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Synthetic Life: Now possible…..

2011-06-15T04:17:00.000-07:00

Now creating an artificial organism that suits our needs comes under realms of possibilities. The well known maverick in the science society named Craig Venter and his colleagues were first to make such an effort and were successful.
The entire procedure to reach this pinnacle is explained by Craig Venter in an interview.

What I'm going to tell you about in my 18 minutes is how we're about to switch from reading the genetic code to the first stages of beginning to write the code ourselves. It's only 10 years ago this month when we published the first sequence of a free living organism, that of haemophilus influenzae. That took a genome project from 13 years down to four months. We can now do that same genome project in the order of two to eight hours. So in the last decade, a large number of genomes have been added: most human pathogens, a couple of plants, several insects and several mammals, including the human genome. Genomics at this stage of the thinking from a little over 10 years ago was by the end of this year, we might have between three and five genomes sequenced; it's on the order of several hundred. We just got a grant from the Gordon and Betty Moore Foundation to sequence 130 genomes this year, as a side project from environmental organisms. So the rate of reading the genetic code has changed.
But as we look, what's out there, we've barely scratched the surface on what is available on this planet. Most people don't realize it, because they're invisible, but microbes make up about a half of the Earth's biomass, whereas all animals only make up about about one one-thousandth of all the biomass. And maybe it's something that people in Oxford don't do very often, but if you ever make it to the sea, and you swallow a mouthful of seawater, keep in mind that each milliliter has about a million bacteria and on the order of 10 million viruses.
Less than 5,000 microbial species have been characterized as of two years ago, and so we decided to do something about it. And we started the Sorcerer II Expedition, where we were, as with great oceanographic expeditions, trying to sample the ocean every 200 miles. We started in Bermuda for our test project. Then moved up to Halifax, working down the U.S. East Coast, the Caribbean Sea, the Panama Canal, through to the Galapagos, then across the Pacific, and we're in the process now of working our way across the Indian Ocean. It's very tough duty; we're doing this on a sailing vessel, in part to help excite young people about going into science. The experiments are incredibly simple. We just take seawater and we filter it, and we collect different size organisms on different filters. And then take their DNA back to our lab in Rockville, where we can sequence a hundred million letters of the genetic code every 24 hours. And with doing this, we've made some amazing discoveries.
For example, it was thought that the visual pigments that are in our eyes - there was only one or two organisms in the environment that had these same pigments. It turns out, almost every species in the upper parts of the ocean in warm parts of the world have these same photo receptors, and use sunlight as the source of their energy and communication. From one site, from one barrel of seawater, we discovered 1.3 million new genes and as many as 50,000 new species.
We've extended this to the air now with a grant from the Sloan Foundation. We're measuring how many viruses and bacteria all of us are breathing in and out every day, particularly on airplanes or closed auditoriums. (Laughter) We filter through some simple apparatuses; we collect on the order of a billion microbes from just a day filtering on top of a building in New York City. And we're in the process of sequencing all that at the present time.
Just on the data collection side, just where we are through the Galapagos, we're finding that almost every 200 miles, we see tremendous diversity in the samples in the ocean. Some of these make logical sense, in terms of different temperature gradients. So this is a satellite photograph based on temperatures - red being warm, blue being cold - and we found there's a tremendous difference between the warm water samples and the cold water samples, in terms of abundant species. The other thing that surprised us quite a bit is these photo receptors detect different wavelengths of light, and we can predict that based on their amino acid sequence. And these vary tremendously from region to region. Maybe not surprisingly, in the deep ocean, where it's mostly blue, the photo receptors tend to see blue light. When there's a lot of chlorophyll around, they see a lot of green light. But they vary even more, possibly moving towards infrared and ultraviolet in the extremes.
Just to try and get an assessment of what our gene repertoire was, we assembled all the data - including all of ours thus far from the expedition, which represents more than half of all the gene data on the planet - and it totaled around 29 million genes. And we tried to put these into gene families to see what these discoveries are: Are we just discovering new members of known families, or are we discovering new families? And it turns out we have about 50,000 major gene families, but every new sample we take in the environment adds in a linear fashion to these new families. So we're at the earliest stages of discovery about basic genes, components and life on this planet.
When we look at the so-called evolutionary tree, we're up on the upper right-hand corner with the animals. Of those roughly 29 million genes, we only have around 24,000 in our genome. And if you take all animals together, we probably share less than 30,000 and probably maybe a dozen or more thousand different gene families. I view that these genes are now not only the design components of evolution. And we think in a gene-centric view - maybe going back to Richard Dawkins' ideas - than in a genome-centric view, which are different constructs of these gene components.
Synthetic DNA, the ability to synthesize DNA, has changed at sort of the same pace that DNA sequencing has over the last decade or two, and is getting very rapid and very cheap. Our first thought about synthetic genomics came when we sequenced the second genome back in 1995, and that from mycoplasma genitalium. And we have really nice T-shirts that say, you know, "I heart my genitalium." This is actually just a microorganism. But it has roughly 500 genes. Haemophilus had 1,800 genes. And we simply asked the question, if one species needs 800, another 500, is there a smaller set of genes that might comprise a minimal operating system?
So we started doing transposon mutagenesis. Transposons are just small pieces of DNA that randomly insert in the genetic code. And if they insert in the middle of the gene, they disrupt its function. So we made a map of all the genes that could take transposon insertions and we called those "non-essential genes." But it turns out the environment is very critical for this, and you can only define an essential or non-essential gene based on exactly what's in the environment. We also tried to take a more directly intellectual approach with the genomes of 13 related organisms, and we tried to compare all of those, to see what they had in common. and we got these overlapping circles. And we found only 173 genes common to all 13 organisms. The pool expanded a little bit if we ignored one intracellular parasite; it expanded even more when we looked at core sets of genes of 310 or so. So we think that we can expand or contract genomes, depending on your point of view here, to maybe 300 to 400 genes from the minimal of 500.
