How do we know the genome sequence?

Imagine someone asked you to explain how a car works. Even if you knew nothing about cars, you could take the car apart piece by piece, inspect each piece in your hand and probably draw a pretty good diagram of how a car is put together.  You wouldn’t understand how it works, but you’d have a good start in trying to figure it out.

Now what if someone asked you to figure out how the genome works? You know it’s made of DNA, but it’s the ORDER of the nucleotides that helps to understand how the genome works (remember genes and proteins?). All the time in the news, you hear about a scientist or a doctor who looked at the sequence of the human genome and from that information could conclude possible causes of the disease or a way to target the treatment. DNA sequencing forms a cornerstone of personalized medicine, but how does this sequencing actually work? How do you take apart the genome like a car so you can start to understand how it works?

As a quick reminder – DNA is made out of four different nucleotides, A, T, G, and C, that are lined up in a specific order to make up the 3 billion nucleotides in the human genome.  DNA looks like a ladder where the rungs are made up of bases that stick to one another: A always sticking to T and G always sticking to C.  Since A always sticks to T and G always sticks to C, if you know the sequence that makes up one side of the ladder, you also know the sequence of the other side.

DNA_ladder

The first commonly used sequencing is called Sanger sequencing, named after Frederick Sanger who invented the method in 1977. Sanger sequencing takes advantage of this DNA ladder – this method breaks it in half and using glowing (fluorescent) nucleotides of different colors, this technique rebuilds the other side of the ladder one nucleotide at a time. A detector that can detect the different fluorescent colors creates an image of these colors that a program then “reads” to give the researcher the sequence of the nucleotides (see image below to see what this looks like).  These sequences are just long strings of As, Ts, Gs, and Cs that the researcher can analyze to better understand the sequence for their experiments.

sanger_sequencing

This was a revolutionary technique, and when the Human Genome Project started in 1990, Sanger Sequencing was the only technique available to scientists. However, this method can only sequence about 700 nucleotides at one time and even the most advanced machine in 2015 only runs 96 sequencing reactions at one time.  In 1990, using Sanger sequencing, scientists planned on running lots and lots of sequencing reaction at one time, and they expected this effort would take 15 years and cost $3 Billion. The first draft of the Human Genome was published in 2000 through a public effort and a parallel private effort by Celera Genomics that cost only $300 million and took only 3 years once they jumped into the ring at 2007 (why was it cheaper and fast, you ask? They developed a fast “shotgun” method and analysis techniques that sped up the process).

As you may imagine, for personalized medicine where sequencing a huge part of the genome may be necessary for every man, woman, and child, 3-15 years and $300M-$3B dollars per sequence is not feasible. Fortunately, the genome sequencing technology advanced in the 1990s to what’s called Next Generation Sequencing. There are a lot of different versions of the Next Gen Sequencing (often abbreviated as NGS), but basically all of them run thousands and thousands of sequencing reactions all at the same time. Instead of reading 700 nucleotides at one time in Sanger sequencing, NGS methods can read up to 3 billion bases in one experiments.

How does this work? Short DNA sequences are stuck to a slide and replicated over and over. This makes dots of the exact same sequence and thousands and thousands of these dots are created on one slide. Then, like Sanger sequencing, glowing nucleotides build the other side of the DNA ladder one nucleotide at a time. In this case though, the surface looks like a confetti of dots that have to be read by a sophisticated computer program to determine the millions of sequencing.

NGS

So what has this new technology allowed scientists to do? It has decreased the cost of sequencing a genome to around $1000. It has also allowed researchers to sequence large numbers of genomes to better understand the genetic differences between people, to better understand other species genomes (including the bacteria that colonize us or the viruses that infect us), and to help determineexomee the genetic changes in tumors to better detect and treat these diseases. Next Generation Sequencing allows doctors to actually use genome sequencing in the
clinic. A version of genome sequencing has been developed called “exome sequencing” that only sequences the genes.  Since genes only make up about 1-2% of the genome, NGS of the exome takes less time and money but provides lots of information about what some argue is the most important part of the genome – the part that encodes proteins.  Much of the promise of personalized medicine can be found through this revolutionary DNA sequencing technique – and with the cost getting lower and lower, there may be a day soon when you too will have your genome sequence as part of your medical record.


For more information about the history of Sequencing, check out this article “DNA Sequencing: From Bench to Bedside and Beyond” in the journal Nucleic Acids Research.

Here is an amusing short video about how Next Generation Sequencing works described by the most interesting pathologist in the world.

Personalized Medicine: A Cure for HIV

Personalized Medicine – finding the right treatment for the right patient at the right time – is quickly becoming a buzzword both in the medical field but also to the public. But is it just hype? No!  I discussed a number of examples of how personalized medicine is currently be used in breast cancer in a previous post. In this and future posts, I’ll talk about a few fascinating emerging examples of the promise of personalized medicine.  These are NOT currently being used for patient treatment as part of standard of care, but could be someday.

