - - ~ ) i-~. W e h a v e chosen ~ --~ 10 -3 so t h a t the higher powers of ~ m a y be neglected. The Pk,i m a t r i x becomes i

I20~ --0¢

20¢ 20¢

(1-2~)

2~X . . , 2(X . . .

20¢ 2¢X

o

o

(I - 3 ~ ) • - •

2~

o

o

o...

o

[I- (~-i'I)~l

Given the {Ci,o} we are now able to c o m p u t e the {Ci,t}, i.e. the p o l y s o m e distrib u t i o n a f t e r a ( t × A t ) t i m e of ribonuclease action b y m a k i n g t t i m e s the m a t r i x p r o d u c t . A p r o g r a m was w r i t t e n in F o r t r a n I V to test this m o d e l i t e r a t i v e l y on a I B M 704 ° c o m p u t e r . Biochim. Biophys. Acta, 224 (197 o) 155-164

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The results c o m p a r e d with the e x p e r i m e n t a l d a t a of NOLL et al. 2 are shown in Fig. 2.

70C

50C

30C 100 123456

2 3 4 5 6 7891011121314

4 5 67891011121314

Fig. 2. Random interribosome bond rupture. Results of simulation, using as imput data a polysome distribution given by ~N~OLLet al. 2, are compared with the polysome profiles these authors obtained after given times of ribonuclease action. The dotted line indicates an arbitrary distribution of the large polysomes which were not resoluted by ultracentrifugation techniques. The number of ruptures were calculated from the number of new polysomes created (given by NOLL el al.2). The units in ordinate are arbitrary.

W e a s s u m e d in this m o d e l t h a t ~ r e m a i n s c o n s t a n t t h r o u g h o u t the simulation, which is of course not necessarily the case. However, a v a r i a t i o n of ~ would o n l y affect the kinetics of the phenomenon. I n this model, therefore, there is no necessary p r o p o r t i o n a l i t y between the evolution t i m e in the s i m u l a t i o n a n d in experiments. Only the p a t t e r n of p o l y s o m e d i s t r i b u t i o n given b y the s i m u l a t i o n a n d t h a t given e x p e r i m e n t a l l y should be c o m p a r e d , B . Stochastic model

Let C8,o have the same significance as in t h e d e t e r m i n i s t i c model; we comp u t e Ys, i.e. the n u m b e r of b o n d s between contiguous ribosomes present in t h e class of the 8-somes at the beginning of an e x p e r i m e n t . If we assume (Fig. 3) t h a t t h e ribonuclease b r e a k s the b o n d between the t h i r d a n d the fourth ribosome of a 8-some, two new polysomes, a 3-some a n d a 5-some are c r e a t e d a n d the 8-some is d i s r u p t e d . If we define Y3 a n d Ys in the same w a y as Ys, we can s i m u l a t e this r u p t u r e b y s u b s t r a c t i n g 7 (the n u m b e r of b o n d s in a 8-some) from Y8 a n d b y a d d i n g 2 to Y3, a n d 4 to Y5 (respectively t h e n u m b e r of b o n d s of a 3- a n d a 5-some). Biochim. Biophys. Acta, 224 (197o) 155-164

SIMULATION OF POLYRIBOSOME DISAGGREGATION

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Generalizing this method, we compute {Y,, Y2, Y3 . . . . Y~} from {C.... C.... C3,o, . . . C~,o}" Yi ~ ( i - - I ) • Ci,o. Using a uniform random generation subroutine n in a Fortran program running on a IBM 7o4 ° computer, one bond (e.g. p-th bond) in one class of polysomes (e.g. /-some) is picked up at random, and its rupture simulated by substracting ( i - - i ) bonds from Yi and by adding ( p - - I ) bonds to Y~, and ( i - - I ) - - p bonds to Yi_~ (Fig. 3). =3 1

