Team:Groningen/Project/Accumulation

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{{Team:Groningen/Project/Header|}}
{{Team:Groningen/Project/Header|}}
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==Introduction==
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<div style="float:left" >{{linkedImage|GroningenPrevious.png|Team:Groningen/Project/Transport}}</div>
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Once heavy metals have entered the cell it is key to keep them there. As these metals are toxic to cell survival in critical amounts evolution has provided us with biological detoxicification proteins such as [http://en.wikipedia.org/wiki/Metallothionein metallothioneins]. These proteins can aid us in our quest to accumulate a variaty of heavy metals as they bind to a wide range of metals including cadmium, zinc, mercury, copper, arsenic, silver, etc..
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<div title="Arsie Says UP TO METAL SENSITIVE PROMOTORS" style="float:right" >{{linkedImage|Next.JPG|Team:Groningen/Project/Promoters}}</div>
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===Metallothioneins===
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<div class="introduction">
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Metallothioneins are a class of low molecular-weight metal-binding proteins rich in cysteines residues. They are capable of binding a variety of heavy metals. And they have readily been used to create cell based systems for purification of contaminated water <SUP><FONT SIZE="-1">[http://www.ncbi.nlm.nih.gov/pubmed/9758654][http://www.ncbi.nlm.nih.gov/pubmed/18618649]</FONT></SUP>.  In addition to their wide application possibilities they also have the capacity to carry multiple metal ions at one time, in contrast to some other metalloproteins that carry them one-on-one<SUP><FONT SIZE="-1">[http://www.ncbi.nlm.nih.gov/pubmed/9579658]</FONT></SUP>.
+
-
Many forms of metallothioneins are known and their affinity for different metals has been investigated on several occasions, such as for cadmium<SUP><FONT SIZE="-1">[http://www.ncbi.nlm.nih.gov/pubmed/16890348]</FONT></SUP>, arsenic <SUP><FONT SIZE="-1">[http://www.ncbi.nlm.nih.gov/pubmed/16984198][http://www.ncbi.nlm.nih.gov/pubmed/15294789][http://www.ncbi.nlm.nih.gov/pubmed/18326684]</FONT></SUP>, mercury<SUP><FONT SIZE="-1">[[http://www.ncbi.nlm.nih.gov/pubmed/9758654 1]][http://www.ncbi.nlm.nih.gov/pubmed/9342882][http://www.ncbi.nlm.nih.gov/pubmed/17920767]</FONT></SUP>, nickel<SUP><FONT SIZE="-1">[http://www.ncbi.nlm.nih.gov/pubmed/12727263]</FONT></SUP> or a combination of metals<SUP><FONT SIZE="-1">[[http://www.ncbi.nlm.nih.gov/pubmed/9579658 3]][http://www.ncbi.nlm.nih.gov/pubmed/18313216]</FONT></SUP>.
+
-
Metal-protein complexes can be quantified using a fluorescent molecule<SUP><FONT SIZE="-1">[http://www.ncbi.nlm.nih.gov/pubmed/19133293]</FONT></SUP>.
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===Alternatives===
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{|style="clear:both"
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{{todo|Inclusion bodies}}<SUP><FONT SIZE="-1">[http://www.ncbi.nlm.nih.gov/pubmed/3297654]</FONT></SUP><br>
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|<html><style type="text/css">
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{{todo|(Bacterio)Ferritins}}<br>
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.intro { margin-left:0px; margin-top:10px; padding:10px; border-left:solid 5px #FFF6D5; border-right:solid 5px #FFF6D5; text-align:justify;background:#FFFFE5; }
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{{todo|Phytochelatins}}<br>
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</style></html>
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[http://www.wiley.com/legacy/products/subject/reference/messerschmidt_toc.html A list of opportunities]
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<div class="intro">
 +
=Accumulation=
 +
Once heavy metals have entered the cell, it is crucial to keep them there. As these metals are toxic to cell survival in critical amounts, evolution has provided us with biological detoxicification proteins such as [http://en.wikipedia.org/wiki/Metallothionein metallothioneins]. These proteins can aid us in our quest to accumulate a variety of heavy metals as they bind to a wide range of metals including cadmium, zinc, mercury, copper, arsenic, silver, coordinated in metal-thiolates. The metal chelating proteins are cloned in a synthetic operon with a metal specific transporter to make up the accumulation device. For arcummulation of arsenite fMT and ArsR used,  which were characterized by our model. Enhanced arsenite uptake by ''E. coli'' fMT could not be determined by the arsenite uptake assay, where the internal arsenic concentration was measured by ICP-MS.
 +
</div>
 +
|}
 +
</div>
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===Inhibitory characteristics?===
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==Metallothioneins==
 +
Metallothioneins are a class of low molecular-weight metal-binding proteins (<10kDa) rich in cysteines residues(~30%). They contain a conserved cys-x-cys or cys-x-his motif which coordinates metal binding, as can be seen in zinc finger depicted in figure 1.  They are capable of binding a variety of heavy metals (''e.g.'' Zn, Cu, Cd, Hg, As) with high avidity (Kb), they are ''in vivo'' used as a defense against oxidative stress by chelating metals. These proteins also have a function in storing, detoxifying and distributing metals throughout the cell ([[Team:Groningen/Literature#Merrifield2004|Merrifield 2004]], [[Team:Groningen/Literature#Gold2008|Gold 2008]]). These proteins have been readily used to create cell based systems for purification of contaminated water ([[Team:Groningen/Literature#Chen1998|Chen 1998]], [[Team:Groningen/Literature#Brady1994|Brady 1994]]). In addition to their wide application possibilities, they also have the capacity to carry multiple metal ions at one time, in contrast to some other metalloproteins that carry them one-on-one ([[Team:Groningen/Literature#Chang1998|Chang 1998]]).
 +
Many forms of metallothioneins are known and their affinity for different metals has been investigated on several occasions, such as for cadmium ([[Team:Groningen/Literature#Deng2007|Deng 2007]]), arsenic ([[Team:Groningen/Literature#Ngu2006|Ngu 2006]], [[Team:Groningen/Literature#Kostal2004|Kostal 2004]], [[Team:Groningen/Literature#Singh2008|Singh 2008]]), mercury ([[Team:Groningen/Literature#Chen1998|Chen 1998]], [[Team:Groningen/Literature#Chen1998|Chen 1997-2]], [[Team:Groningen/Literature#Deng2008|Deng 2008]]), nickel ([[Team:Groningen/Literature#Deng2003|Deng 2003]]) or a combination of metals ([[Team:Groningen/Literature#Chang1998|Chang 1998]], [[Team:Groningen/Literature#Kao2008|Kao 2008]]).
 +
Metal-protein complexes can be quantified using a fluorescent molecule ([[Team:Groningen/Literature#Cadosch2008 |Cadosch 2008]]) but Cu(I) binding to metallothioneins in metal thiolates, was shown to cause a concentration dependant increase in luminescence. These Cu(I) binding metallothioneins were shown to give rise to a Stokes shift of approximately 300 nm upon excitation at 280 nm ([[Team:Groningen/Literature#Beltramini1981|Beltramini 1981]], [[Team:Groningen/Literature#Gold2008|Gold 2008]]).
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==Modelling==
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 +
<center>[[Image:800px-Zinc finger rendered.png|250px]]
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:Figure 1: Zinc finger protein, consisting of a α-helix and an anti-parallel β-sheet. The zinc atom (green) is bound by two histidines and two cysteines.</center>
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==Cloning strategy==
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In order to have a functional accumulation device, the cDNA of a metallothionein (MT) will be amplified using [http://en.wikipedia.org/wiki/PCR PCR] and cloned into <partinfo>pSB1A2</partinfo>, also a corresponding metal-ion transporter was amplified by PCR and cloned behind the MT. Both will expressed by one promoter (constitutive or lactose inducible). In this way the bacterium will take up the metal-ion and consecutively the metal-ion will be sequestered by the MT. When this device is combined with the [[Team:Groningen/Project/Vesicle#Cloning_strategy|floating device]], the bacteria will start floating when a certain threshold of intracellular metal concentration is reached, because the negative regulator of the buoyancy device will be released and the gas vesicle cluster can be transcribed.
 +
 
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<center>[[Image:Accumulation device.PNG]]
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:Figure 2: Cloning strategy for the metal accumulation device. A promoter taken from <partinfo>J61002</partinfo> will be cloned in front of a metallothionein and a metal transporter in a <partinfo>pSB1A2</partinfo> vector. This device will be combined with the floating device.</center>
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===Practical note===
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MTs are degraded intracellular inside lysozymes, especially when they are in the apo/non-bound state ([[Team:Groningen/Literature#Gold2008|Gold 2008]]), for bacteria the degradation rate is not known, but for
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mammalian MT this can be estimated around 0.8 nmol apo-MT/mg protein/min ([[Team:Groningen/Literature#Klaassen1994|Klaassen 1994]]). This can be avoided by adding metal-salts (ZnCl<sub>2</sub>, CuSO<sub>4</sub>, CdCl<sub>2</sub>) to cells expressing the protein.
 +
 
