Seven N-terminal Residues of a Thermophilic Xylanase Are Sufficient to Confer Hyperthermostability on Its Mesophilic Counterpart

<div><p>Xylanases, and especially thermostable xylanases, are increasingly of interest for the deconstruction of lignocellulosic biomass. In this paper, the termini of a pair of xylanases, mesophilic SoxB and thermophilic TfxA, were studied. Two regions in the N-terminus of TfxA were discovered to be potentially important for the thermostability. By focusing on Region 4, it was demonstrated that only two mutations, N32G and S33P cooperated to improve the thermostability of mesophilic SoxB. By introducing two potential regions into SoxB in combination, the most thermostable mutant, M2-N32G-S33P, was obtained. The M2-N32G-S33P had a melting temperature (Tm) that was 25.6°C higher than the Tm of SoxB. Moreover, M2-N32G-S33P was even three-fold more stable than TfxA and had a Tm value that was 9°C higher than the Tm of TfxA. Thus, for the first time, the mesophilic SoxB “pupil” outperformed its thermophilic TfxA “master” and acquired hyperthermostability simply by introducing seven thermostabilizing residues from the extreme N-terminus of TfxA. This work suggested that mutations in the extreme N-terminus were sufficient for the mesophilic xylanase SoxB to acquire hyperthermostability.</p></div

Correlations of monthly temperatures (left) and precipitation (right) with vegetation activity during grassland senescence (as measured by the NDVI) on the Tibetan Plateau, according to Partial Least Squares (PLS) regression.

<p>For each variable, pixels for which the variable-importance-in-the-projection score was<0.8 are shown in gray. Pixels with insufficient data for PLS analysis are shown in white.</p

Comparsion of the thermostabilities of double region mutants with wildtype parents, SoxB and TfxA.

a<p>The xylanase lost all of its enzyme activity within only 1 min so that the t_1/2 could not be determined.</p

Analysis of the effect of mutations in R4 on thermostability.

<p>(A) DSC profiles. (B) The thermal inactivation profiles at 70°C for the mutants.</p

Mean phenological dates and vegetation activity during different growth stages on the Tibetan Plateau, based on NDVI data between 1982 and 2006.

<p>Mean phenological dates and vegetation activity during different growth stages on the Tibetan Plateau, based on NDVI data between 1982 and 2006.</p

Correlations of monthly temperatures (left) and precipitation (right) with the timing of grassland senescence on the Tibetan Plateau, according to Partial Least Squares (PLS) regression.

<p>For each variable, pixels for which the variable-importance-in-the-projection score was<0.8 are shown in gray. Pixels with insufficient data for PLS analysis are shown in white.</p

Seasonal Response of Grasslands to Climate Change on the Tibetan Plateau

<div><h3>Background</h3><p>Monitoring vegetation dynamics and their responses to climate change has been the subject of considerable research. This paper aims to detect change trends in grassland activity on the Tibetan Plateau between 1982 and 2006 and relate these to changes in climate.</p> <h3>Methodology/Principal Findings</h3><p>Grassland activity was analyzed by evaluating remotely sensed Normalized Difference Vegetation Index (NDVI) data collected at 15-day intervals between 1982 and 2006. The timings of vegetation stages (start of green-up, beginning of the growing season, plant maturity, start of senescence and end of the growing season) were assessed using the NDVI ratio method. Mean NDVI values were determined for major vegetation stages (green-up, fast growth, maturity and senescence). All vegetation variables were linked with datasets of monthly temperature and precipitation, and correlations between variables were established using Partial Least Squares regression. Most parts of the Tibetan Plateau showed significantly increasing temperatures, as well as clear advances in late season phenological stages by several weeks. Rainfall trends and significant long-term changes in early season phenology occurred on small parts of the plateau. Vegetation activity increased significantly for all vegetation stages. Most of these changes were related to increasing temperatures during the growing season and in some cases during the previous winter. Precipitation effects appeared less pronounced. Warming thus appears to have shortened the growing season, while increasing vegetation activity.</p> <h3>Conclusions/Significance</h3><p>Shortening of the growing season despite a longer thermally favorable period implies that vegetation on the Tibetan Plateau is unable to exploit additional thermal resources availed by climate change. Ecosystem composition may no longer be well attuned to the local temperature regime, which has changed rapidly over the past three decades. This apparent lag of the vegetation assemblage behind changes in climate should be taken into account when projecting the impacts of climate change on ecosystem processes.</p> </div

Illustration of the NDVI ratio method for determining the timing of vegetation stages.

<p>All NDVI values are expressed relative to the range between minimum (substituted here by the mean of all positive NDVI values during February and March) and maximum NDVI of the season. Rules for determining the timing and beginning of the Start of Green-up (SOG), the Beginning of the Growing Season (BGS), Maturity, Start of Senescence (SOS) and the End of the Growing Season (EGS) are given in the text.</p

Schematic representation of widetype xylanases and mutants.

<p>(A) Region mutants were produced according to the divergent regions between the N-termini of SoxB and TfxA. (B) Focusing on R4, three mutants (T30E, N32G and S33P), each containing a single mutation and three double mutants (T30E-N32G, T30E-S33P and N32G-S33P) were created. (C) Two double region mutants were produced by introducing two potential regions into SoxB.</p

Trends in monthly mean temperature (left) and precipitation (right) on the Tibetan Plateau between 1982 and 2006.

<p>Gray areas indicate regions, for which no significant trends were detected by the Mann-Kendall test at p<0.1.</p