Journal Club – A mutation in mice to study ALS

Amyotrophic Lateral Sclerosis (ALS) is a debilitating neurodegenerative disease that affects neurons in the brain, brain stem, and spinal cord. When these neurons die, it affects the connections that they have to muscles throughout the body resulting in muscle weakness that affects speaking, swallowing and breathing leading to paralysis and eventual dead.  The cause of ALS isn’t known in 90-95% of cases.  However, recently scientists have identified a mutation in a gene nondescriptly called “chromosome 9 open reading frame 72,” which is abbreviated to C9ORF72.  This mutation results in six nucleotides, GGGGCC, being repeating up to 1000 times within this gene in ALS patients.  Even though this is the most common mutation found in ALS patients, it’s still unclear exactly how these repeats affect neurons or the progression of the disease. The two hypotheses that are most studied are that the mutated C9ORF72 makes mutated RNA transcripts (RNA is the molecule that usually helps DNA be translated into proteins) or makes unusual proteins called dipeptide repeat proteins (DRPs), each of which can aggregate (clump) together and disrupt the normal activity of the neurons leading to neurodegeneration.

neuron_als_c9ORF72

The pink dots show clumped up RNA from the many many repeats in the C9ORF72 gene. Each panel shows these clumps in different areas of the mouse brain. Taken from the article Peters et al. 2015 Neuron

In two recent publications in the journal Neuron, researchers have used mice as a model system to look at how these large GGGGCC repeats in C9ORF72 affect the mouse nervous system.  Why use a mouse? First, scientists know how to experimentally change the mouse genome in order to add hundreds or thousands of repeats to a single gene, like C9ORF72.  Second, mouse and human genes are about 85% identical, so if scientists can understand how a gene like the mutated C9ORF72 affects neurons in mice, it may also help scientists understand how it works in humans. Third, by creating a mouse “model” of ALS, scientists can use this model to better understand ALS and to test potential future therapies (it’s worth noting that only one drug currently exists for ALS and it typically extends life only by a few months).

In each article, the mouse model was slightly different – one had a mutated C9ORF72 with 500 GGGGCC repeats and the other varied between 100-1000 repeats. However, both sets of researchers found the same results.  The mice had aggregated RNA transcripts and DRPs in their neurons just like what are found in human patients with ALS, but none of the mice had behavioral changes or neurodegeneration that are seen in human ALS patients.  So why didn’t the clumped up RNA and proteins cause neurodegeneration in mice like they do in humans?  There are lots of potential reasons – including the fact that even though mice and humans are similar, there are still lots of differences and mice may respond to these aggregated RNA and proteins differently than humans.  However, the authors of these papers suggest that other environmental and/or genetic factors along with the aggregates caused by the C9ORF72 mutation must be involved in developing the neurodegeneration.  It may also mean that getting rid of these aggregates before neurodegeneration occurs may prevent development of ALS.  Now that these mice are available to study, they should help in identifying the other factors involved in ALS development along with developing possible treatments for this debilitating disease.

Want to read the articles?  Unfortunately, they are behind a paywall, but you can see the abstracts here:

O’Rourke et al. (2015) C9orf72 BAC Transgenic Mice Display Typical Pathologic Features of ALS/FTD. Neuron. Volume 88, Issue 5, p892–901, 2 December 2015 Article

Peters et al. (2015) Human C9OFR72 Hexanucleotide Expansion Reproduces RNA Foci and Dipeptide Repeat Proteins but Not Neurodegeneration in BAC Transgenic Mice. Neuron. Volume 88, Issue 5, p902–909, 2 December 2015 Article

Read the Article from PN News that I contributed to here

The Cancer Genome Atlas Project (TCGA): Understanding Glioblastoma

TCGAIn 2003, Cold Spring Harbor Laboratory (CSHL) and researchers around the world celebrated the 50th Anniversary of the discovery of the structure of DNA by Jim Watson and Francis Crick.  I was a graduate student in the Watson School of Biological Science at CSHL, named after James Watson who was the chancellor of the CSHL, and in 2003, I participated in (and planned!) some of the 50th anniversary events. Coinciding with this celebration was a meeting about DNA that brought world-renowned scientists and Nobel Prize winners from around the world to CSHL to celebrate how much had been accomplished in 50 years (including sequencing the human genome) and to look to the future for what could be done next. That meeting was the first time I had heard about the Cancer Genome Atlas Project. At this point, the TCGA (as the project was affectionately called) was just a pipe dream – a proposal by the National Cancer Institute and the National Human Genome Research Institute (two institutes in the National Institutes of Health – the NIH).  The idea was to use DNA sequencing and other techniques to understand different types of cancer at the genome level. The goal was to see what changes are happening in these cancer cells that might be exploited to detect or treat these cancers.  I remember that there was a heated debate about whether or not this idea would work. I was actually firmly against it, but now with the luxury of hindsight, the scientific advances of the TCGA seem to be clearly worth the time and cost.

