Microplastics in aquatic ecosystems of Africa: A comprehensive review and meta-analysis.

Microplastic pollution is a global issue of great public concern. Africa is flagged to host some of the most polluted water bodies globally, but there is no enough information on the extent of microplastic contamination and the potential risks of microplastic pollution in African aquatic ecosystems. This meta-analysis has integrated data from published articles about microplastic pollution in African aquatic ecosystems. The data on the microplastic distribution and morphological characteristics in water, sediments and biota from African rivers, lakes, oceans and seas were extracted from 75 selected studies. Multivariate statistics were used to critically analyze the effects of sampling and detection methods, ecological risks, spatial distribution and similarity of microplastics in relation to the geographical distance between sampling sites. This study found that sampling methods have significant effect on abundance and morphological characteristics of microplastics and that African aquatic ecosystems are highly contaminated with microplastics compared to global data. The most prevalent colors were white, transparent and black, the most prevalent shapes were fibres and fragments, and the most available polymers were polypropylene (PP), polystyrene (PS) and polyethene terephthalate (PET). Microplastic polymers similarity decreased with an increase in geographical distance between sites. Risk levels of microplastics in African aquatic ecosystems were comparatively high, and more than 40 % of water and sediments showed highest level of ecological risk. This review provides recent information on the prevalence, distribution and risks of microplastics in African aquatic ecosystems.

Machine learning reveals the complex ecological interplay of microbiome in a full-scale membrane bioreactor wastewater treatment plant.

Membrane bioreactor (MBR) systems are one of the most widely used wastewater treatment processes for various municipal and industrial waste streams. The present study aimed to advance the understanding of ecologically important keystone taxa that play an important role in full-scale MBR systems. A machine-learning (ML) modeling framework based on microbiome data was developed to successfully predict, with an average accuracy of >91.6%, the operational characteristics of three representative full-scale wastewater systems: an MBR, a conventional activated sludge system, and a sequencing batch reactor. ML-based feature-importance analysis identified Ferruginibacter as a keystone organism in the MBR system. The phylogeny and known ecophysiology of members of Ferruginibacter supported their role in metabolizing complex organic polymers (e.g., extracellular polymeric substances) in MBR systems characterized by high concentrations of mixed liquor suspended solids and a high solid retention time. ML regression modeling also revealed temporal patterns of Ferruginibacter in response to water temperature. ML modeling was thus successfully employed in the present study to investigate complex/non-linear relationships between keystone taxa and environmental conditions that cannot be detected using conventional approaches. Overall, our microbiome-data-enabled ML modeling approach represents a methodological advance for identifying keystone taxa and their complex ecological interactions, which has implications for the sustainable and predictive management of MBR systems.

Comprehensive assessment of chlorination disinfection on microplastic-associated biofilms.

Chlorination on microplastic (MP) biofilms was comprehensively investigated with respect to disinfection efficiency, morphology, and core microbiome. The experiments were performed under various conditions: i) MP particles; polypropylene (PP) and polystyrene (PS), ii) MP biofilms; Escherichia coli for single-species and river water microorganisms for multiple-species, iii) different chlorine concentrations, and iv) different chlorine exposure periods. As a result, chlorination effectively inactivated the MP biofilm microorganisms. The disinfection efficiency increased with increasing the free chlorination concentration and exposure periods for both single- and multiple-species MP biofilms. The multiple-species MP biofilms were inactivated 1.3-6.0 times less than single-species MP biofilms. In addition, the PP-MP biofilms were more vulnerable to chlorination than the PS-MP biofilms. Morphology analysis verified that chlorination detached most MP biofilms, while a small part still remained. Interestingly, chlorination strongly changed the biofilm microbiome on MPs; the relative abundance of some microbes increased after the chlorination, suggesting they could be regarded as chlorine-resistant bacteria. Some potential pathogens were also remained on the MP particles after the chlorination. Notably, chlorination was effective in inactivating the MP biofilms. Further research should be performed to evaluate the impacts of residual MP biofilms on the environment.

