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.

Associations between bacterial and fungal communities in the human gut microbiota and their implications for nutritional status and body weight.

This study examined the interplay between bacterial and fungal communities in the human gut microbiota, impacting on nutritional status and body weight. Cohorts of 10 participants of healthy weight, 10 overweight, and 10 obese individuals, underwent comprehensive analysis, including dietary, anthropometric, and biochemical evaluations. Microbial composition was studied via gene sequencing of 16S and ITS rDNA regions, revealing bacterial (bacteriota) and fungal (mycobiota) profiles. Bacterial diversity exceeded fungal diversity. Statistically significant differences in bacterial communities were found within healthy-weight, overweight, and obese groups. The Bacillota/Bacteroidota ratio (previously known as the Firmicutes/Bacteroidetes ratio) correlated positively with body mass index. The predominant fungal phyla were Ascomycota and Basidiomycota, with the genera Nakaseomyces, Kazachstania, Kluyveromyces, and Hanseniaspora, inversely correlating with weight gain; while Saccharomyces, Debaryomyces, and Pichia correlated positively with body mass index. Overweight and obese individuals who harbored a higher abundance of Akkermansia muciniphila, demonstrated a favorable lipid and glucose profiles in contrast to those with lower abundance. The overweight group had elevated Candida, positively linked to simple carbohydrate consumption. The study underscores the role of microbial taxa in body mass index and metabolic health. An imbalanced gut bacteriota/mycobiota may contribute to obesity/metabolic disorders, highlighting the significance of investigating both communities.

Internet of Things and citizen science as alternative water quality monitoring approaches and the importance of effective water quality communication.

The increasing demand for water and worsening climate change place significant pressure on this vital resource, making its preservation a global priority. Water quality monitoring programs are essential for effectively managing this resource. Current programs rely on traditional monitoring approaches, leading to limitations such as low spatiotemporal resolution and high operational costs. Despite the adoption of novel monitoring approaches that enable better data resolution, the public's comprehension of water quality matters remains low, primarily due to communication process deficiencies. This study explores the advantages and challenges of using Internet of Things (IoT) and citizen science as alternative monitoring approaches, emphasizing the need for enhancing public communication of water quality data. Through a systematic review of studies implemented on-field, we identify and propose strategies to address five key challenges that IoT and citizen science monitoring approaches must overcome to mature into robust sources of water quality information. Additionally, we highlight three fundamental problems affecting the water quality communication process and outline strategies to convey this topic effectively to the public.

Characterizing a subtropical hypereutrophic lake: From physicochemical variables to shotgun metagenomic data.

Lake Cajititlán is a subtropical and endorheic lake, which is heavily impacted by nutrient pollution. Agricultural runoff and poorly treated wastewater have entered this reservoir at alarming rates during past rainy seasons, causing the cultural eutrophication of this body of water and resulting in several massive fish kill events. In this study, shotgun metagenomic sequencing was used to examine the taxonomic and functional structure of microbial communities in Lake Cajititlán during the rainy season. Several water quality features and their interactions with microbial communities were also assessed to identify the major factors affecting the water quality and biota, specifically fish species. According to current water quality regulations, most of the physicochemical variables analyzed (dissolved oxygen, pH, Secchi disk, NH4 +, NO3 -, blue-green algae, total phosphorus, and chlorophyll-a) were outside of the permissible limits. Planktothrix agardhii and Microcystis aeruginosa were the most abundant phytoplankton species, and the dominant bacterial genera were Pseudomonas, Streptomyces, and Flavobacterium, with Pseudomonas fluorescens, Stenotrophomonas maltophilia, and Aeromonas veronii representing the most abundant bacterial species. All of these microorganisms have been reported to be potentially harmful to fish, and the latter three (P. fluorescens, S. maltophilia, A. veronii) also contain genes associated with pathogenicity in fish mortality (fur, luxS, aer, act, aha, exu, lip, ser). Genetic evidence from the microbial communities analyzed herein reveals that anthropogenic sources of nutrients in the lake altered genes involved in nitrogen, phosphorus, sulfur, and carbon metabolism, mainly at the beginning of the rainy season. These findings suggest that abiotic factors influence the structure of the microbial communities, along with the major biogeochemical cycles of Lake Cajititlán, resulting in temporal variations and an excess of microorganisms that can thrive in high-nutrient and low-oxygen environments. After reviewing the literature, this appears to be the first study that focuses on characterizing the water quality of a subtropical hypereutrophic lake through associations between physicochemical variables and shotgun metagenomic data. In addition, there are few studies that have coupled the metabolism of aquatic ecosystems with nutrient cycles.

