Identifying priority core habitats and corridors for effective conservation of brown bears in Iran.

Iran lies at the southernmost range limit of brown bears globally. Therefore, understanding the habitat associations and patterns of population connectivity for brown bears in Iran is relevant for the species' conservation. We applied species distribution modeling to predict habitat suitability and connectivity modeling to identify population core areas and corridors. Our results showed that forest density, topographical roughness, NDVI and human footprint were the most influential variables in predicting brown bear distribution. The most crucial core areas and corridor networks for brown bear are concentrated in the Alborz and Zagros Mountains. These two core areas were predicted to be fragmented into a total of fifteen isolated patches if dispersal of brown bear across the landscape is limited to 50,000 cost units, and aggregates into two isolated habitat patches if the species is capable of dispersing 400,000 cost units. We found low overlap between corridors, and core habitats with protected areas, suggesting that the existing protected area network may not be adequate for the conservation of brown bear in Iran. Our results suggest that effective conservation of brown bears in Iran requires protection of both core habitats and the corridors between them, especially outside Iran's network of protected areas.

Dietary weight loss in insulin-resistant non-obese humans: Metabolic benefits and relationship to adipose cell size.

BACKGROUND AND AIMS: Overweight and obesity increase risk for diabetes and cardiovascular disease, largely through development of insulin resistance. Benefits of dietary weight loss are documented for obese individuals with insulin resistance. Similar benefits have not been shown in overweight individuals. We sought to quantify whether dietary weight loss improves metabolic risk profile in overweight insulin-resistant individuals, and evaluated potential mediators between weight loss and metabolic response. METHODS AND RESULTS: Healthy volunteers with BMI 25-29.9 kg/m2 underwent detailed metabolic phenotyping including insulin-mediated-glucose disposal, fasting/daylong glucose, insulin, triglycerides, FFA, and cholesterol. Subcutaneous fat biopsies were performed for measurement of adipose cell size. After 14 weeks of hypocaloric diet and 2 weeks of weight maintenance, cardiometabolic measures and biopsies were repeated. Changes in weight, % body fat, waist circumference, adipose cell size and FFA were evaluated as predictors of change in insulin resistance. Weight loss (4.3 kg) yielded significant improvements in insulin resistance and all cardiovascular risk markers except glucose, HDL-C, and LDL-C. Improvement in insulin sensitivity was greater among those with <2 vs >2 cardiovascular risk factors at baseline. Decrease in adipose cell size and waist circumference, but not weight or body fat, independently predicted improvement in insulin resistance. CONCLUSIONS: Weight loss yields metabolic health benefits in insulin-resistant overweight adults, even in the absence of classic cardiovascular risk factors. Weight loss-related improvement in insulin sensitivity may be mediated through changes in adipose cell size and/or central distribution of body fat. The insulin-resistant subgroup of overweight individuals should be identified and targeted for dietary weight loss. CLINICAL TRIALS IDENTIFIER: NCT00186459.

A comparison of individual-based genetic distance metrics for landscape genetics.

A major aim of landscape genetics is to understand how landscapes resist gene flow and thereby influence population genetic structure. An empirical understanding of this process provides a wealth of information that can be used to guide conservation and management of species in fragmented landscapes and also to predict how landscape change may affect population viability. Statistical approaches to infer the true model among competing alternatives are based on the strength of the relationship between pairwise genetic distances and landscape distances among sampled individuals in a population. A variety of methods have been devised to quantify individual genetic distances, but no study has yet compared their relative performance when used for model selection in landscape genetics. In this study, we used population genetic simulations to assess the accuracy of 16 individual-based genetic distance metrics under varying sample sizes and degree of population genetic structure. We found most metrics performed well when sample size and genetic structure was high. However, it was much more challenging to infer the true model when sample size and genetic structure was low. Under these conditions, we found genetic distance metrics based on principal components analysis were the most accurate (although several other metrics performed similarly), but only when they were derived from multiple principal components axes (the optimal number varied depending on the degree of population genetic structure). Our results provide guidance for which genetic distance metrics maximize model selection accuracy and thereby better inform conservation and management decisions based upon landscape genetic analysis.