2

3

i=g

/,

5

6

7

8

CI

(3

(3

0

('3

81 628304050,6070 ' 24 1 2X3 4 5 ST-ST8 8q-82838 8 Fig. 3. Ribonuclease action, stochastic model: example of a 8-some rupture giving a 3-some plus a 5-some. Rupture stimulation by substracting i--I = 7 from Ys, adding p - - i = z to Y3. / - - i - - p = 4toYs. After an arbitrary number of ruptures (each one represented by one iteration of the computer program), we compute the new {C,,t, C2,t, C3,t . . . Cn,t}. The results compared with the experimental data and with the results of the deterministic model are shown in Fig. 2. The probability for one bond being ruptured is not considered in this model; rather one bond is broken at random during each iteration of the program. In this model also, the relation between number of ruptures and duration of the process is not necessarily linear. To understand the slight discordance between the results of the deterministic model and those of the stochastic one, one should keep in mind that one run of the stochastic program on the computer realizes only one experiment of degradation. A second run with the same input data would give slightly different results. The results of several runs are statistically the same.

Model II. PreJerential bond ruptures in large polysomes (mechanical degradation) We intend to simulate a situation in which a polysome population is exposed to mechanical forces (e.g. during homogenization of a preparation), and to follow its distribution during such a situation. The model is based on the hypothesis that the probability of rupture of a bond is related to the length of the polysome 5,~. This hypothesis could be explained b y two subassumptions: (a) Each bond between contiguous ribosomes of any polysome is equally resistant to disruption in resting conditions. (b) In polysomes exposed to the shear and tear of homogenization, forces acting on a polysome (flow of the medium, adherence to glassware etc.) will be proportional to the length of polysomes to which the forces are applied. Opposing forces will therefore more likely rupture polysomes of large size. To our knowledge, the experimental validity of this hypothesis has not been tested. Our model for this situation is derived from the deterministic model of ribonuclease action. It also assumes that ribosomes or polysomes do not reaggregate Biochim. Biophys. Acta, 224 (197o) 155-164

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a n d t h a t ribosomes are not degraded. The method is similar, b u t we have to define a new Pk,i m a t r i x for this model• For instance, if we call fl the p r o b a b i l i t y for the b o n d of a 2-sonle to be broken d u r i n g At, this p r o b a b i l i t y will be a 3 X fl in a 3-some where a 3 is a coefficient defining the fragility of a 3-some b o n d relatively to the fragility of a 2-some bond, if the polysomes are exposed to mechanical degradation. The p r o b a b i l i t y for a b o n d of a n-some to be r u p t u r e d d u r i n g At will be a n Xti. The Pk,~ m a t r i x of our model is now o b t a i n e d b y replacing ~ b y a i x/~ in the i.th column of the Pk,i m a t r i x of the preceding model.

o

--a

i

2 • fl

0__.,.,a

DATA OF NOLL

2

..

a 3 •

2an'

2a3.~ "'" ~~,./~ 1

0

et el.

time 0

1 2 3 4 5 6 7 8 91011121314

1 rain 1,0 ng/ml ribonuclease = 330 ruptures

...

I --(~--I)

.., • ,a

MECHANfCA L DEGRADATION no rupture

1 23456

7891011121314

330 ruptures

!00

1 2345

6

1 2345

8rain 1.0 ng/ml rlbonucleose = 950 ruptures

900

~ i i J i I J-J 6 7 8 91011121314

950 ruptures

700 50C 30(: 10C 2

456

l q i ~ i i i i t J 3 4 5 6 7 8 91011121314

Fig. 4• Preferential bond rupture in large polysomes. Results of a simulation were compared in the same way as in Fig. 2 with the evolution of a polysome distribution during a ribonuclease treatment (NOLLet al.~). Biochim. Biophys. Acta, 224 (197o) I55-I64

