EpiGenie | Epigenetics, Stem Cell, and Synthetic Biology News http://epigenie.com Scientific News, Technology, and Product Information Wed, 26 Aug 2015 16:44:28 +0000 en-US hourly 1 http://wordpress.org/?v=4.2.4 UBER: Cross-Species, Drag-and-Drop Gene Circuits http://epigenie.com/uber-cross-species-drag-and-drop-gene-circuits/ http://epigenie.com/uber-cross-species-drag-and-drop-gene-circuits/#respond Wed, 26 Aug 2015 16:44:28 +0000 http://epigenie.com/?p=23969 There’s a bit of a dirty little secret in synthetic biology – gene circuits that work great in one species often require a lot of changes to work in anything else.  This is one reason so many synbio papers contain the same two key words: E. and coli.  Now, a new approach called UBER (Universal Bacterial Expression Resource) promises to make it a lot easier to get where you want to go in a strange new environment (no app yet, though).

The main problem in porting gene circuits between species is that expression levels change.  Different bugs express genes from different promoters and ribosome binding sites at different rates.  One solution is to use an orthogonal RNA polymerase, like that from the T7 phage, which recognizes a unique promoter.  Unfortunately, T7 RNAP at high levels can be toxic to cells.  

In their new UBER system, Manish Kushwaha and Howard Salis devised a set of coupled feedback loops to keep T7 RNAP at a desired level.  In the positive feedback loop, T7 RNAP produces itself from its own promoter, and in the negative feedback loop, it also transcribes tetR, which represses T7 RNAP production.  For translation, they designed a library of ribosome binding sites (RBSes) that should work similarly across species.


The UBER system for drag-and-drop gene circuits.  Image: Manish Kushwaha & Howard Salis

This feedback-controlled T7 RNAP was able to produce high GFP output while avoiding host toxicity.  When tested in three species (E. coli, P. putida, and B. subtilis), the system had a wide range of outputs, but at least different RBS variants had the same output rank from low to high in each species.

The team also did some rigorous modeling, and in an interesting side note, they found that competition for T7 RNAP among promoters has a big impact on output gene expression.  When tetR represses the T7 RNAP promoter, that frees up more RNAP to bind the output GFP promoter, resulting in more output even with less RNAP.

UBER is a good step toward making drag-and-drop gene circuits that work the same in any species you drop them into.  True, the output spread from B. subtilis to E. coli was ~5-10-fold for an identical circuit, but that’s not so bad, considering that the copy number varied from 1 chromosomal integration to 50 plasmids.  Gene expression can be adjusted with known libraries of T7 promoters and UBER’s universal RBS library, making it much easier to work with species that don’t have standard genetic parts.

Hail yourself an UBER over at Nature Communications, July 2015

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RiboT: Synthetic Ribosome Opens Door to Independent Genetic Codes http://epigenie.com/ribot-synthetic-ribosome-opens-door-to-independent-genetic-codes/ http://epigenie.com/ribot-synthetic-ribosome-opens-door-to-independent-genetic-codes/#respond Tue, 25 Aug 2015 18:13:34 +0000 http://epigenie.com/?p=23962 Synthetic biologists have made a lot of progress in developing “orthogonal” genetic systems.  DNA and RNA have been made with synthetic base pairs, and cells have been coaxed to produce proteins with synthetic amino acids.  This expands the genetic code beyond the standard letters used by life on Earth, which could potentially open up new functions.

It also helps us understand more about life itself.  Is there some deep reason why life uses only so many base pairs and amino acids?  Or did life on Earth land on this genetic system by luck?  Just how alien can life really be?

The Ribosome Problem

Despite the progress in exploring alternate genetic codes, one major sticking point has been the ribosome.  All life on Earth uses a two-part ribosome to translate mRNA into proteins.  We can change the small subunit to translate mRNAs with a different start signal, but to really expand the range of amino acids life can use, we would have to change the large subunit.

This is much more difficult because the two subunits are not monogamous; after making a baby protein they split apart and find another partner.  So if we tried to evolve new large subunits inside cells, they would have flings with native small subunits, they’d either get stuck or make broken protein babies, and the host cell would die.

