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Toxic cyanobacterial blooms represent a natural phenomenon caused by a mass proliferation of photosynthetic prokaryotic microorganisms in water environments. Bloom events have been increasingly reported worldwide and their occurrence can pose serious threats to aquatic organisms and human health. In this study, we assessed the microbial composition, with a focus on Cyanobacteria, in Lake Varese, a eutrophic lake located in northern Italy. Water samples were collected and used for obtaining a 16S-based taxonomic profile and performing a shotgun sequencing analysis. The phyla found to exhibit the greatest relative abundance in the lake included Proteobacteria, Cyanobacteria, Actinobacteriota and Bacteroidota. In the epilimnion and at 2.5 × Secchi depth, Cyanobacteria were found to be more abundant compared to the low levels detected at greater depths. The blooms appear to be dominated mainly by the species Lyngbya robusta, and a specific functional profile was identified, suggesting that distinct metabolic processes characterized the bacterial population along the water column. Finally, analysis of the shotgun data also indicated the presence of a large and diverse phage population., (© 2021. The Author(s).)

The development of sensitive methods for the determination of potential bacterial contamination is of upmost importance for environmental monitoring and food safety. In this study, we present a new method combining a fast pre-enrichment step using a microporous cryogel and a detection and identification step using antimicrobial peptides (AMPs) and labelled antibodies, respectively. The experimental method consists of: (i) the capture of large amounts of bacteria from liquid samples by using a highly porous and functionalized cryogel; (ii) the detection and categorisation of Gram-positive and Gram-negative bacteria by determining their affinities toward a small set of AMPs; and (iii) the identification of the bacterial strain by using labelled detection antibodies. As proof of concept, the assessment of the three steps of the analysis was performed by using Escherichia coli and Bacillus sp. as models for Gram-negative and Gram-positive bacteria, respectively. The use of AMPs with broad specificity combined with labelled antibodies enabled the detection and potential categorization of a large spectrum of unknown or unexpected bacteria.

Development of sensitive methods for the determination of E. coli bacteria contamination in water distribution systems is of paramount importance to ensure the microbial safety of drinking water. This work presents a new sensing platform enabling the fast detection of bacteria in field samples by using specific antibodies as the biorecognition element and dark field microscopy as the detection technique. The development of the sensing platform was performed using non-pathogenic bacteria, with the E. coli DH5α strain as the target, and Bacillus sp. 9727 as the negative control. The identification of the captured bacteria was made by analyzing the dark field microscopy images and screening the detected objects by using object circularity and size parameters. Specificity tests revealed the low unspecific attachment of either E. coli over human serum albumin antibodies (negative control for antibody specificity) and of Bacillus sp . over E. coli antibodies. The system performance was tested using field samples, collected from a wastewater treatment plant, and compared with two quantification techniques (i.e., Colilert-18 test and quantitative polymerase chain reaction (qPCR)). The results showed comparable quantification capability. Nevertheless, the present method has the advantage of being faster, is easily adaptable to in-field analysis, and can potentially be extended to the detection of other bacterial strains.

The detection and quantification of nanoparticles is a complex issue due to the need to combine "classical" identification and quantification of the constituent material, with the accurate determination of the size of submicrometer objects, usually well below the optical diffraction limit. In this work, the authors show that one of the most used analytical methods for silver nanoparticles, asymmetric flow field-flow fractionation, can be strongly influenced by the presence of dissolved organic matter (such as alginate) and lead to potentially misleading results. The authors explain the anomalies in the separation process and show a very general way forward based on the combination of size separation and size measurement techniques. This combination of techniques results in more robust AF4-based methods for the sizing of silver nanoparticles in environmental conditions and could be generally applied to the sizing of nanoparticles in complex matrices.

The use of nanotechnology-based products is constantly increasing and there are concerns about the fate and effect on the aquatic environment of antimicrobial products such as silver nanoparticles. By combining different characterization techniques (asymmetric flow field-flow fractionation, single particle ICP-MS, UV-Vis) we show that it is possible to assess in detail the agglomeration process of silver nanoparticles in artificial seawater. In particular we show that the presence of alginate or humic acid differentially affects the kinetic of the agglomeration process. This study provides an experimental methodology for the in-depth analysis of the fate and behaviour of silver nanoparticles in the aquatic environment., (Copyright © 2015. Published by Elsevier Ltd.)

In the following article an electron/ion microscopy study will be presented which investigates the uptake of silver nanoparticles (AgNPs) by the marine diatom Thalassiosira pseudonana, a primary producer aquatic species. This organism has a characteristic silica exoskeleton that may represent a barrier for the uptake of some chemical pollutants, including nanoparticles (NPs), but that presents a technical challenge when attempting to use electron-microscopy (EM) methods to study NP uptake. Here we present a convenient method to detect the NPs interacting with the diatom cell. It is based on a fixation procedure involving critical point drying which, without prior slicing of the cell, allows its inspection using transmission electron microscopy. Employing a combination of electron and ion microscopy techniques to selectively cut the cell where the NPs were detected, we are able to demonstrate and visualize for the first time the presence of AgNPs inside the cell membrane.

In the year 2010, effluents from 90 European wastewater treatment plants (WWTPs) were analyzed for 156 polar organic chemical contaminants. The analyses were complemented by effect-based monitoring approaches aiming at estrogenicity and dioxin-like toxicity analyzed by in vitro reporter gene bioassays, and yeast and diatom culture acute toxicity optical bioassays. Analyses of organic substances were performed by solid-phase extraction (SPE) or liquid-liquid extraction (LLE) followed by liquid chromatography tandem mass spectrometry (LC-MS-MS) or gas chromatography high-resolution mass spectrometry (GC-HRMS). Target microcontaminants were pharmaceuticals and personal care products (PPCPs), veterinary (antibiotic) drugs, perfluoroalkyl substances (PFASs), organophosphate ester flame retardants, pesticides (and some metabolites), industrial chemicals such as benzotriazoles (corrosion inhibitors), iodinated x-ray contrast agents, and gadolinium magnetic resonance imaging agents; in addition biological endpoints were measured. The obtained results show the presence of 125 substances (80% of the target compounds) in European wastewater effluents, in concentrations ranging from low nanograms to milligrams per liter. These results allow for an estimation to be made of a European median level for the chemicals investigated in WWTP effluents. The most relevant compounds in the effluent waters with the highest median concentration levels were the artificial sweeteners acesulfame and sucralose, benzotriazoles (corrosion inhibitors), several organophosphate ester flame retardants and plasticizers (e.g. tris(2-chloroisopropyl)phosphate; TCPP), pharmaceutical compounds such as carbamazepine, tramadol, telmisartan, venlafaxine, irbesartan, fluconazole, oxazepam, fexofenadine, diclofenac, citalopram, codeine, bisoprolol, eprosartan, the antibiotics trimethoprim, ciprofloxacine, sulfamethoxazole, and clindamycine, the insect repellent N,N'-diethyltoluamide (DEET), the pesticides MCPA and mecoprop, perfluoroalkyl substances (such as PFOS and PFOA), caffeine, and gadolinium., (Copyright © 2013 Elsevier Ltd. All rights reserved.)