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The oil palm fruit produces highly valuable edible oil from its fleshy mesocarp and seed. Aside from the palm oil and palm kernel oil of economic importance, the non-oil components of the oil palm fruit hold great potential as natural and sustainable products. Most studies focus on the molecular mechanisms regulating the oil palm lipid production and accumulation but little is known about secondary metabolism, specifically stilbenoids in the fruit tissues. This work aims to profile the proteomes and metabolomes of the exocarp, mesocarp, shell and kernel at the ripening stage and to identify the enzymes and metabolites associated with stilbenoid biosynthesis. From a total of 1964 proteins, the mesocarp and exocarp tissues were characterized by high abundance of proteins related to fatty acid, glycolysis and secondary metabolism. Proteins more abundant in the kernel and shell tissues were linked to storage and triacylglycerol synthesis. The enzymes directly involved in stilbenoid biosynthesis are 4-coumarate: coenzyme A ligase (4CL), hydroxycinnamoyl-CoA: shikimate hydroxycinnamoyl transferase (HCT) and trans -resveratrol di- O -methyltransferase (ROMT) which were highly expressed (p < 0.05) in the exocarp, mesocarp and shell tissues but not in the kernel. Trans -resveratrol was detected in the shell and mesocarp from comprehensive metabolome screening, with piceatannol in the shell, exocarp and kernel as well as trans -piceid in the exocarp. The oil palm fruit key proteins reveal tissue-specific cellular functions for primary and secondary metabolism in corroboration with the metabolome profiles, prospective for further quality improvement and optimum utilization of this rich resource. [Display omitted] • The oil palm fruit tissues were comprehensively profiled using MS omics platform. • The first work on oil palm fruit stilbenoids-related enzymes and metabolites. • Oil palm offers natural, safe and plant-based preservatives for food and cosmetics. • Stilbenoids in oil palm fruit can be harnessed besides the oil fraction. • This effort optimizes resource yields for a circular economy, ensuring zero waste. [ABSTRACT FROM AUTHOR]

Plasma membranes (PMs) act as primary cellular checkpoints for sensing signals and controlling solute transport. Membrane proteins communicate with intracellular processes through protein interaction networks. Deciphering these signaling networks provides crucial information for elucidating in vivo cellular regulation. Large-scale proteomics enables system-wide characterization of the membrane proteome, identification of ligand–receptor pairs, and elucidation of signals originating at membranes. In this review we assess recent progress in the development of mass spectrometry (MS)-based proteomic pipelines for determining membrane signaling pathways. We focus in particular on current techniques for the analysis of membrane protein phosphorylation and interaction, and how these proteins may be connected to downstream changes in gene expression, metabolism, and physiology. Membrane receptors, kinases, and transporters communicate with intracellular processes through protein interaction networks. Characterization of plant PM proteins – especially hydrophobic proteins – remains challenging despite advances in separation and analysis techniques. Rapid advances in MS instrumentation and data analysis have enabled marked progress in deciphering the membrane proteome and mapping protein interaction partners, leading to a better understanding of PM protein complexes. Analysis of membrane protein phosphorylation under specific cellular conditions is crucial for elucidating the molecular mechanisms underlying signal sensing, transport, and metabolic processes. Phosphoproteomics allows unbiased localization and site-specific quantification of in vivo protein phosphorylation, thus facilitating the dissection of membrane signaling networks. [ABSTRACT FROM AUTHOR]

The intestinal epithelium has a high turnover rate and constantly renews itself through proliferation of intestinal crypt cells, which depends on insufficiently characterized signals from the microenvironment. Here, we showed that colonic macrophages were located directly adjacent to epithelial crypt cells in mice, where they metabolically supported epithelial cell proliferation in an mTORC1-dependent manner. Specifically, deletion of tuberous sclerosis complex 2 (Tsc2) in macrophages activated mTORC1 signaling that protected against colitis-induced intestinal damage and induced the synthesis of the polyamines spermidine and spermine. Epithelial cells ingested these polyamines and rewired their cellular metabolism to optimize proliferation and defense. Notably, spermine directly stimulated proliferation of colon epithelial cells and colon organoids. Genetic interference with polyamine production in macrophages altered global polyamine levels in the colon and modified epithelial cell proliferation. Our results suggest that macrophages act as "commensals" that provide metabolic support to promote efficient self-renewal of the colon epithelium. [Display omitted] • Macrophages are located directly adjacent to epithelial crypt cells in mice • Activation of mTORC1 in macrophages induces polyamine synthesis • Epithelial cells take up the polyamines, which supports their proliferation • Macrophage-derived polyamines support the metabolic rewiring of colonic epithelial cells Fritsch et al. show that macrophages are located directly adjacent to epithelial cells in the mouse colonic crypt and support their proliferation during homeostasis and colitis. Macrophages synthesize polyamines via a mTORC1-arginase-1-dependent pathway that are being taken up by the epithelial cells, which induce metabolic reprogramming and enhanced proliferation. [ABSTRACT FROM AUTHOR]

