We propose a suite of simple equations to estimate the probability and duration of two important processes in microbial ecology: immigration and extinction. Our work is based on the gambler's ruin equation, which determines the probability that a number of immigrants (i) can attain an abundance N given the ratio of the probabilities of death q and division (or birth) p. We estimate the probability of an organism attaining a value of N in the context of bioaugmentation, transplantation, infection, mutation, and extinction. For example, an inoculum of 108 bacteria with a q/p of 1.00000001 has a 10-43 chance of attaining an abundance of 1010. The ratio of deaths to births controls the immigration parameter used in neutral models (m), and infectious dose in pathogens. We use Vibrio cholerae infections to demonstrate that the gambler's ruin equation can be used to estimate the infectious dose in naturally occurring infections. We calculated the long-term average value of m and q/p in a wastewater treatment plant. All values of q/p were ≥1. We expect the long-term average value of q/p to be ~1 in all stable microbial communities. In the absence of migration, bacterial populations with q/p ≥ 1 will go extinct with probability 1. We use the ratio q/p and simple recurrence relationships to estimate the time for a given change in abundance to occur. When q/p = 1, extinction in even a small microbial population will take thousands of years. Our simple mechanistic models could play a powerful role in theory and practice.

Antibiotic resistance poses a significant threat to human health, and wastewater treatment plants (WWTPs) are important reservoirs of antibiotic resistance genes (ARGs). Here, we analyze the antibiotic resistomes of 226 activated sludge samples from 142 WWTPs across six continents, using a consistent pipeline for sample collection, DNA sequencing and analysis. We find that ARGs are diverse and similarly abundant, with a core set of 20 ARGs present in all WWTPs. ARG composition differs across continents and is distinct from that of the human gut and the oceans. ARG composition strongly correlates with bacterial taxonomic composition, with Chloroflexi, Acidobacteria and Deltaproteobacteria being the major carriers. ARG abundance positively correlates with the presence of mobile genetic elements, and 57% of the 1112 recovered high-quality genomes possess putatively mobile ARGs. Resistome variations appear to be driven by a complex combination of stochastic processes and deterministic abiotic factors.

The term Environmental Biotechnology is widely used, but lacks a universally accepted definition, with varying interpretations across disciplines and sectors leading to challenges in funding, policy formulation, and interdisciplinary collaboration. Through a literature review and engagement activities, this study examines existing definitions, identifies key areas of divergence, and explores pathways toward a more cohesive understanding. Findings reveal a spectrum of valid interpretations, often shaped by specific contexts, with researchers generally recognising a shared conceptual framework within their own subfields but encountering ambiguities across subject boundaries. Common points of difference include whether Environmental Biotechnology is restricted to microorganisms or encompasses other biological systems. Some understandings reflect sector-specific needs, contributing to fragmentation, though a broader approach could strengthen the field’s identity by providing a unifying framework, mapping overlaps with related fields such as Industrial Biotechnology. A working definition is proposed for Environmental Biotechnology as the use of biologically mediated systems for environmental protection and bioremediation, incorporating resource recovery and bioenergy production where these enhance system sustainability. Importantly, it was recognised that any definition must remain adaptable, reflecting the evolving nature of both the science and its applications.

Cassava processing requires substantial water, producing an effluent with organic pollutants and cyanide. This study sought to improve wastewater management in the cassava agro-industry in Cauca, Colombia, by integrating community participation with technical design. The integration was achieved by finding sustainable water management strategies that considered technical, social, and environmental criteria. Five cassava processing plants were involved, using participatory action research to characterize the production system, analyze water discharges, and select management strategies. The community identified a suitable water management option. This preferred option includes primary treatment for solids separation, secondary treatment using anaerobic reactors to reduce the organic load and cyanide content, and tertiary treatment for further purification. We concluded that integrating community knowledge with technical expertise is essential for developing sustainable environmental solutions. Incorporating participatory methodology into decision-making is expected to significantly improve wastewater management by highlighting the importance of socio-ecological considerations in engineering practices. Furthermore, our collaborative approach is expected to promote local ownership and empowerment, ensuring long-term sustainability and compliance with the proposed strategies. This holistic approach demonstrates how community participation can be used to achieve effective and lasting environmental management solutions.