The first part of the TCGA started in 2006 as a pilot project to study glioblastoma multiforme, lung, and ovarian cancer. In 2009, the project was expanded, and in the end, the TCGA consortium studied over 33 cancer types (including 10 rare cancers).  All of the data that was made publically available so that any results could be used by any scientist to better understand these diseases. To accomplish this goal, the TCGA created a network of institutions to provide the tissue for over 11,000 tumor and normal samples (from biobanks including the one that I currently manage).  These samples were analyzed using techniques like Next Generation Sequencing and researchers used heavy-duty computing power to put all of the data together. So what did they find? This data has contributed to hundreds of publications, but the one I’m going to talk about today is the results from the analysis of the glioblastoma multiforme tumors.

Title: Comprehensive genomic characterization defines human glioblastoma genes and core pathways published in Nature in October 2008.

Authors: The Cancer Genome Atlas Network

gbmBackground: Glioblastoma is a fast-growing, high grade, malignant brain tumor​ that is the most common brain tumor found in adults.  The most common treatments are surgery​, radiation therapy​, and/or chemotherapy (temozolomide​). Researchers are also testing new treatments such as NovoTFF, but these have not yet been approved for regular use. However, even with these treatments the median survival for someone diagnosed with glioblastoma is only ~15 months.  At the time that this study was published, little was known about the genetic cause of glioblastoma – a small handful of mutations were known, but nothing comprehensive. Because of the poor prognosis and lack of understanding of this disease, the TGCA targeting it for a full molecular analysis.

Methods: The TCGA requested tissue samples from glioblastoma patients from biobanks around the country. They received 206 samples that were of good enough quality to use for these experiments.  143 of these also had matching blood samples.  Because the DNA changes in the tumor only happen in the tumor, the blood is a good source of normal, unchanged DNA to compare the tumor DNA to. To these samples, the study sites did a number of different analyses:

  • They looked at the number of copies of each piece of DNA. This is called DNA copy number, and copy number is often changed in tumor cells (see more about what changes in the number of chromosomes can do here)
  • They looked at gene expression.  The genes are what makes proteins, which do all of the stuff in your body.  If you have a mutation in a gene, it could change the protein so that it contributes to the development of cancer.
  • They also looked at DNA methylation.  Methylation is a mark that can be added to the DNA telling the cell to turn off that part of DNA.  If there is methylation on gene that normally stops a cell from growing like crazy, that methylation would turn that gene off and the cell could grow out of control.
  • In a subset of samples, they performed next generation sequencing to know the full sequence of the tumor genomes.

Results and Discussion: From all of this data, the researchers found  quite a bit.

  • Copy number results: There were many differences in copy number including deletions of genes important for slowing growth and duplications of genes the told the cell to grow more.
  • Gene expression results: Genes that are responsible for cell growth, like the gene EGFR, were expressed more in glioblastoma tumor cells.  This has proven to be an interesting result because there are drugs that inhibit EGFR.  These drugs are currently being tested in the clinic to see if this EGFR drug is a good treatment for patients with a glioblastoma that expresses a lot of EGFR.
  • Methylation results: They found a gene called MGMT that is responsible for fixing mutated DNA was highly methylated.  This mutation was actually beneficial to patients because it made them more sensitive to the most common chemotherapy, temozolomide.  However, this result also suggests that losing MGMT methylation may cause treatment resistance.
  • Sequencing results: From all of the sequencing they created over 97 million base pairs of data! They found mutations in over 200 human genes. From statistical analysis, seven genes had significant mutations including a gene called p53, which usually prevents damaged cells from growing, but when mutated the cell can more easily grow out of control
glioblastoma_pathways

This is the summary figure from this paper that shows the three main pathways changed in glioblastoma and the evidence they found to support these genes’ involvement. Each colored circle or rectangle represents a different gene. Blue means that the gene is deleted and red means that there is more of that gene in glioblastoma tumors.

