Dataset Information

High-Throughput Detection of Bacterial Community and Its Drug-Resistance Profiling From Local Reclaimed Wastewater Plants.

ABSTRACT: Treated wastewater from reclaimed facilities (WWTP) has become a reusable source for a variety of applications, such as agricultural irrigation. However, it is also a potential reservoir of clinically-relevant multidrug resistant (MDR) pathogens, including ESKAPE (Enterococcus faecium and Streptococcus surrogates, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species along with the emerging nosocomial Escherichia strains). This study was performed to decipher the bacterial community structure through Illumina high throughput 16S rRNA gene sequencing, and to determine the resistance profile using the Sensititre antimicrobial susceptibility test (AST) conforming to clinical lab standards (NCCLS). Out of 1747 bacterial strains detected from wastewater influent and effluent, Pseudomonas was the most predominant genus related to ESKAPE in influent, with sequence reads corresponding to 21.356%, followed by Streptococcus (6.445%), Acinetobacter (0.968%), Enterococcus (0.063%), Klebsiella (0.038%), Escherichia (0.028%) and Staphylococcus (0.004%). Despite the different treatment methods used, the effluent still revealed the presence of some Pseudomonas strains (0.066%), and a wide range of gram-positive cocci, including Staphylococcus (0.194%), Streptococcus (0.63%) and Enterococcus (0.037%), in addition to gram-negative Acinetobacter (0.736%), Klebsiella (0.1%), and Escherichia sub-species (0.811%). The AST results indicated that the strains Escherichia along with Klebsiella and Acinetobacter, isolated from the effluent, displayed resistance to 11 antibiotics, while Pseudomonas was resistant to 7 antibiotics, and Streptococcus along with Staphylococcus were resistant to 9 antibiotics. Results herein, proved the existence of some nosocomial MDR pathogens, known for ESKAPE, with potential drug resistance transfer to the non-pathogen microbes, requiring targeted remediation.

SUBMITTER: Limayem A

PROVIDER: S-EPMC6787911 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BACKGROUND:Currently, the effect of the bacterial community on cast iron corrosion process does not reach consensus. Moreover, some studies have produced contrasting results, suggesting that bacteria can either accelerate or inhibit corrosion. RESULTS:The long-term effects of the bacterial community on cast iron corrosion in reclaimed wastewater distribution systems were investigated from both spatial (yellow layer vs. black layer) and temporal (1-year dynamic process) dimensions of the iron coupon-reclaimed wastewater microcosm using high-throughput sequencing and flow cytometry approaches. Cast iron coupons in the NONdisinfection and UVdisinfection reactors suffered more severe corrosion than did those in the NaClOdisinfection reactor. The bacterial community significantly promoted cast iron corrosion, which was quantified for the first time in the practical reclaimed wastewater and found to account for at least 30.5% ± 9.7% of the total weight loss. The partition of yellow and black layers of cast iron corrosion provided more accurate information on morphology and crystal structures for corrosion scales. The black layer was dense, and the particles looked fusiform, while the yellow layer was loose, and the particles were ellipse or spherical. Goethite was the predominant crystalline phase in black layers, while corrosion products mainly existed as an amorphous phase in yellow layers. The bacterial community compositions of black layers were distinctly separated from yellow layers regardless of disinfection methods. The NONdisinfection and UVdisinfection reactors had a more similar microbial composition and variation tendency for the same layer type than did the NaClOdisinfection reactor. Biofilm development can be divided into the initial start-up stage, mid-term development stage, and terminal stable stage. In total, 12 potential functional genera were selected to establish a cycle model for Fe, N, and S metabolism. Desulfovibrio was considered to accelerate the transfer of Fe0 to Fe2+ and speed up weight loss. CONCLUSION:The long-term effect of disinfection processes on corrosion behaviors of cast iron in reclaimed wastewater distribution systems and the hidden mechanisms were deciphered for the first time. This study established a cycle model for Fe, N, and S metabolism that involved 12 functional genera and discovered the significant contribution of Desulfovibrio in promoting corrosion.

Project description:Water recycling continues to expand across the United States, from areas that have access to advanced, potable-level treated reclaimed water, to those having access only to reclaimed water treated at conventional municipal wastewater treatment plants. This expansion makes it important to further characterize the microbial quality of these conventionally-treated water sources. Therefore, we used 16S rRNA gene sequencing to characterize total bacterial communities present in differentially-treated wastewater and reclaimed water (n = 67 samples) from four U.S. wastewater treatment plants and one associated spray irrigation site conducting on-site ultraviolet treatment and open-air storage. The number of observed operational taxonomic units was significantly lower (p < 0.01) in effluent, compared to influent, after conventional treatment. Effluent community structure was influenced more by treatment method than by influent community structure. The abundance of Legionella spp. increased as treatment progressed in one treatment plant that performed chlorination and in another that seasonally chlorinated. Overall, the alpha-diversity of bacterial communities in reclaimed water decreased (p < 0.01) during wastewater treatment and spray irrigation site ultraviolet treatment (p < 0.01), but increased (p < 0.01) after open-air storage at the spray irrigation site. The abundance of Legionella spp. was higher at the sprinkler system pumphouse at the spray irrigation site than in the influent from the treatment plant supplying the site. Legionella pneumophila was detected in conventionally treated effluent samples and in samples collected after ultraviolet treatment at the spray irrigation site, while Legionella feeleii persisted throughout on-site treatment at the spray irrigation site, and, along with Mycobacterium gordonae, was also detected at the sprinkler system pumphouse at the spray irrigation site. These data could inform the development of future treatment technologies and reuse guidelines that address a broader assemblage of the bacterial community of reclaimed water, resulting in reuse practices that may be more protective of public health.

