Journal of Clinical Microbiology

BackgroundLower respiratory tract infections (LRTIs) remain diagnostically challenging when culture and molecular assays are negative or delayed. We evaluated ONETest Pathogenome (OT), an automated hybrid-capture metagenomic assay with core-genome enrichment probes, for direct pathogen detection in bronchoalveolar lavage (BAL). MethodsAnalytical performance (LoD, precision, continuity) was assessed using whole-cell spike-ins into culture-negative BAL fluid. Technical performance was assessed in 119 specimens profiled by OT and whole-metagenome shotgun sequencing (WmGS, cohort 1). Clinical accuracy was evaluated in 360 specimens (cohort 2) benchmarked against routine bacterial and acid-fast bacillus (AFB) culture. Laboratory-developed test (LDT) validation included 43 specimens (cohort 3) benchmarked to bacterial and AFB culture. ResultsOT uses 6.2 million probes covering core genomes across 50 microbial families (>250 respiratory pathogens). In BAL specimens, OT increased normalized on-target microbial abundance 26-fold versus that of WmGS while preserving within-sample microbial diversity. In cohort 2, OT achieved species-level sensitivity of 80% and specificity of 99% across culture-confirmed isolates and detected [&ge;]1 culture-confirmed organism in 100/115 culture-positive specimens (87%), while applying species-specific background baselines to mitigate overcalling. Additive yield was 21% (76/360), with 7.5% (27/360) of specimens having [&ge;]1 additional finding supported by orthogonal testing. In LDT validation, OT identified [&ge;]1 culture-confirmed organism in 34/40 culture-positive specimens (85%) with one OT-positive/culture-negative specimen. ConclusionsOT is an assay with a turnaround time <24 h complementary to culture that improves pathogen detection and expands microbiologic findings through additional detections and co-detections, including slow-growing organisms that may require prolonged incubation by conventional methods.

BackgroundMatrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is pivotal in clinical microbiology. The VITEK MS Research Use Only (RUO) database offers broader species coverage, yet its clinical adoption is hindered by insufficient performance validation against the approved in vitro diagnostic (IVD) database and inefficient manual operational workflows. ObjectiveThis two-phase study first aimed to develop and evaluate an automated integrated workflow to enhance laboratory efficiency and diagnostic capability. MethodsThe RUO databases two-tier identification architecture was utilized and in-house automated relay software was developed to parse IVD results and fully automate RUO reanalysis. Phase 1 (Mar 2021-Jun 2022) involved parallel manual testing of 2,432 isolates with both databases to analyze concordance and supplementary performance. Phase 2 (Jul-Nov 2022) prospectively incorporated 3,954 isolates to implement and assess the "IVD screening - automated RUO reanalysis" workflow. ResultsPhase 1 demonstrated high RUO-IVD concordance (95.7% species/genus agreement). The RUO database correctly identified 98.9% of isolates and provided valid supplementary identification for 84.4% (108/128) of IVD-failed cases, with Tier 2 contributing 28.9%. Phase 2 revealed that the integrated workflow increased the overall identification rate from 95.5% to 98.7%, with Tier 2 contributing an additional 14.5%. The automated software reduced reanalysis turnaround time by > 75%, saving consumables and labor. ConclusionThe VITEK MS RUO database is a reliable and complementary tool to the IVD database. Integration with automated software creates an efficient, compliant clinical workflow, providing a practical model to enhance pathogen identification for infectious disease management. IMPORTANCEThe present study bridges the validation-to-application gap for the VITEK MS RUO database. We confirm its high concordance (95.7%) and complementary value to the IVD database, quantify the impact of manual workflow inefficiency and introduce an automated software solution. The strategy highlights the key role of Reference Spectra (Tier 2) in expanding coverage and simultaneously improves diagnostic efficacy ([~]99% ID rate), operational efficiency (> 75% time saved) and cost-effectiveness, offering a practical model to accelerate pathogen reporting and to guide therapy.

