Spatiotemporal variation in urban wastewater pollution impacts on river microbiomes and associated hazards in the Akaki catchment, Addis Ababa, Ethiopia

Performance evaluation of a brewery wastewater treatment plant: A case of Heineken Brewery, Addis Ababa, Ethiopia

Untreated wastewater from the brewing industry poses significant environmental risks due to its high organic content. Therefore, this study evaluates the wastewater treatment system at Heineken Brewery in Addis Ababa, Ethiopia. Key parameters analyzed include COD, BOD₅, TSS, pH, ammonia (NH₃), total nitrogen (TN), total phosphorus (TP), electrical conductivity (EC), temperature, turbidity, and volatile fatty acids (VFA). These parameters were analyzed following the procedures of the American Public Health Association's standard. The treatment system demonstrated notable efficiency, with influent temperature decreasing from 29.37 °C to 25.35 °C, remaining well below the acceptable limit of 40 °C. The pH dropped from a mean of 9.3 to 7.5, aligning with the acceptable range of 6-9. COD and BOD₅ were significantly reduced by 97.2 %, achieving levels well below discharge limits of 250 mg/L and 60 mg/L, respectively. TSS levels decreased by 95.7 %, with a mean of 32.3 mg/L. However, TP and TN removal efficiencies were lower at 49.4 % and 57.6 %, respectively, with TP slightly exceeding the limit of 5 mg/L. The system effectively reduced VFA by 94.3 % and turbidity by 71.5 %. While parameters such as pH, temperature, TN, NH₄-N, and EC were within acceptable limits, the high nutrient concentrations in the final effluent indicate potential environmental contamination if discharged untreated. Overall, while the treatment plant shows commendable pollutant removal efficiency, further optimization is needed for improved nutrient management.

Healthcare waste management and antimicrobial resistance: a critical review

The rapid growth of populations and urbanization has led to a significant increase in healthcare waste, posing serious health risks. A search on Google Scholar identified seven relevant articles from Ethiopia that examine the relationship between improper waste management in healthcare facilities (HCFs) and the rise of antimicrobial resistance (AMR) genes. This review aims to highlight key concepts, evidence sources, and knowledge gaps specific to the Ethiopian context. The unsafe disposal of antibiotics through leaks and solid waste has contributed to what some are calling a 'silent pandemic,' raising concerns about emerging infectious diseases. Studies have revealed alarming rates of infectious agents and AMR in healthcare wastewater. Isolates of C. jejuni, Escherichia coli, Enterococcus faecalis, and Enterococcus faecium from various healthcare waste sites in Ethiopia demonstrate high levels of AMR genes. Additionally, research indicates that HCFs produce significant amounts of waste, with high per-person daily waste production rates. Leachate from landfills containing this waste can negatively affect soil health, biological activity, water quality, agriculture, animal health, and human well-being. To mitigate these risks, effective waste management practices and the promotion of alternative antimicrobial use are essential strategies for reducing the emergence of pandemic diseases in developing countries.

Harnessing biotechnology for penicillin production: Opportunities and environmental considerations

Since the discovery of antibiotics, penicillin has remained the top choice in clinical medicine. With continuous advancements in biotechnology, penicillin production has become cost-effective and efficient. Genetic engineering techniques have been employed to enhance biosynthetic pathways, leading to the production of new penicillin derivatives with improved properties and increased efficacy against antibiotic-resistant pathogens. Advances in bioreactor design, media formulation, and process optimization have contributed to higher yields, reduced production costs, and increased penicillin accessibility. While biotechnological advances have clearly benefited the global production of this life-saving drug, they have also created challenges in terms of waste management. Production fermentation broths from industries contain residual antibiotics, by-products, and other contaminants that pose direct environmental threats, while increased global consumption intensifies the risk of antimicrobial resistance in both the environment and living organisms. The current geographical and spatial distribution of antibiotic and penicillin consumption dramatically reveals a worldwide threat. These challenges are being addressed through the development of novel waste management techniques. Efforts are aimed at both upstream and downstream processing of antibiotic and penicillin production to minimize costs and improve yield efficiency while lowering the overall environmental impact. Yield optimization using artificial intelligence (AI), along with biological and chemical treatment of waste, is also being explored to reduce adverse impacts. The implementation of strict regulatory frameworks and guidelines is also essential to ensure proper management and disposal of penicillin production waste. This review is novel because it explores the key remaining challenges in antibiotic development, the scope of machine learning tools such as Quantitative Structure-Activity Relationship (QSAR) in modern biotechnology-driven production, improved waste management for antibiotics, discovering alternative path to reducing antibiotic use in agriculture through alternative meat production, addressing current practices, and offering effective recommendations.

