The dynamics of the non-heme iron in bacterial reaction centers from Rhodobacter sphaeroides

AbstractWe investigate the dynamical properties of the non-heme iron (NHFe) in His-tagged photosynthetic bacterial reaction centers (RCs) isolated from Rhodobacter (Rb.) sphaeroides. Mössbauer spectroscopy and nuclear inelastic scattering of synchrotron radiation (NIS) were applied to monitor the arrangement and flexibility of the NHFe binding site. In His-tagged RCs, NHFe was stabilized only in a high spin ferrous state. Its hyperfine parameters (IS=1.06±0.01mm/s and QS=2.12±0.01mm/s), and Debye temperature (θD0~167K) are comparable to those detected for the high spin state of NHFe in non-His-tagged RCs. For the first time, pure vibrational modes characteristic of NHFe in a high spin ferrous state are revealed. The vibrational density of states (DOS) shows some maxima between 22 and 33meV, 33 and 42meV, and 53 and 60meV and a very sharp one at 44.5meV. In addition, we observe a large contribution of vibrational modes at low energies. This iron atom is directly connected to the protein matrix via all its ligands, and it is therefore extremely sensitive to the collective motions of the RC protein core. A comparison of the DOS spectra of His-tagged and non-His-tagged RCs from Rb. sphaeroides shows that in the latter case the spectrum was overlapped by the vibrations of the heme iron of residual cytochrome c2, and a low spin state of NHFe in addition to its high spin one. This enabled us to pin-point vibrations characteristic for the low spin state of NHFe

Emerging interdependence between stock values during financial crashes

To identify emerging interdependencies between traded stocks we investigate the behavior of the stocks of FTSE 100 companies in the period 2000-2015, by looking at daily stock values. Exploiting the power of information theoretical measures to extract direct influences between multiple time series, we compute the information flow across stock values to identify several different regimes. While small information flows is detected in most of the period, a dramatically different situation occurs in the proximity of global financial crises, where stock values exhibit strong and substantial interdependence for a prolonged period. This behavior is consistent with what one would generally expect from a complex system near criticality in physical systems, showing the long lasting effects of crashes on stock markets

Coral microbiome composition along the northern Red Sea suggests high plasticity of bacterial and specificity of endosymbiotic dinoflagellate communities

Background The capacity of reef-building corals to tolerate (or adapt to) heat stress is a key factor determining their resilience to future climate change. Changes in coral microbiome composition (particularly for microalgal endosymbionts and bacteria) is a potential mechanism that may assist corals to thrive in warm waters. The northern Red Sea experiences extreme temperatures anomalies, yet corals in this area rarely bleach suggesting possible refugia to climate change. However, the coral microbiome composition, and how it relates to the capacity to thrive in warm waters in this region, is entirely unknown. Results We investigated microbiomes for six coral species (Porites nodifera, Favia favus, Pocillopora damicornis, Seriatopora hystrix, Xenia umbellata, and Sarcophyton trocheliophorum) from five sites in the northern Red Sea spanning 4° of latitude and summer mean temperature ranges from 26.6 °C to 29.3 °C. A total of 19 distinct dinoflagellate endosymbionts were identified as belonging to three genera in the family Symbiodiniaceae (Symbiodinium, Cladocopium, and Durusdinium). Of these, 86% belonged to the genus Cladocopium, with notably five novel types (19%). The endosymbiont community showed a high degree of host-specificity despite the latitudinal gradient. In contrast, the diversity and composition of bacterial communities of the surface mucus layer (SML)—a compartment particularly sensitive to environmental change—varied significantly between sites, however for any given coral was species-specific. Conclusion The conserved endosymbiotic community suggests high physiological plasticity to support holobiont productivity across the different latitudinal regimes. Further, the presence of five novel algal endosymbionts suggests selection of certain genotypes (or genetic adaptation) within the semi-isolated Red Sea. In contrast, the dynamic composition of bacteria associated with the SML across sites may contribute to holobiont function and broaden the ecological niche. In doing so, SML bacterial communities may aid holobiont local acclimatization (or adaptation) by readily responding to changes in the host environment. Our study provides novel insight about the selective and endemic nature of coral microbiomes along the northern Red Sea refugia

Obstacles on the way to the clinical visualisation of beta cells: looking for the Aeneas of molecular imaging to navigate between Scylla and Charybdis

For more than a decade, researchers have been trying to develop non-invasive imaging techniques for the in vivo measurement of viable pancreatic beta cells. However, in spite of intense research efforts, only one tracer for positron emission tomography (PET) imaging is currently under clinical evaluation. To many diabetologists it may remain unclear why the imaging world struggles to develop an effective method for non-invasive beta cell imaging (BCI), which could be useful for both research and clinical purposes. Here, we provide a concise overview of the obstacles and challenges encountered on the way to such BCI, in both native and transplanted islets. We discuss the major difficulties posed by the anatomical and cell biological features of pancreatic islets, as well as the chemical and physical limits of the main imaging modalities, with special focus on PET, SPECT and MRI. We conclude by indicating new avenues for future research in the field, based on several remarkable recent results

Dynamical complexity of short and noisy time series: Compression-Complexity vs. Shannon entropy

Shannon entropy has been extensively used for characteriz- ing complexity of time series arising from chaotic dynamical systems and stochastic processes such as Markov chains. However, for short and noisy time series, Shannon entropy performs poorly. Complexity measures which are based on lossless compression algorithms are a good substitute in such scenarios. We evaluate the performance of two such Compression-Complexity Measures namely Lempel-Ziv complexity(LZ)andEffort-To-Compress( ETC)onshorttimeseriesfrom chaoticdynamicalsystemsinthepresenceofnoise.Both LZ and ETC outperform Shannon entropy (H) in accurately characterizing the dynamical complexity of such systems. For very short binary sequences (which arise in neuroscience applications), ETC has higher number of distinct complexity values than LZ and H, thus enabling a finer resolution. For two-state ergodic Markov chains, we empirically show that ETC converges to a steady state value faster than LZ. Compression-Complexity measures are promising for applications which involve short and noisy time series