Bacteroides spp. and traditional fecal indicator bacteria in water quality assessment - An integrated approach for hydric resources management in urban centers

Alteration of bacterial community composition in the sediments of an urban artificial river caused by sewage discharge

Background

Urbanization has an ecological and evolutionary effect on urban microorganisms. Microorganisms are fundamental to ecosystem functions, such as global biogeochemical cycles, biodegradation and biotransformation of pollutants, and restoration and maintenance of ecosystems. Changes in microbial communities can disrupt these essential processes, leading to imbalances within ecosystems. Studying the impact of human activities on urban microbes is critical to protecting the environment, human health, and overall urban sustainability.

Methods

In this study, bacterial communities in the sediments of an urban artificial river were profiled by sequencing the 16S rRNA V3-V4 region. The samples collected from the eastern side of the Jiusha River were designated as the JHE group and were marked by persistent urban sewage discharges. The samples collected on the western side of the Jiusha River were categorized as the JHW group for comparative analysis.

Results

The calculated alpha diversity indices indicated that the bacterial community in the JHW group exhibited greater species diversity and evenness than that of the JHE group. Proteobacteria was the most dominant phylum between the two groups, followed by Bacteroidota. The relative abundance of Proteobacteria and Bacteroidota accumulated in the JHE group was higher than in the JHW group. Therefore, the estimated biomarkers in the JHE group were divided evenly between Proteobacteria and Bacteroidota, whereas the biomarkers in the JHW group mainly belonged to Proteobacteria. The Sulfuricurvum, MND1, and Thiobacillus genus were the major contributors to differences between the two groups. In contrast to JHW, JHE exhibited higher enzyme abundances related to hydrolases, oxidoreductases, and transferases, along with a prevalence of pathways associated with carbohydrate, energy, and amino acid metabolisms. Our study highlights the impact of human-induced water pollution on microorganisms in urban environments.

Identification of fecal contamination sources of groundwater in rural areas of Vhembe District Municipality, Limpopo Province, South Africa

Groundwater is a valuable source of drinking water worldwide, recognized as an improved drinking water source. However, on-site sanitation systems may put groundwater at risk of fecal contamination. In the present study, two approaches were used to ascertain the sources of fecal contamination in groundwater used by communities of the Vhembe District Municipality. Overall, 87.5% of boreholes (n = 70) in the wet and 72.5% in the dry season were contaminated with Escherichia coli, and septic tank (n = 18) wastewaters displayed up to 104  cfu/mL E. coli. Host-specific Bacteroidales quantitative polymerase chain reaction (qPCR) assays established the presence of human (BacHum and HF183) and animal (Cytb, BacCan, and Pig-2Bac) genetic markers in groundwater from 15.7% of boreholes (wet) and 10% of boreholes (dry). No strong associations were founded between culturable E. coli counts and the presence/absence of marker genes for all the markers except for Cytb marker, which showed a weak significant correlation (r = 0.217; p = <0.01) between E. coli and the Cytb marker under dry seasonal conditions. Human markers and Cytb were present in the household septic tank wastewater samples. Significant differences in marker genes distribution in wastewater were observed using the Chi-squared test: HF183 (p = <0.001) and BacHum (p = <0.001). Overall, no association was recorded between markers in groundwater and in wastewater for 18 households' septic tanks. A combined culturable E. coli and host-specific Bacteroidales qPCR assays remain an appropriate approach for the identification of fecal contamination of groundwater. PRACTITIONER POINTS: Households primarily used private boreholes for drinking water, as a primary source. Most households used on-site sanitation systems, including ventilated improved pit latrines and flush toilets connected to septic tanks. Escherichia coli was detected in groundwater, and the sources of fecal contamination were humans and animals (pigs, dogs, and chickens). The presence of human and animal markers in groundwater suggests that humans and animals are liable for fecal contamination. Fecal contamination in drinking water sources poses a significant concern due to pathogenic microorganisms posing potential human health risks.

