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Systems Biology ofMammalian Circadian Clocks
Hideki Ukai1 and Hiroki R. Ueda1,2
1

Laboratory for Systems Biology and 2 Functional Genomics Unit, RIKEN Center for
Developmental Biology, Hyogo 650-0047, Japan; email: uedah-tky@umin.ac.jp

Annu. Rev. Physiol. 2010. 72:579–603

Key Words

First published online as a Review in Advance on
November 13, 2009transcriptional circuit, temperature compensation, singularity,
artificial circuit

The Annual Review of Physiology is online at
physiol.annualreviews.org
This article’s doi:
10.1146/annurev-physiol-073109-130051
c 2010 by Annual Reviews.
Copyright !
All rights reserved
0066-4278/10/0315-0579$20.00

Abstract
Systems biology is a natural extension of molecular biology; it can be
defined as biology after identification of key gene(s). Systems-biologicalresearch is a multistage process beginning with (a) the comprehensive
identification and (b) quantitative analysis of individual system components and their networked interactions, which lead to the ability to(c) control existing systems toward the desired state and (d ) design newones based on an understanding of the underlying structure and dynamical principles. In this review, we use the mammalian circadian clock as
a model system and describe the application of systems-biological approaches to fundamental problems in this model. This application has
allowed the identification of transcriptional/posttranscriptional circuits,
the discovery of a temperature-insensitive period-determining process,and the discovery of desynchronization of individual clock cells underlying the singularity behavior of mammalian clocks.

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INTRODUCTION: SYSTEMSBIOLOGY AS BIOLOGY AFTERIDENTIFICATION

are approached as complex and dynamic
systems. Systems biology is a natural extensionof molecular biology and can be defined as
biology after identification of key gene(s).
We consider systems-biological research asa multistage process (Figure 1) that comprises
four steps: (a) identification of the whole network structure through functional genomics
and comparative genomics (system identification), (b) prediction and validation of the system’s behavior to derive the design principle
through the accurate measurement and (static)
perturbation of network dynamics (system analysis), (c) control and repair of the network state
toward the desired state through the precise andRecent large-scale efforts in genome sequencing, expression profiling, and functional
screening have produced an embarrassmentof riches for life science researchers, and biological data can now be accessed in quantities
that are orders of magnitude greater than wereavailable even a few years ago. The growing
need for interpretation of data sets, as well as
the accelerating demand for their integration toa higher-level understanding of life, has set thestage for the advent of systems biology (1, 2),
in which biological processes and phenomenaabSystem identification
Divide into components
E4BP4

System analysis
Accurately measure
E4BP4

DBP

DBP

TEF

TEF
HLF

HLF

BMAL2
BMAL1

0
22

23 24(0)

BMAL1

CLOCK

1

Identify

2

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3
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BMAL2

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NPAS2
E/E'box

CRY2

D-box

15

FBXL3

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D-box

CRY1
RevErbAa

RevErbAa

DEC1

RevErbAb
DEC2

RORa
PER1

GSK3b

10

CKId

Mammalian circadian
clock

CKIe

RORa

CKId

RORc

Step B
4h

RRE

PER3

PP2A

CKIe

Systems
biology

Step C
4h
Step D
6h

RORc
PER3

RRE

Genetic networkof clock

Genetic networkof clock

Oscillator

RORb
PER2

PP1

System control
Operate intentionally

c

PER1

GSK3b

RORb
PER2

PP1
PP2A

Step E
4h

DEC1
RevErbAb

DEC2

12

Step A
6h

FBXL3

CRY1

6

9
14

E/E'box

CRY2

8

16

Prediction
Verification

CLOCK

NPAS2

Naturalcircadian rhythm

System design
Synthesize from scratchdDesignReconstruction

StimuliControl
Repair

1
0.75
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circadian rhythm

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D-box

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Rev
ErbAa RORa
Rev
ErbAb RORb

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Networkcomponents

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RORc

PP2A

RORb
PER2

PP1

DEC1

D-box

FBXL3

CKIe

RORc
PER3

RRE

Genetic networkof clock

Figure 1
Systems biology. (a) Systems-biological research begins with comprehensive identification. In this step, individual system components
and their networked interactions are comprehensively identified. (b) In the second step, to derive the design principle of a target system,
the behavior of the system is predicted and validated through an accurate measurement with perturbations. (c) An understanding of thedesign principle of the system is needed to derive the method of controlling the system toward the desired state. (d ) Finally, the level ofunderstanding is confirmed by reconstruction of the system.
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dynamic perturbation of its components (system control), and (d ) reconstruction and designof systems based on the design principles derived from the identified structure and observed
dynamics (system design). These processes are
required to elucidate the design principles ofcomplex and dynamic biological systems, suchas the mammalian circadian clock.

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MAMMALIAN CIRCADIAN
CLOCK AS A MODEL SYSTEM
The mammalian circadian clock is an ideal
model system for the study of complex and dynamic biological systems. The mammalian circadian clock consists of complexly integrated
feedback and feed-forward loops (3) and exhibits well-defined dynamical properties (4),including (a) endogenous oscillations with anapproximately 24-h period, (b) entrainment toexternal environmental changes (temperatureand light cycle), (c) temperature compensation
over a wide range of temperatures, and (d ) synchronization of multiple cellular clocks despite
the inevitable molecular noise. All of these dynamical properties would be difficult to elucidate without utilizing such system-level approaches. In addition to its advantages as abasic model system for systems-biological research, the circadian clock is intimately involved in the control of metabolic and physiological processes (3, 5), and its dysregulation
is associated with the onset and development of
numerous human diseases, including sleep disorders, depression, and dementia. An improved
system-level understanding promises to provide biomedical and clinical investigators with apowerful new arsenal with which to attack these
conditions.
Some systems-biological efforts to elucidate
the design principles of complex and dynamic
biological systems such as the mammalian circadian clock have been reported. In the following
sections, we describe in detail the strategies andtechnologies developed for systems-biologicalresearch, in addition to their applicability to
the specific case of the mammalian circadianclock.

IDENTIFICATION OF CLOCKS
Following the completion of genome projects
for species such as mouse and human,
genome-wide resources such as small interfering RNA (siRNA) and complementary DNA(cDNA) libraries have undergone considerable
expansion. Development of high-throughput
technologies also allows efficient use of theseresources. These genome-wide resources andtechnologies, as well as genome-associated information, allow us to comprehensively identify
complex systems such as the mammalian circadian clock (system identification).

Temperaturecompensation:
phenomenon thatcauses the period of an
oscillation to be stable
despite temperaturechange
SCN: suprachiasmatic
nucleus

Identification of theTranscriptional Circuit
The mammalian circadian master clock is primarily located in the suprachiasmatic nucleus(SCN) (3). Transcript analyses have indicatedthat circadian clocks are not restricted to SCN
but are found in various tissues (6), including
liver, and in cultured fibroblast cells such as Rat1 (7, 8), NIH3T3 (9), and U2OS (10) cells. Increasing numbers of so-called clock genes wereidentified in mammalian clocks; these genes include three basic helix-loop-helix (bHLH)-PAS(PER-ARNT-SIM) transcription factors (Clock,Npas2, and Arntl; the latter is also known as
Bmal1 or Mop3) (11–14), two period genes (Per1and Per2) (15, 16), two cryptochrome genes(Cry1 and Cry2) (17, 18), casein kinase I epsilonand delta (Csnk1e and Csnk1d ) (19, 20), andtwo orphan nuclear hormone receptors (Nr1d1
and Rora, also known as RevErbα and Rorα,
respectively) (21, 22). A number of other transcriptional factors also thought to function in
the circadian regulation of gene expression were
gradually clarified; these include four bZipfamily genes (Dbp, Tef, Hfl, and Nfl3; the latter isalso termed E4bp4 ) (23, 24), three bHLH transcription factors (Arntl2, Bhlhb2, and Bhlhb3,
also known as Bmal2, Dec1 or Stra13, and Dec2,
respectively) (25), one period-related gene
(Per3) (26), and three genes related to Nr1d1
and Rora (Nr1d2, Rorb, and Rorc, also known
as RevErbβ, Rorβ, and Rorγ , respectively)(22, 27).
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CCEs: clockcontrolled elements

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dLuc: destabilized
luciferase
In cellulo cycling
assay: means of
performing real-timemonitoring oftranscriptional
dynamics of clockcontrolled promotersin a cell via dLuc

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Molecular interactions among these clock
genes and clock-related genes have also beenat least partly identified. For example, thetranscription factors CLOCK and BMAL1
dimerize and directly and indirectly activatetranscription of the Per and Cry genes throughE-box elements (5! -CACGTG-3! ) (28, 29).
The PER and CRY proteins accumulate in
the cytosol and are then translocated following
phosphorylation into the nucleus, where they
inhibit the activity of CLOCK and BMAL1(3). The turnover of the inhibitory PER and
CRY proteins leads to a new cycle of activation
by CLOCK and BMAL1 via E-box elements.
The transcriptional regulation network ofthese genes forms a circadian clock oscillator,
which is known to control output genes andto affect physiological and metabolic processes(3, 5). This type of transcriptional feedback
mechanism underlying circadian rhythms
seems to be conserved across species (4).
Despite reports of many transcriptional regulations of each gene, however, an overview of
the circadian clock core network remains to be
put forward.
Complicated networks cannot be elucidated
without both a comprehensive identificationof network circuits and an accurate measurement of system dynamics. In the first step
toward complete identification of the circadianclock core network, several groups utilized
DNA microarray to comprehensively andquantitatively measure genome-wide gene
expression of mammalian circadian clocks (27,
30–54). For example, Ueda et al. (27) identified
so-called clock-controlled genes and demonstrated circadian oscillation with characteristic
expression patterns in mouse SCN and liver
through use of a high-density oligonucleotide
probe array (55) and biostatistics. In thesecond step, the authors comprehensively
determined the transcription start sites via theoligo-capping method (56) to construct the
genome-wide promoter/enhancer database.
Using these data, the authors predicted a
relationship between expression patterns ofidentified genes and DNA-regulatory elements on their promoter/enhancer regions.
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Three types of clock-controlled elements(CCEs)—E-boxes (5! -CACGTG-3! ) (57)plus E! -boxes (5! -CACGTT-3! ) (58, 59),
D-boxes [5! -TTATG(C/T)AA-3! ] (60), andRevErbA/ROR-binding elements (RREs) [5! (A/T)A(A/T)NT(A/G)GGTCA-3! ] (61)—are
distributed throughout the oscillatory genes.
To determine the role of these elements inthe circadian clock, Ueda et al. (27, 58) utilized acell-culture system in which circadian rhythms
in transcriptional dynamics are monitored via adestabilized luciferase (dLuc) reporter driven byclock-controlled promoters. In this cell-culture
system—termed the in cellulo cycling assay—
cultured Rat-1 cells were transiently transfectedby reporter constructs and stimulated with dexamethasone, and their bioluminescences were
measured. Dexamethasone was administrated
to induce macroscopic circadian oscillationsin the cultured cells. Through the genomewide searching process described above, theauthors found CCEs on 16 clock/clockcontrolled gene promoters/enhancers. Via thecellulo cycling assay system, Ueda et al. revealed that functionally and evolutionarily conserved E/E! -boxes are located on the noncoding regions of nine genes (Per1, Per2, Cry1,
Dbp, Rorγ , RevErbα/Nr1d1, RevErbβ/Nr1d2,
Dec1/Bhlhb2, and Dec2/Bhlhb3); that D-boxes
are located on those of seven genes (Per1, Per2,
Per3, RevErbα, RevErbβ, Rorα, and Rorβ); andthat RREs are located on those of six genes(Bmal1/Arntl, Clock, Npas2, Cry1, E4bp4/Nfil3,
and Rorγ ). On the basis of this functional andconserved transcriptional regulatory mechanism, investigators successfully drew transcriptional circuits underlying mammalian circadianrhythms (Figure 2a) (58). We note that further
characterization of these three CCEs was recently performed (62–65).
Ueda et al. (58) further suggested that regulation of E/E! -boxes is the topological vulnerability point in the mammalian circadian clock,and they functionally verified this concept using in cellulo cycling assay systems. Overexpression of repressors of E/E! -box regulation[CRY1 (29)], RRE regulation [REVERBα (22,27)], or D-box regulation [E4BP4 (24)] affected

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a

E4BP4

DBP
TEF
HLF

BMAL2
BMAL1
CLOCK

E/E'-box

CRY2

D-box

FBXL3
CRY1
RevErbAα

DEC1

RevErbAβ
DEC2
RORα
PER1

GSK3b
CKIδ

PER2

PP1

b

Period length(h CT)

PP2A

48

RORβ

CKIε

RORγ
RRE

PER3

TG003

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24

0

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Concentration (µM)

48

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24

42
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NPAS2

Concentration (µM)

Figure 2
System identification of clocks. (a) Schematic representation of the transcriptional network of the
mammalian circadian clock. Genes and clock-controlled elements are depicted as ovals and rectangles,
respectively. Transcriptional/translational expression, activation, and repression are depicted as gray, green,and magenta lines, respectively. (b) Dose-dependent effects of SP600125 and TG003 on period length in
U2OS-hPer2-Luc cells. The period length is indicated both in real time (right axis) and in circadian time
(CT; left axis). For CT, the average period length in two independent control experiments was assigned as
24 h. The two lines in each graph correspond to two independent experiments (99). Each value represents
the mean ± SEM (standard error of the mean). At the concentrations without data points, the cells behaved
arrhythmically. High-dose pharmacological inhibition of the casein kinase I epsilon (CKIε) activity
lengthened the circadian (∼24-h) period to an almost circabidian (∼48-h) period.

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circadian rhythmicity in Per2 or Bmal1 promoter activity. The effects differed, however,among repressors, and the severest effect wasobserved when the E/E! -box was attacked. Such
different modes of effect cannot be explainedby mere quantitative differences in the strengthof these three repressors, indicating that there
is some qualitative difference among E/E! box, D-box, and RRE regulation in circadianrhythmicity (58).
We also note that a novel strategy termed
gene-dosage network analysis was recently
developed by Baggs et al. (66). In this strategy,siRNA-induced dose-dependent changes ingene expression were used to build geneassociation networks consistent with known
biochemical constraints (66). Baggs et al.
observed that several genes are upregulated
following knockdown of their paralogs, whichsuggests that the clock network utilizes active
compensatory mechanisms rather than simple
redundancy to confer robustness and maintainfunction.

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The Role of Negative Feedback
The identification of transcriptional circuitsof mammalian circadian clock has revealed
the topological importance of E-box, the socalled morning element. This is consistent
with the prevailing transcriptional feedback
model, which is believed to be mediated in the
mammalian circadian clock by the CRY1 and-2 (17, 18, 29) and PER1 and -2 (16, 67,68) proteins. More specifically, the CRY andPER proteins are hypothesized to autoregulate their own expression by repressing theheterodimeric complex of the bHLH-PASdomain transcriptional activators CLOCK and
BMAL1, which bind to E-box elements in the
CRY (69) and PER (28, 58, 59) promoters.
Similar autoregulatory loops, in which negative
feedback regulation of transcriptional and/ortranslational processes are involved, seem tobe evolutionarily conserved among a wide variety of species (3, 70, 71). Thus, transcriptional/translational feedback repressions areproposed to generate a 24-h periodicity. The
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question of universal necessity for transcriptional/translational feedback repression, however, arose primarily from recent studies of
cyanobacterial circadian rhythms, in which therepression was shown to be not necessary (72,73). Direct evidence for the requirement of
CRY-mediated repression of CLOCK/BMAL1
transcriptional activity in the maintenance of
circadian clock function thus remains to bepresented.
To determine the requirement of feedback
repression in circadian clock function, Satoet al. (78) changed the molecular parameter for
feedback repression by functional genomics,
then tested the cellular phenotype caused bythis parameter change via the in cellulo cycling
assay system. The authors sought to identify
the CLOCK alleles that were insensitive
to CRY1 repression but maintained normaltranscriptional activity. They generated alibrary of ∼6000 random point mutants ofhuman alleles for both CLOCK and BMAL1,
then screened clones individually in cell-based
reporter assays with wild-type Bmal1 cDNAand a Per1 promoter–luciferase (Per1-Luc)
construct (28) in the presence of cotransfected
Cry1. Compared with wild-type alleles, of the
CLOCK and BMAL1 clones screened, several
reproducibly maintained threefold or greater
reporter activity in the presence of CRY1.
Notably, these clones demonstrated similartranscriptional activities as wild types in theabsence of cotransfected Cry1, suggesting thatthese mutations do not cause overt alterationsin the heterodimerization, nuclear localization,
DNA-binding, and transactivation propertiesof the mutant CLOCK/BMAL1 complex.
The prevailing transcriptional feedback
model predicts that impairment of CRYmediated repression should have marked effects on circadian expression of the Per genes.
This notion is supported by in vivo observations that expression of Per1 and Per2 is constitutively elevated in Cry1/Cry2 double-knockout
mice (18, 74). To determine whether these mutations in CLOCK and BMAL1 cause phenotypic changes in circadian gene expression, investigators performed in cellulo cycling assays