M1 (LPS) macrophages are characterized by a high expression of pro-inflammatory mediators, and distinct metabolic features that comprise increased glycolysis, a broken TCA cycle, or impaired OXPHOS with augmented mitochondrial ROS production. This study investigated whether the phytochemical sulforaphane (Sfn) influences mitochondrial reprogramming during M1 polarization, as well as to what extent this can contribute to Sfn-mediated inhibition of M1 marker expression in murine macrophages. The use of extracellular flux-, metabolite-, and immunoblot analyses as well as fluorescent dyes indicative for mitochondrial morphology, membrane potential or superoxide production, demonstrated that M1 (LPS/Sfn) macrophages maintain an unbroken TCA cycle, higher OXPHOS rate, boosted fusion dynamics, lower membrane potential, and less superoxide production in their mitochondria when compared to control M1 (LPS) cells. Sustained OXPHOS and TCA activity but not the concomitantly observed high dependency on fatty acids as fuel appeared necessary for M1 (LPS/Sfn) macrophages to reduce expression of nos2, il1β, il6 and tnfα. M1 (LPS/Sfn) macrophages also displayed lower nucleo/cytosolic acetyl-CoA levels in association with lower global and site-specific histone acetylation at selected pro-inflammatory gene promoters than M1 (LPS), evident in colorimetric coupled enzyme assays, immunoblot and ChIP-qPCR analyses, respectively. Supplementation with acetate or citrate was able to rescue both histone acetylation and mRNA expression of the investigated M1 marker genes in Sfn-treated cells. Overall, Sfn preserves mitochondrial functionality and restricts indispensable nuclear acetyl-CoA for histone acetylation and M1 marker expression in LPS-stimulated macrophages. [Display omitted] • Sfn prevents mitochondrial reprogramming from ATP to ROS production in M1 (LPS) macrophages. • OXPHOS activity supports the anti-inflammatory potential of Sfn. • Increased dependency on fatty acid oxidation alone is insufficient for reduced marker gene expression in M1 (LPS/Sfn) macrophages. • Limited extramitochondrial acetyl-CoA and reduced histone acetylation blunt M1 marker expression in M1 (LPS/Sfn) macrophages. [ABSTRACT FROM AUTHOR]

Metabolomics is a technology that aims to identify and quantify the metabolome – the dynamic set of all small molecules present in an organism or a biological sample. In this sense, the technique is distinct from metabolic profiling, which looks for target compounds and their biochemical transformation. The combination of both approaches is an emerging technique for the characterization of biological samples and for drug treatment. Metabolomics has proven to be very rapid and superior to any other post-genomics technology for pattern-recognition analyses of biological samples. Changing steady state concentrations and fluctuations of metabolites that occur within milliseconds are a result of biochemical processes such as signalling cascades: metabolomic techniques are instrumental in measuring these changes rapidly and sensitively. Metabolite data can be complemented by protein, transcript and external (environmental) data, thereby leading to the identification of multiple physiological biomarkers embedded in correlative molecular networks that are not approachable with targeted studies. [Copyright &y& Elsevier]

Metabolomic analysis aims at the identification and quantitation of all metabolites in a given biological sample. Current data acquisition and network analysis strategies are classified on the basis of pathway elucidation and characteristics of theoretical networks. The development of metabolomic methods and tools is progressing rapidly, but an understanding of the resulting data is limited owing to a fundamental lack of biochemical and physiological knowledge about network organization in plants. [Copyright &y& Elsevier]

