Biophysical physiology of phosphoinositide rapid dynamics and regulation in living cells

Phosphoinositide membrane lipids are ubiquitous low-abundance signaling molecules. They direct many physiological processes that involve ion channels, membrane identification, fusion of membrane vesicles, and vesicular endocytosis. Pools of these lipids are continually broken down and refilled in living cells, and the rates of some of these reactions are strongly accelerated by physiological stimuli. Recent biophysical experiments described here measure and model the kinetics and regulation of these lipid signals in intact cells. Rapid on-line monitoring of phosphoinositide metabolism is made possible by optical tools and electrophysiology. The experiments reviewed here reveal that as for other cellular second messengers, the dynamic turnover and lifetimes of membrane phosphoinositides are measured in seconds, controlling and timing rapid physiological responses, and the signaling is under strong metabolic regulation. The underlying mechanisms of this metabolic regulation remain questions for the future

Can biodiversity of preexisting and created salt marshes match across scales? An assessment from microbes to predators

Coastal wetlands are rapidly disappearing worldwide due to a variety of processes, including climate change and flood control. The rate of loss in the Mississippi River Delta is among the highest in the world and billions of dollars have been allocated to build and restore coastal wetlands. A key question guiding assessment is whether created coastal salt marshes have similar biodiversity to preexisting, reference marshes. However, the numerous biodiversity metrics used to make these determinations are typically scale dependent and often conflicting. Here, we applied ecological theory to compare the diversity of different assemblages (surface and below-surface soil microbes, plants, macroinfauna, spiders, and on-marsh and off-marsh nekton) between two created marshes (4–6 years old) and four reference marshes. We also quantified the scale-dependent effects of species abundance distribution, aggregation, and density on richness differences and explored differences in species composition. Total, between-sample, and within-sample diversity (γ, β, and α, respectively) were not consistently lower at created marshes. Richness decomposition varied greatly among assemblages and marshes (e.g., soil microbes showed high equitability and α diversity, but plant diversity was restricted to a few dominant species with high aggregation). However, species abundance distribution, aggregation, and density patterns were not directly associated with differences between created and reference marshes. One exception was considerably lower density for macroinfauna at one of the created marshes, which was drier because of being at a higher elevation and having coarser substrate compared with the other marshes. The community compositions of created marshes were more dissimilar than reference marshes for microbe and macroinfauna assemblages. However, differences were small, particularly for microbes. Together, our results suggest generally similar taxonomic diversity and composition between created and reference marshes. This provides support for the creation of marsh habitat as tools for the maintenance and restoration of coastal biodiversity. However, caution is needed when creating marshes because specific building and restoration plans may lead to different colonization patterns

Kinetics of M1 muscarinic receptor and G protein signaling to phospholipase C in living cells

G protein–coupled receptors (GPCRs) mediate responses to external stimuli in various cell types. Early events, such as the binding of ligand and G proteins to the receptor, nucleotide exchange (NX), and GTPase activity at the Gα subunit, are common for many different GPCRs. For Gq-coupled M1 muscarinic (acetylcholine) receptors (M1Rs), we recently measured time courses of intermediate steps in the signaling cascade using Förster resonance energy transfer (FRET). The expression of FRET probes changes the density of signaling molecules. To provide a full quantitative description of M1R signaling that includes a simulation of kinetics in native (tsA201) cells, we now determine the density of FRET probes and construct a kinetic model of M1R signaling through Gq to activation of phospholipase C (PLC). Downstream effects on the trace membrane lipid phosphatidylinositol 4,5-bisphosphate (PIP2) and PIP2-dependent KCNQ2/3 current are considered in our companion paper in this issue (Falkenburger et al. 2010. J. Gen. Physiol. doi:10.1085/jgp.200910345). By calibrating their fluorescence intensity, we found that we selected transfected cells for our experiments with ∼3,000 fluorescently labeled receptors, G proteins, or PLC molecules per µm2 of plasma membrane. Endogenous levels are much lower, 1–40 per µm2. Our kinetic model reproduces the time courses and concentration–response relationships measured by FRET and explains observed delays. It predicts affinities and rate constants that align well with literature values. In native tsA201 cells, much of the delay between ligand binding and PLC activation reflects slow binding of G proteins to receptors. With M1R and Gβ FRET probes overexpressed, 10% of receptors have G proteins bound at rest, rising to 73% in the presence of agonist. In agreement with previous work, the model suggests that binding of PLC to Gαq greatly speeds up NX and GTPase activity, and that PLC is maintained in the active state by cycles of rapid GTP hydrolysis and NX on Gαq subunits bound to PLC

