Perturbation-Specific Transcriptional Mapping facilitates unbiased target elucidation of antibiotics.

The rising prevalence of antibiotic resistance threatens human health. While more sophisticated strategies for antibiotic discovery are being developed, target elucidation of new chemical entities remains challenging. In the post-genomic era, expression profiling can play an important role in mechanism-of-action (MOA) prediction by reporting on the cellular response to perturbation. However, the broad application of transcriptomics has yet to fully fulfill its promise of transforming target elucidation. We developed an unbiased strategy for MOA prediction, called Perturbation-Specific Transcriptional Mapping (PerSpecTM), in which large-throughput expression profiling of wild-type or hypomorphic mutants depleted for essential targets, enables a reference-based strategy to associate similar perturbations, whether small molecule or genetic, based on the principle that similar perturbations will elicit similar transcriptional responses. We applied this approach to rapidly elucidate the MOAs of three new molecules with activity against the important bacterial pathogen Pseudomonas aeruginosa by mapping their expression profiles to those generated for a reference set of antimicrobial compounds with known MOA. Meanwhile, we also show that small molecule inhibition can be mapped to genetic depletion of essential targets by CRISPRi by PerSpecTM, thus demonstrating proof-of-concept that correlations between expression profiles of small molecule and genetic perturbations can predict MOA when no chemical entities exist to serve as a reference. Empowered by PerSpecTM and its leveraging of reference transcriptional profiles for known small molecule or genetic perturbations, this work lays the foundation for an unbiased, readily scalable, systematic reference-based strategy for MOA elucidation that could transform antibiotic discovery efforts. Significance Statement: In an era of increasing antibiotic resistance, new antibiotics are critically needed. However, MOA elucidation remains a challenging step in antibiotic discovery and thus a major bottleneck. Building on the principle that molecules with similar MOAs elicit similar transcriptional responses, we have now developed a highly scalable strategy for MOA prediction in the important bacterial pathogen Pseudomonas aeruginosa based on correlations between the expression profiles of new molecules and known perturbations, either small molecule inhibition by known antibiotics or transcriptional repression of essential targets by CRISPRi. By rapidly assigning MOA to three new molecules with anti-pseudomonal activity, we provide proof-of-concept for a rapid, comprehensive, systematic, reference-based approach to MOA prediction, with the potential to transform antibiotic discovery efforts.

Massively parallel combination screen reveals small molecule sensitization of antibiotic-resistant Gram-negative ESKAPE pathogens.

Antibiotic resistance, especially in multidrug-resistant ESKAPE pathogens, remains a worldwide problem. Combination antimicrobial therapies may be an important strategy to overcome resistance and broaden the spectrum of existing antibiotics. However, this strategy is limited by the ability to efficiently screen large combinatorial chemical spaces. Here, we deployed a high-throughput combinatorial screening platform, DropArray, to evaluate the interactions of over 30,000 compounds with up to 22 antibiotics and 6 strains of Gram-negative ESKAPE pathogens, totaling to over 1.3 million unique strain-antibiotic-compound combinations. In this dataset, compounds more frequently exhibited synergy with known antibiotics than single-agent activity. We identified a compound, P2-56, and developed a more potent analog, P2-56-3, which potentiated rifampin (RIF) activity against Acinetobacter baumannii and Klebsiella pneumoniae. Using phenotypic assays, we showed P2-56-3 disrupts the outer membrane of A. baumannii. To identify pathways involved in the mechanism of synergy between P2-56-3 and RIF, we performed genetic screens in A. baumannii. CRISPRi-induced partial depletion of lipooligosaccharide transport genes (lptA-D, lptFG) resulted in hypersensitivity to P2-56-3/RIF treatment, demonstrating the genetic dependency of P2-56-3 activity and RIF sensitization on lpt genes in A. baumannii. Consistent with outer membrane homeostasis being an important determinant of P2-56-3/RIF tolerance, knockout of maintenance of lipid asymmetry complex genes and overexpression of certain resistance-nodulation-division efflux pumps - a phenotype associated with multidrug-resistance - resulted in hypersensitivity to P2-56-3. These findings demonstrate the immense scale of phenotypic antibiotic combination screens using DropArray and the potential for such approaches to discover new small molecule synergies against multidrug-resistant ESKAPE strains.

Essential and virulence-related protein interactions of pathogens revealed through deep learning.