RiboT: A Single-Subunit Ribosome

To get around this road block, Cedric Orelle and Erik Carlson, working in the labs of Michael Jewett and Alexander Manklin in Chicago, made RiboT – life’s first known single-subunit ribosome.  In a clever bit of rearranging, they connected the two main rRNAs with short tethers (hence the T), as seen to the left.  Amazingly, this unprecedented-in-the-history-of-life bio-machine was able to fully support the growth of E. coli (albeit, at half speed).

RiboT pities the fool who uses bipartite protein translation machines.

As proof of principle, the team also made an orthogonal RiboT that recognized an alternate ribosome binding site.  Even more intriguingly, they mutated the large subunit half of RiboT to read through an RNA sequence that stalls normal ribosomes, even though the mutation would be dominantly lethal in untethered ribosomes.

This work is cool just for showing, once again, that fundamental designs not found anywhere in nature can nevertheless support life.  But it also opens up brand new possibilities.  For example, we can now imagine cells with two completely orthogonal genetic codes operating side by side.  The standard system would be left alone to keep a cell alive while an “alien” code could produce enzymes with synthetic amino acids too big or unwieldy for the standard ribosome.

I pity the fool who doesn’t check out this paper, in Nature, August 2015

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ChIPmentation: The Next Fast and Low-Input ChIP-seq Sensation http://epigenie.com/chipmentation-the-next-fast-and-low-input-chip-seq-sensation/ http://epigenie.com/chipmentation-the-next-fast-and-low-input-chip-seq-sensation/#respond Tue, 25 Aug 2015 18:10:29 +0000 http://epigenie.com/?p=23957 ChIP-Seq is the bread and butter of histone and transcription factor research. It has seen countless modifications to allow it to perform under all the variables biology can throw at it, but with that specialization has come limitations to generalization.

Now the methodological maestros in the lab of Christoph Bock, which brought us single-cell methylome sequencing, have created an all purpose ChIP-Seq method that can handle all the challenges thrown at it.

This new method, called ChIPmentation takes advantage of tn5 transposase library prep. This ChIP-Seq library prep technique has been used to create the assay for transposase-accessible chromatin using sequencing (ATAC-seq), which has allowed for the indirect study of open chromatin but has not yet been applied to directly study histone modifications and transcription factors.

Co-first author Christian Schmidl shares, “We first tried to tagment the purified ChIP-DNA, but we found it difficult to set up robust tagmentation reactions with the low and very variable amounts of fragmented DNA recovered by ChIP. The trick is not to purify the DNA from the ChIP assay for tagmentation-based library preparation, but to tagment the chromatin during the immunoprecipitation step while still bound to the antibody and magnetic beads.”

The advantages behind a transposase library prep for ChIP-Seq are:

  • Fragmented and immunoprecipitated chromatin, instead of the standard purified (protein free) immunoprecipitated DNA, has the sequencing compatible adapters tagged on.
  • There are no sequencing adapter dimers.
  • A much lower input of DNA is required for library prep, thus enabling the study of rare cell types.
  • It requires only a single downstream purification before library amplification.
  • The process is quicker than ‘Greased Lightning’.

Since the tagmentation is done on the immunoprecipitated and bead bound chromatin, the chromatin proteins appear to prevent extensive tagmentation. The team then used ChIPmentation across a 25-fold difference in tranposase concentrations to assess performance by examining:

  • Size distribution of ChIPmentation libraries.
  • Size distribution inferred from paired-end sequencing reads.
  • Read-mapping performance.
  • Concordance between sequencing profiles and signal correlations.

Using these metrics ChIPmentation was applied to study five histone mods (H3K4me1, H3K4me3, H3K27ac, H3K27me3, and H3K36me3) and four transcription factors (CTCF, GATA1, PU.1 and REST). When compared to standard ChIP-Seq it was found that:

  • The ChIPmentation profiles were concordant with ChIP-Seq and biological replicates.
  • There was a large reduction in the number of cells required, with the histones marks (H3K4me3 &HK27me3) generally needing 10,000 cells and 100, 000 cells for transcription factors (CTCF and GATA1).
  • Just like standard ChIP-seq the outcome is dependent on antibody quality.
  • It doesn’t require optimization of the tagementation for the different antibody optimized protocols, making it easy to ‘tag on’ to existing protocols.