Mechanistic or mammalian target of rapamycin complex 1 (mTORC1) is an important regulator of effector functions, proliferation, and cellular metabolism in macrophages. The biochemical processes that are controlled by mTORC1 are still being defined. Here, we demonstrate that integrative multiomics in conjunction with a data-driven inverse modeling approach, termed COVRECON, identifies a biochemical node that influences overall metabolic profiles and reactions of mTORC1-dependent macrophage metabolism. Using a combined approach of metabolomics, proteomics, mRNA expression analysis, and enzymatic activity measurements, we demonstrate that Tsc2, a negative regulator of mTORC1 signaling, critically influences the cellular activity of macrophages by regulating the enzyme phosphoglycerate dehydrogenase (Phgdh) in an mTORC1-dependent manner. More generally, while lipopolysaccharide (LPS)-stimulated macrophages repress Phgdh activity, IL-4-stimulated macrophages increase the activity of the enzyme required for the expression of key anti-inflammatory molecules and macrophage proliferation. Thus, we identify Phgdh as a metabolic checkpoint of M2 macrophages. • Metabolomics and inverse modeling reveal a Tsc2/mTORC1-dependent checkpoint in macrophages • M2 macrophages have high Phgdh activity • Phgdh activity promotes M2 polarization • Phgdh activity supports macrophage proliferation Wilson et al. show that Tsc2, a negative regulator of mTORC1 signaling, critically influences the metabolome of macrophages. Inverse data-driven modeling and multiomics data reveal that Phgdh is an mTORC1-dependent metabolic checkpoint of macrophage proliferation and polarization. Phgdh is required for the expression of key anti-inflammatory molecules and M2 proliferation. [ABSTRACT FROM AUTHOR]

Nitrification and denitrification are soil biological processes responsible for large nitrogen losses from agricultural soils and generation of the greenhouse gas (GHG) N 2 O. Increased use of nitrogen fertilizer and the resulting decline in nitrogen use efficiency (NUE) are a major concern in agroecosystems. This nitrogen cycle in the rhizosphere is influenced by an intimate soil microbiome–root exudate interaction and biological nitrification inhibition (BNI). A PANOMICS approach can dissect these processes. We review breakthroughs in this area, including identification and characterization of root exudates by metabolomics and proteomics, which facilitate better understanding of belowground chemical communications and help identify new biological nitrification inhibitors (BNIs). We also address challenges for advancing the understanding of the role root exudates play in biotic and abiotic stresses. Understanding the complex nature of root exudate and soil microbiome interaction at the root–soil interface has greatly intensified recently. Biological nitrification inhibition (BNI) can help to reduce excess nitrogen leaching into the outer soil layers, improving nitrogen use efficiency (NUE) and reducing the negative impact of excess nitrogen fertilization on the environment. Single omics analysis will not help understand complex interactions at the root–soil interface. Instead, a PANOMICS approach can determine the spatiotemporal dynamics of root exudates and microbiome. Root exudates mediate plant–microbe interactions, facilitating nutrient uptake and specifically inhibiting soil nitrification, thereby reducing our dependency on fertilizer. Metabolomics of root exudates is widely studied in different crops and germplasm under diverse environmental conditions; combining this with rhizosphere microbiota metabolomics is an upcoming trend. [ABSTRACT FROM AUTHOR]

Crop production systems need to expand their outputs sustainably to feed a burgeoning human population. Advances in genome sequencing technologies combined with efficient trait mapping procedures accelerate the availability of beneficial alleles for breeding and research. Enhanced interoperability between different omics and phenotyping platforms, leveraged by evolving machine learning tools, will help provide mechanistic explanations for complex plant traits. Targeted and rapid assembly of beneficial alleles using optimized breeding strategies and precise genome editing techniques could deliver ideal crops for the future. Realizing desired productivity gains in the field is imperative for securing an adequate future food supply for 10 billion people. The rapid advances in plant genome sequencing and phenotyping have enhanced trait mapping and gene discovery in crops. Increasing adoption of machine learning algorithms is crucial to derive meaningful inferences from complex multidimensional phenotyping data. Emerging breeding approaches like optimal contribution selection, alone or in combination with genomic selection, will enhance the genetic base of breeding programs while accelerating genetic gain. Integrating speed breeding with new-age genomic breeding technologies holds promise to relieve the long-standing bottleneck of lengthy crop breeding cycles. Haplotype-based breeding, genomic prediction, and genome editing will hasten targeted assembly of superior alleles in future cultivars for sustainable agricultural development and long-term food security. [ABSTRACT FROM AUTHOR]

