Chemical mixtures and fluorescence in situ hybridization analysis of natural microbial community in the Tiber river

Higher-order interactions and emergent properties of microbial communities: The power of synthetic ecology

Humans have long relied on microbial communities to create products, produce energy, and treat waste. The microbiota residing within our bodies directly impacts our health, while the soil and rhizosphere microbiomes influence the productivity of our crops. However, the complexity and diversity of microbial communities make them challenging to study and difficult to develop into applications, as they often exhibit the emergence of unpredictable higher-order phenomena. Synthetic ecology aims at simplifying complexity by constituting synthetic or semi-natural microbial communities with reduced diversity that become easier to study and analyze. This strategy combines methodologies that simplify existing complex systems (top-down approach) or build the system from its constituent components (bottom-up approach). Simplified communities are studied to understand how interactions among populations shape the behavior of the community and to model and predict their response to external stimuli. By harnessing the potential of synthetic microbial communities through a multidisciplinary approach, we can advance knowledge of ecological concepts and address critical public health, agricultural, and environmental issues more effectively.

Habitat changes due to glacial freezing and melting reshape microbial networks

The phenomenon of glacial freezing and thawing involves microbial sequestration, release, and colonization, which has the potential to impact ecosystem functioning through changes in microbial diversity and interactions. In this study, we examined the structural features of microbial communities of the Dongkemadi glacier, including bacteria, fungi, and archaea, in four distinct glacial environments (snow, ice, meltwater, and frontier soil). The sequestration, release, and colonization of glacial microbes have been found to significantly impact the diversity and structure of glacial microbial communities, as well as the complexity of microbial networks. Specifically, the complexity of bacterial networks has been observed to increase in a sequential manner during these processes. Utilizing the Inter-Domain Ecological Network approach, researchers have further explored the cross-trophic interactions among bacteria, fungi, and archaea. The complexity of the bacteria-fungi-archaea network exhibited a sequential increase due to the processes of sequestration, release, and colonization of glacial microbes. The release and colonization of glacial microbes led to a shift in the role of archaea as key species within the network. Additionally, our findings suggest that the hierarchical interactions among various microorganisms contributed to the heightened complexity of the bacteria-fungi-archaea network. The primary constituents of the glacial microbial ecosystem are unclassified species associated with the Polaromonas. It is noteworthy that various key species in glacial ecosystems are influenced by the distinct environmental factors. Moreover, our findings suggest that key species are not significantly depleted in response to abrupt alterations in individual environmental factors, shedding light on the dynamics of microbial cross-trophic interactions within glacial ecosystems.

Impact of nutrients and trace elements on freshwater microbial communities in Croatia: identifying bacterial bioindicator taxa

Since aquatic microbial communities promptly respond to environmental changes, it is now evident that they can complement traditional taxa such as fish, macroinvertebrates and algae as bioindicators of water quality. The aim of this study was to correlate the physico-chemical parameters of water with the microbial community structure and the occurrence of putative bioindicator taxa. Thirty-five water samples were collected throughout Croatia and their physico-chemical parameters, including the concentration of trace elements using the high-resolution inductively coupled plasma mass spectrometry (HR-ICP-MS), and the composition of the microbial communities by high-throughput sequencing of the 16S rRNA marker gene, were analysed in parallel. Partial least squares regression (PLS-R) modelling revealed that a number of microbial taxa were positively correlated with some of the water parameters. For example, some taxa from the phylum Proteobacteria were positively correlated with the ion content of the water (e.g. Erythrobacter, Rhodobacteraceae, Alteromonadaceae), while some Firmicutes taxa, such as the well-known faecal indicators Enterococcus and Clostridium, were correlated with nutrient content (ammonium and total phosphorus). Among the trace elements, uranium was positively correlated with a highest number of microbial taxa. The results obtained will aid in development of protocols for eDNA-based biological assessment of water quality.

