Team:Peking/CellularBurden

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        <li><a href="#010killing">Introduction</a></li>
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    <li><a href="#cellularburden01">Introduction</a></li>
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            <div id="sidenavsublist">
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    <li><a href="#igemclub02">Society Goals</a></li>
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            <ul>
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    <li><a href="#igemclub03">Future iGEMers</a></li>
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                <li><a href="#0101killing">1.Hen egg lysozyme</a></li>
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                <li><a href="#0102killing">2.Secretion</a></li>
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                <li><a href="#0103killing">3.Immunity System</a></li>
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        <li><a href="#020killing">Design</a></li>
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        <li><a href="#030killing">Result</a></li>
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  <h2 id="010killing">Introduction</h2>
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    <h2 id="cellularburden01">Introduction</h2>
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  <p> Algal blooms seriously threat the ecological integrity and sustainability of aquatic ecosystems. They can deplete oxygen causing harmful effects to the phytoplankton, and also produce a variety of toxic secondary metabolites such as microcystin. Among many kinds of algae potentially causing water bloom, <i>Microcystis Aeruginosa</i> accounts for a significant proportion [1]. We developed a new approach to control the population of <i>Microcystis Aeruginosa</i> in the water which can overcome the weakness of other methods. Our genetically engineered <i>E. coli</i>, which can express and secrete hen egg lysozyme and kill <i>Microcystis Aeruginosa</i> efficiently, safely, and controllably, with the help of α- hemolysin type I secretion system in <i>E. coli</i>. Moreover, an immunity system is introduced into the <i>E. coli</i> in case that secreted lysozyme could potentially be harmful to out genetically engineered <i>E. coli</i>.  
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    </p>
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  <h2 id="020killing">Design</h2>
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    <p>In most iGEM project and synthetic biology researches, complex genetic circuits are imported into bacteria to achieve variable functions. Such plenty of extra proteins, however, brings out serious burden to the host. Numerous researches reported this burden profoundly influence the general physiological state of the cell reflected by growth rate variation in steady state conditions<sup>[1]</sup>. <b>(Fig. 1)</b> This negative effect might lead to serious result, for example, unexpected performance of genetic circuits which needs strict parameters to function, but rarely attracts enough attention. Precise description to evaluate the actual influence of this phenomenon is expected.</p>
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      <h3 id="0101killing">1.Hen egg lysozyme</h3>
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<p><i>Microcystis Aeruginosa</i> is a species of freshwater cyanobacteria which can form harmful algal blooms (HABs) [1]. It almost has the same cell wall components with gram negative bacteria, such as outer membrane, peptidoglycan and inner membrane. Peptidoglycan, as an important structural component of bacterial cell wall, can provide resistance against turgor pressure [2]. Peptidoglycan can be cleaved by bacterial cell-wall hydrolases (BCWHs), causing the lysis of bacteria. So we put our attention to lysozymes, the well-known and best-studied group of BCWHs. </p>
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    <figure><img src="https://static.igem.org/mediawiki/2014/8/8d/Peking2014Ycy_CBFigure_1.png" style="height:308px"/>
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<p>Among the various kinds of lysozymes, we choose to work with hen egg lysozyme. Hen egg lysozyme, also known as lysozyme C (chicken-type), is one of the most widely used lysozyme, which has high antibacterial effect and easily available. Hen egg lysozyme is a kind of 1,4 -β-N- acetylmuramidase which causes the cleaving of the glycosidic bond between N-acetylmuramic acid and N-acetylglucosamine in the bacterial peptidoglycan, further causing the lysis of bacteria [3]. The hen egg lysozyme gene was de novo synthesized from commercial company (Genscript, Nanjing, China), and we cloned this gene into the plasmid pET-21a to test the efficiency of lysozyme being expressed from engineered <i>E. coli</i>. This plasmid was transformed into <i>E. coli</i> BL21(DE3) and defined as strain A.</p>
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        <figcaption><b>Figure.1<b>: 图一图注啦啦啦</b><figcaption>
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<img src="https://static.igem.org/mediawiki/2014/e/ee/Peking2014ylq_1.png" />
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    <p>In addition, this year Peking strives for greater efficiency of killing algae, thus pursues maximum gross production of killing protein. Gross production of protein relies on both expression level of each cell and the number of cells, and generally the two items are usually contradictive, that is, increasing expression level may lade cells and slow down the growth rate, and eventually the population size. <b>(Fig. 2)</b> Therefore, it is necessary to establish a balance between them to optimize the whole production.</p>
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<figcaption>Figure 2: HlyA is the C-terminal signal sequence; HlyB and HlyD are the membrane proteins involved in type I secretion; TolC is an outer membrane protein that is essential in the type I secretion pathway together with membrane proteins HlyB and HlyD.</figcaption>
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    <figure><img src="https://static.igem.org/mediawiki/2014/d/df/Peking2014Ycy_CBFigure_2.png" style="height:266px"/>
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<h3 id="0102killing">2.Secretion</h3>
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        <figcaption><b>Figure.2<b>: 图二图注啦啦啦</b>figcaption>
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<p>To achieve our goal of controlling the growth of <i>Microcystis Aeruginosa</i>, our <i>E. coli</i> should have the ability to secrete hen egg lysozyme. Therefore it`s necessary to introduce a secretion system to our <i>E. coli</i>.</p>
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    </figure>
