Large Hadron Collider: Apocalypse Soon?

Probably Not

While looking over my site visit statistics, I found that many of my visits are to my article a few months back about the Large Hadron Collider under construction in France and Switzerland. A quick glance through the search terms that have led people to the article yield the following:

• LHC Black Hole
• Large Hadron Collider Doomsday
• Large Hadron Collider Apocalypse
• Large Hadron Collider Destroy Universe
• Harge Hadron Collider End of the World
• CERN destroy world

These searches are coming from the UK, France, Texas, Massachusetts, Singapore...you get the point. It seems like a lot of people are worried about CERN's LHC destroying the world.

Since this seems to being weighing heavily on the consciences of many people, I thought I would address it with a little more detail.

The nature of black holes has been debated for quite some time. What most people know about black holes is that they are incredibly dense masses in the universe. Since the force of gravity is dependent on mass, a black hole has an incredibly strong force that is powerful enough to capture even electromagnetic waves like visible light. For me, this has always been a little bit preplexing becase I used to wonder why Black holes ever stopped engulfing everything around them. To my mind, if something was massive enough to capture anything of mass around it, then it would continue to add mass. If it continued to add mass, it would then have an even greater gravitational force. Why would it ever stop?

It seems that black holes do lose their mass. They emit radiation which is actually representative of the mass and energy consumed by the black hole. Eventually, they radiate into nothingness; particularly small black holes created by collisions of tiny subatomic particles.

Now, I cannot claim that these are unequivocal facts. Much of this has been debated since the early 1970's. Stephen Hawking himselfrecently retracted his postulation that the radiation out of black holes carries no information from the mass and energy captured by it. He now believes that the radiation does carry information about what the black holes is made out of. He hsays the only problem with the information is that it is so random and jumbled that piecing it together into something we can interpret is virtually impossible.

However, the idea of black holes quickly radiating their energy such that they lose their mass makes a lot of sense to me. Otherwise I can envision black holes ever growing and consuming the whole universe...there is no evidence of this in astronomy.

So in the case of the tiny little subatomic particle derived black holes generated by CERN at the Large Hadron Collider, it seems very unlikely that a sustained black hole can possibly be produced. It will lose its mass to radiation faster than it can collect mass do to its gravitational pull.

Counting Chickens: Cancer Still Tough to Crack

Pennsylvanian Inventor Touting Cancer "Cure"

Cancer is a challenge. It is a challenge to patients. It is a challenge to their families. It is a challenge to researchers.

A leukemia patient from Erie, Pennsylvania decided to take matters into his own hands. His name is John Kanzius and he doesn't have an MD, Phd, or even a bachelors degree. He is, however, a creative mind who has been a radio and TV engineer for most of his life. Kanzius put his experience with radio wave technology to use when he coupled it with cutting edge nanotechnology. He and his partners have created injectable nanoparticles which generate heat when they are exposed to low frequency radio waves. This is definately and interesting and inspirational story.

Kanzius's energy transfer technology sounds fascinating, it really does. The idea of being able to heat small particles with projected radio waves could have lots of uses. Unfortunately, I just don't think its a cure or even a particularly useful technology for the treatment for cancer. Sorry, Mr. Kanzius.

Basically, Kanzius wants to physically perturb the cancerous cells by cooking them. He says that cancer cells will die when exposed to temperatures over 130 degrees. Well, so will healthy cells. While that is an interesting idea, it really isn't very much different from killing the cancerous cells chemically with chemotherapeutics or with targeted radiation. One would still need to contend with the issue of cell/tissue specificity.

The biggest challenge, which Kanzius addresses/glosses over in interviews, will be the targeting of cancer cells only. How will he keep his nanoparticles from cooking the rest of patients' cells? How is this any different from chemotherapy which targets cancer cells in a rudimentary way by targeting dividing cells? Honestly, one could make a case to say that chemotherapies are ahead of Kanzius' radio nanoparticles because at least there is some specificity. I suppose the advantage of his technology is the fact that "treatment" can be turned off when the radio wave generator is turned off.

For his technology to work, aptamers will need to be developed. Aptamers are oligonucleotides or peptides which stick to cell specific molecules. In research, they are often bound to pharmacological agents or cell markers.

The aptamers, whether for Kanzius' superheated nanoparticle antennas or cytotoxic chemicals, would likely need to be different for each tumor type. The means that the problem remains a discovery biology dilemma. Discovery biologists and the pharmaceutical companies for whom Kanzius seems to express considerable disdain have been working on this same problem for years. They've just been trying to selectively target their chemotherapy drugs instead of superheatable nanoparticles. Discovery efforts to generate cell specific aptamers are almost as involved and expensive as any drug discovery effort. Also, the idea of verifying that an aptamer only binds to a tumor cell is a huge undertaking. Researchers would basically need to undertake an enormous protein specificity assay. Today, proteomics efforts are still cumbersome and expensive. If researchers try to take short cuts and bypass any of these experiments, we might have doctors saying, "Oops, I fried your kidney...Sorry, didn't think it was going to do that...". More concerns involve heavy metal poisoning, nanoparticle immunoreactivity, and the pharmacodynamics of the aptamer, just to name a few.

So while Kanzius should be commended for his ingenuity in introducing a new technology to the cancer fight, Joyce Savocchio (the former mayor of Erie) probably should not be declaring him a future Nobel Laureate or calling Erie the place where cancer was cured. Perhaps he should also temper his own rhetoric a little bit, particularly when he implies that no one else is working very hard on the cancer problem. He and Ms. Savocchio sound ignorant to the real issues.

Absence Makes the Heart Grow Fonder

It has been far too long since I last posted. I have missed the Omnome project and the Science Blogging community as a whole quite a bit while I have been distracted. I realized in the first months after initiating this blog site that the diversity of discussion in the science blog community really expanded my scientific thinking.

I hope my experiences in the past few weeks that have caused me to be so absent from Omnome will have provided me some insights that will enrich my posts on a few subjects that are regularly addressed here.

So what have I been doing? First of all, to say that I have been doing anything is a gross overstatement as anything I do is as part of a massive team effort. Secondly, I am somewhat constrained by organizational confidentiality agreements so it would be unprofessional for me to say too much. However, I think I can safely tell you the following about my past month:

1) Data was finally compiled and made accessible to me from a very large gene expression profiling effort which took my group one full year to complete. The dataset is made up of about 9 million data points. Mining is fun! Spotfire software can be fun as a visualization tool of the data. However, the statistical power of the program is sorely lacking.

