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A series of synthetic lethal strategies identifies a small-molecule inhibitor of Staphylococcus aureus DltB, links teichoic acid D -alanylation to virulence and identifies synergistic antibiotic drug combinations. The majority of bacterial proteins are dispensable for growth in the laboratory but nevertheless have important physiological roles. There are no systematic approaches to identify cell-permeable small-molecule inhibitors of these proteins. We demonstrate a strategy to identify such inhibitors that exploits synthetic lethal relationships both for small-molecule discovery and for target identification. Applying this strategy in Staphylococcus aureus , we have identified a compound that inhibits DltB, a component of the teichoic acid D -alanylation machinery that has been implicated in virulence. This D -alanylation inhibitor sensitizes S. aureus to aminoglycosides and cationic peptides and is lethal in combination with a wall teichoic acid inhibitor. We conclude that DltB is a druggable target in the D -alanylation pathway. More broadly, the work described demonstrates a systematic method to identify biologically active inhibitors of major bacterial processes that can be adapted to numerous organisms.

Pathway docking ( in silico docking of metabolites to several enzymes and binding proteins in a metabolic pathway) enables the discovery of a catabolic pathway for the osmolyte trans -4-hydroxy- l -proline betaine. Structural key to predicting enzyme function Overprediction and database annotation errors in genome-sequencing projects have caused much confusion because of the difficulty of assigning valid functions to the proteins identified. These authors use structure-guided approaches for predicting the substrate specificities of several enzymes encoded by a bacterial gene cluster to correctly predict the in vitro activity of an enzyme of unknown function and identify the catabolic pathway in which it participates in cells. The substrate-liganded pose predicted by virtual library screening was confirmed experimentally, enzyme activities in the predicted pathway were confirmed by in vitro assays and genetic analyses, the intermediates were identified by metabolomics, and repression of the genes encoding the pathway by high salt concentrations was established by transcriptomics. This study establishes the utility of structure-guided functional predictions for the discovery of new metabolic pathways. Assigning valid functions to proteins identified in genome projects is challenging: overprediction and database annotation errors are the principal concerns 1 . We and others 2 are developing computation-guided strategies for functional discovery with ‘metabolite docking’ to experimentally derived 3 or homology-based 4 three-dimensional structures. Bacterial metabolic pathways often are encoded by ‘genome neighbourhoods’ (gene clusters and/or operons), which can provide important clues for functional assignment. We recently demonstrated the synergy of docking and pathway context by ‘predicting’ the intermediates in the glycolytic pathway in Escherichia coli 5 . Metabolite docking to multiple binding proteins and enzymes in the same pathway increases the reliability of in silico predictions of substrate specificities because the pathway intermediates are structurally similar. Here we report that structure-guided approaches for predicting the substrate specificities of several enzymes encoded by a bacterial gene cluster allowed the correct prediction of the in vitro activity of a structurally characterized enzyme of unknown function (PDB 2PMQ), 2-epimerization of trans -4-hydroxy- l -proline betaine (tHyp-B) and cis -4-hydroxy- d -proline betaine (cHyp-B), and also the correct identification of the catabolic pathway in which Hyp-B 2-epimerase participates. The substrate-liganded pose predicted by virtual library screening (docking) was confirmed experimentally. The enzymatic activities in the predicted pathway were confirmed by in vitro assays and genetic analyses; the intermediates were identified by metabolomics; and repression of the genes encoding the pathway by high salt concentrations was established by transcriptomics, confirming the osmolyte role of tHyp-B. This study establishes the utility of structure-guided functional predictions to enable the discovery of new metabolic pathways.

Through the use of genetic, enzymatic, metabolomic, and structural analyses, we have discovered the catabolic pathway for proline betaine, an osmoprotectant, in Paracoccus denitrificans and Rhodobacter sphaeroides . Genetic and enzymatic analyses showed that several of the key enzymes of the hydroxyproline betaine degradation pathway also function in proline betaine degradation. Metabolomic analyses detected each of the metabolic intermediates of the pathway. The proline betaine catabolic pathway was repressed by osmotic stress and cold stress, and a regulatory transcription factor was identified. We also report crystal structure complexes of the P. denitrificans HpbD hydroxyproline betaine epimerase/proline betaine racemase with l -proline betaine and cis -hydroxyproline betaine. IMPORTANCE At least half of the extant protein annotations are incorrect, and the errors propagate as the number of genome sequences increases exponentially. A large-scale, multidisciplinary sequence- and structure-based strategy for functional assignment of bacterial enzymes of unknown function has demonstrated the pathway for catabolism of the osmoprotectant proline betaine. At least half of the extant protein annotations are incorrect, and the errors propagate as the number of genome sequences increases exponentially. A large-scale, multidisciplinary sequence- and structure-based strategy for functional assignment of bacterial enzymes of unknown function has demonstrated the pathway for catabolism of the osmoprotectant proline betaine.

