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The hottest technique in gene editing, called CRISPR, could soon be used to study human embryos. On 14 January, a regulatory committee in the United Kingdom will evaluate a request to knock out development genes in day-old embryos. In a press conference today, Kathy Niakan, a researcher at the Francis Crick Institute in London, discussed the rationale behind her proposed project and the hope that this line of inquiry might one day improve treatments for infertility.

Niakan studies how the single cell of a fertilized egg turns into a blastocyst, the approximately 5-day-old structure that subsequently implants in the mother’s uterus. The blastocyst contains several types of cells. Those destined to become the fetus are called epiblast progenitor cells. They are surrounded by two other types of cells, which become the placenta and another structure, the yolk sac. Niakan’s research uses human embryos, created in fertility clinics, that are left over from in vitro fertilization attempts and donated for research. After being studied, the embryos are destroyed when they are 7 days old.

Researchers have already identified several thousand genes that are active in the early embryo. To find out what these genes do, and which ones are master regulators of development, researchers have several approaches, including deactivating embryonic genes in mice. But only one group of researchers, in Guangzhou, China, has published a paper describing attempts to use this technique in human embryos.

This past September, when Niakan applied to the U.K.’s Human Fertilisation and Embryology Authority (HFEA) for a renewal of her license to conduct research on human embryos ,  she proposed to extend her work to include CRISPR editing. She hopes CRISPR will reduce the number of embryos required for her research, she said at the press conference; in several organisms, CRISPR has been shown to have higher efficiency compared with other approaches. Niakan believes her team would able to successfully edit up to 8 out of 10 embryos using CRISPR. “If we start off with good quality zygotes, this is likely to work efficiently,” she said.

As a pilot project, Niakan plans to knock out OCT4, a gene that is turned on in embryonic stem cells in both humans and mice. Researchers think that OCT4 is important for pluripotent cells, which can ultimately become any type of tissue. A way to test this idea is to knock out the gene when the embryo is 1 day old and still a single cell. The prediction, based on studies in mice, is that human embryos will continue to develop, but without pluripotent cells.

Niakan will then look at less-well-known genes that may be crucial for early development of human embryos. Unlike OCT4, these genes can only be studied in human embryos because they are not expressed the same way, or at all, in mouse embryos or immortalized lines of human stem cells, says her colleague Robin Lovell-Badge, also at the Crick Institute. The application contains a request to further study two or three such genes, Niakan said, depending on how many embryos will be available. The research would likely require 20 to 30 embryos per gene.

Niakan did not express any opinions at the press conference about the merits or dangers of one day using CRISPR or other techniques for gene therapy of infertility. “At the moment it’s very important to continue the ethical discussions,” she said. But after several questions about potential outcomes of such early research, Niakan did “wildly speculate” that, if certain genes are found to be particularly important for development, one eventual approach might be to check during IVF whether eggs were making the proteins encoded by those genes, and if not, then add them to culture media. But the immediate goal of the research is far more basic: Understand what genes do in blastocysts.

If the HFEA approves the application, Niakan hopes to start research within months. The project would also need to be approved by the U.K. equivalent of an institutional review board.

In a statement about the application, Hugh Whittall, director of the Nuffield Council on Bioethics in London noted: “The changes to DNA made for the purposes of this research could not themselves be used as part of a treatment procedure. There are, however, possible future scenarios in which a modification made in a research context—for example to correct a disease-causing genetic mutation—could, if this were to become permissible, be used in a treatment that would result in the birth of a child.  Such research, which could also be licensed under current legislation, would raise a number of significant questions that should be addressed before any such work is undertaken, including about whether, and under what circumstances, a move into treatment (which would require new legislation to be permissible in the U.K.) could be desirable.”  

Bay Area biologist's gene-editing kit lets do-it-yourselfers play God at the kitchen table

Gold nanoparticles have unusual optical, electronic, and chemical properties. But the tiny particles are much more interesting when they are closer to each other—either in small clusters or as crystals made up of millions of them.

Yet particles that are just millionths of an inch in size are too small to be manipulated by conventional lab tools, so a major challenge has been finding ways to assemble these bits of gold while controlling the three-dimensional shape of their arrangement.

One approach that researchers have developed has been to use tiny structures made from synthetic strands of DNA to help organize nanoparticles. Since DNA strands are programmed to pair with other strands in certain patterns, scientists have attached individual strands of DNA to gold particle surfaces to create a variety of assemblies.

[STUFF IN STYROFOAM MAKES NANOCOMPOSITES REALLY TOUGH]

But these hybrid gold-DNA nanostructures are intricate and expensive to generate, limiting their potential for use in practical materials. The process is similar, in a sense, to producing books by hand.

