Chronic signaling via the metabolic checkpoint kinase mTORC1 induces macrophage granuloma formation and marks sarcoidosis progression.

The aggregation of hypertrophic macrophages constitutes the basis of all granulomatous diseases, such as tuberculosis or sarcoidosis, and is decisive for disease pathogenesis. However, macrophage-intrinsic pathways driving granuloma initiation and maintenance remain elusive. We found that activation of the metabolic checkpoint kinase mTORC1 in macrophages by deletion of the gene encoding tuberous sclerosis 2 (Tsc2) was sufficient to induce hypertrophy and proliferation, resulting in excessive granuloma formation in vivo. TSC2-deficient macrophages formed mTORC1-dependent granulomatous structures in vitro and showed constitutive proliferation that was mediated by the neo-expression of cyclin-dependent kinase 4 (CDK4). Moreover, mTORC1 promoted metabolic reprogramming via CDK4 toward increased glycolysis while simultaneously inhibiting NF-κB signaling and apoptosis. Inhibition of mTORC1 induced apoptosis and completely resolved granulomas in myeloid TSC2-deficient mice. In human sarcoidosis patients, mTORC1 activation, macrophage proliferation and glycolysis were identified as hallmarks that correlated with clinical disease progression. Collectively, TSC2 maintains macrophage quiescence and prevents mTORC1-dependent granulomatous disease with clinical implications for sarcoidosis.

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.

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.

Fast-forward breeding for a food-secure world.

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.

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.

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.

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.

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.

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.

Proteomics for abiotic stresses in legumes: present status and future directions.

Legumes are the most important crop plants in agriculture, contributing 27% of the world's primary food production. However, productivity and production of Legumes is reduced due to increasing environmental stress. Hence, there is a pressing need to understand the molecular mechanism involved in stress response and legumes adaptation. Proteomics provides an important molecular approach to investigate proteins involved in stress response. Both the gel-based and gel-free-based techniques have significantly contributed to understanding the proteome regulatory network in leguminous plants. In the present review, we have discussed the role of different proteomic approaches (2-DE, 2 D-DIGE, ICAT, iTRAQ, etc.) in the identification of various stress-responsive proteins in important leguminous crops, including soybean, chickpea, cowpea, pigeon pea, groundnut, and common bean under variable abiotic stresses including heat, drought, salinity, waterlogging, frost, chilling and metal toxicity. The proteomic analysis has revealed that most of the identified differentially expressed proteins in legumes are involved in photosynthesis, carbohydrate metabolism, signal transduction, protein metabolism, defense, and stress adaptation. The proteomic approaches provide insights in understanding the molecular mechanism of stress tolerance in legumes and have resulted in the identification of candidate genes used for the genetic improvement of plants against various environmental stresses. Identifying novel proteins and determining their expression under different stress conditions provide the basis for effective engineering strategies to improve stress tolerance in crop plants through marker-assisted breeding.

Spatial distribution of proteins and metabolites in developing wheat grain and their differential regulatory response during the grain filling process.

Grain filling and grain development are essential biological processes in the plant's life cycle, eventually contributing to the final seed yield and quality in all cereal crops. Studies of how the different wheat (Triticum aestivum L.) grain components contribute to the overall development of the seed are very scarce. We performed a proteomics and metabolomics analysis in four different developing components of the wheat grain (seed coat, embryo, endosperm, and cavity fluid) to characterize molecular processes during early and late grain development. In-gel shotgun proteomics analysis at 12, 15, 20, and 26 days after anthesis (DAA) revealed 15 484 identified and quantified proteins, out of which 410 differentially expressed proteins were identified in the seed coat, 815 in the embryo, 372 in the endosperm, and 492 in the cavity fluid. The abundance of selected protein candidates revealed spatially and temporally resolved protein functions associated with development and grain filling. Multiple wheat protein isoforms involved in starch synthesis such as sucrose synthases, starch phosphorylase, granule-bound and soluble starch synthase, pyruvate phosphate dikinase, 14-3-3 proteins as well as sugar precursors undergo a major tissue-dependent change in abundance during wheat grain development suggesting an intimate interplay of starch biosynthesis control. Different isoforms of the protein disulfide isomerase family as well as glutamine levels, both involved in the glutenin macropolymer pattern, showed distinct spatial and temporal abundance, revealing their specific role as indicators of wheat gluten quality. Proteins binned into the functional category of cell growth/division and protein synthesis/degradation were more abundant in the early stages (12 and 15 DAA). At the metabolome level all tissues and especially the cavity fluid showed highly distinct metabolite profiles. The tissue-specific data are integrated with biochemical networks to generate a comprehensive map of molecular processes during grain filling and developmental processes.