SIMULATION OF POLYRIBOSOME DISAGGREGATION

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To test this model we need a function expressing the fragility of bonds to the polysome dimensions, i.e. a s = ](i). We have assumed that a s ---- i - - i (i ---- 2, i = n), i.e. that the fragility of one bond is proportional to the number of bonds in the polysome. Results of this simulation have been compared with data of NOLL et al. 2 on ribonuclease-induced polysome degradation (Fig. 4). Model I I I . Sequential release o/ ribosomes (Protein synthesis in acellular systems) In experiments of protein synthesis performed in the absence of initiation factors in acellular systems, authors have observed a shift of polysome distribution towards the light polysomes, associated with an asymptotic curve of protein synthesis. WETTSTEIN et al. 2 have suggested that this evolution of tile polysome profiles was a consequence of inhibited initiation of the translation phenomenon, the rest of the translation continuing until all polysomial m R N A is read out. To simulate this phenomenon, a model has been developed which involves the following assumptions: (i) There is no new sequential attachment of ribosomes

DATA OF NOLL et al.

STOCHASTIC MODEL

time 0

1 23456789101112

llllIlIil

1 23 45 6789101112

5 min

5 3 0 ruptures

5°°t

300[ I001 23456

234

56789101112

90C 10 min

8 6 0 ruptures

700"

500"

300"

100"

2 3 456

23456789101112

Fig. 5. Sequential release of ribosomes. Results of a simulation, using as input data a p o l y s o m e distribution given b y NOEL et al. 2 were compared with the p o l y s o m e profiles these authors obtained in acellular protein synthesis experiments. These profiles were compared in the same w a y as in Fig. 2. Biochim. Biophys. Acta, 224 (197 o) 1 5 5 - 1 6 4

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on the mRNA. (2) The distance between contiguous ribosomes on the polysomes remains constant as the translation goes on; i.e. the ribosomes progress statistically at the same speed on the mRNA. This assumption is consistent with data obtained by electron microscopy of reticulocyte polysomes TM. (3) There is no distinguishable difference in ultracentrifugation sedimentation rate and ultraviolet absorbance between free ribosomes and monosomes (one ribosome plus one mRNA). As in the ribonuclease model it is also assumed that ribosomes and polysomes do not aggregate and that ribosomes are not degraded. In this model the sequential release of ribosomes after completion of protein synthesis can be simulated by successive amputation of the last ribosome of each polysome. Indeed ribosomes with or without a fragment of mRNA would not be distinguished by sedimentation rate of ultraviolet absorbance. Such a model is obtained by a slight modification of the program of the stochastic model for polysome degradation by ribonuclease described above. Results of the sinmlation are compared to the experimental data of NOLL et al. 2 in Fig. 5-

RESULTS AND DISCUSSION

Three different models for polysome disaggregation have been simulated, assuming random interribosomal rupture (Model I), preferential bond rupture in large polysomes (Model II), and sequential release of ribosomes (Model III). In the three models reaggregation of ribosomes, or reattachment of ribosomes on mRNA do not occur. In Model I, simulated polyribosome centrifugation profiles show a progressive shift from large polysomes to small polysomes and monosomes; there is no preferential formation of monosomes and the width of the group of the small polysome peaks decreases steadily with time. Results obtained by simulation with the deterministic model closely agree with those obtained with the stochastic model (Fig. 2). The pattern of polysome profile evolution obtained by model I simulation is very similar to patterns recorded in the literature of effects of treatment by ribonuclease of polyribosomes in various acellular systems 13. Application of the model to the polysome profiles presented by NOLL et al. 2 shows a close agreement between the results of simulation and the experimental data (Fig. 2). The slight discrepancy mainly concerning the 5- and 6-somes after a long period of ribonuclease action probably results from the uncertainty that exists about the distribution of large polysomes at time zero in experimental data. Indeed in the simulation, this distribution was postulated arbitrarily. To reduce this error, we have tested the stochastic model, using as a starting distribution the experimental profile after 3 min of ribonaclease treatment (in which the proportion of large polysomes, i.e. nonresoluted components is smaller). In this case, the simulation results were distinctly closer to the experimental results, which confirms our interpretation of the discrepancy. Application of Model I1 (preferential bond rupture in large polysomes) to the data of NOEL et al. 2 demonstrates a pattern of polysome profile evolution, which is quite different from the experimental pattern observed in ribonuclease treatment (Fig. 4). This pattern is characterized by a marked dominance of small polysomes over monosome formation. Biochim. Biophys. Acta, 224 (197 o) I55-I64

