Clinical Pilot of Bacterial Transcriptional Profiling as a Combined Genotypic and Phenotypic Antimicrobial Susceptibility Test.

Antimicrobial resistance is a growing health threat, but standard methods for determining antibiotic susceptibility are slow and can delay optimal treatment, which is especially consequential in severe infections such as bacteremia. Novel approaches for rapid susceptibility profiling have emerged that characterize either bacterial response to antibiotics (phenotype) or detect specific resistance genes (genotype). GoPhAST-R is a novel assay, performed directly on positive blood cultures, that integrates rapid transcriptional response profiling with detection of key resistance gene transcripts, thereby providing simultaneous data on both phenotype and genotype. Here, we performed the first clinical pilot of GoPhAST-R on 42 positive blood cultures: 26 growing Escherichia coli, 15 growing Klebsiella pneumoniae, and 1 with both. An aliquot of each positive blood culture was exposed to 9 different antibiotics, lysed, then underwent rapid transcriptional profiling on the NanoString® platform; results were analyzed using an in-house susceptibility classification algorithm. GoPhAST-R achieved 95% overall agreement with standard antimicrobial susceptibility testing methods, with the highest agreement for beta-lactams (98%) and the lowest for fluoroquinolones (88%). Epidemic resistance genes including the extended spectrum beta-lactamase bla CTX-M-15 and the carbapenemase bla KPC were also detected within the population. This study demonstrates the clinical feasibility of using transcriptional response profiling for rapid resistance determination, although further validation with larger and more diverse bacterial populations will be essential in future work. GoPhAST-R represents a promising new approach for rapid and comprehensive antibiotic susceptibility testing in clinical settings.

Candida albicans extracellular vesicles trigger type I IFN signalling via cGAS and STING.

The host type I interferon (IFN) pathway is a major signature of inflammation induced by the human fungal pathogen, Candida albicans. However, the molecular mechanism for activating this pathway in the host defence against C. albicans remains unknown. Here we reveal that mice lacking cyclic GMP-AMP synthase (cGAS)-stimulator of IFN genes (STING) pathway components had improved survival following an intravenous challenge by C. albicans. Biofilm-associated C. albicans DNA packaged in extracellular vesicles triggers the cGAS-STING pathway as determined by induction of interferon-stimulated genes, IFNß production, and phosphorylation of IFN regulatory factor 3 and TANK-binding kinase 1. Extracellular vesicle-induced activation of type I IFNs was independent of the Dectin-1/Card9 pathway and did not require toll-like receptor 9. Single nucleotide polymorphisms in cGAS and STING potently altered inflammatory cytokine production in human monocytes challenged by C. albicans. These studies provide insights into the early innate immune response induced by a clinically significant fungal pathogen.

Clinical and Genomic Characterization of a Cohort of Patients With Klebsiella pneumoniae Bloodstream Infection.

BACKGROUND: The clinical and microbial factors associated with Klebsiella pneumoniae bloodstream infections (BSIs) are not well characterized. Prior studies have focused on highly resistant or hypervirulent isolates, limiting our understanding of K. pneumoniae strains that commonly cause BSI. We performed a record review and whole-genome sequencing to investigate the clinical characteristics, bacterial diversity, determinants of antimicrobial resistance, and risk factors for in-hospital death in a cohort of patients with K. pneumoniae BSI. METHODS: We identified 562 patients at Massachusetts General Hospital with K. pneumoniae BSIs between 2016 and 2022. We collected data on comorbid conditions, infection source, clinical outcomes, and antibiotic resistance and performed whole-genome sequencing on 108 sequential BSI isolates from 2021 to 2022. RESULTS: Intra-abdominal infection was the most common source of infection accounting for 34% of all BSIs. A respiratory tract source accounted for 6% of BSIs but was associated with a higher in-hospital mortality rate (adjusted odds ratio, 5.4 [95% confidence interval, 2.2-12.8]; P < .001 for comparison with other sources). Resistance to the first antibiotic prescribed was also associated with a higher risk of death (adjusted odds ratio, 5.2 [95% confidence interval, 2.2-12.4]; P < .001). BSI isolates were genetically diverse, and no clusters of epidemiologically and genetically linked cases were observed. Virulence factors associated with invasiveness were observed at a low prevalence, although an unexpected association between O-antigen type and the source of infection was found. CONCLUSIONS: These observations demonstrate the versatility of K. pneumoniae as an opportunistic pathogen and highlight the need for new approaches for surveillance and the rapid identification of patients with invasive antimicrobial-resistant K. pneumoniae infection.

