Residual risk of Pseudomonas aeruginosa waterborne contamination in intensive care unit despite the presence of filters on all water points-of-use

OBJECTIVE

To assess the residual risk of waterborne contamination by Pseudomonas aeruginosa (PA) from water network colonized by a single genotype (Sequence Type (ST)299) despite the presence of antimicrobial filters in a medical intensive care unit (ICU).

METHODS

During the first 19-month period after ICU opening, water network contamination was assessed monthly by collecting water upstream the filters. Downstream water was also sampled to assess filters efficiency. PA clinical isolates from patients were collected and compared to the waterborne ST299-PA by multiplex-rep PCR, Pulsed-Field Gel Electrophoresis (PFGE) and whole-genome sequencing. Cross-transmission events occurring independently of the genotype of PA involved were also assessed.

RESULTS

From 449 samples of filtered water, 1.3% were positive for PA in inoculum varying between 1 to 104 Colony Forming Unit (CFU)/100mL according to the tap. All PA hydric isolates belonged to PA-ST299 and displayed <2 Single Nucleotide Polymorphisms (SNPs). Among 278 clinical isolates from 122 patients, 10 isolates in 5 patients showed identical profiles to the hydric PA-ST299 clone in both multiplex-rep PCR and PFGE and differed by <5 SNPs on average, confirming the water network reservoir as the source of contamination by PA for 4.09% of patients. Cross-transmission events by other genotypes of PA than PA-ST299 were responsible for the contamination of 1.75 % of patients.

DISCUSSION/CONCLUSION

Antimicrobial filters are not sufficient to preserve patients from waterborne pathogens when the water network is highly contaminated. The microbiological survey of filtered water may be needed in units hosting at-risk patients for PA infections, even when all water points-of-use are protected by filters.

Resource Allocation Optimization in IoT-Enabled Water Quality Monitoring Systems

Water quality monitoring systems that are enabled by the Internet of Things (IoT) and used in water applications to collect and transmit water data to data processing centers are often resource-constrained in terms of power, bandwidth, and computation resources. These limitations typically impact their performance in practice and often result in forwarding their data to remote stations where the collected water data are processed to predict the status of water quality, because of their limited computation resources. This often negates the goal of effectively monitoring the changes in water quality in a real-time manner. Consequently, this study proposes a new resource allocation method to optimize the available power and time resources as well as dynamically allocate hybrid access points (HAPs) to water quality sensors to improve the energy efficiency and data throughput of the system. The proposed system is also integrated with edge computing to enable data processing at the water site to guarantee real-time monitoring of any changes in water quality and ensure timely access to clean water by the public. The proposed method is compared with a related method to validate the system performance. The proposed system outperforms the existing system and performs well in different simulation experiments. The proposed method improved the baseline method by approximately 12.65% and 16.49% for two different configurations, demonstrating its effectiveness in improving the energy efficiency of a water quality monitoring system.

Mutational Studies of Aldose Reductase to Trace a Transient Pocket Opening and to Explain Ligand Affinity Cliffs

Human aldose reductase, a target for the development of inhibitors for preventing diabetic complications, displays a transient specificity pocket which opens upon binding with specific, potent inhibitors. We investigated the opening mechanism of this pocket by mutating leucine residues involved in the gate keeping mechanism to alanine. Two isostructural inhibitors distinguished only by a single nitro to carboxy group replacement, have a 1000-fold difference in their binding affinity to the wild type. This difference is reduced to 10-fold in the mutated variants as the nitro derivative loses in affinity but conserves binding to the open transient pocket. The affinity of the carboxylate analog is minimally altered but the analog binding preference changes from the closed to open state of the transient pocket. Differences in the solvation properties of ligands and the transient pocket as well as changes from induced fit to conformational selections provide an explanation for the altered behavior of the ligands with respect to their binding to the different variants.

Modulating the Interfacial Water Network of Dual-Site Pd/FeOx/C Catalyst for Efficient Formate Electrooxidation

The rational design of electrocatalysts for formate oxidation reaction (FOR) in alkaline media is crucial to promote the practical applications of direct formate fuel cells (DFFCs). The FOR kinetic on palladium (Pd) based electrocatalysts is strongly hindered by unfavorably adsorbed hydrogen (H_ad) as the major intermediate species blocking the active sites. Herein, we report a strategy of modulating the interfacial water network of dual-site Pd/FeO_x/C catalyst to significantly enhance the desorption kinetics of H_ad during FOR. Aberration-corrected electron microscopy and synchrotron characterizations revealed the successful construction of Pd/FeO_x interfaces on carbon support as a dual-site electrocatalyst for FOR. Electrochemical tests and in situ Raman spectroscopy results showed that H_ad could be effectively removed from the active sites of the as-designed Pd/FeO_x/C catalyst. CO-stripping voltammetry and density functional theory calculations (DFT) demonstrated that the introduced FeO_x could effectively accelerate the dissociative adsorption of water molecules on active sites, which accordingly generates adsorbed hydroxyl species (OH_ad) to facilitate the removal of H_ad during FOR. This work provides a novel route to develop advanced FOR catalysts for fuel cell applications.

Tap water as the source of a Legionnaires' disease outbreak spread to several residential buildings and one hospital, Finland, 2020 to 2021

In Finland, all microbiology laboratories notify Legionella findings and physicians notify Legionnaires' disease (LD) cases to the National Infectious Disease Register. All cases are interviewed, and water samples obtained from potential places of exposure. Legionella isolates from humans and water are compared by whole genome sequencing (WGS). In March 2021, Legionella pneumophila serogroup 1 (Lp 1) pneumonia cases increased in one Finnish city (120,000 inhabitants) where single LD cases are detected annually. We identified 12 LD cases, nine living in different residential buildings and three nosocomial, linked by identical human and/or water isolates. Three of these cases were from January 2020, October 2020 and February 2021 and identified retrospectively. Eleven were diagnosed by urinary antigen test, 10 by PCR and five by culture; age ranged between 52 and 85 years, and 10 had underlying diseases. Nine of 12 homes of LD cases and 15 of 26 water samples from the hospital were positive for Lp 1, with concentrations up to 640,000 cfu/L. Water samples from regional storage tanks were negative. Positivity in homes and the hospital suggested inadequate maintenance measures. Enhanced surveillance combined with WGS was crucial in detecting this unusual LD outbreak related to domestic and hospital water systems.

Introducing Water-Network-Assisted Proton Transfer for Boosted Electrocatalytic Hydrogen Evolution with Cobalt Corrole

Proton transfer is vital for many biological and chemical reactions. Hydrogen-bonded water-containing networks are often found in enzymes to assist proton transfer, but similar strategy has been rarely presented by synthetic catalysts. We herein report the Co corrole 1 with an appended crown ether unit and its boosted activity for the hydrogen evolution reaction (HER). Crystallographic and 1H NMR studies proved that the crown ether of 1 can grab water via hydrogen bonds. By using protic acids as proton sources, the HER activity of 1 was largely boosted with added water, while the activity of crown-ether-free analogues showed very small enhancement. Inhibition studies by adding (1) external 18-crown-6-ether to extract water molecules and (2) potassium ion or N-benzyl-n-butylamine to block the crown ether of 1 further confirmed its critical role in assisting proton transfer via grabbed water molecules. This work presents a synthetic example to boost HER through water-containing networks.

A Hybrid Methodology to Minimize Freshwater Consumption during Shrimp Shell Waste Valorization Combining Multi-Contaminant Pinch Analysis and Superstructure Optimization

The conservation and proper management of natural resources constitute one of the main objectives of the 2030 Agenda for Sustainable Development designed by the Member States of the United Nations. In this work, a hybrid strategy based on process integration is proposed to minimize freshwater consumption while reusing wastewater. As a novelty, the strategy included a heuristic approach for identifying the minimum consumption of freshwater with a preliminary design of the water network, considering the concept of reuse and multiple pollutants. Then, mathematical programming techniques were applied to evaluate the possibilities of regeneration of the source streams through the inclusion of intercept units and establish the optimal design of the network. This strategy was used in the shrimp shell waste process to obtain chitosan, where a minimum freshwater consumption of 277 t/h was identified, with a reuse strategy and an optimal value of US $5.5 million for the design of the water network.