Bringing all of this data together, scientists found three main pathways that lead to cancer in glioblastoma (see the image above for these pathways).  These pathways provide targets for treatment by targeting drugs to specific genes in these pathways. Scientists also identified a new glioblastoma subtype that has improved survival​. This is great for patients who find out that they have this subtype!  Changes in the methylation also show how patients could acquire resistance to chemotherapy. Although chemotherapy resistance is bad for the patient, understanding how it happens allows scientists to develop drugs to overcome the resistance based on these specific pathways.

Although this is where the story ended for this article, the TCGA data has been used for many more studies about glioblastoma.  For example, in 2010, TCGA data was used to identify four different subtypes of glioblastoma: Proneural, Neural, Classical, and Mesenchymal that have helped to tailor the type of treatments use for each group. For example proneural glioblastoma does not benefit from aggressive treatment, whereas other subtypes do. Other researchers are using the information about glioblastoma mutations to develop new treatments for the disease

To learn more about the Cancer Genome Atlas Project, check out this article “The Cancer Genome Atlas: an immeasurable source of knowledge” in the journal or watch this video about the clinical implications of the TCGA finding about glioblastoma

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.

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!

 

What is Personalized Medicine?

bullseyeA few years ago I was asked to teach a course to adults at the ASU Osher School of Lifelong Learning about the Emerging Era of Personalized Medicine. This was exciting because it would give me the opportunity to help empower these adults to better understand their health, the science behind what make them sick, and what scientists and doctors are doing to cure them.  This was also a challenging course to develop because only a few years ago personalized medicine wasn’t the common buzzword like it is today. In fact, in early 2014, the Personalized Medicine Coalition contracted a research survey that found that 6 in 10 of people surveyed hadn’t heard of the term “personalized medicine” (see all results of the survey here). Despite the public being unaware of this huge advance, in the past few years, scientists and doctors continue to evolve this concept and medicine isn’t just “personalized” but now it can also be described as “precision,” predictive,” “individualized,” “stratified,” “evidence-based,” “genomic” and much, much more.

So what is new about this type of medicine?  Of course since the days of Hippocrates, doctors have provided care to patients that take their “personalized” needs in mind. Based on the patient’s symptoms and their experiences, the doctor provides treatment. But what if two patients have the same symptoms but different underlying diseases?  A fever and a headache could be the flu or malaria. Or two people could have the same disease, like breast cancer, but the underlying genetic changes are different so that the cancer should be treated differently for each patient.

The current concept of personalized/precision medicine uses each person’s individual traits (genetic, proteomic, metabolomic, all the -omics) and harnesses our molecular understanding of disease for the prevention, diagnosis, and treatment of disease.

personalized-med2The ultimate goal of personalized medicine is to improve patient health and disease outcomes. The graph above shows how better understanding the genetic and molecular causes of disease can improve health at all phases of disease progression.

  1. Knowing the risk factors that cause of disease (either environmental, like smoking, or genetic, like the BRCA gene mutation) can help to prevent disease before it starts by eliminating the risk factors or providing additional screening to catch the disease early.
  2. Biomarkers that detect disease before major symptoms can be used to treat the disease early, which usually has a better outcome than treating a disease that has progressed further (think stage 1 versus stage 4 metastatic cancer).
  3. Once a disease has been diagnosed, the molecular understanding of the disease can help determine what treatment the patient should receive (see below for an example).
  4. Biomarkers can also be used to predict whether the disease will progress slowly or quickly or whether or not a selected treatment is working.

For all aspects of personalized medicine, there lies the promise to make an enormous impact both on public health but also on decreasing the cost of healthcare.

breast_cancerLet’s use breast cancer as an example of how personalized medicine plays out in real life, right now. For breast cancer detection, breast self-exams and mammograms are typically used.  With personalized medicine, we now have an understanding of one of the genetic risk factors of breast cancer – mutations in the BRCA genes.  Patients at higher risk for developing breast cancer because of these mutations can be monitored more closely or preventative action can be taken. In the past, breast cancer treatment focused on treated with non-specific chemotherapy and surgery. Although both of these treatments are still of value, now doctors also test for the presence of certain breast cancer genes like Her2.  If Her2 is present in breast cancer cell, the drug Herceptin that specifically targets this Her2 gene can be used to specifically kill those cancer cells. If Her2 isn’t present, this drug isn’t effective, causes negative side effects and wastes time and money when a more effective treatment could be used.  Once breast cancer is diagnosed, a patient would be interested in knowing how quickly their cancer will progress. This used to be primarily based on the stage of the cancer, where stage 4 cancers have spread to other locations in the body so the prognosis isn’t great. Based on molecular markers, scientists have now created panels of biomarkers (Oncotype DX and MammaPrint) that predict breast cancer recurrence after treatment.

