Hemolytic uremic syndrome as the presenting manifestation of WT1 mutation and Denys-Drash syndrome: a case report.

BACKGROUND: Hemolytic uremic syndrome (HUS) can occur as a primary process due to mutations in complement genes or secondary to another underlying disease. HUS sometimes occurs in the setting of glomerular diseases, and it has been described in association with Denys-Drash syndrome (DDS), which is characterized by the triad of abnormal genitourinary development; a pathognomonic glomerulopathy, diffuse mesangial sclerosis; and the development of Wilms tumor. CASE PRESENTATION: We report the case of a 46, XX female infant who presented with HUS and biopsy-proven thrombotic microangiopathy. Next generation sequencing of genes with known mutations causative of atypical HUS found that she was homozygous for the Complement Factor H H3 haplotype and heterozygous for a variant of unknown significance in the DGKE gene. Whole exome sequencing identified a de novo heterozygous WT1 c.1384C > T; p.R394W mutation, which is classically associated with Denys-Drash syndrome (DDS). At the time of bilateral nephrectomy five months after her initial biopsy, she had diffuse mesangial sclerosis, typical of Denys-Drash syndrome, without evidence of thrombotic microangiopathy. CONCLUSION: This unique case highlights HUS as a rare but important manifestation of WT1 mutation and provides new insight into the genetics underlying this association.

Systematic exploration of unsupervised methods for mapping behavior.

To fully understand the mechanisms giving rise to behavior, we need to be able to precisely measure it. When coupled with large behavioral data sets, unsupervised clustering methods offer the potential of unbiased mapping of behavioral spaces. However, unsupervised techniques to map behavioral spaces are in their infancy, and there have been few systematic considerations of all the methodological options. We compared the performance of seven distinct mapping methods in clustering a wavelet-transformed data set consisting of the x- and y-positions of the six legs of individual flies. Legs were automatically tracked by small pieces of fluorescent dye, while the fly was tethered and walking on an air-suspended ball. We find that there is considerable variation in the performance of these mapping methods, and that better performance is attained when clustering is done in higher dimensional spaces (which are otherwise less preferable because they are hard to visualize). High dimensionality means that some algorithms, including the non-parametric watershed cluster assignment algorithm, cannot be used. We developed an alternative watershed algorithm which can be used in high-dimensional spaces when a probability density estimate can be computed directly. With these tools in hand, we examined the behavioral space of fly leg postural dynamics and locomotion. We find a striking division of behavior into modes involving the fore legs and modes involving the hind legs, with few direct transitions between them. By computing behavioral clusters using the data from all flies simultaneously, we show that this division appears to be common to all flies. We also identify individual-to-individual differences in behavior and behavioral transitions. Lastly, we suggest a computational pipeline that can achieve satisfactory levels of performance without the taxing computational demands of a systematic combinatorial approach.

Variability in thermal and phototactic preferences in Drosophila may reflect an adaptive bet-hedging strategy.

Organisms use various strategies to cope with fluctuating environmental conditions. In diversified bet-hedging, a single genotype exhibits phenotypic heterogeneity with the expectation that some individuals will survive transient selective pressures. To date, empirical evidence for bet-hedging is scarce. Here, we observe that individual Drosophila melanogaster flies exhibit striking variation in light- and temperature-preference behaviors. With a modeling approach that combines real world weather and climate data to simulate temperature preference-dependent survival and reproduction, we find that a bet-hedging strategy may underlie the observed interindividual behavioral diversity. Specifically, bet-hedging outcompetes strategies in which individual thermal preferences are heritable. Animals employing bet-hedging refrain from adapting to the coolness of spring with increased warm-seeking that inevitably becomes counterproductive in the hot summer. This strategy is particularly valuable when mean seasonal temperatures are typical, or when there is considerable fluctuation in temperature within the season. The model predicts, and we experimentally verify, that the behaviors of individual flies are not heritable. Finally, we model the effects of historical weather data, climate change, and geographic seasonal variation on the optimal strategies underlying behavioral variation between individuals, characterizing the regimes in which bet-hedging is advantageous.

Neuronal control of locomotor handedness in Drosophila.

Genetically identical individuals display variability in their physiology, morphology, and behaviors, even when reared in essentially identical environments, but there is little mechanistic understanding of the basis of such variation. Here, we investigated whether Drosophila melanogaster displays individual-to-individual variation in locomotor behaviors. We developed a new high-throughout platform capable of measuring the exploratory behavior of hundreds of individual flies simultaneously. With this approach, we find that, during exploratory walking, individual flies exhibit significant bias in their left vs. right locomotor choices, with some flies being strongly left biased or right biased. This idiosyncrasy was present in all genotypes examined, including wild-derived populations and inbred isogenic laboratory strains. The biases of individual flies persist for their lifetime and are nonheritable: i.e., mating two left-biased individuals does not yield left-biased progeny. This locomotor handedness is uncorrelated with other asymmetries, such as the handedness of gut twisting, leg-length asymmetry, and wing-folding preference. Using transgenics and mutants, we find that the magnitude of locomotor handedness is under the control of columnar neurons within the central complex, a brain region implicated in motor planning and execution. When these neurons are silenced, exploratory laterality increases, with more extreme leftiness and rightiness. This observation intriguingly implies that the brain may be able to dynamically regulate behavioral individuality.

Phototactic personality in fruit flies and its suppression by serotonin and white.

Drosophila typically move toward light (phototax positively) when startled. The various species of Drosophila exhibit some variation in their respective mean phototactic behaviors; however, it is not clear to what extent genetically identical individuals within each species behave idiosyncratically. Such behavioral individuality has indeed been observed in laboratory arthropods; however, the neurobiological factors underlying individual-to-individual behavioral differences are unknown. We developed "FlyVac," a high-throughput device for automatically assessing phototaxis in single animals in parallel. We observed surprising variability within every species and strain tested, including identically reared, isogenic strains. In an extreme example, a domesticated strain of Drosophila simulans harbored both strongly photopositive and strongly photonegative individuals. The particular behavior of an individual fly is not heritable and, because it persists for its lifetime, constitutes a model system for elucidating the molecular mechanisms of personality. Although all strains assayed had greater than expected variation (assuming binomial sampling), some had more than others, implying a genetic basis. Using genetics and pharmacology, we identified the metabolite transporter White and white-dependent serotonin as suppressors of phototactic personality. Because we observed behavioral idiosyncrasy in all experimental groups, we suspect it is present in most behaviors of most animals.