Subcutaneous adipose cell size and distribution: relationship to insulin resistance and body fat.

OBJECTIVE: Metabolic heterogeneity among obese individuals may be attributable to differences in adipose cell size. We sought to clarify this by quantifying adipose cell size distribution, body fat, and insulin-mediated glucose uptake in overweight to moderately-obese individuals. METHODS: A total of 148 healthy nondiabetic subjects with BMI 25-38 kg/m2 underwent subcutaneous adipose tissue biopsies and quantification of insulin-mediated glucose uptake with steady-state plasma glucose (SSPG) concentrations during the modified insulin suppression test. Cell size distributions were obtained with Beckman Coulter Multisizer. Primary endpoints included % small adipose cells and diameter of large adipose cells. Cell-size and metabolic parameters were compared by regression for the whole group, according to insulin-resistant (IR) and insulin-sensitive (IS) subgroups, and by body fat quintile. RESULTS: Both large and small adipose cells were present in nearly equal proportions. Percent small cells was associated with SSPG (r = 0.26, P = 0.003). Compared to BMI-matched IS individuals, IR counterparts demonstrated fewer, but larger large adipose cells, and a greater proportion of small-to-large adipose cells. Diameter of the large adipose cells was associated with % body fat (r = 0.26, P = 0.014), female sex (r = 0.21, P = 0.036), and SSPG (r = 0.20, P = 0.012). In the highest versus lowest % body fat quintile, adipose cell size increased by only 7%, whereas adipose cell number increased by 74%. CONCLUSIONS: Recruitment of adipose cells is required for expansion of body fat mass beyond BMI of 25 kg/m2 . Insulin resistance is associated with accumulation of small adipose cells and enlargement of large adipose cells. These data support the notion that impaired adipogenesis may underlie insulin resistance.

Simulating natural selection in landscape genetics.

Linking landscape effects to key evolutionary processes through individual organism movement and natural selection is essential to provide a foundation for evolutionary landscape genetics. Of particular importance is determining how spatially-explicit, individual-based models differ from classic population genetics and evolutionary ecology models based on ideal panmictic populations in an allopatric setting in their predictions of population structure and frequency of fixation of adaptive alleles. We explore initial applications of a spatially-explicit, individual-based evolutionary landscape genetics program that incorporates all factors--mutation, gene flow, genetic drift and selection--that affect the frequency of an allele in a population. We incorporate natural selection by imposing differential survival rates defined by local relative fitness values on a landscape. Selection coefficients thus can vary not only for genotypes, but also in space as functions of local environmental variability. This simulator enables coupling of gene flow (governed by resistance surfaces), with natural selection (governed by selection surfaces). We validate the individual-based simulations under Wright-Fisher assumptions. We show that under isolation-by-distance processes, there are deviations in the rate of change and equilibrium values of allele frequency. The program provides a valuable tool (cdpop v1.0; http://cel.dbs.umt.edu/software/CDPOP/) for the study of evolutionary landscape genetics that allows explicit evaluation of the interactions between gene flow and selection in complex landscapes.

FoxP3 interacts with linker histone H1.5 to modulate gene expression and program Treg cell activity.

The forkhead box transcription factor FoxP3 controls the development and function of CD4+CD25+ regulatory T (Treg) cell. FoxP3 modulates gene expression in Treg cells by multiple epigenetic mechanisms that are not clearly defined. We identified FoxP3-interacting proteins in human T cells by co-immunoprecipitation/MS. We discovered that FoxP3 interacted with linker histone H1.5 via the leucine zipper (LZ) domain. Two independent IPEX patient-derived single residue mutations in the LZ of FoxP3 both abrogated its interaction with H1.5. Functionally, FoxP3 and H1.5 cooperatively repressed interleukin-2 (IL-2) expression in human T cells; and silencing of H1.5 expression inhibited the ability of FoxP3 to suppress IL-2 expression. We show that FoxP3 specifically enhanced H1.5 association at the IL-2 promoter, but reduce its association at the CTLA4 promoter, correlated with higher or lower histone acetylation of the respective promoters. Finally, silencing of H1.5 expression in human Treg cells impaired the Treg function to suppress target T cells. We conclude that FoxP3 interacts with H1.5 to alter its binding to target genes to modulate their expression and to program Treg function.

sGD: software for estimating spatially explicit indices of genetic diversity.

