Innate Immune Training of Granulopoiesis Promotes Anti-tumor Activity.

Trained innate immunity, induced via modulation of mature myeloid cells or their bone marrow progenitors, mediates sustained increased responsiveness to secondary challenges. Here, we investigated whether anti-tumor immunity can be enhanced through induction of trained immunity. Pre-treatment of mice with ß-glucan, a fungal-derived prototypical agonist of trained immunity, resulted in diminished tumor growth. The anti-tumor effect of ß-glucan-induced trained immunity was associated with transcriptomic and epigenetic rewiring of granulopoiesis and neutrophil reprogramming toward an anti-tumor phenotype; this process required type I interferon signaling irrespective of adaptive immunity in the host. Adoptive transfer of neutrophils from ß-glucan-trained mice to naive recipients suppressed tumor growth in the latter in a ROS-dependent manner. Moreover, the anti-tumor effect of ß-glucan-induced trained granulopoiesis was transmissible by bone marrow transplantation to recipient naive mice. Our findings identify a novel and therapeutically relevant anti-tumor facet of trained immunity involving appropriate rewiring of granulopoiesis.

Lipidome Unsaturation Affects the Morphology and Proteome of the Drosophila Eye.

Organisms respond to dietary and environmental challenges by altering the molecular composition of their glycerolipids and glycerophospholipids (GPLs), which may favorably adjust the physicochemical properties of lipid membranes. However, how lipidome changes affect the membrane proteome and, eventually, the physiology of specific organs is an open question. We addressed this issue in Drosophila melanogaster, which is not able to synthesize sterols and polyunsaturated fatty acids but can acquire them from food. We developed a series of semisynthetic foods to manipulate the length and unsaturation of fatty acid moieties in GPLs and singled out proteins whose abundance is specifically affected by membrane lipid unsaturation in the Drosophila eye. Unexpectedly, we identified a group of proteins that have muscle-related functions and increased their abundances under unsaturated eye lipidome conditions. In contrast, the abundance of two stress response proteins, Turandot A and Smg5, is decreased by lipid unsaturation. Our findings could guide the genetic dissection of homeostatic mechanisms that maintain visual function when the eye is exposed to environmental and dietary challenges.

Eye proteome of Drosophila melanogaster.

Drosophila melanogaster is a popular model organism to elucidate the molecular mechanisms that underlie the structure and function of the eye as well as the causes of retinopathies, aging, light-induced damage, or dietary deficiencies. Large-scale screens have isolated genes whose mutation causes morphological and functional ocular defects, which led to the discovery of key components of the phototransduction cascade. However, the proteome of the Drosophila eye is poorly characterized. Here, we used GeLC-MS/MS to quantify 3516 proteins, including the absolute (molar) quantities of 43 proteins in the eye of adult male Drosophila reared on standard laboratory food. This work provides a generic and expandable resource for further genetic, pharmacological, and dietary studies.

Nonalcoholic fatty liver disease stratification by liver lipidomics.

Nonalcoholic fatty liver disease (NAFLD) is a common metabolic dysfunction leading to hepatic steatosis. However, NAFLD's global impact on the liver lipidome is poorly understood. Using high-resolution shotgun mass spectrometry, we quantified the molar abundance of 316 species from 22 major lipid classes in liver biopsies of 365 patients, including nonsteatotic patients with normal or excessive weight, patients diagnosed with NAFL (nonalcoholic fatty liver) or NASH (nonalcoholic steatohepatitis), and patients bearing common mutations of NAFLD-related protein factors. We confirmed the progressive accumulation of di- and triacylglycerols and cholesteryl esters in the liver of NAFL and NASH patients, while the bulk composition of glycerophospho- and sphingolipids remained unchanged. Further stratification by biclustering analysis identified sphingomyelin species comprising n24:2 fatty acid moieties as membrane lipid markers of NAFLD. Normalized relative abundance of sphingomyelins SM 43:3;2 and SM 43:1;2 containing n24:2 and n24:0 fatty acid moieties, respectively, showed opposite trends during NAFLD progression and distinguished NAFL and NASH lipidomes from the lipidome of nonsteatotic livers. Together with several glycerophospholipids containing a C22:6 fatty acid moiety, these lipids serve as markers of early and advanced stages of NAFL.

