Global genomic surveillance of monkeypox virus.

Monkeypox virus (MPXV) is endemic in Western and Central Africa and, in May 2022, a clade IIb lineage (B.1) caused a global outbreak outside Africa, resulting in its detection in 116 countries/territories. To understand the global phylogenetics of MPXV, we analysed all available MPXV sequences, including 10,670 sequences from 65 countries collected between 1958 and 2024. Our analysis reveals high mobility of clade I viruses within Central Africa, sustained human-to-human transmission of clade IIb lineage A viruses within the Eastern Mediterranean region, and distinct mutational signatures that can distinguish sustained human-to-human from animal-to-animal transmission. Moreover, distinct clade I sequences from Sudan suggest local MPXV circulation in areas of Eastern Africa over the past four decades. Our study underscores the importance of genomic surveillance in tracking spatiotemporal dynamics of MXPV clades and the need to strengthen such surveillance, including in some parts of Eastern Africa.

Evolution and host-specific adaptation of Pseudomonas aeruginosa.

The major human bacterial pathogen Pseudomonas aeruginosa causes multidrug-resistant infections in people with underlying immunodeficiencies or structural lung diseases such as cystic fibrosis (CF). We show that a few environmental isolates, driven by horizontal gene acquisition, have become dominant epidemic clones that have sequentially emerged and spread through global transmission networks over the past 200 years. These clones demonstrate varying intrinsic propensities for infecting CF or non-CF individuals (linked to specific transcriptional changes enabling survival within macrophages); have undergone multiple rounds of convergent, host-specific adaptation; and have eventually lost their ability to transmit between different patient groups. Our findings thus explain the pathogenic evolution of P. aeruginosa and highlight the importance of global surveillance and cross-infection prevention in averting the emergence of future epidemic clones.

A Fragment-Based Competitive 19F†LB-NMR Platform For Hotspot-Directed Ligand Profiling.

Ligand binding hotspots are regions of protein surfaces that form particularly favourable interactions with small molecule pharmacophores. Targeting interactions with these hotspots maximises the efficiency of ligand binding. Existing methods are capable of identifying hotspots but often lack assays to quantify ligand binding and direct elaboration at these sites. Herein, we describe a fragment-based competitive 19F Ligand Based NMR (LB-NMR) screening platform that enables routine, quantitative ligand profiling focused at ligand-binding hotspots. As a proof of concept, the method was applied to 4'-phosphopantetheine adenylyltransferase (PPAT) from Mycobacterium abscessus (Mabs). X-ray crystallographic characterisation of the hits from a 960-member fragment screen identified three ligand-binding hotspots across the PPAT active site. From the fragment hits a collection of 19F reporter candidates were designed and synthesised. By rigorous prioritisation and use of optimisation workflows, a single 19F reporter molecule was generated for each hotspot. Profiling the binding of a set of structurally characterised ligands by competitive 19F LB-NMR with this suite of 19F reporters recapitulated the binding affinity and site ID assignments made by ITC and X-ray crystallography. This quantitative mapping of ligand binding events at hotspot level resolution establishes the utility of the fragment-based competitive 19F LB-NMR screening platform for hotspot-directed ligand profiling.

In vitro platform to model the function of ionocytes in the human airway epithelium.

BACKGROUND: Pulmonary ionocytes have been identified in the airway epithelium as a small population of ion transporting cells expressing high levels of CFTR (cystic fibrosis transmembrane conductance regulator), the gene mutated in cystic fibrosis. By providing an infinite source of airway epithelial cells (AECs), the use of human induced pluripotent stem cells (hiPSCs) could overcome some challenges of studying ionocytes. However, the production of AEC epithelia containing ionocytes from hiPSCs has proven difficult. Here, we present a platform to produce hiPSC-derived AECs (hiPSC-AECs) including ionocytes and investigate their role in the airway epithelium. METHODS: hiPSCs were differentiated into lung progenitors, which were expanded as 3D organoids and matured by air-liquid interface culture as polarised hiPSC-AEC epithelia. Using CRISPR/Cas9 technology, we generated a hiPSCs knockout (KO) for FOXI1, a transcription factor that is essential for ionocyte specification. Differences between FOXI1 KO hiPSC-AECs and their wild-type (WT) isogenic controls were investigated by assessing gene and protein expression, epithelial composition, cilia coverage and motility, pH and transepithelial barrier properties. RESULTS: Mature hiPSC-AEC epithelia contained basal cells, secretory cells, ciliated cells with motile cilia, pulmonary neuroendocrine cells (PNECs) and ionocytes. There was no difference between FOXI1 WT and KO hiPSCs in terms of their capacity to differentiate into airway progenitors. However, FOXI1 KO led to mature hiPSC-AEC epithelia without ionocytes with reduced capacity to produce ciliated cells. CONCLUSION: Our results suggest that ionocytes could have role beyond transepithelial ion transport by regulating epithelial properties and homeostasis in the airway epithelium.