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The compatibility between results of simulation with model I and experimental data supports the validity of the assumptions of model I in the case of ribonuclease action on polyribosomes, mainly the hypothesis of random rupture action of ribonuclease on interribonucleotide links in the polysome population. The effect of "rough" homogenization and mechanical treatment has not, to our knowledge, been systematically investigated on purified polysome preparations. The effects of such treatments on whole homogenates presumably involves both mechanical effect and ribonuclease release, and can therefore not be considered as experimental counterparts of Model II simulation. The prediction of this model, that large polysomes will soon disappear from roughly treated preparations (Fig. 4), agrees however with the common experience of the researcher in the field. Simulation of polyribosome disaggregation with Model III (sequential release of ribosome) demonstrates a pattern of polyribosome profiles characterized by a general decrease of the polysome peaks with a concomitant very marked compensatory increase of the monosome peak. At no time during the process a marked increase of the small polysome fraction can be observed (Fig. 5). This pattern of evolution is strikingly similar, qualitatively, to patterns observed in in vitro acellular systems of protein synthesis 14,1,1~,16,2. There is also a close quantitative agreement between the results of simulation by Model III of polysome disaggregation and the experimental results of NOLL et al. 2 in in vitro acellular protein synthesis systems (Fig. 5). These data support the validity of Model III assumptions for such systems. The recognition of the very different patterns of polyribosome disaggregation, after ribonuclease treatment or under conditions of sequential release of ribosomes in the absence of reattachment, might provide useful clues in the interpretation of polysome profiles from tissues submitted to various experimental conditions. Looking back, in retrospect, to the literature, one can indeed recognize patterns of polysome profiles suggestive of an absence, or a marked decrease in ribosome attachment to mRNA in a wide variety of experimental conditions: e.g. reticulocytes treated with pactamycin 17, rabbit cerebral cortex after electroshock treatment is, rat hepatoma cells treated with phenethyl alcohol 19,2°, livers of mice 21 and rats 2~,4 fed tryptophan-deficient diets, rat livers under perfusion 23, Chang liver cells cultured in glutamate-deficient medium 24, livers of rats treated with ethionine 25 and HeLa cells during metaphase 26. Of course, such a pattern could also result from other mechanisms such as changes (e.g. general decrease) in the available population of mRNA. Simulation studies to define the effects of such changes are in progress. Nevertheless, the great rapidity of the polysome disaggregation, the actinomycin resistance and sometimes rapid reversibility of this disaggregation, the concomitant decrease of amino acid incorporation into proteins by the polysomes and ribosomes, in some of these cases 1~-22,4,1s would favour the hypothesis of changes in rate of ribosome attachment to mRNA and initiation. While in some cases this hypothesis has been proposed ~,2°,~s,17 in other cases ~6,~°,23,z2, it has not been considered explicitly. From a teleological point of view, regulation of protein synthesis at the translation level by way of alterations in the initiation rate would certainly be economical for the cell. Such an hypothesis might also explain the striking correlation in many tissues between in vivo rates of protein synthesis and shift of the polysome profiles from monosomes to heavy polysomes27. ExperiBiochim. Biophys. Acta, 224 (197 o) 155-164

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mental support for the validity of this hypothesis in incubated reticulocvtes has been provided ~s.