Anthropogenic landscape changes have greatly reduced the population size, range and migration rates of many terrestrial species. The small local effective population size of remnant populations favours loss of genetic diversity leading to reduced fitness and adaptive potential, and thus ultimately greater extinction risk. Accurately quantifying genetic diversity is therefore crucial to assessing the viability of small populations. Diversity indices are typically calculated from the multilocus genotypes of all individuals sampled within discretely defined habitat patches or larger regional extents. Importantly, discrete population approaches do not capture the clinal nature of populations genetically isolated by distance or landscape resistance. Here, we introduce spatial Genetic Diversity (sGD), a new spatially explicit tool to estimate genetic diversity based on grouping individuals into potentially overlapping genetic neighbourhoods that match the population structure, whether discrete or clinal. We compared the estimates and patterns of genetic diversity using patch or regional sampling and sGD on both simulated and empirical populations. When the population did not meet the assumptions of an island model, we found that patch and regional sampling generally overestimated local heterozygosity, inbreeding and allelic diversity. Moreover, sGD revealed fine-scale spatial heterogeneity in genetic diversity that was not evident with patch or regional sampling. These advantages should provide a more robust means to evaluate the potential for genetic factors to influence the viability of clinal populations and guide appropriate conservation plans.

Why replication is important in landscape genetics: American black bear in the Rocky Mountains.

We investigated how landscape features influence gene flow of black bears by testing the relative support for 36 alternative landscape resistance hypotheses, including isolation by distance (IBD) in each of 12 study areas in the north central U.S. Rocky Mountains. The study areas all contained the same basic elements, but differed in extent of forest fragmentation, altitude, variation in elevation and road coverage. In all but one of the study areas, isolation by landscape resistance was more supported than IBD suggesting gene flow is likely influenced by elevation, forest cover, and roads. However, the landscape features influencing gene flow varied among study areas. Using subsets of loci usually gave models with the very similar landscape features influencing gene flow as with all loci, suggesting the landscape features influencing gene flow were correctly identified. To test if the cause of the variability of supported landscape features in study areas resulted from landscape differences among study areas, we conducted a limiting factor analysis. We found that features were supported in landscape models only when the features were highly variable. This is perhaps not surprising but suggests an important cautionary note - that if landscape features are not found to influence gene flow, researchers should not automatically conclude that the features are unimportant to the species' movement and gene flow. Failure to investigate multiple study areas that have a range of variability in landscape features could cause misleading inferences about which landscape features generally limit gene flow. This could lead to potentially erroneous identification of corridors and barriers if models are transferred between areas with different landscape characteristics.

Quantifying the lag time to detect barriers in landscape genetics.

Understanding how spatial genetic patterns respond to landscape change is crucial for advancing the emerging field of landscape genetics. We quantified the number of generations for new landscape barrier signatures to become detectable and for old signatures to disappear after barrier removal. We used spatially explicit, individual-based simulations to examine the ability of an individual-based statistic [Mantel's r using the proportion of shared alleles' statistic (Dps)] and population-based statistic (FST ) to detect barriers. We simulated a range of movement strategies including nearest neighbour dispersal, long-distance dispersal and panmixia. The lag time for the signal of a new barrier to become established is short using Mantel's r (1-15 generations). FST required approximately 200 generations to reach 50% of its equilibrium maximum, although G'ST performed much like Mantel's r. In strong contrast, FST and Mantel's r perform similarly following the removal of a barrier formerly dividing a population. Also, given neighbour mating and very short-distance dispersal strategies, historical discontinuities from more than 100 generations ago might still be detectable with either method. This suggests that historical events and landscapes could have long-term effects that confound inferences about the impacts of current landscape features on gene flow for species with very little long-distance dispersal. Nonetheless, populations of organisms with relatively large dispersal distances will lose the signal of a former barrier within less than 15 generations, suggesting that individual-based landscape genetic approaches can improve our ability to measure effects of existing landscape features on genetic structure and connectivity.