HIV

HIV lentivirus

The Human Immunodeficiency Virus (HIV), the cause of AIDS, is a virus that attacks the immune system.  This attack prevents immune cells from fighting other infections.  The result of this is that the patient is more likely to acquire other infections and cancers that ultimately kill them.  When first discovered in the early 1980s, HIV infection was a death sentence. Untreated, survival is 9 to 11 years.  In the past 30 years, antiviral treatments have been developed that, when taken as prescribed, essentially make HIV infection a chronic disease, extending life to 25-50 years. But there is no cure for HIV, and as of 2012, over 35.3 million people were infected with the virus.

The lack of a vaccine to prevent the disease or of a cure to treat those infected isn’t because no one is trying. Since the virus was identified as the cause of the disease, scientists have been working to find a prevention or cure (along with developing all of the antiretroviral drugs that delay/treat the disease). I’m not going to discuss all of this interesting research (though it is worthy of discussion), instead I’m going to talk about one patient, Timothy Ray Brown, who was cured of HIV/AIDS through a stroke of genetic understanding and luck!

Brown was HIV positive and had been on antiretroviral therapy for over 10 years when he was diagnosed with leukemia in 2007. His leukemia – Acute Myeloid Leukemia (AML) – is caused by too many white blood cells in the bone marrow, which interferes with the creation of red blood cells, platelets and normal white blood cells. Chemotherapy and radiation are used to treat AML by wiping out all of the cells in the bone marrow – both the cancer cells and the normal cells. Brown’s doctors then replaced the cells in the bone marrow with non-cancerous bone marrow cells of a donor.  This is called a stem cell transplant, and it is commonly used to treat leukemia – often resulting in long term remission or a cure of the disease.

But the really cool part of this story isn’t the treatment itself.  Rather it’s that that Brown’s doctor selected bone marrow from a donor that had a mutation in the gene CCR5. So what? The CCR5 protein is found on the outside of the cells that the HIV virus infects. CCR5 is REQUIRED for the virus to get inside the cell, replicate, and kill the cell. Without CCR5, HIV is harmless. There is a deletion mutation in CCR5 called delta32 that prevents HIV from binding to the cell and infecting it.  Blocking HIV from getting into the cell prevents HIV infection.  In fact, it’s been found that some people are naturally resistant to HIV infection because they have this deletion. Two copies of the gene are found in 1% of the Caucasian population, and it’s thought that this mutation was selected for because it also prevents smallpox infection.
HIV_ccr5So Brown’s doctors repopulated his bone marrow with cells that had the CCR5-delta32 mutation.  This didn’t just cure his leukemia but it also prevented the HIV from infecting his new blood cells, curing his HIV. He is still cured from HIV today!

What does this mean for others who are infected with HIV? Is a stem cell transplant going to work for everyone?  Unfortunately, no. This mutation is very rare, so finding donors with this mutation isn’t feasible.  Plus, this is a very expensive therapy that comes with risks such as graft-versus-host disease from the mismatch between the person receiving the transplant and the transplanted cells themselves. However, there are possible options to overcoming these challenges, including “gene editing.” In this method, T cells from HIV-positive patients would be removed from the body and then gene editing would be used to to make the CCR5-delta32 mutation in these cells.  These cells could then be re-introduced into the patient.  With the mutation, HIV won’t be able to infect these T cells, which would hopefully cure the disease, while avoiding some of the major graft-versus-host side effects. A small clinical trial tested this idea in 2014 (full article can be found in the New England Journal of Medicine), and HIV couldn’t be detected in one out of four patients who could be evaluated. Although this is a preliminary study using an older gene-editing technique, it shows promise for “personalized gene therapy” to potentially cure HIV.

Growing tumors outside the body to kill the tumor still inside

To understand how to kill a tumor, you have to study the tumor. Historically, much of how scientists understand tumors comes from removing a tumor from a patient’s body, putting Cell_Cultureit in a plastic dish (called a petri dish), and studying whatever cells are grown in this dish. You may be familiar with the book “The Immortal Life of Henrietta Lacks” by Rebecca Skloot. This book talks about HeLa cells, which are cells that were taken from Henrietta’s cervical cancer, grown in a dish, and propagated for the past 60+ years as what is called a “cell line“.  These cells grow and divide indefinitely, and have been propagated and transferred from lab to lab to be studied.  HeLa cells are one of the most famous and most-researched cells that have helped scientists better understand cancer. HeLa cells are not the only cell line that exists or has been used to study cancer.  There are cell lines from lung cancer tumors, prostate cancer, brain cancer, and most other major cancers. However, there are a few problem with using cell lines to understand and treat cancer.

  1. Cell lines are EXTREMELY hard to create.  As you may imagine, a plastic dish is nothing like the environment inside the body that the tumor was removed from.  In the petri dish the cells are put into “media,”t he liquid that is used to feed the cells in the petri dish, and this media is also nothing like the nutrients and other growth factors feeding the tumor inside the body. Because of this unnatural environment, some of the tumor cells die – and in many cases mostor all of the tumor cells die.
  2. The cells that are left in the petri dish do not accurately represent the tumor anymore. A tumor isn’t a whole bunch of identical cells, but rather a tumor contains a lot of genetically different cells.  Scientists call this tumor heterogeneity. This is one of the reasons why drug resistant cells emerge after treating a tumor with drugs (like in the case of melanomadescribed in a previous post).  There are already drug resistant cells inside the tumor that don’t die when treated with drug.  Unfortunately, not all of these different cells in the tumor will live in a petri dish, so only a selected type or types of cells will live and can be studied.
  3. Even though cell lines had been the most useful tool in the past to understand cancer biology, they are not at all useful in understanding the EXACT tumor from a particular person. What does this mean? For example, drugs that kill HeLa cells in a petri dish might not work to kill another person’s cervical cancer because the genetic cause of that cervical cancer is different. In personalized medicine, the goal is to identify the drugs that will work to kill a particular patient’s tumor. Because of this, cell lines just aren’t good enough.

