A method for early detection and identification of fungal contamination of building materials using e-nose

Traditional and new proposals for environmental microbial indicators-a review

The continuous increment in world population coupled with the greatest natural resource consumption and waste generation has an enormous impact on the environment. To date, using biological indicators (bioindicators) to evaluate the biological quality of natural environments is very common. Nonetheless, selecting those suitable for each ecosystem or contaminant is one of the most important issues for environmental sciences. Bacteria and helminths are mainly related to fecal contamination, while antibiotic-resistant bacteria, fungi, viruses, and microalgae are organisms used to determine deteriorated ecosystems by diverse contaminants. Nowadays, each bioindicator is used as a specific agent of different contaminant types, but detecting and quantifying these bioindicator microorganisms can be performed from simple microscopy and culture methods up to a complex procedure based on omic sciences. Developing new techniques based on the metabolism and physiological responses of traditional bioindicators is shown in a fast environmental sensitivity analysis. Therefore, the present review focuses on analyzing different bioindicators to facilitate developing suitable monitoring environmental systems according to different pollutant agents. The traditional and new methods proposed to detect and quantify different bioindicators are also discussed. Their vital role is considered in implementing efficient ecosystem bioprospection, restoration, and conservation strategies directed to natural resource management.

Sterility testing of germ-free mouse colonies

In biomedical research, germ-free and gnotobiotic mouse models enable the mechanistic investigation of microbiota-host interactions and their role on (patho)physiology. Throughout any gnotobiotic experiment, standardized and periodic microbiological testing of defined gnotobiotic housing conditions is a key requirement. Here, we review basic principles of germ-free isolator technology, the suitability of various sterilization methods, and the use of sterility testing methods to monitor germ-free mouse colonies. We also discuss their effectiveness and limitations, and share the experience with protocols used in our facility. In addition, possible sources of isolator contamination are discussed and an overview of reported contaminants is provided.

A Pilot Study for Legionella pneumophila Volatilome Characterization Using a Gas Sensor Array and GC/MS Techniques

Legionellosis is a generic term describing the pneumonic (Legionnaires' disease, LD) and non-pneumonic (Pontiac fever, PF) forms of infection with bacteria belonging to the genus Legionella. Currently, the techniques used to detect Legionella spp. in water samples have certain limitations and drawbacks, and thus, there is a need to identify new tools to carry out low-cost and rapid analysis. In this regard, several studies demonstrated that a volatolomics approach rapidly detects and discriminates different species of microorganisms via their volatile signature. In this paper, the volatile organic compounds (VOCs) pattern emitted in vitro by Legionella pneumophila cultures is characterized and compared to those produced by other Legionella species and by Pseudomonas aeruginosa, using a gas sensor array and gas chromatograph mass spectrometer (GC-MS). Bacterial cultures were measured at the 3rd and 7th day after the incubation. Sensor array data analyzed via the K-nearest neighbours (k-NN) algorithm showed a sensitivity to Legionella pneumophila identification at around 89%. On the other hand, GC-MS identified a bouquet of VOCs, mainly alcohols and ketones, that enable the differentiation of Legionella pneumophila in respect to other waterborne microorganisms.

A Collection of Molecular Fingerprints of Single Aerosol Particles in Air for Potential Identification and Detection Using Optical Trapping-Raman Spectroscopy

Characterization, identification, and detection of aerosol particles in their native atmospheric states remain a challenge. Recently, optical trapping-Raman spectroscopy (OT-RS) has been developed and demonstrated for characterization of single, airborne particles. Such particles in different chemical groups have been characterized by OT-RS in recent years and many more are being studied. In this work, we collected single-particle Raman spectra measured using the OT-RS technique and began construction of a library of OT-RS fingerprints that may be used as a reference for potential detection and identification of aerosol particles in the atmosphere. We collected OT-RS fingerprints of aerosol particles from eight different categories including carbons, bioaerosols (pollens, fungi, vitamins, spores), dusts, biological warfare agent surrogates, etc. Among the eight categories, spectral fingerprints of six groups of aerosol particles have been published previously and two other groups are new. We also discussed challenges, limitations, and advantages of using single-particle optical trapping-Raman spectroscopy for aerosol-particle characterization, identification, and detection.

Hyperspectral imaging and machine learning in food microbiology: Developments and challenges in detection of bacterial, fungal, and viral contaminants

Hyperspectral imaging (HSI) is a robust and nondestructive method that can detect foreign particles such as microbial, chemical, and physical contamination in food. This review summarizes the work done in the last two decades in this field with a highlight on challenges, risks, and research gaps. Considering the challenges of using HSI on complex matrices like food (e.g., the confounding and masking effects of background signals), application of machine learning and modeling approaches that have been successful in achieving better accuracy as well as increasing the detection limit have also been discussed here. Foodborne microbial contaminants such as bacteria, fungi, viruses, yeast, and protozoa are of interest and concern to food manufacturers due to the potential risk of either food poisoning or food spoilage. Detection of these contaminants using fast and efficient methods would not only prevent outbreaks and recalls but will also increase consumer acceptance and demand for shelf-stable food products. The conventional culture-based methods for microbial detection are time and labor-intensive, whereas hyperspectral imaging (HSI) is robust, nondestructive with minimum sample preparation, and has gained significant attention due to its rapid approach to detection of microbial contaminants. This review is a comprehensive summary of the detection of bacterial, viral, and fungal contaminants in food with detailed emphasis on the specific modeling and datamining approaches used to overcome the specific challenges associated with background and data complexity.

Comparison of the Moist Material Relative Permittivity Readouts Using the Non-Invasive Reflectometric Sensors and Microwave Antenna

The article concerns the issue of non-invasive moisture sensing in building materials. Two techniques that enable evaluating the value of the relative permittivity of the material, being the measure of porous material moisture, have been utilized for the research. The first is the microwave technique that utilizes the non-contact measurement of velocity of microwave radiation across the tested material and the second is the time domain reflectometry (TDR) technique based on the measurement of electromagnetic pulse propagation time along the waveguides, being the elements of sensor design. The tested building material involved samples of red ceramic brick that differed in moisture, ranging between 0% and 14% moisture by weight. The main goal of the research was to present the measuring potential of both techniques for moisture evaluation as well as emphasize the advantages and disadvantages of each method. Within the research, it was stated that both methods provide similar measuring potential, with a slight advantage in favor of a microwave non-contact sensor over surface TDR sensor designs.

Emerging Methods of Monitoring Volatile Organic Compounds for Detection of Plant Pests and Disease

Each year, unwanted plant pests and diseases, such as Hendel or potato soft rot, cause damage to crops and ecosystems all over the world. To continue to feed the growing population and protect the global ecosystems, the surveillance and management of the spread of these pests and diseases are crucial. Traditional methods of detection are often expensive, bulky and require expertise and training. Therefore, inexpensive, portable, and user-friendly methods are required. These include the use of different gas-sensing technologies to exploit volatile organic compounds released by plants under stress. These methods often meet these requirements, although they come with their own set of advantages and disadvantages, including the sheer number of variables that affect the profile of volatile organic compounds released, such as sensitivity to environmental factors and availability of soil nutrients or water, and sensor drift. Furthermore, most of these methods lack research on their use under field conditions. More research is needed to overcome these disadvantages and further understand the feasibility of the use of these methods under field conditions. This paper focuses on applications of different gas-sensing technologies from over the past decade to detect plant pests and diseases more efficiently.