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(27, 58). Mouse NIH3T3 cells were transfected with plasmids harboring dLuc driven
by the Per2 or SV40 basic promoters, alongwith the BMAL1 and CLOCK mutant alleles,
and were monitored via the in cellulo cycling
assay. Compared with empty vector transfection, cotransfection of wild-type CLOCK and
BMAL1 did not substantially alter rhythmicity,and the transfected cells’ period lengths were21.4 ± 0.4 h. In contrast, transfection of either CLOCK or BMAL1 mutant alleles, whencompared with wild-type CLOCK/BMAL1,
resulted in substantial impairment of circadian rhythmicity after one or two cycles ofoscillations. Notably, cotransfection of CRYinsensitive mutant CLOCK and BMAL1 together resulted in the loss of circadian Per2
promoter activity. Sato et al. (78) therefore
demonstrated that the transcriptional repression of CLOCK/BMAL1 by CRY was requiredfor circadian E-box activity.
In addition to that of Per and Cry, the rhythmic expression of Bmal1 mRNA is also subject to circadian clock regulation (75). The
Bmal1 promoter used in this study, however,does not have E-box sites and instead contains
RRE (22, 27), whose activities are reciprocallycontrolled by the rhythmically expressed transcriptional repressor REVERBα (22) and theactivator RORα (21). In an additional test forcircadian clock function, the effects of mutant
CLOCK and BMAL1 on rhythmic RRE activity were examined via in cellulo cycling assays with a Bmal1-dLuc reporter. Similar to theresults obtained from the Per2-dLuc reporter,transfection of single CLOCK or BMAL1
mutants resulted in the decreased amplitudeof cycling of Bmal1-dLuc activity comparedwith wild-type CLOCK/BMAL1 transfection.
Moreover, this decrease in cycling amplitude
was further exacerbated upon cotransfectionof the double-mutant heterodimer. These results indicate that transcriptional repression of
CLOCK/BMAL1 by CRY is also required forcircadian BMAL1 expression through RRE,
which in turn depends on transcriptional, translational, and posttranslational actions of endogenous cellular factors.

Arrhythmic Per2 expression, observed ina population of cells expressing the doublemutant CLOCK/BMAL1 complex, may be
due to the disruption of oscillator function
or a lack of synchrony between individual
rhythmic cells. To address these possibilities,
quantitative imaging of Per2-dLuc reporter
activity from individual NIH3T3 cells wasmeasured by an approach similar to that used inanalyzing Bmal1 reporter rhythms from single
cells (76). As in the whole-well assays, themedian reporter activity for the population ofimaged individual cells coexpressing wild-type
CLOCK/BMAL1 oscillated rhythmically.
In contrast, the population of individual
Clock/Bmal1 mutant cells was visibly arrhythmic. Individual reporter activities from single
wild-type cells were rhythmic, as expected,
whereas individual Clock/Bmal1 double-mutant
cells showed arrhythmic reporter activities.
These differences in activity patterns were evaluated by two independent statistical methods
that score the circadian rhythmicity of experimental time-course data. These data provide
direct evidence that CRY-mediated feedback
repression of the CLOCK/BMAL1 complex isrequired for mammalian clock function.
We also note that functional genomics technology utilized in Sato et al.’s study has successfully been applied to other clock proteins(CRY1 and CRY2) to further characterize theirmolecular properties (77). Thus, the application of cellular genetics technology will probably have as significant an impact on mammalian biology as similar approaches have hadon prokaryotic and yeast biology.

The Identification of theRate-Limiting Process
The
E-box-mediatedtranscriptional/
posttranscriptional loop is the critical core loopof the mammalian circadian clock (58, 78).
Despite this finding, the specific processes in
the core loop that determine the period length
remain elusive. In this section, we describe theidentification of the rate-limiting process ofthe mammalian circadian clock.
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Circadian time (CT):standardized 24-h
notation of the phasein a circadian cycle.
CT0 indicates the
beginning of a
subjective day, andCT12 indicates the
beginning of a
subjective night

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As described above, comprehensive geneexpression profiling is a basic approachto system identification (27, 30–54), andsuch gene-expression profiles are integrated
with comparative genomics to characterize
the clock-controlled DNA elements in the
mammalian genomes (62, 64, 65). However,mammalian circadian clocks cannot be understood only through the identification oftranscriptional circuits; posttranscriptional
regulations need to be identified (79–82). This
lack of information about posttranscriptional
regulations will be able to be complemented byhigh-throughput measurement technologies
such as proteomics (46, 83), metabolomics (84,85), and other functional genomics resources
such as RNA interference (RNAi) (10, 66,
86, 87) and chemical or peptide libraries (88,89). Using these technologies and resources,
Nakahata et al. (88) identified 15d-PGJ2 andHatcher et al. (84) identified little SAAS as entrainment factors for NIH3T3 cells and SCN,
respectively. In a high-throughput RNAi-based
genetic screening, Maier et al. (86) identified
CK2 as a PER2-phosphorylating kinase andcomponent of the mammalian circadian clock.
A chemical-biological approach is also effective at elucidating the basic processes that
underlie circadian clocks (90). Although performed on a relatively small scale, early studies revealed that several protein kinase inhibitors [such as IC261 (91, 92), CKI7 (93),lithium chloride (94, 95), SP600125 (92,96), SB203580 (97), DRB, LY294002, BML297, and SB202190 (98)], adenylate cyclase
inhibitors [such as THFA (9-tetrahydro-2furyl-denine), 2! 5! -dideoxyadonosine, and 9cyclopentyladenine (92)], and proteasome inhibitors [such as MG132 and lactacystin (91)]
can lengthen the period of mammalian circadian clocks by 2% to ∼40%. High-throughput
screening of a large chemical compound library
was also performed (89). The results showedthat the inhibition of glycogen synthase kinase 3 beta (GSK3β) shortens the period of
mammalian clock cells, superseding a previous
proposal about the function of GSK3β thatwas based on the period-lengthening effects
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of lithium (94, 95). This evidence supported
the use of a chemical-biological approach inprobing the fundamental processes of the mammalian circadian clock.
To systematically identify the fundamental processes involved in determining the period length of mammalian clocks, Isojima et al.
(99) tested 1260 pharmacologically active compounds for their effect on period length inmouse and human clock cell lines, NIH3T3
and U2OS, and found 10 compounds thatmost markedly lengthened the period of bothclock cell lines and affected both the central(SCN) and peripheral (mouse embryonic fibroblast) circadian clocks. Most compounds inhibited CKIε or CKIδ activity, and the siRNAknockdown of Csnk1e or Csnk1d exhibited great
period-lengthening effects—more than 28 h incircadian time (CT). Moreover, the combinatorial knockdown of Csnk1e and Csnk1d additively
lengthened the period of circadian oscillations
to over 30 h in CT, and high-dose pharmacological inhibition of the CKIε/δ activity lengthened the circadian (∼24-h) period to an almost circabidian (∼48-h) period (Figure 2b).
Inhibition of CKIε/δ activity led to deceleration of the PER2 degradation rate, which isregulated by CKIε-dependent phosphorylation(100). Moreover, the period length of the circadian oscillation is strongly correlated with the
PER2 stability under the administration of the
CKI inhibitor. These data suggest that CKIε/δdependent phosphorylation on the PER2 protein is an important period-determining process in the mammalian circadian clock.
As these studies have shown, both the perturbation of components’ quantity via cDNA,
siRNA, and chemical libraries and the perturbation of components’ quality (parameter change)
via functional genomics are important for theidentification of complex and dynamic biological systems, such as that of the mammalian circadian clock.