The data also correlated with ATAC-seq and DNase-seq profiles after bioinformatic correction for the inherit biases of transposase. Once they fixed that all up they were able to match up the transcription factor footprints and also made some new observations on GATA1 and PU.1. Finally, they found that the average distance between tagmentation events was ~10bp, suggesting that nucleosome occupancy may be able to be inferred.

Future Applications: Transcription Factor Footprints and High Res Nucleosome Maps

The group shares that “Transcription factor (TF) footprinting can be used to understand high-resolution interactions of TFs with DNA beyond just describing a binding event. In addition, techniques that probe accessible chromatin including DNase-seq and ATAC-seq can infer factor binding without actually immunoprecipitating the factor. They do so by assessing regions that are protected from reactions (DNase digestion or transposase insertion in DNase-seq and ATAC-seq, respectively), creating an impression of the TF presence — a “footprint”.”

“Since ChIPmentation also uses a tagmentation reaction and this is performed on chromatin with DNA-binding proteins still in it, we have seen patterns that resemble footprints from TFs on ChIPmentation data from TFs. Furthermore, we hypothesise that an additional utility of TF footprint detection in ChIPmentation data will be the ability to distinguish real TF binding from indirect binding, which cannot be detected solely by ChIP.

“In a recent publication by the Greenleaf lab at Stanford it is shown that ATAC-seq generates a highly structured pattern of DNA fragment lengths and positions around nucleosomes. The correlation of this pattern with the ATAC-seq signal, along with elegant bias correction and background modeling allowed them to detect “nucleosome-bound” and “nucleosome-free” regions, inferring nucleosome positions with high precision.”

“ChIPmentation data from histones is different from ATAC-seq in that the majority of signal is depleted of the “nucleosome-free” signal, due to the enrichment of the histone mark by the ChIP procedure. We are interested in pursuing methods to model the ChIPmentation signal around nucleosomes, integrating bias and background correction, procedures which will be also useful for the more accurate detection of TF footprints. If it works, we would be able to position nucleosomes with high precision in all regions that are precipitated with a histone mark of choice

Co-first author André Rendeiro shares that “We are working on computational methods to better understand the biological relevance of these high-resolution patterns obtained by ChIPmentation. The usefulness of the high resolution patterns is under investigation at the moment, and it is highly dependent on good background model for the inherent Tn5 sequence bias.”

The authors elaborate that “The combination of various data from several histone marks on the same cells could greatly expand the amount of positioned nucleosomes and allow to tag each with the modifications it contains, generating a more complete chromatin map. Additionally, a great advantage is that regions typically beyond the reach of ATAC-seq (repressed chromatin and gene bodies) would still be profiled. This information would again, come along “for free” with ChIPmentation in addition to a normal ChIP-seq readout.”

The Clinical Potential of ChIPmentation

Bock concludes that “The protocol opens the possibility to analyse patient samples on a clinical timescale. With the current protocol it would take around 3 days from blood draw to analysed data, and we are working at an even faster version of ChIPmentation at the moment. Hence, we reach the timeframe to use personalized epigenomics to support clinical decision making, *e.g* by profiling the regulatory landscapes of patient cells and how they react to a certain drug. An advancement from the clinical perspective is the fact that ChIPmentation has relatively low input requirements, and could therefore be used to profile rare cell populations or minimize invasiveness to get material for personalized epigenomes.”

