Vaguery + molecular-biology   14

Supermultiplexed optical imaging and barcoding with engineered polyynes | Nature Methods
Optical multiplexing has a large impact in photonics, the life sciences and biomedicine. However, current technology is limited by a 'multiplexing ceiling' from existing optical materials. Here we engineered a class of polyyne-based materials for optical supermultiplexing. We achieved 20 distinct Raman frequencies, as 'Carbon rainbow', through rational engineering of conjugation length, bond-selective isotope doping and end-capping substitution of polyynes. With further probe functionalization, we demonstrated ten-color organelle imaging in individual living cells with high specificity, sensitivity and photostability. Moreover, we realized optical data storage and identification by combinatorial barcoding, yielding to our knowledge the largest number of distinct spectral barcodes to date. Therefore, these polyynes hold great promise in live-cell imaging and sorting as well as in high-throughput diagnostics and screening.
materials-science  nanotechnology  indistinguishable-from-magic  molecular-design  molecular-biology  to-write-about  rather-interesting 
december 2018 by Vaguery
Scientists Create Alternate Evolutionary Histories in Test Tube
Thornton said that deep mutational scanning will be a powerful tool for evolutionary biologists, geneticists and biochemists, and he looks forward to using the approach on successive ancestors at different points in history to see how the set of possible outcomes changed through time.
scanning-mutagenesis  hey-that-was-chapter-three-of-my-thesis-project  biological-engineering  molecular-biology  practical-genomics  reverse-bioinformatics 
september 2017 by Vaguery
[1605.01941] Partial DNA Assembly: A Rate-Distortion Perspective
Earlier formulations of the DNA assembly problem were all in the context of perfect assembly; i.e., given a set of reads from a long genome sequence, is it possible to perfectly reconstruct the original sequence? In practice, however, it is very often the case that the read data is not sufficiently rich to permit unambiguous reconstruction of the original sequence. While a natural generalization of the perfect assembly formulation to these cases would be to consider a rate-distortion framework, partial assemblies are usually represented in terms of an assembly graph, making the definition of a distortion measure challenging. In this work, we introduce a distortion function for assembly graphs that can be understood as the logarithm of the number of Eulerian cycles in the assembly graph, each of which correspond to a candidate assembly that could have generated the observed reads. We also introduce an algorithm for the construction of an assembly graph and analyze its performance on real genomes.
bioinformatics  algorithms  DNA-assembly  molecular-biology  statistics  inference  nudge-targets  consider:performance-measures 
may 2016 by Vaguery
Chromatin structure shapes the search process of transcription factors | bioRxiv
The diffusion of regulatory proteins within the nucleus plays a crucial role in the dynamics of transcriptional regulation. The standard model assumes a 3D plus 1D diffusion process: regulatory proteins either move freely in solution or slide on DNA. This model however does not considered the 3D structure of chromatin. Here we proposed a multi-scale stochastic model that integrates, for the first time, high-resolution information on chromatin structure as well as DNA-protein interactions. The dynamics of transcription factors was modeled as a slide plus jump diffusion process on a chromatin network based on pair-wise contact maps obtained from high-resolution Hi-C experiments. Our model allowed us to uncover the effects of chromatin structure on transcription factor occupancy profiles and target search times. Finally, we showed that binding sites clustered on few topological associated domains leading to a higher local concentration of transcription factors which could reflect an optimal strategy to efficiently use limited transcriptional resources.
structural-biology  molecular-design  molecular-biology  systems-biology  bioinformatics  it's-more-complicated-than-you-think 
may 2016 by Vaguery
[1505.01215] Binding of transcription factors adapts to resolve information-energy trade-off
We examine the binding of transcription factors to DNA in terms of an information transfer problem. The input of the noisy channel is the biophysical signal of a factor bound to a DNA site, and the output is a distribution of probable DNA sequences at this site. This task involves an inherent tradeoff between the information gain and the energetics of the binding interaction - high binding energies provide higher information gain but hinder the dynamics of the system as factors are bound too tightly. We show that adaptation of the binding interaction towards increasing information transfer under a general energy constraint implies that the information gain per specific binding energy at each base-pair is maximized. We analyze hundreds of prokaryote and eukaryote transcription factors from various organisms to evaluate the discrimination energies. We find that, in accordance with our theoretical argument, binding energies nearly maximize the information gain per energy. This work suggests the adaptation of information gain as a generic design principle of molecular recognition systems.
