Raising awareness of antimicrobial resistance: development of an 'antibiotic footprint calculator'.

Non-academic partners can be vital in successful public engagement activities on antimicrobial resistance. With collaboration between academic and non-academic partners, we developed and launched an open-access web-based application, the 'antibiotic footprint calculator', in both Thai and English. The application focused on a good user experience, addressing antibiotic overuse and its impact, and encouraging immediate action. The application was unveiled in joint public engagement activities. From 1 Nov 2021 to 31 July 2022 (9 month period), 2554 players estimated their personal antibiotic footprint by using the application.

Microbiome Dysbiosis Shows Strong Association of Gut-Derived Altered Metabolomic Profile in Gulf War Chronic Multisymptom Illness Symptom Persistence Following Western Diet Feeding and Development of Obesity.

The pathophysiology of Gulf War Illness (GWI) remains elusive even after three decades. The persistence of multiple complex symptoms along with metabolic disorders such as obesity worsens the health of present Gulf War (GW) Veterans often by the interactions of the host gut microbiome and inflammatory mediators. In this study, we hypothesized that the administration of a Western diet might alter the host metabolomic profile, which is likely associated with the altered bacterial species. Using a five-month symptom persistence GWI model in mice and whole-genome sequencing, we characterized the species-level dysbiosis and global metabolomics, along with heterogenous co-occurrence network analysis, to study the bacteriome-metabolomic association. Microbial analysis at the species level showed a significant alteration of beneficial bacterial species. The beta diversity of the global metabolomic profile showed distinct clustering due to the Western diet, along with the alteration of metabolites associated with lipid, amino acid, nucleotide, vitamin, and xenobiotic metabolism pathways. Network analysis showed novel associations of gut bacterial species with metabolites and biochemical pathways that could be used as biomarkers or therapeutic targets to ameliorate symptom persistence in GW Veterans.

Detection of SARS-CoV-2 in high-efficiency particulate air (HEPA) filters of low-cost air purifiers in community-based organizations.

This study aims to investigate the presence of SARS-CoV-2 in public spaces and assess the utility of inexpensive air purifiers equipped with high-efficiency particulate air (HEPA) filters for viral detection. Samples were collected from six community-based organizations in underserved minority neighborhoods in Northwest Miami, Florida, from February to May 2022. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to detect SARS-CoV-2 in air purifier filters and surface swabs. Among 32 filters tested, three yielded positive results, while no positive surface swabs were found. Notably, positive samples were obtained exclusively from child daycare centers. These findings highlight the potential for airborne transmission of SARS-CoV-2 in indoor air, particularly in child daycare centers. Moreover, the study demonstrates the effectiveness of readily available HEPA filters in detecting the virus. Improving indoor ventilation and implementing air filtration systems are crucial in reducing COVID-19 transmission where people gather. Air filtration systems incorporating HEPA filters offer a valuable approach to virus detection and reducing transmission risks. Future research should explore the applicability of this technology for early identification and mitigation of viral outbreaks.

Rhizospheric and endophytic Pseudomonas aeruginosa in edible vegetable plants share molecular and metabolic traits with clinical isolates.

AIM: Pseudomonas aeruginosa, a leading opportunistic pathogen causing hospital-acquired infections, is also commonly found in agricultural settings. However, there are minimal attempts to examine the molecular and functional attributes shared by agricultural and clinical strains of P. aeruginosa. This study investigates the presence of P. aeruginosa in edible vegetable plants (including salad vegetables) and analyses the evolutionary and metabolic relatedness of the agricultural and clinical strains. METHODS AND RESULTS: Eighteen rhizospheric and endophytic P. aeruginosa strains were isolated from cucumber, tomato, eggplant, and chili directly from the farms. The identity of these strains was confirmed using biochemical and molecular assays. The genetic and metabolic traits of these plant-associated P. aeruginosa isolates were compared with clinical strains. DNA fingerprinting and 16S rDNA-based phylogenetic analyses revealed that the plant- and human-associated strains are evolutionarily related. Both agricultural and clinical isolates possessed plant-beneficial properties, including mineral solubilization to release essential nutrients (phosphorous, potassium, and zinc), ammonification, and the ability to release extracellular pyocyanin, siderophore, and indole-3 acetic acid. CONCLUSION: These findings suggest that rhizospheric and endophytic P. aeruginosa strains are genetically and functionally analogous to the clinical isolates. In addition, the genotypic and phenotypic traits do not correlate with plant sources or ecosystems. SIGNIFICANCE AND IMPACT OF THE STUDY: This study reconfirms that edible plants are the potential source for human and animal transmission of P. aeruginosa.