Go check out the detailed protocol with interactive browser tracks and the paper in Nature Methods, August 2015

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Two Cocktails to Boost Reprogramming to Neurons http://epigenie.com/two-cocktails-to-boost-reprogramming-to-neurons/ http://epigenie.com/two-cocktails-to-boost-reprogramming-to-neurons/#respond Mon, 17 Aug 2015 19:23:38 +0000 http://epigenie.com/?p=23937 Trendy drinks come and go, but it looks like there are a couple of new cocktails that will have some staying power within the stem cell community. In last week’s issue of Cell Stem Cell, two independent groups report in back-to-back papers the development of small molecule chemical cocktails, which enable neurons to be directly derived from skin fibroblasts by “just” soaking them in the drug cocktail and without going through an intermediate pluripotent step.

While you won’t find these cocktails in your average hotel bar anytime soon, these small molecule cocktails could represent a significant step forward in the induction and use of reprogrammed cells in vivo and their possible therapeutic applications.

In the first paper, a group led by Dr. Hongkui Deng from the Peking University used a chemical screen for small molecules promoting Ascl1-based reprogramming of mouse fibroblasts to neurons.

Here’s what they found:

  • A combination of four molecules (Forskolin; ISX9; CHIR99021, a GSK3 beta inhibitor, and I-BET151), which they called FICB, induced the reprogramming of a whooping 90% of fibroblasts into neurons.
  • FICB-induced cells, termed chemically induced neurons (CiNs), showed electrophysiological properties characteristic of functional neurons.
  • As 80% of the induced immature neurons failed to incorporate the DNA replication marker BrdU, the authors concluded that cell fate reprogramming bypassed an intermediate proliferative stage.

In the second paper, scientists led by Dr. Gang Pei from The Chinese Academy of Sciences in Shanghai, used their previously described small molecule cocktail VCR (valproic acid; CHIR99021 and Repsox) to manipulate the cell fate of adult human foreskin fibroblasts and convert them into neurons.

Here’s what they found:

  • By itself, VCR had no effect on neuronal differentiation, but the addition of forskolin and other compounds known to induce neuronal differentiation such as SP600125 (JNK inhibitor), GO6983 (PKC inhibitor) and Y-27632 (ROCK inhibitor), made a potent seven-component cocktail, VCRFSGY, which induced neuronal conversion 7 days after incubation.
  • Hallmark genes of neuroprogenitor cell fate, such as Sox2, Pax6, FoxG1 or nestin were never expressed in the chemically-induced cells, suggesting that the VCRFSGY cocktail induces the direct conversion of fibroblasts into neurons.
  • The physiological properties of the human CiNs resembled those previously seen in neurons derived from iPSCs and neurons directly induced from fibroblasts by the expression of exogenous transcription factors (TF-iNs).
  • Human CiNs from familial Alzheimer’s patients displayed similar neuronal characteristics but exhibit abnormal amyloid beta protein production, suggesting CiNS can be used to model neurological disorders.

There are interesting similarities between the two papers. Both cocktail recipes use forskolin to increase cyclic AMP levels and CHIR99021 to inhibit GSK3 beta activity, suggesting these cocktails work via common mechanisms. In both studies, fibroblast genes were downregulated and neuronal genes were upregulated during reprogramming, although the exact genes differ between the two studies.

So, next time you need some neurons for your disease model, remember to ask for your favorite cocktail…but shaken, not stirred.

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New Insights into Puzzling Placental DNA Methylation Domains http://epigenie.com/puzzling-placental-dna-methylation-domains/ http://epigenie.com/puzzling-placental-dna-methylation-domains/#respond Fri, 14 Aug 2015 17:42:57 +0000 http://epigenie.com/?p=23931 The human placental methylome was the first normal tissue where partially methylated domains (PMDs) were characterized, found to be developmentally dynamic, and distinct from highly methylated domains (HMDs, methylation >70%).

PMDs are a large scale genomic feature with DNA methylation levels that are less than 70% but nowhere near 0% and tend to harbour neuron specific genes. In human placenta, PMDs and HMDs are distinct large scale domains that show a bimodal distribution and can cover entire gene clusters. However, the evolutionary origins of such a large scale epigenomic feature in humans has remained a mystery.

