Background: Studies in bioconversions have continuously sought the development of processing strategies to overcome the "close physical association" between plant cell wall polymers thought to significantly contribute to biomass recalcitrance [Adv Space Res 18:251-265, 1996],[ Science 315:804-807, 2007]. To a lesser extent, studies have sought to understand biophysical factors responsible for the resistance of lignocelluloses to enzymatic degradation. Provided here are data supporting our hypothesis that the inhibitory potential of different cell wall polymers towards enzymatic cellulose hydrolysis is related to how much these polymers constrain the water surrounding them. We believe the entropy-reducing constraint imparted to polymer associated water plays a negative role by increasing the probability of detrimental interactions such as junction zone formation and the non-productive binding of enzymes.
Results: Selected commercial lignocellulose-derived polymers, including hemicelluloses, pectins, and lignin, showed varied potential to inhibit 24-h cellulose conversion by a mix of purified cellobiohydrolase I and β-glucosidase. At low dry matter loadings (0.5% w/w), insoluble hemicelluloses were most inhibitory (reducing conversion relative to cellulose-only controls by about 80%) followed by soluble xyloglucan and wheat arabinoxylan (reductions of about 70% and 55%, respectively), while the lignin and pectins tested were the least inhibitory (approximately 20% reduction). Low field nuclear magnetic resonance (LF-NMR) relaxometry used to observe water-related proton relaxation in saturated polymer suspensions (10% dry solids, w/w) showed spin-spin, T2, relaxation time curves generally approached zero faster for the most inhibitory polymer preparations. The manner of this decline varied between polymers, indicating different biophysical aspects may differentially contribute to overall water constraint in each case. To better compare the LF-NMR data to inhibitory potential, T2 values from monocomponent exponential fits of relaxation curves were used as a measure of overall water constraint. These values generally correlated faster relaxation times (greater water constraint) with greater inhibition of the model cellulase system by the polymers.
Conclusions: The presented correlation of cellulase inhibition and proton relaxation data provides support for our water constraint-biomass recalcitrance hypothesis. Deeper investigation into polymer-cellulose-cellulase interactions should help elucidate the types of interactions that may be propagating this correlation. If these observations can be verified to be more than correlative, the hypothesis and data presented suggest that a focus on water-polymer interactions and ways to alter them may help resolve key biological lignocellulose processing bottlenecks.
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http://dx.doi.org/10.1186/s13068-014-0159-x | DOI Listing |
Sci Rep
January 2025
Center for Economic and Social Studies, Documentation and Research (CEDRES), Thomas Sankara University (UTS), 12 BP 417, Ouagadougou 12, Burkina Faso.
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View Article and Find Full Text PDFEnviron Res
January 2025
School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150030, China. Electronic address:
Gross primary production (GPP) plays a crucial role in carbon cycling and ecosystem productivity, yet its variability is significantly influenced by climatic factors. This study investigates the spatiotemporal variability of GPP in China's terrestrial ecosystems, with a focus on water and energy limitations. It aims to clarify the relationship between GPP and climatic variables across different regimes.
View Article and Find Full Text PDFACS Earth Space Chem
January 2025
Department of Earth Sciences, Utrecht University, 3584 CB Utrecht, The Netherlands.
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Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China.
Fatty acid can potentially serve as biomarker for evaluating metabolic disorder and inflammation condition, and quantifying the double bonds is the key for revealing fatty acid information. This study presents an assessment of a deep learning approach utilizing deep image prior (DIP) for the quantification of double bonds and methylene-interrupted double bonds of triglyceride derived from chemical-shift encoded multi-echo gradient echo images, all achieved without the necessity for network training. The methodology implemented a cost function grounded in signal constraints to continually refine the neural network's parameters on a single slice of images through iterative processes.
View Article and Find Full Text PDFJ Fish Biol
January 2025
School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK.
The urgency of rapid species monitoring is at an all-time high due to the increasing threat of climate change to global ecosystems, in particular freshwater habitats. Fish such as Arctic charr, Salvelinus alpinus, are particularly vulnerable to increasing water temperatures and changes in land use due to their dependence on cold waters and confinement to lacustrine environments. Nonetheless, current monitoring practices, relying on physical capture of organisms, are hindered by resource constraints, desire to manage habitats for recreational fishing, and restricted access to sites.
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