Cheminformatics Study on Structural and Bactericidal Activity of Latest Generation ß-Lactams on Widespread Pathogens.

Raman spectra of oxacillin (OXN), carbenicillin (CBC), and azlocillin (AZL) are reported for the first time together with their full assignment of the normal modes, as calculated using Density Functional Theory (DFT) methods with the B3LYP exchange-correlation functional coupled to the 6-31G(d) and 6-311+G(2d,p) basis sets. Molecular docking studies were performed on five penicillins, including OXN, CBC, and AZL. Subsequently, their chemical reactivity and correlated efficiency towards specific pathogenic strains were revealed by combining frontier molecular orbital (FMO) data with molecular electrostatic potential (MEP) surfaces. Their bactericidal activity was tested and confirmed on a couple of species, both Gram-positive and Gram-negative, by using the disk diffusion method. Additionally, a surface-enhanced Raman spectroscopy (SERS)-principal component analysis (PCA)-based resistogram of A. hydrophila is proposed as a clinically relevant insight resulting from the synergistic cheminformatics and vibrational study on CBC and AZL.

Detection and Characterization of Nodularin by Using Label-Free Surface-Enhanced Spectroscopic Techniques.

Nodularin (NOD) is a potent toxin produced by Nodularia spumigena cyanobacteria. Usually, NOD co-exists with other microcystins in environmental waters, a class of cyanotoxins secreted by certain cyanobacteria species, which makes identification difficult in the case of mixed toxins. Herein we report a complete theoretical DFT-vibrational Raman characterization of NOD along with the experimental drop-coating deposition Raman (DCDR) technique. In addition, we used the vibrational characterization to probe SERS analysis of NOD using colloidal silver nanoparticles (AgNPs), commercial nanopatterned substrates with periodic inverted pyramids (KlariteTM substrate), hydrophobic Tienta® SpecTrimTM slides, and in-house fabricated periodic nanotrenches by nanoimprint lithography (NIL). The 532 nm excitation source provided more well-defined bands even at LOD levels, as well as the best performance in terms of SERS intensity. This was reflected by the results obtained with the KlariteTM substrate and the silver-based colloidal system, which were the most promising detection approaches, providing the lowest limits of detection. A detection limit of 8.4 × 10-8 M was achieved for NOD in solution by using AgNPs. Theoretical computation of the complex vibrational modes of NOD was used for the first time to unambiguously assign all the specific vibrational Raman bands.

Characterization of Clinically Relevant Fungi via SERS Fingerprinting Assisted by Novel Chemometric Models.

Nonculture-based tests are gaining popularity and upsurge in the diagnosis of invasive fungal infections (IFI) fostered by their main asset, the reduced analysis time, which enables a more rapid diagnosis. In this project, three different clinical isolates of relevant filamentous fungal species were discriminated by using a rapid (less than 5 min) and sensitive surface-enhanced Raman scattering (SERS)-based detection method, assisted by chemometrics. The holistic evaluation of the SERS spectra was performed by employing appropriate chemometric tools-classical and fuzzy principal component analysis (FPCA) in combination with linear discriminant analysis (LDA) applied to the first relevant principal components. The efficiency of the proposed robust algorithm is illustrated on the data set including three fungal isolates (Aspergillus fumigatus sensu stricto, cryptic A. fumigatus complex species, and Rhizomucor pusillus) that were isolated from patient materials. The accurate and reliable discrimination between species of common fungal pathogen strains suggest that the developed method has the potential as an alternative, spectroscopic-based routine analysis tool in IFI diagnosis.

SERS-based antibiotic susceptibility testing: Towards point-of-care clinical diagnosis.

Emerging antibiotic resistant bacteria constitute one of the biggest threats to public health. Surface-enhanced Raman scattering (SERS) is highly promising for detecting such bacteria and for antibiotic susceptibility testing (AST). SERS is fast, non-destructive (can probe living cells) and it is technologically flexible (readily integrated with robotics and machine learning algorithms). However, in order to integrate into efficient point-of-care (PoC) devices and to effectively replace the current culture-based methods, it needs to overcome the challenges of reliability, cost and complexity. Recently, significant progress has been made with the emergence of both new questions and new promising directions of research and technological development. This article brings together insights from several representative SERS-based AST studies and approaches oriented towards clinical PoC biosensing. It aims to serve as a reference source that can guide progress towards PoC routines for identifying antibiotic resistant pathogens. In turn, such identification would help to trace the origin of sporadic infections, in order to prevent outbreaks and to design effective medical treatment and preventive procedures.

A Review on Integrated ZnO-Based SERS Biosensors and Their Potential in Detecting Biomarkers of Neurodegenerative Diseases.