A plant's genome encodes enzymes, transporters and many other proteins which constitute metabolism. Interactions of plants with their environment shape their growth, development and resilience towards adverse conditions. Although genome sequencing technologies and applications have experienced triumphantly rapid development during the last decades, enabling nowadays a fast and cheap sequencing of full genomes, prediction of metabolic phenotypes from genotype × environment interactions remains, at best, very incomplete. The main reasons are a lack of understanding of how different levels of molecular organisation depend on each other, and how they are constituted and expressed within a setup of growth conditions. Phenotypic plasticity, e.g., of the genetic model plant Arabidopsis thaliana , has provided important insights into plant-environment interactions and the resulting genotype x phenotype relationships. Here, we summarize previous and current findings about plant development in a changing environment and how this might be shaped and reflected in metabolism and its regulation. We identify current challenges in the study of plant development and metabolic regulation and provide an outlook of how methodological workflows might support the application of findings made in model systems to crops and their cultivation. [ABSTRACT FROM AUTHOR]

The traceability of palm oil to determine its geographical origins within the palm oil supply chains is of importance to ensure quality and sustainable production. The current traceability systems are insufficient, thus requiring a more viable and effective approach to improve the traceability framework of the palm oil supply chain. In this study, the feasibility of Fourier transform infrared (FTIR) and chemometric methods for the traceability of crude palm oil (CPO) samples in Malaysia was investigated. The orthogonal partial least squares-discriminant analysis (OPLS-DA) was used to examine the FTIR spectral data of 354 CPO samples collected from four different mills in Malaysia from February until July 2019. The optimal OPLS-DA models were achieved with standard normal variate (SNV) preprocessing and Pareto (Par) scaling to discriminate the CPO according to its geographical provenance and time of sampling. OPLS-DA models using CPO fingerprints successfully discriminated CPO samples according to their geographical origin and production month, with a total accuracy of correct classification for the blind samples (test set) in the prediction models greater than 90% and with the area under the receiver operating characteristic (ROC) curve values exceeding 0.9. The OPLS-DA loading plot indicated that spectral regions associated with free fatty acid (FFA), iodine value (IV) as well as the saturated and unsaturated fatty acid content were responsible for the discrimination patterns and can be potentially used as spectral markers to differentiate CPO samples. Overall, the study shows that combination of FTIR fingerprinting and chemometric methods could serve as an effective tool to trace and discriminating CPO samples according to their geographical origins and production times. The approaches used in the study present an innovative strategy for monitoring quality of palm oil, and moving forward will also facilitate efforts at successful tracking of palm oil across supply chains, especially when combined with additional analytical techniques. [Display omitted] • FTIR and chemometric methods were used to investigate the origin of 354 CPO samples. • The OPLS-DA model based on CPO fingerprints was established and optimized. • FFA, IV, and saturated and unsaturated fatty acids could be CPO traceability markers. [ABSTRACT FROM AUTHOR]

Abstract: Recently it has been reported that boron (B) deficiency increases the expression of Nicotiana tabacum asparagine synthetase (AS) gene in roots, and that AS might play a main role as a detoxifying mechanism to convert ammonium into asparagine. Interestingly, glutamate dehydrogenase (GDH) genes, Ntgdh-NAD;A1 and Ntgdh-NAD;B2, were up-regulated when tobacco roots were subjected to B deprivation for 8 and 24 h. In addition, aminating and deaminating GDH (EC 1.4.1.2) activities were higher in B-deficient than in B-sufficient plants after 24 h of B deficiency. Ammonium concentrations were kept sufficiently low and with similar values in B-deficient roots when compared to control. Glucose and fructose contents decreased after 24 h of B deprivation. This drop in hexoses, which was corroborated by metabolomic analysis, correlated with higher GDH gene expression. Furthermore, metabolomic profiling showed that concentrations of several organic acids, phenolics, and amino acids increased after 24 h of B deficiency. Our results suggest that GDH enzyme plays an important role in metabolic acclimation of tobacco roots to B deprivation. A putative model to explain these results is proposed and discussed. [Copyright &y& Elsevier]