Inferring landscape effects on gene flow: a new model selection framework.

Populations in fragmented landscapes experience reduced gene flow, lose genetic diversity over time and ultimately face greater extinction risk. Improving connectivity in fragmented landscapes is now a major focus of conservation biology. Designing effective wildlife corridors for this purpose, however, requires an accurate understanding of how landscapes shape gene flow. The preponderance of landscape resistance models generated to date, however, is subjectively parameterized based on expert opinion or proxy measures of gene flow. While the relatively few studies that use genetic data are more rigorous, frameworks they employ frequently yield models only weakly related to the observed patterns of genetic isolation. Here, we describe a new framework that uses expert opinion as a starting point. By systematically varying each model parameter, we sought to either validate the assumptions of expert opinion, or identify a peak of support for a new model more highly related to genetic isolation. This approach also accounts for interactions between variables, allows for nonlinear responses and excludes variables that reduce model performance. We demonstrate its utility on a population of mountain goats inhabiting a fragmented landscape in the Cascade Range, Washington.

Pioglitazone increases the proportion of small cells in human abdominal subcutaneous adipose tissue.

Rodent and in vitro studies suggest that thiazolidinediones promote adipogenesis but there are few studies in humans to corroborate these findings. The purpose of this study was to determine whether pioglitazone stimulates adipogenesis in vivo and whether this process relates to improved insulin sensitivity. To test this hypothesis, 12 overweight/obese nondiabetic, insulin-resistant individuals underwent biopsy of abdominal subcutaneous adipose tissue at baseline and after 12 weeks of pioglitazone treatment. Cell size distribution was determined via the Multisizer technique. Insulin sensitivity was quantified at baseline and postpioglitazone by the modified insulin suppression test. Regional fat depots were quantified by computed tomography (CT). Insulin resistance (steady-state plasma insulin and glucose (SSPG)) decreased following pioglitazone (P < 0.001). There was an increase in the ratio of small-to-large cells (1.16 +/- 0.44 vs. 1.52 +/- 0.66, P = 0.03), as well as a 25% increase in the absolute number of small cells (P = 0.03). The distribution of large cell diameters widened (P = 0.009), but diameter did not increase in the case of small cells. The increase in proportion of small cells was associated with the degree to which insulin resistance improved (r = -0.72, P = 0.012). Visceral abdominal fat decreased (P = 0.04), and subcutaneous abdominal (P = 0.03) and femoral fat (P = 0.004) increased significantly. Changes in fat volume were not associated with SSPG change. These findings demonstrate a clear effect of pioglitazone on human subcutaneous adipose cells, suggestive of adipogenesis in abdominal subcutaneous adipose tissue, as well as redistribution of fat from visceral to subcutaneous depots, highlighting a potential mechanism of action for thiazolidinediones. These findings support the hypothesis that defects in subcutaneous fat storage may underlie obesity-associated insulin resistance.

Inflammation in subcutaneous adipose tissue: relationship to adipose cell size.

AIMS/HYPOTHESIS: Inflammation is associated with increased body mass and purportedly with increased size of adipose cells. We sought to determine whether increased size of adipose cells is associated with localised inflammation in weight-stable, moderately obese humans. METHODS: We recruited 49 healthy, moderately obese individuals for quantification of insulin resistance (modified insulin suppression test) and subcutaneous abdominal adipose tissue biopsy. Cell size distribution was analysed with a multisizer device and inflammatory gene expression with real-time PCR. Correlations between inflammatory gene expression and cell size variables, with adjustment for sex and insulin resistance, were calculated. RESULTS: Adipose cells were bimodally distributed, with 47% in a 'large' cell population and the remainder in a 'small' cell population. The median diameter of the large adipose cells was not associated with expression of inflammatory genes. Rather, the fraction of small adipose cells was consistently associated with inflammatory gene expression, independently of sex, insulin resistance and BMI. This association was more pronounced in insulin-resistant than insulin-sensitive individuals. Insulin resistance also independently predicted expression of inflammatory genes. CONCLUSIONS/INTERPRETATION: This study demonstrates that among moderately obese, weight-stable individuals an increased proportion of small adipose cells is associated with inflammation in subcutaneous adipose tissue, whereas size of mature adipose cells is not. The observed association between small adipose cells and inflammation may reflect impaired adipogenesis and/or terminal differentiation. However, it is unclear whether this is a cause or consequence of inflammation. This question and whether small vs large adipose cells contribute differently to inflammation in adipose tissue are topics for future research. TRIAL REGISTRATION: ClinicalTrials.gov NCT00285844.

cdpop: A spatially explicit cost distance population genetics program.

