HIV and COVID-19: two pandemics with significant (but different) central nervous system complications.

Human immunodeficiency virus (HIV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cause significant neurologic disease. Central nervous system (CNS) involvement of HIV has been extensively studied, with well-documented invasion of HIV into the brain in the initial stage of infection, while the acute effects of SARS-CoV-2 in the brain are unclear. Neuropathologic features of active HIV infection in the brain are well characterized whereas neuropathologic findings in acute COVID-19 are largely non-specific. On the other hand, neuropathologic substrates of chronic dysfunction in both infections, as HIV-associated neurocognitive disorders (HAND) and post-COVID conditions (PCC)/long COVID are unknown. Thus far, neuropathologic studies on patients with HAND in the era of combined antiretroviral therapy have been inconclusive, and autopsy studies on patients diagnosed with PCC have yet to be published. Further longitudinal, multidisciplinary studies on patients with HAND and PCC and neuropathologic studies in comparison to controls are warranted to help elucidate the mechanisms of CNS dysfunction in both conditions.

Clinical Whole-Genome Sequencing Assay for Rapid Mycobacterium tuberculosis Complex First-Line Drug Susceptibility Testing and Phylogenetic Relatedness Analysis.

The global rise of drug resistant tuberculosis has highlighted the need for improved diagnostic technologies that provide rapid and reliable drug resistance results. Here, we develop and validate a whole genome sequencing (WGS)-based test for identification of mycobacterium tuberculosis complex (MTB) drug resistance to rifampin, isoniazid, pyrazinamide, ethambutol, and streptomycin. Through comparative analysis of drug resistance results from WGS-based testing and phenotypic drug susceptibility testing (DST) of 38 clinical MTB isolates from patients receiving care in Los Angeles, CA, we found an overall concordance between methods of 97.4% with equivalent performance across culture media. Critically, prospective analysis of 11 isolates showed that WGS-based testing provides results an average of 36 days faster than phenotypic culture-based methods. We showcase the additional benefits of WGS data by investigating a suspected laboratory contamination event and using phylogenetic analysis to search for cryptic local transmission, finding no evidence of community spread amongst our patient population in the past six years. WGS-based testing for MTB drug resistance has the potential to greatly improve diagnosis of drug resistant MTB by accelerating turnaround time while maintaining accuracy and providing additional benefits for infection control, lab safety, and public health applications.

FDA trial regulation of laboratory developed tests (LDTs): An academic medical center's experience with Mpox in-house testing.

The 2022 mpox outbreak presented a familiar challenge to clinical laboratories. Accordingly, our institution was able to swiftly implement in-house mpox testing to meet the imminent diagnostic needs of the public health emergency. While the FDA authorized laboratory-developed tests (LDTs) for lesion specimens, however, it restricted the testing of rectal swabs despite mounting evidence of its clinical utility. Notably, within the short timeframe when rectal testing was available, we identified a high-risk patient without apparent lesions who tested monkeypox-positive only by our in-house rectal swab assay. In order for our institution to continue testing non-lesion samples, The FDA required a separate Emergency Use Authorization (EUA) application that demanded additional resource-costly validation studies despite utilizing the same testing platform as lesion samples. Here, we provide a brief review of the history, current status, and legal scope surrounding LDT validations, with an in-depth comparison of the technical requirements by CLIA, CAP and the FDA. Importantly, we provide our experience with the mpox EUA submission process to serve as context for the challenges that may be imposed by the new FDA regulations. We hope that our experience will offer a valuable perspective that promotes constructive discourse towards addressing the imperative to offer high-quality laboratory diagnostics without compromising on the need of the medical laboratory community to provide effective patient care.

Amphiphilic Particle-Stabilized Nanoliter Droplet Reactors with a Multimodal Portable Reader for Distributive Biomarker Quantification.

Compartmentalization, leveraging microfluidics, enables highly sensitive assays, but the requirement for significant infrastructure for their design, build, and operation limits access. Multimaterial particle-based technologies thermodynamically stabilize monodisperse droplets as individual reaction compartments with simple liquid handling steps, precluding the need for expensive microfluidic equipment. Here, we further improve the accessibility of this lab on a particle technology to resource-limited settings by combining this assay system with a portable multimodal reader, thus enabling nanoliter droplet assays in an accessible platform. We show the utility of this platform in measuring N-terminal propeptide B-type natriuretic peptide (NT-proBNP), a heart failure biomarker, in complex medium and patient samples. We report a limit of detection of ∼0.05 ng/mL and a linear response between 0.2 and 2 ng/mL in spiked plasma samples. We also show that, owing to the plurality of measurements per sample, "swarm" sensing acquires better statistical quantitation with a portable reader. Monte Carlo simulations show the increasing capability of this platform to differentiate between negative and positive samples, i.e., below or above the clinical cutoff for acute heart failure (∼0.1 ng/mL), as a function of the number of particles measured. Our platform measurements correlate with gold standard ELISA measurement in cardiac patient samples, and achieve lower variation in measurement across samples compared to the standard well plate-based ELISA. Thus, we show the capabilities of a cost-effective droplet-reader system in accurately measuring biomarkers in nanoliter droplets for diseases that disproportionately affect underserved communities in resource-limited settings.

Single-tier point-of-care serodiagnosis of Lyme disease.

Point-of-care (POC) serological testing provides actionable information for several difficult to diagnose illnesses, empowering distributed health systems. Accessible and adaptable diagnostic platforms that can assay the repertoire of antibodies formed against pathogens are essential to drive early detection and improve patient outcomes. Here, we report a POC serologic test for Lyme disease (LD), leveraging synthetic peptides tuned to be highly specific to the LD antibody repertoire across patients and compatible with a paper-based platform for rapid, reliable, and cost-effective diagnosis. A subset of antigenic epitopes conserved across Borrelia burgdorferi genospecies and targeted by IgG and IgM antibodies, were selected based on their seroreactivity to develop a multiplexed panel for a single-step measurement of combined IgM and IgG antibodies from LD patient sera. Multiple peptide epitopes, when combined synergistically using a machine learning-based diagnostic model, yielded a high sensitivity without any loss in specificity. We blindly tested the platform with samples from the U.S. Centers for Disease Control & Prevention (CDC) LD repository and achieved a sensitivity and specificity matching the lab-based two-tier results with a single POC test, correctly discriminating cross-reactive look-alike diseases. This computational LD diagnostic test can potentially replace the cumbersome two-tier testing paradigm, improving diagnosis and enabling earlier effective treatment of LD patients while also facilitating immune monitoring and surveillance of the disease in the community.

Epidemiology and SARS-CoV-2 Infection Patterns among Youth Followed at a Large Los Angeles Health Network during 2020-2022: Clinical Presentation, Prevalent Strains, and Correlates of Disease Severity.

BACKGROUND: Outcomes of SARS CoV-2 infection in infants, children and young adults are reported less frequently than in older populations. The evolution of SARS-CoV-2 cases in LA County youths followed at a large health network in southern California over two years was evaluated. METHODS: A prospective cohort study of patients aged 0-24 years diagnosed with COVID-19 was conducted. Demographics, age distribution, disease severity, circulating variants of concern (VOCs), and immunization rates were compared between first and second pandemic years. Logistic regression estimated odds ratios (OR) and 95% confidence intervals (CI) of factors associated with severe/critical COVID-19. RESULTS: In total, 61,208 patients 0-24 years of age were tested for SARS-CoV-2 by polymerase chain reaction (PCR); 5263 positive patients (8.6%) with available data were identified between March 2020 and March 2022. In Year 1, 5.8% (1622/28,088) of youths tested positive, compared to 11% (3641/33,120) in Year 2 (p < 0.001). Most youths had mild/asymptomatic illness over two years. SARS-CoV-2 positivity was >12% across all age groups in the second half of Year 2, when Omicron prevailed. Pulmonary disease was associated with higher risk of severe COVID-19 in both years (OR: 2.4, 95% CI: 1.4-4.3, p = 0.002, Year 1; OR: 11.3, 95% CI: 4.3-29.6, Year 2, p < 0.001). Receipt of at least one COVID-19 vaccine dose was protective against severe COVID-19 (OR: 0.3, 95% CI: 0.11-0.80, p < 0.05). CONCLUSIONS: Despite different VOCs and higher rates of test positivity in Year 2 compared to Year 1, most youths with COVID-19 had asymptomatic/mild disease. Underlying pulmonary conditions increased the risk of severe COVID-19, while vaccination was highly protective against severe disease in youths.