Scientists have been working on a number of solutions, and I’ll talk about four:

  1. Biobanking. A biobank collects excess tumor tissue from patients who are having a
    liquidnitrogenfreezers

    Where tumor tissue is stored in a biobank before researchers use it

    tumor removed as part of a surgery.  This tissue is immediately preserved by freezing and can then be used by researchers to study that particular tumor or many tumors of a particular type (e.g., lung cancer).  The disadvantage to this is that the tumor sample isn’t an unlimited resource. Once the tissue has been used up – it’s gone. The remaining examples all focus on growing the tumor tissue so that it can be propagated and used for many experiments.

  2. Modified cell line growth. HeLa cells were not grown in any special way, but researchers at Georgetown Universityhave found ways to grow tumor cells in a petri dish  that are identical to the tumor and nearly all tumors can grow under these conditions. So what are these conditions?  The researchers grow cells on top of a layer of mouse cells called feeder cells because they provide the cell-based nutrients to “feed” the tumor and allow it to grow.  They also use a particular inhibitor that allows the cells to grow indefinitely. They have created these modified cell lines from different types of tumors, from frozen biobanked tumors, and from as few as 4 live cells.  Even though this system, is better, it still doesn’t replicate the 3D architecture of a tumor…
  3. cancer organoids

    Cancer organoids. Notice the 3D clumps of cells after 217 days of growth. Thanks to the Kuo lab for the image

    Organoids. As you would expect the word to mean, an organoid is a mini 3D organ bud grown in a dish. Don’t imagine a teeny tiny beating heart.  These organoids are just clumps of cells, but an organized clump of cells that can help better understand cells and organs. The discovery of how to create organoids was so interesting that it was a 2013 Big Advance of the Year by The Scientists magazine. Scientist have also found a way to grow cancer cells into these 3D organoid structures. With tumor organoids, researchers can both study the genetics of the tumor (like you can with cell lines) as well as how the tumor behaved in a 3D environment that is more similar to what the tumor encounters in the body.  But what if we could do even better?

  4. Patient-derived xenograftsare when tumor tissue is taken directly from a patient’s tumor and put directly into a mouse.  Why would this be so awesome? The environment inside a mouse is more similar to the environment that the tumor is used to inside a person’s body.  The cells are less likely to die because they aren’t living in unnatural plastic. Also, a whole piece of tumor can be implanted into the mouse, maintaining the tumor cells connections to neighboring cells, which are critical for the tumor cells to communicate with one another for survival.

With all of these systems available to study tumors from a specific patient, what are scientists actually doing with these cells? In some cases, they are being used to sequence the genomes of the tumors to identify mutations that may be causing the tumor. If a tumor can be grown so that there is a lot of it, the tumor cells themselves can also be used to test treatments either in a dish or inside of a mouse. Imagine a cancer patient getting their tumor removed, part of the tumor is grown in one of the ways described above. Then the tumor is exposed to the top 10, or 50 or 100 anti-tumor drugs or combination of drugs to see what kills the tumor. This drug or combo of drugs can then be used to treat the patient. There are companies that are currently working on doing exactly this (check out Champions Oncology) so this “big dream” may soon become a cancer patient’s more promising reality.

 

The best week ever – Nobel Prize week!

nobelLast week was one of my favorite weeks of the year – Nobel Prize week. Some people wait for the Emmys or the Superbowl or Christmas.  I wait for the Nobels. To be fair, I care most about the science Nobels – Physics, Chemistry and Physiology or Medicine, though one cannot ignore the amazing accomplishments of the winners in Literature, Peace, and Economics. Every year, I try to guess who may win – though Thomson Reuters and others are far more scientific about their guesses than I am.  And each morning of Nobel Week, first thing I do is check the news on my phone to see who won, what for and whether or not I know them (this year – no).  Let’s talk about who won the science awards this year and what amazing discoveries they won for.

Physiology or Medicine. A lot of attention has been given to infectious diseases this year with the huge Ebola outbreak in western Africa.  Although tens of thousands of people were infected and died, other infectious diseases are even more widespread and affect millions of people a year. Malaria is a parasitic disease transmitted by mosquitoes that 3.4 billion people are at risk of contracting and that kills over 450,000 people per year. Parasitic worms are also rampant in the third world, can affect up to a third of the human population, and cause such diseases as river blindness.  This is the second most common cause of blindness by infection, with 17 million people infected and 0.8 million blinded by the disease.  The three winners of the Nobel for Physiology or Medicine this year discovered novel treatments for these parasitic diseases.  William C. Campbell and Satoshi Ōmura for roundworm parasites and Youyou Tu for malaria, saving hundreds of thousands of lives each year.

