The secondary multidrug transporter LmrP contains multiple drug interaction sites.

The secondary multidrug transporter LmrP of Lactococcus lactis mediates the efflux of Hoechst 33342 from the cytoplasmic leaflet of the membrane. Kinetic analysis of Hoechst 33342 transport in inside-out membrane vesicles of L. lactis showed that the LmrP-mediated H(+)/Hoechst 33342 antiport reaction obeyed Michaelis-Menten kinetics, with a low apparent affinity constant of 0.63 microM Hoechst 33342 (= 0.5 mmol Hoechst 33342/mol phospholipid). Several drugs significantly inhibited LmrP-mediated Hoechst 33342 transport through a direct interaction with the protein rather than through dissipation of the proton motive force or reduction of the membrane partitioning of Hoechst 33342. The characterization of the mechanism of inhibition of LmrP-mediated Hoechst 33342 transport indicated competitive inhibition by quinine and verapamil, noncompetitive inhibition by nicardipin and vinblastin, and uncompetitive inhibition by TPP(+). The three types of inhibition of LmrP-mediated Hoechst 33342 transport in inside-out membrane vesicles indicate for the first time the presence of multiple drug interaction sites in a secondary multidrug transporter.     

Embryonic Morphogen Nodal Promotes Breast Cancer Growth and Progression

Breast cancers expressing human embryonic stem cell (hESC)-associated genes are more likely to progress than well-differentiated cancers and are thus associated with poor patient prognosis. Elevated proliferation and evasion of growth control are similarly associated with disease progression, and are classical hallmarks of cancer. In the current study we demonstrate that the hESC-associated factor Nodal promotes breast cancer growth. Specifically, we show that Nodal is elevated in aggressive MDA-MB-231, MDA-MB-468 and Hs578t human breast cancer cell lines, compared to poorly aggressive MCF-7 and T47D breast cancer cell lines. Nodal knockdown in aggressive breast cancer cells via shRNA reduces tumour incidence and significantly blunts tumour growth at primary sites. In vitro, using Trypan Blue exclusion assays, Western blot analysis of phosphorylated histone H3 and cleaved caspase-9, and real time RT-PCR analysis of BAX and BCL2 gene expression, we demonstrate that Nodal promotes expansion of breast cancer cells, likely via a combinatorial mechanism involving increased proliferation and decreased apopotosis. In an experimental model of metastasis using beta-glucuronidase (GUSB)-deficient NOD/SCID/mucopolysaccharidosis type VII (MPSVII) mice, we show that although Nodal is not required for the formation of small (<100 cells) micrometastases at secondary sites, it supports an elevated proliferation:apoptosis ratio (Ki67:TUNEL) in micrometastatic lesions. Indeed, at longer time points (8 weeks), we determined that Nodal is necessary for the subsequent development of macrometastatic lesions. Our findings demonstrate that Nodal supports tumour growth at primary and secondary sites by increasing the ratio of proliferation:apoptosis in breast cancer cells. As Nodal expression is relatively limited to embryonic systems and cancer, this study establishes Nodal as a potential tumour-specific target for the treatment of breast cancer.     

Lumbar muscle electromyographic dynamic topography during flexion-extension

The objective of this study is to introduce dynamic topography of surface electromyography (SEMG) to visualize lumbar muscle myoelectric activity and provides a new view to analyze muscle activity in vivo. A total of 20 healthy male subjects and 15 males LBP were enrolled. An electrode-array was applied to the lumbar region to collect SEMG. The root mean square (RMS) value was calculated for each channel, and then a 160×120 matrix was constructed using a linear cubic spline interpolation of each scan to create a 2-D color topographic image. Along a definite interval of action, a series of RMS topography matrices was concatenated as a function of position and time, to form a dynamic topographical video of lumbar muscle activity. Relative area (RA), relative width (RW), relative height (RH) and Width-to-Height Ratio (W/H) were chosen as the four quantitative parameters in measuring topographic features. Normal RMS dynamic topography was found to have a consistent, symmetric pattern with a high intensity area in the paraspinal area. LBP patients had a different RMS dynamic topography, with an asymmetric, broad, or disorganized distribution. Quantitative SEMG features were found significantly different between normal control and LBP. After physiotherapy rehabilitation, the dynamic topography images of LBP tended towards the normal pattern.There are obvious differences in lumbar muscle coordination between healthy subjects and LBP patients. The dynamic topography allows the continuous visualization of the distribution of surface EMG signals and the coordination of muscular contractions.     

Challenges in analysis and interpretation of microsatellite data for population genetic studies

Advancing technologies have facilitated the ever‐widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (F_ST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity‐based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration‐specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context‐dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non‐human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high‐throughput technologies in population genetics.     

