High-throughput virtual search of small molecules for controlling the mechanical stability of human CD4.

Protein mechanical stability determines the function of a myriad of proteins, especially proteins from the extracellular matrix. Failure to maintain protein mechanical stability may result in diseases and disorders such as cancer, cardiomyopathies, or muscular dystrophy. Thus, developing mutation-free approaches to enhance and control the mechanical stability of proteins using pharmacology-based methods may have important implications in drug development and discovery. Here, we present the first approach that employs computational high-throughput virtual screening and molecular docking to search for small molecules in chemical libraries that function as mechano-regulators of the stability of human cluster of differentiation 4, receptor of HIV-1. Using single-molecule force spectroscopy, we prove that these small molecules can increase the mechanical stability of CD4D1D2 domains over 4-fold in addition to modifying the mechanical unfolding pathways. Our experiments demonstrate that chemical libraries are a source of mechanoactive molecules and that drug discovery approaches provide the foundation of a new type of molecular function, that is, mechano-regulation, paving the way toward mechanopharmacology.

The fate of sulfamethoxazole and trimethoprim in a micro-aerated anaerobic membrane bioreactor and the occurrence of antibiotic resistance in the permeate.

This study investigates the effects, conversions, and resistance induction, following the addition of 150 µg·L-1 of two antibiotics, sulfamethoxazole (SMX) and trimethoprim (TMP), in a laboratory-scale micro-aerated anaerobic membrane bioreactor (MA-AnMBR). TMP and SMX were removed at 97 and 86%, indicating that micro-aeration did not hamper their removal. These antibiotics only affected the pH and biogas composition of the process, with a significant change in pH from 7.8 to 7.5, and a decrease in biogas methane content from 84 to 78%. TMP was rapidly adsorbed onto the sludge and subsequently degraded during the long solids retention time of 27 days. SMX adsorption was minimal, but the applied hydraulic retention time of 2.6 days was sufficiently long to biodegrade SMX. The levels of three antibiotic-resistant genes (ARGs) (sul1, sul2, and dfrA1) and one mobile genetic element biomarker (intI1) were analyzed by qPCR. Additions of the antibiotics increased the relative abundances of all ARGs and intI1 in the MA-AnMBR sludge, with the sul2 gene folding 15 times after 310 days of operation. The MA-AnMBR was able to reduce the concentration of antibiotic-resistant bacteria (ARB) in the permeate by 3 log.

Candidate biomarkers of antibiotic resistance for the monitoring of wastewater and the downstream environment.

Urban wastewater treatment plants (UWTPs) are essential for reducing the pollutants load and protecting water bodies. However, wastewater catchment areas and UWTPs emit continuously antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs), with recognized impacts on the downstream environments. Recently, the European Commission recommended to monitor antibiotic resistance in UWTPs serving more than 100 000 population equivalents. Antibiotic resistance monitoring in environmental samples can be challenging. The expected complexity of these systems can jeopardize the interpretation capacity regarding, for instance, wastewater treatment efficiency, impacts of environmental contamination, or risks due to human exposure. Simplified monitoring frameworks will be essential for the successful implementation of analytical procedures, data analysis, and data sharing. This study aimed to test a set of biomarkers representative of ARG contamination, selected based on their frequent human association and, simultaneously, rare presence in pristine environments. In addition to the 16S rRNA gene, ten potential biomarkers (intI1, sul1, ermB, ermF, aph(3'')-Ib, qacEΔ1, uidA, mefC, tetX, and crAssphage) were monitored in DNA extracts (n = 116) from raw wastewater, activated sludge, treated wastewater, and surface water (upstream and downstream of UWTPs) samples collected in the Czech Republic, Denmark, Israel, the Netherlands, and Portugal. Each biomarker was sensitive enough to measure decreases (on average by up to 2.5 log-units gene copy/mL) from raw wastewater to surface water, with variations in the same order of magnitude as for the 16S rRNA gene. The use of the 10 biomarkers allowed the typing of water samples whose origin or quality could be predicted in a blind test. The results show that, based on appropriate biomarkers, qPCR can be used for a cost-effective and technically accessible approach to monitoring wastewater and the downstream environment.

Catch me if you can: capturing microbial community transformation by extracellular DNA using Hi-C sequencing.