Fluorescence changes reveal kinetic steps of muscarinic receptor–mediated modulation of phosphoinositides and Kv7.2/7.3 K+ channels

G protein–coupled receptors initiate signaling cascades. M1 muscarinic receptor (M1R) activation couples through Gαq to stimulate phospholipase C (PLC), which cleaves phosphatidylinositol 4,5-bisphosphate (PIP2). Depletion of PIP2 closes PIP2-requiring Kv7.2/7.3 potassium channels (M current), thereby increasing neuronal excitability. This modulation of M current is relatively slow (6.4 s to reach within 1/e of the steady-state value). To identify the rate-limiting steps, we investigated the kinetics of each step using pairwise optical interactions likely to represent fluorescence resonance energy transfer for M1R activation, M1R/Gβ interaction, Gαq/Gβ separation, Gαq/PLC interaction, and PIP2 hydrolysis. Electrophysiology was used to monitor channel closure. Time constants for M1R activation (<100 ms) and M1R/Gβ interaction (200 ms) are both fast, suggesting that neither of them is rate limiting during muscarinic suppression of M current. Gαq/Gβ separation and Gαq/PLC interaction have intermediate 1/e times (2.9 and 1.7 s, respectively), and PIP2 hydrolysis (6.7 s) occurs on the timescale of M current suppression. Overexpression of PLC accelerates the rate of M current suppression threefold (to 2.0 s) to become nearly contemporaneous with Gαq/PLC interaction. Evidently, channel release of PIP2 and closure are rapid, and the availability of active PLC limits the rate of M current suppression

Determining the Electronic Confinement of a Subsurface Metallic State

Dopant profiles in semiconductors are important for understanding nanoscale electronics. Highly conductive and extremely confined phosphorus doping profiles in silicon, known as Si:P δ-layers, are of particular interest for quantum computer applications, yet a quantitative measure of their electronic profile has been lacking. Using resonantly enhanced photoemission spectroscopy, we reveal the real-space breadth of the Si:P δ-layer occupied states and gain a rare view into the nature of the confined orbitals. We find that the occupied valley-split states of the δ-layer, the so-called 1Γ and 2Γ, are exceptionally confined with an electronic profile of a mere 0.40 to 0.52 nm at full width at half-maximum, a result that is in excellent agreement with density functional theory calculations. Furthermore, the bulk-like Si 3pz orbital from which the occupied states are derived is sufficiently confined to lose most of its pz-like character, explaining the strikingly large valley splitting observed for the 1Γ and 2Γ states

Ovarian and Breast Cancer Risks Associated With Pathogenic Variants in RAD51C and RAD51D.

