Synergy between silk fibroin and ionic liquids for active gas-sensing materials.

Silk fibroin is a biobased material with excellent biocompatibility and mechanical properties, but its use in bioelectronics is hampered by the difficult dissolution and low intrinsic conductivity. Some ionic liquids are known to dissolve fibroin but removed after fibroin processing. However, ionic liquids and fibroin can cooperatively give rise to functional materials, and there are untapped opportunities in this combination. The dissolution of fibroin, followed by gelation, in designer ionic liquids from the imidazolium chloride family with varied alkyl chain lengths (2-10 carbons) is shown here. The alkyl chain length of the anion has a large impact on fibroin secondary structure which adopts unconventional arrangements, yielding robust gels with distinct hierarchical organization. Furthermore, and due to their remarkable air-stability and ionic conductivity, fibroin ionogels are exploited as active electrical gas sensors in an electronic nose revealing the unravelled possibilities of fibroin in soft and flexible electronics.

Tackling Humidity with Designer Ionic Liquid-Based Gas Sensing Soft Materials.

Relative humidity is simultaneously a sensing target and a contaminant in gas and volatile organic compound (VOC) sensing systems, where strategies to control humidity interference are required. An unmet challenge is the creation of gas-sensitive materials where the response to humidity is controlled by the material itself. Here, humidity effects are controlled through the design of gelatin formulations in ionic liquids without and with liquid crystals as electrical and optical sensors, respectively. In this design, the anions [DCA]- and [Cl]- of room temperature ionic liquids from the 1-butyl-3-methylimidazolium family tailor the response to humidity and, subsequently, sensing of VOCs in dry and humid conditions. Due to the combined effect of the materials formulations and sensing mechanisms, changing the anion from [DCA]- to the much more hygroscopic [Cl]- , leads to stronger electrical responses and much weaker optical responses to humidity. Thus, either humidity sensors or humidity-tolerant VOC sensors that do not require sample preconditioning or signal processing to correct humidity impact are obtained. With the wide spread of 3D- and 4D-printing and intelligent devices, the monitoring and tuning of humidity in sustainable biobased materials offers excellent opportunities in e-nose sensing arrays and wearable devices compatible with operation at room conditions.

Stable and Oriented Liquid Crystal Droplets Stabilized by Imidazolium Ionic Liquids.

Liquid crystals represent a fascinating intermediate state of matter, with dynamic yet organized molecular features and untapped opportunities in sensing. Several works report the use of liquid crystal droplets formed by microfluidics and stabilized by surfactants such as sodium dodecyl sulfate (SDS). In this work, we explore, for the first time, the potential of surface-active ionic liquids of the imidazolium family as surfactants to generate in high yield, stable and oriented liquid crystal droplets. Our results show that [C12MIM][Cl], in particular, yields stable, uniform and monodisperse droplets (diameter 74 ± 6 µm; PDI = 8%) with the liquid crystal in a radial configuration, even when compared with the standard SDS surfactant. These findings reveal an additional application for ionic liquids in the field of soft matter.

Optical Gas Sensing with Liquid Crystal Droplets and Convolutional Neural Networks.

Liquid crystal (LC)-based materials are promising platforms to develop rapid, miniaturised and low-cost gas sensor devices. In hybrid gel films containing LC droplets, characteristic optical texture variations are observed due to orientational transitions of LC molecules in the presence of distinct volatile organic compounds (VOC). Here, we investigate the use of deep convolutional neural networks (CNN) as pattern recognition systems to analyse optical textures dynamics in LC droplets exposed to a set of different VOCs. LC droplets responses to VOCs were video recorded under polarised optical microscopy (POM). CNNs were then used to extract features from the responses and, in separate tasks, to recognise and quantify the vapours exposed to the films. The impact of droplet diameter on the results was also analysed. With our classification models, we show that a single individual droplet can recognise 11 VOCs with small structural and functional differences (F1-score above 93%). The optical texture variation pattern of a droplet also reflects VOC concentration changes, as suggested by applying a regression model to acetone at 0.9-4.0% (v/v) (mean absolute errors below 0.25% (v/v)). The CNN-based methodology is thus a promising approach for VOC sensing using responses from individual LC-droplets.

Ionogels Based on a Single Ionic Liquid for Electronic Nose Application.

Ionogel are versatile materials, as they present the electrical properties of ionic liquids and also dimensional stability, since they are trapped in a solid matrix, allowing application in electronic devices such as gas sensors and electronic noses. In this work, ionogels were designed to act as a sensitive layer for the detection of volatiles in a custom-made electronic nose. Ionogels composed of gelatin and a single imidazolium ionic liquid were doped with bare and functionalized iron oxide nanoparticles, producing ionogels with adjustable target selectivity. After exposing an array of four ionogels to 12 distinct volatile organic compounds, the collected signals were analyzed by principal component analysis (PCA) and by several supervised classification methods, in order to assess the ability of the electronic nose to distinguish different volatiles, which showed accuracy above 98%.

Microfluidics in Gas Sensing and Artificial Olfaction.

Rapid, real-time, and non-invasive identification of volatile organic compounds (VOCs) and gases is an increasingly relevant field, with applications in areas such as healthcare, agriculture, or industry. Ideal characteristics of VOC and gas sensing devices used for artificial olfaction include portability and affordability, low power consumption, fast response, high selectivity, and sensitivity. Microfluidics meets all these requirements and allows for in situ operation and small sample amounts, providing many advantages compared to conventional methods using sophisticated apparatus such as gas chromatography and mass spectrometry. This review covers the work accomplished so far regarding microfluidic devices for gas sensing and artificial olfaction. Systems utilizing electrical and optical transduction, as well as several system designs engineered throughout the years are summarized, and future perspectives in the field are discussed.

Affinity-Triggered Assemblies Based on a Designed Peptide-Peptide Affinity Pair.

Affinity-triggered assemblies rely on affinity interactions as the driving force to assemble physically crosslinked networks. WW domains are small hydrophobic proteins binding to proline-rich peptides that are typically produced in the insoluble form. Previous works attempted the biological production of the full WW domain in tandem to generate multivalent components for affinity-triggered hydrogels. In this work, an alternative approach is followed by engineering a 13-mer minimal version of the WW domain that retains the ability to bind to target proline-rich peptides. Both ligand and target peptides are produced chemically and conjugated to multivalent polyethylene glycol, yielding two components. Upon mixing together, they form soft biocompatible affinity-triggered assemblies, stable in stem cell culture media, and display mechanical properties in the same order of magnitude as for those hydrogels formed with the full WW protein in tandem.

Free Marine Natural Products Databases for Biotechnology and Bioengineering.

Marine organisms and micro-organisms are a source of natural compounds with unique chemical features. These chemical properties are useful for the discovery of new functions and applications of marine natural products (MNPs). To extensively exploit the potential implementations of MNPs, they are gathered in chemical databases that allow their study and screening for applications of biotechnological interest. However, the classification of MNPs is currently poor in generic chemical databases. The present availability of free-access-focused MNP databases is scarce and the molecular diversity of these databases is still very low when compared to the paid-access ones. In this review paper, the current scenario of free-access MNP databases is presented as well as the hindrances involved in their development, mainly compound dereplication. Examples and opportunities for using freely accessible MNP databases in several important areas of biotechnology are also assessed. The scope of this paper is, as well, to notify the latent potential of these information sources for the discovery and development of new MNPs in biotechnology, and push future efforts to develop a public domain MNP database freely available for the scientific community.

Enhanced Gas Sensing with Soft Functional Materials.

The materials described in this work result from the self-assembly of liquid crystals and ionic liquids into droplets, stabilized within a biopolymeric matrix. These systems are extremely versatile gels, in terms of composition, and offer potential for fine tuning of both structure and function, as each individual component can be varied. Here, the characterization and application of these gels as sensing thin films in gas sensor devices is presented. The unique supramolecular structure of the gels is explored for molecular recognition of volatile organic compounds (VOCs) by employing gels with distinct formulations to yield combinatorial optical and electrical responses used in the distinction and identification of VOCs.

Effect of film thickness in gelatin hybrid gels for artificial olfaction.

Artificial olfaction is a fast-growing field aiming to mimic natural olfactory systems. Olfactory systems rely on a first step of molecular recognition in which volatile organic compounds (VOCs) bind to an array of specialized olfactory proteins. This results in electrical signals transduced to the brain where pattern recognition is performed. An efficient approach in artificial olfaction combines gas-sensitive materials with dedicated signal processing and classification tools. In this work, films of gelatin hybrid gels with a single composition that change their optical properties upon binding to VOCs were studied as gas-sensing materials in a custom-built electronic nose. The effect of films thickness was studied by acquiring signals from gelatin hybrid gel films with thicknesses between 15 and 90 µm when exposed to 11 distinct VOCs. Several features were extracted from the signals obtained and then used to implement a dedicated automatic classifier based on support vector machines for data processing. As an optical signature could be associated to each VOC, the developed algorithms classified 11 distinct VOCs with high accuracy and precision (higher than 98%), in particular when using optical signals from a single film composition with 30 µm thickness. This shows an unprecedented example of soft matter in artificial olfaction, in which a single gelatin hybrid gel, and not an array of sensing materials, can provide enough information to accurately classify VOCs with small structural and functional differences.

Identification and Antibiotic-Susceptibility Profiling of Infectious Bacterial Agents: A Review of Current and Future Trends.

Antimicrobial resistance is one of the most worrying threats to humankind with extremely high healthcare costs associated. The current technologies used in clinical microbiology to identify the bacterial agent and profile antimicrobial susceptibility are time-consuming and frequently expensive. As a result, physicians prescribe empirical antimicrobial therapies. This scenario is often the cause of therapeutic failures, causing higher mortality rates and healthcare costs, as well as the emergence and spread of antibiotic resistant bacteria. As such, new technologies for rapid identification of the pathogen and antimicrobial susceptibility testing are needed. This review summarizes the current technologies, and the promising emerging and future alternatives for the identification and profiling of antimicrobial resistance bacterial agents, which are expected to revolutionize the field of clinical diagnostics.

Protein- and Peptide-Based Biosensors in Artificial Olfaction.

Animals' olfactory systems rely on proteins, olfactory receptors (ORs) and odorant-binding proteins (OBPs), as their native sensing units to detect odours. Recent advances demonstrate that these proteins can also be employed as molecular recognition units in gas-phase biosensors. In addition, the interactions between odorant molecules and ORs or OBPs are a source of inspiration for designing peptides with tunable odorant selectivity. We review recent progress in gas biosensors employing biological units (ORs, OBPs, and peptides) in light of future developments in artificial olfaction, emphasizing examples where biological components have been employed to detect gas-phase analytes.

Author Correction: Machine learning for the meta-analyses of microbial pathogens' volatile signatures.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Tilapia fish microbial spoilage monitored by a single optical gas sensor.

As consumption of fish and fish-based foods increases, non-destructive monitoring of fish freshness also becomes more prominent. Fish products are very perishable and prone to microbiological growth, not always easily detected by organoleptic evaluation. The analysis of the headspace of fish specimens through gas sensing is an interesting approach to monitor fish freshness. Here we report a gas sensing method for monitoring Tilapia fish spoilage based on the application of a single gas sensitive gel material coupled to an optical electronic nose. The optical signals of the sensor and the extent of bacterial growth were followed over time, and results indicated good correlation between the two determinations, which suggests the potential application of this simple and low cost system for Tilapia fish freshness monitoring.

Machine learning for the meta-analyses of microbial pathogens' volatile signatures.

Non-invasive and fast diagnostic tools based on volatolomics hold great promise in the control of infectious diseases. However, the tools to identify microbial volatile organic compounds (VOCs) discriminating between human pathogens are still missing. Artificial intelligence is increasingly recognised as an essential tool in health sciences. Machine learning algorithms based in support vector machines and features selection tools were here applied to find sets of microbial VOCs with pathogen-discrimination power. Studies reporting VOCs emitted by human microbial pathogens published between 1977 and 2016 were used as source data. A set of 18 VOCs is sufficient to predict the identity of 11 microbial pathogens with high accuracy (77%), and precision (62-100%). There is one set of VOCs associated with each of the 11 pathogens which can predict the presence of that pathogen in a sample with high accuracy and precision (86-90%). The implemented pathogen classification methodology supports future database updates to include new pathogen-VOC data, which will enrich the classifiers. The sets of VOCs identified potentiate the improvement of the selectivity of non-invasive infection diagnostics using artificial olfaction devices.

Tunable Gas Sensing Gels by Cooperative Assembly.

The cooperative assembly of biopolymers and small molecules can yield functional materials with precisely tunable properties. Here, the fabrication, characterization, and use of multicomponent hybrid gels as selective gas sensors are reported. The gels are composed of liquid crystal droplets self-assembled in the presence of ionic liquids, which further coassemble with biopolymers to form stable matrices. Each individual component can be varied and acts cooperatively to tune gels' structure and function. The unique molecular environment in hybrid gels is explored for supramolecular recognition of volatile compounds. Gels with distinct compositions are used as optical and electrical gas sensors, yielding a combinatorial response conceptually mimicking olfactory biological systems, and tested to distinguish volatile organic compounds and to quantify ethanol in automotive fuel. The gel response is rapid, reversible, and reproducible. These robust, versatile, modular, pliant electro-optical soft materials possess new possibilities in sensing triggered by chemical and physical stimuli.

Integration of Molecular Dynamics Based Predictions into the Optimization of De Novo Protein Designs: Limitations and Benefits.

Recent advances in de novo protein design have gained considerable insight from the intrinsic dynamics of proteins, based on the integration of molecular dynamics simulations protocols on the state-of-the-art de novo protein design protocols used nowadays. With this protocol we illustrate how to set up and run a molecular dynamics simulation followed by a functional protein dynamics analysis. New users will be introduced to some useful open-source computational tools, including the GROMACS molecular dynamics simulation software package and ProDy for protein structural dynamics analysis.

The future of protein scaffolds as affinity reagents for purification.

Affinity purification is one of the most powerful separation techniques extensively employed both at laboratory and production scales. While antibodies still represent the gold standard affinity reagents, others derived from non-immunoglobulin scaffolds emerged as interesting alternatives in particular for affinity purification. The lower costs of production, fast ligand development, and high robustness are appealing advantages of non-immunoglobulin scaffolds. These have successfully been used in the affinity purification of relevant targets as antibodies, human serum albumin, transferrin, and other biomarkers, as reviewed in this work. Furthermore, a critical assessment on the strengths, weaknesses, opportunities, and threats related with the implementation of non-immunoglobulin scaffolds as ligands in affinity purification are discussed. Biotechnol. Bioeng. 2017;114: 481-491. © 2016 Wiley Periodicals, Inc.

Petasis-Ugi ligands: New affinity tools for the enrichment of phosphorylated peptides.

Affinity chromatography is a widespread technique for the enrichment and isolation of biologics, which relies on the selective and reversible interaction between affinity ligands and target molecules. Small synthetic affinity ligands are valuable alternatives due to their robustness, low cost and fast ligand development. This work reports, for the first time, the use of a sequential Petasis-Ugi multicomponent reaction to generate rationally designed solid-phase combinatorial libraries of small synthetic ligands, which can be screened for the selection of new affinity adsorbents towards biological targets. As a proof of concept, the Petasis-Ugi reaction was here employed in the discovery of affinity ligands suitable for phosphopeptide enrichment. A combinatorial library of 84 ligands was designed, synthesized on a chromatographic solid support and screened in situ for the specific binding of phosphopeptides binding human BRCA1C-terminal domains. The success of the reaction on the chromatographic matrix was confirmed by both inductively coupled plasma atomic emission spectroscopy and fluorescence microscopy. Three lead ligands were identified due to their superior performance in terms of binding capacity and selectivity towards the phosphorylated moiety on peptides, which showed the feasibility of the Petasis-Ugi reaction for affinity ligand development.

Mimicking nature: Phosphopeptide enrichment using combinatorial libraries of affinity ligands.

Phosphorylation is a reversible post-translational modification of proteins that controls a plethora of cellular processes and triggers specific physiological responses, for which there is a need to develop tools to characterize phosphorylated targets efficiently. Here, a combinatorial library of triazine-based synthetic ligands comprising 64 small molecules has been rationally designed, synthesized and screened for the enrichment of phosphorylated peptides. The lead candidate (coined A8A3), composed of histidine and phenylalanine mimetic components, showed high binding capacity and selectivity for binding mono- and multi-phosphorylated peptides at pH 3. Ligand A8A3 was coupled onto both cross-linked agarose and magnetic nanoparticles, presenting higher binding capacities (100-fold higher) when immobilized on the magnetic support. The magnetic adsorbent was further screened against a tryptic digest of two phosphorylated proteins (α- and ß-caseins) and one non-phosphorylated protein (bovine serum albumin, BSA). The MALDI-TOF mass spectra of the eluted peptides allowed the identification of nine phosphopeptides, comprising both mono- and multi-phosphorylated peptides.