New dynamic microreactor system to mimic biofilm formation and test anti-biofilm activity of nanoparticles.

Microbial biofilms are composed of surface-adhered microorganisms enclosed in extracellular polymeric substances. The biofilm lifestyle is the intrinsic drug resistance imparted to bacterial cells protected by the matrix. So far, conventional drug susceptibility tests for biofilm are reagent and time-consuming, and most of them are in static conditions. Rapid and easy-to-use methods for biofilm formation and antibiotic activity testing need to be developed to accelerate the discovery of new antibiofilm strategies. Herein, a Lab-On-Chip (LOC) device is presented that provides optimal microenvironmental conditions closely mimicking real-life clinical biofilm status. This new device allows homogeneous attachment and immobilization of Pseudomonas aeruginosa PA01-EGFP cells, and the biofilms grown can be monitored by fluorescence microscopy. P. aeruginosa is an opportunistic pathogen known as a model for drug screening biofilm studies. The influence of flow rates on biofilms growth was analyzed by flow simulations using COMSOL® 5.2. Significant cell adhesion to the substrate and biofilm formation inside the microchannels were observed at higher flow rates > 100 µL/h. After biofilm formation, the effectiveness of silver nanoparticles (SNP), chitosan nanoparticles (CNP), and a complex of chitosan-coated silver nanoparticles (CSNP) to eradicate the biofilm under a continuous flow was explored. The most significant loss of biofilm was seen with CSNP with a 65.5% decrease in average live/dead cell signal in biofilm compared to the negative controls. Our results demonstrate that this system is a user-friendly tool for antibiofilm drug screening that could be simply applied in clinical laboratories.Key Points• A continuous-flow microreactor that mimics real-life clinical biofilm infections was developed.• The antibiofilm activity of three nano drugs was evaluated in dynamic conditions.• The highest biofilm reduction was observed with chitosan-silver nanoparticles.

Multi-Run Concrete Autoencoder to Identify Prognostic lncRNAs for 12 Cancers.

BACKGROUND: Long non-coding RNA plays a vital role in changing the expression profiles of various target genes that lead to cancer development. Thus, identifying prognostic lncRNAs related to different cancers might help in developing cancer therapy. METHOD: To discover the critical lncRNAs that can identify the origin of different cancers, we propose the use of the state-of-the-art deep learning algorithm concrete autoencoder (CAE) in an unsupervised setting, which efficiently identifies a subset of the most informative features. However, CAE does not identify reproducible features in different runs due to its stochastic nature. We thus propose a multi-run CAE (mrCAE) to identify a stable set of features to address this issue. The assumption is that a feature appearing in multiple runs carries more meaningful information about the data under consideration. The genome-wide lncRNA expression profiles of 12 different types of cancers, with a total of 4768 samples available in The Cancer Genome Atlas (TCGA), were analyzed to discover the key lncRNAs. The lncRNAs identified by multiple runs of CAE were added to a final list of key lncRNAs that are capable of identifying 12 different cancers. RESULTS: Our results showed that mrCAE performs better in feature selection than single-run CAE, standard autoencoder (AE), and other state-of-the-art feature selection techniques. This study revealed a set of top-ranking 128 lncRNAs that could identify the origin of 12 different cancers with an accuracy of 95%. Survival analysis showed that 76 of 128 lncRNAs have the prognostic capability to differentiate high- and low-risk groups of patients with different cancers. CONCLUSION: The proposed mrCAE, which selects actual features, outperformed the AE even though it selects the latent or pseudo-features. By selecting actual features instead of pseudo-features, mrCAE can be valuable for precision medicine. The identified prognostic lncRNAs can be further studied to develop therapies for different cancers.

So you think you can PLS-DA?