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<p>To date, five kinds of translocation pathways have been identified in <i>E. coli</i>. These pathways can either deliver proteins from the cytosol to the medium through only one-step process, or via a periplasmic intermediate which need two steps. In order to prevent the contact between lysozyme and peptidoglycan, we utilized a one-step process system, type I secretion system, to deliver the lysozyme to the medium directly.</p>
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<p>Type I secretion system, which is also known as ABC transporter, works in a continuous secretion process across both the inner and the outer membrane of gram-negative bacteria. The proteins involved in Type I secretion system form a channel that exports proteins from the cytoplasm to the extracellular environment. </p>
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    <p>In this part, aiming at the two questions, we focus on experimentally constructing and verifying the relationship between cell cost and growth rate, which is similar with previous reported results[2], and finally calculating the optimal expression level. Furthermore, we also explore the growth rate under different nutritional condition, representing the different capability to afford protein burden. Combining these two parameters, we would establish a mathematical model based on partial differential equations to analysis the process of our project.<b>(Fig. 3)</b>.</p>
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<p>All of the Type I secretion systems, α-hemolysin(HlyA) secretion system is the best characterized and studied which has been widely used. Therefore we chose to work with this system to achieve the secretion of hen egg lysozyme.</p>
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<p>α-hemolysin(HlyA) secretion system contains 4 parts: They are HlyA, HlyB, HlyD and TolC respectively. HlyA is the C-terminal signal sequence of α-hemolysin, which can be recognized by HlyB. HlyB is an ATP-binding cassette. HlyD is a membrane fusion protein, which can be links between the outer and the inner membrane components of the system. And TolC is a specific outer membrane protein, which forms a long channel throughout the outer membrane and the periplasm, largely open towards the extracellular medium.</p>
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    <figure><img src="https://static.igem.org/mediawiki/2014/2/28/Peking2014Ycy_CBFigure_3.png" style="height:287px"/>
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<p>We got the following genes, HlyB(Genscript, Nanjing, China), HlyD (Genscript, Nanjing, China) and TolC (BBa_K554009) from iGEM part. We firstly cloned these three genes with RBSes Bba_B0034 before ATG and inserted them at site after the constitutive promoter, Bba_J23105. Then Gibson Assembling was used to assemble these 3 promoter followed by RBS and genes together. At the same time, we use pET-21a as a backbone to constructed another plasmid, which contains the hen egg lysozyme gene, a Glu-Ser linker, and a HlyA signal sequence at the C-terminal of hen egg lysozyme-GS linker. We did the co-transformation, and put these two plasmid that mentioned above in the same <i>E. coli</i> BL21(DH3), which was defined as Stain A <B>(Fig. 3)</B>.</p>
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<p>In order to improve the efficiency of the hen egg lysozyme secretion, we also constructed a plasmid that contains both the lysozyme-linker-hlyA signal sequence and these 3 components. We transformed this plasmid, whose backbone is pET-21a, into the the <i>E. coli</i> BL21(DH3). This strain was defined as Stain B (Fig. 3B). We could further induce both Stain A and Stain B with IPTG and then tested the effect of the lysozyme secretion as well as the killing effect of the secreted lysozyme. </p>
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        <figcaption><b>Figure.3<b>: 图三图注啦啦啦</b>figcaption>
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            </figure>
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<h3 id="0103killing">3. Immunity System</h3>
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    <h2 id="cellularburden02">Gene Expression Effects</h2>
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<p>The function of lysozyme is to provide hydrolysis of peptidoglycan by lysing bacterial cell-wall. Under the critical threat of lysozymes, bacteria in turn evolved mechanisms to avoid bacteriolysis, such as highly specific and potent lysozyme inhibitors production [4].
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There are several inhibitors that are specific for the hen egg lysozyme. In our project, we introduced the protein ykfE to protect our <i>E. coli</i> effectively against lysozyme while killing <i>Microcystis Aeruginosa</i> with lysozyme. YkfE is the product of the ORFan gene, which is one of the inhibitor of various kinds of lysozyme. The ykfE`s inhibition of lysozyme occurs via a key-lock type of interaction <B>(Fig. 4)</B>, without the conformational changes in the lysozyme inhibitor and lysozyme molecules [5].  
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    <p>Considering the low toxicity of mRFP, a serial of high-copy plasmids containing mRFP under gradient intensity of promoters is transformed into E. coli, and the growth curve of different strains are characterized. (Fig. 4a) We use the fluorescence intensity provided by iGEM Registry (http://parts.igem.org/Part:BBa_J23100) to evaluate the different expression levels. According to our result, we successfully verify the empirical relationship between cell cost and growth rate. <b>(Fig. 4b)</b>.</p>
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</p>
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<p>There are several inhibitors that are specific for the hen egg lysozyme. In our project, we introduced the protein ykfE to protect our <i>E. coli</i> effectively against lysozyme while killing <i>Microcystis Aeruginosa</i> with lysozyme. YkfE is the product of the ORFan gene, which is one of the inhibitor of various kinds of lysozyme. The ykfE`s inhibition of lysozyme occurs via a key-lock type of interaction <B>(Fig. 4)</B>, without the conformational changes in the lysozyme inhibitor and lysozyme molecules [5]. </p>
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    <figure><img src="https://static.igem.org/mediawiki/2014/f/fa/Peking2014Ycy_CBFigure_4.png" style="height:284px"/>
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<p>Our construct contains the ykfE gene under control of T7 promoter in the pET-21a plasmid was designated Stain C. This pET-21a plasmid was transformed into <i>E. coli</i> BL21, and the resulting strain was designated as ykfE overexpression strain <B>(Fig. 5)</B>.</p>
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        <figcaption><b>Figure.4<b>: 图四图注啦啦啦</b>figcaption>
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            </figure>
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    <h2 id="cellularburden03">Nutritional Condition</h2>
 +
   
