Team:Stockholm/Modelling/model discuss

From 2010.igem.org

(Difference between revisions)

Latest revision as of 19:44, 27 October 2010

How predictive and precise can this model be?

This model lacks lots of details in it, so it can't be a precise model for calculating a steady state for a protein production in bacteria. But the toy model that we presented in the final equations for a gene in our plasmid can be extended and one needs to take into account several factor before extending the model to a more informative one.

Good timing: Since we are using CPP fused to our proteins this could be interesting to consider critical CPP concentrations in bacteria. Because it is hypothesized that CPP can lead to its host's death by penetrating membrane.
Rare codons: Will process stall because of rare codons? The amount of rare codons, and how repetitivet they are is an important factor. (for more information look in [5] and [6])
RNAP: How strong will RNAP bind? and How long is the transcription initiation time? This is very interesting question, since in our model we didn't consider them (because we removed time delays in our final set of equations)
Diffusion time: Do you really need to worry about diffusion? if yes, then this will introduce another type of delay which is usually negligible.
CPP interactions: If your proteins are fused with CPPs, then the only case that you need to take care of is the amount of secretion. So one needs to take care of external concentration and if it is lethal to its host.

References

Analysis of the Lactose Metabolism in E Coli Using Sum of Squares Decomposition. A. Ahmadzadeh, A. Halasz, S. Prajna, A. Jadbabaie, V. Kumar. Proceedings of the IEEE Conference on Decision and Control (CDC), Seville, Spain. 2005
Feedback Regulation in the Lactose Operon: A Mathematical Modeling Study and Comparison with Experimental Data Necmettin Yildirim and Michael C. Mackey, Biophys J. 2003 May; 84(5): 2841–2851.
All things must pass: contrasts and commonalities in eukaryotic and bacterial mRNA decay, Joel G. Belasc, Nature Reviews Molecular Cell Biology 11, 467-478 (July 2010) | doi:10.1038/nrm2917
Mathematical modeling of translation initiation for the estimation of its efficiency to computationally design mRNA sequences with desired expression levels in prokaryotes, Dokyun Na, Sunjae Lee and Doheon Lee, BMC Systems Biology 2010, 4:71doi:10.1186/1752-0509-4-71
Codon usage determines translation rate in Escherichia coli, Michael A. Sørensen1, C. G. Kurland and Steen Pedersen, J Mol Biol. 1989 May 20;207(2):365-77
Cooperation Between Translating Ribosomes and RNA Polymerase in Transcription Elongation, Sergey Proshkin, A. Rachid Rahmouni, Alexander Mironov, Evgeny Nudler, Science 23 April 2010: Vol. 328. no. 5977, pp. 504 - 508 DOI: 10.1126/science.1184939
Bremer H, Dennis PP: Modulation of chemical composition and other parameters of the cell by growth rate. In: Escherichia coli and Salmonella: Cellular and Molecular Biology (edited by Neidhart F. C. et al.), ASM Press, Washington DC, ed. 2 1996 , 1553-1569.
The mathematics of tanning, Josef Thingnes, Leiv Øyehaug, Eivind Hovig, and Stig W Omholt, BMC Systems Biology 2009, 3:60doi:10.1186/1752-0509-3-60

The Faculty of Science at Stockholm University

Swedish Vitiligo association (Svenska Vitiligoförbundet)

@@ Line 1: / Line 1: @@
 {{Stockholm/modelling}}
 __NOTOC__
 {|
 |[[image:SU_modelling_Icon.gif|200px]]
@@ Line 7: / Line 6: @@
 |width="590px"|
 <div align="justify">
-=== Discussion ===
+=== How predictive and precise can this model be? ===
-==== References ====
+This model lacks lots of details in it, so it can't be a precise model for calculating a steady state for a protein production in bacteria. But the '''toy model''' that we presented in the final equations for a gene in our plasmid can be extended and one needs to take into account several factor before extending the model to a more informative one.
-# Analysis of the Lactose Metabolism in E Coli Using Sum of Squares Decomposition.
-A. Ahmadzadeh, A. Halasz, S. Prajna, A. Jadbabaie, V. Kumar.
-Proceedings of the IEEE Conference on Decision and Control (CDC), Seville, Spain. 2005
-# Feedback Regulation in the Lactose Operon: A Mathematical Modeling Study and Comparison with Experimental Data
+#'''Good timing''': Since we are using CPP fused to our proteins this could be interesting to consider critical CPP concentrations in bacteria. Because it is hypothesized that CPP can lead to its host's death by penetrating membrane.
-Necmettin Yildirim and Michael C. Mackey,
+#'''Rare codons''': Will process stall because of rare codons? The amount of rare codons, and how repetitivet they are is an important factor. (for more information look in [5] and [6])
-Biophys J. 2003 May; 84(5): 2841–2851.
+#'''RNAP''': How strong will RNAP bind? and How long is the transcription initiation time? This is very interesting question, since in our model we didn't consider them (because we removed time delays in our final set of equations)
+#'''Diffusion time''': Do you really need to worry about diffusion? if yes, then this will introduce another type of delay which is usually negligible.
+#'''CPP interactions''': If your proteins are fused with CPPs, then the only case that you need to take care of is the amount of secretion. So one needs to take care of external concentration and if it is lethal to its host.
-# All things must pass: contrasts and commonalities in eukaryotic and bacterial mRNA decay
-Joel G. Belasc
-Nature Reviews Molecular Cell Biology 11, 467-478 (July 2010) | doi:10.1038/nrm2917
-# Mathematical modeling of translation initiation for the estimation of its efficiency to computationally design mRNA sequences with desired expression levels in prokaryotes Dokyun Na1,2, Sunjae Lee1 and Doheon Lee*1
+==== References ====
-Codon usage determines translation rate in Escherichia coli*1 Michael A. Sørensen1, C. G. Kurland2 and Steen Pedersen1
+# Analysis of the Lactose Metabolism in E Coli Using Sum of Squares Decomposition. A. Ahmadzadeh, A. Halasz, S. Prajna, A. Jadbabaie, V. Kumar. Proceedings of the IEEE Conference on Decision and Control (CDC), Seville, Spain. 2005
-Varying Rate of RNA Chain Elongation during rrn Transcription in Escherichia coli P. P. Dennis,1* M. Ehrenberg,2 D. Fange,2 and H. Bremer3
+# Feedback Regulation in the Lactose Operon: A Mathematical Modeling Study and Comparison with Experimental Data Necmettin Yildirim and Michael C. Mackey, Biophys J. 2003 May; 84(5): 2841–2851.
-Cooperation Between Translating Ribosomes and RNA Polymerase in Transcription Elongation Sergey Proshkin,1,2 A. Rachid Rahmouni,3 Alexander Mironov,2 Evgeny Nudler1,
+# All things must pass: contrasts and commonalities in eukaryotic and bacterial mRNA decay, Joel G. Belasc, Nature Reviews Molecular Cell Biology 11, 467-478 (July 2010) | doi:10.1038/nrm2917
-=== Network analysis and prove of concept ===
+# Mathematical modeling of translation initiation for the estimation of its efficiency to computationally design mRNA sequences with desired expression levels in prokaryotes, Dokyun Na, Sunjae Lee and Doheon Lee, BMC Systems Biology 2010, 4:71doi:10.1186/1752-0509-4-71
-[[Image:Net_Image_confidence_View_igem_stockholm_modelling_report.png|590px|thumb|center|Figure 1 Produced by STRING database Jensen et al. Nucleic Acids Res. 2009, 37(Database issue):D412-6]]
+# Codon usage determines translation rate in Escherichia coli, Michael A. Sørensen1, C. G. Kurland and Steen Pedersen, J Mol Biol. 1989 May 20;207(2):365-77
+#Cooperation Between Translating Ribosomes and RNA Polymerase in Transcription Elongation, Sergey Proshkin, A. Rachid Rahmouni, Alexander Mironov, Evgeny Nudler, Science 23 April 2010: Vol. 328. no. 5977, pp. 504 - 508 DOI: 10.1126/science.1184939
-Currently Wet-lab members are working on several proteins that according to previous research have been pointed out to have a positive effect on repigmentation of vitiligo affected skin areas. The idea behind why we chose the biomolecules of interest is presented under the section planning on our wiki homepage.  In this section we try to explain a simple interaction network of the specific genes coding the biomolecules. The goal is to give a clear picture of how the genes interact with other potential genes in a way that could result a restroring of the affected skin color.
+#Bremer H, Dennis PP: Modulation of chemical composition and other parameters of the cell by growth rate. In: Escherichia coli and Salmonella: Cellular and Molecular Biology (edited by Neidhart F. C. et al.), ASM Press, Washington DC, ed. 2 1996 , 1553-1569.
+#The mathematics of tanning, Josef Thingnes, Leiv Øyehaug, Eivind Hovig,  and Stig W Omholt, BMC Systems Biology 2009, 3:60doi:10.1186/1752-0509-3-60
-As a starting point, we began with the article [http://www.ncbi.nlm.nih.gov/pubmed/18426409 Strömberg S et al. (2008)]. In this paper they identified some 859 genes as differentially regulated genes in pigment skin cells called melanocytes. These genes can be classified in several groups based on their possible cellular role (Strömberg et al. 2008). These groups are:
-# Developing melanocytes
-# Melanin synthesis (melanogenesis) and transport of melanosomes to keratinocytes
-# Cell adhesion
-# Antigen presenting
-In fig. 1, a summarized regulatory network of some candidate genes are illustated. We intentionally chose to present interactions that have currently been investigated in order to support our study.
-[[Image:SU_igem_mitf_regulatory_site.jpg|200px|thumb|left|Figure 2 Regulators and transcription-factor binding sites on the MITF promoter. Levy et al., 2006]]
-out of those genes, it seemed that [http://www.ncbi.nlm.nih.gov/gene/4286 MITF] is one of the most regulated and regulating genes in vitiligo disease. This was the first block of the map. . The MITF promoter is targeted by several transcription factors that are important in neural-crest development and signaling. Transcription factors implicated in the regulation of the MITF promoter include PAX3, cAMP-responsive element binding protein (CREB), SOX10, LEF1 (also known as TCF), one cut domain 2 (ONECUT-2) and MITF itself, Fig. 2 (Levy et al., 2006). It also regulates both the survival and differentiation of melanocytes, and enzymes which are necessary for melanin production. (Levy et al., 2006; T.J. Hemesath et al., 1994; N.J. Bentley et al., 1994;  K. Yasumoto et al., 1994; C. Bertolotto et al., 1998). So, the regulation of multiple pigmentation and differentiation related genes by MITF (Levy et al., 2006) convinced us that MITF is a central regulator of melanogenesis.
-There are evidences for the accumulation of H2O2 in vitiliginous skin  (K. U. Schallreuter et al., 1999, 2001, 2006) and low levels of SOD and CAT (A. Jalel et. al., 2008; Koca R et. al., 2004; K. U. Schallreuter et al. 1991; Maresca V et. al. , 1997; ). It was also shown that calcium uptake is defective in vitiliginous skin in keratocytes (K. U. Schallreuter et al. 1988) as well as Melanocytes(K.U. Schallreuter et al., 1996), later the effect of accumulation of H2O2 in the epidermis of patients with vitiligo which leads to disruption calcium homeostasis in the skin was observed (K. U. Schallreuter et al. ,2007). This suggests that an oxidative stress is a pathogenic event in the degeneration of melanocytes (Strömberg S et al. ,2008).
-We hypothesized that extra levels of SOD could improve the Melanocytes survivability and help re-pigmentation.
-When thinking about re-pigmentation in vitiliginous skin, the first thing comes to mind is lack of melanin. There are evidences that melanocytes are still available in depigmented epidermis of patients with vitiligo even after 25 years (Tobin DJ et. al., 2000). So if melanocytes can't deliver melanin to keratinocytes or they are producing very low amount, it is possible to produce melanin using synthetic biology and deliver it to help re-pigmentation.
-[http://www.nature.com/jid/journal/v125/n2/full/5603495a.html ]
-</div>
 |}
 {{Stockholm/Footer}}