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创建页面，内容为“==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…”
==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。
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。
===Negative auto-regulation (NAR)===
[[Image:Autoregulation motif.png|thumb|Schematic representation of an auto-regulation motif]]
One of simplest and most abundant network motifs in ''[[Escherichia coli|E. coli]]'' is negative auto-regulation in which a transcription factor (TF) represses its own transcription. This motif was shown to perform two important functions. The first function is response acceleration. NAR was shown to speed-up the response to signals both theoretically <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> and experimentally. This was first shown in a synthetic transcription network<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> and later on in the natural context in the SOS DNA repair system of E .coli.<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> The second function is increased stability of the auto-regulated gene product concentration against stochastic noise, thus reducing variations in protein levels between different cells.<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>
===负自反馈调节(NAR)===
[[Image:Autoregulation motif.png|thumb|Schematic representation of an auto-regulation motif]]
One of simplest and most abundant network motifs in ''[[Escherichia coli|E. coli]]'' is negative auto-regulation in which a transcription factor (TF) represses its own transcription. This motif was shown to perform two important functions. The first function is response acceleration. NAR was shown to speed-up the response to signals both theoretically <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> and experimentally. This was first shown in a synthetic transcription network<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> and later on in the natural context in the SOS DNA repair system of E .coli.<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> The second function is increased stability of the auto-regulated gene product concentration against stochastic noise, thus reducing variations in protein levels between different cells.<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>
===Positive auto-regulation (PAR)===
Positive auto-regulation (PAR) occurs when a transcription factor enhances its own rate of production. Opposite to the NAR motif this motif slows the response time compared to simple regulation.<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> In the case of a strong PAR the motif may lead to a bimodal distribution of protein levels in cell populations.<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>
===Feed-forward loops (FFL)===
[[Image:Feed-forward motif.GIF|thumb|Schematic representation of a Feed-forward motif]]
This motif is commonly found in many gene systems and organisms. The motif consists of three genes and three regulatory interactions. The target gene C is regulated by 2 TFs A and B and in addition TF B is also regulated by TF A . Since each of the regulatory interactions may either be positive or negative there are possibly eight types of FFL motifs.<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> Two of those eight types: the coherent type 1 FFL (C1-FFL) (where all interactions are positive) and the incoherent type 1 FFL (I1-FFL) (A activates C and also activates B which represses C) are found much more frequently in the transcription network of ''[[Escherichia coli|E. coli]]'' and yeast than the other six types.<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> In addition to the structure of the circuitry the way in which the signals from A and B are integrated by the C promoter should also be considered. In most of the cases the FFL is either an AND gate (A and B are required for C activation) or OR gate (either A or B are sufficient for C activation) but other input function are also possible.
===Coherent type 1 FFL (C1-FFL)===
The C1-FFL with an AND gate was shown to have a function of a ‘sign-sensitive delay’ element and a persistence detector both theoretically <ref name="man1"/> and experimentally<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> with the arabinose system of ''[[Escherichia coli|E. coli]]''. This means that this motif can provide pulse filtration in which short pulses of signal will not generate a response but persistent signals will generate a response after short delay. The shut off of the output when a persistent pulse is ended will be fast. The opposite behavior emerges in the case of a sum gate with fast response and delayed shut off as was demonstrated in the flagella system of ''[[Escherichia coli|E. coli]]''.<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> De novo evolution of C1-FFLs in [[gene regulatory network]]s has been demonstrated computationally in response to selection to filter out an idealized short signal pulse, but for non-idealized noise, a dynamics-based system of feed-forward regulation with different topology was instead favored.<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>
===Incoherent type 1 FFL (I1-FFL)===
The I1-FFL is a pulse generator and response accelerator. The two signal pathways of the I1-FFL act in opposite directions where one pathway activates Z and the other represses it. When the repression is complete this leads to a pulse-like dynamics. It was also demonstrated experimentally that the I1-FFL can serve as response accelerator in a way which is similar to the NAR motif. The difference is that the I1-FFL can speed-up the response of any gene and not necessarily a transcription factor gene.<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> An additional function was assigned to the I1-FFL network motif: it was shown both theoretically and experimentally that the I1-FFL can generate non-monotonic input function in both a synthetic <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> and native systems.<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> Finally, expression units that incorporate incoherent feedforward control of the gene product provide adaptation to the amount of DNA template and can be superior to simple combinations of constitutive promoters.<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> Feedforward regulation displayed better adaptation than negative feedback, and circuits based on RNA interference were the most robust to variation in DNA template amounts.<ref name="ble1"/>
===Multi-output FFLs===
In some cases the same regulators X and Y regulate several Z genes of the same system. By adjusting the strength of the interactions this motif was shown to determine the temporal order of gene activation. This was demonstrated experimentally in the flagella system of ''[[Escherichia coli|E. coli]]''.<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>
===Single-input modules (SIM)===
This motif occurs when a single regulator regulates a set of genes with no additional regulation. This is useful when the genes are cooperatively carrying out a specific function and therefore always need to be activated in a synchronized manner. By adjusting the strength of the interactions it can create temporal expression program of the genes it regulates.<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>
In the literature, Multiple-input modules (MIM) arose as a generalization of SIM. However, the precise definitions of SIM and MIM have been a source of inconsistency. There are attempts to provide orthogonal definitions for canonical motifs in biological networks and algorithms to enumerate them, especially SIM, MIM and Bi-Fan (2x2 MIM).<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>
===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.