ADVERTISEMENT RETURN TO ISSUEPREVViewpointNEXTScaling-up Engineering Biology for Enhanced Environmental SolutionsFrancis HassardFrancis HassardCranfield University, Bedford MK43 0AL, U.K.More by Francis Hassardhttps://orcid.org/0000-0003-4803-6523, Thomas P. CurtisThomas P. CurtisNewcastle University, Newcastle upon Tyne NE4 5TG, U.K.More by Thomas P. Curtishttps://orcid.org/0000-0002-9009-1748, Gabriela C. DotroGabriela C. DotroCranfield University, Bedford MK43 0AL, U.K.More by Gabriela C. Dotro, Peter GolyshinPeter GolyshinBangor University, Gwynedd LL57 2UW, U.K.More by Peter Golyshinhttps://orcid.org/0000-0002-5433-0350, Tony GutierrezTony GutierrezHeriot-Watt University, Edinburgh, EH14 4AS, U.K.More by Tony Gutierrez, Sonia HeavenSonia HeavenUniversity of Southampton, Southampton SO16 7QF, U.K.More by Sonia Heaven, Louise HorsfallLouise HorsfallUniversity of Edinburgh, Edinburgh EH9 3FF, U.K.More by Louise Horsfallhttps://orcid.org/0000-0003-1594-2992, Bruce JeffersonBruce JeffersonCranfield University, Bedford MK43 0AL, U.K.More by Bruce Jefferson, Davey L. JonesDavey L. JonesBangor University, Gwynedd LL57 2UW, U.K.More by Davey L. Jones, Natalio KrasnogorNatalio KrasnogorNewcastle University, Newcastle upon Tyne NE4 5TG, U.K.More by Natalio Krasnogorhttps://orcid.org/0000-0002-2651-4320, Vinod KumarVinod KumarCranfield University, Bedford MK43 0AL, U.K.More by Vinod Kumarhttps://orcid.org/0000-0001-8967-6119, David J. Lea-SmithDavid J. Lea-SmithUniversity of East Anglia, Norwich NR4 7TJ, U.K.More by David J. Lea-Smith, Kristell Le Corre PidouKristell Le Corre PidouCranfield University, Bedford MK43 0AL, U.K.More by Kristell Le Corre Pidou, Yongqiang LiuYongqiang LiuUniversity of Southampton, Southampton SO16 7QF, U.K.More by Yongqiang Liuhttps://orcid.org/0000-0001-9688-1786, Tao LyuTao LyuCranfield University, Bedford MK43 0AL, U.K.More by Tao Lyuhttps://orcid.org/0000-0001-5162-8103, Ronan R. McCarthyRonan R. McCarthyBrunel University London, Uxbridge UB8 3PH, U.K.More by Ronan R. McCarthy, Boyd McKewBoyd McKewUniversity of Essex, Colchester, Essex CO4 3SQ, U.K.More by Boyd McKew, Cindy SmithCindy SmithUniversity of Glasgow, Glasgow G12 8LT, U.K.More by Cindy Smith, Alexander YakuninAlexander YakuninBangor University, Gwynedd LL57 2UW, U.K.More by Alexander Yakuninhttps://orcid.org/0000-0003-0813-6490, Zhugen YangZhugen YangCranfield University, Bedford MK43 0AL, U.K.More by Zhugen Yanghttps://orcid.org/0000-0003-4183-8160, Yue ZhangYue ZhangUniversity of Southampton, Southampton SO16 7QF, U.K.More by Yue Zhang, and Frederic Coulon*Frederic CoulonCranfield University, Bedford MK43 0AL, U.K.*Email: [email protected]More by Frederic Coulonhttps://orcid.org/0000-0002-4384-3222Cite this: ACS Synth. Biol. 2024, 13, 6, 1586–1588Publication Date (Web):June 21, 2024Publication History Received25 April 2024Published online21 June 2024Published inissue 21 June 2024https://pubs.acs.org/doi/10.1021/acssynbio.4c00292https://doi.org/10.1021/acssynbio.4c00292article-commentaryACS PublicationsCopyright © 2024 The Authors. Published by American Chemical Society. This publication is licensed under CC-BY 4.0. License Summary*You are free to share (copy and redistribute) this article in any medium or format and to adapt (remix, transform, and build upon) the material for any purpose, even commercially within the parameters below:Creative Commons (CC): This is a Creative Commons license.Attribution (BY): Credit must be given to the creator.View full license*DisclaimerThis summary highlights only some of the key features and terms of the actual license. It is not a license and has no legal value. Carefully review the actual license before using these materials. This publication is Open Access under the license indicated. Learn MoreArticle Views-Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail PDF (2 MB) Get e-AlertscloseSUBJECTS:Bioengineering and biotechnology,Biology,Biotechnology,Genomics,Synthetic biology Get e-Alerts

