An untargeted analytical workflow based on Kendrick mass defect filtering reveals dysregulations in acylcarnitines in prostate cancer tissue.

BACKGROUND: Metabolomics is nowadays considered one the most powerful analytical for the discovery of metabolic dysregulations associated with the insurgence of cancer, given the reprogramming of the cell metabolism to meet the bioenergetic and biosynthetic demands of the malignant cell. Notwithstanding, several challenges still exist regarding quality control, method standardization, data processing, and compound identification. Therefore, there is a need for effective and straightforward approaches for the untargeted analysis of structurally related classes of compounds, such as acylcarnitines, that have been widely investigated in prostate cancer research for their role in energy metabolism and transport and ß-oxidation of fatty acids. RESULTS: In the present study, an innovative analytical platform was developed for the straightforward albeit comprehensive characterization of acylcarnitines based on high-resolution mass spectrometry, Kendrick mass defect filtering, and confirmation by prediction of their retention time in reversed-phase chromatography. In particular, a customized data processing workflow was set up on Compound Discoverer software to enable the Kendrick mass defect filtering, which allowed filtering out more than 90 % of the initial features resulting from the processing of 25 tumoral and adjacent non-malignant prostate tissues collected from patients undergoing radical prostatectomy. Later, a partial least square-discriminant analysis model validated by repeated double cross-validation was built on the dataset of 74 annotated acylcarnitines, with classification rates higher than 93 % for both groups, and univariate statistical analysis helped elucidate the individual role of the annotated metabolites. SIGNIFICANCE: Hydroxylation of short- and medium-chain minor acylcarnitines appeared to be a significant variable in describing tissue differences, suggesting the hypothesis that the neoplastic growth is linked to oxidation phenomena on selected metabolites and reinforcing the need for effective methods for the annotation of minor metabolites.

Biosignatures of defective sebaceous gland activity in sebum-rich and sebum-poor skin areas in adult atopic dermatitis.

Atopic dermatitis (AD) is a composite disease presenting disruption of the skin permeability barrier (SPB) in the stratum corneum (SC). Recent evidence supports derangement of the sebaceous gland (SG) activity in the AD pathomechanisms. The objective of this study was to delineate profiles of both sebaceous and epidermal lipids and of aminoacids from SG-rich (SGR) and SG-poor (SGP) areas in AD. Both sebum and SC were sampled from SGR areas, while SC was sampled also from SGP areas in 54 adult patients with AD, consisting of 34 and 20 subjects, respectively with and without clinical involvement of face, and in 44 age and sex-matched controls. Skin biophysics were assessed in all sampling sites. Disruption of the SBP was found to be associated with dysregulated lipidome. Abundance of sapienate and lignocerate, representing, respectively, sebum and the SC type lipids, were decreased in sebum and SC from both SGR and SGP areas. Analogously, squalene was significantly diminished in AD, regardless the site. Extent of lipid derangement in SGR areas was correlated with the AD severity. The abundance of aminoacids in the SC from SGR areas was altered more than that determined in SGP areas. Several gender-related differences were found in both controls and AD subgroups. In conclusion, the SG activity was differently compromised in adult females and males with AD, in both SGR and SGP areas. In AD, alterations in the aminoacidome profiles were apparent in the SGR areas. Lipid signatures in association with aminoacidome and skin physical properties may serve the definition of phenotype clusters that associate with AD severity and gender.

An atlas of cells in the human tonsil.

Palatine tonsils are secondary lymphoid organs (SLOs) representing the first line of immunological defense against inhaled or ingested pathogens. We generated an atlas of the human tonsil composed of >556,000 cells profiled across five different data modalities, including single-cell transcriptome, epigenome, proteome, and immune repertoire sequencing, as well as spatial transcriptomics. This census identified 121 cell types and states, defined developmental trajectories, and enabled an understanding of the functional units of the tonsil. Exemplarily, we stratified myeloid slan-like subtypes, established a BCL6 enhancer as locally active in follicle-associated T and B cells, and identified SIX5 as putative transcriptional regulator of plasma cell maturation. Analyses of a validation cohort confirmed the presence, annotation, and markers of tonsillar cell types and provided evidence of age-related compositional shifts. We demonstrate the value of this resource by annotating cells from B cell-derived mantle cell lymphomas, linking transcriptional heterogeneity to normal B cell differentiation states of the human tonsil.

