Kinetic Modeling and Mathematical Analysis Indicate ThatAcute Phase Gene Expression in Hep 3B Cells Is Regulated byBoth Transcriptional and Posttranscriptional MechanismsShun-Lin Jiang,* David Samols,* Debra Rzewnicki,§ Stephen S. Macintyre,§ Isaac Greber,* Jean Sipe,1'and Irving Kushner§*Departnent of Biochemistry and *Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland,Ohio 44106; 'Department of Medicine, MetroHealth Medical Center, Cleveland, Ohio 44109; and IlDepartment of Biochemistry,Boston University School of Medicine, Boston, Massachusetts 02118

Abstract

To evaluate the possible role of posttranscriptional mecha-nisms in the acute phase response, we determined the kinet-ics of transcription (by nuclear run-on assay) and mRNAaccumulation of five human acute phase genes in Hep 3Bcells incubated with conditioned medium from LPS-stimu-lated monocytes. Increase in mRNAaccumulation was com-parable to increase in transcription rate for fibrinogen-aand a-i protease inhibitor, suggesting largely transcrip-tional regulation. In contrast, mRNAaccumulation wasabout 10-20-fold greater than transcriptional increase forserum amyloid A, C3, and factor B, suggesting participationof posttranscriptional mechanisms. Since finding a disparitybetween the magnitudes of increase in mRNAand transcrip-tion does not definitively establish involvement of posttran-scriptional mechanisms, we subjected our data to modelingstudies and dynamic mathematical analysis to evaluate thispossibility more rigorously. In modeling studies, accumula-tion curves resembling those observed for these threemRNAscould be generated from the nuclear run-on resultsonly if posttranscriptional regulation was assumed. Dy-namic mathematical analysis of relative transcription ratesand relative mRNAabundance also strongly supported par-ticipation of posttranscriptional mechanisms. These obser-vations suggest that posttranscriptional regulation plays asubstantial role in induction of some, but not all acute phaseproteins. (J. Clin. Invest. 1995. 95:1253-1261.) Key words:cytokine * serum amyloid A * complement factor B * in-terleukin-6 * mRNAstability

Introduction

The acute phase response is characterized by a complex set ofchanges in the concentrations of many plasma proteins, re-flecting reorchestration of the pattern of plasma protein geneexpression by hepatocytes. A number of inflammation-associ-ated cytokines and hormones have been found to be capable ofparticipating in induction of these changes (1-5). Althoughtranscriptional regulation has been shown to play a major role

Address correspondence to Irving Kushner, MD, Metro Health MedicalCenter, 2500 MetroHealth Drive, Cleveland, OH44109 1998.

Receivedfor publication 3 June 1994 and in revisedform 6 Septem-ber 1994.

in induction of all positive acute phase genes studied thus far,both in vivo and in vitro studies have demonstrated that changesin specific mRNAabundance are not always accompanied bycomparable increases in the magnitude of transcription (6-13),suggesting a role for posttranscriptional mechanisms.

The finding of an increase in mRNAlevels without a changein transcription is generally accepted as evidence of posttran-scriptional control, but the interpretation is more difficult whensome increase in transcription is induced but a substantiallygreater increase in mRNAlevels is found. Although this findingis frequently taken to indicate participation of posttranscrip-tional mechanisms, such conclusions may not always be justi-fied for several reasons. First, when initially low and hencesomewhat uncertain transcription rates and mRNAlevels areused to calculate the magnitude of increase, substantial errorscan result. Second, estimation of transcription rates by nuclearrun-on analysis does not yield precise results; a severalfoldrange of error is not unexpected, rendering interpretation ofdifferences between increases in mRNAand transcription diffi-cult. Third, measurement of increase in transcription and mRNAlevels at the same time point may not provide an accurate pictureof relative changes in these two parameters, since about fivehalf-lives elapse after the change in transcription rate before anew steady state is reached ( 14). Only in the case of an mRNAthat is rapidly degraded would both transcription rates andmRNAlevels be expected to reach their peaks at about thesame time. Finally, true steady-state equilibria may not occurduring an experiment, since transcription rates, mRNAdegrada-tion, and mRNAlevels may all be changing continuously overthe course of the study.

To evaluate critically the role of cytokine-induced posttran-scriptional mechanisms in regulation of human acute phasechanges, we determined the effect of continuous exposure toconditioned medium (CM)' from LPS-stimulated humanmonocytes on the kinetics of transcription and mRNAaccumu-lation of serum amyloid A (SAA), complement factors B (f B)and C3, fibrinogen-a (a-fib), and a-I protease inhibitor (a-PI)in Hep 3B cells. To ensure that maximal changes in transcriptionand mRNAabundance were determined, we performed studiesover a period long enough to include peak levels of both tran-scription and mRNA. To minimize the possible confoundingeffect of errors resulting from low baseline values of transcrip-tion and mRNA,we subjected our data to rigorous mathematicalanalysis in which neither initial transcription rates nor initialmRNAlevels were used in the calculations. Both this approach

1. Abbreviations used in this paper: a-fib, fibrinogen-a; a-PI, a- 1 prote-ase inhibitor; CM, conditioned medium; fB, complement factor B; SAA,serum amyloid A.