A novel comprehensive framework for analyzing and assessing water quality and failure consequences based on Bayesian networks

The study of the effects of mixing potable water with wastewater is a complex and difficult research area. This difficulty is because water and sewage networks are subject to various physical, environmental, and operational factors. The main objective of the study was to propose a new comprehensive framework for analyzing and assessing water quality based on Bayesian networks. An intervention plan was proposed to reduce the consequences of water quality and networks failure. The proposed framework was applied to water distribution network of Mdaourouch city (Souk Ahras, Algeria) to demonstrate its effectiveness. The results indicated that the water contamination rate has reached 33.9 %, which caused severe consequences. The effectiveness of the proposed plan has been verified theoretically using simulations, and the results have proven to be very satisfactory. The proposed model is a decision support tool, which is expected to assist decision-makers and engineers in reviewing their plans and making the right decision. PRACTITIONER POINTS: This paper proposes a novel comprehensive framework for analyzing and assessing water quality and failure consequences based on Bayesian networks. This paper revisits the failure consequences. An intervention plan is proposed to reduce failure consequences. Results demonstrate that the proposed plan leads to fewer consequences probabilities. The proposed method can give the probability of failure of water and sewer network.

Interdependent Networks: A Data Science Perspective

Traditionally, networks have been studied in an independent fashion. With the emergence of novel smart city technologies, coupling among networks has been strengthened. To capture the ever-increasing coupling, we explain the notion of interdependent networks, i.e., multi-layered networks with shared decision-making entities, and shared sensing infrastructures with interdisciplinary applications. The main challenge is how to develop data analytics solutions that are capable of enabling interdependent decision making. One of the emerging solutions is agent-based distributed decision making among heterogeneous agents and entities when their decisions are affected by multiple networks. We first provide a big picture of real-world interdependent networks in the context of smart city infrastructures. We then provide an outline of potential challenges and solutions from a data science perspective. We discuss potential hindrances to ensure reliable communication among intelligent agents from different networks. We explore future research directions at the intersection of network science and data science.

This article provides a holistic overview of interdependent cyber-physical-societal networks. We envision the subsequent research directions that require contribution of the data science community as well as interdisciplinary collaboration with network scientists, social scientists, computer scientists, and engineers to tackle the emerging problems raised by the notion of interdependent networks: (1) developing novel algorithms for data analytics and enabling interdependent decision making, (2) proposing holistic models that are capable of capturing the interdependence among human-centered multi-layer critical infrastructures, and (3) developing efficient solutions that are capable of finding globally optimum solutions using information from each network as well as modeling the interdependent information exchange. In addition to these directions, we outline policy and access-control issues, including conflict of interest among stakeholders and operators of each network. Successful implementation and development of an interdependent data analytics framework and its required algorithms will improve the quality of life of citizens by enabling globally optimum decision making, increasing efficiency, preserving privacy of intelligent agents, and reducing operational cost of interdependent networks. Further reading: Sustainable Interdependent Networks book series (interdependentnetworks.com) and Optimization, Learning, and Control for Interdependent Complex Networks (edited by M.H. Amini).

