Dmitri S. Pavlichin

Single Molecule Analysis Research Tool (SMART): An Integrated Approach for Analyzing Single Molecule Data

Single molecule studies have expanded rapidly over the past decade and have the ability to provide an unprecedented level of understanding of biological systems. A common challenge upon introduction of novel, data-rich approaches is the management, processing, and analysis of the complex data sets that are generated. We provide a standardized approach for analyzing these data in the freely available software package SMART: Single Molecule Analysis Research Tool. SMART provides a format for organizing and easily accessing single molecule data, a general hidden Markov modeling algorithm for fitting an array of possible models specified by the user, a standardized data structure and graphical user interfaces to streamline the analysis and visualization of data. This approach guides experimental design, facilitating acquisition of the maximal information from single molecule experiments. SMART also provides a standardized format to allow dissemination of single molecule data and transparency in the analysis of reported data.

Specification of photonic circuits using quantum hardware description language

Following the simple observation that the interconnection of a set of quantum optical input–output devices can be specified using structural mode VHSIC hardware description language, we demonstrate a computer-aided schematic capture workflow for modelling and simulating multi-component photonic circuits. We describe an algorithm for parsing circuit descriptions to derive quantum equations of motion, illustrate our approach using simple examples based on linear and cavity-nonlinear optical components, and demonstrate a computational approach to hierarchical model reduction.

The Human Genome Contracts Again

UNLABELLED The number of human genomes that have been sequenced completely for different individuals has increased rapidly in recent years. Storing and transferring complete genomes between computers for the purpose of applying various applications and analysis tools will soon become a major hurdle, hindering the analysis phase. Therefore, there is a growing need to compress these data efficiently. Here, we describe a technique to compress human genomes based on entropy coding, using a reference genome and known Single Nucleotide Polymorphisms (SNPs). Furthermore, we explore several intrinsic features of genomes and information in other genomic databases to further improve the compression attained. Using these methods, we compress James Watsons genome to 2.5 megabytes (MB), improving on recent work by 37%. Similar compression is obtained for most genomes available from the 1000 Genomes Project. Our biologically inspired techniques promise even greater gains for genomes of lower organisms and for human genomes as more genomic data become available. AVAILABILITY Code is available at sourceforge.net/projects/genomezip/

Design of nanophotonic circuits for autonomous subsystem quantum error correction

We reapply our approach to designing nanophotonic quantum memories in order to formulate an optical network that autonomously protects a single logical qubit against arbitrary single-qubit errors. Emulating the nine-qubit Bacon–Shor subsystem code, the network replaces the traditionally discrete syndrome measurement and correction steps by continuous, time-independent optical interactions and coherent feedback of unitarily processed optical fields.

Roles of Long-Range Tertiary Interactions in Limiting Dynamics of the Tetrahymena Group I Ribozyme

We determined the effects of mutating the long-range tertiary contacts of the Tetrahymena group I ribozyme on the dynamics of its substrate helix (referred to as P1) and on catalytic activity. Dynamics were assayed by fluorescence anisotropy of the fluorescent base analogue, 6-methyl isoxanthopterin, incorporated into the P1 helix, and fluorescence anisotropy and catalytic activity were measured for wild type and mutant ribozymes over a range of conditions. Remarkably, catalytic activity correlated with P1 anisotropy over 5 orders of magnitude of activity, with a correlation coefficient of 0.94. The functional and dynamic effects from simultaneous mutation of the two long-range contacts that weaken P1 docking are cumulative and, based on this RNA’s topology, suggest distinct underlying origins for the mutant effects. Tests of mechanistic predictions via single molecule FRET measurements of rate constants for P1 docking and undocking suggest that ablation of the P14 tertiary interaction frees P2 and thereby enhances the conformational space explored by the undocked attached P1 helix. In contrast, mutation of the metal core tertiary interaction disrupts the conserved core into which the P1 helix docks. Thus, despite following a single correlation, the two long-range tertiary contacts facilitate P1 helix docking by distinct mechanisms. These results also demonstrate that a fluorescence anisotropy probe incorporated into a specific helix within a larger RNA can report on changes in local helical motions as well as differences in more global dynamics. This ability will help uncover the physical properties and behaviors that underlie the function of RNAs and RNA/protein complexes.

Single-molecule dataset (SMD): a generalized storage format for raw and processed single-molecule data