Spatially explicit simulation of gene flow in complex landscapes is essential to explain observed population responses and provide a foundation for landscape genetics. To address this need, we wrote a spatially explicit, individual-based population genetics model (cdpop). The model implements individual-based population modelling with Mendelian inheritance and k-allele mutation on a resistant landscape. The model simulates changes in population and genotypes through time as functions of individual based movement, reproduction, mortality and dispersal on a continuous cost surface. This model will be a valuable tool for the study of landscape genetics by increasing our understanding about the effects of life history, vagility and differential models of landscape resistance on the genetic structure of populations in complex landscapes.

Relationships between migration rates and landscape resistance assessed using individual-based simulations.

Linking landscape effects on gene flow to processes such as dispersal and mating is essential to provide a conceptual foundation for landscape genetics. It is particularly important to determine how classical population genetic models relate to recent individual-based landscape genetic models when assessing individual movement and its influence on population genetic structure. We used classical Wright-Fisher models and spatially explicit, individual-based, landscape genetic models to simulate gene flow via dispersal and mating in a series of landscapes representing two patches of habitat separated by a barrier. We developed a mathematical formula that predicts the relationship between barrier strength (i.e., permeability) and the migration rate (m) across the barrier, thereby linking spatially explicit landscape genetics to classical population genetics theory. We then assessed the reliability of the function by obtaining population genetics parameters (m, F(ST) ) using simulations for both spatially explicit and Wright-Fisher simulation models for a range of gene flow rates. Next, we show that relaxing some of the assumptions of the Wright-Fisher model can substantially change population substructure (i.e., F(ST) ). For example, isolation by distance among individuals on each side of a barrier maintains an F(ST) of ∼0.20 regardless of migration rate across the barrier, whereas panmixia on each side of the barrier results in an F(ST) that changes with m as predicted by classical population genetics theory. We suggest that individual-based, spatially explicit modelling provides a general framework to investigate how interactions between movement and landscape resistance drive population genetic patterns and connectivity across complex landscapes.

Insulin resistance is associated with a modest increase in inflammation in subcutaneous adipose tissue of moderately obese women.

AIMS/HYPOTHESIS: We have previously described differences in adipose cell size distribution and expression of genes related to adipocyte differentiation in subcutaneous abdominal fat obtained from insulin-sensitive (IS) and -resistant (IR) persons, matched for degree of moderate obesity. To determine whether other biological properties also differ between IR and IS obese individuals, we quantified markers of inflammatory activity in adipose tissue from overweight IR and IS individuals. METHODS: Subcutaneous abdominal tissue was obtained from moderately obese women, divided into IR (n = 14) and IS (n = 19) subgroups by determining their steady-state plasma glucose (SSPG) concentrations during the insulin suppression test. Inflammatory activity was assessed by comparing expression of nine relevant genes and by immunohistochemical quantification of CD45- and CD68-containing cells. RESULTS: SSPG concentrations were approximately threefold higher in IR than in IS individuals. Expression levels of CD68, EMR1, IL8, IL6 and MCP/CCL2 mRNAs were modestly but significantly increased (p < 0.05) in IR compared with IS participants. Results of immunohistochemical staining were consistent with gene expression data, demonstrating modest differences between IR and IS individuals. Crown-like structures, in which macrophages surround single adipocytes, were rarely seen in tissue from either subgroup. CONCLUSIONS/INTERPRETATION: A modest increase in inflammatory activity was seen in subcutaneous adipose tissue from IR compared with equally obese IS individuals. Together with previous evidence of impaired adipose cell differentiation in IR vs equally obese individuals, it appears that at least two biological processes in subcutaneous adipose tissue characterize the insulin-resistant state independent of obesity per se.

