Journal of Clinical Microbiology最新文献

Left-ventricular assist devices (LVADs) are increasingly used as a bridge to heart transplantation and destination therapy. These devices, especially the driveline, are susceptible to difficult-to-treat infections, associated with high morbidity and mortality rates. Staphylococcus aureus (S. aureus) is a major causative pathogen of LVAD infections. Antibiotic resistance and biofilm formation can complicate the treatment of these infections. A novel in vitro assay was developed to study the antibiotic susceptibility of S. aureus biofilm grown on LVAD drivelines. Besides antibiotic monotherapy, the effect of various antibiotics combined with rifampicin was studied. Additionally, we explored the efficacy of four individual phages and phage-antibiotic combinations as potential treatment strategies. Our data showed a decrease of susceptibility of the S. aureus biofilms to antibiotic monotherapy compared to planktonic S. aureus. With only rifampicin and erythromycin monotherapy resulting in full bacterial clearance. Combining antibiotics with rifampicin showed similar antimicrobial efficacy against S. aureus biofilms as rifampicin monotherapy. While both individual phages and a phage cocktail were effective against planktonic bacteria, phage efficacy was limited against S. aureus in biofilm. Combining phages with antibiotics did not clearly improve treatment efficacy, compared to antibiotic monotherapy. Contrarily, it even increased bacterial growth when phage administration preceded antibiotic treatment. Here, both antibiotic- and phage monotherapy showed reduced efficacy on LVAD-driveline biofilms. Additionally, phages did not show an additive value to antibiotic treatment of LVAD driveline infections. Further studies are needed to elucidate optimal treatment strategies for LVAD-driveline infections.IMPORTANCECurrent treatment strategies for S. aureus LVAD-driveline infections are based on in vitro antibiotic susceptibility of planktonic bacteria. However, LVAD infections are most often biofilm-related, which decreases antibiotic susceptibility significantly, resulting in discrepancies between in vitro antibiotic susceptibility and in vivo treatment success. Here, we have developed a novel in vitro assay to determine antibiotic susceptibility of S. aureus biofilm, grown in conditions relevant to LVAD-driveline infections. Next to antibiotic susceptibility, the susceptibility of this biofilm to bacteriophage mono- and combination treatment with antibiotics was evaluated as an alternative treatment strategy. In the future, this assay can be used to provide a better insight in in vivo antibiotic- and bacteriophage susceptibility of LVAD-driveline biofilms. Thereby improving in vivo treatment strategies for LVAD-driveline infections.

Providing timely and accurate antimicrobial susceptibility testing (AST) results is a crucial component of clinical microbiology practice. Commercial rapid AST (RAST) is an emerging and quickly expanding area. These phenotypic RAST systems use various novel methods to monitor bacterial growth and replication in order to shorten the duration of time required for testing. Implementation of RAST has the potential to expedite antimicrobial therapeutic optimization, which can improve patient care. This minireview describes the current state of commercial phenotypic RAST including tests designed to report antimicrobial susceptibilities directly from clinical specimens.

The reported human infections with the emerging zoonotic pathogen Streptococcus parasuis are steadily rising. Rapid and standardized genotyping tools specific to S. parasuis are critically needed for epidemiological surveillance and identification of strains with zoonotic potential. This study developed a whole-genome sequence (WGS)-based typing strategy, encompassing average nucleotide identity, a minimum core genome (MCG) typing scheme, and a multilocus sequence typing (MLST) scheme using 255 S. parasuis genomes isolated from eight countries between the 1980s and 2024. The S. parasuis population was categorized into 12 MCG clusters based on 72,172 SNPs in non-recombining regions distributed across an MCG comprising 607 genes, forming two distinct lineages. The rapid MCG typing program accurately assigned 92.5% of S. parasuis genomes to their corresponding MCG clusters by identifying 4,509 cluster/subcluster-specific SNPs. To elucidate the clonal relationships among S. parasuis genomes, an MLST scheme was developed, defining 161 sequence types (STs) based on the allelic profiles of seven housekeeping loci (aroA, cpn60, gki, mutS, sdhA, recA, and thrA). Thirty-two STs that shared identical alleles at 6 loci were assigned to 10 complex clones, whereas 100 STs that shared identical alleles at 4 or more loci were grouped into 9 ST clades. The MCG typing scheme and the MLST scheme demonstrated sufficient discriminatory power, with Simpson's diversity index values of 0.8864 and 0.9821, respectively. This study characterized the S. parasuis population and provided a rapid, reproducible, and expandable WGS-based typing strategy for taxonomic identification, epidemiological surveillance, and evaluation of the zoonotic potential of S. parasuis.IMPORTANCEOur study provides valuable insights for developing effective prevention and control strategies for Streptococcus parasuis infections, by revealing the structural characteristics and phylogenetic relationship of S. parasuis population, by developing a whole-genome sequence-based typing strategy applicable for epidemiological surveillance, transmission investigation, and zoonotic potential evaluation.

