Upstream land use with microbial downstream consequences: Iron and humic substances link to Legionella spp.

Intensified land use can disturb water quality, potentially increasing the abundance of bacterial pathogens, threatening public access to clean water. This threat involves both direct contamination of faecal bacteria as well as indirect factors, such as disturbed water chemistry and microbiota, which can lead to contamination. While direct contamination has been well described, the impact of indirect factors is less explored, despite the potential of severe downstream consequences on water supply. To assess direct and indirect downstream effects of buildings, farms, pastures and fields on potential water sources, we studied five Swedish lakes and their inflows. We analysed a total of 160 samples in a gradient of anthropogenic activity spanning four time points, including faecal and water-quality indicators. Through species distribution modelling, Random Forest and network analysis using 16S rRNA amplicon sequencing data, our findings highlight that land use indirectly impacts lakes via inflows. Land use impacted approximately one third of inflow microbiota taxa, in turn impacting ∼20-50 % of lake taxa. Indirect effects via inflows were also suggested by causal links between e.g. water colour and lake bacterial taxa, where this influenced the abundance of several freshwater bacteria, such as Polynucleobacter and Limnohabitans. However, it was not possible to identify direct effects on the lakes based on analysis of physiochemical- or microbial parameters. To avoid potential downstream consequences on water supply, it is thus important to consider possible indirect effects from upstream land use and inflows, even when no direct effects can be observed on lakes. Legionella (a genus containing bacterial pathogens) illustrated potential consequences, since the genus was particularly abundant in inflows and was shown to increase by the presence of pastures, fields, and farms. The approach presented here could be used to assess the suitability of lakes as alternative raw water sources or help to mitigate contaminations in important water catchments. Continued broad investigations of stressors on the microbial network can identify indirect effects, avoid enrichment of pathogens, and help secure water accessibility.

Inoculation with adapted bacterial communities promotes development of full scale slow sand filters for drinking water production.

Gravity-driven filtration through slow sand filters (SSFs) is one of the oldest methods for producing drinking water. As water passes through a sand bed, undesired microorganisms and chemicals are removed by interactions with SSF biofilm and its resident microbes. Despite their importance, the processes through which these microbial communities form are largely unknown, as are the factors affecting these processes. In this study, two SSFs constructed using different sand sources were compared to an established filter and observed throughout their maturation process. One SSF was inoculated through addition of sand scraped from established filters, while the other was not inoculated. The operational and developing microbial communities of SSFs, as well as their influents and effluents, were studied by sequencing of 16S ribosomal rRNA genes. A functional microbial community resembling that of the established SSF was achieved in the inoculated SSF, but not in the non-inoculated SSF. Notably, the non-inoculated SSF had significantly (p < 0.01) higher abundances of classes Armatimonadia, Elusimicrobia, Fimbriimonadia, OM190 (phylum Planctomycetota), Parcubacteria, Vampirivibrionia and Verrucomicrobiae. Conversely, it had lower abundances of classes Anaerolineae, Bacilli, bacteriap25 (phylum Myxococcota), Blastocatellia, Entotheonellia, Gemmatimonadetes, lineage 11b (phylum Elusimicrobiota), Nitrospiria, Phycisphaerae, subgroup 22 (phylum Acidobacteriota) and subgroup 11 (phylum Acidobacteriota). Poor performance of neutral models showed that the assembly and dispersal of SSF microbial communities was mainly driven by selection. The temporal turnover of microbial species, as estimated through the scaling exponent of the species-time relationship, was twice as high in the non-inoculated filter (0.946 ± 0.164) compared to the inoculated filter (0.422 ± 0.0431). This study shows that the addition of an inoculum changed the assembly processes within SSFs. Specifically, the rate at which new microorganisms were observed in the biofilm was reduced. The reduced temporal turnover may be driven by inoculating taxa inhibiting growth, potentially via secondary metabolite production. This in turn would allow the inoculation community to persist and contribute to SSF function.

Bacterial composition in Swedish raw drinking water reveals three major interacting ubiquitous metacommunities.

BACKGROUND: Surface raw water used as a source for drinking water production is a critical resource, sensitive to contamination. We conducted a study on Swedish raw water sources, aiming to identify mutually co-occurring metacommunities of bacteria, and environmental factors driving such patterns. METHODS: The water sources were different regarding nutrient composition, water quality, and climate characteristics, and displayed various degrees of anthropogenic impact. Water inlet samples were collected at six drinking water treatment plants over 3 years, totaling 230 samples. The bacterial communities of DNA sequenced samples (n = 175), obtained by 16S metabarcoding, were analyzed using a joint model for taxa abundance. RESULTS: Two major groups of well-defined metacommunities of microorganisms were identified, in addition to a third, less distinct, and taxonomically more diverse group. These three metacommunities showed various associations to the measured environmental data. Predictions for the well-defined metacommunities revealed differing sets of favored metabolic pathways and life strategies. In one community, taxa with methanogenic metabolism were common, while a second community was dominated by taxa with carbohydrate and lipid-focused metabolism. CONCLUSION: The identification of ubiquitous persistent co-occurring bacterial metacommunities in freshwater habitats could potentially facilitate microbial source tracking analysis of contamination issues in freshwater sources.