The transformation of environmental microorganisms by extracellular DNA is an overlooked mechanism of horizontal gene transfer and evolution. It initiates the acquisition of exogenous genes and propagates antimicrobial resistance alongside vertical and conjugative transfers. We combined mixed-culture biotechnology and Hi-C sequencing to elucidate the transformation of wastewater microorganisms with a synthetic plasmid encoding GFP and kanamycin resistance genes, in the mixed culture of chemostats exposed to kanamycin at concentrations representing wastewater, gut and polluted environments (0.01-2.5-50-100 mg L-1). We found that the phylogenetically distant Gram-negative Runella (102 Hi-C links), Bosea (35), Gemmobacter (33) and Zoogloea (24) spp., and Gram-positive Microbacterium sp. (90) were transformed by the foreign plasmid, under high antibiotic exposure (50 mg L-1). In addition, the antibiotic pressure shifted the origin of aminoglycoside resistance genes from genomic DNA to mobile genetic elements on plasmids accumulating in microorganisms. These results reveal the power of Hi-C sequencing to catch and surveil the transfer of xenogenetic elements inside microbiomes.

Low-Cost COTS GNSS Interference Monitoring, Detection, and Classification System.

Interference signals cause position errors and outages to global navigation satellite system (GNSS) receivers. However, to solve these problems, the interference source must be detected, classified, its purpose determined, and localized to eliminate it. Several interference monitoring solutions exist, but these are expensive, resulting in fewer nodes that may miss spatially sparse interference signals. This article introduces a low-cost commercial-off-the-shelf (COTS) GNSS interference monitoring, detection, and classification receiver. It employs machine learning (ML) on tailored signal pre-processing of the raw signal samples and GNSS measurements to facilitate a generalized, high-performance architecture that does not require human-in-the-loop (HIL) calibration. Therefore, the low-cost receivers with high performance can justify significantly more receivers being deployed, resulting in a significantly higher probability of intercept (POI). The architecture of the monitoring system is described in detail in this article, including an analysis of the energy consumption and optimization. Controlled interference scenarios demonstrate detection and classification capabilities exceeding conventional approaches. The ML results show that accurate and reliable detection and classification are possible with COTS hardware.

Microbiome, resistome and mobilome of chlorine-free drinking water treatment systems.

Drinking water treatment plants (DWTPs) are designed to remove physical, chemical, and biological contaminants. However, until recently, the role of DWTPs in minimizing the cycling of antibiotic resistance determinants has got limited attention. In particular, the risk of selecting antibiotic-resistant bacteria (ARB) is largely overlooked in chlorine-free DWTPs where biological processes are applied. Here, we combined high-throughput quantitative PCR and metagenomics to analyze the abundance and dynamics of microbial communities, antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs) across the treatment trains of two chlorine-free DWTPs involving dune-based and reservoir-based systems. The microbial diversity of the water increased after all biological unit operations, namely rapid and slow sand filtration (SSF), and granular activated carbon filtration. Both DWTPs reduced the concentration of ARGs and MGEs in the water by circa 2.5 log gene copies mL-1, despite their relative increase in the disinfection sub-units (SSF in dune-based and UV treatment in reservoir-based DWTPs). The total microbial concentration was also reduced (2.5 log units), and none of the DWTPs enriched for bacteria containing genes linked to antibiotic resistance. Our findings highlight the effectiveness of chlorine-free DWTPs in supplying safe drinking water while reducing the concentration of antibiotic resistance determinants. To the best of our knowledge, this is the first study that monitors the presence and dynamics of antibiotic resistance determinants in chlorine-free DWTPs.

Metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings.

The success of antibiotics as a therapeutic agent has led to their ineffectiveness. The continuous use and misuse in clinical and non-clinical areas have led to the emergence and spread of antibiotic-resistant bacteria and its genetic determinants. This is a multi-dimensional problem that has now become a global health crisis. Antibiotic resistance research has primarily focused on the clinical healthcare sectors while overlooking the non-clinical sectors. The increasing antibiotic usage in the environment - including animals, plants, soil, and water - are drivers of antibiotic resistance and function as a transmission route for antibiotic resistant pathogens and is a source for resistance genes. These natural compartments are interconnected with each other and humans, allowing the spread of antibiotic resistance via horizontal gene transfer between commensal and pathogenic bacteria. Identifying and understanding genetic exchange within and between natural compartments can provide insight into the transmission, dissemination, and emergence mechanisms. The development of high-throughput DNA sequencing technologies has made antibiotic resistance research more accessible and feasible. In particular, the combination of metagenomics and powerful bioinformatic tools and platforms have facilitated the identification of microbial communities and has allowed access to genomic data by bypassing the need for isolating and culturing microorganisms. This review aimed to reflect on the different sequencing techniques, metagenomic approaches, and bioinformatics tools and pipelines with their respective advantages and limitations for antibiotic resistance research. These approaches can provide insight into resistance mechanisms, the microbial population, emerging pathogens, resistance genes, and their dissemination. This information can influence policies, develop preventative measures and alleviate the burden caused by antibiotic resistance.

