Training-free Measures Based on Algorithmic Probability Identify High Nucleosome Occupancy in DNA Sequences

We introduce and study a set of training-free methods of information-theoretic and algorithmic complexity nature applied to DNA sequences to identify their potential capabilities to determine nucleosomal binding sites. We test our measures on well-studied genomic sequences of different sizes drawn from different sources. The measures reveal the known in vivo versus in vitro predictive discrepancies and uncover their potential to pinpoint (high) nucleosome occupancy. We explore different possible signals within and beyond the nucleosome length and find that complexity indices are informative of nucleosome occupancy. We compare against the gold standard (Kaplan model) and find similar and complementary results with the main difference that our sequence complexity approach. For example, for high occupancy, complexity-based scores outperform the Kaplan model for predicting binding representing a significant advancement in predicting the highest nucleosome occupancy following a training-free approach.Comment: 8 pages main text (4 figures), 12 total with Supplementary (1 figure

UCN-01 enhances cytotoxicity of irinotecan in colorectal cancer stem-like cells by impairing DNA damage response

Colorectal cancer (CRC) is one of the most common and lethal cancers worldwide. Despite recent progress, the prognosis of advanced stage CRC remains poor, mainly because of cancer recurrence and metastasis. The high morbidity and mortality of CRC has been recently ascribed to a small population of tumor cells that hold the potential of tumor initiation, i.e. cancer stem cells (CSCs), which play a pivotal role in cancer recurrence and metastasis and are not eradicated by current therapy. We screened CRC-SCs in vitro with a library of protein kinase inhibitors and showed that CRC-SCs are resistant to specific inhibition of the major signaling pathways involved in cell survival and proliferation. Nonetheless, broad-spectrum inhibition by the staurosporin derivative UCN-01 blocks CRC-SC growth and potentiates the activity of irinotecan in vitro and in vivo CRC-SC-derived models. Reverse-Phase Protein Microarrays (RPPA) revealed that, albeit CRC-SCs display individual phospho-proteomic profiles, sensitivity of CRC-SCs to UCN-01 relies on the interference with the DNA damage response mediated by Chk1. Combination of LY2603618, a specific Chk1/2 inhibitor, with irinotecan resulted in a significant reduction of CRC-SC growth in vivo, confirming that irinotecan treatment coupled to inhibition of Chk1 represents a potentially effective therapeutic approach for CRC treatment

Synthetic in vitro transcriptional oscillators

The construction of synthetic biochemical circuits from simple components illuminates how complex behaviors can arise in chemistry and builds a foundation for future biological technologies. A simplified analog of genetic regulatory networks, in vitro transcriptional circuits, provides a modular platform for the systematic construction of arbitrary circuits and requires only two essential enzymes, bacteriophage T7 RNA polymerase and Escherichia coli ribonuclease H, to produce and degrade RNA signals. In this study, we design and experimentally demonstrate three transcriptional oscillators in vitro. First, a negative feedback oscillator comprising two switches, regulated by excitatory and inhibitory RNA signals, showed up to five complete cycles. To demonstrate modularity and to explore the design space further, a positive-feedback loop was added that modulates and extends the oscillatory regime. Finally, a three-switch ring oscillator was constructed and analyzed. Mathematical modeling guided the design process, identified experimental conditions likely to yield oscillations, and explained the system's robust response to interference by short degradation products. Synthetic transcriptional oscillators could prove valuable for systematic exploration of biochemical circuit design principles and for controlling nanoscale devices and orchestrating processes within artificial cells

DNA meets the SVD

This paper introduces an important area of computational cell biology where complex, publicly available genomic data is being examined by linear algebra methods, with the aim of revealing biological and medical insights

High-throughput sequencing reveals a simple model of nucleosome energetics

We use nucleosome maps obtained by high-throughput sequencing to study sequence specificity of intrinsic histone-DNA interactions. In contrast with previous approaches, we employ an analogy between a classical one-dimensional fluid of finite-size particles in an arbitrary external potential and arrays of DNA-bound histone octamers. We derive an analytical solution to infer free energies of nucleosome formation directly from nucleosome occupancies measured in high-throughput experiments. The sequence-specific part of free energies is then captured by fitting them to a sum of energies assigned to individual nucleotide motifs. We have developed hierarchical models of increasing complexity and spatial resolution, establishing that nucleosome occupancies can be explained by systematic differences in mono- and dinucleotide content between nucleosomal and linker DNA sequences, with periodic dinucleotide distributions and longer sequence motifs playing a secondary role. Furthermore, similar sequence signatures are exhibited by control experiments in which genomic DNA is either sonicated or digested with micrococcal nuclease in the absence of nucleosomes, making it possible that current predictions based on high-throughput nucleosome positioning maps are biased by experimental artifacts.Comment: 36 pages, 13 figure

First-principles calculation of DNA looping in tethered particle experiments

We calculate the probability of DNA loop formation mediated by regulatory proteins such as Lac repressor (LacI), using a mathematical model of DNA elasticity. Our model is adapted to calculating quantities directly observable in Tethered Particle Motion (TPM) experiments, and it accounts for all the entropic forces present in such experiments. Our model has no free parameters; it characterizes DNA elasticity using information obtained in other kinds of experiments. [...] We show how to compute both the "looping J factor" (or equivalently, the looping free energy) for various DNA construct geometries and LacI concentrations, as well as the detailed probability density function of bead excursions. We also show how to extract the same quantities from recent experimental data on tethered particle motion, and then compare to our model's predictions. [...] Our model successfully reproduces the detailed distributions of bead excursion, including their surprising three-peak structure, without any fit parameters and without invoking any alternative conformation of the LacI tetramer. Indeed, the model qualitatively reproduces the observed dependence of these distributions on tether length (e.g., phasing) and on LacI concentration (titration). However, for short DNA loops (around 95 basepairs) the experiments show more looping than is predicted by the harmonic-elasticity model, echoing other recent experimental results. Because the experiments we study are done in vitro, this anomalously high looping cannot be rationalized as resulting from the presence of DNA-bending proteins or other cellular machinery. We also show that it is unlikely to be the result of a hypothetical "open" conformation of the LacI tetramer.Comment: See the supplement at http://www.physics.upenn.edu/~pcn/Ms/TowlesEtalSuppl.pdf . This revised version accepted for publication at Physical Biolog

High resolution mapping of Twist to DNA in Drosophila embryos: Efficient functional analysis and evolutionary conservation

Cis-regulatory modules (CRMs) function by binding sequence specific transcription factors, but the relationship between in vivo physical binding and the regulatory capacity of factor-bound DNA elements remains uncertain. We investigate this relationship for the well-studied Twist factor in Drosophila melanogaster embryos by analyzing genome-wide factor occupancy and testing the functional significance of Twist occupied regions and motifs within regions. Twist ChIP-seq data efficiently identified previously studied Twist-dependent CRMs and robustly predicted new CRM activity in transgenesis, with newly identified Twist-occupied regions supporting diverse spatiotemporal patterns (>74% positive, n = 31). Some, but not all, candidate CRMs require Twist for proper expression in the embryo. The Twist motifs most favored in genome ChIP data (in vivo) differed from those most favored by Systematic Evolution of Ligands by EXponential enrichment (SELEX) (in vitro). Furthermore, the majority of ChIP-seq signals could be parsimoniously explained by a CABVTG motif located within 50 bp of the ChIP summit and, of these, CACATG was most prevalent. Mutagenesis experiments demonstrated that different Twist E-box motif types are not fully interchangeable, suggesting that the ChIP-derived consensus (CABVTG) includes sites having distinct regulatory outputs. Further analysis of position, frequency of occurrence, and sequence conservation revealed significant enrichment and conservation of CABVTG E-box motifs near Twist ChIP-seq signal summits, preferential conservation of ±150 bp surrounding Twist occupied summits, and enrichment of GA- and CA-repeat sequences near Twist occupied summits. Our results show that high resolution in vivo occupancy data can be used to drive efficient discovery and dissection of global and local cis-regulatory logic

Bacteria in the airways of patients with cystic fibrosis are genetically capable of producing VOCs in breath.

Breath contains hundreds of volatile organic compounds (VOCs), the composition of which is altered in a wide variety of diseases. Bacteria are implicated in the formation of VOCs, but the biochemical mechanisms that lead to the formation of breath VOCs remain largely hypothetical. We hypothesized that bacterial DNA fragments in sputum of CF patients could be sequenced to identify whether the bacteria present were capable of producing VOCs found in the breath of these patients. Breath from seven patients with cystic fibrosis was sampled and analyzed by gas-chromatography and mass-spectrometry. Sputum samples were also collected and microbial DNA was isolated. Metagenomic sequencing was performed and the DNA fragments were compared to a reference database with genes that are linked to the metabolism of acetaldehyde, ethanol and methanol in the KEGG database. Bacteria in the genera Escherichia, Lactococcus, Pseudomonas, Rothia and Streptococcus were found to have the genetic potential to produce acetaldehyde and ethanol. Only DNA sequences from Lactococcus were implicated in the formation of acetaldehyde from acetate through aldehyde dehydrogenase family 9 member A1 (K00149). Escherichia was found to be genetically capable of producing ethanol in all patients, whilst there was considerable heterogeneity between patients for the other genera. The ethanol concentration in breath positively correlated with the amount of Escherichia found in sputum (Spearman rho  =  0.85,  P  =  0.015). Rothia showed the most versatile genetic potential for producing methanol. To conclude, bacterial DNA fragments in sputum of CF patients can be linked to enzymes implicated in the production of ethanol, acetaldehyde and methanol, which are VOCs that are predictive of respiratory tract colonization and/or infection. This supports that the lung microbiome can produce VOCs directly