Re-vitalizing wastewater: Nutrient recovery and carbon capture through microbe-algae synergy using omics-biology.

Increasing amounts of wastewater is the most pervasive and challenging environmental problem globally. Conventional treatment methods are costly and entail huge energy, carbon consumption and greenhouse gas emissions. Owing to their unique ability of carbon capturing and resource recovery, microalgae-microbiome based treatment is a potential approach and is widely used for carbon-neutral wastewater treatment. Microalgae-bacteria synergy (i.e., the functionally beneficial microbial synthetic communities) performs better and enhances carbon-sequestration and nutrient recovery from wastewater treatment plants. This review presents a comprehensive information regarding the potential of microalgae-microbiome as a sustainable agent for wastewater and discusses synergistic approaches for effective nutrient removal. Moreover, this review discusses, the role of omics-biology and Insilco approaches in unravelling and understanding the algae-microbe synergism and their response toward wastewater treatment. Finally, it discusses various microbiome engineering approaches for developing the effective microalgae-bacteria partners for carbon sequestration and nutrient recovery from wastewater, and summarizes future research perspectives on microalgae-microbiome based bioremediation.

Discerning the role of a site cation in ACoO3 perovskites for boosting Co3+/Co2+ redox cycle for pollutant degradation: DFT calculation, mechanism and toxicity evolution.

The degradation of persistent and refractory pollutants, particularly plastic and resins manufacturing wastewater, poses a significant challenge due to their high toxicity and high concentrations. This study developed a novel hybrid ACoO3 (A = La, Ce, Sr)/PMS perovskite system for the treatment of multicomponent (MCs; ACN, ACM and ACY) from synthetic resin manufacturing wastewater. Synthesized perovskites were characterized by various techniques i.e., BET, XRD, FESEM with EDAX, FTIR, TEM, XPS, EIS, and Tafel analysis. Perovskite LaCoO3 exhibited the highest degradation of MCs i.e., ACN (98.7%), ACM (86.3%), and ACY (56.4%), with consumption of PMS (95.2%) under the optimal operating conditions (LaCoO3 dose 0.8 g/L, PMS dose 2 g/L, pH 7.2 and reaction temperature 55 °C). The quantitative contribution (%) of reactive oxygen species (ROS) reveals that SO4•- are the dominating radical species, which contribute to ACN (58.3% for SO4•- radicals) and ACM degradation (46.4% for SO4•- radicals). The tafel plots and EIS spectra demonstrated that perovskites LaCoO3 have better charge transfer rates and more reactive sites that are favorable for PMS activation. Further, four major degradation pathways were proposed based on Fukui index calculations, as well as GC-MS characterization of intermediate byproducts. Based on a stability and reusability study, it was concluded that LaCoO3 perovskites are highly stable, and minimal cobalt leaching occurs (0.96 mg/L) after four cycles. The eco-toxicity assessment performed using QSAR model indicated that the byproducts of the LaCoO3/PMS system are non-toxic nature to common organism (i.e., fish, daphnids and green algae). In addition, the cost of the hybrid LaCoO3/PMS system in a single cycle was estimated to be $34.79 per cubic meter of resin wastewater.

Digitalization of phosphorous removal process in biological wastewater treatment systems: Challenges, and way forward.

Phosphorus in wastewater poses a significant environmental threat, leading to water pollution and eutrophication. However, it plays a crucial role in the water-energy-resource recovery-environment (WERE) nexus. Recovering Phosphorus from wastewater can close the phosphorus loop, supporting circular economy principles by reusing it as fertilizer or in industrial applications. Despite the recognized importance of phosphorus recovery, there is a lack of analysis of the cyber-physical framework concerning the WERE nexus. Advanced methods like automatic control, optimal process technologies, artificial intelligence (AI), and life cycle assessment (LCA) have emerged to enhance wastewater treatment plants (WWTPs) operations focusing on improving effluent quality, energy efficiency, resource recovery, and reducing greenhouse gas (GHG) emissions. Providing insights into implementing modeling and simulation platforms, control, and optimization systems for Phosphorus recovery in WERE (P-WERE) in WWTPs is extremely important in WWTPs. This review highlights the valuable applications of AI algorithms, such as machine learning, deep learning, and explainable AI, for predicting phosphorus (P) dynamics in WWTPs. It emphasizes the importance of using AI to analyze microbial communities and optimize WWTPs for different various objectives. Additionally, it discusses the benefits of integrating mechanistic and data-driven models into plant-wide frameworks, which can enhance GHG simulation and enable simultaneous nitrogen (N) and Phosphorus (P) removal. The review underscores the significance of prioritizing recovery actions to redirect Phosphorus from effluent to reusable products for future considerations.