ABSTRACT The oral microbiome plays an important role in protecting oral health. Here, we established a controlled mixed-species in vitro biofilm model and used it to assess the impact of glucose and lactate on the ability of Streptococcus mutans , an acidogenic and aciduric species, to compete with commensal oral bacteria. A chemically defined medium was developed that supported the growth of S. mutans and four common early colonizers of dental plaque: Streptococcus gordonii , Actinomyces oris , Neisseria subflava , and Veillonella parvula . Biofilms containing the early colonizers were developed in a continuous flow bioreactor, exposed to S. mutans , and incubated for up to 7 days. The abundance of bacteria was estimated by quantitative polymerase chain reaction (qPCR). At high glucose and high lactate, the pH in bulk fluid rapidly decreased to approximately 5.2, and S. mutans outgrew other species in biofilms. In low glucose and high lactate, the pH remained above 5.5, and V. parvula was the most abundant species in biofilms. By contrast, in low glucose and low lactate, the pH remained above 6.0 throughout the experiment, and the microbial community in biofilms was relatively balanced. Fluorescence in situ hybridization confirmed that all species were present in the biofilm and the majority of cells were viable using live/dead staining. These data demonstrate that carbon source concentration is critical for microbial homeostasis in model oral biofilms. Furthermore, we established an experimental system that can support the development of computational models to predict transitions to microbial dysbiosis based on metabolic interactions. IMPORTANCE We developed a controlled (by removing host factor) dynamic system metabolically representative of early colonization of Streptococcus mutans not measurable in vivo . Hypotheses on factors influencing S. mutans colonization, such as community composition and inoculation sequence and the effect of metabolite concentrations, can be tested and used to predict the effect of interventions such as dietary modifications or the use of toothpaste or mouthwash on S. mutans colonization. The defined in vitro model (species and medium) can be simulated in an in silico model to explore more of the parameter space.

Denitrifying biofilms, in which autotrophic denitrifiers (AD) and heterotrophic denitrifiers (HD) coexist, play a crucial role in removing nitrate from water or wastewater. However, it is difficult to elucidate the interactions between HD and AD through sequencing-based experimental methods. Here, we developed an individual-based model to describe the interspecies dynamics and priority effects between sulfur-based AD (Thiobacillus denitrificans) and HD (Thauera phenylcarboxya) under different C/N ratios. In test I (coexistence simulation), AD and HD were initially inoculated at a ratio of 1:1. The simulation results showed excellent denitrification performance and a coaggregation pattern of denitrifiers, indicating that cooperation was the predominant interaction at a C/N ratio of 0.25 to 1.5. In test II (invasion simulation), in which only one type of denitrifier was initially inoculated and the other was added at the invasion time, denitrifiers exhibited a stratification pattern in biofilms. When HD invaded AD, the final HD abundance decreased with increasing invasion time, indicating an enhanced priority effect. When AD invaded HD, insufficient organic carbon sources weakened the priority effect by limiting the growth of HD populations. This study reveals the interaction between autotrophic and heterotrophic denitrifiers, providing guidance for optimizing wastewater treatment process.