BACKGROUND: Partial Least-Squares Discriminant Analysis (PLS-DA) is a popular machine learning tool that is gaining increasing attention as a useful feature selector and classifier. In an effort to understand its strengths and weaknesses, we performed a series of experiments with synthetic data and compared its performance to its close relative from which it was initially invented, namely Principal Component Analysis (PCA). RESULTS: We demonstrate that even though PCA ignores the information regarding the class labels of the samples, this unsupervised tool can be remarkably effective as a feature selector. In some cases, it outperforms PLS-DA, which is made aware of the class labels in its input. Our experiments range from looking at the signal-to-noise ratio in the feature selection task, to considering many practical distributions and models encountered when analyzing bioinformatics and clinical data. Other methods were also evaluated. Finally, we analyzed an interesting data set from 396 vaginal microbiome samples where the ground truth for the feature selection was available. All the 3D figures shown in this paper as well as the supplementary ones can be viewed interactively at http://biorg.cs.fiu.edu/plsda CONCLUSIONS: Our results highlighted the strengths and weaknesses of PLS-DA in comparison with PCA for different underlying data models.

Inferring directional relationships in microbial communities using signed Bayesian networks.

BACKGROUND: Microbe-microbe and host-microbe interactions in a microbiome play a vital role in both health and disease. However, the structure of the microbial community and the colonization patterns are highly complex to infer even under controlled wet laboratory conditions. In this study, we investigate what information, if any, can be provided by a Bayesian Network (BN) about a microbial community. Unlike the previously proposed Co-occurrence Networks (CoNs), BNs are based on conditional dependencies and can help in revealing complex associations. RESULTS: In this paper, we propose a way of combining a BN and a CoN to construct a signed Bayesian Network (sBN). We report a surprising association between directed edges in signed BNs and known colonization orders. CONCLUSIONS: BNs are powerful tools for community analysis and extracting influences and colonization patterns, even though the analysis only uses an abundance matrix with no temporal information. We conclude that directed edges in sBNs when combined with negative correlations are consistent with and strongly suggestive of colonization order.

Pseudomonas aeruginosa Regulated Intramembrane Proteolysis: Protease MucP Can Overcome Mutations in the AlgO Periplasmic Protease To Restore Alginate Production in Nonmucoid Revertants.

The progression of cystic fibrosis (CF) from an acute to a chronic disease is often associated with the conversion of the opportunistic pathogen Pseudomonas aeruginosa from a nonmucoid form to a mucoid form in the lung. This conversion involves the constitutive synthesis of the exopolysaccharide alginate, whose production is under the control of the AlgT/U sigma factor. This factor is regulated posttranslationally by an extremely unstable process and has been commonly attributed to mutations in the algT (algU) gene. By exploiting this unstable phenotype, we isolated 34 spontaneous nonmucoid variants arising from the mucoid strain PDO300, a PAO1 derivative containing the mucA22 allele commonly found in mucoid CF isolates. Complementation analysis using a minimal tiling path cosmid library revealed that most of these mutants mapped to two protease-encoding genes, algO, also known as prc or PA3257, and mucP Interestingly, our algO mutations were complemented by both mucP and algO, leading us to delete, clone, and overexpress mucP, algO, mucE, and mucD in both wild-type PAO1 and PDO300 backgrounds to better understand the regulation of this complex regulatory mechanism. Our findings suggest that the regulatory proteases follow two pathways for regulated intramembrane proteolysis (RIP), where both the AlgO/MucP pathway and MucE/AlgW pathway are required in the wild-type strain but where the AlgO/MucP pathway can bypass the MucE/AlgW pathway in mucoid strains with membrane-associated forms of MucA with shortened C termini, such as the MucA22 variant. This work gives us a better understanding of how alginate production is regulated in the clinically important mucoid variants of Pseudomonas aeruginosaIMPORTANCE Infection by the opportunistic pathogen Pseudomonas aeruginosa is the leading cause of morbidity and mortality seen in CF patients. Poor patient prognosis correlates with the genotypic and phenotypic change of the bacteria from a typical nonmucoid to a mucoid form in the CF lung, characterized by the overproduction of alginate. The expression of this exopolysaccharide is under the control an alternate sigma factor, AlgT/U, that is regulated posttranslationally by a series of proteases. A better understanding of this regulatory phenomenon will help in the development of therapies targeting alginate production, ultimately leading to an increase in the length and quality of life for those suffering from CF.