 +
==Metals==
===Arsenic===
===Arsenic===
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Below you can calculate how many grams of arsenic will be taken out of the water per cubic meter of cells. This extra weight raises the density of the cell and therefore lowers its buoyancy capacity. Our preliminary results look very promising. Even under the assumption that the weight of the metal is added to the weight of the cells, without increasing their volume, we could add upto a hundred times the currently computed weight without having a large effect on the required fraction of gas vesicles (it will only go up from about 12.2% to 12.7%).
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For the accumulation of arsenic some MTs are possible, like rh-MT (human MT) ([[Team:Groningen/Literature#Ngu2006 |Ngu 2006]]) and fMT (the seaweed species ''Fucus vesiculosis'') both binding As(III). The oxidized version of arsenic (As (V)) can also be bound by the metallothioneins but with lower affinity ([[Team:Groningen/Literature#Singh2008 |Singh 2008]]), another way As(V) is proposed to be accumulated is by conversion of As(V) to As(III) by the arsenate reductase and subsequent bound to the metallothionein or ArsR. rh-MT is known to bind 6x As(III) per molecule, fMT binds 5x As(III). No extra quantitative information is known from literature.
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====ArsR====
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ArsR is a trans-acting repressor that senses environmental As(III) and regulates the chromosomal ars operon. The ArsR protein has a specific binding site for As(III) and discriminates effectively against other metals like: phosphate, cadmium, sulfate and cobalt. The affinity of ArsR for As(III) is very high 10<sup>-15</sup> M of AS(III) can induce the promotor. The specific binding site spans 33 nucleotides in the promotor region including the putative -35 promotor element. When ArsR was purified, its size corresponded to that of a homodimer, bound to promoter DNA. Because of the high affinity of ArsR for As(III) the protein could be used for arsenic remediation. Chen and co-workers overexpressed ArsR in <i>E. coli</i> JM109 cells and found that the specific AS(III) content was 13-fold higher than the control without ArsR expression. High level expression of ArsR appeared to be toxic as a 3-fold reduction in cell density was observed. It has been shown that fusion partners reduce the toxicity of overexpression. Originally, Chen and co-workers made a fusion between ArsR and ELP (elastin protein), which is build out of VPGVG repeats. Because making a ArsR ELP153 fusion is very time consuming, we choose to make a fusion between MBP (maltose binding protein) and ArsR    ([[Team:Groningen/Literature#Chen1998|Chen 1998]]).
 +
<BR>
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Also see the [[Team:Groningen/Project/Promoters|Metal sensitive promoters]]. 
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As ordering rh-MT was not successful, we try to use fMT for accumulation of As(III) and use ArsR to regulate the expression of the ''gvp'' cluster behind the ArsR regulated promoter.
 +
 
 +
=====Results=====
 +
 
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The fusion protein MBP-ArsR was built by creating giving the reverse primer of the MBP and the Forward primer of the ArsR a mutual restriction site SacI. The linker region was designed in such a way that it contained a Tev cleavage site, containing a SacI restriction site and a string of alanine residues to facilitate folding. The fusion protein has been succesfully cloned into the <partinfo>psb1AC3</partinfo> vector creating biobrick {{part|BBa_K190027}}, but further attempts to add a promotor and rbs failed. Due to time the MBP-ArsR fusion protein has not been equipped with a promotor and so overexpression could not be established.
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===fMT===
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The <i>Fucus</i> [[Team:Groningen/Glossary#Metallothionein|Metallothionein]] (fMT) was isolated from the [http://en.wikipedia.org/wiki/Seaweed macroalgae] [http://en.wikipedia.org/wiki/Fucus_vesiculosus <i>Fucus vesiculosus</i> ]([[Team:Groningen/Literature#Morris1999|Morris 1999]]). It consists of 67 amino acid residues and has 16 cysteine residues, a high cysteine content is a key feature of MT. Another characteristic is the lack of aromatic residues is also seen in fMT where it only has one, tryptophan. Two domains containing cysteine residues are presumed to be involved in the metal binding function. Unusual in fMT is the presence of a 14 amino acid linker region between the two putative metal-binding domains which contains no cysteine residues. Plant MTs show this feature with about 40 residues, where vertebrate MTs only have three residues ([[Team:Groningen/Literature#Morris1999|Morris 1999]]). Being a MT, fMT binds a multitude of metal ions, 6 Cd<sup>2+</sup> ions or 5 As<sup>3+</sup> ions in a sequential order, facilitated by the elongated linker domain ([[Team:Groningen/Literature#Ngu2009|Ngu 2009]]). The organisms from which fMT was first isolated are known to have the ability to survive in highly metal polluted water and with it having been expressed in ''E. coli'' previously ([[Team:Groningen/Literature#Singh2008|Singh 2008]]) it was an ideal choice to use as an arsenic sequestering protein.
 +
 
 +
 
 +
====Results====
 +
Arsenite uptake [[Team:Groningen/Protocols#Metal_uptake_assay_for_E._coliKostal_2004|assays]] were done to determine the As(III) accumulation of ''E. coli'' WT and fMT / GlpF overexpression strains. The concentration was measured by [[Team:Groningen/Protocols#Metal_uptake_assay_for_E._coliKostal_2004|ICP-MS]].
 +
 
 +
The arsenic uptake in ''E. coli'' WT (figure 3) as measured during this project (by [http://www.rikilt.wur.nl/NL/ RIKILT], Wageningen University), was compared with the uptake of ''E. coli'' with ArsR overexpression (described by [[Team:Groningen/Literature#Kostal2004|Kostal 2004]], see figure 3). This shows that the arsenic uptake in ''E. coli'' WT behaves similar but has lower final As(III) uptake yield. The difference is about 10% in the standard mode, but a higher extracellular arsenic concentration seems to be needed to saturate the uptake of arsenic in ''E. coli'' WT compared to ''E. coli'' with ArsR overexpression. This can be seen by comparing the transition point to saturation in figure 3, which are respectively around 50 µM As(III) and around 20 µM.
 +
 
 +
<center>[[Image:UptakeEquilibrium.png]]
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:Figure 3: Uptake of As(III) by ''E. coli'' WT (containing pSB1A2-pLac)</center>
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There is a relatively large difference between the data generated by measuring the arsenic concentration with ICP-MS in the standard mode and measuring in the collusion cell technology mode (CCT mode). The difference between these two techniques is that in the standard mode it is possible that multi-atomic compounds lead to interference with the arsenic (mw = 75) peak, like argon-chloride (Ar = 40 + Cl = 35 (75%) or 37 (25%)). Because 25% of this compound is found in the mw = 77 peak, a correction factor may be calculated to correct for this, the ICP-MS software (Thermo) automatically corrects for Ar-Cl interference. It uses the amount of Krypton and Selenium for this correction. In the CCT all multi-atomic compounds are supposed to be decomposed, therefore no interference will be found in this mode. But a disadvantage of this mode is that the resolution is 10x lower than the standard mode, leading to a smaller signal-to-noise ratio. Because of this, we decided to use the standard mode (corrected for interference) to determine the arsenic accumulation by ''E. coli''.
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A second arsenic measurement was performed (by [http://www.vwa.nl/portal/page?_pageid=119,1639634&_dad=portal&_schema=PORTAL Food and Consumer Product Safety Authority], Groningen) using ''E. coli'' WT and ''E. coli'' containing the accumulation device (<partinfo>BBa_K190038</partinfo>) and the different parts ([[Team:Groningen/Project/Transport#Arsenite uptake via GlpF|GlpF]] (<partinfo>BBa_K190028</partinfo>) and [[Team:Groningen/Project/Accumulation#Arsenic|fMT]] (<partinfo>BBa_K190019</partinfo>)). The data was measured in the standard mode and the calculated arsenic imported by the cells is shown in figure 4.
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<center>[[Image:UptakeEquilibrium2.png]]</center>
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:Figure 4: Uptake of As(III) by ''E. coli'' WT, and the strains containing the different parts of the accumulation device. As a control the arsenic uptake of ''E. coli'' with ArsR overexpression (as described by [[Team:Groningen/Literature#Kostal2004|Kostal 2004]]) is also shown.
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The curves in this figure show that there is no difference between the arsenic uptake by ''E. coli'' WT and by ''E. coli'' plus (parts of) the accumulation device. As a second observation, it can be seen that the uptake of arsenic in measured here is higher than found before (figure 3). A ratio of 2-3x was found for the WT strains (<center>pSB1A2</center> and pArsR-RFP). These two differences will be discussed below. fMT shows exceptionally low arsenite uptake, this may be caused by incidentally "burning" the already dried cells at ~100;deg&C.
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The raw data can be found at [[Team:Groningen/Modelling/Downloads| downloads]].
 +
 
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====Discussion====
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Between the two data sets there are a few differences, first there seems to be no difference between arsenic uptake in WT and ''E. coli'' with the accumulation device (or parts of this). Secondly, the data of arsenic uptake by ''E. coli'' WT could was not reproducible and the last data set showed a arsenic uptake which was even higher for ''E. coli'' WT than the ''E. coli'' ArsR overexpression strain.
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*Why is there no difference between the ''E. coli'' WT and the ''E. coli'' with accumulation device?
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This can be caused by non-functional expression of one of the genes (fMT or GlpF) or both. For membrane proteins it is known that functional overexpression is harder than for cytoplasmic proteins ([[Team:Groningen/Literature#Lundstom2006|Lundstom 2006]]). This could be tested by doing As(III) uptake/binding experiments with purified proteins, but this requires protein purification which could be facilitated by the addition of a his-tag (not present yet). The function of the transporter can be tested by measuring the uptake in membrane vesicles and that of the accumulation protein can be tested by measuring metal binding for instance by isothermal titration calorimetry. Otherwise the proteins may not be produced at all, this should be tested by protein purification or SDS-page. Another possibility is that these proteins cannot be produced by ''E. coli'' at once, though functional expression was already proven by Singh ''et al.'' ([[Team:Groningen/Literature#Singh2008|Singh 2008]]).
 +
 
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*Non reproducible concentrations of arsenic, imported by ''E. coli'' WT, which can be seen as there is a large difference (2-3x) in arsenic uptake determined from the first and the second measurement. All data from the second ICP-MS arsenic determination, were also unexpectedly higher than was found in literature ([[Team:Groningen/Literature#Kostal2004|Kostal 2004]], [[Team:Groningen/Literature#Singh2008|Singh 2008]]). This discrepancy may be caused by one of the following reasons.
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During the second arsenic uptake assay the time between the incubation and washing the cells was decreased to the minimum though during the first assay there was some time for the cells to export the As(III) via their exporter ArsB. This may have caused the lower uptake yield of arsenic in the first data set. Also there was a difference in cell concentration, in the second assay this was 2.5 times higher. It is presumable that with a higher cell concentration the uptake rate is slower but a saturating incubation time (>1hr) might cause that the equilibrium of arsenite concentration in/outside the cell is reached faster. After destruction of the samples of the first data set, the samples did not become a clear solution but a suspension containing white flakes. These were removed by centrifugation, but this seems to indicate incomplete destruction. This was not the case for the second samples, therefore an increased arsenite concentration may be measured as arsenite bound to the white flakes is not measured.
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It also might be, that during the second arsenite uptake assay the cells were washed less properly causing the concentration to become way higher than the first measurement. A more acidic buffer should be used for washing the cells, because this should be more efficient in removing metal ions than the [[Team:Groningen/Protocols#TB74S_Buffer|TB74S buffer]] (pH 7.4), but as this protocol was the same as described by [[Team:Groningen/Literature#Kostal2004|Kostal 2004]], this should be a major problem. The expected increase in arsenic concentration should be linear with the external arsenite concentration, but this was not seen (figure 4), a clear saturation curve was seen.
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A plausible cause is that there was a mistake in the calculations, a correction factor which was forgotten to correct for. Another plausible cause is that the concentration is higher because the measured concentration was for some samples 5 times higher than the calibration range. It might be that linear extrapolation is not correct. This can cause the structural increased arsenic uptake.
 +
 