ABSTRACT Mathematical models can provide insights into complex interactions and dynamics within microbial communities to complement and extend experimental laboratory approaches. For dental biofilms, they can give a basis for evaluating biofilm growth or the transition from health to disease. We have developed mathematical models to simulate the transition toward a cariogenic microbial biofilm, modeled as the overgrowth of Streptococcus mutans within a five-species dental community. This work builds on experimental data from a continuous flow reactor with hydroxyapatite coupons for biofilm growth, in a chemically defined medium with varying concentrations of glucose and lactic acid. The biofilms formed on the coupons were simulated using individual-based models (IbMs), with bacterial growth modeled using experimentally measured kinetic parameters. The IbM assumes that the maximum theoretical growth yield for biomass is dependent on the local concentration of reactants and products, while the growth rates were described using traditional Monod equations. We have simulated all the conditions studied experimentally, considering different initial relative abundance of the five species, and also different initial clustering in the biofilm. The simulation results only reproduced the experimental dominance of S. mutans at high glucose concentration after we considered the species-specific effect of pH on growth rates. This highlights the significance of the aciduric property of S. mutans in the development of caries. Our study demonstrates the potential of combining in vitro and in silico studies to gain a new understanding of the factors that influence dental biofilm dynamics.IMPORTANCEWe have developed in silico models able to reproduce the relative abundance measured in vitro in the synthetic dental biofilm communities growing in a chemically defined medium. The advantage of this combination of in vitro and in silico models is that we can study the influence of one parameter at a time and aim for direct validation. Our work demonstrates the utility of individual-based models for simulating diverse conditions affecting dental biofilm scenarios, such as the frequency of glucose intake, sucrose pulsing, or integration of pathogenic or probiotic species. Although in silico models are reductionist approaches, they have the advantage of not being limited in the scenarios they can test by the ethical consideration of an in vivo system, thus significantly contributing to dental biofilm research.

Biofilms are aggregated bacterial communities structured within an extracellular matrix (ECM). ECM controls biofilm architecture and confers mechanical resistance against shear forces. From a physical perspective, biofilms can be described as colloidal gels, where bacterial cells are analogous to colloidal particles distributed in the polymeric ECM. However, the influence of the ECM in altering the cellular packing fraction (ϕ) and the resulting viscoelastic behavior of biofilm remains unexplored. Using biofilms of Pantoea sp. (WT) and its mutant (ΔUDP), the correlation between biofilm structure and its viscoelastic response is investigated. Experiments show that the reduction of exopolysaccharide production in ΔUDP biofilms corresponds with a seven-fold increase in ϕ, resulting in a colloidal glass-like structure. Consequently, the rheological signatures become altered, with the WT behaving like a weak gel, whilst the ΔUDP displayed a glass-like rheological signature. By co-culturing the two strains, biofilm ϕ is modulated which allows us to explore the structural changes and capture a change in viscoelastic response from a weak to a strong gel, and to a colloidal glass-like state. The results reveal the role of exopolysaccharide in mediating a structural transition in biofilms and demonstrate a correlation between biofilm structure and viscoelastic response.

Why are some groups of bacteria more diverse than others? We hypothesize that the metabolic energy available to a bacterial functional group (a biogeochemical group or 'guild') has a role in such a group's taxonomic diversity. We tested this hypothesis by looking at the metacommunity diversity of functional groups in multiple biomes. We observed a positive correlation between estimates of a functional group's diversity and their metabolic energy yield. Moreover, the slope of that relationship was similar in all biomes. These findings could imply the existence of a universal mechanism controlling the diversity of all functional groups in all biomes in the same way. We consider a variety of possible explanations from the classical (environmental variation) to the 'non-Darwinian' (a drift barrier effect). Unfortunately, these explanations are not mutually exclusive, and a deeper understanding of the ultimate cause(s) of bacterial diversity will require us to determine if and how the key parameters in population genetics (effective population size, mutation rate, and selective gradients) vary between functional groups and with environmental conditions: this is a difficult task.

