Mid Sweden University

Aquatic ecosystems in mountainous regions are crucial for fulfilling natural and anthropogenic water demands around the world. This study integrates Escherichia coli (E. coli) enumeration, microbial source tracking (MST), and environmental DNA (eDNA) analysis to identify sources of fecal contamination in oligotrophic mountain waters. Conducted in an area with intense tourism and traditional reindeer herding, this research addresses the urgent need to identify fecal pollution sources to safeguard the water quality of these vital ecosystems. Our study reveals that E. coli levels vary significantly across different locations and times, suggesting varied sources of contamination from humans, wildlife, and livestock animals. MST techniques, alongside eDNA analysis, provided insights into the complex patterns of fecal pollution, allowing for the distinction between human and animal contributions to water contamination. Our findings highlight the importance of combining various analytical methods to track fecal pollution sources effectively, and to develop targeted strategies for water quality management.

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.

The Intergovernmental Panel on Climate Change (IPCC) points out alpine regions worldwide as climate change hotspots. Expanding and diversifying summer tourism in northern Scandinavian mountains exerts additional severe pressure to these areas and their oligotrophic and sensitive aquatic ecosystems. Previous research at Mid Sweden University has shown that fecal contamination of mountain rivers, indicated by the enumeration of E. coli, is frequent in areas that are intensively being used for tourism and reindeer herding. According to the IPCC, climate change is projected to reduce raw water quality, posing risks to drinking water quality even with conventional treatment. Therefore, there is an urgent need for improved monitoring of water quality in such areas to be able to protect the ecosystem as well as the rights of indigenous people, human and animal health and to provide support for water management decision. To be able to monitor the water quality is of great importance for the sustainability of mountain regions and water sources in general. The inaccessibility of the watercourses in remote mountain areas makes it difficult to establish sufficient monitoring programs.

In this research, the use of airborne monitoring systems to assess water quality in remote regions is investigated. Remote monitoring systems based on e.g. drones and satellites have the potential to replace less climate friendly options making use of terrain vehicles, snow mobiles and helicopters. The drones can be equipped with various sensors or sampling equipment, can overcome long transportations as well as time-consuming and expensive field samplings. Drones have great potential to be employed in everyday practices as an essential part of decision support systems for monitoring, evaluation and remediation of contaminated sites. The goal is to use drones to establish water quality monitoring programs in remote regions such as the mountain areas of Northern Sweden. In this research we intend to cover the catchment area of upper parts of river Indalsälven situated in the mountain region on the Swedish/Norwegian border, including the catchment areas of the tributaries Handölan and Enan covering approximately 777km².

One approach in this research is to image large areas of interest by the use of a multispectral camera on a drone and to identify spectral bands or band ratio´s which correlate to physicochemical parameters that are related to water quality. Another approach is to further explore the use of dronebased water sampling for laboratory or in-field analysis of microbial and chemical parameters.

Both approaches should eventually lead to the development of a drone-based monitoring program for oligotrophic rivers that can image or measure water pollution with sufficient spatial coverage and time resolution to enable early warning of outbreaks of fecal pollution. Results of this research will contribute to SDG 6, targets 3 and 6 and SDG 14. 

Most biofilms within the food industry are formed by multiple bacterial specieswhich co-exist on surfaces as a result of interspecies interactions. These ecologicalinteractions often make these communities tolerant against antimicrobials.Our previous work led to the identification of a large number (327) of highlydiverse bacterial species on food contact surfaces of the dairy, meat, and eggindustries after routine cleaning and disinfection (C&D) regimes. In the currentstudy, biofilm-forming ability of 92 bacterial strains belonging to 26 genera and42 species was assessed and synergistic interactions in biofilm formation wereinvestigated by coculturing species in all possible four-species combinations.Out of the total 455 four-species biofilm combinations, greater biofilm massproduction, compared to the sum of biofilm masses of individual species inmonoculture, was observed in 34 combinations. Around half of the combinationsshowed synergy in biofilm mass > 1.5-fold and most of the combinations belongedto dairy strains. The highest synergy (3.13-fold) was shown by a combination ofdairy strains comprising Stenotrophomonas rhizophila, Bacillus licheniformis,Microbacterium lacticum, and Calidifontibacter indicus. The observed synergy inmixed biofilms turned out to be strain-specific rather than species-dependent.All biofilm combinations showing remarkable synergy appeared to have certaincommon species in all combinations which shows there are keystone industryspecificbacterial species which stimulate synergy or antagonism and this mayhave implication for biofilm control in the concerned food industries.