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*Other considerations:
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-Metal buffer interactions, causing a lower free-As(III) concentration surrounding the cell suspension.
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-Arsenic oxidation in aerobic conditions to As(V), this equilibrium may change over hours, so if the stock solution is enriched with As(V) it may take hours before it is changed to As(III) again.
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- Binding of other metal ions to the metallothionein causing competition for arsenite binding to fMT. Possible metal ions can be: Copper(I) or other metal ions present in the undefined LB medium. A requiry is that the metal ion should bind stronger or as strong to the MT as arsenite, which binds less strongly to MT than Zn(II) for instance or Cu(I).
 +
 
 +
====Conclusion====
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The data generated by the arsenic uptake assay and ICP-MS determination of internal arsenic concentrations were unfortunately not reproducable. According to the first measurement, the uptake of arsenic by ''E. coli'' WT showed a little lower final yield and a higher concentration where the system becomes saturated. Because of the lack of reproducibility of the measurements and the extremely high intracellular arsenic concentration found during the second measurement, it cannot be determined whether fMT enhances the arsenic accumulation. In addition, the second measurement showed no difference between WT and the overexpression strains of GlpF, fMT or the fMT-Glpf operon. To establish the functionality of fMT, the arsenic uptake assay should be redone.
 +
 
 +
==Modelling==
 +
<html>
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<script type="text/javascript" src="/Team:Groningen/Modelling/Model.js?action=raw"></script>
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<script type="text/javascript" src="/Team:Groningen/Modelling/Arsenic.js?action=raw"></script>
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</html>
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{{GraphHeader}}
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===Arsenic - ArsR===
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 +
Below you can calculate how many grams of arsenic will be taken out of the water per cubic meter of cells. This extra weight raises the density of the cell and therefore lowers its capacity for buoyancy. Our preliminary results look very promising. Even under the assumption that the weight of the metal is added to the weight of the cells, without increasing their volume, we could add up to a hundred times the currently computed weight without having a large effect on the required fraction of gas vesicles (it will only go up from about 12.2% to 12.7%).
At this moment we use four different variables:
At this moment we use four different variables:
# Molecular weight of arsenic. Source: [http://en.wikipedia.org/wiki/Arsenic Arsenic page on Wikipedia]
# Molecular weight of arsenic. Source: [http://en.wikipedia.org/wiki/Arsenic Arsenic page on Wikipedia]
-
# Millimol arsenic per kg of cell dryweight (note that this is equivalent to nmol/mg). Source: Koster et al
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# Millimol arsenic per kg of cell dryweight (note that this is equivalent to nmol/mg). Source: [[Team:Groningen/Literature#Kostal2004|Kostal 2004]]
# The proportion between the weight of a dry cell and a wet cell. Source: [http://redpoll.pharmacy.ualberta.ca/CCDB/cgi-bin/STAT_NEW.cgi CCDB Database]
# The proportion between the weight of a dry cell and a wet cell. Source: [http://redpoll.pharmacy.ualberta.ca/CCDB/cgi-bin/STAT_NEW.cgi CCDB Database]
# Cell density. Source: see our [[Team:Groningen/Project/Vesicle|gas vesicle page]].
# Cell density. Source: see our [[Team:Groningen/Project/Vesicle|gas vesicle page]].
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<html>
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{|
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|style="vertical-align:top;"|<html>
<div style="background:#efe;border:1px solid #9c9;padding:1em;">
<div style="background:#efe;border:1px solid #9c9;padding:1em;">
<table style="border-collapse:collapse;background:none;"><tr>
<table style="border-collapse:collapse;background:none;"><tr>
Line 41: Line 122:
<td style="padding-left:1em;">
<td style="padding-left:1em;">
<div id="arsenicError" style="color:red"></div>
<div id="arsenicError" style="color:red"></div>
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As(III) intake per volume of cells<br/>
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<nobr>As(III) intake per volume of cells</nobr><br/>
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= <span id="Aspercellvolume"></span> g/m<sup>3</sup><br/>
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<nobr> = <span id="Aspercellvolume"></span> g/m<sup>3</sup></nobr><br/>
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= <span id="molAspercellvolume"></span> &micro;mol/liter (TODO: check)<br/>
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<nobr> = <span id="molAspercellvolume"></span> &micro;mol/liter</nobr><br/>
</td>
</td>
</tr></table>
</tr></table>
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function computeArsenicWeight() {
function computeArsenicWeight() {
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  // Input
 
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  var awAsNode = document.getElementById("awAs");
 
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  var cAsNode = document.getElementById("cAs");
 
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  var McelldrywetNode = document.getElementById("Mcelldrywet");
 
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  var rhocellNode = document.getElementById("rhocell");
 
-
 
   // Intermediates (mostly useful for debugging)
   // Intermediates (mostly useful for debugging)
   var arsenicErrorNode = document.getElementById("arsenicError");
   var arsenicErrorNode = document.getElementById("arsenicError");
   arsenicErrorNode.innerHTML = '';
   arsenicErrorNode.innerHTML = '';
-
 
-
  // Outputs
 
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  var AspercellvolumeNode = document.getElementById("Aspercellvolume");
 
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  var molAspercellvolumeNode = document.getElementById("molAspercellvolume");
 
   // Read inputs
   // Read inputs
-
   var awAs = Number(awAsNode.value); // g/mol
+
   var awAs = getInput('awAs'); // g/mol
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   var cAs = Number(cAsNode.value) * 1e-3; // mmol/kg -> mol/kg
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   var cAs = getInput('cAs') * 1e-3; // mmol/kg -> mol/kg
-
   var Mcelldrywet = Number(McelldrywetNode.value); // kg/kg
+
   var Mcelldrywet = getInput('Mcelldrywet'); // kg/kg
-
   var rhocell = Number(rhocellNode.value); // kg/m^3
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   var rhocell = getInput('rhocell'); // kg/m^3
   // Compute density(/-ies)
   // Compute density(/-ies)
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     arsenicErrorNode.innerHTML = err.message;
     arsenicErrorNode.innerHTML = err.message;
   }
   }
-
 
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  // Set intermediates if they exist
 
   // Set outputs
   // Set outputs
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   setOutput(AspercellvolumeNode, Aspercellvolume);
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   setOutput('Aspercellvolume', Aspercellvolume);
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   setOutput(molAspercellvolumeNode, molAspercellvolume);
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   setOutput('molAspercellvolume', molAspercellvolume);
-
}
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-
 
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function formatNumberToHTML(v,p) {
+
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  if (p===undefined) p = 5;
+
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  return v.toPrecision(p)
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          .replace(/e\+([0-9]+)$/i,'&middot;10<sup>$1</sup>')
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          .replace(/e\-([0-9]+)$/i,'&middot;10<sup>-$1</sup>');
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-
}
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-
 
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-
function setOutput(node,v,p) {
+
-
  node.innerHTML = formatNumberToHTML(v);
+
-
  node.value = v;
+
}
}
</script>
</script>
</html>
</html>
 +
|style="vertical-align:top;"|<pre>
-
The following tries to compute the ratio between bound and unbound arsenic, specifically As(III), in the cell.
+
As per cell volume = awAs * nAs(III) /
-
See our [[Team:Groningen/Modelling|Modelling]] page for information on the constants/variables used. Note that the computations currently involve more variables/constants than strictly necessary.
+
  Mcell(dry) * Mcelldrywet * rhocell
 +
mol As per cell volume = nAs(III) /
 +
  Mcell(dry) * Mcelldrywet * rhocell
 +
 
 +
</pre>
 +
|}
 +
 
 +
[[Image:Arsenic_accumulation.png|frame]]
 +
 
 +
At a lower level arsenic accumulation can be described using reactions between ArsR, As(III) and the ars promoter. As shown in the figure on the right, a number of different substances(/complexes) are involved. For our purposes it is especially important to determine what fraction of As(III) is unbound, if more As(III) is bound we can accumulate more.
 +
 
 +
In addition to binding to As(III), ArsR can repress Ars, creating a negative feedback loop. In effect this regulates the production of ArsR based on the As(III) concentration ([[Team:Groningen/Literature#Chen1997|Chen 1997]]). In the <i>E. coli</i> top 10 there is only ars promoter present on the genome to produce ArsR (see [[Team:Groningen/BLAST|BLAST]] results). There are plasmids which produce both ArsR and ArsD, but these are not used in this project. We intend to introduce instead a constitutive promoter (pro), which produces just ArsR, in order to bind as much As(III) as possible.
 +
 
