Türkçe bilmiyorum 😟
I am
The Past, Present and Future
Facts, opinion and guess
world
chile
Small country of ~17 million people
Universities ranks similar to Turkish ones
Spanish colony 500 years ago (so language is Spanish)
Independent Republic 200 years ago
First Latin American country to recognize Turkish republic
OECD member
Everyday life very similar to Turkey
The most successful soap opera last year was Bin Bir Gece
1st world producer of copper
2nd world producer of salmon
Fruits: peaches, grapes, apples, avocado
Wine: exported worldwide
Official data for 2014
The natural question was
Gene expression analysis for industrial applications:
Chilean Peach (Prunus persica) is exported to USA and Europe
Cold storage can change the texture of the fruit
We identified the genes involved in the stress response by:
For wine and to eat as dessert, like Sultaniye
We want big grapes and small seeds
but grape size depends on hormones produced by the seed
Which genes are involved on seed and grape growth?
Strategy:
Salmon
Farmed salmons are feed with cheap vegetal protein But wild salmons eat animal protein
How is salmon’s metabolism affected by the diet? Which genes change their expression because the changes in food?
… and sequencing of whole Salmo salar genome
(10 million dollars project)
Chilean wine travels long distances to final markets
Any yeast contamination means big economic loses (people stops buying all Chilean brands)
Quality control is usually done growing samples for 3 days But time is expensive: penalty for shipping delays
We designed qPCR method for rapid detection of yeast contamination
It is currently used by one major wine producer in Chile. It may be sold to Roche.
A little chemistry: Copper is part of a compound, with Sulfur and Iron. Ferric acid separates it.
Cu2S + 4Fe3+ ⟶ 2Cu2+ + 4Fe2+ + S
Resulting Cu2+ is soluble and is recovered.
But all Fe3+ transforms to Fe2+ and reaction stops
There are bacteria that “eat” e- and keep the reaction going on
Fe2+ ⟶ Fe3+ + e-
The biological method is much better that the standard one
The goal is to understand and improve the involved bacteria so this technology can be used extensively
It enables building new mines
It is like discovering petrol reserves for the country
We had a research contract with the main mining company
State owned, big enough to pay for long term research
Few papers, many patents
We need to control the “ecosystem” on the mine
Molecular Biology methods are fast, sensible and reliable
They can be used in place: metagenomic approach. No culture
Key problem: Design probes that match a taxonomic branch, not a specific strain
The probes should be tolerant to mutations that occur in environmental samples with many strains
Classical tools don’t work on big scales
I designed and built a solution using a super-computer
Calculation tool one day on 32 processors (one processor month)
Resulting probes worked as expected
They can be used on qPCR or in microarrays.
The microarray was published in N. Ehrenfeld, A. Aravena, A. Reyes-Jara, N. Barreto, R. Assar, A. Maass, P. Parada, Design and use of oligonucleotide microarrays for identification of Biomining microorganisms. Advanced Materials Research 71-73 (2009) 155-158.
The method and the probes have been patented in
To improve the process we need to see inside the black box. We sequenced the complete genome of 3 bacteria
We paid over USD $150K. Today is USD $5K
Hint: Sequence assembly requires a big computer. It does not work on a regular PC
We used Hidden Markov Models and Pattern Matching techniques to determine the genes and their functions
We learned that
We predict which genes code enzymes
Each enzyme catalyzes a reaction, with a known stoichiometry
Every reaction gives an equation
All equations plus boundary conditions give model to predict metabolite concentration
We can predict how the cell adapts to environmental changes
From the genome sequence we can predict which genes code for transcription factors and they bind
They form a putative regulatory network.
But current methods produce too many false positives
We expected ~4K regulations. We got 25K regulations.
I integrate this model with microarray data to find the “most probable” regulatory network using a parsimony criterium
A very active research area that aim to understand the cell as a system with complex interactions
The focus is not on the genes, is on the genome
The key is to understand networks
The present
All experimental values in science are measured with an observational error. (e.g. temperature is 10.2 ± 0.05°C, pressure is 101215 ± 125 Pa)
Except genetic sequences: Nucleotides are either A, C, T or G.
