
Pliakos, E. E., Andreatos, N., Shehadeh, F., Ziakas, P. D. & Mylonakis, E. The cost-effectiveness of rapid diagnostic testing for the diagnosis of bloodstream infections with or without antimicrobial stewardship. Clin. Microbiol. Rev. 31, e00095-e117 (2018).
McNamara, J. F. et al. Long-term morbidity and mortality following bloodstream infection: a systematic literature review. J. Infect. 77, 1–8 (2018).
Singer, M. et al. The third international consensus definitions for sepsis and septic shock (sepsis-3). JAMA 315, 801–810 (2016).
Shankar-Hari, M. et al. Developing a new definition and assessing new clinical criteria for septic shock: for the third international consensus definitions for sepsis and septic shock (sepsis-3). JAMA 315, 775–787 (2016).
Buetti, N., Atkinson, A., Marschall, J. & Kronenberg, A. Swiss Centre for Antibiotic Resistance (ANRESIS): incidence of bloodstream infections: a nationwide surveillance of acute care hospitals in Switzerland 2008–2014. BMJ Open 7, e013665 (2017).
Vihta, K. D. et al. Trends over time in Escherichia coli bloodstream infections, urinary tract infections, and antibiotic susceptibilities in Oxfordshire, UK, 1998–2016: a study of electronic health records. Lancet Infect. Dis. 18, 1138–1149 (2018).
Ferrer, R. et al. Empiric antibiotic treatment reduces mortality in severe sepsis and septic shock from the first hour: results from a guideline-based performance improvement program. Crit. Care Med. 42, 1749–1755 (2014).
Seymour, C. W. et al. Time to treatment and mortality during mandated emergency care for sepsis. N Engl. J. Med. 376, 2235–2244 (2017).
Jones, A. E. & Puskarich, M. A. The surviving sepsis campaign guidelines 2012: update for emergency physicians. Ann. Emerg. Med. 63, 35–47 (2014).
Leibovici, L. et al. Monotherapy versus beta-lactam-aminoglycoside combination treatment for gram-negative bacteremia: a prospective, observational study. Antimicrob. Agents Chemother. 41, 1127–1133 (1997).
Dellinger, R. P. et al. Surviving sepsis campaign guidelines committee including the pediatric subgroup: Surviving Sepsis Campaign: international guidelines for management of severe sepsis and septic shock: 2012. Crit. Care Med. 41, 580–637 (2013).
The Review on Antimicrobial Resistance, chaired by Jim O’Neill. Antimicrobial Resistance: Tackling a crisis for the health and wealth of nations (2014); https://www.jpiamr.eu/wp-content/uploads/2014/12/AMR-Review-Paper-Tackling-a-crisis-for-the-health-and-wealth-of-nations_1-2.pdf.
Clinical and Laboratory Standard Institute. Performance Standards for Antimicrobial Susceptibility Testing; 25th Informational supplement. CLSI document M100-S25 (Clinical and Laboratory Standards Institute, Wayne, PA, 2015).
Fournier, P. E. et al. Modern clinical microbiology: new challenges and solutions. Nat. Rev. Microbiol. 11, 574–585 (2013).
Raoult, D., Fournier, P. E. & Drancourt, M. What does the future hold for clinical microbiology?. Nat. Rev. Microbiol. 2, 151–159 (2004).
Van Belkum, A. & Dunne, W. M. Jr. Next-generation antimicrobial susceptibility testing. J. Clin. Microbiol. 51, 2018–2024 (2013).
Davenport, M. et al. New and developing diagnostic technologies for urinary tract infections. Nat. Rev. Urol. 14, 296–310 (2017).
Doern, C. D. The confounding role of antimicrobial stewardship programs in understanding the impact of technology on patient care. J. Clin. Microbiol. 54, 2420–2423 (2016).
Walker, T. et al. Clinical impact of laboratory implementation of Verigene BC-GN microarray-based assay for detection of Gram-negative bacteria in positive blood cultures. J. Clin. Microbiol. 54, 1789–1796 (2016).
Salimnia, H. et al. Evaluation of the filmarray blood culture identification panel: results of a multicenter controlled trial. J. Clin. Microbiol. 54, 687–698 (2016).
Lange, C., Schubert, S., Jung, J., Kostrzewa, M. & Sparbier, K. Quantitative matrix-assisted laser desorption ionization-time of flight mass spectrometry for rapid resistance detection. J. Clin. Microbiol. 52, 4155–4162 (2014).
Jung, J. S. et al. Evaluation of a semiquantitative matrix-assisted laser desorption ionization-time of flight mass spectrometry for rapid antimicrobial susceptibility testing of positive blood cultures. J. Clin. Microbiol. 54, 2820–2824 (2016).
