Editor's Choice - Validation of the Management of Aortic Graft Infection Collaboration (MAGIC) Criteria for the Diagnosis of Vascular Graft/Endograft Infection: Results from the Prospective Vascular Graft Cohort Study.

OBJECTIVE: The timely management of vascular graft/endograft infection (VGEI) is crucial to a favourable outcome, yet can be challenging as there is no validated gold standard diagnostic test. Recently, a new case definition has been proposed by the Management of Aortic Graft Infection Collaboration (MAGIC) to close the diagnostic gap. The aim of this study was to validate the MAGIC criteria as a suggested diagnostic standard for the diagnosis of suspected VGEI in the prospective Vascular Graft Cohort study (VASGRA). METHODS: VASGRA is an open, prospective, observational cohort study. Prospective participants in VASGRA between 2013 and 2019 were included (257 patients; 137 with VGEI). The accuracy of the MAGIC criteria for a diagnosis of VGEI was evaluated retrospectively by calculating the sensitivity and specificity vs. the consensually adjudicated VASGRA infection status. RESULTS: The VASGRA cohort categorised 137 (53.3%) patients as "diseased" and 120 patients as "not diseased"; using the MAGIC criteria, 183/257 (71.2%) patients were considered to be "diseased". Thus, for the MAGIC criteria, a sensitivity of 99% (95% confidence interval [CI] 96-100) and a specificity of 61% (95% CI 52-70) were calculated. Considering suspected VGEI according to the MAGIC criteria as "not diseased" achieved congruent assessments of the VASGRA team and the MAGIC criteria, with a sensitivity of 93% and a specificity of 93%. The accuracy of the MAGIC criteria for the different graft locations were also compared. If the suspected VGEIs were assigned to the "not diseased" group, VGEIs of the thoracic aorta seemed to have a poorer sensitivity (86%; 95% CI 73-95) than the other graft locations. CONCLUSION: The current MAGIC criteria offer good sensitivity and specificity in the context of true infections but a reduced specificity for a possible VGEI.

Molecular reprogramming and phenotype switching in Staphylococcus aureus lead to high antibiotic persistence and affect therapy success.

Staphylococcus aureus causes invasive infections and easily acquires antibiotic resistance. Even antibiotic-susceptible S. aureus can survive antibiotic therapy and persist, requiring prolonged treatment and surgical interventions. These so-called persisters display an arrested-growth phenotype, tolerate high antibiotic concentrations, and are associated with chronic and recurrent infections. To characterize these persisters, we assessed S. aureus recovered directly from a patient suffering from a persistent infection. We show that host-mediated stress, including acidic pH, abscess environment, and antibiotic exposure promoted persister formation in vitro and in vivo. Multiomics analysis identified molecular changes in S. aureus in response to acid stress leading to an overall virulent population. However, further analysis of a persister-enriched population revealed major molecular reprogramming in persisters, including down-regulation of virulence and cell division and up-regulation of ribosomal proteins, nucleotide-, and amino acid-metabolic pathways, suggesting their requirement to fuel and maintain the persister phenotype and highlighting that persisters are not completely metabolically inactive. Additionally, decreased aconitase activity and ATP levels and accumulation of insoluble proteins involved in transcription, translation, and energy production correlated with persistence in S. aureus, underpinning the molecular mechanisms that drive the persister phenotype. Upon regrowth, these persisters regained their virulence potential and metabolically active phenotype, including reduction of insoluble proteins, exhibiting a reversible state, crucial for recurrent infections. We further show that a targeted antipersister combination therapy using retinoid derivatives and antibiotics significantly reduced lag-phase heterogeneity and persisters in a murine infection model. Our results provide molecular insights into persisters and help explain why persistent S. aureus infections are so difficult to treat.

CASPR, an analysis pipeline for single and paired guide RNA CRISPR screens, reveals optimal target selection for long non-coding RNAs.

MOTIVATION: CRISPR-Cas9 loss-of-function (LOF) pooled screening promises to identify which long non-coding RNAs (lncRNAs), amongst the many thousands to have been annotated so far, are capable of mediating cellular functions. The two principal LOF perturbations, CRISPR-inhibition and CRISPR-deletion, employ one and two guide RNAs, respectively. However, no software solution has the versatility to identify hits across both modalities, and the optimal design parameters for such screens remain poorly understood. RESULTS: Here, we present CRISPR Analysis for Single and Paired RNA-guides (CASPR), a user-friendly, end-to-end screen analysis tool. CASPR is compatible with both CRISPRi and CRISPR-del screens, and balances sensitivity and specificity by generating consensus predictions from multiple algorithms. Benchmarking on ground-truth sets of cancer-associated lncRNAs demonstrates CASPR's improved sensitivity with respect to existing methods. Applying CASPR to published screens, we identify two parameters that predict lncRNA hits: expression and annotation quality of the transcription start site. Thus, CASPR is a versatile and complete solution for lncRNA CRISPR screen analysis, and reveals principles for including lncRNAs in screening libraries. AVAILABILITY AND IMPLEMENTATION: https://judithbergada.github.io/CASPR/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.