Slow Oscillation Amplitudes and Up-State Lengths Relate to Memory Improvement

There is growing evidence of the active involvement of sleep in memory consolidation. Besides hippocampal sharp wave-ripple complexes and sleep spindles, slow oscillations appear to play a key role in the process of sleep-associated memory consolidation. Furthermore, slow oscillation amplitude and spectral power increase during the night after learning declarative and procedural memory tasks. However, it is unresolved whether learning-induced changes specifically alter characteristics of individual slow oscillations, such as the slow oscillation up-state length and amplitude, which are believed to be important for neuronal replay. 24 subjects (12 men) aged between 20 and 30 years participated in a randomized, within-subject, multicenter study. Subjects slept on three occasions for a whole night in the sleep laboratory with full polysomnography. Whereas the first night only served for adaptation purposes, the two remaining nights were preceded by a declarative word-pair task or by a non-learning control task. Slow oscillations were detected in non-rapid eye movement sleep over electrode Fz. Results indicate positive correlations between the length of the up-state as well as the amplitude of both slow oscillation phases and changes in memory performance from pre to post sleep. We speculate that the prolonged slow oscillation up-state length might extend the timeframe for the transfer of initial hippocampal to long-term cortical memory representations, whereas the increase in slow oscillation amplitudes possibly reflects changes in the net synaptic strength of cortical networks.     

Population genetics of chamois in the contact zone between the Alps and the Dinaric Mountains: uncovering the role of habitat fragmentation and past management

The chamois is a habitat specialist ungulate occupying “continental archipelagos” of fragmented rocky habitats which are frequently restricted to high altitudes. It is not clear whether forest habitats separating such population fragments act as barriers to gene flow. We studied the genetic makeup of the chamois in a topographically diverse landscape at the contact zone of two mountain ranges in Slovenia. Based on sequences of mitochondrial DNA, all Slovenian populations belong to a Northern chamois (Rupicapra r. rupicapra) subspecies. The range of chamois in Slovenia encompasses three different regions, each with unique topography, habitat connectivity and abundance of chamois: the Alps, the Dinaric Mts., and the Pohorje Mts. The habitat of the chamois is extensive and more or less continuous in the Alps, but suboptimal and fragmented in the remaining regions. In agreement with neutral genetic theory, large Northern chamois populations tended to have higher allelic richness and observed heterozygosity. Spatial clustering bears the differentiation into four geographically associated clusters within Slovenia and also revealed a strong substructure within all mountain ranges with suboptimal chamois habitat. Surprisingly, some small Dinaric populations have stayed genetically isolated in restricted habitat patches, even if they are geographically very close to each other. The four clusters, each having a unique demographic history, should be regarded as independent units for management purposes.     

Flow Cytometry Bioinformatics

Flow cytometry bioinformatics is the application of bioinformatics to flow cytometry data, which involves storing, retrieving, organizing, and analyzing flow cytometry data using extensive computational resources and tools. Flow cytometry bioinformatics requires extensive use of and contributes to the development of techniques from computational statistics and machine learning. Flow cytometry and related methods allow the quantification of multiple independent biomarkers on large numbers of single cells. The rapid growth in the multidimensionality and throughput of flow cytometry data, particularly in the 2000s, has led to the creation of a variety of computational analysis methods, data standards, and public databases for the sharing of results. Computational methods exist to assist in the preprocessing of flow cytometry data, identifying cell populations within it, matching those cell populations across samples, and performing diagnosis and discovery using the results of previous steps. For preprocessing, this includes compensating for spectral overlap, transforming data onto scales conducive to visualization and analysis, assessing data for quality, and normalizing data across samples and experiments. For population identification, tools are available to aid traditional manual identification of populations in two-dimensional scatter plots (gating), to use dimensionality reduction to aid gating, and to find populations automatically in higher dimensional space in a variety of ways. It is also possible to characterize data in more comprehensive ways, such as the density-guided binary space partitioning technique known as probability binning, or by combinatorial gating. Finally, diagnosis using flow cytometry data can be aided by supervised learning techniques, and discovery of new cell types of biological importance by high-throughput statistical methods, as part of pipelines incorporating all of the aforementioned methods. Open standards, data, and software are also key parts of flow cytometry bioinformatics. Data standards include the widely adopted Flow Cytometry Standard (FCS) defining how data from cytometers should be stored, but also several new standards under development by the International Society for Advancement of Cytometry (ISAC) to aid in storing more detailed information about experimental design and analytical steps. Open data is slowly growing with the opening of the CytoBank database in 2010 and FlowRepository in 2012, both of which allow users to freely distribute their data, and the latter of which has been recommended as the preferred repository for MIFlowCyt-compliant data by ISAC. Open software is most widely available in the form of a suite of Bioconductor packages, but is also available for web execution on the GenePattern platform.

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

     

High Molecular Weight Forms of Mammalian Respiratory Chain Complex II

Mitochondrial respiratory chain is organised into supramolecular structures that can be preserved in mild detergent solubilisates and resolved by native electrophoretic systems. Supercomplexes of respiratory complexes I, III and IV as well as multimeric forms of ATP synthase are well established. However, the involvement of complex II, linking respiratory chain with tricarboxylic acid cycle, in mitochondrial supercomplexes is questionable. Here we show that digitonin-solubilised complex II quantitatively forms high molecular weight structures (CII_hmw) that can be resolved by clear native electrophoresis. CII_hmw structures are enzymatically active and differ in electrophoretic mobility between tissues (500 – over 1000 kDa) and cultured cells (400–670 kDa). While their formation is unaffected by isolated defects in other respiratory chain complexes, they are destabilised in mtDNA-depleted, rho0 cells. Molecular interactions responsible for the assembly of CII_hmw are rather weak with the complexes being more stable in tissues than in cultured cells. While electrophoretic studies and immunoprecipitation experiments of CII_hmw do not indicate specific interactions with the respiratory chain complexes I, III or IV or enzymes of the tricarboxylic acid cycle, they point out to a specific interaction between CII and ATP synthase.     