2) My research group used stem cells in an animal model of neurodegeneration. I am pretty sure that's all I can really say about that. However, I suspect I will interject more thoughts about the technology in future posts as a result of my experiences with these cells.

3) My research group has initiated two large scale gene therapy efforts in animal models of neurodegeneration using adenoviral vectors.

I hope I will be able to find the time to frequent Omnome a bit more again. I look forward to visiting my scienceblogs favorites again as well. However, the people who actually pay me at work will continue to have a say over that.

Tangled Bank #84!

Please stop by Tangled Bank 84 at the Voltage Gate! Omnome got a nod for our post about life, chaos, and disease.

Cows of the World Rejoice!

A Step Toward Treating Prion Pathologies?

In 1997 Dr. Stanley Prusiner of the University of California at San Fransisco was awarded the Nobel Prize in Medicine or Physiology for his discovery of prions approximately 15 years earlier. Prusiner had characterized the first infectious agents that were not somehow regulated by DNAs or RNAs.

Prions are proteinaceous infectious particles which cause diseases in myriad animals by affecting the structure and, subsequently, the function of the brain and other neural tissues. All are fatal. Prions are actually made of a protein which exists normally in healthy humans and animals called PrPc. The infectious, or PrPsc, form is different in that it is folded differently such that it cannot be broken down by proteases; the body's normal protein degrading enzymes. Not only is this aberrant form of PrP undegradable, it can actually transform the normal healthy PrP into the pathological form. It is worthwhile to note that while prion diseases can be infectious, some can be familial and directly inherited.

I like to think of the PrPsc protein as if it were an unruly elementary school student with very rich parents who have funded the new wing to the school. The bad student (PrPsc) should be expelled, but the administrators can't do it because they will lose necessary funding (proteases are unable to degrade PrPsc). As a result, the bad student is a terrible influence and converts formerly good students (PrPc) to his bad behavior. They all eventually burn down the school (Central Nervous System disease eventually resulting in death).

OK, so the analogy is crude, but you get the point, right?

A recent publication in PNAS, describes a simple but only recently possible approach to slowing this protein's infectious misbehavior. The researchers first analyzed the thermodynamic stability of PrPc. They found that the normal protein is most unstable at residues which cause a cavity in the protein. These sites of instability seem to be correlated with mutated regions of the PrP protein in inherited prion diseases.

The researchers then embarked on a "dynamics-based" drug discovery strategy. My impression of the strategy is that they utilized proteomic informatics technology to find chemical structures which might bind to and stabilize the collapsible, unstable, residues of the healthy PrPc. If that isn't what they did, I think that might be a good idea...

The researchers eventually tested a handful of compounds in cell models and in animal models of prion diseases. They settled on one compound which did seem to stabilize the endogenous PrPc and reduced the rate of PrPsc induced degeneration in infected mice.

I have much interest in neurodegenerative protein conformation diseases because I work in amyotrophic lateral sclerosis (ALS) drug discovery. I have developed a bias where I am under the impression that the main key to unlocking neurodegenerative diseases lies in understanding the truth about protein misfolding, degradation, and aggregation and as such I find this publication to be very interesting. I may carry this bias as a result of having been heavily influenced by Dr. Susan Lindquist when my research group met with her about 4 years ago.

Dr. Lindquist is a leading protein misfolding expert and sums my feelings up best in the quote below:

"What do "mad cows", people with neurodegenerative diseases, and an unusual type of inheritance in yeast have in common? They are all experiencing the consequences of misfolded proteins. ... In humans the consequences can be deadly, leading to such devastating illnesses as Alzheimer's Disease. In one case, the misfolded protein is not only deadly to the unfortunate individual in which it has appeared, but it can apparently be passed from one individual to another under special circumstances - producing infectious neurodegenerative diseases such as mad-cow disease in cattle and Creutzfeld-Jacob Disease in humans."

--from "From Mad Cows to 'Psi-chotic' Yeast: A New Paradigm in Genetics," NAS Distinguished Leaders in Science Lecture Series, 10 November 1999.

Cancer: A Mistep into Chaos Quicksand?

I spent much of this weekend pouring over two publications. The first, Probing Genetic Overlap Among Complex Human Phenotypes, was published in PNAS. Gene Expression has a nice post about the publication. While the paper itself focuses on genetic overlap between Autism, Schizophrenia, and Bi-polar Disorder, the scope of the work spans across over 150 diseases which were all compared in a pair-wise fashion. My personal interests in this work lie in their findings regarding Amytrophic Lateral Sclerosis which the authors included in their 200+ pages of supplementary materials. As I learn more about this work, I will share more about my understanding of the potential significance.


----------------------------

The second publication I spent a lot of time attempting to wrap my feeble mind around this past weekend was a fascinating conceptual "modeling" paper written by Dr. Ivo Janecka, MD, MBA, PhD (that's a lot of letters...). As I mentioned in my post about Miuro, I am very much intrigued by chaos mathematics and non-linear dynamics. It is the most ambitious of my many amateur interests.

The introduction of Janecka's publication starts with a quote by Fritjof Capra saying:

"The more we study the major problems of our time, the more we come to realize that they cannot be understood in isolation. They are systemic problems, which means they are interconnected and interdependent."

It is a sentiment which many scientists share, but is very easy to lose site of when we attempt to make our research efforts more manageable. We try to linearize our experiments. We pretend that we can study individual variables. We forget that we are usually attempting to solve complex problems rather than answer simple binary questions. In the twenty-first century, living systems and their "problems" are proving to be more complex than any systems humans have ever tried to understand.

When I decided to pursue a career in life sciences, it was because I could not imagine that any other field of study could offer systems as beautiful and mysterious as life. I also could not imagine a field that could offer so much promise to help fellow humans once some of the mysteries were unlocked.

In this publication, Janecka offers a conceptual model for life systems. He describes life as a "non-linear dynamical system following the principles of organized complexity" with a "health territory" defined by the the systems ability to self-organize and self-adapt.

OK, so what does that mean? Let's take it one part at a time.


What is a non-linear dynamical system?

This is a system where small changes to early conditions can directly result in hugely different results at some later time. Many people have heard of the concept of a butterfly fluttering its wings on the North American west coast resulting in dramatic changes to huge tropical weather system on the east coast. Weather patterns are good examples of non-linear dynamical systems.


What is self-organization?

A system that self-organizes is one that will find a way to go back to "normal" after it has been disrupted. Imagine a beehive that is completely buzzing with activity. Now, imagine throwing a very small pebble at that beehive and disrupting the activity of the bees. For a few moments, the bees buzz away and circle the hive, only to go right back to the hive. The hive then appears almost exactly as it had before it had been disrupted. The system always approaches an organized baseline of activity.