Diane Schroeder of the LaSalle lab at UC Davis led an interesting study recently shedding some light on DNA methylation in the placenta. According to Schroeder, “In human placenta, genes within PMDs are repressed. It’s still unknown whether partial methylation plays a part in the gene repression or whether partial methylation is, for example, a side effect of chromatin inaccessibility. However, for this study we had hoped to use PMDs to trace the evolution of gene regulation in mammalian placentas.”

In order to crack this evolutionary mystery the team used MethylC-seq to analyze the placentas of a number of mammals (human, rhesus macaque, squirrel monkey, mouse, dog, horse, and cow) as well as a marsupial (opossum) extraembryonic membrane (EEM).

Here’s what they found:

  • Mammalian placentas and EEM show lower global methylation than somatic tissues, just like in humans.
  • Evolution threw a curveball and there was no discrete bimodal distribution of PMDs and HMDs in the placentas of many species.
  • Global methylation showed no correlation to evolutionary relationship.
  • Adjusting to the funky pitches of evolution, the team found that high methylation over gene bodies, particularly expressed ones, was a conserved feature across all species that can be used to predict the location of genes.
  • This methylation was typically over single genes and not gene clusters, just like in non-human placentas with PMDs/HMDs.
  • Shedding light on the evolutionary origin of placentas in mammals, it was found that the EEM also has low global methylation and high methylation levels in gene bodies.
  • Intriguingly, oocytes and preimplantation embryos shared this pattern.


Schroeder shares her surprise that, “the PMD story turned out to be much more complicated because although all placentas had hypomethylation, not all had a clear delineation between PMDs and HMDs like the human placenta had. Intriguingly, though, all species had higher methylation over the gene bodies of a specific subset of genes. Those genes also had higher expression in the placentas. But what was really exciting was seeing those same genes have both higher gene body methylation and higher expression in oocytes and early embryos as well. This suggests that placenta retains a small signature of the regulatory program that was set up very early in development.”


LaSalle concludes, “Understanding the methylation rules in early life is important for future studies in identifying epigenetic biomarkers in placenta (an accessible tissue usually discarded at birth) and in cancer, where the methylome is more similar to placenta than normal somatic tissues.”


Get the full digest of placenta over at PLOS Genetics, August 2015

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Phage Therapy: Synthetic Biology Goes Viral http://epigenie.com/phage-therapy-synthetic-biology-goes-viral/ http://epigenie.com/phage-therapy-synthetic-biology-goes-viral/#respond Wed, 12 Aug 2015 19:22:15 +0000 http://epigenie.com/?p=23917 Viruses have long been maligned as worthless, pseudo-alive parasites, but treatment for antibiotic-resistant infections may be about to go viral.  No, we don’t mean cats taking medicine on video (although…).  No, this is phage therapy.

Phages are viruses that infect bacteria, and research into using them to treat bacterial infections goes back decades, especially in the former Soviet states.  Phage therapy never made it very far in the West though; apparently the iron curtain had a sub-micron pore size.

But with antibiotics losing their punch, drug-resistant bacteria have aroused renewed interest in phages.  Phages can be counter-evolved as bacteria develop resistance, and their specificity means they won’t cluster-bomb the gut microbiome, like some antibiotics.

Two papers on the subject recently caught our eyes for their novel approaches.  One used non-replicating “phagemids” to avoid safety issues, and the other aimed to remove resistance genes from resident hospital bacteria.

Phagemids for Safer Phage Therapy

One of the main concerns with phage therapy is safety.  For one thing, the idea of releasing self-replicating viruses into a patient can make people queasy.  For another, when phages lyse bacteria, they release endotoxins that can cause collateral damage.

To get around the replication issue, Russell Krom in Jim Collins’ lab in Boston used a two-plasmid helper system to produce phages.  The first helper plasmid expresses all the necessary phage genes, while the second payload plasmid gets packaged into the phage.  Since the payload plasmid doesn’t have the phage genes, it can’t produce more phages in the wild.  As a second bonus, eliminating phage genes from the payload also avoided superinfection exclusion, in which virus-infected bacteria are resistant to repeated infection.

To avoid lysing targeted bacteria, the researchers found toxin genes that would kill infected cells without lysing them.  In mice, the phagemid system successfully treated peritonitis, and in vitro, it was much better than phages at avoiding bacterial resistance.