There is no “average” or “intermediate case”
So is natural to use computers and information theory to model DNA
but there is another reason …
The sequencing of the human genome, made public by the president of USA, captured the attention of everybody.
Physicists, mathematicians, computer scientist and engineers, turned their attention to molecular biology questions.
They come looking with new eyes and creating new theoretical and practical tools.
Molecular Biology has always interacted with other disciplines
Just consider the word “Biochemistry”
Before Internet times
Structured data is easy to process to discover new knowledge.
The software for this meta-analysis is also Open Source
Scientist can adapt the program internal code to solve their specific question
Anyone can download these programs without cost.
If the analysis requires big computational power you can rent it at low cost
Companies like Amazon.com and Google sell their spare computer power at low prices
This enables researchers to carry computations that would be impossible otherwise.
This democratization of knowledge provides an exciting challenge.
Rich countries have no longer the monopoly of knowledge.
We can be players in the big leagues, on a leveled surface.
We can read the same books and the same articles, use the same machines and the same programs.
Anyone could make the new scientific breakthrough, either in New York, New Delhi or Istanbul.
But the same opportunity presents to everyone else.
Emerging economies push up the number of researchers worldwide
India graduates more than a million engineers each year. Many of them in biotechnology
Egypt has 35.000 PhD students and Israel 10.000.
Many of them will find jobs in Molecular Biology companies or academia
and China, Korea, Ukrania
Hays, Thomas. 2011. “PhDs: Israel Also Trains Plenty.” Nature 473 (7347). Nature Publishing Group: 284–84.
Advances in molecular biology technology has produced
They produce
The first bacterial genomic sequence was published in Science journal.
Today it would be just a shot communication.
National Human Genome Research Institute. http://genome.gov/sequencingcosts
In a few years we passed from lack of data to excess of it
We need to learn how to extract biological meaning from big volumes of data
Classical methods are not enough
What is significant? What is the “null hypothesis”?
The students will learn
Teach Python and BioPython to analyze, model, evaluate and predict the behavior of genomic and molecular biology entities.
The students should be able to interact with high end servers, use command line tools and be comfortable in computing environments others than Microsoft Windows.
Tools include Unix command line tools, SQL and the R statistical package.
The student should be able to understand how computer networks work and what are their limitations.
To test these ideas we start next week an
Introduction to Data Science Workshop
The mathematical tools can be explored together with the biological context, so they make sense and are easier to learn.
I will give you a link at the end of this talk.
If you are interested visit the webpage and send an email.
after all, maybe I’m just crazy
Every normal student is capable of good mathematical reasoning if attention is directed to activities of his interest
Everything we will show is available on the Internet
You just need to look for it
But it is in English
Translation takes too long
Translated science is obsolete science
It is hard to make predictions, especially about the future
Genomic tools are also used outside academia.
Several companies provide “personalized DNA services”.
Both offer to trace ancestry and migrations of the human population. Any person can know which are his true origins.
Today PCR thermocyclers are expensive devices found in universities and research centers, very much like desktop computers were in the 70’s and 80’s.
Nowadays computers are low-cost and found everywhere.
Will the same happen with PCR?
Today only a few companies produce PCR thermocyclers, just like smartphones such as the iPhone and Samsung.
Nevertheless you can see them everywhere.
And this is a big opportunity for creators of software applications.
The value is in the apps. Ask Nokia or Blackberry
A computer on every desk and in every home, all running Microsoft software
Gates set this goal in the late 70’s, when it was not obvious if people would even see a computer in their lives.
PCR technology is now in the same state that Personal Computers were in 1975. If PCR machines become inexpensive,
then who will be making “software apps” for them?
I think we should prepare our students to make these “apps”.
They should have easy access to low-cost thermocyclers, use them frequently and creatively.
Then, like in the computer industry, they may create completely new applications that we cannot foresee now.
They are usually named according to their inventor
Notice that most of these inventors got Nobel prizes for their contributions.
I propose to create a course on “Scientific Instrumentation” using initially software tools.
Making instruments is now “software”, not craftsmanship.
We can understand this with a biological analogy.