Characterization of a Carbapenem-Hydrolyzing Enzyme, PoxB, in Pseudomonas aeruginosa PAO1.

Pseudomonas aeruginosa is an opportunistic pathogen often associated with severe and life-threatening infections that are highly impervious to treatment. This microbe readily exhibits intrinsic and acquired resistance to varied antimicrobial drugs. Resistance to penicillin-like compounds is commonplace and provided by the chromosomal AmpC ß-lactamase. A second, chromosomally encoded ß-lactamase, PoxB, has previously been reported in P. aeruginosa. In the present work, the contribution of this class D enzyme was investigated using a series of clean in-frame ampC, poxB, and oprD deletions, as well as complementation by expression under the control of an inducible promoter. While poxB deletions failed to alter ß-lactam sensitivities, expression of poxB in ampC-deficient backgrounds decreased susceptibility to both meropenem and doripenem but had no effect on imipenem, penicillin, and cephalosporin MICs. However, when expressed in an ampCpoxB-deficient background, that additionally lacked the outer membrane porin-encoding gene oprD, PoxB significantly increased the imipenem as well as the meropenem and doripenem MICs. Like other class D carbapenem-hydrolyzing ß-lactamases, PoxB was only poorly inhibited by class A enzyme inhibitors, but a novel non-ß-lactam compound, avibactam, was a slightly better inhibitor of PoxB activity. In vitro susceptibility testing with a clinical concentration of avibactam, however, failed to reduce PoxB activity against the carbapenems. In addition, poxB was found to be cotranscribed with an upstream open reading frame, poxA, which itself was shown to encode a 32-kDa protein of yet unknown function.

Deep sequencing analyses expands the Pseudomonas aeruginosa AmpR regulon to include small RNA-mediated regulation of iron acquisition, heat shock and oxidative stress response.

Pathogenicity of Pseudomonas aeruginosa, a major cause of many acute and chronic human infections, is determined by tightly regulated expression of multiple virulence factors. Quorum sensing (QS) controls expression of many of these pathogenic determinants. Previous microarray studies have shown that the AmpC ß-lactamase regulator AmpR, a member of the LysR family of transcription factors, also controls non-ß-lactam resistance and multiple virulence mechanisms. Using RNA-Seq and complementary assays, this study further expands the AmpR regulon to include diverse processes such as oxidative stress, heat shock and iron uptake. Importantly, AmpR affects many of these phenotypes, in part, by regulating expression of non-coding RNAs such as rgP32, asRgsA, asPrrF1 and rgRsmZ. AmpR positively regulates expression of the major QS regulators LasR, RhlR and MvfR, and genes of the Pseudomonas quinolone system. Chromatin immunoprecipitation (ChIP)-Seq and ChIP-quantitative real-time polymerase chain reaction studies show that AmpR binds to the ampC promoter both in the absence and presence of ß-lactams. In addition, AmpR directly binds the lasR promoter, encoding the QS master regulator. Comparison of the AmpR-binding sequences from the transcriptome and ChIP-Seq analyses identified an AT-rich consensus-binding motif. This study further attests to the role of AmpR in regulating virulence and physiological processes in P. aeruginosa.

Muropeptides in Pseudomonas aeruginosa and their Role as Elicitors of ß-Lactam-Antibiotic Resistance.

Muropeptides are a group of bacterial natural products generated from the cell wall in the course of its turnover. These compounds are cell-wall recycling intermediates and are also involved in signaling within the bacterium. However, the identity of these signaling molecules remains elusive. The identification and characterization of 20 muropeptides from Pseudomonas aeruginosa is described. The least abundant of these metabolites is present at 100 and the most abundant at 55,000 molecules per bacterium. Analysis of these muropeptides under conditions of induction of resistance to a ß-lactam antibiotic identified two signaling muropeptides (N-acetylglucosamine-1,6-anhydro-N-acetylmuramyl pentapeptide and 1,6-anhydro-N-acetylmuramyl pentapeptide). Authentic synthetic samples of these metabolites were shown to activate expression of ß-lactamase in the absence of any ß-lactam antibiotic, thus indicating that they serve as chemical signals in this complex biochemical pathway.