Oviaño, M. & Bou, G. Matrix-assisted laser desorption ionization-time of flight mass spectrometry for the rapid detection of antimicrobial resistance mechanisms and beyond. Clin. Microbiol. Rev. 32, e00037-18 (2018).
de Cueto, M., Ceballos, E., Martinez-Martinez, L., Perea, E. J. & Pascual, A. Use of positive blood cultures for direct identification and susceptibility testing with the Vitek 2 system. J. Clin. Microbiol. 42, 3734–3738 (2004).
Bobenchik, A. M., Hindler, J. A., Giltner, C. L., Saeki, S. & Humphries, R. M. Performance of Vitek 2 for antimicrobial susceptibility testing of Staphylococcus spp. and Enterococcus spp. J. Clin. Microbiol. 52, 392–397 (2014).
Bobenchik, A.M., Deak, E., Hindler, J.A., Charlton, C.L. & Humphries, R.M. Performance of Vitek 2 for antimicrobial susceptibility testing of Acinetobacter baumannii, Pseudomonas aeruginosa, and Stenotrophomonas maltophilia with Vitek 2 (2009 FDA) and CLSI M100S 26th edition Breakpoints. J Clin. Microbiol. 55, 450–456 (2017).
Giovanni, G. et al. Comparative evaluation of the Vitek-2 Compact and Phoenix systems for rapid identification and antibiotic susceptibility testing directly from blood cultures of Gram-negative and Gram-positive isolates. Diagn. Microbiol. Infect. Dis. 72, 20–31 (2012).
Marschal, M. et al. Evaluation of the accelerate pheno system for fast identification and antimicrobial susceptibility testing from positive blood cultures in bloodstream infections caused by Gram-negative pathogens. J. Clin. Microbiol. 55, 2116–2126 (2017).
Jarvis, R. M. & Goodacre, R. Discrimination of bacteria using surface-enhanced Raman spectroscopy. Anal. Chem. 76, 40–47 (2004).
Liu, T. T. et al. A high speed detection platform based on surface-enhanced Raman scattering for monitoring antibiotic-induced chemical changes in bacteria cell wall. PLoS ONE 4, e5470 (2009).
Liu, C. Y. et al. Rapid bacterial antibiotic susceptibility test based on simple surface-enhanced Raman spectroscopic biomarkers. Sci. Rep. 6, 23375 (2016).
Boardman, A. K. et al. Rapid detection of bacteria from blood with surface-enhanced Raman spectroscopy. Anal. Chem. 88, 8026–8035 (2016).
Premasiri, W. R. et al. The biochemical origins of the surface-enhanced Raman spectra of bacteria: a metabolomics profiling by SERS. Anal. Bioanal. Chem. 408, 4631–4647 (2016).
Chiu, S. W. Y. et al. Quantification of biomolecules responsible for biomarkers in the surface-enhanced Raman spectra of bacteria using liquid chromatography-mass spectrometry. Phys. Chem. Chem. Phys. 20, 8032–8041 (2018).
Xu, H., Bjerneld, E. J., Käll, M. & Börjesson, L. Spectroscopy of single hemoglobin molecules by surface enhanced Raman scattering. Phys. Rev. Lett. 83, 4357 (1999).
Lentacker, I., De Cock, I., Deckers, R., De Smedt, S. C. & Moonen, C. T. Understanding ultrasound induced sonoporation: definitions and underlying mechanisms. Adv. Drug Deliv. Rev. 72, 49–64 (2014).
Fu, H., Comer, J., Cai, W. & Chipot, C. Sonoporation at small and large length scales: effect of cavitation bubble collapse on membranes. J. Phys. Chem. Lett. 6, 413–418 (2015).
Piyasena, P., Mohareb, E. & McKellar, R. C. Inactivation of microbes using ultrasound: a review. Int. J. Food Microbiol. 87, 207–216 (2003).
Gao, S., Lewis, G. D., Ashokkumar, M. & Hemar, Y. Inactivation of microorganisms by low-frequency high-power ultrasound: 1 Effect of growth phase and capsule properties of the bacteria. Ultrason. Sonochem. 21, 446–453 (2013).
Sesal, N. C. & Kekeç, Ö. Inactivation of Escherichia coli and Staphylococcus aureus by ultrasound. J. Ultrasound Med. 33, 1663–1668 (2014).
Wiegand, I., Hilpert, K. & Hancock, R. E. Agar and broth dilution methods to determine the minimal inhibitory concentration (MIC) of antimicrobial substances. Nature Protoc. 3, 163–175 (2008).
Jorgensen, J. H. & Ferraro, M. J. Antimicrobial susceptibility testing: a review of general principles and contemporary practices. Clin. Infect. Dis. 49, 1749–1755 (2009).
Cunha, B. A. Antibiotic essentials 7th edn. (Jones & Bartlett Publishers, Sudbury, MA, 2008).
Wang, H. H. et al. Highly Raman-enhancing substrates based on silver nanoparticle arrays with tunable sub-10 nm gaps. Adv. Mater. 18, 491–495 (2006).
