Protein-protein interaction network-based integration of GWAS and functional data for blood pressure regulation analysis.

BACKGROUND: It is valuable to analyze the genome-wide association studies (GWAS) data for a complex disease phenotype in the context of the protein-protein interaction (PPI) network, as the related pathophysiology results from the function of interacting polyprotein pathways. The analysis may include the design and curation of a phenotype-specific GWAS meta-database incorporating genotypic and eQTL data linking to PPI and other biological datasets, and the development of systematic workflows for PPI network-based data integration toward protein and pathway prioritization. Here, we pursued this analysis for blood pressure (BP) regulation. METHODS: The relational scheme of the implemented in Microsoft SQL Server BP-GWAS meta-database enabled the combined storage of: GWAS data and attributes mined from GWAS Catalog and the literature, Ensembl-defined SNP-transcript associations, and GTEx eQTL data. The BP-protein interactome was reconstructed from the PICKLE PPI meta-database, extending the GWAS-deduced network with the shortest paths connecting all GWAS-proteins into one component. The shortest-path intermediates were considered as BP-related. For protein prioritization, we combined a new integrated GWAS-based scoring scheme with two network-based criteria: one considering the protein role in the reconstructed by shortest-path (RbSP) interactome and one novel promoting the common neighbors of GWAS-prioritized proteins. Prioritized proteins were ranked by the number of satisfied criteria. RESULTS: The meta-database includes 6687 variants linked with 1167 BP-associated protein-coding genes. The GWAS-deduced PPI network includes 1065 proteins, with 672 forming a connected component. The RbSP interactome contains 1443 additional, network-deduced proteins and indicated that essentially all BP-GWAS proteins are at most second neighbors. The prioritized BP-protein set was derived from the union of the most BP-significant by any of the GWAS-based or the network-based criteria. It included 335 proteins, with ~ 2/3 deduced from the BP PPI network extension and 126 prioritized by at least two criteria. ESR1 was the only protein satisfying all three criteria, followed in the top-10 by INSR, PTN11, CDK6, CSK, NOS3, SH2B3, ATP2B1, FES and FINC, satisfying two. Pathway analysis of the RbSP interactome revealed numerous bioprocesses, which are indeed functionally supported as BP-associated, extending our understanding about BP regulation. CONCLUSIONS: The implemented workflow could be used for other multifactorial diseases.

Modern venomics-Current insights, novel methods, and future perspectives in biological and applied animal venom research.

Venoms have evolved >100 times in all major animal groups, and their components, known as toxins, have been fine-tuned over millions of years into highly effective biochemical weapons. There are many outstanding questions on the evolution of toxin arsenals, such as how venom genes originate, how venom contributes to the fitness of venomous species, and which modifications at the genomic, transcriptomic, and protein level drive their evolution. These questions have received particularly little attention outside of snakes, cone snails, spiders, and scorpions. Venom compounds have further become a source of inspiration for translational research using their diverse bioactivities for various applications. We highlight here recent advances and new strategies in modern venomics and discuss how recent technological innovations and multi-omic methods dramatically improve research on venomous animals. The study of genomes and their modifications through CRISPR and knockdown technologies will increase our understanding of how toxins evolve and which functions they have in the different ontogenetic stages during the development of venomous animals. Mass spectrometry imaging combined with spatial transcriptomics, in situ hybridization techniques, and modern computer tomography gives us further insights into the spatial distribution of toxins in the venom system and the function of the venom apparatus. All these evolutionary and biological insights contribute to more efficiently identify venom compounds, which can then be synthesized or produced in adapted expression systems to test their bioactivity. Finally, we critically discuss recent agrochemical, pharmaceutical, therapeutic, and diagnostic (so-called translational) aspects of venoms from which humans benefit.

Mitochondrial protein import determines lifespan through metabolic reprogramming and de novo serine biosynthesis.