Identification of bacterial protein-protein interactions and predicting the structures of the complexes could aid in the understanding of pathogenicity mechanisms and developing treatments for infectious diseases. Here, we developed a deep learning-based pipeline that leverages residue-residue coevolution and protein structure prediction to systematically identify and structurally characterize protein-protein interactions at the proteome-wide scale. Using this pipeline, we searched through 78 million pairs of proteins across 19 human bacterial pathogens and identified 1923 confidently predicted complexes involving essential genes and 256 involving virulence factors. Many of these complexes were not previously known; we experimentally tested 12 such predictions, and half of them were validated. The predicted interactions span core metabolic and virulence pathways ranging from post-transcriptional modification to acid neutralization to outer membrane machinery and should contribute to our understanding of the biology of these important pathogens and the design of drugs to combat them.

"Multiplexed screen identifies a Pseudomonas aeruginosa -specific small molecule targeting the outer membrane protein OprH and its interaction with LPS".

The surge of antimicrobial resistance threatens efficacy of current antibiotics, particularly against Pseudomonas aeruginosa , a highly resistant gram-negative pathogen. The asymmetric outer membrane (OM) of P. aeruginosa combined with its array of efflux pumps provide a barrier to xenobiotic accumulation, thus making antibiotic discovery challenging. We adapted PROSPECT 1 , a target-based, whole-cell screening strategy, to discover small molecule probes that kill P. aeruginosa mutants depleted for essential proteins localized at the OM. We identified BRD1401, a small molecule that has specific activity against a P. aeruginosa mutant depleted for the essential lipoprotein, OprL. Genetic and chemical biological studies identified that BRD1401 acts by targeting the OM ß-barrel protein OprH to disrupt its interaction with LPS and increase membrane fluidity. Studies with BRD1401 also revealed an interaction between OprL and OprH, directly linking the OM with peptidoglycan. Thus, a whole-cell, multiplexed screen can identify species-specific chemical probes to reveal novel pathogen biology.

A dual-plasmid CRISPR/Cas9-based method for rapid and efficient genetic disruption in Mycobacterium abscessus.

Mycobacterium abscessus is increasingly recognized for causing infections that are notoriously difficult to treat, owing to its large arsenal of intrinsic antibiotic resistance mechanisms. Tools for the genetic manipulation of the pathogen are critical for enabling a better understanding of M. abscessus biology, pathogenesis, and antibiotic resistance mechanisms. However, existing methods are largely recombination-based, which are relatively inefficient. Meanwhile, CRISPR/Cas9 has revolutionized the field of genome editing including its recent adaptation for use in mycobacteria. In this study, we report a streamlined and efficient method for rapid genetic disruptions in M. abscessus. Harnessing the CRISPR1 loci from Streptococcus thermophilus, we have developed a dual-plasmid workflow that introduces Cas9 and sgRNA cassettes in separate steps but requires no other additional factors to engineer mutations in single genes or multiple genes simultaneously or sequentially using multiple targeting sgRNAs. Importantly, the efficiency of mutant generation is several orders of magnitude higher than reported for homologous recombination-based methods. This work, thus, reports the first application of CRISPR/Cas9 for gene editing in M. abscessus and is an important tool in the arsenal for the genetic manipulation of this human pathogen. IMPORTANCE: Mycobacterium abscessus is an opportunistic pathogen of increasing clinical importance due to its poor clinical outcomes and limited treatment options. Drug discovery and development in this highly antibiotic-resistant species will require further understanding of M. abscessus biology, pathogenesis, and antibiotic resistance mechanisms. However, existing methods for facile genetic engineering are relatively inefficient. This study reports on the first application of CRISPR/Cas9 for gene editing in M. abscessus using a dual-plasmid workflow. We establish that our method is easily programmable, efficient, and versatile for genetic disruptions in M. abscessus. This is a critical advancement to facilitating targeted gene function studies in this emerging pathogen.

Genetic factors affecting storage and utilization of lipids during dormancy in Mycobacterium tuberculosis.

Mycobacterium tuberculosis (Mtb) can adopt a non-growing dormant state during infection that may be critical to both active and latent tuberculosis. During dormancy, Mtb is widely tolerant toward antibiotics, a significant obstacle in current anti-tubercular drug regimens, and retains the ability to persist in its environment. We aimed to identify novel mechanisms that permit Mtb to survive dormancy in an in vitro carbon starvation model using transposon insertion sequencing and gene expression analysis. We identified a previously uncharacterized component of the lipid transport machinery, omamC, which was upregulated and required for survival during carbon starvation. We show that OmamC plays a role both in increasing fatty acid stores during growth in rich media and enhancing fatty acid utilization during starvation. Besides its involvement in lipid metabolism, OmamC levels affected the expression of the anti-anti-sigma factor rv0516c and other genes to improve Mtb survival during carbon starvation and increase its tolerance toward rifampicin, a first-line drug effective against non-growing Mtb. Importantly, we show that Mtb can be eradicated during carbon starvation, in an OmamC-dependent manner, by inhibiting lipid metabolism with the lipase inhibitor tetrahydrolipstatin. This work casts new light into the survival processes of non-replicating, drug-tolerant Mtb by identifying new proteins involved in lipid metabolism required for the survival of dormant bacteria and exposing a potential vulnerability that could be exploited for antibiotic discovery.IMPORTANCETuberculosis is a global threat, with ~10 million yearly active cases. Many more people, however, live with "latent" infection, where Mycobacterium tuberculosis survives in a non-replicative form. When latent bacteria activate and regrow, they elicit immune responses and result in significant host damage. Replicating and non-growing bacilli can co-exist; however, non-growing bacteria are considerably less sensitive to antibiotics, thus complicating treatment by necessitating long treatment durations. Here, we sought to identify genes important for bacterial survival in this non-growing state using a carbon starvation model. We found that a previously uncharacterized gene, omamC, is involved in storing and utilizing fatty acids as bacteria transition between these two states. Importantly, inhibiting lipid metabolism using a lipase inhibitor eradicates non-growing bacteria. Thus, targeting lipid metabolism may be a viable strategy for treating the non-growing population in strategies to shorten treatment durations of tuberculosis.

Evaluation of Expanded 2-Aminobenzothiazole Library for Inhibition of Pseudomonas aeruginosa Virulence Phenotypes.

Bacterial resistance to antibiotics is a rapidly increasing threat to human health. New strategies to combat resistant organisms are desperately needed. One potential avenue is targeting two-component systems, which are the main bacterial signal transduction pathways used to regulate development, metabolism, virulence, and antibiotic resistance. These systems consist of a homodimeric membrane-bound sensor histidine kinase, and a cognate effector, the response regulator. The high sequence conservation in the catalytic and adenosine triphosphate-binding (CA) domain of histidine kinases and their essential role in bacterial signal transduction could enable broad-spectrum antibacterial activity. Through this signal transduction, histidine kinases regulate multiple virulence mechanisms including toxin production, immune evasion, and antibiotic resistance. Targeting virulence, as opposed to development of bactericidal compounds, could reduce evolutionary pressure for acquired resistance. Additionally, compounds targeting the CA domain have the potential to impair multiple two-component systems that regulate virulence in one or more pathogens. We conducted structure-activity relationship studies of 2-aminobenzothiazole-based inhibitors designed to target the CA domain of histidine kinases. We found these compounds have anti-virulence activities in Pseudomonas aeruginosa, reducing motility phenotypes and toxin production associated with the pathogenic functions of this bacterium.

Benzene Amide Ether Scaffold is Active against Non-replicating and Intracellular Mycobacterium tuberculosis.

New drugs to treat tuberculosis which target intractable bacterial populations are required to develop shorter and more effective treatment regimens. The benzene amide ether scaffold has activity against intracellular Mycobacterium tuberculosis, but low activity against extracellular, actively replicating M. tuberculosis. We determined that these molecules have bactericidal activity against non-replicating M. tuberculosis but not actively replicating bacteria. Exposure to compounds depleted ATP levels in non-replicating bacteria and increased the oxygen consumption rate; a subset of molecules led to the accumulation of intrabacterial reactive oxygen species. A comprehensive screen of M. tuberculosis strains identified a number of under-expressing strains as more sensitive to compounds under replicating conditions including QcrA and QcrB hypomorphs. We determined the global gene expression profile after compound treatment for both replicating and nutrient-starved M. tuberculosis. We saw compound-dependent changes in the expression of genes involved in energy metabolism under both conditions. Taken together, our data suggest that the scaffold targets respiration in M. tuberculosis.

A tryptophan metabolite modulates the host response to bacterial infection via kainate receptors.

Bacterial infection involves a complex interaction between the pathogen and host where the outcome of infection is not solely determined by pathogen eradication. To identify small molecules that promote host survival by altering the host-pathogen dynamic, we conducted an in vivo chemical screen using zebrafish embryos and found that treatment with 3-hydroxy-kynurenine protects from lethal gram-negative bacterial infection. 3-hydroxy-kynurenine, a metabolite produced through host tryptophan metabolism, has no direct antibacterial activity but enhances host survival by restricting bacterial expansion in macrophages by targeting kainate-sensitive glutamate receptors. These findings reveal new mechanisms by which tryptophan metabolism and kainate-sensitive glutamate receptors function and interact to modulate immunity, with significant implications for the coordination between the immune and nervous systems in pathological conditions.