The Effects of High-Speed Resistance Training on Health Outcomes in Independent Older Adults: A Systematic Review and Meta-Analysis.

Human ageing involves several physiological impairments-in particular, a decrease in sensorimotor function and changes in the nervous system reduce muscle strength, power, balance, and functional capacity performance. Preventive strategies are essential to ensure the quality of life of the elderly. High-speed resistance training (HSRT) may be an effective approach to muscle power development in this population, with significant short-term effects on neural adaptations and muscle power production. Therefore, the present study intends to analyze and systematize the studies focused on HSRT interventions and their effects on health outcomes in independent older adults. Four electronic databases (PubMed, Web of Science, EBSCO, and Scielo) were used for the purposes of searching randomized controlled trials that measured at least one key outcome measure focusing on velocity-based training and health outcomes in older adults on 7 March 2022 and identified 1950 studies. At the end of the process, fourteen studies were included in this systematic review and ten studies were included in the quantitative analysis. The main results showed that HSRT interventions would improve health measures, mostly cognitive function (large effects, p = 0.001, SMD = 0.94), neuromuscular function (moderate effects, p = 0.003, SMD = 0.70), and physical function (moderate effects, p = 0.04, SMD = 0.55 and p = 0.009, SMD = -0.59). Additionally, the results suggested that interventions with ten weeks or more, performed three times a week, provide significant improvements in neuromuscular function. In this sense, HSRT is effective for improving overall health outcomes in older adults. Future studies should include proper follow-ups (e.g., minimum six months) to assess the durability of HSRT intervention effects on all health-related variables.

Metagenomic profiling and transfer dynamics of antibiotic resistance determinants in a full-scale granular sludge wastewater treatment plant.

In the One Health context, wastewater treatment plants (WWTPs) are central to safeguarding water resources. Nonetheless, many questions remain about their effectiveness in preventing antimicrobial resistance (AMR) dissemination. Most surveillance studies monitor the levels and removal of selected antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) in intracellular DNA (iDNA) extracted from WWTP influents and effluents. The role of extracellular free DNA (exDNA) in wastewater is mostly overlooked. This study analyzed the transfer of ARGs and MGEs in a full-scale Nereda® reactor removing nutrients with aerobic granular sludge. We tracked the composition and fate of the iDNA and exDNA pools of influent, sludge, and effluent samples. Metagenomics was used to profile the microbiome, resistome, and mobilome signatures of iDNA and exDNA extracts. Selected ARGs and MGEs were analyzed by qPCR. From 2,840 ARGs identified, the genes arr-3 (2%), tetC (1.6%), sul1 (1.5%), oqxB (1.2%), and aph(3")-Ib (1.2%) were the most abundant among all sampling points and bioaggregates. Pseudomonas, Acinetobacter, Aeromonas, Acidovorax, Rhodoferax, and Streptomyces populations were the main potential hosts of ARGs in the sludge. In the effluent, 478 resistance determinants were detected, of which 89% were from exDNA potentially released by cell lysis during aeration in the reactor. MGEs and multiple ARGs were co-localized on the same extracellular genetic contigs. Total intracellular ARGs decreased 3-42% due to wastewater treatment. However, the ermB and sul1 genes increased by 2 and 1 log gene copies mL-1, respectively, in exDNA from influent to effluent. The exDNA fractions need to be considered in AMR surveillance, risk assessment, and mitigation strategies.

Immunohistochemical detection of chlamydia trachomatis in sexually transmitted infectious proctitis.