Sustained mitochondrial fitness relies on coordinated biogenesis and clearance. Both processes are regulated by constant targeting of proteins into the organelle. Thus, mitochondrial protein import sets the pace for mitochondrial abundance and function. However, our understanding of mitochondrial protein translocation as a regulator of longevity remains enigmatic. Here, we targeted the main protein import translocases and assessed their contribution to mitochondrial abundance and organismal physiology. We find that reduction in cellular mitochondrial load through mitochondrial protein import system suppression, referred to as MitoMISS, elicits a distinct longevity paradigm. We show that MitoMISS triggers the mitochondrial unfolded protein response, orchestrating an adaptive reprogramming of metabolism. Glycolysis and de novo serine biosynthesis are causatively linked to longevity, whilst mitochondrial chaperone induction is dispensable for lifespan extension. Our findings extent the pro-longevity role of UPRmt and provide insight, relevant to the metabolic alterations that promote or undermine survival and longevity.

How Far Are We from the Completion of the Human Protein Interactome Reconstruction?

After more than fifteen years from the first high-throughput experiments for human protein-protein interaction (PPI) detection, we are still wondering how close the completion of the genome-scale human PPI network reconstruction is, what needs to be further explored and whether the biological insights gained from the holistic investigation of the current network are valid and useful. The unique structure of PICKLE, a meta-database of the human experimentally determined direct PPI network developed by our group, presently covering ~80% of the UniProtKB/Swiss-Prot reviewed human complete proteome, enables the evaluation of the interactome expansion by comparing the successive PICKLE releases since 2013. We observe a gradual overall increase of 39%, 182%, and 67% in protein nodes, PPIs, and supporting references, respectively. Our results indicate that, in recent years, (a) the PPI addition rate has decreased, (b) the new PPIs are largely determined by high-throughput experiments and mainly concern existing protein nodes and (c), as we had predicted earlier, most of the newly added protein nodes have a low degree. These observations, combined with a largely overlapping k-core between PICKLE releases and a network density increase, imply that an almost complete picture of a structurally defined network has been reached. The comparative unsupervised application of two clustering algorithms indicated that exploring the full interactome topology can reveal the protein neighborhoods involved in closely related biological processes as transcriptional regulation, cell signaling and multiprotein complexes such as the connexon complex associated with cancers. A well-reconstructed human protein interactome is a powerful tool in network biology and medicine research forming the basis for multi-omic and dynamic analyses.

Systems Biology in ELIXIR: modelling in the spotlight.

In this white paper, we describe the founding of a new ELIXIR Community - the Systems Biology Community - and its proposed future contributions to both ELIXIR and the broader community of systems biologists in Europe and worldwide. The Community believes that the infrastructure aspects of systems biology - databases, (modelling) tools and standards development, as well as training and access to cloud infrastructure - are not only appropriate components of the ELIXIR infrastructure, but will prove key components of ELIXIR's future support of advanced biological applications and personalised medicine. By way of a series of meetings, the Community identified seven key areas for its future activities, reflecting both future needs and previous and current activities within ELIXIR Platforms and Communities. These are: overcoming barriers to the wider uptake of systems biology; linking new and existing data to systems biology models; interoperability of systems biology resources; further development and embedding of systems medicine; provisioning of modelling as a service; building and coordinating capacity building and training resources; and supporting industrial embedding of systems biology. A set of objectives for the Community has been identified under four main headline areas: Standardisation and Interoperability, Technology, Capacity Building and Training, and Industrial Embedding. These are grouped into short-term (3-year), mid-term (6-year) and long-term (10-year) objectives.

Untargeted Plasma Metabolomics Unravels a Metabolic Signature for Tissue Sensitivity to Glucocorticoids in Healthy Subjects: Its Implications in Dietary Planning for a Healthy Lifestyle.