Combined omics techniques lead to the functional assignment of four enzymes involved in a new methionine salvage pathway linking polyamine metabolism with isoprenoid biosynthesis. This reaction sequence involves a homolog of nature's most abundant protein, the CO 2 -fixing enzyme RubisCO. Functional assignment of uncharacterized proteins is a challenge in the era of large-scale genome sequencing. Here, we combine in extracto NMR, proteomics and transcriptomics with a newly developed (knock-out) metabolomics platform to determine a potential physiological role for a ribulose-1,5-bisphosphate carboxylase/oxygenase (RubisCO)-like protein from Rhodospirillum rubrum . Our studies unraveled an unexpected link in bacterial central carbon metabolism between S -adenosylmethionine–dependent polyamine metabolism and isoprenoid biosynthesis and also provide an alternative approach to assign enzyme function at the organismic level.

While recent advances in metabolomic measurement technologies have been dramatic, extracting biological insight from complex metabolite profiles remains a challenge. We present an analytical strategy that uses data obtained from high resolution liquid chromatography–mass spectrometry and a bioinformatics toolset for detecting actively changing metabolic pathways upon external perturbation. We begin with untargeted metabolite profiling to nominate altered metabolites and identify pathway candidates, followed by validation of those pathways with transcriptomics. Using the model organisms Rhodospirillum rubrum and Bacillus subtilis , our results reveal metabolic pathways that are interconnected with methionine salvage. The rubrum-type methionine salvage pathway is interconnected with the active methyl cycle in which re-methylation, a key reaction for recycling methionine from homocysteine, is unexpectedly suppressed; instead, homocysteine is catabolized by the trans -sulfuration pathway. Notably, the non-mevalonate pathway is repressed, whereas the rubrum-type methionine salvage pathway contributes to isoprenoid biosynthesis upon 5′-methylthioadenosine feeding. In this process, glutathione functions as a coenzyme in vivo when 1-methylthio- d -xylulose 5-phosphate (MTXu 5-P) methylsulfurylase catalyzes dethiomethylation of MTXu 5-P. These results clearly show that our analytical approach enables unexpected metabolic pathways to be uncovered.

The opportunistic pathogen Staphylococcus aureus is protected by a cell envelope that is crucial for viability. In addition to peptidoglycan, lipoteichoic acid (LTA) is an especially important component of the S. aureus cell envelope. LTA is an anionic polymer anchored to a glycolipid in the outer leaflet of the cell membrane. It was known that deleting the gene for UgtP, the enzyme that makes this glycolipid anchor, causes cell growth and division defects. In Bacillus subtilis, growth abnormalities from the loss of ugtP have been attributed to the absence of the encoded protein, not to loss of its enzymatic activity. Here, we show that growth defects in S. aureus ugtP deletion mutants are due to the long, abnormal LTA polymer that is produced when the glycolipid anchor is missing from the outer leaflet of the membrane. Dysregulated cell growth leads to defective cell division, and these phenotypes are corrected by mutations in the LTA polymerase, ltaS, that reduce polymer length. We also show that S. aureus mutants with long LTA are sensitized to cell wall hydrolases, beta-lactam antibiotics, and compounds that target other cell envelope pathways. We conclude that control of LTA polymer length is important for S. aureus physiology and promotes survival under stressful conditions, including antibiotic stress.

Current strategies to treat pediatric acute lymphoblastic leukemia rely on risk stratification algorithms using categorical data. We investigated whether using continuous variables assigned different weights would improve risk stratification. We developed and validated a multivariable Cox model for relapse-free survival (RFS) using information from 21199 patients. We constructed risk groups by identifying cutoffs of the COG Prognostic Index (PI COG ) that maximized discrimination of the predictive model. Patients with higher PI COG have higher predicted relapse risk. The PI COG reliably discriminates patients with low vs. high relapse risk. For those with moderate relapse risk using current COG risk classification, the PI COG identifies subgroups with varying 5-year RFS. Among current COG standard-risk average patients, PI COG identifies low and intermediate risk groups with 96% and 90% RFS, respectively. Similarly, amongst current COG high-risk patients, PI COG identifies four groups ranging from 96% to 66% RFS, providing additional discrimination for future treatment stratification. When coupled with traditional algorithms, the novel PI COG can more accurately risk stratify patients, identifying groups with better outcomes who may benefit from less intensive therapy, and those who have high relapse risk needing innovative approaches for cure.

