Guiding the choice of informatics software and tools for lipidomics research applications.

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

Challenges and perspectives for naming lipids in the context of lipidomics.

INTRODUCTION: Lipids are key compounds in the study of metabolism and are increasingly studied in biology projects. It is a very broad family that encompasses many compounds, and the name of the same compound may vary depending on the community where they are studied. OBJECTIVES: In addition, their structures are varied and complex, which complicates their analysis. Indeed, the structural resolution does not always allow a complete level of annotation so the actual compound analysed will vary from study to study and should be clearly stated. For all these reasons the identification and naming of lipids is complicated and very variable from one study to another, it needs to be harmonized. METHODS & RESULTS: In this position paper we will present and discuss the different way to name lipids (with chemoinformatic and semantic identifiers) and their importance to share lipidomic results. CONCLUSION: Homogenising this identification and adopting the same rules is essential to be able to share data within the community and to map data on functional networks.

Rhea, the reaction knowledgebase in 2022.

Rhea (https://www.rhea-db.org) is an expert-curated knowledgebase of biochemical reactions based on the chemical ontology ChEBI (Chemical Entities of Biological Interest) (https://www.ebi.ac.uk/chebi). In this paper, we describe a number of key developments in Rhea since our last report in the database issue of Nucleic Acids Research in 2019. These include improved reaction coverage in Rhea, the adoption of Rhea as the reference vocabulary for enzyme annotation in the UniProt knowledgebase UniProtKB (https://www.uniprot.org), the development of a new Rhea website, and the designation of Rhea as an ELIXIR Core Data Resource. We hope that these and other developments will enhance the utility of Rhea as a reference resource to study and engineer enzymes and the metabolic systems in which they function.

Interpreting the lipidome: bioinformatic approaches to embrace the complexity.

BACKGROUND: Improvements in mass spectrometry (MS) technologies coupled with bioinformatics developments have allowed considerable advancement in the measurement and interpretation of lipidomics data in recent years. Since research areas employing lipidomics are rapidly increasing, there is a great need for bioinformatic tools that capture and utilize the complexity of the data. Currently, the diversity and complexity within the lipidome is often concealed by summing over or averaging individual lipids up to (sub)class-based descriptors, losing valuable information about biological function and interactions with other distinct lipids molecules, proteins and/or metabolites. AIM OF REVIEW: To address this gap in knowledge, novel bioinformatics methods are needed to improve identification, quantification, integration and interpretation of lipidomics data. The purpose of this mini-review is to summarize exemplary methods to explore the complexity of the lipidome. KEY SCIENTIFIC CONCEPTS OF REVIEW: Here we describe six approaches that capture three core focus areas for lipidomics: (1) lipidome annotation including a resolvable database identifier, (2) interpretation via pathway- and enrichment-based methods, and (3) understanding complex interactions to emphasize specific steps in the analytical process and highlight challenges in analyses associated with the complexity of lipidome data.

Updates in Rhea: SPARQLing biochemical reaction data.

Rhea (http://www.rhea-db.org) is a comprehensive and non-redundant resource of over 11 000 expert-curated biochemical reactions that uses chemical entities from the ChEBI ontology to represent reaction participants. Originally designed as an annotation vocabulary for the UniProt Knowledgebase (UniProtKB), Rhea also provides reaction data for a range of other core knowledgebases and data repositories including ChEBI and MetaboLights. Here we describe recent developments in Rhea, focusing on a new resource description framework representation of Rhea reaction data and an SPARQL endpoint (https://sparql.rhea-db.org/sparql) that provides access to it. We demonstrate how federated queries that combine the Rhea SPARQL endpoint and other SPARQL endpoints such as that of UniProt can provide improved metabolite annotation and support integrative analyses that link the metabolome through the proteome to the transcriptome and genome. These developments will significantly boost the utility of Rhea as a means to link chemistry and biology for a more holistic understanding of biological systems and their function in health and disease.

Updates in Rhea - an expert curated resource of biochemical reactions.

Rhea (http://www.rhea-db.org) is a comprehensive and non-redundant resource of expert-curated biochemical reactions designed for the functional annotation of enzymes and the description of metabolic networks. Rhea describes enzyme-catalyzed reactions covering the IUBMB Enzyme Nomenclature list as well as additional reactions, including spontaneously occurring reactions, using entities from the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Here we describe developments in Rhea since our last report in the database issue of Nucleic Acids Research. These include the first implementation of a simple hierarchical classification of reactions, improved coverage of the IUBMB Enzyme Nomenclature list and additional reactions through continuing expert curation, and the development of a new website to serve this improved dataset.

