Insights from the reconstitution of the divergent outer kinetochore of Drosophila melanogaster

Accurate chromosome segregation during mitosis and meiosis is crucial for cellular and organismal viability. Kinetochores connect chromosomes with spindle microtubules and are essential for chromosome segregation. These large protein scaffolds emerge from the centromere, a specialized region of the chromosome enriched with the histone H3 variant CENP-A. In most eukaryotes, the kinetochore core consists of the centromere-proximal constitutive centromere-associated network (CCAN), which binds CENP-A and contains 16 subunits, and of the centromere-distal Knl1 complex, Mis12 complex, Ndc80 complex (KMN) network, which binds microtubules and contains 10 subunits. In the fruitfly, Drosophila melanogaster, the kinetochore underwent remarkable simplifications. All CCAN subunits, with the exception of centromeric protein C (CENP-C), and two KMN subunits, Dsn1 and Zwint, cannot be identified in this organism. In addition, two paralogues of the KMN subunit Nnf1 (Nnf1a and Nnf1b) are present. Finally, the Spc105R subunit, homologous to human Knl1/CASC5, underwent considerable sequence changes in comparison with other organisms. We combined biochemical reconstitution with biophysical and structural methods to investigate how these changes reflect on the organization of the Drosophila KMN network. We demonstrate that the Nnf1a and Nnf1b paralogues are subunits of distinct complexes, both of which interact directly with Spc105R and with CENP-C, for the latter of which we identify a binding site on the Mis12 subunit. Our studies shed light on the structural and functional organization of a highly divergent kinetochore particle.     

Borderline Personality and the Detection of Angry Faces

Background

Many studies have assessed emotion recognition in patients with Borderline Personality Disorder and considerable evidence has been accumulated on patients’ ability to categorize emotions. In contrast, their ability to detect emotions has been investigated sparsely. The only two studies that assessed emotion detection abilities found contradictory evidence on patients’ ability to detect angry faces.

Methods

To clarify whether patients with Borderline Personality Disorder show enhanced detection of angry faces, we conducted three experiments: a laboratory study (n = 53) with a clinical sample and two highly powered web studies that measured Borderline features (n₁ = 342, n₂ = 220). Participants in all studies completed a visual search paradigm, and the reaction times for the detection of angry vs. happy faces were measured.

Results

Consistently, data spoke against enhanced detection of angry faces in the Borderline groups, indicated by non-significant group (Borderline vs. healthy control) × target (angry vs. happy) interactions, despite highly satisfactory statistical power to detect even small effects.

Conclusions

In contrast to emotion categorization, emotion detection appears to be intact in patients with Borderline Personality Disorder and individuals high in Borderline features. The importance of distinguishing between these two processes in future studies is discussed.     

Titanium dioxide as a chemo-affinity solid phase in offline phosphopeptide chromatography prior to HPLC-MS/MS analysis

We have developed a new offline chromatographic approach for the selective enrichment of phosphorylated peptides that is directly compatible with subsequent analysis by online nano electrospray ionization tandem mass spectrometry. In this technique, a titanium dioxide (TiO2)-packed pipette tip is used as a phosphopeptide trap that acts as an offline first-dimension separation step in a two-dimensional chromatography system. This is followed by online nano reversed-phase high-performance liquid chromatography. Here, we present suitable methods for enrichment, optimized separately for each step: sample loading, washing and elution from the TiO2-filled tips. To increase the trapping selectivity of the TiO2 column, we used the sodium salt of 1-octanesulfonic acid combined with 2,5-dihydroxybenzoic acid as ion-pairing agents and displacers for acidic peptides. These agents also improve the binding of phosphorylated peptides and block the binding of non-phosphorylated ones. This enrichment procedure takes 30 min, followed by a 100-min HPLC program, including washing and an elution gradient.     

Strong parasitoid-mediated selection in experimental populations of aphids

Clonal diversity in asexual populations may be maintained if different clones are favoured under different environmental conditions. For aphids, parasitoids are an important variable of the biotic environment. To test whether parasitoids can mediate selection among host clones, we used experimental populations consisting of 10 clones of the peach-potato aphid, Myzus persicae, and allowed them to evolve for several generations either without parasitoids or in the presence of two species of parasitoid wasps. In the absence of parasitoids, strong shifts in clonal frequencies occurred, mostly in favour of clones with high rates of increase. The parasitoid Diaeretiella rapae hardly affected aphid densities but changed the outcome of competition by favouring one entirely resistant clone and disfavouring a highly susceptible clone. Aphidius colemani, the more infective parasitoid, strongly reduced aphid densities and dramatically changed host clonal frequencies. The most resistant clone, not a successful clone without parasitoids, became totally dominant. These results highlight the potential of temporal or spatial variation in parasitoid densities to maintain clonal diversity in their aphid hosts.     