Chemistry. This is by far my favorite award this year because it is directly related to how humans safeguard their DNA, but also why when this safeguard does work, that we get cancer.  Awarded to Tomas Lindahl (UK), Paul Modrich (USA), and Aziz Sancar (USA), this Nobel celebrates the discovery of the mechanism of DNA repair. I’ve discussed in this blog how UV and other environmental factors can cause mutations in DNA, and with too many mutations, people can develop cancer or other diseases.  However, the genome doesn’t mutate out of control because cell contain the machinery that is always working to fix any DNA damage using DNA repair mechanisms. It’s like a NASCAR race, where the car is always being monitored, wheels replaced, and minor problems fixed by the pit crew.  DNA repair is the genome’s pit crew and these three scientists figured out three different ways that the cells monitors and fixes the DNA depending on the type of damage that has occurred.

Physics. We all know I’m not a physicist, but I’ll try my best. The Physics Nobel was awarded to Takaaki Kajita of Japan and Arthur B. McDonald of Canada for discovering that neutrinos have mass.  You may remember from high school that atoms are made up of protons, neutrons and electrons. However, scientists now know that there are even tinier parts of an atom called subatomic particles that include the neutrino, fermions and bosons (and others). Other than photons, which are the particles of light, neutrinos are the most numerous subatomic particle in the entire cosmos, so understanding how they work is incredibly important.  These researchers found that the three different types of neutrinos can convert from one to the other. It was predicted by the Standard Model of Physics that these neutrinos wouldn’t have mass, but these scientists also proved that they did. Their studies help to better understand matter and the universe. My favorite reporting of this award was by NPR.

So until next year Nobel Prizes.  I will be waiting with baited breath!

 

Book Club: Bad Science: Quacks, Hacks, and Big Pharma Flacks

quacksandhacks

One responsibility I feel that I have as a scientist is to help people understand the science that affects them and their health. Part of this is to explain the difference between good science, bad science (which is just poorly done science resulting in incorrect conclusions) and pseudoscience (which is a set of claims, belief or practice that is touted as being based on scientific fact).  Some recent examples of my blog posts about bad science or pseudoscience focus on homeopathy, the inaccurate connection between vaccination and autism, and how the media propagates bad and pseudoscientific claims.

The task I’ve given myself with this blog is challenging because as well as explaining the science (good, bad and fake), I ultimately want my readers to be empowered to go into the world, read news stories, visit websites and see Facebook posts and be armed with the knowledge to figure out if what they are reading is legitimate or not.  This is difficult because even as a scientist, I often have to look at the primary data from publications and conflicting information to figure out what’s going on.

However, in my ongoing effort, I found that this book “Bad Science: Quacks, Hacks, and Big Pharma Flacks” by Ben Goldacre provides a great primer on bad science, pseudoscience and how the media hypes both. In the book description, they ask ” How can average readers, who aren’t medical doctors or Ph.D.s in biochemistry, tell what they should be paying attention to and what’s, well, just more bullshit?” and this book is a good first start.  With chapters on homeopathy, the placebo effect, the “science” behind nutrition, the absurd story of an MD offering multivitamins to “cure” AIDS, and the media’s role in propagating these “quacks” and “hacks,” you will get an education on how this terrible science is pushed on the the unaware. I think you’ll walk away illuminated, perhaps a little bit disappointed, but much better armed to understand all the science and “science” you encounter every day.

For more Book Club books, click here.

Sci Snippet – Do iPhones kill people?

Look at this graph. It’s incredible! As iPhone sales increase from 2007 to 2010, so did the number of deaths caused by people falling down the stairs.  They even increased at the same rate.  It’s crazy – iPhones cause people to die falling down the stairs!!

correlation-causation

For this and other hilarious graphs of silly correlations see tylervigen.com

How obviously ridiculous this is.  Most people could logically deduce that just because iPhone sales and deaths from falling down the stairs “correlate” that one does not “cause” the other. There are lots of other examples (and you can create your own silly correlations) from Spurious Correlations or on other news sites here or here.  And in these cases, you can laugh realizing that just because these two things happen together does not mean that one causes the other.

But even though you’ve probably said that “correlation doesn’t imply causation” or heard someone say it, in science (and science news reporting) the difference is critical to tease out. Why? Understanding if something in science is a cause of the effect you’re seeing can

  • Prevent something harmful from causing damage. For example knowing that smoking is a cause of lung cancer resulted in public health efforts to help people quit smoking.
  • Treat a the cause of a disease or fix the cause of the problem.  For example, knowing that the h.pylori bacteria causes gastritis and ulcers provides a method for treating ulcers by killing the h.pylori. Or if you know that factory waste being dumped into a river or lake causes animal life to die or stop procreating, you can work towards stopping the dumping to save wildlife.
  • Prepare for diseases, outbreaks of disease, or natural disasters.  If you know that earthquakes cause tsunamis, then a warning system can be developed to save people in the tsunami zone.
  • Plan ahead and discuss the possible outcomes from a particular action.  When you know that lack of water in a drought causes dry forest conditions leading to forest fires, you can plan to have greater funding available for fighting these fires in a particularly dry year.
cancer-lung

“Cancer smoking lung cancer correlation from NIH” by Sakurambo – Vectorized version of Image:Cancer smoking lung cancer correlation from NIH.png, originally published on the nih.gov website. The source page has been deleted, but an archived copy is still accessible.Own work, created in Adobe Illustrator. Licensed under Public Domain via Commons

It’s just as important though to tease out when something doesn’t cause an effect – and unfortunately many false claims and pseudoscience is based on taking correlations and touting them as causes.  So how do we figure this out?

