Andrew J. Shirk

Mutation of a putative protein degradation gene LITAF/SIMPLE in Charcot-Marie-Tooth disease 1C

Background: Charcot-Marie-Tooth (CMT) neuropathy is a heterogeneous group of inherited disorders of the peripheral nervous system. The authors recently mapped an autosomal dominant demyelinating form of CMT type 1 (CMT1C) to chromosome 16p13.1-p12.3. Objective: To find the gene mutations underlying CMT1C. Methods: The authors used a combination of standard positional cloning and candidate gene approaches to identify the causal gene for CMT1C. Western blot analysis was used to determine relative protein levels in patient and control lymphocyte extracts. Northern blotting was used to characterize gene expression in 1) multiple tissues; 2) developing sciatic nerve; and 3) nerve-crush and nerve-transection experiments. Results: The authors identified missense mutations (G112S, T115N, W116G) in the LITAFgene (lipopolysaccharide-induced tumor necrosis factor-α factor) in three CMT1C pedigrees. LITAF, which is also referred to as SIMPLE, is a widely expressed gene encoding a 161-amino acid protein that may play a role in protein degradation pathways. The mutations associated with CMT1C were found to cluster, defining a domain of the LITAF protein having a critical role in peripheral nerve function. Western blot analysis suggested that the T115N and W116G mutations do not alter the level of LITAF protein in peripheral blood lymphocytes. The LITAF transcript is expressed in sciatic nerve, but its level of expression is not altered during development or in response to nerve injury. This finding is in stark contrast to that seen for other known genes that cause CMT1. Conclusions: Mutations in LITAF may account for a significant proportion of CMT1 patients with previously unknown molecular diagnosis and may define a new mechanism of peripheral nerve perturbation leading to demyelinating neuropathy.

Separating the effects of habitat area, fragmentation and matrix resistance on genetic differentiation in complex landscapes

Little is known about how variation in landscape mosaics affects genetic differentiation. The goal of this paper is to quantify the relative importance of habitat area and configuration, as well as the contrast in resistance between habitat and non-habitat, on genetic differentiation. We hypothesized that habitat configuration would be more influential than habitat area in influencing genetic differentiation. Population size is positively related to habitat area, and therefore habitat area should affect genetic drift, but not gene flow. In contrast, differential rates and patterns of gene flow across a landscape should be related to habitat configuration. Using spatially explicit, individual-based simulation modeling, we found that habitat configuration had stronger relationships with genetic differentiation than did habitat area, but there was a high degree of confounding between the effects of habitat area and configuration. We evaluated the predictive ability of six widely used landscape metrics and found that patch cohesion and correlation length of habitat are among the strongest individual predictors of genetic differentiation. Correlation length, patch density and clumpy are the most parsimonious set of variables to predict the magnitude of genetic differentiation in complex landscapes.

SIMPLE mutation in demyelinating neuropathy and distribution in sciatic nerve

Charcot–Marie–Tooth neuropathy type 1C (CMT1C) is an autosomal dominant demyelinating peripheral neuropathy caused by missense mutations in the small integral membrane protein of lysosome/late endosome (SIMPLE) gene. To investigate the prevalence of SIMPLE mutations, we screened a cohort of 152 probands with various types of demyelinating or axonal and pure motor or sensory inherited neuropathies. SIMPLE mutations were found only in CMT1 patients, including one G112S and one W116G missense mutations. A novel I74I polymorphism was identified, yet no splicing defect of SIMPLE is likely. Haplotype analysis of STR markers and intragenic SNPs linked to the gene demonstrated that families with the same mutation are unlikely to be related. The clustering of the G112S, T115N, and W116G mutations within five amino acids suggests this domain may be critical to peripheral nerve myelination. Electrophysiological studies showed that CMT1C patients from six pedigrees (n = 38) had reduced nerve conduction velocities ranging from 7.5 to 27.0m/sec (peroneal). Two patients had temporal dispersion of nerve conduction and irregularity of conduction slowing, which is unusual for CMT1 patients. We report the expression of SIMPLE in various cell types of the sciatic nerve, including Schwann cells, the affected cell type in CMT1C.

SIMPLE interacts with NEDD4 and TSG101: evidence for a role in lysosomal sorting and implications for Charcot-Marie-Tooth disease.

