The final piece of the Triangle of U: Evolution of the tetraploid Brassica carinata genome.

Ethiopian mustard (Brassica carinata) is an ancient crop with remarkable stress resilience and a desirable seed fatty acid profile for biofuel uses. Brassica carinata is one of six Brassica species that share three major genomes from three diploid species (AA, BB, and CC) that spontaneously hybridized in a pairwise manner to form three allotetraploid species (AABB, AACC, and BBCC). Of the genomes of these species, that of B. carinata is the least understood. Here, we report a chromosome scale 1.31-Gbp genome assembly with 156.9-fold sequencing coverage for B. carinata, completing the reference genomes comprising the classic Triangle of U, a classical theory of the evolutionary relationships among these six species. Our assembly provides insights into the hybridization event that led to the current B. carinata genome and the genomic features that gave rise to the superior agronomic traits of B. carinata. Notably, we identified an expansion of transcription factor networks and agronomically important gene families. Completion of the Triangle of U comparative genomics platform has allowed us to examine the dynamics of polyploid evolution and the role of subgenome dominance in the domestication and continuing agronomic improvement of B. carinata and other Brassica species.

Integrative transcriptomics reveals association of abscisic acid and lignin pathways with cassava whitefly resistance.

BACKGROUND: Whiteflies are a global threat to crop yields, including the African subsistence crop cassava (Manihot esculenta). Outbreaks of superabundant whitefly populations throughout Eastern and Central Africa in recent years have dramatically increased the pressures of whitefly feeding and virus transmission on cassava. Whitefly-transmitted viral diseases threaten the food security of hundreds of millions of African farmers, highlighting the need for developing and deploying whitefly-resistant cassava. However, plant resistance to whiteflies remains largely poorly characterized at the genetic and molecular levels. Knowledge of cassava-defense programs also remains incomplete, limiting characterization of whitefly-resistance mechanisms. To better understand the genetic basis of whitefly resistance in cassava, we define the defense hormone- and Aleurotrachelus socialis (whitefly)-responsive transcriptome of whitefly-susceptible (COL2246) and whitefly-resistant (ECU72) cassava using RNA-seq. For broader comparison, hormone-responsive transcriptomes of Arabidopsis thaliana were also generated. RESULTS: Whitefly infestation, salicylic acid (SA), jasmonic acid (JA), ethylene (ET), and abscisic acid (ABA) transcriptome responses of ECU72 and COL2246 were defined and analyzed. Strikingly, SA responses were largely reciprocal between the two cassava genotypes and we suggest candidate regulators. While susceptibility was associated with SA in COL2246, resistance to whitefly in ECU72 was associated with ABA, with SA-ABA antagonism observed. This was evidenced by expression of genes within the SA and ABA pathways and hormone levels during A. socialis infestation. Gene-enrichment analyses of whitefly- and hormone-responsive genes suggest the importance of fast-acting cell wall defenses (e.g., elicitor recognition, lignin biosynthesis) during early infestation stages in whitefly-resistant ECU72. A surge of ineffective immune and SA responses characterized the whitefly-susceptible COL2246's response to late-stage nymphs. Lastly, in comparison with the model plant Arabidopsis, cassava's hormone-responsive genes showed striking divergence in expression. CONCLUSIONS: This study provides the first characterization of cassava's global transcriptome responses to whitefly infestation and defense hormone treatment. Our analyses of ECU72 and COL2246 uncovered possible whitefly resistance/susceptibility mechanisms in cassava. Comparative analysis of cassava and Arabidopsis demonstrated that defense programs in Arabidopsis may not always mirror those in crop species. More broadly, our hormone-responsive transcriptomes will also provide a baseline for the cassava community to better understand global responses to other yield-limiting pests/pathogens.

MetaOmGraph: a workbench for interactive exploratory data analysis of large expression datasets.

The diverse and growing omics data in public domains provide researchers with tremendous opportunity to extract hidden, yet undiscovered, knowledge. However, the vast majority of archived data remain unused. Here, we present MetaOmGraph (MOG), a free, open-source, standalone software for exploratory analysis of massive datasets. Researchers, without coding, can interactively visualize and evaluate data in the context of its metadata, honing-in on groups of samples or genes based on attributes such as expression values, statistical associations, metadata terms and ontology annotations. Interaction with data is easy via interactive visualizations such as line charts, box plots, scatter plots, histograms and volcano plots. Statistical analyses include co-expression analysis, differential expression analysis and differential correlation analysis, with significance tests. Researchers can send data subsets to R for additional analyses. Multithreading and indexing enable efficient big data analysis. A researcher can create new MOG projects from any numerical data; or explore an existing MOG project. MOG projects, with history of explorations, can be saved and shared. We illustrate MOG by case studies of large curated datasets from human cancer RNA-Seq, where we identify novel putative biomarker genes in different tumors, and microarray and metabolomics data from Arabidopsis thaliana. MOG executable and code: http://metnetweb.gdcb.iastate.edu/ and https://github.com/urmi-21/MetaOmGraph/.

Maternal-to-zygotic transition as a potential target for niclosamide during early embryogenesis.

Niclosamide is an antihelminthic drug used worldwide for the treatment of tapeworm infections. Recent drug repurposing screens have highlighted the broad bioactivity of niclosamide across diverse mechanisms of action. As a result, niclosamide is being evaluated for a range of alternative drug-repurposing applications, including the treatment of cancer, bacterial infections, and Zika virus. As new applications of niclosamide will require non-oral delivery routes that may lead to exposure in utero, it is important to understand the mechanism of niclosamide toxicity during early stages of embryonic development. Previously, we showed that niclosamide induces a concentration-dependent delay in epiboly progression in the absence of effects on oxidative phosphorylation - a well-established target for niclosamide. Therefore, the overall objective of this study was to further examine the mechanism of niclosamide-induced epiboly delay during zebrafish embryogenesis. Based on this study, we found that (1) niclosamide exposure during early zebrafish embryogenesis resulted in a decrease in yolk sac integrity with a concomitant decrease in the presence of yolk sac actin networks and increase in cell size; (2) within whole embryos, niclosamide exposure did not alter non-polar metabolites and lipids, but significantly altered amino acids specific to aminoacyl-tRNA biosynthesis; (3) niclosamide significantly altered transcripts related to translation, transcription, and mRNA processing pathways; and (4) niclosamide did not significantly alter levels of rRNA and tRNA. Overall, our findings suggest that niclosamide may be causing a systemic delay in embryonic development by disrupting the translation of maternally-supplied mRNAs, an effect that may be mediated through disruption of aminoacyl-tRNA biosynthesis.

Complex Interplay Among Nuclear Receptor Ligands, Cytosine Methylation, and the Metabolome in Driving Tris(1,3-dichloro-2-propyl)phosphate-Induced Epiboly Defects in Zebrafish.

Tris(1,3-dichloro-2-propyl)phosphate (TDCIPP) is a high-production-volume organophosphate flame retardant (OPFR) that induces epiboly defects during zebrafish embryogenesis, leading to the disruption of dorsoventral patterning. Therefore, the objectives of this study were to (1) identify the potential mechanisms involved in TDCIPP-induced epiboly defects and (2) determine whether coexposure to triphenyl phosphate (TPHP)-an OPFR commonly detected with TDCIPP-enhances or mitigates epiboly defects. Although TDCIPP-induced epiboly defects were not associated with adverse impacts on cytoskeletal protein abundance in situ, the coexposure of embryos to TPHP partially blocked TDCIPP-induced epiboly defects. As nuclear receptors are targets for both TPHP and TDCIPP, we exposed the embryos to TDCIPP in the presence or absence of 69 nuclear receptor ligands and, similar to TPHP, found that ciglitazone (a peroxisome proliferator-activated receptor γ agonist) and 17ß-estradiol (E2; an estrogen receptor α agonist) nearly abolished TDCIPP-induced epiboly defects. Moreover, E2 and ciglitazone mitigated TDCIPP-induced effects on CpG hypomethylation within the target loci prior to epiboly, and ciglitazone altered TDCIPP-induced effects on the abundance of two polar metabolites (acetylcarnitine and cytidine-5-diphosphocholine) during epiboly. Overall, our results point to a complex interplay among nuclear receptor ligands, cytosine methylation, and the metabolome in both the induction and mitigation of epiboly defects induced by TDCIPP.

Comprehensive transcriptome analyses correlated with untargeted metabolome reveal differentially expressed pathways in response to cell wall alterations.

KEY MESSAGE: This research provides new insights into plant response to cell wall perturbations through correlation of transcriptome and metabolome datasets obtained from transgenic plants expressing cell wall-modifying enzymes. Plants respond to changes in their cell walls in order to protect themselves from pathogens and other stresses. Cell wall modifications in Arabidopsis thaliana have profound effects on gene expression and defense response, but the cell signaling mechanisms underlying these responses are not well understood. Three transgenic Arabidopsis lines, two with reduced cell wall acetylation (AnAXE and AnRAE) and one with reduced feruloylation (AnFAE), were used in this study to investigate the plant responses to cell wall modifications. RNA-Seq in combination with untargeted metabolome was employed to assess differential gene expression and metabolite abundance. RNA-Seq results were correlated with metabolite abundances to determine the pathways involved in response to cell wall modifications introduced in each line. The resulting pathway enrichments revealed the deacetylation events in AnAXE and AnRAE plants induced similar responses, notably, upregulation of aromatic amino acid biosynthesis and changes in regulation of primary metabolic pathways that supply substrates to specialized metabolism, particularly those related to defense responses. In contrast, genes and metabolites of lipid biosynthetic pathways and peroxidases involved in lignin polymerization were downregulated in AnFAE plants. These results elucidate how primary metabolism responds to extracellular stimuli. Combining the transcriptomics and metabolomics datasets increased the power of pathway prediction, and demonstrated the complexity of pathways involved in cell wall-mediated signaling.

Integrating metabolomics and transcriptomics data to discover a biocatalyst that can generate the amine precursors for alkamide biosynthesis.

The Echinacea genus is exemplary of over 30 plant families that produce a set of bioactive amides, called alkamides. The Echinacea alkamides may be assembled from two distinct moieties, a branched-chain amine that is acylated with a novel polyunsaturated fatty acid. In this study we identified the potential enzymological source of the amine moiety as a pyridoxal phosphate-dependent decarboxylating enzyme that uses branched-chain amino acids as substrate. This identification was based on a correlative analysis of the transcriptomes and metabolomes of 36 different E. purpurea tissues and organs, which expressed distinct alkamide profiles. Although no correlation was found between the accumulation patterns of the alkamides and their putative metabolic precursors (i.e., fatty acids and branched-chain amino acids), isotope labeling analyses supported the transformation of valine and isoleucine to isobutylamine and 2-methylbutylamine as reactions of alkamide biosynthesis. Sequence homology identified the pyridoxal phosphate-dependent decarboxylase-like proteins in the translated proteome of E. purpurea. These sequences were prioritized for direct characterization by correlating their transcript levels with alkamide accumulation patterns in different organs and tissues, and this multi-pronged approach led to the identification and characterization of a branched-chain amino acid decarboxylase, which would appear to be responsible for generating the amine moieties of naturally occurring alkamides.

Application of FT-ICR MS Equipped with Quadrupole Detection for Analysis of Crude Oil.

Resolving power is a critical factor determining the quality of ultrahigh-resolving power mass spectra of crude oil. In this study, 7T Fourier-transform ion cyclotron mass spectrometry (FT-ICR MS), equipped with quadrupole detection, was applied and evaluated for crude oil analysis for the first time. Four spectra were obtained from two oil samples using two ionization methods. Resolving power of 1500000 was observed at m/z 400 with 4 s transient signal. Comparison with literature reports revealed that the achieved resolving power was comparable with or superior to those obtained from instruments using higher magnetic fields but without quadrupole detection. A total of 6000-10000 peaks with an S/N ratio of 3 or higher were observed from the obtained spectra and over 97% of the peaks could be assigned to appropriate chemical formulas with an error within 1 ppm. Double bond equivalents vs carbon number plots generated from the obtained data agreed well with those previously reported without quadrupole detection. Mass accuracy values of the assigned elemental formulas were examined and the average root-mean-square error was calculated to be only 160 ppb. Low unassignment rate of the observed peaks and strong agreement with previously reported results suggests that unwanted harmonics of reduced frequency are not significant for the data obtained with quadrupole detection. Overall, the data presented in this study show that FT-ICR MS equipped with quadrupole detection can be a powerful tool to examine complex mixtures like crude oil. To the best of our knowledge, this is the first paper reporting application of FT-ICR MS equipped with quadrupole detection for the oil analysis.

Microbial Community and Chemical Characteristics of Swine Manure during Maturation.

Swine diet formulations have the potential to lower animal emissions, including odor and ammonia (NH). The purpose of this study was to determine the impact of manure storage duration on manure chemical and microbial properties in swine feeding trials. Three groups of 12 pigs were fed a standard corn-soybean meal diet over a 13-wk period. Urine and feces were collected at each feeding and transferred to 12 manure storage tanks. Manure chemical characteristics and headspace gas concentrations were monitored for NH, hydrogen sulfide (HS), volatile fatty acids, phenols, and indoles. Microbial analysis of the stored manure included plate counts, community structure (denaturing gradient gel electrophoresis), and metabolic function (Biolog). All odorants in manure and headspace gas concentrations were significantly ( < 0.01) correlated for length of storage using quadratic equations, peaking after Week 5 for all headspace gases and most manure chemical characteristics. Microbial community structure and metabolic utilization patterns showed continued change throughout the 13-wk trial. Denaturing gradient gel electrophoresis species diversity patterns declined significantly ( < 0.01) with time as substrate utilization declined for sugars and certain amino acids, but functionality increased in the utilization of short chain fatty acids as levels of these compounds increased in manure. Studies to assess the effect of swine diet formulations on manure emissions for odor need to be conducted for a minimum of 5 wk. Efforts to determine the impact of diets on greenhouse gas emissions will require longer periods of study (>13 wk).

A systems biology approach toward understanding seed composition in soybean.

BACKGROUND: The molecular, biochemical, and genetic mechanisms that regulate the complex metabolic network of soybean seed development determine the ultimate balance of protein, lipid, and carbohydrate stored in the mature seed. Many of the genes and metabolites that participate in seed metabolism are unknown or poorly defined; even more remains to be understood about the regulation of their metabolic networks. A global omics analysis can provide insights into the regulation of seed metabolism, even without a priori assumptions about the structure of these networks. RESULTS: With the future goal of predictive biology in mind, we have combined metabolomics, transcriptomics, and metabolic flux technologies to reveal the global developmental and metabolic networks that determine the structure and composition of the mature soybean seed. We have coupled this global approach with interactive bioinformatics and statistical analyses to gain insights into the biochemical programs that determine soybean seed composition. For this purpose, we used Plant/Eukaryotic and Microbial Metabolomics Systems Resource (PMR, http://www.metnetdb.org/pmr, a platform that incorporates metabolomics data to develop hypotheses concerning the organization and regulation of metabolic networks, and MetNet systems biology tools http://www.metnetdb.org for plant omics data, a framework to enable interactive visualization of metabolic and regulatory networks. CONCLUSIONS: This combination of high-throughput experimental data and bioinformatics analyses has revealed sets of specific genes, genetic perturbations and mechanisms, and metabolic changes that are associated with the developmental variation in soybean seed composition. Researchers can explore these metabolomics and transcriptomics data interactively at PMR.

Metabolomic Characterization of Knockout Mutants in Arabidopsis: Development of a Metabolite Profiling Database for Knockout Mutants in Arabidopsis.

Despite recent intensive research efforts in functional genomics, the functions of only a limited number of Arabidopsis (Arabidopsis thaliana) genes have been determined experimentally, and improving gene annotation remains a major challenge in plant science. As metabolite profiling can characterize the metabolomic phenotype of a genetic perturbation in the plant metabolism, it provides clues to the function(s) of genes of interest. We chose 50 Arabidopsis mutants, including a set of characterized and uncharacterized mutants, that resemble wild-type plants. We performed metabolite profiling of the plants using gas chromatography-mass spectrometry. To make the data set available as an efficient public functional genomics tool for hypothesis generation, we developed the Metabolite Profiling Database for Knock-Out Mutants in Arabidopsis (MeKO). It allows the evaluation of whether a mutation affects metabolism during normal plant growth and contains images of mutants, data on differences in metabolite accumulation, and interactive analysis tools. Nonprocessed data, including chromatograms, mass spectra, and experimental metadata, follow the guidelines set by the Metabolomics Standards Initiative and are freely downloadable. Proof-of-concept analysis suggests that MeKO is highly useful for the generation of hypotheses for genes of interest and for improving gene annotation. MeKO is publicly available at http://prime.psc.riken.jp/meko/.

Impacts of neonicotinoid insecticides on bumble bee energy metabolism are revealed under nectar starvation.

Bumble bees are an important group of insects that provide essential pollination services as a consequence of their foraging behaviors. These pollination services are driven, in part, by energetic exchanges between flowering plants and individual bees. Thus, it is important to examine bumble bee energy metabolism and explore how it might be influenced by external stressors contributing to declines in global pollinator populations. Two stressors that are commonly encountered by bees are insecticides, such as the neonicotinoids, and nutritional stress, resulting from deficits in pollen and nectar availability. Our study uses a metabolomic approach to examine the effects of neonicotinoid insecticide exposure on bumble bee metabolism, both alone and in combination with nutritional stress. We hypothesized that exposure to imidacloprid disrupts bumble bee energy metabolism, leading to changes in key metabolites involved in central carbon metabolism. We tested this by exposing Bombus impatiens workers to imidacloprid according to one of three exposure paradigms designed to explore how chronic versus more acute (early or late) imidacloprid exposure influences energy metabolite levels, then also subjecting them to artificial nectar starvation. The strongest effects of imidacloprid were observed when bees also experienced nectar starvation, suggesting a combinatorial effect of neonicotinoids and nutritional stress on bumble bee energy metabolism. Overall, this study provides important insights into the mechanisms underlying the impact of neonicotinoid insecticides on pollinators, and underscores the need for further investigation into the complex interactions between environmental stressors and energy metabolism.

A global approach to analysis and interpretation of metabolic data for plant natural product discovery.

Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publicly available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these datasets with transcriptomic data to create hypotheses concerning specialized metabolisms that generate the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software.

Identification and biosynthesis of acylphloroglucinols in Hypericum gentianoides.

Species of the genus Hypericum contain a rich array of unusual polyketides, however, only a small proportion of the over 450 Hypericum species, other than the popular medicinal supplement St. John's Wort (Hypericum perforatum), have even been chemically characterized. Hypericum gentianoides, a small annual used medicinally by Cherokee Americans, contains bioactive acylphloroglucinols. Here, we identify acylphloroglucinol constituents of H. gentianoides and determine a potential pathway to their synthesis. Liquid chromatography/electrospray ionization-mass spectrometry (LC/ESI-MS) and HPLC-UV indicate that the level of accumulation and profile of acylphloroglucinols in H. gentianoides vary little seasonally when grown in a greenhouse, but do vary with development and are highly dependent on the accession, highlighting the importance of the selection of plant material for study. We identify the chemical structures of the nine prevalent polyketides, based on LC/ESI-MS and hybrid quadrupole orthogonal time-of-flight (Q-TOF) mass spectrometry; these metabolites include one monomeric phlorisobutyrophenone (PIB) derivative and eight dimeric acylphloroglucinols. Q-TOF spectrometry was used to identify eight additional PIB derivatives that were not detected by LC/ESI-MS. These data lead us to propose that diacylphloroglucinols are synthesized via modification of PIB to yield diverse phloroglucinol and filicinic acids moieties, followed by dimerization of a phloroglucinol and a filicinic acid monomer to yield the observed complement of diacylphloroglucinols. The metabolomics data from H. gentianoides are accessible in plant metabolomics resource (PMR) (http://www.metnetdb.org/pmr), a public metabolomics database with analysis software for plants and microbial organisms.

Metabolomic analyses provide insights into the preharvest rind disorder in Satsuma Owari Mandarin.

Citrus fruit's appearance is the primary criterion used to assess its quality for the fresh market, hence the rind's condition is a crucial quality trait. Pre-harvest rind disorder is one of the major physiological problems in mandarins. The disorder occurs right before harvest following rain events in some Mandarin varieties. Despite the economic damage caused by this kind of disorder, very limited information is available about the molecular mechanisms underlying the occurrence of this disorder. In the present study, we evaluated the primary metabolites, antioxidants, and hormones associated with the pre-harvest rind disorder in Mandarins. The study was carried out using ten-year-old 'Owari' Satsuma mandarin trees grafted on 'Carrizo' rootstock and grown in a commercial orchard in San Joaquin Valley, California, USA. Samples were collected from healthy tissue of healthy fruit (HF_HT), healthy tissue of damaged fruit (DF_HT), and damaged tissue of damaged fruit (DF_DT). Damaged fruit (DF_HT and DF_DT) showed lower cellulose concentrations than healthy fruit tissues (HF_HT), however, had similar contents of pectin and hemicellulose. The antioxidant activities showed no significant difference in all paired comparisons between samples as expressed in the malondialdehyde (MDA) content. However, DF_DT had a higher H2O2 content compared to HF_HT, but DF_HT had a similar content to that of HF_HT. Furthermore, peroxidase (POD) and polyphenol oxidase (PPO) activities were increased in DF_DT compared to HF_HT (P = 0.0294) and DF_HT (P = 0.0044), respectively. Targeted metabolomics analysis revealed that a total of 76 metabolites were identified in Satsuma rind tissues, and the relative concentrations of 43 metabolites were significantly different across studied samples. The hormonal analysis showed the involvement of jasmonate O-methyltransferase, jasmonic acid-amido synthetase JAR1-like, and JA-isoleucine may key role in causing the rind disorder in mandarins. In addition, the damaged fruit tissues have a higher level of jasmonic acid (JA), 12-oxo-phytodienoic acid, and JA-isoleucine than undamaged tissue.

COG-imposed Golgi functional integrity determines the onset of dark-induced senescence.

Plant survival depends on dynamic stress-response pathways in changing environments. To uncover pathway components, we screened an ethyl methanesulfonate-mutagenized transgenic line containing a stress-inducible luciferase construct and isolated a constitutive expression mutant. The mutant is the result of an amino acid substitution in the seventh subunit of the hetero-octameric conserved oligomeric Golgi (COG) complex of Arabidopsis thaliana. Complementation studies verified the Golgi localization of cog7, and stress tests established accelerated dark-induced carbon deprivation/senescence of the mutant compared with wild-type plants. Multiomics and biochemical analyses revealed accelerated induction of protein ubiquitination and autophagy, and a counterintuitive increased protein N-glycosylation in senescencing cog7 relative to wild-type. A revertant screen using the overexpressor (FOX)-hunting system established partial, but notable rescue of cog7 phenotypes by COG5 overexpression, and conversely premature senescence in reduced COG5 expressing lines. These findings identify COG-imposed Golgi functional integrity as a main player in ensuring cellular survival under energy-limiting conditions.

An iPSC-derived astrocyte model of fragile X syndrome exhibits dysregulated cholesterol homeostasis.

Cholesterol is an essential membrane structural component and steroid hormone precursor, and is involved in numerous signaling processes. Astrocytes regulate brain cholesterol homeostasis and they supply cholesterol to the needs of neurons. ATP-binding cassette transporter A1 (ABCA1) is the main cholesterol efflux transporter in astrocytes. Here we show dysregulated cholesterol homeostasis in astrocytes generated from human induced pluripotent stem cells (iPSCs) derived from males with fragile X syndrome (FXS), which is the most common cause of inherited intellectual disability. ABCA1 levels are reduced in FXS human and mouse astrocytes when compared with controls. Accumulation of cholesterol associates with increased desmosterol and polyunsaturated phospholipids in the lipidome of FXS mouse astrocytes. Abnormal astrocytic responses to cytokine exposure together with altered anti-inflammatory and cytokine profiles of human FXS astrocyte secretome suggest contribution of inflammatory factors to altered cholesterol homeostasis. Our results demonstrate changes of astrocytic lipid metabolism, which can critically regulate membrane properties and affect cholesterol transport in FXS astrocytes, providing target for therapy in FXS.

Targeted Metabolomics Using LC-MS in Neurospora crassa.

The filamentous fungus Neurospora crassa has historically been a model for understanding the relationship between genes and metabolism-auxotrophic mutants of N. crassa were used by Beadle and Tatum to develop the one-gene-one-enzyme hypothesis for which they earned the Nobel Prize in 1958. In the ensuing decades, several techniques have been developed for the systematic analysis of metabolites in N. crassa and other fungi. Untargeted and targeted approaches have been used, with a focus on secondary metabolites over primary metabolism. Here, we describe a pipeline for sample preparation, metabolite extraction, Liquid Chromatography-Mass Spectrometry (LC-MS), and data analysis that can be used for targeted metabolomics of primary metabolites in N. crassa. Liquid cultures are grown with shaking in a defined minimal medium and then collected using filtration. Samples are lyophilized for 2 days at -80°C, pulverized, and mixed with a solution to extract polar metabolites. The metabolites are separated and identified using LC-MS, with downstream analysis using Skyline interpretive software. Relative levels of hundreds of metabolites can be detected and compared across strains. © 2022 Wiley Periodicals LLC. Basic Protocol: Metabolite extraction and detection from Neurospora crassa cell cultures using Liquid Chromatography-Mass Spectrometry.

Pollen diet mediates how pesticide exposure impacts brain gene expression in nest-founding bumble bee queens.

A primary goal in biology is to understand the effects of multiple, interacting environmental stressors on organisms. Wild and domesticated bees are exposed to a wide variety of interacting biotic and abiotic stressors, with widespread declines in floral resources and agrochemical exposure being two of the most important. In this study, we used examinations of brain gene expression to explore the sublethal consequences of neonicotinoid pesticide exposure and pollen diet composition in nest-founding bumble bee queens. We demonstrate for the first time that pollen diet composition can influence the strength of bumble bee queen responses to pesticide exposure at the molecular level. Specifically, one pollen mixture in our study appeared to buffer bumble bee queens entirely against the effects of pesticide exposure, with respect to brain gene expression. Additionally, we detected unique effects of pollen diet and sustained (versus more temporary) pesticide exposure on queen gene expression. Our findings support the hypothesis that nutritional status can help buffer animals against the harmful effects of other stressors, including pesticides, and highlight the importance of using molecular approaches to explore sublethal consequences of stressors.

Functional genomics of RAP proteins and their role in mitoribosome regulation in Plasmodium falciparum.

The RAP (RNA-binding domain abundant in Apicomplexans) protein family has been identified in various organisms. Despite expansion of this protein family in apicomplexan parasites, their main biological functions remain unknown. In this study, we use inducible knockdown studies in the human malaria parasite, Plasmodium falciparum, to show that two RAP proteins, PF3D7_0105200 (PfRAP01) and PF3D7_1470600 (PfRAP21), are essential for parasite survival and localize to the mitochondrion. Using transcriptomics, metabolomics, and proteomics profiling experiments, we further demonstrate that these RAP proteins are involved in mitochondrial RNA metabolism. Using high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (eCLIP-seq), we validate that PfRAP01 and PfRAP21 are true RNA-binding proteins and interact specifically with mitochondrial rRNAs. Finally, mitochondrial enrichment experiments followed by deep sequencing of small RNAs demonstrate that PfRAP21 controls mitochondrial rRNA expression. Collectively, our results establish the role of these RAP proteins in mitoribosome activity and contribute to further understanding this protein family in malaria parasites.