In science, a lot of this is determined experimentally and statistically.  In statistics (of which I do not claim to be an expert, but see the links below for more details), the strength of the relationship can be calculated and the stronger the more likely that one causes the other.  The cause/effect relationship should also be tested experimentally, if possible, and the experiment should be repeated to see if the same results are obtained every time.  Without experimental or repeatable experimental results, the relationship is less likely to be causal.  Another interesting measurement is to look at the time frame – if the action takes place months, days, or years apart from the effect, you have to consider whether this would make sense or not.  In the case of smoking and lung cancer, the separation of the two events by years makes sense, but in other cases it may not.  Which also brings up the point of looking at the relationship and thinking about whether or not it makes sense or if a mechanism can be found for the cause and effect relationship.  For example, we know that smoking causes DNA mutations and inflammation which is one of the mechanisms that leads to lung cancer. Alternatively, looking at the iPhone and dying from falling down the stairs example, it’s difficult to find a mechanism that could explain this relationship.

A great description of what to look for comes from the book club book that I’ll be talking about on Thursday, “Bad Science: Quacks, Hacks, and Big Pharma Flacks” by Ben Goldacre with a quote describing evidence-based medicine:

it needs to be a strong association, which is consistent, and specific to the thing you are studying, where the putative cause comes before the supposed effect in time; ideally there should be a biological gradient, such as a dose-response effect; it should be consistent or at least not completely at odds with what is already known (because extraordinary claims require extraordinary evidence); and it should be biologically plausible

Overall, it does come down to the data and some common sense.  If there isn’t any data to support the relationship, you might just be looking at correlation and can confidently holler “iPhones do not kill people!”

To better understand the differences between correlation and causation and the math that can show which you are looking at, check out the Kahn Academy course.  Read more about this topic from Stats with Cats Blog

For more Sci Snippets, click here.

Journal Club: The Microbiome Autism Connection

As I’ve mentioned in other posts, scientists have to read about and understand the current scientific literature. Lots of the time this is done alone, at your desk in the office or the lab, for hours and hours so that you can really understand whatever topic it is that you’re studying. But one of my favorite ways to share scientific papers is through a weekly meeting with the whole lab called a Journal Club. Although my husband laughs about this kind of nerdy science “club” (akin to his amusement about scientific societies), it’s a great way to discuss a particular topic and dive deep into a discussion about how the researchers got their results and came to their conclusions. This is the first of many Journal Clubs where we will do an abbreviated version of what we would discuss in a typical journal club in the lab. 

Paper TItle:  Reduced Incidence of Prevotella and Other Fermenters in Intestinal Microflora of Autistic Children

Authors: Dae-Wook Kang , Jin Gyoon Park ,Zehra Esra Ilhan, Garrick Wallstrom, Joshua LaBaer, James B. Adams, Rosa Krajmalnik-Brown
Full disclosure, Dr. LaBaer is the Director of the center I previously worked in at the Biodesign Institute at ASU. Drs. Park and Wallstrom worked in offices down the hall from me and Dr. Krajmalnik-Brown was in another center at the Biodesign Institute.

Journal: PLOS One (PLOS stands for “Public Library of Science”). In case you want to read the whole article, it can be downloaded (for free) here

Background/Introduction: Before this paper was published, scientists knew that many children with autism also had gastrointestinal (GI) issues suggesting that there may be a connection between the two. There have been some studies looking at antibiotic treatment (which could change the gut microbiome) before 3 years of age and how this might be connected with autism.  There have also been studies connecting the gut microbiome and the brain. So there was evidence that the gut microbiome and autism may be related in some way.

When this paper was written, scientists also knew about the microbiome and how changes in the bacteria (all 1,000,000,000,000,000 of them) that are in the gut are found in patients with many different diseases – from C. diff infection to obesity to depression.

Goal of this paper: Look closely at the changes in the gut microbiome of children with autism to better understand how these two might be related.

Methods/what did they do?: Bacteria in fecal samples is considered representative of bacteria in the gut microbiome. Therefore, the researchers collected fecal samples from children both with (20 children) and without (20 children) autism.  The samples from patients without autism were used as a “control” to compare to the autistic samples. The researchers also asked the children (or their parents) questions to help determine the level of GI issues, the severity of their autism, and their environmental factors like their diet. The researchers isolated bacterial DNA from each of these fecal samples and then sequenced the DNA to determine what types of bacteria are in the gut.

autism microbiome diversity

A figure from the paper comparing the phylogenetic diversity (PD) of the bacteria in autistic versus non-autistic children. you can see that the red boxes (for autistic children) are lower than the blue boxes (for non-autistic children) indicating a lower microbiome diversity.

