The NIH Biomedical Information Science and Technology Initiative defines bioinformatics as:

“Research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data.”

Still confused? Don’t fret, most people are when they hear that definition. I usually like to tell people:

“Bioinformatics combines the latest technology with biological research.”

Over the past decade or so, and even prior, computers have become an integral part of every industry. Biological research is no different. Computer technology has dramatically accelerated the rate at which scientists are able to acquire and analyze biological data. The vast amount of data that is produced more rapidly each day has introduced new challenges to the field, involving storing, organizing and archiving this data. The sharp increase in volume of data has also brought about the need for faster and better analysis and visualization tools. Each area of bioinformatics, from acquiring to storing to analyzing the data, has challenges of its own, and it is not uncommon for advancements in one area to drive advancements in another.

To gain a better understanding of the diversity of bioinformatics, let’s invent a hypothetical yet interesting problem that we want to tackle using bioinformatics:

Let’s assume we have a species of bacteria that is part of the normal millions of ‘good’ bacteria living on and inside healthy human beings; we’ll call this Bacteria X.0. One day Bacteria X started making people very ill. What happened to Bacteria X.0 to make it become the harmful Bacteria X.1? Let’s see how we could answer this question using bioinformatics, along the way gaining insight into the wonderful world of bioinformatics.

Using traditional molecular biology techniques, we isolate Bacteria X and extract its DNA. Then we “sequence” this DNA. Cue the first link in the bioinformatics chain: acquiring data! Acquiring data is the process of generating useable data from a biological sample. In our case, deriving and determining the DNA sequence of the Bacteria X genome.

The next link in the chain is storing this sequence data. While bacterial genomes are typically small, other genomes, such as those of human beings, can produce terabytes (1000 gigabytes) of data.

Now we analyze this sequence data. There are people who specialize in developing computational tools to analyze and visualize data, versus people who actually analyze the information. A typical analysis for our sample case might be to first graphically visualize and compare the genome of the original, harmless Bacteria X.0 with the genome of the new, harmful Bacteria X.1. A scientist might observe a segment of DNA in Bacteria X.1 which is not present in the original Bacteria X.0. This new region of DNA may be responsible for the harmful effects, so the next analysis steps might be to drill down deeper into this region and see what genes lie there, what the function of those genes are, where they may have come from, etc.

[Remember: all assumptions made and conclusions drawn in this example are hypothetical and for illustrative purposes only.]

In this example, we encountered at least 4 different specialized areas within the field of bioinformatics:

1)      Acquiring of data (working with machines and equipment, sequencing DNA)
2)      Storing data (typically working with databases)
3)      Developing tools to analyze and visualize data (programming)
4)      Analyzing data (statistics, analysis)

Typically, individuals will specialize in one particular area rather than working simultaneously across all these fields. That, combined with all the different applications of bioinformatics, means you could ask 100 different “bioinformaticians” what they do and get 100 very different answers!

Bioinformatics techniques are now employed in every area of biology and research, some of which include cancer research, crop yield optimization studies, medical genomics, ecology and evolution. The emerging field of DNA barcoding combines laboratory and bioinformatics techniques to catalogue all living species as well as identify new species. Since DNA is the blueprint of life, bioinformatics can be applied to any research involving living organisms (or organisms which once lived, see Otzi the Iceman).

One thing to remember: the four areas described above are not as simple as I’ve portrayed them to be. For example:

• When sequencing a sample, you might be interested in sequencing RNA as opposed to DNA.
• Before analyzing sequence data, the quality of this data must be validated. Sometimes large chunks of sequences need to be ‘put together’ (e.g., ‘genome assembly’). Both these areas (quality analysis and genome assembly) are highly sought after areas of specialization.
• In addition to sequencing, data analysis can also generate vast amounts of new data.

The field of bioinformatics is ever changing and rapidly evolving. Techniques that were new 2–3 years ago might be outdated today; vice-versa, techniques that were unpractical 2–3 years ago might be invaluable today, thanks to advances in computational processing capabilities, for instance.

So, whether you’re interested in plants, animals, bacteria, fungi, virology, genetics, developing databases, writing code, statistics, engineering, computer hardware, or web technologies, there may be a spot waiting for you in the field of bioinformatics.