Characterization of the aroma profile of edible flowers using HS-SPME/GC-MS and chemometrics.

In recent years the consumption of edible flowers has gained new popularity, and their use seems destined to grow thanks to their potential as functional elements and their ability to impart aroma to traditional foods. In this study, the volatile profile of several edible flowers was investigated to identify characteristic compounds to be used as product markers. 85 samples belonging to four cultivars were analyzed by HS-SPME/GC-MS. A PLS-DA was used to build a model capable of differentiating the investigated classes. The resulting model correctly predicted over 95% of the validation samples, highlighting a significant difference between the four types of edible flowers. The VIP analysis highlighted 29 compounds relevant for the characterization of different flowers, many of which were biologically active. The study aims to broaden the framework of objectively measurable tools useful for enhancing the qualitative peculiarity of one product compared to another and offering growth opportunities to emerging food chains.

Impact of plastic-related compounds on the gene expression signature of HepG2 cells transfected with CYP3A4.

The presence of plastic and microplastic within the oceans as well as in marine flora and fauna have caused a multitude of problems that have been the topic of numerous investigations for many years. However, their impact on human health remains largely unknown. Such plastic and microplastic particles have been detected in blood and placenta, underlining their ability to enter the human body. Plastics also contain other compounds, such as plasticizers, antioxidants, or dyes, whose impact on human health is currently being studied. Critical enzymes within the metabolism of endogenous molecules, especially of xenobiotics, are the cytochrome P450 monooxygenases (CYPs). Although their importance in maintaining cellular balance has been confirmed, their interactions with plastics and related products are poorly understood. In this study, the possible relationship between different plastic-related compounds and CYP3A4 as one of the most important CYPs was analyzed using hepatic cells overexpressing this enzyme. Beginning with virtual compound screening and molecular docking of more than 1000 plastic-related compounds, several candidates were identified to interact with CYP3A4. In a second step, RNA-sequencing was used to study in detail the transcriptome-wide gene expression levels affected by the selected compounds. Three candidate molecules ((2,2'-methylenebis(6-tert-butyl-4-methylphenol), 1,1-bis(3,5-di-tert-butyl-2-hydroxyphenyl)ethane, and 2,2'-methylenebis(6-cyclohexyl-4-methylphenol)) had an excellent binding affinity to CYP3A4 in-silico as well as cytotoxic effects and interactions with several metabolic pathways in-vitro. We identified common pathways influenced by all three selected plastic-related compounds. In particular, the suppression of pathways related to mitosis and 'DNA-templated DNA replication' which were confirmed by cell cycle analysis and single-cell gel electrophoresis. Furthermore, several mis-regulated metabolic and inflammation-related pathways were identified, suggesting the induction of hepatotoxicity at different levels. These findings imply that these compounds may cause liver problems subsequently affecting the entire organism.

Using single-cell chromatin accessibility sequencing to characterize CD4+ T cells from murine tissues.

The Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) is a cutting-edge technology that enables researchers to assess genome-wide chromatin accessibility and to characterize cell type specific gene-regulatory programs. Recent technological progress allows for using this technology also on the single-cell level. In this article, we describe the whole value chain from the isolation of T cells from murine tissues to a complete bioinformatic analysis workflow. We start with methods for isolating scATAC-seq-ready CD4+ T cells from murine tissues such as visceral adipose tissue, skin, colon, and secondary lymphoid tissues such as the spleen. We describe the preparation of nuclei and quality control parameters during library preparation. Based on publicly available sequencing data that was generated using these protocols, we describe a step-by-step bioinformatic analysis pipeline for data pre-processing and downstream analysis. Our analysis workflow will follow the R-based bioinformatics framework ArchR, which is currently well established for scATAC-seq datasets. All in all, this work serves as a one-stop shop for generating and analyzing chromatin accessibility landscapes in T cells.

A20 regulates lymphocyte adhesion in murine neuroinflammation by restricting endothelial ICOSL expression in the CNS.

A20 is a ubiquitin-modifying protein that negatively regulates NF-κB signaling. Mutations in A20/TNFAIP3 are associated with a variety of autoimmune diseases, including multiple sclerosis (MS). We found that deletion of A20 in central nervous system (CNS) endothelial cells (ECs) enhances experimental autoimmune encephalomyelitis (EAE), a mouse model of MS. A20ΔCNS-EC mice showed increased numbers of CNS-infiltrating immune cells during neuroinflammation and in the steady state. While the integrity of the blood-brain barrier (BBB) was not impaired, we observed a strong activation of CNS-ECs in these mice, with dramatically increased levels of the adhesion molecules ICAM-1 and VCAM-1. We discovered ICOSL to be expressed by A20-deficient CNS-ECs, which we found to function as adhesion molecules. Silencing of ICOSL in CNS microvascular ECs partly reversed the phenotype of A20ΔCNS-EC mice without reaching statistical significance and delayed the onset of EAE symptoms in WT mice. In addition, blocking of ICOSL on primary mouse brain microvascular ECs impaired the adhesion of T cells in vitro. Taken together, we propose that CNS EC-ICOSL contributes to the firm adhesion of T cells to the BBB, promoting their entry into the CNS and eventually driving neuroinflammation.

Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data.

The tremendous rate with which data is generated and analysis methods emerge makes it increasingly difficult to keep track of their domain of applicability, assumptions, limitations, and consequently, of the efficacy and precision with which they solve specific tasks. Therefore, there is an increasing need for benchmarks, and for the provision of infrastructure for continuous method evaluation. APAeval is an international community effort, organized by the RNA Society in 2021, to benchmark tools for the identification and quantification of the usage of alternative polyadenylation (APA) sites from short-read, bulk RNA-sequencing (RNA-seq) data. Here, we reviewed 17 tools and benchmarked eight on their ability to perform APA identification and quantification, using a comprehensive set of RNA-seq experiments comprising real, synthetic, and matched 3'-end sequencing data. To support continuous benchmarking, we have incorporated the results into the OpenEBench online platform, which allows for continuous extension of the set of methods, metrics, and challenges. We envisage that our analyses will assist researchers in selecting the appropriate tools for their studies, while the containers and reproducible workflows could easily be deployed and extended to evaluate new methods or data sets.

Tumor-infiltrating CCR2+ inflammatory monocytes counteract specific immunotherapy.

Tumor development and progression is shaped by the tumor microenvironment (TME), a heterogeneous assembly of infiltrating and resident host cells, their secreted mediators and intercellular matrix. In this context, tumors are infiltrated by various immune cells with either pro-tumoral or anti-tumoral functions. Recently, we published our non-invasive immunization platform DIVA suitable as a therapeutic vaccination method, further optimized by repeated application (DIVA2). In our present work, we revealed the therapeutic effect of DIVA2 in an MC38 tumor model and specifically focused on the mechanisms induced in the TME after immunization. DIVA2 resulted in transient tumor control followed by an immune evasion phase within three weeks after the initial tumor inoculation. High-dimensional flow cytometry analysis and single-cell mRNA-sequencing of tumor-infiltrating leukocytes revealed cytotoxic CD8+ T cells as key players in the immune control phase. In the immune evasion phase, inflammatory CCR2+ PDL-1+ monocytes with immunosuppressive properties were recruited into the tumor leading to suppression of DIVA2-induced tumor-reactive T cells. Depletion of CCR2+ cells with specific antibodies resulted in prolonged survival revealing CCR2+ monocytes as important for tumor immune escape in the TME. In summary, the present work provides a platform for generating a strong antigen-specific primary and memory T cell immune response using the optimized transcutaneous immunization method DIVA2. This enables protection against tumors by therapeutic immune control of solid tumors and highlights the immunosuppressive influence of tumor infiltrating CCR2+ monocytes that need to be inactivated in addition for successful cancer immunotherapy.

Using combined single-cell gene expression, TCR sequencing and cell surface protein barcoding to characterize and track CD4+ T cell clones from murine tissues.

Single-cell gene expression analysis using sequencing (scRNA-seq) has gained increased attention in the past decades for studying cellular transcriptional programs and their heterogeneity in an unbiased manner, and novel protocols allow the simultaneous measurement of gene expression, T-cell receptor clonality and cell surface protein expression. In this article, we describe the methods to isolate scRNA/TCR-seq-compatible CD4+ T cells from murine tissues, such as skin, spleen, and lymph nodes. We describe the processing of cells and quality control parameters during library preparation, protocols for multiplexing of samples, and strategies for sequencing. Moreover, we describe a step-by-step bioinformatic analysis pipeline from sequencing data generated using these protocols. This includes quality control, preprocessing of sequencing data and demultiplexing of individual samples. We perform quantification of gene expression and extraction of T-cell receptor alpha and beta chain sequences, followed by quality control and doublet detection, and methods for harmonization and integration of datasets. Next, we describe the identification of highly variable genes and dimensionality reduction, clustering and pseudotemporal ordering of data, and we demonstrate how to visualize the results with interactive and reproducible dashboards. We will combine different analytic R-based frameworks such as Bioconductor and Seurat, illustrating how these can be interoperable to optimally analyze scRNA/TCR-seq data of CD4+ T cells from murine tissues.

Untargeted cannabinomics reveals the chemical differentiation of industrial hemp based on the cultivar and the geographical field location.

Cannabis sativa has long been harvested for industrial applications related to its fibers. Industrial hemp cultivars, a botanical class of Cannabis sativa with a low expression of intoxicating Δ9-tetrahydrocannabinol (Δ9-THC) have been selected for these purposes and scarcely investigated in terms of their content in bioactive compounds. Following the global relaxation in the market of industrial hemp-derived products, research in industrial hemp for pharmaceutical and nutraceutical purposes has surged. In this context, metabolomics-based approaches have proven to fulfill the aim of obtaining comprehensive information on the phytocompound profile of cannabis samples, going beyond the targeted evaluation of the major phytocannabinoids. In the present paper, an HRMS-based metabolomics study was addressed to seven distinct industrial hemp cultivars grown in four experimental fields in Northern, Southern, and Insular Italy. Since the role of minor phytocannabinoids as well as other phytocompounds was found to be critical in discriminating cannabis chemovars and in determining its biological activities, a comprehensive characterization of phytocannabinoids, flavonoids, and phenolic acids was carried out by LC-HRMS and a dedicated data processing workflow following the guidelines of the metabolomics Quality Assurance and Quality Control Consortium. A total of 54 phytocannabinoids, 134 flavonoids, and 77 phenolic acids were annotated, and their role in distinguishing hemp samples based on the geographical field location and cultivar was evaluated by ANOVA-simultaneous component analysis. Finally, a low-level fused model demonstrated the key role of untargeted cannabinomics extended to lesser-studied phytocompound classes for the discrimination of hemp samples.

Authentication and discrimination of new Brazilian Canephora coffees with geographical indication using a miniaturized near-infrared spectrometer.

New Brazilian Canephora coffees (Conilon and Robusta) of high added value from specific origins have been protected by geographical indication to guarantee their origin and quality. Recently, benchtop near-infrared (NIR) spectroscopy combined with chemometrics has demonstrated its usefulness to discriminate them. It was the first study, however, and therefore the possibility exists to develop a new portable NIR method for this purpose. This work assessed a miniaturized NIR as a cheaper spectrometer to discriminate and authenticate new Brazilian Canephora coffees with certified geographical origins and to differentiate them from specialty Arabica. Discriminant chemometric and class modeling techniques have been applied and have obtained good predictive ability on external test sets. In addition, models with similar classification purpose were compared with those obtained in previous research carried out with benchtop NIR for the same samples, obtaining comparable results. In this context, the portable method was used as a laboratory technique and has the advantage of being cheaper than benchtop NIR spectrometer. Furthermore, it brings a high possibility to be implemented in small coffee cooperatives, industries or control agencies in the future that do not have high economic resources.

Determination of Enantiomeric Excess and Diastereomeric Excess via Optical Methods. Application to α-methyl-ß-hydroxy-carboxylic acids.

Characterization of chiral molecules in solution is paramount for measuring reaction success. However, techniques to distinguish between chiral molecules containing more than one stereocenter through the use of optical techniques remains a challenge. Herein, we report a techique using a series of circular dichroism spectra to train multivariate regression models that are capable of predicting the complete speciation of 3-hydroxy-2-methylbutanoic acid stereoisomers. From this, it is possible to rapidly and accurately determine the enantiomeric excess and diastereomeric excess of the solution without the need for chiral chromatography.