Life, specifically human life, is very much the same. Our bodies work to self-organize. When we suffer lacerations, bleeding stops and the lesion closes/heals. This propensity to self-organize is catagorized by Janecka into a "zone of order".


What is self-adaptation?

Self-adaptation can be described as a systems flexibility to change based on information received from outside to the system. If you have ever attempted to play the guitar, you will know that it hurts at first. Fingertips become raw. Forearms become very sore. Over time, the muscles in the hand and forearm become much stronger and the fingertips become calloused and less sensitive to pain. The system is self-adapting to the information conveyed from the environment. If we could not adapt the environment around us and we didn't have flexibility to express a variety of phenotypes, our species could not survive. This flexibility is catagorized by Janecka within the "inner edge of chaos".

If life is a self-organizing and self-adapting system, then, Janecka reasons, it can be described as a pendulum swinging back and forth through the "zone of order" and the "inner edge of chaos".

When life swings too far into the "zone of order", it is at the expense of adaptability. This can result in detrimental rigidity as in the case of ECG cardiac signalling. Lack of chaotic fluctuations in cardiac electical signalling invariably indicates cardiac disease because of its lack of adaptability to variable conditions of stress and strain. Imagine if your heart couldn't beat faster when you needed to run. You wouldn't be able to get oxygen to your blood and muscles fast enough. It would be detrimental to you as a "living system".

Likewise, when life swings too far past the "inner edge of chaos", the system loses its ability to self organize. This can be observed in cases of cancer where a subsystem of cells within the complete living system loses the ability to regulate expenditure of resources. In cancer, most cellular resources are allocated to reproduction instead of differentiation and functionality. The cancer cells replicate in exponential self-similar chaos fractal patterns like the common Mandelbrot geometic patterns of Merkel cell carcinomas.

Janecka suggests that many untreatable human diseases can be catagorized as pendulum swinging too far in either direction of the self-organizing/self-adapting systems. A swing in either direction plunges the living system into a stage of accelerating entropy ontil the system completely unravels at death. He goes on to suggest that scientists and clinicians could use the model to evaluate what needs to happen to a diseased patient to best bring them back to their healthy balance of order and chaos. In the case of cancer, Janecka proposes that efforts be made to re-educate the cancer cells to move back toward efficient energy consumption. Teach the cancer cells to differentiate again instead of reproduce. Re-balance the system.

The concept is fascinating and I look forward to following up on researcher who reference this publication.

The Tangled Bank #83

The 83rd Tangled Bank has been posted at Aardvarchaeology. Omnome's Parkinson's gene therapy post was included in the carnival.

Good Deeds

Dr. Ryan Gregory at Genomicron has posted about his father's mission to make a difference in Africa. Please take a moment to visit his site and pass along news about the effort.

Scientists Stressed About Weight Loss

Do researchers really think neuropeptide Y can sculpt the perfect body?


Every few years, researchers challenge Jenny Craig's and the late Dr. Atkins' stranglehold on the weight loss industry. (Honestly, I don't know what they are thinking. I wouldn't take Kirstie Alley on.)

I remember back around 2001 when a biotech company, Regeneron, was developing a drug trademarked as Axokine (it was actually ciliary neurotrophic factor, or CNTF) in hopes of manipulating the leptin "hunger" pathway. At the time, it was suggested that both leptin and Axokine worked in large part by inhibiting the activity of neuropeptide Y in neurons. Neuropeptide Y (NPY) was reputed to increase appetite in small animals when small doses were delivered directly to their brains. Additionally, when NPY receptor positive neurons are selectively destroyed, experimental animals eat much less. Regeneron generated data that showed that CNTF, like leptin, suppressed activity of NPY receptor positive neurons in the hypothalamus. Unfortunately for Regeneron and its stockholders in March of 2003, Phase III clinical trial results for Axokine indicated that the weight loss in the treatment group was a marginal 6.2 lbs loss. Additionally, a subset of Axokine treated patients developed antibodies to the drug which neutralized its effects. While leptin and NPY were still obvious players in appetite and weight gain/loss, it had become clear that manipulating the pathway would not be a trivial effort.

Now 4 years later, leptin and NPY are back in the news because of work published in Nature Medicine by researchers at Georgetown University Medical Center. As usual, the media has produced article titles like "Scientists Find Way to Block Weight Gain in Stressed People". (I often hate the news media, particularly FOXNews). These titles imply that overworked fat people will be able to take a pill that makes them lose weight within the next year. While there are a couple of clinical trials tied to the freshly reported research, we're going to have to wait for a little while before knowing how it will all play out. Not all of the current reports are promising. Well, let me put it this way, the research that is currently making news is right about where Regeneron was with Axokine circa 2000; and we all know how far that got.

With silly media coverage aside, the research conclusions by scientists at Georgetown University Medical Center are very interesting. It seems that NPY does not only work via appetite mediation in the brain signaling pathway. Rather, their data in mice suggest that when animals become stressed by aggression or temperature changes, their sympathetic nerves generate more NPY and NPY receptors in abdominal fat. This upregulation is concurrent with increased growth of new fat cells and in fat tissue angiogenesis . Fat tissue, just like any other tissue, needs blood supply to grow and sustain itself. The researchers backed up their conclusions further by suppressing the abdominal fat growth in stressed animals using a NPY blocker injected directly into the abdominal fat of stressed animals.

Aside from having discovered a potential way of reducing fat in the abdomen, there are other implications to this research:

1. Could anti-anxiety medications reduce this stress signaling pathway that causes weight gain?
2. Could NPY be injected to increase fat where desired? More natural looking breast implants?
3. Can increasing peripheral (outside of the brain) levels of NPY increase appetite while decreasing weight?


Major questions still remain, however. First and foremost, do human really work the same way as rodents in this case. Secondly, would this be a safe therapeutics. And, thirdly, most obviously to me, why do most of the stressed out people who I know appear emaciated. Personally, I lose weight when I get stressed. My guess is that, as usual, the physiology and molecular biology of this is far more nuanced than the current story allows. Time will tell.

Doing the Robot to a Chaotic Beat

Omnome is dedicated to talking about three broad subjects and how they intersect at the point of human application; technology. The subjects are:

• Biology
  
• Physics
• Mathematics

So far, we have talked a LOT about biology, a little about physics, and not at all about math. Honestly, it bothers me that I haven't written about math at all. Mathematics is what ties all of this together. Mathematics, by one definition, is the study of quantity, structure, space, and change. That covers a great deal since most scientific study can catagorized as the study of quantity, structure, space, and change.

