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Headspace analyses over microbial cultures using multi-capillary column-ion mobility spectrometry (MCC-IMS) could lead to a faster, safe and cost-effective method for the identification of pathogens. Recent studies have shown that MCC-IMS allows identification of bacteria and fungi, but no information is available from when on during their growth a differentiation between bacteria is possible. Therefore, we analysed the headspace over human pathogenic reference strains of Escherichia coli and Pseudomonas aeruginosa at four time points during their growth in a complex fluid medium. In order to validate our findings and to answer the question if the results of one bacterial strain can be transferred to other strains of the same species, we also analysed the headspace over cultures from isolates of random clinical origin. We detected 19 different volatile organic compounds (VOCs) that appeared or changed their signal intensity during bacterial growth. These included six VOCs exclusively changing over E. coli cultures and seven exclusively changing over P. aeruginosa cultures. Most changes occurred in the late logarithmic or static growth phases. We did not find differences in timing or trends in signal intensity between VOC patterns of different strains of one species. Our results show that differentiation of human pathogenic bacteria by headspace analyses using MCC-IMS technology is best possible during the late phases of bacterial growth. Our findings also show that VOC patterns of a bacterial strain can be transferred to other strains of the same species.

The plant microbiome can influence plant phenotype in diverse ways, yet microbial contribution to plant volatile phenotype remains poorly understood. We examine the presence of fungi and bacteria in the nectar of a coflowering plant community, characterize the volatiles produced by common nectar microbes and examine their influence on pollinator preference. Nectar was sampled for the presence of nectar-inhabiting microbes. We characterized the headspace of four common fungi and bacteria in a nectar analog. We examined electrophysiological and behavioral responses of honey bees to microbial volatiles. Floral headspace samples collected in the field were surveyed for the presence of microbial volatiles. Microbes commonly inhabit floral nectar and the common species differ in volatile profiles. Honey bees detected most microbial volatiles tested and distinguished among solutions based on volatiles only. Floral headspace samples contained microbial-associated volatiles, with 2-ethyl-1-hexanol and 2-nonanone – both detected by bees – more often detected when fungi were abundant. Nectar-inhabiting microorganisms produce volatile compounds, which can differentially affect honey bee preference. The yeast Metschnikowia reukaufii produced distinctive compounds and was the most attractive of all microbes compared. The variable presence of microbes may provide volatile cues that influence plant–pollinator interactions.

The effect of vacuum is an emerging experimental parameter to consider during optimization of a variety of headspace microextraction methodologies. The positive effect of vacuum was initially demonstrated for headspace solid-phase microextraction and was recently expanded to single-drop microextraction and higher capacity sorbents i.e. stir bar sorptive extraction. In all cases, sampling under vacuum greatly accelerated the extraction kinetics of analytes exhibiting long equilibration times under atmospheric pressure. At the same time, the extraction of analytes that reached equilibrium fast was not affected. In all optimized methods, extraction times were greatly reduced and/or sampling temperatures were lower to those reported with the standard methodology under atmospheric pressure. This work succinctly overviews the effect of vacuum on the different headspace microextraction technologies reported so far. The fundamental concepts describing the pressure dependence of each methodology are pulled together and presented in a simplified manner. The latest findings on the combined effects of vacuum and several selected experimental parameters typically examined during method optimization are then presented and the practical aspects of past outcomes are highlighted. The discussion also includes the air-evacuation step and the analysis of complex matrices. This article is intended for readers who are either new to the field of vacuum headspace microextraction sampling or its use and want to exploit this powerful approach.

When a fire is suspected to be intentionally set, fire debris samples can be collected and analyzed for ignitable liquid residues (ILRs). In some cases, samples will contain highly organic substrates such as soil or rotting wood. These substrates will contain a high bacterial load, which can result in systematic and irreversible damage to the ILR due to microbial degradation. This paper explores ways to preserve ILR by sterilizing fire debris samples without interfering with their subsequent analysis. There are many methods reported in the literature for sterilizing soil, such as freezing, irradiation, autoclaving, and various chemical fumigation techniques. However, these methods either do not kill all bacterial species, cannot be easily applied in the field or would interfere with the analysis of the ILRs. For this work, various anti-microbial compounds including triclosan (2,4,4′-trichloro-2′-hydroxydiphenyl ether) were tested for their efficacy at killing bacteria present in the soil. Triclosan was highly effective in qualitative growth studies and was therefore used to measure bacterial growth (or lack thereof) by spectroscopic analysis as well as passive headspace analysis. These experiments showed that triclosan was able to sterilize soil samples in less than 60s, maintain their sterility for at least 77h and preserve gasoline residues on a soil matrix for at least 30 days.