BackgroundSingle-molecule techniques have emerged as incisive approaches for addressing a wide range of questions arising in contemporary biological research [Trends Biochem Sci 38:30–37, 2013; Nat Rev Genet 14:9–22, 2013; Curr Opin Struct Biol 2014, 28C:112–121; Annu Rev Biophys 43:19–39, 2014]. The analysis and interpretation of raw single-molecule data benefits greatly from the ongoing development of sophisticated statistical analysis tools that enable accurate inference at the low signal-to-noise ratios frequently associated with these measurements. While a number of groups have released analysis toolkits as open source software [J Phys Chem B 114:5386–5403, 2010; Biophys J 79:1915–1927, 2000; Biophys J 91:1941–1951, 2006; Biophys J 79:1928–1944, 2000; Biophys J 86:4015–4029, 2004; Biophys J 97:3196–3205, 2009; PLoS One 7:e30024, 2012; BMC Bioinformatics 288 11(8):S2, 2010; Biophys J 106:1327–1337, 2014; Proc Int Conf Mach Learn 28:361–369, 2013], it remains difficult to compare analysis for experiments performed in different labs due to a lack of standardization.ResultsHere we propose a standardized single-molecule dataset (SMD) file format. SMD is designed to accommodate a wide variety of computer programming languages, single-molecule techniques, and analysis strategies. To facilitate adoption of this format we have made two existing data analysis packages that are used for single-molecule analysis compatible with this format.ConclusionAdoption of a common, standard data file format for sharing raw single-molecule data and analysis outcomes is a critical step for the emerging and powerful single-molecule field, which will benefit both sophisticated users and non-specialists by allowing standardized, transparent, and reproducible analysis practices.

Kinetic and thermodynamic framework for P4-P6 RNA reveals tertiary motif modularity and modulation of the folding preferred pathway.

Significance Many biological processes, including splicing, translation, and genome maintenance, require structured RNAs to fold into complex three-dimensional shapes. Our current understanding of these processes is based on distilling principles from descriptive folding studies. Moving toward predictive models will require coupling observed structural changes with kinetic and thermodynamic measurements. We have dissected P4-P6 RNA folding through distinct structural states and measured the rate and equilibrium constants for transitions between these states. Common kinetics found for RNA tertiary elements embedded in different structural contexts may help develop predictive folding models. Also, our results suggest that RNA folding may be well described by a model analogous to the diffusion-collision model for protein folding. The past decade has seen a wealth of 3D structural information about complex structured RNAs and identification of functional intermediates. Nevertheless, developing a complete and predictive understanding of the folding and function of these RNAs in biology will require connection of individual rate and equilibrium constants to structural changes that occur in individual folding steps and further relating these steps to the properties and behavior of isolated, simplified systems. To accomplish these goals we used the considerable structural knowledge of the folded, unfolded, and intermediate states of P4-P6 RNA. We enumerated structural states and possible folding transitions and determined rate and equilibrium constants for the transitions between these states using single-molecule FRET with a series of mutant P4-P6 variants. Comparisons with simplified constructs containing an isolated tertiary contact suggest that a given tertiary interaction has a stereotyped rate for breaking that may help identify structural transitions within complex RNAs and simplify the prediction of folding kinetics and thermodynamics for structured RNAs from their parts. The preferred folding pathway involves initial formation of the proximal tertiary contact. However, this preference was only ∼10 fold and could be reversed by a single point mutation, indicating that a model akin to a protein-folding contact order model will not suffice to describe RNA folding. Instead, our results suggest a strong analogy with a modified RNA diffusion-collision model in which tertiary elements within preformed secondary structures collide, with the success of these collisions dependent on whether the tertiary elements are in their rare binding-competent conformations.

Transformation of Quantum Photonic Circuit Models by Term Rewriting

The development of practical methods for synthesis and verification of complex photonic circuits presents a grand challenge for the nascent field of quantum engineering. Of course, classical electrical engineering provides essential foundations and serves to illustrate the degree of sophistication that can be achieved in automated circuit design. In this paper, we explore the utility of term rewriting approaches to the transformation of quantum circuit models, specifically applying rewrite rules for both reduction/verification and robustness analysis of photonic circuits for autonomous quantum error correction. We outline a workflow for quantum photonic circuit analysis that leverages the Modelica framework for multidomain physical modeling, which parallels a previously described approach based on VHSIC Hardware Description Language (VHDL).

Photonic circuits for iterative decoding of a class of low-density parity-check codes

Photonic circuits in which stateful components are coupled via guided electromagnetic fields are natural candidates for resource-efficient implementation of iterative stochastic algorithms based on propagation of information around a graph. Conversely, such message=passing algorithms suggest novel circuit architectures for signal processing and computation that are well matched to nanophotonic device physics. Here, we construct and analyze a quantum optical model of a photonic circuit for iterative decoding of a class of low-density parity-check (LDPC) codes called expander codes. Our circuit can be understood as an open quantum system whose autonomous dynamics map straightforwardly onto the subroutines of an LDPC decoding scheme, with several attractive features: it can operate in the ultra-low power regime of photonics in which quantum fluctuations become significant, it is robust to noise and component imperfections, it achieves comparable performance to known iterative algorithms for this class of codes, and it provides an instructive example of how nanophotonic cavity quantum electrodynamic components can enable useful new information technology even if the solid-state qubits on which they are based are heavily dephased and cannot support large-scale entanglement.

The dressed atom as binary phase modulator: towards attojoule/edge optical phase-shift keying

We use a single 133Cs atom strongly coupled to an optical resonator to induce random binary phase modulation of a near infra-red, ∼ 500 pW laser beam, with each modulation edge caused by the dissipation of a single photon (≈ 0.23 aJ) by the atom. While our ability to deterministically induce phase edges with an additional optical control beam is limited thus far, theoretical analysis of an analogous, solid-state system indicates that efficient external control should be achievable in demonstrated nanophotonic systems.