In any case, I am going to introduce math to Omnome by talking about a little Japanese robot named Miuro that has a few functions. First and foremost, Miuro is a music player that can play music from an iPod or from a WiFi connection. Secondly, though, Miuro can dance. Ok, so I have watched the video, and I find Miuro's dancing to be rather lame and nondescript. It basically rolls around with a few shimmies to the beat of the music it is playing. See the video below:



Like I said, kind of lame and non-descript, right? However, the interesting thing about Miuro is that it doesn't actually have pre-programmed dance patterns. I remember very distinctly the first time I found myself almost uncontrollably tapping my feet as a young child listening to a song that came on the radio in the car. I had never learned any dance moves, yet my brain picked up a pattern in a song that made me decide to tap my feet in time with one of the song's cadences. Miuro is designed to do the same thing.

Miuro has software rooted in mathematic chaos theory that allows it to decide how to react to the music. So what is chaos theory and how would it allow a robot to "decide" anything? The study of chaos in mathematics is the study of systems with more than one changing variable that seems random, but is very much dependent on the initial conditions. Weather patterns are chaotic systems as are Earth's magnetic fields and human economies. Basically, any system that can change exponentially as a result of numerous variables in time can be considered a chaotic system. Most things still to be discovered in most fields of study will somehow be tied to these very complex systems.

So Miuro is a robot that has software that is designed to change its movement unpredicably based on: 1) The motion it is already carrying out and 2) the many musical tracks recorded in a given song 3) Where it is dancing. Any of these many variables will make Miuro decide how it wants to bust a move. Most artifical intelligence (AI) researchers believe that AI break-throughs will be ushered in via harnessing of chaotic decision making models somewhat like the Miuro model.

So this is a humble introduction to the world of Chaos Mathematics and/or Non-linear Dynamics. These are subjects of much interest to me. Unfortunately, I know very little about them right now. I am a sub-amateur student of them. I hope to change that over the coming years. I hope you, my readers, can teach me a little bit about the subjects. I hope to broach the subjects with regards to genetics, proteomics, physics, weather, disease epidemiology, and much more in the future.

Gene Swap Meet

Sorry it has been so long since our last post.

This has been a very crazy week for me that I can most aptly describe with a quote from Dr. Peter Venkman in Ghostbusters when he described "...human sacrifice, dogs and cats living together - mass hysteria!"

Anyways, I am glad the week is over. We hope to get back to more regular posting again.

While I am admittedly tired of talking about genetics here, I am going to address the subject at least 3 more times in the near future. We have two more posts to go in our State of the Art series and we have the post that I am about to write.

Currently in the news, we are hearing about steps closer to "artificial life". The idea of artificial life is an odd one to me since life can largely be catagorized as a binary state, alive or not alive. It seems difficult to me to be artificially alive. Oh, I know many of you will want to nitpick about grey areas like viruses and such, but that's a completely different question. My bottom line is that life is real or not alive. There will never be artificial life. Ah, the wonders of semantics.

So what am I talking about here? What is the big news? Researchers at the J. Craig Venter Institute in Maryland have published a paper in Science explaining how they transfered an entire genome from one species of bacteria (Mycoplasma mycoides) into a population of a completely different species of bacteria (Mycoplasma capricolum). On the surface, this might seem unremarkable since Dolly the sheep was cloned back in 1996 by transferring the entire genetic code of one sheep into a sheep egg cell. However, up until now, no cells of one species have been made to "engraft" an entirely transplanted genome of another species.

While the idea that this will lead to "artificial life" is somewhat absurd since the concept doesn't really exist, this is exciting because it could be a first step toward creating novel organisms specifically designed for a human need. Imagine a bacteria that could be designed to metabolize sugar and produce propane for fuel. While I am not sure that is an attainable endeavor, Venter seems to think it is. I imagine, to him, this publication is one more step in the right direction. Not sure it is the right direction, but it is definately a step toward his goals.

Speaking of AAV, Parkinson's Gene Therapy progress?

Considering that we've been talking about gene therapy a lot here lately, I think this news is quite relevant. Current Omnome topics aside, this news is very important.

There have been recent reports about a gene therapy strategy that resulted in symptom amelioration in Parkinson's patients. The project was spearheaded in part by Dr. Matthew During of Ohio State University. Having met Dr. During at the Society for Neuroscience conference in Orlando in 2002, I am not at all surprised that he would be part of a project that could stand at the cutting edge of clinical translational research. As a trained neurosurgeon with a PhD, this New Zealander came across as not only talented, but also as having major cojones.

So let's talk about the therapeutic that was tested by During and his colleagues. The researchers used an adeno-associated virus (AAV) to deliver a gene encoding the protein, glutamic acid decarboxylase (GAD), to the subthalamic nucleus in the brains of Parkinson's patients.

So what does that all mean? Well, let's briefly review AAV. AAV are small viruses that do not induce an immune response in humans. Additionally, they deliver DNA genetic material which directly incorporates into the cellular genome. It gets copied when transduced cells divide into daughter cells. Now we'll talk about Parkinson's Disease. Parkinson's is a complicated disease which results in neuronal death, neurodegeneration. Specific parts of the brain are very susceptible to this neurodegeneration. The substantia nigra of the brain is one of those parts. As a result the neurotransmitter balance is thrown off to the point where the substantia nigra is too "excited". The aim of a GAD gene therapy is to turn part of the substantia nigra from a primarily excitatory nucleus to a primarily inhibitory system.

Whether or not the gene therapy is working the way the researchers think it does is always up for debate. What isn't as debatable is the fact that most of the patients who received the injection of GAD encoding virus had symptomatic improvements. Since this was mainly a dose ranging and safety Phase I/II clinical trial, the number of patients was not high enough to power a statistically significant symptom amelioration metric. However, all signs point toward some hope for improved quality of life for Parkinson's patients. What this also provides is another glimmer of hope that gene therapy strategies might be in the clinic sooner than later. What this certainly is NOT is a cure. Patients need to remember that the neurons are still dying. Neurodegeneration is an extremely tough nut to crack (trust me on this one...I'm in neurodegeneration research for the long haul). Maybe one day we'll come up with a gene therapy that can protect the neurons...

State of the Art: GENE THERAPY- Pt2

See part 1

Viral Delivery

Most gene therapy strategies in research and clinical labs up until now have revolved around harnessing the evolved capabilities of viruses to deliver their viral genomes into cells. This is commonly known as use of a viral vector.