To evaluate the diagnostic performance of clinical shotgun metagenomic sequencing (SMg) for detecting medically relevant fungi and parasites compared with standard of care (SoC), and to define read-based thresholds for interpretation, we retrospectively analyzed 198 clinical samples from 187 patients across four university hospitals (2018-2022): blood (n=37), faeces (n=63), respiratory fluids (n=54), other biological fluids (n=24), and tissue biopsies (n=20). Total nucleic acids were sequenced ([&ge;]10 million reads per library) and processed with MetaMIC v2.2.1. Data were normalized as reads per million (RPM). Receiver operating characteristic analyses were used to derive optimal RPM thresholds by sample type. SoC identified microorganisms in 152/198 samples (76.8%). All 46 SoC-negative samples were also negative by SMg. At the genus level, SoC identified 187 taxa and SMg 175. Of these, 147 (78.6%) were detected by both methods, 40 (21.4%) by SoC only, and 28 (14.9%) by SMg only. The overall genus-level F1-score was 0.84. Quantification cycle (Cq) values (n=57) correlated inversely with RPM (p<0.001), and no false negatives occurred with Cq<28.6. Optimal thresholds were 0.06 RPM for faeces (AUC 0.89), 0.07 for respiratory fluids (AUC 0.93; sensitivity 88.9%, specificity 90.7%), 0.09 for blood (AUC 0.99), 0.19 for other fluids (AUC 0.94), and 0.57 for biopsies (AUC 0.89). A global threshold of 0.06 RPM yielded an AUC of 0.92 (sensitivity 88.9%, specificity 88.5%). A pragmatic uniform 0.1 RPM threshold maintained performance, while sample-type specific thresholds further improved accuracy, supporting standardized implementation of clinical metagenomics for fungal and parasitic diagnostics.

Studies have shown that metagenomic next-generation sequencing (mNGS) testing of cerebrospinal fluid (CSF) in central nervous system (CNS) infections can improve diagnostic yields and provide actionable information. We analyzed the results of all CSF mNGS tests (n=4,828) performed at the University of California, San Francisco (UCSF) clinical microbiology laboratory from June 2016 to April 2023. We also assessed clinical metadata from a subset of samples that corresponded to a cohort of UCSF patients (n=1,164) who received CSF mNGS testing, and retrospectively evaluated performance compared to conventional microbiologic testing and adjudicated clinical diagnosis. Overall, 14.4% of CSF mNGS tests were positive for any microorganism. DNA viruses (7% of all samples) were detected most often, followed by RNA viruses (4.3%), bacteria (2.7%), fungi (1.4%), and parasites (0.5%). Using a composite gold standard obtained from clinical adjudication and all microbiological test results, sensitivity, specificity, and accuracy of CSF mNGS in the UCSF cohort who had clinically diagnosed infections were 56.5%, 98.8%, and 90.5%, respectively. The sensitivity of CSF mNGS testing (56.5%) was statistically higher than that from all direct detection testing from CSF (44.8%, p = 0.004), direct detection testing from samples other than CSF (15.2%, p<0.001), and indirect serologic testing (34%, p<0.001). When only considering diagnoses made by direct detection of pathogens on CSF, sensitivity of mNGS was 80.7%. These results justify the incorporation of CSF mNGS testing as part of the routine diagnostic workup in hospitalized patients presenting with potential CNS infection.

Streptococcus pneumoniae (Spn) is a bacterial pathogen that causes a range of disease manifestations in children, from acute otitis media to pneumonia, septicemia, and meningitis. Primary Spn laboratory diagnostic identification methods include culture, antigen testing, single-plex real-time PCR, and syndromic PCR panels. However, each method lacks sensitivity, specificity, and/or cost efficiency. We developed and validated a quantitative, multiplex PCR assay that uses three Spn genomic targets (lytA, piaB, and SP2020) for improved sensitivity and specificity to detect Spn in pleural fluid (PF), bronchoalveolar lavage (BAL), tracheal aspirate (TA), and upper respiratory (UR, research only) samples. Validation testing included analytical sensitivity (limit of detection), specimen storage, analytical specificity (cross-reactivity), and accuracy studies. Limit of detection is 500 genome copies/mL in lower respiratory samples and 100 copies/mL in upper respiratory specimens, with quantification range of 1,000 to 10,000,000 copies/mL. Specimens can be stored frozen at least 60 days and Spn DNA is stable through 3 freeze-thaw cycles. No cross-reactivity was observed against 20 closely related microorganisms and/or microorganisms that can be detected in similar sample types, including Streptococcus pseudopneumoniae. In reference range testing, Spn was detected in 5 of 23 (21.7%) PF, 2 of 19 (10.5%) BAL, 1 of 20 (5.0%) TA, and 44 of 178 (24.7%) UR residual specimens. For accuracy studies, 98 specimens were tested and overall percent agreement with a qualitative, lytA-based comparator assay was 96.9% across all sample types. This multiplex, quantitative PCR assay is a sensitive and specific method for Spn detection in pediatric respiratory samples.