Hope to see you on the inside!

Are there ways the computer has out-shined the human mind? Perhaps.  But I think the better question is, can computers ever catch up to our incredible brains? I don’t think so.

I was reminded of this the other day when I read an article from “Nature News” regarding  an online game called, “Phylo”, created by computational biologists at McGill University in Montreal, Canada.   People who played this game were able to more accurately solve problems that computers  have had in matching DNA sequences from different organisms/diseases. And this doesn’t require a person with skills in science.  It only requires someone with visual intelligence, something a computer doesn’t have, at least not in the same way.

In this current genomic era, we are confronted by massive amounts of genomic data that we are trying to make sense of. We are trying to figure out how DNA sequences differ between multiple organisms and between diseased organisms and disease-free organisms. Like putting together a puzzle, people have created computer programs that can take multiple sequences from different sources and align them in a way that accurately compares them, pointing out the differences that indicate evolutionary change.  The problem computers have is in figuring out where to create proper alignments between many different sequences. In other words, where do the matches make the most sense across the board? Computers do a decent job with this enormous task, but are limited in accurately aligning sequences every time, especially with several sequences that may have more differences than similarities.

“Phylo” was created to help address the problems computers have in matching many sequences together. In this game, the goal is to match as many colored blocks from one string of blocks to other strings of blocks. Each string of blocks is a DNA sequence.  Each differently colored block represents a base (A, T, G or C) in our DNA.  This is essentially a game of matching colors between as many as 8 strings of blocks using a set of rules that helps gamers create the best matches.  No scientific experience is required.

The “Phylo” game has been used to help more accurately align sequences of promoter regions that control expression in 521 disease-associated genes in 44 vertebrate species.  The game has drawn over 3000 regular visitors and the gamers have been able to surpass the accuracy of traditional algorithmic Multiple Sequence Alignment (MSA) tools used by the computer in as many as 70% of the sequences.

If you have never had a chance to help out scientists in the comparative genomics field before, now is the time! Plus, it is a lot of fun.

Check out Phylo!

For more information go to:

Kawrykow, A. et al. PLoS ONE 7, e31362 (2012)

Gamers outdo computers at matching up disease genes

Tumor cells are a mosaic of different cell types

For the last decade or so, progressive cancer treatments involved taking samples of tumors, testing the cells to determine the genetic makeup, and then prescribing medicines targeted to specific mutations. There are many benefits to this approach, but it doesn’t always work.

It turns out that tumors aren’t uniform; they are mosaics of cells that can be genetically very different. A recent paper in the New England Journal of Medicine showed that a cell in one area may not be the same as a call in another area (a phenomenon called “intratumor heterogeneity”). So a treatment based on a sample from one area may not work for the whole tumor. Some tumor cells may be resistant to the drug so the cancer persists, or even grows.

In this British pilot study, cells from 9 different locations within a primary kidney tumor, and several metastatic tumors, were analyzed using next generation DNA sequencing. Only 34% of the 118 mutations identified were present in all the samples, and several of the major cancer genes were mutated in different ways in different locations. This turned traditional ideas about cancer cells being “clones” of a single, mutated cell on its head.

Previously, it was thought that a tumor develops when a single cell accumulates sufficient mutations over time that eventually lead to it dividing uncontrollably. Therefore if you could find the original mutation, and target treatment to that, then every cell would react to the treatment. But if the tumor is made up of a mosaic of cells, then they could all react differently to the drug. The researchers then created a phylogenetic “tree,” identifying which cells were more persistent, being in the trunk of the tree. They proposed that if those cells were receptive to a targeted medicine, the treatment might be more effective; if not, less so.

Although this study only involved four patients, the results provide a new way of thinking for researchers and clinicians. If we remove the presumption that all tumor cells are identical, we open the way for more creative thinking about how to tackle the problem.

Alu is an example of a so-called “jumping gene” – a transposable DNA sequence that “reproduces” by copying itself and inserting into new locations throughout the genome. Alu elements are classified as SINEs, or Short INterspersed Elements. All Alus are approximately 300 bp in length and derive their name from a single recognition site for the restriction enzyme AluI located near the middle of the Alu element. Alus are also classified as retrotransposons, because they need a special enzyme (a reverse transcriptase) to produce mobile copies. However Alus are “defective transposons” as they depend on the enzymes of other transposons for mobility, like the best characterized retrotransposon family called L1, a Long INterspersed Element (LINE).