In clinical practice, differences in glucocorticoid sensitivity among healthy subjects may influence the outcome and any adverse effects of glucocorticoid therapy. Thus, a fast and accurate methodology that could enable the classification of individuals based on their tissue glucocorticoid sensitivity would be of value. We investigated the usefulness of untargeted plasma metabolomics in identifying a panel of metabolites to distinguish glucocorticoid-resistant from glucocorticoid-sensitive healthy subjects who do not carry mutations in the human glucocorticoid receptor (NR3C1) gene. Applying a published methodology designed for the study of glucocorticoid sensitivity in healthy adults, 101 healthy subjects were ranked according to their tissue glucocorticoid sensitivity based on 8:00 a.m. serum cortisol concentrations following a very low-dose dexamethasone suppression test. Ten percent of the cohort, i.e., 11 participants, on each side of the ranking, with no NR3C1 mutations or polymorphisms, were selected, respectively, as the most glucocorticoid-sensitive and most glucocorticoid-resistant of the cohort to be analyzed and compared with untargeted blood plasma metabolomics using gas chromatography-mass spectrometry (GC-MS). The acquired metabolic profiles were evaluated using multivariate statistical analysis methods. Nineteen metabolites were identified with significantly lower abundance in the most sensitive compared to the most resistant group of the cohort, including fatty acids, sugar alcohols, and serine/threonine metabolism intermediates. These results, combined with a higher glucose, sorbitol, and lactate abundance, suggest a higher Cori cycle, polyol pathway, and inter-tissue one-carbon metabolism rate and a lower fat mobilization rate at the fasting state in the most sensitive compared to the most resistant group. In fact, this was the first study correlating tissue glucocorticoid sensitivity with serine/threonine metabolism. Overall, the observed metabolic signature in this cohort implies a worse cardiometabolic profile in the most glucocorticoid-sensitive compared to the most glucocorticoid-resistant healthy subjects. These findings offer a metabolic signature that distinguishes most glucocorticoid-sensitive from most glucocorticoid-resistant healthy subjects to be further validated in larger cohorts. Moreover, they support the correlation of tissue glucocorticoid sensitivity with insulin resistance and metabolic syndrome-associated pathways, further emphasizing the need for nutritionists and doctors to consider the tissue glucocorticoid sensitivity in dietary and exercise planning, particularly when these subjects are to be treated with glucocorticoids.

Metabolic Profiling Indicates Diversity in the Metabolic Physiologies Associated With Maternal Postpartum Depressive Symptoms.

Background: Postpartum depression (PPD) is a devastating disease requiring improvements in diagnosis and prevention. Blood metabolomics identifies biological markers discriminatory between women with and those without antenatal depressive symptoms. Whether this cutting-edge method can be applied to postpartum depressive symptoms merits further investigation. Methods: As a substudy within the Biology, Affect, Stress, Imagine and Cognition Study, 24 women with PPD symptom (PPDS) assessment at 6 weeks postpartum were included. Controls were selected as having a score of ≤ 6 and PPDS cases as ≥12 on the Edinburgh Postnatal Depression Scale. Blood plasma was collected at 10 weeks postpartum and analyzed with gas chromatography-mass spectrometry metabolomics. Results: Variations of metabolomic profiles within the PPDS samples were identified. One cluster showed altered kidney function, whereas the other, a metabolic syndrome profile, both previously associated with depression. Five metabolites (glycerol, threonine, 2-hydroxybutanoic acid, erythritol, and phenylalanine) showed higher abundance among women with PPDSs, indicating perturbations in the serine/threonine and glycerol lipid metabolism, suggesting oxidative stress conditions. Conclusions: Alterations in certain metabolites were associated with depressive pathophysiology postpartum, whereas diversity in PPDS physiologies was revealed. Hence, plasma metabolic profiling could be considered in diagnosis and pathophysiological investigation of PPD toward providing clues for treatment. Future studies require standardization of various subgroups with respect to symptom onset, lifestyle, and comorbidities.

PICKLE 3.0: enriching the human meta-database with the mouse protein interactome extended via mouse-human orthology.