BackgroundInvasive mold infections (IMIs) such as aspergillosis, mucormycosis, fusariosis, and lomentosporiosis are associated with high morbidity and mortality, particularly in immunocompromised patients, with mortality rates as high as 40% to 80%. Outcomes could be substantially improved with early initiation of appropriate antifungal therapy, yet early diagnosis remains difficult to establish and often requires multidisciplinary teams evaluating clinical and radiological findings plus supportive mycological findings. Universal digital high resolution melting analysis (U-dHRM) may enable rapid and robust diagnosis of IMI. This technology aims to accomplish timely pathogen detection at the single genome level by conducting broad-based amplification of microbial barcoding genes in a digital polymerase chain reaction (dPCR) format, followed by high-resolution melting of the DNA amplicons in each digital reaction to generate organism-specific melt curve signatures that are identified by machine learning. MethodsA universal fungal assay was developed for U-dHRM and used to generate a database of melt curve signatures for 19 clinically relevant fungal pathogens. A machine learning algorithm (ML) was trained to automatically classify these 19 fungal melt curves and detect novel melt curves. Performance was assessed on 73 clinical bronchoalveolar lavage (BAL) samples from patients suspected of IMI. Novel curves were identified by micropipetting U-dHRM reactions and Sanger sequencing amplicons. ResultsU-dHRM achieved an average of 97% fungal organism identification accuracy and a turn-around-time of 4hrs. Pathogenic molds (Aspergillus, Mucorales, Lomentospora and Fusarium) were detected by U-dHRM in 73% of BALF samples suspected of IMI. Mixtures of pathogenic molds were detected in 19%. U-dHRM demonstrated good sensitivity for IMI, as defined by current diagnostic criteria, when clinical findings were also considered. ConclusionsU-dHRM showed promising performance as a separate or combination diagnostic approach to standard mycological tests. The speed of U-dHRM and its ability to simultaneously identify and quantify clinically relevant mold pathogens in polymicrobial samples as well as detect emerging opportunistic pathogens may provide information that could aid in treatment decisions and improve patient outcomes.

Metagenomic next-generation sequencing (mNGS) is a diagnostic tool allowing near universal pathogen detection directly from clinical specimens. Despite promising clinical data, broad adoption of mNGS has been hindered by high cost and reduced sensitivity relative to targeted nucleic acid amplification tests (NAATs). Recently, Ultima Genomics revealed the UG 100 NGS platform which advertises 10 billion reads per $2,400 sequencing wafer. By significantly lowering costs and improving sequencing depth, the historical value proposition of mNGS may be improved. This study evaluates the UG 100 sequencer for metagenomic pathogen detection from cerebrospinal fluid in suspected cases of meningitis and encephalitis. Of 28 specimens with a pathogen identified by routine clinical testing, reads matching to the known pathogen were identified in 93% (26/28) of cases. Near full-length genomes were recovered for three organisms (human herpesvirus-1, Streptococcus pneumonia, and Haemophilus influenzae), with the ability to detect putative antimicrobial resistance genes for H. influenzae. Recovery of Borrelia burgdorferi reads (6.1 RPM and 9.03 RPM) was achieved from clinical samples with late cycle threshold values (39.7 and 43.0, respectively). Limit of detection (LOD) studies demonstrated detection of HSV-1 and S. pneumoniae at 50 and 5 copies/mL, respectively, which is below the reported limit of detection for the orthogonal NAATs used in this study. Reducing sequencing costs and improving the analytical sensitivity removes two major hurdles for mNGS adoption by clinical laboratories. While these results are preliminary, they demonstrate a future in which mNGS may be more widely implemented. ImportanceMetagenomic next-generation sequencing has struggled to gain wider adoption for nearly a decade, due in part to concerns related to its high cost and reduced performance versus targeted molecular assays. This study demonstrates the ability of the UG100 sequencing platform to significantly reduce metagenomic sequencing costs (to approximately $12 per 50M reads) while maintaining highly sensitive pathogen detection rates. Improvements to cost and analytical performance may shift clinical metagenomics from an expensive test-of-last-resort to a front-line diagnostic for identifying infections.

