Introducing Simple Detection of Bioavailable Arsenic at Rafaela (Santa Fe Province, Argentina) Using the ARSOlux Biosensor.

Numerous articles have reported the occurrence of arsenic in drinking water in Argentina, and the resulting health effects in severely affected regions of the country. Arsenic in drinking water in Argentina is largely naturally occurring due to elevated background content of the metalloid in volcanic sediments, although, in some regions, mining can contribute. While the origin of arsenic release has been discussed extensively, the problem of drinking water contamination has not yet been solved. One key step in progress towards mitigation of problems related with the consumption of As-containing water is the availability of simple detection tools. A chemical test kit and the ARSOlux biosensor were evaluated as simple analytical tools for field measurements of arsenic in the groundwater of Rafaela (Santa Fe, Argentina), and the results were compared with ICP-MS and HPLC-ICP-MS measurements. A survey of the groundwater chemistry was performed to evaluate possible interferences with the field tests. The results showed that the ARSOlux biosensor performed better than the chemical field test, that the predominant species of arsenic in the study area was arsenate and that arsenic concentration in the studied samples had a positive correlation with fluoride and vanadium, and a negative one with calcium and iron.

Population dynamics within a microbial consortium during growth on diesel fuel in saline environments.

The diversity and dynamics of a bacterial community extracted from an exploited oil field with high natural soil salinity near Comodoro Rivadavia in Patagonia (Argentina) were investigated. Community shifts during long-term incubation with diesel fuel at four salinities between 0 and 20% NaCl were monitored by single-strand conformation polymorphism community fingerprinting of the PCR-amplified V4-V5 region of the 16S rRNA genes. Information obtained by this qualitative approach was extended by flow cytometric analysis to follow quantitatively the dynamics of community structures at different salinities. Dominant and newly developing clusters of individuals visualized via their DNA patterns versus cell sizes were used to identify the subcommunities primarily involved in the degradation process. To determine the most active species, subcommunities were separated physically by high-resolution cell sorting and subsequent phylogenetic identification by 16S rRNA gene sequencing. Reduced salinity favored the dominance of Sphingomonas spp., whereas at elevated salinities, Ralstonia spp. and a number of halophilic genera, including Halomonas, Dietzia, and Alcanivorax, were identified. The combination of cytometric sorting with molecular characterization allowed us to monitor community adaptation and to identify active and proliferating subcommunities.