The only way to prove these ideas was to construct an artificial chromosome with those genes in them, and we had to do this in a cassette-based fashion. We found that synthesizing accurate DNA in large pieces was extremely difficult. Ham Smith and Clyde Hutchison, my colleagues on this, developed an exciting new method that allowed us to synthesize a 5,000 -base pair virus in only a two-week period that was 100 percent accurate, in terms of its sequence and its biology. It was a quite exciting experiment - when we just took the synthetic piece of DNA, injected it in the bacteria and all of a sudden, that DNA started driving the production of the virus particles that turned around and then killed the bacteria. This was not the first synthetic virus - a polio virus had been made a year before - but it was only one ten-thousandth as active and it took three years to do. This is a cartoon of the structure of Phi X-174. This is a case where the software now builds its own hardware, and that's the notions that we have with biology.
People immediately jump to concerns about biological warfare, and I had recent testimony before a Senate committee, and a special committee the U.S. government has set up to review this area. And I think it's important to keep reality in mind, versus what happens with people's imaginations. Basically, any virus that's been sequenced today - that genome can be made. And people immediately freak out about things about Ebola or smallpox, but the DNA from this organism is not infective. So even if somebody made the smallpox genome, that DNA itself would not cause infections. The real concern that security departments have is designer viruses. And there's only two countries, the U.S. and the former Soviet Union, that had major efforts on trying to create biological warfare agents. If that research is truly discontinued, there should be very little activity on the know-how to make designer viruses in the future.
I think single-cell organisms are possible within two years. And possibly eukaryotic cells, those that we have, are possible within a decade. So we're now making several dozen different constructs, because we can vary the cassettes and the genes that go into this artificial chromosome. The key is, how do you put all of the others? We start with these fragments, and then we have a homologous recombination system that reassembles those into a chromosome.
This is derived from an organism, deinococcus radiodurans, that can take three million rads of radiation and not be killed. It reassembles its genome after this radiation burst in about 12 to 24 hours, after its chromosomes are literally blown apart. This organism is ubiquitous on the planet, and exists perhaps now in outer space due to all our travel there. This is a glass beaker after about half a million rads of radiation. The glass started to burn and crack, while the microbes sitting in the bottom just got happier and happier. Here's an actual picture of what happens: the top of this shows the genome after 1.7 million rads of radiation. The chromosome is literally blown apart. And here's that same DNA automatically reassembled 24 hours later. It's truly stunning that these organisms can do that, and we probably have thousands, if not tens of thousands of different species on this planet that are capable of doing that. After these genomes are synthesized, the first step is just transplanting them into a cell without a genome.
So we think synthetic cells are going to have tremendous potential, not only for understanding the basis of biology but for hopefully environmental and society issues. For example, from the third organism we sequenced, Methanococcus jannaschii: it lives in boiling water temperatures, its energy source is hydrogen and all its carbon comes from CO2 it captures back from the environment. So we know lots of different pathways, thousands of different organisms now that live off of CO2, and can capture that back. So instead of using carbon from oil for synthetic processes, we have the chance of using carbon and capturing it back from the atmosphere, converting that into biopolymers or other products. We have one organism that lives off of carbon monoxide, and we use as a reducing power to split water to produce hydrogen and oxygen. Also, there's numerous pathways that can be engineered metabolising methane. And DuPont has a major program with Statoil in Norway to capture and convert the methane from the gas fields there into useful products.
Within a short while, I think there's going to be a new field called Combinatorial Genomics, because with these new synthesis capabilities, these vast gene array repertoires and the homologous recombination, we think we can design a robot to make maybe a million different chromosomes a day. And therefore, as with all biology, you get selection through screening, whether you're screening for hydrogen production, or chemical production, or just viability. To understand the role of these genes is going to be well within reach.
We're trying to modify photosynthesis to produce hydrogen directly from sunlight. Photosynthesis is modulated by oxygen, and we have an oxygen-insensitive hydrogenase that we think will totally change this process. We're also combining cellulases, the enzymes that break down complex sugars into simple sugars and fermentation in the same cell for producing ethanol. Pharmaceutical production is already under way in major laboratories using microbes. The chemistry from compounds in the environment is orders of magnitude more complex than our best chemists can produce. I think future engineered species could be the source of food, hopefully a source of energy, environmental remediation and perhaps replacing the petrochemical industry.
Let me just close with ethical and policy studies. We delayed the start of our experiments in 1999 until we completed a year-and-a-half bioethical review as to whether we should try and make an artificial species. Every major religion participated in this. It was actually a very strange study, because the various religious leaders were using their scriptures as law books, and they couldn't find anything in them prohibiting making life, so it must be OK. The only ultimate concerns were biological warfare aspects of this, but gave us the go ahead to start these experiments for the reasons we were doing them.
Right now the Sloan Foundation has just funded a multi-institutional study on this, to work out what the risk and benefits to society are, and the rules that scientific teams such as my own should be using in this area, and we're trying to set good examples as we go forward. These are complex issues. Except for the threat of bio-terrorism, they're very simple issues in terms of, can we design things to produce clean energy, perhaps revolutionizing what developing countries can do and provide through various simple processes. Thank you very much.

