Decay of sewage-associated bacterial communities in fresh and marine environmental waters and sediment

Invisible threat: Marine suspended particles mediate delayed decay of antibiotic resistome in coastal effluents

Suspended particles are recognized as hotspots of antibiotic resistance genes (ARGs) in coastal waters. However, the dynamics of ARGs associated with suspended particles during sewage discharge into coastal environments remain poorly understood. This study simulated sewage influx into coastal waters using microcosms to investigate the decay dynamics of particle-associated (PA) and free-living (FL) ARGs. Results showed that four ARGs, including two sulfonamide resistance genes (sul1 and sul2) and two tetracycline resistance genes (tetB and tetG), exhibited significantly lower decay rates in the PA fraction than in the FL fraction. Specifically, bacterial decay (k = 0.96 day⁻¹) and horizontal gene transfer decay (k = 0.62 day⁻¹) were both slower in the PA fraction compared to the FL fraction (1.56 day⁻¹ and 1.98 day⁻¹, respectively). These results indicated that suspended particles slow down the decay of ARGs. Microbial community analysis revealed approximately 80 % similarity between sewage and seawater at day 0, but a marked increase in unique bacterial genera and unknown-source taxa was observed at day 15. These results suggest that sewage discharge rapidly alters the composition of native seawater communities. Furthermore, suspended particles harbored higher abundances of unknown-source bacteria and displayed stronger bacterial community interactions than the surrounding water. These findings advance our understanding of ARG persistence and microbial community dynamics, offering critical insights for understanding ARGs dissemination from wastewater discharge.

Engineering Useful Microbial Species for Pharmaceutical Applications

Microbial engineering has made a significant breakthrough in pharmaceutical biotechnology, greatly expanding the production of biologically active compounds, therapeutic proteins, and novel drug candidates. Recent advancements in genetic engineering, synthetic biology, and adaptive evolution have contributed to the optimization of microbial strains for pharmaceutical applications, playing a crucial role in enhancing their productivity and stability. The CRISPR-Cas system is widely utilized as a precise genome modification tool, enabling the enhancement of metabolite biosynthesis and the activation of synthetic biological pathways. Additionally, synthetic biology approaches allow for the targeted design of microorganisms with improved metabolic efficiency and therapeutic potential, thereby accelerating the development of new pharmaceutical products. The integration of artificial intelligence (AI) and machine learning (ML) plays a vital role in further advancing microbial engineering by predicting metabolic network interactions, optimizing bioprocesses, and accelerating the drug discovery process. However, challenges such as the efficient optimization of metabolic pathways, ensuring sustainable industrial-scale production, and meeting international regulatory requirements remain critical barriers in the field. Furthermore, to mitigate potential risks, it is essential to develop stringent biocontainment strategies and implement appropriate regulatory oversight. This review comprehensively examines recent innovations in microbial engineering, analyzing key technological advancements, regulatory challenges, and future development perspectives.

Effects of chlorination on the survival of sewage bacteria in seawater microcosms

Chlorination is a commonly used disinfection method in sewage treatment process. However, resistant bacteria may survive chlorination and enter the receiving aquatic environment upon effluent discharge. There has been limited research on the effects of chlorination on bacterial survival in seawater. To address this knowledge gap, microcosm experiments were conducted to simulate the discharge of chlorinated effluents into coastal seawater. The results revealed that bacterial communities in seawater-based effluents survived better in seawater than those in freshwater-based effluents. High chlorine dosages could significantly reduce the viable bacterial populations and their chance of regrowth in seawater. Additionally, faecal indicator bacteria (FIB) that entered the viable but non-culturable (VBNC) state under chlorination tended to persist in the VBNC state without resuscitation during seawater incubation. Because of the prevalence of VBNC indicator bacteria, qPCR quantification of FIB was more effective than conventional culture-based methods in tracing viable pathogenic chlorine-resistant bacteria, although the correlation strength varied depending on the type of effluent. This study sheds light on how chlorine dosages and the intrinsic properties of effluents affect bacterial survival in seawater and highlights the potential and limitations of using FIB in monitoring the health risks associated with the discharge of chlorinated effluents.

Advances in machine learning-based bacteria analysis for forensic identification: identity, ethnicity, and site of occurrence

When faced with an unidentified body, identifying the victim can be challenging, particularly if physical characteristics are obscured or masked. In recent years, microbiological analysis in forensic science has emerged as a cutting-edge technology. It not only exhibits individual specificity, distinguishing different human biotraces from various sites of occurrence (e.g., gastrointestinal, oral, skin, respiratory, and genitourinary tracts), each hosting distinct bacterial species, but also offers insights into the accident's location and the surrounding environment. The integration of machine learning with microbiomics provides a substantial improvement in classifying bacterial species compares to traditional sequencing techniques. This review discusses the use of machine learning algorithms such as RF, SVM, ANN, DNN, regression, and BN for the detection and identification of various bacteria, including Bacillus anthracis, Acetobacter aceti, Staphylococcus aureus, and Streptococcus, among others. Deep leaning techniques, such as Convolutional Neural Networks (CNN) models and derivatives, are also employed to predict the victim's age, gender, lifestyle, and racial characteristics. It is anticipated that big data analytics and artificial intelligence will play a pivotal role in advancing forensic microbiology in the future.