Lipoarabinomannan modification as a source of phenotypic heterogeneity in host-adapted Mycobacterium abscessus isolates.

Mycobacterium abscessus is increasingly recognized as the causative agent of chronic pulmonary infections in humans. One of the genes found to be under strong evolutionary pressure during adaptation of M. abscessus to the human lung is embC which encodes an arabinosyltransferase required for the biosynthesis of the cell envelope lipoglycan, lipoarabinomannan (LAM). To assess the impact of patient-derived embC mutations on the physiology and virulence of M. abscessus, mutations were introduced in the isogenic background of M. abscessus ATCC 19977 and the resulting strains probed for phenotypic changes in a variety of in vitro and host cell-based assays relevant to infection. We show that patient-derived mutational variations in EmbC result in an unexpectedly large number of changes in the physiology of M. abscessus, and its interactions with innate immune cells. Not only did the mutants produce previously unknown forms of LAM with a truncated arabinan domain and 3-linked oligomannoside chains, they also displayed significantly altered cording, sliding motility, and biofilm-forming capacities. The mutants further differed from wild-type M. abscessus in their ability to replicate and induce inflammatory responses in human monocyte-derived macrophages and epithelial cells. The fact that different embC mutations were associated with distinct physiologic and pathogenic outcomes indicates that structural alterations in LAM caused by nonsynonymous nucleotide polymorphisms in embC may be a rapid, one-step, way for M. abscessus to generate broad-spectrum diversity beneficial to survival within the heterogeneous and constantly evolving environment of the infected human airway.

Unlocking Amides: A General Method for the Self-Immolative Release of Amide-Containing Molecules.

The controlled liberation of molecules from a constructed framework is a subject of profound interest across various chemical fields. It allows for the masking of a molecule's properties and precise deployment upon a single controllable release event. While numerous methodologies have been developed for amines, alcohols, and thiols, approaches for utilising amides as payload-release handles are still in their early stages of development, despite the prevalence of amides in therapeutic compounds and materials. Herein, is presented a comprehensive strategy for the controlled and selective release of a diverse range of amides with stable linkers. The versatility of this approach is demonstrated by its successful application in the targeted release of various amide-containing drugs in their natural form via the use of commonly used trigger motifs, such as dipeptides or glycosides. As a proof of concept, the FDA-approved antibiotic linezolid has been successfully converted into a prodrug form and released selectively only in the presence of the trigger event. Significantly, in its prodrug state, no activity against Mycobacterium tuberculosis was exhibited. Linezolid's full potential was achieved only upon controlled release, where an equipotent efficacy to the free linezolid control was demonstrated, thus emphasising the immense potential of this method.

Mutational spectra are associated with bacterial niche.

As observed in cancers, individual mutagens and defects in DNA repair create distinctive mutational signatures that combine to form context-specific spectra within cells. We reasoned that similar processes must occur in bacterial lineages, potentially allowing decomposition analysis to detect both disruption of DNA repair processes and exposure to niche-specific mutagens. Here we reconstruct mutational spectra for 84 clades from 31 diverse bacterial species and find distinct mutational patterns. We extract signatures driven by specific DNA repair defects using hypermutator lineages, and further deconvolute the spectra into multiple signatures operating within different clades. We show that these signatures are explained by both bacterial phylogeny and replication niche. By comparing mutational spectra of clades from different environmental and biological locations, we identify niche-associated mutational signatures, and then employ these signatures to infer the predominant replication niches for several clades where this was previously obscure. Our results show that mutational spectra may be associated with sites of bacterial replication when mutagen exposures differ, and can be used in these cases to infer transmission routes for established and emergent human bacterial pathogens.

Clinically relevant mutations in the PhoR sensor kinase of host-adapted Mycobacterium abscessus isolates impact response to acidic pH and virulence.

IMPORTANCE: Difficult-to-treat pulmonary infections caused by nontuberculous mycobacteria of the Mycobacterium abscessus group have been steadily increasing in the USA and globally. Owing to the relatively recent recognition of M. abscessus as a human pathogen, basic and translational research to address critical gaps in diagnosis, treatment, and prevention of diseases caused by this microorganism has been lagging behind that of the better-known mycobacterial pathogen, Mycobacterium tuberculosis. To begin unraveling the molecular mechanisms of pathogenicity of M. abscessus, we here focus on the study of a two-component regulator known as PhoPR which we found to be under strong evolutionary pressure during human lung infection. We show that PhoPR is activated at acidic pH and serves to regulate a defined set of genes involved in host adaptation. Accordingly, clinical isolates from chronically infected human lungs tend to hyperactivate this regulator enabling M. abscessus to escape macrophage killing.

Evaluating Listening Performance for COVID-19 Detection by Clinicians and Machine Learning: Comparative Study.

BACKGROUND: To date, performance comparisons between men and machines have been carried out in many health domains. Yet machine learning (ML) models and human performance comparisons in audio-based respiratory diagnosis remain largely unexplored. OBJECTIVE: The primary objective of this study was to compare human clinicians and an ML model in predicting COVID-19 from respiratory sound recordings. METHODS: In this study, we compared human clinicians and an ML model in predicting COVID-19 from respiratory sound recordings. Prediction performance on 24 audio samples (12 tested positive) made by 36 clinicians with experience in treating COVID-19 or other respiratory illnesses was compared with predictions made by an ML model trained on 1162 samples. Each sample consisted of voice, cough, and breathing sound recordings from 1 subject, and the length of each sample was around 20 seconds. We also investigated whether combining the predictions of the model and human experts could further enhance the performance in terms of both accuracy and confidence. RESULTS: The ML model outperformed the clinicians, yielding a sensitivity of 0.75 and a specificity of 0.83, whereas the best performance achieved by the clinicians was 0.67 in terms of sensitivity and 0.75 in terms of specificity. Integrating the clinicians' and the model's predictions, however, could enhance performance further, achieving a sensitivity of 0.83 and a specificity of 0.92. CONCLUSIONS: Our findings suggest that the clinicians and the ML model could make better clinical decisions via a cooperative approach and achieve higher confidence in audio-based respiratory diagnosis.

A lung-specific mutational signature enables inference of viral and bacterial respiratory niche.

Exposure to different mutagens leaves distinct mutational patterns that can allow inference of pathogen replication niches. We therefore investigated whether SARS-CoV-2 mutational spectra might show lineage-specific differences, dependent on the dominant site(s) of replication and onwards transmission, and could therefore rapidly infer virulence of emergent variants of concern (VOCs). Through mutational spectrum analysis, we found a significant reduction in G>T mutations in the Omicron variant, which replicates in the upper respiratory tract (URT), compared to other lineages, which replicate in both the URT and lower respiratory tract (LRT). Mutational analysis of other viruses and bacteria indicates a robust, generalizable association of high G>T mutations with replication within the LRT. Monitoring G>T mutation rates over time, we found early separation of Omicron from Beta, Gamma and Delta, while mutational patterns in Alpha varied consistent with changes in transmission source as social restrictions were lifted. Mutational spectra may be a powerful tool to infer niches of established and emergent pathogens.

Butyrate regulates neutrophil homeostasis and impairs early antimicrobial activity in the lung.

Short-chain fatty acids (SCFAs) are metabolites that are produced after microbial fermentation of dietary fiber and impact cell metabolism and anti-inflammatory pathways both locally in the gut and systemically. In preclinical models, administration of SCFAs, such as butyrate, ameliorates a range of inflammatory disease models including allergic airway inflammation, atopic dermatitis, and influenza infection. Here we report the effect of butyrate on a bacteria-induced acute neutrophil-driven immune response in the airways. Butyrate impacted discrete aspects of hematopoiesis in the bone marrow resulting in the accumulation of immature neutrophils. During Pseudomonas aeruginosa infection, butyrate treatment led to the enhanced mobilization of neutrophils to the lungs as a result of increased CXCL2 expression by lung macrophages. Despite this increase in granulocyte numbers and their enhanced phagocytic capacity, neutrophils failed to control early bacterial growth. Butyrate reduced the expression of nicotinamide adenine dinucleotide phosphate, oxidase complex components required for reactive oxygen species production, and reduced secondary granule enzymes, culminating in impaired bactericidal activity. These data reveal that SCFAs tune neutrophil maturation and effector function in the bone marrow under homeostatic conditions, potentially to mitigate against excessive granulocyte-driven immunopathology, but their consequently restricted bactericidal capacity impairs early control of Pseudomonas infection.

