Multidrug-resistant bacteria stem from the massive use of non-specific antibiotics prescribed to manage bacterial infections. The therapeutic use of viruses called bacteriophages is a promising complementary and personalised strategy requiring very accurate phage selection for patient administration. Therefore, we are developing an interdisciplinary methodology for phage susceptibility testing (PST) based on bio-photonic microsystems. We demonstrated the use of on-chip optical photonic crystals on silicon-on-insulator (SOI) for the spatial confinement of bacteria and phages. We will present our state of the art of this project and the methods currently used to study the interactions between SOI and biological objects.
Antibiotic resistance is a critical public health concern requiring fast, affordable, and reliable diagnostic methods. This study focuses on identifying optimal wavelengths for multispectral imaging in antibiotic susceptibility testing. Deuterium isotope probing and FTIR spectroscopy were used to analyze the metabolic impact of antibiotics on bacteria. Characteristic wavelengths indicating variations in bacterial metabolism were identified. This approach holds promise for expedited antibiotic sensitivity assessment, potentially delivering results within two hours. The utilization of multispectral imaging presents a cost-effective and innovative tool for bacterial identification and combating antibiotic resistance.
We will show results towards a new method to perform antibiotic or phage susceptibility test with single phages or bacteria trapped in an optical chip. The system used is a photonic chip containing photonic crystal hollow cavities topped by a microfluidic system allowing the transport of bacteria and phages. We will report the optical signature of the trapping of bacteria and phages in the transmitted light exciting the optical trap. This allows the distinction of different phages families as well as the level of stress or death of a single bacteria in the presence of antibiotics or phages.
The proliferation of multiresistant bacteria is having an increasing and profound impact on the world. A credible alternative to antibiotics is bacteriophage therapy, which are expected in the near future to form the basis of an entirely new treatment paradigm for infectious diseases. In order to facilitate such an epochal transition, new tools are needed for the rapid and multiplexed screening of large libraries of candidate bacteriophages in order to provide a personalized bacteriophage cocktail for each patient. This talk presents recent progress towards the development of a SPR-based screening method, wherein immobilized bacteriophages form a biosensing layer which produces a measurable surface plasmon resonance signal as a result of the specific interaction between the bacteriophages and their host bacterial cells in a microfluidic flow above the sensor surface.
Identifying the microbial species present in a sample is critical in healthcare, industry, ecology and even national security. The traditional diagnosis process involves the growth of colonies of microorganisms on a solid-state medium in a Petri dish. This step provides great amounts of biological material, allows spatial separation of the different microorganisms and can help to visually discriminate potentially harmful species. However, it does not allow a precise identification and thereby requires further sample preparation and analysis to offer a proper diagnosis. Here, a new optical-based Petri dish analysis technology is discussed. This technique, called lensless multispectral mid-infrared imaging, relies on the acquisition of images at nine wavelengths corresponding to relevant chemical functions. It provides both morphological and discrete spectral data, which allows to discriminate even closely related species. The instrument is simply made of a laser source (four quantum cascade lasers) and a microbolometer array as the imager. A total of 1050 colonies belonging to three Staphylococcus species and two strains of Staphylococcus epidermidis have been acquired. After feature extraction and classification by Support Vector Machine, the tenfold cross-validation test yields a correct identification rate between 93 % and 96 %, with only a 5 % confusion between the two strains of S. epidermidis. Further work on the data analysis algorithms could dramatically improve these already promising results. Therefore, considering its label-free and non-destructive aspects, as well as its absence of secondary sample preparation, this technology has a great potential to offer precise Petri-dish based diagnosis.
Microbial identification is a critical process aiming at identifying the species contained in a biological sample, with applications in healthcare, industry or even national security. Traditionally, this process relies either on MALDI-TOF mass spectroscopy, on biochemical tests and on the observation of the morphology of colonies after growth on a Petri dish. Here is presented an innovative method for label-free optical identification of pathogens, based on the multispectral infrared imaging of colonies. This lensless imaging technique enables a high-throughput analysis and wide-field analysis of agar plates. It could yield very high correct identification rates as it relies on an optical fingerprint gathering both spectroscopic and morphologic features. The setup consists of a Quantum Cascade Lasers light source and an imager, a square 2.72 by 2.72 mm uncooled bolometer array. Microorganisms to be analyzed are streaked on a porous growth support compatible with infrared imaging, laid on top of an agar plate for incubation. When imaging is performed, growth support is put in close contact with the imaging sensor and illuminated at different wavelengths. After acquisition, an image descriptor based on spectral and morphological features is extracted for each microbial colony. Supervised classification is finally performed with a Support Vector Machine algorithm and tested with tenfold cross-validation. A first database collecting 1012 multispectral images of colonies belonging to five different species has already been acquired with this system, resulting in a correct identification rate of 92%. For these experiments, multispectral images are acquired at nine different wavelengths, between 5.6 and 8 μm. Considering the optimization possibilities of the image descriptors currently used and the ongoing development of the uncooled bolometers technology, these very first results are promising and could be dramatically improved with further experiments. Thereby, mid-infrared multispectral lensless imaging has the potential to become a fast and precise Petri dish analysis technology.
With the rise of antibiotic resistance, phage therapy is seen as a promising alternative to cure infection to multiresistant bacteria strains. However, phage susceptibility tests currently carried out are time-consuming and are not compliant with the automated environment of hospital laboratories. In this work, we present a method for phage susceptibility testing through optical density measurement with the use of a lensless imaging technique. Fluid assays containing bacteria and phages are loaded in the wells of a 5mm-thick custom-made microfluidic card. The card is put on a 3.3 cm2 CMOS imaging sensor taken from a CANON dslr camera. It is illuminated by a screen paired with a 560 nm spectral filter to provide a homogeneous monochromatic lighting over the whole sensor area. Thanks to the large imaging area of the CMOS sensor, it is possible to simultaneously monitor the level of light transmitted through the well of the microfluidic card and hence to compute the optical density of a dozen sample without the need of mechanical elements. We thus monitor the decay or increase of optical density to determine respectively the lysis or growth of the bacteria under test. This method provides a reliable result of optical phage susceptibility testing in less than 4 hours. The prototype shown here is compact, inexpensive (<1 k€) and is compliant with automated environment of hospital laboratories. Moreover, it is versatile and can be used for other application such as lysis plaque imaging to provide a fast measurement of a viral titer of a bacteriophage suspension.
With the rise of antibiotic resistance, phage therapy is seen as a promising alternative to cure infection to multiresistant bacteria strains. However, phage susceptibility tests currently carried out are time-consuming and are not compliant with the automated environment of hospital laboratories.
In this work, we present a method for phage susceptibility testing through optical density measurement with the use of lensless imaging technique. Using a 3.3 cm2 area CANON sensor and a custom test card, we are able to simultaneously monitor the bacterial growth or inhibition of multiple bacterial/phage samples and to provide reliable results in less than 4 hour.
Spontaneous Raman scattering is a reliable technique for fast identification of single bacterial cells, when spectra are acquired in laboratory conditions where bacteria growth and state are controlled. We have developed a multi-modal system combining Raman spectroscopy and darkfield imaging, aiming at analysing environmental samples, typically in the field context of biological pathogens detection. Such samples are heterogeneous, both in terms of phenotype content and environmental matrix, even after a preliminary purification step. In this paper, we report a study on the identification of Bacillus Thuriengensis (BT) mimicing pathogen bacteria, embedded in a real-world matrix: a sample of surface water enriched with environmental bacterial species. The purpose is to evaluate both the detection limit of aging BT over time and the false alarm rate, in the conditions of our experiment.
The development of methods for the rapid analysis of pathogenic bacteria or viruses is of crucial interest in the clinical diagnosis of infectious diseases. In the last decade, optical resonators integrated with microfluidic layers arose as promising tools for biological analysis, notably thanks to their ability to trap objects with low powers, beneath the damage threshold of biological entities, and with a small footprint. Moreover, the resonant nature of optical cavities allows for the simultaneous acquisition of information on the trapped objects, thanks to the feedback effect induced by the specimen on the trapping field itself.
Here we report on the trapping and on the Gram-type differentiation of seven types of living bacteria in an optofluidic system based on an optical cavity consisting in a large hole in a 2D silicon photonic crystal membrane. The hollow nature of the resonant cavity results in a large overlap between the confined field and the hollow volume, allowing for a maximum interaction between the trapping field and the trapped cell. The optical cavity was excited at the resonance wavelength and the shift induced by the trapped bacteria was analysed. To test the trapping capabilities of our structure, we investigated seven types of bacteria, featuring different morphologies, Gram-types and mobilities (presence or absence of flagella). The analysis of the resonance shift yielded Gram typing in a label-free and not destructive way, due to differences in the refractive index and in the deformability of the cell wall. In particular, Gram negative bacteria showed a larger shift.
Antibiotic resistance kills an estimated 700,000 people each year worldwide and experts predict that this number could hit 10 million by 2050. Rapid diagnostics would play an essential role in the fight against this alarming phenomenon by improving the way in which antibiotherapy is used, notably by stopping the unnecessary use of antibiotics. Clinical microbiology has relied on culture as the standard method for characterizing pathogens over the past century. This process is time-consuming and requires large biomasses. In this context, single-cell monitoring would be a significant breakthrough compared to Petri dishes culture. A first step was achieved by the demonstration of single bacterium trapping by optical tweezers and integrated photonics. Here, the nondestructive real-time state monitoring of a single alive trapped bacterium is demonstrated. In order to achieve this, a two-laser setup was developed to simultaneously trap and monitor a single bacterium in the near-field of a nanobeam microcavity. While the first laser is used to excite the optical field tweezing the bacterium, the second laser probes the cavity resonance spectrum. The bacterium optical interaction with the resonant cavity mode allows to assess the bacterium state in real time when subjected to an antibacterial agent (antibiotics, alcohol, temperature). Confronted to standards culture-based methods, this optical label-free approach yields relevant information about bacterial viability, without time-consuming culture or staining.