molecular-design  molecular-biology  information-theory  theoretical-biology  adaptationism  robustness 
march 2016 by Vaguery
[1501.04648] Fast, approximate kinetics of RNA folding
In this paper, we introduce the software suite, Hermes, which provides fast, novel algorithms for RNA secondary structure kinetics. Using the fast Fourier transform to e?ciently compute the Boltzmann probability that a secondary structure S of a given RNA sequence has base pair distance x [resp. y] from reference structure A [resp. B], Hermes computes the exact kinetics of folding from A to B in this coarse-grained model. In particular, Hermes computes the mean ?rst passage time from the transition probability matrix by using matrix inversion, and also computes the equilibrium time from the rate matrix by using spectral decomposition. Due to the model granularity and the speed of Hermes, it is capable of determining secondary structure refolding kinetics for large RNA sequences, beyond the range of other methods. Comparative benchmarking of Hermes with other methods indicates that Hermes provides refolding kinetics of accuracy suitable for use in computational design of RNA, an important area of synthetic biology. Source code and documentation for Hermes are available at this http URL
RNA  molecular-biology  biophysics  bioinformatics  optimization  simulation  approximation  algorithms  nudge-targets  consider:representation  rather-interesting 
november 2015 by Vaguery
[1412.8634] Transcriptional bursting in gene expression: analytical results for general stochastic models
Gene expression in individual cells is highly variable and sporadic, often resulting in the synthesis of mRNAs and proteins in bursts. Bursting in gene expression is known to impact cell-fate in diverse systems ranging from latency in HIV-1 viral infections to cellular differentiation. It is generally assumed that bursts are geometrically distributed and that they arrive according to a Poisson process. On the other hand, recent single-cell experiments provide evidence for complex burst arrival processes, highlighting the need for more general stochastic models. To address this issue, we invoke a mapping between general models of gene expression and systems studied in queueing theory to derive exact analytical expressions for the moments associated with mRNA/protein steady-state distributions. These moments are then used to derive explicit conditions, based entirely on experimentally measurable quantities, that determine if the burst distributions deviate from the geometric distribution or if burst arrival deviates from a Poisson process. For non-Poisson arrivals, we develop approaches for accurate estimation of burst parameters.
biophysics  molecular-machinery  molecular-biology  queueing-theory  planning  inference  rather-interesting  models  nudge-targets 
june 2015 by Vaguery
Software for the analysis and visualization of deep mutational scanning data | bioRxiv
Background Deep mutational scanning is a technique to estimate the impacts of mutations on a gene by using deep sequencing to count mutations in a library of variants before and after imposing a functional selection. The impacts of mutations must be inferred from changes in their counts after selection. Results I describe a software package, dms_tools, to infer the impacts of mutations from deep mutational scanning data using a likelihood-based treatment of the mutation counts. I show that dms_tools yields more accurate inferences on simulated data than the widely used but statistically biased approach of calculating ratios of counts pre- and post-selection. Using dms_tools, one can infer the preference of each site for each amino acid given a single selection pressure, or assess the extent to which these preferences change under different selection pressures. The preferences and their changes can be intuitively visualized with sequence-logo-style plots created using an extension to weblogo. Conclusions dms_tools implements a statistically principled approach for the analysis and subsequent visualization of deep mutational scanning data.
bioinformatics  systems-biology  molecular-biology  statistics  data-analysis  rather-interesting  consider:adapt-for-GP 
may 2015 by Vaguery
Systematic Imaging Reveals Features of Localized mRNAs and Their Changing Subcellular Destinations in Development | bioRxiv
The asymmetric distribution of cytoplasmic components by mRNA localization is critical for eukaryotic cells and affects large numbers of transcripts. How such global subcellular localization of mRNAs is regulated is still unknown. We combined transcriptomics and systematic imaging to determine tissue-specific expression and subcellular localizations of 5862 mRNAs during Drosophila oogenesis. While the transcriptome is stable and alternative splicing and polyadenylation is rare, cytoplasmic localization of mRNAs is widespread. Localized mRNAs have distinct gene features and diverge in expression level, 3'UTR length and sequence conservation. We show that intracellular localization of mRNAs depends on an intact microtubule cytoskeleton and that specifically the posterior enrichment requires the localization of oskar mRNA to the posterior cortex. Using cross-tissue comparison we revealed that the localization landscape differs substantially between epithelial, germline and embryonic cells and the localization status of mRNAs also changes considerably within the oocyte over the course of oogenesis.
evo-devo  developmental-biology  experiment  molecular-biology  visualization  dynamical-systems  rather-interesting  molecular-design  biological-engineering  self-organization  design-patterns 
november 2014 by Vaguery
[1410.0652] Using Simulations and kinetic network models to reveal the dynamics and functions of Riboswitches
Riboswitches, RNA elements found in the untranslated region, regulate gene expression by binding to target metaboloites with exquisite specificity. Binding of metabolites to the conserved aptamer domain allosterically alters the conformation in the downstream expression platform. The fate of gene expression is determined by the changes in the downstream RNA sequence. As the metabolite-dependent cotranscriptional folding and unfolding dynamics of riboswitches is the key determinant of gene expression, it is important to investigate both the thermodynamics and kinetics of riboswitches both in the presence and absence of metabolite. Single molecule force experiments that decipher the free energy landscape of riboswitches from their mechanical responses, theoretical and computational studies have recently shed light on the distinct mechanism of folding dynamics in different classes of riboswitches. Here we first discuss the dynamics of water around riboswitch, highlighting that water dynamics can enhance the fluctuation of nucleic acid structure. To go beyond native state fluctuations we used the Self-Organized Polymer (SOP) model to predict the dynamics of add adenine riboswitch under mechanical forces. In addition to quantitatively predicting the folding landscape of add-riboswitch our simulations also explain the difference in the dynamics between pbuE adenine- and add adenine-riboswitches. In order to probe the function {\it in vivo} we use the folding landscape to propose a system level kinetic network model to quantitatively predict how gene expression is regulated for riboswitches that are under kinetic control.
