Nanotools and molecular techniques to rapidly identify and fight bacterial infections

    Nanotools and molecular techniques to rapidly identify and fight bacterial infections S. Dinarelli, M. Girasole, S. Kasas, G. Longo PII: DOI: Reference:

S0167-7012(16)30006-9 doi: 10.1016/j.mimet.2016.01.005 MIMET 4819

To appear in:

Journal of Microbiological Methods

Received date: Revised date: Accepted date:

21 October 2015 13 January 2016 13 January 2016

Please cite this article as: Dinarelli, S., Girasole, M., Kasas, S., Longo, G., Nanotools and molecular techniques to rapidly identify and fight bacterial infections, Journal of Microbiological Methods (2016), doi: 10.1016/j.mimet.2016.01.005

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ACCEPTED MANUSCRIPT REVISED MANUSCRIPT

Nanotools and molecular techniques to rapidly identify and fight bacterial

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infections

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S. Dinarelli1, M. Girasole1, S. Kasas2,3 and G. Longo1*

Istituto di Struttura della Materia, CNR, Rome (IT)

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Ecole Polytechnique Fédérale de Lausanne, LPMV, Lausanne (CH)

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Département des Neurosciences Fondamentales, Université de Lausanne, Lausanne (CH)

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Corresponding author : Giovanni Longo, Istituto di Struttura della Materia – CNR, Via del Fosso

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del Cavaliere 100, 00133 Rome (IT), Tel. 0645488121, email: [email protected]

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Sponsor editor: Robert S. Burlage, Ph.D., Chairman, Pharmaceutical and Administrative Sciences

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Abstract

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Department. Concordia University of Wisconsin, USA.

Reducing the emergence and spread of antibiotic-resistant bacteria is one of the major healthcare issues of our century. In addition to the increased mortality, infections caused by multi-resistant

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bacteria drastically enhance the healthcare costs, mainly because of the longer duration of illness and treatment. While in the last 20 years, bacterial identification has been revolutionized by the introduction of new molecular techniques, the current phenotypic techniques to determine the susceptibilities of common Gram-positive and Gram-negative bacteria require at least two days from collection of clinical samples. Therefore, there is an urgent need for the development of new technologies to determine rapidly drug susceptibility in bacteria and to achieve faster diagnoses. These techniques would also lead to a better understanding of the mechanisms that lead to the insurgence of the resistance, greatly helping the quest for new antibacterial systems and drugs. In this review, we describe some of the tools most currently used in clinical and microbiological research to study bacteria and to address the challenge of infections. We discuss the most interesting advancements in the molecular susceptibility testing systems, with a particular focus on the many applications of the MALDI-TOF MS system. In the field of the phenotypic characterization protocols, we detail some of the most promising semi-automated commercial systems and we focus

ACCEPTED MANUSCRIPT on some emerging developments in the field of nanomechanical sensors, which constitute a step towards the development of rapid and affordable point-of-care testing devices and techniques. While there is still no innovative technique that is capable of completely substituting the

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conventional protocols and clinical practices, many exciting new experimental setups and tools

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could constitute the basis of the standard testing package of the future microbiological tests.

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techniques, phenotypic methods, molecular methods.

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Keywords: Microbiology, bacterial resistances, antibiotics, susceptibility, identification, innovative

ACCEPTED MANUSCRIPT 1. Introduction Microorganisms are among the oldest living beings on Earth and their presence has been essential in prehistoric ages to model and modify the environment, providing the basic conditions for

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complex life and evolution. Microbiology is particularly focused on the study of microorganisms,

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their metabolic pathways, their interaction with the environment and their response to external stimuli. In this view, it is quite surprising that there is still relatively little knowledge of bacteria.

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For instance, it is believed that less than 10% of the prokaryotes are properly described in the Bergey’s manual of Systematic Bacteriology. Human interactions with bacteria are complex and there is a consortial relationship developed between humans and microbes that makes their presence

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in our body (for instance in our digestive system) fundamental for our survival. In addition to their importance in sustaining life and maintaining the Earth’s environmental condition, microorganisms,

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and in particular bacteria, pose a potential risk for health safety due to their pathogenicity. Since this discovery, there has been a race to fight infections that appeared to be over with the invention of antibiotics, which represent one of the most important medical discoveries in the history of

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humanity. However, due to the renowned adaptability of bacteria (Martinez and Baquero, 2000),

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there is an alarming increase of antibiotic-resistance among the most medically relevant species, which is now recognized as a major health challenge. The insurgence of resistances and the

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mechanisms involved in the response to antibiotic pressure are mostly unknown and this lack of knowledge has led to the rise of an alarming health issue. To face this challenge, we need new strategies based on the development of new and complementary technologies to understand better bacteria and their response to external stimuli.