BINC 2010 Questions

2010-07-24T04:18:00.001-07:00

What is the program saved in the ROM?
1. Software
2. Hardware
3. Romware
4. Firmware
Answer:
Read-only memory (usually known by its acronym, ROM) is a class of storage media used in computers and other electronic devices. Because data stored in ROM cannot be modified (at least not very quickly or easily), it is mainly used to distribute firmware
(software that is very closely tied to specific hardware, and unlikely to require frequent updates)
Ramachandran Plot is symmetric for
1. Glycine
2. Proline
3. Serine
4. Threonine
Answer:
The Ramachandran plot is the 2d plot of the φ-ψ torsion angles of the protein backbone. It provides a simple view of the conformation of a protein. The φ-ψ angles cluster into distinct regions in the Ramachandran plot where each region corresponds to a particular secondary structure. There are four basic types of Ramachandran plots, depending on the stereo-chemistry of the amino acid: generic (which refers to the 18 non-glycine non-proline amino acids), glycine, proline, and pre-proline (which refers to residues preceding a proline ). The observed glycine Ramachandran plot has a distinctive distribution quite different to the generic Ramachandran plot. Unlike the generic Ramachandran plot, the glycine α region is symmetric to the αL region. In the generic Ramachandran plot, there is also a γ region corresponding to the hydrogen bonded γ-turn . The glycine Ramachandran plot does not have any density in the γ region.
TPCK is an enzyme inhibitor of following category:
1. Allosteric
2. Competitive
3. Noncompetitive
4. Irreversible
Answer:
Tosyl phenylalanyl chloromethyl ketone (TPCK) is a protease inhibitor. Its structural formula is 1-chloro-3-tosylamido-4-phenyl-2-butanone. TPCK is the irreversible inhibitor of chymotrypsin. Also inhibits some cysteine proteases such as papain, bromelain or ficin. It does not inhibit trypsin nor zymogens. Irreversible inhibitors usually covalently modify an enzyme, and inhibition cannot therefore be reversed.
Which is the default return type?
1. int
2. float
3. char
4. void
Answer:
A function without an explicit return type returned an
int. But recent compiler show an error when a function is without an explicit return type.
Last In First Out refers to
1. Stack
2. Tree
3. Queue
4. Lists
Answer:
A stack is a last in, first out (LIFO) abstract data type and data structure.
Which of the multiuser operating system made of higher level programming language?
1. Windows Vista
2. Windows XP
3. Unix
4. DOS
Answer:
The answer to it is really perplexing.
The "machine language" and "assembly language" for CPU architecture are the lowest-level programming languages.
The "Fortran language" and the "C programming language" are perhaps the most popular non-CPU-specific low-level programming languages. They were once considered high-level programming languages, and certainly they are at a higher level than assembly language, but now they are considered low-level programming languages when compared to the much higher-level languages available today (Python, Java, C++ ,etc)
Low-level programming languages provide little or no abstraction from the CPU's instruction set architecture; typically they interact with the hardware directly.
Now look at these operating system and the languages they are made from.
DOS is probably made of assembly language which is of course a low level language.
The codes of Unix are written is C which is also considered now a low level language.
Windows XP is originally written is C, C++ , and Visual Basic and assembly language. Both C++ and Visual Basic is considered as high level languages.
Windows Vista was programmed in multiple languages such as C, C++ and probably .NET and C#.
As the source code is not available for Windows version, so only Microsoft can say in what language it is made of.
So the appropriate answer to this question might be Windows Vista.
Which of these can access the data faster?
1. Hard disk
2. Floppy disk
3. CD-ROM
4. DVD
Answer:
Obviously, Hard Disk
If pH = 3, what is the hydroxyl ion concentration?
1. 10^-11
2. 10^-3
3. 10^-6
4. 10³
Answer:
pH is the negative logarithm of hydronium ion H₃O⁺ concentration.
pH = - log[H₃O⁺]
pOH = -log[OH^-]
pH + pOH = 14
So, at pH = 3, pOH will be 11.
And the concentration of hydroxyl ion will be 10^-11.
(At pH =3 , concentration of H⁺ or H₃O⁺ is 10^-3).
MASCOT is used for
1. Pairwise alignment of protein.
2. Identify functions of protein.
3. Identify sequence of protein.
4. Multiple Sequence Alignment of protein.
Answer:

MASCOT is algorithm that help to identify protein sequence from mass spectrum. Other algorithms are SEQUEST, Prospector.
Which one of these is a cancer database?
1. GeneCards
2. OMIM
3. caBIG
4. CAGE

Answer:

The cancer Biomedical Informatics Grid (caBIG®) is an open source, open access information network with the mission of enabling secure data exchange throughout the cancer community. The initiative was developed by the National Cancer Institute (part of the National Institutes of Health) and is maintained by the Center for Biomedical Informatics and Information Technology (CBIIT).

More questions will be posted soon.

Contributed by: Chandan, Mahesh, Mrunmaya , Jitu.

Comments on correction and improvements are most welcome.

@Disclaimer:
The questions are based upon memory and contain manipulation. The accuracy of the questions can't be claimed.

Ab-Initio Protein Structure Prediction

2009-01-31T10:09:00.001-08:00

In this type of protein structure prediction 3-D models are built absolutely from scratch. It makes use of physical principle rather than previously solved structures. Prediction is done with no information about protein except amino acid sequence. The computer simulates physical process and forces that drive proteins into native conformation.

