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Remediation of environmental toxic pollutants has attracted extensive attention in recent years. Microbial bioremediation has been an important technology for removing toxic pollutants. However, microbial activity is also susceptible to toxicity stress in the process of intracellular detoxification, which significantly reduces microbial activity. Electroactive microorganisms (EAMs) can detoxify toxic pollutants extracellularly to a certain extent, which is related to their unique extracellular electron transfer (EET) function. In this review, the extracellular and intracellular aspects of the EAMs’ detoxification mechanisms are explored separately. Additionally, various strategies for enhancing the effect of extracellular detoxification are discussed. Finally, future research directions are proposed based on the bottlenecks encountered in the current studies. This review can contribute to the development of toxic pollutants remediation technologies based on EAMs, and provide theoretical and technical support for future practical engineering applications.

The display of recombinant proteins on the surfaces of bacteria is a research topic with many possible biotechnology applications—among which, the choice of host cell and anchoring motif is the key for efficient display. Corynebacterium glutamicum is a promising host for surface display due to its natural advantages, while single screening methods and fewer anchor proteins restrict its application. In this study, the subcellular localization (SCL) predictor LocateP and tied-mixture hidden Markov models were used to analyze all five known endogenous anchor proteins of C. glutamicum and test the accuracy of the predictions. Using these two tools, the SCLs of all proteins encoded by the genome of C. glutamicum 13032 were predicted, and 14 potential anchor proteins were screened. Compared with the positive controls NCgl1221 and NCgl1337, three anchoring proteins—NCgl1307, NCgl2775, and NCgl0717—performed better. This study also discussed the applicability of the anchor protein screening method used in this experiment to other bacteria.

To manipulate nasal microbiota for respiratory health, we need to better understand how this microbial community is assembled and maintained. Previous work has demonstrated that the pH in the nasal passage experiences temporal fluctuations. Yet, the impact of such pH fluctuations on nasal microbiota is not fully understood. Here, we examine how temporal fluctuations in pH might affect the coexistence of nasal bacteria in in silico communities. We take advantage of the cultivability of nasal bacteria to experimentally assess their responses to pH and the presence of other species. Based on experimentally observed responses, we formulate a mathematical model to numerically investigate the impact of temporal pH fluctuations on species coexistence. We assemble in silico nasal communities using up to 20 strains that resemble the isolates that we have experimentally characterized. We then subject these in silico communities to pH fluctuations and assess how the community composition and coexistence is impacted. Using this model, we then simulate pH fluctuations—varying in amplitude or frequency—to identify conditions that best support species coexistence. We find that the composition of nasal communities is generally robust against pH fluctuations within the expected range of amplitudes and frequencies. Our results also show that cooperative communities and communities with lower niche overlap have significantly lower composition deviations when exposed to temporal pH fluctuations. Overall, our data suggest that nasal microbiota could be robust against environmental fluctuations.