Salt-stress induced changes in the leaf proteome of diploid and tetraploid mandarins with contrasting Na and Cl accumulation behaviour

To understand the genotypic variation of citrus to mild salt stress, a proteomic approach has been carried out in parallel on two citrus genotypes (‘Cleopatra’ and ‘Willow leaf’ mandarins), which differ for Na⁺ and Cl⁻ accumulation, and their cognate autotetraploids (4×). Using two-dimensional electrophoresis approximately 910 protein spots were reproducibly detected in control and salt-stressed leaves of all genotypes. Among them, 44 protein spots showing significant variations at least in one genotype were subjected to mass spectrometry analysis for identification. Salt-responsive proteins were involved in several functions, including photosynthetic processes, ROS scavenging, stress defence, and signalling. Genotype factors affect the salt-responsive pattern, especially that of carbon metabolism. The no ion accumulator ‘Cleopatra’ mandarin genotype showed the highest number of salt-responsive proteins, and up-regulation of Calvin cycle-related proteins. Conversely the ion accumulator ‘Willow leaf’ mandarin showed high levels of several photorespiration-related enzymes. A common set of proteins (twelve spots) displayed higher levels in salt-stressed leaves of 2× and 4× ‘Cleopatra’ and 4× ‘Willow leaf’ mandarin. Interestingly, antioxidant enzymes and heat shock proteins showed higher constitutive levels in 4× ‘Cleopatra’ mandarin and 4× ‘Willow leaf’ mandarin compared with the cognate 2× genotype. This work provides for the first time information on the effect of 8 weeks of salt stress on citrus genotypes contrasting for ion accumulation and their cognate autotetraploids. Results underline that genetic factors have a predominant effect on the salt response, although a common stress response independent from genotype was also found.     

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.     

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     

Long-term,large scale cryopreservation of insect cells at −80 °C

Standard tissue culture methods advise freezing cells in small aliquots (≤1 × 10⁷ cells in 1 mL), and storing in liquid nitrogen. This is inconvenient for laboratories culturing large quantities of insect cells for recombinant baculovirus expression, owing to the length of time taken to produce large scale cultures from small aliquots of cells. Liquid nitrogen storage requires use of specialized cryovials, personal protective equipment and oxygen monitoring systems. This paper describes the long-term, large scale cryopreservation of 8 × 10⁸ insect cells at −80 °C, using standard 50 mL conical tubes to contain a 40 mL cell suspension. Sf9, Sf21 and High 5 cells were recovered with a viability > 90 % after storage for one year under these conditions, which compared favorably with the viability of cells stored in liquid nitrogen for the same length of time. Addition of green fluorescent protein encoding baculovirus demonstrated that cells were “expression ready” immediately post thaw. Our method enables large scale cultures to be recovered rapidly from stocks cryopreserved at −80 °C, thus avoiding the inconvenience, hazards and expense associated with liquid nitrogen.

Electronic supplementary material

The online version of this article (doi:10.1007/s10616-014-9781-5) contains supplementary material, which is available to authorized users.     

Ectomycorrhizal fungal exoenzyme activity differs on spruce seedlings planted in forests versus clearcuts

Key message

Ectomycorrhizal (ECM) fungal community structure and potential exoenzymatic activity change after clearcut harvesting, but functional complementarity and redundancy among those ECM fungal species remaining support growth of regenerating seedlings.

Abstract

Ectomycorrhizal (ECM) fungal community composition is altered by forest harvesting, but it is not clear if this shift in structure influences ECM fungal physiological function at the community level. In this study, we characterized activities of extracellular enzymes in the ectomycorrhizospheres of Picea engelmannii seedlings grown in forest and clearcut plots. These exoenzymes are critical for the breakdown of large organic molecules, from which nutrients are subsequently absorbed and translocated by ECM fungi to host plants. We found that ectomycorrhizae on seedlings planted in forests had different exoenzyme activity profiles than those on seedlings planted in clearcuts. Specifically, the activities of glucuronidase, laccase, and acid phosphatase were higher on forest seedlings (P ≤ 0.006). These differences may have been partly driven by soil properties. Total carbon, total nitrogen (N), extractable phosphorus, extractable ammonium-N, and mineralizable N were higher, while pH was lower in forest plots (P ≤ 0.01). However, we also found that enzyme activity only shifted where community composition also changed. Functional complementarity can be inferred within ECM fungal communities in both forests and clearcuts because ectomycorrhizae formed by different species in the same environment had distinct enzyme profiles (P < 0.0001). However, ectomycorrhizae of Thelephora terrestris exhibited high levels of N- and P-mobilizing exoenzyme activities. Seedling biomass did not differ between forest and clearcut environments, so the high abundance of T. terrestris ectomycorrhizae in the clearcuts may have sustained nutrient acquisition by clearcut seedlings even in soils with lower N and P and with reduced ECM fungal species richness.