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Typically, when a patient is admitted in a clinic and particularly in urgent and serious cases (such as sepsis or meningitis), the doctors administer immediately non-specific antibiotics (or a combination of antibiotics and antivirals). On one hand, these drugs help keeping the infection under control, but on the other, they artificially select resistant mutants by eliminating susceptible microorganisms. This general treatment lasts until the clinic’s laboratories identify and characterize such microorganisms. This long time-frame, combined with the use and misuse of antibiotics in the everyday clinical practice, is greatly increasing the frequency of resistant strains and reducing the number of available antibiotics and their effectiveness. In addition to the increased mortality, when infections become resistant to first-line medicines, more expensive therapies must be used and these are often badly tolerated. The longer duration of illness, as well as the insurgence of resistant strains, increase healthcare costs and the financial burden to families and societies. For instance, the development of a new antibiotic requires between 12 and 15 years and half a billion dollars in investment. However, bacteria do not take more than 2-3 years to develop new resistances and we

ACCEPTED MANUSCRIPT are now at risk of being depleted of effective antibiotics. Indeed, the investment of big pharmaceutical companies into antibiotic research has drastically declined in the last decade, and now there are very few new molecules in the development pipeline.(Bassetti et al., 2013)

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The conventional clinical workflow involves a first bacterial identification step (ID), which is

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followed by an antibiotic susceptibility testing (AST). For both common Gram-positive and Gramnegative bacteria, the input sample is taken from the patient (e.g. positive blood culture, spinal fluid,

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urine, faeces, nasal or throat swab), streaked on agar nutrient media and, after a 12-24 hour incubation, is transferred to the analysis. This culture step provides an easy sample preparation (isolation of pathogens from a clinical sample) as well as amplification of the cultured

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cells.(Steward et al., 2005) (Figure 1)

In this review, we will present the most current tools available for clinical and microbiological

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research to study bacteria and to address the challenge of infections. We will focus in particular on some interesting new developments in the field of nanomechanical sensors, which constitute a step towards the development of rapid and affordable point-of-care testing devices.

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The more conventional characterization tools are based on optical microscopy, Gram staining or

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simple optical density measurements, which are quite simple and well established methods that have the drawback of a very limited sensitivity. In the last decades, we have witnessed

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extraordinary advances in genomics, nanotechnology, microelectronics and optics that have demonstrated unprecedented sensitivity for label-free identification of biological systems as well as for detection of biological interactions. Although in some cases, the promise was frustrated by a lack of reproducibility, which is intolerable in the clinical field, some technologies have

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demonstrated an enormous potential and high reliability to revolutionize the clinical diagnosis.

2. Bacterial Identification The ID step is fundamental to determine the best antibiotics to be employed in the fight against the infection, and a rapid identification of the aetiology of the microbes can positively affect the patient care. The most important requirements for the ID techniques, beside their accuracy, are the rapidity of the response and the cost-effectiveness. Indeed, identification through conventional microbiological techniques involves a subculture on solid media with 18-24h incubation, prior to the identification step, traditionally performed by using biochemical tests or enzyme assays.(van Belkum et al., 2013) The development of new and more precise identification techniques has greatly modified the field of microbiology throughout the years. In fact, the number of identified bacterial species increases continuously(Jones et al., 2008) and, due to the introduction of molecular techniques, such as real-

ACCEPTED MANUSCRIPT time polymerase chain reaction (RT-PCR), gene sequencing and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS)(Seng et al., 2009), approximately 500 new species are described each year(Janda and Abbott, 2007) (Figure 2). In fact, since their

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introduction, such molecular techniques have radically changed the time-frame for bacterial

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identification (ID).(Fournier et al., 2013)

MALDI-TOF MS is now routinely employed in clinical settings throughout the world and has

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shown excellent performances, equalling or surpassing the conventional methods to ID a wide range of microorganisms even in clinical settings (Neville et al., 2011, Seng et al., 2009) and in any part of the world(Fall et al., 2015). It has been used to ID Gram-negative bacilli (Degand et al., 2008) or

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Gram-positive cocci (Dubois et al., 2010), mycobacteria (Saleeb et al., 2011) and even yeasts (Dhiman et al., 2011). Furthermore, by coupling MALDI TOF MS with microarray blood-culture

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techniques (Ledeboer et al., 2015) or rapid bacterial isolation protocols (Croxatto et al., 2014, Opota et al., 2015, Opota et al., 2015), the technique is now used routinely in hospitals to ID bacteria directly from positive blood cultures. The overall performances are very good as they ensure an

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identification rate of more than 80% in timescales that are well below the first day from the

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admittance of the patients. (Bizzini et al., 2010) New MALDI-TOF MS-based assays have been reported to identify the -lactamase activity of

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bacteria, which is the target for several first line antibiotics and treatments. (Ledeboer and Hodinka, 2011, Ledeboer et al., 2015) For example, Burkhardt and Zimmermann (Burckhardt and Zimmermann, 2011), as well as Hrabak and co-workers (Hrabak et al., 2011, Papagiannitsis et al., 2015) have demonstrated rapid identification of carbapenemase activity and detection of hydrolysis