Those results evidence that on-chip devices operating at telecom wavelength may greatly enhance the monitoring of bacteria in the near future leading to major improvements in health care diagnosis and patient treatments.
Elastic Light Scattering (ELS) is an innovative technique to identify bacterial pathogens directly on culture plates. Compelling results have already been reported for agri-food applications. Here, we have developed ELS for clinical diagnosis, starting with Staphylococcus aureus early screening. Our goal is to bring a result (positive/negative) after only 6 h of growth to fight surgical-site infections. The method starts with the acquisition of the scattering pattern arising from the interaction between a laser beam and a single bacterial colony growing on a culture medium. Then, the resulting image, considered as the bacterial species signature, is analyzed using statistical learning techniques. We present a custom optical setup able to target bacterial colonies with various sizes (30-500 microns). This system was used to collect a reference dataset of 38 strains of S. aureus and other Staphyloccocus species (5459 images) on ChromIDSAID/ MRSA bi-plates. A validation set from 20 patients has then been acquired and clinically-validated according to chromogenic enzymatic tests. The best correct-identification rate between S. aureus and S. non-aureus (94.7%) has been obtained using a support vector machine classifier trained on a combination of Fourier-Bessel moments and Local- Binary-Patterns extracted features. This statistical model applied to the validation set provided a sensitivity and a specificity of 90.0% and 56.9%, or alternatively, a positive predictive value of 47% and a negative predictive value of 93%. From a clinical point of view, the results head in the right direction and pave the way toward the WHO’s requirements for rapid, low-cost, and automated diagnosis tools.
We report here on the ability of elastic light scattering in discriminating Gram+, Gram- and yeasts at an early stage of growth (6h). Our technique is non-invasive, low cost and does require neither skilled operators nor reagents. Therefore it is compatible with automation. It is based on the analysis of the scattering pattern (scatterogram) generated by a bacterial microcolony growing on agar, when placed in the path of a laser beam. Measurements are directly performed on closed Petri dishes.
The characteristic features of a given scatterogram are first computed by projecting the pattern onto the Zernike orthogonal basis. Then the obtained data are compared to a database so that machine learning can yield identification result. A 10-fold cross-validation was performed on a database over 8 species (15 strains, 1906 scatterograms), at 6h of incubation. It yielded a 94% correct classification rate between Gram+, Gram- and yeasts. Results can be improved by using a more relevant function basis for projections, such as Fourier-Bessel functions. A fully integrated instrument has been installed at the Grenoble hospital’s laboratory of bacteriology and a validation campaign has been started for the early screening of MSSA and MRSA (Staphylococcus aureus, methicillin-resistant S. aureus) carriers.
Up to now, all the published studies about elastic scattering were performed in a forward mode, which is restricted to transparent media. However, in clinical diagnostics, most of media are opaque, such as blood-supplemented agar. That is why we propose a novel scheme capable of collecting back-scattered light which provides comparable results.
In this paper we present a longitudinal study of bacteria metabolism performed with a novel Raman spectrometer system.
Longitudinal study is possible with our Raman setup since the overall procedure to localize a single bacterium and
collect a Raman spectrum lasts only 1 minute. Localization and detection of single bacteria are performed by means of
lensfree imaging, whereas Raman signal (from 600 to 3200 cm-1) is collected into a prototype spectrometer that allows
high light throughput (HTVS technology, Tornado Spectral System). Accomplishing time-lapse Raman spectrometry
during growth of bacteria, we observed variation in the net intensities for some band groups, e.g. amides and proteins.
The obtained results on two different bacteria species, i.e. Escherichia coli and Bacillus subtilis clearly indicate that
growth affects the Raman chemical signature. We performed a first analysis to check spectral differences and
similarities. It allows distinguishing between lag, exponential and stationary growth phases. And the assignment of
interest bands to vibration modes of covalent bonds enables the monitoring of metabolic changes in bacteria caused by
growth and aging. Following the spectra analysis, a SVM (support vector machine) classification of the different growth
phases is presented.
In sum this longitudinal study by means of a compact and low-cost Raman setup is a proof of principle for routine
analysis of bacteria, in a real-time and non-destructive way. Real-time Raman studies on metabolism and viability of
bacteria pave the way for future antibiotic susceptibility testing.
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