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。
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。
===Negative auto-regulation (NAR)===
[[Image:Autoregulation motif.png|thumb|Schematic representation of an auto-regulation motif]]
One of simplest and most abundant network motifs in ''[[Escherichia coli|E. coli]]'' is negative auto-regulation in which a transcription factor (TF) represses its own transcription. This motif was shown to perform two important functions. The first function is response acceleration. NAR was shown to speed-up the response to signals both theoretically <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> and experimentally. This was first shown in a synthetic transcription network<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> and later on in the natural context in the SOS DNA repair system of E .coli.<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> The second function is increased stability of the auto-regulated gene product concentration against stochastic noise, thus reducing variations in protein levels between different cells.<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>
===负自反馈调节(NAR)===
[[Image:Autoregulation motif.png|thumb|Schematic representation of an auto-regulation motif]]
One of simplest and most abundant network motifs in ''[[Escherichia coli|E. coli]]'' is negative auto-regulation in which a transcription factor (TF) represses its own transcription. This motif was shown to perform two important functions. The first function is response acceleration. NAR was shown to speed-up the response to signals both theoretically <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> and experimentally. This was first shown in a synthetic transcription network<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> and later on in the natural context in the SOS DNA repair system of E .coli.<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> The second function is increased stability of the auto-regulated gene product concentration against stochastic noise, thus reducing variations in protein levels between different cells.<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>
===Positive auto-regulation (PAR)===
Positive auto-regulation (PAR) occurs when a transcription factor enhances its own rate of production. Opposite to the NAR motif this motif slows the response time compared to simple regulation.<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> In the case of a strong PAR the motif may lead to a bimodal distribution of protein levels in cell populations.<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>
===Feed-forward loops (FFL)===
[[Image:Feed-forward motif.GIF|thumb|Schematic representation of a Feed-forward motif]]
This motif is commonly found in many gene systems and organisms. The motif consists of three genes and three regulatory interactions. The target gene C is regulated by 2 TFs A and B and in addition TF B is also regulated by TF A . Since each of the regulatory interactions may either be positive or negative there are possibly eight types of FFL motifs.<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> Two of those eight types: the coherent type 1 FFL (C1-FFL) (where all interactions are positive) and the incoherent type 1 FFL (I1-FFL) (A activates C and also activates B which represses C) are found much more frequently in the transcription network of ''[[Escherichia coli|E. coli]]'' and yeast than the other six types.<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> In addition to the structure of the circuitry the way in which the signals from A and B are integrated by the C promoter should also be considered. In most of the cases the FFL is either an AND gate (A and B are required for C activation) or OR gate (either A or B are sufficient for C activation) but other input function are also possible.
===Coherent type 1 FFL (C1-FFL)===
The C1-FFL with an AND gate was shown to have a function of a ‘sign-sensitive delay’ element and a persistence detector both theoretically <ref name="man1"/> and experimentally<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> with the arabinose system of ''[[Escherichia coli|E. coli]]''. This means that this motif can provide pulse filtration in which short pulses of signal will not generate a response but persistent signals will generate a response after short delay. The shut off of the output when a persistent pulse is ended will be fast. The opposite behavior emerges in the case of a sum gate with fast response and delayed shut off as was demonstrated in the flagella system of ''[[Escherichia coli|E. coli]]''.<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> De novo evolution of C1-FFLs in [[gene regulatory network]]s has been demonstrated computationally in response to selection to filter out an idealized short signal pulse, but for non-idealized noise, a dynamics-based system of feed-forward regulation with different topology was instead favored.<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>
===Incoherent type 1 FFL (I1-FFL)===
The I1-FFL is a pulse generator and response accelerator. The two signal pathways of the I1-FFL act in opposite directions where one pathway activates Z and the other represses it. When the repression is complete this leads to a pulse-like dynamics. It was also demonstrated experimentally that the I1-FFL can serve as response accelerator in a way which is similar to the NAR motif. The difference is that the I1-FFL can speed-up the response of any gene and not necessarily a transcription factor gene.<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> An additional function was assigned to the I1-FFL network motif: it was shown both theoretically and experimentally that the I1-FFL can generate non-monotonic input function in both a synthetic <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> and native systems.<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> Finally, expression units that incorporate incoherent feedforward control of the gene product provide adaptation to the amount of DNA template and can be superior to simple combinations of constitutive promoters.<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> Feedforward regulation displayed better adaptation than negative feedback, and circuits based on RNA interference were the most robust to variation in DNA template amounts.<ref name="ble1"/>
===Multi-output FFLs===
In some cases the same regulators X and Y regulate several Z genes of the same system. By adjusting the strength of the interactions this motif was shown to determine the temporal order of gene activation. This was demonstrated experimentally in the flagella system of ''[[Escherichia coli|E. coli]]''.<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>
===Single-input modules (SIM)===
This motif occurs when a single regulator regulates a set of genes with no additional regulation. This is useful when the genes are cooperatively carrying out a specific function and therefore always need to be activated in a synchronized manner. By adjusting the strength of the interactions it can create temporal expression program of the genes it regulates.<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>
In the literature, Multiple-input modules (MIM) arose as a generalization of SIM. However, the precise definitions of SIM and MIM have been a source of inconsistency. There are attempts to provide orthogonal definitions for canonical motifs in biological networks and algorithms to enumerate them, especially SIM, MIM and Bi-Fan (2x2 MIM).<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>
===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.