Development of a logic regression-based approach for the discovery of host- and niche-informative biomarkers in Escherichia coli and their application for microbial source tracking.

Microbial source tracking leverages a wide range of approaches designed to trace the origins of fecal contamination in aquatic environments. Although source tracking methods are typically employed within the laboratory setting, computational techniques can be leveraged to advance microbial source tracking methodology. Herein, we present a logic regression-based supervised learning approach for the discovery of source-informative genetic markers within intergenic regions across the Escherichia coli genome that can be used for source tracking. With just single intergenic loci, logic regression was able to identify highly source-specific (i.e., exceeding 97.00%) biomarkers for a wide range of host and niche sources, with sensitivities reaching as high as 30.00%-50.00% for certain source categories, including pig, sheep, mouse, and wastewater, depending on the specific intergenic locus analyzed. Restricting the source range to reflect the most prominent zoonotic sources of E. coli transmission (i.e., bovine, chicken, human, and pig) allowed for the generation of informative biomarkers for all host categories, with specificities of at least 90.00% and sensitivities between 12.50% and 70.00%, using the sequence data from key intergenic regions, including emrKY-evgAS, ibsB-(mdtABCD-baeSR), ompC-rcsDB, and yedS-yedR, that appear to be involved in antibiotic resistance. Remarkably, we were able to use this approach to classify 48 out of 113 river water E. coli isolates collected in Northwestern Sweden as either beaver, human, or reindeer in origin with a high degree of consensus-thus highlighting the potential of logic regression modeling as a novel approach for augmenting current source tracking efforts.IMPORTANCEThe presence of microbial contaminants, particularly from fecal sources, within water poses a serious risk to public health. The health and economic burden of waterborne pathogens can be substantial-as such, the ability to detect and identify the sources of fecal contamination in environmental waters is crucial for the control of waterborne diseases. This can be accomplished through microbial source tracking, which involves the use of various laboratory techniques to trace the origins of microbial pollution in the environment. Building on current source tracking methodology, we describe a novel workflow that uses logic regression, a supervised machine learning method, to discover genetic markers in Escherichia coli, a common fecal indicator bacterium, that can be used for source tracking efforts. Importantly, our research provides an example of how the rise in prominence of machine learning algorithms can be applied to improve upon current microbial source tracking methodology.

Fecal indicator organisms in northern oligotrophic rivers: An explorative study on Escherichia coli prevalence in a mountain region with intense tourism and reindeer herding.

Increasing pollution levels in waters from remote mountain areas in northern Sweden have been observed. To support a sustainable water quality management, it is necessary to know which environmental and antrophogenic factors influence the water quality. The purpose of this study was to map the Escherichia coli prevalence in the catchment area of the upper part of a large northern Scandinavian river and investigate the controlling factors of microbial contamination. A total of 112 water samples were collected from various locations in the research area between July 2020 and December 2020. These samples were analyzed for microbial and chemical characteristics, and information about tourism and reindeer herding was compiled. Additionally, microbial and physicochemical water characteristics collected by Indalsälven Water Conservation Association (IWCA, 1993-2020) and Swedish Meteorological and Hydrological Institute (SMHI, 2004-2020) were analyzed. The results showed that E. coli enumerations ranged between 0 and 500 CFU/100 ml. There was generally no obvious relation between suspected point sources, e.g., sewage treatment plants at mountain stations, and E. coli levels at downstream sampling points. Principal component analysis showed that E. coli was correlated to coliforms, total heterotrophic count, river discharge, CODMn and river color. Since microbial analyses are time-consuming, expensive and difficult to perform in remote areas, it is important to find more easily extracted water parameters that can serve as a proxy for E. coli. In particular, river color and discharge are promising parameters that may serve as an early indication of bacterial outbreak and fecal contamination in mountain waters.

Effect of pine bark on the biotransformation of trinitrotoluene and on the bacterial community structure in a batch experiment.

Pine bark, a low-cost industrial residue, has been suggested as a promising substitute for granular activated carbon in the on-site treatment of water contaminated with 2,4,6-trinitrotoluene (TNT). However, the complex organic structure and indigenous microbial community of pine bark have thus far not been thoroughly described in the context of TNT-contaminated water treatment. This two-week batch study examined the removal efficiency ofTNT from water by (1) adsorption on pine bark and (2) simultaneous adsorption on pine bark and biotransformation by specialized TNT-biotransforming microbial inocula. The bacterial community composition of experimental batches, inocula and pine bark, was profiled by Illumina sequencing of the V6 region of the 16S rRNA gene. The results revealed that the inocula and experimental batches were dominated by phylotypes belonging to the Enterobacteriaceae family and that the tested inocula had good potential for TNT biotransformation. The type of applied inocula had the most profound effect on the TNT-transforming bacterial community structure in the experimental batches. The indigenous microbial community of pine bark harboured phylotypes that also have a potential to degrade TNT. Altogether, the combination of a specialized inoculum and pine bark proved to be the most efficient treatment option for TNT-contaminated water.

Applications of optical sensing and imaging spectroscopy in indoor farming: A systematic review.