 +
    <p>The nutritional condition is also a limitation on growth rate. We measure corresponding growth rate λ and the maximum environmental capacity N_K under different concentration nutrient, realized by diluting the medium. In order to better mimic the real situation, other than standard LB medium, lysed algae culture is also used as medium. (Fig. 5a, 5b) Results show that the growth rates in different nutrition condition follow the equations: (Fig. 5c, 5d)</p>
 +
    <p>λ=α( Cm )</p>
 +
    <p>dN/dt=N(1-N/N_K  )α( Cm )</p>
 +
    <p>Combined the unnecessary gene expression and nutritional condition effects, we drive a phenomenological relationship:</p>
 +
    <p>λ=α(Cm)  ∙ (1-βϕ)</p>
 +
    <p>dN/dt=N(1-N/N_K )∙α( Cm )∙ (1-βϕ)          (equ1)</p>
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 +
    <figure><img src="https://static.igem.org/mediawiki/2014/2/25/Peking2014Ycy_CBFigure_5.png" style="height:368px"/>
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        <figcaption><b>Figure.5<b>: 图五图注啦啦啦</b>figcaption>
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            </figure>
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<h2 id="030killing">Result</h2>
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    <h2 id="cellularburden04">Model</h2>
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<h3>1. Growth of algae and the killing efficiency of hen egg lysozymes</h3>
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<p>Whether the lysozyme could kill the algae is highly significant for the validity of our design. The growth curve of algae should be measured firstly. OD670nm, the absorbance of Chlorophyll a, was measured to illustrate the algal density. The algae were grinded before measuring OD for higher measurement accuracy. Absorbance was monitored every day until the growth of algae reached a stationary phase <B>(Fig. 1A)</B>.</p>
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    <p>Based on previous experiments and equations, the accumulated protein amount A could be represented by a multiplication between the current population of bacteria N(t) and expression level ϕ. The former is the integral of growth rate λ to time. The complete formula has the following form:</p>
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<p>To quantify the killing efficiency of hen egg lysozyme, The killing efficiency was tested by adding different concentration of hen egg lysozymes into algae culture. Since the corpse of dead algae remains float and still have absorbance, we measure the killing effect both by direct observation and absorbance at specific wavelength<B> (Fig. 1B, C)</B>. </p>
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    A=ϕ∫_0^t▒〖N(t)dt〗= Numerical simulation provides the extremum of this function in different nutritional condition. (Fig. 6)</p>
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 +
  <figure><img src="https://static.igem.org/mediawiki/2014/7/72/Peking2014Ycy_CBFigure_6.png" style="height:373px"/>
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      <figcaption><b>Figure.6<b>: 图六图注啦啦啦</b>figcaption>
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          </figure>
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  <h2 id="cellularburden05">Project Process Model</h2>
 +
 
