Complex Insight - Understanding our world

Analysis: With experts concerned over rising UK case rates, where are we also with deaths, hospital admissions, long Covid and the economy?

Oldest known ancestor of octopuses unearthed in Montana in form of approximately 330m-year-old fossil...

Researchers at MIT have developed a synthetic gene circuit that triggers the body’s immune system to attack cancers when it detects signs of the disease.
The circuit, which will only activate a therapeutic response when it detects two specific cancer markers, is described in a paper published today in the journal Cell.
Immunotherapy is widely seen as having considerable potential in the fight against a range of cancers. The approach has been demonstrated successfully in several recent clinical trials, according to Timothy Lu, associate professor of biological engineering and of electrical engineering and computer science at MIT.
“There has been a lot of clinical data recently suggesting that if you can stimulate the immune system in the right way you can get it to recognize cancer,” says Lu, who is head of the Synthetic Biology Group in MIT’s Research Laboratory of Electronics. “Some of the best examples of this are what are called checkpoint inhibitors, where essentially cancers put up stop signs [that prevent] T-cells from killing them. There are antibodies that have been developed now that basically block those inhibitory signals and allow the immune system to act against the cancers.”
However, despite this success, the use of immunotherapy remains limited by the scarcity of tumor-specific antigens — substances that can trigger an immune system response to a particular type of cancer. The toxicity of some therapies, when delivered as a systemic treatment to the whole body, for example, is another obstacle.
What’s more, the treatments are not successful in all cases. Indeed, even in some of the most successful tests, only 30-40 percent of patients will respond to a given therapy, Lu says.
As a result, there is now a push to develop combination therapies, in which different but complementary treatments are used to boost the immune response. So, for example, if one type of immunotherapy is used to knock out an inhibitory signal produced by a cancer, and the tumor responds by upregulating a second signal, an additional therapy could then be used to target this one as well, Lu says.
“Our belief is that there is a need to develop much more specific, targeted immunotherapies that work locally at the tumor site, rather than trying to treat the entire body systemically,” he says. “Secondly, we want to produce multiple immunotherapies from a single package, and therefore be able to stimulate the immune system in multiple different ways.”
To do this, Lu and a team including MIT postdocs Lior Nissim and Ming-Ru Wu, have built a gene circuit encoded in DNA designed to distinguish cancer cells from noncancer cells.
The circuit, which can be customized to respond to different types of tumor, is based on the simple AND gates used in electronics. Such AND gates will only switch on a circuit when two inputs are present.
Cancer cells differ from normal cells in the profile of their gene expression. So the researchers developed synthetic promoters — DNA sequences designed to initiate gene expression but only in cancer cells.
The circuit is delivered to cells in the affected area of the body using a virus. The synthetic promotors are then designed to bind to certain proteins that are active in tumor cells, causing the promoters to turn on.
“Only when two of these cancer promoters are activated, does the circuit itself switch on,” Lu says.
This allows the circuit to target tumors more accurately than existing therapies, as it requires two cancer-specific signals to be present before it will respond.
Once activated, the circuit expresses proteins designed to direct the immune system to target the tumor cells, including surface T cell engagers, which direct T cells to kill the cells. The circuit also expresses a checkpoint inhibitor designed to lift the brakes on T cell activity.
When the researchers tested the circuit in vitro, they found that it was able to detect ovarian cancer cells from amongst other noncancerous ovarian cells and other cell types.
They then tested the circuit in mice implanted with ovarian cancer cells, and demonstrated that it could trigger T cells to seek out and kill the cancer cells without harming other cells around them.
Finally, the researchers showed that the circuit could be readily converted to target other cancer cells.
“We identified other promoters that were selective for breast cancer, and when these were encoded into the circuit, it would target breast cancer cells over other types of cell,” Lu says.
Ultimately, they hope they will also be able to use the system to target other diseases, such as rheumatoid arthritis, inflammatory bowel disease, and other autoimmune diseases.
This advance will open up a new front against cancer, says Martin Fussenegger, a professor of biotechnology and bioengineering at ETH Zurich in Switzerland, who was not involved in the research.
“First author Lior Nissim, who pioneered the very first genetic circuit targeting tumor cells, has now teamed up with Timothy Lu to design RNA-based immunomodulatory gene circuits that take cancer immunotherapy to a new level,” Fussenegger says. “The design of this highly complex tumor-killing gene circuit was made possible by meticulous optimization and integration of several components that target and program tumor cells to become a specific prey for the immune system — this is very smart technology.”
The researchers now plan to test the circuit more fully in a range of cancer models. They are also aiming to develop a delivery system for the circuit, which would be both flexible and simple to manufacture and use.

Every cell needs a shell. The cell interior is separated from its surroundings by a membrane made up of fat molecules, helping to create the environment needed for the cell to survive. Development of artificial cells is similarl

A study by an international consortium of scientists reached a major milestone in establishing a baseline understanding of gene expression across healthy human tissues, and linking genes to disease.

Which mattered first at the dawn of life: proteins or nucleic acids? Proteins may have had the edge if a theorized process let them grow long enough to become self-replicating catalysts. 

