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

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.

Eco-friendly biopesticides derived from CO2-Fixing cyanobacteria

There is currently an escalating global demand for the utilization of plant and natural extracts as pesticides due to their minimal health risks. Cyanobacteria are highly valuable organisms with significant potential in agriculture and are of great interest for the development of agrochemical agents as biopesticides. The flexibility and adaptability of Cyanobacteria to various environmental conditions are facilitated by the presence of specialized enzymes involved in the production of biologically active diverse secondary metabolites, including alkaloids, lipopolysaccharides, non-protein amino acids, non-ribosomal peptides, polyketides, terpenoids, and others. This review focuses on the metabolites synthesized from cyanobacteria that have demonstrated effectiveness as antibacterial, antiviral, antifungal agents, insecticides, herbicides, and more. The potential role of cyanobacteria as an alternative to chemical pesticides for environmental conservation is discussed.

Simultaneous targeted amplicon deep sequencing and library preparation for a time and cost-effective universal parasite diagnostic sequencing approach

We recently described a targeted amplicon deep sequencing (TADS) strategy that utilizes a nested PCR targeting the 18S rDNA gene of blood-borne parasites. The assay facilitates selective digestion of host DNA by targeting enzyme restriction sites present in vertebrates but absent in parasites. This enriching of parasite-derived amplicon drastically reduces the proportion of host-derived reads during sequencing and results in the sensitive detection of several clinically important blood parasites including Plasmodium spp., Babesia spp., kinetoplastids, and filarial nematodes. Despite these promising results, high costs and the laborious nature of metagenomics sequencing are prohibitive to the routine use of this assay in most laboratories. We describe and evaluate a new metagenomic approach that utilizes a set of primers modified from our original assay that incorporates Illumina barcodes and adapters during the PCR steps. This modification makes amplicons immediately compatible with sequencing on the Illumina MiSeq platform, removing the need for a separate library preparation, which is expensive and time-consuming. We compared this modified assay to our previous nested TADS assay in terms of preparation speed, limit of detection (LOD), and cost. Our modifications reduced assay turnaround times from 7 to 5 days. The cost decreased from approximately $40 per sample to $11 per sample. The modified assay displayed comparable performance in the detection and differentiation of human-infecting Plasmodium spp., Babesia spp., kinetoplastids, and filarial nematodes in clinical samples. The LOD of this modified approach was determined for malaria parasites and remained similar to that previously reported for our earlier assay (0.58 Plasmodium falciparum parasites/µL of blood). These modifications markedly reduced costs and turnaround times, making the assay more amenable to routine diagnostic applications.

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.

Retrieving Inland Reservoir Water Quality Parameters Using Landsat 8-9 OLI and Sentinel-2 MSI Sensors with Empirical Multivariate Regression

Improving water quality is one of the top priorities in the global agenda endorsed by the United Nations. To ensure the achievement of this goal, governments have developed plans to continuously monitor the status of inland waters. Remote sensing provides a low-cost, high-frequency, and practical complement to monitoring systems that can cover a large area. However, it is crucial to evaluate the suitability of sensors for retrieving water quality parameters (WQPs), owing to differences in spatial and spectral sampling from different satellites. Taking Shanmei Reservoir in Fuzhou City, Fujian Province as a case study, this study collected and sorted the water quality data measured at the site in 2020 to 2022 and Landsat 8-9 OLI and Sentinel-2 MSI images, simulated the chlorophyll-a (Chl-a) concentration, algae density, and turbidity using empirical multivariate regression, and explored the relationship between different WQPs using correlation analysis and principal component analysis (PCA). The results showed that the fitting effect of Landsat OLI data was better than that of the Sentinel-2 MSI data. The coefficient of determination (R2) values of Chl-a, algal density, and turbidity simulated by Landsat OLI data were 0.70, 0.81, and 0.80, respectively. Furthermore, the parameters of its validation equation were also smaller than those of Sentinel MSI data. The spatial distribution of three key WQPs retrieved from Landsat OLI data shows their values were generally low, with the mean values of the Chl-a concentration, algal density, and turbidity being 4.25 μg/L, 4.11 × 106 cells/L, and 1.86 NTU, respectively. However, from the end of February 2022, the values of the Chl-a concentration and algae density in the reservoir gradually increase, and the risk of water eutrophication also increases. Therefore, it is still necessary to pay continuous attention and formulate corresponding water quality management measures. The correlation analysis shows that the three key WQPs in this study have a high correlation with pH, water temperature (WT), and dissolved oxygen (DO). The results of PCA showed that pH, DO, Chl-a concentration, WT, TN, and CODMn were dominant in PC1, explaining 35.57% of the total variation, and conductivity, algal density, and WT were dominant in PC2, explaining 13.34% of the total variation. Therefore, the water quality of the Shanmei Reservoir can be better evaluated by measuring pH, conductivity, and WT at the monitoring station, or by establishing the regression fitting equations between DO, CODMn, and TN. The regression algorithm used in this study can identify the most important water quality features in the Shanmei Reservoir, which can be used to monitor the nutritional status of the reservoir and provide a reference for other similar inland water bodies.