Results: Through sequence analysis and other statistical methods, the authors found that children who did not have autism have a more diverse microbiome compared to autistic children.  If there is higher diversity, it means that the gut contains more different types of bacteria, and lower diversity means a smaller variety of bacteria in the gut. They also found that in the autistic patients with a greater diversity in their microbiome, their autism was generally less severe. They also did not find any correlation between age, gender or diet with these microbiome changes.

The scientists also looked at what specific genus and species of bacteria were more represented in non-autistic versus autistic children. Specifically the bacteria from genus Veillonellacaea, Provetella, and Coprococcus  are less abundant in autistic children.

Discussion/Significance: What does this all mean?  The researchers did find a correlation between decreased gut microbiome diversity and autism. It should be clarified that just because GI problems are often found in autistic children and the severity of the GI issues correlates with the severity of autism, this does not necessary mean that GI issues cause autism or vice versa.  That still needs to be determined. Also because the diversity of bacteria in autistic children is low, it is not clear if this is a cause of autism or an effect of a child having autism.  However, this paper does provide a “stepping stone” to better understand what is happening in the gut of autistic children and may help define a target for diagnosing autism (by looking at the decreased diversity in the gut as a diagnostic test) or treatment (perhaps through fecal transplant).

What has been done since? This paper was published in 2013.  So what has changed since the paper was published?  Do we know whether or not changes in the gut microbiome cause autism or not?  Unfortunately, this is still unclear.  However, if these microbiome changes are a cause of the neurological changes in autism, then one would want to do a clinical trial to test what happens to autism symptoms when the microbiome has been altered.  This could be done in a number ways including diet modulations, prebiotics, probiotics, synbiotics, postbiotics, antibiotics, fecal transplantation, and activated charcoal.  Researchers have started this process by holding a meeting that included patients and their families to figure out how this type of trial could be designed (for more details, check out this journal article).

For more information about the microbiome/autism connection, check out Autism Speaks. To read more Journal Clubs, visit the archives here.

Killing brain cancer with electricity

Cancer is a disease that involves cells dividing faster than they should (check this out for a review of how cells divide) along with many other complicated processes.  But if you simplify cancer to this one concept – cells dividing too fast – then you can think of interesting ways to kill cancer cells by targeting cells that are dividing quickly.  In fact, many (if not most) current cancer treatments do just that  – they create too much DNA damage for the cancer cells to handle, so the cancer cells kill themselves. There is a bit of a problem with this though – cancer cells aren’t the only cells that are quickly dividing.  Hair follicles, cells in the lining of the gut and blood cells all also divide quickly.  This is why non-specific cancer treatments like chemo that go throughout the body also end up killing these fast dividing cells, which is why cancer patients often lose their hair, have low blood counts and have gastrointestinal issues.

spindles

By Kelvinsong (Own work) [CC BY 3.0], via Wikimedia Commons

Wouldn’t it be great if the cell division part of cancer cells could be more targeted, less toxic, and avoid many of the difficult side effects from cancer treatment?  Scientists are working on a number of different treatments that do just that, but in this post I’m going to talk about one that is particularly interesting because it’s being used in clinical trials in our backyard at the Barrow Neurological Institute to treat glioblastoma multiforme (abbreviated GBM). GBM is the most common form and aggressive adult brain cancer. GBM has a terrible prognosis – with 50% of patients diagnosed dying within one year and 90% dying within 3 years. Standard treatment involves surgery to remove the tumor, and then radiation and chemotherapy treatment.  Treatment is difficult, and because this is a brain tumor, there are additional challenges involving brain damage from surgery, radiation and/or chemo and getting drugs through the blood-brain barrier into the brain tumor.

NovoTFF

Thanks to MedGadget for the image

A new treatment called NovoTFF (TFF stands for Tumor Treating Fields) goes directly after the dividing GBM cells. Receiving FDA approval in 2011, it is a device that is worn as a cap (see image at left) and uses a battery pack that can be worn in a backpack to create wave-like electronic fields that penetrate the brain.  These fields disrupt the spindles that are responsible for separating the chromosomes during the cell cycle (see image above). There is also some evidence that these electric fields disrupt the cell membrane of dividing cells as well. Since the GBM cancer cells are dividing, they will be most likely to have their cell cycle disrupted and the cells’ natural response to this kind of major disruption is to die.  This treatment has amazing advantages.  Because it’s worn outside the body, NovoTFF isn’t invasive like surgery.  It’s also just worn on the head so it won’t have side effects like the ones from treatments that go throughout the body.  Also, the electric fields won’t affect cells that aren’t dividing (like most brain cells), so this treatment is less likely to cause damage to the non-cancerous brain cells.  But does it work?  Yes! In multiple clinical trials, this treatment was shown to slow the growth of recurrent GBMs and increase the length of progression-free survival compared to patients who did not use NovoTFF. The only disadvantage might be that the cap needs to be worn for 18 hours a day.  Then again, if that 18 hours a day can prolong a patient’s life, the inconvenience might be worth it.