About Protein Folding:

Each specific sequence of polypeptide yields only single, compact, biologically active fold in native state. This fold generally has many sub-states with minor structural differences between them, but all of these sub-states have the same general fold.
In other words, under physiological conditions there appears to be one conformation for a given amino acid sequence that has a significantly lower free energy than any other. So, one can search all possible conformation in random fashion until we get lower energy conformation of native state.

But this seems to be impossible : Each peptide group has 3 possible conformation (i.e. allowed regions of α ,β, L) in Ramachandran diagram. A polypeptide of 150 residues will have 3¹³⁰ approx. 10⁶⁸conformation to search. It will take about 10⁴⁴ years. But actual folding time is between 0.1 to 1000 sec. in vivo or in vitro. To occur on this short time scale, the folding process must be directed in some way through a kinetic pathway of unstable intermediates to escape sampling a large number of irrelevant conformations.

A force field equation is used for prediction of structure. This force field includes all the physical forces that drive proteins into native conformation.

A typical Force Field: e.g ecepp

Free Energy Landscape

To find the energy minimum of a protein different softwares are used the use molecular dynamics. When we reach nearest local minimum this algorithm or mathematical routine gets trapped in the local minimum. Global minimum is the local minimum with lowest energy. To escape local minimum there are algorithm like metropolis monte carlo, simulated annealing. We have to repeat this process until global minimum is found. We don't really know how many times we have to repeat this process and there is nothing to distinguish the global minimum with local minimum except global minimum has lowest energy than all other local minimum. This whole problem is called multiple minima problem.

Secondary Structure Prediction

2008-11-25T11:45:00.001-08:00

It allows us to find where secondary structural elements (α helices, β sheets, loops) are located.

Secondary Structure Predictors

Chou-Fasman
COMBINE
GORIII
PRISM
PHD0
PHD3
PSIPred

PSIPred uses most recent algorithm that can predict secondary structure of about 80% accuracy.

Protein Threading or Protein Fold Recognition

Although proteins are of large no, tertiary structural motifs are limited to which most protein belongs. It is speculated that about 1000 distinct protein folding patterns may be present in total. Surprisingly, a few dozen folding patterns account for about half of all known protein structures. This helps to use previously solved structures as starting point.

To identify the fold the sequence is compared with all 500+ folds in library of known protein structure.

If pair-wise alignment shows less than or nearly 30% identity then it is ideal to be used for protein fold recognitions.

When successful, structure from fold recognition may be about 3-6Å RMSD (root mean square deviation) from actual structure.

Problems:

Only 70% chance there that top 10 prediction contain correct fold.
To reduce the number of predictions one requires more information like functional information (as function depicts structure), motifs, and position of exposed residues.
Still there is 30% chance that none of top prediction correct.
Quality result heavily depends on amount of information from other methods and human expertise.

Protein Structure Prediction

2008-11-19T10:46:00.001-08:00

Why prediction of protein structure important? You may ask what is there in protein structure??

That is because structure determines function of the protein. Take the example of enzyme dehydrogenases. It has an NAD-binding site called Rossaman fold ( Dinucleotide binding fold). This fold is made up a pair of βαβαβ subunit. Thus if a protein contain a βαβαβ subunit than it acts as a binding site for a nucleotide.

Structure is better conserved than sequences in protein during the course of evolution e.g. take the example of Cytochrome C of eukaryotes and C-cytochromes of prokaryotes in different species(which change with evolution in prokaryotes) where all perform general functions i.e. electron carrier. But different species exibit low degree of similarity of sequence to each other and to that of eukaryotes. They also differ in polypeptide loops on surface. But X-Ray structure are similar particularly chain folds and side chain packing to interior.

We require structural knowledge for rational drug design, protein engineering, for detail study of protein-biomolecule interactions.

Experimental methods to find structure of protein

X-Ray Crystallography: In order to know the structure using it we first have to crystallize the protein. We must have 20mg of material to start with. The results produced by it are accurate.

NMR: Can't be used for structures with more than 120 residues. Protein must be soluble and requires about 30mg/ml. It can locate flexible/rigid regions.

Other methods are Cryo-EM(electron microscopy),
CD(Circular dichroism)

X-Ray Crystallography, NMR, Cryo-EM gives 3D information of proteins but CD only gives one dimensional structure of protein i.e. secondary structure only

Why do we want predicted methods ??

Computer based prediction are much easier to handle with. E.g. one is free to make errors with out compensating much as it is inexpensive at least in future. Moreover we don't have always sufficient material for experimental methods. Some proteins even don't crystallize. So we turn to predicted method if experimental methods fail.

Computation Method of structure prediction

Secondary structure prediction
Protein Threading or Fold Family Recognition
Ab-initio structure prediction
Homology Modeling

Restriction Enzyme

2008-10-19T10:17:00.001-07:00

Have you ever asked a question that if restriction enzyme could ingest invading viral DNA then why don't it destroy cell's own DNA????

Reason behind it that all restriction enzyme are paired with methylases that recognize and methylate restriction DNA sites. After methylation, DNA site(e.g. GAATTC in case of EcoRI) are protected against most restriction endonucleases.

The two enzymes: Restriction endonuclease and methylase are collectively called Restriction-Modification system or R-M System.

But what about newly synthesized strand that will be unmethylated just after replication?? How does it protect it self from its own restriction enzymes??