SUMMARY: The PICKLE 3.0 upgrade refers to the enrichment of this human protein-protein interaction (PPI) meta-database with the mouse protein interactome. Experimental PPI data between mouse genetic entities are rather limited; however, they are substantially complemented by PPIs between mouse and human genetic entities. The relational scheme of PICKLE 3.0 has been amended to exploit the Mouse Genome Informatics mouse-human ortholog gene pair collection, enabling (i) the extension through orthology of the mouse interactome with potentially valid PPIs between mouse entities based on the experimental PPIs between mouse and human entities and (ii) the comparison between mouse and human PPI networks. Interestingly, 43.5% of the experimental mouse PPIs lacks a corresponding by orthology PPI in human, an inconsistency in need of further investigation. Overall, as primary mouse PPI datasets show a considerably limited overlap, PICKLE 3.0 provides a unique comprehensive representation of the mouse protein interactome. AVAILABILITY AND IMPLEMENTATION: PICKLE can be queried and downloaded at http://www.pickle.gr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Probing the Response of the Amphibious Plant Butomus umbellatus to Nutrient Enrichment and Shading by Integrating Eco-Physiological With Metabolomic Analyses.

Amphibious plants, living in land-water ecotones, have to cope with challenging and continuously changing growth conditions in their habitats with respect to nutrient and light availability. They have thus evolved a variety of mechanisms to tolerate and adapt to these changes. Therefore, the study of these plants is a major area of ecophysiology and environmental ecological research. However, our understanding of their capacity for physiological adaptation and tolerance remains limited and requires systemic approaches for comprehensive analyses. To this end, in this study, we have conducted a mesocosm experiment to analyze the response of Butomus umbellatus, a common amphibious species in Denmark, to nutrient enrichment and shading. Our study follows a systematic integration of morphological (including plant height, leaf number, and biomass accumulation), ecophysiological (photosynthesis-irradiance responses, leaf pigment content, and C and N content in plant organs), and leaf metabolomic measurements using gas chromatography-mass spectrometry (39 mainly primary metabolites), based on bioinformatic methods. No studies of this type have been previously reported for this plant species. We observed that B. umbellatus responds to nutrient enrichment and light reduction through different mechanisms and were able to identify its nutrient enrichment acclimation threshold within the applied nutrient gradient. Up to that threshold, the morpho-physiological response to nutrient enrichment was profound, indicating fast-growing trends (higher growth rates and biomass accumulation), but only few parameters changed significantly from light to shade [specific leaf area (SLA); quantum yield (φ)]. Metabolomic analysis supported the morpho-physiological results regarding nutrient overloading, indicating also subtle changes due to shading not directly apparent in the other measurements. The combined profile analysis revealed leaf metabolite and morpho-physiological parameter associations. In this context, leaf lactate, currently of uncertain role in higher plants, emerged as a shading acclimation biomarker, along with SLA and φ. The study enhances both the ecophysiology methodological toolbox and our knowledge of the adaptive capacity of amphibious species. It demonstrates that the educated combination of physiological with metabolomic measurements using bioinformatic approaches is a promising approach for ecophysiology research, enabling the elucidation of discriminatory metabolic shifts to be used for early diagnosis and even prognosis of natural ecosystem responses to climate change.

Blood plasma metabolic profiling of pregnant women with antenatal depressive symptoms.

Antenatal depression affects ~9-19% of pregnant women and can exert persistent adverse effects on both mother and child. There is a need for a deeper understanding of antenatal depression mechanisms and the development of tools for reliable diagnosis and early identification of women at high risk. As the use of untargeted blood metabolomics in the investigation of psychiatric and neurological diseases has increased substantially, the main objective of this study was to investigate whether untargeted gas chromatography-mass spectrometry (GC-MS) plasma metabolomics in 45 women in late pregnancy, residing in Uppsala, Sweden, could indicate metabolic differences between women with and without depressive symptoms. Furthermore, seasonal differences in the metabolic profiles were explored. When comparing the profiles of cases with controls, independently of season, no differences were observed. However, seasonal differences were observed in the metabolic profiles of control samples, suggesting a favorable cardiometabolic profile in the summer vs. winter, as indicated by lower glucose and sugar acid concentrations and lactate to pyruvate ratio, and higher abundance of arginine and phosphate. Similar differences were identified between cases and controls among summer pregnancies, indicating an association between a stressed metabolism and depressive symptoms. No depression-specific differences were apparent among depressed and non-depressed women, in the winter pregnancies; this could be attributed to an already stressed metabolism due to the winter living conditions. Our results provide new insights into the pathophysiology of antenatal depression, and warrant further investigation of the use of metabolomics in antenatal depression in larger cohorts.

