Comparative analysis of geotypic variations in the proteome of Nostoc commune.

Cyanobacterium Nostoc commune is a filamentous terrestrial prokaryotic organism widely distributed, which suggest its high adaptive potential to environmental or abiotic stress. Physiological parameters and proteomic analysis were performed in two accession of N. commune with the aim to elucidate the differences of physiological trails between distant geotypes, namely Antarctic (AN) and central European (CE). The result obtained clearly showed that the AN geotype demonstrates elevated levels of total phenols, flavonoids, carotenoids, and phycobiliproteins, indicative of its adaptation to environmental stress as referred by comparison to CE sample. Additionally, we employed LC-MS analysis to investigate the proteomes of N. commune from AN and CE geotypes. In total, 1147 proteins were identified, among which 646 proteins expressed significant (up-regulation) changes in both accessions. In the AN geotype, 83 exclusive proteins were identified compared to 25 in the CE geotype. Functional classification of the significant proteins showed a large fraction involved in photosynthesis, amino acid metabolism, carbohydrate metabolism and protein biosynthesis. Further analysis revealed some defense-related proteins such as, superoxide dismutase (SOD) and glutathione reductase, which are rather explicitly expressed in the AN N. commune. The last two proteins suggest a more stressful condition in AN N. commune. In summary, our findings highlight biochemical processes that safeguard the AN geotype of N. commune from extreme environmental challenges, not recorded in CE accession, probably due to less stressful environment in Europe. This study brings the first ever proteomic analysis of N. commune, emphasizing the need for additional investigations into the climate adaptation of this species with rather plastic genome.

Corrigendum: Sulforaphane diminishes moonlighting of pyruvate kinase M2 and interleukin 1ß expression in M1 (LPS) macrophages.

[This corrects the article DOI: 10.3389/fimmu.2022.935692.].

Elevated PINK1/Parkin-Dependent Mitophagy and Boosted Mitochondrial Function Mediate Protection of HepG2 Cells from Excess Palmitic Acid by Hesperetin.

Deregulation of mitochondrial functions in hepatocytes contributes to many liver diseases, such as nonalcoholic fatty liver disease (NAFLD). Lately, it was referred to as MAFLD (metabolism-associated fatty liver disease). Hesperetin (Hst), a bioactive flavonoid constituent of citrus fruit, has been proven to attenuate NAFLD. However, a potential connection between its preventive activities and the modulation of mitochondrial functions remains unclear. Here, our results showed that Hst alleviates palmitic acid (PA)-triggered NLRP3 inflammasome activation and cell death by inhibition of mitochondrial impairment in HepG2 cells. Hst reinstates fatty acid oxidation (FAO) rates measured by seahorse extracellular flux analyzer and intracellular acetyl-CoA levels as well as intracellular tricarboxylic acid cycle metabolites levels including NADH and FADH2 reduced by PA exposure. In addition, Hst protects HepG2 cells against PA-induced abnormal energetic profile, ATP generation reduction, overproduction of mitochondrial reactive oxygen species, and collapsed mitochondrial membrane potential. Furthermore, Hst improves the protein expression involved in PINK1/Parkin-mediated mitophagy. Our results demonstrate that it restores PA-impaired mitochondrial function and sustains cellular homeostasis due to the elevation of PINK1/Parkin-mediated mitophagy and the subsequent disposal of dysfunctional mitochondria. These results provide therapeutic potential for Hst utilization as an effective intervention against fatty liver disease.

A perspective on genetic and polygenic risk scores-advances and limitations and overview of associated tools.

Polygenetic Risk Scores are used to evaluate an individual's vulnerability to developing specific diseases or conditions based on their genetic composition, by taking into account numerous genetic variations. This article provides an overview of the concept of Polygenic Risk Scores (PRS). We elucidate the historical advancements of PRS, their advantages and shortcomings in comparison with other predictive methods, and discuss their conceptual limitations in light of the complexity of biological systems. Furthermore, we provide a survey of published tools for computing PRS and associated resources. The various tools and software packages are categorized based on their technical utility for users or prospective developers. Understanding the array of available tools and their limitations is crucial for accurately assessing and predicting disease risks, facilitating early interventions, and guiding personalized healthcare decisions. Additionally, we also identify potential new avenues for future bioinformatic analyzes and advancements related to PRS.

Stress Knowledge Map: A knowledge graph resource for systems biology analysis of plant stress responses.