Posttranscriptional Regulation of Acute Phase Genes 1253

J. Clin. Invest.X The American Society for Clinical Investigation, Inc.0021-9738/95/03/1253/09 $2.00Volume 95, March 1995, 1253-1261

and kinetic modeling, which also applied quantitative ap-proaches (15) to analysis of our data, were found to supportsubstantial involvement of posttranscriptional mechanisms ininduction of SAA, fB, and C3.

Methods

CMwas prepared from LPS-stimulated human monocytes as previouslydescribed (16). Hep 3B cells in RPMI 1640 medium were incubatedwith 20% CMby our standard methods with a change of medium,including fresh CM, after each 24-h period. Specific mRNAlevels weredetermined by Northern blot analysis, and relative transcription rateswere determined by nuclear run-on assays from monolayers derivedfrom the same cells.

For the nuclear run-on assays (17, 18), nuclei from cells in four100-mm dishes were prepared by lysing washed cells in 10 mMTris,pH 7.4, 10 mMNaCl, 3 mMMgCl2, 0.5% NP-40 and centrifuging. Theresulting nuclei were suspended in 50 mMTris, pH 8.3, 40% glycerol,5 mMMnCl2, 0.1 mMEDTA and then frozen in aliquots at -70°C.For in vitro transcription assays, 2 x 107 to 4 x 107 nuclei in 90 yIwere diluted to a final volume of 200 ,ul in buffer so that the finalconcentrations were 50 mMHEPES, 112 Ag/ml creatinine kinase, 2.25mg/ml creatinine phosphate, 4 mMDTT, 0.5 mMCTP, 0.5 mMGTP,1 mMATP, and 200 tsCi of [32P] UTP. Extension of RNAchains thathad been initiated at the time of nuclear isolation was continued (runon) by incubating the reaction mixture at 26°C for 45 min before diges-tion with RNase-free DNase I, proteinase K and RNApurification byphenol extraction. For hybridization, 1-5 ,ig of denatured plasmid DNAwas loaded into each well of a nitrocellulose filter-containing dot blotmanifold, baked at 80°C for 2 h, and hybridized with 107 cpm run-onRNA. Hybridization was performed in 10 mMTES, pH 7.4, 10 mMEDTA, 0.2% SDS, 0.3 MNaCl at 65°C for 40 h. Filters were washedwith 2x SSC at 65°C for 2 h and with 20 jtg/ml RNase A at 37°C for30 min. Autoradiographic signals after the hybridization were quanti-tated by densitometry with a Phosphorlmager (Molecular Dynamics,Sunnyvale, CA) and expressed as ratios to the constitutively expressedgene glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (19).

As probes, we used cDNAs for SAA, pAl0, courtesy of J. Sipe,Boston, MA(20-22); a-fib, courtesy of G. Crabtree, Stanford Univer-sity, Palo Alto, CA (23); a-PI, p8alpp9, courtesy of D. Perlmutter,Washington University, St. Louis, MO(24); GAPDH,pHlcGAp3, cour-tesy of R. Wu, Cornell University, New York (25); C3, C3ALI, cour-tesy of D. Perlmutter (26); fB, a 1-kb subclone from clone pGEM.Bf,courtesy of D. Perlmutter and H. Colten, Washington University, St.Louis, MO(27).

In initial experiments, we noted a significant signal in baseline nu-clear run-on assays of fB, when fB mRNAwas undetectable, that didnot increase 6 h after exposure to cytokines. These findings raised thepossibility that the apparent signal found on nuclear run-on assay mightbe an artifact due to transcription originating outside the gene. To inves-tigate further the nature of the baseline signal in the fB nuclear run-onassay, we used a plasmid representing a nonrepetitive genomic fragmentderived from the 5' flanking region of the fB gene. Wealso controlledfor possible symmetric transcription during the run-on assay by usinga single-stranded DNA probe generated by subcloning our existingcDNA into an Ml 3 vector in an orientation such that the RNAcomple-mentary strand was produced. An experiment using unstimulated Hep3B cells revealed no detectable transcription with either the promoterprobes or the single-stranded probe. This finding indicated that the ele-vated fB nuclear run-on signal observed with our double-stranded cDNAprobe was an artifact due to symmetric transcription extending into thefB gene. We concluded that the single-stranded probe provided thetruest measure of fB transcription in our assay system. Accordingly,for later experiments the fB subclone was inserted into M13MP18, anda single-stranded DNAwas prepared with a sequence complementaryto fB mRNA. Using this subclone as the fB probe, an appropriatelylow baseline transcription rate was found that rose sharply during incu-

