Intracellular trafficking of polyamidoamine-poly(ethylene glycol) block copolymers in DNA delivery

The delivery of nucleic acids has the potential to revolutionize medicine by allowing previously untreatable diseases to be clinically addressed. Viral delivery systems have shown immunogenicity and toxicity dangers, but synthetic vectors have lagged in transfection efficiency. Previously, we developed a modular, linear-dendritic block copolymer architecture with high gene transfection efficiency compared to commercial standards. This rationally designed system makes use of a cationic dendritic block to condense the anionic DNA and forms complexes with favorable endosomal escape properties. The linear block provides biocompatibility and protection from serum proteins, and can be functionalized with a targeting ligand. In this work, we quantitate performance of this system with respect to intracellular barriers to gene delivery using both high-throughput and traditional approaches. An image-based, high-throughput assay for endosomal escape is described and applied to the block copolymer system. Nuclear entry is demonstrated to be the most significant barrier to more efficient delivery and will be addressed in future versions of the system.     

The sample processing time interval as an influential factor in flow cytometry analysis of lymphocyte subsets

The objective of this paper is to propose a protocol to analyze blood samples in yellow fever 17DD vaccinated which developed serious adverse events. We investigated whether or not the time between sample collection and sample processing could interfere in lymphocyte subset percentage, for it is often impossible to analyze blood samples immediately after collection due to transport delay from collection places to the flow cytometry facility. CD4+CD38+ T, CD8+CD38+ T, CD3+ T, CD19+ B lymphocyte subsets were analyzed by flow cytometry in nine healthy volunteers immediately after blood collection and after intervals of 24 and 48 h. The whole blood lysis method and gradient sedimentation by Histopaque were applied to isolate peripheral blood mononuclear cells for flow cytometry analyses. With the lysis method, there was no significant change in lymphocyte subset percentage between the two time intervals (24 and 48 h). In contrast, when blood samples were processed by Histopaque gradient sedimentation, time intervals for sample processing influenced the percentage in T lymphocyte subsets but not in B cells. From the results obtained, we could conclude that the whole blood lysis method is more appropriate than gradient sedimentation by Histopaque for immunophenotyping of blood samples collected after serious adverse events, due to less variation in the lymphocyte subset levels with respect to the time factor.     

Distinctive patterns of DNA methylation associated with Parkinson disease

Parkinson disease (PD) is a multifactorial neurodegenerative disorder with high incidence in the elderly, where environmental and genetic factors are involved in etiology. In addition, epigenetic mechanisms, including deregulation of DNA methylation have been recently associated to PD. As accurate diagnosis cannot be achieved pre-mortem, identification of early pathological changes is crucial to enable therapeutic interventions before major neuropathological damage occurs. Here we investigated genome-wide DNA methylation in brain and blood samples from PD patients and observed a distinctive pattern of methylation involving many genes previously associated to PD, therefore supporting the role of epigenetic alterations as a molecular mechanism in neurodegeneration. Importantly, we identified concordant methylation alterations in brain and blood, suggesting that blood might hold promise as a surrogate for brain tissue to detect DNA methylation in PD and as a source for biomarker discovery.     

Early evolution of the megadiverse subtribe Philonthina (Staphylinidae: Staphylininae: Staphylinini) and its Neotropical lineage