Mutation of the SIMPLE gene (small integral membrane protein of the lysosome/late endosome) is the molecular basis of Charcot‐Marie‐Tooth disease type 1C (CMT1C), a demyelinating peripheral neuropathy. Although the precise function of SIMPLE is unknown, prior reports suggest it localizes to the lysosome/late endosome. Furthermore, murine Simple interacts with Nedd4 (neural precursor cell expressed, developmentally downregulated 4), an E3 ubiquitin ligase that is important for regulating lysosomal degradation of plasma membrane proteins. To bring insights into the biochemical function of human SIMPLE, we confirmed that human SIMPLE interacts with NEDD4 and also report a novel interaction with tumor susceptibility gene 101 (TSG101), a class E vacuolar sorting protein. TSG101 is known to function downstream of NEDD4, sorting ubiquitinated substrates into multivesicular bodies (MVBs), which then deliver their cargo into the lysosomal lumen for degradation. Given the interaction with NEDD4 and TSG101, and the localization of SIMPLE along the lysosomal degradation pathway, we hypothesize that SIMPLE plays a role in the lysosomal sorting of plasma membrane proteins. We examine three CMT1C‐associated SIMPLE mutations and show that they do not affect the interaction with NEDD4 or TSG101, nor do they lead to altered subcellular localization.

Landscape genetics and limiting factors

Population connectivity is mediated by the movement of organisms or propagules through landscapes. However, little is known about how variation in the pattern of landscape mosaics affects the detectability of landscape genetic relationships. The goal of this paper is to explore the impacts of limiting factors on landscape genetic processes using simulation modeling. We used spatially explicit, individual-based simulation modeling to quantify the effects of habitat area, fragmentation and the contrast in resistance between habitat and non-habitat on the apparent strength and statistical detectability of landscape genetic relationships. We found that landscape genetic effects are often not detectable when habitat is highly connected. In such situations landscape structure does not limit gene flow. We also found that contrast in resistance values between habitat and non-habitat interacts with habitat extensiveness and fragmentation to affect detectability of landscape genetic relationships. Thus, the influence of landscape features critical to providing connectivity may not be detectable if gene flow is not limited by spatial patterns or resistance contrast of these features. We developed regression equations that reliably predict whether or not isolation by resistance will be detected independently of isolation by distance as a function of habitat fragmentation and contrast in resistance between habitat and non-habitat.

Polarized cholesterol and phospholipid efflux in cultured gall-bladder epithelial cells: evidence for an ABCA1-mediated pathway

Gall-bladder epithelial cells (GBEC) are exposed to high concentrations of cholesterol in bile. Whereas cholesterol absorption by GBEC is established, the fate of this absorbed cholesterol is not known. The aim of this study was to determine whether ABCA1 (ATP-binding cassette transporter A1) mediates cholesterol efflux in GBEC. Polarized canine GBEC were cultured on porous membrane filters allowing separate access to apical (AP) and basolateral (BL) compartments. After AP loading of cells with model bile and [14C]cholesterol, cholesterol efflux was measured. Cholesterol loading together with 8-bromo-cAMP treatment, which increased ABCA1 expression, led to a significant increase in cholesterol efflux with apolipoprotein A-I (apoA-I) as the acceptor. Cholesterol efflux was observed predominantly into the BL compartment. Similar results were found for phospholipid efflux. Confocal immunofluorescence microscopy showed a predominantly BL ABCA1 localization. Interestingly, apoA-I added to either the AP or the BL compartments elicited BL lipid efflux with cAMP treatment. No paracellular or transcellular passage of 125I-apoA-I occurred. Ligands for the nuclear hormone receptors liver X receptor alpha (LXRalpha) and retinoid X receptor (RXR) elicited AP and BL cholesterol efflux, suggesting the involvement of both ABCA1- and non-ABCA1-mediated pathways. In summary, BL cholesterol/phospholipid efflux consistent with an ABCA1-mediated mechanism occurs in GBEC. This efflux pathway is stimulated by cAMP and by LXRalpha/RXR ligands, and in the case of the cAMP pathway appears to involve a role for biliary apoA-I.