 +
The calculator below tries to compute the ratio between bound and unbound arsenic, specifically As(III), in the cell.
 +
See our [[Team:Groningen/Modelling/Arsenic|Modelling]] page for detailed information on the constants/variables used and a derivation of the formulas. Note that the computations currently involve slightly more variables/constants than strictly necessary.
<html>
<html>
-
<div style="background:#efe;border:1px solid #9c9;padding:1em;">
+
<table style="background:#efe;border:1px solid #9c9;padding:1em;"><tr><td>
<table style="border-collapse:collapse;background:none;"><tr>
<table style="border-collapse:collapse;background:none;"><tr>
<td style="border-right:1px solid #9c9;padding-right:1em;">
<td style="border-right:1px solid #9c9;padding-right:1em;">
-
K1<sub>d</sub> = <input type="text" id="K1d" value="6"/> &micro;M (?)<br/>
+
<dl>
-
K2<sub>d</sub> = <input type="text" id="K2d" value="60"/> &micro;M<br/>
+
<dt>Dissociation constants</dt>
-
K3<sub>d</sub> = <input type="text" id="K3d" value="0.33"/> &micro;M<br/>
+
<dd>
-
K4<sub>d</sub> = <input type="text" id="K4d" value="65"/> &micro;M<br/>
+
KR<sub>d</sub> (ArsR<sub>As</sub>) = <input type="text" id="K1d" value="6"/> &micro;M (??)<br/>
-
&tau;1 = <input type="text" id="tau1" value="30"/> min (??)<br/>
+
<nobr>KA<sub>d</sub> (ArsR<sub>ars</sub>) = <input type="text" id="K3d" value="0.33"/> &micro;M (</html>[[Team:Groningen/Literature#Chen1997|Chen1997]]<html>)</nobr><br/>
-
&tau;2 = <input type="text" id="tau2" value="30"/> min (??)<br/>
+
KM<sub>d</sub> (MBPArsR<sub>As</sub>) = <input type="text" id="KMd" value="6"/> &micro;M (???)<br/>
-
&beta;1 = <input type="text" id="beta1" value="1"/> 1/second (???)<br/>
+
KF<sub>d</sub> (fMTArsR<sub>As</sub>) = <input type="text" id="KFd" value="6"/> &micro;M (???)<br/>
-
&beta;2 = <input type="text" id="beta2" value="1"/> 1/second (???)<br/>
+
n<sub>f</sub> = <input type="text" id="nf" value="3"/> (???)<br/>
-
&beta;3 = <input type="text" id="beta3" value="1"/> 1/second (???)<br/>
+
</dd>
 +
<dt>Half-lifes</dt>
 +
<dd>
 +
&tau;R (ArsR) = <input type="text" id="tauR" value="0.1"/> min (???)<br/>
 +
&tau;M (MBPArsR) = <input type="text" id="tauM" value="0.1"/> min (???)<br/>
 +
&tau;F (fMT) = <input type="text" id="tauF" value="0.1"/> min (???)<br/>
 +
</dd>
 +
<dt>Production rates of the promoters</dt>
 +
<dd>
 +
<nobr>&beta;RN (ars1 &rarr; ArsR) = <input type="text" id="beta1" value="100"/> 1/second (???)</nobr><br/>
 +
<nobr>&beta;R (proR &rarr; ArsR) = <input type="text" id="beta3" value="100"/> 1/second (???)</nobr><br/>
 +
<nobr>&beta;M (proM &rarr; MBPArsR) = <input type="text" id="betaM" value="26.6"/> 1/second (???)</nobr><br/>
 +
<nobr>&beta;F (proF &rarr; fMT) = <input type="text" id="betaF" value="200"/> 1/second (???)</nobr><br/>
 +
</dd>
<!--As(III) = <input type="text" id="As3Concentration" value="10"/> &micro;M<br/>-->
<!--As(III) = <input type="text" id="As3Concentration" value="10"/> &micro;M<br/>-->
-
OpN<sub>total</sub> = <input type="text" id="OpNTotalConcentration" value="0.00166054"/> &micro;M (??)<br/> <!-- 1/(avogadro's constant)/micrometer^3 in micromoles/liter -->
+
<dt>Promoter concentrations<dt>
-
OpG<sub>total</sub> = <input type="text" id="OpGTotalConcentration" value="0"/> &micro;M (??)<br/>
+
<dd>
-
OpH<sub>total</sub> = <input type="text" id="OpHTotalConcentration" value="0.0166054"/> &micro;M (??)<br/> <!-- 10/(avogadro's constant)/micrometer^3 in micromoles/liter -->
+
ars1<sub>total</sub> = <input type="text" id="ars1TPerCell" value="1"/> per cell<br/>
 +
<nobr>proR = <input type="text" id="proRPerCell" value="0"/> per cell (??)</nobr><br/>
 +
<nobr>proM = <input type="text" id="proMPerCell" value="100"/> per cell (??)</nobr><br/>
 +
<nobr>proF = <input type="text" id="proFPerCell" value="0"/> per cell (??)</nobr><br/>
 +
V<sub>cell</sub> = <input type="text" id="Vcell" value="1"/> &micro;m<sup>3</sup> </html>
 +
([http://gchelpdesk.ualberta.ca/CCDB/cgi-bin/STAT_NEW.cgi| CCBD])<html>
 +
 
 +
</dd>
 +
</dl>
<button onClick="computeArsenicEquilibrium()">Compute</button><br/>
<button onClick="computeArsenicEquilibrium()">Compute</button><br/>
Line 128: Line 221:
<td style="padding-left:1em;">
<td style="padding-left:1em;">
<div id="arsenicEquilibriumError" style="color:red"></div>
<div id="arsenicEquilibriumError" style="color:red"></div>
-
Operator = <span id="OpConcentration"></span> &micro;M<br/>
+
<dl>
-
ArsR = <span id="ArsRConcentration"></span> &micro;M<br/>
+
<dt>ArsR</dt>
-
ArsD = <span id="ArsDConcentration"></span> &micro;M<br/>
+
<dd>
-
<!--ArsR<sub>As</sub> = <span id="ArsRAs3Concentration"></span> &micro;M<br/>
+
ars / ars<sub>total</sub> = <span id="arsFraction"></span><br/>
-
ArsD<sub>As</sub> = <span id="ArsDAs3Concentration"></span> &micro;M<br/>-->
+
ArsR = <span id="ArsR"></span> &micro;M<br/>
-
ArsR<sub>op</sub> = <span id="ArsROpConcentration"></span> &micro;M<br/>
+
<!--ArsR<sub>total</sub> = <span id="ArsRT"></span> &micro;M<br/>-->
-
ArsD<sub>op</sub> = <span id="ArsDOpConcentration"></span> &micro;M<br/>
+
</dd>
-
<br/>
+
<dt>"Accumulation factor"</dt>
-
<!--As(III)<sub>total</sub> = <span id="As3TotalConcentration"></span> &micro;M<br/>-->
+
<dd>
-
As(III)<sub>total</sub>/As(III) = <span id="As3TotalFactor"></span><br/>
+
<!--As(III)<sub>total</sub> = <span id="AsinT"></span> &micro;M<br/>-->
 +
As(III)<sub>total</sub>/As(III) = <span id="AsinTfactor"></span><br/>
 +
</dd>
 +
</dl>
 +
</html>
 +
<span id="accumulationFactorData"></span>
 +
{{graph|Team:Groningen/Graphs/AccumulationFactor|id=accumulationFactorGraph}}
 +
(For constants other than the ones on the left the [[Team:Groningen/Modelling/Arsenic.js|default values]] are used.)
 +
<html>
</td>
</td>
</tr></table>
</tr></table>
-
</div>
+
</td></tr></table>
<script type="text/javascript">
<script type="text/javascript">
Line 146: Line 247:
function computeArsenicEquilibrium() {
function computeArsenicEquilibrium() {
-
  // Input
 
-
  var K1dNode = document.getElementById("K1d");
 
-
  var K2dNode = document.getElementById("K2d");
 
-
  var K3dNode = document.getElementById("K3d");
 
-
  var K4dNode = document.getElementById("K4d");
 
-
  var tau1Node = document.getElementById("tau1");
 
-
  var tau2Node = document.getElementById("tau2");
 
-
  var beta1Node = document.getElementById("beta1");
 
-
  var beta2Node = document.getElementById("beta2");
 
-
  var beta3Node = document.getElementById("beta3");
 
-
  //var As3ConcentrationNode = document.getElementById("As3Concentration");
 
-
  var OpNTotalConcentrationNode = document.getElementById("OpNTotalConcentration");
 
-
  var OpGTotalConcentrationNode = document.getElementById("OpGTotalConcentration");
 
-
  var OpHTotalConcentrationNode = document.getElementById("OpHTotalConcentration");
 
-
 
   // Intermediates (mostly useful for debugging)
   // Intermediates (mostly useful for debugging)
-
  var OpConcentrationNode = document.getElementById("OpConcentration");
 
-
  var ArsRConcentrationNode = document.getElementById("ArsRConcentration");
 
-
  var ArsDConcentrationNode = document.getElementById("ArsDConcentration");
 
-
  //var ArsRAs3ConcentrationNode = document.getElementById("ArsRAs3Concentration");
 
-
  //var ArsDAs3ConcentrationNode = document.getElementById("ArsDAs3Concentration");
 
-
  var ArsROpConcentrationNode = document.getElementById("ArsROpConcentration");
 
-
  var ArsDOpConcentrationNode = document.getElementById("ArsDOpConcentration");
 
   var errorNode = document.getElementById("arsenicEquilibriumError");
   var errorNode = document.getElementById("arsenicEquilibriumError");
   errorNode.innerHTML = '';
   errorNode.innerHTML = '';
-
 
-
  // Outputs
 
-
  //var As3TotalConcentrationNode = document.getElementById("As3TotalConcentration");
 
-
  var As3TotalFactorNode = document.getElementById("As3TotalFactor");
 