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of carbapenems by different bacterial strains. Yet, it must be noted that these analyses still lack the standardization and reliability necessary for transfer to the clinical settings.(Mirande et al., 2015) An alternative to MALDI-TOF MS are the fluorescent in situ hybridization assays (FISH), which allow performing identification directly from positive blood culture bottles, avoiding the subculture steps, consequently saving medically relevant time.(Peters et al., 2006) For instance, Cattoir and coworkers have used these assays to identify Pseudomonas aeruginosa in blood cultures(Cattoir et al., 2010) and Jukes and collaborators have exploited similar techniques to differentiate between different staphylococci in positive blood samples(Jukes et al., 2010). In a recent work, Cerqueira and co-workers validated FISH for the determination of clarithromycin resistance in Helicobacter pylori directly from gastric biopsy specimens.(Cerqueira et al., 2013) Finally, Caballero and collaborators employed FISH to identify vancomycin-Resistant Enterococcus faecium and carbapenem resistant Klebsiella pneumoniae in colon sections.(Caballero et al., 2015) (Figure 3) Overall, FISH assays are more cost effective than conventional techniques and have good

ACCEPTED MANUSCRIPT correlation with most molecular techniques(Bao et al., 2007) but are limited in the number of species that can be identified. Overall, a general limitation of the molecular techniques is the high cost and the requirement for

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complex instrumentation and training. Another limitation is the throughput of these techniques,

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which is often limited by the need to perform one strain per analysis, even though some reports are surfacing on the ability to achieve high-throughput ID with MALDI-TOF MS(van Veen et al.,

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2010). To solve this problem, many new tools are now proposed to ensure a phenotypic identification of the bacteria and a greater throughput. An extremely interesting proposal involves the use of elastic forward scattering directly on microcolonies growing on solid supports, to identify

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bacterial colonies rapidly, label-free and in a non-destructive manner.(Marcoux et al., 2014) In addition, other spectroscopies such as the Raman techniques have been shown to accurately and

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rapidly characterize bacteria(Buijtels et al., 2008, Hamasha et al., 2013, Willemse-Erix et al., 2009), yeasts(Chouthai et al., 2015) and fungi(Rodriguez et al., 2013) allowing rapid ID(Ashton et al., 2011) as well as the determination of the effect of antibiotics(Liu et al., 2009). Finally, high-

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throughput phenotypic microarrays have been used to study the genetic fingerprint of the bacterial

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strain, adding the ability to determine other metabolic and chemical properties of the

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bacteria.(Friedrich et al., 2010, Johnson et al., 2008, Khatri et al., 2013)

3. Antibiotic susceptibility

The classical determination of antibiotic susceptibility is based on diffusive disks.(Matuschek et al., 2014) The fundamental guidelines for these analyses can be found on the European Committee on

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Antimicrobial Susceptibility Testing - EUCAST website (www.eucast.org). They require a first incubation of the bacteria in liquid to achieve a turbidity of 0.5 McFarland (approximately 108 CFU/ml), followed by the deposition on modified agar disks and a second incubation for 16-24 hours. The optical analysis of the resulting colony formation indicates the bacterial susceptibility to the chosen antibiotic, and in particular the minimum inhibitory concentration (the minimal concentration that inhibits bacterial replication - MIC). This protocol is quite simple, very well established and commonly utilized in most clinics or research labs, yet it is very slow since it may require days, or even weeks, depending on the bacterium. A further aspect to take into consideration is the culturability and the related issue of viable but non-culturable (VNBC) microorganisms. Many bacteria, although maintaining metabolic activity and often pathogenicity, are non-culturable due to their physiology, fastidiousness, or mechanisms for adaptation to the environment.(Sandle, 2011) These microbes are extremely difficult to study and diagnose with conventional techniques

ACCEPTED MANUSCRIPT and new rapid microbiological methods (RMMs) that do not rely on growth, are now proposed to provide a higher recovery count as compared with traditional methods. Consequently, there is a large need for new, rapid, accurate and cost-effective characterization

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techniques, aimed to define in few hours the most effective treatment and to reduce the risks

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associated with new bacterial resistances. In fact, a fast diagnosis would also allow a more specific, tailored treatment, which will be more effective, better tolerated by the patient and less likely to

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produce relapses. As for the case of the determination of the bacterial ID, most new techniques that are used or have been proposed to determine the susceptibility of bacteria to antibiotics (antibiotic

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susceptibility test – AST) can be divided in molecular or phenotypic.(Fournier et al., 2013)

3.1. Molecular techniques

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The molecular techniques to perform AST, such as real-time PCR (RT PCR) and DNA microarrays rely mainly on the determination of the particular genetic fingerprint that is associated with the resistance to a specific antibiotic.(Didelot et al., 2012, Frye et al., 2006) To understand the

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mechanisms and epidemiology of antimicrobial resistance, Frye and co-workers have employed

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specific DNA microarrays, to detect simultaneously a large spectrum of genes involved in the insurgence of resistance to different antibiotics.(Frye et al., 2010)

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On the other hand, Huletsky and co-workers have employed real-time PCR to identify Staphylococcus aureus from a bacterial mixture(Huletsky et al., 2004), while Furukawa and collaborators used this technique to determine the presence of the vancomycin resistant gene in enterococci from sewer treatment facilities(Furukawa et al., 2015). Finally, in a clinical-oriented

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work, Diene and collaborators have employed RT PCR to study bacteria from patients returning from New Delhi, proposing this technique for a rapid evaluation of the presence of carbapenemresistant bacterial isolates.(Diene et al., 2011) Different PCR-based genotypic or molecular methods for predicting drug resistance have been developed and commercialized (e.g., the MTB/RIF™ assay, part of the Cepheid Gene Xpert System (Boehme et al., 2010, Helb et al., 2010)). These techniques are extremely promising due to the very high reliability and speed of the single experiment. However, they are still relatively expensive (beyond the means of many developing countries, where the need is the greatest) and the identification requires diffuse biotechnology competences, as prior knowledge of the bacteria ID and the specific genetic fragment that must be identified is required. Furthermore, these techniques are unable to distinguish between living or dead bacteria as both contain the target DNA that is amplified (a limitation that also applies to other diagnostic methodologies such as the line-probe assays(Brossier et al., 2006, Morgan et al., 2005)), opening the way to possible misreading of the results, which is unacceptable in a clinical

ACCEPTED MANUSCRIPT setting.(Barbau-Piednoir et al., 2014) To solve this latter issue, some innovative protocols have been recently proposed, combining rapid PCR with the use of DNA cross-linking agents. These are able to affect only the genetic material from dead bacteria, effectively enhancing the contribution to

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the results from live microorganisms. For instance, Soejima and co-workers have exposed Listeria

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monocytogenes to Ethidium monoazide to induce the DNA cleaving of the non-viable bacteria, actively suppressing the PCR efficiency of these microorganisms.(Soejima et al., 2008)

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Following the increased use of MALDI-TOF MS for the rapid identification of bacteria, this technique has been proposed as a possible alternative to characterize bacterial susceptibility.(Schubert and Kostrzewa) As described in the ID section of this review, the

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capabilities of this technique are extremely high and many studies aim to combine the MALDI-TOF MS with the speed of other AST techniques to achieve a rapid and reliable characterization of

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bacteria. Idelevich and co-workers used this procedure to study Candida spp. from blood cultures(Idelevich et al., 2014) while Croxatto, Opota and collaborators studied several Grampositive and -negative bacteria.(Croxatto et al., 2014, Opota et al., 2015) In fact, even if the

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capabilities of MALDI-TOF MS are quite evident, there are still very few studies focusing on the

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extension of the ID protocols to perform susceptibility tests and assays, suggesting that specific preparation and extraction protocols must be developed and optimized to perform these AST measurements.(Fournier et al., 2013, Hrabak et al., 2013) For instance, Schaumann and co-workers

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used MALDI-TOF MS to determine the production of -lactamase in different bacterial isolates (Enterobacteriaceae and P. aeruginosa) obtaining no significant result.(Schaumann et al., 2012) Yet, the very same group was capable, in a subsequent work, to discriminate enterohemorrhagic and

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enteropathogenic Escherichia coli from the non-enteropathogenic E. coli.(Schaumann et al., 2013) Probably, the presence and thickness of the cell wall, and in particular of the peptidoglycan layer, reduces the sensitivity of the measurements, making particularly complex the characterization of some specific bacterial strains. To circumvent this problem, some groups have introduced the combination of mass spectrometry and labelling techniques to enhance specific proteins or genetic markers. An example is the SELDITOF, a combination of MALDI-TOF MS with the selective protein binding using the ProteinChip array. Using this technique, Shah and co-workers have been able to discriminate between methicillin-susceptible (MSSA) and resistant Staphylococcus aureus strains (MRSA)(Shah et al., 2011), while Majcherczk and collaborators have studied the same bacteria focusing on the teicoplanin resistance(Majcherczyk et al., 2006). Dubska and co-workers have exploited this technique on 10 different E. coli strains (Dubska et al., 2011), while Camara and Hays have shown how SELDI-TOF MS can be useful in the analysis of ampicillin resistance of these bacteria,

ACCEPTED MANUSCRIPT opening the way to the exploitation of the technique for rapid susceptibility assays(Camara and Hays, 2007). Another particularly interesting effort to optimize the MALDI-TOF MS to achieve a rapid and

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reliable susceptibility characterization is to combine it with techniques that ensure a fast bacterial

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extraction from bodily samples (Chen et al., 2013, March et al., 2015) or a reliable susceptibility test. This is the case, for instance, of the combination of MALDI-TOF MS with Vitek-2(Kathuria et

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al., 2015) or with BD Phoenix automated systems (Hazelton et al., 2014, Morgenthaler and Kostrzewa, 2015).

A novel experimental setup involves the combination of stable isotope labelling by amino acid in

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cell culture (SILAC) with MALDI-TOF MS. The idea is that only metabolically active microorganisms can incorporate labelled amino acids provided with the growth medium into

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cellular proteins. This results in a peak shift that can be detected by MALDI-TOF MS under the same conditions that are used for the identification of pathogens. If the bacterium is no longer metabolically active due to the impact of an inhibiting antibiotic, no peak shift will be observed in

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the mass spectrum. This means that the combination of these two techniques can determine rapidly

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almost any antibiotic resistance, and is not limited by the mechanism of action or by the bacterial identification.(Jung et al., 2014) The main limitation of this combined approach is that the outcome

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of the investigation is an antibiotic concentration that is not always related to the conventional MIC values and this produces complications in the introduction of this technique in the everyday clinical practice.

To conclude, in recent years, several alternative techniques have been developed to measure the

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growth or viability of microorganisms, often by identifying the metabolic subproducts of the living specimens (e.g. the mycobacterial growth indicator tube (Diacon et al., 2010), the resazurinreduction microplate assay (Palomino et al., 2002) or the BacTiter-Glo™ microbial cell-viability assay(Nilsson et al., 1988)). In these cases, the assay cost is relatively inexpensive and the sample handling procedures are rather simple, but the mean time required to obtain results is very long (up to 7 days may be needed). 3.2. Phenotypic techniques Most of the current methods for antibiotic susceptibility testing (AST) are still based on phenotypic assays (e.g. growth measurements) which may require days, or even weeks, depending on the bacterium. This time is needed to allow growing enough microorganisms for ID as well as for successive disk-diffusion-based AST, which are performed after the incubation time, often two days after the admittance of the patient.(Horvat, 2010)

ACCEPTED MANUSCRIPT To reduce the time needed for AST, several phenotypic automated systems, such as MicroScan WalkAway (Beckman Coulter), BD Phoenix (Dickinson Becton) or Vitek-2 (bioMérieux), have emerged to achieve a reduction in the time needed to obtain an AST.(Mittman et al., 2009) In

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addition to these tools, it is worth naming the Wider system (Francisco Soria Melguizo S.A.), a

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computer-assisted image recognition system capable of automated reading of microdilution panels and wells.(Cantón et al., 2000) These are semi-automated systems, with different formats, that

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essentially incubate test panels, perform automated readings and report the results to a computer system.(Rhoads et al., 1995) In some cases, the test can be completed rapidly, in 6-8 hours, delivering a fast result to the medical doctor, with large advantages for the outcome of the

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treatment.(Doern et al., 1994) Unfortunately, while the level of technological advancement ensures that all the automated systems have minimal rate of major error, the complexity of the phenomena

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leading to the insurgence of bacterial resistance and the coexistence of a large number of techniques and protocols, induce some imprecision in the determination of the susceptibilities.(Chatzigeorgiou et al., 2011) This is enhanced in the cases in which the MIC is at the border of the critical

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breakpoint.(Rodriguez-Martinez et al., 2015) For instance, the Vitek-2 is an extremely reliable

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system and is routinely used in many clinical laboratories and hospitals. Its performances have been studied and verified in many different conditions and with a wide range of bacteria and antibiotics.

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Swenson and co-workers studied vancomycin-intermediate S. aureus (Swenson et al., 2009), while Junkins and collaborators have compared Vitek-2 and BD Phoenix systems in the analysis of mecAmediated resistance in S. aureus (Junkins et al., 2009). Other groups have used Vitek-2 to determine the clindamycin resistance of Staphylococcus spp (Lavallée and co-workers(Lavallee et al., 2010))

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and of S. aureus (Gardiner and collaborators(Gardiner et al., 2013)). In most cases, the results were in excellent agreement with the conventional phenotypic tools, but there were some discrepancies, which led to susceptibility reporting errors. For instance, Tan and co-workers reported that in the case of Enterococcus faecalis, Penicillin minimum inhibitory concentrations (MICs) generated by the Vitek-2 system were two doubling dilutions higher compared to those obtained by the reference tests.(Tan et al., 2014) In another study, Won and co-workers compared the Phoenix and Vitek-2 capability of identifying yeast isolates, obtaining results ranging from 65% to 95%.(Won et al., 2014) While, for research applications, a sensitivity of 80-90% is extremely positive, such amount of false negatives could lead to potentially serious clinical implications. Overall, these promising automated techniques are still far from substituting the conventional protocols, but are used currently in parallel, to deliver a rapid suggestion of the best treatment.

3.3. Nanomechanical sensors

ACCEPTED MANUSCRIPT Among the new technological improvements that have been applied to the determination of the viability and of antibiotic resistance of bacteria, nanomechanical oscillators stand out as small, precise experimental platforms that can perform high-sensitivity analyses of nanosized biological

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specimens.(Longo and Kasas, 2014) A nanomechanical sensor is a very sensitive oscillator,

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typically an AFM cantilever, which is coupled with a displacement detector to produce powerful and versatile tools(Tamayo et al., 2013) capable of characterizing biological systems with

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unprecedented detail and time resolution.(Calleja et al., 2012) Due to the extreme high sensitivity of the cantilever, these devices have the potential to provide a breakthrough in the field of nanomedicine(Huber et al., 2013, Shekhawat and Dravid, 2013) and in particular in the

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investigation of bacteria and of their response to antibiotics.(Lang and Gerber, 2008) These new systems are increasingly employed for several applications(Alvarez and Lechuga, 2010,

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Boisen et al., 2011, Hansen and Thundat, 2005, Waggoner and Craighead, 2007) ranging from artificial noses(Djuric and Jokic, 2007, Lang et al., 1999, McKendry et al., 2002) to temperature measurement(Barnes et al., 1994, Berger et al., 1996), and particularly for the detection of very

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small masses(Braun et al., 2009, Ilic et al., 2000) or for nano-stress sensing in molecular

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biology(Fritz et al., 2000, Godin et al., 2010, Ndieyira et al., 2008). To apply these sensing devices to the investigation of bacteria and to the rapid characterization of the effects of environmental

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stimuli to the bacterial growth and proliferation, several elegant solutions have been conceived. For instance, Ndieyira and co-workers have shown recently how the surface-stress sensing ability of nanomechanical cantilevers can be exploited to describe quantitatively the mechanical response of a bacterial surface receptor to different antibiotics in the presence of competing ligands in

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solution.(Ndieyira et al., 2014) Other groups have monitored the cantilever resonant frequency, using high-resolution determination of the mechanical properties of one(Wali et al., 2010) or several parallel sensors,(Reed et al., 2006) to determine the presence of added mass in liquid environment. Other works consider coating of the sensor’s surface with a thin nutritive layer (typically agarose) in humid atmosphere to support the local growth of bacteria(Gfeller et al., 2005) or fungal spores(Nugaeva et al., 2005). Barton and collaborators have modified sensors to introduce micro-fluidic components to monitor the presence and growth of cells and bacteria without modifying the mechanical properties of the sensor(Barton et al., 2010). For instance, Burg et al. used fluid filled microcantilevers to weigh single bacterial cells in water with a resolution that allowed measuring the mass of a single E. coli or Bacillus subtilis cell (below the femtogram)(Burg et al., 2007). Park and collaborators have proposed new micro-mechanical pedestals as sensitive oscillators capable of controlled, high-resolution measurements in liquid environment.(Park et al., 2010)

ACCEPTED MANUSCRIPT Very recently, our group has introduced a new technique to exploit the capabilities of cantilever nanosensors: the nanomotion detector. This allows real-time detection of the movements of biological samples within a physiological medium, in the Angstrom-to-micrometre range and with

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unprecedented speed, sensitivity and time resolution. The idea is to exploit the intimate link

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between life and motion, to transduce the metabolism of living specimens through the fluctuation of flexible cantilevers that act as solid support for the microorganisms.(Kasas et al., 2015) If the

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exposure to a particular concentration of antibiotics will cause the death or inactivation of the bacteria, the amplitude of the fluctuation will be reduced very rapidly, indicating the effectiveness of the antibacterial drug (Figure 4).(Longo G et al., 2013)

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Overall, while the application of nanomechanical sensors and of the nanomotion sensor in particular, are still far from a clinical transition, the use of small nanosensors have the potentiality to

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become a major player in the fight against bacterial infections.(McKendry and Kappeler, 2013)

4. Ultrastructural characterization

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In combination with the fast determination of the susceptibility of bacteria to antibiotics, it is

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extremely important to determine the effect of the drugs on these microorganisms and their response to these stimuli. Most of the techniques described up to now in this review deliver a quite

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simple answer to these questions by focusing on the determination of the viability of the bacteria at the population level. This is because many conventional characterization techniques are based on the assumption that the organisms under investigation exhibit homogenous physiological and physical properties as a population. This is not entirely true for all living systems and, in particular,

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in the case of bacterial infections. In view of this, modern bacteriology is increasingly demanding a more in-depth study of bacterial characteristics, abandoning the overall population analyses and leaning towards the single-cell level (Brehm-Stecher and Johnson, 2004). Nowadays, several instruments are available to characterize specific physiologically related properties of living microscopic samples. Optical imaging is hindered by the diffraction limit and other powerful techniques require expensive apparata and specialized sample preparation. On the other hand, the atomic force microscope (AFM)(Binnig et al., 1986) stands out as an extremely versatile and powerful tool to characterize bacterial morphology as well as physico-chemical properties at a single-cell level and with nanometre scale resolution. One of the great peculiarities of the AFM in biology is that it can work in any environmental condition, and that the measurement requires very little sample preparation. For instance, it can study living bacteria in physiological medium and even changing the medium during the analysis(Kasas et al., 2013), allowing a real-time investigation of the effects of antibacterial agents and drugs. For example, Fantner and co-workers

ACCEPTED MANUSCRIPT have shown how to extend the use of AFM imaging to monitor, with high resolution, several individual bacterial cells with an imaging rate of just few seconds per image. They studied the kinetics of the cell wall of E. coli exposed to antimicrobial peptides, achieving an unprecedented

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insight in the dynamics of the ultrastructural damage to the bacterial cell wall. In fact, they

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highlighted a two-step killing process: a time-variable incubation phase (that can last between seconds and minutes) followed by a relatively fast (less than one minute) execution phase.(Fantner

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et al., 2010) (Figure 5)

In addition, to these more conventional applications, the cantilever itself can be used as a very precise and local force sensor, capable of measuring forces with extremely high resolution. In this

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mode of operation, the AFM tip is pressed on the sample’s surface and the cantilever can measure the applied forces in order to determine the mechanical properties of the sample under investigation

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with a pN force resolution (force-curve).(Weisenhorn et al., 1989) These force sensors can be employed to measure intermolecular forces (covalent and non-covalent bonds), antigen-antibody bonding, or the nanomechanical properties of specimens, including living bacteria (Longo et al.,

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2012)and cells(Roduit et al., 2012).

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Notably, the force curves recorded on multiple locations over a surface can reconstruct spatially resolved maps of the physical and mechanical properties of the cell with nanometer scale resolution

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(force volume maps)(Radmacher et al., 1994 ). Modern AFMs can produce, in parallel, maps of the morphology, of the elasticity and of the adhesive properties of bacteria. This combination of morphological and nanomechanical information obtained in the force-volume maps with nanometer resolution, is called ultrastructural characterization. Up to very recently, the force-volume AFM

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modality had been plagued by low temporal and lateral resolution. A single force curve typically requires several tens of milliseconds to be completed, as consequence force volume images have been a compromise between long completion times (from several minutes to several hours) or small number of points (32x32 or 64x64 pixel images are commonly reported). Luckily, many technological solutions to solve such drawback have been developed and several AFM manufacturers have introduced faster modalities specifically conceived to perform high-resolution force-volume maps in minutes. For example, JPK (Germany) has equipped its latest Nanowizard III microscope with a quantitative imaging modality (QI mode), which can collect 512x512 point force-volume images in minutes.(Chopinet et al., 2013) Remarkably, these improved force-volume modes can be used to obtain rapidly information on living bacteria, with a spatial resolution that is unachievable using other techniques. Since, the AFM tip is a nanosized sensor placed directly in contact with the living bacterium, it can give a large array of information on the surface of the

ACCEPTED MANUSCRIPT bacterium, and even some insight in its internal composition.(Longo et al., 2012, Roduit et al., 2009) In particular, we have exploited this capability on the study of the mechanisms of action of

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antibiotics and in the determination of the morphological and nanomechanical response

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mechanisms of the resistant bacteria. In some of these works, we focused on the mechanical properties of living E. coli, by operating in force-volume (FV) modality(Longo et al., 2012, Longo

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et al., 2013) and were able to monitor the stiffness of their membrane when exposed to different media, including a buffer containing a bactericidal dose of ampicillin. (Figure 6)

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5. Conclusions

The fight against bacterial infections is arguably one of the major healthcare issues of our century.

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Bacterial infections cause millions of deaths every year, both in developing and developed regions. The insurgence of resistances to antibiotics and of multiresistant pathogens is alarming and our best weapons, antibiotics, are starting to lose their effectiveness. Thus, there is a large need for new

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technological tools capable of performing rapid and reliable identification and susceptibility testing.

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This would allow studying the origin of resistances and characterizing the bacterial metabolism in order to exploit this information to develop new antibacterial protocols and agents.

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In this review we have summarized and briefly described some of the new and exciting options that are now emerging to achieve a rapid, accurate and cost-effective AST system. Such a fast diagnostic tool would be used to determine an effective treatment and would, therefore, reduce the risks associated with emerging bacterial resistances. Up to now, the molecular identification

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systems, coupled with the semi-automated susceptibility assays, hold the promise to affect, in the very near future, the clinical protocols. On the other hand, on a more long-term vision, new sensors, based on nanomechanical oscillators or soft micro pedestals, have the potential to achieve a higher throughput and to deliver a faster complete bacterial characterization, all in less than one working day. This could pave the way to the development of innovative point-of-care systems and will allow rapid, cost-effective and, possibly, personalized treatments not only in the developed regions but also in the developing areas were the fight against bacterial infections is most challenging.

