Metagenomic next-generation sequencing (mNGS) offers an agnostic approach for emerging pathogen detection directly from clinical specimens. In contrast to targeted methods, mNGS also provides valuable information on the composition of the microbiome and might uncover coinfections that may associate with disease progression and impact prognosis. To evaluate the use of mNGS for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and/or other infecting pathogens, we applied direct Oxford Nanopore long-read third-generation metatranscriptomic and metagenomic sequencing. Nasopharyngeal (NP) swab specimens from 50 patients under investigation for CoV disease 2019 (COVID-19) were sequenced, and the data were analyzed by the CosmosID bioinformatics platform. Further, we characterized coinfections and the microbiome associated with a four-point severity index. SARS-CoV-2 was identified in 77.5% (31/40) of samples positive by RT-PCR, correlating with lower cycle threshold (Ct) values and fewer days from symptom onset. At the time of sampling, possible bacterial or viral coinfections were detected in 12.5% of SARS-CoV-2-positive specimens. A decrease in microbial diversity was observed among COVID-19-confirmed patients (Shannon diversity index, P = 0.0082; Chao richness estimate, P = 0.0097; Simpson diversity index, P = 0.018), and differences in microbial communities were linked to disease severity (P = 0.022). Furthermore, statistically significant shifts in the microbiome were identified among SARS-CoV-2-positive and -negative patients, in the latter of whom a higher abundance of Propionibacteriaceae (P = 0.028) and a reduction in the abundance of Corynebacterium accolens (P = 0.025) were observed. Our study corroborates the growing evidence that increased SARS-CoV-2 RNA detection from NP swabs is associated with the early stages rather than the severity of COVID-19. Further, we demonstrate that SARS-CoV-2 causes a significant change in the respiratory microbiome. This work illustrates the utility of mNGS for the detection of SARS-CoV-2, for diagnosing coinfections without viral target enrichment or amplification, and for the analysis of the respiratory microbiome. IMPORTANCE SARS-CoV-2 has presented a rapidly accelerating global public health crisis. The ability to detect and analyze viral RNA from minimally invasive patient specimens is critical to the public health response. Metagenomic next-generation sequencing (mNGS) offers an opportunity to detect SARS-CoV-2 from nasopharyngeal (NP) swabs. This approach also provides information on the composition of the respiratory microbiome and its relationship to coinfections or the presence of other organisms that may impact SARS-CoV-2 disease progression and prognosis. Here, using direct Oxford Nanopore long-read third-generation metatranscriptomic and metagenomic sequencing of NP swab specimens from 50 patients under investigation for COVID-19, we detected SARS-CoV-2 sequences by applying the CosmosID bioinformatics platform. Further, we characterized coinfections and detected a decrease in the diversity of the microbiomes in these patients. Statistically significant shifts in the microbiome were identified among COVID-19-positive and -negative patients, in the latter of whom a higher abundance of Propionibacteriaceae and a reduction in the abundance of Corynebacterium accolens were observed. Our study also corroborates the growing evidence that increased SARS-CoV-2 RNA detection from NP swabs is associated with the early stages of disease rather than with severity of disease. This work illustrates the utility of mNGS for the detection and analysis of SARS-CoV-2 from NP swabs without viral target enrichment or amplification and for the analysis of the respiratory microbiome.

Background: Cefiderocol antimicrobial susceptibility testing (AST) poses challenges because of its unique mechanism of action (i.e., requiring an iron depleted state) and due to differences in interpretative criteria by the Clinical and Laboratory Standards Institute (CLSI), U.S. Food and Drug Administration (FDA), and European Committee of Antimicrobial Susceptibility Testing (EUCAST). Our objective was to compare cefiderocol disk diffusion methods (DD) to broth microdilution (BMD) for AST of Gram-negative bacilli (GNB). Methods: Cefiderocol AST was performed on consecutive carbapenem-resistant Enterobacterales (CRE; 58) and glucose-non-fermenting GNB (50) isolates by BMD (lyophilized panels; Sensititer, Thermo Fisher) and DD (30 μg; Research Use Only [RUO] MASTDISCS and FDA-cleared HardyDisks). Results were interpreted using investigational CLSI, FDA, and EUCAST breakpoints (BPs). Categorical agreement (CA), minor errors (mE), major errors (ME), and very major errors (VME) were calculated for DD methods. Results: The susceptibility of all isolates by BMD ranged from 72% (FDA), 75% (EUCAST) and 90% (CLSI). For DD methods, EUCAST BPs demonstrated lower susceptibility at 65% and 66%, compared to 74% and 72% (FDA), and 87% and 89% (CLSI) by HardyDisks and MASTDISCS, respectively. CA ranged from 75% to 90%, with 8-25% mE, 0-19% ME, and 0-20% VME and varied based on disk, GNB, and BPs evaluated. Both DD methods performed poorly for Acinetobacter baumannii complex. Conclusions: There is considerable variability when interpreting cefiderocol ASTs using CLSI, FDA, and EUCAST breakpoints. DD offers a convenient, alternative approach to BMD methods for cefiderocol AST testing, with the exception of A. baumannii complex isolates.

Next-generation sequencing (NGS) workflows applied to bronchoalveolar lavage (BAL) fluid specimens could enhance the detection of respiratory pathogens, although optimal approaches are not defined. This study evaluated the performance of the Respiratory Pathogen ID/AMR (RPIP) kit (Illumina, Inc.) with automated Explify bioinformatic analysis (IDbyDNA, Inc.), a targeted NGS workflow enriching specific pathogen sequences and antimicrobial resistance (AMR) markers, and a complementary untargeted metagenomic workflow with in-house bioinformatic analysis.