Biomass formation and organic carbon migration potential of microplastics from a PET recycling plant: Implication of biostability.

The growth of the polyethylene terephthalate (PET) mechanical recycling industry has resulted in the challenge of generating microplastics (MPs). However, little attention has been given to investigating the release of organic carbon from these MPs and their roles in promoting bacterial growth in aquatic environments. In this study, a comprehensive method is proposed to access the potential of organic carbon migration and biomass formation of MPs generated from a PET recycling plant, and to understand its impact on the biological systems of freshwater habitats. Various MPs sizes from a PET recycling plant were selected to conduct a series of tests, including the organic carbon migration test, biomass formation potential test, and microbial community analysis. The MPs smaller than 100 µm, which are difficult to remove from the wastewater, exhibited greater biomass in the observed samples (1.05 × 1011 bacteria per gram MPs). Moreover, PET MPs altered the microbial diversity, with Burkholderiaceae becoming the most abundant, while Rhodobacteraceae was eliminated after being incubated with MPs. This study partly revealed that organic matter adsorbed on the surface of MPs was a significant nutrient source that increased biomass formation. PET MPs acted not only as carriers for microorganisms but also for organic matter. As a result, it is crucial to develop and refine recycling methods in order to decrease the production of PET MPs and minimize their adverse effects on the environment.

Anaerobic membrane bioreactor performance with varying feed concentrations of ciprofloxacin.

The anaerobic membrane bioreactor (AnMBR) has considerable potential for treating wastewater, although there is very little data on the effect of antibiotics on AnMBR performance. This study examined the effect of Ciprofloxacin (CIP) - an antibiotic that can occur at high concentrations, and has a substantial impact on ecosystems, on AnMBR performance. The long-term (44 days) presence of 0.5 mg/L CIP in the feed did not have a strong effect on COD removal, volatile fatty acid (VFA) accumulation, or methane yield, but did affect the pH, soluble microbial products (SMPs) and suspended solids. However, at 4.7 mg/L CIP, a significant effect on all the parameters tested was seen. 16S rRNA gene-based community analysis demonstrated that CIP changed the phylogenetic structure and altered the species richness and diversity. The relative abundance of various genera was also changed, and this explained much of the change in AnMBR behavior.

Enrichment and characterization of microbial consortia degrading soluble microbial products discharged from anaerobic methanogenic bioreactors.

Soluble microbial products (SMP) produced in bioprocesses have been known as a main cause to decrease treatment efficiency, lower effluent quality, and promote membrane fouling in water reclamation plants. In this study, biological degradation of SMP using selectively enriched microbial consortia in a down-flow hanging sponge (DHS) reactor was introduced to remove SMP discharged from anaerobic methanogenic reactors. On average, 68.9-87.5% SMP removal was achieved by the enriched microbial consortia in the DHS reactor for >800 days. The influent SMP fed to the DHS reactor exhibited a bimodal molecular weight (MW) distribution with 14-20 kDa and <4 kDa. Between these two types of SMP, the small MW SMP were biodegraded in the upper part of the reactor, together with most of the large MW SMP. Using 16S rRNA gene pyrosequencing technology, the microbial community composition and structure were characterized and correlated with operational factors, such as hydraulic retention time, organic loading rate, and removal of soluble chemical oxygen demand at different depths of the reactor, by performing network and redundancy analyses. The results revealed that Saprospiraceae was strongly correlated to the increasing SMP loading condition, indicating positive co-occurrences with neighboring bacterial populations. Different microbial diversity along with the depth of the reactor implies that stratified microbial communities could participate in the process of SMP degradation. Taken together, these observations indicate that the spatial and temporal variability of the enriched microbial community in the DHS reactor could effectively treat SMP with respect to changes in the operational factors.