Microbial Interactions - Underexplored Links Between Public Health Relevant Bacteria and Protozoa in Coastal Environments.

The co-existence of bacteria and protozoa in aquatic environments has led to the evolution of predation defense mechanisms by the bacteria. Some of the predation-resistant bacteria (PRB) are also pathogenic to humans and other mammals. The links between PRB and protozoa in natural aquatic systems are poorly known, but they are important in predicting outbreaks and determining the long-term consequences of a contamination event. To elucidate co-occurrence patterns between PRB (16S rRNA) and bacterivorous protozoa (18S rRNA), we performed a field study in a coastal area in the northern Baltic Sea. Interactions between bacteria and protozoa were explored by using two complementary statistical tools. We found co-occurrence patterns between specific PRB and protozoa, such as Legionella and Ciliophora, and we also found that the interactions are genotype-specific as, for example, Rickettsia. The PRB sequence diversity was larger in bays and freshwater inlets compared to offshore sites, indicating local adaptions. Considering the PRB diversity in the freshwater in combination with the large spring floods in the area, freshwater influxes should be considered a potential source of PRB in the coastal northern Baltic Sea. These findings are relevant for the knowledge of survival and dispersal of potential pathogens in the environment.

FlexTaxD: flexible modification of taxonomy databases for improved sequence classification.

SUMMARY: The Flexible Taxonomy Database framework provides a method for modification and merging official and custom taxonomic databases to create improved databases. Using such databases will increase accuracy and precision of existing methods to classify sequence reads. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://github.com/FOI-Bioinformatics/flextaxd and installable through Bioconda.

Life stage-specific inbreeding depression in long-lived Pinaceae species depends on population connectivity.

Inbreeding depression (ID) is a fundamental selective pressure that shapes mating systems and population genetic structures in plants. Although it has been shown that ID varies over the life stages of shorter-lived plants, less is known about how the fitness effects of inbreeding vary across life stages in long-lived species. We conducted a literature survey in the Pinaceae, a tree family known to harbour some of the highest mutational loads ever reported. Using a meta-regression model, we investigated distributions of inbreeding depression over life stages, adjusting for effects of inbreeding levels and the genetic differentiation of populations within species. The final dataset contained 147 estimates of ID across life stages from 41 studies. 44 Fst estimates were collected from 40 peer-reviewed studies for the 18 species to aid genetic differentiation modelling. Partitioning species into fragmented and well-connected groups using Fst resulted in the best way (i.e. trade-off between high goodness-of-fit of the model to the data and reduced model complexity) to incorporate genetic connectivity in the meta-regression analysis. Inclusion of a life stage term and its interaction with the inbreeding coefficient (F) dramatically increased model precision. We observed that the correlation between ID and F was significant at the earliest life stage. Although partitioning of species populations into fragmented and well-connected groups explained little of the between-study heterogeneity, the inclusion of an interaction between life stage and population differentiation revealed that populations with fragmented distributions suffered lower inbreeding depression at early embryonic stages than species with well-connected populations. There was no evidence for increased ID in late life stages in well-connected populations, although ID tended to increase across life stages in the fragmented group. These findings suggest that life stage data should be included in inbreeding depression studies and that inbreeding needs to be managed over life stages in commercial populations of long-lived plants.

Airborne microbial biodiversity and seasonality in Northern and Southern Sweden.

Microorganisms are essential constituents of ecosystems. To improve our understanding of how various factors shape microbial diversity and composition in nature it is important to study how microorganisms vary in space and time. Factors shaping microbial communities in ground level air have been surveyed in a limited number of studies, indicating that geographic location, season and local climate influence the microbial communities. However, few have surveyed more than one location, at high latitude or continuously over more than a year. We surveyed the airborne microbial communities over two full consecutive years in Kiruna, in the Arctic boreal zone, and Ljungbyhed, in the Southern nemoral zone of Sweden, by using a unique collection of archived air filters. We mapped both geographic and seasonal differences in bacterial and fungal communities and evaluated environmental factors that may contribute to these differences and found that location, season and weather influence the airborne communities. Location had stronger influence on the bacterial community composition compared to season, while location and season had equal influence on the fungal community composition. However, the airborne bacterial and fungal diversity showed overall the same trend over the seasons, regardless of location, with a peak during the warmer parts of the year, except for the fungal seasonal trend in Ljungbyhed, which fluctuated more within season. Interestingly, the diversity and evenness of the airborne communities were generally lower in Ljungbyhed. In addition, both bacterial and fungal communities varied significantly within and between locations, where orders like Rhizobiales, Rhodospirillales and Agaricales dominated in Kiruna, whereas Bacillales, Clostridiales and Sordariales dominated in Ljungbyhed. These differences are a likely reflection of the landscape surrounding the sampling sites where the landscape in Ljungbyhed is more homogenous and predominantly characterized by artificial and agricultural surroundings. Our results further indicate that local landscape, as well as seasonal variation, shapes microbial communities in air.

