Polyethylenimine of various molecular weights as adjuvant for transfection mediated by cationic liposomes

Over the last years significant progress has been made in non-viral gene delivery mediated by cationic liposomes. However, the results obtained are still far from being satisfactory regarding transfection efficiency, particularly when compared to that achieved using viral vectors. We have previously demonstrated that association of transferrin with cationic liposomes significantly improves transfection in a large variety of cells, both in vitro and in vivo. In this work, several strategies have been explored in order to further improve transfection mediated by transferrin-associated lipoplexes. To this regard, the effect on transfection of pre-condensation of DNA with polyethylenimine of low MWs (2.7, 2.0 and 0.8 KDa) at various N/P ratios, lipid composition, cationic lipid/DNA (+/-) charge ratio and the presence of a surfactant in the lipoplexes was investigated. Two different modes for preparing the liposomes were tested and the extent of cell association of their complexes with DNA as well as their capacity to protect the carried DNA were evaluated. Our results show that complexes generated from cationic liposomes prepared by the ethanol injection method in which the carried DNA was pre-condensed with low MW polyethylenimine are highly efficient in mediating transfection. The differential modulating effect observed upon association of transferrin to various liposome formulations on transfection mediated by the polyethylenimine-complexes suggests that these complexes enter into the cells through different pathways (involving clathrin versus caveolin), most likely by taking advantage of their intrinsic biophysical properties to escape from the endosome to the cytosol.     

Dissecting a complex chemical stress: chemogenomic profiling of plant hydrolysates

The efficient production of biofuels from cellulosic feedstocks will require the efficient fermentation of the sugars in hydrolyzed plant material. Unfortunately, plant hydrolysates also contain many compounds that inhibit microbial growth and fermentation. We used DNA‐barcoded mutant libraries to identify genes that are important for hydrolysate tolerance in both Zymomonas mobilis (44 genes) and Saccharomyces cerevisiae (99 genes). Overexpression of a Z. mobilis tolerance gene of unknown function (ZMO1875) improved its specific ethanol productivity 2.4‐fold in the presence of miscanthus hydrolysate. However, a mixture of 37 hydrolysate‐derived inhibitors was not sufficient to explain the fitness profile of plant hydrolysate. To deconstruct the fitness profile of hydrolysate, we profiled the 37 inhibitors against a library of Z. mobilis mutants and we modeled fitness in hydrolysate as a mixture of fitness in its components. By examining outliers in this model, we identified methylglyoxal as a previously unknown component of hydrolysate. Our work provides a general strategy to dissect how microbes respond to a complex chemical stress and should enable further engineering of hydrolysate tolerance.     

Stand-replacing wildfires alter the community structure of wood-inhabiting fungi in southwestern ponderosa pine forests of the USA

Increases in stand-replacing wildfires in the western USA have widespread implications for ecosystem carbon (C) cycling, in part because the decomposition of trees killed by fire can be a long-term source of CO₂ to the atmosphere. Knowledge of the composition and function of decay fungi communities may be important to understanding how wildfire alters C cycles. We assessed the effects of stand-replacing wildfires on the community structure of wood-inhabiting fungi along a 32-yr wildfire chronosequence. Fire was associated with low species richness for up to 4 yr and altered species composition relative to unburned forest for the length of the chronosequence. A laboratory incubation demonstrated that species varied in their capacity to decompose wood; Hypocrea lixii, an indicator of the most recent burn, caused the lowest decomposition rate. Our results show that stand-replacing wildfires have long-term effects on fungal communities, which may have consequences for wood decomposition and C cycling.     

Successful Human Infection with P. falciparum Using Three Aseptic Anopheles stephensi Mosquitoes: A New Model for Controlled Human Malaria Infection

Controlled human malaria infection (CHMI) is a powerful method for assessing the efficacy of anti-malaria vaccines and drugs targeting pre-erythrocytic and erythrocytic stages of the parasite. CHMI has heretofore required the bites of 5 Plasmodium falciparum (Pf) sporozoite (SPZ)-infected mosquitoes to reliably induce Pf malaria. We reported that CHMI using the bites of 3 PfSPZ-infected mosquitoes reared aseptically in compliance with current good manufacturing practices (cGMP) was successful in 6 participants. Here, we report results from a subsequent CHMI study using 3 PfSPZ-infected mosquitoes reared aseptically to validate the initial clinical trial. We also compare results of safety, tolerability, and transmission dynamics in participants undergoing CHMI using 3 PfSPZ-infected mosquitoes reared aseptically to published studies of CHMI using 5 mosquitoes. Nineteen adults aged 18–40 years were bitten by 3 Anopheles stephensi mosquitoes infected with the chloroquine-sensitive NF54 strain of Pf. All 19 participants developed malaria (100%); 12 of 19 (63%) on Day 11. The mean pre-patent period was 258.3 hours (range 210.5–333.8). The geometric mean parasitemia at first diagnosis by microscopy was 9.5 parasites/µL (range 2–44). Quantitative polymerase chain reaction (qPCR) detected parasites an average of 79.8 hours (range 43.8–116.7) before microscopy. The mosquitoes had a geometric mean of 37,894 PfSPZ/mosquito (range 3,500–152,200). Exposure to the bites of 3 aseptically-raised, PfSPZ-infected mosquitoes is a safe, effective procedure for CHMI in malaria-naïve adults. The aseptic model should be considered as a new standard for CHMI trials in non-endemic areas. Microscopy is the gold standard used for the diagnosis of Pf malaria after CHMI, but qPCR identifies parasites earlier. If qPCR continues to be shown to be highly specific, and can be made to be practical, rapid, and standardized, it should be considered as an alternative for diagnosis.