In this case every time the cellular DNA replicates, one strand of the daughter duplex will be a newly made strand and will be unmethylated. But the other will be a parental strand and therefore be methylated. This half-methylation (hemimethylation) is enough to protect the DNA duplex against cleavage by the great majority of restriction endonucleases, so the methylase has time to find the site and methylate the other strand yielding fully methylated DNA.

Comparative genomics

2008-09-25T11:20:00.001-07:00

Let us first define what comparative genomics actually mean.

It is practice of analyzing and comparing genetic material of different species for purpose of studying functions of genes, studying evolution and inherited diseases.

But why
do we require comparative genomics? What is importance of it?

It tells us what are unique and common
between different species at genome level. E.g. To identify unique crucial protein in pathogens to use as
targets for products that are both safe and effective.
Genome comparison is surest and most reliable way to indentify genes , predict their functions and interactions. E.g. To distinguish between orthologues and paralogues.
Here we have two new terms: Orthologues and Paralogues. Actually genes with similar sequence are called homologous genes. These genes may undergo gene duplication or even get divergent in functions during the course of evolution. Genes with similar sequence and functions are called orthologues and genes with similar sequence and different functions are called paralogues. E.g. Genes encoding myoglobin and hemoglobin are paralogues.
Functions of human genes and other regions of DNA can be revealed by studying their counterpart in lower organisims.

Comparison of Complete Genome Sequences

Here we take example of
helicobacter pylori. We shall compare 2 strains of H.pylori and study their strain specific diversity.

Let's first give you a note for Helicobacter Pylori. It is an organism that colonizes in the human gastric mucosa. It induces gastric inflammation which can progress to ulcer, gastric cancer, or mucosal associated lymphoma.

About 60 to 80% of Asian and 30 to 40% of population in US are being affected by this. Remember that not all strains of H.Pylori cause diseases. Some are even beneficial to host. So the question arises what cause the difference??? Is it strain specific diversity or host diversity? R A Alm was the person who first compared genomes of two strains of H. Pylori: J99 and 26695.

What shall we compare??

Statistics of Genome

Size of genome i.e. total number of base pairs.
Overall G+C content
Location of regions with different GC content and are they located in corresponding regions in both genomes.
The two strains had similar genome size and G+C content and there were about 4 regions of different G+C content.

Predicted Open Reading Frames

Before knowing what to compare let us first describe how to identify genes in genome??

For identifying genes in case of prokaryotes there are different statistical methods such as GenMark, Glimmer. But eukaryotes are far more complex because of large intron regions and alternate splicing. So predicting of genes becomes quite difficult. Different statistical methods used to indentify genes in case of eukaryotes are GenScan, Genie.

Here are the thing that we have to find out.

Total no. of predicted ORFs.
% of coding regions
Average length of ORFs
Predicted genes with homology and its assigned function
Predicted genes with homology and no assigned function
Organism specific genes i.e. the genes that are not found yet in any other organism genome.
Strain – specific genes
Location of strain specific genes

In H.Pylori half of strain-specific genes are clustered in plasticity zone with different G+C content which suggests horizontal DNA transfer (Horizontal evolution and not vertical which is the general case)

Paralogues and Othologues

Find out if gene belongs to which paralogous family
DNA sequence difference between orthologues
Protein sequence difference between orthologues
In J99 strain 337 genes are members of 113 paralogous family.
DNA-sequence differences between orthologues are mainly found in the third position of coding triplets.

8 genes were with more than 98% nucleotide identity.
310 proteins were with more than 98% amino-acid identity.

Genomic Organization and gene order

Look for duplication, inversion, translocation
Check if gene order is conserved between genomes

In J99 3 single copy genes have complete or partial duplication.

10 regions showed translocation and inversion.

In case of gene order conservation,

84% have same neighbor in each side in both genomes
13% are flanked by strain specific genes, so no same neighbor
1.8% have different neighbor on one side because of organization difference

Bioinformatics Companies

2008-09-05T23:20:00.001-07:00

Metahelix Life Sciences Pvt. Ltd. ( Biotech )
Invitrogen ( bioinfo + biotech )
Brainwave Biosolutions limited ( bioinfo)

+ Data mining using our proprietary software and manual curation, backed by NLP

+ Design, implementation & integration of biological and chemical databases; relational, xml, various parsers

+ Data analysis support; neural network, HMM

+ Customized tool development to support laboratory experiments

+ Analytical tool development as per the scientific requirements

Connexios Life Sciences Pvt. Ltd. ( biotech+ bioinfo)
Invenio Biosolutions ( biotech )

Offers custom software development for gene and protein sequence analysis, and drug discovery.
Infosys Technologies Ltd ( bioinfo)
Accelrys Software Solutions Pvt. Ltd. ( bioinfo )
MWG Biotech Pvt. Ltd.
Quintiles Technologies (India) Pvt. Ltd.( clinical trial )
Carl Zeiss India Pvt. Ltd. ( biomedical instruements )
ReaMetrix India Pvt. Ltd. ( biotech )
Infovalley, Bangalore ( bioinfo )