INTRODUCTION: Since 2003, a progressive increase in sexually transmitted infections (STI), presented as proctitis, has been described in homosexual men. In 2013 Arnold et al. described microscopic features that enable pathologists to formulate a histological diagnosis of STI related proctitis. The aim of this study is to identify the presence of Chlamydia trachomatis by immunohistochemistry in a group of patients with male to male sexual activity and pathology compatible with STI proctitis. METHODS: Cross-sectional study. The study included 54 patients with risky sexual activity and histopathology compatible with STI-proctitis according to Arnold´s recommendations. The Chlamydia trachomatis identification was carried out retrospectively on paraffin blocks using mouse monoclonal antibodies from Santa Cruz biotechnology. RESULTS: all patients were young men with male to male sexual activity, 69% were positive for HIV. The most common endoscopic presentation was rectal ulcer (61%). Basal lymphoplasmacytic inflammation and mild crypt distortion were the most common histological findings. The immunohistochemical study identified positivity for Chlamydia trachomatis in 40% (18 of 45 tested) of STI proctitis cases. DISCUSSION: The epidemiological and endoscopic characteristics of the patients studied are similar to those previously reported. In accordance with Arnold et al., the most common histological findings were (a) mild distortion of the crypts; (b) dense and basal lymphoplasmacytic infiltrate and (c) scarcity of eosinophils. The positivity of chlamydia trachomatis in immunohistochemistry was lower than others studies that used PCR for this purpose. We did not find similar published studies to compare our results. CONCLUSIONS: In summary, 54 cases of patients with STI related proctitis are presented, all of them with distinctive histological characteristics and third of the cases tested positive by IHC for Chlamydia trachomatis.

Wide-Band Interference Mitigation in GNSS Receivers Using Sub-Band Automatic Gain Control.

The performance of global navigation satellite system (GNSS) receivers is significantly affected by interference signals. For this reason, several research groups have proposed methods to mitigate the effect of different kinds of jammers. One effective method for wide-band interference mitigation (IM) is the high-rate DFT-based data manipulator (HDDM) pulse blanker (PB). It provides good performance to pulsed and frequency sparse interference. However, it and many other methods have poor performance against wide-band noise signals, which are not frequency-sparse. This article proposes to include automatic gain control (AGC) in the HDDM structure to attenuate the signal instead of removing it: the HDDM-AGC. It overcomes the wide-band noise limitation for IM at the cost of limiting mitigation capability to other signals. Previous studies with this approach were limited to only measuring the carrier-to-noise density ratio (C/N0) performance of tracking, but this article extends the analysis to include the impact of the HDDM-AGC algorithm on the position, velocity, and time (PVT) solution. It allows an end-to-end evaluation and impact assessment of mitigation to a GNSS receiver. This study compares two commercial receivers: one high-end and one low-cost, with and without HDDM IM against laboratory-generated interference signals. The results show that the HDDM-AGC provides a PVT availability and precision comparable to high-end commercial receivers with integrated mitigation for most interference types. For pulse interferences, its performance is superior. Further, it is shown that degradation is minimized against wide-band noise interferences. Regarding low-cost receivers, the PVT availability can be increased up to 40% by applying an external HDDM-AGC.

Monitoring antibiotic resistance genes in wastewater environments: The challenges of filling a gap in the One-Health cycle.

Antibiotic resistance (AR) is a global problem requiring international cooperation and coordinated action. Global monitoring must rely on methods available and comparable across nations to quantify AR occurrence and identify sources and reservoirs, as well as paths of AR dissemination. Numerous analytical tools that are gaining relevance in microbiology, have the potential to be applied to AR research. This review summarizes the state of the art of AR monitoring methods, considering distinct needs, objectives and available resources. Based on the overview of distinct approaches that are used or can be adapted to monitor AR, it is discussed the potential to establish reliable and useful monitoring schemes that can be implemented in distinct contexts. This discussion places the environmental monitoring within the One-Health approach, where two types of risk, dissemination across distinct environmental compartments, and transmission to humans, must be considered. The plethora of methodological approaches to monitor AR and the variable features of the monitored sites challenge the capacity of the scientific community and policy makers to reach a common understanding. However, the dialogue between different methods and the production of action-oriented data is a priority. The review aims to warm up this discussion.

