User:Msommer

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Contents

Morten Sommer wiki page

101 Week 10

Nov29 Presentation here

I wrote a perl script for determining the positions of deviations between two genomes - leading to a variability map. Perl script and in/out files are here

Also using as input copy genomes in Jasons difference format script here The variations can then be characterized as either point mutations or duplication/deletions.

The resulting variability map can then be mapped to various genome categories such as:

  • Protein coding regions
  • Regulatory regions
  • Metabolic pathways

101 Week 9

Prioritizing the effects of mutations in a genome.

I will go trough the various classes of mutations that can happen be it in protein coding regions, regulatory regions or junk DNA. I have tried the tool PolyPhen and will briefly review their approach - which useful for estimating whether a particular amino acid substitution causes a loss of function of a given protein. Furthermore, I will discuss some of the resources that are available for defining or predicting the regulatory regions of genomes which are useful when assessing whether a particular nucleotide mutation causes changes in the regulation of a particular pathway.

Presentation can be downloaded as a pdf here

101 Week 8

My perl script for characterization of the human chromosome 11 is here.

What if we had a 1000 human genomes

  • General statistical study

If we had a 1000 diploid human genome sequences, what would we do?

  1. Establish the normal genome sequence - that is which nucleotide is most common at each position. How does this compare with the present Human Genome draft.
  2. Variability map for the human genome - which nucleotide positions are most variable. Creating a variability map for the human genome in which each position is assigned a value representing how much variability there is in nucleotide choice on that position across the 1000 genomes.
    1. How does well characterized 'objects' like: extrons, introns, known transcription factor binding sites, siRNA, and 'junk' DNA etc. map onto the variability map. For instance are extrons primarily in regions of low variability whereas introns are in regions of high variability?
    2. How are DNA segments that are related to human disease mapped onto variability map.
  3. Conservation of amino acid sequence
    1. For all protein coding DNA frames how are amino acid sequences conserved.
      1. Characterize different types of changes of amino acids (i.e. from charged to neutral, large to small etc.)
      2. Are there particular changes (ex.: charged to neutral) that are more frequent than others.
      3. Which amino acids are most conserved
    2. For all disease related protein coding sequences - how well are the amino acids conserved.
    3. How does the frequency of amino acid changing mutations compare between all protein coding sequences compared to those linked to disease? Maybe disease related protein coding sequences are the ones that have high frequency of amino acid changing mutations.
  • Personalized medicine

That is given a personal genome what should we look for.

  1. Determine deviations from the normal sequence.
  2. Categorize the variations
    1. Nucleotide changes in non protein coding regions of genome
      1. Nucleotide changes in known regulatory regions of genome (Transcription factor binding sites, etc.)
      2. Nucleotide changes in 'junk' dna
      3. Known disease causing nucleotide changes (mutations on transcription factor binding sites)- is the mutation dominant or recessive
    2. Amino acid changes in coding regions of genome
      1. Different classes of amino acid changes (charged to non charged)
      2. Changes of amino acid sequence in proteins linked to disease
      3. Known disease causing amino acid mutations - is the mutation dominant or recessive

Interesting organisms for biodiesel metabolic engineering

In the search for some enzymes that metabolize octane I have found the following organisms, that are worth looking further into:

  • Gloeobacter violaceus
  • P.aeruginosa
  • Nocardia farcinica
  • Mycobacterium bovis
  • Mycobacterium tuberculosis CDC1551
  • Mycobacterium tuberculosis H37Rv
  • Burkholderia sp. 383
  • Burkholderia pseudomallei 1710b
  • Burkholderia mallei

101 Week 7

Here is my perl script [1]:

New study about economic cost of global climate change from harvard [2]

Some interesting enzymes/organisms metabolizing octanes:

  • Alkane hydroxylases [3]
  • Octane 1,3 diol [4]
  • Octane metabolizing organisms: Corynebacterium sp. Strain 7E1C*, Pseudomonas oleovorans (Alk operon has been characterized in mid 90'ies).

101 Week 6

Octane producing photosynthetic organism

It would be neat if we could engineer an organism that produces octane (gasoline) from sunlight to complement the biodiesel. The enzymatic reaction performed by alkane hydroxylase may be of interest [5].

In silico organisms for metabolic network analysis

  • Another useful resource is the Kyoto Encyclopedia of Genes and Genomes KEGG which has listed metabolic pathways of many organisms including an extensive database of ligands, enzymes, reactions etc.

OptStrain

The rutine OptStrain is likely to prove highly useful for maximizing the biofuel production of a suitable organism.

The OptStrain rutine consist of the following 4 simple steps:

  • Compile Universal Database of all comfirmed enzyme catalyzed reactions
  • Calculate maximum theoretical yield of product given a particular substrate input using all reactions available in Universal Database
  • Identify a pathway that maximizes yield of product while minimizing number of non native functionalities
  • Optimize the resulting metabolic network by knocking out enzymes that direct flux away from the product pathway. (OptKnock) - See Jeremy description

101 Week 5

Metabolic Engineering and Optimization

I have been writing the initial draft outline for the biodiesel project and have been looking at Jeremy's metabolic engineering tutorial and the Pallson review paper PDF to familiarize myself with the field.