The Structural Basis for a Transition State That Regulates Pore Formation in a Bacterial Toxin

The cholesterol-dependent cytolysin (CDC) genes are present in bacterial species that span terrestrial, vertebrate, and invertebrate niches, which suggests that they have evolved to function under widely different environmental conditions. Using a combination of biophysical and crystallographic approaches, we reveal that the relative stability of an intramolecular interface in the archetype CDC perfringolysin O (PFO) plays a central role in regulating its pore-forming properties. The disruption of this interface allows the formation of the membrane spanning β-barrel pore in all CDCs. We show here that the relative strength of the stabilizing forces at this interface directly impacts the energy barrier posed by the transition state for pore formation, as reflected in the Arrhenius activation energy (E_a) for pore formation. This change directly impacts the kinetics and temperature dependence of pore formation. We further show that the interface structure in a CDC from a terrestrial species enables it to function efficiently across a wide range of temperatures by minimizing changes in the strength of the transition state barrier to pore formation. These studies establish a paradigm that CDCs, and possibly other β-barrel pore-forming proteins/toxins, can evolve significantly different pore-forming properties by altering the stability of this transitional interface, which impacts the kinetic parameters and temperature dependence of pore formation.IMPORTANCE The cholesterol-dependent cytolysins (CDCs) are the archetype for the superfamily of oligomeric pore-forming proteins that includes the membrane attack complex/perforin (MACPF) family of immune defense proteins and the stonefish venom toxins (SNTX). The CDC/MACPF/SNTX family exhibits a common protein fold, which forms a membrane-spanning β-barrel pore. We show that changing the relative stability of an extensive intramolecular interface within this fold, which is necessarily disrupted to form the large β-barrel pore, dramatically alters the kinetic and temperature-dependent properties of CDC pore formation. These studies show that the CDCs and other members of the CDC/MACPF/SNTX superfamily have the capacity to significantly alter their pore-forming properties to function under widely different environmental conditions encountered by these species.

The Crystal Structure of a hCA VII Variant Provides Insights into the Molecular Determinants Responsible for Its Catalytic Behavior

Although important progress has been achieved in understanding the catalytic mechanism of Carbonic Anhydrases, a detailed picture of all factors influencing the catalytic efficiency of the various human isoforms is still missing. In this paper we report a detailed structural study and theoretical pKa calculations on a hCA VII variant. The obtained data were compared with those already known for another thoroughly investigated cytosolic isoform, hCA II. Our structural studies show that in hCA VII the network of ordered water molecules, which connects the zinc bound solvent molecule to the proton shuttle His64, is altered compared to hCA II, causing a reduction of the catalytic efficiency. Theoretical calculations suggest that changes in solvent network are related to the difference in pKa of the proton shuttle in the two enzymes. The residue that plays a major role in determining the diverse pKa values of the proton shuttle is the one in position four, namely His for hCA II and Gly for hCA VII. This residue is located on the protein surface, outside of the active site cavity. These findings are in agreement with our previous studies that highlighted the importance of histidines on the protein surface of hCA II (among which His4) as crucial residues for the high catalytic efficiency of this isoform.

coli loop E of 5S rRNA: a molecular dynamics and reference interaction site model (RISM) study

The non-Watson-Crick (non-WC) base pairs of Escherichia coli loop E of 5S rRNA are stabilized by Mg²⁺ ions through water-mediated interaction. It is important to know the synergic role of Mg²⁺ and the water network surrounding Mg²⁺ in stabilizing the non-WC base pairs of RNA. For this purpose, free energy change of the system is calculated using molecular dynamics (MD) simulation as Mg²⁺ is pulled from RNA, which causes disturbance of the water network. It was found that Mg²⁺ remains hexahydrated unless it is close to or far from RNA. In the pentahydrated form, Mg²⁺ interacts directly with RNA. Water network has been identified by two complimentary methods; MD followed by a density-based clustering algorithm and three-dimensional-reference interaction site model. These two methods gave similar results. Identification of water network around Mg²⁺ and non-WC base pairs gives a clue to the strong effect of water network on the stability of this RNA. Based on sequence analysis of all Eubacteria 5s rRNA, we propose that hexahydrated Mg²⁺ is an integral part of this RNA and geometry of base pairs surrounding it adjust to accommodate the [Formula: see text]. Overall the findings from this work can help in understanding the basis of the complex structure and stability of RNA with non-WC base pairs.