Metabolic profiling of respiratory samples from individuals infected and uninfected with respiratory viral infections may identify biomarker signatures that complement routine clinical diagnostic testing and offer unique insights into pathophysiology. We used liquid chromatography quadrupole time-of-flight mass spectrometry to generate untargeted metabolomic profiles and identified top biomarker signatures differentiating severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) positive from negative samples via machine learning. We then adapted these signatures to liquid chromatography-tandem mass spectrometry for targeted profiling and assessed classification performance, including samples positive for other respiratory viruses and negative for viral testing. A total of 1,226 samples were tested, including 521 positive samples for SARS-CoV-2, 97 for influenza A, 96 for respiratory syncytial virus (RSV), 211 for other respiratory viruses, and 301 negative samples. The top-performing model was the Light Gradient Boosting Model, which showed an area under the receiver operating characteristic curve (AUC) of 0.99 (95% confidence interval [CI], 0.99-1.00), sensitivity of 0.96 (95% CI, 0.91-0.99), and specificity of 0.95 (95% CI, 0.90-0.97). A separate machine learning analysis investigating the performance by viral subtype showed high performance for the identification of influenza A virus with an AUC of 0.97 (95% CI, 0.94-0.99) and RSV with an AUC of 0.99 (95% CI, 0.97-1.00). The two features with the highest ranking were identified as 3-oxo-heneicosanoic acid and 2-(4-hydroxyphenyl) ethanol. These findings extend our understanding of the metabolic impact of respiratory viral infections and support the potential of metabolomics to complement routine clinical diagnostic methods.IMPORTANCEMolecular testing has greatly improved how viruses are diagnosed; however, gaps remain, including limited sensitivity directly from specimens and inability to differentiate active from resolved infection. In this study, we investigated the use of a distinct diagnostic approach, mass spectrometry for detection of metabolites (small molecules) combined with machine learning analysis, for the diagnosis of SARS-CoV-2 and other respiratory viruses. We demonstrated strong performance of this approach directly from upper respiratory swab samples to differentiate SARS-CoV-2-infected versus uninfected individuals. Extension of this approach to influenza and RSV maintained a high level of performance. This research suggests that mass spectrometry-based infectious disease diagnostic testing has clinical potential and that these metabolomic features may reveal novel host-pathogen interactions and therapeutic targets. Applying a similar approach to prospective, multisite cohorts of patients with other infectious diseases carries potential to extend our understanding of the metabolic pathways involved in the host response to infection.

