HtrA1 Mediated Intracellular Effects on Tubulin Using a Polarized RPE Disease Model

Age-related macular degeneration (AMD) is the leading cause of irreversible vision loss. The protein HtrA1 is enriched in retinal pigment epithelial (RPE) cells isolated from AMD patients and in drusen deposits. However, it is poorly understood how increased levels of HtrA1 affect the physiological function of the RPE at the intracellular level. Here, we developed hfRPE (human fetal retinal pigment epithelial) cell culture model where cells fully differentiated into a polarized functional monolayer. In this model, we fine-tuned the cellular levels of HtrA1 by targeted overexpression. Our data show that HtrA1 enzymatic activity leads to intracellular degradation of tubulin with a corresponding reduction in the number of microtubules, and consequently to an altered mechanical cell phenotype. HtrA1 overexpression further leads to impaired apical processes and decreased phagocytosis, an essential function for photoreceptor survival. These cellular alterations correlate with the AMD phenotype and thus highlight HtrA1 as an intracellular target for therapeutic interventions towards AMD treatment

Effects of Natura 2000 on nontarget bird and butterfly species based on citizen science data

ABSTRACT The European Union's Natura 2000 (N2000), is one of the largest international networks of protected areas. One of its aims is to secure the status of a pre-determined set of (targeted) bird and butterfly species. However, also non-target species may benefit from N2000. We evaluated how the terrestrial component of this network relates to the abundance of non-targeted, more common bird and butterfly species using data from long-term volunteer-based monitoring programs in 9,602 sites for birds and 2,001 sites for butterflies. In almost half of the 155 bird species assessed, and particularly among woodland specialists, abundance increased with the proportion of N2000 sites in the landscape. The corresponding positive relationship was found for 27 of the 104 butterfly species, although most of these species were generalists. These positive relationships disappeared for most of the species when land-cover covariates were taken into account, hinting that land-cover is a primary factor defining the positive effects of the N2000 network. The increase in abundance with N2000 was correlated with the specialization index for bird species, but not for butterfly species. Although the N2000 network supports higher abundance of a large spectrum of species, the low number of specialist butterfly species showing a positive association stresses the need to implement management plan improving the quality of habitats of N2000 areas potentially harboring openland butterfly specialists. For a better understanding of the processes involved, we advocate for a standardized collection of data on N2000 sites. Article impact statement: Across Europe the abundance of a majority of nontarget birds and a quarter of nontarget butterflies increased with Natura 2000 coverage. This article is protected by copyright. All rights reservedpeerReviewe

Efficient occupancy model-fitting for extensive citizen-science data

Appropriate large-scale citizen-science data present important new opportunities for biodiversity modelling, due in part to the wide spatial coverage of information. Recently proposed occupancy modelling approaches naturally incorporate random effects in order to account for annual variation in the composition of sites surveyed. In turn this leads to Bayesian analysis and model fitting, which are typically extremely time consuming. Motivated by presence-only records of occurrence from the UK Butterflies for the New Millennium data base, we present an alternative approach, in which site variation is described in a standard way through logistic regression on relevant environmental covariates. This allows efficient occupancy model-fitting using classical inference, which is easily achieved using standard computers. This is especially important when models need to be fitted each year, typically for many different species, as with British butterflies for example. Using both real and simulated data we demonstrate that the two approaches, with and without random effects, can result in similar conclusions regarding trends. There are many advantages to classical model-fitting, including the ability to compare a range of alternative models, identify appropriate covariates and assess model fit, using standard tools of maximum likelihood. In addition, modelling in terms of covariates provides opportunities for understanding the ecological processes that are in operation. We show that there is even greater potential; the classical approach allows us to construct regional indices simply, which indicate how changes in occupancy typically vary over a species’ range. In addition we are also able to construct dynamic occupancy maps, which provide a novel, modern tool for examining temporal changes in species distribution. These new developments may be applied to a wide range of taxa, and are valuable at a time of climate change. They also have the potential to motivate citizen scientists