Prevalence and antimicrobial susceptibility pattern of Vibrio cholerae isolates from cholera outbreak sites in Ethiopia

BACKGROUND

Cholera is an acute infectious disease caused by ingestion of contaminated food or water with Vibrio cholerae. Cholera remains a global threat to public health and an indicator of inequity and lack of social development. The aim of this study was to assess the prevalence and antimicrobial susceptibility pattern of V. cholerae from cholera outbreak sites in Ethiopia.

METHODS

Across-sectional study was conducted from May 2022 to October 2023 across different regions in Ethiopia: Oromia National Regional State, Amhara National Regional State and Addis Ababa City Administration. A total of 415 fecal samples were collected from the three regions. Two milliliter fecal samples were collected from each study participants. The collected samples were cultured on Blood Agar, MacConkey Agar and Thiosulfate Citrate Bile Salt Sucrose Agar. A series of biochemical tests Oxidase test, String test, Motility, Indole, Citrate, Gas production, H2S production, Urease test were used to identify V. cholerae species. Both polyvalent and monovalent antisera were used for agglutination tests to identify and differentiate V. cholerae serogroup and serotypes. In addition, Kirby-Bauer Disk diffusion antibiotic susceptibility test method was done. Data were registered in epi-enfo version 7 and analyzed by Statistical Package for Social Science version 25. Descriptive statistics were used to determine the prevalence of Vibrio cholerae. Logistic regression model was fitted and p-value < 0.05 was considered as statically significant.

RESULTS

The prevalence of V. cholerae in the fecal samples was 30.1%. Majority of the isolates were from Oromia National Regional State 43.2% (n = 54) followed by Amhara National Regional State 31.2% (n = 39) and Addis Ababa City Administration 25.6% (n = 32). Most of the V. cholerae isolates were O1 serogroups 90.4% (n = 113) and Ogawa serotypes 86.4% (n = 108). Majority of the isolates were susceptible to ciprofloxacin 100% (n = 125), tetracycline 72% (n = 90) and gentamycin 68% (n = 85). More than half of the isolates were resistant to trimethoprim-sulfamethoxazole 62.4% (n = 78) and ampicillin 56.8% (n = 71). In this study, participants unable to read and write were about four times more at risk for V. cholerae infection (AOR: 3.8, 95% CI: 1.07-13.33). In addition, consumption of river water were about three times more at risk for V. cholerae infection (AOR: 2.8, 95% CI: 1.08-7.08).

CONCLUSION

our study revealed a high prevalence of V. cholerae from fecal samples. The predominant serogroups and serotypes were O1 and Ogawa, respectively. Fortunately, the isolates showed susceptible to most tested antibiotics. Drinking water from river were the identified associated risk factor for V. cholerae infection. Protecting the community from drinking of river water and provision of safe and treated water could reduce cholera outbreaks in the study areas.

Land use/cover drive functional patterns of bacterial communities in sediments of a subtropical river, China

The bacterial community in sediment serves as an important indicator for assessing the environmental health of river ecosystems. However, the response of bacterial community structure and function in river basin sediment to different land use/cover changes has not been widely studied. To characterize changes in the structure, composition, and function of bacterial communities under different types of land use/cover, we studied the bacterial communities and physicochemical properties of the surface sediments of rivers. Surface sediment in cropland and built-up areas was moderately polluted with cadmium and had high nitrogen and phosphorus levels, which disrupted the stability of bacterial communities. Significant differences in the α-diversity of bacterial communities were observed among different types of land use/cover. Bacterial α-diversity and energy sources were greater in woodlands than in cropland and built-up areas. The functional patterns of bacterial communities were shown that phosphorus levels and abundances of pathogenic bacteria and parasites were higher in cropland than in the other land use/cover types; Urban activities have resulted in the loss of the denitrification function and the accumulation of nitrogen in built-up areas, and bacteria in forested and agricultural areas play an important role in nitrogen degradation. Differences in heavy metal and nutrient inputs driven by land use/cover result in variation in the composition, structure, and function of bacterial communities.