Clinical next-generation sequencing assay combining full-length gene amplification and shotgun sequencing for the detection of CMV drug resistance mutations.

Cytomegalovirus (CMV) causes severe systemic and tissue-invasive disease in immunocompromised patients, particularly solid organ and hematopoietic stem cell transplant recipients. While antiviral drugs offer promising efficacy, clinical management is complicated by the high frequency of drug resistance-associated mutations. The most commonly encountered mutations occur in the genes encoding for the drug targets: UL54 (DNA polymerase), UL56 (terminase complex), and UL97 (phosphotransferase), conferring resistance to ganciclovir/cidofovir/foscarnet, letermovir, and ganciclovir/maribavir, respectively. Currently, standard practice for detecting drug resistance is sequencing-based genotypic analysis by commercial reference laboratories with strictly prescribed sample requirements and reporting parameters that can often restrict testing in a highly vulnerable population. In order to circumvent these limitations, we developed a dual-step next-generation sequencing (NGS)-based clinical assay that utilizes full-length gene amplification by long-range PCR followed by shotgun sequencing for mutation analysis. This laboratory-developed test (LDT) achieved satisfactory performance with 96.4% accuracy, 100% precision, and an analytical sensitivity of 300IU/mL with 20% allele frequency. Highlighted by two clinical cases, our NGS LDT was able to provide critical results from patient specimens with viral loads <500IU/mL and volumes <0.5 mL - conditions otherwise unacceptable by reference laboratories. Here, we describe the development and implementation of a robust NGS LDT that offers greater testing flexibility and sensitivity to accommodate a more diverse patient population.

Using an Antibiogram Profile to Improve Infection Control and Rational Antimicrobial Therapy in an Urban Hospital in The Gambia, Strategies and Lessons for Low- and Middle-Income Countries.

Antimicrobial resistance is a global health threat and efforts to mitigate it is warranted, thus the need for local antibiograms to improve stewardship. This study highlights the process that was used to develop an antibiogram to monitor resistance at a secondary-level health facility to aid empirical clinical decision making in a sub-Saharan African county. This retrospective cross-sectional descriptive study used 3 years of cumulative data from January 2016 to December 2018. Phenotypic data was manually imputed into WHONET and the cumulative antibiogram constructed using standardized methodologies according to CLSI M39-A4 guidelines. Pathogens were identified by standard manual microbiological methods and antimicrobial susceptibility testing was performed using Kirby-Bauer disc diffusion method according to CLSI M100 guidelines. A total of 14,776 non-duplicate samples were processed of which 1163 (7.9%) were positive for clinically significant pathogens. Among the 1163 pathogens, E. coli (n = 315) S. aureus (n = 232), and K. pneumoniae (n = 96) were the leading cause of disease. Overall, the susceptibility for E. coli and K. pneumoniae from all samples were: trimethoprim-sulfamethoxazole (17% and 28%), tetracycline (26% and 33%), gentamicin (72% and 46%), chloramphenicol (76 and 60%), and ciprofloxacin (69% and 59%), and amoxicillin/clavulanic (77% and 54%) respectively. Extended spectrum beta-lactamase (ESBL) resistance was present in 23% (71/315) vs. 35% (34/96) respectively. S. aureus susceptibility for methicillin was 99%. This antibiogram has shown that improvement in combination therapy is warranted in The Gambia.

Deep Learning-Enabled Multiplexed Point-of-Care Sensor using a Paper-Based Fluorescence Vertical Flow Assay.

Multiplexed computational sensing with a point-of-care serodiagnosis assay to simultaneously quantify three biomarkers of acute cardiac injury is demonstrated. This point-of-care sensor includes a paper-based fluorescence vertical flow assay (fxVFA) processed by a low-cost mobile reader, which quantifies the target biomarkers through trained neural networks, all within <15 min of test time using 50 µL of serum sample per patient. This fxVFA platform is validated using human serum samples to quantify three cardiac biomarkers, i.e., myoglobin, creatine kinase-MB, and heart-type fatty acid binding protein, achieving less than 0.52 ng mL-1 limit-of-detection for all three biomarkers with minimal cross-reactivity. Biomarker concentration quantification using the fxVFA that is coupled to neural network-based inference is blindly tested using 46 individually activated cartridges, which shows a high correlation with the ground truth concentrations for all three biomarkers achieving >0.9 linearity and <15% coefficient of variation. The competitive performance of this multiplexed computational fxVFA along with its inexpensive paper-based design and handheld footprint makes it a promising point-of-care sensor platform that can expand access to diagnostics in resource-limited settings.