As demand for food continues to rise, innovative methods are needed to sustainably and efficiently meet the growing pressure on agriculture. Indoor farming and controlled environment agriculture have emerged as promising approaches to address this challenge. However, optimizing fertilizer usage, ensuring homogeneous production, and reducing agro-waste remain substantial challenges in these production systems. One potential solution is the use of optical sensing technology, which can provide real-time data to help growers make informed decisions and enhance their operations. optical sensing can be used to analyze plant tissues, evaluate crop quality and yield, measure nutrients, and assess plant responses to stress. This paper presents a systematic literature review of the current state of using spectral-optical sensors and hyperspectral imaging for indoor farming, following the PRISMA 2020 guidelines. The study surveyed existing studies from 2017 to 2023 to identify gaps in knowledge, provide researchers and farmers with current trends, and offer recommendations and inspirations for possible new research directions. The results of this review will contribute to the development of sustainable and efficient methods of food production.

Applying the Triad method in a risk assessment of a former surface treatment and metal industry site.

With a greater focus on soil protection in the E.U., the need for ecological risk assessment tools for cost-effective characterization of site contamination is increasing. One of the challenges in assessing the risk of soil contaminants is to accurately account for changes in mobility of contaminants over time, as a result of ageing. Improved tools for measuring the bioavailable and mobile fraction of contaminants is therefore highly desirable. In this study the Triad method was used to perform a risk characterization of a former surface treatment and metal industry in Eskilstuna, Sweden. The risk assessment confirmed the environmental risk of the most heavily contaminated sample and showed that the toxic effect was most likely caused by high metal concentrations. The assessment of the two soil samples with low to moderate metal contamination levels was more complex, as there was a higher deviation between the results from the three lines of evidence; chemistry, (eco)toxicology and ecology. For the slightly less contaminated sample of the two, a weighting of the results from the ecotoxicological LoE would be recommended in order to accurately determine the risk of the metal contamination at the sampling site as the toxic effect detected in the Microtox® test and Ostracodtoxkit™ test was more likely to be due to oil contamination. The soil sample with higher total metal concentrations requires further ecotoxicological testing, as the integrated risk value indicated an environmental risk from metal contamination. The applied methodology, the Triad method, is considered appropriate for conducting improved environmental risk assessments in order to achieve sustainable remediation processes.

Ecotoxicological assessment and evaluation of a pine bark biosorbent treatment of five landfill leachates.

When selecting a landfill leachate treatment method the contaminant composition of the leachate should be considered in order to obtain the most cost-effective treatment option. In this study the filter material pine bark was evaluated as a treatment for five landfill leachates originating from different cells of the same landfill in Sweden. The objective of the study was to determine the uptake, or release, of metals and dissolved organic carbon (DOC) during a leaching test using the pine bark filter material with the five different landfill leachates. Furthermore the change of toxicity after treatment was studied using a battery of aquatic bioassays assessing luminescent bacteria (Vibrio fischeri) acute toxicity (30-min Microtox®), immobility of the crustacean Daphnia magna, growth inhibition of the algae Pseudokirchneriella subcapitata and the aquatic plant Lemna minor; and genotoxicity with the bacterial Umu-C assay. The results from the toxicity tests and the chemical analysis were analyzed in a Principal Component Analysis and the toxicity of the samples before and after treatment was evaluated in a toxicity classification. The pine bark filter material reduced the concentrations of metal contaminants from the landfill leachates in the study, with some exceptions for Cu and Cd. The Zn uptake of the filter was high for heavily contaminated leachates (≥73%), although some desorption of zinc occurred in less contaminated waters. Some of the leachates may require further treatment due to discharge into a natural recipient in order to reduce the risk of possible biological effects. The difference in pH changes between the different leachates was probably due to variations in buffering capacity, affected by physicochemical properties of the leachate. The greatest desorption of phenol during filtration occurred in leachates with high conductivity or elevated levels of metals or salts. Generally, the toxicity classification of the leachates implies that although filter treatment with pine bark removes metal contaminants from the leachates effectively, it does not alter leachate toxicity noticeably. The leachates with the highest conductivity, pH and metal concentrations are most strongly correlated with an increased toxic response in the score plots of both untreated and treated leachates. This is in line with the toxicity classification of the leachate samples. The results from this study highlight the importance of evaluating treatment efficiency from the perspective of potential recipient effects, rather than in terms of residual concentrations of individual contaminants when treating waters with a complex contamination matrix, such as landfill leachates.

Leaching of contaminants from untreated pine bark in a batch study: chemical analysis and ecotoxicological evaluation.

Low cost sorbents have been widely studied in recent years in the search for filter materials that retain contaminants from water. One promising, low cost material is pine bark, a by-product from the forest industry. Many studies have shown that pine bark has great potential for the treatment of metals and organic substances, as a replacement for other commercial sorbents such as active carbon. However, some potential problems are introduced through the use of natural materials and by-products. One such problem that must be addressed is the possibility of leaching of contaminants from the filter material, especially in the initial filtration step or during flushes of lightly contaminated water, e.g. during rainfall for on-site treatment of storm water or landfill leachate. The aim of this preliminary study was therefore to identify potential risks and limitations of using pine bark as a filter material. Leachate from a standardized batch test was analysed for metals, dissolved organic carbon (DOC) and phenols. In addition to these chemical analyses, an ecotoxicological test was conducted using the test organism Daphnia magna. The results showed significant leaching of DOC and some metals. Only a small fraction of the DOC was present as phenols. The leachate was however found to be toxic to the test organism without pH adjustment, and the EC(50) was established at an approximate leachate concentration of 40%. This was concluded to be related to the low pH in the eluate, since no toxicity was observed after pH adjustment before the toxicity tests.