Consolidated bioprocessing (CBP) by using microbial consortium was considered as a promising approach to achieve direct biofuel production from lignocellulose. In this study, the interaction mechanism of microbial consortium consisting of Thermoanaerobacterium thermosaccharolyticum M5 and Clostridium acetobutylicum NJ4 was analyzed, which could achieve efficient butanol production from xylan through CBP. Strain M5 possesses efficient xylan degradation capability, as 19.73 g/L of xylose was accumulated within 50 hr. The efficient xylose utilization capability of partner strain NJ4 could relieve the substrate inhibition to hydrolytic enzymes of xylanase and xylosidase secreted by strain M5. In addition, the earlier solventogenesis of strain NJ4 was observed due to the existence of butyrate generated by strain M5. The mutual interaction of these two strains finally gave 13.28 g/L of butanol from 70 g/L of xylan after process optimization, representing a relatively high butanol production from hemicellulose. Moreover, 7.61 g/L of butanol was generated from untreated corncob via CBP. This successfully constructed microbial consortium exhibits efficient cooperation performance on butanol production from lignocellulose, which could provide a platform for the emerging butanol production from lignocellulose.

Microbial communities are ubiquitous in nature and exhibit several attractive features, such as sophisticated metabolic capabilities and strong environment robustness. Inspired by the advantages of natural microbial consortia, diverse artificial co-cultivation systems have been metabolically constructed for biofuels, chemicals and natural products production. In these co-cultivation systems, especially genetic engineering ones can reduce the metabolic burden caused by the complex of metabolic pathway through labor division, and improve the target product production significantly. This review summarized the most up-to-dated co-cultivation systems used for biofuels, chemicals and nature products production. In addition, major challenges associated with co-cultivation systems are also presented and discussed for meeting further industrial demands.

Subgroup detection has received increasing attention recently in different fields such as clinical trials, public management and market segmentation analysis. In these fields, people often face time‐to‐event data, which are commonly subject to right censoring. This paper proposes a semiparametric Logistic‐Cox mixture model for subgroup analysis when the interested outcome is event time with right censoring. The proposed method mainly consists of a likelihood ratio‐based testing procedure for testing the existence of subgroups. The expectation–maximization iteration is applied to improve the testing power, and a model‐based bootstrap approach is developed to implement the testing procedure. When there exist subgroups, one can also use the proposed model to estimate the subgroup effect and construct predictive scores for the subgroup membership. The large sample properties of the proposed method are studied. The finite sample performance of the proposed method is assessed by simulation studies. A real data example is also provided for illustration.

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