Let’s talk a little bit about viruses. Viruses are particles which can infect cells of living organisms. Viruses are made up of a protein shell encasing viral genetic material. In order to reproduce, viruses attach via their protein shells to cell surface membranes where they inject their genetic material. For normal disease causing viruses, the viral genetic material hijacks the cell’s protein and nucleotide generating machinery to produce more complete virus particles. The cycle continues until the immune system can seek and destroy the viral particles (unless the immune system is the target of the virus; as in the case of HIV). The process by which viruses deliver their viral genomes into cells is referred to as viral transduction.

In order to use a virus as a delivery vector, the viral genetic material basically needs to be removed and replaced with genetic material encoding the desired cellular product.

Retroviruses

There are a few different kinds of viruses which can be used for gene transduction. Retroviruses are one kind. Retroviruses store their genetic material in the form of RNA. When a retrovirus infects or transduces a cell, it introduces ins RNA and a few additional enzymes to the cell. The RNA is then copied to DNA inside the cell my an enzyme called reverse transcriptase. The new DNA is then inserted into the cell’s own genome by the integrase enzyme. The viral DNA is now a part of the host cell’s DNA. If the host cell divides, then any daughter cells will share the new DNA. The great thing about that from a gene therapy standpoint is the fact that there would be little or no need to introduce the therapeutic gene more than once. The downsides to it, however, are that:

1) The viral DNA can be incorporated into portions of the cell genome that result in faulty transcription of important genes. This could lead to cancer conditions caused by the gene therapy in the same way that human papillomavirus (HPV) predosiposes women for cervical cancer.

2) If the virus inserts itself into the wrong cell type, the genetic material could be passed on indefinitely within unintended cells for unintended results.

Adenoviruses

Adenoviruses are very different from retroviruses in that the genomic material which adenoviruses use to hijack a cell starts as DNA. Additionally, the DNA does not incorporate itself in the host cell’s genome. The viral DNA finds its way into the host cell’s nucleus where it is transcribed to RNA in the same way all nuclear DNA is transcribed. However, since the viral genes are not incorporated into the cell’s genome, the gene will not be duplicated and passed on to daughter cells after cell division. In one sense, this is advantageous from a gene therapists standpoint. It means that the gene product will only be produced as long as the transduced cells are alive. Long term side effects are minimal. The downside of this approach, however, is the fact that the virus would likely need to be administered more than once.

Adeno-Associated Viruses

Adeno-associated viruses (AAV) are like adenoviruses in that they carry DNA. They are like retroviruses in that the viral genomic material that they carry will be incorporated into the host cell’s genome. Daughter cells will carry the gene, but the genes will not incorporate by integrase into a random portion of the host genome. Instead, AAV always incorporates into chromosome 19. One of the biggest advantages of the AAV, however, has nothing to do with its transduction approach. AAV does not induce an immune response in humans so it can pass through the body as a vector without risk of being destroyed by T cells or macrophages. AAV will not cause fevers or inflammation when administered.

The major downside to AAV is the fact that the viral particles are very small and cannot hold very much genetic material. They would be limited in what gene products they could code for.

So now you know the three types of viruses used for gene therapies. You also know their basic advantages and disadvantages. The next installment in this series will talk about non viral gene delivery techniques. After that, we will summarize the potentially therapeutic gene products being tested in contemporary research labs. We hope you are enjoying the content so far.

State of the Art: GENE THERAPY- Pt 1

What is Gene Therapy?

Gene therapy is the term used for a biological treatment that is designed to introduce new active genetic material to living cells in order to increase or reduce a genetic product or products. These products can include either RNA or proteins or both. For the crudest of analogies, imagine the cell is a factory. This factory has assembly lines that currently build blenders. The blenders are great, but you also want to make toasters now. You send instructions to the factory to reconfigure some of its assembly lines to make toasters for at least part of the time. That is basically what is happening in gene therapy.

The most easily related example that I can think of where this technology could be useful is in Type I diabetes mellitus, where there is a deficiency in production of the protein, insulin, which is encoded by DNA on chromosome 11 in humans. An easy illustration of how a gene therapy could work would be to say that the gene for insulin production could be introduced to cells of a Type 1 diabetes patient so that their body would then be capable of generating insulin on their own. They would no longer need to take insulin shots to control high levels of blood sugar. I will stop there and now posit the emphatic caveat that the case of Type 1 diabetes is much more complex than I just described. The lack of insulin production is not because a gene is missing, rather it is because the cells that normally produce insulin are missing. In fact, diabetes might be better treated with a stem cell therapy than a gene therapy; but I digress (a topic for another State of the Art series). The main point of this ambling monologue is that, by using gene therapy, a new gene or genes can be introduced so that a cell can generate a product that it wasn’t previously generating in order to achieve a variety of net effects.

In the United States, there are currently as many as 30 clinical trials active or enrolling to test the safety and efficacy of myriad gene therapy, or gene transfer, strategies. The trials hope to find treatments for conditions ranging from X-linked Chronic Granulomatous Disease (CGD) where patients’ neutrophils cannot make a key protein necessary for infection defense to Advanced Pancreatic Cancer where a researchers are trying to test safety and dose response of delivering a “tumor killing” gene.

While there are dozens of gene therapy clinical trials and hundreds of labs worldwide conducting research with gene therapy technologies, there is still no FDA approved gene therapy product on the market; nearly 17 years after the first human gene therapy trial was conducted on a 4 year old girl with severe combined immunodeficiency (SCID) at the U.S. National Institutes of Health in 1990.

Why are gene transfers so challenging to develop and administer? There are many pitfalls. First of all, it is simply difficult to incorporate new genes into living cells, especially in a multicellular tissue system. Secondly, once the gene is there, it doesn’t always produce an active protein (or RNA). Thirdly, if the gene does work, it is very difficult, if not impossible, to turn it off, thereby rendering overdoses and immune reactions virtually impossible to treat. Forthly, it is difficult to target genes to show up in the correct cells while not also affecting cells that don’t need the gene. Lastly, there are some questions about potential to pass on the therapeutic gene to offspring who won’t need it.

These issues are currently being addressed with variable success in research around the world. They are testing many different genes and gene deliver strategies in hopes of harnessing biology’s machinery to treat diseases. In the next installments of State of the Art: GENE THERAPY, we will talk about specifics of where the technology is right now. For now, chew on this one. Think of questions. Tell me I am an idiot. Thanks for reading. :)

Upcoming Posts!

