New parts

J23101x series

1. BBa_K516130 (wiki name: J101-E5 ) J101-RBS30-RFP-TT
2. BBa_K516131 (wiki name: J101-31 ) J101-RBS31-mRFP-TT
3. BBa_K516132 (wiki name: J101-E7 ) J101-RBS32-mRFP-TT

BBa_J23101 is the reference standard promoter for the computation of RPUs. As discussed in 'data analysis' section, RPUs are relative units for the evaluation of promoter strength, based on a mathematical model of the transcription and the translation of a reporter gene.
The RPUs are supposed to be indepedent on the experimental setup, provided that the reference standard BBa_J23101 must be assayed in the same experimental condition of the studied promoter.
It means that if the studied promoter is in a low copy number plasmid and drives the expression of a reporter protein P, J23101 must be assembled in the same vector upstream of the same reporter P.
This approach is in accordance with the philosophy of synthetic biology, based on the concept of 'modularity' of the components. According to this approach, the assembly of basic well characterized modules to build complex circuits allows the prediction of the circuit behavior starting from the knowledge on the basic parts.
Salis et al. [Nat Biotec, 2009] stated that

'Identical ribosome binding site sequences in different genetic contexts can result in different protein expression levels'

and again

'It is likely that this absence of modularity is caused by the formation of strong secondary structures between the RBS-containing RNA sequence and one protein coding sequence but not another.'

For this reason, RPUs might not be reliable when comparing the same promoter with different RBSs because of the un-modularity of the RBS.
In order to asses what's the effect of RBS 'un-modularity' on RPUs reliability, we have built a set of four constitutive promoters (BBa_J23101) followed by one of the four RBSs tested. These parts were used to evaluate RBS efficiency. Data were collected and analyzed as described in 'Measurements' and 'Data analysis' sections. RPUs and Synthesis rate per cell [AUr] were computed and results are summarized in the table below.

NB: for the RPU computation, the J23101-RBS34-mRFP-TT construct has been considered as the reference standard. With this assumption, RPUs are identical to the estimated RBS efficiency.

If the hypothesis of RBS modularity depending on the promoter is accepted, the J23101-RBSx series we have provided can be used as a library of ready-to-use reference standard for RPU evaluation, that allows to depurate RPU measurement from RBS effect, thus providing only the promoter strength.

J23101 promoter with RBS Scell R.P.U.s RBS30 150.97 [15.34] 3.17 RBS31 2.30 [0.37] 0.05 RBS32 17.60 [5.85] 0.37 RBS34 47.57 [0.82] 1

AiiA expression cassette driven by aTc-inducible pTet promoter

• BBa_K516220 (wiki name: E24 ) pTet-RBS30-AiiA-TT
• BBa_K516221 (wiki name: E25 ) pTet-RBS31-AiiA-TT
• BBa_K516222 (wiki name: E26 ) pTet-RBS32-AiiA-TT
• BBa_K516224 (wiki name: E27 ) pTet-RBS34-AiiA-TT

LuxI expression cassette driven by aTc-inducible pTet promoter

• BBa_K516210 (wiki name: E13 ) pTet-RBS30-LuxI
• BBa_K516211 (wiki name: E14 ) pTet-RBS31-LuxI
• BBa_K516212 (wiki name: E15 ) pTet-RBS32-LuxI
• BBa_K516214 (wiki name: E16 ) pTet-RBS34-LuxI

Existing parts

Notes for promoter characterization

Inducible and constitutive promoters were assembled upstream of different coding sequences containing an RBS from the Community collection.

The assembled RBSs are:

For an inducible device, the RBS variation has the purpose to stretch the induction curve, thus modulating its PoPs-OUT range.

The complex RBS-promoter acts as a whole regulatory element and determines the amount of translated protein. RBSs have been reported to have an un-modular behavior, since the translational efficiency is not independent on the coding sequences, but variates as an effect of different mRNA structure stability [Salis et al., Nat Biotec, 2009]. In addition, it is not possible to separate the effects of the sole promoter and of the sole RBS on the total amount/activity of gene product (in this case study, mRFP).

For this reason, every combination 'Promoter+RBS' was studied as a different regulatory element. Regulatory elements were characterized using mRFP reporter protein for different RBSs in terms of Synthesis rate per Cell (S_cell) and R.P.U.s (Relative Promoter Units) as explained in measurements section.

Operative parameters of the promoter are derived from the estimated Hill equations obtained by lsqnonlin fitting of the Hill function expressed in RPUs :

• RPU_max is equal to the α and represents the maximum promoter activity,
• RPU_min is equal to the α * δ represents the minimum promoter activity,
• Switch point is computed as the abscissa of the inflection point of the Hill curve and represents the heart of linear region,
• Linearity boundaries are determined as the intersection between the tangent line to the inflection point and the upper and lower horizontal boundaries of the Hill curve.