Enter the nanoparticle equivalent of the printing press.

It’s efficient, re-usable, and carries more information than previously possible. In results reported in Nature Chemistry, researchers from McGill University outline a procedure for making a DNA structure with a specific pattern of strands coming out of it; at the end of each strand is a chemical “sticky patch.”

HOW IT WORKS
When a gold nanoparticle is brought into contact to the DNA nanostructure, it sticks to the patches. The scientists then dissolve the assembly in distilled water, separating the DNA nanostructure into its component strands and leaving behind the DNA imprint on the gold nanoparticle.

Circadian clocks are oscillatory systems that allow organisms to anticipate rhythmic changes in the environment. Several studies have shown that circadian clocks are connected to metabolism, but it is not generally clear whether metabolic signaling is one voice among many that influence the clock or whether metabolic cycling is the major clock synchronizer. To address this question in cyanobacteria, we used a synthetic biology approach to make normally autotrophic cells capable of growth on exogenous sugar. This allowed us to manipulate metabolism independently from light and dark. We found that feeding sugar to cultures blocked the clock-resetting effect of a dark pulse. Furthermore, in the absence of light, the clock efficiently synchronizes to metabolic cycles driven by rhythmic feeding. We conclude that metabolic activity, independent of its source, is the primary clock driver in cyanobacteria.

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Learn about science's new dna origami and art of folding to transform raw materials into dynamic three-dimensional objects. Instead of paper, it's DNA.

By Aakriti Jain

Dr. Dan Nicholson is first a scientist, a molecular biologist. However, unlike most researchers in the constantly changing and expanding field of biology, Dan questions the very directions fields like synthetic biology are taking us. With his PhD in Philosophy, Dan’s research now is centered around understanding how machine models can explain biology. I had a Q&A with Dan on his publications on the machine conception of organisms to gain some interesting insights on the direction of biological research today:

Aakriti: Before getting into the meat of things, I’m interested in understanding how you got interested in this topic? Could you give me a brief description of your background and what events led you to start thinking and researching on the similarities and differences between organisms and machines? How did you come up with your specific conclusions?

Dan: My background is in molecular biology. However, I quickly became disenchanted with the mindless minutiae of actual biological practice (that is, with the tediousness and monotony of experimental research) and so I reoriented my efforts away from doing biology and towards thinking about biology. In practical terms, this meant switching my career from molecular biology to the history and philosophy of science. Then, when I began to examine the historical development of philosophical debates regarding the nature of life (‘life’ understood here not in the waffly philosophical sense but as a strictly biological phenomenon) l discovered that the organism-machine analogy lied at the very heart of the matter. What a past biological thinker may have supposed about the nature of life or about the relation of biology to physics derived more or less directly from his stance on whether he took organisms to be mechanical in nature, or whether he thought this to be a dangerously misleading characterization. And its importance is not simply a matter for historians of science. Machine analogies are everywhere in biology today! Molecular biologists speak of protein complexes as ‘molecular machines’; developmental biologists speak of the unfolding of development as the execution of a ‘program’ encoded in the genome; and evolutionary biologists refer to natural selection as an engineer and to adaptations as products of design. So it is very much a current issue in contemporary biology, even if this is not always appreciated.

Aakriti: In your papers, one of your main arguments against the machine conception of organisms (MCO) is that an organism is intrinsically purposive whereas machines are extrinsically so. Why do you conclude this? Could one argue that an organism itself doesn’t care about itself, it is only deluded into believing that it does, but that it actually serves a larger purpose (such as, procreating and passing down it’s genetic material, and furthering its species)? Or have I misconstrued what you mean by intrinsically purposive?