Identification of key lipids critical for platelet activation by comprehensive analysis of the platelet lipidome.

Platelet integrity and function critically depend on lipid composition. However, the lipid inventory in platelets was hitherto not quantified. Here, we examined the lipidome of murine platelets using lipid-category tailored protocols on a quantitative lipidomics platform. We could show that the platelet lipidome comprises almost 400 lipid species and covers a concentration range of 7 orders of magnitude. A systematic comparison of the lipidomics network in resting and activated murine platelets, validated in human platelets, revealed that <20% of the platelet lipidome is changed upon activation, involving mainly lipids containing arachidonic acid. Sphingomyelin phosphodiesterase-1 (Smpd1) deficiency resulted in a very specific modulation of the platelet lipidome with an order of magnitude upregulation of lysosphingomyelin (SPC), and subsequent modification of platelet activation and thrombus formation. In conclusion, this first comprehensive quantitative lipidomic analysis of platelets sheds light on novel mechanisms important for platelet function, and has therefore the potential to open novel diagnostic and therapeutic opportunities.

Potential of Artificial Intelligence to Accelerate Drug Development for Rare Diseases.

The growth in breadth and depth of artificial intelligence (AI) applications has been fast, running hand in hand with the increasing amount of digital data available. Here, we comment on the application of AI in the field of drug development, with a strong focus on the specific achievements and challenges posed by rare diseases. Data paucity and high costs make drug development for rare diseases especially hard. AI can enable otherwise inaccessible approaches based on the large-scale integration of heterogeneous datasets and knowledge bases, guided by expert biological understanding. Obstacles still exist for the routine use of AI in the usually conservative pharmaceutical domain, which can easily become disillusioned. It is crucial to acknowledge that AI is a powerful, supportive tool that can assist but not replace human expertise in the various phases and aspects of drug discovery and development.

Eye proteome of Drosophila melanogaster.

The Drosophila melanogaster eye is a popular model to elucidate the molecular mechanisms that underlie the structure and function of the eye as well as the causes of retinopathies. For instance, the Drosophila eye has been used to investigate the impacts of ageing and environmental stresses such as light-induced damage or dietary deficiencies. Moreover, large-scale screens have isolated genes whose mutation causes morphological and functional ocular defects, which includes key components of the phototransduction cascade. However, the proteome of the Drosophila eye is poorly characterized. Here, we used GeLC-MS/MS to quantify 3516 proteins he adult Drosophila melanogaster eye and provide a generic and expandable resource for further genetic, pharmacological, and dietary studies.

Lipidome unsaturation affects the morphology and proteome of the Drosophila eye.

While the proteome of an organism is largely determined by the genome, the lipidome is shaped by a poorly understood interplay of environmental factors and metabolic processes. To gain insights into the underlying mechanisms, we analyzed the impacts of dietary lipid manipulations on the ocular proteome of Drosophila melanogaster . We manipulated the lipidome with synthetic food media that differed in the supplementation of an equal amount of saturated or polyunsaturated triacylglycerols. This allowed us to generate flies whose eyes had a highly contrasting length and unsaturation of glycerophospholipids, the major lipid class of biological membranes, while the abundance of other membrane lipid classes remained unchanged. By bioinformatically comparing the resulting ocular proteomic trends and contrasting them with the impacts of vitamin A deficiency, we identified ocular proteins whose abundances are differentially affected by lipid saturation and unsaturation. For instance, we unexpectedly identified a group of proteins that have muscle-related functions and increase their abundances in the eye upon lipidome unsaturation but are unaffected by lipidome saturation. Moreover, we identified two differentially lipid-responsive proteins involved in stress responses, Turandot A and Smg5, whose abundances decrease with lipid unsaturation. Lastly, we discovered that the ocular lipid class composition is robust to dietary changes and propose that this may be a general homeostatic feature of the organization of eukaryotic tissues, while the length and unsaturation of fatty acid moieties is more variable to compensate environmental challenges. We anticipate that these insights into the molecular responses of the Drosophila eye proteome to specific lipid manipulations will guide the genetic dissection of the mechanisms that maintain visual function when the eye is exposed to dietary challenges.