Stress Knowledge Map (SKM; https://skm.nib.si) is a publicly available resource containing two complementary knowledge graphs that describe the current knowledge of biochemical, signaling, and regulatory molecular interactions in plants: a highly curated model of plant stress signaling (PSS; 543 reactions) and a large comprehensive knowledge network (488 390 interactions). Both were constructed by domain experts through systematic curation of diverse literature and database resources. SKM provides a single entry point for investigations of plant stress response and related growth trade-offs, as well as interactive explorations of current knowledge. PSS is also formulated as a qualitative and quantitative model for systems biology and thus represents a starting point for a plant digital twin. Here, we describe the features of SKM and show, through two case studies, how it can be used for complex analyses, including systematic hypothesis generation and design of validation experiments, or to gain new insights into experimental observations in plant biology.

CAM evolution is associated with gene family expansion in an explosive bromeliad radiation.

The subgenus Tillandsia (Bromeliaceae) belongs to one of the fastest radiating clades in the plant kingdom and is characterised by the repeated evolution of Crassulacean acid metabolism (CAM). Despite its complex genetic basis, this water-conserving trait has evolved independently across many plant families and is regarded as a key innovation trait and driver of ecological diversification in Bromeliaceae. By producing high-quality genome assemblies of a Tillandsia species pair displaying divergent photosynthetic phenotypes, and combining genome-wide investigations of synteny, transposable element (TE) dynamics, sequence evolution, gene family evolution and temporal differential expression, we were able to pinpoint the genomic drivers of CAM evolution in Tillandsia. Several large-scale rearrangements associated with karyotype changes between the two genomes and a highly dynamic TE landscape shaped the genomes of Tillandsia. However, our analyses show that rewiring of photosynthetic metabolism is mainly obtained through regulatory evolution rather than coding sequence evolution, as CAM-related genes are differentially expressed across a 24-hour cycle between the two species but are not candidates of positive selection. Gene orthology analyses reveal that CAM-related gene families manifesting differential expression underwent accelerated gene family expansion in the constitutive CAM species, further supporting the view of gene family evolution as a driver of CAM evolution.

Sulforaphane impedes mitochondrial reprogramming and histone acetylation in polarizing M1 (LPS) macrophages.

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, il1ß, 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.

Targeting PHGDH reverses the immunosuppressive phenotype of tumor-associated macrophages through α-ketoglutarate and mTORC1 signaling.

Phosphoglycerate dehydrogenase (PHGDH) has emerged as a crucial factor in macromolecule synthesis, neutralizing oxidative stress, and regulating methylation reactions in cancer cells, lymphocytes, and endothelial cells. However, the role of PHGDH in tumor-associated macrophages (TAMs) is poorly understood. Here, we found that the T helper 2 (Th2) cytokine interleukin-4 and tumor-conditioned media upregulate the expression of PHGDH in macrophages and promote immunosuppressive M2 macrophage activation and proliferation. Loss of PHGDH disrupts cellular metabolism and mitochondrial respiration, which are essential for immunosuppressive macrophages. Mechanistically, PHGDH-mediated serine biosynthesis promotes α-ketoglutarate production, which activates mTORC1 signaling and contributes to the maintenance of an M2-like macrophage phenotype in the tumor microenvironment. Genetic ablation of PHGDH in macrophages from tumor-bearing mice results in attenuated tumor growth, reduced TAM infiltration, a phenotypic shift of M2-like TAMs toward an M1-like phenotype, downregulated PD-L1 expression and enhanced antitumor T-cell immunity. Our study provides a strong basis for further exploration of PHGDH as a potential target to counteract TAM-mediated immunosuppression and hinder tumor progression.

Integrated multi-omics analysis reveals drought stress response mechanism in chickpea (Cicer arietinum L.).

Drought is one of the major constraints limiting chickpea productivity. To unravel complex mechanisms regulating drought response in chickpea, we generated transcriptomics, proteomics, and metabolomics datasets from root tissues of four contrasting drought-responsive chickpea genotypes: ICC 4958, JG 11, and JG 11+ (drought-tolerant), and ICC 1882 (drought-sensitive) under control and drought stress conditions. Integration of transcriptomics and proteomics data identified enriched hub proteins encoding isoflavone 4'-O-methyltransferase, UDP-d-glucose/UDP-d-galactose 4-epimerase, and delta-1-pyrroline-5-carboxylate synthetase. These proteins highlighted the involvement of pathways such as antibiotic biosynthesis, galactose metabolism, and isoflavonoid biosynthesis in activating drought stress response mechanisms. Subsequently, the integration of metabolomics data identified six metabolites (fructose, galactose, glucose, myoinositol, galactinol, and raffinose) that showed a significant correlation with galactose metabolism. Integration of root-omics data also revealed some key candidate genes underlying the drought-responsive "QTL-hotspot" region. These results provided key insights into complex molecular mechanisms underlying drought stress response in chickpea.