Philonthina (2864 species in 74 genera) represents almost one-half of the diversity of Staphylinini and is the largest of its subtribes. Most Philonthina species are found in tropical areas, but the origin of this diversity is still not well understood, mainly because their systematics belongs to a past era of taxonomy. Such is the case of a group of genera, most of them endemic to the Neotropical region (NT), whose monophyly has been repeatedly confirmed and which constitutes the so-called Neotropical lineage (NL). However, basal relationships have not been clarified, neither for Philonthina nor its NL. The NL includes ∼300 species and 26 genera, but two of them (Belonuchus Nordmann and Paederomimus Sharp) account for two-thirds of its species. Here, using the largest molecular-based phylogeny of Philonthina and its NL to date, a time-calibrated phylogeny, and ancestral range reconstructions for the NL, we explore the evolutionary history of Philonthina with a focus on its NL to reveal their early evolution and diversification in the NT. We show that Philonthina originated during the Late Cretaceous ∼ 67.6 Ma and diversified into five main lineages mostly during the Eocene. The NL originated in northwestern South America (SA) and the Andes not earlier than 64.2 Ma from a Laurasian lineage present in SA ∼49.1–69.9 Ma. Shortly afterward, that is, 39.9–56.9 Ma, the NL diversified into the Andean clade and the most species-rich Belonuchus-Paederomimus group. Our analyses recover northwestern SA and the Andes as the primary centers of diversification. Dispersal events to the northern landmasses took place at least three times during the Miocene in the early evolution of the NL.     

A mouse model for Li-Fraumeni-Like Syndrome with cardiac angiosarcomas associated to POT1 mutations

The shelterin protein POT1 has been found mutated in many different familial and sporadic cancers, however, no mouse models to understand the pathobiology of these mutations have been developed so far. To address the molecular mechanisms underlying the tumorigenic effects of POT1 mutant proteins in humans, we have generated a mouse model for the human POT1^R117C mutation found in Li-Fraumeni-Like families with cases of cardiac angiosarcoma by introducing this mutation in the Pot1a endogenous locus, knock-in for Pot1a^R117C. We find here that both mouse embryonic fibroblasts (MEFs) and tissues from Pot1a^+/ki mice show longer telomeres than wild-type controls. Longer telomeres in Pot1a^+/ki MEFs are dependent on telomerase activity as they are not found in double mutant Pot1a^+/ki Tert^-/- telomerase-deficient MEFs. By using complementation assays we further show that POT1a pR117C exerts dominant-negative effects at telomeres. As in human Li-Fraumeni patients, heterozygous Pot1a^+/ki mice spontaneously develop a high incidence of angiosarcomas, including cardiac angiosarcomas, and this is associated to the presence of abnormally long telomeres in endothelial cells as well as in the tumors. The Pot1a^+/R117C mouse model constitutes a useful tool to understand human cancers initiated by POT1 mutations.     

Guidelines for model adaptation: A study of the transferability of a general seagrass ecosystem Dynamic Bayesian Networks model

In general, it is not feasible to collect enough empirical data to capture the entire range of processes that define a complex system, either intrinsically or when viewing the system from a different geographical or temporal perspective. In this context, an alternative approach is to consider model transferability, which is the act of translating a model built for one environment to another less well‐known situation. Model transferability and adaptability may be extremely beneficial—approaches that aid in the reuse and adaption of models, particularly for sites with limited data, would benefit from widespread model uptake. Besides the reduced effort required to develop a model, data collection can be simplified when transferring a model to a different application context. The research presented in this paper focused on a case study to identify and implement guidelines for model adaptation. Our study adapted a general Dynamic Bayesian Networks (DBN) of a seagrass ecosystem to a new location where nodes were similar, but the conditional probability tables varied. We focused on two species of seagrass (Zostera noltei and Zostera marina) located in Arcachon Bay, France. Expert knowledge was used to complement peer‐reviewed literature to identify which components needed adjustment including parameterization and quantification of the model and desired outcomes. We adopted both linguistic labels and scenario‐based elicitation to elicit from experts the conditional probabilities used to quantify the DBN. Following the proposed guidelines, the model structure of the general DBN was retained, but the conditional probability tables were adapted for nodes that characterized the growth dynamics in Zostera spp. population located in Arcachon Bay, as well as the seasonal variation on their reproduction. Particular attention was paid to the light variable as it is a crucial driver of growth and physiology for seagrasses. Our guidelines provide a way to adapt a general DBN to specific ecosystems to maximize model reuse and minimize re‐development effort. Especially important from a transferability perspective are guidelines for ecosystems with limited data, and how simulation and prior predictive approaches can be used in these contexts.     

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