Scalable inference of heterogeneous reaction kinetics from pooled single-cell recordings.

Mathematical methods combined with measurements of single-cell dynamics provide a means to reconstruct intracellular processes that are only partly or indirectly accessible experimentally. To obtain reliable reconstructions, the pooling of measurements from several cells of a clonal population is mandatory. However, cell-to-cell variability originating from diverse sources poses computational challenges for such process reconstruction. We introduce a scalable Bayesian inference framework that properly accounts for population heterogeneity. The method allows inference of inaccessible molecular states and kinetic parameters; computation of Bayes factors for model selection; and dissection of intrinsic, extrinsic and technical noise. We show how additional single-cell readouts such as morphological features can be included in the analysis. We use the method to reconstruct the expression dynamics of a gene under an inducible promoter in yeast from time-lapse microscopy data.

De novo characterization of the Timema cristinae transcriptome facilitates marker discovery and inference of genetic divergence.

Adaptation to different ecological environments can promote speciation. Although numerous examples of such 'ecological speciation' now exist, the genomic basis of the process, and the role of gene flow in it, remains less understood. This is, at least in part, because systems that are well characterized in terms of their ecology often lack genomic resources. In this study, we characterize the transcriptome of Timema cristinae stick insects, a system that has been researched intensively in terms of ecological speciation, but for which genomic resources have not been previously developed. Specifically, we obtained >1 million 454 sequencing reads that assembled into 84,937 contigs representing approximately 18,282 unique genes and tens of thousands of potential molecular markers. Second, as an illustration of their utility, we used these genomic resources to assess multilocus genetic divergence within both an ecotype pair and a species pair of Timema stick insects. The results suggest variable levels of genetic divergence and gene flow among taxon pairs and genes and illustrate a first step towards future genomic work in Timema.

Source inference of exogenous gamma-hydroxybutyric acid (GHB) administered to humans by means of carbon isotopic ratio analysis: novel perspectives regarding forensic investigation and intelligence issues.

γ-Hydroxybutyric acid (GHB) is an endogenous short-chain fatty acid popular as a recreational drug due to sedative and euphoric effects, but also often implicated in drug-facilitated sexual assaults owing to disinhibition and amnesic properties. Whilst discrimination between endogenous and exogenous GHB as required in intoxication cases may be achieved by the determination of the carbon isotope content, such information has not yet been exploited to answer source inference questions of forensic investigation and intelligence interests. However, potential isotopic fractionation effects occurring through the whole metabolism of GHB may be a major concern in this regard. Thus, urine specimens from six healthy male volunteers who ingested prescription GHB sodium salt, marketed as Xyrem(®), were analysed by means of gas chromatography/combustion/isotope ratio mass spectrometry to assess this particular topic. A very narrow range of δ(13)C values, spreading from -24.810/00 to -25.060/00, was observed, whilst mean δ(13)C value of Xyrem(®) corresponded to -24.990/00. Since urine samples and prescription drug could not be distinguished by means of statistical analysis, carbon isotopic effects and subsequent influence on δ(13)C values through GHB metabolism as a whole could be ruled out. Thus, a link between GHB as a raw matrix and found in a biological fluid may be established, bringing relevant information regarding source inference evaluation. Therefore, this study supports a diversified scope of exploitation for stable isotopes characterized in biological matrices from investigations on intoxication cases to drug intelligence programmes.

Effect of genetic convergence on phylogenetic inference.

Phylogenetic reconstructions are a major component of many studies in evolutionary biology, but their accuracy can be reduced under certain conditions. Recent studies showed that the convergent evolution of some phenotypes resulted from recurrent amino acid substitutions in genes belonging to distant lineages. It has been suggested that these convergent substitutions could bias phylogenetic reconstruction toward grouping convergent phenotypes together, but such an effect has never been appropriately tested. We used computer simulations to determine the effect of convergent substitutions on the accuracy of phylogenetic inference. We show that, in some realistic conditions, even a relatively small proportion of convergent codons can strongly bias phylogenetic reconstruction, especially when amino acid sequences are used as characters. The strength of this bias does not depend on the reconstruction method but varies as a function of how much divergence had occurred among the lineages prior to any episodes of convergent substitutions. While the occurrence of this bias is difficult to predict, the risk of spurious groupings is strongly decreased by considering only 3rd codon positions, which are less subject to selection, as long as saturation problems are not present. Therefore, we recommend that, whenever possible, topologies obtained with amino acid sequences and 3rd codon positions be compared to identify potential phylogenetic biases and avoid evolutionarily misleading conclusions.

High specificity of line-immunoassay based algorithms for recent HIV-1 infection independent of viral subtype and stage of disease.