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Figure 1. Schematic representation of a conventional AST/ID analysis. From the collection of the sample to the ID and the AST or using MALDI-TOF MS and semiatutomated systems. The overall time scale is well beyond the two working days. Artwork from G. Longo

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Figure 2: The number of identified microbial species from 1979 to 2012. The development of new technologies has had a substantial impact on the number of microbial species that are identified each year. Obtained with permission from (Fournier et al., 2013)

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Figure 3. K. pneumoniae and VRE occupy a fraction of the total available space in the colon. (A-E) Visualization of bacterial localization by FISH. Entire colon cross-sections from untreated mice (A) and mice treated with ampicillin for 3 weeks (B) were stained with a universal probe that targets the 16S rRNA gene of all bacteria. Cross-sections from ampicillin-treated mice colonized with K. pneumoniae (C) or VRE (D) for 21 days were hybridized with probes specific for K. pneumoniae (Kpn) and Enterococcus, respectively. Sections were counterstained with Hoechst dye to visualize nuclei. Images are representative of 5 mice per group. Scale bar, 500 μm. (E) Number of bacteria per unit area of whole colon cross-sections. n = 3 per group. ND = non-detectable. Error bars (mean ± SEM). **P<0.005, ***P<0.0005 by the Mann-Whitney test. Obtained from (Caballero et al., 2015)

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Figure 4. Schematics of a typical nanomotion experiment. The protocol starts from the incubation step, left panel, and ends at the AST performed using the nanomotion sensor, right panel. Artwork from G. Longo.

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Figure 5. Time series of CM15 antimicrobial action. CM15 injected at t = −6 s and images recorded every 13 s, with a resolution of 1,024 × 256 pixels and a rate of 20 lines s−1. The surface of the upper bacterium (1) starts changing within 13 s. The lower bacterium (2) resists changing for 78 s. b, Larger-area view recorded 12 min after addition of CM15. Most bacteria are corrugated, but some are still smooth. c, High-resolution image of bacterium 3 showing that this bacterium is still smooth at t = 16 min. d, Image of the now corrugated bacterium 3 at t = 30 min. Eventually, all bacteria in the field of view are affected by CM15. Images were recorded in liquid in tapping mode with a tapping frequency of 110 kHz. Phase images are shown here for high contrast. Images b–d were recorded with a resolution of 1,024 × 256 pixels at 2 lines s−1. Obtained with permission from (Fantner et al., 2010) Figure 6. Ultrastructural characterization of E.coli membranes exposed to ampicillin. Panel A: 5×5 μm, 32×32 pixel topography image of a single E. coli in PBS. Panel B: corresponding stiffness image evidencing that the mechanical properties are uniform throughout most of the bacterial membrane, except two well-defined stiffer areas. Panel C: histogram of the stiffness values obtained from several images collected on the very same area. Two curves are evidenced: in red the membrane contribution and in black the peak of the substrate stiffness. Panel D: 5×5 μm, 32×32 pixel topography image of the very same E. coli imaged after introduction of ampicillin. Panel E: there is a reduction of the overall stiffness of the two stiff areas. Panel F: The substrate peak has moved towards lower stiffness values. Panel G: 5×5 μm, 32×32 pixel topography image of the same E. coli, deflated after introduction of LB. Panel H: one of the two stiff areas has disappeared and the other shows reduced stiffness. Panel I: the membrane peak indicated a dramatic reduction of the stiffness of the entire membrane. Obtained with permission from (Longo et al., 2013)

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Reducing the emergence and spread of antibiotic-resistant bacteria is one of the major healthcare issues of our century. There is an urgent need for new technologies to identify infections and assess rapidly drug susceptibility in bacteria. Here we discuss the most promising recent innovations in this field with particular focus on MALDI-TOF MS, semi-automated commercial systems and nanomechanical sensors, which constitute a step towards the development of rapid and affordable point-of-care devices and techniques.

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Graphical abstract

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The fight against bacterial infections and multi resistant bacteria is one of the major healthcare issues of our time There is a need for new rapid and reliable techniques to perform bacterial identification and susceptibility test We have reviewed different innovative molecular and phenotypic techniques that are currently considered for the study of bacterial infections MALDI-TOF MS is the fundamental technique for bacterial identification, but is now used in combination with other techniques to discriminate between susceptible and resistant strains Semi automated phenotypic techniques are altready used in clinical laboratories around the world, but their reliability in some particular cases requires the concurrent use of conventional susceptibility technques. Nanomechanical sensors have the potentiality to constitute the next player in the field of rapid susceptibility tests. Having both molecular and phenotypic applications, these sensors hold the promise to lead to point-of-care systems.

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