Determinants and Assembly Mechanism of Bacterial Community Structure in Ningxia Section of the Yellow River

The Yellow River is a valuable resource in the Ningxia Hui Autonomous Region and plays a vital role in local human activities and biodiversity. Bacteria are a crucial component of river ecosystems, but the driving factors and assembly mechanisms of bacterial community structure in this region remain unclear. Herein, we documented the bacterial community composition, determinants, co-occurrence pattern, and assembly mechanism for surface water and sediment. In comparison to sediment, the bacterioplankton community showed significant seasonal variation, as well as less diversity and abundance. The network topology parameters indicated that the sediment bacterial network was more stable than water, but the bacterioplankton network had higher connectivity. In this lotic ecosystem, COD_Mn, Chl a, and pH affected the structure of the bacterioplankton community, while TP was the primary factor influencing the structure of the sediment bacterial community. The combined results of the neutral community model and the phylogenetic null model indicate that Bacterial communities in both habitats were mainly affected by stochastic processes, with ecological processes dominated by ecological drift for bacterioplankton and dispersal limitation for sediment bacteria. These results provide essential insights into future research on microbial ecology, environmental monitoring, and classified management in the Ningxia section of the Yellow River.

Study of antibiotic resistance in freshwater ecosystems with low anthropogenic impact

This study aimed to investigate the bacterial diversity and the background level of antibiotic resistance in two freshwater ecosystems with low anthropogenic impact in order to evaluate the presence of natural antimicrobial resistance in these areas and its potential to spread downstream. Water samples from a pre-Alpine and an Apennine river (Variola and Tiber, respectively) were collected in three different sampling campaigns and bacterial diversity was assessed by 16S sequencing, while the presence of bacteria resistant to five antibiotics was screened using a culturable approach. Overall bacterial load was higher in the Tiber River compared with the Variola River. Furthermore, the study revealed the presence of resistant bacteria, especially the Tiber River showed, for each sampling, the presence of resistance to all antibiotics tested, while for the Variola River, the detected resistance was variable, comprising two or more antibiotics. Screening of two resistance genes on a total of one hundred eighteen bacterial isolates from the two rivers showed that bla_TEM, conferring resistance to β-lactam antibiotics, was dominant and present in ~58 % of isolates compared to only ~9 % for mefA/E conferring resistance to macrolides. Moreover, β-lactam resistance was detected in various isolates showing also resistance to additional antibiotics such as macrolides, aminoglycosides and tetracyclines. These observations would suggest the presence of co-resistant bacteria even in non-anthropogenic environments and this resistance may spread from the environment to humans and/or animals.

Development of Microbial Indicators in Ecological Systems

Indicators can monitor ecological environment changes and help maintain ecological balance. Bioindicators are divided into animal, plant, and microbial indicators, of which animal and plant indicators have previously been the most researched, but microbial indicators have drawn attention recently owing to their high sensitivity to the environment and their potential for use in monitoring environmental changes. To date, reviews of studies of animals and plants as indicator species have frequently been conducted, but reviews of research on microorganisms as indicator species have been rare. In this review, we summarize and analyze studies using microorganisms as indicator species in a variety of ecosystems, such as forests, deserts, aquatic and plateau ecosystems, and artificial ecosystems, which are contained in wetlands, farmlands, and mining ecosystems. This review provides useful information for the further use of microorganisms as indicators to reflect the changes in different environmental ecosystems.

Use of large datasets of measured environmental concentrations for the ecological risk assessment of chemical mixtures in Italian streams: A case study

A method to evaluate the ecological risk of chemical mixtures in water bodies is here presented. In the first phase, the approach considered routine chemical monitoring data (MEC: measured environmental concentrations) obtained from the Italian National Institute for Environmental Protection and Research, which were georeferenced to a single coordinate system for each monitoring station. The overall mixture toxicity were then evaluated for three representative aquatic organisms (algae, Daphnia, fish) using the concentration addition model to combine exposure with ecotoxicological data (from different databases). A database management system was used to facilitate the creation, organisation, and management of the large datasets of this study. The outputs were obtained as GIS-based mixture risk maps and tables (listing the toxic unit of mixtures and individual substances) useful for further analysis. The method was applied to an Italian watershed (Adda River) as a case study. In the first phase, the mixture toxicity was calculated using two scenarios: best- and worst-case; wherein the former included only those compounds that were be detected, while the latter involved also substances with concentrations below the limit of quantification. The ratio between the two scenarios indicated the range within which mixture toxicity should ideally vary. The method demonstrates that these ratios were very small when the calculated toxicity using the best case indicated a potential risk and vice versa, indicating that the worst-case scenario could not be appropriate (extremely conservative). Consequently, in the successive phase, we focused exclusively on the best-case scenario. Finally, this approach allowed the priority mixture identification (those most likely occurring in the analysed water samples), algae as the organism at the highest risk, and the substances that contributed the most to the overall mixture toxicity (terbuthylazine and s-metolachlor for algae, and chlorpyrifos and chlorpyrifos-CH₃ for Daphnia and fish).