 +
  <p>In our design, almost all of nutrition comes from algae lysed by lysozyme. Thus the nutrition condition is related to the lysozyme production. Consider this relation, the population variation is characterized by this formula in a specific algae concentration:</p>
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 +
   
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<h2 id="cellularburden06">Discussion</h2>
 +
<p>In this part, we originally investigate the potential negative influence of cell physiological state on synthetic biology design and propose a method to quantitatively evaluate this effect based on growth rate. Actually, this phenomenon is not rare in experiments, for example, strains carrying high-copy plasmids usually has slower growth rate than that carrying low-copy plasmids in same growth condition. Unfavorable physiological state caused by excess burden influence on expression of promoters and proliferation rate, therefore might block the function of circuits relying on this key parameters. Our model provides a choice to describe this unknown effect. In process of network design, this factor would be considered a priori and thus be repressed, which enhance the robustness of circuits.</p>
 +
<p>Moreover, similar with that in our project, industry which produces protein by engineered bacteria could also use this model to obtain maximum producing efficiency through adjusting expression intensity of target protein and nutrition condition of medium. At the time that accumulation of product needs to be controlled to prevent toxicity, it is a feasible measure to make engineered bacteria devote more resource into proliferation, and vice versa.</p>
 +
<p>In general, this kind of questions should be paid more attention on, and our model provides a simple attempt to solve them. We hope that more sophisticated models would be proposed in the future, which would make the evaluation more precise and reliable.</p>
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<h3>1. Growth of algae and the killing efficiency of hen egg lysozymes</h3>
 
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<p>The result indicates that 200ng/L lysozyme could kill the algae effectively within 72h. So the hen egg lysozyme, if could be properly expressed by our genetically engineered <i>E. coli</i>, would be a valid approach to kill the algae. </p>
 
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<h3>2.The lysozyme immune system</h3>
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<p><h2>References</h2></p>
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<p>Considering the working mechanism of lysozyme that cleaving the peptidoglycan of bacterial cell wall can also wound the "manufacturer", our genetically engineered <i>E. coli</i>. Such a detrimental effect to <i>E. coli</i> was firstly measured<B> (Fig. 2A)</B>. To counteract this effect, the best solution to overcome the detrimental effect is to build an immune system for our genetically engineered <i>E. coli</i>. We utilized ykfE, a native inhibitor of lysozyme of <i>E. coli</i>. The circuit for the strain has been constructed <B>(Fig. 2B)</B>, and further experimental is expected coming soon. </p>
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<p>Scott, M., Hwa, T. (2011). Bacterial growth laws and their applications.Current opinion in biotechnology, 22(4), 559-565.</p>
 +
<p>Scott, M., Gunderson, C. W., Mateescu, E. M., Zhang, Z., Hwa, T. (2010). Interdependence of cell growth and gene expression: origins and consequences. Science, 330(6007), 1099-1102.</p>
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<h3>3. The killing efficiency of Lysozyme expressed by genetically engineered <i>E. coli</i></h3>
 
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<p>We have constructed plasmids to express the hen egg lysozyme under the inducible promoter on the expression vector pET-21a. The expression of lysozyme in <i>E. coli</i> was verified by PAGE electrophoresis <B>(Fig. 3)</B>. We have verified that the hen egg lysozyme was successfully expressed in our <i>E. coli</i>. Although we have prepared the analysis that to use sonication lysed <i>E. coli</i> or purified protein to test whether the lysozyme is functionally expressed, the difficulty in the experimental protocol and time limit restrict our further trials. More data could probably be shown in our coming oral and poster presentations. </p>
 
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<h3>4.Perspective experiments</h3>
 
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<p>Further experiments would focus on testing killing efficiency, testing the lysozyme immune system, and developing the lysozyme secretion system. The construction shown in the design part (LINK) should transport the properly expressed lysozyme to the out membrane space of <i>E. coli</i>. Further work would significantly strengthen the proposed while not fully achieved killing system. We believe the full version of our killing system would potentially efficiently kill algae while protect the <i>E. coli</i> to maintain productive state. </p>
 
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Revision as of 22:25, 17 October 2014

Introduction

In most iGEM project and synthetic biology researches, complex genetic circuits are imported into bacteria to achieve variable functions. Such plenty of extra proteins, however, brings out serious burden to the host. Numerous researches reported this burden profoundly influence the general physiological state of the cell reflected by growth rate variation in steady state conditions[1]. (Fig. 1) This negative effect might lead to serious result, for example, unexpected performance of genetic circuits which needs strict parameters to function, but rarely attracts enough attention. Precise description to evaluate the actual influence of this phenomenon is expected.