The Effect of Plastic-Related Compounds on Transcriptome-Wide Gene Expression on CYP2C19-Overexpressing HepG2 Cells.

In recent years, plastic and especially microplastic in the oceans have caused huge problems to marine flora and fauna. Recently, such particles have also been detected in blood, breast milk, and placenta, underlining their ability to enter the human body, presumably via the food chain and other yet-unknown mechanisms. In addition, plastic contains plasticizers, antioxidants, or lubricants, whose impact on human health is also under investigation. At the cellular level, the most important enzymes involved in the metabolism of xenobiotic compounds are the cytochrome P450 monooxygenases (CYPs). Despite their extensive characterization in the maintenance of cellular balance, their interactions with plastic and related products are unexplored. In this study, the possible interactions between several plastic-related compounds and one of the most important cytochromes, CYP2C19, were analyzed. By applying virtual compound screening and molecular docking to more than 1000 commercially available plastic-related compounds, we identified candidates that are likely to interact with this protein. A growth inhibition assay confirmed their cytotoxic activity on a CYP2C19-transfected hepatic cell line. Subsequently, we studied the effect of the selected compounds on the transcriptome-wide gene expression level by conducting RNA sequencing. Three candidate molecules were identified, i.e., 2,2'-methylene bis(6-tert-butyl-4-methylphenol), 1,1-bis(3,5-di-tert-butyl-2-hydroxyphenyl) ethane, and 2,2'-methylene bis(6-cyclohexyl-4-methylphenol)), which bound with a high affinity to CYP2C19 in silico. They exerted a profound cytotoxicity in vitro and interacted with several metabolic pathways, of which the 'cholesterol biosynthesis process' was the most affected. In addition, other affected pathways involved mitosis, DNA replication, and inflammation, suggesting an increase in hepatotoxicity. These results indicate that plastic-related compounds could damage the liver by affecting several molecular pathways.

Commensal bacteria weaken the intestinal barrier by suppressing epithelial neuropilin-1 and Hedgehog signaling.

The gut microbiota influences intestinal barrier integrity through mechanisms that are incompletely understood. Here we show that the commensal microbiota weakens the intestinal barrier by suppressing epithelial neuropilin-1 (NRP1) and Hedgehog (Hh) signaling. Microbial colonization of germ-free mice dampens signaling of the intestinal Hh pathway through epithelial Toll-like receptor (TLR)-2, resulting in decreased epithelial NRP1 protein levels. Following activation via TLR2/TLR6, epithelial NRP1, a positive-feedback regulator of Hh signaling, is lysosomally degraded. Conversely, elevated epithelial NRP1 levels in germ-free mice are associated with a strengthened gut barrier. Functionally, intestinal epithelial cell-specific Nrp1 deficiency (Nrp1ΔIEC) results in decreased Hh pathway activity and a weakened gut barrier. In addition, Nrp1ΔIEC mice have a reduced density of capillary networks in their small intestinal villus structures. Collectively, our results reveal a role for the commensal microbiota and epithelial NRP1 signaling in the regulation of intestinal barrier function through postnatal control of Hh signaling.

Effect of wheat roasting conditions and wheat type on short-wave infrared (SWIR) spectral data of whole and milled wheat by ANOVA-simultaneous component analysis.

ANOVA-simultaneous component analysis (ASCA) was used to investigate the effect of roasting and wheat type on shortwave-infrared (SWIR) spectra of whole wheat and flour through assessment of statistical significance and characterisation of the contributing spectral features. The full factorial experimental design included two wheat types, three roasting temperatures and three roasting frequencies. SWIR spectral images were collected from the two roasted wheat types and their two milled samples. Three ASCA models, one for each wheat conformation (kernel, whole wheat flour, white flour) were investigated. It was evidenced that all factors and interaction in the whole wheat flour model had a significant (p ≤ 0.05) effect on spectral data. Only the factor roasting frequency was not significant in white flour model and only the interaction between roasting frequency and wheat type was not significant for the kernel model. The main variations in the loading line plots were identified and characterised by chemical structural differences that occur within the sample. The effect of roasting frequency had a more adverse effect on protein stability, moisture evaporation, water soluble carbohydrates and aromatic amino acids, compared to roasting temperature. A Rapid Visco-Analyser (RVA) was used to further investigate difference in wheat type as almost all spectral data sets differed significantly. The most prominent difference between the two wheat types was observed as differences in amylase activity and presence of lipids. ASCA applied to SWIR whole wheat and flour spectral data effectively characterised the significant effect of roasting on wheat starch and protein structures.

