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| ===Dense overlapping regulons (DOR)=== | | ===Dense overlapping regulons (DOR)=== |
| This motif occurs in the case that several regulators combinatorially control a set of genes with diverse regulatory combinations. This motif was found in ''[[Escherichia coli|E. coli]]'' in various systems such as carbon utilization, anaerobic growth, stress response and others.<ref name="she1"/><ref name="boy1"/> In order to better understand the function of this motif one has to obtain more information about the way the multiple inputs are integrated by the genes. Kaplan ''et al.''<ref name="kap2">{{cite journal |vauthors=Kaplan S, Bren A, Zaslaver A, Dekel E, Alon U |title=Diverse two-dimensional input functions control bacterial sugar genes |journal=Mol. Cell |volume=29 |issue=6 |pages=786–92 |date=March 2008 |pmid=18374652 |pmc=2366073 |doi=10.1016/j.molcel.2008.01.021 }}</ref> has mapped the input functions of the sugar utilization genes in ''[[Escherichia coli|E. coli]]'', showing diverse shapes. | | This motif occurs in the case that several regulators combinatorially control a set of genes with diverse regulatory combinations. This motif was found in ''[[Escherichia coli|E. coli]]'' in various systems such as carbon utilization, anaerobic growth, stress response and others.<ref name="she1"/><ref name="boy1"/> In order to better understand the function of this motif one has to obtain more information about the way the multiple inputs are integrated by the genes. Kaplan ''et al.''<ref name="kap2">{{cite journal |vauthors=Kaplan S, Bren A, Zaslaver A, Dekel E, Alon U |title=Diverse two-dimensional input functions control bacterial sugar genes |journal=Mol. Cell |volume=29 |issue=6 |pages=786–92 |date=March 2008 |pmid=18374652 |pmc=2366073 |doi=10.1016/j.molcel.2008.01.021 }}</ref> has mapped the input functions of the sugar utilization genes in ''[[Escherichia coli|E. coli]]'', showing diverse shapes. |
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| + | ==完善的模体及其功能== |
| + | 许多实验工作致力于理解[[基因调控网络]]中的网络模体。在响应生物信号的过程中,这些网络控制细胞中的哪些基因来表达。这样的网络以基因作为节点,有向边代表对某个基因的调控,基因调控通过其他基因编码的转录因[[结合在DNA上的调控蛋白]]子来实现。因此,网络模体是基因之间相互调控转录速率的模式。在分析转录调控网络的时候,人们发现相同的网络模体在不同的物种中不断地出现,从细菌到人类。例如,''[[大肠杆菌]]''和酵母的转录网络由三种主要的网络模体家族组成,它们可以构建几乎整个网络。主要的假设是在进化的过程中,网络模体是被以收敛的方式独立选择出来的。<ref name="bab1">{{cite journal |vauthors=Babu MM, Luscombe NM, Aravind L, Gerstein M, Teichmann SA |title=Structure and evolution of transcriptional regulatory networks |journal=Current Opinion in Structural Biology |volume=14 |issue=3 |pages=283–91 |date=June 2004 |pmid=15193307 |doi=10.1016/j.sbi.2004.05.004 |citeseerx=10.1.1.471.9692 }}</ref><ref name="con1">{{cite journal |vauthors=Conant GC, Wagner A |title=Convergent evolution of gene circuits |journal=Nat. Genet. |volume=34 |issue=3 |pages=264–6 |date=July 2003 |pmid=12819781 |doi=10.1038/ng1181}}</ref> 因为相对于基因改变的速率,转录相互作用产生和消失的时间尺度在进化上是很快的。<ref name="bab1"/><ref name="con1"/><ref name="dek1">{{cite journal |vauthors=Dekel E, Alon U |title=Optimality and evolutionary tuning of the expression level of a protein |journal=Nature |volume=436 |issue=7050 |pages=588–92 |date=July 2005 |pmid=16049495 |doi=10.1038/nature03842 |bibcode=2005Natur.436..588D }}</ref> 此外,对活细胞中网络模体所产生的动力学行为的实验表明,它们具有典型的动力学功能。这表明,网络模体是基因调控网络中对生物体有益的基本单元。 |
