A metagenomic study of antibiotic resistance genes in a hypereutrophic subtropical lake contaminated by anthropogenic sources

Antibiotic resistance genes (ARGs) are a major threat to human and environmental health. This study investigated the occurrence and distribution of ARGs in Lake Cajititlán, a hypereutrophic subtropical lake in Mexico contaminated by anthropogenic sources (urban wastewater and runoff from crop and livestock production). ARGs (a total of 475 genes) were detected in 22 bacterial genera, with Pseudomonas (144 genes), Stenotrophomonas (88 genes), Mycobacterium (54 genes), and Rhodococcus (27 genes) displaying the highest frequencies of ARGs. Among these, Pseudomonas aeruginosa and Stenotrophomonas maltophilia showed the highest number of ARGs. The results revealed a diverse array of ARGs, including resistance to macrolides (11.55 %), aminoglycosides (8.22 %), glycopeptides (6.22 %), tetracyclines (4 %), sulfonamides (4 %), carbapenems (1.11 %), phenicols (0.88 %), fluoroquinolones (0.44 %), and lincosamides (0.22 %). The most frequently observed ARGs were associated with multidrug resistance (63.33 %), with MexF (42 genes), MexW (36 genes), smeD (31 genes), mtrA (25 genes), and KHM-1 (22 genes) being the most common. Lake Cajititlán is a recreational area for swimming, fishing, and boating, while also supporting irrigation for agriculture and potentially acting as a drinking water source for some communities. This raises concerns about the potential for exposure to antibiotic-resistant bacteria through these activities. The presence of ARGs in Lake Cajititlán poses a significant threat to both human and environmental health. Developing strategies to mitigate the risks of antibiotic resistance, including improving wastewater treatment, and promoting strategic antibiotic use and disposal, is crucial. This study represents a significant advancement in the understanding of antibiotic resistance dynamics in a hypereutrophic subtropical lake in a developing country, providing valuable insights for the scientific community and policymakers.

Yeast community composition impacts on tequila industry waste treatment for pollution control and waste-to-product synthesis

The Tequila industry is a major producer of wastewater in the state of Jalisco, Mexico. Tequila vinasses (TV) are a residue from the distillation of fermented agave wort during tequila production. TV are difficult to treat due their high organic content, high nutrient loads, acidic pH and high discharge temperature. TV are frequently released into waterbodies or soil without any treatment, leading to environmental degradation of soil and water sources. To reduce the environmental impact of the tequila industry, cost-effective TV revalorization approaches must be developed. The goals of the present study were to assess the treatment and revalorization potential of TV using mono and mixed yeast cultures to produce single-cell protein (SCP) and to analyze yeast community composition using high-throughput sequencing during the mixed-culture fermentation of TV. The fermentation process was performed using a mixed culture of three fodder yeast species (Candida utilis, Rhodotorula mucilaginosa and Kluyveromyces marxianus) during 48 h at benchtop-scale. High-throughput sequencing was performed to assess the relative abundance of the yeast communities. Additionally, a redundancy analysis was performed to analyze the bidirectional influence between yeast communities and pollutant removal (COD, nitrogen, phosphorus, proteins, and sugars). Mixed yeast cultures displayed overall higher pollutant removal rates than monocultures, where C. utilis and K. marxianus contributed the most to pollutant removal and protein accumulation. The R. mucilaginosa population declined rapidly in mixed culture, presumably due to TV acidity and phenolic composition. However, the presence of The R. mucilaginosa in the mixed culture enhanced pollutant removal and amino acid contents. Accordingly, the protein and amino acid content within mixed cultures were significantly higher than those of monocultures, indicating that mixed cultures have a strong potential to produce protein rich biomass from TV, aiding in the transition of both the tequila and the livestock industries to a sustainable circular bioeconomy model by the reintegration of organic material flows into productive processes, reducing raw resource intake and waste generation. The present circular bioeconomy approach could represent a potential to produce 45,664 tons of protein feed yearly, based on the current tequila vinasses generated in the state of Jalisco.

Assessment of the water quality of a subtropical lake using the NSF-WQI and a newly proposed ecosystem specific water quality index

A Water Quality Index (WQI) is a formulation that enables the estimation of the overall quality of a water body based on significant parameters. One example of this is the well-known and widely accepted NSF-WQI, which is frequently used to assess chemical, physical, and microbiologic features of waterbodies in temperate latitudes. In this work, a well-structured method, completely based on multivariate statistical methods and historical data distributions, was used to develop an ecosystem specific water quality index (ES-WQI). Lake Cajititlán, a subtropical Mexican lake located in Tlajomulco de Zúñiga, was selected as a case of study because it is an endorheic shallow lake that shows signs of high levels of eutrophication due to anthropogenic contamination. As a result of the contamination, and its sensibility to changes in the water level, it undergoes important changes in its water features, such as turbidity and intense green color, and experiences massive events of fish mortality. The proposed ES-WQI describes the changes in water quality over the year well and correlates with the capability of the lake to support aquatic life, as the lowest estimated values coincide with the biggest events of massive fish mortality in the lake. Furthermore, the ES-WQI clearly differentiates between typical cyclic behaviors and actual deteriorating trends and is capable of tracking incremental changes all over the range of the possible concentration values of the water quality parameters.