Impact of anti-acidification microbial consortium on carbohydrate metabolism of key microbes during food waste composting

2018 ◽  
Vol 259 ◽  
pp. 1-9 ◽  
Author(s):  
Caihong Song ◽  
Mingxiao Li ◽  
Hui Qi ◽  
Yali Zhang ◽  
Dongming Liu ◽  
...  
2018 ◽  
Vol 11 (6) ◽  
pp. 1124-1136 ◽  
Author(s):  
Caihong Song ◽  
Yali Zhang ◽  
Xunfeng Xia ◽  
Hui Qi ◽  
Mingxiao Li ◽  
...  

Fermentation ◽  
2019 ◽  
Vol 5 (4) ◽  
pp. 98 ◽  
Author(s):  
Nathan D. Schwalm ◽  
Wais Mojadedi ◽  
Elliot S. Gerlach ◽  
Marcus Benyamin ◽  
Matthew A. Perisin ◽  
...  

Food waste disposal and transportation of commodity chemicals to the point-of-need are substantial challenges in military environments. Here, we propose addressing these challenges via the design of a microbial consortium for the fermentation of food waste to hydrogen. First, we simulated the exchange metabolic fluxes of monocultures and pairwise co-cultures using genome-scale metabolic models on a food waste proxy. We identified that one of the top hydrogen producing co-cultures comprised Clostridium beijerinckii NCIMB 8052 and Yokenella regensburgei ATCC 43003. A consortium of these two strains produced a similar amount of hydrogen gas and increased butyrate compared to the C. beijerinckii monoculture, when grown on an artificial garbage slurry. Increased butyrate production in the consortium can be attributed to cross-feeding of lactate produced by Y. regensburgei. Moreover, exogenous lactate promotes the growth of C. beijerinckii with or without a limited amount of glucose. Increasing the scale of the consortium fermentation proved challenging, as two distinct attempts to scale-up the enhanced butyrate production resulted in different metabolic profiles than observed in smaller scale fermentations. Though the genome-scale metabolic model simulations provided a useful starting point for the design of microbial consortia to generate value-added products from waste materials, further model refinements based on experimental results are required for more robust predictions.


2021 ◽  
Vol 787 (1) ◽  
pp. 012026
Author(s):  
Qingbo Meng ◽  
Yude Gao ◽  
Shuangke Li ◽  
Bini Jiang ◽  
Mingfei He ◽  
...  

Author(s):  
Mohit Mishra ◽  
Sushma Chauhan ◽  
Balasubramanian Velramar ◽  
Rakesh Kumar Soni ◽  
Sudheer Deva Venkata Narayana Pamidimarri

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