Training the next generation of researchers is an essential component of any healthy academic field. Here William Bialek and Joshua Shaevitz, Professors of Physics at Princeton University and Co-Directors of the Center for the Physics of Biological Function, request three years of support for a Center Fellow pursuing physics-of-life research. This prestigious postdoctoral fellowship will offer a young researcher both intellectual freedom and a support structure, and grant funds would support either a theorist or an experimentalist. A fellowship offering intellectual freedom to an early-career scholar is typically challenging to fund through federal agencies focused on supporting specific projects, despite the fact that this freedom can play an important role in establishing a young scientist as an independent researcher. The Center for the Physics of Biological Function is a partnership between Princeton and the Graduate Center of the City University of New York; a partnership anchored by a core community of sixteen CUNY/Princeton faculty. The Center focuses on science at the interface of physics and biology with the goal of creating ‘a physicist’s understanding of living systems: a physics of biological function that connects the myriad details of life, across all scales, to fundamental and universal physical principles.’ Center Fellows will be offered a competitive salary, travel funds, and independence to select a compelling line of research. The Center Fellow is not obligated to any particular faculty member, instead the Center exposes young physicists to problems posed by a wide range of living systems and gives them ‘considerable freedom to explore these problems, crossing boundaries among topics that would be in separate groups or departments at most institutions.’ This freedom is balanced by a support system as the Fellow is held accountable to formulating a feasible plan by interacting with senior Center faculty, and there’s a community of Fellows that provide peer advice and guidance.

Systems chemistry is a branch of chemical research that examines large, complicated chemical networks and focuses on understanding how complexity and function can emerge from the many diverse chemical interactions within the network. This grant provides support to a team led by Rein Ulijn, Professor of Physics and Director of the Nanoscience Initiative at the City University of New York Graduate Center, to induce a chemical system to demonstrate a life-like behavior; specifically, a primitive form of learning and memory. Dr. Ulijn’s basic chemical system will be composed of peptides (short proteins; a sequence of amino acids) that -with the help of an enzyme- can be reversibly combined into more complex peptides (oligopeptides). The team plans to expose a chemical network to a molecule that acts as an environmental stimulus that will cause a reaction, the formation of new peptide molecules and various phase-separated peptide ‘structures.’ After removing the stimulus molecules from the network, they will be re-introducing at some later time.  If the network responds more rapidly to the stimulus than when the molecules were first introduced, it has, in a basic sense, “remembered” the initial stimulus and ‘learned’ to respond faster.  The project begins by choosing an initial set of (2-6) interacting dipeptides. Molecular dynamics simulations will inform selection of the initial dipeptide system to ensure that the dipeptides have a propensity for self-assembly. This makes it likely that more complex peptides and (peptide) structures will form. Once an initial system has been selected, the researchers will synthesize the system in their lab, allow the peptide chemistry to run to a steady state, and then characterize the steady state distribution of peptides and phase-separated structures in the unperturbed system (i.e. before a stimulus molecule is introduced). The formation of oligopeptides and phase-separated structures will be monitored using a combination of microscopy, optical spectroscopy, liquid chromatography, mass spectrometry, and dynamic light scattering. Once the steady state properties of the unperturbed peptide system have been characterized, a stimulus molecule will be introduced and the researchers will characterize how the distribution of peptides and the formation of structures is modified. The characterization will be done for each of several stimulus molecules (flavor molecules grape, raspberry, banana and apple) selected based on their simplicity and because they offer a systematic variation in chemical-interaction potential.  Finally, the researchers will determine whether repeated exposure to a given stimulus molecule can condition the system to respond more rapidly; the stimulus molecules will be removed between exposures. The researchers will study how learning and memory are influenced by variation of experimental parameters such as pH, temperature, and molecular target concentration. They’ll also test the hypothesis that the physical basis of memory lies in remnant structures retained by the solution. This idea will be tested by using heat to melt any remnant structural nuclei; something that should eliminate any observed memory effects. Beyond demonstration of learning and memory induced by a single type of stimulus molecule, the researchers will also explore exposure to competing stimuli, by examining whether mixing of separately conditioned solutions yields a different response when compared to that obtained from a solution conditioned by simultaneous exposure to several types of stimulus molecules.

Earth biochemistry relies on DNA as the information-carrying polymer and water as the chemistry-facilitating solvent. Life on other planets, however, could leverage very different chemistry. This grant supports work by Sara Seager, Professor of Planetary Science, Physics, and Aeronautical and Astronautical Engineering at the Massachusetts Institute of Technology, that will explore an alternative to Earth biochemistry. The proposed research focuses on identifying a DNA-like molecule that is functional in concentrated sulfuric acid (CSA), the primary component of Venus’ atmosphere and a water-alternative solvent found on many planets in our galaxy.   There are several steps to establishing that a DNA-like molecule can function in CSA, and Professor Seager is tackling what is perhaps the core challenge: identifying components of a DNA-analog molecule that are structurally stable and appropriately reactive in CSA, focusing on the three primary molecular components of DNA: nucleic acid bases, so-called ‘linker’ molecules, and a ‘molecular backbone’ structure. Her project is divided into four tasks. In Task 1 Seager and her researcher team will determine the CSA reactivity of the nucleic acid bases found in DNA/RNA. While Seager has demonstrated that the core structures of these canonical bases are CSA-stable, it’s not yet known whether the bases can bond with one another in CSA; something required to form a DNA-like molecule.   Excess protons found in CSA (or in any acid) may interfere with the hydrogen bonding that holds two bases together in a DNA molecule, making base-pairing with these canonical bases impossible in CSA. Accordingly, in Task 2 the researcher team will test the CSA stability and reactivity of ‘alternative’ nucleic acid bases that do not rely on hydrogen bonding for base-pairing. In Task 3, the researchers will develop a list of linker and backbone molecule candidates that promise to be stable in CSA and in Task 4 these candidates will be subjected to CSA stability/reactivity testing.   Establishing that a replicating, information-bearing molecule can exist in CSA goes a long way to establishing CSA as a solvent that can host life. Such a finding would significantly impact exoplanet research, expand the number of planets regarded as habitable, and inform planned and proposed missions to Venus aimed at searching for signs of extraterrestrial life.

