An efficient cellulose degrading bacteria exists in the thermophilic wheat straw-degrading community, WDC2. However, this strain cannot be isolated and cultured using conventional separation techniques under strict anaerobic conditions. We successfully isolated a strain of effective cellulose degrading bacteria CTL-6 using a wash, heat shock, and solid-liquid alternating process. Analysis of its properties revealed that, although the community containing the strain CTL-6 grew under aerobic conditions, the purified strain CTL-6 only grew under anaerobic culture conditions. The strain CTL-6 had a striking capability of degrading cellulose (80.9% weight loss after 9 days of culture). The highest efficiency value of the endocellulase (CMCase activity) was 0.404 μtmol/(min-mL), cellulose degradation efficiency by CTL-6 was remarkably high at 50-65°C with the highest degradation efficiency observed at 60°C. The 16S rRNA gene sequence analysis indicated that the closest relative to strain CTL-6 belonged to the genus Clostridium thermocellum. Strain CTL-6 was capable of utilizing cellulose, celiobiose, and glucose. Strain CTL-6 also grew with Sorbitol as the sole carbon source, whereas C.therrnocellum is unable to do so. 相似文献
In this paper, we present a three-step methodological framework, including location identification, bias modification, and out-of-sample validation, so as to promote human mobility analysis with social media data. More specifically, we propose ways of identifying personal activity-specific places and commuting patterns in Beijing, China, based on Weibo (China’s Twitter) check-in records, as well as modifying sample bias of check-in data with population synthesis technique. An independent citywide travel logistic survey is used as the benchmark for validating the results. Obvious differences are discerned from Weibo users’ and survey respondents’ activity-mobility patterns, while there is a large variation of population representativeness between data from the two sources. After bias modification, the similarity coefficient between commuting distance distributions of Weibo data and survey observations increases substantially from 23% to 63%. Synthetic data proves to be a satisfactory cost-effective alternative source of mobility information. The proposed framework can inform many applications related to human mobility, ranging from transportation, through urban planning to transport emission modeling.