ANALYSIS OF CLOCKS
To derive the design principle of a system ofinterest, one must validate the behavior of aAnnu. Rev. Physiol. 2010.72:579-603. Downloaded from arjournals.annualreviews.org
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predicted system through an accurate measurement with several types of perturbations(system analysis). In this section, we describe
the quantitative analysis of identified perioddetermining biochemical reactions in the above
section, which is probably important for determining the temperature compensation of the
mammalian circadian clock.
A 24-h period that protects against environmental changes, such as in temperature and nutrition, is one of the most intriguing aspectsof the circadian clock. The robustness of thisprotection against temperature change isknown as temperature compensation. Typicalbiochemical reactions, such as enzymatic reactions, show temperature dependency, which isrepresented by a Q10 value of approximately
two. In contrast, the period of circadian rhythm
is independent of or compensated against temperature change (i.e., the Q10 value of the period is approximately one). The importanceof temperature compensation in poikilotherms
can be easily understood. This aspect of the
mammalian circadian clock had been controversial, but in 2003 it was confirmed in cultured
mammalian cells (101, 102). Temperature compensation has proved to be one of the generalcharacteristics of circadian clocks, appearing inspecies ranging from cyanobacteria to humans.
Despite our increasing knowledge of the molecular mechanism of circadian clocks, however, it
is difficult to explain how circadian clocks sustain such a constant period against temperaturechange.
To explain this phenomenon, theoreticalstudies (103, 104) have proposed a balanced reaction model (Figure 3a) in which (a) increasing kinetic parameters of some reactions in anegative feedback loop shorten the period and(b) other parameters prolong the period. If theperiod-accelerating and period-decelerating
reactions were equally sensitive to temperature, the frequency of the circadian oscillation
would increase with an increase in temperature.
To reconcile this issue, the balance reaction
model proposes that the period-accelerating
reaction(s) are less temperature sensitive thanthe period-decelerating reaction(s) and, hence,that these two sets of enzymatic reactions arebalanced to maintain a constant circadian oscillation. These theoretical explanations seemplausible, but the balance of effects on the period length between basic reactions can be easily broken by perturbations, such as inhibitors
and point mutations on clock proteins. Furthermore, these theoretical models are inconsistent
with the fact that many circadian clock mutants
show diverse periods but sustain temperaturecompensation. How do circadian clocks acquirerobustness against temperature change?
The circadian rhythm of KaiC (a circadianclock protein) phosphorylation can be reconstituted by only three Kai proteins, KaiA, KaiB,
and KaiC, in a test tube, demonstrating that thisrhythm is the central oscillator of the cyanobacterial circadian clock (72). In this test tube, theoscillation period of KaiC phosphorylation isunaffected by temperature change despite theoccurrence of biochemical reactions. This observation indicates that the robustness of circadian oscillation against temperature differencein cyanobacterial cells depends on the biochemical properties of three clock proteins. Although
the mechanism of the KaiC phosphorylation
cycle remains unclear, these findings suggest arobust reaction model (Figure 3a) for temperature compensation in circadian clocks, at leastin cyanobacteria.
Isojima et al. (99) demonstrated that CKIε/δ
activity on the PER2 protein is one of themost potent period-determining processes in
the mammalian circadian oscillator. If potent
period-determination processes were highly
sensitive to temperature, it would be very difficult, if not impossible, to maintain temperaturecompensation over the entire circadian period.
Thus, Isojima et al. (99) investigated the temperature dependency of this process in living
clock cells and found that (a) the degradation
rate of mPER2, which is regulated by CKIεdependent phosphorylation (100), and (b) the
period length were completely temperature insensitive in cellulo (Figure 3b,c). These findings imply that the period-determination process is remarkably robust against temperature
differences.
www.annualreviews.org • Systems Biology of Mammalian Clocks

Q10 : the change in therate of a process as aresult of increasing thetemperature by 10◦ C

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25°C

Step A

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Balanced reaction theory
Step B

Fast
Slow
RobustStep E Oscillator
Step C
Step D

Robust reaction theory

100

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Time (min)

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d

36

200

Pi incorporation(mol mol−1 CKI)c
Period Length (h)mPER2::LUC (%)

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150

24

12

25°C
35°C

100

27

32

Temperature (˚C)

37

50
0

0

50 100 150 200 250
Time (min)Figure 3
System analysis of clocks. (a) Two theoretical models of temperature compensation of the circadian clock.
Steps A through E indicate the basic molecular reactions of circadian clock components. In the balanced
reaction theory, increasing kinetic parameters of some basic reactions (magenta) shorten period, and those ofother basic reactions (blue) lead to prolonging the period. These effects are offset so that the period issustained. In the robust reaction model, such as the cyanobacterial circadian clock, temperaturecompensation of the circadian clock is caused by reactions of which kinetic parameters are independent( green). (b) The temperature dependency of decay for the mPER2::LUC bioluminescence in mPer2Luc
mouse embryonic fibroblasts (MEFs). The degradation of the mPER2::LUC protein was monitored after
the addition of cycloheximide to MEFs. The time-course data of each sample were normalized to an
approximate function in which time point zero was 100%. Each value represents the mean ± SEM (standard
error of the mean) of the normalized data. The lines represent an approximated curve in which y = 100 attime zero and y = 50 at the averaged half-life time. The blue dots and line indicate the data at 27◦ C, green
indicates 32◦ C, and magenta indicates 37◦ C (N = 23). (c) Temperature compensation in the period length ofmPer2Luc MEFs. The graph indicates the mean ± SEM. The gray broken line indicates the approximatedline described by the equation y = 19.02 + 0.097x, and the Q10 value between 27◦ C and 37◦ C calculated
from the equation is 0.957. (d ) Temperature dependency of the $CKIε(wt) phosphorylation activity for the
βTrCP-peptide substrate. Assays were performed at 25◦ C (blue) and 35◦ C (magenta). Abbreviations:$CKIε(wt), catalytic domain of wild-type (wt) casein kinase I epsilon (CKIε); Q10 , the change in the rate ofa process caused by increasing the temperature by 10◦ C; βTrCP, β-transducin repeats–containing protein.

To examine the biochemical foundation underlying the observed temperature insensitivity, Isojima et al. (99) analyzed the phosphorylation activity of CKIε and CKIδ in vitro.
They used synthetic peptide substrate derived from the putative β-transducin repeats–
containing protein (βTrCP)-binding region ofmouse PER2 and the catalytic domain of wildtype CKIε, lacking the C-terminal regulatory

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domain [$CKIε(wt)], to prevent the confusionthat could result from the autophosphorylationof this regulatory domain and the subsequent
repression of CKIε kinase activity. This use of
the catalytic domain was also justified by evidence that CKIε is kept in a dephosphorylated,
active state in vivo (105). Under this experimental condition, $CKIε(wt) phosphorylated the
peptide substrate at similar rates both at 25◦ C