The Mechanical Behaviour of Chondrocytes Predicted with a Micro-structural Model of Articular Cartilage

The integrity of articular cartilage depends on the proper functioning and mechanical stimulation of chondrocytes, the cells that synthesize extracellular matrix and maintain tissue health. The biosynthetic activity of chondrocytes is influenced by genetic factors, environmental influences, extracellular matrix composition, and mechanical factors. The mechanical environment of chondrocytes is believed to be an important determinant for joint health, and chondrocyte deformation in response to mechanical loading is speculated to be an important regulator of metabolic activity. In previous studies of chondrocyte deformation, articular cartilage was described as a biphasic material consisting of a homogeneous, isotropic, linearly elastic solid phase, and an inviscid fluid phase. However, articular cartilage is known to be anisotropic and inhomogeneous across its depth. Therefore, isotropic and homogeneous models cannot make appropriate predictions for tissue and cell stresses and strains. Here, we modelled articular cartilage as a transversely isotropic, inhomogeneous (TI) material in which the anisotropy and inhomogeneity arose naturally from the microstructure of the depth-dependent collagen fibril orientation and volumetric fraction, as well as the chondrocyte shape and volumetric fraction. The purpose of this study was to analyse the deformation behaviour of chondrocytes using the TI model of articular cartilage. In order to evaluate our model against experimental results, we simulated indentation and unconfined compression tests for nominal compressions of 15%. Chondrocyte deformations were analysed as a function of location within the tissue. The TI model predicted a non-uniform behaviour across tissue depth: in indentation testing, cell height decreased by 43% in the superficial zone and between 11 and 29% in the deep zone. In unconfined compression testing, cell height decreased by 32% in the superficial zone, 25% in the middle, and 18% in the deep zones. This predicted non-uniformity is in agreement with experimental studies. The novelty of this study is the use of a cartilage material model accounting for the intrinsic inhomogeneity and anisotropy of cartilage caused by its microstructure.     

Diversity of archaea and niche preferences among putative ammonia-oxidizing Nitrososphaeria dominating across European arable soils

Archaeal communities in arable soils are dominated by Nitrososphaeria, a class within Thaumarchaeota comprising all known ammonia-oxidizing archaea (AOA). AOA are key players in the nitrogen cycle and defining their niche specialization can help predicting effects of environmental change on these communities. However, hierarchical effects of environmental filters on AOA and the delineation of niche preferences of nitrososphaerial lineages remain poorly understood. We used phylogenetic information at fine scale and machine learning approaches to identify climatic, edaphic and geomorphological drivers of Nitrososphaeria and other archaea along a 3000 km European gradient. Only limited insights into the ecology of the low-abundant archaeal classes could be inferred, but our analyses underlined the multifactorial nature of niche differentiation within Nitrososphaeria. Mean annual temperature, C:N ratio and pH were the best predictors of their diversity, evenness and distribution. Thresholds in the predictions could be defined for C:N ratio and cation exchange capacity. Furthermore, multiple, independent and recent specializations to soil pH were detected in the Nitrososphaeria phylogeny. The coexistence of widespread ecophysiological differences between closely related soil Nitrososphaeria highlights that their ecology is best studied at fine phylogenetic scale.     

Novelty is not surprise: Human exploratory and adaptive behavior in sequential decision-making

Classic reinforcement learning (RL) theories cannot explain human behavior in the absence of external reward or when the environment changes. Here, we employ a deep sequential decision-making paradigm with sparse reward and abrupt environmental changes. To explain the behavior of human participants in these environments, we show that RL theories need to include surprise and novelty, each with a distinct role. While novelty drives exploration before the first encounter of a reward, surprise increases the rate of learning of a world-model as well as of model-free action-values. Even though the world-model is available for model-based RL, we find that human decisions are dominated by model-free action choices. The world-model is only marginally used for planning, but it is important to detect surprising events. Our theory predicts human action choices with high probability and allows us to dissociate surprise, novelty, and reward in EEG signals.