Evaluating storage conditions and enhancement strategies on viral biomarker recovery for WBE applications.

Wastewater-based epidemiology (WBE) is a valuable disease surveillance tool. However, little is known on how factors such as transportation, storage, and wastewater characteristics influence the accuracy of the quantification methods. Hence, this study investigated the impact of storage temperatures and physicochemical characteristics of wastewater on SARS-CoV-2 and influenza A stability using droplet digital PCR. Additionally, strategies to enhance viral recovery were explored. Municipal influent wastewater stored between ±25 and -80 °C was assessed for a period of 84 days to determine viral degradation. Degradation up to 94.1% of influenza A and SARS-CoV-2 was observed in all samples with the highest at ±25 °C. Viral degradation was correlated to the changes in wastewater physicochemical characteristics. The low degradation observed of SARS-CoV-2 in the spiked pellets were indicative of viral adhesion to wastewater solids, which correlated with changes in pH. Ultrasonication frequencies ranging from 4 to 16 kHz, increased SARS-CoV-2 concentrations in the supernatant between 3.30 and 35.65%, indicating viral RNA attachment to wastewater solids. These results highlight the importance of additional pretreatment methods for maximizing RNA recovery from wastewater samples. Based on these findings, it was deduced that wastewater preservation studies are essential, and pretreatment should be included in the WBE methodology.

Applications of mathematical modelling for assessing microplastic transport and fate in water environments: a comparative review.

Microplastics in the environment are considered complex pollutants as they are chemical and corrosive-resistant, non-biodegradable and ubiquitous. These microplastics may act as vectors for the dissemination of other pollutants and the transmission of microorganisms into the water environment. The currently available literature reviews focus on analysing the occurrence, environmental effects and methods of microplastic detection, however lacking a wide-scale systematic review and classification of the mathematical microplastic modelling applications. Thus, the current review provides a global overview of the modelling methodologies used for microplastic transport and fate in water environments. This review consolidates, classifies and analyses the methods, model inputs and results of 61 microplastic modelling studies in the last decade (2012-2022). It thoroughly discusses their strengths, weaknesses and common gaps in their modelling framework. Five main modelling types were classified as follows: hydrodynamic, process-based, statistical, mass-balance and machine learning models. Further, categorisations based on the water environments, location and published year of these applications were also adopted. It is concluded that addressed modelling types resulted in relatively reliable outcomes, yet each modelling framework has its strengths and weaknesses. However, common issues were found such as inputs being unrealistically assumed, especially biological processes, and the lack of sufficient field data for model calibration and validation. For future research, it is recommended to incorporate macroplastics' degradation rates, particles of different shapes and sizes and vertical mixing due to biofouling and turbulent conditions and also more experimental data to obtain precise model inputs and standardised sampling methods for surface and column waters.

Exploring the role of wastewater-based epidemiology in understanding tuberculosis burdens in Africa.

Tuberculosis (TB) remains a persistent challenge to public health and presents a substantial menace, especially in developing nations of sub-Saharan Africa. It exerts a considerable strain on healthcare systems in these regions. Effective control requires reliable surveillance, which can be improved by incorporating environmental data alongside clinical data. Molecular advances have led to the development of alternative surveillance methods, such as wastewater-based epidemiology. This studyinvestigated the presence, concentration, and diversity of Mycobacterium tuberculosis complex, the cause of TB, in from six African countries: Ghana, Nigeria, Kenya, Uganda, Cameroon, and South Africa. Samples were collected from wastewater treatment plants. All samples were found to contain Mycobacterium species that have been linked to TB in both humans and animals, including Mycobacterium tuberculosis complex, Mycobacterium tuberculosis, Mycobacterium bovis, Mycobacterium africanum, and Mycobacterium caprae, at varying concentrations. The highest median concentration was found in Ghana, reaching up to 4.7 Log copies/ml for MTBC, 4.6 Log copies/ml for M. bovis, and 3.4 Log copies/ml for M. africanum. The presence of M. africanum outside of West Africa was found in South Africa, Kenya, and Uganda and could indicate the spread of the pathogen. The study underscores the usefulness of wastewater-based epidemiology for tracking TB and shows that even treated wastewater may contain these pathogens, posing potential public health risks.