Life as we know it is primarily chemistry: all living organisms are composed of carbon-based molecules such as proteins, carbohydrates, and nucleic acids that are the result of chemical reactions between different elements like carbon, hydrogen, oxygen, nitrogen, and sulfur. Understanding the basic principles underlying chemical reactions is important to understanding life. When thinking about reactions in a chemical context, scientists typically think about reactants interacting in a homogeneous solution that’s essentially the same in any given place. But the cytoplasm, the liquid in cells where biochemical reactions take place, is a biological context that’s quite different from the simplified models of chemistry textbooks. Cytoplasm is a heterogeneous fluid that looks and functions differently across the cell and so it’s not accurately represented by simplifying assumptions of homogeneity. Precisely how these assumptions are distorting our picture of cellular chemistry, and therefore our understanding of fundamental biochemistry, is not well understood. This grant supports Lauren Zarzar and Ayusman Sen at the Pennsylvania State University who will study how solution heterogeneity influences reactivity for three important classes of biochemical reactions. First, they will study autocatalytic reactions, in which one of the reaction products facilitates (i.e. is a catalyst for) the same, or a coupled, reaction. Autocatalysis is a mechanism for chemical self-replication and is considered a key aspect of the prebiotic chemistry that gave rise to life. Next, the team will study enzyme reaction cascades, a sequence of enzyme-catalyzed reactions whereby the product of one reaction is the reactant for the next reaction. They’ll focus on chemotaxis (chemical activity that leads to motion towards or away from a higher concentration of some substance) to study how solution structure affects enzyme cascades. Finally, they will study polymerization reactions and, in doing so, address an important question in prebiotic chemistry: how polymers with specific monomer sequences arise without a specific sequence-directing mechanism. Ultimately, this project will deepen our understanding of specific reactions central to cellular chemistry and shed light on the role solution heterogeneity plays in driving the chemistry of life.

This grant supports Ben Machta at Yale University who will use tools from information theory and statistical physics to explore how bacteria process signals from their environment, and how they use this information to drive behavior. Machta will use bacteria to study one aspect of information processing: how noise (spurious signal accompanying the information-carrying signal) limits bacterial behavior. Specifically, Machta  will investigate how bacteria navigate their local chemical environment through chemotaxis (movement along a concentration gradient of a substance) and how they communicate with one another through quorum sensing (chemical signaling that reflects the density of nearby bacteria). Grant funds will allow Machta to determine the theoretical limit on the rate at which E. coli acquire behaviorally-relevant information (the concentration of so-called attractant molecules) and to measure this information-acquisition rate, to provide the first direct measurement of whether any organism’s biochemical sensory system approaches the performance limits imposed by the laws of physics. Additionally, Machta and colleagues will study how E. coli amplify signals without introducing noise via experiments that will test whether equilibrium or non-equilibrium models do a better job of describing chemotactic signal amplification. Finally, the researchers will use V. cholerae bacteria as a model organism to study the fidelity of information transmission as multiple signals propagate through the quorum sensing signal processing pathway. Collectively, these experiments will provide an important demonstration of how the tools of  information theory and statistical physics can be used to gain mechanistic insight into the information processing that drives behavior in simple living systems. 

This grant funds an ambitious plan by an international collaboration of six laboratories to achieve a milestone that science, and humanity more generally, has imagined for quite some time: building some version of life from scratch. That claim must be qualified by cautions that the effort may not succeed and by clarification that the proposed entity is probably better viewed as a minimal form of life rather than as a (much more complex) natural cell. To be clear about the version of life herein proposed, the goal of this project is to design and build a protocell from nonliving chemicals that is capable of indefinite cycles of genetic replication, growth, and division, and which over "generations" exhibits environmentally driven Darwinian evolution. The project team is led by Jack Szostak, Professor of Chemistry at the University of Chicago and includes researchers Irene Chen (UC Santa Barbara. U.S.), Sheref Mansy (University of Alberta, Canada), Arvind Murugan (University of Chicago, U.S.), John Sutherland (Medical Research Council, United Kingdom), and Anna Wang (University of New South Wales, Australia).Project activities will consist of laboratory experiments guided by theory and computation, organized along three primary research thrusts. First, the team will conduct research to achieve indefinite cycles of RNA replication by achieving high-fidelity copying of the entire RNA-based genome. The two major components of this first thrust are optimizing the chemistry for copying a given gene sequence from a template and ensuring that the entire genome is copied. The second research thrust focuses on achieving indefinite cycles of cell growth and division. Here the primary challenge is understanding and controlling membrane growth and division, and the team will experiment with several different approaches to using fatty-acid vesicles as the primary protocell container. In the third research thrust, the research team will address issues associated with making the genetic and compartmentalization systems mutually compatible. After these major goals are achieved, the team will then observe this primitive living system over several generations as it increases in complexity, adapts and evolves, and as its genome grows to encode more information about the world.