Bioinformatician
Responsibilities:
•Provide training on bioinformatics-related concepts, applications and tools
•Collaborate and con9ult with researchers to analyze problems, recommend technology-based solutions, and design computational strategies for a wide range of biological research
•contribute to the design, development, implementation, and testing of biocomputing tools
.Develop computational tools in biology that use genomic data to generate biological hrohteseel
•Create or modify web-based bioinformatics tools, public domain biological databases and software tools for sequence, domain, and structural analysis
•ensure completion of deliverables and adherence to timelines
•Analyze and resolve issues that have the potential to jsparchze perfomiance and/or ability to meet agreed upon daliverables
•Perform any other related duties incidental to the wirk described herein
•Other duties as assigned
Job Specification:
•work requires a BSc. in Bioinformatics or Biotechnology with demonstrable computational skills or a BSc. in computer science with a strong interest in biology/genomics. Master or Ph.D. preferred.
•work requires at least 1 years of experience in bioinformatics.
•Experience with web-based bioinformatics tools, public domain biological databeses and software tools for sequenoe, domain and structural analysis.
•Familiarity with and development of computational tools in biology that use genomic data to ganerate biological hypotheses.
•Experience with a procedural language, proficient in Java, Peil, 'C', web design, DNA genome informatics, proteomics informatics, statistics, and computer science.
•Expeiience with relational databases and sQL helpful.
•Fresh graduate is enoouraged to apply.
Molecular Connection Pvt Ltd ( bioinfo )
Biocon Ltd. ( biotech )
Mphasis IT Services( clinical data mangement )
Vivus Health Center, Bangalore ( helth care )
AstraZeneca India Pvt Ltd.( drug discovery )
Ocimum Biosolutions Ltd., Hyderabad ( bioinfo )

Ocimum Biosolutions is a leading integrated genomics company providing comprehensive Genomic Reference Databases, Life-Science Lab Information Management Solutions, GLP compliant Microarray Services and essential research consumables. Over 2/3rd of the top 25 Pharma companies, leading research institutes and emerging biotech companies worldwide have chosen us as their preferred outsourcing partner and utilize our expertise for understanding underlying mechanisms of diseases, discovery and prioritization of gene targets & biomarkers.
Gene Logic Databases and Software
BioExpress®
ToxExpress®
Genesis and GX Connect Bioinformatics Products / Web Solutions
ToxShield™
ASCENTA® and SCIANTIS®
Genowiz™, Genchek™, iRNAchek™ and OptGene™

LIMS Solutions
Biotracker™ for Life Science Research
Biotracker™ for Manufacturing
Biotracker™ for Pre-Clinical Custom Bioinformatics Services
Pharmacogenomics

The BioIT Division consists of reference databases like The BioExpress® and The ToxExpress® System, Enterprise software solutions like Genesis, web based solutions like ASCENTA® and SCIANTIS® . It also includes three 21 CFR Part 11 & GLP compliant, Lab Information Management Systems (LIMS) products - Biotracker™, Biotracker™ for Manufacturing and Biotracker™ for Pre-Clinical and a suite of bioinformatics products, Genchek™ (sequence analysis), OptGene™ (gene design), Genowiz™ (microarray data analysis) and iRNAchek™ (iRNA template design). The division also offers specialized data analysis for different kinds of "omics" data and other custom software services.
Cell Works Group Inc.( bioinfo)
GE India Technology Centre Pvt. Ltd ( biomedical sciences )
Strand Life Sciences ( bioinfo )
Siri Technologies Pvt. Ltd.( bioinfo )
Thyrocare Technologies Limited ( biotech )
Millipore (India) Pvt. Ltd.( biomedical sciences )
Tata Consultancy Services , hyd ( bioinfo )
TechnoConcepts Pvt. Ltd.( biomed instruments )
Gangagen Biotechnology Pvt. Ltd ( biotech)
Lab India Instruments Pvt. Ltd. ( biotech instruments )
Simenens pvt ltd ( biomedical instruments )

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DNA Sequencing Methods

2008-08-26T11:25:00.001-07:00

Chain Termination Method (Sanger et al 1977)

In this method sequence of single stranded DNA molecule determined.

This is done by enzymatic synthesis of complementary polynucleotide chain. These chains terminate at specific nucleotide positions.

Principle

Single stranded DNA differing in length by single nucleotide can be separated by polyacrylamine gel electrophoresis. So we can get lengths from 10 to 1500 nucleotide into series of bands.

Steps

Starting material is identical single stranded DNA molecule.

Then short oligonucleotide is annealed to each single stranded molecule at same position. These gonucleotide acts as primer.

Strand synthesis requires DNA polymerase , dNTPs (Deoxyribonuleotide triphosphate) as substrate.

The DNA synthesis doesn't continue for long because along with dNTPs small amount of ddNTPs( Dideoxyribonucleotide triphosphate – It lacks 3'-hydroxyl group need to form connection with next nucleotide) is added.

The polymerase can't discriminate ddNTPs and dNTPs , so when corporated is growing chain causes termination i.e. blocks next nucleotide addition.

Chain Termination Sequencing

If ddATP is present then it causes termination at position opposite in T of template DNA

But as dATP is also present
termination may not occur at first T. It will continue until ddATP is incorporated

So a set of new chains all of different lengths ending with ddATP is produced

These chains is loaded into one lane

Similarly family generated form ddGTP, ddCTP, ddTTP is loaded into 3 adjacent lanes

Then electrophoresis is done.

Now the sequence can be directly read for position of band in gel

Production of Single Stranded Template

Cloning DNA in Plasmid Vector: Resulting DNA is double stranded. It is converted to single stranded by denaturation with alkali or boiling
Shortcoming: Difficult to prepare sample which is not contaminated with small quantities of bacterial RNA and DNA which may act as spurious primer or template.
Cloning DNA in Bacteriophage M13 Vector: M13 bacteriophage has single stranded DNA genome. It is converted to double stranded replicative form after infection. The advantage is that these replicative forms can be manipulated in same way as plasmid vector i.e. inserted by restriction followed by ligation. Then single stranded DNA clone can be obtained from multiplied M13 bacteriophage after infection. The disadvantage is DNA fragments inserted longer than 3kb
suffer deletions or rearrangement.
PCR: There are various ways. One of them is carrying out PCR with one normal primer and one labeled with metallic bead. Labeled strand can be purified by using magnetic device.