RBSs

The complex RBS-promoter acts as a whole regulatory element and determines the amount of translated protein. RBSs have been reported to have an un-modular behavior, since the translational efficiency is not independent on the coding sequences, but variates as an effect of different mRNA structure stability [Salis et al., Nat Biotec, 2009]. In addition, it is not possible to separate the effects of the sole promoter and of the sole RBS on the total amount of mRFP produced. For this reason, every combination 'Promoter+RBS' was studied as a different regulatory element. The evaluation of RBS efficiency can be performed in a very intuitive fashion:

• select the RBSs you want to study,
• assemble them in a Promoter - XX - Coding sequence circuit,

• measure the output of the circuits and calculate the RBS efficiency as the ratio of the output relative to the output of the circuit with the standard RBS.

This simple measurement system allows the quantification of RBS efficiency depending on the whole measurement system (i.e.: promoter and encoded gene). Today it has not still been completely validated the hypothesis that every functional module in a genetic circuit maintains its behavior when assembled in a complex circuits, even if many researchers implicitly accept this hypothesis when performing characterization experiments.
To rationally assess the impact that this hypothesis has on the genetic circuit design and fine tuning, several measurement systems were built to evaluate the dependance of RBS modularity from the promoter or the coding sequence separately.
In particular, in order to investigate if RBS efficiency depends on the promoter, the same coding devices (RBSx-RFP-TT) were assembled downstream of different promoters (J23101, pTet, pLux). Measuring the system output and evaluating the RBS efficiency. The results are summarized in the table below:

RBS	effpLux*	effpTet*	effJ23101**	Declared efficiency
B0030	0.40	1.72	3.17	0,6
B0031	0.01	0.03	0.05	0,07
B0032	0.19	0.37	0.37	0,3
B0034	1	1	1	1

On the other end, to investigate the dependance of RBS modularity on the coding sequence, the same regulatory elements (pTet-RBSx) were assembled upstream of different encoded gene (mRFP, AiiA and LuxI). RBS efficiency was assessed and the results are summarized in the table below:

RBS	effmRFP	effAiiA	effLuxI	Declared efficiency
B0030	1.72	0.53	0.64	0,6
B0031	0.03	0.83	0.08	0,07
B0032	0.37	0.50	N.D.	0.3
B0034	1	1	1	1

^* The RBS efficiency for inducible devices was estimated as the ratio of the AUCs (Area under the curve) of the induction curves: AUC_{P, RBSx}/AUC_{P, B0034} ^** The RBS efficiency was computed as ratio between S_{cellP, RBSx}/S_{cellP, B0034}

The parts we used to characterize the RBSs are listed here:

• mRFP expression with different promoters
• J23101
• BBa_K516130 J101-RBS30-RFP-TT
• BBa_K516131 J101-RBS31-mRFP-TT
• BBa_K516132 J101-RBS32-mRFP-TT
• BBa_J23101 J101-RBS34-mRFP-TT
• pTet
• BBa_K516230 pTet-RBS30-mRFP-TT
• BBa_K516231 pTet-RBS31-mRFP-TT
• BBa_K516232 pTet-RBS32-mRFP-TT
• BBa_I13521 pTet-RBS34-mRFP-TT
• pLux
• BBa_K516330 pLambda-RBS30-LuxR-T-pLux-RBS30-mRFP-TT
• BBa_K516331 pLambda-RBS30-LuxR-T-pLux-RBS31-mRFP-TT
• BBa_K516332 pLambda-RBS30-LuxR-T-pLux-RBS32-mRFP-TT
• BBa_K516334 pLambda-RBS30-LuxR-T-pLux-RBS34-mRFP-TT
• pTet driving the expression of different genes
• mRFP
• BBa_K516230 pTet-RBS30-mRFP-TT
• BBa_K516231 pTet-RBS31-mRFP-TT
• BBa_K516232 pTet-RBS32-mRFP-TT
• BBa_I13521 pTet-RBS34-mRFP-TT
• AiiA
• BBa_K516220 pTet-RBS30-AiiA-TT
• BBa_K516221 pTet-RBS31-AiiA-TT
• BBa_K516222 pTet-RBS32-AiiA-TT
• BBa_K516224 pTet-RBS34-AiiA-TT
• LuxI
• BBa_K516210 pTet-RBS30-LuxI
• BBa_K516211 pTet-RBS31-LuxI
• BBa_K516212 pTet-RBS32-LuxI
• BBa_K516214 pTet-RBS34-LuxI

pLux promoter

• BBa_K516330 (wiki name: E17 ) pLambda-RBS30-LuxR-T-pLux-RBS30-mRFP-TT
• BBa_K516331 (wiki name: E18 ) pLambda-RBS30-LuxR-T-pLux-RBS31-mRFP-TT
• BBa_K516332 (wiki name: E19 ) pLambda-RBS30-LuxR-T-pLux-RBS32-mRFP-TT
• BBa_K516334 (wiki name: E20 ) pLambda-RBS30-LuxR-T-pLux-RBS34-mRFP-TT