Heat stress response mechanisms in pollen development.

Being rooted in place, plants are faced with the challenge of responding to unfavourable local conditions. One such condition, heat stress, contributes massively to crop losses globally. Heatwaves are predicted to increase, and it is of vital importance to generate crops that are tolerant to not only heat stress but also to several other abiotic stresses (e.g. drought stress, salinity stress) to ensure that global food security is protected. A better understanding of the molecular mechanisms that underlie the temperature stress response in pollen will be a significant step towards developing effective breeding strategies for high and stable production in crop plants. While most studies have focused on the vegetative phase of plant growth to understand heat stress tolerance, it is the reproductive phase that requires more attention as it is more sensitive to elevated temperatures. Every phase of reproductive development is affected by environmental challenges, including pollen and ovule development, pollen tube growth, male-female cross-talk, fertilization, and embryo development. In this review we summarize how pollen is affected by heat stress and the molecular mechanisms employed during the stress period, as revealed by classical and -omics experiments.

Snf1-RELATED KINASE1-Controlled C/S1-bZIP Signaling Activates Alternative Mitochondrial Metabolic Pathways to Ensure Plant Survival in Extended Darkness.

Sustaining energy homeostasis is of pivotal importance for all living organisms. In Arabidopsis thaliana, evolutionarily conserved SnRK1 kinases (Snf1-RELATED KINASE1) control metabolic adaptation during low energy stress. To unravel starvation-induced transcriptional mechanisms, we performed transcriptome studies of inducible knockdown lines and found that S1-basic leucine zipper transcription factors (S1-bZIPs) control a defined subset of genes downstream of SnRK1. For example, S1-bZIPs coordinate the expression of genes involved in branched-chain amino acid catabolism, which constitutes an alternative mitochondrial respiratory pathway that is crucial for plant survival during starvation. Molecular analyses defined S1-bZIPs as SnRK1-dependent regulators that directly control transcription via binding to G-box promoter elements. Moreover, SnRK1 triggers phosphorylation of group C-bZIPs and the formation of C/S1-heterodimers and, thus, the recruitment of SnRK1 directly to target promoters. Subsequently, the C/S1-bZIP-SnRK1 complex interacts with the histone acetylation machinery to remodel chromatin and facilitate transcription. Taken together, this work reveals molecular mechanisms underlying how energy deprivation is transduced to reprogram gene expression, leading to metabolic adaptation upon stress.

Paraburkholderia dioscoreae sp. nov., a novel plant associated growth promotor.

A novel bacterium, designated strain Msb3T, was recently isolated from leaves of the yam family plant Dioscorea bulbifera (Dioscoreaceae). Phylogenetic analysis based on the 16S rRNA gene sequence indicated that this strain belonged to the genus Paraburkholderia with Paraburkholderia xenovorans as nearest validly named neighbour taxon (99.3 % sequence similarity towards the P. xenovorans type strain). Earlier genome sequence analysis revealed a genome of 8.35 Mb in size with a G+C content of 62.5 mol%, which was distributed over two chromosomes and three plasmids. Here, we confirm that strain Msb3T represents a novel Paraburkholderia species. In silico DNA-DNA hybridization and average nucleotide identity (OrthoANIu) analyses towards P. xenovorans LB400T yielded 58.4 % dDDH and 94.5 % orthoANIu. Phenotypic and metabolic characterization revealed growth at 15 °C on tryptic soy agar, growth in the presence of 1 % NaCl and the lack of assimilation of phenylacetic acid as distinctive features. Together, these data demonstrate that strain Msb3T represents a novel species of the genus Paraburkholderia, for which we propose the name Paraburkholderia dioscoreae sp. nov. The type strain is Msb3T (=LMG 31881T, DSM 111632T, CECT 30342T).