0 6 12 24 48 72 96 120

SAA *

fB ssDNAfBssCDNA *f B5'Ilank "

C3 *

Pi

ACT

FIB *

AI.B * * * *

AFP s

GAPDH * * *

pUCiB

0

*0

0

Figure 1. Nuclear run-on assay of acute phase protein genes in Hep 3Bcells exposed to CM. 1-5 Ag of plasmid DNAfor each gene indicatedwas loaded onto a nitrocellulose filter through a dot blot apparatus.cDNAs for each gene except fB were used. For f B, DNAisolated fromthe 5' flanking region of the gene and single-stranded DNAcomple-mentary to fB mRNAwere included. ACT, AFP, and ALB determina-tions, shown in this figure, are not reported in this manuscript. The filterwas cut into strips and hybridized with 32P-labeled RNAderived fromnuclei from cells exposed to CMfor the indicated times. The figureshows a representative autoradiograph of an experiment extending over120 h of CMexposure. The autoradiograph was scanned in a densitome-ter for quantitative analysis.

bation with CM(Fig. 1). There was no reason to suspect comparableartifacts for any of the other probes used.

Levels of specific RNAwere determined by Northern blot analysisof total RNA. RNAsamples ( 15-25 jg) were heat denatured for 5 minat 65°C in 2 M formaldehyde and fractionated on 0.9% agarose gelscontaining 1 M formaldehyde. RNAwas transferred to a membrane(GeneScreen, Du Pont, Wilmington, DE) filter that was baked at 80°Cfor 2 h. Each cDNA probe described was labeled by random primingin the presence of [32P]dCTP and hybridized (106 cpm); the filter waswashed with 2x SSC, 0.1% SDS at 25°C for 15 min and with 0.2xSSC, 0.1% SDS at 65°C for 1 h. Hybridized counts were stripped fromthe filter by heating in H20 for 15 min at 85°C before hybridizationwith the next labeled probe. The amounts of RNA in each lane werenormalized to the final hybridization of the filters with a GAPDHprobe.Quantitation by densitometry on Phosphorlmager was performed aspreviously described. As a control for cell viability during the 120-hculture period, RNA was isolated from Hep 3B cells maintained inserum-free RPMI1640 medium in parallel with CM-treated cells andanalyzed by Northern blots for levels of a-PI, albumin, and GAPDHmRNA.These levels were found to be unchanged relative to 18S rRNAduring the culture period, indicating that the cells remain viable duringthis extended period of time without serum.

For secreted protein assays, medium from each sample collectionor medium change was saved and used to measure the accumulatedamount of each protein at 24-h intervals. Rocket immunoelectrophoresiswas used to measure fB, C3, and a-PI accumulated in medium. SAAlevels were determined using a specific ELISA (28).

Results

Kinetic studies were performed over 22, 72, and 120 h of incu-bation of Hep 3B cells with CM. The temporal pattems ofresponse observed were comparable in all experiments, al-though peaks of both transcription and mRNAaccumulationwere achieved at slightly later time points in the 120-h experi-ment (shown in Table I), than in the 72-h experiment. Fig. 1

1254 S.-L. Jiang, D. Samols, D. Rzewnicki, S. S. Macintyre, I. Greber, J. Sipe, and L Kushner

Table L Kinetics of Relative mRNALevels and Transcription Rates during Incubation with CM

Incubation

Gene 0 h 6 h 12 h 24 h 48 h 72 h 96 h 120 h

mRNAabundanceSAA <0.02 0.5 1.6 3.5 8.6 10.0 10.1 7.2fB <0.05 0.7 2.2 4.3 7.5 8.5 7.6 5.2C3 <0.05 0.5 1.3 3.0 5.5 6.8 5.9 4.5a-PI 2.3 2.1 2.6 3.1 3.6 3.8 3.4 3.2a-fib 0.7 1.6 2.2 2.6 3.8 3.2 2.7 1.2

Nuclear run-onSAA 0.05 0.8 0.9 1.2 1.0 1.0 0.9 0.6fB (dsDNA) 0.06 0.9 1.2 1.5 0.7 0.6 0.8 0.4C3 0.2 0.6 0.9 1.5 1.4 1.1 0.9 0.6a-PI 0.7 0.8 1.2 1.5 1.0 0.8 0.1 0.7a-fib 0.3 0.7 1.4 1.3 2.1 1.1 0.8 0.2

Data are expressed in densitometric units (ratio of gene of interest to GAPDH). dsDNA, double-stranded DNA.

illustrates a nuclear run-on assay, and Fig. 2 showstive Northem blot of fB over 120 h of CMexposurbaseline values of mRNAfor SAA, fB, and C3undetectable, serial dilutions of RNA extractedloaded on the same agarose gel, and the sensitivityem blot assay for each of these mRNAspecies w;(see Fig. 2 for dilutions with fB probe). Weassisteady-state levels of these mRNAspecies in unsticould be no more than the lower limit of sensitivimined and used these values in Table I and in cthe magnitude of change.