Updates in Rhea--a manually curated resource of biochemical reactions.

Rhea (http://www.ebi.ac.uk/rhea) is a comprehensive and non-redundant resource of expert-curated biochemical reactions described using species from the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Rhea has been designed for the functional annotation of enzymes and the description of genome-scale metabolic networks, providing stoichiometrically balanced enzyme-catalyzed reactions (covering the IUBMB Enzyme Nomenclature list and additional reactions), transport reactions and spontaneously occurring reactions. Rhea reactions are extensively curated with links to source literature and are mapped to other publicly available enzyme and pathway databases such as Reactome, BioCyc, KEGG and UniPathway, through manual curation and computational methods. Here we describe developments in Rhea since our last report in the 2012 database issue of Nucleic Acids Research. These include significant growth in the number of Rhea reactions and the inclusion of reactions involving complex macromolecules such as proteins, nucleic acids and other polymers that lie outside the scope of ChEBI. Together these developments will significantly increase the utility of Rhea as a tool for the description, analysis and reconciliation of genome-scale metabolic models.

The SwissLipids knowledgebase for lipid biology.

MOTIVATION: Lipids are a large and diverse group of biological molecules with roles in membrane formation, energy storage and signaling. Cellular lipidomes may contain tens of thousands of structures, a staggering degree of complexity whose significance is not yet fully understood. High-throughput mass spectrometry-based platforms provide a means to study this complexity, but the interpretation of lipidomic data and its integration with prior knowledge of lipid biology suffers from a lack of appropriate tools to manage the data and extract knowledge from it. RESULTS: To facilitate the description and exploration of lipidomic data and its integration with prior biological knowledge, we have developed a knowledge resource for lipids and their biology-SwissLipids. SwissLipids provides curated knowledge of lipid structures and metabolism which is used to generate an in silico library of feasible lipid structures. These are arranged in a hierarchical classification that links mass spectrometry analytical outputs to all possible lipid structures, metabolic reactions and enzymes. SwissLipids provides a reference namespace for lipidomic data publication, data exploration and hypothesis generation. The current version of SwissLipids includes over 244 000 known and theoretically possible lipid structures, over 800 proteins, and curated links to published knowledge from over 620 peer-reviewed publications. We are continually updating the SwissLipids hierarchy with new lipid categories and new expert curated knowledge. AVAILABILITY: SwissLipids is freely available at http://www.swisslipids.org/. CONTACT: alan.bridge@isb-sib.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Diet-induced metabolic change induces estrogen-independent allometric mammary growth.

Lifetime breast cancer risk reflects an unresolved combination of early life factors including diet, body mass index, metabolic syndrome, obesity, and age at first menses. In parallel, the onset of allometric growth by the mammary glands around puberty is widely held to be estrogen (E)-dependent. Here we report that several physiological changes associated with metabolic syndrome in response to a diet supplemented with the trans-10, cis-12 isomer of conjugated linoleic acid lead to ovary-independent allometric growth of the mammary ducts. The E-independence of this diet-induced growth was highlighted by the fact that it occurred both in male mice and with pharmacological inhibition of either E receptor function or E biosynthesis. Reversal of the metabolic phenotype with the peroxisome proliferator-activated receptor-γ agonist rosiglitazone abrogated diet-induced mammary growth. A role for hyperinsulinemia and increased insulin-like growth factor-I receptor (IGF-IR) expression during mammary growth induced by the trans-10, cis-12 isomer of conjugated linoleic acid was confirmed by its reversal upon pharmacological inhibition of IGF-IR function. Diet-stimulated ductal growth also increased mammary tumorigenesis in ovariectomized polyomavirus middle T-antigen mice. Our data demonstrate that diet-induced metabolic dysregulation, independently of ovarian function, stimulates allometric growth within the mammary glands via an IGF-IR-dependent mechanism.

EnzChemRED, a rich enzyme chemistry relation extraction dataset.