Enhanced proportion of small adipose cells in insulin-resistant vs insulin-sensitive obese individuals implicates impaired adipogenesis.

AIMS/HYPOTHESIS: The biological mechanism by which obesity predisposes to insulin resistance is unclear. One hypothesis is that larger adipose cells disturb metabolism via increased lipolysis. While studies have demonstrated that cell size increases in proportion to BMI, it has not been clearly shown that adipose cell size, independent of BMI, is associated with insulin resistance. The aim of this study was to test this widely held assumption by comparing adipose cell size distribution in 28 equally obese, otherwise healthy individuals who represented extreme ends of the spectrum of insulin sensitivity, as defined by the modified insulin suppression test. SUBJECTS AND METHODS: Subcutaneous periumbilical adipose tissue biopsy samples were fixed in osmium tetroxide and passed through the Beckman Coulter Multisizer to obtain cell size distributions. Insulin sensitivity was quantified by the modified insulin suppression test. Quantitative real-time PCR for adipose cell differentiation genes was performed for 11 subjects. RESULTS: All individuals exhibited a bimodal cell size distribution. Contrary to expectations, the mean diameter of the larger cells was not significantly different between the insulin-sensitive and insulin-resistant individuals. Moreover, insulin resistance was associated with a higher ratio of small to large cells (1.66 +/- 1.03 vs 0.94 +/- 0.50, p = 0.01). Similar cell size distributions were observed for isolated adipose cells. The real-time PCR results showed two- to threefold lower expression of genes encoding markers of adipose cell differentiation (peroxisome proliferator-activated receptor gamma1 [PPARgamma1], PPARgamma2, GLUT4, adiponectin, sterol receptor element binding protein 1c) in insulin-resistant compared with insulin-sensitive individuals. CONCLUSIONS/INTERPRETATION: These results suggest that after controlling for obesity, insulin resistance is associated with an expanded population of small adipose cells and decreased expression of differentiation markers, suggesting that impairment in adipose cell differentiation may contribute to obesity-associated insulin resistance.

Characterisation of insulin-resistant phenotype of cultured rat primary adipose cells.

AIMS/HYPOTHESIS: We characterised insulin resistance, metabolic defects and endocrine dysfunction in cultured adipose cells and examined the autocrine or paracrine roles of cytokines/adipokines in the progression of insulin resistance. MATERIALS AND METHODS: Rat primary adipose cells were prepared and cultured for 24 and 48 h. Insulin resistance and gene expression were examined by glucose uptake assay, cDNA microarray and real-time RT-PCR. RESULTS: After 24 h in culture, the fold increase of insulin-stimulated glucose uptake in adipose cells was markedly reduced; after 48 h the response of the cells to insulin decreased. cDNA microarray analysis showed that the expression of 514 genes was altered in adipose cells after 24 h in culture. The dysregulated genes included those involved in the citric acid cycle and in fatty acid and pyruvate metabolism. Specifically, the following genes were all downregulated: genes encoding lipolytic and lipogenic enzymes; uncoupling protein 1 and 2 genes; peroxisome proliferator-activated receptor gamma, coactivator 1 alpha gene. This indicates that lipolytic and lipogenic activity, as well as mitochondria capacity decline in adipose cells cultured for 24 h. The mRNAs encoding 40 adipokines were also dysregulated in cultured cells. Strikingly, the dysregulated adipokines in cultured cells and in freshly isolated adipose cells from insulin-resistant Zucker fa/fa rats displayed a similar pattern with regard to protein functions. Also striking was the fact that progression of insulin resistance was promoted by the adipokines secreted from insulin-resistant adipose tissue or cells. CONCLUSIONS/INTERPRETATION: Our data demonstrate that the impairment of metabolism and endocrine dysfunction in cultured adipose cells mimics the insulin resistance occurring in vivo. Cytokines and adipokines appear to play a critical role in the progression of insulin resistance in adipose cells.

Insulin-regulated trafficking of dual-labeled glucose transporter 4 in primary rat adipose cells.