Fig. 3 illustrates kinetics of change in mRNtranscription rates during a 120-h exposure to Cas fold increase compared with observed or calcuvalues. Rapidly rising transcription rates were obacute phase genes during incubation with CM; peaattained at 24 h with the exception of a-fib, whi

hrs o 6 12 24 48 72 96 120

Figure 2. Northern blot analysis of fB mRNAin Hep 3]to CM. Total RNAfrom Hep 3B cells exposed to CMf(times was isolated and fractionated by formaldehyde-aelectrophoresis before transfer to GeneScreen membranestion as described in Methods. The figure shows a repres(diograph using a fB cDNAprobe of an experiment exteh of CMexposure. The right-hand panel is another portifilter showing the fB Northern blot signal of the 6-h RNthe dilutions indicated to determine the limit of detecticwhich only a weak signal was evident in the unstimulatetion. The autoradiograph was scanned in a densitometeranalysis before removal of hybridized RNAand countewith another probe.

s a representa- peak at 48 h. Table II depicts calculated ratios between increasese. To estimate in mRNAand in transcription, as well as the time lags between1, which were peak transcription and peak or plateau mRNAlevels for all

at 6 h were genes studied. Two kinetic pattems emerged from these data.of our North- SAA, fB, and C3 mRNAlevels increased - 10-20-fold more

as determined than did transcription rates. Weconcluded that posttranscrip-umed that the tional events might play an important role in regulation of theseimulated cells genes by CM. In contrast, increases in transcription rates andity thus deter- mRNAlevels were roughly comparable for both a-fib and a-alculations of PI. For these genes, we concluded that transcriptional changes

could largely account for the changes in mRNAinducedIA levels and by CM.'M, expressed SAA, fB, and C3 mRNAlevels continued to rise after tran-ilated baseline scription rates began to fall, with a consequent substantial lagserved for all between peak transcription and mRNAlevels, suggesting thatk values were these mRNAsare relatively long lived (14). In contrast, for a-ich attained a PI and a-fib, no significant time lag was seen between peaks

of transcription and mRNAaccumulation, suggesting that thesemRNAsare relatively unstable.

6hr dilutions Secretion of SAA, fB, C3, and a-PI into medium was essen-1/40 1/20 1/10 tially linear during a 120-h incubation with CM(Fig. 4). Com-

parable linear secretion of these proteins was found in the 72-h experiment. These findings attested to the continued viabilityof our cells during the entire period of study.

- Modeling and mathematical analysis of data. To test ourtentative conclusion that these data suggested substantialinvolvement of posttranscriptional mechanisms in induction ofSAA, fB, and C3, we used first a curve-fitting, modeling ap-proach and then a rigorous mathematical analysis of the data.

B cells exposed The modeling method makes the simplifying assumption thator the indicated any posttranscriptional effects are exerted at the level of mRNAtgarose gel degradation, which is then used as a surrogate for posttranscrip-s and hybridiza- tional regulation in general. This method allows the initial half-entative autora- life of an mRNAto be varied and then predicts the accumulatedbnding over 120 mRNAlevels (based on observed changes in transcription rate)ion of the same under conditions in which the mRNAhalf-life either remainsIA sample after constant or changes after stimulus. The predicted mRNAaccu-d RNApopula- mulation curves are then compared with the observed data fromforquantitative Northem blots. In each case, the initial transcription rate isr-hybridization assigned a value of 1 unit, and the units expected to be present

in the initial, steady-state mRNApool are determined for each

Posttranscriptional Regulation of Acute Phase Genes 1255

Factor BSAA

0 24 48 72 96 120

Duration of CM exposure (hr)

C3

0 24 48 72 96 120

Duration of CM exposure (hr)

0 24 48 72 96 120

Duration of CM exposure (hr)

PI

0 24 48 72 96Duration of CM exposure (hr)

10

as

la

04

0 24 48 72 96Duration of CM exposure (hr)

Figure 3. Kinetics of change in transcription as reflected by nuclear run-on assays (Trans) and mRNAabundance (mRNA) of five acute phasegenes in Hep 3B cells during a 120-h incubation with CM. Points are represented as fold increase over baseline values set equal to 1.

assigned initial half-life as follows: for each time interval, thesize of the mRNApool is the sum of the number of units atthe beginning of the interval, plus the input to the pool, less theexit from the pool as determined by the assigned half-life. Thesize of the initial mRNApool (in arbitrary units) is then usedas the denominator to predict relative fold increases in the pre-dicted pool values. The same procedure is then applied to inter-vals after stimulus, in which relative transcription rates are var-ied, as determined from the nuclear run-on data, in order to

