Lifeboat Foundation

The discipline of systems chemistry deals with the analysis and synthesis of various autocatalytic systems and is therefore closely related to the study of the origin of life, since it investigates systems that can be considered as a transition between chemical and biological evolution: more complex than simple molecules, but simpler than living cells.

Tibor Gánti described the theory of self-replicating microspheres as early as 1978. These still lacked genetic material, but concealed within their membranes an autocatalytic metabolic network of small molecules, isolated (compartmentalized) within their membranes.

As the autocatalytic process takes place, the membrane-building material is also produced, leading to the division of the sphere. This system may appear to be a living cell, and although it lacks genetic material, this can only be verified experimentally. These microspheres can be considered as “infrabiological” chemical systems, since they do not reach the level of biological organization, but they exceed the complexity of normal chemical reactions.

One of the most actively debated questions about human and non-human culture is this: under what circumstances might we expect culture, in particular the ability to learn from one another, to be favored by natural selection? Researchers at the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany, have developed a simulation model of the evolution of social learning. They showed that the interplay between learning, memory and forgetting broadens the conditions under which we expect to see social learning to evolve.

Social learning is typically thought to be most beneficial when the environments in which individuals live change quite slowly – they can safely learn tried and tested information from one another and it does not go out of date quickly. Innovating brand-new information, on the other hand, is thought to be useful in dynamic and rapidly changing environments.

Researchers Madeleine Ammar, Laurel Fogarty and Anne Kandler at the Max Planck Institute for Evolutionary Anthropology developed an agent-based simulation model of the evolution of social learning that incorporated the ways in which animals might remember, forget, and share crucial pieces of information throughout their lives. They asked: when do the agents want to learn from others? When is it best to forget or retain information that they have learned? When is it best to innovate?

“I view string theory as the most promising way to quantize matter and gravity in a unified way. We need both quantum gravity and we need unification and a quantization of gravity. One of the reasons why string theory is promising is that there are no singularities associated with those singularities are the same type that they offer point particles.” — Robert Brandenberger.

In this thought-provoking conversation, my grad school mentor, Robert Brandenberger shares his unique perspective on various cosmological concepts. He challenges the notion of the fundamental nature of the Planck length, questioning its significance and delving into intriguing debates surrounding its importance in our understanding of the universe. He also addresses some eyebrow-raising claims made by Elon Musk about the limitations imposed by the Planck scale on the number of digits of pi.

Continue reading “Unseen Fluctuations: Challenging Inflation | Robert Brandenberger” »

Bacterial cells can easily share genes with one another, and have a few ways to do so. Viruses called bacteriophages infect bacterial cells, and they can also transfer genes between bacterial cells in a process known as transduction. Often, the genes that are being shared confer resistance to a drug, and once a bacterial cell gains the ability, antibiotic resistance can easily spread through populations of microbial cells. Now scientists have discovered another mechanism that bacteria use to share genes, and it can help microbes evolve even faster than we knew. The findings have been reported in Cell.

There are three types of transduction that we now know about: generalized, specialized, and lateral. The newly revealed mechanism is called lateral cotransduction. It is about as rapid as lateral transduction, which itself is far faster than generalized transduction. However, the study indicated that lateral cotransduction is more complex and versatile than the other modes of transduction. Lateral transduction happens when phages that have integrated into bacterial genomes are reactivated, and trigger reproduction in the lytic cycle; but lateral cotransduction can while new bacterial cells are being infected, and during the reactivation process.

Evolution doesn’t fix things — it reinvents them. A biologist explains.

The Belle II cooperation project at the Japanese research center KEK is helping researchers from all over the world to hunt for new phenomena in particle physics. The international experiment has now reached a major milestone after a team successfully installed a new pixel detector in its final location in Japan.

The size of a soda can, the detector was developed in order to make out the signals coming from certain types of particle decays, that can shed light on the origin of the matter–antimatter asymmetry that has been observed in the universe. The installation ran without a hitch and is a key milestone in the evolution of the experiment and German–Japanese research collaboration.

Based at the SuperKEKB accelerator in Japan’s KEK research center, Belle II is an international collaborative project involving researchers from all over the world. The experiment aims to find answers to the many unresolved questions about the universe that are out there. To this end, the 1,200 or so members of the international Belle II collaboration are searching for signs of new phenomena in physics and unknown particles not covered by the established Standard Model of particle physics.

An interdisciplinary team of mathematicians, engineers, physicists, and medical scientists has discovered a surprising connection between pure mathematics and genetics. This connection sheds light on the structure of neutral mutations and the evolution of organisms.

Number theory, the study of the properties of positive integers, is perhaps the purest form of mathematics. At first sight, it may seem far too abstract to apply to the natural world. In fact, the influential American number theorist Leonard Dickson wrote “Thank God that number theory is unsullied by any application.”

And yet, again and again, number theory finds unexpected applications in science and engineering, from leaf angles that (almost) universally follow the Fibonacci sequence, to modern encryption techniques based on factoring prime numbers. Now, researchers have demonstrated an unexpected link between number theory and evolutionary genetics.

Each cell in the body stores its genetic information in DNA in a stable and protected form that is readily accessible for the cell to carry on its activities. Nevertheless, mutations—changes in genetic information—occur throughout the human genome and can have a powerful influence on human health and evolution.

“Our team is interested in a classical question about mutation—why do mutation rates in the genome vary so tremendously from one DNA location to another? We just do not have a clear understanding of why this occurs,” said Dr. Md. Abul Hassan Samee, assistant professor of integrative physiology at Baylor College of Medicine and corresponding author of the work.

Previous studies have shown that the DNA sequences flanking a mutated position—the sequence context—play a strong role in the mutation rate. “But this explanation still leaves unanswered questions,” Samee said. “For example, one type of mutation occurs frequently in a specific sequence context while a different type of mutation occurs infrequently in that same sequence context. So, we think that a different mechanism could explain how mutation rates vary in the genome. We know that each building block or base that makes up a DNA sequence has its own 3D chemical shape. We proposed, therefore, that there is a connection between DNA shape and mutations rates, and this paper shows that our idea was correct.”

Experimental studies of microbial evolution have largely focused on monocultures of model organisms, but most microbes live in communities where interactions with other species may impact rates and modes of evolution. Using the cheese rind model microbial community, we determined how species interactions shape the evolution of the widespread food-and animal-associated bacterium Staphylococcus xylosus. We evolved S. xylosus for 450 generations alone or in co-culture with one of three microbes: the yeast Debaryomyces hansenii, the bacterium Brevibacterium aurantiacum, and the mold Penicillium solitum. We used the frequency of colony morphology mutants (pigment and colony texture phenotypes) and whole-genome sequencing of isolates to quantify phenotypic and genomic evolution. The yeast D. hansenii strongly promoted diversification of S. xylosus.