Anthelmintic resistance in soil-transmitted helminths: One-Health considerations.

The One-Health approach recognizes the intricate connection between human, animal, and environmental health, and that cooperative effort from various professionals provides comprehensive awareness and potential solutions for issues relating to the health of people, animals, and the environment. This approach has increasingly gained appeal as the standard strategy for tackling emerging infectious diseases, most of which are zoonoses. Treatment with anthelmintics (AHs) without a doubt minimizes the severe consequences of soil-transmitted helminths (STHs); however, evidence of anthelmintic resistance (AR) development to different helminths of practically every animal species and the distinct groups of AHs is overwhelming globally. In this regard, the correlation between the application of anthelmintic drugs in both human and animal populations and the consequent development of anthelmintic resistance in STHs within the context of a One-Health framework is explored. This review provides an overview of the major human and animal STHs, treatment of the STHs, AR development and drug-related factors contributing towards AR, One-Health and STHs, and an outline of some One-Health strategies that may be used in combating AR.

Modeling and optimization of chlorpyrifos and glyphosate biodegradation using RSM and ANN: Elucidating their degradation pathways by GC-MS based metabolomics.

Ongoing and extensive use of pesticides negatively impact the environment and human health. Microbe-based remediation bears importance as it is an eco-friendly and cost-effective technique. The present study investigated chlorpyrifos (CHL) and glyphosate (GLY) degrading potential of Bacillus cereus AKAD 3-1, isolated from the soybean rhizosphere. Optimization and validation of different process variables were carried out by response surface methodology (RSM) and artificial neural network (ANN). Critical parameters which affect the degradation process are initial pesticide concentration, pH, and inoculum size. At optimum conditions, the bacterial strain demonstrated 94.52% and 83.58% removal of chlorpyrifos and glyphosate, respectively. Both Central-composite design (CCD-RSM) and ANN approaches proved to perform well in modeling and optimizing the growth conditions. The optimum ANN-GA model resulted in R2 ≥ 0.99 for chlorpyrifos and glyphosate, while in the case of RSM, the obtained R2 value was 0.96 and 0.95, respectively. Results indicated that the process variables significantly (p < 0.05) impact chlorpyrifos and glyphosate biodegradation. Moreover, the predicted RSM model had a "lack of fit p-value" of "0.8849" and "0.2502" for chlorpyrifos and glyphosate, respectively. GC-MS analysis revealed that the strain first converted chlorpyrifos into 3,5,6-trichloro pyridin-2-ol & O, O-diethyl O-hydrogen phosphorothiate. Later, these intermediate metabolites were broken and completely mineralized into non-toxic by-products. Similarly, glyphosate was first converted into 2-(methylamino) acetic acid and amino-oxyphosphonic acid, which were further mineralized without any toxic by-products. Taken together, the results of this study clarify the biodegradation pathways and highlights the promising potential of B. cereus AKAD 3-1 in the bioremediation of chlorpyrifos and glyphosate-polluted environments.

Effect of selected wastewater characteristics on estimation of SARS-CoV-2 viral load in wastewater.