Dan: The intrinsic vs. extrinsic purposiveness distinction is meant to encapsulate most (if not all) the major differences between organisms and machines by appealing to what prima facie appears to be their most obvious similarity, namely the fact that they operate towards the attainment of particular ends. However, the key point is that they do so in fundamentally different respects. A machine is extrinsically purposive in the sense that it works/functions towards an end that is external to itself; that is, it does not serve its own interests but those of its maker or user. An organism, on the other hand, is intrinsically purposive in the sense that its activities are directed towards the maintenance of its own organization; that is, it acts on its own behalf. The intrinsic purposiveness of organisms is grounded on the fact that they are self-organizing, self-producing, self-maintaining, and self-regenerating systems. Conversely, the extrinsic purposiveness of machines is grounded on the fact that they are organized, assembled, maintained, and repaired by external agents. An organism maintains its integrity and autonomy as a whole by regulating, repairing, and regenerating its parts, whereas a machine relies on outside intervention not just for its construction and assembly, but also for its maintenance and repair. I take this to be a crucial and very general difference, which underlies why talk of design is appropriate when discussing machines but not organisms, why reductionism suffices as an explanatory strategy in the context of machines but not organisms, and why we speak of machines that malfunction in ways that we don’t about organisms. I can elaborate on any of these claims if you wish further clarification. Organisms, whether conscious of their own existence or not, function and operate in ways that ensure the maintenance of their own organization, and hence the continuation of their own existence. What an organism does (and that includes all the physiological and biochemical reactions that take place within it) ultimately serves the purpose of maintaining its own existence through time. The organism needn’t be aware of this for it to be true. Of course, staying alive is not the only purpose in life. Reproduction, as you point out, is also of central importance, and depending on what branch of biology you specialize in you may be inclined to believe that it is more important. But the fact of the matter is that one can survive without reproducing, but one cannot reproduce without surviving (at least, survive until one can reproduce!). So I believe that the thermodynamic challenge of staying alive and ordered in a world that is inexorably moving towards ever greater degrees of entropic disorder is the most basic, and most formidable, of all of life’s goals. And for this reason it provides a useful means of distinguishing the biological from the mechanical.

Aakriti: You mention that organisms are self-generating and self-maintaining and this differentiates them from machines; but what are your opinions on the dependent nature of organisms? What I mean by this is, organisms need food, sustenance, particular environments, in our case, doctors, and other infrastructure. In this sense, can an organism not be seen as just a more intelligent or more evolutionarily progressed machine? In the same vein, are AI robots organisms (a bit sci-fi here, but maybe something like the robots in the Terminator, if it ever comes down to that).

Dan: I don’t see a conflict here. To say that organisms are autonomous systems (that is, that they act on their own behalf) is not to say that they are self-sufficient. As you note, organisms are strongly dependent on their environment. By virtue of existing in a highly organized state far from thermodynamic equilibrium, an organism must continuously exchange matter and energy with its surroundings in order to stay alive. When this flow stops, death ensues. The contrast with machines is particularly telling here. A machine can be operating to perform a particular task, or it can be at rest. Organisms, however, don’t have an ‘off’ switch. When an organism stops working (in the thermodynamic sense), it stops existing. So the important point here is not to assume that just because organisms have autonomous capacities that they don’t rely on their environment for their continued existence.

A potential problem for any attempt to demarcate organisms from machines is that one must always allow for the possibility that future technology will eventually develop to such an extent that it will enable us to create machines with the features that we consider most distinctive of organisms. What then? My answer is that if we ever succeed in engineering an artificial system that possessed all the attributes proper to living systems (self-organization, self-production, self-maintenance, self-regeneration, and consequently intrinsic purposiveness) then I would not have a problem to declare it to be alive, despite its artificial origin. If you think about it, the question of origins is not that important. Yes, it is true that until now all organisms have evolved naturally and all machines have been artificially created. But being the product of evolution is not what makes organisms what they are. And being the product of artificial design is not what makes machines what they are. The distinction between intrinsic and extrinsic forms of purposiveness is, I think, far better suited than the distinction between natural and artificial origins to capture the respective features of organisms and machines.

Aakriti: In your writings, you mention that we study organisms “top-down”, whereas we study machines “bottom up”. Is this because we are only beginning to understand what organisms are made of, etc., and therefore we haven’t developed a bottom-up approach yet, since machines are obviously a human creation and therefore we understand them better than we do ourselves?

Dan: What I say (in p. 163 of my 2014 paper) is that embryonic development is a ‘top-down’ process, whereas machine construction is ‘bottom up’. What does this mean and why does it matter? In that passage I am drawing attention to the fact that organisms and machines come into existence in radically different ways. The whole that constitutes the finished machine does not exist as such prior to the assembly of the parts that compose it. One first designs all the machine parts and then these are arranged to constitute the whole. In the case of the organism the situation is reversed. Here, one already starts out with a rudimentary integrated ‘whole’, i.e. the fertilized egg. As the zygote develops, its regions begin to differentiate into tissues and organs. In a way, the parts that one identifies in an adult organism emerge much later than the whole from which they derive. This ontological difference has important epistemological and methodological implications. The reductionistic approach (i.e. breaking down the system to its parts in order to understand it) works brilliantly with machines because reductionism is simply the reverse of assembly. When we study machines by decomposing them, all we are doing is invert the process by which they come into existence. In the case of organisms, however, breaking them down is to do ‘violence’ to their nature given that, strictly speaking, organisms are not made of parts to begin with. Parts are parts by virtue of the whole. Thus, these cannot be fully understood in isolation from the whole from which they are extracted (note my emphasis on ‘fully’ – of course, one can learn a great deal by studying biological parts, as biochemistry and molecular biology clearly testify). The difficulty of building an organism from scratch (through a genuinely ‘bottom-up’ approach) is that many of its properties and capacities depend on it already existing as an integrated, organized whole. None of the parts that compose it suffice by themselves (or in different combinations) to explain why the whole system functions the way it does. Only when they are all taken as a collective, systemic entity can one truly make sense of why organisms function and behave the way they do. This obviously imposes some rather severe restrictions on the explanatory adequacy of reductionistic programs in biology. What is certain, at any rate, is that such approaches do not suffice (as they do in the case of machines).

Aakriti: What are your thoughts on genetic engineering? You touch upon this briefly in one of your papers, but I’d like to hear if you have anything more to add to this. For example, is an E. coli that we engineer to produce specific chemicals, such as biofuels, still considered an organism or is it now a machine because it serves an extrinsic purpose? Furthermore, and excuse me if this is an incorrect line of questioning, is this good or not? That is, should we control other organisms to serve our purpose in such a way?

Dan: Genetic engineering does complicate the intrinsic vs. extrinsic purposiveness distinction to a certain extent, as we do modify bacteria to serve our own ends (just as in the past we have domesticated animals and cultivated plans to serve our own ends). In such cases these organisms do appear to have an extrinsic purpose (at least for us, as their users and exploiters). Still, this only represents a contingent interference with the natural workings of these organisms, which left to their own devices, would act intrinsically purposive on their own behalf (rather than on our behalf). In fact, even when these organisms are being used by us, they are still primarily working for themselves. Bacteria that produce specific chemicals for us (to use your example) still also produce all the other chemicals they require to maintain their own metabolic integrity. Indeed, we cannot work against an organism’s intrinsic ‘interests’. Quite the opposite, our success in exploiting organisms (through domestication, cultivation, and now through GE) crucially relies on ensuring that our extrinsic purposes do not conflict with the basic organismic drive for survival that all living systems possess. Only once this basic need is met can organisms be found useful to other organisms (like ourselves). We can again contrast this with the case of machines. As its user, you can get a machine to do anything you want it to do without having to worry whether this goes against the machine’s interests. The machine has no interests of its own. It is an instrument designed, created, and operated by us in order to serve our own ends. In a way, machines are extensions of ourselves. They have no agency of their own.

As to the question of whether using organisms is good or not, that’s a very convoluted issue that lies outside my expertise (here we leave philosophy of biology and enter bioethics). It is obvious, though, that if one thinks of organisms as machines then one needn’t feel a moral obligation towards organisms (for the reasons discussed above). As machines don’t have interests and organisms are machines, we can do with organisms what we please without feeling morally responsible for our actions. Having said this, I don’t wish to say that we shouldn’t use organisms. I’m simply saying that realising that organisms are fundamentally different from machines forces us to be more aware about how we treat them

NSF puts $30M behind software bug killing, synthetic biology & computational sustainability

“Cytokine converter” AND-gate synthetic-biology prosthesis used to treat psoriasis in mice. Top left: skin before; right: skin after. (credit: Lina Schukur et al./Science Translational Medicine)

An advanced “molecular prosthetic” — a cell with synthetic gene circuits that can be implanted into an organism to take over metabolic functions that the organism cannot perform itself — has been developed by ETH Zurich scientists.

Previous gene circuits typically monitored only whether one disease-causing molecule (called a cytokine) was present in their environment and if so, produced a single therapeutic cytokine as a response. The new “cytokine converter” synthetic circuit functions like an AND gate: It can detect two different cytokines simultaneously, and if (and only if) both are present, produces two different cytokines that can treat a disease.

Keith Joung remembers the first time he took CRISPR for a spin. In late 2012, the pathologist at Massachusetts General Hospital in Boston assembled the components of the new gene-editing technology and fiddled with the DNA of a zebrafish embryo. “It was so easy to do,” he says. “It was just stunning.”

CRISPR—the highly efficient set of molecular scissors recently selected as Science’s Breakthrough of the Year—might be easy to use, but it’s not perfect. Joung and his colleagues soon found that these scissors could get too slice-happy, cutting DNA in unexpected and unwanted locations. In early experiments, the group observed that these off-target effects could occur at some DNA sites with nearly the same frequency as the desired edits. That’s a problem if CRISPR is to form the basis of human therapies, for example, repairing the defective genes that cause muscular dystrophy or hereditary liver disease. Researchers’ primary concern is that cutting into an unwanted gene could cause uncontrolled growth and cancer.