Table II. Transcriptional and mRNAChanges during 120-hIncubation with CM

Time lag (h) betweenFold increase in mRNA/ transcription peak and

fold increase in transcription mRNAplateau or peak

a-PI 1.7/2.2 = 0.8 24a-fib 5.4/7.2 = 0.75 0SAA >430/24 = >17.9 48fB >240/25 = >9.6 48C3 >147/7.3 = >20.1 48

generate predicted fold increases in the mRNApool. Whilethis approach makes predictions on the basis of an essentiallyinstantaneous change in half-life that is maintained, unchanged,during the course of observation, it is likely that changes inmessage half-life take a finite time to evolve and might beexpected to return gradually to baseline with continued timeafter stimulus. As a result, the model curves would be expectedto show less of a lag in rising mRNAlevels during the ascendingportion of the curve and a less rapid fall in the descendingportion than would be seen in the observed curves.

In applying this model to the data obtained for the SAAandfB genes, none of a wide range of assigned half-lives accuratelypredicted the accumulation curves if the half-lives were keptconstant (Fig. 5 A). Short half-lives were found to generatethe necessary level of mRNAaccumulation, but plateaus were

achieved too early compared with the observed data. Assigninglonger half-lives generated curves that reached plateau levelsat times consistent with those observed, but at mRNAlevelsthat were much lower than those observed experimentally. Incontrast, for each of these genes, a relatively narrow range ofinitial half-lives was found to approximate more closely theobserved levels of mRNAaccumulation, if the initial half-liveswere allowed to increase after stimulus (Fig. 5 B). The best fit

1256 S.-L Jiang, D. Samols, D. Rzewnicki, S. S. Macintyre, I. Greber, J. Sipe, and I. Kushner

4)

asUCu

co0

3

qGoco

Cu

10

-a- Trans.- mRNA

1*

120120

so -0 Pi

C3

40 * fB

30

20

10

0 _o

factor on the left-hand side of Eq. 2, Xr/prtr, is the averagemRNAabundance over the course of the experiment dividedby the total amount transcribed. Wewill call this the "abun-dance ratio" and denote it by C. Observe that the abundanceratio is not determined by the experiments and cannot be knownunless one can obtain absolute rather than relative values. Typi-cally xo/x, is much less than unity, so that C can take on valuesin the range 0 to 1.

By applying Eq. 2 at different times, one can obtain thenormalized accumulated degradation to that time, for specifiedvalues of the abundance ratio. The explicit formula, a rewritingof Eq. 2, is

Pr tr JoPr tr) Xr xo(3)

. . . I . . . I . .- I A .A When Eq. 3 is applied to a time interval rather than to the

24 48 72 96 120 total time, one can deduce the average degradation rate for thattime interval. One also can obtain the corresponding normalized

Time (hrs) degradation rate per unit abundance by dividing the degradation

.- . rntp hv thp crnlhl- nninrnli7d-d ninLJinrl P t thp mititila nf thpFigure 4. Secretion of plasma proteins into medium. Aliquots of mediumwere collected after 6, 12, 24, 48, 72, 96, and 120 h, and the concen-

tration of plasma proteins was determined. Results are plotted as cu-

mulative amounts.

for SAA was observed with an assigned initial half-life of 5-6 h and a 5-7-fold increase after stimulus; the best fit for fBwas observed with an assumed initial half-life of 7-8 h and a

4-6-fold increase after stimulus. In contrast, the model indi-cated that the observed accumulation of a-fib could be ac-

counted for on the basis of an initial half-life of 12 h, with

no change after stimulus (Fig. 5 C).In addition to modeling, the observed data were subjected to

dynamic mathematical analysis to estimate changes in fractionaldegradation of mRNAover the course of the experiments. Aswith the modeling approach, mRNAdegradation was used as a

surrogate for all posttranscriptional effects. Since only relative,rather than absolute, values of mRNAabundance and transcrip-tion rates can be obtained from the experiments, all valuesare referred to reference values (described in the followingdiscussion). The notation is as follows: p is the transcriptionrate at any time; Pr is the reference transcription rate; x is theabundance of any species of mRNAat any time; xr is the refer-ence abundance; and r is the degradation rate at any time.

The amount existing at any time (the abundance) minus theinitial amount is equal to the amount produced minus theamount degraded. Symbolically, this can be written as

rt %.x - xo= pdt rdt. (1)

The experiments determine PlPr and x/Xr. Rewriting Eq. interms of the measurable values, one has

x It'r p

Prtr Xr Xr Pr Pr tr

where tr is a reference time.Average values during the period of the study have been

selected as the reference values, among other reasons becausethese minimize any errors due to uncertainties in determinationof baseline values. If one uses average values as the referencevalues and the total time as the reference time, then the front

time Vi tel; explicU1t111forU d IsL9 L L119 111lU19 V L119

time interval; the explicit formula is

1 dxd = I rlp= RIC

x d(t/tr) CX/Xr (4)

where xd is the amount degraded. For convenience, in scales ofthe graphs we will use R as a nondimensional measure of therate per unit abundance and will call R the fractional degradationrate.