A Current Encyclopedia of Bioinformatics Tools, Data Formats and Resources for Mass Spectrometry Lipidomics.

Mass spectrometry is a widely used technology to identify and quantify biomolecules such as lipids, metabolites and proteins necessary for biomedical research. In this study, we catalogued freely available software tools, libraries, databases, repositories and resources that support lipidomics data analysis and determined the scope of currently used analytical technologies. Because of the tremendous importance of data interoperability, we assessed the support of standardized data formats in mass spectrometric (MS)-based lipidomics workflows. We included tools in our comparison that support targeted as well as untargeted analysis using direct infusion/shotgun (DI-MS), liquid chromatography-mass spectrometry, ion mobility or MS imaging approaches on MS1 and potentially higher MS levels. As a result, we determined that the Human Proteome Organization-Proteomics Standards Initiative standard data formats, mzML and mzTab-M, are already supported by a substantial number of recent software tools. We further discuss how mzTab-M can serve as a bridge between data acquisition and lipid bioinformatics tools for interpretation, capturing their output and transmitting rich annotated data for downstream processing. However, we identified several challenges of currently available tools and standards. Potential areas for improvement were: adaptation of common nomenclature and standardized reporting to enable high throughput lipidomics and improve its data handling. Finally, we suggest specific areas where tools and repositories need to improve to become FAIRer.

Vitamin A Deficiency Alters the Phototransduction Machinery and Distinct Non-Vision-Specific Pathways in the Drosophila Eye Proteome.

The requirement of vitamin A for the synthesis of the visual chromophore and the light-sensing pigments has been studied in vertebrate and invertebrate model organisms. To identify the molecular mechanisms that orchestrate the ocular response to vitamin A deprivation, we took advantage of the fact that Drosophila melanogaster predominantly requires vitamin A for vision, but not for development or survival. We analyzed the impacts of vitamin A deficiency on the morphology, the lipidome, and the proteome of the Drosophila eye. We found that chronic vitamin A deprivation damaged the light-sensing compartments and caused a dramatic loss of visual pigments, but also decreased the molar abundance of most phototransduction proteins that amplify and transduce the visual signal. Unexpectedly, vitamin A deficiency also decreased the abundances of specific subunits of mitochondrial TCA cycle and respiratory chain components but increased the levels of cuticle- and lens-related proteins. In contrast, we found no apparent effects of vitamin A deficiency on the ocular lipidome. In summary, chronic vitamin A deficiency decreases the levels of most components of the visual signaling pathway, but also affects molecular pathways that are not vision-specific and whose mechanistic connection to vitamin A remains to be elucidated.

Multiomics of synaptic junctions reveals altered lipid metabolism and signaling following environmental enrichment.

Membrane lipids and their metabolism have key functions in neurotransmission. Here we provide a quantitative lipid inventory of mouse and rat synaptic junctions. To this end, we developed a multiomics extraction and analysis workflow to probe the interplay of proteins and lipids in synaptic signal transduction from the same sample. Based on this workflow, we generate hypotheses about novel mechanisms underlying complex changes in synaptic connectivity elicited by environmental stimuli. As a proof of principle, this approach reveals that in mice exposed to an enriched environment, reduced endocannabinoid synthesis and signaling is linked to increased surface expression of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) in a subset of Cannabinoid-receptor 1 positive synapses. This mechanism regulates synaptic strength in an input-specific manner. Thus, we establish a compartment-specific multiomics workflow that is suitable to extract information from complex lipid and protein networks involved in synaptic function and plasticity.

