The rhizosphere microbiome underpins plant nutrition, health, and stress resilience, making it central to sustainable agriculture. Although soil physicochemical properties and environmental variability shape microbial communities, converging evidence shows that specific microbial taxa repeatedly associate with particular plant genotypes. This host-dependent stability implies that plant genomes impose selective filters on microbial assembly through root exudation, immunity, and developmental traits. This review outlines a mechanistic framework that partitions rhizosphere microbiome assembly into two components: (i) an environment-driven microbiome shaped predominantly by edaphic conditions, climate, and management practices, and (ii) a host genetics-driven microbiome structured by plant molecular and physiological determinants. We aim to disentangle the assembly rules governing each component and assess their potential for targeted manipulation in crop improvement. The environment-driven component arises from microbial responses to nutrient availability, pH, moisture (including drought and salinity-driven osmotic/ionic stress), and agronomic inputs, and is dominated by ecological filtering and resource competition. The host-genetics-driven component arises from genotype-specific traits, including root architecture, exudate chemistry, and immune signaling pathways, that modulate colonization and persistence. This distinction highlights complementary leverage points: agronomic strategies to steer environment-driven processes and genetic dissection of loci controlling microbial recruitment. Major challenges include strong context dependency across soil–genotype combinations, limited power to link plant alleles to microbiome functions, and the lack of predictive models integrating host genetics, environment, and microbial dynamics. A dual-strategy environmental optimization, combined with breeding to enhance the recruitment of beneficial microbes, offers a tractable route to microbiome-informed crop improvement and more resilient production systems.
Retrieving decision-support data from complex large-scale databases is a common requirement in business consulting to answer diverse customer questions. However, most existing methods focus on generating SQL queries from straightforward questions using simple schemas, which does not reflect real business-analysis tasks. In this work, we propose a priority-aware chain-of-multiple-thought (PCoMT) framework for text-to-SQL generation, which uses LLMs to reason about the construction of multiple complex SQL queries. PCoMT encodes complex customer requirements and filters relevant table schemas by fine-grained contrastive table representation. Reference cases are selected to supplement SQL query preparation. An end-to-end chain-of-thought prompting workflow designs diverse reasoning paths for SQL query construction based on pre-defined principles. These reasoning paths correspond to different SQL sub-queries, which are aggregated to construct final SQL queries based on maintenance priorities. We construct a challenging financial dataset with large schemas and colloquial queries. Experiments show that PCoMT achieves competitive execution accuracy with significant column-selection improvements, further corroborated by domain-expert usability ratings and a pilot evaluation on anonymized real-world cases.
The environmental challenges presented by plastic waste, particularly poly(ethylene terephthalate) (PET), necessitate innovative biodegradation strategies. The cutinase from Thermobifida cellulosilytica, Thc_Cut1 (Cut), was site-specifically conjugated with alkyl tethers of varying lengths (C3, C6, C9) through 1H-1,2,3-triazole-4-carbaldehyde (TA4C) derivatives. These conjugations were designed to enhance affinity for PET by adjusting the enzyme's hydrophobicity. The enzyme kinetic parameters of both conjugated and unconjugated cutinases revealed that the modifications have a minimal impact on catalytic activity. However, a significant improvement in the PET hydrolysis efficiency was observed. Specifically, hexyl and nonyl TA4C-containing cutinase displayed notable increases in terephthalic acid (TPA) release, exceeding the performance of unconjugated cutinase by 65% and 69%, respectively. Scanning electron microscopy and water contact angle measurements confirmed the enhanced erosion and hydrophilicity of the PET surface following the enzyme treatment. Increased enzyme adsorption on the PET surface for C6-Cut and C9-Cut was validated by X-ray photoelectron spectroscopy. Moreover, high-speed atomic force microscopy demonstrated faster and more stable adsorption of C6-Cut and C9-Cut on PET surfaces compared with the slower adsorption of unconjugated cutinase. Additionally, molecular dynamics simulations indicate a higher affinity of conjugated cutinase for PET film. These results suggest that conjugating an alkyl tether to the N-terminus strengthens the interaction between cutinase and PET, improving hydrolysis.
The formation and distribution of microplastics are alarming and could have adverse effects on the food sources for insects, fish, animals and human beings. The bio-recycling processes, such as the black soldier fly (BSF) technology, are evolving with great prospects. The BSFL technology is a potential biological resource recovery method that is known to valorize organic substrates, but the larvae’s growth and development on substrates with microplastic inclusions is not well known. Therefore, this study investigates the valorization of wheat-bran substrate with microplastic inclusions using the BSFL technology and assessed the effect on frass and larval development. Substrates were prepared from milled wheat-bran mixed with microplastics of 1 mm particle-sized sourced from waste sachet water plastic films. Substrate treatments were prepared and labelled P1, P2 and P3 according to the inclusion level of the microplastic. Thus, P1 had 0.2 g/kg of microplastic, while P2 and P3 had 0.4 and 0.8 g/kg respectively. The control P4 had no microplastic in the substrate. Samples of BSFL and frass were collected and analyzed at the end of the study for proximate composition. The control (P4) recorded the highest larval weight gain curve while P3 had the lowest curve. This demonstrated that the wheat-plastic inclusion substrate did not cause any larval mortality but had a retardation on the larvae development. Results also showed that the highest percentage crude protein in BSFL from the wheat-plastic inclusion substrate occurred at P1 (26.77 ± 8.71