Phillips, W. A., Hosking, C. S. & Shelton, M. J. Effect of ammonium chloride treatment on human polymorphonuclear leucocyte iodination. J. Clin. Pathol. 36, 808–810 (1983).
Marshall, P. N. Flow cytometry lytic agent and method enabling 5-part leukocyte differential count. U.S. Patent, US5510267A (1996).
Lorenz, B., Rösch, P. & Popp, J. Isolation matters-processing blood for Raman microspectroscopic identification of bacteria. Anal. Bioanal. Chem. 411, 5445–5454 (2019).
Rinas, U., Hellmuth, K., Kang, R., Seeger, A. & Schlieker, H. Entry of Escherichia coli into stationary phase is indicated by endogenous and exogenous accumulation of nucleobases. Appl. Environ. Microbiol. 61, 4147–4151 (1995).
Brauer, M. J. et al. Conservation of the metabolomic response to starvation across two divergent microbes. Proc. Natl. Acad. Sci. U.S.A. 103, 19302–19307 (2006).
Link, H., Fuhrer, T., Gerosa, L., Zamboni, N. & Sauer, U. Real-time metabolome profiling of the metabolic switch between starvation and growth. Nat. Methods 12, 1091–1097 (2015).
Liebeke, M. et al. A metabolomics and proteomics study of the adaptation of Staphylococcus aureus to glucose starvation. Mol. Biosyst. 7, 1241–1253 (2011).
Belenky, P. et al. Bactericidal antibiotics induce toxic metabolic perturbations that lead to cellular damage. Cell Rep. 13, 968–980 (2015).
Zampieri, M., Zimmermann, M., Claassen, M. & Sauer, U. Nontargeted metabolomics reveals the multilevel response to antibiotic perturbations. Cell Rep. 19, 1214–1228 (2017).
Yang, J. H. et al. A white-box machine learning approach for revealing antibiotic mechanisms of action. Cell 177, 1649–1661 (2019).
Lopatkin, A. J. et al. Bacterial metabolic state more accurately predicts antibiotic lethality than growth rate. Nat. Microbiol. 4, 2109–2117 (2019).
Dörries, K., Schlueter, R. & Lalk, M. Impact of antibiotics with various target sites on the metabolome of Staphylococcus aureus. Antimicrob. Agents Chemother. 58, 7151–7163 (2014).
Schelli, K., Zhong, F. & Zhu, J. Comparative metabolomics revealing Staphylococcus aureus metabolic response to different antibiotics. Microbiol. Biotechnol. 10, 1764–1774 (2017).
Stiles, P. L., Dieringer, J. A., Shah, N. C. & Van Duyne, R. P. Surface-enhanced Raman spectroscopy. Annu. Rev. Anal. Chem. 1, 601–626 (2008).
Biring, S., Wang, H. H., Wang, J. K. & Wang, Y. L. Light scattering from 2D arrays of monodispersed Ag-nanoparticles separated by tunable nano-gaps: spectral evolution and analytical analysis of plasmonic coupling. Opt. Express. 16, 15312–15324 (2008).
Lin, B. Y. et al. Unraveling near-field origin of electromagnetic waves scattered from silver nanorod arrays using pseudo-spectral time-domain calculation. Opt. Express. 17, 14211–14228 (2009).
Cheng, T. Y. et al. Revealing local, enhanced optical field characteristics of Au nanoparticle arrays with 10 nm gap using scattering-type scanning near-field optical microscopy. Phys. Chem. Chem. Phys. 15, 4275–4282 (2013).
Dvoynenko, M. M. & Wang, J. K. Finding electromagnetic and chemical enhancement factors of surface-enhanced Raman scattering. Opt. Lett. 32, 3552–3554 (2007).
Dvoynenko, M. M. & Wang, J. K. Can electrodynamic interaction between a molecule and metal dominate a continuum background in surface-enhanced Raman scattering?. Phys. Chem. Chem. Phys. 17, 27258 (2015).
Dvoynenko, M. M., Wang, H. H., Hsiao, H. H., Wang, Y. L. & Wang, J. K. Study of Signal-to-background ratio of surface-enhanced raman scattering: dependences on excitation wavelength and hot-spot gap. J. Phys. Chem. C. 121, 26438–26445 (2017).
Sinha, M. et al. Emerging technologies for molecular diagnosis of sepsis. Clin. Microbiol. Rev. 31, e00089-17 (2018).
Samuel, L. Direct detection of pathogens in bloodstream during sepsis: are we there yet?. JALM. 3, 631–642 (2019).
Eling, N., Morgan, M. D. & Marioni, J. C. Challenges in measuring and understanding biological noise. Nature Rev. Genet. 20, 536–548 (2019).
Takhaveev, V. & Heinemann, M. Metabolic heterogeneity in clonal microbial populations. Curr. Opin. Microbiol. 45, 30–38 (2018).
Mitchell, S. & Hoffmann, A. Identifying noise sources governing cell-to-cell variability. Curr. Opin. Syst. Biol. 8, 39–45 (2018).