State of the Art: GENE THERAPY- Pt2
Viral Delivery

State of the Art: GENE THERAPY- Pt3
Non-Viral Delivery

OMNOME in the Tangled Bank

Please take a moment to visit the 82nd installment of the weekly science blog carnival, Tangled Bank hosted at gregladen.com. It seems that each week, a different member of the science blog community writes a themed post while addressing and linking to recent pertinent posts from the science blog community. We've been informed that this week omnome.com's post about the ENCODE publication in Nature was included.

Greg Laden's post is very informative and entertaining. Take a look!

Welcome to OMNOME!

Welcome to www.omnome.com and thank you for reading. If you have already been frequenting our site, you’ve probably got some idea of what we’ll be talking about here.

We picked the name, OMNOME, because we wanted this project to broadly address, with varied levels of depth, the study of all sciences. Most of our topics will fall under three main categories: 1) Biology, 2) Physics, and 3) Mathematics. We understand that we can't be experts across such a diverse array of subjects, but we hope we can talk about what we know and learn accurately and articulately.

Most articles will stand alone, but we will also regularly publish segments in a “State of the Art” series which will describe where general classes of technologies such as nanoparticles, gene therapies, stem cells, and fiber optics currently stand.

Finally, you might be wondering about the “sheep” theme of the site. We picked it as a homage to Dolly, the cute clone sheep. Dolly’s arrival in 1996 ushered in a maelstrom of news coverage which told us that Dolly would either cure diseases or lead humanity into an ethical crisis. Neither of those scenarios proved to be immediately true while potential still exists for both to become true in time. Much science coverage today follows the same model of conveying hope and fear simultaneously. We hope that we can cut through a little bit of the hyperbole in the coverage and help you get a clearer picture of what is going on in the research labs of the world.

EARTH II: How to Find Earth-like Planets

There has been a lot of press lately about the discoveries of many “Earth-like” planets outside of our solar system orbiting other stars, otherwise known as terrestrial exo-planets. When I read press releases about these things, I picture exotic worlds filled with oddly colored vegetation, some animal like creatures, and maybe skinny humanoid biped extraterrestrials

with some intelligence and language. I also wonder how long before humans can colonize.

Then I remember that I am probably getting way ahead of myself and I start asking annoying questions like:

• What is the definition of an “Earth-like” exo-planet?
• What technologies are scientists using to discover exo-planets?
• What technologies are scientists using to discover the nature of these planets?

What do scientists mean when they call a planet “Earth-like”?

Historically, an Earth-like, or terrestrial, planet has been characterized as a rocky planet like Earth or Mars, as opposed to a gas giant like Jupiter. However, recent news articles seem to be adding an additional element to the vernacular connotation of “Earth-like”; they seem to be talking about rocky planets that are the same distance from their star as we are from our sun. The basic implication here is that scientists are trying to find environs that might be adequate or ideal to support life; like the our home planet Earth.

The most interesting thing to note about the definition of “Earth-like”planet is that it is a very broad definition. A planet exactly like Mars in another solar system would easily fall under the definition. As we all know, Mars is hardly lush with tropical rainforests.

What technologies are scientists using to discover exo-planets?

Right now, scientists can’t see these planets directly through conventional light telescopes, not even with the amazing Hubble Space Telescope without first knowing exactly where to look. This is because the planets are not bright or big enough relative to their cosmic surroundings to stand out. In the same way that ambient city lights make it difficult for us to distinguish stars in the night sky, bright stars make it very difficult for us to distinguish nearby planets in the night sky even with high powered telescopes. Because of this, scientists need to be creative when discovering distant non-star celestial bodies.

Most exo-planet discovery has been accomplished with a technique called gravitational microlensing. Gravitational microlensing harnesses one of clever Albert Einstein’s equations predicting the nature of light and gravity. Einstein predicted that light observed from a distant source, like a bright star, would bend whenever a massive object passes near the light beams between the source and observer. Not surprisingly, Einstein was right and scientists can use these light bends to determine when planets are passing between stars and us. Depending on how big the star is, scientists can use the degree of light bending to determine how big an orbiting planet is.

What technologies are scientists using to discover the nature of exo-planets?

Basically, gravitational microlensing can indicate the presence of a planet and a little bit about its mass. Once we know where a planet is, we can point high powered telescopes at it in order to catch a glimmer of its reflected light. Once we can observe the reflected light, we can learn more about a planet’s orbit using another indirect observation technique called radial velocity analysis.

To explain radial velocity analysis, we will talk a little bit about the nature of light. Light travels in waves with specific wavelengths for each color of light. Longer wavelengths look redder and shorter wavelengths look bluer. Another one of Einstein’s clever insights was that if a light source, in this case a planet, was moving toward you, its light wavelength would shorten and look then look bluer. When it is moving away, it will look redder. Because of this we can determine the distance and duration of a planet’s orbit. This is how, besides knowing a planet’s size, scientists can determine how far it is from parent star.

When will we know more?

In general, all we can really know about the exo-planets right now are the following characteristics:

1. That the planet is there.
2. How big it is
3. How close it is to its sun
4. How fast it moves

Because of those facts, we can guess what the planet is made of and how hot or cold it is.

We will know much more within the next decade when NASA launches its Terrestrial Planet Finder project into space and when ESA launches its DARWIN project. These two projects will take the technologies which we described above and lunch them into outer space to get a closer, less noisy, view of what is out there. Eventually we will be able to use color spectrometry to determine which elements and molecules constitute the planets’ masses. We will see if there is oxygen, methane, water, etc…all clues that would indicate possibilities of life elsewhere in the galaxy.

We have a ways to go, but maybe someday will finding ourselves looking at someone who is looking back at us. Well, because of the speed of light it would mean they were looking at us about 30 years ago and we are just seeing them now.

What did ENCODE decode?

As recently as five days ago, I penned a post about what the Human Genome Project (HGP) had and had not accomplished. I wish I could say that I had written that with the full knowledge that it would be a great primer for a piece about the genome discoveries released today by ENCODE , the NIH follow-up effort to the HGP. I would be lying if I did.

Anyways, front and center at Nature.com is a pdf of the publication by the Encode Consortium outlining the highlights of their efforts to pass a fine toothed comb through approximately 1% of the human genome.

The publication is fascinating in both its breadth and detail. Before I expound on its virtues, let me first comment on my only suspicion about the project. From my own somewhat limited experience in biomedical research, I am not a big fan of large consortium efforts. While I love the concept of open source sharing of data and collaboration, I have usually found that huge efforts across many labs breed data inconsistencies as a result of methodological and analytical differences. Differences in variables as small as humidity in the lab can yield differences in datasets that can obscure the real story. All of that said, it would be very hard to argue with the key points that are coming out of this publication, because the key points make a lot more sense than the conventional wisdom that has been coming out of college biology text books for years (at least when I was in college).

