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.

Comparison of Skimmed Milk and Lanthanum Flocculation for Concentration of Pathogenic Viruses in Water.

Concentration of viruses in water is necessary for detection and quantification of the viruses present, in order to evaluate microbiological barriers in water treatment plants and detect pathogenic viruses during waterborne outbreaks, but there is currently no standardised procedure. In this study, we implemented a previously described fast and simple lanthanum-based protocol for concentration of norovirus genogroup I (GI), genogroup II (GII) and hepatitis A virus (HAV) in drinking and surface water. We compared the results with those of a widely used skimmed milk flocculation method, followed by nucleic acid extraction and RT-qPCR detection. Three seeding levels, with intended concentrations 5 × 103, 5 × 104 and 5 × 105 genome copies/10 L, were added to drinking water or surface water. All seed levels were detected with both flocculation methods. Samples extracted with skimmed milk flocculation had on average 1.82, 1.86 and 1.38 times higher measured concentration of norovirus GI, GII and HAV, respectively, than those extracted with lanthanum flocculation, across all seeding levels and water types tested. Mengovirus was used as a positive process control. Mengovirus recovery was higher for skimmed milk (40.7% in drinking water, 26.0% in surface water) than for lanthanum flocculation (24.4% in drinking water, 9.7% in surface water). Together, this indicates that skimmed milk flocculation provides higher viral recovery than lanthanum flocculation. However, lanthanum-based flocculation can be performed much faster than skimmed milk flocculation (1.5 h versus 16 h flocculation time) and thus could be a good alternative for rapid monitoring of viruses in water.

Addressing Learning Needs on the Use of Metagenomics in Antimicrobial Resistance Surveillance.

One Health surveillance of antimicrobial resistance (AMR) depends on a harmonized method for detection of AMR. Metagenomics-based surveillance offers the possibility to compare resistomes within and between different target populations. Its potential to be embedded into policy in the future calls for a timely and integrated knowledge dissemination strategy. We developed a blended training (e-learning and a workshop) on the use of metagenomics in surveillance of pathogens and AMR. The objectives were to highlight the potential of metagenomics in the context of integrated surveillance, to demonstrate its applicability through hands-on training and to raise awareness to bias factors. The target participants included staff of competent authorities responsible for AMR monitoring and academic staff. The training was organized in modules covering the workflow, requirements, benefits and challenges of surveillance by metagenomics. The training had 41 participants. The face-to-face workshop was essential to understand the expectations of the participants about the transition to metagenomics-based surveillance. After revision of the e-learning, we released it as a Massive Open Online Course (MOOC), now available at https://www.coursera.org/learn/metagenomics. This course has run in more than 20 sessions, with more than 3,000 learners enrolled, from more than 120 countries. Blended learning and MOOCs are useful tools to deliver knowledge globally and across disciplines. The released MOOC can be a reference knowledge source for international players in the application of metagenomics in surveillance.

Evaluation of Methods for the Concentration and Extraction of Viruses from Sewage in the Context of Metagenomic Sequencing.

Viral sewage metagenomics is a novel field of study used for surveillance, epidemiological studies, and evaluation of waste water treatment efficiency. In raw sewage human waste is mixed with household, industrial and drainage water, and virus particles are, therefore, only found in low concentrations. This necessitates a step of sample concentration to allow for sensitive virus detection. Additionally, viruses harbor a large diversity of both surface and genome structures, which makes universal viral genomic extraction difficult. Current studies have tackled these challenges in many different ways employing a wide range of viral concentration and extraction procedures. However, there is limited knowledge of the efficacy and inherent biases associated with these methods in respect to viral sewage metagenomics, hampering the development of this field. By the use of next generation sequencing this study aimed to evaluate the efficiency of four commonly applied viral concentrations techniques (precipitation with polyethylene glycol, organic flocculation with skim milk, monolithic adsorption filtration and glass wool filtration) and extraction methods (Nucleospin RNA XS, QIAamp Viral RNA Mini Kit, NucliSENS® miniMAG®, or PowerViral® Environmental RNA/DNA Isolation Kit) to determine the viriome in a sewage sample. We found a significant influence of concentration and extraction protocols on the detected viriome. The viral richness was largest in samples extracted with QIAamp Viral RNA Mini Kit or PowerViral® Environmental RNA/DNA Isolation Kit. Highest viral specificity were found in samples concentrated by precipitation with polyethylene glycol or extracted with Nucleospin RNA XS. Detection of viral pathogens depended on the method used. These results contribute to the understanding of method associated biases, within the field of viral sewage metagenomics, making evaluation of the current literature easier and helping with the design of future studies.

Protection of human myeloid dendritic cell subsets against influenza A virus infection is differentially regulated upon TLR stimulation.

The proinflammatory microenvironment in the respiratory airway induces maturation of both resident and infiltrating dendritic cells (DCs) upon influenza A virus (IAV) infection. This results in upregulation of antiviral pathways as well as modulation of endocytic processes, which affect the susceptibility of DCs to IAV infection. Therefore, it is highly relevant to understand how IAV interacts with and infects mature DCs. To investigate how different subsets of human myeloid DCs (MDCs) involved in tissue inflammation are affected by inflammatory stimulation during IAV infection, we stimulated primary blood MDCs and inflammatory monocyte-derived DCs (MDDCs) with TLR ligands, resulting in maturation. Interestingly, MDDCs but not MDCs were protected against IAV infection after LPS (TLR4) stimulation. In contrast, stimulation with TLR7/8 ligand protected MDCs but not MDDCs from IAV infection. The reduced susceptibility to IAV infection correlated with induction of type I IFNs. We found that differential expression of TLR4, TRIF, and MyD88 in the two MDC subsets regulated the ability of the cells to enter an antiviral state upon maturation. This difference was functionally confirmed using small interfering RNA and inhibitors. Our data show that different human MDC subsets may play distinct roles during IAV infection, as their capacity to induce type I IFNs is dependent on TLR-specific maturation, resulting in differential susceptibility to IAV infection.

Detection of pathogenic viruses in sewage provided early warnings of hepatitis A virus and norovirus outbreaks.

Most persons infected with enterically transmitted viruses shed large amounts of virus in feces for days or weeks, both before and after onset of symptoms. Therefore, viruses causing gastroenteritis may be detected in wastewater, even if only a few persons are infected. In this study, the presence of eight pathogenic viruses (norovirus, astrovirus, rotavirus, adenovirus, Aichi virus, parechovirus, hepatitis A virus [HAV], and hepatitis E virus) was investigated in sewage to explore whether their identification could be used as an early warning of outbreaks. Samples of the untreated sewage were collected in proportion to flow at Ryaverket, Gothenburg, Sweden. Daily samples collected during every second week between January and May 2013 were pooled and analyzed for detection of viruses by concentration through adsorption to milk proteins and PCR. The largest amount of noroviruses was detected in sewage 2 to 3 weeks before most patients were diagnosed with this infection in Gothenburg. The other viruses were detected at lower levels. HAV was detected between weeks 5 and 13, and partial sequencing of the structural VP1protein identified three different strains. Two strains were involved in an ongoing outbreak in Scandinavia and were also identified in samples from patients with acute hepatitis A in Gothenburg during spring of 2013. The third strain was unique and was not detected in any patient sample. The method used may thus be a tool to detect incipient outbreaks of these viruses and provide early warning before the causative pathogens have been recognized in health care.