These personalized medicine-based tests and drugs are incredible. However, this is a field that both holds considerable promise and requires lots of work to be done.  For every incredible targeted therapy developed, there are patients that are still waiting for the treatment for their disease or the genetic variant of their disease.  In future posts, I’ll talk a lot about both the promise and the pitfalls of personalized medicine.

If you want to learn more about personalized medicine, check out this YouTube video with a cartoon comparing treatment with and without the concept of personalized medicine.

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.

What is that? A pipette!

pipetteMost of the time, biologist in the lab aren’t working with things that they can see. You need to look at cell under a microscope, proteins using X-Ray crystallography (for example), and DNA and RNA by various methods like gel electrophoresis or cell staining (see more about visualizing DNA here).  Many experiments require scientists to manipulate DNARNA or proteins in small liquid volumes to do experiments to understand the sequence of these molecules, to discover what other molecules they bind to, or to change them to figure out how they work in cells. To manipulate these small volumes, we use a tool called a pipette (shown at left) – also called a micropipette to be even more precise. It’s similar in concept to the baster you have in your kitchen that sucks up liquid when basting your turkey, except it’s for much smaller volumes and is exquisitely precise.

Pipettes come in different sizes, and the size of the pmulti_size_pipettesipette determines the volume that they can dispense (see picture at right).  They dispense microliter (abbreviated as “ul”) volumes of liquid. To give you an idea of scale, 1 drop of water is about 50ul.  One milliliter (ml) is1000ul, which is the largest micropipette volume you can dispense, and there are about 44ml in a shot of vodka. These are small volumes we are talking about!!

The sizes shown to the right dispense up to 2ul (called a “p2”), 200ul (“p200”), or 1000ul (“p1000”). By spinning the plunger on the pipette, you can change the volume that is dispensed within the range that the pipette allows.  You then put disposable tip to the end of the pipette and suck up that volume of liquid. As an example, check out the photo below of the p1000 dispensing 600ul of water and the p200 dispensing 20ul of water.  The image to the left is the pipette tip filled with that volume and to the right is the water in a tube. This type of tube is used every day in the lab and is called an eppendorf tube. IT can hold 1.5ml (or 1500ul) of water. These small plastic tubes have attached caps that can snap the tube closed to allow you to mix the contents or do whatever is needed for the experiment (like heat it up, cool it down, spin the contents, etc). And if you’re wondering why they are called “eppendorf” tubes, it’s after the name of a German company called Eppendorf that is one manufacturer of this kind of tubes (similar to how the brand Kleenex is now synonymous with tissues)

pipette volumes

Maybe you’re wondering why scientists have to use such small volumes?  One reason is because there isn’t a large amount of DNA or RNA or proteins in cells, so when it’s isolated, it doesn’t take up a large volume. As an example, if you isolate the genomic DNA from  5 million cells, you would isolate 10-30ug  of DNA. That’s MICRO grams of DNA – or 0.00003 grams.  As comparison, a grain of salt weighs more than 1200x more than the amount of DNA that you would isolate from 5 million cells!  And this is all in just 50ul of liquid.  Very small amounts! The good news is that working in large volumes isn’t really needed because most experiments don’t need a large quantity of materials to get the answer. Not to mention that working with larger volumes for experiments would be more expensive.  If you are doing an enzymatic reaction, a larger volume reaction would require more enzyme.  To get an idea of what this would cost,  a very common reaction cuts DNA with restriction enzymes, which are essentially super-specific DNA scissors. These restriction enzymes cost several hundred dollars per tube and you use 0.5-1ul for every 50ul reaction.  If you did a reaction in a large test tube of 10ml, you’d need 200 times more enzyme and would go through hundreds or thousands of dollars if enzyme for each experiment.  Labs are not that rich!

Fortunately scientists have developed techniques and equipment, like the micropipette, that can manipulate, detect and analyze incredibly small amount of DNA or RNA or proteins. For most bench scientists, learning how to use a micropipette is done on day one (I learned how to use one in high school at City Lab) and pretty soon becomes second nature.  In grad school, I pipetted so much that there were days I’d go home with a sore thumb or pipetting  calluses. However all this practice did pay off.  I picked up a pipette for the first time in 8 years a few weeks ago to start doing experiments in my new lab. After all these years, it was just like riding a bike – or in this case just like “using a pipette”.