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| + | 一些研究从理论和实验两方面探讨和论证了转录网络中与共同网络模体相关的功能。下面是一些最常见的网络模体及其相关功能。 |
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| + | ===负自反馈调控(NAR)=== |
| + | [[Image:Autoregulation motif.png|thumb|Schematic representation of an auto-regulation motif]] |
| + | 负自反馈调控是[[大肠杆菌]]中最简单和最冗余的网络模体之一,其中一个转录因子抑制它自身的转录。这种网络模体有两个重要的功能,其中第一个是加速响应。人们发现在实验和理论上, <ref name="zab1">{{cite journal |doi=10.1016/j.jtbi.2011.06.021 |author=Zabet NR |title=Negative feedback and physical limits of genes |journal=Journal of Theoretical Biology |volume= 284|issue=1 |pages=82–91 |date=September 2011 |pmid=21723295 |arxiv=1408.1869 |citeseerx=10.1.1.759.5418 }}</ref>NAR都可以加快对信号的响应。这个功能首先在一个人工合成的转录网络中被发现,<ref name="ros1">{{cite journal |doi=10.1016/S0022-2836(02)00994-4 |vauthors=Rosenfeld N, Elowitz MB, Alon U |title=Negative autoregulation speeds the response times of transcription networks |journal=J. Mol. Biol. |volume=323 |issue=5 |pages=785–93 |date=November 2002 |pmid=12417193 |citeseerx=10.1.1.126.2604 }}</ref> 然后在大肠杆菌SOS DAN修复系统这个自然体系中也被发现。<ref name="cam1">{{cite journal |vauthors=Camas FM, Blázquez J, Poyatos JF |title=Autogenous and nonautogenous control of response in a genetic network |journal=Proc. Natl. Acad. Sci. U.S.A. |volume=103 |issue=34 |pages=12718–23 |date=August 2006 |pmid=16908855 |pmc=1568915 |doi=10.1073/pnas.0602119103 |bibcode=2006PNAS..10312718C }}</ref> 自负反馈网络的第二个功能是增强自调控基因的产物浓度的稳定性,从而抵抗随机的噪声,减少该蛋白含量在不同细胞中的差异。<ref name="bec1">{{cite journal |vauthors=Becskei A, Serrano L |title=Engineering stability in gene networks by autoregulation |journal=Nature |volume=405 |issue=6786 |pages=590–3 |date=June 2000 |pmid=10850721 |doi=10.1038/35014651}}</ref><ref name="dub1">{{cite journal |vauthors=Dublanche Y, Michalodimitrakis K, Kümmerer N, Foglierini M, Serrano L |title=Noise in transcription negative feedback loops: simulation and experimental analysis |journal=Mol. Syst. Biol. |volume=2 |pages=41 |year=2006 |pmid=16883354 |pmc=1681513 |doi=10.1038/msb4100081 |issue=1}}</ref><ref name="shi1">{{cite journal |vauthors=Shimoga V, White J, Li Y, Sontag E, Bleris L |title= Synthetic mammalian transgene negative autoregulation |journal=Mol. Syst. Biol. |volume=9 |pages=670 |year=2013|doi=10.1038/msb.2013.27|pmid= 23736683 |pmc= 3964311 }}</ref> |
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| + | ===正自反馈调控(PAR)=== |
| + | 正自反馈调控是指转录因子增强它自身转录速率的调控。和负自反馈调节相反,NAR模体相对于简单的调控能够延长反应时间。<ref name="mae1">{{cite journal |vauthors=Maeda YT, Sano M |title=Regulatory dynamics of synthetic gene networks with positive feedback |journal=J. Mol. Biol. |volume=359 |issue=4 |pages=1107–24 |date=June 2006 |pmid=16701695 |doi=10.1016/j.jmb.2006.03.064 }}</ref> 在强PAR的情况下,模体可能导致蛋白质水平在细胞群中呈现双峰分布。<ref name="bec2">{{cite journal |vauthors=Becskei A, Séraphin B, Serrano L |title=Positive feedback in eukaryotic gene networks: cell differentiation by graded to binary response conversion |journal=EMBO J. |volume=20 |issue=10 |pages=2528–35 |date=May 2001 |pmid=11350942 |pmc=125456 |doi=10.1093/emboj/20.10.2528}}</ref> |