If desired, the degradation half-life at any time can be deter-mined from R and C as follows:

tl/2 = [tr ln (2)](CIR). (5)

Note that tl12 is not a constant.One can arbitrarily assign abundance ratios within allowable

limits, to determine relative changes in fractional degradationrates with time. The allowable abundance ratios range from thelargest value consistent with the requirement that the degrada-tion at any time cannot be < 0 to values approaching 0, re-

flecting high degrees of degradation. It is likely that the com-

plexity of the RNAbeing transcribed and measured by nuclearrun-on assay is far greater than that of the mature RNAspeciesmeasured by Northern blots. Given the known rapid turnoverrates of the highly complex nuclear pre-mRNA, it is likely thatthe lower values of C more closely reflect the biological state.This is particularly true when one appreciates that the denomina-tor of C represents total transcription over the course of theexperiment, independent of degradation; it must be a relativelylarge quantity, and C, of necessity, must be small.

As shown in Fig. 6, at all assumed values of C, rangingfrom 0.25 to 0.001, fractional degradation rates of SAAdemon-strated the same behavior: a rapid fall after the first 6-h period,with persistently low values thereafter. This observation, thatfractional degradation rates fall (and half-lives increase) withcytokine exposure, confirms the conclusion that posttranscrip-tional mechanisms participate in SAAmRNAinduction by CM.For fB and C3, similar curves were seen with assigned Cvaluesof 0. and lower, but not at values of 0.25 and 0. 15, respectively(Fig. 6). These observations are consistent with, but do notestablish the conclusion that posttranscriptional mechanismsparticipate in induction of fB and C3. This conclusion is, how-ever, more strongly supported if the lower values of C are

regarded as valid, consistent with the known rapid turnover of

Posttranscriptional Regulation of Acute Phase Genes 1257

E0

2z0P-i

U

00.

A

700 fBCo 3000> 600

Fu500 M Observed - - Observeda: - --2.5h 20 U-3hS ~~~~~~~~0--3h-0-4

mRNAvaue orSA ndfBa dffrntasine -al om 4h -speds A 6hare 300icated byteclsedircls.()PrdictdmNAvluesforAAadfBassmin6h i 12h

200 --in--- ~~~~ ~~~~12h100 -U--24hV -a--- ~~~~~~~~~~~24h0a 36h

100

0 20 40 60 80 100 120 0 20 40 60 80 100 120

Time After Induction (h)

BSMA 250 fB0 *~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Observed>600~~~~~~~~~~~~~~~~~~~---No change>) 600

0 200--

Z - - 3xa: 5E 400 4xCo --0- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~5x

100 -. - 6x

C200~~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ --- 7x

0

0 20 40 60 80 100 120 20 40 60 80 100 120

Time After Induction (h)

Fibrinogen0 10

0 - - Observed8 6h

a:E 6 0- 8hC ..- 12h

4~~~ ~ ~ ~ ~ ~ ~ ~ .~~~ 18h_~~~~~~~~~~~~ ~~~24h

0 2 -36h

0.LJ

0 20 40 60 80 100 120

Time After Induction (h)

Figure 5. Mathematically predicted mRNAlevels at intervals after stimulus, assuming different half-lives of mRNA,based on modeling. (A) PredictedmRNAvalues for SAAand fB at different assigned values of mRNAhalf-lives, held constant. Experimentally observed changes in mRNAaccumulationare indicated by the closed circles. (B) Predicted mRNAvalues for SAA and f B, assumung initial half-lives of 5 h for SAA, 7 h for f B, and increasesin half-life as indicated. (C) Predicted mRNAvalues for a-fib at different assigned values of mRNAhalf-lives, held constant.

1258 S.-L Jiang, D. Samols, D. Rzewnicki, S. S. Macintyre, I. Greber, J. Sipe, and L Kushner

z 14 10 7

12 SAA mactLo r 6 C3

10 7..i5 mO

4C~~~~~~~~~~~06 4L3

4 2

0 10 20 30 40 50 60 7080 901001 1 0 10 20 30 40 50 60 70 0 90 100110 10 20 30 40 50 60 70 90100110lime (h) Time (h) Time (h)

Figure 6. Calculated normalized fractional degradation rates of SAA, f B, and C3 mRNAsfor different assigned values of abundance ratios (C)during incubation of Hep 3B cells.

nuclear pre-mRNA. In contrast, for a-PI and a-fib, relativelyminor changes in fractional degradation rates were found at allassigned values of C, and substantial decreases in fractionaldegradation rates were not seen. These observations suggestthat posttranscriptional mechanisms do not play major roles ininduction of these mRNAs.