Expert curation is essential to capture knowledge of enzyme functions from the scientific literature in FAIR open knowledgebases but cannot keep pace with the rate of new discoveries and new publications. In this work we present EnzChemRED, for Enzyme Chemistry Relation Extraction Dataset, a new training and benchmarking dataset to support the development of Natural Language Processing (NLP) methods such as (large) language models that can assist enzyme curation. EnzChemRED consists of 1,210 expert curated PubMed abstracts in which enzymes and the chemical reactions they catalyze are annotated using identifiers from the UniProt Knowledgebase (UniProtKB) and the ontology of Chemical Entities of Biological Interest (ChEBI). We show that fine-tuning pre-trained language models with EnzChemRED can significantly boost their ability to identify mentions of proteins and chemicals in text (Named Entity Recognition, or NER) and to extract the chemical conversions in which they participate (Relation Extraction, or RE), with average F1 score of 86.30% for NER, 86.66% for RE for chemical conversion pairs, and 83.79% for RE for chemical conversion pairs and linked enzymes. We combine the best performing methods after fine-tuning using EnzChemRED to create an end-to-end pipeline for knowledge extraction from text and apply this to abstracts at PubMed scale to create a draft map of enzyme functions in literature to guide curation efforts in UniProtKB and the reaction knowledgebase Rhea. The EnzChemRED corpus is freely available at https://ftp.expasy.org/databases/rhea/nlp/.

Diverse and active roles for adipocytes during mammary gland growth and function.

The mammary gland is unique in its requirement to develop in close association with a depot of adipose tissue that is commonly referred to as the mammary fat pad. As discussed throughout this issue, the mammary fat pad represents a complex stromal microenvironment that includes a variety of cell types. In this article we focus on adipocytes as local regulators of epithelial cell growth and their function during lactation. Several important considerations arise from such a discussion. There is a clear and close interrelationship between different stromal tissue types within the mammary fat pad and its adipocytes. Furthermore, these relationships are both stage- and species-dependent, although many questions remain unanswered regarding their roles in these different states. Several lines of evidence also suggest that adipocytes within the mammary fat pad may function differently from those in other fat depots. Finally, past and future technologies present a variety of opportunities to model these complexities in order to more precisely delineate the many potential functions of adipocytes within the mammary glands. A thorough understanding of the role for this cell type in the mammary glands could present numerous opportunities to modify both breast cancer risk and lactation performance.

Aluminium and lead: molecular mechanisms of brain toxicity.

The fact that aluminium (Al) and lead (Pb) are both toxic metals to living organisms, including human beings, was discovered a long time ago. Even when Al and Pb can reach and accumulate in almost every organ in the human body, the central nervous system is a particular target of the deleterious effects of both metals. Select human population can be at risk of Al neurotoxicity, and Al is proposed to be involved in the etiology of neurodegenerative diseases. Pb is a widespread environmental hazard, and the neurotoxic effects of Pb are a major public health concern. In spite of the numerous efforts and the accumulating evidence in this area of research, the mechanisms of Al and Pb neurotoxicity are still not completely elucidated. This review will particularly address the involvement of oxidative stress, membrane biophysics alterations, deregulation of cell signaling, and the impairment of neurotransmission as key aspects involved Al and Pb neurotoxicity.

The Transcriptome of Estrogen-Independent Mammary Growth in Female Mice Reveals That Not All Mammary Glands Are Created Equally.

Allometric growth of ducts in the mammary glands (MGs) is widely held to be estrogen dependent. We previously discovered that the dietary fatty acid trans-10, cis-12 conjugated linoleic acid (CLA) stimulates estrogen-independent allometric growth and terminal end bud formation in ovariectomized mice. Given the similar phenotype induced by estrogen and CLA, we investigated the shared and/or divergent mechanisms underlying these changes. We confirmed MG growth induced by CLA is temporally distinct from that elicited by estrogen. We then used RNA sequencing to compare the transcriptome of the MG during similar proliferative and morphological states. Both estrogen and CLA affected the genes involved in proliferation. The transcriptome for estrogen-treated mice included canonical estrogen-induced genes, including Pgr, Areg, and Foxa1. In contrast, their expression was unchanged by CLA. However, CLA, but not estrogen, altered expression of a unique set of inflammation-associated genes, consistent with stromal changes. This CLA-altered signature included increased expression of epidermal growth factor receptor (EGFR) pathway components, consistent with the demonstration that CLA-induced MG growth is EGFR dependent. Our findings highlight a unique role for diet-induced inflammation that underlies estrogen-independent MG development.