The carbapenem inoculum effect provides insight into the molecular mechanisms underlying carbapenem resistance in Enterobacterales.

Carbapenem-resistant Enterobacterales (CRE) are important pathogens that can develop resistance via multiple molecular mechanisms, including hydrolysis or reduced antibiotic influx. Identifying these mechanisms can improve pathogen surveillance, infection control, and patient care. We investigated how resistance mechanisms influence the carbapenem inoculum effect (IE), a phenomenon where inoculum size affects antimicrobial susceptibility testing (AST). We demonstrated that seven different carbapenemases impart a meropenem IE in Escherichia coli. Across 110 clinical CRE isolates, the carbapenem IE strictly depended on resistance mechanism: all carbapenemase-producing CRE (CP-CRE) exhibited a strong IE, whereas porin-deficient CRE displayed none. Concerningly, 50% and 24% of CP-CRE isolates changed susceptibility classification to meropenem and ertapenem, respectively, across the allowable inoculum range in clinical guidelines. The meropenem IE, and the ratio of ertapenem to meropenem minimal inhibitory concentration (MIC) at standard inoculum, reliably identified CP-CRE. Understanding how resistance mechanisms affect AST could improve diagnosis and guide therapies for CRE infections.

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.

Detection of early-stage lung cancer in sputum using automated flow cytometry and machine learning.

BACKGROUND: Low-dose spiral computed tomography (LDCT) may not lead to a clear treatment path when small to intermediate-sized lung nodules are identified. We have combined flow cytometry and machine learning to develop a sputum-based test (CyPath Lung) that can assist physicians in decision-making in such cases. METHODS: Single cell suspensions prepared from induced sputum samples collected over three consecutive days were labeled with a viability dye to exclude dead cells, antibodies to distinguish cell types, and a porphyrin to label cancer-associated cells. The labeled cell suspension was run on a flow cytometer and the data collected. An analysis pipeline combining automated flow cytometry data processing with machine learning was developed to distinguish cancer from non-cancer samples from 150 patients at high risk of whom 28 had lung cancer. Flow data and patient features were evaluated to identify predictors of lung cancer. Random training and test sets were chosen to evaluate predictive variables iteratively until a robust model was identified. The final model was tested on a second, independent group of 32 samples, including six samples from patients diagnosed with lung cancer. RESULTS: Automated analysis combined with machine learning resulted in a predictive model that achieved an area under the ROC curve (AUC) of 0.89 (95% CI 0.83-0.89). The sensitivity and specificity were 82% and 88%, respectively, and the negative and positive predictive values 96% and 61%, respectively. Importantly, the test was 92% sensitive and 87% specific in cases when nodules were < 20 mm (AUC of 0.94; 95% CI 0.89-0.99). Testing of the model on an independent second set of samples showed an AUC of 0.85 (95% CI 0.71-0.98) with an 83% sensitivity, 77% specificity, 95% negative predictive value and 45% positive predictive value. The model is robust to differences in sample processing and disease state. CONCLUSION: CyPath Lung correctly classifies samples as cancer or non-cancer with high accuracy, including from participants at different disease stages and with nodules < 20 mm in diameter. This test is intended for use after lung cancer screening to improve early-stage lung cancer diagnosis. Trial registration ClinicalTrials.gov ID: NCT03457415; March 7, 2018.

Cloacaenodin, an Antimicrobial Lasso Peptide with Activity against Enterobacter.

Using genome mining and heterologous expression, we report the discovery and production of a new antimicrobial lasso peptide from species related to the Enterobacter cloacae complex. Using NMR and mass spectrometric analysis, we show that this lasso peptide, named cloacaenodin, employs a threaded lasso fold which imparts proteolytic resistance that its unthreaded counterpart lacks. Cloacaenodin has selective, low micromolar, antimicrobial activity against species related to the E. cloacae complex, including species implicated in nosocomial infections and against clinical isolates of carbapenem-resistant Enterobacterales. We further used site-directed mutagenesis to probe the importance of specific residues to the peptide's biosynthesis, stability, and bioactivity.

Pre-Existing Population Immunity and severe acute respiratory syndrome coronavirus 2 Variant Establishment and Dominance Dynamics in the United States: An Ecological Study.

We conducted an ecological analysis of the dynamics of Delta and Omicron establishment and dominance in US states. Omicron became the dominant circulating variant later in states with higher population-level immunity. By contrast, population immunity did not impact the maximum rate of takeover by Delta or Omicron from prior variants.