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and at 35◦ C, indicating a strong temperature
insensitivity (Q10 = 1.0) (Figure 3d ). Similar temperature insensitivity was also observedwith $CKIδ(wt) at a Q10 of 1.2. However, theQ10 of $CKIε/δ(wt) activity for two clockunrelated substrates—casein, a conventional
protein substrate, and CK1tide, a commerciallyavailable peptide substrate for CKIε/δ, which
is a peptide substrate already phosphorylated at
two residues on the N terminus of the CKIε/δphosphorylation site—was 1.6 for casein and
1.4 for CK1tide. This finding indicates that thetemperature insensitivity depends substantiallyon the substrate. Earlier and Isojima et al.’sreports (99, 106) indicated that preincubating
full-length CKIε with ATP repressed CKIε enzymatic activity ∼15-fold and 8-fold at 25◦ C
and 35◦ C, respectively (99), probably as a resultof the autophosphorylation of the C-terminal
regulatory domain. Isojima et al. (99) investigated the effect of autophosphorylation of fulllength CKIε on temperature insensitivity; theirresults indicated that autophosphorylation increases temperature sensitivity, suggesting that
CKI-dependent phosphorylation can be temperature insensitive, depending both on thesubstrate and on the state of the enzyme. Moreover, the expression of exogenous full-length
mPER2 protein and the catalytic domain of
CKIε in NIH3T3 cells recapitulated the temperature insensitivity of degradation rate. On
the basis of these experimental data, Isojima
et al. (99) proposed that CKIε/δ-dependent
phosphorylation is probably a temperatureinsensitive period-determining process in the
mammalian circadian clock.
The evidence for the existence of atemperature-insensitive reaction in vitro and incellulo, with possible implications for temperature compensation in circadian clocks, suggests
the surprising capability of CKIε/δ-dependent
phosphorylation. Therefore, the remaining
challenge is to obtain the atomic resolution
model of this temperature-insensitive reaction.
In addition to the robustness of the circadian clock against temperature differences,mammalian circadian clocks also seem to haveadditional interesting dynamical characteristics. Recently, Dibner et al. (107) manipulated
the general transcriptional rates by using a specific inhibitor of RNA polymerases II and III;
they suggested that mammalian circadian oscillators are resilient to large fluctuations in general transcription rates. The authors also suggested that PER1 has an important function
in transcription compensation (107). As thesereports have shown, static perturbation of thesystem of interest and subsequent quantitative
measurements of its dynamics yield importantresults that will aid our understanding of thesystem.

Singularity:
the suppression of
circadian rhythms by acritical perturbation

CONTROL OF CLOCKS
System control aims to regulate the target system toward the desired state through the precise perturbation of its components. To achieve
this regulation, one must develop an assay system that can be controlled in a dynamic andquantitative manner.
The circadian clock is known to be entrainable by external cues such as light. Information
obtained from light is transmitted to the circadian clock through sensing mechanisms containing photoreceptors, and as a result of lightpulses the dynamics of the clock system change
drastically. In this section, we describe the intentional control of the oscillating clock system
in individual cultured cells via artificial lightsensing mechanisms (108, 109). We also explain
how Ukai et al. (108) and Pulivarthy et al. (109)independently applied this photoperturbation
system to a longstanding and unsolved biological phenomenon known as the singularity behavior of circadian clocks.
Circadian clocks exhibit various dynamic
properties, making them difficult to elucidate
without quantitative perturbation and precise
measurement of their dynamics. One of themost fundamental but still unsolved dynamical properties of circadian clocks is singularity
behavior, in which robust circadian rhythmicity
can be abolished after a certain critical stimulus,
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the appropriate timing and strength. Since thefirst report of singularity behavior in Drosophila
pseudoobscura by Winfree (110), circadian clock
singularities have been experimentally observedin various organisms, including unicells such
as Gonyaulax (111), Euglena (112), and Chlamydomonas (113); fungi (114); insects (115); plants(116, 117); and mammals (118, 119). This evidence suggests that this behavior is a sharedproperty of an extremely broad range of circadian clocks (4).
Although singularity behavior has been
widely observed, little is known about its underlying mechanisms. Because such behaviors
were experimentally observed at the multicell
level (i.e., the collective behavior of unicells or
the physiological or locomotor activity of multicellular organisms), two alternative singlecell-level mechanisms have been proposed to
explain their collapse to singularity: (a) arrhythmicity of individual clocks (Figure 4a) and(b) desynchronization of individual rhythmically oscillating clocks (Figure 4b) (115, 120).
In the former mechanism, individual clocks
become arrhythmic; that is, the amplitude of
the individual cells is substantially attenuatedby the application of the critical light pulse. In
contrast, in the latter mechanism of desynchronization, the phases of individual clocks arediversified by the critical light pulse. Althoughboth mechanisms can explain substantial
suppression of the multicell-level amplitude ofcircadian rhythm, the dynamical properties of
the two fundamentally differ: The oscillationsof individual cells are impaired in the arrhythmicity mechanism, whereas individual cells
maintain their oscillations in the desynchronization mechanism. Importantly, althoughmany researchers have observed multicell-levelsingularity behaviors in various organisms,
it remains unknown whether arrhythmicity
or desynchronization of individual clocks
underlies the singularity behavior of circadianclocks.
Determination of the underlying mechanism for singularity behaviors of circadianclocks may require adjustable perturbation,

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given that the ability of a critical stimulus todrive circadian clocks into singularity depends
on its timing and strength. Various stimuli,
such as reagents and temperature, have beenreported to directly reset mammalian cellular
clocks (7–9, 101, 121–126). Unfortunately, it isdifficult, although not impossible, for these factors to achieve the requisite flexibility in timing and strength. In contrast to perturbations
achieved by the use of reagents or temperaturechange, photoperturbation provides an ideal
range of adjustability in timing and strength.
Whereas most mammalian cells cannot senselight, recent studies showed that mammaliancells (specifically Neuro-2a and HEK293 cells)
become photoresponsive following the introduction of an exogenous Gαq protein–coupled
photoreceptor, melanopsin (also known as
Opn4 ) (127, 128). It was reported that photostimulation of melanopsin triggers a release of
intracellular calcium mediated through the Gαq
protein signaling pathway; importantly, there
are several reports that mammalian cellular
clocks can be reset by this pathway via a releaseof intracellular calcium (123, 124). These results suggest that melanopsin-dependent photoperturbation may enable the adjustable andquantitative perturbation of mammalian cellular clocks by changing intracellular calcium
levels.
To experimentally reveal the underlying
mechanism of the singularity behavior of
mammalian cells, Ukai et al. (108) synthetically implemented photoresponsive mammalian cells by exogenously introducing
melanopsin (Figure 4c). To continuously andquantitatively monitor the effect of photoperturbation on the state of cellular clocks, theauthors devised a high-throughput monitoring
system with a light-exposure unit. Using thissystem, Ukai et al. revealed that a critical lightpulse drives cellular clocks into a singularity behavior in which robust circadian rhythmicity
can be abolished after a certain stimulus. Theoretical analysis and subsequent single-celllevel observation consistently predicted anddirectly observed that desynchronization of

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b

Figure 4

Time (h)c
Circadian clock
Melanopsin

Photoinsensitive NIH3T3

b

Gaq
g

PIP2
DAG

PLCβ4

Synthetic implementation ofphotoresponsiveness
Melanopsin

IP3
Ca2+ stores
Ca2+

Circadian clock
PKC

Photoresponsive NIH3T3

individual cellular clocks underlies this singularity behavior. Ukai et al. (108) also constructed a theoretical framework to explain why
singularity behaviors have been experimentally

System control ofclocks. (a,b) Diagramsof two alternative
single-cell-levelmechanisms for
multicell-levelsingularity behavior.
(a) Arrhythmicity and(b) desynchronizationof individual cellular
clocks. (c) Synthetic
implementation ofphotoresponsivenesswithin mammalianclock cells. Schematic
representation ofmelanopsin-dependent
photoresponsive
NIH3T3 cells and the
known Gαq signaling
pathway.
Abbreviations: DAG,
diacylglycerol; IP3 ,inositol triphosphate;
PIP2 ,
phosphatidylinositol
4,5-bisphosphate;
PLCβ4, phospholipase
C beta 4; PKC,
protein kinase C.