Successful combination of benchtop nuclear magnetic resonance spectroscopy and chemometric tools: A review.

Low-field nuclear magnetic resonance (NMR) has three general modalities: spectroscopy, imaging, and relaxometry. In the last twelve years, the modality of spectroscopy, also known as benchtop NMR, compact NMR, or just low-field NMR, has undergone instrumental development due to new permanent magnetic materials and design. As a result, benchtop NMR has emerged as a powerful analytical tool for use in process analytical control (PAC). Nevertheless, the successful application of NMR devices as an analytical tool in several areas is intrinsically linked to its coupling with different chemometric methods. This review focuses on the evolution of benchtop NMR and chemometrics in chemical analysis, including applications in fuels, foods, pharmaceuticals, biochemicals, drugs, metabolomics, and polymers. The review also presents different low-resolution NMR methods for spectrum acquisition and chemometric techniques for calibration, classification, discrimination, data fusion, calibration transfer, multi-block and multi-way.

Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data.

The tremendous rate with which data is generated and analysis methods emerge makes it increasingly difficult to keep track of their domain of applicability, assumptions, and limitations and consequently, of the efficacy and precision with which they solve specific tasks. Therefore, there is an increasing need for benchmarks, and for the provision of infrastructure for continuous method evaluation. APAeval is an international community effort, organized by the RNA Society in 2021, to benchmark tools for the identification and quantification of the usage of alternative polyadenylation (APA) sites from short-read, bulk RNA-sequencing (RNA-seq) data. Here, we reviewed 17 tools and benchmarked eight on their ability to perform APA identification and quantification, using a comprehensive set of RNA-seq experiments comprising real, synthetic, and matched 3'-end sequencing data. To support continuous benchmarking, we have incorporated the results into the OpenEBench online platform, which allows for seamless extension of the set of methods, metrics, and challenges. We envisage that our analyses will assist researchers in selecting the appropriate tools for their studies. Furthermore, the containers and reproducible workflows generated in the course of this project can be seamlessly deployed and extended in the future to evaluate new methods or datasets.

Circulating microRNAs predict recurrence and death following venous thromboembolism.

BACKGROUND: Recurrent events frequently occur after venous thromboembolism (VTE) and remain difficult to predict based on established genetic, clinical, and proteomic contributors. The role of circulating microRNAs (miRNAs) has yet to be explored in detail. OBJECTIVES: To identify circulating miRNAs predictive of recurrent VTE or death, and to interpret their mechanistic involvement. METHODS: Data from 181 participants of a cohort study of acute VTE and 302 individuals with a history of VTE from a population-based cohort were investigated. Next-generation sequencing was performed on EDTA plasma samples to detect circulating miRNAs. The endpoint of interest was recurrent VTE or death. Penalized regression was applied to identify an outcome-relevant miRNA signature, and results were validated in the population-based cohort. The involvement of miRNAs in coregulatory networks was assessed using principal component analysis, and the associated clinical and molecular phenotypes were investigated. Mechanistic insights were obtained from target gene and pathway enrichment analyses. RESULTS: A total of 1950 miRNAs were detected across cohorts after postprocessing. In the discovery cohort, 50 miRNAs were associated with recurrent VTE or death (cross-validated C-index, 0.65). A weighted miRNA score predicted outcome over an 8-year follow-up period (HRSD, 2.39; 95% CI, 1.98-2.88; P < .0001). The independent validation cohort validated 20 miRNAs (ORSD for score, 3.47; 95% CI, 2.37-5.07; P < .0001; cross-validated-area under the curve, 0.61). Principal component analysis revealed 5 miRNA networks with distinct relationships to clinical phenotype and outcome. Mapping of target genes indicated regulation via transcription factors and kinases involved in signaling pathways associated with fibrinolysis. CONCLUSION: Circulating miRNAs predicted the risk of recurrence or death after VTE over several years, both in the acute and chronic phases.