Inferring hidden Markov models from noisy time sequences: a method to alleviate degeneracy in molecular dynamics

We present a new method for inferring hidden Markov models from noisy time sequences without the necessity of assuming a model architecture, thus allowing for the detection of degenerate states. This is based on the statistical prediction techniques developed by Crutchfield et al., and generates so called causal state models, equivalent to hidden Markov models. This method is applicable to any continuous data which clusters around discrete values and exhibits multiple transitions between these values such as tethered particle motion data or Fluorescence Resonance Energy Transfer (FRET) spectra. The algorithms developed have been shown to perform well on simulated data, demonstrating the ability to recover the model used to generate the data under high noise, sparse data conditions and the ability to infer the existence of degenerate states. They have also been applied to new experimental FRET data of Holliday Junction dynamics, extracting the expected two state model and providing values for the transition rates in good agreement with previous results and with results obtained using existing maximum likelihood based methods.Comment: 19 pages, 9 figure

Low Phytoestrogen Levels in Feed Increase Fetal Serum Estradiol Resulting in the “Fetal Estrogenization Syndrome” and Obesity in CD-1 Mice

doi:10.1289/ehp.10448Although estrogenic chemicals can disrupt development of the reproductive system, there is debate about whether phytoestrogens in soy are beneficial, benign, or harmful. We compared reproductive and metabolic characteristics in male and female mice reared and maintained on non-soy low-phytoestrogen feed or soy-based high-phytoestrogen feed. Removing phytoestrogens from mouse feed produces an obese phenotype consistent with metabolic syndrome, and the associated reproductive system abnormalities are consistent with FES due to elevated endogenous fetal estradiol. Laboratory rodents may have become adapted to high-phytoestrogen intake over many generations of being fed soy-based commercial feed; removing all phytoestrogens from feed leads to alterations that could disrupt many types of biomedical research

Graphical models for inferring single molecule dynamics

<p>Abstract</p> <p>Background</p> <p>The recent explosion of experimental techniques in single molecule biophysics has generated a variety of novel time series data requiring equally novel computational tools for analysis and inference. This article describes in general terms how graphical modeling may be used to learn from biophysical time series data using the variational Bayesian expectation maximization algorithm (VBEM). The discussion is illustrated by the example of single-molecule fluorescence resonance energy transfer (smFRET)<it> versus</it> time data, where the smFRET time series is modeled as a hidden Markov model (HMM) with Gaussian observables. A detailed description of smFRET is provided as well.</p> <p>Results</p> <p>The VBEM algorithm returns the model’s evidence and an approximating posterior parameter distribution given the data. The former provides a metric for model selection via maximum evidence (ME), and the latter a description of the model’s parameters learned from the data. ME/VBEM provide several advantages over the more commonly used approach of maximum likelihood (ML) optimized by the expectation maximization (EM) algorithm, the most important being a natural form of model selection and a well-posed (non-divergent) optimization problem.</p> <p>Conclusions</p> <p>The results demonstrate the utility of graphical modeling for inference of dynamic processes in single molecule biophysics.</p

Stage-variations of anandamide hydrolase activity in the mouse uterus during the natural oestrus cycle

Recent studies have demonstrated that the endogenous cannabinoids are important modulators of fertility in mammals. In particular, a role of the endocannabinoid system in early stages of embryo development, oviductal transport of embryos, pregnancy maintenance and labour has been demonstrated in rodents and/or in humans. In the present paper, we report the analysis of FAAH activity and protein content in the mouse uterus as a function of the natural oestrus cycle stages. Variations of FAAH activity are discussed in relationship to changes in sex steroid levels and to the possible action of AEA on remodelling of uterine tissues

VAC14 nucleates a protein complex essential for the acute interconversion of PI3P and PI(3,5)P2 in yeast and mouse