Cold atmospheric plasma can effectively disinfect SARS-CoV-2 in the wastewater

COVID-19 is currently pandemic and the detection of SARS-CoV-2 variants in wastewater is causing widespread concern. Herein, cold atmospheric plasma (CAP) is proposed as a novel wastewater disinfection technology that effectively inactivates SARS-CoV-2 transcription- and replication-competent virus-like particles, coronavirus GX_P2V, pseudotyped SARS-CoV-2 variants, and porcine epidemic diarrhoea virus in a large volume of water within 180 s (inhibition rate > 99%). Further, CAP disinfection did not adversely affect the viability of various human cell lines. It is identified that CAP produced peroxynitrite (ONOO-), ozone (O3), superoxide anion radicals (O2 -), and hydrogen peroxide (H2O2) as the major active substances for coronavirus disinfection. Investigation of the mechanism showed that active substances not only reacted with the coronavirus spike protein and affected its infectivity, but also destroyed the nucleocapsid protein and genome, thus affecting virus replication. This method provides an efficient and environmentally friendly strategy for the elimination of SARS-CoV-2 and other coronaviruses from wastewater.

Source apportionment based on EEM-PARAFAC combined with microbial tracing model and its implication in complex pollution area, Wujin District, China

Further improving the quality of surface water is becoming more difficult after the control of main point-sources, especially in the complex pollution area with mixed industrial and agricultural productions, whereas the pollution source apportionment might be the key to quantify different pollution sources and developing some effective measures. In this study, a technical framework for source apportionment based on three-dimensional fluorescence and microbial traceability model is developed. Based on screening of the main environmental factors and their spatiotemporal characteristics, potential pollution sources have been tentatively identified. Then, the pollution sources are further tested based on the analysis of fluorescence excitation-emission matrix (EEM) and the similarity of fluorescence components in surface water and potential pollution sources. At the same time, the correlation between microbial species and pollution sources is constructed by analyzing the spatiotemporal characteristics of microbial composition and the response of main species to environmental factors. Therefore, pollution source apportionment is quantified using PCA-APCS-MLR, Fast Expectation-maximization for Microbial Source Tracking (FEAST), and Bayesian community-wide culture-independent microbial source tracking (SourceTracker). PCA-APCS-MLR could not effectively distinguish the contributions of different industrial sources in the complex environment of this study, and the contribution of unknown sources was high (average 39.60%). In contrast, the microbial traceability model can accurately identify the contribution of 7 pollution sources and natural sources, effectively reduce the proportion of unknown sources (average of FEAST is 19.81%, SourceTracker is 16.72%), and show better pollution identification and distribution capabilities. FEAST exhibits a more sensitive potential in source apportionment and shorter calculation time than SourceTracker, thus might be used to guide the precise regional pollution control, especially in the complex pollution environments.

Effective removal of iron, nutrients, micropollutants, and faecal bacteria in constructed wetlands cotreating mine water and sewage treatment plant effluent

Regulators in England and Wales have set new targets under the Environment Act 2021 for freshwater quality by 2038 that include halving the length of rivers polluted by harmful metals from abandoned mines and reducing phosphorus loadings from treated wastewater by 80%. In this context, an intriguing win-win opportunity exists in the removal of iron from abandoned mines and phosphate from small sewage treatment plants by coprecipitation in constructed wetlands (CWs). We investigated such a CW located at Lamesley, Northeast England, which cotreats abandoned coal mine and secondary-treated sewage treatment plant effluents. We assessed the removal of nutrients, heavy metals, organic micropollutants, and faecal coliforms by the CW, and characterized changes in the water bacteriology comprehensively using environmental DNA. The CW effectively removed ammonium-nitrogen, phosphorus, iron, and faecal coliforms by an average of 86, 74, 98, and 75%, respectively, to levels below or insignificantly different from those in the receiving river. The CW also effectively removed micropollutants such as acetaminophen, caffeine, and sulpiride by 70-100%. Molecular microbiology methods showed successful conversion of sewage and mine water microbiomes into a freshwater microbiome. Overall, the CW significantly reduced impacts on the rural water environment with minimal operational requirements.