Bacterial Dynamics and Their Influence on the Biogeochemical Cycles in a Subtropical Hypereutrophic Lake During the Rainy Season.

Lakes in subtropical regions are highly susceptible to eutrophication due to the heavy rainfall, which causes significant runoff of pollutants (e.g., nutrients) to reach surface waters, altering the water quality and influencing the microbial communities that regulate the biogeochemical cycles within these ecosystems. Lake Cajititlán is a shallow, subtropical, and endorheic lake in western Mexico. Nutrient pollution from agricultural activity and wastewater discharge have affected the lake's water quality, leading the reservoir to a hypereutrophic state, resulting in episodes of fish mortality during the rainy season. This study investigated the temporal dynamics of bacterial communities within Lake Cajititlán and their genes associated with the nitrogen, phosphorus, sulfur, and carbon biogeochemical cycles during the rainy season, as well as the influences of physicochemical and environmental variables on such dynamics. Significant temporal variations were observed in the composition of bacterial communities, of which Flavobacterium and Pseudomonas were the dominant genera. The climatological parameters that were most correlated with the bacterial communities and their functional profiles were pH, DO, ORP, turbidity, TN, EC, NH4 +, and NO3 -. The bacterial communities displayed variations in their functional composition for nitrogen, phosphorus, and sulfur metabolisms during the sampling months. The bacterial communities within the lake are highly susceptible to nutrient loads and low DO levels during the rainy season. Bacterial communities had a higher relative abundance of genes associated with denitrification, nitrogen fixation, assimilatory sulfate reduction, cysteine, SOX system, and all phosphorus metabolic pathways. The results obtained here enrich our understanding of the bidirectional interactions between bacterial communities and major biogeochemical processes in eutrophic subtropical lakes.

Rapid Changes in the Phytoplankton Community of a Subtropical, Shallow, Hypereutrophic Lake During the Rainy Season.

Lake Cajititlán is a small, shallow, subtropical lake located in an endorheic basin in western Mexico. It is characterized by a strong seasonality of climate with pronounced wet and dry seasons and has been classified as a hypereutrophic lake. This eutrophication was driven by improperly treated sewage discharges from four municipal wastewater treatment plants (WWTPs) and by excessive agricultural activities, including the overuse of fertilizers that reach the lake through surface runoff during the rainy season. This nutrient rich runoff has caused algal blooms, which have led to anoxic or hypoxic conditions, resulting in large-scale fish deaths that have occurred during or immediately after the rainy season. This study investigated the changes in the phytoplankton community in Lake Cajititlán during the rainy season and the association between these changes and the physicochemical water quality and environmental parameters measured in the lake's basin. Planktothrix and Cylindrospermopsis were the dominant genera of the cyanobacterial community, while the Chlorophyceae, Chrysophyceae, and Trebouxiophyceae classes dominated the microalgae community. However, the results showed a significant temporal shift in the phytoplankton communities in Lake Cajititlán induced by the rainy season. The findings of this study suggest that significant climatic variations cause high seasonal surface runoff and rapid changes in the water quality (Chlorophyll-a, DO, NH4 +, and NO3 -) and in variations in the composition of the phytoplankton community. Finally, an alternation between phosphorus and nitrogen limitation was observed in Lake Cajititlán during the rainy season, clearly correlating to the presence of Planktothrix when the lake was limited by phosphorus and to the presence of Cylindrospermopsis when the lake was limited by nitrogen. The evidence presented in this study supports the idea that the death of fish in Lake Cajititlán could be mainly caused by anoxia, caused by rapid changes in water quality during the rainy season. Based on our review of the literature, this is the first study on the phytoplankton community in a subtropical lake during the rainy season using high throughput 16S rRNA and 18S rRNA amplicon sequencing.