An integrated approach for chemical water quality assessment of an urban river stretch through Effect-Based Methods and emerging pollutants analysis with a focus on genotoxicity

The impact of emerging chemical pollutants, on both status and functionality of aquatic ecosystems is worldwide recognized as a relevant issue of concern that should be assessed and managed by researchers, policymakers, and all relevant stakeholders. In Europe, the Reach Regulation has registered more than 100.000 chemical substances daily released in the environment. Furthermore, the effects related to the mixture of substances present in aquatic ecosystems may not be predictable on the basis of chemical analyses alone. This evidence, coupled with the dramatic effects of climate changes on water resources through water scarcity and flooding, makes urgent the application of innovative, fast and reliable monitoring methods. In this context, Effect-Based Methods (EBMs) have been applied in the urban stretch of the Tiber River (Central Italy) with the aim of understanding if detrimental pressures affect aquatic environmental health. In particular, different eco-genotoxicological assays have been used in order to detect genotoxic activity of chemicals present in the river, concurrently characterized by chemical analysis. Teratogenicity and embryo-toxicity have been studied in order to cover additional endpoints. The EBMs have highlighted the presence of diffuse chemical pollution and ecotoxicological effects in the three sampling stations, genotoxicological effects have been also detected through the use of different tests and organisms. The chemical analyses confirmed that in the aquatic ecosystems there is a diffuse presence, even at low concentrations, of emerging contaminants such as pharmaceuticals, not routinely monitored pesticides, personal care products, PFAS. The results of this study can help to identify an appropriate battery of EBMs for future studies and the application of more appropriate measures in order to monitor, mitigate or eliminate chemical contamination and remediate its adverse/detrimental effects on the ecosystem health.

Legacy and Emerging Pollutants in an Urban River Stretch and Effects on the Bacterioplankton Community

River contamination is due to a chemical mixture of point and diffuse pollution, which can compromise water quality. Polycyclic Aromatic Hydrocarbons (PAHs) and emerging compounds such as pharmaceuticals and antibiotics are frequently found in rivers flowing through big cities. This work evaluated the presence of fifteen priority PAHs, eight pharmaceuticals including the antibiotics ciprofloxacin (CIP) and sulfamethoxazole (SMX), together with their main antibiotic resistant genes (ARGs) and the structure of the natural bacterioplankton community, in an urbanized stretch of the river Danube. SMX and diclofenac were the most abundant chemicals found (up to 20 ng/L). ARGs were also found to be detected as ubiquitous contaminants. A principal component analysis of the overall microbiological and chemical data revealed which contaminants were correlated with the presence of certain bacterial groups. The highest concentrations of naphthalene were associated with Deltaproteobacteria and intI1 gene. Overall, the most contaminated site was inside the city and located immediately downstream of a wastewater treatment plant. However, both the sampling points before the river reached the city and in its southern suburban area were still affected by emerging and legacy contamination. The diffuse presence of antibiotics and ARGs causes particular concern because the river water is used for drinking purposes.

Seasonal effects of river flow on microbial community coalescence and diversity in a riverine network

Terrestrial microbial communities may take advantage of running waters and runoff to enter rivers and mix with aquatic microorganisms. However, the environmental factors governing the interchange of the microbial community within a watercourse and its surrounding environment and the composition of the resulting community are often underestimated. The present study investigated the effect of flow rate on the mixing of water, soil, sediment and biofilm at four sites along the Lancang River and one branch of the river in winter and summer and, in turn, the resultant changes in the microbial community within each habitat. 16S rRNA gene-based Illumina high-throughput sequencing illustrated that bacterial communities were apparently distinct among biofilm, water, soil and sediment. Biofilms had the lowest richness, Shannon diversity and evenness indices compared with other habitats, and those three indices in all habitats increased significantly from winter to summer. SourceTracker analysis showed a significant coalescence between the bacterial communities of sediment, water and biofilm samples at lower flow rates. Additionally, the proportion of Betaproteobacteria in sediment and biofilms increased with a decrease in flow rate, suggesting the flow rate had a strong impact on microbial community composition and exchange among aquatic habitats. These results were further confirmed by a Mantel test and linear regression analysis. Microbial communities in all samples exhibited a significant but very weak distance-decay relationship (r = 0.093, P = 0.024). Turbidity played a much more important role on water bacterial community structure in summer (i.e. rainy season) (BIOENV, r = 0.92). Together, these results suggest that dispersal is an important factor affecting bacterial community structure in this system.