The signalling lipid PI(3,5)P2 is generated on endosomes and regulates retrograde traffic to the trans-Golgi network. Physiological signals regulate rapid, transient changes in PI(3,5)P2 levels. Mutations that lower PI(3,5)P2 cause neurodegeneration in human patients and mice. The function of Vac14 in the regulation of PI(3,5)P2 was uncharacterized previously. Here, we predict that yeast and mammalian Vac14 are composed entirely of HEAT repeats and demonstrate that Vac14 exerts an effect as a scaffold for the PI(3,5)P2 regulatory complex by direct contact with the known regulators of PI(3,5)P2: Fig4, Fab1, Vac7 and Atg18. We also report that the mouse mutant ingls (infantile gliosis) results from a missense mutation in Vac14 that prevents the association of Vac14 with Fab1, generating a partial complex. Analysis of ingls and two additional mutants provides insight into the organization of the PI(3,5)P2 regulatory complex and indicates that Vac14 mediates three distinct mechanisms for the rapid interconversion of PI3P and PI(3,5)P2. Moreover, these studies show that the association of Fab1 with the complex is essential for viability in the mouse

Single-Molecule Analysis Reveals the Kinetics and Physiological Relevance of MutL-ssDNA Binding

DNA binding by MutL homologs (MLH/PMS) during mismatch repair (MMR) has been considered based on biochemical and genetic studies. Bulk studies with MutL and its yeast homologs Mlh1-Pms1 have suggested an integral role for a single-stranded DNA (ssDNA) binding activity during MMR. We have developed single-molecule Förster resonance energy transfer (smFRET) and a single-molecule DNA flow-extension assays to examine MutL interaction with ssDNA in real time. The smFRET assay allowed us to observe MutL-ssDNA association and dissociation. We determined that MutL-ssDNA binding required ATP and was the greatest at ionic strength below 25 mM (KD = 29 nM) while it dramatically decreases above 100 mM (KD>2 µM). Single-molecule DNA flow-extension analysis suggests that multiple MutL proteins may bind ssDNA at low ionic strength but this activity does not enhance stability at elevated ionic strengths. These studies are consistent with the conclusion that a stable MutL-ssDNA interaction is unlikely to occur at physiological salt eliminating a number of MMR models. However, the activity may infer some related dynamic DNA transaction process during MMR

Shorter spontaneous fixation durations in infants with later emerging autism

Little is known about how spontaneous attentional deployment differs on a millisecond-level scale in the early development of autism spectrum disorders (ASD). We measured fine-grained eye movement patterns in 6-to 9-month-old infants at high or low familial risk (HR/LR) of ASD while they viewed static images. We observed shorter fixation durations (i.e. the time interval between saccades) in HR than LR infants. Preliminary analyses indicate that these results were replicated in a second cohort of infants. Fixation durations were shortest in those infants who went on to receive an ASD diagnosis at 36 months. While these findings demonstrate early-developing atypicality in fine-grained measures of attentional deployment early in the etiology of ASD, the specificity of these effects to ASD remains to be determined

Engineering modular and orthogonal genetic logic gates for robust digital-like synthetic biology

Modular and orthogonal genetic logic gates are essential for building robust biologically based digital devices to customize cell signalling in synthetic biology. Here we constructed an orthogonal AND gate in Escherichia coli using a novel hetero-regulation module from Pseudomonas syringae. The device comprises two co-activating genes hrpR and hrpS controlled by separate promoter inputs, and a σ54-dependent hrpL promoter driving the output. The hrpL promoter is activated only when both genes are expressed, generating digital-like AND integration behaviour. The AND gate is demonstrated to be modular by applying new regulated promoters to the inputs, and connecting the output to a NOT gate module to produce a combinatorial NAND gate. The circuits were assembled using a parts-based engineering approach of quantitative characterization, modelling, followed by construction and testing. The results show that new genetic logic devices can be engineered predictably from novel native orthogonal biological control elements using quantitatively in-context characterized parts