   // Read inputs
   // Read inputs
-
   var K1d = Number(K1dNode.value) * 1e-6; // micromolar -> molar
+
   var c = arsenicModelConstants();
-
   var K2d = Number(K2dNode.value) * 1e-6; // micromolar -> molar
+
  c.AsT = 0;
-
   var K3d = Number(K3dNode.value) * 1e-6; // micromolar -> molar
+
  c.K1d = getInput('K1d') * 1e-6; // micromolar -> molar
-
   var K4d = Number(K4dNode.value) * 1e-6; // micromolar -> molar
+
   c.K3d2 = Math.pow(getInput('K3d') * 1e-6,2); // micromolar -> molar
-
   var tau1 = Number(tau1Node.value) * 60; // minutes -> seconds
+
   c.KMd = getInput('KMd') * 1e-6; // micromolar -> molar
-
   var tau2 = Number(tau2Node.value) * 60; // minutes -> seconds
+
   c.KFd = getInput('KFd') * 1e-6; // micromolar -> molar
-
   var beta1 = Number(beta1Node.value); // 1/second
+
   c.nf = getInput('nf') * 1e-6; // micromolar -> molar
-
   var beta2 = Number(beta2Node.value); // 1/second
+
  c.tauR = getInput('tauR') * 60; // minutes -> seconds
-
   var beta3 = Number(beta3Node.value); // 1/second
+
   c.tauM = getInput('tauM') * 60; // minutes -> seconds
-
   //var As3Concentration = Number(As3ConcentrationNode.value) * 1e-6; // micromolar -> molar
+
  c.tauF = getInput('tauF') * 60; // minutes -> seconds
-
   var OpNTotalConcentration = Number(OpNTotalConcentrationNode.value) * 1e-6; // micromolar -> molar
+
   c.beta1 = getInput('beta1'); // 1/second
-
   var OpGTotalConcentration = Number(OpGTotalConcentrationNode.value) * 1e-6; // micromolar -> molar
+
   c.beta3 = getInput('beta3'); // 1/second
-
   var OpHTotalConcentration = Number(OpHTotalConcentrationNode.value) * 1e-6; // micromolar -> molar
+
   c.betaM = getInput('betaM'); // 1/second
-
   var OpTotalConcentration = OpNTotalConcentration + OpGTotalConcentration;
+
  c.betaF = getInput('betaF'); // 1/second
 +
   var avogadro = 6.02214179e23; // 1/mol
 +
  var Vcell = getInput('Vcell') * 1e-15; // micrometer^3/cell -> liter/cell
 +
   c.ars1T = getInput('ars1TPerCell') / (avogadro*Vcell); // 1/cell -> mol/liter
 +
   c.ars2T = 0;
 +
  c.pro = getInput('proRPerCell') / (avogadro*Vcell); // 1/cell -> mol/liter
 +
   c.proM = getInput('proMPerCell') / (avogadro*Vcell); // 1/cell -> mol/liter
 +
   c.proF = getInput('proFPerCell') / (avogadro*Vcell); // 1/cell -> mol/liter
   // Compute density(/-ies)
   // Compute density(/-ies)
   try {
   try {
-
    // Fixed point iteration
+
     var x = arsenicModelEquilibrium(c);
-
     var ArsRConcentration = 1;
+
     var ArsR = x._ArsR;
-
    var ArsDConcentration = 1;
+
    var arsFraction = x._arsF;
-
    var c2 = K4d * (tau2/Math.LN2) * beta2 * OpNTotalConcentration;
+
    var AsinTfactor = 1 + ArsR/c.K1d;
-
     if (!(c2>0)) throw new Error("c2<=0, c2="+c2);
+
-
 
+
-
    do {
+
-
      var oldArsR = ArsRConcentration;
+
-
      var b2 = 0.5 * K4d * (ArsRConcentration/K3d + 1);
+
-
      var D2 = Math.sqrt(b2*b2 + c2);
+
-
      ArsDConcentration = -b2 + D2;
+
-
      var b1 = 0.5 * (K3d * (ArsDConcentration/K4d + 1)
+
-
                      - (tau1/Math.LN2) * beta3 * OpHTotalConcentration);
+
-
      var c1 = K3d * (tau1/Math.LN2) * (beta1 * OpTotalConcentration
+
-
                                        + beta3 * OpHTotalConcentration * (ArsDConcentration/K4d + 1));
+
-
      var D1 = Math.sqrt(b1*b1 + c1);
+
-
      ArsRConcentration = -b1 + D1;
+
-
 
+
-
      // Some general assertions
+
-
      if (!(b2>0)) throw new Error("b2<=0, b2="+b2);
+
-
      if (!(ArsDConcentration>0)) throw new Error("ArsD<=0, ArsD="+ArsDConcentration);
+
-
      //if (!(b1>0)) throw new Error("b1<=0, b1="+b1);
+
-
      if (!(c1>0)) throw new Error("c1<=0, c1="+c1);
+
-
      if (!(ArsRConcentration>0)) throw new Error("ArsR<=0, ArsR="+ArsRConcentration);
+
-
 
+
-
      // Check that we don't encounter too steep a derivative
+
-
      var b2d = 0.5 * (K4d/K3d);
+
-
      var ArsDConcentrationd = -b2d + (2*b2*b2d)/D2;
+
-
      var c1d = (tau1/Math.LN2) * beta3 * OpHTotalConcentration * (K3d/K4d) * ArsDConcentrationd;
+
-
      var b1d = 0.5 * (K3d/K4d) * ArsDConcentrationd;
+
-
      var fd = -b1d + (2*b1*b1d+c1d)/D1;
+
-
      if (Math.abs(fd)>1) throw new Error("|fd|>1, no convergence?"); // According to Wikipedia
+
-
    } while(Math.abs(oldArsR-ArsRConcentration)>1e-6*Math.abs(ArsRConcentration));
+
-
 
+
-
    var OpConcentration = OpTotalConcentration/(ArsRConcentration/K3d + ArsRConcentration/K4d + 1);
+
-
    //var ArsRAs3Concentration = ArsRConcentration * As3Concentration / K1d;
+
-
    //var ArsDAs3Concentration = ArsDConcentration * As3Concentration / K2d;
+
-
    var ArsROpConcentration = ArsRConcentration * OpConcentration / K3d;
+
-
    var ArsDOpConcentration = ArsDConcentration * OpConcentration / K4d;
+
-
 
+
-
    //var As3TotalConcentration = As3Concentration + ArsRAs3Concentration + ArsDAs3Concentration;
+
-
    //var As3TotalFactor = As3TotalConcentration/As3Concentration;
+
-
    var As3TotalFactor = 1 + ArsRConcentration/K1d + ArsDConcentration/K2d;
+
   } catch(err) {
   } catch(err) {
     errorNode.innerHTML = err.message;
     errorNode.innerHTML = err.message;
Line 242: Line 285:
   // Set intermediates if they exist
   // Set intermediates if they exist
-
   if (OpConcentrationNode) setOutput(OpConcentrationNode, OpConcentration * 1e6);
+
   setOutput('arsFraction', arsFraction);
-
   if (ArsRConcentrationNode) setOutput(ArsRConcentrationNode, ArsRConcentration * 1e6);
+
   setOutput('ArsR', ArsR * 1e6);
-
  if (ArsDConcentrationNode) setOutput(ArsDConcentrationNode, ArsDConcentration * 1e6);
+
-
  //if (ArsRAs3ConcentrationNode) setOutput(ArsRAs3ConcentrationNode, ArsRAs3Concentration * 1e6);
+
-
  //if (ArsDAs3ConcentrationNode) setOutput(ArsDAs3ConcentrationNode, ArsDAs3Concentration * 1e6);
+
-
  if (ArsROpConcentrationNode) setOutput(ArsROpConcentrationNode, ArsROpConcentration * 1e6);
+
-
  if (ArsDOpConcentrationNode) setOutput(ArsDOpConcentrationNode, ArsDOpConcentration * 1e6);
+
   // Set outputs
   // Set outputs
-
   //setOutput(As3TotalConcentrationNode, As3TotalConcentration * 1e6);
+
  setOutput('AsinTfactor', AsinTfactor);
-
   setOutput(As3TotalFactorNode, As3TotalFactor);
+
 
 +
   // Draw graph
 +
  var dataNode = document.getElementById("accumulationFactorData");
 +
  var graphNode = document.getElementById("accumulationFactorGraph");
 +
  var data = {AsT:[], AsexT0:[], AsinT:[], AsinT2:[]};
 +
  var bAsin, cAsin, Asin;
 +
  // Some guesses
 +
  var c2 = {}, x2;
 +
  for(var a in c) c2[a] = c[a];
 +
  c2.v5 *= 2;
 +
  for(var AsexT0uM=0.1; AsexT0uM<=100; AsexT0uM*=1.1) {
 +
    c.AsT = c.Vs*AsexT0uM*1e-6;
 +
    c2.AsT = c.AsT;
 +
    x = arsenicModelEquilibrium(c);
 +
    x2 = arsenicModelEquilibrium(c2);
 +
    data.AsT.push(c.AsT);
 +
    data.AsexT0.push(c.AsT/c.Vs);
 +
    data.AsinT.push(x.AsinT*c.Vc/c.AsT);
 +
    data.AsinT2.push(x2.AsinT*c.Vc/c.AsT);
 +
   }
 +
  dataNode.data = data;
 +
  if (graphNode.refresh) graphNode.refresh();
}
}
</script>
</script>
</html>
</html>
-
==Planning and requirements:==
+
'''In conclusion:'''
 +
 
 +
* Even at the accumulation levels of Koster <i>et al.</i> the amount of arsenic accumulated in <i>E. coli</i> is so little that it should not matter much for the buoyant density (which normally is about 1100kg/m<sup>3</sup>).
 +
* If you substitute constitutive promotors for Ars promotors, you can see that it is clearly advantageous to use constitutive promotors as just adding ars promoters does not increase the accumulation factor. A plasmid containing an ars promoter and (just) a gene coding for ArsR behind it might contain more arsenic, but there would also be more unbound arsenic, increasing the toxicity.
 +
* The model is not very sensitive to different values for K3d (with K3d=1mM the accumulation factor is 248.06 and with K3d=1nM it is 240.57).
 +
* The accumulation factor is greatly affected by the product of the half-life of ArsR and the production rate.
 +
 
 +
<!-- ==Planning and requirements:==
* '''Modelling'''
* '''Modelling'''
** Speed
** Speed
** Metaliotheines concentration  
** Metaliotheines concentration  
 +
**      How often does the ArsR sensitive operator/operon occur in our <i>E. coli</i>?
* '''Lab'''
* '''Lab'''
** Measurements
** Measurements
 +
***    Transport Assays
 +
****    Protein expression levels determined by immunoblotting using anti-ArsA and anti-ArsD antibodies [[Team:Groningen/Literature#Lin2007-2|Lin 2007]]
 +
****    Inductively coupled mass spectrometry (ICP-MS) ([[Team:Groningen/Literature#Meng2004|Meng 2004]])
*** Measure accumulation. By measuring before/after concentration metal with and without accumulation protein.
*** Measure accumulation. By measuring before/after concentration metal with and without accumulation protein.
 +
***    Determine the dissociation constant of ArsR and As(III). (By measuring the ratio between bound and unbound ArsR?)
 +
**** It might be possible to do this with (tryptophan related) fluorescence (that is how it is done for ArsD in [[Team:Groningen/Literature#Chen1997|Chen 1997]]). In the paper ArsD is purified, but if that is not feasible for us, we might try to simply do it in living cells (and hope that ArsR both fluoresces enough and is produced enough to be measurable).
 +
***    Production rate of ArsR?
** Biobrick Bba_K129004
** Biobrick Bba_K129004
-
** Rest
+
** Rest-->
 +
 