observed in various organisms, and they proposed desynchronization as a plausible mechanism for the observable singularity of circadianclocks.
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In an independent study, Pulivarthy et al.
(109) implemented the same photoreceptor(Opn4 ) into the immortalized fibroblast derived from Per2LUC knockin mice and created
Per2LUC ;Opn4 cell lines. Using this cell line,
Pulivarthy et al. observed a 40% amplitude reduction of PER2::LUC bioluminescence levels
of individual cells under the experimental condition inducing singularity-like behavior. This
reduction had not been observed in Ukai et al.’s
study using Per2-Luc and Bmal1-Luc. However, Pulivarthy et al. and Ukai et al. simultaneously observed the remarkable desynchronization of individual cellular oscillations. Although
there are some differences between the twostudies, which could be due to different meansof readouts, each observed desynchronizationof individual cellular oscillations, which thus
seems to underlie the singularity behavior of
mammalian circadian clocks. Importantly, thesein cellulo and in silico findings are further supported by in vivo observations by Ukai et al.
(108) that desynchronization actually underlies
the multicell-level amplitude decrease in rat
SCN that is induced by the critical light pulses,
which in turn can predispose organisms’ locomotor activity to transient amplitude decrease.
To elucidate the underlying mechanism of
singularity behaviors, Winfree (115, 120) conducted a two-pulse experiment that revealed theunclocklike behavior of the circadian clock. In
this experiment, the critical light pulse inducing
the singularity behavior seemed to decrease theamplitude of the circadian clock without affecting its frequency. This finding seemed to contradict both the tenets of the simple limit-cycle
model and its prediction that arrhythmicity
underlies the singularity behavior. To explain
this unclocklike behavior, Winfree proposed
the so-called clockshop hypothesis, in which
an organism-level circadian clock consists ofmultiple circadian oscillators with substantial
fluctuations, and predicted that the desynchronization of individual circadian oscillators
underlie the singularity behavior (multicelllevel amplitude decrease). He was unable to test
this prediction, however, as there was no way toobserve single-cell-level circadian rhythmicity

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at that time (1975). The studies by Ukai
et al. (108) and Pulivarthy et al. (109) proved
Winfree’s prediction on the desynchronization,
at least in the mammalian circadian system,
more than 30 years after it was originallyproposed (120).

DESIGN OF CLOCKSThe final step in the systems-biological process is system design, the reconstruction anddesign of a dynamical system based on the design principles revealed through the efforts ofsystem identification, system analysis, and system control. In Escherichia coli, various dynamical systems, including the toggle switch (129),the repressilator (130), the metabolic oscillator (131), and the tunable oscillator (132), havebeen designed and implemented. Tigges et al.
(133) recently designed and implemented tunable oscillators in mammalian cells. Such a synthetic approach can be applied to a complex anddynamic system such as a mammalian circadianclock and will enhance its understanding. A synthetic approach is especially useful in validating the hypothesis derived from the identified
structure and observed dynamics.
A possible synthetic approach is to extend
the in cellulo cycling assay system describedabove (27) and utilize it as a physical simulator, which allows implementation of artificial transcriptional circuits to mimic transcriptional circuits of mammalian circadian clocks
and, hence, to test the design principles of natural systems. To this end, Ukai-Tadenuma et al.
(134) have developed an in cellulo system withwhich to validate the sufficiency of the components of a natural circadian phase-controllingmechanism. Alternatively, a more radical synthetic approach, such as an in vitro reconstruction of a mammalian circadian clock, could beundertaken. We describe these two synthetic
approaches in the following sections.

Design of Transcriptional Circuits
The network structure comprising clock genes
and CCEs has been comprehensively described.

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However, the dynamic principles governing
this transcriptional circuit remain elusive. A
key issue concerning the logic of the mammalian circadian clock is how the expression
peaks (phases) of circadian oscillating genes
are determined. To understand the molecular
logic of the phase-controlling system(s), UkaiTadenuma et al. (134) focused on the threemain CCEs: the E/E! -box, the D-box, and theRRE. The transcriptional activator DBP activates gene expression via the D-box, whereas
the transcriptional repressor E4BP4 represses
gene expression (Figure 2a). Dbp is regulatedby the E-box, the morning control element;
E4bp4, however, is regulated by the RRE, thenighttime control element. On the basis of
this transcriptional circuit information, the investigators hypothesized that a morning activator and a nighttime repressor determine
the daytime transcriptional output mediatedthrough the D-box. Similarly, RRE activators(e.g., Rorα) are expressed during the daytime
under the control of the D-box, and the RRE
repressors (e.g., RevErbα) seem to be strongly
influenced by a morning element (the E! -box;
Figure 2a). These observations led to the hypothesis that a daytime activator and a morning
repressor can specify the nighttime transcriptional output mediated through the RRE. To
test this hypothesis, Ukai-Tadenuma et al. (134)adopted a synthetic approach to physically simulate an identified structure, and they observed
the resulting dynamics through use of artificialtranscriptional circuits.
To design and implement artificial transcriptional circuits in mouse NIH3T3 cells, whichhave a self-oscillating circadian clock, UkaiTadenuma et al. (134) developed an in vitro cycling assay system composed of three components: (a) an artificial activator (a destabilized
GAL4-VP16 fusion protein, dGAL4-VP16),(b) an artificial repressor (a destabilized GAL4
protein, dGAL4), and (c) an output reporter
gene (dLuc) driven by a minimal TATA box
fused with four tandem repeats of the upstream
activator sequence (UAS; the GAL4-binding
sequence) (Figure 5a). Because the artificial activator and repressor are driven by the SV40

basic promoter fused with three tandem repeatsof CCEs, the expression timing of these artificial regulators is controlled via the morning (E! box), daytime (D-box), and nighttime (RRE) elements. The authors reasoned that if and only if
the phases of the transcriptional activator(s) andrepressor(s) are acceptable determinants of thephase of the downstream transcriptional output, then it should be possible to generate thenatural phases using synthetic transcriptional
regulators and promoters. If this proved to betrue, it would be very significant, as transcription factors are regulated by various posttranscriptional mechanisms—including translation,
phosphorylation, ubiquitination, sumoylation,and nuclear transportation—that are thought
to contribute at least in part to the controlof phases of the downstream transcriptional
outputs.
Using the in vitro cycling assay system as aphysical simulator, Ukai-Tadenuma et al. (134)tested the hypothesis for daytime output by
examining the dynamic behavior of the transcriptional output generated from the competition between an artificial morning activator
controlled via E! -box and a nighttime repressor
controlled via RRE. The phases of the activator and repressor in this experiment were detected at CT4.0 ± 0.29 (n = 2) and CT17.1 ±0.37 (n = 2). The transcriptional output driven
by these regulators exhibited circadian oscillation with a phase at CT7.7 ± 0.85 (n =2), which is very close (≤1.0 h) to the corresponding natural daytime (D-box) phase,CT8.7 ± 1.13 (Figure 5b). These results suggest that morning activation and nighttime repression are sufficient to determine the daytime transcriptional output. Importantly, highamplitude circadian oscillation was not observed when only the morning activator or only
the nighttime repressor was expressed. The authors concluded that both morning activationand nighttime repression are necessary for daytime output.
Moreover, the hypothesis for nighttime output was tested through examination of another artificial circuit consisting of an artificial
daytime activator under D-box control and a
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a

dGAL4
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CCE × 3 − SV40 promoter

Gal4-VP16-PEST

dGAL4

Artificial transcriptional repressor
Gal4-PEST

CCE × 3 − SV40 promoter

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Bioluminescence
Output from the artificial network