Longitudinal characterization of circulating neutrophils uncovers phenotypes associated with severity in hospitalized COVID-19 patients.

Mechanisms of neutrophil involvement in severe coronavirus disease 2019 (COVID-19) remain incompletely understood. Here, we collect longitudinal blood samples from 306 hospitalized COVID-19+ patients and 86 controls and perform bulk RNA sequencing of enriched neutrophils, plasma proteomics, and high-throughput antibody profiling to investigate relationships between neutrophil states and disease severity. We identify dynamic switches between six distinct neutrophil subtypes. At days 3 and 7 post-hospitalization, patients with severe disease display a granulocytic myeloid-derived suppressor cell-like gene expression signature, while patients with resolving disease show a neutrophil progenitor-like signature. Humoral responses are identified as potential drivers of neutrophil effector functions, with elevated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific immunoglobulin G1 (IgG1)-to-IgA1 ratios in plasma of severe patients who survived. In vitro experiments confirm that while patient-derived IgG antibodies induce phagocytosis in healthy donor neutrophils, IgA antibodies predominantly induce neutrophil cell death. Overall, our study demonstrates a dysregulated myelopoietic response in severe COVID-19 and a potential role for IgA-dominant responses contributing to mortality.

A novel rRNA hybridization-based approach to rapid, accurate Candida identification directly from blood culture.

Invasive fungal infections are increasingly common and carry high morbidity and mortality, yet fungal diagnostics lag behind bacterial diagnostics in rapidly identifying the causal pathogen. We previously devised a fluorescent hybridization-based assay to identify bacteria within hours directly from blood culture bottles without subculture, called phylogeny-informed rRNA-based strain identification (Phirst-ID). Here, we adapt this approach to unambiguously identify 11 common pathogenic Candida species, including C. auris, with 100% accuracy from laboratory culture (33 of 33 strains in a reference panel, plus 33 of 33 additional isolates tested in a validation panel). In a pilot study on 62 consecutive positive clinical blood cultures from two hospitals that showed yeast on Gram stain, Candida Phirst-ID matched the clinical laboratory result for 58 of 59 specimens represented in the 11-species reference panel, without misclassifying the 3 off-panel species. It also detected mixed Candida species in 2 of these 62 specimens, including the one discordant classification, that were not identified by standard clinical microbiology workflows; in each case the presence of both species was validated by both clinical and experimental data. Finally, in three specimens that grew both bacteria and yeast, we paired our prior bacterial probeset with this new Candida probeset to detect both pathogen types using Phirst-ID. This simple, robust assay can provide accurate Candida identification within hours directly from blood culture bottles, and the conceptual approach holds promise for pan-microbial identification in a single workflow. LAY SUMMARY: Candida bloodstream infections cause considerable morbidity and mortality, yet slow diagnostics delay recognition, worsening patient outcomes. We develop and validate a novel molecular approach to accurately identify Candida species directly from blood culture one day faster than standard workflows.

Multiplexed detection of bacterial nucleic acids using Cas13 in droplet microarrays.

Rapid and accurate diagnosis of infections is fundamental to individual patient care and public health management. Nucleic acid detection methods are critical to this effort, but are limited either in the breadth of pathogens targeted or by the expertise and infrastructure required. We present here a high-throughput system that enables rapid identification of bacterial pathogens, bCARMEN, which utilizes: (1) modular CRISPR-Cas13-based nucleic acid detection with enhanced sensitivity and specificity; and (2) a droplet microfluidic system that enables thousands of simultaneous, spatially multiplexed detection reactions at nanoliter volumes; and (3) a novel preamplification strategy that further enhances sensitivity and specificity. We demonstrate bCARMEN is capable of detecting and discriminating 52 clinically relevant bacterial species and several key antibiotic resistance genes. We further develop a simple proof of principle workflow using stabilized reagents and cell phone camera optical readout, opening up the possibility of a rapid point-of-care multiplexed bacterial pathogen identification and antibiotic susceptibility testing.

Inter-species geographic signatures for tracing horizontal gene transfer and long-term persistence of carbapenem resistance.