Phage to Purge Resistance Genes from Hospitals

In a completely different approach, Ido Yosef and Miriam Manor in Udi Qimron’s lab aimed to treat the hospital instead of the patient.  Many hospital infections come from bacteria that escape cleaning and then make their way into vulnerable patients.  Because hospitals use antibiotics so often, their residential microbes have been selected for antibiotic resistance.

Phage therapy could eliminate resistance genes by delivering CRISPR cassettes that target those genes, but combining this with antibiotics will always promote “escape” mutants that remain resistant.  To avoid this, these researchers propose a two-step method.

First, lysogenic (genomically integrating) phages would deliver a CRISPR cassette targeting resistance genes.  Next, antibiotic-sensitive bacteria would be selected by infecting with lytic (killer) phages with the same short sequence targeted by the CRISPR payload.  CRISPR would chop up resistance genes (and the lytic phage) in lysogenized bacteria, while non-lysogenized bacteria would be killed by the lytic phage.

The idea here is that it’s impossible to eliminate all bacteria from hospitals, so we may as well make them antibiotic-susceptible.  Then when infections do occur, they can easily be treated.  Similar to how a healthy gut microbiome can prevent bad bacteria from taking over, maybe we can make the hospital microbiome “healthy”, or at least less threatening.

The authors envision this targeted selection step being used in sprays and hand soaps alongside traditional disinfection and cleaning.  The idea is definitely cool, but if bad bacteria somehow escape normal cleaning, it’s not clear if the combo-phage spray would get to them any better.  We’ll keep a spare spray can around just in case.

Let’s help these papers go viral!  Here are the links:

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Epigenetics Drives Genetics Straight Into Evolution http://epigenie.com/epigenetics-drives-genetics-straight-into-evolution-2/ http://epigenie.com/epigenetics-drives-genetics-straight-into-evolution-2/#respond Sun, 09 Aug 2015 19:52:13 +0000 http://epigenie.com/?p=23884 In today’s fast-paced world, quickly adapting to your environment is a game-changer. But genetic determinism cannot fully explain the rapid adaption seen in many species, which has left evolution in a dark age.

That is until the enlightening work of Michael Skinner’s laboratory at Washington State University. Their observations on transgenerational epigenetic inheritance have been turning classical evolutionary theory upside down ever since they provided a much needed explanation for why genetics alone cannot explain molecular inheritance.

Since then there’s been a lot of controversy about who’s taking who along for the ride. Some folk have stuck to genetic determinism, swearing that sequence alone drives epigenetic marks.  Now Skinner’s second paradigm shift puts the nail in the coffin and synthesizes Darwinian and Lamarckian evolutionary theory by showing that alterations to DNA methylation resulting from environmental factors promote the generation of CNVs across generations.

Here’s what the pioneering team found in the sperm of rats with MeDIP-CHIP after exposing them to vinclozolin and comparing them with matched controls:

  • The first generation had not only altered DNAm but also a minimal amount of CNVs that were within the range of natural biological variation.
  • In the third generation, the CNVs occurred with a whopping 13 times higher frequency than in the first generation.
  • These CNVs cluster into distinct regions that contain both gains and losses and the epimutations were mainly in CpG deserts and not promoters.
  • Surprisingly, none of the CNVs and epimuations overlapped and very few were close together, suggesting that these are intergenic regulatory regions or that genetic mutations result in the removal of epimutations.

Living by his motto, “If you are not doing something controversial, you are not doing something important”, Skinner shares that the next steps are to “repeat this with other types of genetic mutations being examined, and with different environmental toxicants.”

This leaves Skinner concluding that “There’s not a type of genetic mutation known that’s not potentially influenced by environmental epigenetic effects.”