Sampling frequency optimization of the water quality monitoring network in São Paulo State (Brazil) towards adaptive monitoring in a developing country

Water quality monitoring networks (WQMNs) that capture both the temporal and spatial dimensions are essential to provide reliable data for assessing water quality trends in surface waters, as well as for supporting initiatives to control anthropogenic activities. Meeting these monitoring goals as efficiently as possible is crucial, especially in developing countries where the financial resources are limited and the water quality degradation is accelerating. Here, we asked if sampling frequency could be reduced while maintaining the same degree of information as with bimonthly sampling in the São Paulo State (Brazil) WQMN. For this purpose, we considered data from 2004 to 2018 for 56 monitoring sites distributed into four out of 22 of the state's water resources management units (UGRHIs, "Unidades de Gerenciamento de Recursos Hídricos"). We ran statistical tests for identifying data redundancy among two-month periods in the dry and wet seasons, followed by objective criteria to develop a sampling frequency recommendation. Our results showed that the reduction would be feasible in three UGRHIs, with the number of annual samplings ranging from two to four (instead of the original six). In both seasons, dissolved oxygen and Escherichia coli required more frequent sampling than the other analyzed parameters to adequately capture variability. The recommendation was compatible with flexible monitoring strategies observed in well-structured WQMNs worldwide, since the suggested sampling frequencies were not the same for all UGRHIs. Our approach can contribute to establishing a methodology to reevaluate WQMNs, potentially resulting in less costly and more adaptive strategies in São Paulo State and other developing areas with similar challenges.

ResNet14Attention network for identifying the titration end-point of potassium dichromate

With the rapid development of industry, the increasing discharge of sewage causes the detection of water quality to be of increasing importance. Potassium dichromate titration is one of the most important testing methods in water quality detection; the ability to accurately identify the titration end-point of potassium dichromate is currently a research challenge. To identify titration end-point quickly and accurately, this study proposes a ResNet14Attention network, which utilizes residual modules that focus on original image information and an attention mechanism that focuses highly on classification targets. The proposed ResNet14Attention network is compared with 12 convolutional neural networks such as ResNet series networks, VGG, and GoogLeNet. The results of comparison experiments reveal that only the proposed ResNet14Attention network has the highest training and testing accuracy of 100% among all convolutional neural networks in the comparison experiment; the proposed ResNet14Attention network has the highest training speed compared to all the networks that over 90% accuracy.

Microbiological quality of irrigation water for cultivation of fruits and vegetables: An overview of available guidelines, water testing strategies and some factors that influence compliance

Contaminated irrigation water is among many potential vehicles of human pathogens to food plants, constituting significant public health risks especially for the fresh produce category. This review discusses some available guidelines or regulations for microbiological safety of irrigation water, and provides a summary of some common methods used for characterizing microbial contamination. The goal of such exploration is to understand some of the considerations that influence formulation of water testing guidelines, describe priority microbial parameters particularly with respect to food safety risks, and attempt to determine what methods are most suitable for their screening. Furthermore, the review discusses factors that influence the potential for microbiologically polluted irrigation water to pose substantial risks of pathogenic contamination to produce items. Some of these factors include type of water source exploited, irrigation methods, other agro ecosystem features/practices, as well as pathogen traits such as die-off rates. Additionally, the review examines factors such as food safety knowledge, other farmer attitudes or inclinations, level of social exposure and financial circumstances that influence adherence to water testing guidelines and other safe water application practices. A thorough understanding of relevant risk metrics for the application and management of irrigation water is necessary for the development of water testing criteria. To determine sampling and analytical approach for water testing, factors such as agricultural practices (which differ among farms and regionally), as well as environmental factors that modulate how water quality may affect the microbiological safety of produce should be considered. Research and technological advancements that can improve testing approach and the determination of target levels for hazard characterization or description for the many different pollution contexts as well as farmer adherence to testing requirements, are desirable.