ABSTRACT: BACKGROUND: Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information for HIV surveillance. We have shown that a patient's antibody reaction in a confirmatory line immunoassay (INNO-LIATM HIV I/II Score, Innogenetics) provides information on the duration of infection. Here, we sought to further investigate the diagnostic specificity of various Inno-Lia algorithms and to identify factors affecting it. METHODS: Plasma samples of 714 selected patients of the Swiss HIV Cohort Study infected for longer than 12 months and representing all viral clades and stages of chronic HIV-1 infection were tested blindly by Inno-Lia and classified as either incident (up to 12 m) or older infection by 24 different algorithms. Of the total, 524 patients received HAART, 308 had HIV-1 RNA below 50 copies/mL, and 620 were infected by a HIV-1 non-B clade. Using logistic regression analysis we evaluated factors that might affect the specificity of these algorithms. RESULTS: HIV-1 RNA <50 copies/mL was associated with significantly lower reactivity to all five HIV-1 antigens of the Inno-Lia and impaired specificity of most algorithms. Among 412 patients either untreated or with HIV-1 RNA ≥50 copies/mL despite HAART, the median specificity of the algorithms was 96.5% (range 92.0-100%). The only factor that significantly promoted false-incident results in this group was age, with false-incident results increasing by a few percent per additional year. HIV-1 clade, HIV-1 RNA, CD4 percentage, sex, disease stage, and testing modalities exhibited no significance. Results were similar among 190 untreated patients. CONCLUSIONS: The specificity of most Inno-Lia algorithms was high and not affected by HIV-1 variability, advanced disease and other factors promoting false-recent results in other STARHS. Specificity should be good in any group of untreated HIV-1 patients.

Endoleak and in-stent thrombus detection with CT angiography in a thoracic aortic aneurysm phantom at different tube energies using filtered back projection and iterative algorithms.

PURPOSE: To determine the lower limit of dose reduction with hybrid and fully iterative reconstruction algorithms in detection of endoleaks and in-stent thrombus of thoracic aorta with computed tomographic (CT) angiography by applying protocols with different tube energies and automated tube current modulation. MATERIALS AND METHODS: The calcification insert of an anthropomorphic cardiac phantom was replaced with an aortic aneurysm model containing a stent, simulated endoleaks, and an intraluminal thrombus. CT was performed at tube energies of 120, 100, and 80 kVp with incrementally increasing noise indexes (NIs) of 16, 25, 34, 43, 52, 61, and 70 and a 2.5-mm section thickness. NI directly controls radiation exposure; a higher NI allows for greater image noise and decreases radiation. Images were reconstructed with filtered back projection (FBP) and hybrid and fully iterative algorithms. Five radiologists independently analyzed lesion conspicuity to assess sensitivity and specificity. Mean attenuation (in Hounsfield units) and standard deviation were measured in the aorta to calculate signal-to-noise ratio (SNR). Attenuation and SNR of different protocols and algorithms were analyzed with analysis of variance or Welch test depending on data distribution. RESULTS: Both sensitivity and specificity were 100% for simulated lesions on images with 2.5-mm section thickness and an NI of 25 (3.45 mGy), 34 (1.83 mGy), or 43 (1.16 mGy) at 120 kVp; an NI of 34 (1.98 mGy), 43 (1.23 mGy), or 61 (0.61 mGy) at 100 kVp; and an NI of 43 (1.46 mGy) or 70 (0.54 mGy) at 80 kVp. SNR values showed similar results. With the fully iterative algorithm, mean attenuation of the aorta decreased significantly in reduced-dose protocols in comparison with control protocols at 100 kVp (311 HU at 16 NI vs 290 HU at 70 NI, P ≤ .0011) and 80 kVp (400 HU at 16 NI vs 369 HU at 70 NI, P ≤ .0007). CONCLUSION: Endoleaks and in-stent thrombus of thoracic aorta were detectable to 1.46 mGy (80 kVp) with FBP, 1.23 mGy (100 kVp) with the hybrid algorithm, and 0.54 mGy (80 kVp) with the fully iterative algorithm.

Landscape structure affects dispersal in the greater white-toothed shrew: inference between genetic and simulated ecological distances

Animal dispersal in a fragmented landscape depends on the complex interaction between landscape structure and animal behavior. To better understand how individuals disperse, it is important to explicitly represent the properties of organisms and the landscape in which they move. A common approach to modelling dispersal includes representing the landscape as a grid of equal sized cells and then simulating individual movement as a correlated random walk. This approach uses a priori scale of resolution, which limits the representation of all landscape features and how different dispersal abilities are modelled. We develop a vector-based landscape model coupled with an object-oriented model for animal dispersal. In this spatially explicit dispersal model, landscape features are defined based on their geographic and thematic properties and dispersal is modelled through consideration of an organism's behavior, movement rules and searching strategies (such as visual cues). We present the model's underlying concepts, its ability to adequately represent landscape features and provide simulation of dispersal according to different dispersal abilities. We demonstrate the potential of the model by simulating two virtual species in a real Swiss landscape. This illustrates the model's ability to simulate complex dispersal processes and provides information about dispersal such as colonization probability and spatial distribution of the organism's path

Inference of chromosomal inversion dynamics from Pool-Seq data in natural and laboratory populations of Drosophila melanogaster.