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.

The naturally oligotrophic rivers in northern Sweden are generally characterized by a low pollution level. However, an increasing trend in E. coli contamination has been observed in the most upstream catchment area of one of the large rivers of Norhtern Sweden. This change in microbial water quality will have a severe negative impact on the ecosystem, wild animals, visitors, inhabitants as well as indigenous people dependent on the land for their daily income, such as Sami herders. To limit or prevent the discharge of fecal pollution into the river system and also to estimate the danger that this contamination can pose to human health, it is important to know the source of this contamination. Based solely on structured water sampling, it is still very difficult to pinpoint the sources of fecal pollution. Therefore, a combined analysis of eDNA and microbial source tracking of E. coli isolates from river samples was performed to identify the source of fecal pollution in the research area. E. coli isolates were collected from water samples taken along the tributaries Enan and Handölan. Simultaneously, eDNA samples were collected on the same locations. Additionally, fecal and sewage samples were taken to collect E. coli isolates with a known host source being either human, beaver or reindeer. Also, sequences from genomic E. coli DNA originating from human (obtained from NCBI and University of Alberta, School of Public Health) and from beaver (obtained from University of Alberta, School of Public Health) were collected and included in the study. E. coli isolates were used for the amplification of three Intergenic Regions and subsequent analysis of Single Nucleotide Polymorphisms to identify host-specific genetic markers in the E. coli genome. eDNA samples were subjected to metabarcoding targeting mammal DNA to determine the relative species abundance in the water samples. The E. coli prevalence in the research area varies between <1 and 210 CFU/100mL and is dependent on e.g. sampling location (possible point sources), time (tourist intensity and area specific events such as reindeer calve marking) and weather (precipitation, river flow, UV radiation). A library containing the data from E. coli isolates that are known to be originating from the species human, beaver and reindeer was developed and used to identify the host source of the E. coli isolates collected from water samples. Consequently, E. coli isolates could be identified as originating from human, beaver, reindeer or a different mammal species. Results from the eDNA analysis provides information about the relative abundance of mammal species on a certain location. Although these results don´t provide a direct link to the presence or absence of fecal pollution by these species, it can provide interesting knowledge about the source of fecal pollution when combined with the E. coli prevalence data from the same sampling locations and times.

Background: Environmental biofilms can induce attachment and protection of other microorganisms includingpathogens, but can also prevent them from invasion and colonization. This opens the possibility for so-calledbiocontrol strategies, wherein microorganisms are applied to control the presence of other microbes. The potentialfor both positive and negative interactions between microbes, however, raises the need for in depthcharacterization of the sociobiology of candidate biocontrol agents (BCAs). The inside of the drinking water system(DWS) of broiler houses is an interesting niche to apply BCAs, because contamination of these systems withpathogens plays an important role in the infection of broiler chickens and consequently humans. In this study,Pseudomonas putida, which is part of the natural microbiota in the DWS of broiler houses, was evaluated as BCA against the broiler pathogen Salmonella Java.

Results: To study the interaction between these species, an in vitro model was developed simulating biofilmformation in the drinking water system of broilers. Dual-species biofilms of P. putida strains P1, P2, and P3 with S.Java were characterized by competitive interactions, independent of P. putida strain, S. Java inoculum density andapplication order. When equal inocula of S. Java and P. putida strains P1 or P3 were simultaneously applied, theinteraction was characterized by mutual inhibition, whereas P. putida strain P2 showed an exploitation of S. Java.Lowering the inoculum density of S. Java changed the interaction with P. putida strain P3 also into an exploitationof S. Java. A further increase in S. Java inhibition was established by P. putida strain P3 forming a mature biofilmbefore applying S. Java.

Conclusions: This study provides the first results showing the potential of P. putida as BCA against S. Java in thebroiler environment. Future work should include more complex microbial communities residing in the DWS,additional Salmonella strains as well as chemicals typically used to clean and disinfect the system.