Cell-type proteomic and metabolomic resolution of early and late grain filling stages of wheat endosperm.

The nutritional value of wheat grains, particularly their protein and metabolite composition, is a result of the grain-filling process, especially in the endosperm. Here, we employ laser microdissection (LMD) combined with shotgun proteomics and metabolomics to generate a cell type-specific proteome and metabolome inventory of developing wheat endosperm at the early (15 DAA) and late (26 DAA) grain-filling stages. We identified 1803 proteins and 41 metabolites from four different cell types (aleurone (AL), sub-aleurone (SA), starchy endosperm (SE) and endosperm transfer cells (ETCs). Differentially expressed proteins were detected, 67 in the AL, 31 in the SA, 27 in the SE and 50 in the ETCs between these two-time points. Cell-type accumulation of specific SUT and GLUT transporters, sucrose converting and starch biosynthesis enzymes correlate well with the respective sugar metabolites, suggesting sugar upload and starch accumulation via nucellar projection and ETC at 15 DAA in contrast to the later stage at 26 DAA. Changes in various protein levels between AL, SA and ETC support this metabolic switch from 15 to 26 DAA. The distinct spatial and temporal abundances of proteins and metabolites revealed a contrasting activity of nitrogen assimilation pathways, e.g. for GOGAT, GDH and glutamic acid, in the different cell types from 15 to 26 DAA, which can be correlated with specific protein accumulation in the endosperm. The integration of cell-type specific proteome and metabolome data revealed a complex metabolic interplay of the different cell types and a functional switch during grain development and grain-filling processes.

Low dose ribosomal DNA P-loop mutation affects development and enforces autophagy in Arabidopsis.

Arabidopsis contains hundreds of ribosomal DNA copies organized within the nucleolar organizing regions (NORs) in chromosomes 2 and 4. There are four major types of variants of rDNA, VAR1-4, based on the polymorphisms of 3' external transcribed sequences. The variants are known to be differentially expressed during plant development. We created a mutant by the CRISPR-Cas9-mediated excision of ~ 25 nt from predominantly NOR4 ribosomal DNA copies, obtaining mosaic mutational events on ~ 5% of all rDNA copies. The excised region consists of P-loop and Helix-82 segments of 25S rRNA. The mutation led to allelic, dosage-dependent defects marked by lateral root inhibition, reduced size, and pointy leaves, all previously observed for defective ribosomal function. The mutation in NOR4 led to dosage compensation from the NOR2 copies by elevated expression of VAR1 in mutants and further associated single-nucleotide variants, thus, resulting in altered rRNA sub-population. Furthermore, the mutants exhibited rRNA maturation defects specifically in the minor pathway typified by 32S pre-rRNA accumulation. Density-gradient fractionation and subsequent RT-PCR of rRNA analyses revealed that mutated copies were not incorporated into the translating ribosomes. The mutants in addition displayed an elevated autophagic flux as shown by the autophagic marker GFP-ATG8e, likely related to ribophagy.

Detecting horizontal gene transfer among microbiota: an innovative pipeline for identifying co-shared genes within the mobilome through advanced comparative analysis.

Horizontal gene transfer (HGT) is a key driver in the evolution of bacterial genomes. The acquisition of genes mediated by HGT may enable bacteria to adapt to ever-changing environmental conditions. Long-term application of antibiotics in intensive agriculture is associated with the dissemination of antibiotic resistance genes among bacteria with the consequences causing public health concern. Commensal farm-animal-associated gut microbiota are considered the reservoir of the resistance genes. Therefore, in this study, we identified known and not-yet characterized mobilized genes originating from chicken and porcine fecal samples using our innovative pipeline followed by network analysis to provide appropriate visualization to support proper interpretation.

Metabolic support by macrophages sustains colonic epithelial homeostasis.

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.

Quantifying the impact of dynamic plant-environment interactions on metabolic regulation.