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| + | ===前馈回路 (FFL)=== |
| + | [[Image:Feed-forward motif.GIF|thumb|Schematic representation of a Feed-forward motif]] |
| + | 前馈回路普遍存在于许多基因系统和生物体中。这种模体包括三个基因以及三个相互作用。目标基因C被两个转录因子(TFs)A和B调控,并且TF B同时被TF A调控。由于每个调控相互作用可以是正的或者负的,所以总共可能有八种类型的FFL模体。<ref name="man1">{{cite journal |vauthors=Mangan S, Alon U |title=Structure and function of the feed-forward loop network motif |journal=Proc. Natl. Acad. Sci. U.S.A. |volume=100 |issue=21 |pages=11980–5 |date=October 2003 |pmid=14530388 |pmc=218699 |doi=10.1073/pnas.2133841100 |bibcode=2003PNAS..10011980M }}</ref> 其中的两种:一致前馈回路的类型一(C1-FFL)(所有相互作用都是正的)和不一致前馈回路的类型一(I1-FFL)(A激活C和B,B抑制C)在[[大肠杆菌]]和酵母中相比于其他六种更频繁的出现。<ref name="man1"/><ref name="ma1">{{cite journal |vauthors=Ma HW, Kumar B, Ditges U, Gunzer F, Buer J, Zeng AP |title=An extended transcriptional regulatory network of ''Escherichia coli'' and analysis of its hierarchical structure and network motifs |journal=Nucleic Acids Res. |volume=32 |issue=22 |pages=6643–9 |year=2004 |pmid=15604458 |pmc=545451 |doi=10.1093/nar/gkh1009 |url=http://nar.oxfordjournals.org/cgi/pmidlookup?view=long&pmid=15604458}}</ref> 除了网络的结构外,还应该考虑来自A和B的信号被C的启动子集成的方式。在大多数情况下,FFL要么是一个与门(激活C需要A和B),要么是或门(激活C需要A或B),但也可以是其他输入函数。 |
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| + | ===一致前馈回路类型一(C1-FFL)=== |
| + | 具有与门的C1-FFL有“符号-敏感延迟”单元和持久性探测器的功能,这一点在[[大肠杆菌]]阿拉伯糖系系统的理论<ref name="man1"/>和实验上<ref name="man2">{{cite journal |doi=10.1016/j.jmb.2003.09.049 |vauthors=Mangan S, Zaslaver A, Alon U |title=The coherent feedforward loop serves as a sign-sensitive delay element in transcription networks |journal=J. Mol. Biol. |volume=334 |issue=2 |pages=197–204 |date=November 2003 |pmid=14607112 |citeseerx=10.1.1.110.4629 }}</ref> 都有发现。这意味着该模体可以提供脉冲过滤,短脉冲信号不会产生响应,而持久信号在短延迟后会产生响应。当持久脉冲结束时,输出的关闭将很快。与此相反的行为出现在具有快速响应和延迟关闭特性的加和门的情况下,这在[[大肠杆菌]]的鞭毛系统中得到了证明。<ref name="kal1">{{cite journal |vauthors=Kalir S, Mangan S, Alon U |title=A coherent feed-forward loop with a SUM input function prolongs flagella expression in ''Escherichia coli'' |journal=Mol. Syst. Biol. |volume=1 |pages=E1–E6 |year=2005 |pmid=16729041 |pmc=1681456 |doi=10.1038/msb4100010 |issue=1}}</ref>在[[基因调控网络]]的重头进化中,对于滤除理想化的短信号脉冲作为进化压,C1-FFLs已经在计算上被证明可以进化出来。但是对于非理想化的噪声,不同拓扑结构前馈调节的动态系统将被优先考虑。 <ref>{{cite journal |last1=Xiong |first1=Kun |last2=Lancaster |first2=Alex K. |last3=Siegal |first3=Mark L. |last4=Masel |first4=Joanna |title=Feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise |journal=Nature Communications |date=3 June 2019 |volume=10 |issue=1 |pages=2418 |doi=10.1038/s41467-019-10388-6|pmid=31160574 |pmc=6546794 }}</ref> |
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| + | ===非一致前馈回路类型一(I1-FFL)=== |