Once an Alu inserts at a chromosome locus, it can copy itself for transposition, but there is no evidence that it is ever excised or lost from a chromosome locus. So, each Alu insertion gets fixed through evolutionary time. Like genes, Alu insertions are inherited in a Mendelian fashion from parents to children.

First discovered in corn about 60 years ago by Nobel laureate Barbara McClintock of Cold Spring Harbor Laboratory, jumping genes are now known to make up more than 40 percent of the entire human genome and may play an important role in genome evolution by creating new mutations and gene combinations.

Until this recent study, L1 retrotransposition was assumed to take place during early development mainly in germ cells (ovaries and testes) and rarely in somatic tissues (non-sex cells). Now researchers from the Roslin Institute near Edinburgh, Scotland, have capaciously mapped retrotransposon insertion sites in the genomes of normal human brain cells.

The researchers used state-of-the-art DNA sequencing technology to identify retrotransposons in brain tissue samples taken at postmortem from three individuals who were healthy when alive and had no neurological disease, nor signs of abnormality in their brain tissue. Focusing on two regions—the hippocampus and caudate nucleus (that is also involved in memory)—they identified nearly 25,000 different sites for the three main retrotransposon families: L1, Alu and SVA.

The numbers are impressive: their analyses identified a total of 7,743 insertions of L1s in the hippocampus and caudate nucleus, areas that were known to show cell division after embryogenesis. They also found nearly 14,000 insertion sites for the Alu family, which has not been encountered before in the brain.

Interestingly each sample showed its own set of unique retrotransposition events, which meant each one had an individual mutagenesis background. According to the study, retrotransposons more likely to be integrated in genes that were expressed in the brain, perhaps because these genes are more susceptible, as their DNA is packaged in a more accessible way.

So what is the consequence when retrotransposons preferentially jump within genes that play key roles in normal brain function? They cause normal gene expression to shut down, disrupting normal gene function. Affected genes include those genes encoding receptors for the neurotransmitter dopamine and membrane transporters. Others integrated in tumor-suppressor genes, which are deleted in several different types of brain cancer. Jumping genes were also found within genes encoding regulatory proteins linked to psychiatric illnesses, such as schizophrenia and Alzheimer’s disease. As well as generating mutations by inserting themselves into and disrupting genes, retrotransposons can alter gene activity if inserted into adjacent regulatory regions of DNA. Such alterations can have a valuable or harmful outcome, without doubt a powerful tool driving evolution.

The researchers also reported that jumping genes were more active in the hippocampus compared to the caudate nucleus. This is highly interesting, because the hippocampus is known to be critical for memory and learning, and is thought to be one of the few parts of the brain that continues to produce new cells throughout life. Are jumping genes therefore involved in how we learn? Researchers are now beginning to investigate whether jumping genes help us adapt processing information through learning.
So when do jumping genes actually get mobile?  It has to happen during the brain’s development because retrotransposition requires cell division. After early childhood this does not take place in the brain; new neurons are generated in the hippocampus from stem cells, through a process called neurogenesis.  Retrotransposons then take the opportunity to jump randomly (!) into parts of the chromosome that have been opened up for DNA replication.

Once thought to be rare, these neural integration events actually take place surprisingly often. The analyses in this latest study suggested that most brain cells undergo an average of 80 L1 integration events! This means each neuron is likely subjected to a unique combination of insertions, leading to a “genomic plasticity” within populations of cells.

This research completely overturns the belief that the genetic make-up of brain cells remains static throughout life. It indicates that neuronal networks are constantly changing with each new experience as novelty and challenge both trigger neurogenesis. It may finally result in differences in brain function among individuals, even in genetically identical twins.

Further reading:

Video link about Alu elements and Autism.

Nature papers about L1 transposition in human neurons and the impact of Alus on human evolution.

