Approximate Bayesian Computation

Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology).

This is a “Topic Page” article for PLOS Computational Biology.

     

Metabolomics identifies a biological response to chronic low-dose natural uranium contamination in urine samples

Because uranium is a natural element present in the earth’s crust, the population may be chronically exposed to low doses of it through drinking water. Additionally, the military and civil uses of uranium can also lead to environmental dispersion that can result in high or low doses of acute or chronic exposure. Recent experimental data suggest this might lead to relatively innocuous biological reactions. The aim of this study was to assess the biological changes in rats caused by ingestion of natural uranium in drinking water with a mean daily intake of 2.7 mg/kg for 9 months and to identify potential biomarkers related to such a contamination. Subsequently, we observed no pathology and standard clinical tests were unable to distinguish between treated and untreated animals. Conversely, LC–MS metabolomics identified urine as an appropriate biofluid for discriminating the experimental groups. Of the 1,376 features detected in urine, the most discriminant were metabolites involved in tryptophan, nicotinate, and nicotinamide metabolic pathways. In particular, N-methylnicotinamide, which was found at a level seven times higher in untreated than in contaminated rats, had the greatest discriminating power. These novel results establish a proof of principle for using metabolomics to address chronic low-dose uranium contamination. They open interesting perspectives for understanding the underlying biological mechanisms and designing a diagnostic test of exposure.     

A Cryptic Cytoplasmic Male Sterility Unveils a Possible Gynodioecious Past for Arabidopsis thaliana

Gynodioecy, the coexistence of hermaphrodites and females (i.e. male-sterile plants) in natural plant populations, most often results from polymorphism at genetic loci involved in a particular interaction between the nuclear and cytoplasmic genetic compartments (cytonuclear epistasis): cytoplasmic male sterility (CMS). Although CMS clearly contributes to the coevolution of involved nuclear loci and cytoplasmic genomes in gynodioecious species, the occurrence of CMS genetic factors in the absence of sexual polymorphism (cryptic CMS) is not easily detected and rarely taken in consideration. We found cryptic CMS in the model plant Arabidopsis thaliana after crossing distantly related accessions, Sha and Mr-0. Male sterility resulted from an interaction between the Sha cytoplasm and two Mr-0 genomic regions located on chromosome 1 and chromosome 3. Additional accessions with either nuclear sterility maintainers or sterilizing cytoplasms were identified from crosses with either Sha or Mr-0. By comparing two very closely related cytoplasms with different male-sterility inducing abilities, we identified a novel mitochondrial ORF, named orf117Sha, that is most likely the sterilizing factor of the Sha cytoplasm. The presence of orf117Sha was investigated in worldwide natural accessions. It was found mainly associated with a single chlorotype in accessions belonging to a clade predominantly originating from Central Asia. More than one-third of accessions from this clade carried orf117Sha, indicating that the sterilizing-inducing cytoplasm had spread in this lineage. We also report the coexistence of the sterilizing cytoplasm with a non-sterilizing cytoplasm at a small, local scale in a natural population; in addition a correlation between cytotype and nuclear haplotype was detected in this population. Our results suggest that this CMS system induced sexual polymorphism in A. thaliana populations, at the time when the species was mainly outcrossing.     

Metabonomics Analysis of Plasma Reveals the Lactate to Cholesterol Ratio as an Independent Prognostic Factor of Short-Term Mortality in Acute Heart Failure

Objective

Mortality in heart failure (AHF) remains high, especially during the first days of hospitalization. New prognostic biomarkers may help to optimize treatment. The aim of the study was to determine metabolites that have a high prognostic value.

Methods

We conducted a prospective study on a training cohort of AHF patients (n = 126) admitted in the cardiac intensive care unit and assessed survival at 30 days. Venous plasmas collected at admission were used for ¹H NMR – based metabonomics analysis. Differences between plasma metabolite profiles allow determination of discriminating metabolites. A cohort of AHF patients was subsequently constituted (n = 74) to validate the findings.