Development and validation of a CRISPR interference system for gene regulation in Campylobacter jejuni.

BACKGROUND: Campylobacter spp. are the leading cause of bacterial food-borne illness in humans worldwide, with Campylobacter jejuni responsible for 80% of these infections. There is an urgent need to understand fundamental C. jejuni biology for the development of new strategies to prevent and treat infections. The range of molecular tools available to regulate gene expression in C. jejuni is limited, which in turn constrains our ability to interrogate the function of essential and conditionally essential genes. We have addressed this by developing and utilising a CRISPR-based interference system known as CRISPRi in C. jejuni to control gene expression. To achieve this, a catalytically inactive ("dead") cas9 and sgRNA backbone from the Streptococcus pyogenes CRISPRi system was combined with C. jejuni-derived promoters of predetermined expression activities to develop a CRISPRi-based repression tool in C. jejuni strains M1Cam and 81-176. RESULTS: The CRISPRi tool was validated through successful repression of the arylsulphatase-encoding gene astA using a range of sgRNA target sequences spanning the astA gene. The tool was also applied to target astA in an M1Cam CRISPR-Cas9 deletion strain, which showed that the presence of an endogenous CRISPR-Cas9 system did not affect the activity of the CRISPRi-based repression tool. The tool was further validated against the hippicurase-encoding gene hipO. Following this, the flagella genes flgR, flaA, flaB and both flaA and flaB were targeted for CRISPRi-based repression, which resulted in varying levels of motility reduction and flagella phenotypes as determined by phenotypical assays and transmission electron microscopy (TEM). CONCLUSIONS: This is the first report of a CRISPRi-based tool in C. jejuni, which will provide a valuable resource to the Campylobacter community.

Structural Characterization of Mycobacterium abscessus Phosphopantetheine Adenylyl Transferase Ligand Interactions: Implications for Fragment-Based Drug Design.

Anti-microbial resistance is a rising global healthcare concern that needs urgent attention as growing number of infections become difficult to treat with the currently available antibiotics. This is particularly true for mycobacterial infections like tuberculosis and leprosy and those with emerging opportunistic pathogens such as Mycobacterium abscessus, where multi-drug resistance leads to increased healthcare cost and mortality. M. abscessus is a highly drug-resistant non-tuberculous mycobacterium which causes life-threatening infections in people with chronic lung conditions such as cystic fibrosis. In this study, we explore M. abscessus phosphopantetheine adenylyl transferase (PPAT), an enzyme involved in the biosynthesis of Coenzyme A, as a target for the development of new antibiotics. We provide structural insights into substrate and feedback inhibitor binding modes of M. abscessus PPAT, thereby setting the basis for further chemical exploration of the enzyme. We then utilize a multi-dimensional fragment screening approach involving biophysical and structural analysis, followed by evaluation of compounds from a previous fragment-based drug discovery campaign against M. tuberculosis PPAT ortholog. This allowed the identification of an early-stage lead molecule exhibiting low micro molar affinity against M. abscessus PPAT (Kd 3.2 ± 0.8 µM) and potential new ways to design inhibitors against this enzyme. The resulting crystal structures reveal striking conformational changes and closure of solvent channel of M. abscessus PPAT hexamer providing novel strategies of inhibition. The study thus validates the ligandability of M. abscessus PPAT as an antibiotic target and identifies crucial starting points for structure-guided drug discovery against this bacterium.

Exploring Longitudinal Cough, Breath, and Voice Data for COVID-19 Progression Prediction via Sequential Deep Learning: Model Development and Validation.