Mechanisms underlying the cardiometabolic protective effect of walnut consumption in obese people: A cross-over, randomized, double-blind, controlled inpatient physiology study.

AIMS: To assess the effects of walnuts on cardiometabolic outcomes in obese people and to explore the underlying mechanisms using novel methods including metabolomic, lipidomic, glycomic and microbiome analysis, integrated with lipid particle fractionation, appetite-regulating hormones and haemodynamic measurements. MATERIALS AND METHODS: A total of 10 obese individuals were enrolled in this cross-over, randomized, double-blind, placebo-controlled clinical trial. The participants had two 5-day inpatient stays, during which they consumed a smoothie containing 48 g walnuts or a macronutrient-matched placebo smoothie without nuts, with a 1-month washout period between the two visits. RESULTS: Walnut consumption improved aspects of the lipid profile; it reduced fasting small and dense LDL particles (P < 0.02) and increased postprandial large HDL particles (P < 0.01). Lipoprotein insulin resistance score, glucose and the insulin area under the curve (AUC) decreased significantly after walnut consumption (P < 0.01, P < 0.02 and P < 0.04, respectively). Consuming walnuts significantly increased 10 N-glycans, with eight of them carrying a fucose core. Lipidomic analysis showed a robust reduction in harmful ceramides, hexosylceramides and sphingomyelins, which have been shown to mediate effects on cardiometabolic risk. The peptide YY AUC significantly increased after walnut consumption (P < 0.03). No major significant changes in haemodynamic or metabolomic analysis or in microbiome host health-promoting bacteria such as Faecalibacterium were found. CONCLUSIONS: These data provide a more comprehensive mechanistic perspective of the effect of dietary walnut consumption on cardiometabolic variables. Lipidomic and lipid nuclear magnetic resonance spectroscopy analysis showed an early but significant reduction in ceramides and other atherogenic lipids with walnut consumption, which may explain the longer-term benefits of walnuts or other nuts on insulin resistance, cardiovascular risk and mortality.

Changes in size and composition of pigweed (Amaranthus hybridus L.) calcium oxalate crystals under CO2 starvation conditions.

The functional role(s) of plant calcium oxalate (CaOx) crystals are still poorly understood. Recently, it was shown that crystals function as dynamic carbon pools whose decomposition could provide CO2 to photosynthesis when stomata are closed (e.g. under drought conditions) and CO2 starvation conditions may be created within the mesophyll. This biochemical process, named as 'alarm photosynthesis', can become crucial for plant survival under adverse conditions. Here, we study crystal decomposition under controlled CO2 starvation conditions (either in the shoot or in the root) to obtain a better insight into the process of crystal formation and function. Hydroponically grown pigweed plants were kept in CO2 -free air and/or CO2 -free nutrient medium for 9 days. Crystal volume was monitored daily, and carbon stable isotope composition (δ13 C) and Fourier transformation Raman spectra were obtained at the end of the experiment. A considerable reduction in the leaf crystal volume was observed in shoot-CO2 -starved plants at the end of the experiment. The smallest crystals were isolated from the plants in which carbon was excluded from both the shoot and the root and contained potassium nitrate. Crystal δ13 C of CO2 -starved plants was altered in a predicted way. Specifically, it depended on the average calculated isotope fractionation of all carbon fixation processes considered to be contributing in each experimental treatment. The results of the present study confirmed the correlation between CO2 starvation conditions and the CaOx crystal decomposition. Inorganic carbon fixed in the root may represent a major carbon source for CaOx formation.