Antimicrobial resistance genes in microbiota associated with sediments and water from the Akaki river in Ethiopia

The spread of antimicrobial-resistant pathogens is a global health concern. Most studies report high levels of antimicrobial resistance genes (ARGs) in the aquatic environment; however, levels associated with sediments are limited. This study aimed to investigate the distribution of ARGs in the sediments and water of the Akaki river in Addis Ababa, Ethiopia. The diversity and abundance of 84 ARGs and 116 clinically important bacteria were evaluated from the sediments and water collected from five sites in the Akaki river. Most of the ARGs were found in the city close to anthropogenic activities. Water samples collected in the middle catchment of the river contained 71-75% of targeted ARGs, with genes encoding aminoglycoside acetyltransferase (aac(6)-Ib-cr), aminoglycoside adenylyl transferase (aadA1), β-lactamase (bla_OXA-10)_, quinolone resistance S (qnrS), macrolide efflux protein A (mefA), and tetracycline resistance (tetA), were detected at all sampling sites. Much fewer ARGs were detected in all sediments, and those near the hospitals had the highest diversity and level. Despite the lower levels and diversity, there were no unique ARGs detected in the sediments that were also not detected in the waters. A wide range of clinically relevant pathogens were also detected in the Akaki river. The findings suggest that the water phase, rather than the sediments in the Akaki river, is a potential conduit for the spread of ARGs and antibiotic-resistant bacteria.

Attenuation of bacterial hazard indicators in the subsurface of an informal settlement and their application in quantitative microbial risk assessment

Pit latrines provide essential onsite sanitation services to over a billion people, but there are concerns about their role in infectious disease transmission, and impacts on groundwater resources. We conducted fieldwork in an informal settlement in Dar es Salaam, where cholera is endemic. We combined plate counting with portable MinION sequencing and quantitative polymerase chain reaction (qPCR) methods for characterization of bacteria in pit latrine sludge, leachate, shallow and deep groundwater resources. Pit latrine sludge was characterized by log₁₀ marker gene concentrations per 100 mL of 11.2 ± 0.2, 9.9 ± 0.9, 6.0 ± 0.3, and 4.4 ± 0.8, for total bacteria (16S rRNA), E. coli (rodA), human-host-associated Bacteroides (HF183), and Vibrio cholerae (ompW), respectively. The ompW gene observations suggested 5 % asymptomatic Vibrio cholerae carriers amongst pit latrine users. Pit leachate percolation through one-meter-thick sand beds attenuated bacterial hazard indicators by 1 to 4 log₁₀ units. But first-order removal rates derived from these data substantially overestimated the longer-range hazard attenuation in the sand aquifers. Cooccurrence of human sewage marker gene HF183 in all shallow groundwater samples testing positive for ompW genes demonstrated the human origin of Vibrio cholerae hazards in the subsurface. All borehole water samples tested negative for ompW and HF183 genes, but 16S rRNA gene sequencing data suggested ingress of faecal pollution into boreholes at the peak of the "long rainy season". Quantitative microbial risk assessment (QMRA) predicted a gastrointestinal disease burden of 0.05 DALY per person per year for the community, well above WHO targets of 10^-4-10^-6 DALY for disease related to drinking water.

A Mobile Laboratory Enables Fecal Pollution Source Tracking in Catchments Using Onsite qPCR Assays

Onsite molecular diagnostics can revolutionize fecal pollution source tracking. We aimed to validate a method for onsite qPCR assays with a miniature speaker-sized Q qPCR instrument and other portable equipment items. We showed that marker genes for total bacteria (16S) and E. coli (rodA) in 100 mL of river water measured with this method agreed within ±0.3 log10 units with results obtained when using conventional laboratory equipment items. We then deployed the portable method in a mobile laboratory (‘lab in a van’) and quantified HF183 marker genes for human host associated Bacteroides in river water within 3 h of sampling. We also used the mobile laboratory to investigate urban river water and effluents from two storm drains and a retention pond and collected comprehensive microbial and physicochemical water quality data. We found significantly higher HF183 gene levels in the older storm drain compared to the river water (6.03 ± 0.04 vs. 4.23 ± 0.03 log10 gene copies per 100 mL), and a principal component analysis revealed that storm drain effluent retention in a pond beneficially altered water characteristics, making them more like those of the receiving river. In conclusion, onsite qPCR assays can be performed with portable equipment items to quickly test water.