It should be reemphasized that regulation of either transcriptprocessing or transport of mRNAfrom the nucleus to the cyto-plasm could be consistent with these data as well, since aninitial assumption that mRNAdegradation was the only effec-tive posttranscriptional mechanism was made for these analyses.

Discussion

These kinetic studies were undertaken to help determinewhether changes in acute phase mRNAlevels induced by CMinHep 3B cells could be fully explained by effects of transcriptionalone, or whether posttranscriptional mechanisms need to beinvoked to explain the changes observed. CMcaused increasedtranscription of each of the positive acute phase genes we stud-ied, indicating that the changes in mRNAwere at least partiallyattributable to transcriptional regulation. However, the observa-tion that the magnitudes of increase in mRNAfor SAA, fB, andC3 were substantially greater than the magnitudes of increasein transcription suggested that posttranscriptional mechanismscontributed to the changes in expression induced in these genesby CM. To evaluate this possibility rigorously, we undertooktwo mathematically based, quantitative approaches to test thevalidity of this conclusion.

Our curve-fitting, modeling approach supported the conclu-sion that posttranscriptional mechanisms must be invoked toexplain the observed effects on mRNAof SAA, fB, and C3,since no constant half-life values were capable of predicting theobserved mRNAaccumulation curves. In addition, making theworking assumption that these posttranscriptional mechanismsinfluenced mRNAdegradation rather than affected nuclear pro-cessing of primary transcripts or export of mature mRNA, theypermitted crude estimates of the magnitudes of effect on mRNAstability required to account for the observed findings.

A significant concern in the interpretation of these data wasthe need to use relatively small transcription rates found inunstimulated cells as denominators for determination of themagnitude of increase in transcription. Were these values falselyhigh, the true magnitude of transcription rate increase would,in fact, be higher than we calculated and closer to the changes

seen with mRNA. Similarly, low, imperfectly quantitated initialmRNAlevels might lead to false calculation of the magnitudeof increase. To avoid the necessity of relying on initial transcrip-tion and mRNAvalues for mathematical analysis, we usedabundance ratios (which represented average-rather than ini-tial-mRNA abundance) divided by total transcription over theperiod of the experiment (which also avoided use of initialtranscription rate values). Thus, neither numerator nor denomi-nator was subject to the sources of error that might result fromthe use of very small baseline values. Using this approach,dynamic mathematical analyses indicated that SAA inductionby CMinvolved substantial participation of posttranscriptionalmechanisms and was strongly supportive of such a conclusionfor fB and C3. Although intranuclear processing, decay of tran-scripts, and nucleocytoplasmic export of mRNAmight all theo-retically serve as posttranscriptional regulatory mechanisms (forreview see reference 29), kinetic modeling has suggested thatsuch mechanisms would be relatively inefficient in affectingcytoplasmic mRNAconcentrations and that the main points ofcontrol must be transcriptional processes and regulation ofmRNAdegradation (14). Thus far, in a few limited studies,relatively modest direct effects of cytokines on stability of acutephase mRNAsin cell lines have been reported (30-32). Studiesof some murine SAA genes (9, 12) have suggested posttran-scriptional control, but effects on mRNAstability could not bedemonstrated using the transcriptional inhibitor actinomycin D.However, the observations of Steel et al. (33) that the disappear-ance rate of SAA mRNAduring actinomycin D treatment issubstantially slower than its disappearance rate after cytokineinduction, which we have independently confirmed, indicatethat this method cannot be used for estimation of the stabilityof SAA mRNA.

Weused CMas a potent stimulus to induce acute phasechanges since such preparations have repeatedly been found toinduce the entire spectrum of these changes in Hep 3B cells( 16, 34, 35 ). CMpreparations consist of a crude and undefinedmixture of IL-6 and other inflammation-associated cytokines,cytokine modulators (such as IL-1 receptor antagonist), andendocrine hormones, such as dexamethasone and insulin. Thepotency of various CMpreparations may vary from one experi-ment to another; greater effects were seen in our 120-h experi-ment than in our 72-h experiment. Future studies delineatingspecific mechanisms involved in acute phase induction will re-quire the use of defined cytokines, cytokine modulators, andhormones. In initial studies of this type, we have found that the

Posttranscriptional Regulation of Acute Phase Genes 1259

combination of IL-6 and IL-I/# caused a substantially greaterincrease in mRNAlevels than in transcription for SAA, fB,and C3, but not for a-PI, supporting the findings observedwith CM(35a).