Accurate subspecies-level identification of clinically significant Mycobacterium avium and Mycobacterium intracellulare by whole-genome sequencing.

Whole genome sequencing (WGS) of Mycobacterium avium complex (MAC) isolates in the clinical laboratory setting allows for rapid and reliable subspecies identification of a closely related complex of human pathogens. We developed a bioinformatics pipeline for accurate subspecies identification and tested 74 clinical MAC isolates from various anatomical sites. We demonstrate that reliable subspecies level identification of these common and clinically significant MAC isolates, including M. avium subsp. hominissuis (most dominant in causing lower respiratory tract infections in our cohort), M. avium subsp. avium, M. intracellulare subsp. intracellulare, and M. intracellulare subsp. chimaera, can be achieved by analysis of only two marker genes (rpoB and groEL/hsp65). We then explored the relationship between these subspecies and anatomical site of infection. Further, we conducted an in silico analysis and showed our algorithm also performed well for M. avium subsp. paratuberculosis but failed to consistently identify M. avium subsp. silvaticum and M. intracellulare subsp. yongonense, likely due to a lack of available reference genome sequences; all the 3 subspecies were not found in our clinical isolates and rarely reported to cause human infections. Accurate MAC subspecies identification may provide the tool and opportunity for better understanding of the disease-subspecies dynamics in MAC infections.

Correction: An amplification-free, 16S rRNA test for Neisseria gonorrhoeae in urine.

[This corrects the article DOI: 10.1039/D2SD00128D.].

Real-world performance of SARS-Cov-2 serology tests in the United States, 2020.

BACKGROUND: Real-world performance of COVID-19 diagnostic tests under Emergency Use Authorization (EUA) must be assessed. We describe overall trends in the performance of serology tests in the context of real-world implementation. METHODS: Six health systems estimated the odds of seropositivity and positive percent agreement (PPA) of serology test among people with confirmed SARS-CoV-2 infection by molecular test. In each dataset, we present the odds ratio and PPA, overall and by key clinical, demographic, and practice parameters. RESULTS: A total of 15,615 people were observed to have at least one serology test 14-90 days after a positive molecular test for SARS-CoV-2. We observed higher PPA in Hispanic (PPA range: 79-96%) compared to non-Hispanic (60-89%) patients; in those presenting with at least one COVID-19 related symptom (69-93%) as compared to no such symptoms (63-91%); and in inpatient (70-97%) and emergency department (93-99%) compared to outpatient (63-92%) settings across datasets. PPA was highest in those with diabetes (75-94%) and kidney disease (83-95%); and lowest in those with auto-immune conditions or who are immunocompromised (56-93%). The odds ratios (OR) for seropositivity were higher in Hispanics compared to non-Hispanics (OR range: 2.59-3.86), patients with diabetes (1.49-1.56), and obesity (1.63-2.23); and lower in those with immunocompromised or autoimmune conditions (0.25-0.70), as compared to those without those comorbidities. In a subset of three datasets with robust information on serology test name, seven tests were used, two of which were used in multiple settings and met the EUA requirement of PPA ≥87%. Tests performed similarly across datasets. CONCLUSION: Although the EUA requirement was not consistently met, more investigation is needed to understand how serology and molecular tests are used, including indication and protocol fidelity. Improved data interoperability of test and clinical/demographic data are needed to enable rapid assessment of the real-world performance of in vitro diagnostic tests.

Fungal Whole-Genome Sequencing for Species Identification: From Test Development to Clinical Utilization.