Now, Joung and colleagues have found a way to make CRISPR more precise. In a new study, they modified its cutting enzyme to reduce off-target effects below detectable levels.

“I think that this is a potential breakthrough,” says Jin-Soo Kim, a molecular biologist at Seoul National University who was not involved with the work. But the quest to perfect CRISPR doesn’t have a clear end. “No drugs are free of off-target effects,” he notes. With CRISPR-based therapies still far from human testing, no one knows just how precise is precise enough.

CRISPR relies on a DNA-cutting enzyme called Cas9 attached to a short strand of RNA that guides it to specific point in the genome. When the RNA finds a complementary—or nearly complementary—sequence, Cas9 makes its slice. There are already several approaches to prevent unintended slicing. Shortening the length of the guide RNA makes it more sensitive to mismatched sequences, but it can also create entirely new off-target effects. Some labs have experimented with a version of Cas9 that cuts through a single DNA strand instead of two. That means two Cas9 enzymes bearing two different guide RNAs have to recognize their target sequences to cut both strands—a more demanding matching process. But doubling the number of RNA guides adds bulk, which could make it harder to deliver a CRISPR-based treatment into cells.

In the new work, published online today in Nature, Joung and colleagues took a different approach. They modified the Cas9 enzyme itself to change the way it interacts with DNA. They first altered some of the “residues” on the enzyme’s surface that presumably help the guide RNA pair with its matching DNA strand. One set of modifications created a new variant of Cas9, called Cas9-HF1, that appears to be much more discriminating in its cuts. The researchers made seven different edits guided by seven different RNA strands, each known to produce off-target effects with Cas9. But Cas9-HF1 showed no detectable off-target effects in six of these cases—and just one errant slice in the seventh, they report. Joung adds that the apparent slice could actually be the result of a sequencing error.

The results come on the heels of a similar feat, led by CRISPR pioneer Feng Zhang of Harvard University and the Broad Institute in Cambridge, Massachusetts, published last month in Science. That team modified Cas9 to change how it interacts with a different part of a cell’s DNA. It, too, dramatically improved CRISPR’s specificity. But it’s hard to compare those results directly with the new paper because they used slightly different methods to measure off-target effects.

Joung claims his group’s measurements are roughly 10-fold more sensitive than the one used in the Science paper. Both studies rely on methods that attach molecular tags to all points in the genome where a double-stranded break has occurred, before sequencing the short, flagged segments to count the cuts in various genes. Joung’s team claims to detect edits that occur in at least 0.1% of the genome. Zhang says the method used in his paper has been validated down 0.3%, and it may be even more sensitive.

Does detecting just a couple of faulty cuts in a thousand matter? Absolutely, Joung says. “A lot of therapeutic strategies envision manipulating millions, tens of millions, even hundreds of millions of cells, potentially. So one in 1000 sounds pretty good, but that number can become quite large.” He argues that the field needs tests that root out these potentially harmful effects at frequencies of 0.01% or even lower.

Others are less focused on increasingly sensitive tests. Because CRISPR will never fully be rid of off-target effects, the key question for a given therapy is not strictly how many unwanted cuts it makes, but whether it disrupts any essential genes, says Jiing-Kuan Yee, a molecular biologist at the research center City of Hope in Duarte, California. Each therapeutic application will require its own carefully selected Cas9 molecule—and modifications like those in the two recent papers might be combined.

“Pretty soon, I think everybody’s going to start using these modified Cas9s,” he says. “The [off-target] problem will still be there, but it’s going to be much, much reduced.”

"The cytoplasm of prokaryotes contains many molecular machines interacting directly with the chromosome. These vital interactions depend on the chromosome structure, as a molecule, and on the genome organization, as a unit of genetic information. Strong selection for the organization of the genetic elements implicated in these interactions drives replicon ploidy, gene distribution, operon conservation, and the formation of replication-associated traits. The genomes of prokaryotes are also very plastic with high rates of horizontal gene transfer and gene loss. The evolutionary conflicts between plasticity and organization lead to the formation of regions with high genetic diversity whose impact on chromosome structure is poorly understood. Prokaryotic genomes are remarkable documents of natural history because they carry the imprint of all of these selective and mutational forces. Their study allows a better understanding of molecular mechanisms, their impact on microbial evolution, and how they can be tinkered in synthetic biology."