The widespread capability of methylphosphonate utilization in filamentous cyanobacteria and its ecological significance

Aquatic ecosystems comprise almost half of total global methane emissions. Recent evidence indicates that a few strains of cyanobacteria, the predominant primary producers in bodies of water, can produce methane under oxic conditions with methylphosphonate serving as substrate. In this work, we have screened the published 2 568 cyanobacterial genomes for genetic elements encoding phosphonate-metabolizing enzymes. We show that phosphonate degradation (phn) gene clusters are widely distributed in filamentous cyanobacteria, including several bloom-forming genera. Algal growth experiments revealed that methylphosphonate is an alternative phosphorous source for four of five tested strains carrying phn clusters, and can sustain cellular metabolic homeostasis of strains under phosphorus stress. Liberation of methane by cyanobacteria in the presence of methylphosphonate occurred mostly during the light period of a 12 h/12 h diurnal cycle and was suppressed in the presence of orthophosphate, features that are consistent with observations in natural aquatic systems under oxic conditions. The results presented here demonstrate a genetic basis for ubiquitous methane emission via cyanobacterial methylphosphonate mineralization, while contributing to the phosphorus redox cycle.

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.

Characterizing Trophic State in Tropical/Subtropical Reservoirs: Deviations among Indexes in the Lower Latitudes

Trophic state indexes (TSI) guide management strategies regarding eutrophication control worldwide. Such indexes usually consider chlorophyll-a (Chl-a), total phosphorus (TP), and Secchi disk depth (SDD) as independent variables for estimating aquatic productivity and the degree of impairment. TSIs for each of these components are frequently averaged to produce a single TSI value associated with a trophic state classification (e.g., oligotrophic, mesotrophic, or eutrophic). The potential divergence among equations and classification systems originally developed for temperate lakes or tropical/subtropical reservoirs might be particularly relevant in the tropics, where there is a lack of data and the use of equations originally developed for temperate systems may be inappropriate. We calculated two widely used TSIs for temperate lakes (TSI_temp) or tropical reservoirs (TSI_trop) and explored the deviations among TSI components in Brazilian reservoirs. When applied to our tropical/subtropical reservoirs, the TSI_temp provided a conservative approach, with lower limits anticipating increasing trophic state classification. TSI components for Chl-a and SDD significantly deviated for both sets of equations, and these discrepancies were related to turbidity, water temperature, and cyanobacterial biomass. For TSI_temp, but not for TSI_trop, TSI values in relation to Chl-a and TP were also significantly different. All such deviations have important management implications especially when Chl-a, TP, and SDD are averaged in a single TSI, representing loss of information and less useful trophic state classifications. Our results demonstrate that tropical water bodies may respond to drivers of eutrophication differently than temperate systems, highlighting the need for more data to better inform management of these understudied ecosystems. As managers collect data from more tropical water bodies, regional models may offer even better understanding of factors influencing trophic state.