Lessons Learned from the Studies of Roots Shaded from Direct Root Illumination.

The root is the below-ground organ of a plant, and it has evolved multiple signaling pathways that allow adaptation of architecture, growth rate, and direction to an ever-changing environment. Roots grow along the gravitropic vector towards beneficial areas in the soil to provide the plant with proper nutrients to ensure its survival and productivity. In addition, roots have developed escape mechanisms to avoid adverse environments, which include direct illumination. Standard laboratory growth conditions for basic research of plant development and stress adaptation include growing seedlings in Petri dishes on medium with roots exposed to light. Several studies have shown that direct illumination of roots alters their morphology, cellular and biochemical responses, which results in reduced nutrient uptake and adaptability upon additive stress stimuli. In this review, we summarize recent methods that allow the study of shaded roots under controlled laboratory conditions and discuss the observed changes in the results depending on the root illumination status.

Tissue-Specific Proteome and Subcellular Microscopic Analyses Reveal the Effect of High Salt Concentration on Actin Cytoskeleton and Vacuolization in Aleurone Cells during Early Germination of Barley.

Cereal grain germination provides the basis for crop production and requires a tissue-specific interplay between the embryo and endosperm during heterotrophic germination involving signalling, protein secretion, and nutrient uptake until autotrophic growth is possible. High salt concentrations in soil are one of the most severe constraints limiting the germination of crop plants, affecting the metabolism and redox status within the tissues of germinating seed. However, little is known about the effect of salt on seed storage protein mobilization, the endomembrane system, and protein trafficking within and between these tissues. Here, we used mass spectrometry analyses to investigate the protein dynamics of the embryo and endosperm of barley (Hordeum vulgare, L.) at five different early points during germination (0, 12, 24, 48, and 72 h after imbibition) in germinated grains subjected to salt stress. The expression of proteins in the embryo as well as in the endosperm was temporally regulated. Seed storage proteins (SSPs), peptidases, and starch-digesting enzymes were affected by salt. Additionally, microscopic analyses revealed an altered assembly of actin bundles and morphology of protein storage vacuoles (PSVs) in the aleurone layer. Our results suggest that besides the salt-induced protein expression, intracellular trafficking and actin cytoskeleton assembly are responsible for germination delay under salt stress conditions.

Subcellular dynamics of proteins and metabolites under abiotic stress reveal deferred response of the Arabidopsis thaliana hexokinase-1 mutant gin2-1 to high light.

Stress responses in plants imply spatio-temporal changes in enzymes and metabolites, including subcellular compartment-specific re-allocation processes triggered by sudden changes in environmental parameters. To investigate interactions of primary metabolism with abiotic stress, the gin2-1 mutant, defective in the sugar sensor hexokinase 1 (HXK1) was compared with its wildtype Landsberg erecta (Ler) based on time resolved, compartment-specific metabolome and proteome data obtained over a full diurnal cycle. The high light sensitive gin2-1 mutant was substantially delayed in subcellular re-distribution of metabolites upon stress, and this correlated with a massive reduction in proteins belonging to the ATP producing electron transport chain under high light, while fewer changes occurred in the cold. In the wildtype, compounds specifically protecting individual compartments could be identified, e.g., maltose and raffinose in plastids, myo-inositol in mitochondria, but gin2-1 failed to recruit these substances to the respective compartments, or responded only slowly to high irradiance. No such delay was obtained in the cold. At the whole cell level, concentrations of the amino acids, glycine and serine, provided strong evidence for an important role of the photorespiratory pathway during stress exposure, and different subcellular allocation of serine may contribute to the slow growth of the gin2-1 mutant under high irradiance.

Resolving subcellular plant metabolism.