BackgroundThis multi-year study (2014-19) compared identification of rare and unusual GNB by MALDI-TOF MS (VITEK(R) MS, bioMerieux, Laval Que.) to 16S rRNA gene sequencing (16S) according to our laboratories routine workflow; 16S is done if initial MALDI-TOF MS results were discordant, wrong or absent. Materials and MethodsGNB isolates were first analyzed by standard phenotypic methods and MALDI-TOF MS using direct deposit with full formic acid extraction; proteomics was repeated if no result occurred. Medically approved 16S analyses were done using fast protocols. Isolate sequences were analyzed using IDNS3 bacterial database (SmartGene, Lausanne, Switzerland). Results329 GNB isolates were recovered from 304 specimens; >1 isolate was recovered from 19(6%). 250(76%) NFGNBs, 62(19%) fGNBs, and 17(5%) CAMPB were mainly recovered from blood cultures (31.6%) and lower respiratory specimens (43%) (one-half were isolated from cystic fibrosis patients). Accurate genus vs. species identities were obtained for 67.2%/26% NFGNBs, 74.2%/53.2% fGNBs, and 22% CAMPB (with no discrepant species), respectively. Wrong or no results were obtained for 82(32.8%) NFGNB, 17(27.4%) fGNB, and 13(72.2%) CAMPB. Absent or misidentifications occurred for NFGNBs (33%), fGNBs (26%) and CAMPB (89%) due to absence of species in the instruments database. VITEK MS performance remained stable for NFGNBs and fGNBs but improved for CAMPB but with the addition of Campylobacter rectus and Campylobacter curvus to the database. ConclusionsVITEK(R) MS databases need to be continually updated to include an increasing number of rare and unusual GNBs causing invasive human infections. 16S remains important for identification of GNBs where proteomics fails.

Illumina sequencing of primary MGIT cultures is an established workflow in several reference mycobacteriology laboratories. Oxford Nanopore Technologies (ONT) provides real-time genetic sequencing yielding long reads which help resolve repetitive genomes and is being explored for in-house implementation within diagnostic laboratories. However, low DNA yields from primary MGIT cultures frequently limit the application of ONT workflows, due to high minimum DNA input requirements for library preparation. We evaluated a modified ONT workflow combining rapid, semi-automated DNA extraction from MGIT cultures with PCR-based whole-genome amplification, and compared its performance with Illumina sequencing for species identification and Mycobacterium tuberculosis complex (MTBC) single-nucleotide polymorphism (SNP) detection. A platformagnostic analysis pipeline enabled consistent human read removal, taxonomic assignment, and MTBC genomic characterisation. ONT sequencing data was subsampled at 1 h, 6 h, and 72 h to determine the earliest time point for reliable species identification. The concordance between sequencing platforms of species classification and MTBC lineage assignment was 95%. SNP agreement was high, with a mean of 1.0 and a median of 0 SNP differences between sequencing platforms after masking. These findings demonstrate the feasibility of PCR-amplified ONT sequencing as a reliable alternative for routine genomic characterisation of MGIT cultures. IMPORTANCERapid genomic characterisation of mycobacteria from primary MGIT cultures is valuable for timely and accurate clinical diagnosis. Although Illumina sequencing provides high sequence accuracy, its longer turnaround time and workflow complexity limit the rapid delivery of actionable results. Oxford Nanopore Technologies (ONT) sequencing enables continuous data generation and analysis, allowing real-time species identification and genomic characterisation. However, low DNA yield from primary MGIT cultures has limited the reliable application of ONT sequencing using standard extraction and PCR-free rapid library preparation methods. This study shows that combining semi-automated DNA extraction with PCR-based wholegenome amplification substantially improves ONT sequencing performance from primary MGIT cultures. The resulting increase in data yield enables more samples to be multiplexed and shorter sequencing run times while retaining comprehensive diagnostic information from a single whole-genome sequencing assay. Together, these improvements enable the practical implementation of ONT sequencing for routine mycobacterial diagnostics and may reduce both turnaround time and sequencing costs in clinical laboratories.