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.

Candidate pathogenicity factor/effector proteins of 'Candidatus Phytoplasma solani' modulate plant carbohydrate metabolism, accelerate the ascorbate-glutathione cycle, and induce autophagosomes.

The pathogenicity of intracellular plant pathogenic bacteria is associated with the action of pathogenicity factors/effectors, but their physiological roles for most phytoplasma species, including 'Candidiatus Phytoplasma solani' are unknown. Six putative pathogenicity factors/effectors from six different strains of 'Ca. P. solani' were selected by bioinformatic analysis. The way in which they manipulate the host cellular machinery was elucidated by analyzing Nicotiana benthamiana leaves after Agrobacterium-mediated transient transformation with the pathogenicity factor/effector constructs using confocal microscopy, pull-down, and co-immunoprecipitation, and enzyme assays. Candidate pathogenicity factors/effectors were shown to modulate plant carbohydrate metabolism and the ascorbate-glutathione cycle and to induce autophagosomes. PoStoSP06, PoStoSP13, and PoStoSP28 were localized in the nucleus and cytosol. The most active effector in the processes studied was PoStoSP06. PoStoSP18 was associated with an increase in phosphoglucomutase activity, whereas PoStoSP28, previously annotated as an antigenic membrane protein StAMP, specifically interacted with phosphoglucomutase. PoStoSP04 induced only the ascorbate-glutathione cycle along with other pathogenicity factors/effectors. Candidate pathogenicity factors/effectors were involved in reprogramming host carbohydrate metabolism in favor of phytoplasma own growth and infection. They were specifically associated with three distinct metabolic pathways leading to fructose-6-phosphate as an input substrate for glycolysis. The possible significance of autophagosome induction by PoStoSP28 is discussed.

Leaf metabolic traits reveal hidden dimensions of plant form and function.

The metabolome is the biochemical basis of plant form and function, but we know little about its macroecological variation across the plant kingdom. Here, we used the plant functional trait concept to interpret leaf metabolome variation among 457 tropical and 339 temperate plant species. Distilling metabolite chemistry into five metabolic functional traits reveals that plants vary on two major axes of leaf metabolic specialization-a leaf chemical defense spectrum and an expression of leaf longevity. Axes are similar for tropical and temperate species, with many trait combinations being viable. However, metabolic traits vary orthogonally to life-history strategies described by widely used functional traits. The metabolome thus expands the functional trait concept by providing additional axes of metabolic specialization for examining plant form and function.

Recurrent allopolyploidizations diversify ecophysiological traits in marsh orchids (Dactylorhiza majalis s.l.).

Whole-genome duplication has shaped the evolution of angiosperms and other organisms, and is important for many crops. Structural reorganization of chromosomes and repatterning of gene expression are frequently observed in allopolyploids, with physiological and ecological consequences. Recurrent origins from different parental populations are widespread among polyploids, resulting in an array of lineages that provide excellent models to uncover mechanisms of adaptation to divergent environments in early phases of polyploid evolution. We integrate here transcriptomic and ecophysiological comparative studies to show that sibling allopolyploid marsh orchid species (Dactylorhiza, Orchidaceae) occur in different habitats (low nutrient fens vs. meadows with mesic soils) and are characterized by a complex suite of intertwined, pronounced ecophysiological differences between them. We uncover distinct features in leaf elemental chemistry, light-harvesting, photoprotection, nutrient transport and stomata activity of the two sibling allopolyploids, which appear to match their specific ecologies, in particular soil chemistry differences at their native sites. We argue that the phenotypic divergence between the sibling allopolyploids has a clear genetic basis, generating ecological barriers that maintain distinct, independent lineages, despite pervasive interspecific gene flow. This suggests that recurrent origins of polyploids bring about a long-term potential to trigger and maintain functional and ecological diversity in marsh orchids and other groups.

COVRECON: automated integration of genome- and metabolome-scale network reconstruction and data-driven inverse modeling of metabolic interaction networks.

MOTIVATION: One central goal of systems biology is to infer biochemical regulations from large-scale OMICS data. Many aspects of cellular physiology and organismal phenotypes can be understood as results of metabolic interaction network dynamics. Previously, we have proposed a convenient mathematical method, which addresses this problem using metabolomics data for the inverse calculation of biochemical Jacobian matrices revealing regulatory checkpoints of biochemical regulations. The proposed algorithms for this inference are limited by two issues: they rely on structural network information that needs to be assembled manually, and they are numerically unstable due to ill-conditioned regression problems for large-scale metabolic networks. RESULTS: To address these problems, we developed a novel regression loss-based inverse Jacobian algorithm, combining metabolomics COVariance and genome-scale metabolic RECONstruction, which allows for a fully automated, algorithmic implementation of the COVRECON workflow. It consists of two parts: (i) Sim-Network and (ii) inverse differential Jacobian evaluation. Sim-Network automatically generates an organism-specific enzyme and reaction dataset from Bigg and KEGG databases, which is then used to reconstruct the Jacobian's structure for a specific metabolomics dataset. Instead of directly solving a regression problem as in the previous workflow, the new inverse differential Jacobian is based on a substantially more robust approach and rates the biochemical interactions according to their relevance from large-scale metabolomics data. The approach is illustrated by in silico stochastic analysis with differently sized metabolic networks from the BioModels database and applied to a real-world example. The characteristics of the COVRECON implementation are that (i) it automatically reconstructs a data-driven superpathway model; (ii) more general network structures can be investigated, and (iii) the new inverse algorithm improves stability, decreases computation time, and extends to large-scale models. AVAILABILITY AND IMPLEMENTATION: The code is available in the website https://bitbucket.org/mosys-univie/covrecon.

Phyllosphere symbiont promotes plant growth through ACC deaminase production.

Plant growth promoting bacteria can confer resistance to various types of stress and increase agricultural yields. The mechanisms they employ are diverse. One of the most important genes associated with the increase in plant biomass and stress resistance is acdS, which encodes a 1-aminocyclopropane-1-carboxylate- or ACC-deaminase. The non-proteinogenic amino acid ACC is the precursor and means of long-distance transport of ethylene, a plant hormone associated with growth arrest. Expression of acdS reduces stress induced ethylene levels and the enzyme is abundant in rhizosphere colonizers. Whether ACC hydrolysis plays a role in the phyllosphere, both as assembly cue and in growth promotion, remains unclear. Here we show that Paraburkholderia dioscoreae Msb3, a yam phyllosphere symbiont, colonizes the tomato phyllosphere and promotes plant growth by action of its ACC deaminase. We found that acdS is required for improved plant growth but not for efficient leaf colonization. Strain Msb3 readily proliferates on the leaf surface of tomato, only occasionally spreading to the leaf endosphere through stomata. The strain can also colonize the soil or medium around the roots but only spreads into the root if the plant is wounded. Our results indicate that the degradation of ACC is not just an important trait of plant growth promoting rhizobacteria but also one of leaf dwelling phyllosphere bacteria. Manipulation of the leaf microbiota by means of spray inoculation may be more easily achieved than that of the soil. Therefore, the application of ACC deaminase containing bacteria to the phyllosphere may be a promising strategy to increasing plant stress resistance, pathogen control, and harvest yields.

Metabolome plasticity in 241 Arabidopsis thaliana accessions reveals evolutionary cold adaptation processes.

Acclimation and adaptation of metabolism to a changing environment are key processes for plant survival and reproductive success. In the present study, 241 natural accessions of Arabidopsis (Arabidopsis thaliana) were grown under two different temperature regimes, 16 °C and 6 °C, and growth parameters were recorded, together with metabolite profiles, to investigate the natural genome × environment effects on metabolome variation. The plasticity of metabolism, which was captured by metabolic distance measures, varied considerably between accessions. Both relative growth rates and metabolic distances were predictable by the underlying natural genetic variation of accessions. Applying machine learning methods, climatic variables of the original growth habitats were tested for their predictive power of natural metabolic variation among accessions. We found specifically habitat temperature during the first quarter of the year to be the best predictor of the plasticity of primary metabolism, indicating habitat temperature as the causal driver of evolutionary cold adaptation processes. Analyses of epigenome- and genome-wide associations revealed accession-specific differential DNA-methylation levels as potentially linked to the metabolome and identified FUMARASE2 as strongly associated with cold adaptation in Arabidopsis accessions. These findings were supported by calculations of the biochemical Jacobian matrix based on variance and covariance of metabolomics data, which revealed that growth under low temperatures most substantially affects the accession-specific plasticity of fumarate and sugar metabolism. Our findings indicate that the plasticity of metabolic regulation is predictable from the genome and epigenome and driven evolutionarily by Arabidopsis growth habitats.