Wastewater-based epidemiology has been used as a tool for surveillance of COVID-19 infections. This approach is dependent on the detection and quantification of SARS-CoV-2 RNA in untreated/raw wastewater. However, the quantification of the viral RNA could be influenced by the physico-chemical properties of the wastewater. This study presents the first use of Adaptive Neuro-Fuzzy Inference System (ANFIS) to determine the potential impact of physico-chemical characteristics of wastewater on the detection and concentration of SARS-CoV-2 RNA in wastewater. Raw wastewater samples from four wastewater treatment plants were investigated over four months. The physico-chemical characteristics of the raw wastewater was recorded, and the SARS-CoV-2 RNA concentration determined via amplification with droplet digital polymerase chain reaction. The wastewater characteristics considered were chemical oxygen demand, flow rate, ammonia, pH, permanganate value, and total solids. The mean SARS-CoV-2 RNA concentrations ranged from 648.1(±514.6) copies/mL to 1441.0(±1977.8) copies/mL. Among the parameters assessed using the ANFIS model, ammonia and pH showed significant association with the concentration of SARS-CoV-2 RNA measured. Increasing ammonia concentration was associated with increasing viral RNA concentration and pH between 7.1 and 7.4 were associated with the highest SARS-CoV-2 concentration. Other parameters, such as total solids, were also observed to influence the viral RNA concentration, however, this observation was not consistent across all the wastewater treatment plants. The results from this study indicate the importance of incorporating wastewater characteristic assessment into wastewater-based epidemiology for a robust and accurate COVID-19 surveillance.

The source and fate of Mycobacterium tuberculosis complex in wastewater and possible routes of transmission.

BACKGROUND: The Mycobacterium tuberculosis complex (MTBC) consists of causative agents of both human and animal tuberculosis and is responsible for over 10 million annual infections globally. Infections occur mainly through airborne transmission, however, there are possible indirect transmissions through a faecal-oral route which is poorly reported. This faecal-oral transmission could be through the occurrence of the microbe in environments such as wastewater. This manuscript, therefore, reviews the source and fate of MTBC in the wastewater environment, including the current methods in use and the possible risks of infections. RESULTS: The reviewed literature indicates that about 20% of patients with pulmonary TB may have extra-pulmonary manifestations such as GITB, resulting in shedding in feaces and urine. This could potentially be the reason for the detection of MTBC in wastewater. MTBC concentrations of up to 5.5 × 105 (±3.9 × 105) copies/L of untreated wastewater have been reported. Studies have indicated that wastewater may provide these bacteria with the required nutrients for their growth and could potentially result in environmental transmission. However, 98.6 (± 2.7) %, removal during wastewater treatment, through physical-chemical decantation (primary treatment) and biofiltration (secondary treatment) has been reported. Despite these reports, several studies observed the presence of MTBC in treated wastewater via both culture-dependent and molecular techniques. CONCLUSION: The detection of viable MTBC cells in either treated or untreated wastewater, highlights the potential risks of infection for wastewater workers and communities close to these wastewater treatment plants. The generation of aerosols during wastewater treatment could be the main route of transmission. Additionally, direct exposure to the wastewater containing MTBC could potentially contribute to indirect transmissions which may lead to pulmonary or extra-pulmonary infections. This calls for the implementation of risk reduction measures aimed at protecting the exposed populations.

Effects of antimicrobials in anammox mediated systems: critical review.

Anammox-mediated systems are thought to be cost-effective and efficient technologies for removing nitrogen from wastewater by converting nitrite and ammonium into dinitrogen gas. However, there are inhibitory substances that reduce the effectiveness and efficiency of these processes, preventing their widespread application. Antimicrobial agents are among these substances that have been observed to inhibit anammox-mediated processes. Therefore, this review provides a comprehensive overview of the effects of various antimicrobials on the anammox-based systems with emphasis on the effects in different reactor configurations, sludge types and microbial population of anammox-based systems. In addition, this review also discusses the mechanisms by which nitrifying bacteria are inhibited by the antimicrobials. Gaps in knowledge based on this review as well as future research needs have also been suggested. This review gives a better knowledge of antimicrobial effects on anammox-based systems and provides some guidance on the type of system to use to treat antimicrobial-containing wastewater using anammox-based processes.

Critical Analysis of Biomass Retention Strategies in Mainstream and Sidestream ANAMMOX-Mediated Nitrogen Removal Systems.