Results

Lactate and cholesterol were the major discriminating metabolites predicting 30-day mortality. Mortality was increased in patients with high lactate and low total cholesterol concentrations at admission. Accuracies of lactate, cholesterol concentration and lactate to cholesterol (Lact/Chol) ratio to predict 30-day mortality were evaluated using ROC analysis. The Lact/Chol ratio provided the best accuracy with an AUC of 0.82 (P < 0.0001). The acute physiology and chronic health evaluation (APACHE) II scoring system provided an AUC of 0.76 for predicting 30-day mortality. APACHE II score, Cardiogenic shock (CS) state and Lact/Chol ratio ≥ 0.4 (cutoff value with 82% sensitivity and 64% specificity) were significant independent predictors of 30-day mortality with hazard ratios (HR) of 1.11, 4.77 and 3.59, respectively. In CS patients, the HR of 30-day mortality risk for plasma Lact/Chol ratio ≥ 0.4 was 3.26 compared to a Lact/Chol ratio of < 0.4 (P  =  0.018). The predictive power of the Lact/Chol ratio for 30-day mortality outcome was confirmed with the independent validation cohort.

Conclusion

This study identifies the plasma Lact/Chol ratio as a useful objective and simple parameter to evaluate short term prognostic and could be integrated into quantitative guidance for decision making in heart failure care.     

Use of a Molecular Genetic Platform Technology to Produce Human Wnt Proteins Reveals Distinct Local and Distal Signaling Abilities

Functional and mechanistic studies of Wnt signaling have been severely hindered by the inaccessibility of bioactive proteins. To overcome this long-standing barrier, we engineered and characterized a panel of Chinese hamster ovary (CHO) cell lines with inducible transgenes encoding tagged and un-tagged human WNT1, WNT3A, WNT5A, WNT7A, WNT11, WNT16 or the soluble Wnt antagonist Fzd8CRD, all integrated into an identical genomic locus. Using a quantitative real-time bioluminescence assay, we show that cells expressing WNT1, 3A and 7A stimulate Wnt/beta-catenin reporter activity, while the other WNT expressing cell lines interfere with this activation. Additionally, in contrast to WNT3A, WNT1 only exhibits activity when cell-associated, and thus only signals to neighboring cells. The reporter assay also revealed a rapid decline of Wnt activity at 37°C, indicating that Wnt activity is highly labile. These engineered cell lines will reduce the cost of making and purifying Wnt proteins and serve as a continuous, reliable and regulatable source of Wnts to research laboratories around the world.     

Detection and Characterisation of Mutations Responsible for Allele-Specific Protein Thermostabilities at the Mn-Superoxide Dismutase Gene in the Deep-Sea Hydrothermal Vent Polychaete Alvinella pompejana

Alvinella pompejana (Polychaeta, Alvinellidae) is one of the most thermotolerant marine eukaryotes known to date. It inhabits chimney walls of deep-sea hydrothermal vents along the East Pacific Rise (EPR) and is exposed to various challenging conditions (e.g. high temperature, hypoxia and the presence of sulphides, heavy metals and radiations), which increase the production of dangerous reactive oxygen species (ROS). Two different allelic forms of a manganese-superoxide dismutase involved in ROS detoxification, ApMnSOD1 and ApMnSOD2, and differing only by two substitutions (M110L and A138G) were identified in an A. pompejana cDNA library. RFLP screening of 60 individuals from different localities along the EPR showed that ApMnSOD2 was rare (2 %) and only found in the heterozygous state. Dynamic light scattering measurements and residual enzymatic activity experiments showed that the most frequent form (ApMnSOD1) was the most resistant to temperature. Their half-lives were similarly long at 65 °C (>110 min) but exhibited a twofold difference at 80 °C (20.8 vs 9.8 min). Those properties are likely to be explained by the occurrence of an additional sulphur-containing hydrogen bond involving the M110 residue and the effect of the A138 residue on the backbone entropy. Our results confirm the thermophily of A. pompejana and suggest that this locus is a good model to study how the extreme thermal heterogeneity of the vent conditions may help to maintain old rare variants in those populations.     