Identification of Olfactory Nuisance of Floor Products Containing Bitumens with the TD-GC-MS/O Method

The adopted TD-GC-MS/O method helps determine the correlation between the odour signals and compounds separated on the chromatographic column, from the analysed gas mixture. It is possible to compare the retention times at which the odour signals were identified with the retention time of eluting compounds, when the test system and matrix are known. The presented study describes the details of representative samples obtained from (1) indoor air samples from a room where floor materials containing bitumen are present, (2) wooden floor staves placed in an emission chamber, and (3) fragments (chips) of the materials mentioned above, placed in glass tubes, exposed to an elevated desorption temperature. The results, presented in the paper, describe the identified odours and their intensity and assign chemical compounds to each odour, indicating their likely source of origin. The results presented in the manuscript are intended to show what methodology can be adopted to obtain intense odours from the tested samples, without losing the sensitivity derived from GC-MS. The manuscript presents representative results-case studies. The results for various types of samples were not very reproducible, related to the complex matrix of bituminous products. The enormity of compounds present in tar adhesives makes it possible to indicate only the groups of compounds that emit from these systems. They include, primarily, aliphatic, aromatic and heteroaromatic hydrocarbons, particularly Naphthalene and Phenol derivatives.

Conditions Influencing Mould Growth for Effective Prevention of Wood Deterioration Indoors

Effective prevention of mould growth indoors is still an important topic considering that mould growth is frequently observed in buildings, it causes serious health hazards and can irreversibly damage infected objects. Several studies have been conducted and mould growth models developed. Despite that, some potentially important aspects such as water damage and spore contamination have received only little attention. The objective of the present study was to investigate the effect of the initial moisture content of wood and spore contamination on mould development indoors. The mould tests were performed in constant temperature (10, 20 and 30 °C) and relative humidity (91% and 97%) conditions. The results show that wetting of wood specimens prior to the test significantly accelerates mould growth at a temperature of 10 °C. For the other temperatures, the effect was insignificant. Similar results were obtained for the test involving dry (conditioned at RH 50%) and conditioned specimens (RH 91% or RH 97%). The results regarding initial spore contamination show that significantly longer periods are required for mould to develop without spore contamination at 10 °C and 20 °C, while at 30 °C the effect is relatively small.

Electronic Nose Differentiation between Quercus robur Acorns Infected by Pathogenic Oomycetes Phytophthora plurivora and Pythium intermedium

Identification of the presence of pathogenic oomycetes in infected plant material proved possible using an electronic nose, giving hope for a tool to assist nurseries and quarantine services. Previously, species of Phytophthora plurivora and Pythium intermedium have been successfully distinguished in germinated acorns of English oak Quercus robur L. Chemical compound analyses performed by HS-SPME/GC-MS (Headspace Solid-Phase Microextraction/Gas Chromatography-Mass Spectrometry) revealed the presence of volatile antifungal molecules produced by oak seedlings belonging to terpenes and alkanes. Compounds characteristic only of Phytophthora plurivora or Pythium intermedium were also found. Methylcarveol occurred when germinated acorns were infected with Pythium, while neophytadiene (isomer 2 and 3) occurred only when infected with Phytophthora. Moreover, isopentanol was found in acorns infected with Phytophthora, while in control, isopentyl vinyl ether was not observed anywhere else. Among the numerous volatile compounds, isopentanol only occurred in acorns infected with Phytophthora and methylcarveol in acorns infected with Pythium.

Optimization of Classification Prediction Performances of an Instrumental Odour Monitoring System by Using Temperature Correction Approach

Odour emissions generated by industrial and environmental protection plants are often a cause of nuisances and consequent conflicts in exposed populations. Their control is a key action to avoid complaints. Among the odour measurement techniques, the sensory-instrumental method with the application of Instrumental Odour Monitoring Systems (IOMSs) currently represents an effective solution to allow a continuous classification and quantification of odours in real time, combining the advantages of conventional analytical and sensorial techniques. However, some aspects still need to be improved. The study presents and discusses the investigation and optimization of the operational phases of an advanced IOMS, applied for monitoring of environmental odours, with the aim of increasing their performances and reliability of the measures. Accuracy rates of over 98% were reached in terms of classification performances. The implementation of automatic correction systems for the resistance values of the measurement sensors, by considering the influence of the temperature, has been proven to be a solution to further improve the reliability of IOMS. The proposed approach was based on the application of corrective coefficients experimentally determined by analyzing the correlation between resistance values and operating conditions. The paper provides useful information for the implementation of real-time management activities by using a tailor-made software, able to increase and enlarge the IOMS fields of application.