Figure.1: 图一图注啦啦啦

In addition, this year Peking strives for greater efficiency of killing algae, thus pursues maximum gross production of killing protein. Gross production of protein relies on both expression level of each cell and the number of cells, and generally the two items are usually contradictive, that is, increasing expression level may lade cells and slow down the growth rate, and eventually the population size. (Fig. 2) Therefore, it is necessary to establish a balance between them to optimize the whole production.

Figure.2: 图二图注啦啦啦figcaption>

In this part, aiming at the two questions, we focus on experimentally constructing and verifying the relationship between cell cost and growth rate, which is similar with previous reported results[2], and finally calculating the optimal expression level. Furthermore, we also explore the growth rate under different nutritional condition, representing the different capability to afford protein burden. Combining these two parameters, we would establish a mathematical model based on partial differential equations to analysis the process of our project.(Fig. 3).

Figure.3: 图三图注啦啦啦figcaption>

Gene Expression Effects

Considering the low toxicity of mRFP, a serial of high-copy plasmids containing mRFP under gradient intensity of promoters is transformed into E. coli, and the growth curve of different strains are characterized. (Fig. 4a) We use the fluorescence intensity provided by iGEM Registry (http://parts.igem.org/Part:BBa_J23100) to evaluate the different expression levels. According to our result, we successfully verify the empirical relationship between cell cost and growth rate. (Fig. 4b).

Figure.4: 图四图注啦啦啦figcaption>

Nutritional Condition

The nutritional condition is also a limitation on growth rate. We measure corresponding growth rate λ and the maximum environmental capacity N_K under different concentration nutrient, realized by diluting the medium. In order to better mimic the real situation, other than standard LB medium, lysed algae culture is also used as medium. (Fig. 5a, 5b) Results show that the growth rates in different nutrition condition follow the equations: (Fig. 5c, 5d)

λ=α( Cm )

dN/dt=N(1-N/N_K )α( Cm )

Combined the unnecessary gene expression and nutritional condition effects, we drive a phenomenological relationship:

λ=α(Cm) ∙ (1-βϕ)

dN/dt=N(1-N/N_K )∙α( Cm )∙ (1-βϕ) (equ1)

Figure.5: 图五图注啦啦啦figcaption>

Model

Based on previous experiments and equations, the accumulated protein amount A could be represented by a multiplication between the current population of bacteria N(t) and expression level ϕ. The former is the integral of growth rate λ to time. The complete formula has the following form:

A=ϕ∫_0^t▒〖N(t)dt〗= Numerical simulation provides the extremum of this function in different nutritional condition. (Fig. 6)

Figure.6: 图六图注啦啦啦figcaption>

Project Process Model

In our design, almost all of nutrition comes from algae lysed by lysozyme. Thus the nutrition condition is related to the lysozyme production. Consider this relation, the population variation is characterized by this formula in a specific algae concentration:

Discussion

In this part, we originally investigate the potential negative influence of cell physiological state on synthetic biology design and propose a method to quantitatively evaluate this effect based on growth rate. Actually, this phenomenon is not rare in experiments, for example, strains carrying high-copy plasmids usually has slower growth rate than that carrying low-copy plasmids in same growth condition. Unfavorable physiological state caused by excess burden influence on expression of promoters and proliferation rate, therefore might block the function of circuits relying on this key parameters. Our model provides a choice to describe this unknown effect. In process of network design, this factor would be considered a priori and thus be repressed, which enhance the robustness of circuits.

Moreover, similar with that in our project, industry which produces protein by engineered bacteria could also use this model to obtain maximum producing efficiency through adjusting expression intensity of target protein and nutrition condition of medium. At the time that accumulation of product needs to be controlled to prevent toxicity, it is a feasible measure to make engineered bacteria devote more resource into proliferation, and vice versa.

In general, this kind of questions should be paid more attention on, and our model provides a simple attempt to solve them. We hope that more sophisticated models would be proposed in the future, which would make the evaluation more precise and reliable.

References

Scott, M., Hwa, T. (2011). Bacterial growth laws and their applications.Current opinion in biotechnology, 22(4), 559-565.

Scott, M., Gunderson, C. W., Mateescu, E. M., Zhang, Z., Hwa, T. (2010). Interdependence of cell growth and gene expression: origins and consequences. Science, 330(6007), 1099-1102.

Retrieved from "http://2014.igem.org/Team:Peking/CellularBurden"