Microbial "social networks".

BACKGROUND: It is well understood that distinct communities of bacteria are present at different sites of the body, and that changes in the structure of these communities have strong implications for human health. Yet, challenges remain in understanding the complex interconnections between the bacterial taxa within these microbial communities and how they change during the progression of diseases. Many recent studies attempt to analyze the human microbiome using traditional ecological measures and cataloging differences in bacterial community membership. In this paper, we show how to push metagenomic analyses beyond mundane questions related to the bacterial taxonomic profiles that differentiate one sample from another. METHODS: We develop tools and techniques that help us to investigate the nature of social interactions in microbial communities, and demonstrate ways of compactly capturing extensive information about these networks and visually conveying them in an effective manner. We define the concept of bacterial "social clubs", which are groups of taxa that tend to appear together in many samples. More importantly, we define the concept of "rival clubs", entire groups that tend to avoid occurring together in many samples. We show how to efficiently compute social clubs and rival clubs and demonstrate their utility with the help of examples including a smokers' dataset and a dataset from the Human Microbiome Project (HMP). RESULTS: The tools developed provide a framework for analyzing relationships between bacterial taxa modeled as bacterial co-occurrence networks. The computational techniques also provide a framework for identifying clubs and rival clubs and for studying differences in the microbiomes (and their interactions) of two or more collections of samples. CONCLUSIONS: Microbial relationships are similar to those found in social networks. In this work, we assume that strong (positive or negative) tendencies to co-occur or co-infect is likely to have biological, physiological, or ecological significance, possibly as a result of cooperation or competition. As a consequence of the analysis, a variety of biological interpretations are conjectured. In the human microbiome context, the pattern of strength of interactions between bacterial taxa is unique to body site.

A dynamic and intricate regulatory network determines Pseudomonas aeruginosa virulence.

Pseudomonas aeruginosa is a metabolically versatile bacterium that is found in a wide range of biotic and abiotic habitats. It is a major human opportunistic pathogen causing numerous acute and chronic infections. The critical traits contributing to the pathogenic potential of P. aeruginosa are the production of a myriad of virulence factors, formation of biofilms and antibiotic resistance. Expression of these traits is under stringent regulation, and it responds to largely unidentified environmental signals. This review is focused on providing a global picture of virulence gene regulation in P. aeruginosa. In addition to key regulatory pathways that control the transition from acute to chronic infection phenotypes, some regulators have been identified that modulate multiple virulence mechanisms. Despite of a propensity for chaotic behaviour, no chaotic motifs were readily observed in the P. aeruginosa virulence regulatory network. Having a 'birds-eye' view of the regulatory cascades provides the forum opportunities to pose questions, formulate hypotheses and evaluate theories in elucidating P. aeruginosa pathogenesis. Understanding the mechanisms involved in making P. aeruginosa a successful pathogen is essential in helping devise control strategies.

Structural and functional characterization of Pseudomonas aeruginosa global regulator AmpR.

Pseudomonas aeruginosa is a dreaded pathogen in many clinical settings. Its inherent and acquired antibiotic resistance thwarts therapy. In particular, derepression of the AmpC ß-lactamase is a common mechanism of ß-lactam resistance among clinical isolates. The inducible expression of ampC is controlled by the global LysR-type transcriptional regulator (LTTR) AmpR. In the present study, we investigated the genetic and structural elements that are important for ampC induction. Specifically, the ampC (PampC) and ampR (PampR) promoters and the AmpR protein were characterized. The transcription start sites (TSSs) of the divergent transcripts were mapped using 5' rapid amplification of cDNA ends-PCR (RACE-PCR), and strong σ(54) and σ(70) consensus sequences were identified at PampR and PampC, respectively. Sigma factor RpoN was found to negatively regulate ampR expression, possibly through promoter blocking. Deletion mapping revealed that the minimal PampC extends 98 bp upstream of the TSS. Gel shifts using membrane fractions showed that AmpR binds to PampC in vitro whereas in vivo binding was demonstrated using chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR). Additionally, site-directed mutagenesis of the AmpR helix-turn-helix (HTH) motif identified residues critical for binding and function (Ser38 and Lys42) and critical for function but not binding (His39). Amino acids Gly102 and Asp135, previously implicated in the repression state of AmpR in the enterobacteria, were also shown to play a structural role in P. aeruginosa AmpR. Alkaline phosphatase fusion and shaving experiments suggest that AmpR is likely to be membrane associated. Lastly, an in vivo cross-linking study shows that AmpR dimerizes. In conclusion, a potential membrane-associated AmpR dimer regulates ampC expression by direct binding.