In isolated rat adipose cells, physiologically relevant insulin target cells, glucose transporter 4 (GLUT4) subcellular trafficking can be assessed by transfection of exofacially HA-tagged GLUT4. To simultaneously visualize the transfected GLUT4, we fused GFP with HA-GLUT4. With the resulting chimeras, GFP-HA-GLUT4 and HA-GLUT4-GFP, we were able to visualize for the first time the cell-surface localization, total expression, and intracellular distribution of GLUT4 in a single cell. Confocal microscopy reveals that the intracellular proportions of both GFP-HA-GLUT4 and HA-GLUT4-GFP are properly targeted to the insulin-responsive aminopeptidase-positive vesicles. Dynamic studies demonstrate close similarities in the trafficking kinetics between the two constructs and with native GLUT4. However, while the basal subcellular distribution of HA-GLUT4-GFP and the response to insulin are indistinguishable from those of HA-GLUT4 and endogenous GLUT4, most of the GFP-HA-GLUT4 is targeted to the plasma membrane with little further insulin response. Thus, HA-GLUT4-GFP will be useful to study GLUT4 trafficking in vivo while GFP on the N-terminus interferes with intracellular retention.

Targeting of GLUT6 (formerly GLUT9) and GLUT8 in rat adipose cells.

The subcellular targeting of the two recently cloned novel mammalian glucose transporters, GLUT6 [previously referred to as GLUT9 [Doege, Bocianski, Joost and Schürmann (2000) Biochem. J. 350, 771-776] and GLUT8, was analysed by expression of haemagglutinin (HA)-epitope-tagged GLUTs in transiently transfected primary rat adipose cells. Similar to HA-GLUT4, both transporters, HA-GLUT6 and HA-GLUT8, were retained in intracellular compartments in non-stimulated cells. In contrast, mutation of the N-terminal dileucine motifs in both constructs led to constitutive expression of the proteins on the plasma membrane. Likewise, when endocytosis was blocked by co-expression of a dominant-negative mutant of the dynamin GTPase, wild-type HA-GLUT6 and HA-GLUT8 accumulated on the cell surface. However, in contrast with HA-GLUT4, no translocation of HA-GLUT6 and HA-GLUT8 to the plasma membrane was observed when the cells were stimulated with insulin, phorbol ester or hyperosmolarity. Thus GLUT6 and GLUT8 appear to recycle in a dynamin-dependent manner between internal membranes and the plasma membrane in rat adipose cells, but are unresponsive to stimuli that induce translocation of GLUT4.

A central role for the T1 domain in voltage-gated potassium channel formation and function.

To interpret the recent atomic structures of the Kv (voltage-dependent potassium) channel T1 domain in a functional context, we must understand both how the T1 domain is integrated into the full-length functional channel protein and what functional roles the T1 domain governs. The T1 domain clearly plays a role in restricting Kv channel subunit heteromultimerization. However, the importance of T1 tetramerization for the assembly and retention of quarternary structure within full-length channels has remained controversial. Here we describe a set of mutations that disrupt both T1 assembly and the formation of functional channels and show that these mutations produce elevated levels of the subunit monomer that becomes subject to degradation within the cell. In addition, our experiments reveal that the T1 domain lends stability to the full-length channel structure, because channels lacking the T1 containing N terminus are more easily denatured to monomers. The integration of the T1 domain ultrastructure into the full-length channel was probed by proteolytic mapping with immobilized trypsin. Trypsin cleavage yields an N-terminal fragment that is further digested to a tetrameric domain, which remains reactive with antisera to T1, and that is similar in size to the T1 domain used for crystallographic studies. The trypsin-sensitive linkages retaining the T1 domain are cleaved somewhat slowly over hours. Therefore, they seem to be intermediate in trypsin resistance between the rapidly cleaved extracellular linker between the first and second transmembrane domains, and the highly resistant T1 core, and are likely to be partially structured or contain dynamic structure. Our experiments suggest that tetrameric atomic models obtained for the T1 domain do reflect a structure that the T1 domain sequence forms early in channel assembly to drive subunit protein tetramerization and that this structure is retained as an integrated stabilizing structural element within the full-length functional channel.