Drug-resistant tuberculosis (TB) remains a primary global health concern. Multidrug-resistant TB is defined by resistance to at least rifampicin (RIF) and isoniazid (INH), the two key drugs used in TB treatment. The BD MAX Multi-Drug Resistant Tuberculosis (BD MAX) assay is a fully automated real-time PCR platform recommended by the World Health Organization for the initial diagnosis of TB and RIF and INH resistance (RIF-R and INH-R) directly from pulmonary clinical samples. This study aimed to assess the off-label performance of BD MAX in clinical M. tuberculosis complex (MTBC) isolates under routine laboratory conditions. The assay was first validated using non-tuberculous mycobacteria (NTM) and MTBC isolates with known mutations. For real-world validation, it was compared to the GenoType MTBDRplus by testing 1,440 clinical isolates prospectively. The BD MAX assay correctly excluded MTBC from all NTM cultures. Among MTBC isolates with known mutations, it identified 19 of 20 RIF-R isolates and 14 of 15 INH-R isolates. In prospective testing, BD MAX achieved 99.6% sensitivity (1,403/1,409), 96.8% specificity (30/31), and 99.5% overall accuracy (1,433/1,440) for MTBC detection. For drug resistance detection, it showed 95.2% (40/42) concordance for RIF, 96.8% (30/31) for INH, and 81.3% (13/16) for MDR when compared to MTBDRplus. Discrepancies between MTBDRplus and BD MAX included heteroresistant cases and unreportable resistance results by BD MAX due to infrequent mutations or low bacterial load. Overall, this study confirms BD MAX as an accurate and reliable tool for MTBC detection and drug resistance profiling in clinical isolates in high-volume TB laboratories.IMPORTANCEThis study highlights the importance of the BD MAX Multi-Drug Resistant Tuberculosis assay (BD MAX) applied in clinical isolates for the detection of multidrug-resistant tuberculosis (MDR-TB), i.e., Mycobacterium tuberculosis resistance to rifampicin and isoniazid. TB is a global health issue, and drug-resistant TB makes treatment more difficult, favoring transmission and disease amplification. The BD MAX platform offers a faster and more automated way to detect TB and drug resistance. The study showed that BD MAX, applied off-label in clinical isolates, accurately identified TB and resistance to rifampicin and isoniazid, with results comparable to those of the widely used line probe assay. This is significant in a high-volume laboratory because it is more straightforward and more rapid than the line probe assay. BD MAX showed some limitations, especially in detecting rare mutations and in cases of low bacterial levels. Overall, this tool could improve TB care, especially in high-volume laboratories.

Timely and accurate diagnosis is essential for the effective treatment of Haemophilus influenzae (HI) infection. Notably, a rapid point-of-care testing (POCT) method for the diagnosis of HI DNA is still lacking. The aim of this study was to establish a one-pot detection device for HI DNA detection using CRISPR/Cas13a that would be applicable for POCT. We established a two-step polymerase chain reaction (PCR)-CRISPR assay, a two-step recombinase-aided amplification (RAA)-CRISPR assay, and a one-pot RAA-CRISPR assay. Additionally, reagent lyophilization, rapid lysis technology, and a one-pot detection device were integrated to construct an extraction-free one-pot detection device, named EFORCA (extraction-free one-pot RAA-CRISPR/Cas13a assay). Validation was performed on 90 simulated samples and 77 clinical samples. The two-step PCR/RAA-CRISPR assay for HI DNA detection was established and optimized, with a detection limit of 1 copy/μL and 100% specificity. The sensitivity and specificity of the two-step PCR-CRISPR assay for the 90 simulated clinical samples were 96.7% and 95%, respectively, and for the 77 clinical samples, 97.5% and 100%, respectively. The one-pot RAA-CRISPR assay and the EFORCA detected 50 and 25 CFU/mL HI in bacterial suspensions within 30 min, respectively. The valuation results for 77 clinical samples demonstrated that the sensitivity of both methods was 95%, which was greater than the sensitivity of quantitative real-time PCR (qPCR) (92.5%) with the same specificity of 100%. We developed an extraction-free one-pot RAA-CRISPR/Cas13a assay for HI detection, which effectively performs a POCT test and is a valuable tool for the early detection and monitoring of HI infection.IMPORTANCETimely and accurate diagnosis is essential for the effective treatment of Haemophilus influenzae (HI) infection. Notably, a rapid point-of-care testing (POCT) method for the diagnosis of HI DNA is still lacking. In this study, sensitive two-step polymerase chain reaction (PCR)-CRISPR and recombinase-aided amplification (RAA)-CRISPR assays were developed, followed by the establishment of the one-pot RAA-CRISPR assay through integration of RAA, CRISPR, and rapid lysis for HI detection. Additionally, reagent lyophilization, rapid lysis technology, and a one-pot detection device were integrated to construct the extraction-free one-pot RAA-CRISPR/Cas13a assay (EFORCA). With its high sensitivity, specificity, rapid turnaround time, and operational simplicity, this assay shows great potential as a practical diagnostic tool for HI infection in small laboratory settings.