A multi-omics analysis reveals the unfolded protein response regulon and stress-induced resistance to folate-based antimetabolites.

Stress response pathways are critical for cellular homeostasis, promoting survival through adaptive changes in gene expression and metabolism. They play key roles in numerous diseases and are implicated in cancer progression and chemoresistance. However, the underlying mechanisms are only poorly understood. We have employed a multi-omics approach to monitor changes to gene expression after induction of a stress response pathway, the unfolded protein response (UPR), probing in parallel the transcriptome, the proteome, and changes to translation. Stringent filtering reveals the induction of 267 genes, many of which have not previously been implicated in stress response pathways. We experimentally demonstrate that UPR-mediated translational control induces the expression of enzymes involved in a pathway that diverts intermediate metabolites from glycolysis to fuel mitochondrial one-carbon metabolism. Concomitantly, the cells become resistant to the folate-based antimetabolites Methotrexate and Pemetrexed, establishing a direct link between UPR-driven changes to gene expression and resistance to pharmacological treatment.

Transcriptomic analysis of boron hyperaccumulation mechanisms in Puccinellia distans.

Puccinellia distans, common alkali grass, is found throughout the world and can survive in soils with boron concentrations that are lethal for other plant species. Indeed, P. distans accumulates very high levels of this element. Despite these interesting features, very little research has been performed to elucidate the boron tolerance mechanism in this species. In this study, P. distans samples were treated for three weeks with normal (0.5 mg L-1) and elevated (500 mg L-1) boron levels in hydroponic solution. Expressed sequence tags (ESTs) derived from shoot tissue were analyzed by RNA sequencing to identify genes up and down-regulated under boron stress. In this way, 3312 differentially expressed transcripts were detected, 67.7% of which were up-regulated and 32.3% of which were down-regulated in boron-treated plants. To partially confirm the RNA sequencing results, 32 randomly selected transcripts were analyzed for their expression levels in boron-treated plants. The results agreed with the expected direction of change (up or down-regulation). A total of 1652 transcripts had homologs in A. thaliana and/or O. sativa and mapped to 1107 different proteins. Functional annotation of these proteins indicated that the boron tolerance and hyperaccumulation mechanisms of P. distans involve many transcriptomic changes including: alterations in the malate pathway, changes in cell wall components that may allow sequestration of excess boron without toxic effects, and increased expression of at least one putative boron transporter and two putative aquaporins. Elucidation of the boron accumulation mechanism is important in developing approaches for bioremediation of boron contaminated soils.

PGMiner reloaded, fully automated proteogenomic annotation tool linking genomes to proteomes.

Improvements in genome sequencing technology increased the availability of full genomes and transcriptomes of many organisms. However, the major benefit of massive parallel sequencing is to better understand the organization and function of genes which then lead to understanding of phenotypes. In order to interpret genomic data with automated gene annotation studies, several tools are currently available. Even though the accuracy of computational gene annotation is increasing, a combination of multiple lines of experimental evidences should be gathered. Mass spectrometry allows the identification and sequencing of proteins as major gene products; and it is only these proteins that conclusively show whether a part of a genome is a coding region or not to result in phenotypes. Therefore, in the field of proteogenomics, the validation of computational methods is done by exploiting mass spectrometric data. As a result, identification of novel protein coding regions, validation of current gene models, and determination of upstream and downstream regions of genes can be achieved. In this paper, we present new functionality for our proteogenomic tool, PGMiner which performs all proteogenomic steps like acquisition of mass spectrometric data, peptide identification against preprocessed sequence databases, assignment of statistical confidence to identified peptides, mapping confident peptides to gene models, and result visualization. The extensions cover determining proteotypic peptides and thus unambiguous protein identification. Furthermore, peptides conflicting with gene models can now automatically assessed within the context of predicted alternative open reading frames.