Using next-generation sequencing (NGS), we developed and validated a whole-genome sequencing (WGS)-based clinical test for fungal species identification on clinical isolates. The identification is mainly based on the fungal ribosomal internal transcribed spacer (ITS) region as the primary marker, and additional marker and genomic analysis applied for species within the Mucorales family (using the 28S rRNA gene) and Aspergillus genus (using the beta-tubulin gene and k-mer tree-based phylogenetic clustering). The validation study involving 74 unique fungal isolates (22 yeasts, 51 molds, and 1 mushroom-forming fungus) showed high accuracy, with 100% (74/74) concordance on the genus-level identifications and 89.2% (66/74) concordance on the species level. The 8 discrepant results were due to either the limitation of conventional morphology-based methodology or taxonomic changes. After one year of implementation in our clinical laboratory, this fungal NGS test was utilized in 29 cases; the majority of them were transplant and cancer patients. We demonstrated the utility of this test by detailing five case studies, in which accurate fungal species identification led to correct diagnosis, treatment adjustment or was ruled out for hospital acquired infection. This study provides a model for validation and implementation of WGS for fungal identification in a complex health system that serves a large immunocompromised patient population.

An amplification-free, 16S rRNA test for Neisseria gonorrhoeae in urine.

An amplification-free, nanopore-based nucleic acid detection platform has been demonstrated for rapid, 16S rRNA sequence-specific detection of Neisseria gonorrhoeae at 10-100 CFU mL-1 in human urine against background bacterial flora at 1000 CFU mL-1. Gonorrhea is a very common notifiable communicable disease, antibiotic resistant strains have emerged, and the rate of reported gonococcal infections continues to increase. Since rapid clinical identification of bacterial pathogens in clinical samples is needed to guide proper antibiotic treatment and to control disease spread, it is important to engineer rapid, sensitive, selective, and inexpensive point-of-care (POC) diagnostic devices for pathogens such as N. gonorrhoeae. Our detector technology is based on straightforward conductometric detection of sustained blockage of a glass nanopore. Charge neutral, complementary peptide nucleic acid probes are conjugated to polystyrene beads to capture N. gonorrhoeae 16S rRNA selectively. In the presence of an electric field applied externally through a glass nanopore, the PNA-microbead conjugates that acquire substantial negative charge upon target hybridization are driven to the smaller diameter nanopore. At least partial blockage of the nanopore results in a sustained drop in ionic current that can be measured easily with simple electronics. The ability to detect N. gonorrhoeae over the range of 10 to 100 CFU mL-1 spiked in human urine was demonstrated successfully with estimated sensitivity and specificity of ∼98% and ∼100%, respectively. No false positives were observed for the control group of representative background flora (E. coli, K. pneumoniae, and E. faecalis) at 1000 CFU mL-1. Also, N. gonorrhoeae at 50 CFU mL-1 was successfully detected against 1000 CFU mL-1 of background flora in urine. These results suggest that this amplification-free technology may serve as the basis for rapid, inexpensive, low-power detection of pathogens in clinical samples at the POC.

Real-world utilization of SARS-CoV-2 serological testing in RNA positive patients across the United States.

BACKGROUND: As diagnostic tests for COVID-19 were broadly deployed under Emergency Use Authorization, there emerged a need to understand the real-world utilization and performance of serological testing across the United States. METHODS: Six health systems contributed electronic health records and/or claims data, jointly developed a master protocol, and used it to execute the analysis in parallel. We used descriptive statistics to examine demographic, clinical, and geographic characteristics of serology testing among patients with RNA positive for SARS-CoV-2. RESULTS: Across datasets, we observed 930,669 individuals with positive RNA for SARS-CoV-2. Of these, 35,806 (4%) were serotested within 90 days; 15% of which occurred <14 days from the RNA positive test. The proportion of people with a history of cardiovascular disease, obesity, chronic lung, or kidney disease; or presenting with shortness of breath or pneumonia appeared higher among those serotested compared to those who were not. Even in a population of people with active infection, race/ethnicity data were largely missing (>30%) in some datasets-limiting our ability to examine differences in serological testing by race. In datasets where race/ethnicity information was available, we observed a greater distribution of White individuals among those serotested; however, the time between RNA and serology tests appeared shorter in Black compared to White individuals. Test manufacturer data was available in half of the datasets contributing to the analysis. CONCLUSION: Our results inform the underlying context of serotesting during the first year of the COVID-19 pandemic and differences observed between claims and EHR data sources-a critical first step to understanding the real-world accuracy of serological tests. Incomplete reporting of race/ethnicity data and a limited ability to link test manufacturer data, lab results, and clinical data challenge the ability to assess the real-world performance of SARS-CoV-2 tests in different contexts and the overall U.S. response to current and future disease pandemics.