The estimated parameters for the Hill functions are summarized in the table below. For more details on parameter estimation, see the model section.

RBS	αpLux	δpLux	ηpLux	kpLux
BBa_B0030	438 [10]	0.05 [>100]	2 [47]	1.88 [27]
BBa_B0031	9.8 [7]	0.11 [57]	1.2 [29]	1.5 [26]
BBa_B0032	206 [3]	0 [>>100]	1.36 [10]	1.87 [9]
BBa_B0034	1105 [6]	0.02 [>100]	1.33 [19]	2.34 [18]

Data are provided as average [CV%]

The operative parameters are summarized in the table below:

RBS	RPUmax	RPUmin	Switch point [nM]	Linear boundaries [MIN; MAX] [nM]
B0030	4.28	0.20	1.08	[0.36; 3.27]
B0031	4.93	0.55	0.25	[0.03; 2.30]
B0032	9.49	0.02	0.47	[0.07; 3.07]
B0034	21.53	0.51	0.53	[0.08; 3.77]

pTet promoter

• BBa_K516230 (wiki name: E21 ) pTet-RBS30-mRFP-TT
• BBa_K516231 (wiki name: E22 ) pTet-RBS31-mRFP-TT
• BBa_K516232 (wiki name: E23 ) pTet-RBS32-mRFP-TT
• BBa_I13521 pTet-RBS34-mRFP-TT

The protocols for the characterization of pTet promoter are reported in the pTet measurement section.
This promoter is widely studied and characterized usually using the strong RBS BBa_B0034. Here we have characterized its transcriptional strength as a function of aTc induction (ng/ul) for different RBSs. Four different induction curves were obtained and are reported in figure:



The data collected from the mRFP measurement systems were processed as described in data analysis section. The induction curves were obtained by fitting a Hill function as described in modelling section and the estimated parameters for pTet are reported in the pictures and in table below.

The estimated parameters of the Hill curves described in the figures are summarized in the table below:

RBS	αpTet	δpTet	ηpTet	kpTet
BBa_B0030	215 [2]	0.001 [>>100]	4.3 [12]	8.3 [2]
BBa_B0031	0.7 [>>100]	0[>>100]	18.84[>>100]	47.51[>>100]
BBa_B0032	45.7 [11]	0.02 [>>100]	83 [>>100]	8 [>>100]
BBa_B0034	125 [12]	0.12 [61]	71.8 [>>100]	9.8 [>>100]

Data are provided as average [CV%]

While α parameter (representing the maximum trascriptional rate in the studied range of induction) varies as expected with the RBS variation , the K and η parameters (determining the switch-point of the induction curve) are quite constant among all the RBS variations.
This suggests that the RBS variation only modulates the amplitude of the induction curve, but doesn't affect the shape, i.e. the translational promoter activity. These results are quite encouraging, because suggest that, given the non-modular behavior of RBS dpending on the encoded gene, the RBS has a modular behaviour respect to the promoter.

The operative parameters are summarized in the table below:

RBS	RPUmax	RPUmax	Switch point [ng/μ]	Linear boundaries [MIN; MAX] [ng/μ]
B0030	1.43	~0	7.47	[4.66;11.99]
B0031	0.33	~0	ND	ND
B0032	2.60	0.04	8.03	[7.85;8.24]
B0034	2.63	0.31	9.79	[9.52;10.07]

AiiA gene - BBa_C0060

The activity of AiiA enzyme has been evaluated by testing the properly built measurement systems pTet-RBSx-AiiA-TT The HSL synthesis rate has been evaluated according to the model equations, properly adjusted. In particular, the ODE system is reported here:

dAiiA/dt=α_pTet*(δ_pTet+(1-δ_pTet)/(1+(K_pTet/aTc)^η))

d[HSL]/dt=N*K_cat*AiiA*HSL/(K_{M, AiiA}+AiiA))

dN/dt=N*μ*(N_max-N)/N_max

The parameters of the first equation (estimated from the part pTet-RBSx-mRFP-TT) and N_max, μ and γ_HSL (see the Results section for more details) are known.
These parameters are summarized in the table below:

RBS	αpTet	δpTet	ηpTet	kpTet	Nmax	μ	γHSL
BBa_B0030	215 [2]	0.001 [>>100]	4.3 [12]	8.3 [2]	1*109	0.003152	0
BBa_B0031	0.7 [>>100]	0[>>100]	18.84[>>100]	47.51[>>100]
BBa_B0032	45.7 [11]	0.02 [>>100]	83 [>>100]	8 [>>100]
BBa_B0034	125 [12]	0.12 [61]	71.8 [>>100]	9.8 [>>100]

The parameters K_cat and K_M,AiiA were estimated with a simultaneous fitting of the data collected as described in measurement section for the four measurement parts pTet-RBSx-AiiA-TT assayed by BBa_T9002 biosensor section. The estimated parameters for the enzymatic activity of AiiA are reported in the table below:

Kcat KM, AiiA

LuxI gene - BBa_C0061

LuxI has been characterized through the Biosensor BBa_T9002 (see modeling section).
The HSL synthesis rate has been evaluated according to the model equations, properly adjusted. In particular, the ODE system is reported here:

dLuxI/dt=α_pTet*(δ_pTet+(1-δ_pTet)/(1+(K_pTet/aTc)^η))

d[HSL]/dt=N*V_max*1/(1+(K_{M, LuxI}/LuxI))

dN/dt=N*μ*(N_max-N)/N_max

The parameters of the first equation (estimated from the part pTet-RBSx-mRFP-TT) and N_max, μ and γ_HSL (see the Results section for more details) are known.
These parameters are summarized in the table below:

RBS	αpTet	δpTet	ηpTet	kpTet	Nmax	μ	γHSL
BBa_B0030	215 [2]	0.001 [>>100]	4.3 [12]	8.3 [2]	1*109	0.003152	0
BBa_B0031	0.7 [>>100]	0[>>100]	18.84[>>100]	47.51[>>100]
BBa_B0032	45.7 [11]	0.02 [>>100]	83 [>>100]	8 [>>100]
BBa_B0034	125 [12]	0.12 [61]	71.8 [>>100]	9.8 [>>100]

The parameters V_max and K_M,LuxI were estimated with a simultaneous fitting of the data collected as described in measurement section for the four measurement parts pTet-RBSx-LuxI-TT assayed by BBa_T9002 biosensor section. The estimated parameters for the enzymatic activity of LuxI are reported in the table below:

KM, LuxI Vmax

Explain that in all these evaluations we have estimated Nmax, mu, gamma_HSL from previous experiments - see measurement and modelling sections. When do we talk about HSL stability as a function of pH? Provide parameters of HSL. How do we present these data? It would be nice also to say what's the amount of HSL produced by a liquid 5 ml culture at a given OD600 in M9 medium after tot hours starting from 1:1000 dilution of a saturated ON culture.. We nee a synthetic parameter to express LuxI activity as a function of PoPS in. I suggest to report the HSL vs pH analysis here AND in the AiiA section of registry and, for what concerns our wiki, to add an appendix to the 'measurement section' to wich link when explaining.. Decide figures!

pSB1C3 plasmid with mRFP between S and P bearing pTet (easy-to-clone)

Existing parts: sequence debugging

• BBa_K516021 (wiki name: E10 ) RBS31-AiiA-TT Rebuilt existing part from BBa_I13914 (DNA planning)
• BBa_K516022 (wiki name: E11 ) RBS32-AiiA-TT Rebuilt existing part from BBa_I13912 (DNA planning)
• BBa_K516030 (wiki name: E5 ) RBS30-mRFP-TT Rebuilt existing part from BBa_S04180 (DNA planning)
• BBa_K516032 (wiki name: E7 ) RBS32-mRFP-TT Rebuilt existing part from BBa_ J133000 (DNA planning)
• BBa_K516214 (wiki name: E16 ) pTet-RBS34-LuxI Rebuilt existing part from BBa_S03623 (DNA available, only 2008 kit, inconsistent)
• BBa_K516222 (wiki name: E26 ) pTet-RBS32-AiiA-TT Rebuilt existing part from BBa_ J22071 (2008 only, Bad sequencing)
• BBa_K516224 (wiki name: E27 ) pTet-RBS34-AiiA-TT Rebuilt existing part from BBa_K077047 (Part deleted)
• BBa_K516232 (wiki name: E23 ) pTet-RBS32-mRFP-TT Rebuilt existing part from BBa_I20252 (DNA planning)