Static headspace gas chromatography-ion mobility spectrometry (SHS GC-IMS) is a relatively new analytical technique that has considerable potential for analysis of volatile organic compounds (VOCs). In this study, SHS GC-IMS was used for the identification of the major terpene components of various essential oils (EOs). Based on the data obtained from 25 terpene standards and 50 EOs, a database for fingerprint identification of characteristic terpenes and EOs was generated utilizing SHS GC-IMS for authenticity testing of fragrances in foods, cosmetics, and personal care products. This database contains specific normalized IMS drift times and GC retention indices for 50 terpene components of EOs. Initially, the SHS GC-IMS parameters, e.g., drift gas and carrier gas flow rates, drift tube, and column temperatures, were evaluated to determine suitable operating conditions for terpene separation and identification. Gas chromatography-mass spectrometry (GC-MS) was used as a reference method for the identification of terpenes in EOs. The fingerprint pattern based on the normalized IMS drift times and retention indices of 50 terpenes is presented for 50 EOs. The applicability of the method was proven on examples of ten commercially available food, cosmetic, and personal care product samples. The results confirm the suitability of SHS GC-IMS as a powerful analytical technique for direct identification of terpene components in solid and liquid samples without any pretreatment. Graphical abstract Fingerprint pattern identification of terpenes and essential oils using static headspace gas chromatography-ion mobility spectrometry.

A prototype gas chromatography-ion mobility spectrometry (GC-IMS) system, hyphenating temperature-ramped headspace GC to a modified drift time IMS cell, was evaluated and compared to a conventional, isothermal capillary column (CC)-IMS system on the example of the geographical differentiation of extra virgin olive oils (EVOO) from Spain and Italy. It allows orthogonal, 2D separation of complex samples and individual detection of compounds in robust and compact benchtop systems. The information from the high-resolution 3D fingerprints of volatile organic compound (VOC) fractions of EVOO samples were extracted by specifically developed chemometric MATLAB® routines to differentiate between the different olive oil provenances. A combination of unsupervised principal component analysis (PCA) with two supervised procedures, linear discriminant analysis (LDA) and k -nearest neighbors (kNN), was applied to the experimental data. The results showed very good discrimination between oils of different geographical origins, featuring 98 and 92% overall correct classification rate for PCA-LDA and kNN classifier, respectively. Furthermore, the results showed that the higher resolved 3D fingerprints obtained from the GC-IMS system provide superior resolving power for non-targeted profiling of VOC fractions from highly complex samples such as olive oil. Graphical abstract Principle of the determination of geographic origins of olive oils by chemometric analysis of three-dimensional HS-GC-IMS fingerprints

• Volatile organic compounds (VOCs) play vital roles in the interaction of fungi with plants and other organisms. A systematic study of the global fungal VOC profiles is still lacking, though it is a prerequisite for elucidating the mechanisms of VOC-mediated interactions. Here we present a versatile system enabling a high-throughput screening of fungal VOCs under controlled temperature. In a proof-of-principle experiment, we characterized the volatile metabolic fingerprints of four Trichoderma spp. over a 48 h growth period. • The developed platform allows automated and fast detection of VOCs from up to 14 simultaneously growing fungal cultures in real time. The comprehensive analysis of fungal odors is achieved by employing proton transfer reaction-time of flight-MS and GC-MS. The data-mining strategy based on multivariate data analysis and machine learning allows the volatile metabolic fingerprints to be uncovered. • Our data revealed dynamic, development-dependent and extremely species-specific VOC profiles from the biocontrol genus Trichoderma. The two mass spectrometric approaches were highly complementary to each other, together revealing a novel, dynamic view to the fungal VOC release. • This analytical system could be used for VOC-based chemotyping of diverse small organisms, or more generally, for any in vivo and in vitro real-time headspace analysis.

Chemical control of Drosophila suzukii (Diptera: Drosophilidae) based on the use of insecticides is particularly challenging as the insect attacks ripening fruits shortly before harvest. An alternative strategy may rely on the use of yeasts as phagostimulants and baits, applied on canopy as attract-and-kill formulations. The aim of this research was to identify the most attractive among six yeast species for D. suzukii: Saccharomyces cerevisiae, Hanseniaspora uvarum, Clavispora santaluciae, Saccharomycopsis vini, Issatchenkia terricola, and Metschnikowia pulcherrima. The volatile profile of C. santaluciae was described for the first time. Behavioural experiments identified H. uvarum and S. vini as the most attractive yeasts. The characterization of yeast headspace volatiles using direct headspace (DHS) and solid-phase microextraction (SPME) revealed several strain-specific compounds. With DHS injection, 19 volatiles were characterised, while SPME revealed 71 compounds constituting the yeast headspace. Both analyses revealed terpenoids including β-ocimene, citronellol, (Z)-geraniol (nerol), and geranial as distinct constituents of S. vini. H. uvarum and S. vini were further investigated using closed-loop stripping analysis (CSLA) and electroantennography. Out of 14 compounds quantified by CSLA, ethyl acetate, isoamyl acetate, β-myrcene, benzaldehyde and linalool were detected by D. suzukii antennae and might generate the strong attractiveness of S. vini and H. uvarum. Our results highlight a strong attraction of D. suzukii to various yeasts associated with both the flies and their habitat and demonstrate how different sampling methods can impact the results of volatile compound characterization. It remains to be demonstrated whether the distinct attraction is based on special adaptations to certain yeasts and to what extent the metabolites causing attraction are interchangeable.

Aroma is a key grain quality trait that directly influences the market price of rice globally. Loss of function of betaine aldehyde dehydrogenase 2 (OsBADH2) affects the biosynthesis of 2‐acetyl‐1‐pyrroline (2‐AP), which is responsible for aroma in fragrant rice. The current study was aimed at creating new alleles of BADH2 using CRISPR/Cas9 gene editing technology under the genetic background of the japonica Ningjing 1 (NJ1) and indica Huang Huazhan (HHZ) varieties. Sensory evaluation and analysis using headspace solid‐phase microextraction gas chromatography–mass spectrometry (HS‐SPME‐GC‐MS) showed that the grains of the four homozygous T1 lines with new alleles of BADH2 (nj1‐cr BADH2‐1, nj1‐cr BADH2‐2, hhz‐cr BADH2‐1 and hhz‐cr BADH2‐2) produced moderate fragrance and had significantly increased 2‐AP content compared with wild‐types. Moreover, there were no significant differences in the amylose content and gelatinization temperature among the four lines with new alleles of BADH2 to the wild‐types. Thereafter, we crossed the HHZ background new alleles of BADH2 with CMS line Taonong 1A (TN1A) to produce a three‐line hybrid variety B‐Tao‐You‐Xiangzhan (BTYXZ) with increased grain aroma. The 2‐AP content in grains of the improved BTYXZ‐1 and BTYXZ‐2 reached at 26.16 and 18.74 μg/kg, and the gel consistency of BTYXZ‐1 and BTYXZ‐2 increased significantly by 9.1% and 6.5%, respectively, compared with the wild‐type Tao‐You‐Xiangzhan (TYXZ). However, the γ‐aminobutyric acid (GABA) content in the improved three‐line hybrid rice BTYXZ‐1 (5.6 mg/100 g) and BTYXZ‐2 (10.7 mg/100 g) was significantly lower than that of the TYXZ. These results demonstrated that CRISPR/Cas9 gene editing technology could be successfully utilized in improving aroma in non‐fragrant japonica and indica varieties. In addition, the newly developed BADH2 alleles provided important genetic resources for grain aroma improvement in three‐line hybrid rice.

White teas are produced in the simple process of withering and drying the tender leaves of the plant Camellia sinensis. Tea aroma created in this way exhibits a unique profile. Studies were carried out on the molecular contributors to the aroma character of the four well-known traditional white teas: Baihaoyingzhen (BHYZ), Baimudan (BMD), Gongmei (GM), and Shoumei (SM). Volatiles of the tea infusions were enriched by solvent partitioning followed by solid-phase extraction (SPE). The highly volatile compounds were captured by headspace solid-phase microextraction (HS SPME). Gas chromatography–olfactometry (GC-O) experiments discovered 37 odor-active components. Quantitation of aroma compounds was achieved using the method of standard addition (SAM). Calculation of odor activity value (OAV) and aroma reconstitution experiments revealed that the aroma profiles of the four white teas were attributed by 15 compounds, although a total of 179 volatile components were found in the extracts. BHYZ had distinct floral, fruity, and sweet characters, while BMD, GM, and SM had stronger woody and fermented notes. The major aroma contributors to the floral and sweet characters were geraniol and linalool for BHYZ and BMD; 2-phenylethanol and phenylacetaldehyde for GM and SM. The compounds produced from amino acid reactions during tea manufacturing, e.g. dimethyl sulfide, 3-methylbutanal, phenylacetaldehyde, etc., formed the basis of fruity and refreshing attributes. Degradation products of glycosides and carotenoids, such as geraniol, linalool, and ionones, contributed to the essential floral and sweet characters of the white teas.