This theme issue holds contributions from a diverse group of individuals and research groups all dedicated to applying the power and principles of microbial ecology to create the environmental biotechnologies needed in the twenty-first century.These people came together in March 2022 at a Royal Society Theo Murphy meeting to discuss the matter.This is a vibrant field with many opportunities, challenges and barriers.In the final session of the meeting, we had participants break into small groups and asked them to discuss how we could accelerate progress.Progress to develop the new technologies that would help us to solve some of the grand challenges that humanity currently faces.To our surprise, every single group identified the culture of academia as a key issue impeding progress.We learnt that our culture prevents successful cross-disciplinary collaboration.We learnt that the competitive nature of research environments and the lack of inclusivity make us less than the sum of our parts.We heard how the reward structure of academia perversely incentivizes those activities and behaviours that hamper successful trans-disciplinary collaboration.Of course, such a diverse group brought a variety of experiences to the discussion.Some were fortunate to have experienced supportive, collegiate and creative cultures.Others less so.Nevertheless, even the most fortunate of us were touched by the unpleasant consequences of the pervasive rules of the academic game.In order to move faster and more effectively as a field, we need to build a new culture that is focused on collaboration and better solutions rather than one that is centred on competition and metrics.What then is our culture?It is simply the values, norms and behaviours that we espouse as a community.The culture of microbial ecologists and engineering biologists naturally reflects those of our societies and the demands and rewards of our employers and employment, and thus much of twenty-first century science.However, there is no reason to assume or accept that the culture that spontaneously arises is the culture we want.Indeed our colleagues have made it abundantly clear that we do not have the culture we need or desire.We envision a culture that allows all of us to have fulfilling and enriched research careers and to meet the very real societal challenges that we face.The clarion call from our confederates is a clear confirmation that we need to do better in both the quality and the effectiveness of our research environments.We argue that the two are intimately connected; an improved research culture will not simply bring us more fulfilling careers, but also more effective ones.Perhaps one of the most pernicious ideas in contemporary academia is that an unpleasant culture is somehow more effective at creating progress and societal solutions.We contest that tacit assumption.Recognizing and acknowledging that a cultural change is needed is the first step to change.That being said, people have been talking about the ineffective

Abstract Background Inflammation is present in neurological and peripheral disorders. Thus, targeting inflammation has emerged as a viable option for treating these disorders. Previous work indicated pretreatment with beta-funaltrexamine (β-FNA), a selective mu-opioid receptor (MOR) antagonist, inhibited inflammatory signaling in vitro in human astroglial cells, as well as lipopolysaccharide (LPS)-induced neuroinflammation and sickness-like-behavior in mice. This study explores the protective effects of β-FNA when treatment occurs 10 h after LPS administration and is the first-ever investigation of the sex-dependent effects of β-FNA on LPS-induced inflammation in the brain and peripheral tissues, including the intestines. Results Male and female C57BL/6J mice were administered LPS followed by treatment with β-FNA-immediately or 10 h post-LPS. Sickness- and anxiety-like behavior were assessed using an open-field test and an elevated-plus-maze test, followed by the collection of whole brain, hippocampus, prefrontal cortex, cerebellum/brain stem, plasma, spleen, liver, large intestine (colon), proximal small intestine, and distal small intestine. Levels of inflammatory chemokines/cytokines (interferon γ-induced-protein, IP-10 (CXCL10); monocyte-chemotactic-protein 1, MCP-1 (CCL2); interleukin-6, IL-6; interleukin-1β, IL-1β; and tumor necrosis factor-alpha, TNF-α) in tissues were measured using an enzyme-linked immunosorbent assay. Western blot analysis was used to assess nuclear factor-kappa B (NF-κB) expression. There were sex-dependent differences in LPS-induced inflammation across brain regions and peripheral tissues. Overall, LPS-induced CXCL10, CCL2, TNF-α, and NF-κB were most effectively downregulated by β-FNA; and β-FNA effects differed across brain regions, peripheral tissues, timing of the dose, and in some instances, in a sex-dependent manner. β-FNA reduced LPS-induced anxiety-like behavior most effectively in female mice. Conclusion These findings provide novel insights into the sex-dependent anti-inflammatory effects of β-FNA and advance this agent as a potential therapeutic option for reducing both neuroinflammation an intestinal inflammation.

Conventionally, nitrification in biological nitrogen removal (BNR) requires high dissolved oxygen (DO) concentrations (>2 mg L−1), making the process energy intensive. Recent studies have shown that efficient ammonium removal and energy reduction can be realized by operating the nitrification at low DO concentrations (<1 mg L−1). In this study, the low-DO oxic anoxic (low-DO OA) process was operated in a pilot-scale sequencing batch reactor (SBR) over 218 days to evaluate the feasibility of nitrogen removal from low chemical oxygen demand-to-nitrogen ratio (COD/N) tropical municipal wastewater. The results revealed that the low-DO OA process attained high removal efficiency for ammonium (97%) and total nitrogen (TN) (80%) under an average DO concentration of 0.6 mg L−1. The effective TN removal efficiency is attributed to the occurrence of simultaneous nitrification–denitrification (SND) under low DO conditions. Further batch tests revealed that slowly biodegradable COD (sbCOD) in tropical wastewater can support denitrification in the post-anoxic phase, resulting in a high TN removal rate. Compared with high DO concentrations (2 mg L−1), low DO conditions achieved 10% higher TN removal efficiency, with similar ammonium and COD removal efficiency. This study is crucial in promoting the energy efficiency and sustainability of wastewater treatment plants treating low COD/N wastewater.