Prevalence, Distribution, and Diversity of Salmonella Strains Isolated From a Subtropical Lake.

This study investigated the prevalence, serovar distribution, antimicrobial resistance, and pulsed field gel electrophoresis (PFGE) typing of Salmonella enterica isolated from Lake Zapotlán, Jalisco, Mexico. Additionally, the association of the presence of Salmonella with physicochemical and environmental parameters was analyzed using Pearson correlation analysis and principal component analysis (PCA). Salmonella spp. were identified in 19 of 63 (30.15%) samples. The prevalence of Salmonella was positively correlated with air temperature, electrical conductivity, pH, and dissolved oxygen and negatively correlated with relative humidity, water temperature, turbidity, and precipitation. The predominant serotype identified was Agona (68.48%), followed by Weltevreden (5.26%), Typhimurium (5.26%), and serogroup B (21.05%). Overall, the highest detected antimicrobial resistance was toward colistin (73.68%), followed by sulfamethoxazole (63.15%), tetracycline (57.89%), nalidixic acid (52.63%), and trimethoprim (52.63%). All Salmonella strains were genetically diverse, with a total of 11 XbaI and four BlnI profiles on PFGE. The use of these two enzymes allowed differentiate strains of Salmonella of the same serotype. The results obtained in this study contribute to a better understanding of the Salmonella spp. ecology in an endorheic subtropical lake and provide information for decision makers to propose and implement effective strategies to control point and non-point sources of pathogen contamination.

Assessment of heavy metals in the surface sediments and sediment-water interface of Lake Cajititlán, Mexico.

Lake Cajititlán is an endorheic tropical lake located in the state of Jalisco, Mexico, which has suffered the consequences of high levels of eutrophication. This study assessed the presence of heavy metals and metalloids in Lake Cajititlán to ascertain possible risks to its aquatic biota and the environment. Eleven monitoring sites were selected throughout the lake; from each site, one sample was taken from the sediments and another from the sediment-water interface by using an Ekman dredger and a Van Dorn bottle, respectively. The measured metals in each sample were As, Cd, Cr, Hg, Pb, Zn, Cu, Ni, Fe, Mn, and Al. The results showed the following sequence of heavy metal concentrations Al > Fe > Mn > Zn > Cu > Cr, wherein Al had the highest average concentration and Cr had the lowest. As, Cd, Hg, and Pb were practically undetectable. Because the predominant rock in the lake basin is volcanic tuff and the soil is vertisol, the high quantities of Al and Fe suggest the weathering of the basin's minerals. The analyses of the sediment-water samples contained small amounts of dissolved Al, Fe, and Mn. According to the Håkanson equations with Hg, Cd, As, Cu, Pb, Cr, and Zn, the calculations of the contamination degree and ecological risk revealed that the presence of metals and metalloids does not present a potential risk to the aquatic biota; nonetheless, the water is not suitable for local human consumption due to an unrelated factor associated with nutrient and bacteriological contamination. The results show that heavy metals in the sediments were dispersed throughout the lake mostly because of the weathering of minerals from the local basin and not because of the punctual discharges of the pollutants from the municipal wastewater treatment plants (WWTPs). However, to ensure that the small amounts of dissolved metals (Al, Fe, and Mn) do not affect the aquatic biota, the fish species and phytoplankton need to be internally analyzed.