Correlation Between Microbial Community and Hatching Failure in Loggerhead Sea Turtle Caretta caretta

Microbial communities provide essential information about host ecology and could be helpful as a tool to improve species conservation efforts. However, microbes can also infect and compromise the host development process and viability. Caretta caretta is the most widespread marine turtle species in the Mediterranean basin and is the only species of sea turtle nesting along the Italian coasts. Little is known about the microbiota composition of the nest of sea turtles and its correlation with hatching failures. In this study, the microbial composition of two nests of C. caretta featuring different rates of hatching success from a nesting beach in Lampedusa (Italy) was analyzed and compared. The bacterial community was determined using culture-dependent methods and next-generation sequencing based on 16S rRNA gene metabarcoding analysis. Our results showed five dominant bacterial phyla (Proteobacteria, Bacteroidetes, Actinobacteria, Verrucomicrobia, and Firmicutes) and indicated different bacterial families (Pseudomonadaceae and Brucellaceae) as likely causes of hatching failures. Besides, our findings demonstrated the nests' active role in modulating the sand's bacterial communities. This study suggests microbiological analysis could be a valuable tool in monitoring nests to take preventive actions and reduce hatching failures.

Bacterial bioindicators enable biological status classification along the continental Danube river

Despite the importance of bacteria in aquatic ecosystems and their predictable diversity patterns across space and time, biomonitoring tools for status assessment relying on these organisms are widely lacking. This is partly due to insufficient data and models to identify reliable microbial predictors. Here, we show metabarcoding in combination with multivariate statistics and machine learning allows to identify bacterial bioindicators for existing biological status classification systems. Bacterial beta-diversity dynamics follow environmental gradients and the observed associations highlight potential bioindicators for ecological outcomes. Spatio-temporal links spanning the microbial communities along the river allow accurate prediction of downstream biological status from upstream information. Network analysis on amplicon sequence veariants identify as good indicators genera Fluviicola, Acinetobacter, Flavobacterium, and Rhodoluna, and reveal informational redundancy among taxa, which coincides with taxonomic relatedness. The redundancy among bacterial bioindicators reveals mutually exclusive taxa, which allow accurate biological status modeling using as few as 2-3 amplicon sequence variants. As such our models show that using a few bacterial amplicon sequence variants from globally distributed genera allows for biological status assessment along river systems.

Development of two microbial source tracking markers for detection of wastewater-associated Escherichia coli isolates

Escherichia coli has been used as an indicator of fecal pollution in environmental waters. However, its presence in environmental waters does not provide information on the source of water pollution. Identifying the source of water pollution is paramount to be able to effectively reduce contamination. The present study aimed to identify E. coli microbial source tracking (MST) markers that can be used to identify domestic wastewater contamination in environmental waters. We first analyzed wastewater E. coli genomes sequenced by us (n = 50) and RefSeq animal E. coli genomes of fecal origin (n = 82), and identified 144 candidate wastewater-associated marker genes. The sensitivity and specificity of the candidate marker genes were then assessed by screening the genes in 335 RefSeq wastewater E. coli genomes and 3318 RefSeq animal E. coli genomes. We finally identified two MST markers, namely W_nqrC and W_clsA_2, which could be used for detection of wastewater-associated E. coli isolates. These two markers showed higher performance than the previously developed human wastewater-associated E. coli markers H8 and H12. When used in combination, W_nqrC and W_clsA_2 showed specificity of 98.9 % and sensitivity of 25.7 %. PCR assays to detect W_nqrC and W_clsA_2 were also developed and validated. The developed PCR assays are potentially useful for detecting E. coli isolates of wastewater origin in environmental waters, though users should keep in mind that the sensitivity of these markers is not high. Further studies are needed to assess the applicability of the developed markers to a culture-independent approach.