ANAMMOX (anaerobic ammonium oxidation) represents an energy-efficient process for biological nitrogen removal, particularly from wastewater streams with low chemical oxygen demand (COD) to nitrogen (C/N) ratios. Its widespread application, however, is still hampered by a lack of access to biomass-enriched with ANAMMOX bacteria (AMX), slow growth rates of AMX, and their sensitivity to inhibition. Although the coupling of ANAMMOX processes with partial nitrification is already widespread, especially for sidestream treatment, maintaining a functional population density of AMX remains a challenge in these systems. Therefore, strategies that maximize retention of AMX-rich biomass are essential to promote process stability. This paper reviews existing methods of biomass retention in ANAMMOX-mediated systems, focusing on (i) granulation; (ii) biofilm formation on carrier materials; (iii) gel entrapment; and (iv) membrane technology in mainstream and sidestream systems. In addition, the microbial ecology of different ANAMMOX-mediated systems is reviewed.

Fuzzy inference optimization algorithms for enhancing the modelling accuracy of wastewater quality parameters.

To ensure the safe discharge of treated wastewater to the environment, continuous efforts are vital to enhance the modelling accuracy of wastewater treatment plants (WWTPs) through utilizing state-of-art techniques and algorithms. The integration of metaheuristic modern optimization algorithms that are natlurally inspired with the Fussy Inference Systems (FIS) to improve the modelling performance is a promising and mathematically suitable approach. This study integrates four population-based algorithms, namely: Particle swarm optimization (PSO), Genetic algorithm (GA), Hybrid GA-PSO, and Mutating invasive weed optimization (M-IWO) with FIS system. A full-scale WWTP in South Africa (SA) was selected to assess the validity of the proposed algorithms, where six wastewater effluent parameters were modeled, i.e., Alkalinity (ALK), Sulphate (SLP), Phosphate (PHS), Total Kjeldahl Nitrogen (TKN), Total Suspended Solids (TSS), and Chemical Oxygen Demand (COD). The results from this study showed that the hybrid PSO-GA algorithm outperforms the PSO and GA algorithms when used individually, in modelling all wastewater effluent parameters. PSO performed better for SLP and TKN compared to GA, while the M-IWO algorithm failed to provide an acceptable modelling convergence for all the studied parameters. However, three out of four algorithms applied in this study proven beneficial to be optimized in enhancing the modelling accuracy of wastewater quality parameters.

Detection of multidrug resistant environmental isolates of acinetobacter and Stenotrophomonas maltophilia: a possible threat for community acquired infections?

Acinetobacter spp. and Stenotrophomonas maltophilia are bacteria commonly associated with infections at the clinical settings. Reports of infections caused by environmental isolates are rare. Therefore, this study focused on determination of the antibiotic resistance patterns, antibiotic resistance genes, efflux pumps and virulence signatures of Acinetobacter spp. and S. maltophilia recovered from river water, plant rhizosphere and river sediment samples. The isolates were identified and confirmed using biochemical tests and PCR. The antimicrobial resistance profiles of the isolates were determined using Kirby Bauer disk diffusion assay and presence of antibiotic resistance and virulence genes were detected using PCR. S. maltophilia was more frequent in plant rhizosphere and sediment samples than the water samples. Acinetobacter spp. were mostly resistant to trimethoprim-sulfamethoxazole (96% of isolates), followed by polymyxin b (86%), cefixime (54%), colistin (42%), ampicillin (35%) and meropenem (19%). The S. maltophilia isolates displayed total resistance (100%) to trimethoprim- sulfamethoxazole, meropenem, imipenem, ampicillin and cefixime, while 80% of the isolates were resistant to ceftazidime. Acinetobacter spp. contained different antibiotic resistance genes such as sul1 (24% of isolates), sul2 (29%), blaOXA 23/51 (21%) and blaTEM (29%), while S. maltophilia harbored sul1 (8%) and blaTEM (20%). Additionally, efflux pump genes were present in all S. maltophilia isolates. The presence of multidrug resistant Acinetobacter spp. and Stenotrophomonas maltophilia in surface water raises concerns for community-acquired infections as this water is directly been used by the community for various purposes. Therefore, there is the need to institute measures aimed at reducing the risks of these infections and the resulting burden this may have on the health care system within the study area.

Identification, antibiotic resistance, and virulence profiling of Aeromonas and Pseudomonas species from wastewater and surface water.

