A well-characterized polycistronic-like gene expression system in yeast

Efficient expression of multiple genes is critical to yeast metabolic engineering for the bioproduction of bulk and fine chemicals. A yeast polycistronic expression system is of particular interest because one promoter can drive the expression of multiple genes. 2A viral peptides enable the cotranslation of multiple proteins from a single mRNA by ribosomal skipping. However, the wide adaptation of 2A viral peptides for polycistronic-like gene expression in yeast awaits in-depth characterizations. Additionally, a one-step assembly of such a polycistronic-like system is highly desirable. To this end, we have developed a modular cloning (MoClo) compatible 2A peptide-based polycistronic-like system capable of expressing multiple genes from a single promoter in yeast. Characterizing the bi-, tri-, and quad-cistronic expression of fluorescent proteins showed high cleavage efficiencies of three 2A peptides: E2A from equine rhinitis B virus, P2A from porcine teschovirus-1, and O2A from Operophtera brumata cypovirus-18. Applying the polycistronic-like system to produce geraniol, a valuable industrial compound, resulted in comparable or higher titers than using conventional monocistronic constructs. In summary, this highly-characterized polycistronic-like gene expression system is another tool to facilitate multigene expression for metabolic engineering in yeast.     

Marginal proportional hazards models for clustered interval-censored data with time-dependent covariates

The Botswana Combination Prevention Project was a cluster-randomized HIV prevention trial whose follow-up period coincided with Botswana's national adoption of a universal test and treat strategy for HIV management. Of interest is whether, and to what extent, this change in policy modified the preventative effects of the study intervention. To address such questions, we adopt a stratified proportional hazards model for clustered interval-censored data with time-dependent covariates and develop a composite expectation maximization algorithm that facilitates estimation of model parameters without placing parametric assumptions on either the baseline hazard functions or the within-cluster dependence structure. We show that the resulting estimators for the regression parameters are consistent and asymptotically normal. We also propose and provide theoretical justification for the use of the profile composite likelihood function to construct a robust sandwich estimator for the variance. We characterize the finite-sample performance and robustness of these estimators through extensive simulation studies. Finally, we conclude by applying this stratified proportional hazards model to a re-analysis of the Botswana Combination Prevention Project, with the national adoption of a universal test and treat strategy now modeled as a time-dependent covariate.     

Coherent modeling of longitudinal causal effects on binary outcomes

Analyses of biomedical studies often necessitate modeling longitudinal causal effects. The current focus on personalized medicine and effect heterogeneity makes this task even more challenging. Toward this end, structural nested mean models (SNMMs) are fundamental tools for studying heterogeneous treatment effects in longitudinal studies. However, when outcomes are binary, current methods for estimating multiplicative and additive SNMM parameters suffer from variation dependence between the causal parameters and the noncausal nuisance parameters. This leads to a series of difficulties in interpretation, estimation, and computation. These difficulties have hindered the uptake of SNMMs in biomedical practice, where binary outcomes are very common. We solve the variation dependence problem for the binary multiplicative SNMM via a reparameterization of the noncausal nuisance parameters. Our novel nuisance parameters are variation independent of the causal parameters, and hence allow for coherent modeling of heterogeneous effects from longitudinal studies with binary outcomes. Our parameterization also provides a key building block for flexible doubly robust estimation of the causal parameters. Along the way, we prove that an additive SNMM with binary outcomes does not admit a variation independent parameterization, thereby justifying the restriction to multiplicative SNMMs.     

A meta-analysis on morphological,physiological and biochemical responses of plants with PGPR inoculation under drought stress

Plant growth-promoting rhizobacteria (PGPR) can help plants to resist drought stress. However, the mechanisms of how PGPR inoculation affect plant status under drought remain incompletely understood. We performed a meta-analysis of plant response to PGPR inoculation by compiling data from 57 PGPR-inoculation studies, including 2, 387 paired observations on morphological, physiological and biochemical parameters under drought and well-watered conditions. We compare the PGPR effect on plants performances among different groups of controls and treatments. Our results reveal that PGPR enables plants to restore themselves from drought-stressed to near a well-watered state, and that C4 plants recover better from drought stress than C3 plants. Furthermore, PGPR is more effective underdrought than well-watered conditions in increasing plant biomass, enhancing photosynthesis and inhibiting oxidant damage, and the responses of C4 plants to the PGPR effect was stronger than that of C3 plants under drought conditions. Additionally, PGPR belonging to different taxa and PGPR with different functional traits have varying degrees of drought-resistance effects on plants. These results are important to improve our understanding of the PGPR beneficial effects on enhanced drought-resistance of plants.     

Rhizosphere effect of nanoscale zero-valent iron on mycorrhiza-dependent maize assimilation

Rhizosphere effect of nanoscale zero-valent iron (nZVI) is crucial but little reported. Maize seeds were dressed with four nZVI concentrations (0, 1.0, 1.5, 2 g kg⁻¹) and inoculated with arbuscular mycorrhizal fungus (AMF) (Funneliformis mosseae). The SEM images illuminated that excessive nZVI particles (2 g kg⁻¹) were agglomerated on the surface of hyphae and spore, causing severe deformation and inactivation of AMF symbionts and thereafter inhibiting water uptake in maize seedlings. This restrained the scavenging effects of enzymatic (superoxide dismutase, peroxidase) and non-enzymatic compounds (proline & malondialdehyde) on ROS, and leaf photoreduction activity and gas exchange ability (p < 0.05). Interestingly, the inoculation with AMF effectively alleviated above negative effects. In contrast, appropriate dose of nZVI, that is, ≤1.5 g kg⁻¹, can be evenly distributed on the hyphae surface and form the ordered symbionts with AMF. This help massively to enhance hyphae growth and water and nutrient uptake. The enhanced mycorrhizal infection turned to promote rhizosphere symbiont activity and leaf Rubisco and Rubisco activase activity. Light compensation point was massively lowered, which increased photosynthetic carbon supply for AMF symbionts. Particularly, such priming effects were evidently enhanced by drought stress. Our findings provided a novel insight into functional role of nZVI in agriculture and AMF-led green production.     

Comment on “Is Yuan in China’s Three Gorges a Gibbon or a Langur?”

International Journal of Primatology -     

Responses of the desert green algae,Chlorella sp. to drought stress

Desert algae are important components of the desert soil crust and play an essential role in desert soil ecosystem development. Owing to their special habitat, desert algae are often exposed to harsh environments, among which drought represents the most common stress. Green algae are considered to have drought tolerance potential; however, only a few studies have investigated this. In this study, we selected the green alga Chlorella sp., which was isolated from desert soil, and studied its physiological response to polyethylene glycol (PEG) 6000-induced drought stress. The results showed that drought stress can affect the photosynthetic efficiency of Chlorella sp., reduce its water retention ability, and destroy its ultrastructure. However, Chlorella sp. can cope with drought stress through a series of physiological regulatory strategies. Protective strategies include quick recovery of photosynthetic efficiency and increased chlorophyll content. In addition, induced synthesis of soluble proteins, lipids, and extracellular polysaccharide (EPS), and accumulation of osmotic regulatory substances, such as sucrose and trehalose, also contribute to improving drought tolerance in Chlorella sp. This study provides insights into the physiological responses of Chlorella sp. to drought stress, which may be valuable for understanding the underlying drought adaptation mechanisms of desert green algae.