Phenotypic drug susceptibility testing (pDST) remains the gold standard for Mycobacterium tuberculosis complex drug resistance determination. Next generation sequencing technologies can identify heteroresistant populations at low frequencies, but little is known about the impact of heteroresistance on bedaquiline (BDQ) pDST results. We simulated heteroresistance using in vitro generated MmpR5 mutants mixed with the progenitor strain at various percentages (1-20%) and did pDST using MGIT960 culture (1 and 2 {micro}g/mL BDQ concentrations). Targeted Next Generation Sequencing (tNGS) was used to quantify the mutant sub-population in growth control tubes, which were expected to maintain the mutant: wild type proportion throughout the assay. Growth units of these growth control tubes were also comparable with minor differences in time-to-positivity between ratio mixtures. Only when intermediate results were considered could BDQ heteroresistance be detected at frequencies of approximately 1% by pDST at a critical concentration of 1 {micro}g/mL using BACTEC MGIT960 coupled with EpiCenter TBeXiST software. The ability of pDST, a widely available DST technique, to reveal the presence of BDQ-resistant subpopulations at the phenotypic testing stage could improve resistance determination and potentially reduce time to effective treatment. ImportanceMultidrug resistant tuberculosis (MDR-TB) is estimated to cause up to 19% of all antimicrobial resistance-attributable deaths worldwide. Further, the success rate for the treatment of drug-resistant TB, in the presence of adherence, is poor at only 68%. The advent of bedaquiline (BDQ) has revolutionized MDR-TB care, but BDQ resistance determination is hampered by several obstacles facing both phenotypic and genotypic testing. Specifically for phenotypic susceptibility testing, BDQ-resistant Mycobacterium tuberculosis isolates with variants in MmpR5, which may display minimal inhibitory concentration values just below the critical concentration or are present at low frequencies (heteroresistance; the presence of mixed mutant and wild-type populations within a specimen), are typically designated as susceptible. This may lead to prescription of an ineffective regimen and amplification of resistance. The BACTEC MGIT960 platform coupled with EpiCenter TBeXiST software for phenotypic testing, which is currently the only routinely used method of BDQ DST, can be used to derive more information about underlying resistant populations. We demonstrate how this is possible through the consideration of intermediate results (i.e., when growth units in a drug-containing tube reach the threshold for resistance but only after a further week of incubation). These intermediate results, commonly disregarded by TB laboratories, could lead to earlier detection of BDQ resistance. This is especially crucial when the genetic mechanism of resistance is unknown, a variant has not been associated with resistance in the interim, and in cases of heteroresistance.

BackgroundDiagnosis of Neisseria (N.) gonorrhoeae is dependent on nucleic acid amplification testing (NAAT), which is not available in resource-limited settings where the prevalence of infection is highest. Recent advances in molecular diagnostics leveraging the high specificity of CRISPR enzymes can permit field-deployable, point-of-care lateral flow assays. We previously reported on the development and in vitro performance of a lateral flow assay for detecting N. gonorrhoeae. Here we aimed to pair that assay with point-of-care DNA extraction techniques and assess the performance on clinical urine specimens. MethodsWe collected an additional urine specimen among individuals enrolling in an ongoing clinical trial at the Massachusetts General Hospital Sexual Health Clinic who presented with symptoms of urethritis or cervicitis (urethral or vaginal discharge, dysuria, or dyspareunia). We then assessed thermal, detergent, and combination DNA extraction conditions, varying the duration of heat at 95{degrees}C and concentration of Triton X. We assessed the efficacy of the various DNA extraction methods by quantitative polymerase chain reaction (qPCR). Once an extraction method was selected, we incubated samples for 90 minutes to permit isothermal recombinase polymerase amplification. We then assessed the performance of lateral flow Cas13a-based detection using our previously designed porA probe and primer system for N. gonorrhoeae detection, comparing lateral flow results with NAAT results from clinical care. ResultsWe assessed DNA extraction conditions on 3 clinical urine specimens. There was no consistent significant difference in copies per microliter of DNA obtained using more or less heat. On average, we noted that 0.02% triton combined with 5 minutes of heating to 95{degrees}C resulted in the highest DNA yield, however, 0.02% triton alone resulted in a quantity of DNA that was above the previously determined analytic sensitivity of the assay. Given that detergent-based extraction is more easily deployable, we selected that as our method for extraction. We treated 23 clinical specimens with 0.02% triton, which we added to the Cas13a detection system. We ran all lateral flow detections in duplicate. The Cas13a-based assay detected 8 of 8 (100%) positive specimens, and 0 of 15 negative specimens. ConclusionUsing point-of-care DNA extraction, isothermal amplification, and Cas13a-based detection, our point-of-care lateral flow N. gonorrhoeae assay correctly identified 23 clinical urine specimens as either positive or negative. Further evaluation of this assay among larger samples and more diverse sample types is warranted.