What is that? A beautiful image of deadly tumor cells

the eye

Thanks to Dr. Roberto Fiorelli of Barrow Neurological Institute for sharing this stunning image

It looks like an eye.  Perhaps a terrifying pink eye, like the Eye of Sauron, coming out of the darkness. It’s not an eye, but it is a bit terrifying. This is an image of a slice of the brain showing tumor cells (in green and red) surrounding a blood vessel.  How does this type of image get made?  How does this type of image help scientists? What does it mean that these tumor cells are near a blood vessel?

This image is created with a microscope – specifically a confocal microscope. I’m going to use a very weird analogy to explain why confocal microscopy is so cool, so stick with me. Imagine that you have a jello mold with an object it and you want to know exactly what the object looks like.  Now imagine a regular microscope is like a flashlight.  When you point the flashlight at the jello mold the whole thing lights up including what’s in front of the object, and if the object is translucent, the jello behind the object lights up too.  This gives you an idea of what the object is, but it may be kind of fuzzy because of all the jello you see in front and behind the object.  Confocal microscopy, on the other hand, is designed to turn that wide flashlight beam into a single pinpoint of light so only one part of the object is illuminated at a time.  So when you move this single pinpoint around (back and forth and up and down) over the object, you can get a clear a crisp image of what is inside the jello.

confocal_microscopy

To bring this analogy back into the science-verse, the jello is a cell or a piece of human tissue with layers of many cells.  The objects inside the jello are certain proteins marked so that they light up in different colors (what we call fluorescence) when excited by the light from the laser (flashlight). When confocal microscopy is used to look at these proteins, you can see clear crisp images of exactly where the proteins are in the cells.  And if you take enough images up and down through the cells and the tissue, you can even create a 3D image of the cell or a piece of tissue. Check out this neat video of a 3D rendering of a piece of the brain called the hippocampus.

Now back to the image above.  This is a piece of tissue taken from a patient with an ependymoma, a tumor derived from brain tissue and is primarily found in younger patients.  The colors you see are:

  1. Blue: a chemical called DAPI (or 4′,6-Diamidino-2-Phenylindole, Dihydrochloride) that binds to DNA. Since DNA is found in the nucleus of every cell, staining cells with DAPI helps you to locate each cell in the image – each blue dot is one cell.
  2. Red: stains a protein called GFAP (Glial Fibrillary Acidic Protein) that is found in different cells of the brain, but is also a marker of particular brain tumors, like ependymomas
  3. Green: stains a protein called vimentin that is also found in different cells of the brain, including cells that make up large blood vessels and brain tumors like ependoymomas

So what are we able to learn from this beautiful picture?  See how there are a lot of red and green cells surrounding an empty round space.  That round space is a blood vessel. Cancer cells need food and oxygen to grow, so the green and red cancer cells are clustering around the blood vessel to get the nutrients they need. Even though this is a beautiful image, it helps scientists to understand how these deadly tumors function within the brain and how they find the resources to grow.

If you want to look at more amazing images taken using confocal microscopy and fluorescently tagged proteins, check out these links

Wellcome Image Awards 2015
The Cell: An Image Library

Thanks to Dr. Roberto Fiorelli of Barrow Neurological Institute for sharing this stunning image from his postdoctoral work in Dr. Nadar Sanai’s Laboratory, the Barrow Brain Tumor Research Center

For more “What is That?”, click here.

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!

Can your body contain DNA that isn’t yours? Yes! Chimerism

There was a House episode (Season 3 Episode 2 Cane an Abel) about a young boy who was convinced that he was being probed by aliens.  Though a series of very House-like (aka “unrealistic”) medical twists and turns, House’s team finds cells clumped together in different parts of this boy’s body, including his brain, that are functioning abnormally and causing his various systems.  From sequencing the DNA from those cells, House’s team finds that those cells have different DNA than the boy’s.  In the fictional world of House, the doctors were able to quickly create a probe for the foreign DNA, find all the cells that were different and remove them (House does brain surgery!!) also removing the symptoms including the alien hallucinations. This episode is so wildly out of the realm of current medical ability and practice – so much so that I participated in a “Science Fiction TV Dinner”  all about the science and “science” found in this episode. You can watch highlight from this discussion, which included Dr. Kenneth Ramos from University of Arizona Center for Precision Medicine, below or listen to the whole podcast here.

Science Fiction TV Dinner: House M.D. from Science & the Imagination on Vimeo.