| + | I1-FFL是一个脉冲生成器和响应加速器。I1-FFL的两种信号通路作用方向相反,一种通路激活Z,而另一种抑制Z。完全的抑制会导致类似脉冲的动力学行为。另外有实验证明,它可以类似于NAR模体起到响应加速器的作用。与NAR模体的不同之处在于,它可以加速任何基因的响应,而不必是转录因子。<ref name="man3">{{cite journal |vauthors=Mangan S, Itzkovitz S, Zaslaver A, Alon U |title=The incoherent feed-forward loop accelerates the response-time of the gal system of ''Escherichia coli'' |journal=J. Mol. Biol. |volume=356 |issue=5 |pages=1073–81 |date=March 2006 |pmid=16406067 |doi=10.1016/j.jmb.2005.12.003 |citeseerx=10.1.1.184.8360 }}</ref>I1-FFL网络还有另外一个功能:在理论和实验上都有证明I1-FFL可以生成非单调的输入函数,无论在人工合成的<ref name="ent1">{{cite journal |vauthors=Entus R, Aufderheide B, Sauro HM |title=Design and implementation of three incoherent feed-forward motif based biological concentration sensors |journal=Syst Synth Biol |volume=1 |issue=3 |pages=119–28 |date=August 2007 |pmid=19003446 |pmc=2398716 |doi=10.1007/s11693-007-9008-6 }}</ref>还是自然的系统中。 <ref name="kap1">{{cite journal |vauthors=Kaplan S, Bren A, Dekel E, Alon U |title=The incoherent feed-forward loop can generate non-monotonic input functions for genes |journal=Mol. Syst. Biol. |volume=4 |pages=203 |year=2008 |pmid=18628744 |pmc=2516365 |doi=10.1038/msb.2008.43 |issue=1}}</ref> 最后,包含非一致前馈调控的基因生成物的表达单元对DNA模板的数量具有适应性,可以优于简单的组合本构启动子。<ref name="ble1">{{cite journal |vauthors=Bleris L, Xie Z, Glass D, Adadey A, Sontag E, Benenson Y |title=Synthetic incoherent feedforward circuits show adaptation to the amount of their genetic template |journal=Mol. Syst. Biol. |volume=7 |pages=519|year=2011 |doi=10.1038/msb.2011.49 |issue=1 |pmid=21811230 |pmc=3202791}}</ref> 前馈调控比负反馈具有更好的适应性,并且基于RNA干扰的网络对DNA模板数具有最高的鲁棒性。<ref name="ble1"/> |
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| + | ===多输出前馈回路=== |
| + | 在某些情况,相同的调控子X和Y可以调控同一系统中的多个Z基因。通过调节相互作用的强度,这些网络可以决定基因激活的时间顺序。这一点在[[大肠杆菌]]的鞭毛系统中有实验证据。<ref name="kal2">{{cite journal |vauthors=Kalir S, McClure J, Pabbaraju K, etal |title=Ordering genes in a flagella pathway by analysis of expression kinetics from living bacteria |journal=Science |volume=292 |issue=5524 |pages=2080–3 |date=June 2001 |pmid=11408658 |doi=10.1126/science.1058758 }}</ref> |
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| + | ===单一输入模块(SIM)=== |
| + | 当单个调控子调控一组基因,并且没有其他的调控因素时,这样的模体叫做单一输入模块(SIM)。当很多基因合作执行某个功能时这是有用的,因为这些基因需要同步地被激活。通过调节相互作用的强度,可以编排它所调控的基因表达的时间顺序。<ref name="zas1">{{cite journal |vauthors=Zaslaver A, Mayo AE, Rosenberg R, etal |title=Just-in-time transcription program in metabolic pathways |journal=Nat. Genet. |volume=36 |issue=5 |pages=486–91 |date=May 2004 |pmid=15107854 |doi=10.1038/ng1348|doi-access=free }}</ref> |
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| + | 在文献中,多输入模块(MIM)来自于SIM的扩展。但是二者的精确定义并不太一致。有一些尝试给出生物网络中规范模体的正交定义,也有一些算法去枚举它们,特别是SIM,MIM和2x2 MIM等。<ref>{{cite journal |vauthors=Konagurthu AS, Lesk AM |title=Single and Multiple Input Modules in regulatory networks |journal=Proteins |volume=73 |issue=2 |pages=320–324 |year=2008 |doi=10.1002/prot.22053|pmid=18433061 }}</ref> |
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| + | ===密集交盖调节网(DOR)=== |
| + | 这种类型的网络存在于多个调节子结合起来控制一组基因的情形,并且有多种调控的组合。这种模体出现在[[大肠杆菌]]的多种系统中,例如碳利用、厌氧生长、应激反应等。<ref name="she1"/><ref name="boy1"/> 为了更好地理解这种网络,我们必须得到关于基因集成多种输入的方式的信息。Kaplan ''et al.''<ref name="kap2">{{cite journal |vauthors=Kaplan S, Bren A, Zaslaver A, Dekel E, Alon U |title=Diverse two-dimensional input functions control bacterial sugar genes |journal=Mol. Cell |volume=29 |issue=6 |pages=786–92 |date=March 2008 |pmid=18374652 |pmc=2366073 |doi=10.1016/j.molcel.2008.01.021 }}</ref>绘制了[[大肠杆菌]]糖利用基因的输入函数,表现出各种各样的形状。 |
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| ==Activity motifs== | | ==Activity motifs== |