We present a model of contagion that unifies and generalizes existing models of the spread of social influences and micro-organismal infections. Our model incorporates individual memory of exposure to a contagious entity (e.g., a rumor or disease), variable magnitudes of exposure (dose sizes), and heterogeneity in the susceptibility of individuals. Through analysis and simulation, we examine in detail the case where individuals may recover from an infection and then immediately become susceptible again (analogous to the so-called SIS model). We identify three basic classes of contagion models which we call \textit{epidemic threshold}, \textit{vanishing critical mass}, and \textit{critical mass} classes, where each class of models corresponds to different strategies for prevention or facilitation. We find that the conditions for a particular contagion model to belong to one of the these three classes depend only on memory length and the probabilities of being infected by one and two exposures respectively. These parameters are in principle measurable for real contagious influences or entities, thus yielding empirical implications for our model. We also study the case where individuals attain permanent immunity once recovered, finding that epidemics inevitably die out but may be surprisingly persistent when individuals possess memory.

A generalized model of social and biological contagion
Peter Sheridan Dodds, Duncan J. Watts

In this paper we present a thorough analysis of the nature of news in different mediums across the ages, introducing a unique mathematical model to fit the characteristics of information spread. This model enhances the information diffusion model to account for conflicting information and the topical distribution of news in terms of popularity for a given era. We translate this information to a separate graphical node model to determine the spread of a news item given a certain category and relevance factor. The two models are used as a base for a simulation of information dissemination for varying graph topoligies. The simulation is stress-tested and compared against real-world data to prove its relevancy. We are then able to use these simulations to deduce some conclusive statements about the optimization of information spread.

Characterizing information importance and the effect on the spread in various graph topologies
James Flamino, Alexander Norman, Madison Wyatt

How cooperation can evolve between players is an unsolved problem of biology. Here we use Hamiltonian dynamics of models of the Ising type to describe populations of cooperating and defecting players to show that the equilibrium fraction of cooperators is given by the expectation value of a thermal observable akin to a magnetization. We apply the formalism to the Public Goods game with three players, and show that a phase transition between cooperation and defection occurs that is equivalent to a transition in one-dimensional Ising crystals with long-range interactions. We also investigate the effect of punishment on cooperation and find that punishment acts like a magnetic field that leads to an "alignment" between players, thus encouraging cooperation. We suggest that a thermal Hamiltonian picture of the evolution of cooperation can generate other insights about the dynamics of evolving groups by mining the rich literature of critical dynamics in low-dimensional spin systems.

Thermodynamics of Evolutionary Games
Christoph Adami, Arend Hintze

The pandemic has taught us that viruses are not easy to identify – and can spread like wildfire...

Remember flu?Despite lockdowns holding it at bay, a small group of scientists is searching the globe for deadly new strains – and to work out what to put in next winter’s vaccines...

Researchers at MIT have developed a synthetic gene circuit that triggers the body's immune system to attack cancers when it detects signs of the disease.

Most drugs work by tinkering with the behavior of proteins. Like meddlesome coworkers, these molecules are designed to latch onto their target proteins and keep them from doing what they need to do.

A new statistical model has enabled researchers to pinpoint 27 novel genes thought to prevent cancer from forming, in an analysis of over 2000 tumours across 12 human cancer types. The findings could help create new cancer treatments that target these genes, and open up other avenues of cancer research.

Results are in from the first phase 1 clinical trial for a Zika vaccine, and they are very promising. A new generation DNA-based Zika vaccine, developed by Wistar scientists in collaboration with Inovio Pharmaceuticals and GeneOne Life Science, was found to be safe and well tolerated by all study participants and was able to elicit an immune response against Zika, opening the door to further and larger trials to move this vaccine forward. 

Poor economies not only produce less; they typically produce things that involve fewer inputs and fewer intermediate steps. Yet the supply chains of poor countries face more frequent disruptions---delivery failures, faulty parts, delays, power outages, theft, government failures---that systematically thwart the production process. To understand how these disruptions affect economic development, we model an evolving input--output network in which disruptions spread contagiously among optimizing agents. The key finding is that a poverty trap can emerge: agents adapt to frequent disruptions by producing simpler, less valuable goods, yet disruptions persist. Growing out of poverty requires that agents invest in buffers to disruptions. These buffers rise and then fall as the economy produces more complex goods, a prediction consistent with global patterns of input inventories. Large jumps in economic complexity can backfire. This result suggests why "big push" policies can fail, and it underscores the importance of reliability and of gradual increases in technological complexity.

Contagious disruptions and complexity traps in economic development
Charles D. Brummitt, Kenan Huremovic, Paolo Pin, Matthew H. Bonds, Fernando Vega-Redondo

One hundred and ten Zika virus genomes from ten countries and territories involved in the Zika virus epidemic reveal rapid expansion of the epidemic within Brazil and multiple introductions to other regions.

Zika virus evolution and spread in the Americas
Hayden C. Metsky, et al.

Nature 546, 411–415 (15 June 2017) doi:10.1038/nature22402