Assessing human-specific CrAssphage recovery after acidification-filtration concentrating method in environmental water

Status and future trends in wastewater management strategies using artificial intelligence and machine learning techniques

The two main things needed to fulfill the world's impending need for water in the face of the widespread water crisis are collecting water and recycling. To do this, the present study has placed a greater focus on water management strategies used in a variety of contexts areas. To distribute water effectively, save it, and satisfy water quality requirements for a variety of uses, it is imperative to apply intelligent water management mechanisms while keeping in mind the population density index. The present review unveiled the latest trends in water and wastewater recycling, utilizing several Artificial Intelligence (AI) and machine learning (ML) techniques for distribution, rainfall collection, and control of irrigation models. The data collected for these purposes are unique and comes in different forms. An efficient water management system could be developed with the use of AI, Deep Learning (DL), and the Internet of Things (IoT) structure. This study has investigated several water management methodologies using AI, DL and IoT with case studies and sample statistical assessment, to provide an efficient framework for water management.

A systematic review of industrial wastewater management: Evaluating challenges and enablers

The study provides a systematic literature review (SLR) encompassing industrial wastewater management research from the past decade, examining enablers, challenges, and prevailing practices. Originating from manufacturing, energy production, and diverse industrial processes, industrial wastewater's handling is critical due to its potential to impact the environment and public health. The research aims to comprehend the current state of industrial wastewater management, pinpoint gaps, and outline future research prospects. The SLR methodology involves scouring the Scopus database, yielding an initial pool of 253 articles. Refinement via search code leaves 101 articles, followed by abstract screening that reduces articles to 79, and finally 66 well-focused articles left for thorough full-text examination. Results underscore the significance of regulatory frameworks, technological innovation, and sustainability considerations as cornerstones for effective wastewater management. However, substantial impediments like; inadequate infrastructure, resource constraints and the necessity for stakeholder collaboration still exist. The study highlights emerging research domains, exemplified by advanced technologies like nanotechnology and bioremediation, alongside the pivotal role of circular economy principles in wastewater management. The SLR offers an exhaustive view of contemporary industrial wastewater management, accentuating the imperative of an all-encompassing approach that integrates regulatory, technological, and sustainability facets. Notably, the research identifies gaps and opportunities for forthcoming exploration, advocating for interdisciplinary research and intensified stakeholder collaboration. The study's insights cater to policymakers, practitioners, and researchers, equipping them to address the challenges and capitalize on prospects in industrial wastewater management effectively.

Meta-analysis of microbial source tracking for the identification of fecal contamination in aquatic environments based on data-mining

Microbial source tracking (MST) technology represents an innovative approach employed to trace fecal contamination in environmental water systems. The performance of primers may be affected by amplification techniques, target primer categories, and regional differences. To investigate the influence of these factors on primer recognition performance, a meta-analysis was conducted on the application of MST in water environments using three databases: Web of Science, Scopus, and PubMed (n = 2291). After data screening, 46 studies were included in the final analysis. The investigation encompassed Polymerase Chain Reaction (PCR)/quantitative PCR (qPCR) methodologies, dye-based (SYBR)/probe-based (TaqMan) techniques, and geographical differences of a human host-specific (HF183) primer and other 21 additional primers. The results indicated that the primers analyzed were capable of differentiating host specificity to a certain degree. Nonetheless, by comparing sensitivity and specificity outcomes, it was observed that virus-based primers exhibited superior specificity and recognition capacity, as well as a stronger correlation with human pathogenicity in water environments compared to bacteria-based primers. This finding highlights an important direction for future advancements. Moreover, within the same category, qPCR did not demonstrate significant benefits over conventional PCR amplification methods. In comparing dye-based and probe-based techniques, it was revealed that the probe-based method's advantage lay primarily in specificity, which may be associated with the increased propensity of dye-based methods to produce false positives. Furthermore, the heterogeneity of the HF183 primer was not detected in China, Canada, and Singapore respectively, indicating a low likelihood of regional differences. The variation among the 21 other primers may be attributable to regional differences, sample sources, detection techniques, or alternative factors. Finally, we identified that economic factors, climatic conditions, and geographical distribution significantly influence primer performance.