Go get your evolutionary paradigm shift on at Epigenetics, August 2015

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Hacking the Microbiome: Bacteria Advance Therapeutics and Diagnostics http://epigenie.com/hacking-the-microbiome-bacteria-advance-therapeutics-and-diagnostics/ http://epigenie.com/hacking-the-microbiome-bacteria-advance-therapeutics-and-diagnostics/#respond Wed, 05 Aug 2015 17:15:00 +0000 http://epigenie.com/?p=23876 Commensal bacteria have long had branding issues.  First there was an awareness problem – “Wait, these things are inside us?”  Then there was an image problem – “Germs! Bad! Kill!”  They even had a Pluto moment, when it turned out a whole bunch of them weren’t even bacteria at all.

Despite these difficulties, the word “probiotic” has helped the bacterial brand tremendously through its association with the deliciousness of yogurt and cheese.  Since we now realize how beneficial bacteria can be, scientists have been wondering if we can make them even better by mixing the right species or designing them to treat particular diseases.

Recent work has shown that transplanting a healthy microbiome (don’t ask) can help treat inflammatory bowel diseases, as can bacteria engineered to secrete anti-inflammatory molecules.  Bacteria have also been engineered to treat autoimmune disorders, cancers, infections, and even obesity.

We here at EpiGenie have seen a batch of cool microbiome-hacking papers come through recently, and we wanted to give a quick run-down.


Yogurt-Based Cancer Screening

It turns out that bacteria tend to colonize tumors.  Noting this, lead authors Tal Danino and Arthur Prindle at UCSD and MIT modified a common probiotic, E. coli Nissle, to express the reporter genes luciferase and lacZ, and then fed it to mice.  The luciferase signal showed that the bacteria specifically colonized liver tumors in the mice but left healthy tissue alone.

In the clever bit, they then fed the mice harmless molecules that are easily detected when cleaved by lacZ.  When mice had liver tumors, they were colonized by lacZ-expressing probiotics, which converted test molecules into detectable signals that were excreted in urine.  So for these mice, at least, cancer screening was as easy as take two and call me if your pee changes color.

Selecting a Designer Microbiome to Treat Hyperammonemia

Another liver-related problem occurs when the liver fails to remove ammonia from the blood.  Most ammonia is produced by gut bacteria breaking down urea, but not all bacteria have urease genes, so another pair of lead authors, Ting-Chin David Shen and Lindsey Albenberg at U. Penn, found a low-urease community of 8 species and tried transplanting them into liver-damaged mice.

This new low-urease microbiome helped the mice keep their ammonia levels low, thus extending their lifespans and avoiding the brain damage usually caused by hyperammonemia. Interestingly, this protection lasted several months to a year, even though the new community evolved over time.

Programmed Bacteria Reprogram Intestinal Cells, Treating Diabetes

Moving away from the liver just a bit,  the focus for Franklin Duan in the lab of John March at Cornell was type 1 diabetes, which  is caused when insulin-secreting cells in the pancreas die off.  A potential treatment was found when it was discovered that intestinal cells, even though not in the pancreas, can differentiate into insulin-secreting cells if they are exposed to GLP-1.  The catch is, GLP-1 only sticks around in the body for a few minutes, making it nearly impossible to give the target cells a high enough dose.

Unless, that is, we had some source that would hang out in the intestine and provide a continuous stream of GLP-1 in just the right place… oh, wait, bacteria!  This lab had previously made GLP-1-secreting Lactobacillus gasseri and shown that they could induce differentiation in a cultured cell line.  In the new paper, they fed the engineered Lactobacilli to diabetic rats.  The probiotic-fed rats still had defective pancreases, but they regained the ability to produce insulin – just from their intestines instead.


Check out these papers (and a review, as a bonus) over a big bowl of yogurt and a fizzy glass of kombucha at:


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Lights Out! Sleep Loss Affects DNA Methylation of Circadian Genes http://epigenie.com/lights-out-sleep-loss-affects-dna-methylation-of-circadian-genes/ http://epigenie.com/lights-out-sleep-loss-affects-dna-methylation-of-circadian-genes/#respond Tue, 04 Aug 2015 22:43:23 +0000 http://epigenie.com/?p=23870  

‘La nuit blanche’. No, it is not a delicious pastry. It’s the French expression for staying up all night and not going to bed until the next evening, which in most cases will leave you pretty irritable. But losing one night’s sleep may affect more than just your mood; a new study by Swedish researchers shows that it also influences the methylation of your genes.