NovoTFF has been so successful that it’s also be tested in clinical trials for pancreatic cancer, ovarian cancer, mesothelioma, and brain metastasis from lung cancer. Obviously in these cases the device has been changed so that it attaches to the torso instead of sitting on the patient’s head.  Research is also being performed by individual doctor’s  to see if NovoTFF may work for newly diagnosed GBM patients or for other kinds of cancer.

If you want to learn more about Tumor Treating fields and this fascinating new treatment, check out this Ted Talk 

 

How do scientific papers get published?

I had a busy week last week.  Besides doing experiments, I was also working on a manuscript about sustainability in biobanking. I’ve talked in other posts about what a scientific paper generally looks like (see here), but not what it takes to get from experiments in the lab to publication.  This is what I’m going to talk about today.

First, you have to know enough of the field to have an understanding of what is known and not known.  Second, you have to identify a hole in that knowledge that you could fill by doing experiments to test hypotheses. Third, you needed to do well-controlled experiments that will hold up to careful analysis.  These will be the basis of your manuscript’s results section.

nytpuzzle

From the NYT article

Let’s talk about this point a bit more, but first, go to the New York Times and take this little puzzle (it’ll only take a minute or so). This puzzle boils down the essence of doing a good experiment.  You start with a hypothesis (e.g., the numbers are all even). You test that hypothesis and see the result. If you get a negative result, you come up with a new hypothesis and test that.  If it’s a positive result, you can do a few things.  You can decide that your hypothesis is correct and try to guess the answer or, in the case of the laboratory, publish a paper about your new amazing result.  However, it won’t get published because you could be wrong. You will have to find other ways to confirm your hypothesis using different or complimentary experiments.  You should also do your best to disprove your hypothesis. Even in the NYT puzzle, you should try to find negative results. This will help you better understand the limitations of your hypothesis and the results you obtain.  In the lab, it will likely also lead you down roads of abject failure that will never see the light of day, but that’s the reality of science.

Now that you have your experiments completed, your forth step is to actually write the paper.  My undergraduate research adviser always had a draft outline of the paper in process as experiments were being done. That way, he could fill in results as he went along. Most researchers aren’t that organized and they get to writing the paper when their adviser (or the head of the lab) looks at them essentially tells them to “get their butt in gear and write the damn paper, already!” Why is starting a manuscript so difficult? Mostly because it involves synthesizing information. Results on their own are beautiful pieces of success that could go anywhere and do anything.  Synthesizing these into a “story” and discussing the implications of these results on the broader field is hard work. And the wrong analysis can affect the chances of the paper being published or your reputation in the field.

The other challenge when starting to write is figuring out what journal to submit the manuscript to – and keep in mind, there are thousands of possibilities.  Depending on the scientific significance, novelty of the results, and general scientific interest, you may submit your paper to one of the top journals (like Nature, Science or Cell) or you may submit to one that isn’t.  Maybe you’re wondering why this matters?  Each journal has an impact factor, which indicates how often papers published in that journal get cited by other authors.  The more prestigious the journal, the more citations your paper gets, indicating generally, that your research is more influential.  This affects how likely it is for you to (fill in the blank): get a job, get tenure, get invited to give talks at meetings around the world, get a raise, get more grants, get more students, be more successful overall etc. Therefore, the higher the impact factor, the more likely it is for you to become a wildly famous (in the ideal) or successful (in reality) scientist.

paper

The first page of a publication I wrote about the DNASU plasmid repository published in the journal Nucleic Acids Research

Once the journal is decided upon, and the manuscript is reformatted to fit the requirements of that journal (which is a whole other pain in the butt sometimes requiring you to cut the manuscript length by 60%) you submit your manuscript and wait. And you may wait a long time.  I’m not a journal editor so I can’t provide all the insider details, but once at the journal there are  levels of review.  Internal reviews by the journal editors sending the manuscript out for review by other scientists in the field, additional editorial review, etc.  At each stage the manuscript can be rejected and each step takes time.

The manuscript reviewers take on an essential role in the scientific process. They help to ensure that the research is high quality and that the claims made in the paper are valid and supported by evidence. Any scientist can be a reviewers (I’ve reviewed a half a dozen manuscripts), but they should ideally have knowledge of the scientific topic being addressed in the manuscript. Typically each manuscript that is sent out to review to three scientists, and they each anonymously provide their comments back to you and to the editors.  This is where the process can get messy.  The reviewers could just flat out suggest your paper should be rejected or accepted.  Then again (and more likely), they may ask for edits – these can be as simple as fixing typos and adding a few clarifying sentences to doing years worth of additional experiments. And the reviewers may not agree – one reviewer could accept the manuscript, one could reject it and one could ask for edits.  It’s then up to the journal editor to decide what to do. For more about reviewers, check out this Sci Snippet about who these reviewers actually are and the crazy things they sometimes do and say.

When you get the reviews back, if your paper hasn’t been immediately accepted, you can choose to make edits, do the suggested experiments and resubmit to the same journal.  If this is your choice, just by re-submission, you are not guaranteed to have your paper accepted.  You may spend months doing experiments, just to have your manuscript rejected at the end of the day.  If the reviewer comments are too negative or the paper was rejected, you may realize that you set your sights too high and you should submit to a different journal that may have a higher likelihood of acceptance.  At that point, you start the review process all over again.

