14 research outputs found

    Human milk from tandem feeding dyads does not differ in metabolite and metataxonomic features when compared to single nursling dyads under six months of age

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    Given the long-term advantages of exclusive breastfeeding to infants and their mothers, there is both an individual and public health benefit to its promotion and support. Data on the composition of human milk over the course of a full period of lactation for a single nursling is sparse, but data on human milk composition during tandem feeding (feeding children of different ages from different pregnancies) is almost entirely absent. This leaves an important knowledge gap that potentially endangers the ability of parents to make a fully informed choice on infant feeding. We compared the metataxonomic and metabolite fingerprints of human milk samples from 15 tandem feeding dyads to that collected from ten exclusively breastfeeding single nursling dyads where the nursling is under six months of age. Uniquely, our cohort also included three tandem feeding nursling dyads where each child showed a preferential side for feeding—allowing a direct comparison between human milk compositions for different aged nurslings. Across our analysis of volume, total fat, estimation of total microbial load, metabolite fingerprinting, and metataxonomics, we showed no statistically significant differences between tandem feeding and single nursling dyads. This included comparisons of preferential side nurslings of different ages. Together, our findings support the practice of tandem feeding of nurslings, even when feeding an infant under six months

    Metabolic phenotyping and strain characterisation of pseudomonas aeruginosa Isolates from cystic fibrosis patients using rapid evaporative ionisation mass spectrometry

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    Rapid evaporative ionisation mass spectrometry (REIMS) is a novel technique for the real-time analysis of biological material. It works by conducting an electrical current through a sample, causing it to rapidly heat and evaporate, with the analyte containing vapour channelled to a mass spectrometer. It was used to characterise the metabolome of 45 Pseudomonas aeruginosa (P. aeruginosa) isolates from cystic fibrosis (CF) patients and compared to 80 non-CF P. aeruginosa. Phospholipids gave the highest signal intensity; 17 rhamnolipids and 18 quorum sensing molecules were detected, demonstrating that REIMS has potential for the study of virulence-related metabolites. P. aeruginosa isolates obtained from respiratory samples showed a higher diversity, which was attributed to the chronic nature of most respiratory infections. The analytical sensitivity of REIMS allowed the detection of a metabolome that could be used to classify individual P. aeruginosa isolates after repeated culturing with 81% accuracy, and an average 83% concordance with multilocus sequence typing. This study underpins the capacities of REIMS as a tool with clinical applications, such as metabolic phenotyping of the important CF pathogen P. aeruginosa, and highlights the potential of metabolic fingerprinting for fine scale characterisation at a sub-species level

    Rapid Evaporative Ionisation Mass Spectrometry (REIMS) provides accurate direct from culture species identification within the genus Candida

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    Members of the genus Candida, such as C. albicans and C. parapsilosis, are important human pathogens. Other members of this genus, previously believed to carry minimal disease risk, are increasingly recognised as important human pathogens, particularly because of variations in susceptibilities to widely used anti-fungal agents. Thus, rapid and accurate identification of clinical Candida isolates is fundamental in ensuring timely and effective treatments are delivered. Rapid Evaporative Ionisation Mass Spectrometry (REIMS) has previously been shown to provide a high-throughput platform for the rapid and accurate identification of bacterial and fungal isolates. In comparison to commercially available matrix assisted laser desorption ionisation time of flight mass spectrometry (MALDI-ToF), REIMS based methods require no preparative steps nor time-consuming cell extractions. Here, we report on the ability of REIMS-based analysis to rapidly and accurately identify 153 clinical Candida isolates to species level. Both handheld bipolar REIMS and high-throughput REIMS platforms showed high levels of species classification accuracy, with 96% and 100% of isolates classified correctly to species level respectively. In addition, significantly different (FDR corrected P value < 0.05) lipids within the 600 to 1000 m/z mass range were identified, which could act as species-specific biomarkers in complex microbial communities

    Evaluation of direct from sample metabolomics of human feces using rapid evaporative ionization mass spectrometry

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    Mass spectrometry is a powerful tool in the investigation of the human fecal metabolome. However, current approaches require time-consuming sample preparation, chromatographic separations, and consequently long analytical run times. Rapid evaporative ionization mass spectrometry (REIMS) is a method of ambient ionization mass spectrometry and has been utilized in the metabolic profiling of a diverse range of biological materials, including human tissue, cell culture lines, and microorganisms. Here, we describe the use of an automated, high-throughput REIMS robotic platform for direct analysis of human feces. Through the analysis of fecal samples from five healthy male participants, REIMS analytical parameters were optimized and used to assess the chemical information obtainable using REIMS. Within the fecal samples analyzed, bile acids, including primary, secondary, and conjugate species, were identified, and phospholipids of possible bacterial origin were detected. In addition, the effect of storage conditions and consecutive freeze/thaw cycles was determined. Within the REIMS mass spectra, the lower molecular weight metabolites, such as fatty acids, were shown to be significantly affected by storage conditions for prolonged periods at temperatures above −80 °C and consecutive freeze/thaw cycles. However, the complex lipid region was shown to be unaffected by these conditions. A further cohort of 50 fecal samples, collected from patients undergoing bariatric surgery, were analyzed using the optimized REIMS parameters and the complex lipid region mass spectra used for multivariate modeling. This analysis showed a predicted separation between pre- and post-surgery specimens, suggesting that REIMS analysis can detect biological differences, such as microbiome-level differences, which have traditionally been reliant upon methods utilizing extensive sample preparations and chromatographic separations and/or DNA sequencing

    Off-colony screening of biosynthetic libraries by rapid laser-enabled mass spectrometry

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    Leveraging advances in DNA synthesis and molecular cloning techniques, synthetic biology increasingly makes use of large construct libraries to explore large design spaces. For biosynthetic pathway engineering the ability to screen these libraries for a variety of metabolites of interest is essential. If the metabolite of interest or the metabolic phenotype is not easily measurable, screening soon becomes a major bottleneck involving time-consuming culturing, sample preparation, and extraction. To address this, we demonstrate the use of automated Laser-Assisted Rapid Evaporative Ionisation Mass Spectrometry (LA-REIMS) - a form of ambient laser desorption ionisation mass spectrometry - to perform rapid mass spectrometry analysis direct from agar plate yeast colonies without sample preparation or extraction. We use LA-REIMS to assess production levels of violacein and betulinic acid directly from yeast colonies at a rate of 6 colonies per minute. We then demonstrate the throughput enabled by LA-REIMS by screening over 450 yeast colonies in under 4 hours, while simultaneously generating recoverable glycerol stocks of each colony in real-time. This showcases LA-REIMS as a pre-screening tool to complement downstream quantification methods such as LCMS. Through pre-screening several hundred colonies with LA-REIMS, we successfully isolate and verify a strain with a 2.5-fold improvement in betulinic acid production. Finally, we show that LA-REIMS can detect 20 out of a panel of 27 diverse biological molecules, demonstrating the broad applicability of LA-REIMS to metabolite detection. The rapid and automated nature of LA-REIMS makes this a valuable new technology to complement existing screening technologies currently employed in academic and industrial workflows

    Utilisation of Ambient Laser Desorption Ionisation Mass Spectrometry (ALDI-MS) improves lipid-based microbial species level identification

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    The accurate and timely identification of the causative organism of infection is important in ensuring the optimum treatment regimen is prescribed for a patient. Rapid evaporative ionisation mass spectrometry (REIMS), using electrical diathermy for the thermal disruption of a sample, has been shown to provide fast and accurate identification of microorganisms directly from culture. However, this method requires contact to be made between the REIMS probe and microbial biomass; resulting in the necessity to clean or replace the probes between analyses. Here, optimisation and utilisation of ambient laser desorption ionisation (ALDI) for improved speciation accuracy and analytical throughput is shown. Optimisation was completed on 15 isolates of Escherichia coli, showing 5 W in pulsatile mode produced the highest signal-to-noise ratio. These parameters were used in the analysis of 150 clinical isolates from ten microbial species, resulting in a speciation accuracy of 99.4% - higher than all previously reported REIMS modalities. Comparison of spectral data showed high levels of similarity between previously published electrical diathermy REIMS data. ALDI does not require contact to be made with the sample during analysis, meaning analytical throughput can be substantially improved, and further, increases the range of sample types which can be analysed in potential direct-from-sample pathogen detection
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