Most of us have been taught at some point that DNA leads to RNA which leads to protein. Well, all of that is still true, but as time goes on, we continue to discover that there are more and more options for the RNA besides producing protein. Without further ado, here are the take home notes on the ENCODE project:

• While it was once thought that a large proportion of DNA was "junk" which did nothing, it is becoming clearer that the vast marority of DNA does transcribe RNA. Many new non-protein coding RNA's have been discovered in the ENCODE effort.
• Chromatin accessibility, basically how tightly the DNA is wound, has a huge effect on how readily it is transcribed to RNA. In turn, many RNA's can affect how tightly the DNA is wound.
• We have evolved in a way that has rendered about 5% of our DNA inactive.
• Some regions of our DNA are wildly variable from person to person, while other regions barely change (this isn't really news, but they've been able to pinpoint some of the specific variable regions).
• RNA can do many things beside encode for protein. Some RNA's are used by the cell to suppress other RNA's...thereby regulating the genome. (this isn't really news either).
  
• There is way too much RNA in cells for us to know what all of it does at this point in time

I do hope you take a look at the pdf file for the original article that I linked to up above. Science journals are tedious to read, especially if it is a new world for you, but it is worth tackling every now and then. There are usually pretty pictures.

AVIAN FLU- Will it ever take off?

A while back, there was a huge media scare about the avian flu. Media fear mongering alternately amuses and irritates me. The media often fills news gaps with whatever they can come up with that might terrify the populace and incite us to improve their ratings and sales. Perhaps one day we can write an article about the psychology behind scare tactics in media programming. Today, however, I am going to talk about the avian flu and the flu in general.

How much do each of us really know about the flu? Before I started my formal medical education, I could barely tell the difference between having the flu and having a bad cold myself. They are both viruses. Both result in the symptoms which can include sore throats, coughing, achiness, and headaches.

So what are the differences? Well, first of all, cold’s are caused by rhinoviruses. As the name implies, rhinoviruses cause symptoms in the nose. That snotty, nasal congestive hell that we all go through at least once yearly can be blamed on the common cold. Generally speaking, the common cold stays in the upper respiratory tract. The flu, or influenza as it is more formally known, is caused by the orthomyxoviridae family of viruses. While some of its symptoms are shared with the common cold, it is noted for knocking us completely out of commission for a day or two. All we can do is just lay in bed and whine to our significant others. In the worst cases, the flu can cause pneumonia. For those of you who have never experienced this fun condition, it’s a lot like drowning in your own mucous. It can be fatal, especially in very young or very old patients. Not fun.

So now that we know what your everyday garden variety flu can do, what was the deal with the avian flu that was terrorizing the world right up until the media forgot to talk about it? Well, there are a few different kinds of influenzas. Humans are most affected by Influenzavirus A, Influenzavirus B, and Influenzavirus C. Within those families, we are most affected by Influenzavirus A. Now make sure you are sitting down for this next part…All viruses in the Influenzavirus A family are kinds of avian flu viruses that have adapted to infect humans! So what I am saying is that you’ve probably been infected by and survived the avian flu! Congratulations!

That’s right, most flu viruses that infect humans are originally avian viruses. Then why the big deal about this new avian flu? Well, it seems that this particular strain, the H5N1 strain, of avian flu is quite deadly when contracted by humans. Fortunately for our species thus far, though we can contract the virus directly from birds, we cannot pass the virus on to other humans.

As CNN, FoxNews, and Katie Couric have all informed us many times, many leading epidemiologists believe that it will only be a matter of time before the H5N1 strain mutates into a form by which humans can infect each other directly. Mass hysteria will follow. Everyone will dress up in football pads and have Mohawks like they did in the post apocalyptic world of Mad Max. It’ll be great. Really.

Just kidding. We won’t be wearing football pads.

The reality is that we don’t know when or if this strain of bird flu will ever undergo the mutation of its protein shell necessary to cause a human pandemic. While our governments should take precautions in case something does occur, there isn’t a whole lot any of us can do as individuals about it right now unless we want to volunteer for vaccine clinical trials (this would probably involve being injected with a watered down form of the avian flu) or become research scientists devoting our lives to studying influenza viruses. Yeah, I don't want to either. Basically, don’t stress about this. Enjoy your daily lives until you hear Katie Couric tell you that the virus has finally mutated. She’ll be right on it. I promise.

Then stay as far away from public transportation and airports as you can possibly get.

CERN's LARGE HADRON COLLIDER- A Big Hit?

You may have recently read in the newspaper or seen television news reports about a brand new particle accelerator in Europe that could provide new information to physicists that might allow for them to settle upon a “Theory of Everything”.

What could anyone possibly mean when they say “Theory of Everything”?

In day to day life, the word theory usually implies conjecture. It is typically a proposed explanation for an unsolved mystery. In science, however, a theory is a mathematic or logical explanation that can be used to reliably predict the outcomes of similar future occurrences. For example, the Theory of Gravity allows us to predict that an apple will fall to the earth. It also tells us that a satellite, if it is traveling fast enough, will orbit the earth. I suppose the apple, if it traveled fast enough, could also orbit the earth; but I digress.

So if theories are supposed to predict similar future occurrences, does it follow that a “Theory of Everything” should predict, well, everything? Sort of.

What physicists aspire to attain in a “Theory of Everything”, or unified theory, is a theory that can account for the force gravity into the mostly reconciled theories of quantum mechanics (really small subatomic stuff) and special relativity (E=mc^2).

Would a unified theory help you predict how your boss will react to your hangover tomorrow? Probably not. In that sense, it isn’t a theory of everything. However, it would make it possible to understand a least a bit more about how our universe began and where we fit into it. On a more practical level, in the same way Einstein’s theories led to nuclear power and space travel, mankind will likely experience similar benefits (and possibly detriments) as a result of any unified theory discovery.

Many possible unified theories have been proposed, the most popular of which are the many variations of String Theory. Unfortunately, much to the consternation of many physicists and other curious observers, up until now the theories have been mostly untestable. That brings us to why that particle accelerator/collider in Europe has been in the news so much.

Brought to you by the inventors of the internet, CERN (The European Organization for Nuclear Research) presents the Large Hadron Collider (LHC)!

What are Hadrons and why will colliding them help lead to a “Theory of Everything”?

In 1995, the CERN Council approved the construction of the world’s largest subatomic particle accelerator and collider to be funded by CERN’s 20 member states. The multibillion euro (or dollar) effort has resulted in a collider housed in a 17 mile circumference tunnel crossing the French/Swiss border twice that sits as far as 450 feet underground.