There remains a clinical need for better approaches to rapid drug susceptibility testing in view of the increasing burden of multidrug resistant tuberculosis. Binary susceptibility phenotypes only capture changes in minimum inhibitory concentration when these cross the critical concentration, even though other changes may be clinically relevant. We developed a machine learning system to predict minimum inhibitory concentration from unassembled whole-genome sequencing data for 13 anti-tuberculosis drugs. We trained, validated and tested the system on 10,859 isolates from the CRyPTIC dataset. Essential agreement rates (predicted MIC within one doubling dilution of observed MIC) were above 92% for first-line drugs, 91% for fluoroquinolones and aminoglycosides, and 90% for new and repurposed drugs, albeit with a significant drop in performance for the very few phenotypically resistant isolates in the latter group. To further validate the model in the absence of external MIC datasets, we predicted MIC and converted values to binary for an external set of 15,239 isolates with binary phenotypes, and compare their performance against a previously validated mutation catalogue, the expected performance of existing molecular assays, and World Health Organization Target Product Profiles. The sensitivity of the model on the external dataset was greater than 90% for all drugs except ethionamide, clofazimine and linezolid. Specificity was greater than 95% for all drugs except ethambutol, ethionamide, bedaquiline, delamanid and clofazimine. The proposed system can provide quantitative susceptibility phenotyping to help guide antimicrobial therapy, although further data collection and validation are required before machine learning can be used clinically for all drugs.

BackgroundA prerequisite to rapid molecular detection of pathogens causing bloodstream infections is an efficient, cost effective and robust DNA extraction solution. We describe methods for microbial DNA extraction direct from positive blood culture broths, suitable for metagenomic sequencing and the application of machine-learning based tools to predict antimicrobial susceptibility. MethodsProspectively collected culture-positive blood culture broths with Gram-negative bacteria, were directly extracted using various commercially available kits. We compared methods for efficient inhibitor removal, avoidance of DNA shearing or degradation, to achieve DNA of high quality and purity. Bacterial species identified via whole-genome metagenomic sequencing (Illumina, MiniSeq) from blood culture extracts were compared to conventional methods from cultured isolates (Vitek MS). A machine-learning algorithm (AREScloud) was used to predict susceptibility against commercially available antibiotics, compared to susceptibility testing (Vitek 2) and other commercially available rapid diagnostic instruments (Accelerate Pheno and BCID). ResultsA two-kit method using a modified MolYsis Basic kit (for host DNA depletion) and extraction using Qiagen DNeasy UltraClean microbial kits resulted in optimal extractions appropriate for multiple molecular applications, including PCR, short-read and long-read sequencing. DNA extracts from 40 blood culture broths were included. Taxonomic profiling by direct metagenomic sequencing matched species identification by conventional methods in 38/40 (95%) of samples, with two showing agreement to genus level. In two polymicrobial samples, a second organism was missed by sequencing. Whole genome sequencing antimicrobial susceptibility testing (WGS-AST) models were able to accurately infer profiles for 6 common pathogens against 17 antibiotics. Overall categorical agreement (CA) was 95%, with 11% very major errors (VME) and 3.9% major errors (ME). CA for WGS-AST was >95% for 5/6 of the most common pathogens (E. coli, K. pneumoniae, P. mirabilis, P. aeruginosa and C. jejuni) while it was lower for K. oxytoca (66.7%), likely due to the presence of inducible cephalosporinases. Performance of WGS-AST was sub-optimal for uncommon pathogens (e.g. Elizabethkingia) and some combination antibiotic compounds (e.g. ticarcillin-clavulanate). Time to pathogen identification and resistance gene detection was fastest with BCID (1 h from blood culture positivity). Accelerate Pheno provided a rapid MIC result in approximately 8 h. While Illumina based direct metagenomic sequencing did not result in faster turn-around times compared conventional methods, use of real-time nanopore sequencing may allow faster data acquisition. ConclusionsThe application of direct metagenomic sequencing from positive blood culture broths is a feasible approach and solves some of the challenges of sequencing from low-bacterial load samples. Machine-learning based algorithms are also accurate for common pathogen / drug combinations, although additional work is required to optimise algorithms for uncommon species and more complex resistance genotypes, as well as streamlining methods to provide more rapid sequencing results.

BackgroundCurrent diagnostic techniques are inadequate for rapid microbial diagnosis and optimal management of patients with suspected sepsis. We assessed the clinical impact of three powerful molecular diagnostic methods. MethodsWith blood samples from 200 consecutive patients with suspected sepsis, we evaluated 1) metagenomic shotgun sequencing together with a Bayesian inference approach for contaminant sequence removal, for detecting bacterial DNA; 2) viral capture sequencing; and 3) transcript-based host response profiling for classifying patients as infected or not, and if infected, with bacteria or viruses. We then evaluated changes in diagnostic decision-making among three expert physicians by unblinding the results of these methods in a staged fashion. ResultsMetagenomic shotgun sequencing confirmed positive blood culture results in 14 of 26 patients. In 17 of 200 patients, metagenomic sequencing and viral capture sequencing revealed organisms that were 1) not detected by conventional hospital tests within 5 days after presentation, and 2) classified as of probable clinical relevance by physician consensus. Host response profiling led at least two of three physicians to change their diagnostic decisions in 46 of 100 patients. The data suggested possible bacterial DNA translocation in 8 patients who were originally classified by physicians as noninfected and illustrate how host response profiling can guide interpretation of metagenomic shotgun sequencing results. ConclusionsThe integration of host response profiling, metagenomic shotgun sequencing, and viral capture sequencing enhances the utility of each, and may improve the diagnosis and management of patients with suspected sepsis.