Because mRNAlevels of SAA, fB, and C3 were undetect-able in unstimulated cells, it was necessary to estimate maximalbaseline mRNAlevels from estimates of the sensitivity of themethod. The approach we used, determining the lower limit ofdetectability of each mRNAby serial dilutions of 6-h samples,yielded the maximal possible value of baseline mRNAlevels.It is likely that actual mRNAlevels were lower than thesevalues, that the magnitudes of increase we calculated were mini-mal estimates, and that we thus underestimated the actual mag-nitude of mRNAincrease that occurred. To the extent that thisis the case, it would further strengthen the argument for partici-pation of substantial posttranscriptional mechanisms in induc-tion of these three genes.

In summary, these studies suggest that posttranscriptionalmechanisms participate in induction of several acute phasegenes by CM. The increasing number of eukaryotic genes foundto be regulated at the level of mRNAstability and the multiplic-ity of mechanisms by which this regulation may be accom-plished (36, 37) suggest that studies of such mechanisms inacute phase genes may prove informative. Future studies shouldinclude critical evaluation of the possible effects of acute phase-inducing cytokines on mRNAstability.

Appendix

Derivation of FormulasAnalysis of degradation. The abundance, x, at any time is the initialabundance, xo, plus the amount produced minus the amount degraded.Calling the rate of production p and the rate of degradation r, the abovestatement can be written

t ,x = xo + f'pdt - f rdt. (Al)

The experiments do not measure abundance or production rates directly;they provide the values relative to the corresponding values of GAPDH.If the GAPDHvalues are assumed to be constant, then the experimentsyield the ratios of abundance and production rate to the correspondingvalues at a chosen reference time. Symbolically this can be written

X XXx=

XIXG (A2)XI XI /XG

P P/PG (A3)PI PI/PG

where the subscripts 1 and Gdenote specified time and GAPDH,respec-tively.

Rewriting Eq. Al as a formula for the amount of degradation yields

pi J dt = p_ P dt -x, x xo (A4)oJ~ oP,\]xl xlj

Instead of using the values of x and p at some specified time as referencevalues, it is convenient to use the average values as reference values.Denoting the average value by the subscript r, the averages can beobtained as follows:

(A5)trt-= X dt,

PI tr = |P dt,pI opI

where t, is the total time of the experiment. Then

x X/X, p p/ps

Xr XrI/X Pr PrIP (A7)

Eq. A4 remains valid with the subscript 1 replaced by subscript r. It isconvenient to perform the integrations Eq. Al using as a variable thetime of the observation relative to the total time of the experiment. ThenEq. A4 can be rewritten

(A8)Prtr d( )= Prtr f"pd(i) Xr(x x

Dividing through by prtr yields

f rrd(t = JrP t)( _ Xr (X XO)0 Pr tr ° Pr tr Prtr Xr Xr

Eq. A9 corresponds to Eq. 3 of the main text. For any assigned valueof xr/prtr, Eq. A9 yields the total amount degraded from the beginningof the experiment until the specified time, relative to the amount thatcould be produced at the average production rate. Applying Eq. A9between two times of observation, a and b, yields the average degrada-tion rate over the time interval tb - ta, in the same nondimensionalsense as described above. This can be written

P(tlt)rr t

Pr ttr P \ tr

Pr (tr )b (tr )a

The above-average value of rip, should be regarded as the value at themidpoint of the time interval tb - ta.

The degradation rate per unit abundance rix is given by

rlx = r(Pr\)( Prt.\) 1X/X, Xr tr

(Al 1)

It is convenient to use the nondimensional value, rtl/x (which we willcall RIC) as a measure of the fractional degradation rate, where C isthe abundance ratio Xr/prtr. The abundance ratio Cis the average mRNAabundance divided by the total amount transcribed. The quantity RICcan be interpreted as the nondimensional derivative, dld(t/t,), of theamount degraded, Xd, per unit abundance. Thus one rewrites Eq. Allas follows:

1 dx=

pt,(rlp, Rx d(tft,) Xr X/Xr, C

(A12)

Eq. A12 corresponds to Eq. 4 of the main text.Relationship of degradation with half-life. The half-life at any time

is obtained by considering a constant fractional rate of degradation andno production. Then the rate at which the abundance increases is thenegative of the degradation rate. This can be written

I dx r-- = - = constant = K.

x dt x

Integrating Eq. A13 yields

In (xlx,) = - Kt.

(A13)

(A14)

The half-life is the time such that xixl = I/2. Then Kt = ln(2). WithK = rix given by Eq. Al1, the half-life is given by

tl,2 = t, ln(2)/R, (A15)

where R is the nondimensional fractional degradation rate given in Eq.A12.

Acknowledgments

Weare grateful for the outstanding secretarial assistance of Nancy Kes-

(A6) sler and Lori Fransen. Appendix prepared by Isaac Greber, Professorof Mechanical & Aeronautical Engineering.

(AIO)

(A9)

1260 S.-L. Jiang, D. Samols, D. Rzewnicki, S. S. Macintyre, 1. Greber, J. Sipe, and 1. Kushner

This work was supported by National Institutes of Health grantAG-02467.

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