Properties of DNA polymerase for Chain Termination Sequencing

High Processivity: So that it doesn't dissociate form template before incorporation chain terminating nucleotide
Negligible or Zero 5' →3' Exonuclease Activity: Removal of nucleotides for 5' ends of newly synthesized strands alters lengths of these strands. So, it becomes impossible to read sequence from banding pattern
Negligible or Zero 3'→5' Exonuclease Activity: To assure polymerase does not remove chain termination nucleotide once incorporated.

The polymerase with these properties doesn't occur naturally. It is produced artificially by modifying enzyme.

Klenow Polymerase: It is version of E.Coli Polymerase I with 5' →3' exonuclease activity removed. It has low processivity. So, gives non-specific bands called shadow bands. Hence it is not used now.
Sequenase: It is modified version of DNA polymerase of T7 bacteriophage. It has high processivity and no exonuclease activity. Hence this is the enzyme which is used in chain termination reaction.

Sequencing and Identification of Protein

2008-08-22T11:48:00.001-07:00

Sample Preparation

Hundreds and thousands of copies of single cell type is made from which protein can be extracted.

Get Cell: Cell of single type is grown, obtained from biopsy or body fluids

Culture Cell: Cells are then placed in growth medium in petridish. Cells feed and multiply. Now base of the petridish is covered with thousands of cells.

Make More Copies: Cells are again divided in more petridishes to get more copies of cells. Millions of copies are produced. Then the cells are scraped from petridish base and put it in test tube

Add Detergent: Detergent added ruptures outer membrane of cell membrane. Now the test tube contains proteins along with cell debris.

Spin: The solution is know centrifuged to separate proteins form cell debris like cell membrane, cytoskeleton. After centrifugation the test tube contains cell debris at bottom and protein above.

Separation

A single cell has millions of protein type. Hence there separation is necessary.

2D Electrophoresis: Separation takes place along line i.e. in one dimension and further separated over an area i.e. in second dimension.

First Dimension Separation: Protein is placed in gel strip. The gel strip has pH gradient that ranges from acidic to alkali. The proteins are color coded based on pI levels i.e. isoelectric point.

Then voltage is applied which moves the protein into location where electric charge of protein balances with gradient. Proteins are now organized according to pI along line i.e. in one dimension.

Second Dimension Separation: A solution is added to proteins to give it negative charge. Then it is transferred to gel sheet in a tray. Voltage is applied. Proteins get separated according to size.

Transfer: Proteins are now organized by pI in one dimension and size in second dimension. But still proteins are not completely separated. A single dot may contain 2 to more different protein type. Now the dots are cut out and transferred to 96 well plate or test tubes. This is done either in hand or using computer through robotic arm.

Ionization

Cut the protein into smaller pieces (peptides), and then provide a steady stream of peptides to the mass spectrometer.

Cleavage of Proteins: Done by enzyme protease. In avg. peptides of 20 amino acids long chain are produced. Then the mixture is evaporated leaving dry peptides. Then another liquid is added that dissolves these dry peptides.

Separation of Peptides: Then the peptides with solution are carried into liquid chromatography (LC). LC has tiny spheres which attracts the peptides. Then the peptides are freed from spheres by changing the content of solution slowly.

Spraying of Peptide ions: Peptides then reach end of the cone shaped tube due to electric field produced. Peptides pulled out of the tube into air by electric field. The solvents evaporate from the airborne droplets. Positive charge is left behind on peptide. Then positively charged peptide moves towards negatively charged mass spectrometer.

Mass Spectroscopy

It measures the mass of the peptides and peptide fragments. From it sequence of amino acid can be identified. It consists of two quadrupole analyzer and time of flight(TOF) analyzer.
Each quadrupole has 4 rods, two with positive charge and other two with negative charge. Rods carry DC charges along with alternative current (AC).

Entry and isolation: Charged peptides enter and feel the charges on rod. By controlling voltage, mass of peptide to be isolated is selected. Most of peptide has unique mass therefore only specific type of peptide with particular mass will pass through the first quadrupole to second. Other peptides collide with walls and rods, and don't enter the second quadrupole.

Second quadrupole entry: Many of the copies of same peptide enter through small hole in first quadrupole to second quadrupole. Inert gases like nitrogen or argon are introduced to second quadrupole. Peptides collide with the gases molecules and break into fragments. Collisions made are infrequent to avoid breaking down of peptide into individual amino acids. The fragments produced don't have same charge. The two fragments produced from single peptide, the right fragment has positive charge and left has no charge.

Mass Measure: Then peptide fragments are entered into TOF section which has a plate of strong positive charge. The positive charge fragment gets repelled from plate and fall down, where as no charge fragment pass by the repeller plate.

Measure of Mass:
Time taken for the fragment to travel from repeller plate to detector at end is observed. Heavier fragment has more inertia then lighter ones. So the heavier fragments don't react quickly to charge on the plate. Hence lighter fragments move faster then heavier.

Record Data: The graph with horizontal axis shows TOF. Hence represent mass. Vertical axis represents intensity.

