Pacemaker and network mechanisms of rhythm generation: cooperation and competition

The origin of rhythmic activity in brain circuits and CPG-like motor networks is still not fully understood. The main unsolved questions are (i) What are the respective roles of intrinsic bursting and network based dynamics in systems of coupled heterogeneous, intrinsically complex, even chaotic, neurons? (ii) What are the mechanisms underlying the coexistence of robustness and flexibility in the observed rhythmic spatio-temporal patterns? One common view is that particular bursting neurons provide the rhythmogenic component while the connections between different neurons are responsible for the regularisation and synchronisation of groups of neurons and for specific phase relationships in multi-phasic patterns. We have examined the spatio-temporal rhythmic patterns in computer-simulated motif networks of H-H neurons connected by slow inhibitory synapses with a non-symmetric pattern of coupling strengths. We demonstrate that the interplay between intrinsic and network dynamics features either cooperation or competition, depending on three basic control parameters identified in our model: the shape of intrinsic bursts, the strength of the coupling and its degree of asymmetry. The cooperation of intrinsic dynamics and network mechanisms is shown to correlate with bistability, i.e., the coexistence of two different attractors in the phase space of the system corresponding to different rhythmic spatio-temporal patterns. Conversely, if the network mechanism of rhythmogenesis dominates, monostability is observed with a typical pattern of winnerless competition between neurons. We analyse bifurcations between the two regimes and demonstrate how they provide robustness and flexibility to the network performance.     

Functional proteometrics for cell migration.

BACKGROUND: Advances in living cellular fluorescence biosensors and computerized microscopy enable a vision of fully automated high-resolution measurements of the detailed intracellular molecular dynamics directly linked to cellular behaviors. Given the heterogeneity of cell populations, a statistically relevant study of molecular-cellular dynamics is a key motivation for improved automation. METHODS: We explored automating computerized, microscope-based data extraction and analyses that monitor cell locomotion, rates of mitoses, and spatiotemporal activities of intracellular proteins via ratiometric fluorescent biosensors in mouse fibroblasts. Novel image processing methods included K-means clustering segmentation preprocessing followed by modified discrete, normalized cross-correlational alignment of two-color images; ratiometric processing for fluorescence resonance energy transfer (FRET) measurements; and intracellular spatial distribution measurements of RhoA GTPase activity. RESULTS: The interdivision time was 19.4 h (mean) +/- 6.0 h (SD) (n = 7) for the GFP-histone cells in the two-by-two field that was scanned for 72 h. After registration and ratioing of the cells with the RhoA biosensor, increases in both cell protrusion and retraction were coincident with to increases in RhoA activity. CONCLUSIONS: These advances lay the foundation for extracting and correlating measurements characterizing the functional relationships of spatial localization and protein activation with features of cell migration such as velocity, polarization, protrusion, retraction, and mitosis.     

Silencing survivin gene expression promotes apoptosis of human breast cancer cells through a caspase-independent pathway

Survivin is recognized as an attractive target in cancer therapy because of its selective overexpression in the majority of tumors. Upregulated expression of this protein correlates with increased tumor grade, recurrence risk and decreased cancer patients survival. In this study, we assessed the efficacy of two survivin-specific small interfering RNA (siRNA) constructs to inhibit T47D human breast cancer cell growth. After siRNA transfection, T47D cells showed a significant reduction in proliferation and survival exhibiting clear signs of apoptosis. pSil_1 that targeted exon 1 exhibited a stronger inhibitory effect on cell growth, and increased cell apoptosis compared to pSil_30 that targeted exon 4. Cell apoptosis was found to be mediated by translocation of the mitochondrial apoptosis inducing factor (AIF), while no changes were observed in caspase-3 activation and Bid cleavage. Thus, silencing survivin expression using siRNA strategies represents a suitable therapeutic approach to selectively modulate the survival and growth of human breast cancer cells.     

Catalytic properties and classification of cellobiose dehydrogenases from ascomycetes

Putative cellobiose dehydrogenase (CDH) genes are frequently discovered in various fungi by genome sequencing projects. The expression of CDH, an extracellular flavocytochrome, is well studied in white rot basidiomycetes and is attributed to extracellular lignocellulose degradation. CDH has also been reported for plant-pathogenic or saprotrophic ascomycetes, but the molecular and catalytic properties of these enzymes are currently less investigated. This study links various ascomycetous cdh genes with the molecular and catalytic characteristics of the mature proteins and suggests a differentiation of ascomycete class II CDHs into two subclasses, namely, class IIA and class IIB, in addition to the recently introduced class III of hypothetical ascomycete CDHs. This new classification is based on sequence and biochemical data obtained from sequenced fungal genomes and a screening of 40 ascomycetes. Thirteen strains showed CDH activity when they were grown on cellulose-based media, and Chaetomium atrobrunneum, Corynascus thermophilus, Dichomera saubinetii, Hypoxylon haematostroma, Neurospora crassa, and Stachybotrys bisbyi were selected for detailed studies. In these strains, one or two cdh-encoding genes were found that stem either from class IIA and contain a C-terminal carbohydrate-binding module or from class IIB without such a module. In several strains, both genes were found. Regarding substrate specificity, class IIB CDHs show a less pronounced substrate specificity for cellobiose than class IIA enzymes. A pH-dependent pattern of the intramolecular electron transfer was also observed, and the CDHs were classified into three groups featuring acidic, intermediate, or alkaline pH optima. The pH optimum, however, does not correlate with the CDH subclasses and is most likely a species-dependent adaptation to different habitats.     

Ecological patterns of blood-feeding by kissing-bugs (Hemiptera: Reduviidae: Triatominae)

Host use by vectors is important in understanding the transmission of zoonotic diseases, which can affect humans, wildlife and domestic animals. Here, a synthesis of host exploitation patterns by kissing-bugs, vectors of Chagas disease, is presented. For this synthesis, an extensive literature review restricted to feeding sources analysed by precipitin tests was conducted. Modern tools from community ecology and multivariate statistics were used to determine patterns of segregation in host use. Rather than innate preferences for host species, host use by kissing-bugs is influenced by the habitats they colonise. One of the major limitations of studies on kissing-bug foraging has been the exclusive focus on the dominant vector species. We propose that expanding foraging studies to consider the community of vectors will substantially increase the understanding of Chagas disease transmission ecology. Our results indicate that host accessibility is a major factor that shapes the blood-foraging patterns of kissing-bugs. Therefore, from an applied perspective, measures that are directed at disrupting the contact between humans and kissing-bugs, such as housing improvement, are among the most desirable strategies for Chagas disease control.     

Neurodynamics: nonlinear dynamics and neurobiology

The use of methods from contemporary nonlinear dynamics in studying neurobiology has been rather limited.Yet, nonlinear dynamics has become a practical tool for analyzing data and verifying models. This has led to productive coupling of nonlinear dynamics with experiments in neurobiology in which the neural circuits are forced with constant stimuli, with slowly varying stimuli, with periodic stimuli, and with more complex information-bearing stimuli. Analysis of these more complex stimuli of neural circuits goes to the heart of how one is to understand the encoding and transmission of information by nervous systems.