ACKNOWLEDGMENTS

We wish to thank Monsieur R. LOCOCQfor helpful discussion and Miss I-IENNAUX for the typing of the manuscript of this work. Work realized under Contract of the "Minist~re de la Politique Scientifique", as a part of the Association Contract Euratom-University of Brussels- University of Pisa - n ° o26-63-4-BIAC (contribution n ° 580 of Euratom-Biology Department). REFERENCES I A. RICH, J. R. WARNER AND H. M. GOODMAN, Cold Spring Harbor Syrup. Quant. Biol., 28 (1963) 269. 2 H. NOLL, T. STAEHELIN AND F. O. WETTSTEIN, Nature, 198 (1963) 632. 3 A. RICH, E. F. EIKENBERRY AND L. I. MALKIN, Cold Spring Harbor Syrup. Quant. Biol., 31 (1966) 303 . 4 H. N. MUNRO, Federation Proc., 27 (1968) 1231. 5 R. A. RIFKIND, L. LUZZATTO AND P. A. MARKS, Proc. Natl. Acad. Sci. U.S., 52 (1964) 1227. 6 T. J. FRANKLIN AND A. GODFREY, Biochem. J., 98 (1968) 513 . 7 H. S. SLAYTER, J. R. WARNER, A. RICH AND C. E. HALL, J. Mol. Biol., 7 (1963) 652. 8 G. MANNER, B. S. GOULD AND I-I. S. SLAYTER, Biochim. Biophys. Aeta, lO8 (1965) 659. 9 B. GOLDBERG, H. GREEN, J. Mol. Biol., 26 (1969) I. IO T. E. WEBB AND V. R. POTTER, Cancer Res., 26 (1966) lO22. I i J. M. HAMMERSLEY AND D. C. HANDCOMB, Monte Carlo Methods, Methuen's Monograph on Applied Probability and Statistics, 1965. 12 J. R. WARNER, A. RICH AND C. E. HALL, Science, 138 (1962) 1399. 13 O. GRAU AND G. FAVELUKES, Arch. Biochem. Biophys., 125 (1968) 647. 14 ]3. S. BALIGA, A. W. PRONCZUK AND H. N. MUNRO, J. Mol. Biol., 34 (1968) 19915 B. /3. COHEN, Biochem. J., IiO (1968) 231. 16 /3. HARDESTY, R. MILLER AND R. SCHWEET, Proc. Natl. Acad. Sci. U.S., 5 ° (1963) 924. 17 /3. COLO~aBO, L. FELICETTI AND C. BAGLIONI, Biochim. Biophys. Acta, 119 (1966) lO9. 18 C. VESCO AND A. GIUDITTA, dr. Neurochem., 15 (1968) 81. 19 P. G. W. PLAGEMANN, Biochim. Biophys. Acta, 155 (1968) 202. 20 P. G. W. PLAGEMANN, dr. Biol. Chem., 243 (1968) 3029 . 21 I-I. SIDRANSKY, D. S. R. SARMA, M. /30NGIORNO AND E. VERNEY, dr. Biol. Chem., 243 (1968) 1123 . 22 W. H. W'UNNER, J. ]DELL AND ]-I. N. M~UNRO, Biochem. J., IOI (1966) 417 . 23 I . / 3 . LEVITAN AND T. E. WEBB, J. Biol. Chem., 244 (1969) 4684. 24 E. ELIASSON, G. E. BAUER AND T. HULTIN, J. Cell Biol., 33 (1967) 287. 25 A. OLER, E. FARBER AND K. H. SHULL, Biochim. Biophys. Acta, 19o (1969) 161. 26 M. D. SCHARFF AND E. ROBBINS, Science, 151 (1966) 992. 27 J. R. TATA, Recent Progr. Hormone Res., 5 (1966) 191. 28 P. M. KNOPF AND H. LAMFROM, Biochim. Biophys. Aeta, 95 (1965) 398.

Biochim. Biophys. Acta, 224 (197 o) 155-164