After cleaning and disinfection (C&D), surface contamination can still be present in the production environment of foodcompanies. Microbiological contamination on cleaned surfaces can be transferred to the manufactured food and consequentlylead to foodborne illness and early food spoilage. However, knowledge about the microbiological composition of residualcontamination after C&D and the effect of this contamination on food spoilage is lacking in various food sectors. In this study,we identified the remaining dominant microbiota on food contact surfaces after C&D in seven food companies and assessed thespoilage potential of the microbiota under laboratory conditions. The dominant microbiota on surfaces contaminated at 102CFU/100 cm2 after C&D was identified based on 16S rRNA sequences. The ability of these microorganisms to hydrolyzeproteins, lipids, and phospholipids, ferment glucose and lactose, produce hydrogen sulfide, and degrade starch and gelatin alsowas evaluated. Genera that were most abundant among the dominant microbiota on food contact surfaces after C&D werePseudomonas, Microbacterium, Stenotrophomonas, Staphylococcus, and Streptococcus. Pseudomonas spp. were identified infive of the participating food companies, and 86.8% of the isolates evaluated had spoilage potential in the laboratory tests.Microbacterium and Stenotrophomonas spp. were identified in five and six of the food companies, respectively, and all testedisolates had spoilage potential. This information will be useful for food companies in their quest to characterize surfacecontamination after C&D, to identify causes of microbiological food contamination and spoilage, and to determine the need formore thorough C&D.

Background: Water quality in the drinking water system (DWS) plays an important role in the general health andperformance of broiler chickens. Conditions in the DWS of broilers are ideal for microbial biofilm formation. Sincepathogens might reside within these biofilms, they serve as potential source of waterborne transmission ofpathogens to livestock and humans. Knowledge about the presence, importance and composition of biofilms inthe DWS of broilers is largely missing. In this study, we therefore aim to monitor the occurrence, and chemicallyand microbiologically characterise biofilms in the DWS of five broiler farms.Results: The bacterial load after disinfection in DWSs was assessed by sampling with a flocked swab followed byenumerations of total aerobic flora (TAC) and Pseudomonas spp. The dominant flora was identified and theirbiofilm-forming capacity was evaluated. Also, proteins, carbohydrates and uronic acids were quantified to analysethe presence of extracellular polymeric substances of biofilms. Despite disinfection of the water and the DWS, averageTAC was 6.03 ± 1.53 log CFU/20cm2. Enumerations for Pseudomonas spp. were on average 0.88 log CFU/20cm2 lower.The most identified dominant species from TAC were Stenotrophomonas maltophilia, Pseudomonas geniculata andPseudomonas aeruginosa. However at species level, most of the identified microorganisms were farm specific. Almostall the isolates belonging to the three most abundant species were strong biofilm producers. Overall, 92% of all testedmicroorganisms were able to form biofilm under lab conditions. Furthermore, 63% of the DWS surfaces appeared tobe contaminated with microorganisms combined with at least one of the analysed chemical components, which isindicative for the presence of biofilm.Conclusions: Stenotrophomonas maltophilia, Pseudomonas geniculata and Pseudomonas aeruginosa are considered asopportunistic pathogens and could consequently be a potential risk for animal health. Additionally, the biofilm-formingcapacity of these organisms could promote attachment of other pathogens such as Campylobacter spp. andSalmonella spp.

Biofilms are an important source of contamination in food companies, yet the composition of biofilms in practice is stillmostly unknown. The chemical and microbiological characterization of surface samples taken after cleaning and disinfection isvery important to distinguish free-living bacteria from the attached bacteria in biofilms. In this study, sampling methods that arepotentially useful for both chemical and microbiological analyses of surface samples were evaluated. In the manufacturingfacilities of eight Belgian food companies, surfaces were sampled after cleaning and disinfection using two sampling methods:the scraper–flocked swab method and the sponge stick method. Microbiological and chemical analyses were performed on thesesamples to evaluate the suitability of the sampling methods for the quantification of extracellular polymeric substancecomponents and microorganisms originating from biofilms in these facilities. The scraper–flocked swab method was mostsuitable for chemical analyses of the samples because the material in these swabs did not interfere with determination of thechemical components. For microbiological enumerations, the sponge stick method was slightly but not significantly moreeffective than the scraper–flocked swab method. In all but one of the facilities, at least 20% of the sampled surfaces had more than102 CFU/100 cm2. Proteins were found in 20% of the chemically analyzed surface samples, and carbohydrates and uronic acidswere found in 15 and 8% of the samples, respectively. When chemical and microbiological results were combined, 17% of thesampled surfaces were contaminated with both microorganisms and at least one of the analyzed chemical components; thus, thesesurfaces were characterized as carrying biofilm. Overall, microbiological contamination in the food industry is highly variable byfood sector and even within a facility at various sampling points and sampling times.