Proper function of a wastewater treatment plant (WWTP) relies on maintaining a delicate balance between a multitude of competing microorganisms. Gaining a detailed understanding of the complex network of interactions therein is essential to maximising not only current operational efficiencies, but also for the effective design of new treatment technologies. Metagenomics offers an insight into these dynamic systems through the analysis of the microbial DNA sequences present. Unique taxa are inferred through sequence clustering to form operational taxonomic units (OTUs), with per-taxa abundance estimates obtained from corresponding sequence counts. The data in this study comprise weekly OTU counts from an activated sludge (AS) tank of a WWTP. To model the OTU dynamics, we develop a Bayesian hierarchical vector autoregressive model, which is a linear approximation to the commonly used generalised Lotka-Volterra (gLV) model. To tackle the high dimensionality and sparsity of the data, they are first clustered into 12 "bins" using a seasonal phase-based approach. The autoregressive coefficient matrix is assumed to be sparse, so we explore different shrinkage priors by analysing simulated data sets before selecting the regularised horseshoe prior for the biological application. We find that ammonia and chemical oxygen demand have a positive relationship with several bins and pH has a positive relationship with one bin. These results are supported by findings in the biological literature. We identify several negative interactions, which suggests OTUs in different bins may be competing for resources and that these relationships are complex. We also identify two positive interactions. Although simpler than a gLV model, our vector autoregression offers valuable insight into the microbial dynamics of the WWTP.

Research on the role of gut microbiota in behavior has grown dramatically. The probiotic L. reuteri can alter social and stress-related behaviors – yet, the underlying mechanisms remain largely unknown. Although traditional laboratory rodents provide a foundation for examining the role of L. reuteri on the gut-brain axis, they do not naturally display a wide variety of social behaviors. Using the highly-social, monogamous prairie vole (Microtus ochrogaster), we examined the effects of L. reuteri administration on behaviors, neurochemical marker expression, and gut-microbiome composition. Females, but not males, treated with live L. reuteri displayed lower levels of social affiliation compared to those treated with heat-killed L. reuteri. Overall, females displayed a lower level of anxiety-like behaviors than males. Live L. reuteri-treated females had lower expression of corticotrophin releasing factor (CRF) and CRF type-2-receptor in the nucleus accumbens, and lower vasopressin 1a-receptor in the paraventricular nucleus of the hypothalamus (PVN), but increased CRF in the PVN. There were both baseline sex differences and sex-by-treatment differences in gut microbiome composition. Live L. reuteri increased the abundance of several taxa, including Enterobacteriaceae, Lachnospiraceae NK4A136, and Treponema. Interestingly, heat-killed L. reuteri increased abundance of the beneficial taxa Bifidobacteriaceae and Blautia. There were significant correlations between changes in microbiota, brain neurochemical markers, and behaviors. Our data indicate that L. reuteri impacts gut microbiota, gut-brain axis and behaviors in a sex-specific manner in socially-monogamous prairie voles. This demonstrates the utility of the prairie vole model for further examining causal impacts of microbiome on brain and behavior.