BACKGROUND: Recent work has shown the potential of using audio data (eg, cough, breathing, and voice) in the screening for COVID-19. However, these approaches only focus on one-off detection and detect the infection, given the current audio sample, but do not monitor disease progression in COVID-19. Limited exploration has been put forward to continuously monitor COVID-19 progression, especially recovery, through longitudinal audio data. Tracking disease progression characteristics and patterns of recovery could bring insights and lead to more timely treatment or treatment adjustment, as well as better resource management in health care systems. OBJECTIVE: The primary objective of this study is to explore the potential of longitudinal audio samples over time for COVID-19 progression prediction and, especially, recovery trend prediction using sequential deep learning techniques. METHODS: Crowdsourced respiratory audio data, including breathing, cough, and voice samples, from 212 individuals over 5-385 days were analyzed, alongside their self-reported COVID-19 test results. We developed and validated a deep learning-enabled tracking tool using gated recurrent units (GRUs) to detect COVID-19 progression by exploring the audio dynamics of the individuals' historical audio biomarkers. The investigation comprised 2 parts: (1) COVID-19 detection in terms of positive and negative (healthy) tests using sequential audio signals, which was primarily assessed in terms of the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity, with 95% CIs, and (2) longitudinal disease progression prediction over time in terms of probability of positive tests, which was evaluated using the correlation between the predicted probability trajectory and self-reported labels. RESULTS: We first explored the benefits of capturing longitudinal dynamics of audio biomarkers for COVID-19 detection. The strong performance, yielding an AUROC of 0.79, a sensitivity of 0.75, and a specificity of 0.71 supported the effectiveness of the approach compared to methods that do not leverage longitudinal dynamics. We further examined the predicted disease progression trajectory, which displayed high consistency with longitudinal test results with a correlation of 0.75 in the test cohort and 0.86 in a subset of the test cohort with 12 (57.1%) of 21 COVID-19-positive participants who reported disease recovery. Our findings suggest that monitoring COVID-19 evolution via longitudinal audio data has potential in the tracking of individuals' disease progression and recovery. CONCLUSIONS: An audio-based COVID-19 progression monitoring system was developed using deep learning techniques, with strong performance showing high consistency between the predicted trajectory and the test results over time, especially for recovery trend predictions. This has good potential in the postpeak and postpandemic era that can help guide medical treatment and optimize hospital resource allocations. The changes in longitudinal audio samples, referred to as audio dynamics, are associated with COVID-19 progression; thus, modeling the audio dynamics can potentially capture the underlying disease progression process and further aid COVID-19 progression prediction. This framework provides a flexible, affordable, and timely tool for COVID-19 tracking, and more importantly, it also provides a proof of concept of how telemonitoring could be applicable to respiratory diseases monitoring, in general.

Hyperphosphorylated tau self-assembles into amorphous aggregates eliciting TLR4-dependent responses.

Soluble aggregates of the microtubule-associated protein tau have been challenging to assemble and characterize, despite their important role in the development of tauopathies. We found that sequential hyperphosphorylation by protein kinase A in conjugation with either glycogen synthase kinase 3ß or stress activated protein kinase 4 enabled recombinant wild-type tau of isoform 0N4R to spontaneously polymerize into small amorphous aggregates in vitro. We employed tandem mass spectrometry to determine the phosphorylation sites, high-resolution native mass spectrometry to measure the degree of phosphorylation, and super-resolution microscopy and electron microscopy to characterize the morphology of aggregates formed. Functionally, compared with the unmodified aggregates, which require heparin induction to assemble, these self-assembled hyperphosphorylated tau aggregates more efficiently disrupt membrane bilayers and induce Toll-like receptor 4-dependent responses in human macrophages. Together, our results demonstrate that hyperphosphorylated tau aggregates are potentially damaging to cells, suggesting a mechanism for how hyperphosphorylation could drive neuroinflammation in tauopathies.

Using Structure-guided Fragment-Based Drug Discovery to Target Pseudomonas aeruginosa Infections in Cystic Fibrosis.

Cystic fibrosis (CF) is progressive genetic disease that predisposes lungs and other organs to multiple long-lasting microbial infections. Pseudomonas aeruginosa is the most prevalent and deadly pathogen among these microbes. Lung function of CF patients worsens following chronic infections with P. aeruginosa and is associated with increased mortality and morbidity. Emergence of multidrug-resistant, extensively drug-resistant and pandrug-resistant strains of P. aeruginosa due to intrinsic and adaptive antibiotic resistance mechanisms has failed the current anti-pseudomonal antibiotics. Hence new antibacterials are urgently needed to treat P. aeruginosa infections. Structure-guided fragment-based drug discovery (FBDD) is a powerful approach in the field of drug development that has succeeded in delivering six FDA approved drugs over the past 20 years targeting a variety of biological molecules. However, FBDD has not been widely used in the development of anti-pseudomonal molecules. In this review, we first give a brief overview of our structure-guided FBDD pipeline and then give a detailed account of FBDD campaigns to combat P. aeruginosa infections by developing small molecules having either bactericidal or anti-virulence properties. We conclude with a brief overview of the FBDD efforts in our lab at the University of Cambridge towards targeting P. aeruginosa infections.