Biological amplification of low frequency mutations unravels laboratory culture history of the bio-threat agent Francisella tularensis.

Challenges of investigating a suspected bio attack include establishing if microorganisms have been cultured to produce attack material and to identify their source. Addressing both issues, we have investigated genetic variations that emerge during laboratory culturing of the bacterial pathogen Francisella tularensis. Key aims were to identify genetic variations that are characteristic of laboratory culturing and explore the possibility of using biological amplification to identify genetic variation present at exceedingly low frequencies in a source sample. We used parallel serial passage experiments and high-throughput sequencing of F. tularensis to explore the genetic variation. We found that during early laboratory culture passages of F. tularensis, gene duplications emerged in the pathogen genome followed by single-nucleotide polymorphisms in genes for bacterial capsule synthesis. Based on a biological enrichment scheme and the use of high-throughput sequencing, we identified genetic variation that likely pre-existed in a source sample. The results support that capsule synthesis gene mutations are common during laboratory culture, and that a biological amplification strategy is useful for linking a F. tularensis sample to a specific laboratory variant among many highly similar variants.

A likelihood ratio-based approach for improved source attribution in microbiological forensic investigations.

A common objective in microbial forensic investigations is to identify the origin of a recovered pathogenic bacterium by DNA sequencing. However, there is currently no consensus about how degrees of belief in such origin hypotheses should be quantified, interpreted, and communicated to wider audiences. To fill this gap, we have developed a concept based on calculating probabilistic evidential values for microbial forensic hypotheses. The likelihood-ratio method underpinning this concept is widely used in other forensic fields, such as human DNA matching, where results are readily interpretable and have been successfully communicated in juridical hearings. The concept was applied to two case scenarios of interest in microbial forensics: (1) identifying source cultures among series of very similar cultures generated by parallel serial passage of the Tier 1 pathogen Francisella tularensis, and (2) finding the production facilities of strains isolated in a real disease outbreak caused by the human pathogen Listeria monocytogenes. Evidence values for the studied hypotheses were computed based on signatures derived from whole genome sequencing data, including deep-sequenced low-frequency variants and structural variants such as duplications and deletions acquired during serial passages. In the F. tularensis case study, we were able to correctly assign fictive evidence samples to the correct culture batches of origin on the basis of structural variant data. By setting up relevant hypotheses and using data on cultivated batch sources to define the reference populations under each hypothesis, evidential values could be calculated. The results show that extremely similar strains can be separated on the basis of amplified mutational patterns identified by high-throughput sequencing. In the L. monocytogenes scenario, analyses of whole genome sequence data conclusively assigned the clinical samples to specific sources of origin, and conclusions were formulated to facilitate communication of the findings. Taken together, these findings demonstrate the potential of using bacterial whole genome sequencing data, including data on both low frequency SNP signatures and structural variants, to calculate evidence values that facilitate interpretation and communication of the results. The concept could be applied in diverse scenarios, including both epidemiological and forensic source tracking of bacterial infectious disease outbreaks.

Accounting for Bacterial Overlap Between Raw Water Communities and Contaminating Sources Improves the Accuracy of Signature-Based Microbial Source Tracking.

Microbial source tracking (MST) analysis is essential to identifying and mitigating the fecal pollution of water resources. The signature-based MST method uses a library of sequences to identify contaminants based on operational taxonomic units (OTUs) that are unique to a certain source. However, no clear guidelines for how to incorporate OTU overlap or natural variation in the raw water bacterial community into MST analyses exist. We investigated how the inclusion of bacterial overlap between sources in the library affects source prediction accuracy. To achieve this, large-scale sampling - including feces from seven species, raw sewage, and raw water samples from water treatment plants - was followed by 16S rRNA amplicon sequencing. The MST library was defined using three settings: (i) no raw water communities represented; (ii) raw water communities selected through clustering analysis; and (iii) local water communities collected across consecutive years. The results suggest that incorporating either the local background or representative bacterial composition improves MST analyses, as the results were positively correlated to measured levels of fecal indicator bacteria and the accuracy at which OTUs were assigned to the correct contamination source increased fourfold. Using the proportion of OTUs with high source origin probability, underpinning a contaminating signal, is a solid foundation in a framework for further deciphering and comparing contaminating signals derived in signature-based MST approaches. In conclusion, incorporating background bacterial composition of water in MST can improve mitigation efforts for minimizing the spread of pathogenic and antibiotic resistant bacteria into essential freshwater resources.