 +
==Copper==
 +
 
 +
===MymT===
 +
 
 +
MymT is a 5kDa-protein which binds Cu(I) but also to less extend Zn(II) from ''Mycobaterterium tuberculosis''. This MT was found to bind 4-6 Cu(I) ions per molecule. Induction of the expression of MymT is the strongest with Cd and Cu. But upon over-expression of MymT in ''E. coli'', the protein becomes insoluble ([[Team:Groningen/Literature#Gold2008|Gold 2008]]). This may be caused by the fact that it is a protein from a gram-positive bacteria expressed in a gram negative bacterium. Therefore specialized cultivation conditions are needed, the cells should be grown at a low temperature (16 &deg;C). The functionality of MymT can be measured by fluorescence spectroscopy, as also found for other copper binding metallothioneins. Copper bound to MT create Cu-thiolates which can be excited at 280nm and gives a Stokes shift towards 600 nm ([[Team:Groningen/Literature#Beltramini1981|Beltramini 1981]]).
 +
 
 +
====Results:====
 +
PCR on ''mym''T from pGB68 unfortunately did not give any correct cDNA fragments, even though the primer quality was improved ([[Team:Groningen/Protocols|Protocol Biobrick primers]]). Therefore the sub-project was discontinued.
 +
 
 +
==Zinc==
 +
Below toxic concentrations, zinc is essential for many biological processes. Examples are enzymatic hydroxylation, DNA and RNA synthesis, transcription and translation, signal transduction and apoptosis regulation  ([[http://en.wikipedia.org/wiki/Zinc 1]] and [[Team:Groningen/Literature#Blindauer2001|Blindauer 2001]]). Methallothioneins can adjust the zinc absorption up to 14-40%, though a real excess of zinc can be toxic. A daily intake of 100–300 mg Zn/day can give rise to copper / iron deficiency and damage of nerve receptors ([[Team:Groningen/Literature#Fosmire1990|Fosmire 1990]]). Examples of metallothioneins sequestering zinc, are SmtA from the cyanobacterium ''Synechococcus'' PCC7942 ([[Team:Groningen/Literature#Blindauer2001|Blindauer 2001]]), ZiaR from ''Synechocystis'' PCC 6803 ([[Team:Groningen/Literature#Robinson2001|Robinson 2001]]), human metallothioneins like MT-1 and -2. The mammalian proteins were found to bind 7 Zn<sup>2+</sup> ions by the thiolate-group of there cysteins.
 +
 
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===SmtA===
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SmtA is a MT from ''Synechococcus'' PCC 6803, it was found to bind 3-4 Zn<sup>2+</sup> ions and is supposed to have a function in preventing zinc toxicity ([[Team:Groningen/Literature#Blindauer2001|Blindauer 2001]]), but it also binds copper and cadmium ([[Team:Groningen/Literature#Shi1992|Shi 1992]]).  Upon binding of Zn<sup>2+</sup>, the glutathione transferase fusion-protein showed a 1:3 stoichiometry and SmtA a 1:4 stoichiometry ([[Team:Groningen/Literature#Robinson2001|Robinson 2001]]). SmtA binds the 4 Zn<sup>2+</sup> ions via cysteine thiolate-bridges, forming a Zn<sub>4</sub>Cys<sub>11</sub> cluster whichs was also found in mammalian MT, though these proteins do not have a homologous DNA sequence ([[Team:Groningen/Literature#Blindauer2001|Blindauer 2001]]). ''SmtA'' is found on an operon with it's transcriptional regulator ''smtB''. SmtB releases from the promoter-operator region in front of this operon, when it binds Zn via its metal binding motif. SmtB and [[Team:Groningen/Project/Accumulation#Arsenic|ArsR]] (negative transcriptional regulator binding arsenic) have similar functionalities but differ in metal binding motifs ([[Team:Groningen/Literature#Robinson2001|Robinson 2001]]). That ''Synechococcus'' is a gram negative bacterium might increase the possibility of functional and stable overexpression in ''E. coli'' .
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===Results===
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PCR reactions to amplify SmtA from pET29a and SmtA-GST from pGEX-3x were successful, but unfortunately the DNA sequence used to design the SmtA primers was not correct so therefore wrong cDNA fragments were amplified. Because it was too late to order new primers, this sub-project was discontinued.
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<!--==Alternatives==
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{{todo|Inclusion bodies}} ([[Team:Groningen/Literature#Fowler1987|Fowler 1987]])<br>
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{{todo|(Bacterio)Ferritins}}<br>
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{{todo|Phytochelatins}}<br>
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[http://www.wiley.com/legacy/products/subject/reference/messerschmidt_toc.html A list of opportunities]
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==Inhibitory characteristics?==-->
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==Literature==
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{{Team:Groningen/Project/Footer}}
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#{{todo|Brady <i>et al.</i>:[http://www.ncbi.nlm.nih.gov/pubmed/18618649 The use of hollow fiber cross-flow microfiltration in bioaccumulation and continuous removal of heavy metals from solution by <i>Saccharomyces cerevisiae</i>], Biotechnology and bioengineering (1994) 44(11);1362-1366}}
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#Cadosch <i>et al.</i>: [http://www.ncbi.nlm.nih.gov/pubmed/19133293 Uptake and intracellular distribution of various metal ions in human monocyte-derived dendritic cells detected by Newport Green DCF diacetate ester]  Journal of Neuroscience Methods (2009) 178(1);182-187
+
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#<b>Chang <i>et al.</i>:[http://www.ncbi.nlm.nih.gov/pubmed/9579658 Cysteine contributions to metal binding preference for Zn/Cd in the b-domain of metallothionein], Protein Engineering 1998 11(1);41–46</b>
+
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#Chen <i>et al.</i>: [http://www.ncbi.nlm.nih.gov/pubmed/9758654 Hg<SUP><FONT SIZE="-1">2+</FONT></SUP> removal by genetically engineered Escherichia coli in a hollow fiber bioreactor], Biotechnology progress (1998) 14(5);667-71
+
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#Chen & Wilson: [http://www.ncbi.nlm.nih.gov/pubmed/9342882 Genetic engineering of bacteria and their potential for Hg<SUP><FONT SIZE="-1">2+</FONT></SUP>  bioremediation], Biodegradation (1997) 8(2);97-103
+
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#Deng <i>et al.</i>:[http://www.ncbi.nlm.nih.gov/pubmed/16890348 Cadmium removal from aqueous solution by gene-modified Escherichia coli JM109] Journal of hazardous materials (2007) 139(2);340-4
+
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#Deng <i>et al.</i>: [http://www.ncbi.nlm.nih.gov/pubmed/17920767 Continuous treatment process of mercury removal from aqueous solution by growing recombinant E. coli cells and modeling study], Journal of hazardous materials (2008) 153(1-2);487-92
+
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#Deng <i>et al.</i>: [http://www.ncbi.nlm.nih.gov/pubmed/12727263 Bioaccumulation of nickel from aqueous solutions by genetically engineered Escherichia coli], Water research (2003) 37(10);2505-11.
+
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#Fowler: [http://www.ncbi.nlm.nih.gov/pubmed/3297654 Intracellular Compartmentation of Metals in Aquatic Organisms: Roles in Mechanisms of Cell injury], Environmental Health Perspectives (1987) 71;121-128
+
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#Kao <i>et al.</i>: [http://www.ncbi.nlm.nih.gov/pubmed/18313216 Biosorption of nickel, chromium and zinc by MerP-expressing recombinant Escherichia coli], Journal of hazardous materials (2008) 158(1);100-106
+
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#Kostal <i> et al.</i>: [http://www.ncbi.nlm.nih.gov/pubmed/15294789 Enhanced Arsenic Accumulation in Engineered Bacterial Cells Expressing ArsR], Applied and environmental microbiology (2004) 70(8);4582–4587
+
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#Ngu & Stillman: [http://www.ncbi.nlm.nih.gov/pubmed/16984198 Arsenic binding to human metallothionein], Journal of the American Chemical Society (2006) 128(38);12473-83.
+
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#Singh <i>et al.</i>: [http://www.ncbi.nlm.nih.gov/pubmed/18326684 Highly Selective and Rapid Arsenic Removal by Metabolically Engineered <i>Escherichia coli Cells</i> Expressing <i>Fucus vesiculosus</i> Metallothionein] Applied and environmental microbiology (2008) 74(9);2924-7
+
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#Yung-Fen <i>et al.</i>: [http://www.jbc.org/cgi/content/full/282/23/16783?view=long&pmid=17439954 ArsD Residues Cys12, Cys13, and Cys18 Form an As(III)-binding Site Required for Arsenic Metallochaperone Activity], The Journal of Biological Chemistry (2007) VOL 282(23); 16783–16791
+
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#Yung-Fen <i>et al.</i>: [http://www.springerlink.com/content/684280r475276335/ ArsD: an As(III) metallochaperone for the ArsAB As(III)-translocating ATPase], Journal of Bioenergetics and Biomembranes (2007) 39;453-458
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Latest revision as of 22:10, 21 October 2009

[http://2009.igem.org/Team:Groningen http://2009.igem.org/wiki/images/f/f1/Igemhomelogo.png]
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Accumulation

Once heavy metals have entered the cell, it is crucial to keep them there. As these metals are toxic to cell survival in critical amounts, evolution has provided us with biological detoxicification proteins such as [http://en.wikipedia.org/wiki/Metallothionein metallothioneins]. These proteins can aid us in our quest to accumulate a variety of heavy metals as they bind to a wide range of metals including cadmium, zinc, mercury, copper, arsenic, silver, coordinated in metal-thiolates. The metal chelating proteins are cloned in a synthetic operon with a metal specific transporter to make up the accumulation device. For arcummulation of arsenite fMT and ArsR used, which were characterized by our model. Enhanced arsenite uptake by E. coli fMT could not be determined by the arsenite uptake assay, where the internal arsenic concentration was measured by ICP-MS.