Cholesterol is a crucial fat-like substance produced by the liver that is required for bodily functions. It is the main sterol synthesized and transported in the blood plasma of all animals. Cholesterol is responsible for a number of functions such as:

1. Building and maintenance of the cell membranes
2. Production of sex hormones (androgens and estrogens)
3. Production of bile
4. Metabolism of fat-soluble vitamins, including vitamins A, D, E, and K
5. Insulation of nerve fibers
6. Conversion of sunshine into vitamin D

Cholesterol being a crucial part of our development can have a dark side. The gene DHCR7 (7-dehydrocholesterol reductase) found on chromosome 11 is responsible for the production of cholesterol and mutations in the gene may lead to a metabolic disorder known as SLOS (Smith-Lemli-Opitz Syndrome). This disorder currently occurs once out of every 20,000 births. Individuals with SLOS are unable to produce enough cholesterol to support normal growth and development. This leads to developmental delays, physical malformations, mental retardation and issues with major organs such as the heart. Currently the only treatment for the disorder is cholesterol supplementation to improve growth and developmental progress.

SLOS is inherited in an autosomal recessive pattern, basically both copies of the gene within a cell are mutated. This identifies that the parents of a person with SLOS each carry a mutated copy of the gene, however they do not have any symptoms or signs of SLOS. It may be that genetic counseling may be one form of a preventative method for the disorder. This brings up a great question, should genetic counseling be mandatory for potential parents to decrease transmission of severe genetic disorders?

What is clear from this recent paper (Neal et.al. Patterns and rates of exonic de novo mutations in autism spectrum disorders, Nature, advance online publication, http://dx.doi.org/10.1038/nature11011) is that ASD is highly polygenic in origin, i.e. hundreds of genes influence autism risk. Getting to this answer, including two genes in particular that were determined to be very strongly linked with autism (CHD8 and KATNAL2), was a real technical achievement in that in involved analyzing the genomes of 175 trios (mother, father, autistic child). Sequencing 525 human genomes is something that would have been unimaginable just a few years ago. While it is clear that we still have much to understand about this complicated disease, the technological limitations that previously limited progress are beginning to fall away. Hopefully many more important clues are just around the corner.

Some fun facts about blood:
There is no substitute for blood.
Red blood cells live about 120 days.
Plasma, which is 90 percent water, is a pale yellow mixture of water, proteins and salts.
Thirteen tests are performed on donated blood, 11 are for infectious disease.
94 percent of blood donors are registered voters.
Newborn baby has about one cup of blood in his or her body.

The method is more effective than just using light. When light passes through tissue, it is scattered, and the scattering blurs images from light reflected off tissue. The effect is dramatic, because sound waves pass through tissue with about 10,000 times less scattering, so the sound waves coming from tissues are much less blurry. This means that tissues can be imaged with good detail up to 10 centimeters deep -rather than a few millimeters using just light.
Photoacoustic tomography is very flexible, as almost all molecules absorb light at some wavelengths. By changing the wavelength of light used to excite the tissue, different molecules can be heated and detected. For instance, DNA and RNA absorb specific wavelengths of ultraviolet light, so by shining UV light on tissue, they can be imaged. This can be used to identify nuclei with abnormal chromosomes, a common defect seen in cancer cells. Hemoglobin is also easy to image, which can identify blood vessel formation around tumors. In fact, the flow of blood can be imaged. Likewise, the level of oxygen can be measured, which can indicate regions with hypoxia which are found at the center of tumors and regions with heightened metabolism, such a quickly growing tumors. Tissues that are hard to image can also be imaged by introducing a dye that changes the light absorption. For instance, nanoparticles designed to stick to cancer cells can increase the contrast of the cells and make them easier to detect.

The technique is now being used to image skin cancer, detect breast and prostate cancer, and to follow the response of tumors to treatments. As the technology gets better, hearing the “echoes” off of tumors may become one of the best ways to find and monitor them!

Reference:
Photoacoustic Tomography: In Vivo Imaging from Organelles to Organs. Lihong V. Wang and Song Hu Science 23 March 2012: 1458-1462

When we walk, our shoes pick up various seen and unseen organisms.  Many of us walking through a field or park may be stepping on and carrying seeds from various plants. Seeds blow in the wind and also creep into the crevices of our clothes and bags.  As carriers, we then transport them to new areas, making each of us essentially a seed planter. At first glance this seems like a nice job description.  However, the problem lies in the fact that seeds can find themselves in uncharted territory.