The Deuterator: software for the determination of backbone amide deuterium levels from H/D exchange MS data

Background  

The combination of mass spectrometry and solution phase amide hydrogen/deuterium exchange (H/D exchange) experiments is an effective method for characterizing protein dynamics, and protein-protein or protein-ligand interactions. Despite methodological advancements and improvements in instrumentation and automation, data analysis and display remains a tedious process. The factors that contribute to this bottleneck are the large number of data points produced in a typical experiment, each requiring manual curation and validation, and then calculation of the level of backbone amide exchange. Tools have become available that address some of these issues, but lack sufficient integration, functionality, and accessibility required to address the needs of the H/D exchange community. To date there is no software for the analysis of H/D exchange data that comprehensively addresses these issues.     

Deepwater Horizon oil spill impacts on sea turtles could span the Atlantic

We investigated the extent that the 2010 Deepwater Horizon oil spill potentially affected oceanic-stage sea turtles from populations across the Atlantic. Within an ocean-circulation model, particles were backtracked from the Gulf of Mexico spill site to determine the probability of young turtles arriving in this area from major nesting beaches. The abundance of turtles in the vicinity of the oil spill was derived by forward-tracking particles from focal beaches and integrating population size, oceanic-stage duration and stage-specific survival rates. Simulations indicated that 321 401 (66 199–397 864) green (Chelonia mydas), loggerhead (Caretta caretta) and Kemp''s ridley (Lepidochelys kempii) turtles were likely within the spill site. These predictions compared favourably with estimates from in-water observations recently made available to the public (though our initial predictions for Kemp''s ridley were substantially lower than in-water estimates, better agreement was obtained with modifications to mimic behaviour of young Kemp''s ridley turtles in the northern Gulf). Simulations predicted 75.2% (71.9–76.3%) of turtles came from Mexico, 14.8% (11–18%) from Costa Rica, 5.9% (4.8–7.9%) from countries in northern South America, 3.4% (2.4–3.5%) from the United States and 1.6% (0.6–2.0%) from West African countries. Thus, the spill''s impacts may extend far beyond the current focus on the northern Gulf of Mexico.     

Finding the ‘lost years’ in green turtles: insights from ocean circulation models and genetic analysis

Organismal movement is an essential component of ecological processes and connectivity among ecosystems. However, estimating connectivity and identifying corridors of movement are challenging in oceanic organisms such as young turtles that disperse into the open sea and remain largely unobserved during a period known as ‘the lost years’. Using predictions of transport within an ocean circulation model and data from published genetic analysis, we present to our knowledge, the first basin-scale hypothesis of distribution and connectivity among major rookeries and foraging grounds (FGs) of green turtles (Chelonia mydas) during their ‘lost years’. Simulations indicate that transatlantic dispersal is likely to be common and that recurrent connectivity between the southwestern Indian Ocean and the South Atlantic is possible. The predicted distribution of pelagic juvenile turtles suggests that many ‘lost years hotspots’ are presently unstudied and located outside protected areas. These models, therefore, provide new information on possible dispersal pathways that link nesting beaches with FGs. These pathways may be of exceptional conservation concern owing to their importance for sea turtles during a critical developmental period.     

Predicted distributions and abundances of the sea turtle ‘lost years’ in the western North Atlantic Ocean

Oceanic dispersal characterizes the early juvenile life-stages of numerous marine species of conservation concern. This early stage may be a ‘critical period’ for many species, playing an overriding role in population dynamics. Often, relatively little information is available on their distribution during this period, limiting the effectiveness of efforts to understand environmental and anthropogenic impacts on these species. Here we present a simple model to predict annual variation in the distribution and abundance of oceanic-stage juvenile sea turtles based on species’ reproductive output, movement and mortality. We simulated dispersal of 25 cohorts (1993–2017) of oceanic-stage juveniles by tracking the movements of virtual hatchling sea turtles released in a hindcast ocean circulation model. We then used estimates of annual hatchling production from Kemp's ridley Lepidochelys kempii (n = 3), green Chelonia mydas (n = 8) and loggerhead Caretta caretta (n = 5) nesting areas in the northwestern Atlantic (inclusive of the Gulf of Mexico, Caribbean Sea and eastern seaboard of the U.S.) and their stage-specific mortality rates to weight dispersal predictions. The model's predictions indicate spatial heterogeneity in turtle distribution across their marine range, identify locations of increasing turtle abundance (notably along the U.S. coast), and provide valuable context for temporal variation in the stranding of young sea turtles across the Gulf of Mexico. Further effort to collect demographic, distribution and behavioral data that refine, complement and extend the utility of this modeling approach for sea turtles and other dispersive marine taxa is warranted. Finally, generating these spatially-explicit predictions of turtle abundance required extensive international collaboration among scientists; our findings indicate that continued conservation of these sea turtle populations and the management of the numerous anthropogenic activities that operate in the northwestern Atlantic Ocean will require similar international coordination.