Informatics

It is the use of computer and database to identify protein. In the graph each peaks represents one peptide fragments i.e. millions of fragments of same mass, hence same sequence. Here 842 represents entire polypeptide with 7 amino acids and 743 represents peptide with 6 amino acid and so on.

Identify Amino Acid: It is done by simple arithmetic. Here subtract 743 from 842 to get 99 i.e. mass of valine.

Protein Identification: Sequence is compared with the database to identify the protein. Since entire human genome sequence is known almost every protein can be identified. If no matches are found then a new peptide is discovered.

Virus Helped to Create Microbatteries

2008-08-20T12:24:00.001-07:00

A virus has helped to create a new type of tiny battery, made with a simple stamping technique that could power miniature devices.

Electronic devices used for controlled drug delivery, or to power tiny lab-on-a-chip applications, need to get their power from somewhere. But as conventional batteries are made smaller and smaller, they contain less and less of the materials that actually store charge, causing a decline in efficiency.

Using nanoscale components can boost a battery's capacity to store charge. Now, scientists at the Massachusetts Institute of Technology, Cambridge, have designed a quick method to build a microbattery that relies on a genetically-engineered virus called M13.

The scientists first made a template from polydimethylsiloxane (PDMS), a commonly used silicon-based organic polymer. After coating it with alternating layers of positive and negative electrolytes, they added the virus.

The virus had been designed to have negatively charged amino acids at its surface, so that it stuck to the template, and an affinity for cobalt — a favoured material for batteries. Each virus is a semi-rigid fibre a few nanometres in diameter and about a micrometre long, which tends to pack tightly into a whorl that looks similar to a fingerprint.

The whole assembly was dipped into a solution of cobalt ions, which coated the viruses to create a very large surface area that could store charge. Stamping the template onto a platinum layer and peeling off the PDMS
left behind an array of small dots of the prepared material, cobalt-side down, which formed the heart of an effective battery. The work is published in the Proceedings of the National Academy of sciences

"This is the first time anyone has ever stamped a battery device," says Paula Hammond, part of the MIT team.

It's also an elegant demonstration of the potential use of viruses for making nanodevices, says Jan van Hest from the Nijmegen Centre for Molecular Life Sciences, the Netherlands. But he wonders if the addition of viruses could actually be overengineering the system. "Using viruses as a template introduces an extra non-active layer, which lowers the percentage of active material," van Hest says. He suggests that cobalt oxide nanoparticles could work just as efficiently.

But the process is certainly an improvement on current technologies, says Hammond, "We're talking about a simple, inexpensive and environmentally better way of generating a microbattery," she says. She hopes to extend the design so that the second electrode necessary for a complete battery can also be stamped using the same process.

First Sequenced human chromosome

2008-08-20T09:17:00.001-07:00

Do you know?

The first human chromosome to be sequenced is chromosome no 22.

The sequencing completed
in December 1999

The genetic code of it comprised of 33.5 million bases

About Chromosome 22

Chromosome 22 is the second smallest of the human autosomes. The short arm (22p) contains a series of tandem repeat structures including the array of genes that encode the structural RNAs of the ribosomes, and is highly similar to the short arms of chromosomes 13, 14, 15 and 21. The long arm (22q) is the portion of human chromosome 22 that contains the protein coding genes and this is the region that has now been sequenced. The completed sequence consisted of 12 contiguous segments covering 33.4 million bps separated by 11 gaps of known size. One of these gaps has subsequenctly been closed by the Oklahoma group. The sequence is estimated to cover 97% of 22q, and is complete to the limits of currently available reagents and methodologies. The largest contiguous contig is >23 million bps, and at that time, this was the largest piece of continuous sequence determined

DNA

2008-08-09T10:53:00.000-07:00

Deoxyribonucleic Acid (DNA), genetic material of all cellular organisms and most viruses. DNA carries the information needed to direct protein synthesis and replication. Protein synthesis is the production of the proteins needed by the cell or virus for its activities and development. Replication is the process by which DNA copies itself for each descendant cell or virus, passing on the information needed for protein synthesis. In most cellular organisms, DNA is organized on chromosomes located in the nucleus of the cell.
a large number of chemical compounds, called nucleotides, linked together to form a chain. These chains are arranged like a ladder that has been twisted into the shape of a winding staircase, called a double helix. Each nucleotide consists of three units: a sugar molecule called deoxyribose, a phosphate group, and one of four different nitrogen-containing compounds called bases. The four bases are adenine (A), guanine (G), thymine (T), and cytosine (C). The deoxyribose molecule occupies the center position in the nucleotide, flanked by a phosphate group on one side and a base on the other. The phosphate group of each nucleotide is also linked to the deoxyribose of the adjacent nucleotide in the chain. These linked deoxyribose-phosphate subunits form the parallel side rails of the ladder. The bases face inward toward each other, forming the rungs of the ladder

The nucleotides in one DNA strand have a specific association with the corresponding nucleotides in the other DNA strand. Because of the chemical affinity of the bases, nucleotides containing adenine are always paired with nucleotides containing thymine, and nucleotides containing cytosine are always paired with nucleotides containing guanine. The complementary bases are joined to each other by weak chemical bonds called hydrogen bonds.
In 1953 American biochemist James D. Watson and British biophysicist Francis Crick published the first description of the structure of DNA. Their model proved to be so important for the understanding of protein synthesis, DNA replication, and mutation that they were awarded the 1962 Nobel Prize for physiology or medicine for their work.