dGAL4
-VP16

dGAL4
Repression

dLuc

Activation

Luciferin+ATP
Luc-PESTUAS × 4 − CMV promoter
Artificial target promoterb

4.0
Morning

7.7

dGAL4
-VP16
Activation

Daytime

Repression
dGAL4

c

3.9

8.9

Morning

Daytime

Repression

Activation

dGAL4
-VP16

dGAL4

Nighttime

Nighttime

17.1

16.6

Figure 5
System design of clocks. (a) The artificial transcriptional system. dGAL4-VP16 and dGAL4 were used as theactivator and the repressor, respectively. These transcriptional factors were expressed under the control ofthree tandem repeats of a clock-controlled element (CCE): the E! -box of Per2, the D-box of Per3, and theRRE (RevErbA/ROR-binding element) of Bmal1. The artificial activator and repressor competitively bindthe four tandem repeats of the upstream activator sequences (UAS) in the artificial promoter to regulate theoutput reporter gene dLuc. NIH3T3 cells were transiently transfected with plasmids harboring the activator,
repressor, or reporter, and the reporter activity was monitored under a real-time bioluminescence-measuringsystem, which allowed observation of this artificial circuit’s dynamic behavior. (b and c) Proof by synthesis ofdaytime and nighttime transcriptional regulations. Synthesis of (b) daytime and (c) nighttime expressions
from two different artificial transcriptional circuits: (b) the morning activator under E! -box control and thenighttime repressor under RRE control and (c) the daytime activator under D-box control and the morning
repressor under E! -box control. The schemes summarize the timing of the peaks (i.e., phases) of promoter
activity. The activator ( green oval and arrow), repressor (magenta oval and arrow), and output reporter are
indicated with their phases in circadian time (numbers).
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morning repressor under E! -box control. The
phases of the transcriptional activator and repressor in this experiment were at CT8.9 ±0.28 (n = 2) and CT3.9 ± 0.13 (n = 2). The
transcriptional output driven by the regulators
exhibited circadian oscillation with a phase at
CT16.6 ± 1.04 (n = 2), which is very close(≤1.0 h) to the corresponding natural nighttime
phase (CT17.0 ± 0.81) (Figure 5c). These results also suggest that daytime activation andmorning repression are necessary and sufficient to generate the circadian nighttime output, which implies that the input phases of transcriptional regulators can determine the phasesof transcriptional output. These findings led tothe idea that various combinations of transcriptional regulators with CCEs for the three basic
circadian phases (morning, daytime, and nighttime) may generate not only the basic phases but
also other phases. Indeed, Ukai-Tadenuma et al.
(134) succeeded in generating various phasesthough simple combinations of the transcriptional regulators of the three basic circadianphases.
These experiments showed that the transcriptional regulation of upstream transcription factors can determine the phase of thedownstream output. This study presents a synthetic approach to the proof by synthesis oftranscriptional logic, which provides us witha new strategy with which to (a) investigate
the requirements for identified components
and/or their interactions and (b) reveal asyet-unidentified components or interactions.
For example, although the authors successfully (re)generated two basic phases, daytime
and nighttime—as well as additional phases
near the subjective noon, dawn, dusk, and latenight—from the three basic circadian phases,
we have not yet been able to regenerate the basic morning phase, which is expected to be regulated directly or indirectly by the three basic
phases to maintain circadian oscillations. Thus,
morning transcriptional regulation remains a
missing link in the mammalian clock system.
Given that a strong repressor at evening phaseseems indispensable to the reconstruction of themorning phase, a candidate transcription factor could be CRY1, a transcriptional repressor expressed during the evening. However,
the expression-regulation mechanism of theCry1 gene remains unknown at present because
more than one DNA element seems to be involved in this expression. Hence, the challengeof synthesizing evening and morning expression, as we work toward the complete reconstruction of the transcriptional circuits underlying mammalian circadian clocks, remains to besolved.

Reconstitution of
Posttranscriptional Circuits
In the preceding section, we described the design of the transcriptional circuits of the mammalian circadian clock. The proof by synthesisof transcriptional circuits is useful because transcriptional feedback repression is important forcircadian clock function, as we discussed in thesection entitled The Role of Negative Feedback. However, the period length of circadianclock is largely determined by posttranscriptional circuits, as we discussed in the section entitled The Identification of the Rate-Limiting
Process. Therefore, synthetic approaches basedon biochemistry toward posttranscriptional circuits will be necessary for attaining a complete understanding of the mammalian circadian clock. Among such synthetic approaches,
one of the most radical and fundamental isto perform an in vitro reconstruction, fromscratch, of the mammalian circadian clock.
Indeed, biochemical studies on the circadianclock of cyanobacteria, the simplest organisms
to possess such a clock, revealed the sufficiencyof posttranscriptional circuits in the circadianclock (72). Interestingly, although ubiquitous
molecular behaviors concerning the circadianclock, such as negative feedback regulationof clock genes, circadian oscillation of accumulation of RNA and clock proteins, andphosphorylation of clock proteins, are observedin cyanobacteria, the robust circadian oscillation of the phosphorylation state of KaiC waswww.annualreviews.org • Systems Biology of Mammalian Clocks

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reconstituted via a mixture of only three
cyanobacterial clock proteins and ATP in a test
tube (72). The circadian oscillation of KaiC
phosphorylation was therefore demonstrated
to be the central oscillator of the cyanobacterial circadian clock. This elegant study on
the cyanobacterial circadian clock evoked theimportance of using a biochemical approachto the circadian clock to answer fundamental questions, such as those of autonomous
oscillation and temperature compensation.
As described in the section entitled Identification of Clocks, the clock-related genes
have been comprehensively identified in mammals, as well as in other model organisms such
as Drosophila and Neurosphora (3, 4, 70, 71).
Furthermore, Isojima et al. (99) have discovered that CKIε/δ-dependent phosphorylation
exhibits temperature insensitivity in vitro, as do
cyanobacteria (72). Although it is not known
whether a temperature-insensitive reverse reaction (i.e., dephosphorylation) exists in the mammalian circadian clock, its discovery would be agreat step toward the complete reconstructionof the autonomous oscillator in the mammalian
circadian clock.
Synthetic approaches based on cell biology
and biochemistry can validate the sufficiencyof transcriptional and posttranscriptional circuits for the dynamical property of interest. Following these approaches will lead to a deeper
understanding of the design principles of the
mammalian circadian clock.

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PERSPECTIVESIn this review, we focused primarily on the intracellular mechanisms of the mammalian circadian clock. However, the mammalian circadian system is organized in a hierarchy ofcellular oscillators and exhibits various intercellular dynamical properties derived from
populations of clock cells. One example ofsuch a property is singularity behavior (desynchronization of multiple circadian clock cells),
discussed in the section entitled Analysis of
Clocks. Other examples, which are not discussed herein, include the synchronization of
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multiple clock cells within the SCN (135–137) as well as the intertissue hierarchical coupling between master clock (SCN) and slave(peripheral) clocks (3, 138).
Synchronization of multiple clock cells
within the SCN is one of the most importantcharacteristics that distinguish the SCN fromperipheral clocks. Coherent circadian rhythms,
probably due to intercellular couplings of individual clock cells in the SCN, are generated
in the SCN (135–137). Interestingly, not only
are intercellular interactions among individual
clock cells in the SCN important for the coupling of multiple circadian oscillators, they arealso necessary for maintaining self-sustained
circadian oscillations of individual clock cells(135). Indeed, self-sustained oscillations of individual cells in the SCN are highly sensitive tointercellular neural communications (135) andcAMP signaling (92). Furthermore, these intercellular coupling–dependent self-sustained oscillations within the SCN seem able to rescue
the molecular defects of individual clock cells.
For example, Liu et al. (139) recently discovered that Per1 and Cry1 are required for selfsustainable oscillations in peripheral clock cells
and in neurons dissociated from the SCN. The
authors also found that intercellular couplingsin the SCN can compensate for those molecular
deficiency.
Intercellular communications in the mammalian clock system are not limited to thesynchronization of clock cells in the SCN.
Intertissue hierarchical coupling between
master clock (SCN) and slave clocks plays
an important role in generation orchestrated
circadian oscillations throughout the body. In
fact, Kornmann et al. (140) discovered—under
the condition that transcription of the essential
core clock gene Bmal1 is repressed in liver—that 31 genes, including core clock gene Per2,
exhibited robust circadian oscillations irrespective of whether the liver clock was running.
In contrast, in liver explants cultured in vitro,
circadian cycles of Per2 were only observed
when hepatocyte oscillators were operational.
These findings indicate that circadian oscillations of gene expression observed in the liverAnnu. Rev. Physiol. 2010.72:579-603. Downloaded from arjournals.annualreviews.org
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of intact animals without functional hepatocyte
oscillations are driven by systemic cues.
These intercellular dynamical properties
would be difficult to understand without
systems-biological approaches and techniquessuch as tissue-specific, conditional, and quantitative perturbation and subsequent quantitative
measurement. Kornmann et al. adopted suchconditional perturbation technique, in which
REVERBa is conditionally overexpressed andrepresses the transcription of Bmal1 in a
doxycycline-dependent manner. Integrative research that makes use of quantitative perturbations with high spatial and temporal resolutions, quantitative measurements with highaccuracy, and appropriate theoretical analysis
will enable us to elucidate unsolved systemslevel questions about complex and dynamic
phenomena.