Microbial Source Tracking as a Method of Determination of Beach Sand Contamination

Beach sand may act as a reservoir for numerous microorganisms, including enteric pathogens. Several of these pathogens originate in human or animal feces, which may pose a public health risk. In August 2019, high levels of fecal indicator bacteria (FIB) were detected in the sand of the Azorean beach Prainha, Terceira Island, Portugal. Remediation measures were promptly implemented, including sand removal and the spraying of chlorine to restore the sand quality. To determine the source of the fecal contamination, during the first campaign, supratidal sand samples were collected from several sites along the beach, followed by microbial source tracking (MST) analyses of Bacteroides marker genes for five animal species, including humans. Some of the sampling sites revealed the presence of marker genes from dogs, seagulls, and ruminants. Making use of the information on biological sources originating partially from dogs, the municipality enforced restrictive measures for dog-walking at the beach. Subsequent sampling campaigns detected low FIB contamination due to the mitigation and remediation measures that were undertaken. This is the first case study where the MST approach was used to determine the contamination sources in the supratidal sand of a coastal beach. Our results show that MST can be an essential tool to determine sources of fecal contamination in the sand. This study shows the importance of holistic management of beaches that should go beyond water quality monitoring for FIB, putting forth evidence for beach sand monitoring.

Campylobacter Species, Microbiological Source Tracking and Risk Assessment of Bacterial pathogens

Campylobacter species continue to remain critical pathogens of public health interest. They are responsible for approximately 500 million cases of gastroenteritis per year worldwide. Infection occurs through the consumption of contaminated food and water. Microbial risk assessment and source tracking are crucial epidemiological strategies to monitor the outbreak of campylobacteriosis effectively. Various methods have been proposed for microbial source tracking and risk assessment, most of which rely on conventional microbiological techniques such as detecting fecal indicator organisms and other novel microbial source tracking methods, including library-dependent microbial source tracking and library-independent source tracking approaches. However, both the traditional and novel methods have their setbacks. For example, while the conventional techniques are associated with a poor correlation between indicator organism and pathogen presence, on the other hand, it is impractical to interpret qPCR-generated markers to establish the exact human health risks even though it can give information regarding the potential source and relative human risk. Therefore, this article provides up-to-date information on campylobacteriosis, various approaches for source attribution, and risk assessment of bacterial pathogens, including next-generation sequencing approaches such as shotgun metagenomics, which effectively answer the questions of potential pathogens are there and in what quantities.

Identification of new eligible indicator organisms for combined sewer overflow via 16S rRNA gene amplicon sequencing in Kanda River, Tokyo

Fecal indicator bacteria (FIB) are commonly used to evaluate the pollution impact of combined sewer overflows (CSOs) in urban rivers. Although water quality assessment with FIB has a long tradition, recent studies demonstrated that FIB have a low correlation with pathogens and therefore are not accurate enough for the assessment of potential human hazards in water. Consequently, new eligible and more specific indicators have to be identified, which was done in this study via sequencing of genetic markers from total community DNA. To identify potential microbiome-based indicators, microbial communities in samples from an urban river in Tokyo under different climatic conditions (dry and rainy) were compared with the influent and effluent of three domestic wastewater treatment plants (WWTPs) by analyzing 16 S rRNA gene amplicon libraries. In the first part of this study, physicochemical parameters and FIB quantification with selective culture techniques facilitated the identification of samples contaminated with CSO, sewage, or both. This allowed the grouping of samples into CSO-contaminated and non-contaminated samples, an essential step prior to the microbiome comparison between samples. Increased turbidity, ammonia concentrations, and E. coli [up to (9.37 ± 0.95) × 10² CFU/mL after 11.5 mm of rainfall] were observed in CSO-contaminated river samples. Comparison of dry weather (including WWTP samples) and rainy weather samples showed a reduction in microbial diversity in CSO-contaminated samples. Furthermore, the results of this study suggest Bacteroides spp. as a novel indicator of sewage pollution in surface waters.