Clinical, microbiological, and genomic characteristics of clade-III Candida auris colonization and infection in southern California, 2019-2022.

BACKGROUND: Candida auris is an emerging fungal pathogen causing outbreaks in healthcare facilities. Five distinctive genomic clades exhibit clade-unique characteristics, highlighting the importance of real-time genomic surveillance and incorporating genotypic information to inform infection prevention practices and treatment algorithms. METHODS: Both active and passive surveillance were used to screen hospitalized patients. C. auris polymerase chain reaction (PCR) assay on inguinal-axillary swabs was performed on high-risk patients upon admission. All clinical yeast isolates were identified to the species level. C. auris isolates were characterized by both phenotypic antifungal susceptibility tests and whole-genome sequencing. RESULTS: From late 2019 to early 2022, we identified 45 patients with C. auris. Most had a tracheostomy or were from a facility with a known outbreak. Moreover, 7 patients (15%) were only identified through passive surveillance. Also, 8 (18%) of the patients had a history of severe COVID-19. The overall mortality was 18%. Invasive C. auris infections were identified in 13 patients (29%), 9 (69%) of whom had bloodstream infections. Patients with invasive infection were more likely to have a central line. All C. auris isolates were resistant to fluconazole but susceptible to echinocandins. Genomic analysis showed that 1 dominant clade-III lineage is circulating in Los Angeles, with very limited intrahost and interhost genetic diversity. CONCLUSIONS: We have demonstrated that a robust C. auris surveillance program can be established using both active and passive surveillance, with multidisciplinary efforts involving the microbiology laboratory and the hospital epidemiology team. In Los Angeles County, C. auris strains are highly related and echinocandins should be used for empiric therapy.

On variants and vaccines: The effectiveness of Covid-19 monoclonal antibody therapy during two distinct periods in the pandemic.

BACKGROUND: While Covid-19 monoclonal antibody therapies (Mab) have been available in the outpatient setting for over a year and a half, little is known about the impact of emerging variants and vaccinations on the effectiveness of Mab therapies. We sought to determine the effectiveness of Covid-19 Mab therapies during the first two waves of the pandemic in Los Angeles County and assess the impact of vaccines, variants, and other confounding factors. METHODS AND FINDINGS: We retrospectively examined records for 2209 patients of with confirmed positive molecular SARS-CoV2 test either referred for outpatient Mab therapy or receiving Mab treatment in the emergency department (ED) between December 2020 and 2021. Our primary outcome was the combined 30-day incidence of ED visit, hospitalization, or death following the date of referral. Additionally, SARS-CoV2 isolates of hospitalized patients receiving Mabs were sequenced. The primary outcome was significantly reduced with combination therapy compared to bamlanivimab or no treatment (aHR 0·60; 95% CI ·37, ·99), with greater benefit in unvaccinated, moderate-to-high-risk patients (aHR ·39; 95% CI ·20, ·77). Significant associations with the primary outcome included history of lung disease (HR 7·13; 95% CI 5·12, 9·95), immunocompromised state (HR 6·59; 95% CI 2·91-14·94), and high social vulnerability (HR 2·29, 95% CI 1·56-3·36). Two predominant variants were noted during the period of observation: the Epsilon variant and the Delta variant. CONCLUSIONS: Only select monoclonal antibody therapies significantly reduced ED visits, hospitalizations, and death due to COVID-19 during. Vaccination diminished effectiveness of Mabs. Variant data and vaccination status should be considered when assessing the benefit of novel COVID-19 treatments.

Case Report: Symptomatic Herpes Simplex Virus Type 2 and Monkeypox Coinfection in an Adult Male.

A 39-year-old man presented with a history of fatigue, malaise, and rash with varied morphology on his perianal region. Polymerase chain reaction testing of the lesions confirmed coinfection with monkeypox and herpes simplex virus type 2. We emphasize the difficulty in distinguishing between monkeypox virus and herpes simplex virus type 2 based on history and examination alone.