Simulating Pattern-Process Relationships to Validate Landscape Genetic Models

Landscapes may resist gene flow and thereby give rise to a pattern of genetic isolation within a population. The mechanism by which a landscape resists gene flow can be inferred by evaluating the relationship between landscape models and an observed pattern of genetic isolation. This approach risks false inferences because researchers can never feasibly test all plausible alternative hypotheses. In this paper, rather than infer the process of gene flow from an observed genetic pattern, we simulate gene flow and determine if the simulated genetic pattern is related to the observed empirical genetic pattern. This is a form of inverse modeling and can be used to independently validate a landscape genetic model. In this study, we used this approach to validate a model of landscape resistance based on elevation, landcover, and roads that was previously related to genetic isolation among mountain goats (Oreamnos americanus) inhabiting the Cascade Range, Washington (USA). The strong relationship between the empirical and simulated patterns of genetic isolation we observed provides independent validation of the resistance model and demonstrates the utility of this approach in supporting landscape genetic inferences.

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.

Epidermal growth factor mediates detachment from and invasion through collagen I and Matrigel in Capan-1 pancreatic cancer cells

BackgroundPancreatic adenocarcinoma is a highly invasive neoplasm. Epidermal growth factor (EGF) and its receptor are over expressed in pancreatic cancer, and expression correlates with invasion and metastasis. We hypothesized that EGF receptor and integrin signalling pathways interact in mediating cellular adhesion and invasion in pancreatic cancer, and that invasiveness correlates temporally with detachment from extracellular matrix.MethodsWe tested this hypothesis by investigating the role of EGF in mediating adhesion to and invasion through collagen I and Matrigel in the metastatic pancreatic adenocarcinoma cell line Capan-1. Adhesion and invasion were measured using in vitro assays of fluorescently-labeled cells. Adhesion and invasion assays were also performed in the primary pancreatic adenocarcinoma cell line MIA PaCa-2.ResultsEGF inhibited adhesion to collagen I and Matrigel in Capan-1 cells. The loss of adhesion was reversed by AG825, an inhibitor of erbB2 receptor signalling and by wortmannin, a PI3K inhibitor, but not by the protein synthesis inhibitor cycloheximide. EGF stimulated invasion through collagen I and Matrigel at concentrations and time courses similar to those mediating detachment from these extracellular matrix components. Adhesion to collagen I was different in MIA PaCa-2 cells, with no significant change elicited following EGF treatment, whereas treatment with the EGF family member heregulin-alpha elicited a marked increase in adhesion. Invasion through Matrigel in response to EGF, however, was similar to that observed in Capan-1 cells.ConclusionAn inverse relationship exists between adhesion and invasion capabilities in Capan-1 cells but not in MIA PaCa-2 cells. EGF receptor signalling involving the erbB2 and PI3K pathways plays a role in mediating these events in Capan-1 cells.

Spatially-explicit estimation of Wright's neighborhood size in continuous populations

Effective population size (Ne) is an important parameter in conservation genetics because it quantifies a population’s capacity to resist loss of genetic diversity due to inbreeding and drift. The classical approach to estimate Ne from genetic data involves grouping sampled individuals into discretely defined subpopulations assumed to be panmictic. Importantly, this assumption does not capture the continuous nature of populations genetically isolated by distance. Alternative approaches based on Wright’s genetic neighborhood concept quantify the local number of breeding individuals (NS) in a continuous population (as opposed to the global Ne). However, they do not reflect the potential for NS to vary spatially nor do they account for the resistance of a heterogeneous landscape to gene flow (isolation by resistance). Here, we describe an application of Wright’s neighborhood concept that provides spatially-explicit estimates of local NS from genetic data in continuous populations isolated by distance or resistance. We delineated local neighborhoods surrounding each sampled individual based on sigma (), a measure of the local extent of breeding. When  was known, the linkage disequilibrium method applied to local neighborhoods produced unbiased estimates of NS that were highly variable across the landscape. NS near the periphery or areas surrounded by high resistance was as much as an order of magnitude lower compared to the center, raising the potential for a spatial component to extinction vortex dynamics in continuous populations. When  is not known, it may be estimated from genetic data, but two methods we evaluated identified analysis extents that produced considerable bias or error in the estimate of NS. When  is known or accurately estimated, and the assumptions of Wright’s neighborhood are met, the method we describe provides spatially explicit information regarding short-term genetic processes that may inform conservation genetic analyses and management.