Evolution of Cyclic Amidohydrolases: A Highly Diversified Superfamily

Dihydroorotases are universal proteins catalyzing the third step of pyrimidine biosynthesis. These zinc metalloenzymes belong to the superfamily of cyclic amidohydrolases, comprising also other enzymes that are involved in degradation of either purines (allantoinases), pyrimidines (dihydropyrimidinases) or hydantoins (hydantoinases). The evolutionary relationships between these mechanistically related enzymes were estimated after designing a method to build an accurate multiple sequence alignment. The amino acid sequences that have been crystallized were used to build a seed alignment. All the remaining homologues were progressively added by aligning their HMM profiles to the seed HMM profile, allowing to obtain a reliable phylogeny of the superfamily. This helped us to propose a new evolutionary classification of dihydroorotases into three major types, while at the same time disentangling an important part of the history of their complex structure–function relationships. Although differing in their substrate specificity, allantoinases, hydantoinases and dihydropyrimidinases are found to be phylogenetically closer to DHOase Type I than the proximity of the three DHOase types to each other. This suggests that the primordial cyclic amidohydrolase was a multifunctional, highly evolvable generalist, with high conformational diversity allowing for promiscuous activities. Then, successive gene duplications allowed resolving the primordial substrate ambiguity in various substrate specificities. The present-day superfamily of cyclic amidohydrolases is the result of the progressive divergence of these ancestral paralogous copies by descent with modification.     

Distinguishing Antimicrobial Models with Different Resistance Mechanisms via Population Pharmacodynamic Modeling

Semi-mechanistic pharmacokinetic-pharmacodynamic (PK-PD) modeling is increasingly used for antimicrobial drug development and optimization of dosage regimens, but systematic simulation-estimation studies to distinguish between competing PD models are lacking. This study compared the ability of static and dynamic in vitro infection models to distinguish between models with different resistance mechanisms and support accurate and precise parameter estimation. Monte Carlo simulations (MCS) were performed for models with one susceptible bacterial population without (M1) or with a resting stage (M2), a one population model with adaptive resistance (M5), models with pre-existing susceptible and resistant populations without (M3) or with (M4) inter-conversion, and a model with two pre-existing populations with adaptive resistance (M6). For each model, 200 datasets of the total bacterial population were simulated over 24h using static antibiotic concentrations (256-fold concentration range) or over 48h under dynamic conditions (dosing every 12h; elimination half-life: 1h). Twelve-hundred random datasets (each containing 20 curves for static or four curves for dynamic conditions) were generated by bootstrapping. Each dataset was estimated by all six models via population PD modeling to compare bias and precision. For M1 and M3, most parameter estimates were unbiased (<10%) and had good imprecision (<30%). However, parameters for adaptive resistance and inter-conversion for M2, M4, M5 and M6 had poor bias and large imprecision under static and dynamic conditions. For datasets that only contained viable counts of the total population, common statistical criteria and diagnostic plots did not support sound identification of the true resistance mechanism. Therefore, it seems advisable to quantify resistant bacteria and characterize their MICs and resistance mechanisms to support extended simulations and translate from in vitro experiments to animal infection models and ultimately patients.     

Effects of MDMA Injections on the Behavior of Socially-Housed Long-Tailed Macaques (Macaca fascicularis)

3,4-methylenedioxy-N-methyl amphetamine (MDMA) is one of the few known molecules to increase human and rodent prosocial behaviors. However, this effect has never been assessed on the social behavior of non-human primates. In our study, we subcutaneously injected three different doses of MDMA (1.0, 1.5 or 2.0mg/kg) to a group of three, socially housed, young male long-tailed macaques. More than 200 hours of behavioral data were recorded, during 68 behavioral sessions, by an automatic color-based video device that tracked the 3D positions of each animal and of a toy. This data was then categorized into 5 exclusive behaviors (resting, locomotion, foraging, social contact and object play). In addition, received and given social grooming was manually scored. Results show several significant dose-dependent behavioral effects. At 1.5mg/kg only, MDMA induces a significant increase in social grooming behavior, thus confirming the prosocial effect of MDMA in macaques. Additionally, at 1.5 and 2.0 mg/kg MDMA injection substantially decreases foraging behavior, which is consistent with the known anorexigenic effect of this compound. Furthermore, at 2.0 mg/kg MDMA injection induces an increase in locomotor behavior, which is also in accordance with its known stimulant property. Interestingly, MDMA injected at 1.0mg/kg increases the rate of object play, which might be interpreted as a decrease of the inhibition to manipulate a unique object in presence of others, or, as an increase of the intrinsic motivation to manipulate this object. Together, our results support the effectiveness of MDMA to study the complex neurobiology of primates’ social behaviors.