Meta-transcriptomic profiling of functional variation of freshwater microbial communities induced by an antidepressant sertraline hydrochloride

Influence of antidepressants on stream microbiota: Consequences for leaf itter breakdown and nutrient cycling

As an emerging pollutant, antidepressants in wastewater have received extensive attention due to their metabolic stability and antimicrobial activity in aquatic systems. However, the scarcity of experimental data limits the validation of their potential impacts on ecosystem functionality. This study examined the effects of fluoxetine and amitriptyline (0-100 ng L-1) on microbial decomposers in stream ecosystems. These two antidepressants exhibited different effects on the process of leaf litter decomposition. Fluoxetine at 1 ng L-1 inhibited the dominance of functional bacteria (Caulobacter and Flavobacterium) and cellobiohydrolase activity, significantly reducing the leaf decomposition rate by 11.5%. Notably, amitriptyline at 10 ng L-1 promoting this ecological process by enhancing fungal biomass and most enzyme activities, and increasing the abundance of functional fungi (Anguillospora and Setophaeosphaeria). Nevertheless, when amitriptyline concentrations exceeded 10 ng L-1, nitrogen-limitation was observed in microbial decomposers. These findings illustrate the complexity of the aquatic microbial community in responding to external factors, underscoring the importance of further research into the effects of antidepressants on the nutrient cycling and organic matter dynamics of ecosystems.

Ecotoxicological effects of ketoprofen and fluoxetine and their mixture in an aquatic microcosm

The effects of fluoxetine (antidepressant) and ketoprofen (analgesic) on aquatic ecosystems are largely unknown, particularly as a mixture. This work aimed at determining the effect of sublethal concentrations of both compounds individually (0.050 mg/L) and their mixture (0.025 mg/L each) on aquatic communities at a microcosm scale for a period of 14 d. Several physicochemical parameters were monitored to estimate functional alterations in the ecosystem, while model organisms (Daphnia magna, Lemna sp., Raphidocelis subcapitata) and the sequencing of 16S/18S rRNA genes permitted to determine effects on specific populations and changes in community composition, respectively. Disturbances were more clearly observed after 14 d, and overall, the microcosms containing fluoxetine (alone or in combination with ketoprofen) produced larger alterations on most physicochemical and biological variables, compared to the microcosm containing only ketoprofen, which suffered less severe changes. Differences in nitrogen species suggest alterations in the N-cycle due to the presence of fluoxetine; similarly, all pharmaceutical-containing systems decreased the brood rate of D. magna, while individual compounds inhibited the growth of Lemna sp. No clear trends were observed regarding R. subcapitata, as indirectly determined by chlorophyll quantification. The structure of micro-eukaryotic communities was altered in the fluoxetine-containing systems, whereas the structure of bacterial communities was affected to a greater extent by the mixture. The disruptions to the equilibrium of the microcosm demonstrate the ecological risk these compounds pose to aquatic ecosystems.

Novel Time-dependent Multi-omics Integration in Sepsis-associated Liver Dysfunction

The recently developed technologies that allow the analysis of each single omics have provided an unbiased insight into ongoing disease processes. However, it remains challenging to specify the study design for the subsequent integration strategies that can associate sepsis pathophysiology and clinical outcomes. Here, we conducted a time-dependent multi-omics integration (TDMI) in a sepsis-associated liver dysfunction (SALD) model. We successfully deduced the relation of the Toll-like receptor 4 (TLR4) pathway with SALD. Although TLR4 is a critical factor in sepsis progression, it is not specified in single-omics analyses but only in the TDMI analysis. This finding indicates that the TDMI-based approach is more advantageous than single-omics analyses in terms of exploring the underlying pathophysiological mechanism of SALD. Furthermore, TDMI-based approach can be an ideal paradigm for insightful biological interpretations of multi-omics datasets that will potentially reveal novel insights into basic biology, health, and diseases, thus allowing the identification of promising candidates for therapeutic strategies.

Impacts of high-quality coal mine drainage recycling for replenishment of aquatic ecosystems in arid regions of China: Bacterial community responses

Coal mine water is usually recycled as supplementary water for aquatic ecosystems in arid and semiarid mining regions of China. To ensure ecosystem health, the coal mine water is rigorously treated using several processes, including reverse osmosis, to meet surface water quality standards. However, the potential environmental impacts of this management pattern on the ecological function of receiving water bodies are unclear. In this study, we built several microcosm water ecosystems to simulate the receiving water bodies. High-quality treated coal mine drainage was mixed into the model water bodies at different concentrations, and the sediment bacterial community response and functional changes were systematically investigated. The results showed that the high-quality coal mine drainage could still shape bacterial taxonomic diversity, community composition and structure, with a concentration threshold of approximately 50%. Moreover, both the Mantel test and the structural equation model indicated that the salinity fluctuation caused by the receiving of coal mine drainage was the primary factor shaping the bacterial communities. 10 core taxa in the molecular ecological network influenced by coal mine drainage were identified, with the most critical taxa being patescibacteria and g_Geothermobacter. Furthermore, the pathway of carbohydrate metabolism as well as signaling molecules and interactions was up-regulated, whereas amino acid metabolism showed the opposite trend. All results suggested that the complex physical-chemical and biochemical processes in water ecosystems may be affected by the coal mine drainage. The bacterial community response and underlying functional changes may accelerate internal nutrient cycling, which may have a potential impact on algal bloom outbreaks.

Xenobiotic pollution affects transcription of antibiotic resistance and virulence factors in aquatic microcosms

Antibiotic resistance genes (ARGs) and virulence factors (VFs) are critical threats to human health. Their abundance in aquatic ecosystems is maintained and enhanced via selection driven by environmental xenobiotics. However, their activity and expression in these environments under xenobiotic stress remains unknown. Here ARG and VF expression profiles were examined in aquatic microcosms under ciprofloxacin, glyphosate and sertraline hydrochloride treatment. Ciprofloxacin increased total expression of ARGs, particularly multidrug resistance genes. Total expression of ARGs and VFs decreased significantly under glyphosate and sertraline treatments. However, in opportunistic human pathogens, these agents increased expression of both ARGs and VFs. Xenobiotic pollutants, such as the compounds we tested here, have the potential to disrupt microbial ecology, promote resistance, and increase risk to human health. This study systematically evaluated the effects of environmental xenobiotics on transcription of ARGs and VFs, both of which have direct relevance to human health. Transcription of such genes has been overlooked in previous studies.