BACKGROUND: Carbapenem-resistant Enterobacterales (CRE) are an urgent global health threat. Inferring the dynamics of local CRE dissemination is currently limited by our inability to confidently trace the spread of resistance determinants to unrelated bacterial hosts. Whole-genome sequence comparison is useful for identifying CRE clonal transmission and outbreaks, but high-frequency horizontal gene transfer (HGT) of carbapenem resistance genes and subsequent genome rearrangement complicate tracing the local persistence and mobilization of these genes across organisms. METHODS: To overcome this limitation, we developed a new approach to identify recent HGT of large, near-identical plasmid segments across species boundaries, which also allowed us to overcome technical challenges with genome assembly. We applied this to complete and near-complete genome assemblies to examine the local spread of CRE in a systematic, prospective collection of all CRE, as well as time- and species-matched carbapenem-susceptible Enterobacterales, isolated from patients from four US hospitals over nearly 5 years. RESULTS: Our CRE collection comprised a diverse range of species, lineages, and carbapenem resistance mechanisms, many of which were encoded on a variety of promiscuous plasmid types. We found and quantified rearrangement, persistence, and repeated transfer of plasmid segments, including those harboring carbapenemases, between organisms over multiple years. Some plasmid segments were found to be strongly associated with specific locales, thus representing geographic signatures that make it possible to trace recent and localized HGT events. Functional analysis of these signatures revealed genes commonly found in plasmids of nosocomial pathogens, such as functions required for plasmid retention and spread, as well survival against a variety of antibiotic and antiseptics common to the hospital environment. CONCLUSIONS: Collectively, the framework we developed provides a clearer, high-resolution picture of the epidemiology of antibiotic resistance importation, spread, and persistence in patients and healthcare networks.

Detection of the Omicron Variant Virus With the Abbott BinaxNow SARS-CoV-2 Rapid Antigen Assay.

We assessed the ability of the BinaxNow rapid test to detect severe acute respiratory syndrome coronavirus 2 antigen from 4 individuals with Omicron and Delta infections. We performed serial dilutions of nasal swab samples, and specimens with concentrations of ≥100 000 copies/swab were positive, demonstrating that the BinaxNow test is able to detect the Omicron variant.

Harnessing the Potential of Multiomics Studies for Precision Medicine in Infectious Disease.

The field of infectious diseases currently takes a reactive approach and treats infections as they present in patients. Although certain populations are known to be at greater risk of developing infection (eg, immunocompromised), we lack a systems approach to define the true risk of future infection for a patient. Guided by impressive gains in "omics" technologies, future strategies to infectious diseases should take a precision approach to infection through identification of patients at intermediate and high-risk of infection and deploy targeted preventative measures (ie, prophylaxis). The advances of high-throughput immune profiling by multiomics approaches (ie, transcriptomics, epigenomics, metabolomics, proteomics) hold the promise to identify patients at increased risk of infection and enable risk-stratifying approaches to be applied in the clinic. Integration of patient-specific data using machine learning improves the effectiveness of prediction, providing the necessary technologies needed to propel the field of infectious diseases medicine into the era of personalized medicine.

Longitudinal characterization of circulating neutrophils uncovers distinct phenotypes associated with disease severity in hospitalized COVID-19 patients.

Multiple studies have identified an association between neutrophils and COVID-19 disease severity; however, the mechanistic basis of this association remains incompletely understood. Here we collected 781 longitudinal blood samples from 306 hospitalized COVID-19 + patients, 78 COVID-19 âˆ' acute respiratory distress syndrome patients, and 8 healthy controls, and performed bulk RNA-sequencing of enriched neutrophils, plasma proteomics, cfDNA measurements and high throughput antibody profiling assays to investigate the relationship between neutrophil states and disease severity or death. We identified dynamic switches between six distinct neutrophil subtypes using non-negative matrix factorization (NMF) clustering. At days 3 and 7 post-hospitalization, patients with severe disease had an enrichment of a granulocytic myeloid derived suppressor cell-like state gene expression signature, while non-severe patients with resolved disease were enriched for a progenitor-like immature neutrophil state signature. Severe disease was associated with gene sets related to neutrophil degranulation, neutrophil extracellular trap (NET) signatures, distinct metabolic signatures, and enhanced neutrophil activation and generation of reactive oxygen species (ROS). We found that the majority of patients had a transient interferon-stimulated gene signature upon presentation to the emergency department (ED) defined here as Day 0, regardless of disease severity, which persisted only in patients who subsequently died. Humoral responses were identified as potential drivers of neutrophil effector functions, as enhanced antibody-dependent neutrophil phagocytosis and reduced NETosis was associated with elevated SARS-CoV-2-specific IgG1-to-IgA1 ratios in plasma of severe patients who survived. In vitro experiments confirmed that while patient-derived IgG antibodies mostly drove neutrophil phagocytosis and ROS production in healthy donor neutrophils, patient-derived IgA antibodies induced a predominant NETosis response. Overall, our study demonstrates neutrophil dysregulation in severe COVID-19 and a potential role for IgA-dominant responses in driving neutrophil effector functions in severe disease and mortality.