Characterization of the Belowground Microbial Community in a Poplar-Phytoremediation Strategy of a Multi-Contaminated Soil

Due to their widespread use in industrial applications in recent decades, Polychlorobiphenyls (PCBs) and heavy metals (HMs) are the most common soil contaminants worldwide, posing a risk for both ecosystems and human health. In this study, a poplar-assisted bioremediation strategy has been applied for more than 4 years to a historically contaminated area (PCBs and HMs) in Southern Italy using the Monviso poplar clone. This clone was effective in promoting a decrease in all contaminants and an increase in soil quality in terms of organic carbon and microbial abundance. Moreover, a significant shift in the structure and predicted function of the belowground microbial community was also observed when analyzing both DNA and cDNA sequencing data. In fact, an increase in bacterial genera belonging to Proteobacteria able to degrade PCBs and resist HMs was observed. Moreover, the functional profiling of the microbial community predicted by PICRUSt2 made it possible to identify several genes associated with PCB transformation (e.g., bphAa, bphAb, bphB, bphC), response to HM oxidative stress (e.g., catalase, superoxide reductase, peroxidase) and HM uptake and expulsion (e.g., ABC transporters). This work demonstrated the effectiveness of the poplar clone Monviso in stimulating the natural belowground microbial community to remove contaminants and improve the overall soil quality. It is a practical example of a nature based solution involving synergic interactions between plants and the belowground microbial community.

Point-of-Care Strategies for Detection of Waterborne Pathogens

Waterborne diseases that originated due to pathogen microorganisms are emerging as a serious global health concern. Therefore, rapid, accurate, and specific detection of these microorganisms (i.e., bacteria, viruses, protozoa, and parasitic pathogens) in water resources has become a requirement of water quality assessment. Significant research has been conducted to develop rapid, efficient, scalable, and affordable sensing techniques to detect biological contaminants. State-of-the-art technology-assisted smart sensors have improved features (high sensitivity and very low detection limit) and can perform in a real-time manner. However, there is still a need to promote this area of research, keeping global aspects and demand in mind. Keeping this view, this article was designed carefully and critically to explore sensing technologies developed for the detection of biological contaminants. Advancements using paper-based assays, microfluidic platforms, and lateral flow devices are discussed in this report. The emerging recent trends, mainly point-of-care (POC) technologies, of water safety analysis are also discussed here, along with challenges and future prospective applications of these smart sensing technologies for water health diagnostics.

Groundwater Autochthonous Microbial Communities as Tracers of Anthropogenic Pressure Impacts: Example from a Municipal Waste Treatment Plant (Latium, Italy)

The groundwater behavior at a municipal solid waste disposal dump, located in Central Italy, was studied using a multi-parameter monitoring over 1 year consisting of 4 seasonal samples. The hydrological and hydrogeological dynamics of water circulation, microbiological parameters (microbial abundance and cell viability of the autochthonous microbial community), dissolved organic carbon, and several contaminants were evaluated and related to the geological structures in both two and three dimensions and used for geostatistical analysis in order to obtain 3D maps. Close relationships between geological heterogeneity, water circulation, pollutant diffusion, dissolved organic carbon, and cell viability were revealed. The highest cell viability values were found with dissolved organic carbon (DOC) values ≤0.5 mg/L; above this value, DOC negatively affected the microbial community. The highest DOC values were detected in groundwater at some sampling points within the site indicating its probable origin from the waste disposal dump. Although legislation limits for the parameters measured were not exceeded (except for a contaminant in one piezometer), the 1-year multi-parameter monitoring approach made it possible to depict both the dynamics and the complexity of the groundwater flux and, with “non-legislative parameters” such as microbial cell viability and DOC, identify the points with the highest vulnerability and their origin. This approach is useful for identifying the most vulnerable sites in a groundwater body.