Development of Inhibitors of SAICAR Synthetase (PurC) from Mycobacterium abscessus Using a Fragment-Based Approach.

Mycobacterium abscessus (Mab) has emerged as a challenging threat to individuals with cystic fibrosis. Infections caused by this pathogen are often impossible to treat due to the intrinsic antibiotic resistance leading to lung malfunction and eventually death. Therefore, there is an urgent need to develop new drugs against novel targets in Mab to overcome drug resistance and subsequent treatment failure. In this study, SAICAR synthetase (PurC) from Mab was identified as a promising target for novel antibiotics. An in-house fragment library screen and a high-throughput X-ray crystallographic screen of diverse fragment libraries were explored to provide crucial starting points for fragment elaboration. A series of compounds developed from fragment growing and merging strategies, guided by crystallographic information and careful hit-to-lead optimization, have achieved potent nanomolar binding affinity against the enzyme. Some compounds also show a promising inhibitory effect against Mab and Mtb. This work utilizes a fragment-based design and demonstrates for the first time the potential to develop inhibitors against PurC from Mab.

Roscovitine Worsens Mycobacterium abscessus Infection by Reducing DUOX2-mediated Neutrophil Response.

Persistent neutrophilic inflammation associated with chronic pulmonary infection causes progressive lung injury and, eventually, death in individuals with cystic fibrosis (CF), a genetic disease caused by biallelic mutations in the CF transmembrane conductance regulator (CFTR) gene. Therefore, we examined whether roscovitine, a cyclin-dependent kinase inhibitor that (in other conditions) reduces inflammation while promoting host defense, might provide a beneficial effect in the context of CF. Herein, using CFTR-depleted zebrafish larvae as an innovative vertebrate model of CF immunopathophysiology, combined with murine and human approaches, we sought to determine the effects of roscovitine on innate immune responses to tissue injury and pathogens in the CF condition. We show that roscovitine exerts antiinflammatory and proresolution effects in neutrophilic inflammation induced by infection or tail amputation in zebrafish. Roscovitine reduces overactive epithelial reactive oxygen species (ROS)-mediated neutrophil trafficking by reducing DUOX2/NADPH-oxidase activity and accelerates inflammation resolution by inducing neutrophil apoptosis and reverse migration. It is important to note that, although roscovitine efficiently enhances intracellular bacterial killing of Mycobacterium abscessus in human CF macrophages ex vivo, we found that treatment with roscovitine results in worse infection in mouse and zebrafish models. By interfering with DUOX2/NADPH oxidase-dependent ROS production, roscovitine reduces the number of neutrophils at infection sites and, consequently, compromises granuloma formation and maintenance, favoring extracellular multiplication of M. abscessus and more severe infection. Our findings bring important new understanding of the immune-targeted action of roscovitine and have significant therapeutic implications for safely targeting inflammation in CF.

Discovery of Novel Inhibitors of Uridine Diphosphate-N-Acetylenolpyruvylglucosamine Reductase (MurB) from Pseudomonas aeruginosa, an Opportunistic Infectious Agent Causing Death in Cystic Fibrosis Patients.

Pseudomonas aeruginosa is of major concern for cystic fibrosis patients where this infection can be fatal. With the emergence of drug-resistant strains, there is an urgent need to develop novel antibiotics against P. aeruginosa. MurB is a promising target for novel antibiotic development as it is involved in the cell wall biosynthesis. MurB has been shown to be essential in P. aeruginosa, and importantly, no MurB homologue exists in eukaryotic cells. A fragment-based drug discovery approach was used to target Pa MurB. This led to the identification of a number of fragments, which were shown to bind to MurB. One fragment, a phenylpyrazole scaffold, was shown by ITC to bind with an affinity of Kd = 2.88 mM (LE 0.23). Using a structure guided approach, different substitutions were synthesized and the initial fragment was optimized to obtain a small molecule with Kd = 3.57 µM (LE 0.35).

The Removal of Airborne Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Other Microbial Bioaerosols by Air Filtration on Coronavirus Disease 2019 (COVID-19) Surge Units.

Airborne severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was detected in a coronavirus disease 19 (COVID-19) ward before activation of HEPA-air filtration but not during filter operation; SARS-CoV-2 was again detected following filter deactivation. Airborne SARS-CoV-2 was infrequently detected in a COVID-19 intensive care unit. Bioaerosol was also effectively filtered.