Identification of host regulators of Mycobacterium tuberculosis phenotypes uncovers a role for the MMGT1-GPR156 lipid droplet axis in persistence.

The ability of Mycobacterium tuberculosis (Mtb) to establish latency affects disease and response to treatment. The host factors that influence the establishment of latency remain elusive. We engineered a multi-fluorescent Mtb strain that reports survival, active replication, and stressed non-replication states and determined the host transcriptome of the infected macrophages in these states. Additionally, we conducted a genome-wide CRISPR screen to identify host factors that modulated the phenotypic state of Mtb. We validated hits in a phenotype-specific manner and prioritized membrane magnesium transporter 1 (MMGT1) for a detailed mechanistic investigation. Mtb infection of MMGT1-deficient macrophages promoted a switch to persistence, upregulated lipid metabolism genes, and accumulated lipid droplets during infection. Targeting triacylglycerol synthesis reduced both droplet formation and Mtb persistence. The orphan G protein-coupled receptor GPR156 is a key inducer of droplet accumulation in ΔMMGT1 cells. Our work uncovers the role of MMGT1-GPR156-lipid droplets in the induction of Mtb persistence.

Genome-wide tiled detection of circulating Mycobacterium tuberculosis cell-free DNA using Cas13.

Detection of microbial cell-free DNA (cfDNA) circulating in the bloodstream has emerged as a promising new approach for diagnosing infection. Microbial diagnostics based on cfDNA require assays that can detect rare and highly fragmented pathogen nucleic acids. We now report WATSON (Whole-genome Assay using Tiled Surveillance Of Nucleic acids), a method to detect low amounts of pathogen cfDNA that couples pooled amplification of genomic targets tiled across the genome with pooled CRISPR/Cas13-based detection of these targets. We demonstrate that this strategy of tiling improves cfDNA detection compared to amplification and detection of a single targeted locus. WATSON can detect cfDNA from Mycobacterium tuberculosis in plasma of patients with active pulmonary tuberculosis, a disease that urgently needs accurate, minimally-invasive, field-deployable diagnostics. We thus demonstrate the potential for translating WATSON to a lateral flow platform. WATSON demonstrates the ability to capitalize on the strengths of targeting microbial cfDNA to address the need for point-of-care diagnostic tests for infectious diseases.

Rapid Single-Shot Synthesis of the 214 Amino Acid-Long N-Terminal Domain of Pyocin S2.

The impermeable outer membrane of Pseudomonas aeruginosa is bypassed by antibacterial proteins known as S-type pyocins. Because of their properties, pyocins are investigated as a potential new class of antimicrobials against Pseudomonas infections. Their production and modification, however, remain challenging. To address this limitation, we employed automated fast-flow peptide synthesis for the rapid production of a pyocin S2 import domain. The N-terminal domain sequence (PyS2NTD) was synthesized in under 10 h and purified to yield milligram quantities of the desired product. To our knowledge, the 214 amino acid sequence of PyS2NTD is among the longest peptides produced from a "single-shot" synthesis, i.e., made in a single stepwise route without the use of ligation techniques. Biophysical characterization of the PyS2NTD with circular dichroism was consistent with the literature reports. Fluorescently labeled PyS2NTD binds to P. aeruginosa expressing the cognate ferripyoverdine receptor and is taken up into the periplasm. This selective uptake was validated with confocal and super resolution microscopy, flow cytometry, and fluorescence recovery after photobleaching. These modified, synthetic S-type pyocin domains can be used to probe import mechanisms of P. aeruginosa and leveraged to develop selective antimicrobial agents that bypass the outer membrane.

Bacterial droplet-based single-cell RNA-seq reveals antibiotic-associated heterogeneous cellular states.