Longitudinal characterization of circulating neutrophils uncovers distinct phenotypes associated with disease severity in hospitalized COVID-19 patients

Multiple studies have identified an association between neutrophils and COVID-19 disease severity; however, the mechanistic basis of this association remains incompletely understood. Here we collected 781 longitudinal blood samples from 306 hospitalized COVID-19+ patients, 78 COVID-19- acute respiratory distress syndrome patients, and 8 healthy controls, and performed bulk RNA-sequencing of enriched neutrophils, plasma proteomics, cfDNA measurements and high throughput antibody profiling assays to investigate the relationship between neutrophil states and disease severity or death. We identified dynamic switches between six distinct neutrophil subtypes using non-negative matrix factorization (NMF) clustering. At days 3 and 7 post-hospitalization, patients with severe disease had an enrichment of a granulocytic myeloid derived suppressor cell-like state gene expression signature, while non-severe patients with resolved disease were enriched for a progenitor-like immature neutrophil state signature. Severe disease was associated with gene sets related to neutrophil degranulation, neutrophil extracellular trap (NET) signatures, distinct metabolic signatures, and enhanced neutrophil activation and generation of reactive oxygen species (ROS). We found that the majority of patients had a transient interferon-stimulated gene signature upon presentation to the emergency department (ED) defined here as Day 0, regardless of disease severity, which persisted only in patients who subsequently died. Humoral responses were identified as potential drivers of neutrophil effector functions, as enhanced antibody-dependent neutrophil phagocytosis and reduced NETosis was associated with elevated SARS-CoV-2-specific IgG1-to-IgA1 ratios in plasma of severe patients who survived. In vitro experiments confirmed that while patient-derived IgG antibodies mostly drove neutrophil phagocytosis and ROS production in healthy donor neutrophils, patient-derived IgA antibodies induced a predominant NETosis response. Overall, our study demonstrates neutrophil dysregulation in severe COVID-19 and a potential role for IgA-dominant responses in driving neutrophil effector functions in severe disease and mortality.

Cross-Sectional Assessment of SARS-CoV-2 Viral Load by Symptom Status in Massachusetts Congregate Living Facilities.

Transmission of coronavirus disease 2019 (COVID-19) from people without symptoms confounds societal mitigation strategies. From April to June 2020, we tested nasopharyngeal swabs by reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) from 15 514 staff and 16 966 residents of nursing homes and assisted living facilities in Massachusetts. Cycle threshold (Ct) distributions were very similar between populations with (n = 739) and without (n = 2179) symptoms at the time of sampling (mean Ct, 25.7 vs 26.4; ranges 12-38). However, as local cases waned, those without symptoms shifted towards higher Ct. With such similar viral load distributions, existing testing modalities should perform comparably regardless of symptoms, contingent upon time since infection.

Plasma from patients with bacterial sepsis or severe COVID-19 induces suppressive myeloid cell production from hematopoietic progenitors in vitro.

Bacterial sepsis and severe COVID-19 share similar clinical manifestations and are both associated with dysregulation of the myeloid cell compartment. We previously reported an expanded CD14+ monocyte state, MS1, in patients with bacterial sepsis and validated expansion of this cell subpopulation in publicly available transcriptomics data. Here, using published datasets, we show that the gene expression program associated with MS1 correlated with sepsis severity and was up-regulated in monocytes from patients with severe COVID-19. To examine the ontogeny and function of MS1 cells, we developed a cellular model for inducing CD14+ MS1 monocytes from healthy bone marrow hematopoietic stem and progenitor cells (HSPCs). We found that plasma from patients with bacterial sepsis or COVID-19 induced myelopoiesis in HSPCs in vitro and expression of the MS1 gene program in monocytes and neutrophils that differentiated from these HSPCs. Furthermore, we found that plasma concentrations of IL-6, and to a lesser extent IL-10, correlated with increased myeloid cell output from HSPCs in vitro and enhanced expression of the MS1 gene program. We validated the requirement for these two cytokines to induce the MS1 gene program through CRISPR-Cas9 editing of their receptors in HSPCs. Using this cellular model system, we demonstrated that induced MS1 cells were broadly immunosuppressive and showed decreased responsiveness to stimulation with a synthetic RNA analog. Our in vitro study suggests a potential role for systemic cytokines in inducing myelopoiesis during severe bacterial or SARS-CoV-2 infection.