BACKGROUND: The purpose of this study was to estimate precise age-specific tubo-ovarian carcinoma (TOC) and breast cancer (BC) risks for carriers of pathogenic variants in RAD51C and RAD51D. METHODS: We analyzed data from 6178 families, 125 with pathogenic variants in RAD51C, and 6690 families, 60 with pathogenic variants in RAD51D. TOC and BC relative and cumulative risks were estimated using complex segregation analysis to model the cancer inheritance patterns in families while adjusting for the mode of ascertainment of each family. All statistical tests were two-sided. RESULTS: Pathogenic variants in both RAD51C and RAD51D were associated with TOC (RAD51C: relative risk [RR] = 7.55, 95% confidence interval [CI] = 5.60 to 10.19; P = 5 × 10-40; RAD51D: RR = 7.60, 95% CI = 5.61 to 10.30; P = 5 × 10-39) and BC (RAD51C: RR = 1.99, 95% CI = 1.39 to 2.85; P = 1.55 × 10-4; RAD51D: RR = 1.83, 95% CI = 1.24 to 2.72; P = .002). For both RAD51C and RAD51D, there was a suggestion that the TOC relative risks increased with age until around age 60 years and decreased thereafter. The estimated cumulative risks of developing TOC to age 80 years were 11% (95% CI = 6% to 21%) for RAD51C and 13% (95% CI = 7% to 23%) for RAD51D pathogenic variant carriers. The estimated cumulative risks of developing BC to 80 years were 21% (95% CI = 15% to 29%) for RAD51C and 20% (95% CI = 14% to 28%) for RAD51D pathogenic variant carriers. Both TOC and BC risks for RAD51C and RAD51D pathogenic variant carriers varied by cancer family history and could be as high as 32-36% for TOC, for carriers with two first-degree relatives diagnosed with TOC, or 44-46% for BC, for carriers with two first-degree relatives diagnosed with BC. CONCLUSIONS: These estimates will facilitate the genetic counseling of RAD51C and RAD51D pathogenic variant carriers and justify the incorporation of RAD51C and RAD51D into cancer risk prediction models

Clinical Sequencing Exploratory Research Consortium: Accelerating Evidence-Based Practice of Genomic Medicine

Despite rapid technical progress and demonstrable effectiveness for some types of diagnosis and therapy, much remains to be learned about clinical genome and exome sequencing (CGES) and its role within the practice of medicine. The Clinical Sequencing Exploratory Research (CSER) consortium includes 18 extramural research projects, one National Human Genome Research Institute (NHGRI) intramural project, and a coordinating center funded by the NHGRI and National Cancer Institute. The consortium is exploring analytic and clinical validity and utility, as well as the ethical, legal, and social implications of sequencing via multidisciplinary approaches; it has thus far recruited 5,577 participants across a spectrum of symptomatic and healthy children and adults by utilizing both germline and cancer sequencing. The CSER consortium is analyzing data and creating publically available procedures and tools related to participant preferences and consent, variant classification, disclosure and management of primary and secondary findings, health outcomes, and integration with electronic health records. Future research directions will refine measures of clinical utility of CGES in both germline and somatic testing, evaluate the use of CGES for screening in healthy individuals, explore the penetrance of pathogenic variants through extensive phenotyping, reduce discordances in public databases of genes and variants, examine social and ethnic disparities in the provision of genomics services, explore regulatory issues, and estimate the value and downstream costs of sequencing. The CSER consortium has established a shared community of research sites by using diverse approaches to pursue the evidence-based development of best practices in genomic medicine

Suicide risk in schizophrenia: learning from the past to change the future

Suicide is a major cause of death among patients with schizophrenia. Research indicates that at least 5–13% of schizophrenic patients die by suicide, and it is likely that the higher end of range is the most accurate estimate. There is almost total agreement that the schizophrenic patient who is more likely to commit suicide is young, male, white and never married, with good premorbid function, post-psychotic depression and a history of substance abuse and suicide attempts. Hopelessness, social isolation, hospitalization, deteriorating health after a high level of premorbid functioning, recent loss or rejection, limited external support, and family stress or instability are risk factors for suicide in patients with schizophrenia. Suicidal schizophrenics usually fear further mental deterioration, and they experience either excessive treatment dependence or loss of faith in treatment. Awareness of illness has been reported as a major issue among suicidal schizophrenic patients, yet some researchers argue that insight into the illness does not increase suicide risk. Protective factors play also an important role in assessing suicide risk and should also be carefully evaluated. The neurobiological perspective offers a new approach for understanding self-destructive behavior among patients with schizophrenia and may improve the accuracy of screening schizophrenics for suicide. Although, there is general consensus on the risk factors, accurate knowledge as well as early recognition of patients at risk is still lacking in everyday clinical practice. Better knowledge may help clinicians and caretakers to implement preventive measures. This review paper is the results of a joint effort between researchers in the field of suicide in schizophrenia. Each expert provided a brief essay on one specific aspect of the problem. This is the first attempt to present a consensus report as well as the development of a set of guidelines for reducing suicide risk among schizophenia patients

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe