Quantitative Lipidomics and Spatial MS-Imaging Uncovered Neurological and Systemic Lipid Metabolic Pathways Underlying Troglomorphic Adaptations in Cave-Dwelling Fish.

Sinocyclocheilus represents a rare, freshwater teleost genus endemic to China that comprises the river-dwelling surface fish and the cave-dwelling cavefish. Using a combinatorial approach of quantitative lipidomics and mass-spectrometry imaging (MSI), we demonstrated that neural compartmentalization of lipid distribution and lipid metabolism is associated with the evolution of troglomorphic traits in Sinocyclocheilus. Attenuated docosahexaenoic acid (DHA) biosynthesis via the Δ4 desaturase pathway led to reductions in DHA-phospholipids in cavefish cerebellum. Instead, cavefish accumulates arachidonic acid-phospholipids that may disfavor retinotectal arbor growth. Importantly, MSI of sulfatides coupled with immunostaining of myelin basic protein and transmission electron microscopy images of hindbrain axons revealed demyelination in cavefish raphe serotonergic neurons. Demyelination in cavefish parallels the loss of neuroplasticity governing social behavior such as aggressive dominance. Outside the brain, quantitative lipidomics and qRT-PCR revealed systemic reductions in membrane esterified DHAs in the liver, attributed to suppression of genes along the Sprecher pathway (elovl2, elovl5, and acox1). Development of fatty livers was observed in cavefish; likely mediated by an impeded mobilization of storage lipids, as evident in the diminished expressions of pnpla2, lipea, lipeb, dagla, and mgll; and suppressed ß-oxidation of fatty acyls via both mitochondria and peroxisomes as reflected in the reduced expressions of cpt1ab, hadhaa, cpt2, decr1, and acox1. These neurological and systemic metabolic adaptations serve to reduce energy expenditure, forming the basis of recessive evolution that eliminates nonessential morphological and behavioral traits and giving cavefish a selective advantage to thrive in caves where proper resource allocation becomes a major determinant of survival.

Endogenous ceramide phosphoethanolamine modulates circadian rhythm via neural-glial coupling in Drosophila.

While endogenous lipids are known to exhibit rhythmic oscillations, less is known about how specific lipids modulate circadian behavior. Through a series of loss-of-function and gain-of-function experiments on ceramide phosphoethanolamine (CPE) synthase of Drosophila, we demonstrated that pan-glial-specific deficiency in membrane CPE, the structural analog of mammalian sphingomyelin (SM), leads to arrhythmic locomotor behavior and shortens lifespan, while the reverse is true for increasing CPE. Comparative proteomics uncovered dysregulated synaptic glutamate utilization and transport in CPE-deficient flies. An extensive genetic screen was conducted to verify the role of differentially expressed proteins in circadian regulation. Arrhythmic locomotion under cpes1 mutant background was rescued only by restoring endogenous CPE or SM through expressing their respective synthases. Our results underscore the essential role of CPE in maintaining synaptic glutamate homeostasis and modulating circadian behavior in Drosophila. The findings suggest that region-specific elevations of functional membrane lipids can benefit circadian regulation.

A multi-omics investigation of the composition and function of extracellular vesicles along the temporal trajectory of COVID-19.

Exosomes represent a subtype of extracellular vesicle that is released through retrograde transport and fusion of multivesicular bodies with the plasma membrane1. Although no perfect methodologies currently exist for the high-throughput, unbiased isolation of pure plasma exosomes2,3, investigation of exosome-enriched plasma fractions of extracellular vesicles can confer a glimpse into the endocytic pathway on a systems level. Here we conduct high-coverage lipidomics with an emphasis on sterols and oxysterols, and proteomic analyses of exosome-enriched extracellular vesicles (EVs hereafter) from patients at different temporal stages of COVID-19, including the presymptomatic, hyperinflammatory, resolution and convalescent phases. Our study highlights dysregulated raft lipid metabolism that underlies changes in EV lipid membrane anisotropy that alter the exosomal localization of presenilin-1 (PS-1) in the hyperinflammatory phase. We also show in vitro that EVs from different temporal phases trigger distinct metabolic and transcriptional responses in recipient cells, including in alveolar epithelial cells, which denote the primary site of infection, and liver hepatocytes, which represent a distal secondary site. In comparison to the hyperinflammatory phase, EVs from the resolution phase induce opposing effects on eukaryotic translation and Notch signalling. Our results provide insights into cellular lipid metabolism and inter-tissue crosstalk at different stages of COVID-19 and are a resource to increase our understanding of metabolic dysregulation in COVID-19.

Omics-Driven Systems Interrogation of Metabolic Dysregulation in COVID-19 Pathogenesis.

The coronavirus disease 2019 (COVID-19) pandemic presents an unprecedented threat to global public health. Herein, we utilized a combination of targeted and untargeted tandem mass spectrometry to analyze the plasma lipidome and metabolome in mild, moderate, and severe COVID-19 patients and healthy controls. A panel of 10 plasma metabolites effectively distinguished COVID-19 patients from healthy controls (AUC = 0.975). Plasma lipidome of COVID-19 resembled that of monosialodihexosyl ganglioside (GM3)-enriched exosomes, with enhanced levels of sphingomyelins (SMs) and GM3s, and reduced diacylglycerols (DAGs). Systems evaluation of metabolic dysregulation in COVID-19 was performed using multiscale embedded differential correlation network analyses. Using exosomes isolated from the same cohort, we demonstrated that exosomes of COVID-19 patients with elevating disease severity were increasingly enriched in GM3s. Our work suggests that GM3-enriched exosomes may partake in pathological processes related to COVID-19 pathogenesis and presents the largest repository on the plasma lipidome and metabolome distinct to COVID-19.

A robust, integrated platform for comprehensive analyses of acyl-coenzyme As and acyl-carnitines revealed chain length-dependent disparity in fatty acyl metabolic fates across Drosophila development.

Acyl-coenzyme A thioesters (acyl-CoAs) denote a key class of intermediary metabolites that lies at the hub of major metabolic pathways. The great diversity in polarity between short- and long-chain acyl-CoAs makes it technically challenging to cover an inclusive range of acyl-CoAs within a single method. Levels of acyl-carnitines, which function to convey fatty acyls into mitochondria matrix for ß-oxidation, indicate the efficiency of mitochondrial import and utilization of corresponding acyl-CoAs. Herein, we report a robust, integrated platform to allow simultaneous quantitation of endogenous acyl-CoAs and acyl-carnitines. Using this method, we monitored changes in intermediary lipid profiles across Drosophila development under control (ND) and high-fat diet (HFD). We observed specific accumulations of medium-chain (C8-C12) and long-chain (≥C16) acyl-carnitines distinct to L3 larval and pupal stages, respectively. These observations suggested development-specific, chain length-dependent disparity in metabolic fates of acyl-CoAs across Drosophila development, which was validated by deploying the same platform to monitor isotope incorporation introduced from labelled 12:0 and 16:0 fatty acids into extra- and intra-mitochondrial acyl-CoA pools. We found that pupal mitochondria preferentially import and oxidise C12:0-CoAs (accumulated as C12:0-carnitines in L3 stage) over C16:0-CoAs. Preferential oxidation of medium-chain acyl-CoAs limits mitochondrial utilization of long-chain acyl-CoAs (C16-C18), leading to pupal-specific accumulation of long-chain acyl-carnitines mediated by enhanced CPT1-6A activity. HFD skewed C16:0-CoAs towards catabolism over anabolism in pupa, thereby adversely affecting overall development. Our developed platform emphasizes the importance of integrating biological knowledge in the design of pathway-oriented platforms to derive maximal physiological insights from analysis of complex biological systems.

Biological relevance of fatty acyl heterogeneity to the neural membrane dynamics of rhesus macaques during normative aging.

Lipidomic analyses of the frontal cortex of Rhesus macaques across three selected age groups (young, sexually-mature, old) revealed that docosahexaenoic acids (DHAs) displayed notable and unique accretions in sexually-mature macaques for all phospholipid classes examined, which were not observable in all remaining polyunsaturated fatty acids (PUFAs) investigated. On the other hand, arachidonic acid (ARA) exhibited sharp attritions in the membrane lipidomes of sexually-mature macaques, a decline which was attenuated only for cardiolipins (CLs). DHA enrichment in phospholipids was lost in old macaques, with accompanying augmentations in very-long-chain sphingomyelins (VLC-SMs). Age-dependent alterations in membrane lipidomes point to a possibly complex temporal interplay between DHA-enriched membrane microdomains and SM-/cholesterol-rich rafts in neural membranes during normative aging. Lipid co-regulation data revealed an increasingly intense degree of co-regulation between membrane lipid classes with age, and suggest that reduction in CLs during normative brain aging may prompt alternative membrane lipid synthetic pathways driven by a compromised energy availability in the aging brain.

Mycolic acids as diagnostic markers for tuberculosis case detection in humans and drug efficacy in mice.

Mycolic acids are attractive diagnostic markers for tuberculosis (TB) infection because they are bacteria-derived, contain information about bacterial species, modulate host-pathogen interactions and are chemically inert. Here, we present a novel approach based on mass spectrometry. Quantification of specific precursor → fragment transitions of approximately 2000 individual mycolic acids (MAs) resulted in high analytical sensitivity and specificity. We next used this tool in a retrospective case-control study of patients with pulmonary TB with varying disease burdens from South Korea, Vietnam, Uganda and South Africa. MAs were extracted from small volume sputum (200 µl) and analysed without the requirement for derivatization. Infected patients (70, 19 of whom were HIV+) could be separated from controls (40, 20 of whom were HIV+) with a sensitivity and specificity of 94 and 93%, respectively. Furthermore, we quantified MA species in lung tissue of TB-infected mice and demonstrated effective clearance of MA levels following curative rifampicin treatment. Thus, our results demonstrate for the first time the feasibility and clinical relevance of direct detection of mycobacterial lipids as biomarkers of TB infection.

Toward one step analysis of cellular lipidomes using liquid chromatography coupled with mass spectrometry: application to Saccharomyces cerevisiae and Schizosaccharomyces pombe lipidomics.

Recent rapid growth of lipidomics is mainly attributed to technological advances in mass spectrometry. Development of soft ionization techniques, in combination with computational tools, has spurred subsequent development of various methods for lipid analysis. However, none of these existing approaches can cover major cellular lipids in a single run. Here we demonstrate that a single method of liquid chromatography coupled with mass spectrometry (LCMS) can be used for simultaneous profiling of major cellular lipids including glycerophospholipids (PLs), sphingolipids (SPLs), waxes, sterols (ST) and mono-, di- as well as triacylglycerides (MAG, DAG, TAG). We applied this approach to analyze these lipids in various organisms including Saccharomyces cerevisiae and Schizosaccharomyces pombe. While phospholipids and triacylglycerides of S. pombe mainly contain 18 : 1 fatty acyls, those of S. cerevisiae contain 16 : 1, 16 : 0 and 18 : 1 fatty acyls. S. cerevisiae and S. pombe contain distinct sphingolipid profiles. S. cerevisiae has abundant inositol phytoceramides (IPC), while S. pombe contains high levels of free phytoceramides as well as short chain phytoceramides (t18:1/20 : 0-B) and IPC (t18:1/20 : 0-B). In S. cerevisiae, our results demonstrated accumulation of ergosterol esters in tgl1Delta cells and accumulation of various TAG species in tgl3Delta cells, which are consistent with the function of the respective enzymes. Furthermore, we, for the first time, systematically characterized lipids in S. pombe and measured their dynamic changes in Deltaplh1Deltadga1 cells at different growth phases. We further discussed dynamic changes of phospholipids, sphingolipids and neutral lipids in the progress of programmed cell death in Deltaplh1Deltadga1 cells of S. pombe.

Substrate specificity of cyclins determined by electrostatics.

Cyclin dependent kinases (CDK) associate with cyclins to regulate cell cycle progression and gene transcription by phosphorylating key proteins. The different cyclin-CDK complexes display differences in substrate specificities with substrates binding across a shallow, hydrophobic, substrate-binding pocket known as the cyclin groove. However the mechanism underlying this differential substrate recognition remains largely unknown and cannot be explained merely on the basis of sequence variability. A subset of cyclins, cyclins A2, E1 and B1 despite being structurally and functionally similar, show marked differences in their interactions with recruitment peptides derived from their substrate or inhibitor proteins p27, p21, p57, E2F1, p53, pRb and p107. While these peptides (characterized by a cyclin binding motif of four residues ZRXL where Z and X are cationic residues) inhibit the activity of cyclins A2 and E1, no such inhibition is observed for cyclin B1. Electrostatic potentials of cyclins A2, E1 and B1 show that anionic regions of cyclins A2 and E1 enable them to bind peptides while cationic regions at homologous locations in cyclin B1 abrogate binding. These arise from charged residues that are conserved. Mutations that switch these characters are suggested. Computed energetics of binding confirms this. Deregulation of the enzymatic activity of this class of enzymes is a ubiquitous feature of human neoplasia, but attempts to exploit this therapeutically have been confounded by a lack of understanding of the precise specificity of the different cyclin complexes. Here we begin to clarify this issue by explaining the mechanism by which cyclin B1 escapes regulation by the p21 family of CDKIs.

In silico analysis of p53 using the p53 knowledgebase: mutations, polymorphisms, microRNAs and pathways.

