Alexander A. Aksenov

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.

Differentiation of Closely Related Isomers: Application of Data Mining Techniques in Conjunction with Variable Wavelength Infrared Multiple Photon Dissociation Mass Spectrometry for Identification of Glucose-Containing Disaccharide Ions

Data mining algorithms have been used to analyze the infrared multiple photon dissociation (IRMPD) patterns of gas-phase lithiated disaccharide isomers irradiated with either a line-tunable CO(2) laser or a free electron laser (FEL). The IR fragmentation patterns over the wavelength range of 9.2-10.6 μm have been shown in earlier work to correlate uniquely with the asymmetry at the anomeric carbon in each disaccharide. Application of data mining approaches for data analysis allowed unambiguous determination of the anomeric carbon configurations for each disaccharide isomer pair using fragmentation data at a single wavelength. In addition, the linkage positions were easily assigned. This combination of wavelength-selective IRMPD and data mining offers a powerful and convenient tool for differentiation of structurally closely related isomers, including those of gas-phase carbohydrate complexes.

Best practices for analysing microbiomes

Complex microbial communities shape the dynamics of various environments, ranging from the mammalian gastrointestinal tract to the soil. Advances in DNA sequencing technologies and data analysis have provided drastic improvements in microbiome analyses, for example, in taxonomic resolution, false discovery rate control and other properties, over earlier methods. In this Review, we discuss the best practices for performing a microbiome study, including experimental design, choice of molecular analysis technology, methods for data analysis and the integration of multiple omics data sets. We focus on recent findings that suggest that operational taxonomic unit-based analyses should be replaced with new methods that are based on exact sequence variants, methods for integrating metagenomic and metabolomic data, and issues surrounding compositional data analysis, where advances have been particularly rapid. We note that although some of these approaches are new, it is important to keep sight of the classic issues that arise during experimental design and relate to research reproducibility. We describe how keeping these issues in mind allows researchers to obtain more insight from their microbiome data sets.Complex microbial communities shape the dynamics of various environments. In this Review, Knight and colleagues discuss the best practices for performing a microbiome study, including experimental design, choice of molecular analysis technology, methods for data analysis and the integration of multiple omics data sets.

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.

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

Increasing appreciation of the gut microbiomes 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).

3D molecular cartography using LC–MS facilitated by Optimus and 'ili software

Our skin, our belongings, the world surrounding us, and the environment we live in are covered with molecular traces. Detecting and characterizing these molecular traces is necessary to understand the environmental impact on human health and disease, and to decipher complex molecular interactions between humans and other species, particularly microbiota. We recently introduced 3D molecular cartography for mapping small organic molecules (including metabolites, lipids, and environmental molecules) found on various surfaces, including the human body. Here, we provide a protocol and open-source software for 3D molecular cartography. The protocol includes step-by-step procedures for sample collection and processing, liquid chromatography-mass spectrometry (LC-MS)-based metabolomics, quality control (QC), molecular identification using MS/MS, data processing, and visualization with 3D models of the sampled environment. The LC-MS method was optimized for a broad range of small organic molecules. We enable scientists to reproduce our previously obtained results, and illustrate the broad utility of our approach with molecular maps of a rosemary plant and an ATM keypad after a PIN code was entered. To promote reproducibility, we introduce cartographical snapshots: files that describe a particular map and visualization settings, and that can be shared and loaded to reproduce the visualization. The protocol enables molecular cartography to be performed in any mass spectrometry laboratory and, in principle, for any spatially mapped data. We anticipate applications, in particular, in medicine, ecology, agriculture, biotechnology, and forensics. The protocol takes 78 h for a molecular map of 100 spots, excluding the reagent setup.

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

This corrects the article DOI: 10.1038/nature24302

Untargeted Mass Spectrometry-Based Metabolomics Tracks Molecular Changes in Raw and Processed Foods and Beverages

A major aspect of our daily lives is the need to acquire, store and prepare our food. Storage and preparation can have drastic effects on the compositional chemistry of our foods, but we have a limited understanding of the temporal nature of processes such as storage, spoilage, fermentation and brewing on the chemistry of the foods we eat. Here, we performed a temporal analysis of the chemical changes in foods during common household preparations using untargeted mass spectrometry and novel data analysis approaches. Common treatments of foods such as home fermentation of yogurt, brewing of tea, spoilage of meats and ripening of tomatoes altered the chemical makeup through time, through both chemical and biological processes. For example, brewing tea altered its composition by increasing the diversity of molecules, but this change was halted after 4 min of brewing. The results indicate that this is largely due to differential extraction of the material from the tea and not modification of the molecules during the brewing process. This is in contrast to the preparation of yogurt from milk, spoilage of meat and the ripening of tomatoes where biological transformations directly altered the foods molecular composition. Comprehensive assessment of chemical changes using multivariate statistics showed the varied impacts of the different food treatments, while analysis of individual chemical changes show specific alterations of chemical families in the different food types. The methods developed here represent novel approaches to studying the changes in food chemistry that can reveal global alterations in chemical profiles and specific transformations at the chemical level. Highlights We created a reference data set for tomato, milk to yogurt, tea, coffee, turkey and beef. We show that normal preparation and handling affects the molecular make-up. Tea preparation is largely driven by differential extraction. Formation of yogurt involves chemical transformations. The majority of meat molecules are not altered in 5 days at room temperature.

Niche partitioning of a pathogenic microbiome driven by chemical gradients

Chemical gradients shape the cystic fibrosis lung microbiome, with marked effects on the outcome of antimicrobial treatments. Environmental microbial communities are stratified by chemical gradients that shape the structure and function of these systems. Similar chemical gradients exist in the human body, but how they influence these microbial systems is more poorly understood. Understanding these effects can be particularly important for dysbiotic shifts in microbiome structure that are often associated with disease. We show that pH and oxygen strongly partition the microbial community from a diseased human lung into two mutually exclusive communities of pathogens and anaerobes. Antimicrobial treatment disrupted this chemical partitioning, causing complex death, survival, and resistance outcomes that were highly dependent on the individual microorganism and on community stratification. These effects were mathematically modeled, enabling a predictive understanding of this complex polymicrobial system. Harnessing the power of these chemical gradients could be a drug-free method of shaping microbial communities in the human body from undesirable dysbiotic states.

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.