An Outlook of Recent Advances in Chemiresistive Sensor-Based Electronic Nose Systems for Food Quality and Environmental Monitoring

An electronic nose (Enose) relies on the use of an array of partially selective chemical gas sensors for identification of various chemical compounds, including volatile organic compounds in gas mixtures. They have been proposed as a portable low-cost technology to analyse complex odours in the food industry and for environmental monitoring. Recent advances in nanofabrication, sensor and microcircuitry design, neural networks, and system integration have considerably improved the efficacy of Enose devices. Here, we highlight different types of semiconducting metal oxides as well as their sensing mechanism and integration into Enose systems, including different pattern recognition techniques employed for data analysis. We offer a critical perspective of state-of-the-art commercial and custom-made Enoses, identifying current challenges for the broader uptake and use of Enose systems in a variety of applications.

Application of a Low-Cost Electronic Nose for Differentiation between Pathogenic Oomycetes Pythium intermedium and Phytophthora plurivora

Compared with traditional gas chromatography-mass spectrometry techniques, electronic noses are non-invasive and can be a rapid, cost-effective option for several applications. This paper presents comparative studies of differentiation between odors emitted by two forest pathogens: Pythium and Phytophthora, measured by a low-cost electronic nose. The electronic nose applies six non-specific Figaro Inc. metal oxide sensors. Various features describing shapes of the measurement curves of sensors' response to the odors' exposure were extracted and used for building the classification models. As a machine learning algorithm for classification, we use the Support Vector Machine (SVM) method and various measures to assess classification models' performance. Differentiation between Phytophthora and Pythium species has an important practical aspect allowing forest practitioners to take appropriate plant protection. We demonstrate the possibility to recognize and differentiate between the two mentioned species with acceptable accuracy by our low-cost electronic nose.

Mass Spectrometry: A Rosetta Stone to Learn How Fungi Interact and Talk

Fungi are a highly diverse group of heterotrophic organisms that play an important role in diverse ecological interactions, many of which are chemically mediated. Fungi have a very versatile metabolism, which allows them to synthesize a large number of still little-known chemical compounds, such as soluble compounds that are secreted into the medium and volatile compounds that are chemical mediators over short and long distances. Mass spectrometry (MS) is currently playing a dominant role in mycological studies, mainly due to its inherent sensitivity and rapid identification capabilities of different metabolites. Furthermore, MS has also been used as a reliable and accurate tool for fungi identification (i.e., biotyping). Here, we introduce the readers about fungal specialized metabolites, their role in ecological interactions and provide an overview on the MS-based techniques used in fungal studies. We particularly present the importance of sampling techniques, strategies to reduce false-positive identification and new MS-based analytical strategies that can be used in mycological studies, further expanding the use of MS in broader applications. Therefore, we foresee a bright future for mass spectrometry-based research in the field of mycology.

Moulds on cementitious building materials-problems, prevention and future perspectives

Materials rich in organic and inorganic compounds, such as building materials or paints, represent an excellent substrate for the development of moulds. Several conditions affect mould's growth on cementitious materials, such as nutrient and water availability, temperature, pH and moisture. Microorganisms, and especially moulds, attack these surfaces and contribute to their erosion, thereby reducing the life of the structure itself and negatively affecting human health through inhalation, ingestion and dermal contact with spores. Interventions are based on The European Communities Council Directive 89/106/EEC, that obliges the use of materials, products and building elements that are resistant to fungi and other forms of degradation, and that do not constitute a health risk for users and the environment. This mini-review summarises the current state of problems related to mould growth on cementitious building materials, emphasising new innovative approaches for limiting or contrasting their growth. In particular, the use of nanoparticles and the related nanomaterials as well as the potential use of new "biocides" from natural sources is discussed.