Metabolite, protein, and transcript analysis at the cellular level gives unparalleled insight into the complex roles tissues play in the plant system. However, while capillary electrophoresis and PCR amplification strategies make the profiling of metabolites and transcripts in specific cell types possible, the profiling of proteins in small samples represents a bottleneck. Here for the first time protein profiling has been achieved in a specific plant cell type: The application of specific cell sampling and shotgun peptide sequencing (nano LC/MS/MS) resulted in the identification of 63 unique proteins from pooled Arabidopsis trichome cells. A complete S-adenosylmethionine pathway cluster, two S-adenosylmethionine synthase isoforms, a glutathione S-conjugate translocator and other proteins involved in sulfur metabolism and detoxification are shown to be present in these cells, in agreement with previous work done at the level of trichome transcript analysis. The technology described here brings the simultaneous identification and localization of physiologically relevant cellular proteins within reach. [Copyright &y& Elsevier]

Twelve previously undescribed mexicanolide-type limonoids, including two pairs of isomers, together with seven known analogues were isolated from the twigs and leaves of Cipadessa baccifera. Their structures were determined by extensive spectroscopic methods and electronic circular dichroism (ECD) calculations. Structural variations mainly occurred at the attachment of C-3 and the carbon residues linked to C-17. 21-deoxo-23-oxofebrifugin A and 3- O -detigloyl-3- O -isobutyryl-21-deoxo-23-oxofebrifugin A are two rare naturally occurring mexicanolide-type limonoids bearing an α , β -unsaturated- γ -lactone motif at C-17. Moreover, cipaferen R is the first degraded tetranortriterpenoid derivative featuring an unique acetyl group at C-17. Some isolated compounds were evaluated for nematicidal, antifungal, cytotoxic (against five human cancer cell lines), and acetylcholinesterase inhibitory activities. No nematicidal and antifungal activities were observed, yet 3- O -detigloyl-3- O -isobutyrylfebrifugin A, febrifugin A, febrifugin, and khaysin T exhibited moderate cytotoxic activity against the tested cells with IC 50 values ranging from 18.56 ± 0.27 to 38.00 ± 0.85 μM, and 3- O -detigloyl-3- O -isobutyrylfebrifugin A, granatumin E, khaysin T, and 2′ S -cipadesin A showed moderate inhibitory activities against acetylcholinesterase (AChE) at 50 μM. Twelve previously undescribed mexicanolide-type limonoids, together with seven known analogues were isolated from the twigs and leaves of Cipadessa baccifera. The nematicidal, antifungal, cytotoxic (against five human cancer cell lines), and acetylcholinesterase inhibitory activities of some isolated compounds were evaluated. Image 1 • Twelve undescribed limonoids were isolated from Cipadessa baccifera. • Cipaferen P is the first degraded limonoid featuring an acetyl group at C-17. • The structures were determined by spectroscopic methods and ECD calculations. • All compounds were evaluated for nematicidal and antifungal activities. • Selected compounds were evaluated for cytotoxic and AchE inhibitory activities. [ABSTRACT FROM AUTHOR]

Tumor cells may adapt to metabolic challenges by alternating between glycolysis and oxidative phosphorylation (OXPHOS). To target this metabolic plasticity, we combined intermittent fasting, a clinically feasible approach to reduce glucose availability, with the OXPHOS inhibitor metformin. In mice exposed to 24-h feeding/fasting cycles, metformin impaired tumor growth only when administered during fasting-induced hypoglycemia. Synergistic anti-neoplastic effects of the metformin/hypoglycemia combination were mediated by glycogen synthase kinase 3β (GSK3β) activation downstream of PP2A, leading to a decline in the pro-survival protein MCL-1, and cell death. Mechanistically, specific activation of the PP2A-GSK3β axis was the sum of metformin-induced inhibition of CIP2A, a PP2A suppressor, and of upregulation of the PP2A regulatory subunit B56δ by low glucose, leading to an active PP2A-B56δ complex with high affinity toward GSK3β. • Metformin plus fasting-induced hypoglycemia synergistically reduces tumor growth • PP2A-GSK3β-MCL-1 axis mediates the synergistic cytotoxicity of the combination • Simultaneous CIP2A inhibition and B56δ upregulation dictate combination specificity Elgendy et al. show that metformin administered during the fasting period synergizes with 24-h feeding/fasting cycles to suppress tumor growth. Inhibition of CIP2A by metformin and upregulation of B56δ by low glucose activates PP2A toward GSK3β leading to reduced pro-survival protein MCL-1 and cell death. [ABSTRACT FROM AUTHOR]