Interactions Among Fuel Management,Species Composition,Bark Beetles,and Climate Change and the Potential Effects on Forests of the Lake Tahoe Basin

Climate-driven increases in wildfires, drought conditions, and insect outbreaks are critical threats to forest carbon stores. In particular, bark beetles are important disturbance agents although their long-term interactions with future climate change are poorly understood. Droughts and the associated moisture deficit contribute to the onset of bark beetle outbreaks although outbreak extent and severity is dependent upon the density of host trees, wildfire, and forest management. Our objective was to estimate the effects of climate change and bark beetle outbreaks on ecosystem carbon dynamics over the next century in a western US forest. Specifically, we hypothesized that (a) bark beetle outbreaks under climate change would reduce net ecosystem carbon balance (NECB) and increase uncertainty and (b) these effects could be ameliorated by fuels management. We also examined the specific tree species dynamics—competition and release—that determined NECB response to bark beetle outbreaks. Our study area was the Lake Tahoe Basin (LTB), CA and NV, USA, an area of diverse forest types encompassing steep elevation and climatic gradients and representative of mixed-conifer forests throughout the western United States. We simulated climate change, bark beetles, wildfire, and fuels management using a landscape-scale stochastic model of disturbance and succession. We simulated the period 2010–2100 using downscaled climate projections. Recurring droughts generated conditions conducive to large-scale outbreaks; the resulting large and sustained outbreaks significantly increased the probability of LTB forests becoming C sources over decadal time scales, with slower-than-anticipated landscape-scale recovery. Tree species composition was substantially altered with a reduction in functional redundancy and productivity. Results indicate heightened uncertainty due to the synergistic influences of climate change and interacting disturbances. Our results further indicate that current fuel management practices will not be effective at reducing landscape-scale outbreak mortality. Our results provide critical insights into the interaction of drivers (bark beetles, wildfire, fuel management) that increase the risk of C loss and shifting community composition if bark beetle outbreaks become more frequent.     

A Boolean Model of the Gene Regulatory Network Underlying Mammalian Cortical Area Development

The cerebral cortex is divided into many functionally distinct areas. The emergence of these areas during neural development is dependent on the expression patterns of several genes. Along the anterior-posterior axis, gradients of Fgf8, Emx2, Pax6, Coup-tfi, and Sp8 play a particularly strong role in specifying areal identity. However, our understanding of the regulatory interactions between these genes that lead to their confinement to particular spatial patterns is currently qualitative and incomplete. We therefore used a computational model of the interactions between these five genes to determine which interactions, and combinations of interactions, occur in networks that reproduce the anterior-posterior expression patterns observed experimentally. The model treats expression levels as Boolean, reflecting the qualitative nature of the expression data currently available. We simulated gene expression patterns created by all possible networks containing the five genes of interest. We found that only of these networks were able to reproduce the experimentally observed expression patterns. These networks all lacked certain interactions and combinations of interactions including auto-regulation and inductive loops. Many higher order combinations of interactions also never appeared in networks that satisfied our criteria for good performance. While there was remarkable diversity in the structure of the networks that perform well, an analysis of the probability of each interaction gave an indication of which interactions are most likely to be present in the gene network regulating cortical area development. We found that in general, repressive interactions are much more likely than inductive ones, but that mutually repressive loops are not critical for correct network functioning. Overall, our model illuminates the design principles of the gene network regulating cortical area development, and makes novel predictions that can be tested experimentally.     

Novel α-L-Fucosidases from a Soil Metagenome for Production of Fucosylated Human Milk Oligosaccharides

This paper describes the discovery of novel α-L-fucosidases and evaluation of their potential to catalyse the transglycosylation reaction leading to production of fucosylated human milk oligosaccharides. Seven novel α-L-fucosidase-encoding genes were identified by functional screening of a soil-derived metagenome library and expressed in E. coli as recombinant 6xHis-tagged proteins. All seven fucosidases belong to glycosyl hydrolase family 29 (GH 29). Six of the seven α-L-fucosidases were substrate-inhibited, moderately thermostable and most hydrolytically active in the pH range 6–7, when tested with para-nitrophenyl-α-L-fucopyranoside (pNP-Fuc) as the substrate. In contrast, one fucosidase (Mfuc6) exhibited a high pH optimum and an unusual sigmoidal kinetics towards pNP-Fuc substrate. When tested for trans-fucosylation activity using pNP-Fuc as donor, most of the enzymes were able to transfer fucose to pNP-Fuc (self-condensation) or to lactose. With the α-L-fucosidase from Thermotoga maritima and the metagenome-derived Mfuc5, different fucosyllactose variants including the principal fucosylated HMO 2’-fucosyllactose were synthesised in yields of up to ~6.4%. Mfuc5 was able to release fucose from xyloglucan and could also use it as a fucosyl-donor for synthesis of fucosyllactose. This is the first study describing the use of glycosyl hydrolases for the synthesis of genuine fucosylated human milk oligosaccharides.