We introduce BacDrop, a highly scalable technology for bacterial single-cell RNA sequencing that has overcome many challenges hindering the development of scRNA-seq in bacteria. BacDrop can be applied to thousands to millions of cells from both gram-negative and gram-positive species. It features universal ribosomal RNA depletion and combinatorial barcodes that enable multiplexing and massively parallel sequencing. We applied BacDrop to study Klebsiella pneumoniae clinical isolates and to elucidate their heterogeneous responses to antibiotic stress. In an unperturbed population presumed to be homogeneous, we found within-population heterogeneity largely driven by the expression of mobile genetic elements that promote the evolution of antibiotic resistance. Under antibiotic perturbation, BacDrop revealed transcriptionally distinct subpopulations associated with different phenotypic outcomes including antibiotic persistence. BacDrop thus can capture cellular states that cannot be detected by bulk RNA-seq, which will unlock new microbiological insights into bacterial responses to perturbations and larger bacterial communities such as the microbiome.

Evaluation of the Access Bio CareStart rapid SARS-CoV-2 antigen test in asymptomatic individuals tested at a community mass-testing program in Western Massachusetts.

Point-of-care antigen-detecting rapid diagnostic tests (RDTs) to detect Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) represent a scalable tool for surveillance of active SARS-CoV-2 infections in the population. Data on the performance of these tests in real-world community settings are paramount to guide their implementation to combat the COVID-19 pandemic. We evaluated the performance characteristics of the CareStart COVID-19 Antigen test (CareStart) in a community testing site in Holyoke, Massachusetts. We compared CareStart to a SARS-CoV-2 reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) reference, both using anterior nasal swab samples. We calculated the sensitivity, specificity, and the expected positive and negative predictive values at different SARS-CoV-2 prevalence estimates. We performed 666 total tests on 591 unique individuals. 573 (86%) were asymptomatic. There were 52 positive tests by RT-qPCR. The sensitivity of CareStart was 49.0% (95% Confidence Interval (CI) 34.8-63.4) and specificity was 99.5% (95% CI 98.5-99.9). Among positive RT-qPCR tests, the median cycle threshold (Ct) was significantly lower in samples that tested positive on CareStart. Using a Ct ≤ 30 as a benchmark for positivity increased the sensitivity of the test to 64.9% (95% CI 47.5-79.8). Our study shows that CareStart has a high specificity and moderate sensitivity. The utility of RDTs, such as CareStart, in mass implementation should prioritize use cases in which a higher specificity is more important, such as triage tests to rule-in active infections in community surveillance programs.

At-home Testing and Risk Factors for Acquisition of SARS-CoV-2 Infection in a Major US Metropolitan Area.

Background: Unbiased assessment of the risks associated with acquisition of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical to informing mitigation efforts during pandemics. The objective of our study was to understand the risk factors for acquiring coronavirus disease 2019 (COVID-19) in a large prospective cohort of adult residents in a large US metropolitan area. Methods: We designed a fully remote longitudinal cohort study involving monthly at-home SARS-CoV-2 polymerase chain reaction (PCR) and serology self-testing and monthly surveys. Results: Between October 2020 and January 2021, we enrolled 10 289 adults reflective of the Boston metropolitan area census data. At study entry, 567 (5.5%) participants had evidence of current or prior SARS-CoV-2 infection. This increased to 13.4% by June 15, 2021. Compared with Whites, Black non-Hispanic participants had a 2.2-fold greater risk of acquiring COVID-19 (hazard ratio [HR], 2.19; 95% CI, 1.91-2.50; P < .001), and Hispanics had a 1.5-fold greater risk (HR, 1.52; 95% CI, 1.32-1.71; P < .016). Individuals aged 18-29, those who worked outside the home, and those living with other adults and children were at an increased risk. Individuals in the second and third lowest disadvantaged neighborhood communities were associated with an increased risk of acquiring COVID-19. Individuals with medical risk factors for severe disease were at a decreased risk of SARS-CoV-2 acquisition. Conclusions: These results demonstrate that race/ethnicity and socioeconomic status are the biggest determinants of acquisition of infection. This disparity is significantly underestimated if based on PCR data alone, as noted by the discrepancy in serology vs PCR detection for non-White participants, and points to persistent disparity in access to testing. Medical conditions and advanced age, which increase the risk for severity of SARS-CoV-2 disease, were associated with a lower risk of COVID-19 acquisition, suggesting the importance of behavior modifications. These findings highlight the need for mitigation programs that overcome challenges of structural racism in current and future pandemics.

Correction to "An Iterative Approach Guides Discovery of the FabI Inhibitor Fabimycin, a Late-Stage Antibiotic Candidate with In Vivo Efficacy against Drug-Resistant Gram-Negative Infections".

[This corrects the article DOI: 10.1021/acscentsci.2c00598.].

An Iterative Approach Guides Discovery of the FabI Inhibitor Fabimycin, a Late-Stage Antibiotic Candidate with In Vivo Efficacy against Drug-Resistant Gram-Negative Infections.