Metallothioneins

Metallothioneins are a class of low molecular-weight metal-binding proteins (<10kDa) rich in cysteines residues(~30%). They contain a conserved cys-x-cys or cys-x-his motif which coordinates metal binding, as can be seen in zinc finger depicted in figure 1. They are capable of binding a variety of heavy metals (e.g. Zn, Cu, Cd, Hg, As) with high avidity (Kb), they are in vivo used as a defense against oxidative stress by chelating metals. These proteins also have a function in storing, detoxifying and distributing metals throughout the cell (Merrifield 2004, Gold 2008). These proteins have been readily used to create cell based systems for purification of contaminated water (Chen 1998, Brady 1994). In addition to their wide application possibilities, they also have the capacity to carry multiple metal ions at one time, in contrast to some other metalloproteins that carry them one-on-one (Chang 1998). Many forms of metallothioneins are known and their affinity for different metals has been investigated on several occasions, such as for cadmium (Deng 2007), arsenic (Ngu 2006, Kostal 2004, Singh 2008), mercury (Chen 1998, Chen 1997-2, Deng 2008), nickel (Deng 2003) or a combination of metals (Chang 1998, Kao 2008). Metal-protein complexes can be quantified using a fluorescent molecule (Cadosch 2008) but Cu(I) binding to metallothioneins in metal thiolates, was shown to cause a concentration dependant increase in luminescence. These Cu(I) binding metallothioneins were shown to give rise to a Stokes shift of approximately 300 nm upon excitation at 280 nm (Beltramini 1981, Gold 2008).


800px-Zinc finger rendered.png
Figure 1: Zinc finger protein, consisting of a α-helix and an anti-parallel β-sheet. The zinc atom (green) is bound by two histidines and two cysteines.

Cloning strategy

In order to have a functional accumulation device, the cDNA of a metallothionein (MT) will be amplified using [http://en.wikipedia.org/wiki/PCR PCR] and cloned into , also a corresponding metal-ion transporter was amplified by PCR and cloned behind the MT. Both will expressed by one promoter (constitutive or lactose inducible). In this way the bacterium will take up the metal-ion and consecutively the metal-ion will be sequestered by the MT. When this device is combined with the floating device, the bacteria will start floating when a certain threshold of intracellular metal concentration is reached, because the negative regulator of the buoyancy device will be released and the gas vesicle cluster can be transcribed.

Accumulation device.PNG
Figure 2: Cloning strategy for the metal accumulation device. A promoter taken from will be cloned in front of a metallothionein and a metal transporter in a vector. This device will be combined with the floating device.

Practical note

MTs are degraded intracellular inside lysozymes, especially when they are in the apo/non-bound state (Gold 2008), for bacteria the degradation rate is not known, but for mammalian MT this can be estimated around 0.8 nmol apo-MT/mg protein/min (Klaassen 1994). This can be avoided by adding metal-salts (ZnCl2, CuSO4, CdCl2) to cells expressing the protein.

Metals

Arsenic

For the accumulation of arsenic some MTs are possible, like rh-MT (human MT) (Ngu 2006) and fMT (the seaweed species Fucus vesiculosis) both binding As(III). The oxidized version of arsenic (As (V)) can also be bound by the metallothioneins but with lower affinity (Singh 2008), another way As(V) is proposed to be accumulated is by conversion of As(V) to As(III) by the arsenate reductase and subsequent bound to the metallothionein or ArsR. rh-MT is known to bind 6x As(III) per molecule, fMT binds 5x As(III). No extra quantitative information is known from literature.

ArsR

ArsR is a trans-acting repressor that senses environmental As(III) and regulates the chromosomal ars operon. The ArsR protein has a specific binding site for As(III) and discriminates effectively against other metals like: phosphate, cadmium, sulfate and cobalt. The affinity of ArsR for As(III) is very high 10-15 M of AS(III) can induce the promotor. The specific binding site spans 33 nucleotides in the promotor region including the putative -35 promotor element. When ArsR was purified, its size corresponded to that of a homodimer, bound to promoter DNA. Because of the high affinity of ArsR for As(III) the protein could be used for arsenic remediation. Chen and co-workers overexpressed ArsR in E. coli JM109 cells and found that the specific AS(III) content was 13-fold higher than the control without ArsR expression. High level expression of ArsR appeared to be toxic as a 3-fold reduction in cell density was observed. It has been shown that fusion partners reduce the toxicity of overexpression. Originally, Chen and co-workers made a fusion between ArsR and ELP (elastin protein), which is build out of VPGVG repeats. Because making a ArsR ELP153 fusion is very time consuming, we choose to make a fusion between MBP (maltose binding protein) and ArsR (Chen 1998).
Also see the Metal sensitive promoters. As ordering rh-MT was not successful, we try to use fMT for accumulation of As(III) and use ArsR to regulate the expression of the gvp cluster behind the ArsR regulated promoter.

Results

The fusion protein MBP-ArsR was built by creating giving the reverse primer of the MBP and the Forward primer of the ArsR a mutual restriction site SacI. The linker region was designed in such a way that it contained a Tev cleavage site, containing a SacI restriction site and a string of alanine residues to facilitate folding. The fusion protein has been succesfully cloned into the vector creating biobrick [http://partsregistry.org/Part:BBa_K190027 BBa_K190027], but further attempts to add a promotor and rbs failed. Due to time the MBP-ArsR fusion protein has not been equipped with a promotor and so overexpression could not be established.

fMT

The Fucus Metallothionein (fMT) was isolated from the [http://en.wikipedia.org/wiki/Seaweed macroalgae] [http://en.wikipedia.org/wiki/Fucus_vesiculosus Fucus vesiculosus ](Morris 1999). It consists of 67 amino acid residues and has 16 cysteine residues, a high cysteine content is a key feature of MT. Another characteristic is the lack of aromatic residues is also seen in fMT where it only has one, tryptophan. Two domains containing cysteine residues are presumed to be involved in the metal binding function. Unusual in fMT is the presence of a 14 amino acid linker region between the two putative metal-binding domains which contains no cysteine residues. Plant MTs show this feature with about 40 residues, where vertebrate MTs only have three residues (Morris 1999). Being a MT, fMT binds a multitude of metal ions, 6 Cd2+ ions or 5 As3+ ions in a sequential order, facilitated by the elongated linker domain (Ngu 2009). The organisms from which fMT was first isolated are known to have the ability to survive in highly metal polluted water and with it having been expressed in E. coli previously (Singh 2008) it was an ideal choice to use as an arsenic sequestering protein.


Results

Arsenite uptake assays were done to determine the As(III) accumulation of E. coli WT and fMT / GlpF overexpression strains. The concentration was measured by ICP-MS.

The arsenic uptake in E. coli WT (figure 3) as measured during this project (by [http://www.rikilt.wur.nl/NL/ RIKILT], Wageningen University), was compared with the uptake of E. coli with ArsR overexpression (described by Kostal 2004, see figure 3). This shows that the arsenic uptake in E. coli WT behaves similar but has lower final As(III) uptake yield. The difference is about 10% in the standard mode, but a higher extracellular arsenic concentration seems to be needed to saturate the uptake of arsenic in E. coli WT compared to E. coli with ArsR overexpression. This can be seen by comparing the transition point to saturation in figure 3, which are respectively around 50 µM As(III) and around 20 µM.

UptakeEquilibrium.png
Figure 3: Uptake of As(III) by E. coli WT (containing pSB1A2-pLac)

There is a relatively large difference between the data generated by measuring the arsenic concentration with ICP-MS in the standard mode and measuring in the collusion cell technology mode (CCT mode). The difference between these two techniques is that in the standard mode it is possible that multi-atomic compounds lead to interference with the arsenic (mw = 75) peak, like argon-chloride (Ar = 40 + Cl = 35 (75%) or 37 (25%)). Because 25% of this compound is found in the mw = 77 peak, a correction factor may be calculated to correct for this, the ICP-MS software (Thermo) automatically corrects for Ar-Cl interference. It uses the amount of Krypton and Selenium for this correction. In the CCT all multi-atomic compounds are supposed to be decomposed, therefore no interference will be found in this mode. But a disadvantage of this mode is that the resolution is 10x lower than the standard mode, leading to a smaller signal-to-noise ratio. Because of this, we decided to use the standard mode (corrected for interference) to determine the arsenic accumulation by E. coli.

A second arsenic measurement was performed (by [http://www.vwa.nl/portal/page?_pageid=119,1639634&_dad=portal&_schema=PORTAL Food and Consumer Product Safety Authority], Groningen) using E. coli WT and E. coli containing the accumulation device () and the different parts (GlpF () and fMT ()). The data was measured in the standard mode and the calculated arsenic imported by the cells is shown in figure 4.

UptakeEquilibrium2.png
Figure 4: Uptake of As(III) by E. coli WT, and the strains containing the different parts of the accumulation device. As a control the arsenic uptake of E. coli with ArsR overexpression (as described by Kostal 2004) is also shown.
The curves in this figure show that there is no difference between the arsenic uptake by E. coli WT and by E. coli plus (parts of) the accumulation device. As a second observation, it can be seen that the uptake of arsenic in measured here is higher than found before (figure 3). A ratio of 2-3x was found for the WT strains (
pSB1A2
and pArsR-RFP). These two differences will be discussed below. fMT shows exceptionally low arsenite uptake, this may be caused by incidentally "burning" the already dried cells at ~100;deg&C.

The raw data can be found at downloads.

Discussion

Between the two data sets there are a few differences, first there seems to be no difference between arsenic uptake in WT and E. coli with the accumulation device (or parts of this). Secondly, the data of arsenic uptake by E. coli WT could was not reproducible and the last data set showed a arsenic uptake which was even higher for E. coli WT than the E. coli ArsR overexpression strain.

  • Why is there no difference between the E. coli WT and the E. coli with accumulation device?

This can be caused by non-functional expression of one of the genes (fMT or GlpF) or both. For membrane proteins it is known that functional overexpression is harder than for cytoplasmic proteins (Lundstom 2006). This could be tested by doing As(III) uptake/binding experiments with purified proteins, but this requires protein purification which could be facilitated by the addition of a his-tag (not present yet). The function of the transporter can be tested by measuring the uptake in membrane vesicles and that of the accumulation protein can be tested by measuring metal binding for instance by isothermal titration calorimetry. Otherwise the proteins may not be produced at all, this should be tested by protein purification or SDS-page. Another possibility is that these proteins cannot be produced by E. coli at once, though functional expression was already proven by Singh et al. (Singh 2008).