Persistence of human- and cattle-associated Bacteroidales and mitochondrial DNA markers in freshwater mesocosms

Accurate identification of the origins of non-point source pollution is essential for the effective control of fecal pollution. Host-associated Bacteroidales and mitochondrial DNA (mtDNA) markers have been developed to identify the sources of human and cattle fecal pollution. However, the differences in persistence between these two types of markers under different environmental conditions are still poorly understood. Here, we conducted mesocosm experiments to investigate the influence of indigenous microbiota and nutrients on the decay of Bacteroidales and mtDNA markers associated with humans and cattle. Raw sewage or cattle feces were inoculated into mesocosms containing natural eutrophic water, sterile eutrophic water or artificial freshwater. The Bacteroidales markers HF183 (human) and CowM3 (cattle) and mtDNA markers HcytB (human) and QMIBo (cattle) were quantified using the quantitative polymerase chain reaction (qPCR) assays. All markers but HF183 decreased the fastest in the presence of indigenous microbiota. Nutrients caused a decrease in the persistence of HF183; however, no significant nutrient effects were observed for HcytB, CowM3, and QMIBo. The time to reach one log reduction (T90) for HF183 and HcytB was similar; CowM3 reached T90 earlier than QMIBo in all the treatments but eutrophic water. E. coli persisted longer than both Bacteroidales and mtDNA markers in the mesocosms regardless of inoculum type. Additionally, 16S rRNA gene amplicon sequencing was used to determine the changes in bacterial communities accompanying the marker decay. Analysis using the SourceTracker software showed that bacterial communities in the mesocosms became more dissimilar to those in the corresponding inoculants over time. Our results indicate that environmental factors are important determinants of genetic markers' persistence, but their impact can vary depending on the genetic markers. The cattle Bacteroidales markers may be more suitable for determining recent fecal contamination than cattle mtDNA.

Decay of four enteric pathogens and implications to wastewater-based epidemiology: Effects of temperature and wastewater dilutions

Measurement of pathogens in raw wastewater from a population within certain sewer catchments can provide quantitative information on public health status within the sampled urban area. This so-called wastewater-based epidemiology (WBE) approach has the potential of becoming a powerful tool to monitor pathogen circulation and support timely intervention during outbreaks. However, many WBE studies failed to account for the pathogen decay during wastewater transportation in back calculating the disease prevalence. Various sewer process factors, including water temperature and infiltration/inflow, can lead to the variation of pathogen decay rates. This paper firstly reviewed the effects of temperature and types of water, i.e., wastewater, freshwater, and saline water, on the decay of four selected enteric pathogens, i.e., Campylobacter, Salmonella, Norovirus, and Adenovirus. To elucidate the importance of the pathogen decay rates (measured by culture and molecular methods) to WBE, a sensitivity analysis was conducted on the back-calculation equation for infection prevalence with decay rates collected from published literature. It was found that WBE back-calculation is more sensitive to decay rates under the condition of high wastewater temperature (i.e., over 25 °C) or if wastewater is diluted by saline water (i.e., sewer infiltration or use of seawater as an alternative source of freshwater constituting around 1/3 household water demand in some cities). Stormwater dilution of domestic wastewater (i.e., sewer inflow might achieve 10 times volumetric dilution) was shown to play a role in increasing the sensitivity of WBE back-calculation to bacterial pathogens, but not viral pathogens. Hence, WBE back-calculation in real sewers should account for in-sewer decay of specific pathogen species under different wastewater temperatures and dilutions. Overall, this review contributes to a better understanding of pathogen decay in wastewater which can lead to improved accuracy of WBE back-calculation.

A Combined Digital PCR and Next Generation DNA-Sequencing Based Approach for Tracking Nearshore Pollutant Dynamics Along the Southwest United States/Mexico Border

Ocean currents, multiple fecal bacteria input sources, and jurisdictional boundaries can complicate pollution source tracking and associated mitigation and management efforts within the nearshore coastal environment. In this study, multiple microbial source tracking tools were employed to characterize the impact and reach of an ocean wastewater treatment facility discharge in Mexico northward along the coast and across the Southwest United States- Mexico Border. Water samples were evaluated for fecal indicator bacteria (FIB), Enterococcus by culture-based methods, and human-associated genetic marker (HF183) and Enterococcus by droplet digital polymerase chain reaction (ddPCR). In addition, 16S rRNA gene sequence analysis was performed and the SourceTracker algorithm was used to characterize the bacterial community of the wastewater treatment plume and its contribution to beach waters. Sampling dates were chosen based on ocean conditions associated with northern currents. Evidence of a gradient in human fecal pollution that extended north from the wastewater discharge across the United States/Mexico border from the point source was observed using human-associated genetic markers and microbial community analysis. The spatial extent of fecal contamination observed was largely dependent on swell and ocean conditions. These findings demonstrate the utility of a combination of molecular tools for understanding and tracking specific pollutant sources in dynamic coastal water environments.