Sequencing of pools of individuals (Pool-Seq) represents a reliable and cost-effective approach for estimating genome-wide SNP and transposable element insertion frequencies. However, Pool-Seq does not provide direct information on haplotypes so that, for example, obtaining inversion frequencies has not been possible until now. Here, we have developed a new set of diagnostic marker SNPs for seven cosmopolitan inversions in Drosophila melanogaster that can be used to infer inversion frequencies from Pool-Seq data. We applied our novel marker set to Pool-Seq data from an experimental evolution study and from North American and Australian latitudinal clines. In the experimental evolution data, we find evidence that positive selection has driven the frequencies of In(3R)C and In(3R)Mo to increase over time. In the clinal data, we confirm the existence of frequency clines for In(2L)t, In(3L)P and In(3R)Payne in both North America and Australia and detect a previously unknown latitudinal cline for In(3R)Mo in North America. The inversion markers developed here provide a versatile and robust tool for characterizing inversion frequencies and their dynamics in Pool-Seq data from diverse D. melanogaster populations.

Comparative performance of supertree algorithms in large data sets using the soapberry family (Sapindaceae) as a case study.

For the last 2 decades, supertree reconstruction has been an active field of research and has seen the development of a large number of major algorithms. Because of the growing popularity of the supertree methods, it has become necessary to evaluate the performance of these algorithms to determine which are the best options (especially with regard to the supermatrix approach that is widely used). In this study, seven of the most commonly used supertree methods are investigated by using a large empirical data set (in terms of number of taxa and molecular markers) from the worldwide flowering plant family Sapindaceae. Supertree methods were evaluated using several criteria: similarity of the supertrees with the input trees, similarity between the supertrees and the total evidence tree, level of resolution of the supertree and computational time required by the algorithm. Additional analyses were also conducted on a reduced data set to test if the performance levels were affected by the heuristic searches rather than the algorithms themselves. Based on our results, two main groups of supertree methods were identified: on one hand, the matrix representation with parsimony (MRP), MinFlip, and MinCut methods performed well according to our criteria, whereas the average consensus, split fit, and most similar supertree methods showed a poorer performance or at least did not behave the same way as the total evidence tree. Results for the super distance matrix, that is, the most recent approach tested here, were promising with at least one derived method performing as well as MRP, MinFlip, and MinCut. The output of each method was only slightly improved when applied to the reduced data set, suggesting a correct behavior of the heuristic searches and a relatively low sensitivity of the algorithms to data set sizes and missing data. Results also showed that the MRP analyses could reach a high level of quality even when using a simple heuristic search strategy, with the exception of MRP with Purvis coding scheme and reversible parsimony. The future of supertrees lies in the implementation of a standardized heuristic search for all methods and the increase in computing power to handle large data sets. The latter would prove to be particularly useful for promising approaches such as the maximum quartet fit method that yet requires substantial computing power.

Counterfactuals and causal inference: Methods and principles for social research

"Most quantitative empirical analyses are motivated by the desire to estimate the causal effect of an independent variable on a dependent variable. Although the randomized experiment is the most powerful design for this task, in most social science research done outside of psychology, experimental designs are infeasible. (Winship & Morgan, 1999, p. 659)." This quote from earlier work by Winship and Morgan, which was instrumental in setting the groundwork for their book, captures the essence of our review of Morgan and Winship's book: It is about causality in nonexperimental settings.

What drives invasibility? A multi-model inference test and spatial modelling of alien plant species richness patterns in northern Portugal

Understanding and anticipating biological invasions can focus either on traits that favour species invasiveness or on features of the receiving communities, habitats or landscapes that promote their invasibility. Here, we address invasibility at the regional scale, testing whether some habitats and landscapes are more invasible than others by fitting models that relate alien plant species richness to various environmental predictors. We use a multi-model information-theoretic approach to assess invasibility by modelling spatial and ecological patterns of alien invasion in landscape mosaics and testing competing hypotheses of environmental factors that may control invasibility. Because invasibility may be mediated by particular characteristics of invasiveness, we classified alien species according to their C-S-R plant strategies. We illustrate this approach with a set of 86 alien species in Northern Portugal. We first focus on predictors influencing species richness and expressing invasibility and then evaluate whether distinct plant strategies respond to the same or different groups of environmental predictors. We confirmed climate as a primary determinant of alien invasions and as a primary environmental gradient determining landscape invasibility. The effects of secondary gradients were detected only when the area was sub-sampled according to predictions based on the primary gradient. Then, multiple predictor types influenced patterns of alien species richness, with some types (landscape composition, topography and fire regime) prevailing over others. Alien species richness responded most strongly to extreme land management regimes, suggesting that intermediate disturbance induces biotic resistance by favouring native species richness. Land-use intensification facilitated alien invasion, whereas conservation areas hosted few invaders, highlighting the importance of ecosystem stability in preventing invasions. Plants with different strategies exhibited different responses to environmental gradients, particularly when the variations of the primary gradient were narrowed by sub-sampling. Such differential responses of plant strategies suggest using distinct control and eradication approaches for different areas and alien plant groups.