Metabolic Fingerprinting Links Oncogenic PIK3CA with Enhanced Arachidonic Acid-Derived Eicosanoids.

Oncogenic transformation is associated with profound changes in cellular metabolism, but whether tracking these can improve disease stratification or influence therapy decision-making is largely unknown. Using the iKnife to sample the aerosol of cauterized specimens, we demonstrate a new mode of real-time diagnosis, coupling metabolic phenotype to mutant PIK3CA genotype. Oncogenic PIK3CA results in an increase in arachidonic acid and a concomitant overproduction of eicosanoids, acting to promote cell proliferation beyond a cell-autonomous manner. Mechanistically, mutant PIK3CA drives a multimodal signaling network involving mTORC2-PKCζ-mediated activation of the calcium-dependent phospholipase A2 (cPLA2). Notably, inhibiting cPLA2 synergizes with fatty acid-free diet to restore immunogenicity and selectively reduce mutant PIK3CA-induced tumorigenicity. Besides highlighting the potential for metabolic phenotyping in stratified medicine, this study reveals an important role for activated PI3K signaling in regulating arachidonic acid metabolism, uncovering a targetable metabolic vulnerability that largely depends on dietary fat restriction. VIDEO ABSTRACT.

Mass spectrometry imaging highlights dynamic patterns of lipid co-expression with Aß plaques in mouse and human brains.

Lipids play crucial roles in the susceptibility and brain cellular responses to Alzheimer's disease (AD) and are increasingly considered potential soluble biomarkers in cerebrospinal fluid (CSF) and plasma. To delineate the pathological correlations of distinct lipid species, we conducted a comprehensive characterization of both spatially localized and global differences in brain lipid composition in AppNL-G-F mice with spatial and bulk mass spectrometry lipidomic profiling, using human amyloid-expressing (h-Aß) and WT mouse brains controls. We observed age-dependent increases in lysophospholipids, bis(monoacylglycerol) phosphates, and phosphatidylglycerols around Aß plaques in AppNL-G-F mice. Immunohistology-based co-localization identified associations between focal pro-inflammatory lipids, glial activation, and autophagic flux disruption. Likewise, in human donors with varying Braak stages, similar studies of cortical sections revealed co-expression of lysophospholipids and ceramides around Aß plaques in AD (Braak stage V/VI) but not in earlier Braak stage controls. Our findings in mice provide evidence of temporally and spatially heterogeneous differences in lipid composition as local and global Aß-related pathologies evolve. Observing similar lipidomic changes associated with pathological Aß plaques in human AD tissue provides a foundation for understanding differences in CSF lipids with reported clinical stage or disease severity.

Mass recalibration for desorption electrospray ionization mass spectrometry imaging using endogenous reference ions.

BACKGROUND: Mass spectrometry imaging (MSI) data often consist of tens of thousands of mass spectra collected from a sample surface. During the time necessary to perform a single acquisition, it is likely that uncontrollable factors alter the validity of the initial mass calibration of the instrument, resulting in mass errors of magnitude significantly larger than their theoretical values. This phenomenon has a two-fold detrimental effect: (a) it reduces the ability to interpret the results based on the observed signals, (b) it can affect the quality of the observed signal spatial distributions. RESULTS: We present a post-acquisition computational method capable of reducing the observed mass drift by up to 60 ppm in biological samples, exploiting the presence of typical molecules with a known mass-to-charge ratio. The procedure, tested on time-of-flight and Orbitrap mass spectrometry analyzers interfaced to a desorption electrospray ionization (DESI) source, improves the molecular annotation quality and the spatial distributions of the detected ions. CONCLUSION: The presented method represents a robust and accurate tool for performing post-acquisition mass recalibration of DESI-MSI datasets and can help to increase the reliability of the molecular assignment and the data quality.

Modelling nonlinear dynamics of Crassulacean acid metabolism productivity and water use for global predictions.

Crassulacean acid metabolism (CAM) crops are important agricultural commodities in water-limited environments across the globe, yet modelling of CAM productivity lacks the sophistication of widely used C3 and C4 crop models, in part due to the complex responses of the CAM cycle to environmental conditions. This work builds on recent advances in CAM modelling to provide a framework for estimating CAM biomass yield and water use efficiency from basic principles. These advances, which integrate the CAM circadian rhythm with established models of carbon fixation, stomatal conductance and the soil-plant-atmosphere continuum, are coupled to models of light attenuation, plant respiration and biomass partitioning. Resulting biomass yield and transpiration for Opuntia ficus-indica and Agave tequilana are validated against field data and compared with predictions of CAM productivity obtained using the empirically based environmental productivity index. By representing regulation of the circadian state as a nonlinear oscillator, the modelling approach captures the diurnal dynamics of CAM stomatal conductance, allowing the prediction of CAM transpiration and water use efficiency for the first time at the plot scale. This approach may improve estimates of CAM productivity under light-limiting conditions when compared with previous methods.

Universal Sample Preparation Unlocking Multimodal Molecular Tissue Imaging.

A new tissue sample embedding and processing method is presented that provides downstream compatibility with numerous different histological, molecular biology, and analytical techniques. The methodology is based on the low temperature embedding of fresh frozen specimens into a hydrogel matrix composed of hydroxypropyl methylcellulose (HPMC) and polyvinylpyrrolidone (PVP) and sectioning using a cryomicrotome. The hydrogel was expected not to interfere with standard tissue characterization methods, histologically or analytically. We assessed the compatibility of this protocol with various mass spectrometric imaging methods including matrix-assisted laser desorption ionization (MALDI), desorption electrospray ionization (DESI) and secondary ion mass spectrometry (SIMS). We also demonstrated the suitability of the universal protocol for extraction based molecular biology techniques such as rt-PCR. The integration of multiple analytical modalities through this universal sample preparation protocol offers the ability to study tissues at a systems biology level and directly linking results to tissue morphology and cellular phenotype.

SPUTNIK: an R package for filtering of spatially related peaks in mass spectrometry imaging data.

Summary: SPUTNIK is an R package consisting of a series of tools to filter mass spectrometry imaging peaks characterized by a noisy or unlikely spatial distribution. SPUTNIK can produce mass spectrometry imaging datasets characterized by a smaller but more informative set of peaks, reduce the complexity of subsequent multi-variate analysis and increase the interpretability of the statistical results. Availability and implementation: SPUTNIK is freely available online from CRAN repository and at https://github.com/paoloinglese/SPUTNIK. The package is distributed under the GNU General Public License version 3 and is accompanied by example files and data. Supplementary information: Supplementary data are available at Bioinformatics online.

Colocalization Features for Classification of Tumors Using Desorption Electrospray Ionization Mass Spectrometry Imaging.

Supervised modeling of mass spectrometry imaging (MSI) data is a crucial component for the detection of the distinct molecular characteristics of cancerous tissues. Currently, two types of supervised analyses are mainly used on MSI data: pixel-wise segmentation of sample images and whole-sample-based classification. A large number of mass spectra associated with each MSI sample can represent a challenge for designing models that simultaneously preserve the overall molecular content while capturing valuable information contained in the MSI data. Furthermore, intensity-related batch effects can introduce biases in the statistical models. Here we introduce a method based on ion colocalization features that allows the classification of whole tissue specimens using MSI data, which naturally preserves the spatial information associated the with the mass spectra and is less sensitive to possible batch effects. Finally, we propose data visualization strategies for the inspection of the derived networks, which can be used to assess whether the correlation differences are related to coexpression/suppression or disjoint spatial localization patterns and can suggest hypotheses based on the underlying mechanisms associated with the different classes of analyzed samples.

Medical Swab Analysis Using Desorption Electrospray Ionization Mass Spectrometry: A Noninvasive Approach for Mucosal Diagnostics.

Medical swabs are routinely used worldwide to sample human mucosa for microbiological screening with culture methods. These are usually time-consuming and have a narrow focus on screening for particular microorganism species. As an alternative, direct mass spectrometric profiling of the mucosal metabolome provides a broader window into the mucosal ecosystem. We present for the first time a minimal effort/minimal-disruption technique for augmenting the information obtained from clinical swab analysis with mucosal metabolome profiling using desorption electrospray ionization mass spectrometry (DESI-MS) analysis. Ionization of mucosal biomass occurs directly from a standard rayon swab mounted on a rotating device and analyzed by DESI MS using an optimized protocol considering swab-inlet geometry, tip-sample angles and distances, rotation speeds, and reproducibility. Multivariate modeling of mass spectral fingerprints obtained in this way readily discriminate between different mucosal surfaces and display the ability to characterize biochemical alterations induced by pregnancy and bacterial vaginosis (BV). The method was also applied directly to bacterial biomass to confirm the ability to detect intact bacterial species from a swab. These results highlight the potential of direct swab analysis by DESI-MS for a wide range of clinical applications including rapid mucosal diagnostics for microbiology, immune responses, and biochemistry.

Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease.

Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge.

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n=30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

Fruit quality, antioxidant, and mineral attributes of pomegranate cv. Ghojagh, influenced by shading and spray applications of potassium sulfate and sodium silicate.

Pomegranate (Punica granatum L.) fruit quality depends on many traits including visual, biochemical and mineral characteristics. One of the negative traits is aril whitening (AW) which is a frequently observed disorder in hot and dry climates, that leads to decline in desirable fruit quality. Color, antioxidant, and mineral contents of the arils are of prime importance as quality traits. Therefore, this study aims to investigate the effect of shading and foliar minerals on fruit quality during the fruit development stages of pomegranate. Treatments included shaded (50% green net) and unshaded trees and foliar application of trees with potassium sulfate (K, 1% and 2%) or sodium silicate (Si, 0.05, 0.1 and 0.15%) during two growing seasons. Results showed that the severity of AW at harvest decreased significantly when trees were covered with shading compared to control. The color values of L* and °hue for arils were lower in fruits grown under shading conditions indicating darker red arils. Shading significantly reduced chilling injury in cold storage compared to open field fruits. Shading and Si 0.15% increased superoxide dismutase, and catalase enzymes activity while decreased Polyphenol oxidase and peroxidase. Covering trees with shading and Si 0.15% spray resulted in the highest total anthocyanin, antioxidant activity, and total phenolics content in the arils. Shading as well as Si 0.15% increased macronutrients content of the arils. The study concluded that covering pomegranate trees and spraying with Si in hot climate reduced AW, increased antioxidant traits, and led to higher fruit quality.

Increased Zygote-Derived Plantlet Formation through In Vitro Rescue of Immature Embryos of Highly Apomictic Opuntia ficus-indica (Cactaceae).

O. ficus-indica (prickly pear cactus) is an important forage and food source in arid and semiarid ecosystems and is the most important cactus species in cultivation globally. The high degree of apomixis in the species is a hindrance in plant breeding programs where genetic segregation is sought for the selection of superior genotypes. To understand if in ovulo embryo rescue could increase the proportion of zygotic seedlings, we compared the mature seed-derived seedlings with those regenerated from in vitro embryo rescue at 20, 25, 30, 35, and 40 post-anthesis days (PADs) in four Italian cultivars. The seedlings were classified as apomictic or zygotic based on molecular marker analysis using inter-sequence single repeat (ISSR) primers. Multiple embryos were recovered from all the cultured immature ovules, and plantlets were regenerated and acclimatized to the field post hardening, with success rates ranging from 62% ('Senza spine') to 83% ('Gialla'). The level of polyembryony differed among cultivars and recovery dates, with the highest being 'Rossa', producing 4.8 embryos/ovule at 35 PADs, and 'Gialla', the lowest, with 2.7 at 40 PADs. The maximum number of embryos observed within a single ovule was 14 in 'Trunzara bianca'. ISSR analysis revealed that ovule culture at 35 PADs produced the highest percentage of zygotic seedlings in all the cultivars, from 51% ('Rossa') to 98% ('Gialla'), with a high genotype effect as well. Mature seeds produced much fewer seedlings per seed, ranging from 1.2 in 'Trunzara bianca' to 2.0 in 'Rossa' and a lower percentage of zygotic seedlings (from 14% in 'Rossa' to 63% in 'Gialla'). Our research opens a pathway to increase the availability of zygotic seedlings in O. ficus-indica breeding programs through in ovulo embryo culture.

Selective advantage of epigenetically disrupted cancer cells via phenotypic inertia.

The evolution of established cancers is driven by selection of cells with enhanced fitness. Subclonal mutations in numerous epigenetic regulator genes are common across cancer types, yet their functional impact has been unclear. Here, we show that disruption of the epigenetic regulatory network increases the tolerance of cancer cells to unfavorable environments experienced within growing tumors by promoting the emergence of stress-resistant subpopulations. Disruption of epigenetic control does not promote selection of genetically defined subclones or favor a phenotypic switch in response to environmental changes. Instead, it prevents cells from mounting an efficient stress response via modulation of global transcriptional activity. This "transcriptional numbness" lowers the probability of cell death at early stages, increasing the chance of long-term adaptation at the population level. Our findings provide a mechanistic explanation for the widespread selection of subclonal epigenetic-related mutations in cancer and uncover phenotypic inertia as a cellular trait that drives subclone expansion.

Targeted Desorption Electrospray Ionization Mass Spectrometry Imaging for Drug Distribution, Toxicity, and Tissue Classification Studies.

With increased use of mass spectrometry imaging (MSI) in support of pharmaceutical research and development, there are opportunities to develop analytical pipelines that incorporate exploratory high-performance analysis with higher capacity and faster targeted MSI. Therefore, to enable faster MSI data acquisition we present analyte-targeted desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) utilizing a triple-quadrupole (TQ) mass analyzer. The evaluated platform configuration provided superior sensitivity compared to a conventional time-of-flight (TOF) mass analyzer and thus holds the potential to generate data applicable to pharmaceutical research and development. The platform was successfully operated with sampling rates up to 10 scans/s, comparing positively to the 1 scan/s commonly used on comparable DESI-TOF setups. The higher scan rate enabled investigation of the desorption/ionization processes of endogenous lipid species such as phosphatidylcholines and a co-administered cassette of four orally dosed drugs-erlotininb, moxifloxacin, olanzapine, and terfenadine. This was used to enable understanding of the impact of the desorption/ionization processes in order to optimize the operational parameters, resulting in improved compound coverage for olanzapine and the main olanzapine metabolite, hydroxy-olanzapine, in brain tissue sections compared to DESI-TOF analysis or matrix-assisted laser desorption/ionization (MALDI) platforms. The approach allowed reducing the amount of recorded information, thus reducing the size of datasets from up to 150 GB per experiment down to several hundred MB. The improved performance was demonstrated in case studies investigating the suitability of this approach for mapping drug distribution, spatially resolved profiling of drug-induced nephrotoxicity, and molecular-histological tissue classification of ovarian tumors specimens.

Vitamin B5 supports MYC oncogenic metabolism and tumor progression in breast cancer.

Tumors are intrinsically heterogeneous and it is well established that this directs their evolution, hinders their classification and frustrates therapy1-3. Consequently, spatially resolved omics-level analyses are gaining traction4-9. Despite considerable therapeutic interest, tumor metabolism has been lagging behind this development and there is a paucity of data regarding its spatial organization. To address this shortcoming, we set out to study the local metabolic effects of the oncogene c-MYC, a pleiotropic transcription factor that accumulates with tumor progression and influences metabolism10,11. Through correlative mass spectrometry imaging, we show that pantothenic acid (vitamin B5) associates with MYC-high areas within both human and murine mammary tumors, where its conversion to coenzyme A fuels Krebs cycle activity. Mechanistically, we show that this is accomplished by MYC-mediated upregulation of its multivitamin transporter SLC5A6. Notably, we show that SLC5A6 over-expression alone can induce increased cell growth and a shift toward biosynthesis, whereas conversely, dietary restriction of pantothenic acid leads to a reversal of many MYC-mediated metabolic changes and results in hampered tumor growth. Our work thus establishes the availability of vitamins and cofactors as a potential bottleneck in tumor progression, which can be exploited therapeutically. Overall, we show that a spatial understanding of local metabolism facilitates the identification of clinically relevant, tractable metabolic targets.

Genotype-Phenotype Taxonomy of Hypertrophic Cardiomyopathy.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is an important cause of sudden cardiac death associated with heterogeneous phenotypes, but there is no systematic framework for classifying morphology or assessing associated risks. Here, we quantitatively survey genotype-phenotype associations in HCM to derive a data-driven taxonomy of disease expression. METHODS: We enrolled 436 patients with HCM (median age, 60 years; 28.8% women) with clinical, genetic, and imaging data. An independent cohort of 60 patients with HCM from Singapore (median age, 59 years; 11% women) and a reference population from the UK Biobank (n=16 691; mean age, 55 years; 52.5% women) were also recruited. We used machine learning to analyze the 3-dimensional structure of the left ventricle from cardiac magnetic resonance imaging and build a tree-based classification of HCM phenotypes. Genotype and mortality risk distributions were projected on the tree. RESULTS: Carriers of pathogenic or likely pathogenic variants for HCM had lower left ventricular mass, but greater basal septal hypertrophy, with reduced life span (mean follow-up, 9.9 years) compared with genotype negative individuals (hazard ratio, 2.66 [95% CI, 1.42-4.96]; P<0.002). Four main phenotypic branches were identified using unsupervised learning of 3-dimensional shape: (1) nonsarcomeric hypertrophy with coexisting hypertension; (2) diffuse and basal asymmetrical hypertrophy associated with outflow tract obstruction; (3) isolated basal hypertrophy; and (4) milder nonobstructive hypertrophy enriched for familial sarcomeric HCM (odds ratio for pathogenic or likely pathogenic variants, 2.18 [95% CI, 1.93-2.28]; P=0.0001). Polygenic risk for HCM was also associated with different patterns and degrees of disease expression. The model was generalizable to an independent cohort (trustworthiness, M1: 0.86-0.88). CONCLUSIONS: We report a data-driven taxonomy of HCM for identifying groups of patients with similar morphology while preserving a continuum of disease severity, genetic risk, and outcomes. This approach will be of value in understanding the causes and consequences of disease diversity.

Effect of Different Modified Atmosphere Packaging on the Quality of Mulberry Fruit (Morus alba L. cv Kokuso 21).

The control of temperature and gas composition is essential to maintain the fresh flavor and quality of perishable fruits like mulberry. This study presented a modified atmosphere experiment (MAP) for fresh fruit showing the potential benefits of innovative gas mixing with argon. The effects of MAP were studied on the physicochemical and qualitative attributes of mulberry preserved at 4 ± 1°C and 90 ± 5% R.H. Fresh mulberries were packaged with different gas combinations: MAP1 (4%O2+6%CO2+90%N2), MAP2 (10%O2+5%CO2+85%Ar), CTR1 (20.9%O2+0.04%CO2), and CTR2 (10%O2+5%CO2+85%N2). Changes in quality parameters were evaluated after 0, 4, 8, and 12 days of storage. Mulberries packaged with MAP had a lower weight loss than CTR samples which lost more than 80% of their initial weight. Furthermore, the results showed that the argon treatment was the best in keeping the fruit juice content, preserving its structure. Despite not showing great differences with MAP1 treatment, Ar allowed to maintain high TSS up to 8 storage days, slowed CO2 production. The sensory profile of mulberry fruit was not significantly affected by storage in modified atmospheres, and the production of potential unpleasant odors in MAP2 could not be perceived. The results of this study confirm that this innovative approach, using MAP technology, has a potential use in maintaining mulberry fruit quality for a longer time.

Effects of Argon-Based and Nitrogen-Based Modified Atmosphere Packaging Technology on the Quality of Pomegranate (Punica granatum L. cv. Wonderful) Arils.

Ready-to-eat pomegranate arils are considered a "functional food" for their health benefits and have desirable sensory characteristics, which have caused an increasing interest by the consumers for this product. The preparation process of ready-to-eat fruit products can cause severe injuries and worsen their quality and shelf life significantly. Modified atmosphere packaging (MAP) has been used broadly in the last years to maintain the quality of processed fruits and showed optimal results, in spite of the possible problems caused by the depletion of O2 and corresponding accumulation of CO2 in the package. This study was conducted to evaluate the effects of different MAP treatments, based on nitrogen or alternatively on a noble gas, argon, in combination with refrigerated storage (0, 4, 8, 12, and 16 days at 4 ± 1 °C and 90 ± 5% RH) on the qualitative parameters of pomegranate arils with the aim to prolong their post-harvest life maintaining the original quality. The argon-based MAP treatment (MAPAr) was the one that provided the best results, assuring a limited loss of weight and juice content. The use of noble gas allowed to maintain a high sugar/acid ratio until 16 days from packaging. Sensory analysis on all MAP treated arils and, on the juice, obtained from them were carried out, and judges showed a preference for MAPAr treated arils and juice until day 12 from packaging.

Fruit Growth Stage Transitions in Two Mango Cultivars Grown in a Mediterranean Environment.

Studying mango (Mangifera indica L.) fruit development represents one of the most important aspects for the precise orchard management under non-native environmental conditions. In this work, precision fruit gauges were used to investigate important eco-physiological aspects of fruit growth in two mango cultivars, Keitt (late ripening) and Tommy Atkins (early-mid ripening). Fruit absolute growth rate (AGR, mm day-1), daily diameter fluctuation (ΔD, mm), and a development index given by their ratio (AGR/ΔD) were monitored to identify the prevalent mechanism (cell division, cell expansion, ripening) involved in fruit development in three ('Tommy Atkins') or four ('Keitt') different periods during growth. In 'Keitt', cell division prevailed over cell expansion from 58 to 64 days after full bloom (DAFB), while the opposite occurred from 74 to 85 DAFB. Starting at 100 DAFB, internal changes prevailed over fruit growth, indicating the beginning of the ripening stage. In Tommy Atkins (an early ripening cultivar), no significant differences in AGR/ΔD was found among monitoring periods, indicating that both cell division and expansion coexisted at gradually decreasing rates until fruit harvest. To evaluate the effect of microclimate on fruit growth the relationship between vapor pressure deficit (VPD) and ΔD was also studied. In 'Keitt', VPD was the main driving force determining fruit diameter fluctuations. In 'Tommy Atkins', the lack of relationship between VPD and ΔD suggest a hydric isolation of the fruit due to the disruption of xylem and stomatal flows starting at 65 DAFB. Further studies are needed to confirm this hypothesis.

Direct on-swab metabolic profiling of vaginal microbiome host interactions during pregnancy and preterm birth.

The pregnancy vaginal microbiome contributes to risk of preterm birth, the primary cause of death in children under 5 years of age. Here we describe direct on-swab metabolic profiling by Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) for sample preparation-free characterisation of the cervicovaginal metabolome in two independent pregnancy cohorts (VMET, n = 160; 455 swabs; VMET II, n = 205; 573 swabs). By integrating metataxonomics and immune profiling data from matched samples, we show that specific metabolome signatures can be used to robustly predict simultaneously both the composition of the vaginal microbiome and host inflammatory status. In these patients, vaginal microbiota instability and innate immune activation, as predicted using DESI-MS, associated with preterm birth, including in women receiving cervical cerclage for preterm birth prevention. These findings highlight direct on-swab metabolic profiling by DESI-MS as an innovative approach for preterm birth risk stratification through rapid assessment of vaginal microbiota-host dynamics.