Structural Dynamics of the Bacillus subtilis MntR Transcription Factor Is Locked by Mn2+ Binding

Molecular basis of protein-DNA interactions between Halalkalibacterium halodurans MntR and its DNA operator sequence

Transition metals such as iron, zinc and manganese are essential for bacterial survival. A pivotal role in regulation of manganese homeostasis in bacterium Halalkalibacterium halodurans has MntR protein (HhMntR). In this work, molecular dynamics simulations of holoprotein (with Mn2+) and apoprotein (without Mn2+) HhMntR in complex with DNA mntA operator were conducted and enabled understanding of interaction between HhMntR and DNA on molecular level. Molecular mechanism through which affinity of HhMntR towards DNA is increased upon Mn2+ binding was revealed. Holoprotein binds DNA through stable and consistent noncovalent interactions, while apoprotein shows highly dynamic behavior, attaching to and detaching from the DNA backbone and inner grooves on a nanosecond time scale. The same observations are seen even during the simulations that started with protein and DNA separated from the complex. Additionally, key amino acids involved in the formation of the HhMntR-DNA complex were identified, leading to the proposal of a molecular framework that allows HhMntR to perform its biological function as a transcription factor. Overall, observed behaviors promote the lateral movement of HhMntR along the DNA sequence, enabling the protein to remain close to the DNA while it seeks out specific base pairs for strong binding upon activation by Mn2+.

Exploring the manganese-dependent interaction between a transcription factor and its corresponding DNA: insights from gas-phase electrophoresis on a nES GEMMA instrument

Manganese ion homeostasis is vital for bacteria and is achieved via manganese-dependent transcription factors. Manganese mediation of transcription factor attachment to the corresponding oligonucleotide sequences can be investigated, e.g. via electrophoretic mobility shift assays (EMSA). Formation of specific biocomplexes leads to differences in the migration pattern upon gel electrophoresis. Focusing on electrophoresis in the gas-phase, applying a nano electrospray gas-phase electrophoretic mobility molecular analyzer (nES GEMMA) also known as nES differential mobility analyzer (nES DMA), and on transcription factors (MntR proteins) from Bacillus subtilis and Mycobacterium tuberculosis, we took interest in the gas-phase electrophoresis of the corresponding biospecific complexes. We compared nES GEMMA, separating analytes in the nanometer regime (a few to several hundred nm in diameter) in the gas-phase in their native state according to particle size, to EMSA data. Indeed we were able to demonstrate manganese-mediated attachment of MntR to target genomic sequences with both analytical techniques. Despite some inherent pitfalls of the nES GEMMA method like analyte/instrument surface interactions, we were able to detect the target complexes. Moreover, we were able to calculate the molecular weight (MW) of the obtained species by application of a correlation function based on nES GEMMA obtained data. As gas-phase electrophoresis also offers the possibility of offline hyphenation to orthogonal analysis techniques, we are confident that nES GEMMA measurements are not just complementary to EMSA, but will offer the possibility of further in-depth characterization of biocomplexes in the future.

Trajectory maps: molecular dynamics visualization and analysis

Molecular dynamics simulations generate trajectories that depict system's evolution in time and are analyzed visually and quantitatively. Commonly conducted analyses include RMSD, Rgyr, RMSF, and more. However, those methods are all limited by their strictly statistical nature. Here we present trajectory maps, a novel method to analyze and visualize protein simulation courses intuitively and conclusively. By plotting protein's backbone movements during the simulation as a heatmap, trajectory maps provide new tools to directly visualize protein behavior over time, compare multiple simulations, and complement established methods. A user-friendly Python application developed for this purpose is presented, alongside detailed documentation for easy usage and implementation. The method's validation is demonstrated on three case studies. Considering its benefits, trajectory maps are expected to adopt broad application in obtaining and communicating meaningful results of protein molecular dynamics simulations in many associated fields such as biochemistry, structural biology, pharmaceutical research etc.

Allosteric mechanism of MntR transcription factor from alkalophilic bacterium Halalkalibacterium halodurans

Bacterium Halalkalibacterium halodurans is an industrially important alkalophilic bacteria. It is recognized as a producer of enzymes such as β-galactosidase, xylanase, amylase and protease which are able to function at higher pH values and thus can be used in textile, food, paper industry and more. This bacterium, as any other bacterium, requires a sensitive mechanism for regulation of homeostasis of manganese ions (Mn2+) in order to survive. The key protein regulating this mechanism in H. halodurans is MntR - a transcriptional factor that binds to DNA and regulates the transcription of genes for proteins involved in manganese homeostasis. Long range all-atom molecular dynamics (MD) simulations, from 500 ns up to 1.25 µs, were used to study different forms of H. halodurans MntR in order to investigate the differences in the protein's structural and dynamical properties upon Mn2+ binding. Simulations revealed an allosteric mechanism which is activated by Mn2+ binding. The results of simulations show that Mn2+ binding alters the non-covalent interaction network of the protein structure which leads to a conformational change that primarily affects the positions of the DNA binding domains and, consequently, the DNA binding affinity of H. halodurans MntR. The key amino acid residues of the proposed mechanism were identified and their role in the proposed mechanism was computationally confirmed by MD simulations of in silico mutants.