CONCLUSION
Following identification of key clock genes, demand for a higher-order understanding of thedesign principles of the mammalian circadianclock has increased. In this review we have described several steps, beginning with comprehensive identification of clock components andtheir networked interactions (system identification) and quantitative analysis (system analysis) of temperature-insensitive reactions andleading to the ability to control existing systems toward the desired state (system control)
and to design new systems according to an understanding of structure and underlying dynamical principles (system design). We strongly
believe that it is time to fully integrate thesesystems-biological approaches to solve systemlevel questions.

SUMMARY POINTS
1. Systems biology can be defined as biology after identification of key gene(s) and contains
four steps: system identification, system analysis, system control, and system design.
2. System identification refers to identification of the whole network structure throughfunctional genomics and comparative genomics.
3. System analysis involves prediction and validation to derive the design principle throughthe accurate measurement and (static) perturbation of network dynamics.
4. System control involves repair and control of the network state so as to achieve thedesired state through the precise perturbation of its components.
5. System design refers to the reconstruction and design of systems according to the designprinciples derived from the identified structure and observed dynamics.

DISCLOSURE STATEMENT
The authors are not aware of any affiliations, memberships, funding, or financial holdings thatmight be perceived as affecting the objectivity of this review.

ACKNOWLEDGMENTS
This work is supported by an intramural grant-in-aid from the RIKEN Center for Developmental Biology (CDB); an intramural grant-in-aid from the Genomic Science Center, RIKEN;
the Director’s Fund from CDB; RIKEN Strategic Programs; the RIKEN Research Collaborations with Industry Program; the National Project on Protein Structural and Functional Analyses;
a Genome Network Project grant from the Japanese Ministry of Education, Culture, Sports,
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Science and Technology; KAKENHI (grant-in-aid for Scientific Research) on Priority Areas Systems Genomics from the Ministry of Education, Culture, Sports, Science and Technology ofJapan; a research and development project of the Industrial Science and Technology Programfrom the New Energy and Industrial Technology Development Organization (NEDO); a grantin-aid for scientific research on “Development of Basic Technology to Control Biological Systems
Using Chemical Compounds” from the NEDO; a grant-in-aid for strategic programs in researchand development from the Institute of Physical and Chemical Research; a grant-in-aid from the
Uehara Memorial Foundation; and research fellowship number 17-4169 of the Japan Society for
the Promotion of Science for Young Scientists.
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Contents

Annual Review ofPhysiology
Volume 72, 2010

PERSPECTIVES, David Julius, Editor
A Conversation with Rita Levi-Montalcini
Moses V. Chao ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 1

CARDIOVASCULAR PHYSIOLOGY, Jeffrey Robbins, Section Editor

Protein Conformation–Based Disease: Getting to the Heart of the
MatterDavid Terrell and Jeffrey Robbins ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !15
Cell Death in the Pathogenesis of Heart Disease: Mechanisms andSignificanceRussell S. Whelan, Vladimir Kaplinskiy, and Richard N. Kitsis ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !19
Autophagy During Cardiac Stress: Joys and Frustrations of Autophagy
Roberta A. Gottlieb and Robert M. Mentzer, Jr. ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !45
The Cardiac Mitochondrion: Nexus of Stress
Christopher P. Baines ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !61
The FoxO Family in Cardiac Function and Dysfunction
Sarah M. Ronnebaum and Cam Patterson ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !81
CELL PHYSIOLOGY, David E. Clapham, Associate and Section Editor

Chloride Channels: Often Enigmatic, Rarely Predictable
Charity Duran, Christopher H. Thompson, Qinghuan Xiao, and H. Criss Hartzell ! ! ! ! !95

ECOLOGICAL, EVOLUTIONARY, AND COMPARATIVE PHYSIOLOGY,
Martin E. Feder, Section Editor

Physiology and Global Climate Change
Martin E. Feder ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 123
Living in the Now: Physiological Mechanisms to Tolerate a
Rapidly Changing Environment
Gretchen E. Hofmann and Anne E. Todgham ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 127vii

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Light, Time, and the Physiology of Biotic Response to Rapid Climate
Change in Animals
William E. Bradshaw and Christina M. Holzapfel ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 147
Locomotion in Response to Shifting Climate Zones: Not So Fast
Martin E. Feder, Theodore Garland, Jr., James H. Marden, and Anthony J. Zera ! ! ! ! 167
ENDOCRINOLOGY, Holly A. Ingraham, Section Editor

Genomic Analyses of Hormone Signaling and Gene Regulation
Edwin Cheung and W. Lee Kraus ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 191

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Macrophages, Inflammation, and Insulin ResistanceJerrold M. Olefsky and Christopher K. Glass ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 219

Structural Overview of the Nuclear Receptor Superfamily: Insights
into Physiology and Therapeutics
Pengxiang Huang, Vikas Chandra, and Fraydoon Rastinejad ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 247
GASTROINTESTINAL PHYSIOLOGY, James M. Anderson, Section Editor

Apical Recycling of the Gastric Parietal Cell H,K-ATPaseJohn G. Forte and Lixin Zhu ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 273
Role of Colonic Short-Chain Fatty Acid Transport in Diarrhea
Henry J. Binder ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 297
The Biogenesis of Chylomicrons
Charles M. Mansbach and Shadab A. Siddiqi ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 315
NEUROPHYSIOLOGY, Roger Nicoll, Section Editor

Integrated Brain Circuits: Astrocytic Networks Modulate Neuronal
Activity and Behavior
Michael M. Halassa and Philip G. Haydon ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 335

RENAL AND ELECTROLYTE PHYSIOLOGY, Gerhard H. Giebisch, Section Editor
Cellular Maintenance and Repair of the Kidney
Jian-Kan Guo and Lloyd G. Cantley ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 357
Intrarenal Purinergic Signaling in the Control of Renal Tubular
Transport
Helle A. Praetorius and Jens Leipziger ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 377
The Physiological Significance of the Cardiotonic
Steroid/Ouabain-Binding Site of the Na,K-ATPase
Jerry B Lingrel ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 395

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RESPIRATORY PHYSIOLOGY, Richard C. Boucher, Jr., Section Editor
Inducible Innate Resistance of Lung Epithelium to Infection
Scott E. Evans, Yi Xu, Michael J. Tuvim, and Burton F. Dickey ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 413

Annu. Rev. Physiol. 2010.72:579-603. Downloaded from arjournals.annualreviews.org
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It’s Not All Smooth Muscle: Non-Smooth-Muscle Elements inControl of Resistance to Airflow
Ynuk Bossé, Erik P. Riesenfeld, Peter D. Paré, and Charles G. Irvin ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 437
Regulation of Endothelial Permeability via Paracellular andTranscellular Transport Pathways
Yulia Komarova and Asrar B. Malik ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 463

TH 17 Cells in Asthma and COPD
John F. Alcorn, Christopher R. Crowe, and Jay K. Kolls ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 495
SPECIAL TOPIC, CELLULAR AND MOLECULAR MECHANISMS
OF CIRCADIAN CLOCKS IN ANIMALS, Joseph S. Takahashi, Special Topic Editor

The Mammalian Circadian Timing System: Organization and
Coordination of Central and Peripheral Clocks
Charna Dibner, Ueli Schibler, and Urs Albrecht ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 517
Suprachiasmatic Nucleus: Cell Autonomy and Network Properties
David K. Welsh, Joseph S. Takahashi, and Steve A. Kay ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 551
Systems Biology of Mammalian Circadian Clocks
Hideki Ukai and Hiroki R. Ueda ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 579
Circadian Organization of Behavior and Physiology in Drosophila
Ravi Allada and Brian Y. Chung ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 605
Mammalian Per-Arnt-Sim Proteins in Environmental Adaptation
Brian E. McIntosh, John B. Hogenesch, and Christopher A. Bradfield ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 625
IndexesCumulative Index of Contributing Authors, Volumes 68–72 ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 647
Cumulative Index of Chapter Titles, Volumes 68–72 ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 650
ErrataAn online log of corrections to Annual Review of Physiology articles may be found at
http://physiol.annualreviews.org/errata.shtml

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