MacKinnon, N. | Search bioRxiv

bioRxiv2022

Integration of synthetic microbial consortia based bioprocessing with pyrolysis for efficient conversion of cellulose to valuables

Improved technologies are needed for sustainable conversion of cellulosic waste to valuable products. Here we demonstrate the successful integration of a synthetic microbial consortium (SynCONS) based consolidated bioprocessing with pyrolysis to produce commodity chemicals from cellulose. Promising microbial partners were rationally identified from 7626 organisms via comparative metabolic mapping which led to establishing two promising SynCONS with abilities to convert cellulose to ethanol and lactate in bioreactors. The partners in the two SynCONS were a) the mesophilic fungus Trichoderma reesei grown sequentially with the thermophilic bacterium Parageobacillus thermoglucosidasius NCIMB 11955 (TrPt) and b) a thermophilic bacterium Thermobifida fusca grown together with Parageobacillus thermoglucosidasius NCIMB 11955 (TfPt). TrPt sequential bioprocessing resulted in 39% (g/g) cellulose consumption with product yields up to 9.3% g/g (ethanol + lactate). The TfPt co-cultures demonstrated a cellulose consumption of 30% (g/g) and combined yields of ethanol and lactic acid up to 23.7% g/g of consumed cellulose. The total product yields were further enhanced (51% g/g cellulose) when commercially available cellulases were used in place of T. fusca. Furthermore, when the metabolically engineered ethanol-producing strain of P. thermoglucosidasius TM242 (TfPt242) was substituted in the thermophilic TfPt co-culture consortium, ethanol yields were substantially higher (32.7% g/g of consumed cellulose). Finally, subjecting the residual cellulose and microbial biomass to pyrolysis resulted in carbon material with physicochemical properties similar to commercially available activated carbon as analysed using Scanning Electron Microscopy, X-Ray Diffraction and Raman spectroscopy. Overall, the integration of this synthetic microbial consortia-based bioprocessing strategy with pyrolysis demonstrated a promising strategy for conversion of waste cellulose to chemicals, biofuels, and industrial carbon potentially suitable for several industrial applications.

bioengineering↗

bioRxiv2019

Motion prediction enables simulated MR-imaging of freely moving model organisms

AbstractMagnetic resonance tomography typically applies the Fourier transform to k-space signals repeatedly acquired from a frequency encoded spatial region of interest, therefore requiring a stationary object during scanning. Any movement of the object results in phase errors in the recorded signal, leading to deformed images, phantoms, and artifacts, since the encoded information does not originate from the intended region of the object. However, if the type and magnitude of movement is known instantaneously, the scanner or the reconstruction algorithm could be adjusted to compensate for the movement, directly allowing high quality imaging with non-stationary objects. This would be an enormous boon to studies that tie cell metabolomics to spontaneous organism behaviour, eliminating the stress otherwise necessitated by restraining measures such as anesthesia or clamping.\n\nIn the present theoretical study, we use a phantom of the animal model C. elegans to examine the feasibility to automatically predict its movement and position, and to evaluate the impact of movement prediction, within a sufficiently long time horizon, on image reconstruction. For this purpose, we use automated image processing to annotate body parts in freely moving C. elegans, and predict their path of movement. We further introduce an MRI simulation platform based on brightfield-videos of the moving worm, combined with a stack of high resolution transmission electron microscope (TEM) slice images as virtual high resolution phantoms. A phantom provides an indication of the spatial distribution of signal-generating nuclei on a particular imaging slice. We show that adjustment of the scanning to the predicted movements strongly reduces distortions in the resulting image, opening the door for implementation in a high-resolution NMR scanner.

systems biology↗