&lt;p&gt;There has been a large output of genomic data in ecological studies of centralised wastewater treatment plants over the past number of years. One significant collaboration of Danish and Swedish research institutions lead to the development of the Microbes of Activated Sludge and Anaerobic Digesters (MiDAS 4) global taxonomic database. The database has been an effective tool in understanding centralised systems, however, there has been no known application of this tool in understanding the ecology of organisms in the on-site wastewater treatment systems. The growth of microbial mats or &quot;biomats&quot; has been identified as an essential component in the attenuation of pollutants within the soil treatment unit (STU) of conventional on-site wastewater treatment systems (OWTSs). Two research sites were employed to determine the influence of the pre-treatment of raw-domestic wastewater on these communities. The STUs at each of the two sites were split, whereby half received effluent directly from septic tanks, and half received more highly treated effluents from packaged aerobic treatment systems [a coconut husk media filter on one site, and a rotating biodisc contactor (RBC) on the other site]. Effluents from the RBC had a higher level of pre-treatment [~90% Total Organic Carbon (TOC) removal], compared to the media filter (~60% TOC removal). &amp;#160;These sites&#039; biomat were sampled two-dimensionally in respect of distance and depth, to configure ecological data with changes in the volumetric water content values which had been used successfully as an indicator of the location of the biomat. A total of 92 samples were obtained from both STU locations and characterized by MiDAS taxonomic database. Our study has shown that the biomats receiving primary or untreated effluent have less pronounced increases in denitrifiers compared to the biomats receiving treated or partially treated effluent. but biomats receiving primary effluents have been found to be capable of removing six times the amount of total nitrogen. This suggests that the increases in functional richness within the STU are secondary to bioclogging, as metabolic rates could be limited by hydraulic conductivity.&lt;/p&gt;

The accuracy of water quality predictions is essential, especially in countries affected by climate change and ecological water diversity. Water quality modelling in rivers is a valuable tool for enabling decision-making in surface water management because water quality prediction using sampling methods is expensive and time-consuming. The collection of technical knowledge of river characteristics and information about the sources of pollution plays a vital role in this context. This research focused on the effects of river geometry and meandering on the one-dimensional pollutant transport process. Flow velocity magnitude and direction in meandering rivers are frequently variable, leading to uncertain dispersion coefficients and massive changes in pollution concentration even over short distances of these rivers. So, the geometry of meandering rivers has a significant effect on their ecological indicators. A new coefficient called Fatigue Factor was introduced and defined in this study to consider this effect. Colidale Beck (CB) and Tyne rivers were selected for water quality modelling and implementation of the Fatigue Factor. The simulation-optimization method was employed to calculate zinc concentrations along the CB river using measured data for performance assessment of the model. The genetic algorithm performed well in predicting measured zinc concentration with high accuracy. Results of the model demonstrated that the mean effect of the Fatigue Factor in reducing the peak concentration of zinc increases by 3.8% compared to ignoring the Fatigue Factor along the CB length. With the Fatigue Factor consideration, the Mean Percentage Error between model outputs and measured data is 4%, while without it is 18%. Also, the Fatigue Factor had a greater impact on river pollution transport than the dispersion coefficient. With a 50% increase in the Fatigue Factor, the zinc concentration decreased by 6.1% more than the same increase in the dispersion coefficient. Moreover, results indicated that a 100% increment in the Fatigue Factor increases the assimilation capacity up to 3.5 times in CB.

Metagenomics sequencing has generated millions of new protein sequences, most of them with unknown functions. A relatively quick first step for function assignment is to use the existing public protein databases and their scanning tools. However, to date these tools are not able to identify all sequence features like conserved motifs or patterns. In this study we evaluated the capability of several protein public databases (e.g., InterPro, PROSITE, ESTHER, pfam, AlphaFold etc) and their scanning tools for identifying lipolytic features in 78 putative cold-adapted bacterial lipase sequences. Novel lipases that can tolerate extreme conditions have great biotechnological importance. We obtained the putative cold-adapted lipolytic sequences from the metagenomic study of anaerobic psychrophilic microbial community treating domestic wastewater at 4 and 15 ℃. Both newer and conventional protein classifiers failed to find lipolytic features for most of the putative lipases. InterProScan predicted lipase family membership for only 18 of the putative lipase sequences. For more than half of them (41 out of 78) InterProScan could not predict any protein family membership, let alone find lipolytic features in them. However, when the Lipase Engineering Database and AlphaFold were used, half of those sequences were classified. Conventional databases like PROSITE could find lipolytic patterns for 9 of the putative lipolytic sequences of which only one was identified by InterProScan as a lipase. Moreover, different scanning tools made different and inconsistent predictions for a certain putative lipase sequence. Even InterProScan, which integrates predictions from 13 protein member databases, did not have a consensus prediction for a certain lipase sequence. Our study shows that there is lack of information in public protein databases about bacterial lipase sequences and this limits their lipolytic feature prediction and biotechnological application. The integration of AlphaFold within the InterPro can improve the lipase identification and classification significantly.