Simply put, the tunnel contains two pipes that are designed to shoot beams of tiny subatomic particles, broadly referred to as hadrons, but mainly in this case the more commonly known protons, directly at each other in order to observe their interactions before, during, and after moment when the beams collide.

What type of information could come out of proton collisions? Well, it can be explained in a small way by addressing the now universally known equation: E =mc^2. That is to say that Energy = mass * the speed of light squared. By accelerating hadrons at each other to speeds approaching the speed of light, the hadrons will acquire very very high energy levels. The energy released during the particle collision will theoretically generate subatomic particles of masses never before observed by humans. These theoretical particles, often referred to as Higg’s Bosons (alias: God Particle), and their properties are expected to fill gaps in current theories. Physicists hope that the gravity force will finally fit into current understandings of quantum mechanics and relativity.

Looking Back in Time

Many scientists believe that the high energy proton collisions generated by the LHC will replay the moments immediately after the “Big Bang” inception of the universe. Some have gone so far as to call the LHC a time machine. Personally, I think that is a pretty lame comparison. The LHC will no more carry as back in time to the Big Bang than a Battle of Gettysburg reenactment takes us back in time to the Civil War. I think the metaphor preys on the sensibilities of us sci-fi geeks who dream of flux capacitors and warp drives. However, what is important to note is that it is possible that the only way for us to understand the underlying nature of the present state of the universe might be for us to understand its nature at its beginnings.

When Will We Know?

Just last month in May of 2007, press releases told us that the accelerator was virtually completed and that the first experiments to unlock the secrets of the universe would be conducted during the summer of 2007. As recently as last week, however, CERN announced that the experiments would be put off until 2008 because a confluence of minor problems across much of the new equipment.

Some doomsday alarmists don’t mind the delay. Some believe that the LHC at CERN will generate a black hole or some other “un”natural manifestation which will destroy the world or maybe even the universe. While the concept would be great for a Dan Brown book about a lone scientist trying to avert global/universal destruction, most of us can choose to rest easy. Experiences with other colliders in the past seem to indicate that any problems with the experiments can be contained neatly below ground.

HUMAN GENOME PROJECT- Where is it now?

The human genome is the genome of Homo sapiens, which is composed of 24 distinct chromosomes (22 autosomal + X + Y) with a total of approximately 3 billion DNA base pairs. -Wikipedia

Let me start by acknowledging that the international public Human Genome Project (HGP) and the private Celera Genomics enterprise achieved a monumental task in sequencing the human genome in 2001. News media outlets trumpeted the accomplishment with verbal steamers and confetti, calling it, among other superlatives, “the Rosetta Stone of Life.” Press releases and magazine features foretold of new disease diagnostics, treatments, and even cures which would emerge from having “decoded” the blueprint for human life while warning about the ethical fallout that could emerge from DNA manipulation.

What They Forgot to Mention

The media outlets were mostly right. They, along with the scientists and the public relations professionals involved with the projects, told us that the sequencing of the human genome was the first step toward understanding and treating many human diseases. What they didn’t tell us was how many additional steps would still need climbing before we would reap those rewards. It seems that what the project yielded was far less “Rosetta Stone” and far more akin to the discovery of a tomb filled with unintelligible Egyptian hieroglyphs.

Many articles describing the HGP erroneously use the words “sequenced” and “decoded” interchangeably. In fact, Wikipedia describes the HGP as “a project to decode (i.e. sequence) more than three billion nucleotides contained in a haploid reference human genome and to identify all the genes presented in it.” The fact is, “decode” and “sequence” are quite different.

What Did the Human Genome Project Accomplish?

If by sequencing the human genome, the HGP and Celera didn’t actually decode it, then what exactly did they accomplish? To explain, we must first take a cursory look at the ingredients that make up the genome, deoxyribonucleic acid (DNA). DNA basically is made of chains of molecules called nucleotides. There are four different nucleotides which make up DNA. These are cytosine (C), thymine (T), adenine (A), and guanine (G). The HGP and Celera looked at the complete genome of one man and cataloged each of his 3 billion plus nucleotides. Basically, the hullabaloo in 2001 was simply the media fanfare that accompanied the inking of the correct order of a single human’s C’s, T’s, G’s, and A’s.

How will this correctly ordered catalog of letters eventually result in disease diagnostics and treatments? It will be a long and winding path along which the science community has only taken a few short steps. After having laid out the map of one man’s genome, researchers are now laying out the genomic maps of many others. In order to learn what each of the 30,000 genes does, researchers must compare the genomes of many humans, determine which nucleotides are ordered differently and how those differences in nucleotides translate into differences in how we each look, behave, grow, age, develop diseases, fight off diseases, and so forth. Objectively speaking, the cataloging of that first genome is no more valuable than any of the genomic catalogs which have followed; or will follow. The mapping of the first genome was a huge milestone, but any one of us could currently have our entire genomes mapped in the exact same way for a cost of approximately $200,000. The information obtained from your genome would have the same research value as the information gleaned from the entire multibillion dollar international effort of the HGP and Celera less than a decade ago.

Where will the Human Genome Project take us?

Research projects, like the international HapMap Project, are currently cataloging and comparing the genomes of humans across relatively tight clusters of human populations. We are learning what the predominant differences in the genetic codes of four distinct populations of African, Asian, and European ancestry. With each of the populations representing variable risk factors for specific diseases and conditions, these comparisons could provide indications of which genes can lead to diseases or protect against diseases (this effort is a minefield of unresolved ethics issues…a topic for another post).

Efforts to take advantage of the ability to map each of our genomes are further confounded by the fact that our genetic codes represent only a small portion of the complexities of our molecular biological systems. The HGP tells us that we have approximately 30,000 genes. Suppositions before the Genome project were that each single gene encodes a single protein . We are left now to wonder how humans are built of approximately 120,000 proteins. To explain this, it must be the case that some genes can be toggled to create more than one gene product. The toggling must be controlled by other genes which might also be “toggle-able”.

The manipulation of genetic circuitry required to treat diseases is almost infinitely complex and requires that major strides are made by researchers who are cataloging the structure and functions of the products of the genome; proteins. This is the study of proteomics (yet another topic for another post).

In the end, like the first moon landing in 1969, the accomplishments of the Human Genome Project represent a huge milestone for humanity. Also, like the first moon landing which only represented a tiny step out into the unfathomable depths of our galaxy, the mapping of the human genome is only a tiny step into the unfathomable complexities of biology and life itself.