Genomic studies and experiments with permeability-deficient strains have revealed a variety of biological targets that can be engaged to kill Gram-negative bacteria. However, the formidable outer membrane and promiscuous efflux pumps of these pathogens prevent many candidate antibiotics from reaching these targets. One such promising target is the enzyme FabI, which catalyzes the rate-determining step in bacterial fatty acid biosynthesis. Notably, FabI inhibitors have advanced to clinical trials for Staphylococcus aureus infections but not for infections caused by Gram-negative bacteria. Here, we synthesize a suite of FabI inhibitors whose structures fit permeation rules for Gram-negative bacteria and leverage activity against a challenging panel of Gram-negative clinical isolates as a filter for advancement. The compound to emerge, called fabimycin, has impressive activity against >200 clinical isolates of Escherichia coli, Klebsiella pneumoniae, and Acinetobacter baumannii, and does not kill commensal bacteria. X-ray structures of fabimycin in complex with FabI provide molecular insights into the inhibition. Fabimycin demonstrates activity in multiple mouse models of infection caused by Gram-negative bacteria, including a challenging urinary tract infection model. Fabimycin has translational promise, and its discovery provides additional evidence that antibiotics can be systematically modified to accumulate in Gram-negative bacteria and kill these problematic pathogens.

Feasibility and lessons learned on remote trial implementation from TestBoston, a fully remote, longitudinal, large-scale COVID-19 surveillance study.

Longitudinal clinical studies traditionally require in-person study visits which are well documented to pose barriers to participation and contribute challenges to enrolling representative samples. Remote trial models may reduce barriers to research engagement, improve retention, and reach a more representative cohort. As remote trials become more common following the COVID-19 pandemic, a critical evaluation of this approach is imperative to optimize this paradigm shift in research. The TestBoston study was launched to understand prevalence and risk factors for COVID-19 infection in the greater Boston area through a fully remote home-testing model. Participants (adults, within 45 miles of Boston, MA) were recruited remotely from patient registries at Brigham and Women's Hospital and the general public. Participants were provided with monthly and "on-demand" at-home SARS-CoV-2 RT-PCR and antibody testing using nasal swab and dried blood spot self-collection kits and electronic surveys to assess symptoms and risk factors for COVID-19 via an online dashboard. Between October 2020 and January 2021, we enrolled 10,289 participants reflective of Massachusetts census data. Mean age was 47 years (range 18-93), 5855 (56.9%) were assigned female sex at birth, 7181(69.8%) reported being White non-Hispanic, 952 (9.3%) Hispanic/Latinx, 925 (9.0%) Black, 889 (8.6%) Asian, and 342 (3.3%) other and/or more than one race. Lower initial enrollment among Black and Hispanic/Latinx individuals required an adaptive approach to recruitment, leveraging connections to the medical system, coupled with community partnerships to ensure a representative cohort. Longitudinal retention was higher among participants who were White non-Hispanic, older, working remotely, and with lower socioeconomic vulnerability. Implementation highlighted key differences in remote trial models as participants independently navigate study milestones, requiring a dedicated participant support team and robust technology platforms, to reduce barriers to enrollment, promote retention, and ensure scientific rigor and data quality. Remote clinical trial models offer tremendous potential to engage representative cohorts, scale biomedical research, and promote accessibility by reducing barriers common in traditional trial design. Barriers and burdens within remote trials may be experienced disproportionately across demographic groups. To maximize engagement and retention, researchers should prioritize intensive participant support, investment in technologic infrastructure and an adaptive approach to maximize engagement and retention.

Integrated genomics and chemical biology herald an era of sophisticated antibacterial discovery, from defining essential genes to target elucidation.

The golden age of antibiotic discovery in the 1940s-1960s saw the development and deployment of many different classes of antibiotics, revolutionizing the field of medicine. Since that time, our ability to discover antibiotics of novel structural classes or mechanisms has not kept pace with the ever-growing threat of antibiotic resistance. Recently, advances at the intersection of genomics and chemical biology have enabled efforts to better define the vulnerabilities of essential gene targets, to develop sophisticated whole-cell chemical screening methods that reveal target biology early, and to elucidate small molecule targets and modes of action more effectively. These new technologies have the potential to expand the chemical diversity of antibiotic candidates, as well as the breadth of targets. We illustrate how the latest tools of genomics and chemical biology are being integrated to better understand pathogen vulnerabilities and antibiotic mechanisms in order to inform a new era of antibiotic discovery.