Persisting antibiotic resistance gene pollution and its association with human sewage sources in tropical marine beach waters

Antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) are pollutants of worldwide concern that threaten human health and ecosystems. Anthropogenic activities and wastewater could be ARB and ARG pollution sources; however, research on ARG abundance and microbial source tracking (MST) of contamination in tropical marine waters is limited. This study examined spatiotemporal variations of six ARGs (bla_NDM, bla_TEM, bla_VIM, mcr-1, sul1, and tetQ) against the widely used antibiotic groups and a class 1 integron-integrase gene (intI1) at two Thai tropical recreational beaches (n = 41). Correlations between ARGs and sewage-specific MST markers (i.e., crAssphage and human polyomaviruses [HPyVs]) and fecal indicator bacteria (i.e., total coliforms, fecal coliforms, and enterococci) were also investigated. Bla_TEM, intI1, sul1, and tetQ were ubiquitous at both beaches (85.4-100% detection rate); intI1 was the most abundant (3-6 orders in log₁₀ copies/100 mL), followed by bla_TEM (2-4 orders), sul1 (2-3 orders), and tetQ (2-4 orders). Bla_NDM was found in 7.3% (up to 4 orders), and no mcr-1 was detected. Interestingly, bla_VIM was prevalent at one beach (2-5 orders; n = 17), but found in only one sample at the other (4 orders). Temporal, but not spatial, differences were noticed; bla_TEM was at higher levels in the wet season. IntI1 correlated with sul1 and tetQ (Spearman's rho = 0.47-0.97), suggesting potential horizontal gene transfer. CrAssphage, but not HPyVs, correlated with intI1, sul1, and tetQ (Spearman's rho = 0.50-0.74). Higher numbers of ARGs tended to co-occur in samples with higher crAssphage concentrations, implying sewage contribution to the marine water, with a persisting ARG background. This study provides insight into the ARG pollution status of tropical coastal waters and suggests crAssphage as a proxy for ARG pollution, which could facilitate effective management policies to minimize ARG dissemination in marine environments.

Performance of viral and bacterial genetic markers for sewage pollution tracking in tropical Thailand

Identifying sewage contamination via microbial source tracking (MST) marker genes has proven useful for effective water quality management worldwide; however, performance evaluations for these marker genes in tropical areas are limited. Therefore, this research evaluated four human-associated MST marker genes (human polyomaviruses (JC and BK viruses [HPyVs]), bacteriophage crAssphage (CPQ_056), Lachnospiraceae Lachno3, and Bacteroides BacV6-21) for tracking sewage pollution in aquatic environments of Thailand. The viral marker genes, HPyV and crAssphage were highly sensitive and specific to sewage from onsite wastewater treatment plants (OWTPs; n = 19), with no cross-detection in 120 composite swine, cattle, chicken, duck, goat, sheep, and buffalo fecal samples. The bacterial marker genes, Lachno3 and BacV6-21, demonstrated high sensitivity but moderate specificity; however, using both markers could improve specificity to >0.80 (max value of 1.00). The most abundant markers in OWTP samples were Lachno3 and BacV6-21 (5.42-8.02 and nondetect-8.05 log₁₀ copies/100 mL), crAssphage (5.28-7.38 log₁₀ copies/100 mL), and HPyVs (3.66-6.53 log₁₀ copies/100 mL), respectively. Due to their increased specificity, the abundance of viral markers were further investigated in environmental waters, in which HPyVs showed greater levels (up to 4.33 log₁₀ copies/100 mL) and greater detection rates (92.7%) in two coastal beaches (n = 41) than crAssphage (up to 3.51 log₁₀ copies/100 mL and 56.1%). HPyVs were also found at slightly lower levels (up to 5.10 log₁₀ copies/100 mL), but at higher detection rates (92.6%), in a freshwater canal (n = 27) than crAssphage (up to 5.21 log₁₀ copies/100 mL and 88.9%). HPyVs and crAssphage marker genes were identified as highly sensitive and specific for tracking sewage pollution in aquatic environments of Thailand. This study underlines the importance of characterizing and validating MST markers in host groups and environmental waters before including them in a water quality management toolbox.

Effect of Quantitative Polymerase Chain Reaction Data Analysis Using Sample Amplification Efficiency on Microbial Source Tracking Assay Performance and Source Attribution

The widely used microbial source tracking (MST) technique, quantitative polymerase chain reaction (qPCR), quantifies host-specific gene abundance in polluted water to identify and prioritize contamination sources. This study characterized the effects of a qPCR data analysis using the sample PCR efficiencies (the LinRegPCR model) on gene abundance and compared them with the standard curve-based method (the mixed model). Five qPCR assays were evaluated: the universal GenBac3, human-specific HF183/BFDrev and CPQ_056, swine-specific Pig-2-Bac, and cattle-specific Bac3qPCR assays. The LinRegPCR model increased the low-copy amplification, especially in the HF183/BFDrev assay, thus lowering the specificity to 0.34. Up to 1.41 log₁₀ copies/g and 0.41 log₁₀ copies/100 mL differences were observed for composite fecal and sewage samples (n = 147) by the LinRegPCR approach, corresponding to an 18.2% increase and 6.4% decrease, respectively. Freshwater samples (n = 48) demonstrated a maximum of 1.95 log₁₀ copies/100 mL difference between the two models. Identical attributing sources by both models were shown in 54.55% of environmental samples; meanwhile, the LinRegPCR approach improved the inability to identify sources by the mixed model in 29.55% of the samples. This study emphasizes the need for a standardized data analysis protocol for qPCR MST assays for interlaboratory consistency and comparability.