P53 is probably the most important tumor suppressor known. Over the years, information about this gene has increased dramatically. We have built a comprehensive knowledgebase of p53, which aims to facilitate wet-lab biologists to formulate their experiments and new-comers to learn whatever they need about the gene and bioinformaticians to make new discoveries through data analysis. Using the information curated, including mutation information, transcription factors, transcriptional targets, and single nucleotide polymorphisms, we have performed extensive bioinformatics analysis, and made several new discoveries about p53. We have identified point missense mutations that are over-represented in cancers, but lack of functional studies. By assessing the capability of six p53 transcriptional targets' tag SNPs selected from HapMap to capture SNPs obtained from National Institute of Environmental Health Sciences (NIEHS) Environmental Genome project and vice versa, we conclude that NIEHS data is a better source for tagSNP selections of these genes in future association studies. Analysis of microRNA regulation in the transcriptional network of the p53 gene reveals potentially important regulatory relationships between oncogenic microRNAs and transcription factors of p53. By mapping transcription factors of p53 to pathways involved in cell cycle and apoptosis, we have identified distinctive transcriptional controls of p53 in these two physiological states.

A topologically related singularity suggests a maximum preferred size for protein domains.

A variety of protein physicochemical as well as topological properties, demonstrate a scaling behavior relative to chain length. Many of the scalings can be modeled as a power law which is qualitatively similar across the examples. In this article, we suggest a rational explanation to these observations on the basis of both protein connectivity and hydrophobic constraints of residues compactness relative to surface volume. Unexpectedly, in an examination of these relationships, a singularity was shown to exist near 255-270 residues length, and may be associated with an upper limit for domain size. Evaluation of related G-factor data points to a wide range of conformational plasticity near this point. In addition to its theoretical importance, we show by an application of CASP experimental and predicted structures, that the scaling is a practical filter for protein structure prediction.

Entropic criteria for protein folding derived from recurrences: six residues patch as the basic protein word.

Some research has suggested that patches of six constitute an important amino acid window length in proteins for conveying information. We present database evidence that supports this conjecture, as well as additional recurrence-based data that characterization and quantification of these words affect the folding/aggregation features of proteins. Other indirect evidence is presented and discussed.

Multiresolution analysis uncovers hidden conservation of properties in structurally and functionally similar proteins.

Physicochemcial properties of amino acids are important factors in determining protein structure and function. Most approaches make use of averaged properties over entire domains or even proteins to analyze their structure or function. This level of coarseness tends to hide the richness of the variability in the different properties across functional domains. This paper studies the conservation of physicochemical properties in a functionally similar family of proteins using a novel wavelet-based technique known as multiresolution analysis. Such an analysis can help uncover characteristics that can otherwise remain hidden. We have studied the protein kinase family of sequences and our findings are as follows: (a) a number of different properties are conserved over the functional catalytic domain irrespective of the sequence identities; (b) conservation of properties can be observed at different frequency levels and they agree well with the known structural/functional properties of the subdomains for the protein kinase family; (c) structural differences between the different kinase family members are reflected in the waveforms; and (d) functionally important mutations show distortions in the waveforms of conserved properties. The potential usefulness of the above findings in identifying functionally similar sequences in the twilight and midnight zones is demonstrated through a simple prediction model for the protein kinase family which achieved a recall of 93.7% and a precision of 96.75% in cross-validation tests.

pSLIP: SVM based protein subcellular localization prediction using multiple physicochemical properties.

BACKGROUND: Protein subcellular localization is an important determinant of protein function and hence, reliable methods for prediction of localization are needed. A number of prediction algorithms have been developed based on amino acid compositions or on the N-terminal characteristics (signal peptides) of proteins. However, such approaches lead to a loss of contextual information. Moreover, where information about the physicochemical properties of amino acids has been used, the methods employed to exploit that information are less than optimal and could use the information more effectively. RESULTS: In this paper, we propose a new algorithm called pSLIP which uses Support Vector Machines (SVMs) in conjunction with multiple physicochemical properties of amino acids to predict protein subcellular localization in eukaryotes across six different locations, namely, chloroplast, cytoplasmic, extracellular, mitochondrial, nuclear and plasma membrane. The algorithm was applied to the dataset provided by Park and Kanehisa and we obtained prediction accuracies for the different classes ranging from 87.7%-97.0% with an overall accuracy of 93.1%. CONCLUSION: This study presents a physicochemical property based protein localization prediction algorithm. Unlike other algorithms, contextual information is preserved by dividing the protein sequences into clusters. The prediction accuracy shows an improvement over other algorithms based on various types of amino acid composition (single, pair and gapped pair). We have also implemented a web server to predict protein localization across the six classes (available at http://pslip.bii.a-star.edu.sg/).