Monitoring SARS-CoV-2 in sewage: Toward sentinels with analytical accuracy.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemia has been one of the most difficult challenges humankind has recently faced. Wastewater-based epidemiology has emerged as a tool for surveillance and mitigation of potential viral outbreaks, circumventing biases introduced by clinical patient testing. Due to the situation urgency, protocols followed for isolating viral RNA from sewage were not adapted for such sample matrices. In parallel to their implementation for fast collection of data to sustain surveillance and mitigation decisions, molecular protocols need to be harmonized to deliver accurate, reproducible, and comparable analytical outputs. Here we studied analytical variabilities linked to viral RNA isolation methods from sewage. Three different influent wastewater volumes were used to assess the effects of filtered volumes (50, 100 or 500 mL) for capturing viral particles. Three different concentration strategies were tested: electronegative membranes, polyethersulfone membranes, and anion-exchange diethylaminoethyl cellulose columns. To compare the number of viral particles, different RNA isolation methods (column-based vs. magnetic beads) were compared. The effect of extra RNA purification steps and different RT-qPCR strategies (one step vs. two-step) were also evaluated. Results showed that the combination of 500 mL filtration volume through electronegative membranes and without multiple RNA purification steps (using column-based RNA purification) using two-step RT-qPCR avoided false negatives when basal viral load in sewage are present and yielded more consistent results during the surveillance done during the second-wave in Delft (The Hague area, The Netherlands). By paving the way for standardization of methods for the sampling, concentration and molecular detection of SARS-CoV-2 viruses from sewage, these findings can help water and health surveillance authorities to use and trust results coming from wastewater based epidemiology studies in order to anticipate SARS-CoV-2 outbreaks.

Achieving Low Latency Communications in Smart Industrial Networks with Programmable Data Planes.

Industrial networks are introducing Internet of Things (IoT) technologies in their manufacturing processes in order to enhance existing methods and obtain smarter, greener and more effective processes. Global predictions forecast a massive widespread of IoT technology in industrial sectors in the near future. However, these innovations face several challenges, such as achieving short response times in case of time-critical applications. Concepts like in-network computing or edge computing can provide adequate communication quality for these industrial environments, and data plane programming has been proved as a useful mechanism for their implementation. Specifically, P4 language is used for the definition of the behavior of programmable switches and network elements. This paper presents a solution for industrial IoT (IIoT) network communications to reduce response times using in-network computing through data plane programming and P4. Our solution processes Message Queuing Telemetry Transport (MQTT) packets sent by a sensor in the data plane and generates an alarm in case of exceeding a threshold in the measured value. The implementation has been tested in an experimental facility, using a Netronome SmartNIC as a P4 programmable network device. Response times are reduced by 74% while processing, and delay introduced by the P4 network processing is insignificant.

Ultra-low dose immunization and multi-component vaccination strategies enhance protection against malaria in mice.

An effective vaccine would be a valuable tool for malaria control and elimination; however, the leading malaria vaccine in development, RTS,S/AS01, provided only partial protection in a Phase 3 trial. R21 is a next-generation RTS,S-like vaccine. We have previously shown in mice that R21 administered in Matrix-M is highly immunogenic, able to elicit complete protection against sporozoite challenge, and can be successfully administered with TRAP based viral-vectors resulting in enhanced protection. In this study, we developed a novel, GMP-compatible purification process for R21, and evaluated the immunogenicity and protective efficacy of ultra-low doses of both R21 and RTS,S when formulated in AS01. We demonstrated that both vaccines are highly immunogenic and also elicit comparable high levels of protection against transgenic parasites in BALB/c mice. By lowering the vaccine dose there was a trend for increased immunogenicity and sterile protection, with the highest dose vaccine groups achieving the lowest efficacy (50% sterile protection). We also evaluated the ability to combine RTS,S/AS01 with TRAP based viral-vectors and observed concurrent induction of immune responses to both antigens with minimal interference when mixing the vaccines prior to administration. These studies suggest that R21 or RTS,S could be combined with viral-vectors for a multi-component vaccination approach and indicate that low dose vaccination should be fully explored in humans to maximize potential efficacy.

Upgrading residues from wastewater and drinking water treatment plants as low-cost adsorbents to remove extracellular DNA and microorganisms carrying antibiotic resistance genes from treated effluents.

Wastewater treatment is challenged by the continuous emergence of chemical and biological contaminants. Disinfection, advanced oxidation, and activated carbon technologies are accessible in high-income countries to suppress them. Low-cost, easily implementable, and scalable solutions are needed for sanitation across regions. We studied the properties of low-cost absorbents recycled from drinking water and wastewater treatment plant residues to remove environmental DNA and xenogenetic elements from used water. Materials characteristics and DNA adsorption properties of used iron-oxide-coated sands and of sewage-sludge biochar obtained by pyrolysis of surplus activated sludge were examined in bench-scale batch and up-flow column systems. Adsorption profiles followed Freundlich isotherms, suggesting a multilayer adsorption of nucleic acids on these materials. Sewage-sludge biochar exhibited high DNA adsorption capacity (1 mg g-1) and long saturation breakthrough times compared to iron-oxide-coated sand (0.2 mg g-1). Selected antibiotic resistance genes and mobile genetic elements present on the free-floating extracellular DNA fraction and on the total environmental DNA (i.e., both extra/intracellular) were removed at 85% and 97% by sewage-sludge biochar and at 54% and 66% by iron-oxide-coated sand, respectively. Sewage-sludge biochar is attractive as low-cost adsorbent to minimize the spread of antimicrobial resistances to the aquatic environment while strengthening the role of sewage treatment plants as resource recovery factories.