Untargeted GC-MS Metabolomics.

Untargeted metabolomics refers to the high-throughput analysis of the metabolic state of a biological system (e.g., tissue, biological fluid, cell culture) based on the concentration profile of all measurable free low molecular weight metabolites. Gas chromatography-mass spectrometry (GC-MS), being a highly sensitive and high-throughput analytical platform, has been proven a useful tool for untargeted studies of primary metabolism in a variety of applications. As an omic analysis, GC-MS metabolomics is a multistep procedure; thus, standardization of an untargeted GC-MS metabolomics protocol requires the integrated optimization of pre-analytical, analytical, and computational steps. The main difference of GC-MS metabolomics compared to other metabolomics analytical platforms, including liquid chromatography-MS, is the need for the derivatization of the metabolite extracts into volatile and thermally stable derivatives, the latter being quantified in the metabolic profiles. This analytical step requires special care in the optimization of the untargeted GC-MS metabolomics experimental protocol. Moreover, both the derivatization of the original sample and the compound fragmentation that takes place in GC-MS impose specialized GC-MS metabolomic data identification, quantification, normalization and filtering methods. In this chapter, we describe the integrated protocol of untargeted GC-MS metabolomics with both the analytical and computational steps, focusing on the GC-MS specific parts, and provide details on any sample depending differences.

Comprehensive subcellular topologies of polypeptides in Streptomyces.

BACKGROUND: Members of the genus Streptomyces are Gram-positive bacteria that are used as important cell factories to produce secondary metabolites and secrete heterologous proteins. They possess some of the largest bacterial genomes and thus proteomes. Understanding their complex proteomes and metabolic regulation will improve any genetic engineering approach. RESULTS: Here, we performed a comprehensive annotation of the subcellular localization of the proteome of Streptomyces lividans TK24 and developed the Subcellular Topology of Polypeptides in Streptomyces database (SToPSdb) to make this information widely accessible. We first introduced a uniform, improved nomenclature that re-annotated the names of ~ 4000 proteins based on functional and structural information. Then protein localization was assigned de novo using prediction tools and edited by manual curation for 7494 proteins, including information for 183 proteins that resulted from a recent genome re-annotation and are not available in current databases. The S. lividans proteome was also linked with those of other model bacterial strains including Streptomyces coelicolor A3(2) and Escherichia coli K-12, based on protein homology, and can be accessed through an open web interface. Finally, experimental data derived from proteomics experiments have been incorporated and provide validation for protein existence or topology for 579 proteins. Proteomics also reveals proteins released from vesicles that bleb off the membrane. All export systems known in S. lividans are also presented and exported proteins assigned export routes, where known. CONCLUSIONS: SToPSdb provides an updated and comprehensive protein localization annotation resource for S. lividans and other streptomycetes. It forms the basis for future linking to databases containing experimental data of proteomics, genomics and metabolomics studies for this organism.

The future of metabolomics in ELIXIR.

Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.

PICKLE 2.0: A human protein-protein interaction meta-database employing data integration via genetic information ontology.