Project description:Mining and other industrial activities worldwide have resulted in Se-enriched surface soils, which pose risks to human and environmental health. Although not well studied, microbial activity can alter Se bioavailability and distribution, even in oxic environments. We used high-throughput sequencing to profile bacterial and fungal communities inhabiting mine soils in southeastern Idaho, comparing mined and unmined locations within two reclaimed phosphate mine areas containing various Se concentrations. The goal was to determine whether microbial communities differed in (i) different mines, (ii) mined areas compared to unmined areas, and (iii) various soil Se concentrations. Though reclamation occurred 20 to 30 years ago, microbial community structures in mined soils were significantly altered compared to unmined soils, suggesting persistent mining-related impacts on soil processes. Additionally, operational taxonomic unit with a 97% sequence similarity cutoff (OTU0.03) richness and diversity were significantly diminished with increasing Se, though not with other geochemical parameters, suggesting that Se contamination shapes communities in favor of Se-tolerant microorganisms. Two bacterial phyla, Actinobacteria and Gemmatimonadetes, were enriched in high-Se soils, while for fungi, Ascomycota dominated all soils regardless of Se concentration. Combining diversity analyses and taxonomic patterns enables us to move toward connecting physiological function of microbial groups to Se biogeochemical cycling in oxic soil environments.IMPORTANCE Selenium contamination in natural environments is of great concern globally, and microbial processes are known to mediate Se transformations. Such transformations alter Se mobility, bioavailability, and toxicity, which can amplify or mitigate Se pollution. To date, nearly all studies investigating Se-microbe interactions have used culture-based approaches with anaerobic bacteria despite growing knowledge that (i) aerobic Se transformations can occur, (ii) such transformations can be mediated by microorganisms other than bacteria, and (iii) microbial community dynamics, rather than individual organismal activities, are important for metal(loid) cycling in natural environments. We examined bacterial and fungal communities in Se-contaminated reclaimed mine soils and found significant declines in diversity at high Se concentrations. Additionally, we identified specific taxonomic groups that tolerate excess Se and may be useful for bioremediation purposes. These patterns were similar across mines of different ages, suggesting that microbial community impacts may persist long after physicochemical parameters indicate complete site recovery.

Project description:Large-scale wastewater surveillance has the ability to greatly augment the tracking of infection dynamics especially in communities where the prevalence rates far exceed the testing capacity. However, current methods for viral detection in wastewater are severely lacking in terms of scaling up for high throughput. In the present study, we employed an automated magnetic-bead-based concentration approach for viral detection in sewage that can effectively be scaled up for processing 24 samples in a single 40-min run. The method compared favorably to conventionally used methods for viral wastewater concentrations with higher recovery efficiencies from input sample volumes as low as 10 ml and can enable the processing of over 100 wastewater samples in a day. The sensitivity of the high-throughput protocol was shown to detect 1 asymptomatic individual in a building of 415 residents. Using the high-throughput pipeline, samples from the influent stream of the primary wastewater treatment plant of San Diego County (serving 2.3 million residents) were processed for a period of 13 weeks. Wastewater estimates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral genome copies in raw untreated wastewater correlated strongly with clinically reported cases by the county, and when used alongside past reported case numbers and temporal information in an autoregressive integrated moving average (ARIMA) model enabled prediction of new reported cases up to 3 weeks in advance. Taken together, the results show that the high-throughput surveillance could greatly ameliorate comprehensive community prevalence assessments by providing robust, rapid estimates.IMPORTANCE Wastewater monitoring has a lot of potential for revealing coronavirus disease 2019 (COVID-19) outbreaks before they happen because the virus is found in the wastewater before people have clinical symptoms. However, application of wastewater-based surveillance has been limited by long processing times specifically at the concentration step. Here we introduce a much faster method of processing the samples and show its robustness by demonstrating direct comparisons with existing methods and showing that we can predict cases in San Diego by a week with excellent accuracy, and 3 weeks with fair accuracy, using city sewage. The automated viral concentration method will greatly alleviate the major bottleneck in wastewater processing by reducing the turnaround time during epidemics.

Dataset Information

High-Throughput Detection of Bacterial Community and Its Drug-Resistance Profiling From Local Reclaimed Wastewater Plants.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets