Author Correction: Inflammation-induced IgA+ cells dismantle anti-liver cancer immunity.

In this Article, the sentence: "After 7 months of HFD, MUP-uPA mice developed HCC15, which contained numerous (usually 50-100 per tumour) non-recurrent coding mutations in pathways that are mutated in human HCC (Fig. 2d and Extended Data Fig. 6a).", should have read: "After 7 months of HFD, MUP-uPA mice developed HCC15, which contained numerous (usually 50-100 per tumour) non-recurrent mutations in pathways that are mutated in human HCC (Fig. 2d and Extended Data Fig. 6a).". This has been corrected online. In Extended Data Fig. 6a and b, which show the number of point mutations identified per sample and the mutational signatures, all sequence variants (including non-coding mutations) are shown. Fig. 2d also presents all variants compared to human mutations. In the Supplementary Information to this Amendment, we now provide the comparisons of all variants and coding variants to human mutations.

Feature-based molecular networking in the GNPS analysis environment.

Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.

ReDU: a framework to find and reanalyze public mass spectrometry data.

We present ReDU ( https://redu.ucsd.edu/ ), a system for metadata capture of public mass spectrometry-based metabolomics data, with validated controlled vocabularies. Systematic capture of knowledge enables the reanalysis of public data and/or co-analysis of one's own data. ReDU enables multiple types of analyses, including finding chemicals and associated metadata, comparing the shared and different chemicals between groups of samples, and metadata-filtered, repository-scale molecular networking.

Inflammation-induced IgA+ cells dismantle anti-liver cancer immunity.

The role of adaptive immunity in early cancer development is controversial. Here we show that chronic inflammation and fibrosis in humans and mice with non-alcoholic fatty liver disease is accompanied by accumulation of liver-resident immunoglobulin-A-producing (IgA+) cells. These cells also express programmed death ligand 1 (PD-L1) and interleukin-10, and directly suppress liver cytotoxic CD8+ T lymphocytes, which prevent emergence of hepatocellular carcinoma and express a limited repertoire of T-cell receptors against tumour-associated antigens. Whereas CD8+ T-cell ablation accelerates hepatocellular carcinoma, genetic or pharmacological interference with IgA+ cell generation attenuates liver carcinogenesis and induces cytotoxic T-lymphocyte-mediated regression of established hepatocellular carcinoma. These findings establish the importance of inflammation-induced suppression of cytotoxic CD8+ T-lymphocyte activation as a tumour-promoting mechanism.

Erratum: Inflammation-induced IgA+ cells dismantle anti-liver cancer immunity.

This corrects the article DOI: 10.1038/nature24302.

SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information.

Mass spectrometry is a predominant experimental technique in metabolomics and related fields, but metabolite structural elucidation remains highly challenging. We report SIRIUS 4 (https://bio.informatik.uni-jena.de/sirius/), which provides a fast computational approach for molecular structure identification. SIRIUS 4 integrates CSI:FingerID for searching in molecular structure databases. Using SIRIUS 4, we achieved identification rates of more than 70% on challenging metabolomics datasets.

Learning representations of microbe-metabolite interactions.

Integrating multiomics datasets is critical for microbiome research; however, inferring interactions across omics datasets has multiple statistical challenges. We solve this problem by using neural networks (https://github.com/biocore/mmvec) to estimate the conditional probability that each molecule is present given the presence of a specific microorganism. We show with known environmental (desert soil biocrust wetting) and clinical (cystic fibrosis lung) examples, our ability to recover microbe-metabolite relationships, and demonstrate how the method can discover relationships between microbially produced metabolites and inflammatory bowel disease.

Progress Toward an Attract-and-Kill Device for Asian Citrus Psyllid (Hemiptera: Liviidae) Using Volatile Signatures of Citrus Infected With Huanglongbing as the Attractant.

Asian citrus psyllid, Diaphorina citri (Kuwayama), preferentially orient toward citrus hosts infected with the phytopathogenic bacterium, Candidatus liberibacter asiaticus (CLas) the agent of citrus greening (Huanglongbing, HLB), compared to uninfected counterparts. We investigated whether this preference for the odors of infected plants could be useful for the development of an attract-and-kill (AK) device for D. citri. Twenty-nine blends of volatile organic compounds derived from the odor of citrus infected with CLas were tested in laboratory olfactometer tests, and two blends were also assessed under field conditions. A seven component blend of tricosane: geranial: methyl salicylate: geranyl acetone: linalool: phenylacetaldehyde: (E)-ß-ocimene in a 0.40: 0.06: 0.08: 0.29: 0.08: 0.06: 0.03 ratio released from a proprietary slow-release matrix attracted twice more D. citri to yellow sticky traps compared with blank control traps. The attractive blend was subsequently co-formulated with spinosad insecticide into a slow-release matrix to create a prototype AK formulation against D. citri. This formulation effectively reduced the population density of D. citri up to 84% as measured with tap counts when deployed at a density of eight 2.5 g dollops per tree as compared with untreated controls in small plot field trials conducted in citrus orchards. Psyllid populations were not statistically affected at a deployment rate of four dollops per tree. Our results indicate that an AK formulation incorporating spinosad and a volatile blend signature of citrus greening into a slow-release matrix may be useful to suppress D. citri populations.

High Asymmetric Longitudinal Field Ion Mobility Spectrometry Device for Low Power Mobile Chemical Separation and Detection.

We have developed a novel chemical sensing technique termed high asymmetric longitudinal field ion mobility spectrometry (HALF-IMS), which allows separation of ions based on mobility differences in high and low electric fields. Our device is microfabricated, has a miniature format, and uses exceptionally low power due to the lack of RF separation fields normally associated with ion mobility spectrometry (IMS) or differential mobility spectrometry (DMS). It operates at room temperature and atmospheric pressure. This HALF-IMS chip contains a microscale drift cell where spatially varying electric field regions of high and low strengths are generated by direct current (DC) applied to the electrodes that are physically placed to cause ionic separation as the ionized chemical flows along the drift cell. Power and complexity are reduced at the chip and system levels by reducing the voltage magnitude and using DC-powered electronics. A testing platform utilizing an ultraviolet (UV) photoionization source was used with custom electronic circuit boards to interface with the chip and provide data inputs and outputs. Precise control of the electrode voltages allowed filtering of the passage of the ion of interest through the drift cell, and ionic current was measured at the detector. The device was tested by scanning of electrode voltages and obtaining ion peaks for methyl salicylate, naphthalene, benzene, and 2-butanone. The current experimental setup was capable of detecting as low as ∼80 ppb of methyl salicylate and naphthalene. The use of benzene as a dopant with 2-butanone allowed one to see two ion peaks, corresponding to benzene and 2-butanone.

SPME-based mobile field device for active sampling of volatiles.

Monitoring plant volatile organic compound (VOC) profiles can reveal information regarding the health state of the plant, such as whether it is nutrient stressed or diseased. Typically, plant VOC sampling uses sampling enclosures. Enclosures require time and equipment which are not easily adapted to high throughput sampling in field environments. We have developed a new, easily assembled active sampling device using solid phase microextraction (SPME) that uses a commercial off the shelf (COTS) hand vacuum base to provide rapid and easy mobile plant VOC collection. Calibration curves for three representative plant VOCs (α-pinene, limonene, and ocimene) were developed to verify device functionality and enable the quantification of field-samples from a Meyer lemon tree. We saw that the active sampling allowed us to measure and quantify this chemical in an orchard setting. This device has the potential to be used for VOC sampling as a preliminary diagnostic in precision agriculture applications due to its ease of manufacturing, availability, and low cost of the COTS hand vacuum module.

Coupling Targeted and Untargeted Mass Spectrometry for Metabolome-Microbiome-Wide Association Studies of Human Fecal Samples.

Increasing appreciation of the gut microbiome's role in health motivates understanding the molecular composition of human feces. To analyze such complex samples, we developed a platform coupling targeted and untargeted metabolomics. The approach is facilitated through split flow from one UPLC, joint timing triggered by contact closure relays, and a script to retrieve the data. It is designed to detect specific metabolites of interest with high sensitivity, allows for correction of targeted information, enables better quantitation thus providing an advanced analytical tool for exploratory studies. Procrustes analysis revealed that untargeted approach provides a better correlation to microbiome data, associating specific metabolites with microbes that produce or process them. With the subset of over one hundred human fecal samples from the American Gut project, the implementation of the described coupled workflow revealed that targeted analysis using combination of single transition per compound with retention time misidentifies 30% of the targeted data and could lead to incorrect interpretations. At the same time, the targeted analysis extends detection limits and dynamic range, depending on the compounds, by orders of magnitude. A software application has been developed as a part of the workflow to allows for quantitative assessments based on calibration curves. Using this approach, we detect expected microbially modified molecules such as secondary bile acids and unexpected microbial molecules including Pseudomonas-associated quinolones and rhamnolipids in feces, setting the stage for metabolome-microbiome-wide association studies (MMWAS).

Noninvasive Respiratory Metabolite Analysis Associated with Clinical Disease in Cetaceans: A Deepwater Horizon Oil Spill Study.

Health assessments of wild cetaceans can be challenging due to the difficulty of gaining access to conventional diagnostic matrices of blood, serum and others. While the noninvasive detection of metabolites in exhaled breath could potentially help to address this problem, there exists a knowledge gap regarding associations between known disease states and breath metabolite profiles in cetaceans. This technology was applied to the largest marine oil spill in U.S. history (The 2010 Deepwater Horizon oil spill in the Gulf of Mexico). An accurate analysis was performed to test for associations between the exhaled breath metabolome and sonographic lung abnormalities as well as hematological, serum biochemical, and endocrine hormone parameters. Importantly, metabolites consistent with chronic inflammation, such as products of lung epithelial cellular breakdown and arachidonic acid cascade metabolites were associated with sonographic evidence of lung consolidation. Exhaled breath condensate (EBC) metabolite profiles also correlated with serum hormone concentrations (cortisol and aldosterone), hepatobiliary enzyme levels, white blood cell counts, and iron homeostasis. The correlations among breath metabolites and conventional health measures suggest potential application of breath sampling for remotely assessing health of wild cetaceans. This methodology may hold promise for large cetaceans in the wild for which routine collection of blood and respiratory anomalies are not currently feasible.

Exhaled breath condensate methods adapted from human studies using longitudinal metabolomics for predicting early health alterations in dolphins.

Monitoring health conditions is essential to detect early asymptomatic stages of a disease. To achieve this, blood, urine and breath samples are commonly used as a routine clinical diagnostic. These samples offer the opportunity to detect specific metabolites related to diseases and provide a better understanding of their development. Although blood samples are commonly used routinely to monitor health, the implementation of a relatively noninvasive technique, such as exhaled breath condensate (EBC) analysis, may further benefit the well-being of both humans and other animals. EBC analysis can be used to track possible physical or biochemical alterations caused by common diseases of the bottlenose dolphin (Tursiops truncatus), such as infections or inflammatory-mediated processes. We have used an untargeted metabolomic method with liquid chromatography-mass spectrometry analysis of EBC samples to determine biomarkers related to disease development. In this study, five dolphins under human care were followed up for 1 year. We collected paired blood, physical examination information, and EBC samples. We then statistically correlated this information to predict specific health alterations. Three dolphins provided promising case study information about biomarkers related to cutaneous infections, respiratory infections, dental disease, or hormonal changes (pregnancy). The use of complementary liquid chromatography platforms, with hydrophilic interaction chromatography and reverse-phased columns, allowed us to detect a wide spectrum of EBC biomarker compounds that could be related to these health alterations. Moreover, these two analytical techniques not only provided complementary metabolite information but in both cases they also provided promising diagnostic information for these health conditions. Graphical abstract Collection of the exhaled condensed breath from a bottlenose dolphin from U.S. Navy Marine Mammal Program (MMP).

Identification of fungal metabolites from inside Gallus gallus domesticus eggshells by non-invasively detecting volatile organic compounds (VOCs).

The natural porosity of eggshells allows hen eggs to become contaminated with microbes from the nesting material and environment. Those microorganisms can later proliferate due to the humid ambient conditions while stored in refrigerators, causing a potential health hazard to the consumer. The microbes' volatile organic compounds (mVOCs) are released by both fungi and bacteria. We studied mVOCs produced by aging eggs likely contaminated by fungi and fresh eggs using the non-invasive detection method of gas-phase sampling of volatiles followed by gas chromatography/mass spectrometry (GC/MS) analysis. Two different fungal species (Cladosporium macrocarpum and Botrytis cinerea) and two different bacteria species (Stenotrophomas rhizophila and Pseudomonas argentinensis) were identified inside the studied eggs. Two compounds believed to originate from the fungi themselves were identified. One fungus-specific compound was found in both egg and the fungi: trichloromethane. Graphical abstract Trichloromethane is a potential biomarker of fungal contamination of eggs.

Determination of iron content and dispersity of intact ferritin by superconducting tunnel junction cryodetection mass spectrometry.

Ferritin is a common iron storage protein complex found in both eukaryotic and prokaryotic organisms. Although horse spleen holoferritin (HS-HoloFt) has been widely studied, this is the first report of mass spectrometry (MS) analysis of the intact form, likely because of its high molecular weight ∼850 kDa and broad iron-core mass distribution. The 24-subunit ferritin heteropolymer protein shell consists of light (L) and heavy (H) subunits and a ferrihydrite-like iron core. The H/L heterogeneity ratio of the horse spleen apoferritin (HS-ApoFt) shell was found to be ∼1:10 by liquid chromatography-electrospray ionization mass spectrometry. Superconducting tunneling junction (STJ) cryodetection matrix-assisted laser desorption ionization time-of-flight MS was utilized to determine the masses of intact HS-ApoFt, HS-HoloFt, and the HS-HoloFt dimer to be ∼505 kDa, ∼835 kDa, and ∼1.63 MDa, respectively. The structural integrity of HS-HoloFt and the proposed mineral adducts found for both purified L and H subunits suggest a robust biomacromolecular complex that is internally stabilized by the iron-based core. However, cross-linking experiments of HS-HoloFt with glutaraldehyde, unexpectedly, showed the complete release of the iron-based core in a one-step process revealing a cross-linked HS-ApoFt with a narrow fwhm peak width of 31.4 kTh compared to 295 kTh for HS-HoloFt. The MS analysis of HS-HoloFt revealed a semiquantitative description of the iron content and core dispersity of 3400 ± 1600 (2σ) iron atoms. Commercially prepared HS-ApoFt was estimated to still contain an average of 240 iron atoms. These iron abundance and dispersity results suggest the use of STJ cryodetection MS for the clinical analysis of iron deficient/overload diseases.

Detection of Huanglongbing disease using differential mobility spectrometry.

The viability of the multibillion dollar global citrus industry is threatened by the "green menace", citrus greening disease (Huanglongbing, HLB), caused by the bacterial pathogen Candidatus Liberibacter. The long asymptomatic stage of HLB makes it challenging to detect emerging regional infections early to limit disease spread. We have established a novel method of disease detection based on chemical analysis of released volatile organic compounds (VOCs) that emanate from infected trees. We found that the biomarkers "fingerprint" is specific to the causal pathogen and could be interpreted using analytical methods such as gas chromatography/mass spectrometry (GC/MS) and gas chromatography/differential mobility spectrometry (GC/DMS). This VOC-based disease detection method has a high accuracy of ∼90% throughout the year, approaching 100% under optimal testing conditions, even at very early stages of infection where other methods are not adequate. Detecting early infection based on VOCs precedes visual symptoms and DNA-based detection techniques (real-time polymerase chain reaction, RT-PCR) and can be performed at a substantially lower cost and with rapid field deployment.

Metabolite content profiling of bottlenose dolphin exhaled breath.

Changing ocean health and the potential impact on marine mammal health are gaining global attention. Direct health assessments of wild marine mammals, however, is inherently difficult. Breath analysis metabolomics is a very attractive assessment tool due to its noninvasive nature, but it is analytically challenging. It has never been attempted in cetaceans for comprehensive metabolite profiling. We have developed a method to reproducibly sample breath from small cetaceans, specifically Atlantic bottlenose dolphins (Tursiops truncatus). We describe the analysis workflow to profile exhaled breath metabolites and provide here a first library of volatile and nonvolatile compounds in cetacean exhaled breath. The described analytical methodology enabled us to document baseline compounds in exhaled breath of healthy animals and to study changes in metabolic content of dolphin breath with regard to a variety of factors. The method of breath analysis may provide a very valuable tool in future wildlife conservation efforts as well as deepen our understanding of marine mammals biology and physiology.

Cellular scent of influenza virus infection.

Volatile organic compounds (VOCs) emanating from humans have the potential to revolutionize non-invasive diagnostics. Yet, little is known about how these compounds are generated by complex biological systems, and even less is known about how these compounds are reflective of a particular physiological state. In this proof-of-concept study, we examined VOCs produced directly at the cellular level from B lymphoblastoid cells upon infection with three live influenza virus subtypes: H9N2 (avian), H6N2 (avian), and H1N1 (human). Using a single cell line helped to alleviate some of the complexity and variability when studying VOC production by an entire organism, and it allowed us to discern marked differences in VOC production upon infection of the cells. The patterns of VOCs produced in response to infection were unique for each virus subtype, while several other non-specific VOCs were produced after infections with all three strains. Also, there was a specific time course of VOC release post infection. Among emitted VOCs, production of esters and other oxygenated compounds was particularly notable, and these may be attributed to increased oxidative stress resulting from infection. Elucidating VOC signatures that result from the host cells response to infection may yield an avenue for non-invasive diagnostics and therapy of influenza and other viral infections.