Effects of Multiple Metal Binding Sites on Calcium and Magnesium-dependent Activation of BK Channels

BK channels are activated by physiological concentrations of intracellular Ca2+ and Mg2+ in a variety of cells. Previous studies have identified two sites important for high-affinity Ca2+ sensing between [Ca2+]i of 0.1–100 μM and a site important for Mg2+ sensing between [Mg2+]i of 0.1–10 mM. BK channels can be also activated by Ca2+ and Mg2+ at concentrations >10 mM so that the steady-state conductance and voltage (G-V) relation continuously shifts to more negative voltage ranges when [Mg2+]i increases from 0.1–100 mM. We demonstrate that a novel site is responsible for metal sensing at concentrations ≥10 mM, and all four sites affect channel activation independently. As a result, the contributions of these sites to channel activation are complex, depending on the combination of Ca2+ and Mg2+ concentrations. Here we examined the effects of each of these sites on Ca2+ and Mg2+-dependent activation and the data are consistent with the suggestion that these sites are responsible for metal binding. We provide an allosteric model for quantitative estimation of the contributions that each of these putative binding sites makes to channel activation at any [Ca2+]i and [Mg2+]i

The interface between membrane-spanning and cytosolic domains in Ca2+-dependent K+ channels is involved in β subunit modulation of gating

Large-conductance, voltage-, and Ca(2+)-dependent K(+) (BK) channels are broadly expressed in various tissues to modulate neuronal activity, smooth muscle contraction, and secretion. BK channel activation depends on the interactions among the voltage sensing domain (VSD), the cytosolic domain (CTD), and the pore gate domain (PGD) of the Slo1 α-subunit, and is further regulated by accessory β subunits (β1–β4). How β subunits fine-tune BK channel activation is critical to understand the tissue-specific functions of BK channels. Multiple sites in both Slo1 and the β subunits have been identified to contribute to the interaction between Slo1 and the β subunits. However, it is unclear whether and how the interdomain interactions among the VSD, CTD, and PGD are altered by the β subunits to affect channel activation. Here we show that human β1 and β2 subunits alter interactions between bound Mg(2+) and gating charge R213 and disrupt the disulfide bond formation at the VSD–CTD interface of mouse Slo1, indicating that the β subunits alter the VSD–CTD interface. Reciprocally, mutations in the Slo1 that alter the VSD–CTD interaction can specifically change the effects of the β1 subunit on the Ca(2+) activation and of the β2 subunit on the voltage activation. Together, our data suggest a novel mechanism by which the β subunits modulated BK channel activation such that a β subunit may interact with the VSD or the CTD and alter the VSD–CTD interface of the Slo1, which enables the β subunit to have effects broadly on both voltage and Ca(2+)-dependent activation

Climate Change Hotspots Identification in China through the CMIP5 Global Climate Model Ensemble

China is one of the countries vulnerable to adverse climate changes. The potential climate change hotspots in China throughout the 21st century are identified in this study by using a multimodel, multiscenario climate model ensemble that includes Phase Five of the Coupled Model Intercomparison Project (CMIP5) atmosphere-ocean general circulation models. Both high (RCP8.5) and low (RCP4.5) greenhouse gas emission trajectories are tested, and both the mean and extreme seasonal temperature and precipitation are considered in identifying regional climate change hotspots. Tarim basin and Tibetan Plateau in West China are identified as persistent regional climate change hotspots in both the RCP4.5 and RCP8.5 scenarios. The aggregate impacts of climate change increase throughout the 21st century and are more significant in RCP8.5 than in RCP4.5. Extreme hot event and mean temperature are two climate variables that greatly contribute to the hotspots calculation in all regions. The contribution of other climate variables exhibits a notable subregional variability. South China is identified as another hotspot based on the change of extreme dry event, especially in SON and DJF, which indicates that such event will frequently occur in the future. Our results can contribute to the designing of national and cross-national adaptation and mitigation policies

Tmem16F forms a Ca2+-Activated Cation Channel Required for Lipid Scrambling in Platelets during Blood Coagulation

Collapse of membrane lipid asymmetry is a hallmark of blood coagulation. TMEM16F of the TMEM16 family that includes TMEM16A/B Ca(2+)-activated Cl(−) channels (CaCCs) is linked to Scott syndrome with deficient Ca(2+)-dependent lipid scrambling. We generated TMEM16F knockout mice that exhibit bleeding defects and protection in an arterial thrombosis model associated with platelet deficiency in Ca(2+)-dependent phosphatidylserine exposure and procoagulant activity and lack a Ca(2+)-activated cation current in the platelet precursor megakaryocytes. Heterologous expression of TMEM16F generates a small-conductance Ca(2+)-activated nonselective cation (SCAN) current with subpicosiemens single-channel conductance rather than a CaCC. TMEM16F-SCAN channels permeate both monovalent and divalent cations, including Ca(2+), and exhibit synergistic gating by Ca(2+) and voltage. We further pinpointed a residue in the putative pore region important for the cation versus anion selectivity of TMEM16F-SCAN and TMEM16A-CaCC channels. This study thus identifies a Ca(2+)-activated channel permeable to Ca(2+) and critical for Ca(2+)-dependent scramblase activity during blood coagulation

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation