Insights into Mycoplasma genitalium metabolism revealed by the structure of MG289, an extracytoplasmic thiamine binding lipoprotein

The substrate-binding domains of the osmoregulatory ABC importer OpuA transiently interact

Bacteria utilize various strategies to prevent internal dehydration during hypertonic stress. A common approach to countering the effects of the stress is to import compatible solutes such as glycine betaine, leading to simultaneous passive water fluxes following the osmotic gradient. OpuA from Lactococcus lactis is a type I ABC-importer that uses two substrate-binding domains (SBDs) to capture extracellular glycine betaine and deliver the substrate to the transmembrane domains for subsequent transport. OpuA senses osmotic stress via changes in the internal ionic strength and is furthermore regulated by the 2nd messenger cyclic-di-AMP. We now show, by means of solution-based single-molecule FRET and analysis with multi-parameter photon-by-photon hidden Markov modeling, that the SBDs transiently interact in an ionic strength-dependent manner. The smFRET data are in accordance with the apparent cooperativity in transport and supported by new cryo-EM data of OpuA. We propose that the physical interactions between SBDs and cooperativity in substrate delivery are part of the transport mechanism.

Essential metabolism for a minimal cell

JCVI-syn3A, a robust minimal cell with a 543 kbp genome and 493 genes, provides a versatile platform to study the basics of life. Using the vast amount of experimental information available on its precursor, Mycoplasma mycoides capri, we assembled a near-complete metabolic network with 98% of enzymatic reactions supported by annotation or experiment. The model agrees well with genome-scale in vivo transposon mutagenesis experiments, showing a Matthews correlation coefficient of 0.59. The genes in the reconstruction have a high in vivo essentiality or quasi-essentiality of 92% (68% essential), compared to 79% in silico essentiality. This coherent model of the minimal metabolism in JCVI-syn3A at the same time also points toward specific open questions regarding the minimal genome of JCVI-syn3A, which still contains many genes of generic or completely unclear function. In particular, the model, its comparison to in vivo essentiality and proteomics data yield specific hypotheses on gene functions and metabolic capabilities; and provide suggestions for several further gene removals. In this way, the model and its accompanying data guide future investigations of the minimal cell. Finally, the identification of 30 essential genes with unclear function will motivate the search for new biological mechanisms beyond metabolism.

One way that researchers can test whether they understand a biological system is to see if they can accurately recreate it as a computer model. The more they learn about living things, the more the researchers can improve their models and the closer the models become to simulating the original. In this approach, it is best to start by trying to model a simple system.

Biologists have previously succeeded in creating ‘minimal bacterial cells’. These synthetic cells contain fewer genes than almost all other living things and they are believed to be among the simplest possible forms of life that can grow on their own. The minimal cells can produce all the chemicals that they need to survive – in other words, they have a metabolism. Accurately recreating one of these cells in a computer is a key first step towards simulating a complete living system.

Breuer et al. have developed a computer model to simulate the network of the biochemical reactions going on inside a minimal cell with just 493 genes. By altering the parameters of their model and comparing the results to experimental data, Breuer et al. explored the accuracy of their model. Overall, the model reproduces experimental results, but it is not yet perfect. The differences between the model and the experiments suggest new questions and tests that could advance our understanding of biology. In particular, Breuer et al. identified 30 genes that are essential for life in these cells but that currently have no known purpose.

Continuing to develop and expand models like these to reproduce more complex living systems provides a tool to test current knowledge of biology. These models may become so advanced that they could predict how living things will respond to changing situations. This would allow scientists to test ideas sooner and make much faster progress in understanding life on Earth. Ultimately, these models could one day help to accelerate medical and industrial processes to save lives and enhance productivity.