However, what I found most interesting about this episode was the fact that the boy had TWO DIFFERENT genomes in his body. Can this actually happen in real life?  If so, how??

chimera

“Chimera d’arezzo, fi, 04” by I, Sailko. Licensed under CC BY-SA 3.0 via Wikimedia Commons

The answer is yes, and it’s called a chimera or chimerism. In mythology, a chimera is a terrifying hybrid animal that’s a lion, with a goat head coming out of it’s back and a tail with a snakes head on the end. It may be clear that I’m a scientist since I’m sitting here wondering whether all three heads eat and if so, do they all connect to the same or different stomachs. But I digress…  In genetics, a chimera is an organism composed of two distinct sets of cells with two different sets of DNA. As you may remember from other discussions on this blog, DNA is the genetic material that provides the blueprint to make an organism.  DNA is also what is passed along to offspring, so that a child has 50% of the DNA from one parent and 50% of the DNA from the other (more about hereditary here). This is also why paternity tests work – if the child has 0% of DNA from the father, it’s clear that he isn’t the father,

So how in the world can a person have two different sets of DNA?  Especially since all people start off as one fertilized egg with one set of DNA instructions?  There are a few ways:

  • Organ transplants or stem cell transplants.  That organ or cells (more about stem cell transplants here) come from another person who has entirely different DNA from the transplant recipient.  So when a person gets an organ transplant, they become a chimera.  This is also true, at least temporarily, for people who have blood transfusions.
  • Are you a mother or a person who a mother gave birth to?  In that case, you might also be a chimera.  This is called fetomaternal microchimerism.  Mothers usually have a few cells identical to their children that stay in their body long term. This is often caused by immune cells being transferred back and forth between the mother and the placenta during development.   Even 22% of adults were found to still have blood cells from their mother! These cells are really difficult to find – in part because there usually isn’t any reason to look for them – but easier if the mother has a boy because then the chimeric cells contain a Y chromosome whereas the mother’s cells do not.
  • In vitro fertilization (IVF) also has the possibility of resulting in chimeric adults.  Since IVF often implants multiple fertilized eggs into the mother, there is an increased possibility of two fertilized eggs fusing – resulting in one developing human developing into an adult with two sets of DNA.
chimericperson

Illustration of a chimeric person from and awesome article about chimeras from the EMBO journal

Let’s talk about this last option a bit more because this is what House and Co. blamed as the cause of the child’s chimerism, but also because this is really interesting medically and socially.  There have been several noteworthy stories about  women who, for different reasons, were found to be chimeras.  Lydia Fairchild was looking for child support after a divorce, but when DNA tests to prove paternity were requested, it was found that the father was the father, but Lydia wasn’t the mother.  After numerous traumatic events, including being accusing of trying to commit fraud to obtain benefits and having the birth of her third child observed (to prove that she was that child’s mother, even though genetically it didn’t appear that the child was), Lydia was lucky.  Her lawyer heard about Karen Keegan, a women in need of a kidney transplant several years earlier, but when testing her three sons for compatibility, the tests indicated that only one was hers.  Only by looking at other cells in her body were doctors able to determine that her body contained two sets of DNA – one set was passed on to two of her boys and the other set was passed on the other.  Fortunately for Lydia, this discovery prompted DNA testing of members of Lydia’s extended family as well as other parts of Lydia’s body.  This testing showed that Lydia’s cervical cells matched her childrens’ and she was able to obtain child support. The media LOVED this. Just an example of the titles for news articles about Lydia and Karen:

However, besides the obvious media hype, chimerism has practical and legal implications. For example, in 2005, a cyclist Tyler Hamilton was charged with blood doping because they found another person’s blood mixed with his own.  He blamed this on chimerism (New York Times article here) where he had chimeric blood cells that had different DNA than the rest of his body.  He lost his case 2-1, but it brings up an interesting idea.  If everyone knows about chimerism – either through the popular media or TV shows like House – then this could lead to the “reverse CSI effect” where the jury is so aware of the possibility of chimerism that they discard all mismatched DNA evidence blaming it on chimerism.

Besides how strange this all seems, what’s even stranger is that more people are probably chimeras that scientists even realize. The only reason we know that Karen Keegan and Lydia Fairchild are chimeras is because scientists were forced to look at them more closely.  For the rest of us, we likely won’t need a transplant or have alien-probing hallucinations that induce scientists to look at many different parts in our body to see if the DNA is different.  And if more of us are chimeras, what does that mean? This is still something scientists will have to figure out.

Want to hear more about this amazing phenonemon? Check out  or this great article from the EMBO journalNPR’s RadioLab story Mix and Match featuring Karen Keegan’s story.