MHC Class IIB Exon 2 Polymorphism in the Grey Partridge (Perdix perdix) Is Shaped by Selection,Recombination and Gene Conversion

Among bird species, the most studied major histocompatibility complex (MHC) is the chicken MHC. Although the number of studies on MHC in free-ranging species is increasing, the knowledge on MHC variation in species closely related to chicken is required to understand the peculiarities of bird MHC evolution. Here we describe the variation of MHC class IIB (MHCIIB) exon 2 in a population of the Grey partridge (Perdix perdix), a species of high conservation concern throughout Europe and an emerging galliform model in studies of sexual selection. We found 12 alleles in 108 individuals, but in comparison to other birds surprisingly many sites show signatures of historical positive selection. Individuals displayed between two to four alleles both on genomic and complementary DNA, suggesting the presence of two functional MHCIIB loci. Recombination and gene conversion appear to be involved in generating MHCIIB diversity in the Grey partridge; two recombination breakpoints and several gene conversion events were detected. In phylogenetic analysis of galliform MHCIIB, the Grey partridge alleles do not cluster together, but are scattered through the tree instead. Thus, our results indicate that the Grey partridge MHCIIB is comparable to most other galliforms in terms of copy number and population polymorphism.     

Niedergang der Insekten

The Decline of Insects – Why moths and other insects are becoming rarer Fifty years of quantitative study of abundance of night-flying insects attracted to ultraviolet light revealed a decrease of more than 80 per cent in moths since the start of the study in 1969 and of 96 per cent in the other (small) insects for the margins of the arable land subjected to conventional farming, but no changes in insect abundance in several areas in the city of Munich. There, at present more insects fly despite light pollution than on the borders of agricultural land on the countryside. The trend of abundance in the quite insect rich riverine forests is inconclusive, and probably due to fluctuations caused by the uninhibited growth of the trees, which are no longer used for fire wood. Concerning agriculture the key factor is overfertilisation which creates conditions too cold and too wet due to vegetation which became much too dense. Additionally the extensive application of pesticides reduces insect population. Second to conventional agriculture, however, is the overzealous cleaning (in fact a shaving) of marginal land in towns, villages and along roads, called the duly public maintenance. This highly destructive practice could be cancelled quite simply.     

Adverse responses of Cabera pusaria caterpillars to high dietary manganese concentration

The adaptation of insects to environmental changes can constitute a crucial factor in their development and activity. The response of Cabera pusaria L. (Lepidoptera: Geometridae) caterpillars to high manganese (Mn) concentrations in the diet was studied. Birch leaves were treated by dipping in MnCl₂·4H₂O solutions, thereby achieving Mn contents of 370 (T0), 695 (T1), 3 198 (T2), and 6 302 mg kg⁻¹ (T3). The reactions were determined by observing caterpillar mortality, development time, food consumption, and pupal weight. Manganese concentrations in larval excrement, pupae, and food were determined. Manganese in the diet at unnaturally increased concentrations caused great stress for caterpillars. All individuals in the treatment with the highest Mn concentration (T3) died during rearing and successful pupation occurred in only four individuals in T2. Even in the case of caterpillars from T1 (twofold higher than T0) a negative reaction (increased food consumption and prolonged development) was recorded. We also determined significantly increased Mn concentration in pupae from T1 (T2 and T3 were not included in this evaluation due to mortality) and excrement (T1‒T3) compared with T0 having a natural Mn concentration. Caterpillars were seen to eliminate negatively acting dietary Mn by its translocation to excrement. However, the highest mortality rate in T2 and T3 and negative reactions of individuals in T1 very likely demonstrate energy insufficiency and the high energy requirements of Mn elimination mechanisms.     

Scaling between macro- to microscale climatic data reveals strong phylogenetic inertia in niche evolution in plethodontid salamanders

Macroclimatic niches are indirect and potentially inadequate predictors of the realized environmental conditions that many species experience. Consequently, analyses of niche evolution based on macroclimatic data alone may incompletely represent the evolutionary dynamics of species niches. Yet, understanding how an organisms’ climatic (Grinnellian) niche responds to changing macroclimatic conditions is of vital importance for predicting their potential response to global change. In this study, we integrate microclimatic and macroclimatic data across 26 species of plethodontid salamanders to portray the relationship between microclimatic niche evolution in response to changing macroclimate. We demonstrate stronger phylogenetic signal in microclimatic niche variables than at the macroclimatic scale. Even so, we find that the microclimatic niche tracks climatic changes at the macroscale, but with a phylogenetic lag at million-year timescales. We hypothesize that behavioral tracking of the microclimatic niche over space and phenology generates the lag: salamanders preferentially select microclimates similar to their ancestral conditions rather than adapting with changes in physiology. We demonstrate that macroclimatic variables are weak predictors of niche evolution and that incorporating spatial scale into analyses of niche evolution is critical for predicting responses to climate change.