In Antarctica, the landscape has changed dramatically in recent years. As the climate is warming, the Antarctic Peninsula is uncovering more areas that are “ice-free”.  These areas are particularly vulnerable as alien species have flourished here.  This is in large part due to the transfer of seeds from visitors to the continent.  Environment correspondent Richard Black of BBC News wrote in his article, “Alien invaders threaten Antarctic fringes,” that an average of 9.5 seeds are carried by each visitor to this continent.  Many of these seeds, coming from as far as the North hemisphere, can survive and thrive in the warmer areas of the continent, potentially causing a major ecological shift.

Some invasive species, such as the grass species Poa annua, have taken over some of the sub-Antarctic islands such as South Georgia.  It is thought that scientists brought this seed to parts of Antarctica due to the proximity of Poa annua grasslands to the different science research stations.

South Georgia has an even bigger problem. Due to whaling expeditions, rats have infested grasslands and have become the dominant predatory species. Perhaps this island is a microcosm of what is to come in the great White Continent.  Covered with rats.

What is the solution? Well, we can’t completely prevent all unwanted seed from arriving in Antarctica, no matter how hard we try. However, organizations are trying to help reduce the amount of alien seed arriving and surviving on the continent. The International Association of Antarctic Tour Operators (IAATO) has been working diligently to ensure that visitors are “seed-free” and some science organizations have created guidelines for checking of vehicles, bags and clothes for seeds. Perhaps extra surveillance of visitors will ensure that Antarctica never becomes a vast grassland.

For more information:

http://www.bbc.co.uk/news/science-environment-17258799

http://blog.earth-touch.com/nature-news/south-georgias-rats-get-the-death-sentence/

Schizophrenia is a mental disorder characterized by a breakdown of thought processes and by poor emotional responsiveness. According to the WHO the disorder affects around 0.3–0.7% of people at some point in their life, or 24 million people worldwide as of 2011. There is no general cure and the pharmacologic treatment of schizophrenia leaves much to be desired.

Now the National Institute for Health Research in the U.K. is funding a large research trial on Minocycline beginning this April.

Scientists believe schizophrenia and other mental illnesses including depression and Alzheimer’s disease may result from inflammatory processes in the brain. Minocycline, which is a broad-spectrum tetracycline antibiotic, has anti-inflammatory and neuroprotective effects, which could account for the recent positive findings.

The new hope comes after case reports from Japan in which the drug was prescribed to a young male patient with schizophrenia.  The young man had no previous psychiatric history but became agitated and suffered auditory hallucinations, anxiety and insomnia. Blood tests and brain scans showed nothing unusual and he was started on the powerful anti-psychotic drug Halperidol. The treatment had no effect and he was still suffering from psychotic symptoms a week later when he developed severe pneumonia and was prescribed the antibiotic Minocycline to treat the infection. This treatment surprisingly led to dramatic improvements in his psychotic symptoms. When the pneumonia cleared and Minocycline treatment was stopped, the schizophrenia symptoms reappeared.

This serendipitous observation prompted researchers to test Minocycline in patients with schizophrenia around the world. Trials have already been held in Israel, Pakistan and Brazil, with schizophrenic patients showing significant improvement.

Minocycline might be a safe and effective solution to bring symptoms of schizophrenia under control. But more work on how antibiotics alter the inflammation status of the brain remains to be done, as well as trying to find a permanent treatment. Using antibiotics in this way presents a problem. Antibiotics are compounds that are literally ´against life,´ aimed against microbial pathogens. The treatment of infectious diseases by antibiotics is compromised by the development of antibiotic resistance of microbial pathogens. There is a direct correlation over time between antibiotic use and the increase in antibiotic-resistant bacteria. Researchers therefore need to address this issue but the signs are good: Minocycline has been on the market for a while, is broadly described, and resistance seems to have been avoided thus far.

Further reading:

Background information, video links and animations about schizophrenia can be found at the DNA Learning Center’s G2C Online webpage.

Van Os J, Kapur S. Schizophrenia. Lancet. 2009;374(9690):635–45. doi:10.1016/S0140-6736(09)60995-8. PMID 19700006