Aquatic environments are hotspots for the spread of antibiotic-resistant bacteria and genes due to pollution caused mainly by anthropogenic activities. The aim of this study was to evaluate the impact of wastewater effluents, informal settlements, hospital, and veterinary clinic discharges on the occurrence, antibiotic resistance profile and virulence signatures of Aeromonas spp. and Pseudomonas spp. isolated from surface water and wastewater. High counts of Aeromonas spp. (2.5 (± 0.8) - 3.3 (± 0.4) log10 CFU mL-1) and Pseudomonas spp. (0.6 (± 1.0) - 1.8 (± 1.0) log10 CFU mL-1) were obtained. Polymerase chain reaction (PCR) and MALDI-TOF characterization identified four species of Aeromonas and five of Pseudomonas. The isolates displayed resistance to 3 or more antibiotics (71% of Aeromonas and 94% of Pseudomonas). Aeromonas spp. showed significant association with the antibiotic meropenem (χ2 = 3.993, P < 0.05). The virulence gene aer in Aeromonas was found to be positively associated with the antibiotic resistance gene blaOXA (χ2 = 6.657, P < 0.05) and the antibiotic ceftazidime (χ2 = 7.537, P < 0.05). Aeromonas recovered from both wastewater and surface water displayed high resistance to ampicillin and had higher multiple antibiotic resistance (MAR) indices close to the hospital. Pseudomonas isolates on the other hand exhibited low resistance to carbapenems but very high resistance to the third-generation cephalosporins and cefixime. The results showed that some of the Pseudomonas spp. and Aeromonas spp. isolates were extended-spectrum ß-lactamase producing bacteria. In conclusion, the strong association between virulence genes and antibiotic resistance in the isolates shows the potential health risk to communities through direct and indirect exposure to the water.

Impact of sludge bulking on receiving environment using quantitative microbial risk assessment (QMRA)-based management for full-scale wastewater treatment plants.

During sludge bulking in wastewater treatment plants (WWTPs), high amounts of potentially pathogenic bacteria would release into the environment, causing various human-health risks. This is the first study attempting to assess the microbial infections associated with the reuse of WWTP effluents under various bulking conditions. Three common waterborne pathogens, viz., E. coli O157:H7, Salmonella, and Mycobacterium, were quantified from full-scale WWTPs using DNA extraction and qPCR at different sludge volume indices (SVIs). The detected pathogens were incorporated into a quantitative microbial risk assessment (QMRA) model to determine the applicability of WWTP discharge for recreational (bathing) activities and agricultural practices. The QMRA exposures were children, women, and men during swimming, and farmers and vegetable consumers during irrigation. Bacterial abundance in the treated wastewater increased in response to SVIs, and the QMRA values at all bulking events exceeded the tolerable risk of one case of infection per 10,000 people per year. Hence, various disinfection scenarios (chlorination, ultraviolet, and ozonation) were hypothetically tested to control the risks associated with pathogenic bacteria, allowing for safe disposal and reuse of the treated effluent. The ultraviolet application provided the highest ability to inactivate the pathogenic bacteria, except for the case of children exposed to Salmonella infection during swimming. The reduction of Mycobacterium infection risks with either chlorination or ozonation showed inefficient results. This study would be helpful for the management of human health risks associated with effluent wastewater containing pathogens, i.e., particularly concerning the case of sludge bulking.

Impact of informal settlements and wastewater treatment plants on helminth egg contamination of urban rivers and risks associated with exposure.

The quality of surface water could be influenced by both anthropogenic and natural factors. This study was designed to determine the impact of informal settlement and wastewater treatment plants on helminth egg contamination of urban rivers and the risks associated with everyday use. We also ascertained the accumulation of these eggs in the river sediments. The study was carried out in two rivers in the eThekwini Municipality of South Africa. Grab samples were taken at different points over a 10-month period. Ascaris spp., hookworm, Toxocara spp., Trichuris spp. and Taenia spp. were the helminth eggs detected in both the water column and sediments, with mean Ascaris spp. eggs of 0-6.3 (± 5.1)/L in the water and 0-6.8 (± 5.2)/kg in sediment samples. The helminth egg concentrations showed seasonal variation, probably due to changes in infection levels of the populations or natural factors, such as rainfall. The informal settlements had a greater impact than treated wastewater. For every 10,000 recreational users of the rivers 19 to 58 may be infected under undisturbed conditions, increasing to 29-88 individuals when the riverbed is disturbed. The risk from agricultural use of the rivers was above the tolerable risk values applicable for wastewater reuse, recommended by the World Health Organization. This calls for a re-evaluation of the policies governing surface water quality assessment, where the inclusion of helminth eggs and sediment monitoring will be critical.