Genetic Predictive Factors for Nonsusceptible Phenotypes and Multidrug Resistance in Expanded-Spectrum Cephalosporin-Resistant Uropathogenic Escherichia coli from a Multicenter Cohort: Insights into the Phenotypic and Genetic Basis of Coresistance.

Antimicrobial resistance in urinary tract infections (UTIs) is a major public health concern. This study aims to characterize the phenotypic and genetic basis of multidrug resistance (MDR) among expanded-spectrum cephalosporin-resistant (ESCR) uropathogenic Escherichia coli (UPEC) causing UTIs in California patient populations. Between February and October 2019, 577 ESCR UPEC isolates were collected from patients at 6 clinical laboratory sites across California. Lineage and antibiotic resistance genes were determined by analysis of whole-genome sequence data. The lineages ST131, ST1193, ST648, and ST69 were predominant, representing 46%, 5.5%, 4.5%, and 4.5% of the collection, respectively. Overall, 527 (91%) isolates had an expanded-spectrum ß-lactamase (ESBL) phenotype, with blaCTX-M-15, blaCTX-M-27, blaCTX-M-55, and blaCTX-M-14 being the most prevalent ESBL genes. In the 50 non-ESBL phenotype isolates, 40 (62%) contained blaCMY-2, which was the predominant plasmid-mediated AmpC (pAmpC) gene. Narrow-spectrum ß-lactamases, blaTEM-1B and blaOXA-1, were also found in 44.9% and 32.1% of isolates, respectively. Among ESCR UPEC isolates, isolates with an ESBL phenotype had a 1.7-times-greater likelihood of being MDR than non-ESBL phenotype isolates (P < 0.001). The cooccurrence of blaCTX-M-15, blaOXA-1, and aac(6')-Ib-cr within ESCR UPEC isolates was strongly correlated. Cooccurrence of blaCTX-M-15, blaOXA-1, and aac(6')-Ib-cr was associated with an increased risk of nonsusceptibility to piperacillin-tazobactam, cefepime, fluoroquinolones, and amikacin as well as MDR. Multivariate regression revealed the presence of blaCTX-M-55, blaTEM-1B, and the ST131 genotype as predictors of MDR. IMPORTANCE The rising incidence of resistance to expanded-spectrum cephalosporins among Escherichia coli strains, the most common cause of UTIs, is threatening our ability to successfully empirically treat these infections. ESCR E. coli strains are often MDR; therefore, UTI caused by these organisms often leads to treatment failure, increased length of hospital stay, and severe complications (D. G. Mark, Y.-Y. Hung, Z. Salim, N. J. Tarlton, et al., Ann Emerg Med 78:357-369, 2021, https://doi.org/10.1016/j.annemergmed.2021.01.003). Here, we performed an in-depth analysis of genetic factors of ESCR E. coli associated with coresistance and MDR. Such knowledge is critical to advance UTI diagnosis, treatment, and antibiotic stewardship.

Ferrobotic swarms enable accessible and adaptable automated viral testing.

Expanding our global testing capacity is critical to preventing and containing pandemics1-9. Accordingly, accessible and adaptable automated platforms that in decentralized settings perform nucleic acid amplification tests resource-efficiently are required10-14. Pooled testing can be extremely efficient if the pooling strategy is based on local viral prevalence15-20; however, it requires automation, small sample volume handling and feedback not available in current bulky, capital-intensive liquid handling technologies21-29. Here we use a swarm of millimetre-sized magnets as mobile robotic agents ('ferrobots') for precise and robust handling of magnetized sample droplets and high-fidelity delivery of flexible workflows based on nucleic acid amplification tests to overcome these limitations. Within a palm-sized printed circuit board-based programmable platform, we demonstrated the myriad of laboratory-equivalent operations involved in pooled testing. These operations were guided by an introduced square matrix pooled testing algorithm to identify the samples from infected patients, while maximizing the testing efficiency. We applied this automated technology for the loop-mediated isothermal amplification and detection of the SARS-CoV-2 virus in clinical samples, in which the test results completely matched those obtained off-chip. This technology is easily manufacturable and distributable, and its adoption for viral testing could lead to a 10-300-fold reduction in reagent costs (depending on the viral prevalence) and three orders of magnitude reduction in instrumentation cost. Therefore, it is a promising solution to expand our testing capacity for pandemic preparedness and to reimagine the automated clinical laboratory of the future.