Application of the ARIMA Model to Predict Under-Reporting of New Cases of Hansen's Disease during the COVID-19 Pandemic in a Municipality of the Amazon Region.

This work aimed to apply the ARIMA model to predict the under-reporting of new Hansen's disease cases during the COVID-19 pandemic in Palmas, Tocantins, Brazil. This is an ecological time series study of Hansen's disease indicators in the city of Palmas between 2001 and 2020 using the autoregressive integrated moving averages method. Data from the Notifiable Injuries Information System and population estimates from the Brazilian Institute of Geography and Statistics were collected. A total of 7035 new reported cases of Hansen's disease were analyzed. The ARIMA model (4,0,3) presented the lowest values for the two tested information criteria and was the one that best fit the data, as AIC = 431.30 and BIC = 462.28, using a statistical significance level of 0.05 and showing the differences between the predicted values and those recorded in the notifications, indicating a large number of under-reporting of Hansen's disease new cases during the period from April to December 2020. The ARIMA model reported that 177% of new cases of Hansen's disease were not reported in Palmas during the period of the COVID-19 pandemic in 2020. This study shows the need for the municipal control program to undertake immediate actions in terms of actively searching for cases and reducing their hidden prevalence.

Free-floating extracellular DNA: Systematic profiling of mobile genetic elements and antibiotic resistance from wastewater.

The free-floating extracellular DNA (exDNA) fraction of microbial ecosystems harbors antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs). Natural transformation of these xenogenetic elements can generate microbial cells resistant to one or more antibiotics. Isolating and obtaining a high yield of exDNA is challenging due to its low concentration in wastewater environments. Profiling exDNA is crucial to unravel the ecology of free-floating ARGs and MGEs and their contribution to horizontal genetransfer. We developed a method using chromatography to isolate and enrich exDNA without causing cell lysis from complex wastewater matrices like influent (9 µg exDNA out of 1 L), activated sludge (5.6 µg out of 1 L), and treated effluent (4.3 µg out of 1 L). ARGs and MGEs were metagenomically profiled for both the exDNA and intracellular DNA (iDNA) of activated sludge, and quantified by qPCR in effluent water. qPCR revealed that ARGs and MGEs are more abundant in the iDNA fraction while still significant on exDNA (100-1000 gene copies mL-1) in effluent water. The metagenome highlighted that exDNA is mainly composed of MGEs (65%). According to their relatively low abundance in the resistome of exDNA, ARGs uptake by natural transformation is likely not the main transfer mechanism. Although ARGs are not highly abundant in exDNA, the prevalence of MGEs in the exDNA fraction can indirectly promote antibiotic resistance development. The combination of this method with functional metagenomics can help to elucidate the transfer and development of resistances in microbial communities. A systematic profiling of the different DNA fractions will foster microbial risk assessments across water systems, supporting water authorities to delineate measures to safeguard environmental and public health.

Yellow Fever Virus Down-Regulates mRNA Expression of SOCS1 in the Initial Phase of Infection in Human Cell Lines.

Flaviviruses are constantly evolving diverse immune evasion strategies, and the exploitation of the functions of suppressors of cytokine signalling (SOCS) and protein inhibitors of activated STATs (PIAS) to favour virus replication has been described for Dengue and Japanese encephalitis viruses but not for yellow fever virus (YFV), which is still of global importance despite the existence of an effective vaccine. Some mechanisms that YFV employs to evade host immune defence has been reported, but the expression patterns of SOCS and PIAS in infected cells is yet to be determined. Here, we show that SOCS1 is down-regulated early in YFV-infected HeLa and HEK 293T cells, while SOCS3 and SOCS5 are not significantly altered, and PIAS mRNA expression appears to follow a rise-dip pattern akin to circadian-controlled genes. We also demonstrate that YFV evades interferon-ß application to produce comparable viral titres. This report provides initial insight into the in vitro expression dynamics of SOCS and PIAS upon YFV infection and a basis for further investigation into SOCS/PIAS expression and how these modulate the immune response in animal models.