Zinc deficiency increases the susceptibility of human neuroblastoma cells to lead-induced activator protein-1 activation.

Lead (Pb2+) is a major environmental pollutant that has severe adverse effects on the nervous system. Similar human populations are at risk of suffering both Pb2+ toxicity and zinc (Zn) deficiency. Thus, in the present study we investigated whether Zn deficiency can increase the susceptibility of human neuroblastoma IMR-32 cells to Pb2+-induced oxidative stress which could trigger the activation of the mitogen-activated protein kinases (MAPKs) c-Jun-N-terminal kinase (JNK) and p38 and subsequently activate transcription factor activator protein-1 (AP-1). After 24 h of incubation, 5-50 microM Pb2+ caused a decrease in cell viability that was markedly higher in the Zn-deficient cells compared to controls. Pb caused a time (2-24 h) and dose (5-50 microM)-dependent increase of cell oxidants, with a significantly higher effect in the Zn-deficient cells. Pb2+ treatment triggered the activation of JNK and p38, measured as the phosphorylation of JNK and p38, only in cells incubated in the Zn-deficient media. The exposure to Pb2+ (2-24 h) led to a higher AP-1 DNA-binding activity and AP-1-dependent gene transactivation, only in the Zn-deficient cells. Results show that Zn deficiency can increase the cytotoxicity of Pb2+ and the susceptibility of neurons to Pb2+-induced oxidative stress, leading to JNK and p38 phosphorylation and, subsequently, AP-1 activation.

alpha-Lipoic acid and N-acetyl cysteine prevent zinc deficiency-induced activation of NF-kappaB and AP-1 transcription factors in human neuroblastoma IMR-32 cells.

This work investigated the capacity of alpha-lipoic acid (LA) and N-acetyl-L-cysteine (NAC) to reduce zinc deficiency-induced oxidative stress, and prevent the activation of nuclear factor-kappaB (NF-kappaB) and activator protein-1 (AP-1), and the cross-talk between both activated cascades through beta-Transducin Repeat-containing Protein (beta-TrCP). IMR-32 cells were incubated in control media or media containing variable concentrations of zinc, without or with 0.5 mM LA or 1 mM NAC. Relative to control and zinc supplemented (15 microM Zn) groups, Hydrogen peroxide (H(2)O(2)) and total oxidant cell concentrations were higher, and total glutathione concentrations were lower in the zinc deficient groups (1.5 and 5 microM Zn). Both, LA and NAC, markedly reduced the increase in cell oxidants and the reduction in glutathione concentrations in the zinc deficient cells. Consistent with this, LA and NAC prevented zinc deficiency-induced activation of the early steps of NF- kappaB (IkappaBalpha phosphorylation) and AP-1 [c-Jun-N-terminal kinase (JNK) and p38 phophorylation] cascades, and the high NF-kappaB- and AP-1-DNA binding activities in total cell extracts. Thus, LA and NAC can reduce the oxidative stress associated with zinc deficiency and the subsequent triggering of NF-kappaB- and AP-1-activation in neuronal cells.

Ascorbyl radical/ascorbate ratio in plasma from iron overloaded rats as oxidative stress indicator.

Oxidative stress has been developed using dietary carbonyl-iron and iron-dextran parenteral administration as models of in vivo iron overload in rats. Carbonyl-iron led to a 2-fold increase in plasma iron content, a significant decrease (34%) in ascorbate plasma content and non-significant changes in plasma ascorbyl radical content. Iron-dextran produced a dramatic increase (6.7-fold) in plasma iron content, overwhelming the plasma total iron binding capacity. The ascorbyl radical content increased significantly in iron-dextran treatment (2.6-fold) and plasma ascorbate level was not affected. Ascorbyl radical/ascorbate ratio was significantly higher in both iron treated groups as compared with the control group (4 x 10(-4)+/-1 x 10(-4)). Data reported here indicate that the ascorbyl radical/ascorbate ratio is an appropriate in vivo indicator of oxidative stress under conditions of iron overload. The overall mechanism that describes the ascorbate status in plasma seems to be strongly dependent on the way the excess of iron is stored and thus, to the availability of the catalytically active iron for interacting with the plasma components. On this regard, evaluation of A*/AH(-) ratio did not help to discriminate between the possible involved mechanisms.

Low extracellular zinc increases neuronal oxidant production through nadph oxidase and nitric oxide synthase activation.