If this sounds frustrating to you, it is.  I have friends who have had papers in the review, edit, review process for over a year.  I have friends who have submitted papers over and over and haven’t been able to get them published. I also have friends that submit to a high profile journal and get accepted right out of the gate.  However, with the stakes being so high and affecting you scientific career so directly, the publishing process is a necessary frustration and if done correctly, can make your science and your research better.

 

Five Ways for You to Participate in Science – Citizen Science

Bunsen_burner

The Bunsen burner I didn’t have. Thanks Wikipedia for the image

I had a chemistry set growing up.  It was small with tiny white bottles holding dry chemicals that sat perfectly on the four tiny shelves of an orange plastic rack.  My dad would let me use the workbench in the basement to do experiments – entirely unsupervised!! You might expect that I did really interesting chemical reactions, and this formative experience helped me to develop into the curious scientist that I am today. Completely wrong.  I remember following the instructions, mixing the chemicals, and then getting stuck because I didn’t have a Bunsen burner.  So many chemical reactions rely on heat, and the green candle stuck to the white plastic top of an aerosol hairspray can wasn’t going to cut it.

My main options for doing science as a kid revolved my failed chemistry experiments, my tiny microscope and slides, and a butterfly net that never netted a single butterfly (not for lack for trying).  However, today with computers (that’s right – no computer growing up – that’s how old I am!) there are hundreds if not thousands of ways for people to get involved in science, without having to invest in a Bunsen burner. This citizen science movement, relies on amateur or nonprofessional scientists crowd-sourcing scientific experiments. I’m talking large scale experiments run by grant-funded university-based scientists that have the possibility of really affecting how we understand the world around us. One example you may have heard about is the now defunct Search for Extraterrestrial Intelligence (SETI) which used people sitting at their computers to analyze radio waves looking for patterns that may be signed of extraterrestrial intelligence. They didn’t find anything, but it doesn’t mean that they wouldn’t have if the program had continued!

Here are five ways that you can become involved in science from where you’re sitting right now!

americangut1. American Gut: Learn about yours (or your dog’s) microbiome

For $99 and a sample of your poop, you will become a participant in the American Gut project. After providing a sample, the scientists will sequence the bacterial DNA to identify all of the bacterial genomes that are present in your gut.  This study already has over 4,000 participants and aims to better understand all of the bacteria that covers and is inside your body – called your microbiome – and to see how the microbiome differs or is similar between different people or between healthy people versus those who may be sick. The famous food writer Michael Pollan wrote about his experience participating this the American Gut project in the New York Times.  They are also looking at dogs and how microbiota are shared with family members, including our pets!

2. Foldit: solve puzzles for sciencefoldit

Puzzles can be infuriating, but at least they have a point to them when you get involved in the Foldit project.  Proteins are the building blocks of life.  Made out of long strings of amino acids, these strings are intricately folded in your cells to make specific 3D shapes that allow them to do their job (like break down glucose to make energy for the cell).  Foldit has you fold structures of selected proteins using tools provided in the game or ones that you create yourself.  These solutions help scientists to better predict how proteins may fold and work in nature.  Over 240,000 people have registered and 57,000 participants were credited in a 2010 publication in Nature for their help in understanding protein structure.  Read more about some of the results here.

3. EyeWire: Mapping the BrainEyeWire-Logo

The FAQs on the EyeWire website are fascinating because as they tell you that there are an estimated 84 billion neurons in the brain, they also insist that we can help map them and their connections. After a brief, easy training, you’re off the the races, working with other people to map the 3D images of neurons in the rat retina.  You win points, there are competitions, and a “happy hour” every Friday night. The goal is to help neuroscientists better understand how neurons connect to one another (the connectome).

4. Personal Genome Project: Understanding pgpyour DNA

The goal of the Personal Genome Project is to create a public database of health, genome and trait data that researchers can then use to better understand how your DNA affects your traits and your health. This project recruits subjects through their website and asks detailed medical and health questions.  Although they aren’t currently collecting samples for DNA sequencing because of lack of funding, they have already sequenced the genomes of over 3,500 participants. The ultimate goal is having public information on over 100,000 people for scientists to use.

mindcrowd5. MindCrowd: Studying memory to understand Alzheimer’s Disease

Alzheimer’s Disease is a disease of the brain and one of the first and most apparently symptoms is memory loss.  MindCrowd wants to start understanding Alzheimer’s disease by first understanding the differences in memory in the normal human brain.  It’s a quick 10 minute test – I took it and it was fun!  They are recruiting an ambitious 1 million people to take this test so that they have a huge set of data to understand normal memory.

This is a randomly selected list based on what I’m interested in and things that I’ve participate in, but you can find a much longer list of projects you can participate in on the Scientific American website or through Wikipedia.  Also, if you’re interested in learning more about the kind of science that people are doing in their own homes, the NY Times wrote an interesting article: Home Labs on the Rise for the Fun of Science.  If decide to try one out, share which one in the comments and what you think!