https://www.cell.com/trends/microbiology/pdf/S0966-842X(04)00264-1.pdf

Survival strategies of infectious biofilms.

The programmable and reliable hybridization of DNA strands has enabled the preparation of a wide variety of structures. This Review discusses how, in addition to these static assemblies, the process of displacing — and ultimately replacing — strands also makes possible the construction of dynamic systems such as logic gates or autonomous walkers.

/pdf/dynamic-dna-nanotechnology-using-strand-displacement-3n3nflfseh.pdf

Dynamic DNA nanotechnology using strand-displacement reactions

The sigma(S) (RpoS) subunit of RNA polymerase is the master regulator of the general stress response in Escherichia coli and related bacteria. While rapidly growing cells contain very little sigma(S), exposure to many different stress conditions results in rapid and strong sigma(S) induction. Consequently, transcription of numerous sigma(S)-dependent genes is activated, many of which encode gene products with stress-protective functions. Multiple signal integration in the control of the cellular sigma(S) level is achieved by rpoS transcriptional and translational control as well as by regulated sigma(S) proteolysis, with various stress conditions differentially affecting these levels of sigma(S) control. Thus, a reduced growth rate results in increased rpoS transcription whereas high osmolarity, low temperature, acidic pH, and some late-log-phase signals stimulate the translation of already present rpoS mRNA. In addition, carbon starvation, high osmolarity, acidic pH, and high temperature result in stabilization of sigma(S), which, under nonstress conditions, is degraded with a half-life of one to several minutes. Important cis-regulatory determinants as well as trans-acting regulatory factors involved at all levels of sigma(S) regulation have been identified. rpoS translation is controlled by several proteins (Hfq and HU) and small regulatory RNAs that probably affect the secondary structure of rpoS mRNA. For sigma(S) proteolysis, the response regulator RssB is essential. RssB is a specific direct sigma(S) recognition factor, whose affinity for sigma(S) is modulated by phosphorylation of its receiver domain. RssB delivers sigma(S) to the ClpXP protease, where sigma(S) is unfolded and completely degraded. This review summarizes our current knowledge about the molecular functions and interactions of these components and tries to establish a framework for further research on the mode of multiple signal input into this complex regulatory system.

Signal transduction and regulatory mechanisms involved in control of the sigma(S) (RpoS) subunit of RNA polymerase.

Inorganic polyphosphate (poly P) is a chain of tens or many hundreds of phosphate (Pi) residues linked by high-energy phosphoanhydride bonds. Despite inorganic polyphosphate's ubiquity--found in every cell in nature and likely conserved from prebiotic times--this polymer has been given scant attention. Among the reasons for this neglect of poly P have been the lack of sensitive, definitive, and facile analytical methods to assess its concentration in biological sources and the consequent lack of demonstrably important physiological functions. This review focuses on recent advances made possible by the introduction of novel, enzymatically based assays. The isolation and ready availability of Escherichia coli polyphosphate kinase (PPK) that can convert poly P and ADP to ATP and of a yeast exopolyphosphatase that can hydrolyze poly P to Pi, provide highly specific, sensitive, and facile assays adaptable to a high-throughput format. Beyond the reagents afforded by the use of these enzymes, their genes, when identified, mutated, and overexpressed, have offered insights into the physiological functions of poly P. Most notably, studies in E. coli reveal large accumulations of poly P in cellular responses to deficiencies in an amino acid, Pi, or nitrogen or to the stresses of a nutrient downshift or high salt. The ppk mutant, lacking PPK and thus severely deficient in poly P, also fails to express RpoS (a sigma factor for RNA polymerase), the regulatory protein that governs > or = 50 genes responsible for stationary-phase adaptations to resist starvation, heat and oxidant stresses, UV irradiation, etc. Most dramatically, ppk mutants die after only a few days in stationary phase. The high degree of homology of the PPK sequence in many bacteria, including some of the major pathogenic species (e.g. Mycobacterium tuberculosis, Neisseria meningitidis, Helicobacter pylori, Vibrio cholerae, Salmonella typhimurium, Shigella flexneri, Pseudomonas aeruginosa, Bordetella pertussis, and Yersinia pestis), has prompted the knockout of their ppk gene to determine the dependence of virulence on poly P and the potential of PPK as a target for antimicrobial drugs. In yeast and mammalian cells, exo- and endopolyphosphatases have been identified and isolated, but little is known about the synthesis of poly P or its physiologic functions. Whether microbe or human, all species depend on adaptations in the stationary phase, which is truly a dynamic phase of life. Most research is focused on the early and reproductive phases of organisms, which are rather brief intervals of rapid growth. More attention needs to be given to the extensive period of maturity. Survival of microbial species depends on being able to manage in the stationary phase. In view of the universality and complexity of basic biochemical mechanisms, it would be surprising if some of the variety of poly P functions observed in microorganisms did not apply to aspects of human growth and development, to aging, and to the aberrations of disease. Of theoretical interest regarding poly P is its antiquity in prebiotic evolution, which along with its high energy and phosphate content, make it a plausible precursor to RNA, DNA, and proteins. Practical interest in poly P includes many industrial applications, among which is the microbial removal of Pi in aquatic environments.

Inorganic polyphosphate: a molecule of many functions.

