Monitoring, assessment, and prediction of microbial shifts in coupled catalysis and biodegradation of 1,4-dioxane and co-contaminants

Yu, Miao; Johnson, Nicholas W.; Phan, Thien; Heck, Kimberly N.; Gedalanga, Phillip B.; Zheng, Xiaoru; Adamson, David T.; Newell, Charles J.; Wong, Michael S.; Mahendra, Shaily

doi:10.1016/j.watres.2020.115540

Cited by 47 publications

(19 citation statements)

References 66 publications

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“…Cooperative bacterial interactions supporting biodegradation of dichloromethanes have been reported (Chen et al 2017 ) and if this is the case in the current studies, these bacteria would be included in the total bacterial quantification. As qPCR approaches are limited to detection of only known groups participating in PCE degradation, broader approaches such as bacterial community or metagenomics approaches, or both (Miao et al 2020 ) could further resolve the bacteria participating in degradation at this site. Costs for these types of analysis continue to fall, and more nuanced and detailed analysis of the microbial processes can be made to explain the distribution of chemical moieties detected, although as they also involve PCR-based amplification, the impact of inhibitory compounds should also be considered in this context (Sidstedt et al 2019 ).…”

Section: Discussionmentioning

confidence: 99%

Characterizing natural degradation of tetrachloroethene (PCE) using a multidisciplinary approach

Åkesson

Sparrenbom

Paul

et al. 2020

Ambio

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A site in mid-western Sweden contaminated with chlorinated solvents originating from a previous dry cleaning facility, was investigated using conventional groundwater analysis combined with compound-specific isotope data of carbon, microbial DNA analysis, and geoelectrical tomography techniques. We show the value of this multidisciplinary approach, as the different results supported each interpretation, and show where natural degradation occurs at the site. The zone where natural degradation occurred was identified in the transition between two geological units, where the change in hydraulic conductivity may have facilitated biofilm formation and microbial activity. This observation was confirmed by all methods and the examination of the impact of geological conditions on the biotransformation process was facilitated by the unique combination of the applied methods. There is thus significant benefit from deploying an extended array of methods for these investigations, with the potential to reduce costs involved in remediation of contaminated sediment and groundwater.

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Section: Discussionmentioning

confidence: 99%

Characterizing natural degradation of tetrachloroethene (PCE) using a multidisciplinary approach

Åkesson

Sparrenbom

Paul

et al. 2020

Ambio

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“…Typically, some trade-off must be made in the experimental design, for which options have been suggested ( Franzosa et al, 2015 ). In metataxonomics, resolution is usually limited to the genus level, though it is the most commonly used omics input for SML ( Table 1 ), wherein relative operational taxonomic unit (OTU) abundances form the feature set ( Miao et al, 2020 ; Janßen et al, 2021 ; Kim and Oh, 2021 ). However, the use of OTUs is inherently limiting for retaining community information and can miss important taxonomic groups.…”

Section: Main Bodymentioning

confidence: 99%

Interfacing Machine Learning and Microbial Omics: A Promising Means to Address Environmental Challenges

et al. 2022

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Microbial communities are ubiquitous and carry an exceptionally broad metabolic capability. Upon environmental perturbation, microbes are also amongst the first natural responsive elements with perturbation-specific cues and markers. These communities are thereby uniquely positioned to inform on the status of environmental conditions. The advent of microbial omics has led to an unprecedented volume of complex microbiological data sets. Importantly, these data sets are rich in biological information with potential for predictive environmental classification and forecasting. However, the patterns in this information are often hidden amongst the inherent complexity of the data. There has been a continued rise in the development and adoption of machine learning (ML) and deep learning architectures for solving research challenges of this sort. Indeed, the interface between molecular microbial ecology and artificial intelligence (AI) appears to show considerable potential for significantly advancing environmental monitoring and management practices through their application. Here, we provide a primer for ML, highlight the notion of retaining biological sample information for supervised ML, discuss workflow considerations, and review the state of the art of the exciting, yet nascent, interdisciplinary field of ML-driven microbial ecology. Current limitations in this sphere of research are also addressed to frame a forward-looking perspective toward the realization of what we anticipate will become a pivotal toolkit for addressing environmental monitoring and management challenges in the years ahead.

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“…This is particularly important for angstrom-scale separations. Within this range, a number of critical and rewarding applications exist: pharmaceutical and antibiotics separations (Harrison et al, 2015;, extraction and recovery of highly valuable metals including light lithium (Liu et al, 2019a), heavy metals (Barakat, 2011;Pollmann et al, 2016;Falagán et al, 2017), noble metals and rare earth elements (Hodnik et al, 2016;Yang et al, 2017;Balaram, 2019;Cheisson and Schelter, 2019), oil and gas refinery (Peng et al, 2018), gas separations (Dalane et al, 2017), separation of challenging environmental co-contaminants (Madsen et al, 2015;Miao et al, 2020) (such as 1,4-dioxane and coexisting chlorinated solvents that are similar in size and shapes). All these applications involve filtrate molecules with similar dimensions, polarities or charges from a few hundred to several thousand Dalton.…”

Section: Future Direction Of Bioinspired and Biomimetic Membranesmentioning

confidence: 99%

Bioinspired and biomimetic membranes for water purification and chemical separation: A review

Abaie

Shen

2021

Front. Environ. Sci. Eng.

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Bioinspired and biomimetic membranes that contain biological transport channels or attain their structural designs from biological systems have been through a remarkable development over the last two decades. They take advantage of the exceptional transport properties of those channels, thus possess both high permeability and selectivity, and have emerged as a promising solution to existing membranes. Since the discovery of biological water channel proteins aquaporins (AQPs), extensive efforts have been made to utilize them to make separation membranes-AQP-based membranes, which have been commercialized. The exploration of AQPs’ unique structures and transport properties has resulted in the evolution of biomimetic separation materials from protein-based to artificial channel-based membranes. However, large-scale, defect-free biomimetic membranes are not available yet. This paper reviews the state-of-the-art biomimetic membranes and summarizes the latest research progress, platform, and methodology. Then it critically discusses the potential routes of this emerging area toward scalable applications. We conclude that an appropriate combination of bioinspired concepts and molecular engineering with mature polymer industry may lead to scalable polymeric membranes with intrinsic selective channels, which will gain the merit of both desired selectivity and scalability.

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Monitoring, assessment, and prediction of microbial shifts in coupled catalysis and biodegradation of 1,4-dioxane and co-contaminants

Cited by 47 publications

References 66 publications

Characterizing natural degradation of tetrachloroethene (PCE) using a multidisciplinary approach

Characterizing natural degradation of tetrachloroethene (PCE) using a multidisciplinary approach

Interfacing Machine Learning and Microbial Omics: A Promising Means to Address Environmental Challenges

Bioinspired and biomimetic membranes for water purification and chemical separation: A review

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