Winter Rye as a Bioenergy Feedstock: Impact of Crop Maturity on Composition, Biological Solubilization and Potential Revenue

Background: Winter annual crops such as winter rye (Secale cereale L) can produce biomass feedstock on seasonally fallow land that continues to provide high-value food and feed from summer annuals such as corn and soybeans. As energy double crops, winter grasses are likely to be harvested while still immature and thus structurally different from the fully senesced plant material typically used for biofuels. This study investigates the dynamic trends in biomass yield, composition, and biological solubilization over the course of a spring harvest season. Results: The water soluble fraction decreased with increasing maturity while total carbohydrate content stayed roughly constant at about 65%. The protein mass fraction decreased with increasing maturity, but was counterbalanced by increasing harvest yield resulting in similar total protein across harvest dates. Winter rye was ground and autoclaved then fermented at 15 g/L total solids by either (1) Clostridium thermocellum or (2) simultaneous saccharification and cofermentation (SSCF) using commercial cellulases (CTec2 and HTec2) and a xylose-fermenting Saccharomyces cerevisiae strain. Solubilization of total carbohydrate dropped significantly as winter rye matured for both C. thermocellum (from approximately 80% to approximately 50%) and SSCF (from approximately 60% to approximately 30%). C. thermocellum achieved total solubilization 33% higher than that of SSCF for the earliest harvest date and 50% higher for the latest harvest date. Potential revenue from protein and bioethanol was stable over a range of different harvest dates, with most of the revenue due to ethanol. In a crop rotation with soybean, recovery of the soluble protein from winter rye could increase per hectare protein production by 20 to 35%. Conclusions: Double-cropping winter rye can produce significant biomass for biofuel production and feed protein as coproduct without competing with the main summer crop. During a 24-day harvest window, the total carbohydrate content remained relatively constant while the early-harvest yielded much higher carbohydrate solubilization for both C. thermocellum fermentation and SSCF. C. thermocellum fermentation achieved higher carbohydrate solubilization than SSCF across all growth stages tested. Although winter rye’s yield, composition, and biological reactivity change rapidly in the spring, it offers a substantial and stable income across the harvest season and thus flexibility for the farmer

Both adhE and a Separate NADPH-Dependent Alcohol Dehydrogenase Gene, adhA, Are Necessary for High Ethanol Production in Thermoanaerobacterium saccharolyticum

Thermoanaerobacterium saccharolyticum has been engineered to produce ethanol at ∼90% theoretical yield and titer of 70 g/L. Its ethanol-producing ability has drawn attention to its metabolic pathways, which could potentially be transferred to other organisms of interest. Here we report that the iron-containing AdhA is important for ethanol production in the high-ethanol strain of T. saccharolyticum (LL1049). A single-gene deletion of adhA in LL1049 reduced ethanol production by ∼50%, whereas multiple gene deletions of all annotated alcohol dehydrogenases except adhA and adhE did not affect ethanol production. Deletion of adhA in wild-type T. saccharolyticum reduced NADPH-linked ADH activity (acetaldehyde-reducing) by 93%

RESEARCH Integrated analysis of hydrothermal flow through pretreatment

Background: The impact of hydrothermal flowthrough (FT) pretreatment severity on pretreatment and solubilization performance metrics was evaluated for three milled feedstocks (corn stover, bagasse, and poplar) and two conversion systems (simultaneous saccharification and fermentation using yeast and fungal cellulase, and fermentation by Clostridium thermocellum). Results: Compared to batch pretreatment, FT pretreatment consistently resulted in higher XMG recovery, higher removal of non-carbohydrate carbon and higher glucan solubilization by simultaneous saccharification and fermentation (SSF). XMG recovery was above 90 % for FT pretreatment below 4.1 severity but decreased at higher severities, particularly for bagasse. Removal of non-carbohydrate carbon during FT pretreatment increased from 65% at low severity to 80 % at high severity for corn stover, and from 40 % to 70 % for bagasse and poplar. Solids obtained by FT pretreatment were amenable to high conversion for all of the feedstocks and conversion systems examined. The optimal time and temperature for FT pretreatment on poplar were found to be 16 min and 210°C. At these conditions, SSF glucan conversion was about 85%, 94 % of the XMG was removed, and 62 % of the non carbohydrate mass was solubilized. Solubilization of FT-pretreated poplar was compared for C. thermocellum fermentation (10 % inoculum), and for yeast-fungal cellulase SSF (5 % inoculum, cellulase loading of 5 and 1

A Markerless Gene Deletion and Integration System for Thermoanaerobacter Ethanolicus