Plant cells are characterized by a high degree of compartmentalization and a diverse proteome and metabolome. Only a very limited number of studies has addressed combined subcellular proteomics and metabolomics which strongly limits biochemical and physiological interpretation of large-scale 'omics data. Our study presents a methodological combination of nonaqueous fractionation, shotgun proteomics, enzyme activities and metabolomics to reveal subcellular diurnal dynamics of plant metabolism. Subcellular marker protein sets were identified and enzymatically validated to resolve metabolism in a four-compartment model comprising chloroplasts, cytosol, vacuole and mitochondria. These marker sets are now available for future studies that aim to monitor subcellular metabolome and proteome dynamics. Comparing subcellular dynamics in wild type plants and HXK1-deficient gin2-1 mutants revealed a strong impact of HXK1 activity on metabolome dynamics in multiple compartments. Glucose accumulation in the cytosol of gin2-1 was accompanied by diminished vacuolar glucose levels. Subcellular dynamics of pyruvate, succinate and fumarate amounts were significantly affected in gin2-1 and coincided with differential mitochondrial proteome dynamics. Lowered mitochondrial glycine and serine amounts in gin2-1 together with reduced abundance of photorespiratory proteins indicated an effect of the gin2-1 mutation on photorespiratory capacity. Our findings highlight the necessity to resolve plant metabolism to a subcellular level to provide a causal relationship between metabolites, proteins and metabolic pathway regulation.

PANOMICS meets germplasm.

Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are emerging providing 1000 and more genotypes and millions of SNPs for one species covering a hitherto inaccessible intraspecific genetic variation. The larger the databases are growing, the better statistical approaches for genomic selection will be available. However, there are clear limitations on the statistical but also on the biological part. Intraspecific genetic variation is able to explain a high proportion of the phenotypes, but a large part of phenotypic plasticity also stems from environmentally driven transcriptional, post-transcriptional, translational, post-translational, epigenetic and metabolic regulation. Moreover, regulation of the same gene can have different phenotypic outputs in different environments. Consequently, to explain and understand environment-dependent phenotypic plasticity based on the available genotype variation we have to integrate the analysis of further molecular levels reflecting the complete information flow from the gene to metabolism to phenotype. Interestingly, metabolomics platforms are already more cost-effective than NGS platforms and are decisive for the prediction of nutritional value or stress resistance. Here, we propose three fundamental pillars for future breeding strategies in the framework of Green Systems Biology: (i) combining genome selection with environment-dependent PANOMICS analysis and deep learning to improve prediction accuracy for marker-dependent trait performance; (ii) PANOMICS resolution at subtissue, cellular and subcellular level provides information about fundamental functions of selected markers; (iii) combining PANOMICS with genome editing and speed breeding tools to accelerate and enhance large-scale functional validation of trait-specific precision breeding.

Male Sterility in Maize after Transient Heat Stress during the Tetrad Stage of Pollen Development.

Shifts in the duration and intensity of ambient temperature impair plant development and reproduction, particularly male gametogenesis. Stress exposure causes meiotic defects or premature spore abortion in male reproductive organs, leading to male sterility. However, little is known about the mechanisms underlying stress and male sterility. To elucidate these mechanisms, we imposed a moderate transient heat stress on maize (Zea mays) plants at the tetrad stage of pollen development. After completion of pollen development at optimal conditions, stress responses were assessed in mature pollen. Transient heat stress resulted in reduced starch content, decreased enzymatic activity, and reduced pollen germination, resulting in sterility. A transcriptomic comparison pointed toward misregulation of starch, lipid, and energy biosynthesis-related genes. Metabolomic studies showed an increase of Suc and its monosaccharide components, as well as a reduction in pyruvate. Lipidomic analysis showed increased levels of unsaturated fatty acids and decreased levels of saturated fatty acids. In contrast, the majority of genes involved in developmental processes such as those required for auxin and unfolded protein responses, signaling, and cell wall biosynthesis remained unaltered. It is noteworthy that changes in the regulation of transcriptional and metabolic pathway genes, as well as heat stress proteins, remained altered even though pollen could recover during further development at optimal conditions. In conclusion, our findings demonstrate that a short moderate heat stress during the highly susceptible tetrad stage strongly affects basic metabolic pathways and thus generates germination-defective pollen, ultimately leading to severe yield losses in maize.