Our metabolism is fine-tuned to ensure that it operates according to our energy needs, i.e., high during the day and low at night. Controlling this is our internal time-keeping mechanism, the circadian clock, in which environmental cues control the rhythmic expression of clock genes that in turn regulate metabolism and behavior.

Disruption of these genes in animals has pretty profound effects on metabolism; they become obese and develop insulin resistance leading to type II diabetes.

People doing shift work or suffering from sleep deprivation may also experience metabolic alterations. However, the effect that sleep loss has at the molecular level in tissues involved in metabolism is still largely unknown in humans.

In their study, Cedernaes and colleagues looked at how one night of sleep deprivation influenced the methylation and expression of core circadian clock genes. They recruited 15 healthy male volunteers prepared to endure two biopsies from their thigh muscle and superficial stomach fat in the name of science: one after a full night’s sleep and another after a night without sleep.

  • Using a methylation array to examine DNA methylation levels in the regulatory sequences of clock genes, they found that methylation at PER1 and CRY1 increased in adipose tissue after sleep deprivation.
  • Sleep deprivation also decreased the abundance of BMAL1 and CRY1 mRNA in skeletal muscle and impaired glucose responses as assessed by an oral glucose tolerance test.

Lead author Cedernaes says, “as far as we know, we are the first to directly show that epigenetic changes can occur after sleep loss in humans, but also in these important tissues. It was interesting that the methylation of these genes was altered so quickly, and that it could occur for these metabolically important clock genes”.


For some bedtime reading, head over to the Journal of Clinical Endocrinology and Metabolism, July 2015.

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Wanted: Serially-Offending Epigenetic Enzymes Implicated In Cancer http://epigenie.com/wanted-serially-offending-epigenetic-enzymes-implicated-in-cancer/ http://epigenie.com/wanted-serially-offending-epigenetic-enzymes-implicated-in-cancer/#respond Tue, 04 Aug 2015 22:20:58 +0000 http://epigenie.com/?p=23866 Epigenetic enzymes are among the prime suspects in the identity parade of genes responsible for the deregulation of the genome in cancer. But are the same epigenetic enzymes always found at the scene of the crime? A new analysis from a team of international researchers led by Andrew Teschendorff identifies three epigenetic enzymes that can only be described as serial offenders in the pathogenesis of cancer.

The deregulation of epigenetic enzymes in cancer leads to alterations in chromatin configuration, DNA methylation, and gene expression and helps cancers to evolve more quickly, promoting invasion and metastasis. Pharmacologically targeting these enzymes is possible, so finding the most important oncogenic or tumor suppressor enzymes has major implications for cancer therapy.

Teschendorff’s team examined the expression of 212 epigenetic enzymes, including all the main writers, readers, and editors of the epigenome using RNA-Seq data from 10 different types of cancer from The Cancer Genome Atlas. They also analyzed DNA methylome data from these cancers to pinpoint the epigenetic enzymes responsible for wreaking havoc on patterns of methylation.

  • The study demonstrated the deregulated expression of 62 epigenetic enzymes (37 upregulated and 25 downregulated) in at least 8 out of the 10 cancer types studied.
  • The analysis of global hypermethylation and hypomethylation in the cancers found that the two were not well correlated, suggesting that they are independent processes in tumor progression under the control of separate epigenetic enzymes.
  • The study also found a link between 18 epigenetic enzymes and instability in DNA methylation across cancer types.
  • Network modeling identified UHRF1 and WHSC1 as the criminal masterminds in DNA hypermethylation, and the loss of CBX7 as a key driver of hypomethylation.

Intriguingly, the deregulation of these genes appears to affect methylation at the same loci across different cancer types, showing that these enzymes leave a characteristic signature at the scene of the crime.

The authors conclude, “These findings show that there are universal patterns of epigenomic deregulation that transcend cancer types”.


Read the full case file at Genome Biology, July 2015.

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