The evaluation of COD fractionation and modeling as a key factor for appropriate optimization and monitoring of modern cost-effective activated sludge systems.

A study was conducted to characterize the raw wastewater entering a modern cost effective municipal WWTP in Poland using two approaches; 1) a combination of modeling and carbonaceous oxygen demand (COD) fractionation using respirometric test coupled with model estimation (RT-ME) and 2) flocculation/filtration COD fractionation method combined with BOD measurements (FF-BOD). It was observed that the particulate fractions of COD obtained using FF-BOD method was higher than those estimated by RT-ME approach. Contrary to the above, the values of inert soluble fraction evaluated by FF-BOD method was significantly lower than RT-ME approach (2.4% and 3.9% respectively). Furthermore, the values for low colloidal and particulate fractions as well as soluble inert fractions were different than expected from a typical municipal wastewater. These observations suggest that even at low load (10% of the total wastewater treatment inflow), the industrial wastewater composition can significantly affect the characteristics of municipal wastewater which could also affect the performance and accuracy of respirometric tests. Therefore, in such cases, comparison of the respirometric tests with flocculation/filtration COD/BOD measurements are recommended. Oxygen uptake rate profile with settled wastewater and/or after coagulation-flocculation, however, could still be recommended as a "rapid" control method for monitoring/optimising modern cost-effective wastewater treatment plants.

Epibiont growth on filamentous bacteria found in activated sludge: a morphological approach.

Occurrence of epibiont attachment on filamentous bacteria is a common phenomenon in activated sludge. In this study, an attempt has been made to elucidate the intrinsic nature of the attachment between the epibionts and filamentous bacteria based on microscopic observations. Characterization of the epiflora based on fluorescence in situ hybridization using group level probes revealed that the epibionts colonizing these filamentous bacteria largely belongs to the class Alphaproteobacteria, followed by Beta and Gammaproteobacteria. The ultrastructural examination using transmission electron microscopy pointed to the existence of a possible cell-to-cell interaction between epibionts and the selected filaments. Common bacterial appendages such as pili and fimbria were absent at the interface and further noted was the presence of cell membrane extensions on epibiont bacteria protruding towards the targeted filamentous cell. Fibrillar structures resembling amyloid-like proteins were observed within the filament cells targeted by the epibionts. An interaction was apparent between amyloid such as proteins and epibionts with regards to the direction of fibrillar structures and the distance of approaching epibiont bacteria. Due to the lack of visual evidence in support of penetration, the role of these amyloid-like fibrils as potential attachment sites for the epibionts was taken into consideration, and required further validation using conformational antibodies.

Comparison of droplet digital PCR and quantitative PCR for the detection of Salmonella and its application for river sediments.

Despite advances in microbial detection that quantitative polymerase chain reaction (qPCR) has led to, complex environmental samples, such as sediments, remain a challenge due to presence of PCR inhibitors. Aquatic sediments accumulate particle-bound microbial contaminants and thereby reflect a cumulative microbial load over time. The relatively new droplet digital PCR (ddPCR) has emerged as a direct quantitative method, highly tolerant to PCR inhibitors and relinquishing the necessity for calibration/standard curves. Information is virtually absent where ddPCR has been applied to detect pathogenic organisms in aquatic sediments. This study compared the efficacy of ddPCR with qPCR, for quantification of Salmonella in sediments from the Palmiet River near an informal settlement in Durban, South Africa. ddPCR significantly improved both analytical sensitivity and detection of low concentrations of Salmonella as compared to qPCR. The expected copy numbers measured from both qPCR and ddPCR showed good R2 values (0.999 and 0.994, respectively). The site mostly affected by the informal settlements exhibited Salmonella in the range of 255 ± 37 and 818 ± 30 Salmonella/g (p ≤ 0.0001) in qPCR and ddPCR, respectively. The improved detection of Salmonella in sediments with ddPCR makes it a promising technical method for the quantification of Salmonella in multifarious environmental samples.