Trial Registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00744133","term_id":"NCT00744133"}}NCT00744133 {"type":"clinical-trial","attrs":{"text":"NCT00744133","term_id":"NCT00744133"}}NCT00744133     

Mitral and Tufted Cells Are Potential Cellular Targets of Nitration in the Olfactory Bulb of Aged Mice

Olfactory sensory function declines with age; though, the underlying molecular changes that occur in the olfactory bulb (OB) are relatively unknown. An important cellular signaling molecule involved in the processing, modulation, and formation of olfactory memories is nitric oxide (NO). However, excess NO can result in the production of peroxynitrite to cause oxidative and nitrosative stress. In this study, we assessed whether changes in the expression of 3-nitrotyrosine (3-NT), a neurochemical marker of peroxynitrite and thus oxidative damage, exists in the OB of young, adult, middle-aged, and aged mice. Our results demonstrate that OB 3-NT levels increase with age in normal C57BL/6 mice. Moreover, in aged mice, 3-NT immunoreactivity was found in some blood vessels and microglia throughout the OB. Notably, large and strongly immunoreactive puncta were found in mitral and tufted cells, and these were identified as lipofuscin granules. Additionally, we found many small-labeled puncta within the glomeruli of the glomerular layer and in the external plexiform layer, and these were localized to mitochondria and discrete segments of mitral and tufted dendritic plasma membranes. These results suggest that mitral and tufted cells are potential cellular targets of nitration, along with microglia and blood vessels, in the OB during aging.     

Using Linkage Analysis to Detect Gene-Gene Interactions. 2. Improved Reliability and Extension to More-Complex Models

Detecting gene-gene interaction in complex diseases has become an important priority for common disease genetics, but most current approaches to detecting interaction start with disease-marker associations. These approaches are based on population allele frequency correlations, not genetic inheritance, and therefore cannot exploit the rich information about inheritance contained within families. They are also hampered by issues of rigorous phenotype definition, multiple test correction, and allelic and locus heterogeneity. We recently developed, tested, and published a powerful gene-gene interaction detection strategy based on conditioning family data on a known disease-causing allele or a disease-associated marker allele⁴. We successfully applied the method to disease data and used computer simulation to exhaustively test the method for some epistatic models. We knew that the statistic we developed to indicate interaction was less reliable when applied to more-complex interaction models. Here, we improve the statistic and expand the testing procedure. We computer-simulated multipoint linkage data for a disease caused by two interacting loci. We examined epistatic as well as additive models and compared them with heterogeneity models. In all our models, the at-risk genotypes are “major” in the sense that among affected individuals, a substantial proportion has a disease-related genotype. One of the loci (A) has a known disease-related allele (as would have been determined from a previous analysis). We removed (pruned) family members who did not carry this allele; the resultant dataset is referred to as “stratified.” This elimination step has the effect of raising the “penetrance” and detectability at the second locus (B). We used the lod scores for the stratified and unstratified data sets to calculate a statistic that either indicated the presence of interaction or indicated that no interaction was detectable. We show that the new method is robust and reliable for a wide range of parameters. Our statistic performs well both with the epistatic models (false negative rates, i.e., failing to detect interaction, ranging from 0 to 2.5%) and with the heterogeneity models (false positive rates, i.e., falsely detecting interaction, ≤1%). It works well with the additive model except when allele frequencies at the two loci differ widely. We explore those features of the additive model that make detecting interaction more difficult. All testing of this method suggests that it provides a reliable approach to detecting gene-gene interaction.     

Detection of silent cells,synchronization and modulatory activity in developing cellular networks

Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell migration, to the refinement of synapses, topographic maps, and the mature composition of ion channels. These emergent activity patterns are not present in all cells simultaneously within the network and more immature “silent” cells, potentially correlated with the presence of silent synapses, are prominent in different networks during early developmental periods. Many current network analyses for detection of synchronous cellular activity utilize activity‐based pixel correlations to identify cellular‐based regions of interest (ROIs) and coincident cell activity. However, using activity‐based correlations, these methods first underestimate or ignore the inactive silent cells within the developing network and second, are difficult to apply within cell‐dense regions commonly found in developing brain networks. In addition, previous methods may ignore ROIs within a network that shows transient activity patterns comprising both inactive and active periods. We developed analysis software to semi‐automatically detect cells within developing neuronal networks that were imaged using calcium‐sensitive reporter dyes. Using an iterative threshold, modulation of activity was tracked within individual cells across the network. The distribution pattern of both inactive and active, including synchronous cells, could be determined based on distance measures to neighboring cells and according to different anatomical layers. © 2015 Wiley Periodicals, Inc. Develop Neurobiol 76: 357–374, 2016