molecular-machinery  molecular-biology  biochemistry  macromolecules  biological-engineering  nanotechnology  experiment  simulation  nudge-targets  consider:rule-discovery 
october 2014 by Vaguery
[1210.0234] Using Ciliate Operations to construct Chromosome Phylogenies
We develop an algorithm based on three basic DNA editing operations suggested by a model for ciliate micronuclear decryption, to transform a given permutation into another. The number of ciliate operations performed by our algorithm during such a transformation is taken to be the distance between two such permutations. Applying well-known clustering methods to such distance functions enables one to determine phylogenies among the items to which the distance functions apply. As an application of these ideas we explore the relationships among the chromosomes of eight fruitfly (drosophila) species, using the well-known UPGMA algorithm on the distance function provided by our algorithm.
phylogenetics  molecular-biology  about-damned-time  string-editing  algorithms  nudge-targets  interesting  rewriting-systems  bioinformatics  genetics  remember:Norm-Alldridge-in-1985 
april 2014 by Vaguery
[1310.3185] Optimization of collective enzyme activity via spatial localization
The spatial organization of enzymes often plays a crucial role in the functionality and efficiency of enzymatic pathways. To fully understand the design and operation of enzymatic pathways, it is therefore crucial to understand how the relative arrangement of enzymes affects pathway function. Here we investigate the effect of enzyme localization on the flux of a minimal two-enzyme pathway within a reaction-diffusion model. We consider different reaction kinetics, spatial dimensions, and loss mechanisms for intermediate substrate molecules. Our systematic analysis of the different regimes of this model reveals both universal features and distinct characteristics in the phenomenology of these different systems. In particular, the distribution of the second pathway enzyme that maximizes the reaction flux undergoes a generic transition from co-localization with the first enzyme when the catalytic efficiency of the second enzyme is low, to an extended profile when the catalytic efficiency is high. However, the critical transition point and the shape of the extended optimal profile is significantly affected by specific features of the model. We explain the behavior of these different systems in terms of the underlying stochastic reaction and diffusion processes of single substrate molecules.
structural-biology  systems-biology  space-matters  departures-from-the-ideal  molecular-biology 
december 2013 by Vaguery
[1310.5778] Interplay between single-stranded binding proteins on RNA secondary structure
RNA protein interactions control the fate of cellular RNAs and play an important role in gene regulation. An interdependency between such interactions allows for the implementation of logic functions in gene regulation. We investigate the interplay between RNA binding partners in the context of the statistical physics of RNA secondary structure, and define a linear correlation function between the two partners as a measurement of the interdependency of their binding events. We demonstrate the emergence of a long-range power-law behavior of this linear correlation function. This suggests RNA secondary structure driven interdependency between binding sites as a general mechanism for combinatorial post-transcriptional gene regulation.
RNA  structural-biology  molecular-biology  molecular-machinery  bioinformatics 
november 2013 by Vaguery
[1303.2411] RNA-Seq Mapping Errors When Using Incomplete Reference Transcriptomes of Vertebrates
Whole transcriptome sequencing is increasingly being used as a functional genomics tool to study non- model organisms. However, when the reference transcriptome used to calculate differential expression is incomplete, significant error in the inferred expression levels can result. In this study, we use simulated reads generated from real transcriptomes to determine the accuracy of read mapping, and measure the error resulting from using an incomplete transcriptome. We show that the two primary sources of count- ing error are 1) alternative splice variants that share reads and 2) missing transcripts from the reference. Alternative splice variants increase the false positive rate of mapping while incomplete reference tran- scriptomes decrease the true positive rate, leading to inaccurate transcript expression levels. Grouping transcripts by gene or read sharing (similar to mapping to a reference genome) significantly decreases false positives, but only by improving the reference transcriptome itself can the missing transcript problem be addressed. We also demonstrate that employing different mapping software does not yield substantial increases in accuracy on simulated data. Finally, we show that read lengths or insert sizes must increase past 1kb to resolve mapping ambiguity.
molecular-biology  mRNA  bioinformatics  inference  sequencing  error  statistics  simulation 
march 2013 by Vaguery

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