CONE: Community Oriented Network Estimation Is a Versatile Framework for Inferring Population Structure in Large-Scale Sequencing Data.

Estimation of genetic population structure based on molecular markers is a common task in population genetics and ecology. We apply a generalized linear model with LASSO regularization to infer relationships between individuals and populations from molecular marker data. Specifically, we apply a neighborhood selection algorithm to infer population genetic structure and gene flow between populations. The resulting relationships are used to construct an individual-level population graph. Different network substructures known as communities are then dissociated from each other using a community detection algorithm. Inference of population structure using networks combines the good properties of: (i) network theory (broad collection of tools, including aesthetically pleasing visualization), (ii) principal component analysis (dimension reduction together with simple visual inspection), and (iii) model-based methods (e.g., ancestry coefficient estimates). We have named our process CONE (for community oriented network estimation). CONE has fewer restrictions than conventional assignment methods in that properties such as the number of subpopulations need not be fixed before the analysis and the sample may include close relatives or involve uneven sampling. Applying CONE on simulated data sets resulted in more accurate estimates of the true number of subpopulations than model-based methods, and provided comparable ancestry coefficient estimates. Inference of empirical data sets of teosinte single nucleotide polymorphism, bacterial disease outbreak, and the human genome diversity panel illustrate that population structures estimated with CONE are consistent with the earlier findings.

Increased knowledge of Francisella genus diversity highlights the benefits of optimised DNA-based assays.

BACKGROUND: Recent advances in sequencing technologies offer promising tools for generating large numbers of genomes, larger typing databases and improved mapping of environmental bacterial diversity. However, DNA-based methods for the detection of Francisella were developed with limited knowledge about genetic diversity. This, together with the high sequence identity between several Francisella species, means there is a high risk of false identification and detection of the highly virulent pathogen Francisella tularensis. Moreover, phylogenetic reconstructions using single or limited numbers of marker sequences often result in incorrect tree topologies and inferred evolutionary distances. The recent growth in publicly accessible whole-genome sequences now allows evaluation of published genetic markers to determine optimal combinations of markers that minimise both time and laboratory costs. RESULTS: In the present study, we evaluated 38 previously published DNA markers and the corresponding PCR primers against 42 genomes representing the currently known diversity of the genus Francisella. The results highlight that PCR assays for Francisella tularensis are often complicated by low specificity, resulting in a high probability of false positives. A method to select a set of one to seven markers for obtaining optimal phylogenetic resolution or diagnostic accuracy is presented. CONCLUSIONS: Current multiple-locus sequence-typing systems and detection assays of Francisella, could be improved by redesigning some of the primers and reselecting typing markers. The use of only a few optimally selected sequence-typing markers allows construction of phylogenetic topologies with almost the same accuracy as topologies based on whole-genome sequences.

Genome characterisation of the genus Francisella reveals insight into similar evolutionary paths in pathogens of mammals and fish.

BACKGROUND: Prior to this study, relatively few strains of Francisella had been genome-sequenced. Previously published Francisella genome sequences were largely restricted to the zoonotic agent F. tularensis. Only limited data were available for other members of the Francisella genus, including F. philomiragia, an opportunistic pathogen of humans, F. noatunensis, a serious pathogen of farmed fish, and other less well described endosymbiotic species. RESULTS: We determined the phylogenetic relationships of all known Francisella species, including some for which the phylogenetic positions were previously uncertain. The genus Francisella could be divided into two main genetic clades: one included F. tularensis, F. novicida, F. hispaniensis and Wolbachia persica, and another included F. philomiragia and F. noatunensis.Some Francisella species were found to have significant recombination frequencies. However, the fish pathogen F. noatunensis subsp. noatunensis was an exception due to it exhibiting a highly clonal population structure similar to the human pathogen F. tularensis. CONCLUSIONS: The genus Francisella can be divided into two main genetic clades occupying both terrestrial and marine habitats. However, our analyses suggest that the ancestral Francisella species originated in a marine habitat. The observed genome to genome variation in gene content and IS elements of different species supports the view that similar evolutionary paths of host adaptation developed independently in F. tularensis (infecting mammals) and F. noatunensis subsp. noatunensis (infecting fish).