Isoniazid (INH) is a critical antibiotic used worldwide for treatment and prophylaxis of tuberculosis. Drug resistance (DR) to INH is the single most common type of DR, mediated by multiple genes/loci including katG, inhA, mabA, mabA-inhA and the oxyR-ahpC intergenic region. Over the course of 6 years, we performed a 2-phase study of 3,696 Mycobacterium tuberculosis complex (MTBC) strains aiming to determine the molecular basis of INH resistance and assess whole genome sequencing (WGS) for predicting resistance. In phase 1, we performed a side-by-side study including 1,767 strains with paired phenotypic drug susceptibility testing (DST) and genotypic DST. We found WGS capable of accurately predicting INH resistance with sensitivity of 90.3%, and specificity of 99.8%. The negative predictive value of WGS for INH susceptibility was 98.8%. Based on these findings, we developed a molecular testing algorithm where phenotypic DST was reduced and applied this new testing algorithm in phase 2 to 1,929 MTBC strains, resulting in streamlined testing, reduced cost and decreasing turnaround time (TAT). The prevalence of INH resistance among MTBC strains in New York was found to be 10.2%. Of the 3,696 isolates tested, 337 were predicted INH resistant by WGS. Of 41 additional strains exhibiting phenotypic INH resistance, 38 were found to have mutations in genes known to be associated with INH resistance. This study demonstrates the utility of WGS as a molecular tool for predicting INH DR and shows that the vast majority of INH resistance in MTBC has a molecular basis in known resistance loci.

Realising the promise of genomics to revolutionise routine AMR diagnosis and surveillance has been a long-standing challenge in clinical and public health microbiology. We have directly addressed this issue by creating and validating abritAMR, an ISO-accredited bioinformatics platform for genomics-based bacterial AMR gene detection. abritAMR utilises the NCBI AMRFinderPlus for detection of AMR genes and mutations, with additional features to classify AMR determinants into an antibiotic class. We validated abritAMR by comparing with multiplex PCR or gold-standard reference genomes, together representing 1500 different bacteria across 29 genera and covering 415 antibiotic resistance alleles. We also assessed inference of phenotypic resistance by comparing genomic predictions with agar dilution results for 864 Salmonella spp. Performance of abritAMR was excellent, detecting AMR genes with 99.9% accuracy (95% CI 99.9-99.9%), 97.9% sensitivity (95% CI 97.5-98.4%) and 100% specificity (100-100%). Phenotypic inference of resistance for Salmonella spp. was equally impressive, with 98.9% accuracy (98.7-99.1%). Validation data were submitted to the governing authority and ISO15189 accreditation was achieved. Implementation of abritAMR resulted in streamlined bioinformatics and reporting pathways, and it was readily updated and re-verified with database revisions or changes in reporting requirements. abritAMR is publicly and freely available to assist clinical and public health microbiology laboratories everywhere harness the power of AMR genomics in their professional practice.

The propensity for M. tuberculosis to develop resistance and the lack of clinical tools for the rapid determination of such resistance has long significantly complicated tuberculosis (TB) therapeutics. Targeted next-generation sequencing (NGS) has improved our understanding of the genetic basis and identification of drug-resistant TB. However, to achieve accurate results reliable enough for clinical implementation, high-quality M. tuberculosis DNA must be extracted from patient-derived samples within high burden routine laboratory workflows. In advance of a large cluster RCT in the Western Cape of South Africa evaluating the Deeplex Myc-TB targeted NGS assay (GenoScreen; Lille, France), we sought to compare DNA extraction methods for both early MGIT culture-positive samples and processed patient sputum. Given the lack of reference standard method, we assessed a representative set of DNA extraction protocols, including the GenoScreen-recommended method, in parallel in South Africa and at UC San Francisco. Our findings provide preliminary insights into an optimal DNA extraction method for the utilization of Deeplex Myc-TB in routine laboratory settings and can inform future experiments evaluating newer generation assays.