A sustained outbreak of H5N1 influenza virus among wild fowl and domestic livestock has caused more than 70 zoonotic infections in humans in North America, including two deaths. The United States Centers for Disease Control and Prevention has recommended rapid H5 subtyping for all hospitalized cases with influenza A virus infection to enable prompt initiation of antiviral treatment, as well as infection prevention and implementation of public health measures to control spread. To address these needs, we developed a qualitative multiplex RT-qPCR assay to subtype H5 influenza virus in nasal, nasopharyngeal, and conjunctival specimens with a limit of detection of 250 copies/mL. No cross-reactivity was observed with other common respiratory viruses, including seasonal H3N2 and H1N1 influenza A viruses. We retrospectively subtyped 590 influenza A virus-positive clinical specimens with Ct values less than 31 processed by University of Washington labs between March 2024 and February 2025, including 512 specimens collected during the 2024-2025 influenza season, and detected no H5 positives. After clinical implementation, we performed 150 clinically ordered H5 subtyping tests between February and April 2025 and again detected no positives. This work enhances clinical pandemic preparedness activities and highlights the exceedingly low prevalence of H5N1 influenza virus during the 2024-2025 respiratory season.IMPORTANCEThe spread of H5N1 influenza virus in the United States has led to the culling of almost 200 million birds, infected cow herds across 17 states, and resulted in 70 human infections as of July 2025. Rapid PCR subtyping of H5 influenza virus is critical to inform hospital infection prevention and public health to enable containment of viral transmission. Here, we report the design, validation, and clinical implementation of a qualitative multiplex H5-subtyping RT-qPCR assay for nasopharyngeal, nasal, and conjunctival swab specimens. Additionally, we offer the largest reported study of H5 subtyping of influenza A virus-positive specimens in the United States to date. No H5 infections were detected in 740 samples collected between March 2024 and April 2025 from patients with confirmed influenza A virus infection in a large academic medical system in Seattle, WA.

Aminoglycoside resistance mediated by 16S rRNA methyltransferases poses a growing threat in both human and veterinary medicine. Here, we conducted a retrospective genomic study of Enterobacterales isolates (n = 789) collected from clinical samples at a veterinary teaching hospital in Spain between 2011 and 2020. We identified four high-level aminoglycoside-resistant ST171 Enterobacter hormaechei subsp. xiangfangensis isolates carrying the armA gene, all from horses. Using Illumina and Nanopore sequencing, we determined that armA was located on a 70 kb IncR plasmid, also carrying other resistance genes such as msr(E), mph(E), bla_DHA-1, and qnrB4, embedded within a Tn1548-like element. Genomic comparisons indicated that the IncR plasmid was linked to a 2008-2010 ST11 Klebsiella pneumoniae outbreak in companion animals at the same hospital, with >95% sequence plasmid identity. Although the IncR plasmid lacked conjugative genes, it was mobilizable in vitro via co-resident conjugative plasmids. To probe for an environmental reservoir, we sampled three horse stalls in 2022 and recovered 19 armA-positive isolates (E. hormaechei, Klebsiella pneumoniae, and Mixta calida) whose IncR plasmids were nearly identical to that found in clinical clones. Broader analysis of 1,330 IncR plasmids from the genomic plasmid database PLSDB revealed that most were mobilizable, frequently co-integrated with other replicons, and carried diverse resistance genes, though armA was uncommon. These findings demonstrate that non-conjugative IncR plasmids can persist in the environment and be horizontally disseminated to clinical isolates over a long period of time, underscoring the need for routine, plasmid-focused genomic surveillance in veterinary healthcare settings within a One Health framework.IMPORTANCEThe spread of antimicrobial resistance threatens both human and animal health. In veterinary hospitals, bacteria can share resistance genes not only through direct transmission but also via mobile plasmids that persist in the environment. In this study, we uncovered a decade-long persistence of a non-conjugative IncR plasmid carrying the armA gene, which confers high-level aminoglycoside resistance, in a Spanish veterinary teaching hospital. This plasmid was found in clinical isolates of Enterobacter hormaechei, Klebsiella pneumoniae, and Mixta calida from horses and from the hospital environment. Our findings show that even plasmids lacking self-transfer capability can be maintained and disseminated across bacterial species over many years. These results highlight the need for routine genomic surveillance of plasmids in veterinary healthcare settings to prevent long-term environmental reservoirs from fueling recurrent outbreaks.