Genomic and metabolic versatility of Pseudomonas aeruginosa contributes to its inter-kingdom transmission and survival.

Pseudomonas aeruginosa is one of the most versatile bacteria with renowned pathogenicity and extensive drug resistance. The diverse habitats of this bacterium include fresh, saline and drainage waters, soil, moist surfaces, taps, showerheads, pipelines, medical implants, nematodes, insects, plants, animals, birds and humans. The arsenal of virulence factors produced by P. aeruginosa includes pyocyanin, rhamnolipids, siderophores, lytic enzymes, toxins and polysaccharides. All these virulent elements coupled with intrinsic, adaptive and acquired antibiotic resistance facilitate persistent colonization and lethal infections in different hosts. To date, treating pulmonary diseases remains complicated due to the chronic secondary infections triggered by hospital-acquired P. aeruginosa. On the contrary, this bacterium can improve plant growth by suppressing phytopathogens and insects. Notably, P. aeruginosa is one of the very few bacteria capable of trans-kingdom transmission and infection. Transfer of P. aeruginosa strains from plant materials to hospital wards, animals to humans, and humans to their pets occurs relatively often. Recently, we have identified that plant-associated P. aeruginosa strains could be pathologically similar to clinical isolates. In this review, we have highlighted the genomic and metabolic factors that facilitate the dominance of P. aeruginosa across different biological kingdoms and the varying roles of this bacterium in plant and human health.

Differences in gut microbiota between Dutch and South-Asian Surinamese: potential implications for type 2 diabetes mellitus.

Gut microbiota, or the collection of diverse microorganisms in a specific ecological niche, are known to significantly impact human health. Decreased gut microbiota production of short-chain fatty acids (SCFAs) has been implicated in type 2 diabetes mellitus (T2DM) disease progression. Most microbiome studies focus on ethnic majorities. This study aims to understand how the microbiome differs between an ethnic majority (the Dutch) and minority (the South-Asian Surinamese (SAS)) group with a lower and higher prevalence of T2DM, respectively. Microbiome data from the Healthy Life in an Urban Setting (HELIUS) cohort were used. Two age- and gender-matched groups were compared: the Dutch (n = 41) and SAS (n = 43). Microbial community compositions were generated via DADA2. Metrics of microbial diversity and similarity between groups were computed. Biomarker analyses were performed to determine discriminating taxa. Bacterial co-occurrence networks were constructed to examine ecological patterns. A tight microbiota cluster was observed in the Dutch women, which overlapped with some of the SAS microbiota. The Dutch gut contained a more interconnected microbial ecology, whereas the SAS network was dispersed, i.e., contained fewer inter-taxonomic correlational relationships. Bacteroides caccae, Butyricicoccus, Alistipes putredinis, Coprococcus comes, Odoribacter splanchnicus, and Lachnospira were enriched in the Dutch gut. Haemophilus, Bifidobacterium, and Anaerostipes hadrus discriminated the SAS gut. All but Lachnospira and certain strains of Haemophilus are known to produce SCFAs. The Dutch gut microbiome was distinguished from the SAS by diverse, differentially abundant SCFA-producing taxa with significant cooperation. The dynamic ecology observed in the Dutch was not detected in the SAS. Among several potential gut microbial biomarkers, Haemophilus parainfluenzae likely best characterizes the ethnic minority group, which is more predisposed to T2DM. The higher prevalence of T2DM in the SAS may be associated with the gut dysbiosis observed.