Microbial Find, Inform, and Test Model for Identifying Spatially Distributed Contamination Sources: Framework Foundation and Demonstration of Ruminant Bacteroides Abundance in River Sediments

Microbial pollution in rivers poses known ecological and health risks, yet causal and mechanistic linkages to sources remain difficult to establish. Host-associated microbial source tracking (MST) markers help to assess the microbial risks by linking hosts to contamination but do not identify the source locations. Land-use regression (LUR) models have been used to screen the source locations using spatial predictors but could be improved by characterizing transport (i.e., hauling, decay overland, and downstream). We introduce the microbial Find, Inform, and Test (FIT) framework, which expands previous LUR approaches and develops novel spatial predictor models to characterize the transported contributions. We applied FIT to characterize the sources of BoBac, a ruminant Bacteroides MST marker, quantified in riverbed sediment samples from Kewaunee County, Wisconsin. A 1 standard deviation increase in contributions from land-applied manure hauled from animal feeding operations (AFOs) was associated with a 77% (p-value <0.05) increase in the relative abundance of ruminant Bacteroides (BoBac-copies-per-16S-rRNA-copies) in the sediment. This is the first work finding an association between the upstream land-applied manure and the offsite bovine-associated fecal markers. These findings have implications for the sediment as a reservoir for microbial pollution associated with AFOs (e.g., pathogens and antibiotic-resistant bacteria). This framework and application advance statistical analysis in MST and water quality modeling more broadly.

Enhanced insights from human and animal host-associated molecular marker genes in a freshwater lake receiving wet weather overflows

This study investigated the magnitude of wet weather overflow (WWO)-driven sewage pollution in an urban lake (Lake Parramatta) located in Sydney, New South Wales, Australia. Water samples were collected during a dry weather period and after two storm events, and tested for a range of novel and established sewage- [Bacteroides HF183, crAssphage CPQ_056 and pepper mild mottle virus (PMMoV)] and animal feces-associated (Bacteroides BacCan-UCD, cowM2 and Helicobacter spp. associated GFD) microbial source tracking marker genes along with the enumeration of culturable fecal indicator bacteria (FIB), namely Escherichia coli (E. coli) and Enterococcus spp. The magnitude of general and source-specific fecal pollution was low in water samples collected during dry weather compared to storm events. The levels of HF183, crAssphage and PMMoV in water samples collected during storm events were as high as 6.39, 6.33 and 5.27 log10 GC/L of water, respectively. Moderate to strong positive correlations were observed among the quantitative occurrence of sewage-associated marker genes. The concentrations of HF183 and PMMoV in most storm water samples exceeded the risk benchmark threshold values established in the literature for primary contact recreators. None of the samples tested was positive for the cowM2 (cow) marker gene, while BacCan-UCD (dog) and GFD (avian) animal-associated markers were sporadically detected in water samples collected from both dry weather and storm events. Based on the results, the ongoing advice that swimming should be avoided for several days after storm events appears appropriate. Further research to determine the decay rates of sewage-associated marker genes in relation to each other and enteric viruses would help refine current advice. Microbial source tracking approaches employed in this study provided insights into sources of contamination over currently used FIB.

The response of dominant and rare taxa for fungal diversity within different root environments to the cultivation of Bt and conventional cotton varieties

BACKGROUND

Bacillus thuringiensis (Bt) crops have been cultivated at a large scale over the past several decades, which have raised concern about unintended effects on natural environments. Microbial communities typically contain numerous rare taxa that make up the majority of community populations. However, the response of dominant and rare taxa for fungal diversity to the different root environments of Bt plants remains unclear.

RESULTS

We quantified fungal population sizes and community composition via quantitative PCR of ITS genes and 18S rRNA gene sequencing of, respectively, that were associated with Bt and conventional cotton variety rhizosphere soils from different plant growth stages. qPCR analyses indicated that fungal abundances reached their peak at the seedling stage and that the taproots and lateral root rhizospheres of the Bt cotton SGK321 were significantly different. However, no significant differences in population sizes were detected between the same root zones from Bt and the conventional cotton varieties. The overall patterns of fungal genera abundances followed that of the dominant genera, whereas overall patterns of fungal genera richness followed those of the rare genera. These results suggest that the dominant and rare taxa play different roles in the maintenance of rhizosphere microhabitat ecosystems. Cluster analyses indicated a separation of fungal communities based on the lateral roots or taproots from the three cotton varieties at the seedling stage, suggesting that root microhabitats had marked effects on fungal community composition. Redundancy analyses indicated that pH was more correlated to soil fungal community composition than Bt protein content.

CONCLUSIONS

In conclusion, these results indicate that dominant and rare fungal taxa differentially contribute to community dynamics in different root microhabitats of both Bt and conventional cotton varieties. Moreover, these results showed that the rhizosphere fungal community of Bt cotton did not respond significantly to the presence of Bt protein when compared to the two conventional cotton varieties.