Bilevel optimization

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An interesting approach to metabolic engineering is bilevel optimization in which the bright researcher modifies the genome of the production organism in such a way that the organism in optimizing its biomass production will produce a particular compound as a biproduct/wasteproduct. This method has been applied by the [Maranas group] at Penn State to vaious processes including the production of Hydrogen, particular amino acids and vannilin.

The figure on the right illustrates the process of bilevel optimization for the case of hydrogen production. The organism will naturally seek to optimize its biomass production shown on the x axis given its particular genotype. When particular pathways are blocked or added the organism the organism may not grow as fast as the wildtype organism; however, a result of the modified pathways is the accumulation of a påarticular reaction product in this case hydrogen. The total hydrogen production that one wishes to maximize is thus given as the product of the biomass production rate times the fraction of the biomass that is hydrogen. From the example on the figure it is seen that Wildtype E.Coli does not produce significant hydrogen; anaerobic E. Coli produces 4.5 mmol/g DW wildtype biomass in an hour; the double knock out produces 16.25 mmol/g DW wildtype biomass; the triple knock out produces 4.8 mmol/g DW wildtype biomass. Thus, significant increases in hydrogen production can be acheived by making a few deletions in the genome of E. Coli.

Bilevel optimization references

  • Pharkya et.al. Genome Research (2004) 14:2367 [[6]]
  • Burgard et.at. BIOTECHNOLOGY AND BIOENGINEERING (2003) 84:647 [[7]]
  • Burgard et.al. Genome Research (2004) 14:301 [[8]]

101 Week 4

Metrics for biofuels

In order to quantitatively evaluate different options of fuels comparable metrics need to be established. I am trying to list a couple, but please fill in--Msommer 00:17, 12 October 2005 (EDT).

  • Fossil fuel energy balance. The ratio of the energy output to the fossil energy input. further info
  • Energy density. (J/L)
  • Required infrastructure investment. ($) The investment required to set up infrastructure to distribute the fuel and develop engines/applicances that utilize the fuel.
  • Net CO2 emmission pr energy unit. (g/J) The net amount of carbon dioxide emitted to the atmosphere from the active production and combustion of x energy units of fuel. active production refering to fuels that are actively produced on a reasonable timescale like alchol from corn or biodiesel from algae.
  • Emmission pr energy unit of other substances. Such as: CO,SO2,NO2page 1773, section 1.2 and 1.3
  • Cost of production/preparation per energy unit. ($/J) The cost of production of an energy unit of the final fuel.
    • The first derivative w/r/t time of the above ($/Jmonth). (this to "Ratio..." --Jleith 08:45, 13 October 2005 (EDT))
    • The estimated cost of production/preparation per energy unit averaged over the next ten years, or thirty years, etc.
  • Proportion of money paid for a fuel that ends up in the hands of regimes or organizations unfriendly or hostile to the U.S. (or to the West, etc.).
  • Ratio of humans' ability to produce this fuel to the worldwide demand for the fuel.

Fuel metric table

Please fill in if you find appropriate information including a link to the source

--Msommer 23:22, 12 October 2005 (EDT)

Metric Gasoline Diesel Ethanol Biodiesel
Fosil fuel energy balance 0.805 1 0.843 1 1.34 1 3.20 1
Energy density. (J/L) 34280000 2 39296000 2  ? 35395000 2
Required infrastructure investment ($) 0 0  ?  ?
Net CO2 emmission pr energy unit (g/J)  ?  ?  ?  ?
Cost of production/preparation pr energy unit US prices ($/GJ) 21.9 Oct 10 2005 21.2 Oct 10 2005  ? 5.2 do it yourself - veg. oil - 14.0 2002 commercial prices
Cost of production/preparation pr energy unit Danish prices ($/GJ) 44.7 Oct 12 2005 42.2 Oct 12 2005  ?  ?
Sustainable fuel production capacity / Global fuel need  ?  ?  ?  ?


101 Week 3

Economics of a Sustainable Environment

Planet Earth is a constrained environment with fixed amounts of natural resources. Making sure that natural resources (clean water, minerals etc.) and services (such as oxygen production etc.) will be available to future generations of humans require moving towards an economy that appreciates the real value of these resources. Real value meaning the cost of renewal NOT the cost of extraction. An economy of this kind has been termed 'Natural Capitalism' by Paul Hawken, Amory Lowins and L Hunter Lovins in their book 'Natural Capitalism'.