Background: Thermoanaerobacter ethanolicus produces a considerable amount of ethanol from a range of carbohydrates and is an attractive candidate for applications in bioconversion processes. A genetic system with reusable selective markers would be useful for deleting acid production pathways as well as other genetic modifications. Results: The thymidine kinase (tdk) gene was deleted from T. ethanolicus JW200 to allow it to be used as a selectable marker, resulting in strain X20. Deletion of the tdk gene reduced growth rate by 20 %; however, this could be reversed by reintroducing the tdk gene (strain X20C). The tdk and high-temperature kanamycin (htk) markers were tested by using them to delete lactate dehydrogenase (ldh). During positive selection of ldh knockouts in strain X20 on kanamycin agar plates, six out of seven picked colonies were verified transformants. Deletion of ldh reduced lactic acid production by 90 %. The tdk and 5-fluoro-2\u27-deoxyuridine (FUDR) combination worked reliably as demonstrated by successful tdk removal in all 21 colonies tested. Conclusion: A gene deletion and integration system with reusable markers has been developed for Thermoanaerobacter ethanolicus JW200 with positive selection on kanamycin and negative selection on FUDR. Gene deletion was demonstrated by ldh gene deletion and gene integration was demonstrated by re-integration of the tdk gene. Transformation via a natural competence protocol could use DNA PCR products amplified directly from Gibson Assembly mixture for efficient genetic modification

Nitrogen-fluorine-codoped TiO2/Zn based MOF binary composites for efficient removal of bisphenol A under visible light

Bisphenol A (BPA) is an environmental estrogen in daily life, and it often appears in sewage, surface water and even drinking water. It will accumulate in the human body and threaten physical health. We prepared a visible light-driven N-F-TiO2/ZIF-8 photocatalyst through an in situ heterogeneous deposition method. The prepared samples were further analysed by XRD, SEM, TEM, PL spectroscopy and UV-vis DRS. Binary N-F-TiO2/ZIF-8 had a good effect on the degradation of BPA under visible light irradiation. It was determined through experiments that the optimal dosage of N-F-TiO2/ZIF-8 (7:3) was 10 mg with the highest observed photocatalytic activity (86.1%). The high adsorption capacity of ZIF-8 was due to its large specific surface area. The improvement of photocatalytic activity was mainly due to the high separation rate of electron-hole pairs of N-F-TiO2/ZIF-8. N-F-TiO2/ZIF-8 also had good stability after five cycles of photodegradation reaction. In addition, the free radical capture experiment confirmed that (OH)-O-center dot was the main active substance for the photocatalytic degradation of BPA. In addition, the removal ability of bisphenol A by the binary composite in real water was studied using lake water

Degradation of bisphenol A through Ti-BiOI/ZIF-8/peroxymonosulfate (PMS): Catalyst preparation, experimental design and catalytic mechanism

In this work, zeolitic imidazolate framework-8 (ZIF-8) was loaded onto Ti-modified BiOI (Ti-BiOI) by in-situ synthesis to prepare novel binary photocatalytic materials (Ti-BiOI/ZIF-8), its physical parameters, chemical parameters, crystal structure and electrochemical properties were characterized. A novel photocatalytic oxidation system (Ti-BiOI/ZIF-8/PMS/Vis) consisting of Ti-BiOI/ZIF-8 and peroxymonosulfate (PMS) could efficiently remove BPA under visible light. In the first 2 min of the photocatalytic reaction, Ti-BiOI/ZIF-8 and PMS were excited to generate a large number of active groups (center dot O-2(-), center dot OH, center dot SO4- and h(+)), more than 90% of BPA was removed, and the degradation rate of Ti-BiOI/ZIF-8/PMS/Vis was 3.5 times higher that of monomer BiOI, and the removal rate of total-organic-carbon reached about 60%. In addition, the effects of PMS dosage and catalyst dosage on the removal of BPA were also investigated. The stability and reusability of the Ti-BiOI/ZIF-8 were verified through four cycles of degradation of BPA

Deep Learning with Quantitative Features of Magnetic Resonance Images to Predict Biochemical Recurrence of Radical Prostatectomy: A Multi-Center Study

Biochemical recurrence (BCR) occurs in up to 27% of patients after radical prostatectomy (RP) and often compromises oncologic survival. To determine whether imaging signatures on clinical prostate magnetic resonance imaging (MRI) could noninvasively characterize biochemical recurrence and optimize treatment. We retrospectively enrolled 485 patients underwent RP from 2010 to 2017 in three institutions. Quantitative and interpretable features were extracted from T2 delineated tumors. Deep learning-based survival analysis was then applied to develop the deep-radiomic signature (DRS-BCR). The model’s performance was further evaluated, in comparison with conventional clinical models. The model achieved C-index of 0.802 in both primary and validating cohorts, outweighed the CAPRA-S score (0.677), NCCN model (0.586) and Gleason grade group systems (0.583). With application analysis, DRS-BCR model can significantly reduce false-positive predictions, so that nearly one-third of patients could benefit from the model by avoiding overtreatments. The deep learning-based survival analysis assisted quantitative image features from MRI performed well in prediction for BCR and has significant potential in optimizing systemic neoadjuvant or adjuvant therapies for prostate cancer patients