Surface-enhanced Raman spectroscopy (SERS) applications in clinical diagnosis and spectral pathology are increasing due to the potential of the technique to bio-barcode incipient and differential diseases via real-time monitoring of biomarkers in fluids and in real-time via biomolecular fingerprinting. Additionally, the rapid advancements in micro/nanotechnology have a visible influence in all aspects of science and life. The miniaturization and enhanced properties of materials at the micro/nanoscale transcended the confines of the laboratory and are revolutionizing domains such as electronics, optics, medicine, and environmental science. The societal and technological impact of SERS biosensing by using semiconductor-based nanostructured smart substrates will be huge once minor technical pitfalls are solved. Herein, challenges in clinical routine testing are addressed in order to understand the context of how SERS can perform in real, in vivo sampling and bioassays for early neurodegenerative disease (ND) diagnosis. The main interest in translating SERS into clinical practice is reinforced by the practical advantages: portability of the designed setups, versatility in using nanomaterials of various matter and costs, readiness, and reliability. As we will present in this review, in the frame of technology readiness levels (TRL), the current maturity reached by semiconductor-based SERS biosensors, in particular that of zinc oxide (ZnO)-based hybrid SERS substrates, is situated at the development level TRL 6 (out of 9 levels). Three-dimensional, multilayered SERS substrates that provide additional plasmonic hot spots in the z-axis are of key importance in designing highly performant SERS biosensors for the detection of ND biomarkers.

3D silver metallized nanotrenches fabricated by nanoimprint lithography as flexible SERS detection platform.

We report the development of highly sensitive substrates with great potential as Surface-enhanced Raman scattering (SERS) spectroscopy detection platforms, consisting of nanoimprint lithography (NIL) fabricated nanotrenches in plastic and covered by nanostructured silver (Ag) films with thicknesses in the 10-100 nm range deposited by direct current (DC) sputtering. The Ag film thickness was increased by using sequential deposition times and its contribution to the obtained enhancement factor was determined. The morphological and structural properties of the metalized nanotrenches were assessed by scanning electron microscopy (SEM) and atomic force microscopy (AFM) techniques. Crystal violet (CV) was used as analyte to test the SERS activity of the substrates prepared with or without the nanoimprinted pattern. Our original approach was to determine the resulted SERS enhancement from the synergy of three key aspects: the Ag metallization of cheap, flexible substrates, the effect of increasing the Ag film thickness and the periodic nanotrenches imprinted by NIL as substrate. We found a dramatical contribution in the SERS signal of the periodical Ag nanopattern in comparison to the Ag film quantified by a calculated enhancement factor (EF) up to 107 in case of the SERS detection platform with a 25 nm Ag layer on top of the periodic nanotrenches. The contribution of plasmonic nanostructures contained in the Ag films as well as the contribution of the periodical nanopatterned trenches was assessed, as a cumulative effect to the first contribution. This substrate showed a considerably lower limit of detection (LOD) for SERS, down to 10 pM, much better uniformity as well as more reproducible signals in comparison with the other thicknesses of the metallic film.

Fuzzy characterization and classification of bacteria species detected at single-cell level by surface-enhanced Raman scattering.

Advanced chemometric methods, such as fuzzy c-means, a semi-supervised clustering method, and fuzzy linear discriminant analysis (FLDA), a new robust supervised classification method in combination with principal component analysis (PCA), namely PCA-FLDA, have been successfully applied for characterization and classification of bacterial species detected at single-cell level by surface-enhanced Raman scattering (SERS) spectroscopy. SERS spectra of three species (S. aureus, E. faecalis and P. aeruginosa) were recorded in an original fashion, using in situ laser induced silver spot as metallic substrate. The detection process of bacteria was isolated inside a hermetically sealed in-house built microfluidic device, connected to a syringe pump for injecting the analytes and a portable Raman spectrometer as detection tool. The obtained results (fuzzy partitions) and spectra of the prototypes (robust fuzzy spectra mean corresponding to each fuzzy partition) clearly demonstrated the efficiency and information power of the advanced fuzzy methods in bacteria characterization and classification based on SERS spectra, and allowed a rationale assigning to a specific group. Also, this powerful detection and classification methodology generates the premises for future investigations of Raman and other spectroscopic data obtained for various samples.

Yeast cell wall - Silver nanoparticles interaction: A synergistic approach between surface-enhanced Raman scattering and computational spectroscopy tools.

Candida species are becoming one of the pathogens developing antifungal resistance due to inappropriate treatment and overuse of antimycotic drugs in building construction and agriculture. Further, fungal infections are often difficult to detect, also due to slow in vitro growth of the organisms from clinical specimens. Thus, fast detection and discrimination of yeast cells in direct patient materials is essential for an adequate treatment and success rate. In this work, we investigated Candida species isolated from patients, by using surface-enhanced Raman scattering (SERS) combined with computational spectroscopy tools, aiming to detect and discriminate between the three considered species, Candida albicans, Candida glabrata, and Candida parapsilosis. Density functional theory (DFT) was used to calculate Raman spectra of yeasts' main cell wall components for elucidating the origin of the observed bands. Accurate assignments of normal modes helped for a better understanding of the interaction between silver nanoparticles with yeasts' cell wall. Further, SERS spectra were used as samples in a database on which we performed multivariate analyses. By Principal component analysis (PCA), we obtained a maximum variation of 79% between the three samples. Linear discriminant analysis (LDA) was successfully used to discriminate between the three species.

Size-tunable Au@Ag nanoparticles for colorimetric and SERS dual-mode sensing of palmatine in traditional Chinese medicine.

Palmatine is a protoberberine alkaloid separated from several plants and application as an anti-inflammatory and antibacterial agent in the therapy of gastrointestinal and genitourinary disorder. Thus, the fast quantification of palmatine is important in clinic medical assays. Herein, we report simple, fast and sensitive colorimetric visualization and surface-enhanced Raman spectroscopy (SERS) dual-mode detection of palmatine basing on bimetallic size tunable silver shell capped gold nanoparticles (Au@Ag NPs). Interesting, the best signals output for dual-mode sensing of palmatine were both 5 nm Ag shell thickness of Au@Ag NPs. Meanwhile, we found that the addition of NaHSO4 significantly improves the aggregating sensitivity of Au@Ag NPs to trace palmatine. Upon exposure to 0.1 µM level palmatine, NaHSO4-optimized Au@Ag NPs solution exhibits a highly sensitive color change from orange to green and rapid aggregation kinetics within the initial 5 min, which can directly be seen with the naked eye and monitored by UV-vis absorbance spectra. In addition, we measured palmatine by SERS with the excellent enhancement effect of Au@Ag NPs for further increase the sensitivity and selectivity. More importantly, other protoberberine alkaloids do not interfere with this dual-mode sensor due to the different interaction force between Au@Ag NPs and these alkaloids, and the applicability of the sensor is well demonstrated in real samples with satisfactory results. This provide a fast and simple assay for the rapid detection of palmatine in traditional Chinese medicine, the limit of detection (LOD) is 0.13 µM by the naked eye and 0.10 µM by UV-vis spectroscopy. Therefore, the size-tunable of NaHSO4-optimized Au@Ag NPs can be used not only as a naked-eye sensor of palmatine, but also as a highly selective SERS probe.

Self-Assembly of Au@Ag Nanoparticles on Mussel Shell To Form Large-Scale 3D Supercrystals as Natural SERS Substrates for the Detection of Pathogenic Bacteria.

Herein, we developed a natural surface-enhanced Raman scattering (SERS) substrate based on size-tunable Au@Ag nanoparticle-coated mussel shell to form large-scale three-dimensional (3D) supercrystals (up to 10 cm2) that exhibit surface-laminated structures and crossed nanoplates and nanochannels. The high content of CaCO3 in the mussel shell results in superior hydrophobicity for analyte enrichment, and the crossed nanoplates and nanochannels provided rich SERS hot spots, which together lead to high sensitivity. Finite-difference time-domain simulations showed that nanoparticles in the channels exhibit apparently a higher electromagnetic field enhancement than nanoparticles on the platelets. Thus, under optimized conditions (using Au@AgNPs with 5 nm shell thickness), highly sensitive SERS detection with a detection limit as low as 10-9 M for rhodamine 6G was obtained. Moreover, the maximum electromagnetic field enhancement of different types of 3D supercrystals shows no apparent difference, and Au@AgNPs were uniformly distributed such that reproducible SERS measurements with a 6.5% variation (613 cm-1 peak) over 20 spectra were achieved. More importantly, the as-prepared SERS substrates can be utilized for the fast discrimination of Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa by discriminant analysis. This novel Au@Ag self-assembled mussel shell template holds considerable promise as low-cost, durable, sensitive, and reproducible substrates for future SERS-based biosensors.

A Critical Review on Ultrasensitive, Spectroscopic-based Methods for High-throughput Monitoring of Bacteria during Infection Treatment.

The world is in the midst of a pre-emptive public health emergency, one that is just as dramatic as the global aggressive viruses-related crises (Ebola, Zika, or SARS), but not as visible. The "superbugs" and their antimicrobial resistance do not cause much public alarm or awareness, but provoke financial losses of $100 trillion annually (WHO, http://www.who.int/mediacentre/commentaries/superbugs-action-now/en/ ). This status quo review offers an overview of ultrasensitive methods for high-throughput monitoring of bacteria during infection treatment, the effects of antibiotics on bacteria at single-cell level and the challenges we will face in their detection due to the extraordinary capability of these "superbugs" to gain and constantly improve multiresistance to antibiotics. A special emphasis is put on the ultrasensitive spectroscopic-based analysis techniques, using nanotechnology or not necessarily, that are more and more promising alternatives to conventional culture-based ones. The particular case of Mycobacteria detection is discussed based on recent reported work.

Characterization and Discrimination of Gram-Positive Bacteria Using Raman Spectroscopy with the Aid of Principal Component Analysis.

Raman scattering and its particular effect, surface-enhanced Raman scattering (SERS), are whole-organism fingerprinting spectroscopic techniques that gain more and more popularity in bacterial detection. In this work, two relevant Gram-positive bacteria species, Lactobacillus casei (L. casei) and Listeria monocytogenes (L. monocytogenes) were characterized based on their Raman and SERS spectral fingerprints. The SERS spectra were used to identify the biochemical structures of the bacterial cell wall. Two synthesis methods of the SERS-active nanomaterials were used and the recorded spectra were analyzed. L. casei and L. monocytogenes were successfully discriminated by applying Principal Component Analysis (PCA) to their specific spectral data.