It has been acknowledged that source databases recording experimentally supported human protein-protein interactions (PPIs) exhibit limited overlap. Thus, the reconstruction of a comprehensive PPI network requires appropriate integration of multiple heterogeneous primary datasets, presenting the PPIs at various genetic reference levels. Existing PPI meta-databases perform integration via normalization; namely, PPIs are merged after converted to a certain target level. Hence, the node set of the integrated network depends each time on the number and type of the combined datasets. Moreover, the irreversible a priori normalization process hinders the identification of normalization artifacts in the integrated network, which originate from the nonlinearity characterizing the genetic information flow. PICKLE (Protein InteraCtion KnowLedgebasE) 2.0 implements a new architecture for this recently introduced human PPI meta-database. Its main novel feature over the existing meta-databases is its approach to primary PPI dataset integration via genetic information ontology. Building upon the PICKLE principles of using the reviewed human complete proteome (RHCP) of UniProtKB/Swiss-Prot as the reference protein interactor set, and filtering out protein interactions with low probability of being direct based on the available evidence, PICKLE 2.0 first assembles the RHCP genetic information ontology network by connecting the corresponding genes, nucleotide sequences (mRNAs) and proteins (UniProt entries) and then integrates PPI datasets by superimposing them on the ontology network without any a priori transformations. Importantly, this process allows the resulting heterogeneous integrated network to be reversibly normalized to any level of genetic reference without loss of the original information, the latter being used for identification of normalization biases, and enables the appraisal of potential false positive interactions through PPI source database cross-checking. The PICKLE web-based interface (www.pickle.gr) allows for the simultaneous query of multiple entities and provides integrated human PPI networks at either the protein (UniProt) or the gene level, at three PPI filtering modes.

Sex-comparative study of mouse cerebellum physiology under adult-onset hypothyroidism: The significance of GC-MS metabolomic data normalization in meta-analysis.

A systematic data quality validation and normalization strategy is an important component of the omic profile meta-analysis, ensuring comparability of the profiles and exclusion of experimental biases from the derived biological conclusions. In this study, we present the normalization methodology applied on the sets of cerebellum gas chromatography-mass spectrometry metabolic profiles of 124days old male and female animals in an adult-onset-hypothyroidism (AOH) mouse model before combining them into a sex-comparative analysis. The employed AOH model concerns the monitoring of the brain physiology of Balb/cJ mice after eight-week administration of 1%w/v KClO4 in the drinking water, initiated on the 60th day of their life. While originating from the same animal study, the tissues of the two sexes were processed and their profiles acquired and analyzed at different time periods. Hence, the previously published profile set of male mice was first re-annotated based on the presently available resources. Then, after being validated as acquired under the same analytical conditions, both profiles sets were corrected for derivatization biases and filtered for low-confidence measurements based on the same criteria. The final normalized 73-metabolite profiles contribute to the currently few available omic datasets of the AOH effect on brain molecular physiology, especially with respect to sex differentiation. Multivariate statistical analysis indicated one (unknown) and three (succinate, benzoate, myristate) metabolites with significantly higher and lower, respectively, cerebellum concentration in the hypothyroid compared to the euthyroid female mice. The respective numbers for the males were two and 24. Comparison of the euthyroid cerebellum metabolic profiles between the two sexes indicated 36 metabolites, including glucose, myo- and scyllo-inositol, with significantly lower concentration in the females versus the males. This implies that the female mouse cerebellum has been conditioned to smaller changes in its metabolic activity with respect to the pathways involving these metabolites compared to the male animals. In conclusion, our study indicated a much subtler AOH effect on the cerebellum metabolic activity of the female compared to the male mice. The leaner metabolic profile of the female mouse cerebellum was suggested as a potential factor contributing to this phenomenon.

Reevaluation of the plant "gemstones": Calcium oxalate crystals sustain photosynthesis under drought conditions.

Land plants face the perpetual dilemma of using atmospheric carbon dioxide for photosynthesis and losing water vapors, or saving water and reducing photosynthesis and thus growth. The reason behind this dilemma is that this simultaneous exchange of gases is accomplished through the same minute pores on leaf surfaces, called stomata. In a recent study we provided evidence that pigweed, an aggressive weed, attenuates this problem exploiting large crystals of calcium oxalate as dynamic carbon pools. This plant is able to photosynthesize even under drought conditions, when stomata are closed and water losses are limited, using carbon dioxide from crystal decomposition instead from the atmosphere. Abscisic acid, an alarm signal that causes stomatal closure seems to be implicated in this function and for this reason we named this path "alarm photosynthesis." The so-far "enigmatic," but highly conserved and widespread among plant species calcium oxalate crystals seem to play a crucial role in the survival of plants.