  • Non reproducible concentrations of arsenic, imported by E. coli WT, which can be seen as there is a large difference (2-3x) in arsenic uptake determined from the first and the second measurement. All data from the second ICP-MS arsenic determination, were also unexpectedly higher than was found in literature (Kostal 2004, Singh 2008). This discrepancy may be caused by one of the following reasons.

During the second arsenic uptake assay the time between the incubation and washing the cells was decreased to the minimum though during the first assay there was some time for the cells to export the As(III) via their exporter ArsB. This may have caused the lower uptake yield of arsenic in the first data set. Also there was a difference in cell concentration, in the second assay this was 2.5 times higher. It is presumable that with a higher cell concentration the uptake rate is slower but a saturating incubation time (>1hr) might cause that the equilibrium of arsenite concentration in/outside the cell is reached faster. After destruction of the samples of the first data set, the samples did not become a clear solution but a suspension containing white flakes. These were removed by centrifugation, but this seems to indicate incomplete destruction. This was not the case for the second samples, therefore an increased arsenite concentration may be measured as arsenite bound to the white flakes is not measured. It also might be, that during the second arsenite uptake assay the cells were washed less properly causing the concentration to become way higher than the first measurement. A more acidic buffer should be used for washing the cells, because this should be more efficient in removing metal ions than the TB74S buffer (pH 7.4), but as this protocol was the same as described by Kostal 2004, this should be a major problem. The expected increase in arsenic concentration should be linear with the external arsenite concentration, but this was not seen (figure 4), a clear saturation curve was seen. A plausible cause is that there was a mistake in the calculations, a correction factor which was forgotten to correct for. Another plausible cause is that the concentration is higher because the measured concentration was for some samples 5 times higher than the calibration range. It might be that linear extrapolation is not correct. This can cause the structural increased arsenic uptake.

  • Other considerations:

-Metal buffer interactions, causing a lower free-As(III) concentration surrounding the cell suspension. -Arsenic oxidation in aerobic conditions to As(V), this equilibrium may change over hours, so if the stock solution is enriched with As(V) it may take hours before it is changed to As(III) again. - Binding of other metal ions to the metallothionein causing competition for arsenite binding to fMT. Possible metal ions can be: Copper(I) or other metal ions present in the undefined LB medium. A requiry is that the metal ion should bind stronger or as strong to the MT as arsenite, which binds less strongly to MT than Zn(II) for instance or Cu(I).

Conclusion

The data generated by the arsenic uptake assay and ICP-MS determination of internal arsenic concentrations were unfortunately not reproducable. According to the first measurement, the uptake of arsenic by E. coli WT showed a little lower final yield and a higher concentration where the system becomes saturated. Because of the lack of reproducibility of the measurements and the extremely high intracellular arsenic concentration found during the second measurement, it cannot be determined whether fMT enhances the arsenic accumulation. In addition, the second measurement showed no difference between WT and the overexpression strains of GlpF, fMT or the fMT-Glpf operon. To establish the functionality of fMT, the arsenic uptake assay should be redone.

Modelling

Arsenic - ArsR

Below you can calculate how many grams of arsenic will be taken out of the water per cubic meter of cells. This extra weight raises the density of the cell and therefore lowers its capacity for buoyancy. Our preliminary results look very promising. Even under the assumption that the weight of the metal is added to the weight of the cells, without increasing their volume, we could add up to a hundred times the currently computed weight without having a large effect on the required fraction of gas vesicles (it will only go up from about 12.2% to 12.7%).

At this moment we use four different variables:

  1. Molecular weight of arsenic. Source: [http://en.wikipedia.org/wiki/Arsenic Arsenic page on Wikipedia]
  2. Millimol arsenic per kg of cell dryweight (note that this is equivalent to nmol/mg). Source: Kostal 2004
  3. The proportion between the weight of a dry cell and a wet cell. Source: [http://redpoll.pharmacy.ualberta.ca/CCDB/cgi-bin/STAT_NEW.cgi CCDB Database]
  4. Cell density. Source: see our gas vesicle page.
awAs(III) = g/mol
nAs(III) / Mcell(dry) = millimole/kg
Mcell(dry) / Mcell(wet) =
ρcell = kg/m3

As(III) intake per volume of cells
= g/m3
= µmol/liter

As per cell volume = awAs * nAs(III) /
   Mcell(dry) * Mcelldrywet * rhocell
mol As per cell volume = nAs(III) / 
   Mcell(dry) * Mcelldrywet * rhocell

Arsenic accumulation.png

At a lower level arsenic accumulation can be described using reactions between ArsR, As(III) and the ars promoter. As shown in the figure on the right, a number of different substances(/complexes) are involved. For our purposes it is especially important to determine what fraction of As(III) is unbound, if more As(III) is bound we can accumulate more.

In addition to binding to As(III), ArsR can repress Ars, creating a negative feedback loop. In effect this regulates the production of ArsR based on the As(III) concentration (Chen 1997). In the E. coli top 10 there is only ars promoter present on the genome to produce ArsR (see BLAST results). There are plasmids which produce both ArsR and ArsD, but these are not used in this project. We intend to introduce instead a constitutive promoter (pro), which produces just ArsR, in order to bind as much As(III) as possible.

The calculator below tries to compute the ratio between bound and unbound arsenic, specifically As(III), in the cell. See our Modelling page for detailed information on the constants/variables used and a derivation of the formulas. Note that the computations currently involve slightly more variables/constants than strictly necessary.

Dissociation constants
KRd (ArsRAs) = µM (??)
KAd (ArsRars) = µM (Chen1997)
KMd (MBPArsRAs) = µM (???)
KFd (fMTArsRAs) = µM (???)
nf = (???)
Half-lifes
τR (ArsR) = min (???)
τM (MBPArsR) = min (???)
τF (fMT) = min (???)
Production rates of the promoters
βRN (ars1 → ArsR) = 1/second (???)
βR (proR → ArsR) = 1/second (???)
βM (proM → MBPArsR) = 1/second (???)
βF (proF → fMT) = 1/second (???)
Promoter concentrations
ars1total = per cell
proR = per cell (??)
proM = per cell (??)
proF = per cell (??)
Vcell = µm3 ([http://gchelpdesk.ualberta.ca/CCDB/cgi-bin/STAT_NEW.cgi| CCBD])

ArsR
ars / arstotal =
ArsR = µM
"Accumulation factor"
As(III)total/As(III) =

Loading graph...

(For constants other than the ones on the left the default values are used.)

In conclusion:

  • Even at the accumulation levels of Koster et al. the amount of arsenic accumulated in E. coli is so little that it should not matter much for the buoyant density (which normally is about 1100kg/m3).
  • If you substitute constitutive promotors for Ars promotors, you can see that it is clearly advantageous to use constitutive promotors as just adding ars promoters does not increase the accumulation factor. A plasmid containing an ars promoter and (just) a gene coding for ArsR behind it might contain more arsenic, but there would also be more unbound arsenic, increasing the toxicity.
  • The model is not very sensitive to different values for K3d (with K3d=1mM the accumulation factor is 248.06 and with K3d=1nM it is 240.57).
  • The accumulation factor is greatly affected by the product of the half-life of ArsR and the production rate.


Copper

MymT

MymT is a 5kDa-protein which binds Cu(I) but also to less extend Zn(II) from Mycobaterterium tuberculosis. This MT was found to bind 4-6 Cu(I) ions per molecule. Induction of the expression of MymT is the strongest with Cd and Cu. But upon over-expression of MymT in E. coli, the protein becomes insoluble (Gold 2008). This may be caused by the fact that it is a protein from a gram-positive bacteria expressed in a gram negative bacterium. Therefore specialized cultivation conditions are needed, the cells should be grown at a low temperature (16 °C). The functionality of MymT can be measured by fluorescence spectroscopy, as also found for other copper binding metallothioneins. Copper bound to MT create Cu-thiolates which can be excited at 280nm and gives a Stokes shift towards 600 nm (Beltramini 1981).

Results:

PCR on mymT from pGB68 unfortunately did not give any correct cDNA fragments, even though the primer quality was improved (Protocol Biobrick primers). Therefore the sub-project was discontinued.

Zinc

Below toxic concentrations, zinc is essential for many biological processes. Examples are enzymatic hydroxylation, DNA and RNA synthesis, transcription and translation, signal transduction and apoptosis regulation (http://en.wikipedia.org/wiki/Zinc 1 and Blindauer 2001). Methallothioneins can adjust the zinc absorption up to 14-40%, though a real excess of zinc can be toxic. A daily intake of 100–300 mg Zn/day can give rise to copper / iron deficiency and damage of nerve receptors (Fosmire 1990). Examples of metallothioneins sequestering zinc, are SmtA from the cyanobacterium Synechococcus PCC7942 (Blindauer 2001), ZiaR from Synechocystis PCC 6803 (Robinson 2001), human metallothioneins like MT-1 and -2. The mammalian proteins were found to bind 7 Zn2+ ions by the thiolate-group of there cysteins.

SmtA

SmtA is a MT from Synechococcus PCC 6803, it was found to bind 3-4 Zn2+ ions and is supposed to have a function in preventing zinc toxicity (Blindauer 2001), but it also binds copper and cadmium (Shi 1992). Upon binding of Zn2+, the glutathione transferase fusion-protein showed a 1:3 stoichiometry and SmtA a 1:4 stoichiometry (Robinson 2001). SmtA binds the 4 Zn2+ ions via cysteine thiolate-bridges, forming a Zn4Cys11 cluster whichs was also found in mammalian MT, though these proteins do not have a homologous DNA sequence (Blindauer 2001). SmtA is found on an operon with it's transcriptional regulator smtB. SmtB releases from the promoter-operator region in front of this operon, when it binds Zn via its metal binding motif. SmtB and ArsR (negative transcriptional regulator binding arsenic) have similar functionalities but differ in metal binding motifs (Robinson 2001). That Synechococcus is a gram negative bacterium might increase the possibility of functional and stable overexpression in E. coli .

Results

PCR reactions to amplify SmtA from pET29a and SmtA-GST from pGEX-3x were successful, but unfortunately the DNA sequence used to design the SmtA primers was not correct so therefore wrong cDNA fragments were amplified. Because it was too late to order new primers, this sub-project was discontinued.