We explore the association between three Alzheimer’s disease-related and ten inflammation-related CSF markers and freezing of gait (FOG) in patients with Parkinson’s disease (PD). The study population includes PD patients with FOG (PD-FOG, N = 12), without FOG (PD-NoFOG, N = 19), and healthy controls (HC, N = 12). Age and PD duration are not significantly different between groups. After adjusting for covariates and multiple comparisons, the anti-inflammatory marker, fractalkine, is significantly decreased in the PD groups compared to HC (P = 0.002), and further decreased in PD-FOG compared to PD-NoFOG (P = 0.007). The Alzheimer’s disease-related protein, Aβ42, is increased in PD-FOG compared to PD-NoFOG and HC (P = 0.001). Group differences obtained in individual biomarker analyses are confirmed with multivariate discriminant partial least squares regression (P < 0.001). High levels of Aβ42 in PD-FOG patients supports an increase over time from early to advanced state. Low levels of fractalkine might suggest anti-inflammatory effect. These findings warrant replication.

We assess the UK Biobank (UKB) Polygenic Risk Score (PRS) Release, a set of PRSs for 28 diseases and 25 quantitative traits that has been made available on the individuals in UKB, using a unified pipeline for PRS evaluation. We also release a benchmarking software tool to enable like-for-like performance evaluation for different PRSs for the same disease or trait. Extensive benchmarking shows the PRSs in the UKB Release to outperform a broad set of 76 published PRSs. For many of the diseases and traits we also validate the PRS algorithms in a separate cohort (100,000 Genomes Project). The availability of PRSs for 53 traits on the same set of individuals also allows a systematic assessment of their properties, and the increased power of these PRSs increases the evidence for their potential clinical benefit.

Extremely preterm (EP) infants frequently receive opioids and/or benzodiazepines, but these drugs' association with neurodevelopmental outcomes is poorly understood. To describe the use of opioids and benzodiazepines in EP infants during neonatal intensive care unit (NICU) hospitalization and to explore these drugs' association with neurodevelopmental outcomes at 2 years' corrected age. This cohort study was a secondary analysis of data from the Preterm Erythropoietin Neuroprotection (PENUT) Trial, which was conducted among infants born between gestational ages of 24 weeks, 0 days, and 27 weeks, 6 days. Infants received care at 19 sites in the United States, and data were collected from December 2013 to September 2016. Data analysis for this study was conducted from March to December 2020. Short (ie, ≤7 days) and prolonged (ie, >7 days) exposure to opioids and/or benzodiazepines during NICU stay. Cognitive, language, and motor development scores were assessed using the Bayley Scales of Infant Development-Third Edition (BSID-III). There were 936 EP infants (448 [48%] female infants; 611 [65%] White infants; mean [SD] gestational age, 181 [8] days) included in the study, and 692 (74%) had neurodevelopmental outcome data available. Overall, 158 infants (17%) were not exposed to any drugs of interest, 297 (32%) received either opioids or benzodiazepines, and 481 (51%) received both. Infants exposed to both had adjusted odds ratios of 9.7 (95% CI, 2.9 to 32.2) for necrotizing enterocolitis and 1.7 (95% CI, 1.1 to 2.7) for severe bronchopulmonary dysplasia; they also had a longer estimated adjusted mean difference in length of stay of 34.2 (95% CI, 26.2 to 42.2) days compared with those who received neither drug. After adjusting for site and propensity scores derived for each exposure category, infants exposed to opioids and benzodiazepines had lower BSID-III cognitive, motor, and language scores compared with infants with no exposure (eg, estimated difference in mean scores on cognitive scale: -5.72; 95% CI, -8.88 to -2.57). Prolonged exposure to morphine, fentanyl, midazolam, or lorazepam was associated with lower BSID-III scores compared with infants without exposure (median [interquartile range] motor score, 85 [73-97] vs 97 [91-107]). In contrast, BSID-III scores for infants with short exposure to both opioids and benzodiazepines were not different than those of infants without exposure. In this study, prolonged combined use of opioids and benzodiazepines was associated with a risk of poorer neurodevelopmental outcomes as measured by BSID-III at 2 years' corrected age.