A closure relation to molecular theory of solvation for macromolecules

We propose a closure to the integral equations of molecular theory of solvation, particularly suitable for polar and charged macromolecules in electrolyte solution. This includes such systems as oligomeric polyelectrolytes at a finite concentration in aqueous and various non-aqueous solutions, as well as drug-like compounds in solution. The new closure by Kobryn, Gusarov, and Kovalenko (KGK closure) imposes the mean spherical approximation (MSA) almost everywhere in the solvation shell but levels out the density distribution function to zero (with the continuity at joint boundaries) inside the repulsive core and in the spatial regions of strong density depletion emerging due to molecular associative interactions. Similarly to MSA, the KGK closure reduces the problem to a linear equation for the direct correlation function which is predefined analytically on most of the solvation shells and has to be determined numerically on a relatively small (three-dimensional) domain of strong depletion, typically within the repulsive core. The KGK closure leads to the solvation free energy in the form of the Gaussian fluctuation (GF) functional. We first test the performance of the KGK closure coupled to the reference interaction site model (RISM) integral equations on the examples of Lennard-Jones liquids, polar and nonpolar molecular solvents, including water, and aqueous solutions of simple ions. The solvation structure, solvation chemical potential, and compressibility obtained from RISM with the KGK closure favorably compare to the results of the hypernetted chain (HNC) and Kovalenko-Hirata (KH) closures, including their combination with the GF solvation free energy. We then use the KGK closure coupled to RISM to obtain the solvation structure and thermodynamics of oligomeric polyelectrolytes and drug-like compounds at a finite concentration in electrolyte solution, for which no convergence is obtained with other closures. For comparison, we calculate their solvation structure from molecular dynamics (MD) simulations. We further couple the 3D-RISM integral equation with the 3D-version of the KGK closure, and solve it for molecular mixtures as well as oligomeric polyelectrolytes and drug-like molecules in electrolyte solutions.

Potential Molecular Targets for Narrow-Spectrum Agents to Combat Mycoplasma pneumoniae Infection and Disease

As Mycoplasma pneumoniae macrolide resistance grows and spreads worldwide, it is becoming more important to develop new drugs to prevent infection or limit disease. Because other mycoplasma species have acquired resistance to other classes of antibiotics, it is reasonable to presume that M. pneumoniae can do the same, so switching to commonly used antibiotics like fluoroquinolones will not result in forms of therapy with long-term utility. Moreover, broad-spectrum antibiotics can have serious consequences for the patient, as these drugs may have severe impacts on the natural microbiota of the individual, compromising the health of the patient either short-term or long-term. Therefore, developing narrow-spectrum antibiotics that effectively target only M. pneumoniae and no more than a small portion of the microbiota is likely to yield impactful, positive results that can be used perhaps indefinitely to combat M. pneumoniae. Development of these agents requires a deep understanding of the basic biology of M. pneumoniae, in many areas deeper than what is currently known. In this review, we discuss potential targets for new, narrow-spectrum agents and both the positive and negative aspects of selecting these targets, which include toxic molecules, metabolic pathways, and attachment and motility. By gathering this information together, we anticipate that it will be easier for researchers to evaluate topics of priority for study of M. pneumoniae.

3D-RISM-Dock: A New Fragment-Based Drug Design Protocol

We explore a new approach in the rational design of specificity in molecular recognition of small molecules based on statistical-mechanical integral equation theory of molecular liquids in the form of the three-dimensional reference interaction site model with the Kovalenko-Hirata closure (3D-RISM-KH). The numerically stable iterative solution of conventional 3D-RISM equations includes the fragmental decomposition of flexible ligands, which are treated as distinct species in solvent mixtures of arbitrary complexity. The computed density functions for solution (including ligand) molecules are obtained as a set of discrete spatial grids that uniquely describe the continuous solvent-site distribution around the protein solute. Potentials of mean force derived from these distributions define the scoring function interfaced with the AutoDock program for an automated ranking of docked conformations. As a case study in terms of solvent composition, we analyze cooperative interactions encountered in the binding of a flexible thiamine molecule to the prion protein at near-physiological conditions. The predicted location and residency times of computed binding modes are in excellent agreement with the available experimental data.

Antifragility and Tinkering in Biology (and in Business) Flexibility Provides an Efficient Epigenetic Way to Manage Risk

The notion of antifragility, an attribute of systems that makes them thrive under variable conditions, has recently been proposed by Nassim Taleb in a business context. This idea requires the ability of such systems to 'tinker', i.e., to creatively respond to changes in their environment. A fairly obvious example of this is natural selection-driven evolution. In this ubiquitous process, an original entity, challenged by an ever-changing environment, creates variants that evolve into novel entities. Analyzing functions that are essential during stationary-state life yield examples of entities that may be antifragile. One such example is proteins with flexible regions that can undergo functional alteration of their side residues or backbone and thus implement the tinkering that leads to antifragility. This in-built property of the cell chassis must be taken into account when considering construction of cell factories driven by engineering principles.