A decrease in zinc (Zn) levels increases the production of cell oxidants, affects the oxidant defense system and triggers oxidant sensitive signals in neuronal cells. However, the underlying mechanisms are still unclear. This work tested the hypothesis that the increase in neuronal oxidants that occurs when cellular Zn decreases is mediated by the activation of the NMDA receptor. Differentiated PC12 cells were cultured in control, Zn-deficient or Zn-repleted media. The incubation in Zn deficient media led to a rapid increase in cellular calcium levels, which was prevented by a NMDA receptor antagonist (MK-801). Cellular calcium accumulation was associated with NADPH oxidase and nitric oxide synthase (NOS) activation, an increase in cell oxidant levels, and an associated activation of a redox-sensitive signal (AP-1). In cells incubated in the Zn deficient medium, NADPH oxidase activation was prevented by MK-801 and by a protein kinase C inhibitor. The rise in cell oxidants was prevented by inhibitors of NADPH oxidase, of the NOS and by MK-801. A similar pattern of inhibitor action was observed for zinc deficiency-induced AP-1 activation. Results demonstrate that a decrease in extracellular Zn leads to an increase in neuronal oxidants through the activation of the NMDAR that leads to calcium influx and to a calcium-mediated activation of protein kinase C/NADPH oxidase and NOS. Changes in extracellular Zn concentrations can be sensed by neurons, which using reactive oxygen and nitrogen species as second messengers, can regulate signaling involved in neuronal development and function.

Gestational zinc deficiency affects the regulation of transcription factors AP-1, NF-κB and NFAT in fetal brain.

Transcription factors AP-1, nuclear factor κB (NF-κB) and NFAT are central to brain development by regulating the expression of genes that modulate cell proliferation, differentiation, apoptosis and synaptic plasticity. This work investigated the consequences of feeding zinc-deficient and marginal zinc diets to rat dams during gestation on the modulation of AP-1, NF-κB and NFAT in fetal brain. Sprague-Dawley rats were fed from gestation day (GD) 0 a control diet ad libitum (25 µg zinc/g diet, C), a zinc-deficient diet ad libitum (0.5 µg zinc/g diet, ZD), the control diet in the amounts eaten by the ZD rats (restrict fed, RF) or a diet containing a marginal zinc concentration ad libitum (10 µg zinc/g diet, MZD) until GD 19. AP-1-DNA binding was higher (50-190%) in nuclear fraction isolated from ZD, RF and MZD fetal brains compared to controls. In MZD fetal brain, high levels of activation of the upstream mitogen-activated protein kinases JNK and p38 and low levels of ERK phosphorylation were observed. Total levels of NF-κB and NFAT activation were higher or similar in the ZD and MZD groups than in controls, respectively. However, NF-κB- and NFAT-DNA binding in nuclear fractions was markedly lower in ZD and MZD fetal brain than in controls (50-80%). The latter could be related to zinc deficiency-associated alterations of the cytoskeleton, which is required for NF-κB and NFAT nuclear transport. In summary, suboptimal zinc nutrition during gestation could cause long-term effects on brain function, partially through a deregulation of transcription factors AP-1, NF-κB and NFAT.

The role of zinc in the modulation of neuronal proliferation and apoptosis.

Although a requirement of zinc (Zn) for normal brain development is well documented, the extent to which Zn can modulate neuronal proliferation and apoptosis is not clear. Thus, we investigated the role of Zn in the regulation of these two critical events. A low Zn availability leads to decreased cell viability in human neuroblastoma IMR-32 cells and primary cultures of rat cortical neurons. This occurs in part as a consequence of decreased cell proliferation and increased apoptotic cell death. In IMR-32 cells, Zn deficiency led to the inhibition of cell proliferation through the arrest of the cell cycle at the G0/G1 phase. Zn deficiency induced apoptosis in both proliferating and quiescent neuronal cells via the intrinsic apoptotic pathway. Reductions in cellular Zn triggered a translocation of the pro-apoptotic protein Bad to the mitochondria, cytochrome c release, and caspase-3 activation. Apoptosis is the resultant of the inhibition of the prosurvival extracellular-signal-regulated kinase, the inhibition of nuclear factor-kappa B, and associated decreased expression of antiapoptotic proteins, and to a direct activation of caspase-3. A deficit of Zn during critical developmental periods can have persistent effects on brain function secondary to a deregulation of neuronal proliferation and apoptosis.