Mass Spectrometric Characterization of Oligomers in Pseudomonas aeruginosa Azurin Solutions

We have employed laser-induced liquid bead ion desorption mass spectroscopy (LILBID MS) to study the solution behavior of Pseudomonas aeruginosa azurin as well as two mutants and corresponding Re-labeled derivatives containing a Re(CO)_(3)(4,7-dimethyl-1,10-phenanthroline)^+ chromophore appended to a surface histidine. LILBID spectra show broad oligomer distributions whose particular patterns depend on the solution composition (pure H_(2)O, 20−30 mM NaCl, 20 and 50 mM NaP_i or NH_(4)P_i at pH = 7). The distribution maximum shifts to smaller oligomers upon decreasing the azurin concentration and increasing the buffer concentration. Oligomerization is less extensive for native azurin than its mutants. The oligomerization propensities of unlabeled and Re-labeled proteins are generally comparable, and only Re126 shows some preference for the dimer that persists even in highly diluted solutions. Peak shifts to higher masses and broadening in 20−50 mM NaP_i confirm strong azurin association with buffer ions and solvation. We have found that LILBID MS reveals the solution behavior of weakly bound nonspecific protein oligomers, clearly distinguishing individual components of the oligomer distribution. Independently, average data on oligomerization and the dependence on solution composition were obtained by time-resolved anisotropy of the Re-label photoluminescence that confirmed relatively long rotation correlation times, 6−30 ns, depending on Re−azurin and solution composition. Labeling proteins with Re-chromophores that have long-lived phosphorescence extends the time scale of anisotropy measurements to hundreds of nanoseconds, thereby opening the way for investigations of large oligomers with long rotation times

Construction task allocation through the collective perception of a dynamic environment

Building structures is a remarkable collective process but its automation remains an open challenge. Robot swarms provide a promising solution to this challenge. However, collective construction involves a number of difficulties regarding efficient robots allocation to the different activities, particularly if the goal is to reach an optimal construction rate. In this paper, we study an abstract construction scenario, where a swarm of robots is engaged in a collective perception process to estimate the density of building blocks around a construction site. The goal of this perception process is to maintain a minimum density of blocks available to the robots for construction. To maintain this density, the allocation of robots to the foraging task needs to be adjusted such that enough blocks are retrieved. Our results show a robust collective perception that enables the swarm to maintain a minimum block density under different rates of construction and foraging. Our approach leads the system to stabilize around a state in which the robots allocation allows the swarm to maintain a tile density that is close to or above the target minimum.info:eu-repo/semantics/publishedDorigo, M. Stützle, T. Blesa, M. J. Blum, C. Hamann, H. Heinrich, M. K. & Strobel, V. (2020). Swarm Intelligence: 12th International Conference, ANTS 2020, Barcelona, Spain, October 26-28, 2020, Proceedings. Cham: Springer International Publishing AG

Functional Dissection of the Proton Pumping Modules of Mitochondrial Complex I

A catalytically active subcomplex of respiratory chain complex I lacks 14 of its 42 subunits yet retains half of its proton-pumping capacity, indicating that its membrane arm has two pump modules

Environment influences on the aromatic character of nucleobases and amino acids

Geometric (HOMA) and magnetic (NICS) indices of aromaticity were estimated for aromatic rings of amino acids and nucleobases. Cartesian coordinates were taken directly either from PDB files deposited in public databases at the finest resolution available (≤1.5 Å), or from structures resulting from full gradient geometry optimization in a hybrid QM/MM approach. Significant environmental effects imposing alterations of HOMA values were noted for all aromatic rings analysed. Furthermore, even extra fine resolution (≤1.0 Å) is not sufficient for direct estimation of HOMA values based on Cartesian coordinates provided by PDB files. The values of mean bond errors seem to be much higher than the 0.05 Å often reported for PDB files. The use of quantum chemistry geometry optimization is strongly advised; even a simple QM/MM model comprising only the aromatic substructure within the QM region and the rest of biomolecule treated classically within the MM framework proved to be a promising means of describing aromaticity inside native environments. According to the results presented, three consequences of the interaction with the environment can be observed that induce changes in structural and magnetic indices of aromaticity. First, broad ranges of HOMA or NICS values are usually obtained for different conformations of nearest neighborhood. Next, these values and their means can differ significantly from those characterising isolated monomers. The most significant increase in aromaticities is expected for the six-membered rings of guanine, thymine and cytosine. The same trend was also noticed for all amino acids inside proteins but this effect was much smaller, reaching the highest value for the five-membered ring of tryptophan. Explicit water solutions impose similar changes on HOMA and NICS distributions. Thus, environment effects of protein, DNA and even explicit water molecules are non-negligible sources of aromaticity changes appearing in the rings of nucleobases and aromatic amino acids residues