The central paradigm of Natural Capitalism is that:

  • Planet Earth should not be depleted for resources at a rate higher than the rate at which resources are generated and waste should not be generated at rates higher than it can be reabsorbed by the ecosystem

In further detail this is presented by Herman E. Daly in an article in the September 2005 issue of Scientific American as three main objectives:

  • Limit use of all resources to rates that ultimately result in levels of waste that can be absorbed by the ecosystem
  • Exploit renewable resources at rates that do not exceed the ability of the ecosystem to regenerate the resources
  • Deplete nonrenewable resources at rates that, as far as possible, do not exceed the rate of development of renewable alternatives

Most researchers agree that the state of the global environment is critical; however, for a different view check out Bjørn Lomborg and his book 'The Skeptical Environmentalist'. In this book he argues that the state environment of the environment is not too bad after all. This book resulted in immense criticism from various experts and acqusations of use of non scientific methods; however, it also had support from various sources.

I beleive that it is important that we take into account these issues in our projects. With respect to the Biodiesel project this is likely to be fulfilled, since biological systems are usually extremely good at cycling resources through the ecosystem without buildup of waste deposits. However, we must fully investigate and understand the pertubations made to the ecosystem by introducing billions of billions of algea into particular locations on the earth as part of the project. A powerful demonstration of the usefulness of genetic engineering would be to engineer the biodiesel producing algea in such a way that a full energy production/consumption cycle did not perturb the ecosystem. --Msommer 12:38, 2 Oct 2005 (EDT)

Copenhagen Consensus - Set priorities for planet Earth

Copenhagen Consensus is an experiment performed by the economist Bjørn Lomborg in May 2004. A panel of eight expert economist (including three nobel laureates) were suposed to make a cost/benefit analysis of how to prioritize funding for 10 major global challenges. The global challenges were: Communicable diseases, Malnutrition and hunger, Subsidies and trade barriers, Climate change, Conflicts, Education, Financial instability, Government and corruption,Population: migration, Sanitation and water. For each of the challenges a set of experts had compiled a report that included a analysis of the challenge, suggested actions (and their cost and benefit). Based on these reports the eight experts had 4 days of round table discussion leading to a prioritization of the challenges.

The Copenhagen Consensus was an exercise in global prioritization and is in my opinion highly relevant for 101. More info can be found at The copenhagen consensus homepage. Furthermore a book has been written about the project including summaries of the reports decribing the challenges. The book is 'Global Crises, Global Solutions.

In my oppinion the outcome of the project seems to neglect the environmental challenges faced by our generation - However, the idea behind the project and the methods are highly relevant and recommendable.--Msommer 12:38, 2 Oct 2005 (EDT)

101 week 2

To be considered in the project description

Draft for graphical description of economic flow in global context
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Draft for graphical description of economic flow in global context

Irespectively of what system we choose to model such as the biodiesel idea I think that it will be important to consider the economical flux of capital (money, bio capital, labor and profit) from a global perspective. To take the example of biodiesel production: How will the source of funding (both in terms of nations and within nations: public versus private) affect the econmical outcome of such a project globally. That is if a project is initially funded by the US government followed by a commercialization through private US companies, how will it differ from a internationally funded public coorporation? (If such a scenario is possible!) How should we make quantitative graphical representations for this? Here is a suggestion for what that may look like. --Msommer 20:31, 28 Sep 2005 (EDT)

Complexity & Randomness

Trying to define what is random: a collection of elements is random when the correlation of the elements behavior/value is unpredictable - however, the properties of the total system may be straight forward to describe. Ex.: A random string of numbers between 1 and 9. There should be no correlation between the number at position a and a+k, but the average value of all the numbers will be appr. 5.

Trying to define a complex system: a collection of elements is complex if the correlation of the elements behavior/value is non trivial, but predictable. As complexity increases determining the underlying correlations become more difficult. The total complex system may exhibit non trivial behavior. Ex. Weather. Or simple behavior, when E.Coli responds to lactose by switching on the lac genes.

My understanding of 101

As I understand the objective of this class, we should try and develop quantitative models that can be used to make qualified policy decisions that impact our life and our world - focus being on technology and research. These models should integrate knowledge from all levels - in a sense showing the relevance of a particular reaction or technological advance to society. This seems in some aspects as a tremendous task - and I think that it is important to establish which 'societal' parameters that we wish to link to the lower level processes. Is it: bio capital, average lifetime, public health and GDP. Furthermore, I think that it will be important to take into consideration that most decisions are not based solely on rationality, but also moral and self interest. So if one wishes to develop tools for decision makers - in order for them to make rational decisions - a framework must be put together minimizing effects of non rational considerations (or at least disclosing them). --68.163.254.63 18:38, 21 Sep 2005 (EDT)

Background

My wife and I
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My wife and I

I am a Biophysics 1 year PhD student. I was born in Denmark and have lived there most my life except for some periods as an exchange student in Pasadena, California. I finished my M.Sc. in Physics and Biophysics Fall 2004 and have been working on microfluidic technology development for protein crystallography before I started at Harvard. I have been very interested in issues regarding society, since I was young, but during my university studies I have not been spending all the time I would have liked to thinking about these issues. Hence, I welcome this course as an opportunity for spending some more time on these subjects.

[Personal webpage]