Mycobacteria that form the Mycobacterium tuberculosis complex are responsible for deadly tuberculosis in animals and patients. Identification of these pathogens at the species level is of primary importance for treatment and source tracing, and currently relies on DNA analysis, including whole genome sequencing (WGS), which takes a whole day. In this study, we report on the unprecedented identification of the M. tuberculosis complex species using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS), with WGS as the comparative gold standard. In a first step, an optimised peptide extraction applied to 24 isolates otherwise identified in three of the 11 M. tuberculosis complex species by WGS, yielded 94 MALDI-TOF spectra which clustered according to WGS identification. In a second step, 70/74 (95%) other isolates were correctly identified at the species level by this clustering method. This study is the first to report a MALDI-TOF-MS method of identification of M. tuberculosis complex mycobacteria at the species level and is easily implantable in clinical microbiology laboratories.

BackgroundGiven the cost and unclear clinical impact of metagenomic next-generation sequencing (mNGS), laboratory stewardship may improve utilization. This study examines mNGS results from two academic medical centers employing different stewardship approaches. Methods80 mNGS orders (54 CSF and 26 plasma) were identified from 2019 to 2021 at the University of Washington (UW), which requires director-level approval for mNGS orders, and the University of Utah (Utah), which does not restrict ordering. The impact of mNGS results and the relationship to traditional microbiology orders were retrospectively evaluated. Results19% (10/54) CSF and 65% (17/26) plasma studies detected at least one organism. Compared to CSF results, plasma results were more frequently clinically significant (23% vs 7%) and led to more novel diagnoses (15% vs 0%). Results affecting antibiotic management were more common for plasma than CSF (32% vs. 2%). Stewardship practices were not associated with statistically significant differences in results or antimicrobial management. The number and cost of traditional microbiology tests at UW was greater than Utah for CSF mNGS testing (UW: 46 tests, $6237; Utah: 26 tests, $2812; p<0.05) but similar for plasma mNGS (UW: 31 tests, $3975; Utah: 21 tests, $2715; p=0.14). mNGS testing accounted for 30-50% of the total microbiology costs. ConclusionsImproving the diagnostic performance of mNGS by stewardship remains challenging due to low positivity rates and difficulties assessing clinical impact. From a fiscal perspective, stewardship efforts should focus on reducing testing in low-yield populations given the high costs of mNGS relative to overall microbiology testing expenditures.

Bacillus paranthracis was formally defined as a species in 2017, after decades of carrying the name "emetic B. cereus" based on cereulide production and clustering within B. cereus sensu lato phylogenetic group III. Commonly associated with foodborne intoxication, reports rarely link B. paranthracis to non-foodborne clinical illness. As such, the new taxonomy and close resemblance of the name to the biothreat pathogen Bacillus anthracis cause confusion in diagnostic and public health settings. To address this issue, B. paranthracis clinical strains (n=20) from the CDC collection were tested with microbiological methods used for identification of B. anthracis and antimicrobial susceptibility testing. Some B. paranthracis phenotypes were similar to B. anthracis, however others were inconsistent across strains. Like B. anthracis: 3 strains tested capsule positive, 5 were non-hemolytic on blood agar, and 9 non-motile. All B. paranthracis strains were resistant to gamma phage lysis, which differentiated them from B. anthracis. Treatment regimens for B. paranthracis infections are not well established, as antimicrobial therapy is not indicated for emetic intoxication caused by B. paranthracis. Notably, six B. paranthracis strains had elevated minimal inhibitory concentrations to anthrax-recommended antibiotics: one for ciprofloxacin, three for doxycycline and tetracycline, and two for clindamycin. Rapid MinION sequencing was assessed for antimicrobial resistance detection prediction but had limited value when using PiMA v.1. These microbiological observations and susceptibility profiles of B. paranthracis expand our understanding of this pathogen, strengthening our ability to differentiate this bacterium from B. anthracis to improve diagnosis and patient outcomes. IMPORTANCEThis study describes in vitro characterization of 20 archived clinical strains of B. paranthracis, an opportunistic pathogen identified more frequently in recent reports. Our findings highlight phenotypic differences and similarities between B. paranthracis and B. anthracis using standard microbiological methods and drug susceptibility profiling. We also assess a rapid B. anthracis specific MinION long read genome sequencing workflow with B. paranthracis. This report highlights the overlapping morphological features shared by B. paranthracis and B. anthracis to improve future laboratory diagnosis and strengthen anthrax preparedness. This article will effectively reach an audience of public health professionals and microbiologists strengthening anthrax preparedness.