Under conditions of nutrient deprivation or stress, or as cells enter stationary phase, Escherichia coli and related bacteria increase the accumulation of RpoS, a specialized sigma factor. RpoS-dependent gene expression leads to general stress resistance of cells. During rapid growth, RpoS translation is inhibited and any RpoS protein that is synthesized is rapidly degraded. The complex transition from exponential growth to stationary phase has been partially dissected by analyzing the induction of RpoS after specific stress treatments. Different stress conditions lead to induction of specific sRNAs that stimulate RpoS translation or to induction of small-protein antiadaptors that stabilize the protein. Recent progress has led to a better, but still far from complete, understanding of how stresses lead to RpoS induction and what RpoS-dependent genes help the cell deal with the stress.

The RpoS-mediated general stress response in Escherichia coli.

Inorganic polyphosphate [poly(P)] levels in Escherichia coli were reduced to barely detectable concentrations by expression of the plasmid-borne gene for a potent yeast exopolyphosphatase [poly(P)ase]. As a consequence, resistance to H2O2 was greatly diminished, particularly in katG (catalase HPI) mutants, implying a major role for the other catalase, the stationary-phase KatE (HPII), which is rpoS dependent. Resistance was restored to wild-type levels by complementation with plasmids expressing ppk, the gene for PPK [the polyphosphate kinase that generates poly(P)]. Induction of expression of both katE and rpoS (the stationary-phase sigma factor) was prevented in cells in which the poly(P)ase was overproduced. Inasmuch as this inhibition by poly(P)ase did not affect the levels of the stringent-response guanosine nucleotides (pppGpp and ppGpp) and in view of the capacity of additional rpoS expression to suppress the poly(P)ase inhibition of katE expression, a role is proposed for poly(P) in inducing the expression of rpoS.

https://www.pnas.org/content/pnas/94/21/11210.full.pdf

Inorganic polyphosphate and the induction of rpoS expression

A Novel ATP Regeneration System Using Polyphosphate-AMP Phosphotransferase and Polyphosphate Kinase

We have developed an algorithm for designing multiple sequences of nucleic acids that have a uniform melting temperature between the sequence and its complement and that do not hybridize non-specifically with each other based on the minimum free energy (DeltaG (min)). Sequences that satisfy these constraints can be utilized in computations, various engineering applications such as microarrays, and nano-fabrications. Our algorithm is a random generate-and-test algorithm: it generates a candidate sequence randomly and tests whether the sequence satisfies the constraints. The novelty of our algorithm is that the filtering method uses a greedy search to calculate DeltaG (min). This effectively excludes inappropriate sequences before DeltaG (min) is calculated, thereby reducing computation time drastically when compared with an algorithm without the filtering. Experimental results in silico showed the superiority of the greedy search over the traditional approach based on the hamming distance. In addition, experimental results in vitro demonstrated that the experimental free energy (DeltaG (exp)) of 126 sequences correlated well with DeltaG (min) (|R| = 0.90) than with the hamming distance (|R| = 0.80). These results validate the rationality of a thermodynamic approach. We implemented our algorithm in a graphic user interface-based program written in Java.

/pdf/design-of-nucleic-acid-sequences-for-dna-computing-based-on-99jcrtgljb.pdf

Design of nucleic acid sequences for DNA computing based on a thermodynamic approach

All 64 possible thermodynamic parameters for a single-bulge loop in the middle of a sequence were derived from optical melting studies. The relative stability of a single bulge depended on both the type of bulged base and its flanking base pairs. The contribution of the single bulge to helix stability ranged from 3.69 kcal/mol for a TAT bulge to -1.05 kcal/mol for an ACC bulge. Thermodynamics for 10 sequences with a GTG bulge were determined to test the applicability of the nearest-neighbor model to a single-bulge loop. Thermodynamic parameters for the GTG bulge and Watson-Crick base pairs predict, DeltaH degrees, DeltaS degrees, and T(M)(50 microM) values with average deviations of 3.0%, 4.3%, 4.7%, and 0.9 degrees C, respectively. The prediction accuracy was within the limits of what can be expected for a nearest-neighbor model. This certified that the thermodynamics for single-bulge loops can be estimated adequately using a nearest-neighbor model.

Thermodynamic parameters based on a nearest-neighbor model for DNA sequences with a single-bulge loop.

In the field of DNA computing, more and more efforts are made for constructing molecular machines made of DNA that work in vitro or in vivo. States of some of those machines are represented by their conformations, such as hairpin and bulge loops, and state transitions are realized by conformational changes, in which such loops are opened. The ultimate goal of this study is to implement not only independent molecular machines, but also networks of interacting machines, called chain reaction systems, where a conformational change of one machine triggers a conformational change of another machine in a cascaded manner. A chain reaction system would result in a much larger computational power than a single machine in the number of states and in the complexity of computation. As a simple example, we propose a general-purpose molecular system consisting of logical gates and sensors. As a more complex example, we present a new idea of constructing a DNA automaton by a chain reaction system, which can have an arbitrary number of states.

/pdf/chain-reaction-systems-based-on-loop-dissociation-of-dna-fexelktp4f.pdf

Atsushi Kameda

Papers

Inorganic polyphosphate and the induction of rpoS expression

A Novel ATP Regeneration System Using Polyphosphate-AMP Phosphotransferase and Polyphosphate Kinase

Design of nucleic acid sequences for DNA computing based on a thermodynamic approach

Thermodynamic parameters based on a nearest-neighbor model for DNA sequences with a single-bulge loop.

Chain reaction systems based on loop dissociation of DNA